ORAL PRESENTATIONS

Population Models for Manatee Conservation in Florida. BRUCE B. ACKERMAN, Florida Marine Research Institute, Florida Dept. Environmental Protection, St. Petersburg, FL.

Recent data on the endangered Florida manatee (Trichechus manatus) yield controversial information on their population dynamics. Field data are ambiguous about the population trends. Two population models were compared for 5 regional subpopulations. A PVA model (Vortex 6.3) used stage-specific survival and reproduction from long-term telemetry and photo-identification studies. An independent discrete equation model used regional numbers of carcass recoveries, reproductive rates from carcasses, and aerial counts. Projections from the 2 models were validated compared to aerial survey and carcass trends. Results were compared to PVA and Lotka models by previous researchers. Models suggest the populations have increased in the 5 regions, but this trend could reverse as human impacts increase. Both the annual number of carcasses recovered (3270 carcasses, 1974-97) and aerial counts have increased. The statewide aerial count of 2639 manatees in February 1996 exceeded previous counts. But carcass numbers in 1996 were also extremely high (n=416 deaths) following catastrophic mortality from a cold winter (47) and from red tide (149). Long-term aerial studies suggest increases of 1 to 10%/year in some areas. Reconciling the divergent data has been controversial. Mortality varies among regions because of differing densities of manatees, humans, and watercraft, crowded waterways, etc. Recovery efforts focus on reducing human-related deaths and injuries, especially watercraft collisions. These models help reconcile differences in field data, assess current population dynamics, predict future trends from increasing human impacts, and improve conservation strategies.

Making PVAs Useful Despite Uncertainties. H. RESIT AKÇAKAYA, Applied Biomathematics, Setauket, NY.

Parameters and structure of models used in PVAs are often estimated based on insufficient data, resulting in large uncertainties. PVAs should treat these uncertainties as well as natural variability in an appropriate way. Stochastic demographic models can be used to systematically incorporate uncertainties due to lack of information or measurement error, in addition to variabilities due to environmental fluctuations and demographic stochasticity. When PVAs are used for impact assessment or making management decisions, accounting for these two fundamentally different types of variability allows the models to be more sensitive to the impact or the management action. Results of recent habitat-based PVAs (involving the Red-cockaded Woodpecker and the Northern Spotted Owl) were sensitive to the effects of alternative management actions or human impact, despite considerable model uncertainty. These results suggest that in most circumstances it is possible to make robust assessments and management decisions despite the inevitable uncertainties. One of the conditions for this involves decomposing the uncertainties when making assessments and making the comparisons with respect to key model assumptions. Other conditions include choosing a model with the appropriate level of detail, using probabilistic results and relative risks, focusing on risk of decline (instead of risk of extinction), and choosing the appropriate time horizon. When these conditions are met, PVAs can be used to compare and rank management alternatives in terms of their effect on the viability of the species studied.

The Role of Genetics in Population Viability Analysis. FRED W. ALLENDORF*, Div. Of Biol. Sci., Univ. Montana, Missoula, MT, and NILS RYMAN, Div. Of Pop. Genet., Univ. Stockholm, Sweden.

Controversy over the importance of genetic considerations in Population Viability Analysis (PVA) in the last decade has occurred partially because of confounding of the different roles that genetics may play in performing PVA. Genetics can play at least three distinct roles. The first is to provide an understanding of the demographic and reproductive relationships of the species to be modeled. For example, do the fish present in a lake comprise one or many separate demographic units? Molecular genetic analysis can be used to detect multiple reproductively isolated demographic units within one geographical area. Genetic analysis may also provide important information about demographic and reproductive relationships within a single local population (e.g., variance in reproductive success, effective population size, or amount of selfing). Second, the inbreeding effect and loss of genetic variation within small populations may decrease the probability of persistence of isolated populations. The consideration of such effects may be important in accurately predicting the viability of some populations. Third, in some circumstances it is important to use genetic goals along with PVA. Persistence of a population for some specified period of time (say 100 or 200 years) is not a sufficient goal if erosion of genetic variation occurs that threatens the longer term persistence of a population. Our presentation will suggest approaches to integrate genetics into PVA in all three of these roles.

Formal Inference from a Suite of PVA Models. DAVID R. ANDERSON*, Colorado Cooperative Fish and Wildlife Research Unit, USGS, Biological Resources Division. Ft. Collins, CO, and KENNETH P. BURNHAM, Colorado Cooperative Fish and Wildlife Research Unit, USGS, Biological Resources Division, Ft. Collins, CO.

Predictions of population viability are typically model-dependent. We provide a theory, based on Kullback-Leibler information, for making formal inference from more than one model (i. e., multi-model inference). We assume (1) relevant quantitative data, (2) a set of a priori models carefully derived and supported, and (3) either likelihood or least squares estimation of model parameters. Quantities can be easily computed to allow models to be ranked from best to worst and scaled to indicate relative "distances" between the models. A transformation allows estimation of the (discrete) likelihood of model i, given the data (i.e., L (model i | data)) and normalizing these to represent probabilities. A confidence set for models can be constructed. Inference concerning predicted values can be based on all the models in the a priori set, using "Akaike weights". Finally, estimates of precision can be computed, including a variance component for model selection uncertainty. Information-theoretic methods avoid the problems surrounding null hypothesis testing (e. g., the arbitrary a -level, the interpretation of P-values, the arbitrary classification of results into biological meaningless classes "significant’ and "not significant"). These issues are important in both applied and theoretical settings.

Utility of Population Viability Analyses for Recovering Kirtland's Warblers. JONATHAN BART*, USGS Forest and Rangeland Ecosystem Science Center, Snake River Field Station, Boise, ID, and CAROL BOCETTI, USGS Patuxent Wildlife Research Center, Laurel, MD.

We evaluate a series of population viability models to determine which—if any—provide reliable, new guidance on the best ways to recover an endangered species, the Kirtland's Warbler. The Kirtland's Warbler Recovery Team has defined "recovery" as occurring when population size reaches 1,000 pairs, and the recovery program, which involves creation of new habitat (jack pine) each year, is thus oriented toward meeting this goal. The management problems include how much habitat to create, whether the Warblers are area sensitive, and whether isolation of habitat patches reduces their likelihood of occupancy. The entire population of Kirtland's Warblers has been censused each spring since 1980. Detailed studies of birth and survival rates have also been conducted. Results from this work have been used to construct a series of viability models varying from simple birth and survival models, with no habitat- or age- based cohorts, to a spatially explicit, individual-based model with a complex movements simulator and age- and habitat-specific birth and survival rates. We will report on the utility of these models for answering the questions above about Kirtland's Warbler recovery and will discuss the applicability of these findings to other species and population viability analyses.

Viability Analysis of a Restored Population of the Federal Threatened Pitcher's Thistle (Cirsium pitcheri) in Illinois. TIMOTHY BELL*, Dept. of Biol. Sci., Chicago State Univ., Chicago, IL, MARLIN BOWLES, Morton Arboretum, Lisle, IL, JENNY MCBRIDE, Morton Arboretum, Lisle, IL, and KAYRI HAVENS, Chicago Botanic Garden, Glencoe, IL.

Pitcher's thistle (Cirsium pitcheri) is a federal threatened monocarpic herbaceous perennial of the western Great Lakes shoreline dune habitats. The plant is self-compatible, with little allozyme variation across its range. Population maintenance of this species depends on cohort replacement and recolonization of successional habitat maintained by shoreline processes. Succession also eliminates populations, while disturbances can either eliminate or create new habitat for populations. These dynamics require metapopulation persistence, in which local populations avoid simultaneous extinction by reacting independently to landscape-scale disturbances and colonizing newly formed habitats. Our population restoration in former Illinois habitat along Lake Michigan comprises Wisconsin, Indiana and Michigan seed sources. Because this species is monocarpic, annual translocation of greenhouse propagated plants was used to build up large cohort numbers. Spontaneous seedlings from flowering plants are now replacing these artificial cohorts, and the first flowering of these plant occurred in 1998. Morphological, demographic, and genetic (as shown by RAPDs) differences occur between geographically different seed sources, with Indiana plants having larger cotyledons and greater growth, survivorship and reproduction in the restoration. The restored Illinois population is now in its seventh year with nearly 150 plants, but population growth rate (lambda) is <1. Stage structured demographic analysis projects cohort sizes, number of spontaneous seedlings and, or, translocations, and amount of flowering needed to sustain population viability. For example, the minimum number of translocated seedlings needed to achieve a positive growth rate is twice the number of currently observed spontaneous seedlings.

How Good Are PVA Models: Testing their Predictions with Experimental Data. GARY E. BELOVSKY, Ecology Center & Dept. of Fisheries & Wildlife, Utah State Univ., Logan, UT.

There are a number of demographic models that have been developed for Population Viability Analysis (PVA). These models have been accepted and applied by conservation biologists although they have not been empirically tested. Testing PVA with the threatened/endangered species for which these models are designed is logistically impossible, and even common species cannot provide the necessary replicated field populations for testing stochastic models. Therefore, I developed an experimental system of populations differing in mean carrying capacity, environmental variability (random variation in carrying capacity) and initial population size that could be sufficiently replicated to test the extinction predictions of stochastic population models used in PVA. The experimental system employed brine shrimp (Artemia franciscana) populations in mesocosms maintained in environmental chambers where a measured food source was added regularly. Standard PVA models did very poorly in predicting observed mean population persistence and its variance. In general, the PVA models: 1) underestimated mean persistence time, and 2) underestimated the influence of carrying capacity and environmental variability. This means that most PVA analyses may be overly optimistic about population persistence. The implications are reviewed for several real conservation cases. Finally, the experimental results for brine shrimp are extended to examine the ability of brine shrimp to withstand current levels of commercial harvesting in The Great Salt Lake.

Effects of Changes in the Demographic Influences of Ocean Conditions on Viability of Pacific Salmon. LOUIS W. BOTSFORD, Dept. of Wildlife, Fish, and Conservation Biology, Univ. California, Davis, CA.

One of the means of improving the projections of population viability analyses is through a better understanding of the effects of demographic uncertainty and environmental variability on extinction probability. Pacific salmon are demographically unique for several reasons and are of great interest due to recent declines and listings. An important, outstanding uncertainty that limits our ability to determine the causes of declines is the influence of ocean conditions on Pacific salmon. Specifically there appears to have been a reduction in ocean survival in the mid-1970s that may have contributed to recent declines. There is also evidence that the age distribution and temporal nature of environmental variability changed. Here we examine how such changes in environmental variability influence probability of extinction using coho salmon and Snake River chinook salmon as examples. Specifically, we explain how various combinations of environmental effects at ocean entry and just prior to the spawning run influence viability of populations with various spawning age structures. The results are useful in planning research to identify mechanisms and in assessing relative jeopardy of various Pacific salmon stocks.

Reconciling the Small Population and Declining Population Paradigms. MARK S. BOYCE, College of Natural Resources, Univ. Wisconsin, Stevens Point, WI.

In a pointed essay in the Journal of Animal Ecology shortly before his death, Graeme Caughley (1994) suggested that conservation biology was plagued with 2 tracks: (1) stochastic models for small populations that have few direct conservation applications, and (2) empirical investigations of declining populations that tend to be case-specific yielding few generalizations. In the 5 years since Caughley's essay, several PVAs have demonstrated that conservation biologists are capable of merging theory and practice. Habitat-based PVAs for California gnatcatchers, grizzly bears, and spotted owls have combined GIS-based spatial analysis with stochastic population models to develop useful links between habitats and extinction risk. Despite progress, many of Caughley's concerns still plague conservation biology, and PVAs in particular. As Caughley pointed out, genetic models are still insufficiently developed and verified to form more than a general basis for conservation management. Theoretical population models are poorly tied to applications because we face major hurdles in developing statistical procedures for fitting models of sufficient complexity to capture the relevant ecology. The very nature of threatened and endangered species means that we seldom have sufficient sample sizes or replication to reliably estimate parameters for complex models. Simple models present fewer problems of statistical estimation, but may have behaviors that are so unrealistic as to be useless for projections into the future. Although adaptive management offered promise for linking science and conservation practice, institutional barriers have proven to be serious impediments. Based on a conviction that science can enhance conservation, we must give urgent priority to Caughley's charge that conservation biologists need to reconcile ecological theory and conservation practice.

Population Viability Analysis for the Marsupial Micoureus demerarae in Small Atlantic Forest Fragments in Southeastern Brazil. DANIEL BRITO*, Depto. Ecologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil, and FERNANDO FERNANDEZ Depto. Ecologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.

The fragmentation of the Brazilian Atlantic Forest has left many populations of forest-dwelling marsupials isolated in small forest remnants. Long-term viability of such populations is an open question. A PVA was carried out for populations of the arboreal didelphid Micoureus demerarae in two small (7.0 and 8.8 ha) fragments at Poço das Antas Biological Reserve. Analysis was based on field data obtained through a detailed demographic study carried out at the fragments since 1995. Both populations are very small (averages below 20 individuals) and are connected by dispersing individuals, therefore forming a metapopulation. Frequency of a catastrophe (fire) was estimated from the Reserve's historical records. A thousand simulations were carried out using Vortex. Results so far indicate that both populations taken separately, as well as their metapopulation, have extinction probabilities below 5% for twenty years, but rising to about 96% in a hundred years. The analysis will be improved by incorporating evaluations of genetic variation which are being undertaken at the same fragments. Our final aim is to carry out sensitivity analysis, in order to help understanding what factors are most critical for the persistence of isolated populations of Micoureus demerarae (Funding: Fundação O Boticário de Proteção à Natureza, MacArthur Foundation, FAPERJ, PROBIO).

Evaluating the Predictions of Population Viability Analysis (PVA). BARRY W. BROOK*, Key Centre for Biodiversity and Bioresources, Macquarie Univ., NSW, Australia, RICHARD FRANKHAM, Key Centre for Biodiversity and Bioresources, Macquarie Univ., NSW, Australia, and MARK A. BURGMAN, School of Botany, Univ. Melbourne, Parkville, Victoria, Australia.

Population viability analysis is widely used in conservation biology to predict extinction probabilities and compare management strategies for endangered species. However, it is unclear if different PVA packages produce similar predictions, and whether the predictive models realistically describe the behavior of wildlife populations. Six commonly applied PVA packages, GAPPS, INMAT, RAMAS (Age, Stage and Metapop) and VORTEX, were compared for a range of life-history types. The major findings were: (1) when complex processes were included in the models, large differences were found between some packages, and even versions of the same package. The pattern of similarities and differences altered depending on the species examined. (2) When completely standardized, a consistent difference was revealed between the predicted extinction probabilities of the matrix-based packages (INMAT and RAMAS) compared to those that were individual-based (GAPPS and VORTEX), due largely to a subtle difference in the way demographic stochasticity is modeled. Clearly caution must exercised when interpreting the outcomes of any one PVA package, as their predictions not necessarily concordant. (3) A set of retrospective tests using the historical data of over twenty long-term population studies was conducted, to test the predictive reliability of PVA. It was found that the quasi- extinction and -recovery probabilities predicted by the PVA packages did not realistically reflect the actual population fluctuations. The models also failed to accurately predict future population abundance. (4) A validation and refinement process for PVA was developed, which helped to improve the projections. Current PVA packages cannot be relied upon to produce accurate quantitative predictions.

Demographic Models and Population Viability Analysis: The Surface Has Only Been Scratched. HAL CASWELL, Biology Dept., Woods Hole Oceanographic Institution, Woods Hole, MA.

Like the rumors of Mark Twain's death, recent claims about the limitation of demographic models (based on matrices or other mathematical frameworks) in PVA are greatly exaggerated. Data on endangered species are often limited and uncertain. Both populations and the environments in which they live are complex systems. Neither of these facts suggests throwing away the most powerful tools available for exploring the consequences of those data and the interaction of the environment and the population. I will show how simple matrix population models can be used to quantify the importance of environmental variation, the consequences of demographic as well as environmental stochasticity, and the importance of uncertainty in data. I will briefly consider the concept of "validation", and argue that it is widely misunderstood in the context of demography.

Effects of Individual Heterogeneity in Estimating the Persistence of Small Populations. MARY M. CONNER*, Dept. of Fishery and Wildlife Biology, Colorado State Univ., Fort Collins, CO, and GARY C. WHITE, Dept. of Fishery and Wildlife Biology, Colorado State Univ., Fort Collins, CO.

Demographic, temporal, spatial, and individual heterogeneity are important factors affecting the probability of persistence of small populations. Demographic, spatial, and temporal stochasticity have been incorporated into some Population Viability Analyses (PVA), but individual heterogeneity has not been taken into account. We developed a mathematical simulation model that included baseline demographic stochasticity with varying amounts of temporal and individual stochasticity for different population sizes. As temporal variation increased, the probability of population persistence decreased no matter what the initial population size. However, individual heterogeneity had the opposite effect of temporal heterogeneity. We found that increases in individual variation lead to an increase in the probability of population persistence. Although the increase in persistence in our model was due to random differences in individual survival and mortality probabilities, natural selection provides a mechanistic explanation for this increase of population persistence. Genotypes persisting through a decline may be those that survive better under the conditions causing the decline. Individuals that survive and reproduce in the face of adverse conditions may extend the probability that a small population persists. If variations in life-history traits, such as birth and death parameters, are considered to be affected only by demographic and temporal factors in PVA models, then probabilities of population persistence may be biased low. From a management standpoint, this bias leads to conservative estimates of population persistence in population viability models.

PVA for Plants: Understanding the Demographic Consequences of Seed Dormancy and Disturbance Events in the Face of Limited Data. DANIEL F. DOAK*, Dept. of Environmental Studies, Univ. California, Santa Cruz, CA, DIANE THOMSON, Dept. of Environmental Studies, Univ. California, Santa Cruz, CA, ERIK S. JULES. Dept. of Environmental Studies, Univ. California, Santa Cruz, CA.

Most PVAs rest upon some form of demographic modeling. However, the life histories of many rare plants share two features that greatly complicate the estimation and use of demographic data for viability assessment: seed banks and strong responses to rare and unpredictable disturbance events. These traits are vexing because they are governed by demographic rates that can be extremely difficult to quantify, especially over the short time periods typically available for conservation planning. Furthermore, in many cases these features can mean that census and demographic information for adult populations of plants may yield virtually no information about population viability. Using data from two rare California forbs, in addition to a variety of simulated data sets, we explore the problems of imperfect data and plant life histories for conservation planning. In particular, we emphasize how poor or misleading data on seed banks and disturbance responses can bias estimates of extinction times and population growth rates for plants, as well as for other species. Finally, we use data on broad life history patterns in plants, in combination with simulation models, to evaluate practical techniques for developing PVAs of difficult species with limited data.

Model-based Conservation Decision Making under Ecological Uncertainty. MARTIN DRECHSLER, Dept. of Ecological Modelling, Environmental Research Centre, Leipzig, Germany.

A method of decision making is presented that can be used to compare alternative management actions under ecological uncertainty and to identify which one is likely to have the strongest effect on population viability. The method combines decision analysis with population modeling and uses both information about the population patterns and the population processes. The process knowledge is used to construct the population model and determine plausible ranges for its parameters. The values of these parameters are likely to have an impact on the rank order of the most effective management actions, and unless their ranges are small, there is uncertainty in the management rank order. This uncertainty is encompassed by considering a number of different population parameter combinations, called key scenarios. For each of them a sensitivity analysis is performed and a management rank order determined. In the following decision analysis each key scenario contributes with a certain weight which reflects its biological plausibility. To determine the weight of a particular key scenario, the population dynamics are simulated and the generated patterns are compared with those observed in the real population. The higher the similarity between the two patterns the higher the weight assigned to the key scenario. The decision analysis finally synthesizes the results of sensitivity and pattern analyses and generates a single rank order of the most promising management actions. The method is demonstrated on a case study of the endangered Orange-bellied Parrot Neophema chrysogaster (Australia).

A Population Viability Assessment Model for Captive Breeding Programs. JOANNE M. EARNHARDT, Lincoln Park Zoo, and Dept. of Ecology and Evolution, Univ. Illinois, Chicago, IL

The interaction between wild and captive populations increases as threats to wild populations increase. Captive and wild populations are inexorably linked because captive populations rely on founders either for their colonization or for maintenance of genetic health, and, increasingly, endangered wild populations rely on captive specimens to augment declining wild populations. Because captive and wild populations are tightly bound, the long-term persistence of captive populations is a critical issue for conservation. Management of both types of populations uses computer modeling tools to direct genetic and demographic decisions; however, those tools are not universally applied across the wild-captive conceptual barrier. Methodologies exist for assessing viability of wild populations in our varying environment, but no comprehensive models have been developed for assessment of long-term viability of captive populations. In the development of a Population Viability Assessment model for captive populations, I compared demographic, genetic, and environmental factors under stochastic scenarios in the extinction assessment for both types of populations. Conceptual models for captive and wild populations were diagramed for comparison, the variation in the magnitude of the variables between captive and wild populations was documented, and a preliminary design for captive population viability analysis was developed. Captive populations present unique modeling issues because of the impact of "ceiling"-type carrying capacity and because of genetic and demographic strategies imposed by managers of captive breeding populations. Yet ultimately, captive population viability, similar to wild population viability, will be based on population size, composition of these populations, and on management strategies.

What Do Rare Species Have in Common? REGIS FERRIERE*, Lab. Ecologie, Ecole Normale Supérieure, Paris, France, and Dept. of Ecology and Evolutionary Biology, Univ. Arizona, Tucson, AZ, and OLIVIER RENAULT, Lab. Ecologie, Univ. Paris 6, France.

Rare species have been attracting much attention in recent years, due to an acute concern for their preservation. Since designing conservation plans requires a detailed knowledge of the target species' life history a major question has arisen: do rare species differ in biologically significant traits from common ones? So far insights into this issue have been scarce, disparate and ambiguous. Beyond the fact that reliable data on the biologies of very rare species are exceedingly difficult to collect, the diversity of ways in which studies have been performed (which definition of rarity is applied, how traits are measured, whether environmental differences between populations and phylogenetic effects are accounted for) have greatly confused the analysis of rare-common differences. Perhaps most importantly, no robust theoretical predictions were available to guide empirical work, due to the difficulty of handling models of small populations in which stochastic effects have paramount importance. Here we make use of recent advances in the mathematical theory of multitype branching processes to derive general predictions on life-history traits expected to be associated with rarity. We use the novel framework of adaptive dynamics theory to examine under which conditions rarity may develop as a by-product of natural selection favoring such trait combinations. We confront these predictions with data obtained from the long-term study (14 yrs) of a community of Mexican mountain rattlesnakes (Crotalus willardi willardi, C. lepidus klauberi and C. pricei pricei) known for having the most restricted geographic range among snakes in the U. S.

Population Viability Analysis with Limited Data. JOHN R. FIEBERG*, Dept. of Biomath., North Carolina State Univ., Raleigh, NC, and STEVE P. ELLNER, Dept. of Biomath., North Carolina State Univ., Raleigh, NC.

Population viability analyses are often based on matrix models, made stochastic to account for demographic, environmental, and catastrophic variation in vital rates. One strategy commonly employed is to simulate population projections by randomly choosing among sampled rates. Alternatively, one can use the sampled data to parameterize a probability distribution from which rates can be drawn each year to project the population. Survival and fecundity rates in many natural populations are highly variable from year to year, and therefore, vital rates may have to be sampled for many years before one can accurately characterize the distribution of vital rates (over time). We examine the reliability of conclusions obtained from the above methods given the paucity of data typically available in real life problems. Our results indicate that even a moderate amount of variation in year to year transition rates can seriously undermine the reliability of conclusions drawn.

The Importance of Parameter and Variance Component Estimation in Population Viability Analysis. ALAN B. FRANKLIN*, Colorado Coop. Fish & Wildlife Research Unit, Colorado State Univ., Fort Collins, CO and TANYA M. SHENK, Colorado Div. of Wildlife, Fort Collins, CO.

The results of any population viability analysis (PVA) are predicated on basic parameter estimates, such as abundance or survival, and their associated variance estimates that are used to construct the PVA model. We investigated two problems in parameter estimation that affect the outcomes of PVA: 1) confusing sampling and process variance associated with parameter estimates, and 2) using invalid estimates of parameters. Associated with any parameter estimate are two types of variance: sampling variance (attributable to estimating a parameter from sample data) and process variation (the variation in a given parameter). In the first problem, either sampling variance or total variation (sampling combined with process variation) is often used in lieu of process variance. While the former tends toward slower extinction times when parameters are precisely estimated, the latter tends toward quicker extinction times. In the second problem, invalid parameter estimates can result from, for example, ignoring detectability by using simple counts of animals to estimate abundance and survival. Besides being biased, invalid parameter estimates can also dramatically affect estimates of process variance. The use of simple counts result in estimates that are confounded with detectability. If the true population varies little but detectability exhibits large variation, then parameter estimates of, say, survival may exhibit large temporal process variation solely due to changes in detectability. We illustrate these points with computer simulations, and case studies from the northern spotted owl and Preble's meadow jumping mouse using popular PVA software packages.

Use of Population Viability Analysis in Endangered Species Act Listing and Recovery Decisions for Marine Mammals. LEAH R. GERBER*, Washington Cooperative Fish and Wildlife Research Unit, School of Fisheries, Univ. Washington, Seattle, WA, and DOUGLAS P. DEMASTER, National Marine Mammal Laboratory, Alaska Fisheries Science Center, Seattle, WA.

The Endangered Species Act mandates that Recovery Plans include specific criteria to determine when a species should be removed from the List of Endangered and Threatened Wildlife. In order to meet this mandate, we develop a new approach to determining classification criteria for large whales. The key idea is that endangerment depends on two critical aspects of a population: population size and trends in population size due to intrinsic variability in population growth rates. The way to combine these features is to identify a population size and range of population growth rates (where l denotes the annual multiplicative rate of change of a population) above which there is a negligible probability of extinction. To do so: 1) information on the current population size and its variance are specified, 2) available information on vital rates or changes in abundance over time is used to generate a probability distribution for the population’s l, 3) the lower 5th %-ile value for l (denoted as l _(.05)) is obtained from the frequency distribution of l’s, and 4a) if l _(.05) is less than 1.0, a backwards population trajectory starting at 500 individuals for a period of 10 years is performed and the resulting population size is designated as the threshold for endangered, or 4b) if l _(.05) is greater than or equal to 1.0, the threshold for endangered is set at 500 animals. A similar approach can be used to determine the threshold for threatened under the ESA. We applied this approach to North Pacific humpback whales, with uncertainty in l’s resulting from sampling error and environmental fluctuations. We used Monte Carlo simulations to produce a frequency distribution of l’s for North Pacific humpbacks under three different scenarios. Using the 5th %-ile l, it was determined for the central and eastern populations of North Pacific humpback whales that the best estimates of current abundance were larger than the estimated threshold for endangered, but less than the estimated thresholds for threatened. This analysis leads to a recommendation to downlist the central stock of humpback whales to a status of threatened, while maintaining the eastern and western stock as endangered.

PVA: Questions, Answers, and the Use of PVA. MICHAEL GILPIN, Dept. of Biology, Univ. California, San Diego, CA..

PVA, population viability analysis, is an umbrella concept that covers a general set of models incorporating a probability of extinction at some time in the intermediate future (10-1000 years). There are three general situations that arise repeatedly in conservation decision making: populations that have declined to very low numbers, populations that have been fragmented into isolated patches, and populations that have been harvested or otherwise perturbed. Different types of PVA models must be used in these different cases. The simplest approach of PVA is to base the extinction probability on a projection of current trends. Often required, however, are more mechanistically based PVAs that allow modification of ecological and landscape parameters, so that the impact on extinction probability of a proposed action can be evaluated. These actions may involve exploitation of resources or development that threaten or jeopardize the population, or they may be conservation programs to recover the population or to establish conservation reserves.

Asymptotic Quasi-stationarity of Markovian Models of PVA. FREDERIC GOSSELIN*, Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, Montpellier, France, and JEAN-DOMINIQUE LEBRETON, Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, Montpellier, France.

Contrary to deterministic matrix population models, PVA models lack a theoretical framework to refer to. Among other things, this implies in different publications the periodical "re-discovery" of theoretical results, the varying estimation of similar quantities, and some difficulty in comparing models' results. We here propose asymptotic mathematical results that are sufficiently general to be referred to in most individual-explicit PVAs and population-explicit metapopulation PVAs. These results imply the quasi-stationarity of the model: i.e. the model ultimately almost surely goes extinct, but, if we consider only the non-extinct replicates at any given time, it asymptotically stabilizes in a probability distribution that does not depend on the initial state of the model. This particularly implies that the population has an asymptotic survival rate, as if it were a unique individual, that exhibits the asymptotic interplay between persistence and extinction. Furthermore, different notions of quasi-stability are obtained whether we consider a unique trajectory or a set of many trajectories. Mathematically, these results somewhat resemble those known for deterministic matrix models. They are however a little more difficult to apprehend, but biologically more general, since, among other things, they can apply to models including both demographic and environmental stochasticity, density-dependence, a finite number of different kinds of individuals. We finally discuss the way these results could be usefully applied in PVAs and other individual or population-based models.

A Unifying Approach to Analyzing Persistence of Model Populations. VOLKER GRIMM*, Dept. Ecological Modelling, Centre for Environmental Research, Leipzig, Germany, and CHRISTIAN WISSEL, Dept. Ecological Modelling, Centre for Environmental Research, Leipzig, Germany

Analyzing persistence of small populations has become a key issue in ecology and conservation during the last decade. Unfortunately, a conceptual unification of this field has not yet been developed. Analytical approaches are ponderous and restricted to very simple models. On the other hand, individual-based simulation models allow for more realism but are often not fully explored because of a lack of tools based on theoretical insights. We present a unifying approach which aims at bridging the gap between analytical and simulation approaches. Our approach is based on the notion of "established state" which means a population dynamic characterized by a quasi-stationary distribution of population sizes and by the fact the extinction risk per short time interval is constant. From this notion, we derive the simple but powerful "ln(1-P₀)-plot" with P₀(t) being the probability of extinction by time t. This plot allows us to determine two quantities which are decisive for assessing persistence: T_m,, the mean time to extinction, and P_e, the probability that a model population which is in a certain state will reach the established population dynamic. With T_m, risk of extinction by time t may be calculated for different time frames of interest, and with P_e a threshold population size can be determined below which a population will go extinct quickly. We demonstrate the potential of our unifying approach by presenting analyses of several models addressing particular problems and species.

Pedigree Models for Managing Small Populations in the Wild. SUSAN M. HAIG, USGS Forest and Rangeland Ecosystem Science Center, Corvallis, OR.

Pedigree analysis is perhaps one of the least known, most poorly understood, but useful genetic models for understanding processes in small populations. Pedigree analysis was developed for assessing management strategies in captive populations, but is helpful in understanding processes in natural populations as well. It is a way of avoiding the adverse effects of inbreeding depression by identification of specific individuals contribution to loss of genetic variability in a population. It can be used as a descriptive tool or as a means of testing hypotheses regarding population structure prior to reintroduction or translocation. Pedigree analysis is based on the Gene Drop model, a Monte Carlo simulation where following construction of a simple data set, 10,000 iterations of the model represents sampling an individual's entire genome. Results are summarized via description of: founder contribution, the number of unique alleles surviving, heterozygosity, founder genome equivalents, mean kinship and inbreeding coefficients. The most positive aspects of pedigree analysis are that the data sets required are easy to construct, the programs are easy to run, and because the model takes into account the exact structure of the pedigree, it is quite realistic. The greatest obstacle is the need for a deep pedigree derived from marked individuals. Gene Drop analyses could be considered intermediate analyses between using molecular markers to identify individuals prior to inclusion in a Gene Drop and subsequent use of PVA to further evaluate consequences of introducing individuals identified in the Gene Drop. Examples from our work on Red-cockaded Woodpeckers will illustrate this point.

Modeling Habitat Restoration for San Joaquin Kit Fox: Effects of Patch Size, Immigration, and Stochastic Prey Abundance on Population Persistence. ROBERT G. HAIGHT*, USDA Forest Service, Pacific Southwest Research Station, Albany, CA, PATRICK A. KELLY, Endangered Species Recovery Program, Fresno, CA. KATHERINE RALLS, National Zoological Park, Smithsonian Institution, Washington, DC.

During the last 100 years, the San Joaquin Valley in central California experienced great loss of biodiversity as millions of acres of natural land were converted to cropland and cities. The recovery plan for upland communities of the San Joaquin Valley is largely based on the habitat needs of the San Joaquin kit fox, a nocturnal species that hunts insects, rodents, and rabbits. Remaining kit fox populations live in a few natural areas in the valley and surrounding foothills. The overarching recovery strategy is the establishment of a network of conservation areas linked by rangeland or restored parcels of marginal agricultural lands. Because funds for farmland retirement and habitat restoration are limited, it is important to identify and prioritize areas for restoration. To help this process, we wanted to know how fox populations would likely grow in more-or-less isolated habitat patches. We were concerned about the efficacy of restored areas because they will likely be small (less than 300 square kilometers) and subject to low levels of immigration because of dispersal barriers in surrounding cropland. Furthermore, because of high year-to-year variation in rainfall, prey abundance will likely fluctuate over time. We addressed our concern by developing a simple meta-population model for a local fox population and predicting the relative effects of patch size, immigration, and stochastic prey abundance on a 50-year population trend. The most important results were the effects of stochastic prey abundance, which caused periodic fluctuations in fox reproduction. With constant prey abundance and reproduction rate, fox populations saturated isolated patches that could support 8-32 fox territories. However, with prey fluctuations based on survey data from the Carrizo Plain (near the southern end of the San Joaquin Valley), consequent fluctuations in reproduction rate caused extinctions across a range of patch sizes. Low levels of immigration (1-2 foxes per year) dampened the effects of prey fluctuations and sustained the populations. The results suggested that fox dispersal between patches will be key to sustaining fox populations in restored valley habitat because of fluctuating prey abundance.

Colonization and Extinction Dynamics and PVA. ILKKA HANSKI, Dept. of Ecology and Systematics, Univ. Helsinki, Finland.

Many species have a fragmented population structure and it is hence appealing to consider applying the classic metapopulation concept in their PVA. By the classic metapopulation concept I refer to situations where there is widespread population turnover and where the metapopulation essentially persists in a stochastic extinction-colonization balance. Examples will be given. n other cases population turnover may not be important yet migration may influence local and metapopulation dynamics and hence also e.g., the risk of extinction. if one is primarily interested in extinction-colonization dynamics, models can be parameterized with data that are not too difficult to obtain if one can assume that the metapopulation from which data are collected occurs at a positive quasi-equilibrium. Once the model has been parameterized, it can be applied to other landscapes to predict e.g., expected time to extinction. The problem however is that many metapopulations of endangered species may not occur at a positive quasi-equilibrium in any landscape. Parameterizing models for such situations is much more difficult. In any case, predictions about ultimate extinction times are hardly of great interest, because substantial environmental changes are likely to occur at a faster time scale. Metapopulation models may be most useful for comparing alternative scenarios of landscape management and especially for predicting the occurrence of currently not critically endangered species. For the latter, population-oriented approaches are probably more helpful.

Is Plant Population Viability Influenced by Metapopulation-level Processes? SUSAN HARRISON, Division of Environmental Studies, Univ. California, Davis, CA.

From the perspective of population and metapopulation viability, plants differ from animals in several important ways. Long-distance dispersal is much harder to observe directly in plants, and it may be generally less important in plants than in animals, since plants may resist local extinction through having seed banks. Pollination provides a second route by which spatial isolation may influence plant population viability, however. A review of plant studies shows almost no evidence for the importance of long-distance seed dispersal in population persistence. There is modest evidence that large-scale spatial isolation influences pollination, reproduction, and persistence in plant populations. Metapopulation aspects of viability may only be worth incorporating into models if they are first demonstrated empirically.

A Population Viability Analysis for the Houston Toad. JEFF S. HATFIELD*, USGS Patuxent Wildlife Research Center, Laurel, MD, ANDREW H. PRICE, Texas Parks and Wildlife Dept., Austin, TX, and LISA O'DONNELL, U.S. Fish and Wildlife Service, Austin, TX.

The endangered Houston toad (Bufo houstonensis) is endemic to central and southeast Texas, occurring in nine isolated populations along two separate geologic bands which support deep, friable sandy soils. This species is thought to be declining due to habitat loss, aggravated by catastrophic events such as droughts, and possibly hybridization with other species. Currently, this toad's habitat is protected in only one area, Bastrop State Park (BSP). We analyzed capture-recapture data collected there during 1990-97 and conducted a population viability analysis with RAMAS Metapop software using an age-structured model. Single population models suggest that the relatively low adult female survival rate of 16% per year, combined with low rates of juvenile survival, along with catastrophic events, may be responsible for the decline of this species. Metapopulation models suggest that a relatively low probability of extinction (over 100 years) can be achieved if several populations, each of the size maintained at BSP, are protected and connected by dispersal of individuals (natural dispersal if corridors are maintained, or human-assisted dispersal if corridors are not an option). Increasing the survival rate of tadpoles by controlling predators in the breeding ponds, preventing ponds from drying out before tadpoles have metamorphosed, and possibly increasing the number of ponds, may also help this species recover.

Application of Molecular Genetics to Managing Endangered Species. PHILIP W. HEDRICK, Dept. of Biology, Arizona State Univ. Tempe, AZ.

Molecular genetics can be used to answer questions in conservation that other information may not be able to explicitly address. For example, highly variable genetic markers have been used to determine what are and what are not evolutionarily significant units and to identify populations that have had reduced population size. Examples of both applications will be discussed. However, application of highly variable markers must be used cautiously. In particular, measures of differentiation may be greatly affected by the amount of genetic variation, genetic distance may be greatly influenced by only a few generations of genetic drift, and statistical significance and biological significance may be uncoupled.

Taking a Broader View: Elasticity Analysis of Species Life Histories to Prioritize Research and Management Efforts. SELINA S. HEPPELL, U.S. Environmental Protection Agency, Western Ecology Div., Corvallis, OR.

For most declining populations we do not have detailed demographic or dispersal data to parameterize spatially explicit, stochastic models. While there is heuristic value to running these models with a range of parameters, the number of potential combinations may be limitless for poorly known species. In these situations, we must rely on simpler models (and hence ask simpler questions) and find ways to group species to avoid the need for complete population-specific demographic information. Elasticity analysis of deterministic matrix models gives the proportional contribution of each vital rate (survival, growth and reproduction) to a population's intrinsic rate of increase. While the assumptions of the model restrict it to qualitative predictions about population responses to perturbation, elasticity analysis can be useful for: 1) identifying management options with high or low probability of success, 2) grouping populations or species according to life history traits that are likely to affect their responses, and 3) providing initial information about the sensitivity of different vital rates to guide more complex models or simulations. In a comparative study of 50 mammal life tables, I found that the elasticity of population growth to changes in fertility, juvenile survival and adult survival follow predictions of life history theory and can be estimated from very limited demographic information. Currently, I am using elasticity analysis to categorize amphibian populations according to their likely response to landscape change. This approach, while unable to predict population viability in the strict sense of extinction probability, utilizes readily available information and provides a first step for prioritizing research and management efforts.

Population Extinction: Genetics, Dynamics and Ecology. KEVIN HIGGINS*, Dept. of Biology, Univ. Oregon, Eugene, OR, and MICHAEL LYNCH, Dept. of Biology, Univ. Oregon, Eugene, OR.

New theoretical results on mechanisms of population extinction have focused on synergistic interactions between population genetics and population dynamics. A mechanistic understanding of extinction in terms of the combined impact of population ecology, population genetics and population dynamics is virtually unexplored. Life history and spatial structure have the potential to markedly influence population dynamics and modify the conclusions of earlier work based on a single panmictic population with simple life history. Within this context 1) we investigate how the accumulation of mildly deleterious alleles is affected by barriers to gene flow; and 2) How the interaction between population dynamics and the accumulation of mildly deleterious alleles sets the probability of metapopulation extinction.

A Bayesian Approach to Including Uncertainty in a Hooker's Sea Lion PVA. RAY HILBORN* Sch. of Fisheries, Univ. Washington, Seattle, WA, MIGUEL PASCUAL, Dept of Zoology, Univ. Washington, Seattle, WA, LEAH GERBER, Washington Cooperative Fish and Wildlife Research Unit, Sch.. of Forestry, Univ. Washington, Seattle, WA, FRANCES GULLAND, The Marine Mammal Center, GGNRA, Sausalito, CA, and MARK MAUNDER, Sch. of Fisheries, Univ. Washington, Seattle, WA.

A Bayesian statistical framework is used to calculate the extinction risk to Hooker's sea lion (Phocarctos hookeri) under different levels of incidental mortality in a squid fishery. The analysis explicitly includes (1) meta-population structure with dispersal between existing and potential breeding sites, (2) random catastrophic events that might strike one or more of the breeding sites, (3) depensatory effects causing reduced population growth rates at small population sites, (4) calculation of extinction risk rather than arbitrary pseudo-extinction thresholds, (5) integrated Bayesian analysis of the existing data for Hooker's sea lion, and (6) an analysis of the frequency of catastrophic events and intensity of depensation from similar species. We considered different models of dispersal and suggest that the probability of dispersal should increase with increasing density, and that the probability of dispersal between two sites should decrease with distance. We found that the extinction risk in 200 years under current levels of by-catch is 0.3%, without by-catch it is 0.16%, and with an adaptive by-catch policy in which the fishery would be closed if the population size declined below a threshold it is 0.22%.

Population Viability Analysis and Conservation Policy: Lessons Learned/Lessons Spurned. LAURA HOOD, Defenders of Wildlife, Washington, D.C., INGRID LATCHIS, Defenders of Wildlife, Washington, D.C., BILL SNAPE, Defenders of Wildlife, Washington, D.C., and MARK SHAFFER, Defenders of Wildlife, Washington, D.C.

A qualitative survey of the application of population viability analysis (PVA) in the policy and management arena suggests three major lessons that have been learned, but not acted upon. First, the major limitation to the meaningful application of PVA to conservation problems, namely the lack of detailed population data for many taxa, has been know for 15 to 20 years, yet little has been done to address that weakness. If research (National Science Foundation, U.S. Geological Survey/Biological Research Division) and management institutions (U.S. Fish and Wildlife Service, Forest Service, etc.) had launched long-term, in-depth population ecology studies of carefully selected surrogate or exemplar species, this problem would now be well on its way to a solution. Second, the single "rule-of-thumb" to emerge from the PVA community that seems to have endured the scrutiny of time is Soule's observation that, for vertebrate species at least, populations of less than a few thousand individuals are either in trouble, or likely will be so in the near future. Yet the median population goal to pronounce a species "recovered" is 1522. Third, for all the talk about PVA, and all the many places in federal wildlife law where its concepts could be put to use, there is still no statutory or regulatory definition that provides a meaningful benchmark for society to know how "conserved" any particular taxa is or is not.

The Use of Population Viability Analysis for the Endangered Sonoran Pronghorn Recovery Plan and in a Legal Challenge. DENNIS A. HOSACK*, Defenders of Wildlife, Washington, DC, PHILIP S. MILLER, Conservation Breeding Specialists Group, Apple Valley, MN, JOHN J. HERVERT, Arizona Game and Fish Dept, Yuma, AZ, and ROBERT C. LACY, Chicago Zoological Society, Brookfield, IL.

Sonoran pronghorn (Antilocapra americana sonoriensis) is one of five subspecies of pronghorn and was listed as an endangered species in 1967. The 1982 recovery plan proposed a recovery goal of 300 individuals, although no credible scientific explanation of this recovery goal number has been put forth A Population Viability Analysis (PVA) workshop was organized in 1996 to attempt to provide a more scientifically valid goal. In addition, and pursuant to Section 7 of the Endangered Species Act, Defenders of Wildlife has filed suit against 12 federal agencies for failure to take appropriate steps to protect and recover the Sonoran pronghorn. Current best estimates for the US population of Sonoran pronghorn is 130-160 animals. The results of the PVA suggest that, given the best estimates of current demographic rates, the likelihood of Sonoran pronghorn extinction is 1% within the next 25 years, 9% within 50 years, and 23% within the next 100 years. In addition, the analysis suggested that the population is extremely sensitive to fawn mortality, with the likelihood of extinction increasing markedly when fawn mortality exceeds 70%. Although there was considerable debate among participants about many of the variables and suggestions for recovering the species, it was unanimous that maintaining 95% of the current genetic diversity was a top priority. The results of the workshop analysis indicated that although carrying capacities of 300 animals might be as likely to insure simple survival, only at carrying capacities at or above 500 would the long-term genetic goal be likely to be achieved.

Modeling Equilibrium Population Size and Life-stage Structure for Site-dependent Species. W. GRAINGER HUNT*, Predatory Bird Research Group, Univ. California, Santa Cruz, CA, and PETER R. LAW, Predatory Bird Research Group, Univ. California, Santa Cruz, CA.

Spatial partitioning by pairs of territorial birds restricts cohort size per unit area of landscape, setting an upper limit to an equilibrium size range for the total population deriving from any defined area. Floaters maintain the lower limit by filling territorial vacancies. This phenomenon, known as Moffat's equilibrium, provides the basis for modeling age- and stage structure either under the assumption of annual constancy in vital rates or with variation thereof. The floater-to-breeder ratio at equilibrium is a more informative indicator of population health and stability than a growth rate estimate. The adaptive threshold of site serviceability implied by the existence of floaters (of both sexes) underscores the importance of identifying and conserving the elements of high quality breeding areas for threatened or endangered species. To illustrate these points, we present modeling results of an ongoing study of golden eagle population dynamics in west central California.

Individual Variation Can Influence Population Extinction Risk. HENRIETTE I. JAGER*, Oak Ridge National Laboratory, Oak Ridge, TN and WEBB VAN WINKLE, Oak Ridge, TN

We are conducting a population viability analysis for a fish species with extreme variability in its reproductive life history characteristics. White sturgeon (Acipenser transmontanus) females mature between the ages of 13 and 25 years and at intervals of 2 to 10 years thereafter. Adults with access to the ocean make periodic spawning migrations from the estuary to the river environment. We examined the effects of individual variability in life history parameters on viability predictions from an individual-based population model that incorporated both genetic and environmental variation among individuals. We addressed the following questions: (1) How does individual variation in two traits, age at first maturity and rematuration interval, influence the likelihood of persistence?; (2) Does heritable variation in these traits increase the likelihood of persistence?; and (3) Do changes in the simulated selective regime corresponding to conditions before and after dam construction lead to a shift in mean age at maturity?. The likelihood of persistence predicted by simulations with no variation differed from those predicted by simulations with realistic individual variation in age at maturity. This suggests that it may be important to represent realistic individual variability in life history traits in population viability models designed for species that show high variation. When we simulated a genetic basis for age at first maturity, we found that heritable individual variation increased the simulated likelihood of persistence. Our results raise questions about predicting population responses to man-altered environments with highly modified selective regimes.

Development of a PVA to Identify Research and Management Priorities for a Population of West Indian Manatees in Northeastern Costa Rica. IGNACIO JIMÉNEZ, Regional Wildlife Management Program for Mesoamerica and the Caribbean, Universidad Nacional, Heredia, Costa Rica.

Northeastern Costa Rica harbors the main population of the West Indian manatee in the country and the species is endangered in the area. I developed a population viability analysis (PVA) for the West Indian manatee in northeastern Costa Rica using the software VORTEX to: 1) identify management and research priorities in the area, 2) assess the temporal margin left to local managers to conserve the species, and 3) identify sources and sinks in the local metapopulation. The PVA detected hunting and migration rates, and the carrying capacity of the southern subpopulations as the factors most relevant to population survival. It also showed that survival of manatees in Costa Rica depends on conservation activities carried out in neighboring Nicaragua. Southern subpopulations in the study area act as sources while the northernmost subpopulation behaves as a sink for the whole metapopulation. Research activities to conserve manatees should focus on the animals’ movements and a more precise estimate of hunting rates at both sides of the border between Costa Rica and Nicaragua. Management activities highlighted by the PVA as most needed are: 1) enforcement of laws against poaching and illegal gillnetting in local watercourses, 2) habitat conservation focused in the southern area, and 3) development of bi-national conservation activities between Nicaragua and Costa Rica. Measures to conserve the species should be taken before it falls into a critical situation that could be too difficult to reverse.

Using Demographic Models to Assess the Causes of Recovery: New Insights into the Management of the Peregrine Falcon in California. MATT KAUFFMAN*, Dept. of Environmental Studies, Univ. California, Santa Cruz, CA, and WINIFRED FRICK, Dept. of Environmental Studies, Univ. California, Santa Cruz, CA.

The peregrine falcon (Falco peregrinus) has been touted as a success story of endangered species management. In 1970, the peregrine was on the brink of extinction due to pesticide-induced eggshell thinning. DDT was banned in the USA in 1972 and re-introduction efforts followed. In California, peregrines have increased steadily (140 birds at present, up from 5 in 1970) and were recently de-listed. However, no studies have analyzed whether this recovery is due to: 1) intensive re-introductions, or 2) real demographic improvement due to DDT dissipation. The re-introduction effort has been substantial and sustained—754 birds released since 1977—while long-term monitoring shows no significant declines in eggshell thinning. We conducted a modeling analysis designed to investigate the effects of augmentation and/or an ameliorating environment on the last twenty years of peregrine population growth. To do this, we combined individual records of stage-specific introductions with long-term demographic data to construct two contrasting models: 1) population growth with augmentation only and no accounting for DDT dissipation, and 2) population growth with augmentation and an ameliorating environment reflected by yearly improvement in nest success. We then tested the results of these models against actual population projections using Maximum Likelihood techniques. Our results provide the first quantitative assessment of the effectiveness of the peregrine re-introduction effort, as well as demographic evidence useful in determining whether or not the effects of DDT have been significantly reduced. This work has implications for predicting peregrine population growth and for establishing future management goals for the de-listed peregrine.

Population Viability Analysis for Serengeti Cheetahs. MARCELLA J. KELLY*, Dept. of Wildlife, Fish, and Conservation Biology, Univ. California, Davis, CA, and SARAH M. DURANT, Inst. of Zoology, Zoological Society of London, Regent's Park, London.

Previous modeling attempts for Serengeti cheetahs have produced conflicting results that have implicated either juvenile or adult survival as the primary factor influencing population dynamics. In this study, we provide a thorough analysis of cheetah population dynamics in order determine the viability of the species. We parameterize our model with values based on 20 years of field data and compare our model projections to the actual data. First, we briefly examine the sensitivity of deterministic growth rate. However, populations that on average are stable or have positive population growth, are still subject to stochastic decline or extinction. Therefore we use simulation modeling to analyze extinction risk based on our variance estimates from our field data. In addition we examine the sensitivity of extinction risk to changes in the demographic parameters and to changes in the variance surrounding those parameters. Our results confirm that the population growth rate is most sensitive to changes in adult survival, followed by juvenile survival. In addition, extinction risk is also most sensitive to changes in adult survival. However, in the Serengeti, adult cheetahs are well protected from poaching within the park boundaries while juvenile cheetahs continue to suffer high predation, primarily from lions. We therefore used our demographic records to simulate the effect of different numbers of lions on juvenile survival. High lion abundance dramatically increased extinction risk.

Expanding PVA: Integrating Wildlife Population Biology Models with Models of Human Demographics, Economic Activities, Social Systems, and Other Processes that Impact Biodiversity Conservation. ROBERT C. LACY*, Dept. of Conservation Biology, Chicago Zoological Society, Brookfield, IL, and PHILIP S. MILLER, IUCN/SSC Conservation Breeding Specialist Group, Apple Valley, MN.

Population Viability Analysis uses population biology models to assess probability of extinction, threats, and effects of possible actions. Yet the conservation of biodiversity is mostly a matter of addressing processes that revolve around human populations. Unfortunately, experts who model human systems (such as human demography, local economics and resource use, industrial activities, social systems, and political systems) rarely interact with biologists who use PVA to model wildlife populations. We propose that it is possible and necessary to integrate analysis of human systems with PVA. The linkages between human demographic, economic, and social systems and wildlife population biology must be identified. Outputs from models of each system are necessary inputs as driving forces into other systems. The linkages between human systems and wildlife population biology will be by way of direct harvest of the species, reduction of habitat area, reduction of habitat quality, and habitat fragmentation. Expansive heuristic models can help us identify pathways by which human systems exert pressure on wildlife populations via these threats. Detailed quantitative models of the relevant human systems are needed to generate the specific inputs into a PVA model of the wildlife population. Integrating understanding of human and natural systems will require a broader range of expertise, models, data, and perspectives than has been applied in most PVAs to date.

PVA’s for Populations with Movements Constrained by Landscape Pattern: The Case of the Southwestern Willow Flycatcher. ROLAND H. LAMBERSON*, Dept. of Mathematics, Humboldt State Univ., Arcata, CA, and BARRY R. NOON, Dept. of Fishery and Wildlife Biology, Colorado State Univ., Ft. Collins, CO.

To develop a population viability analysis for the southwestern willow flycatcher, we are exploring multiple models, looking for concordance in model output among competing approaches. A common thread linking the different models is an initial focus on habitat—its amount, quality, and spatial distribution. The tight relationship between the distribution of flycatchers and riparian habitat strongly suggests that movement may be constrained to these linear habitat patches. Such patches can be viewed as fixed nodes of a graph with multiple patterns of connectivity reflecting different "allowable" pathways of movement. Varying assumptions about the degree to which riparian habitat constrains movement uniquely defines different metapopulation boundaries. Our results demonstrate how different assumptions about the "correct" patterns of connectivity affect estimates of persistence and optimal reserve design. Finally, we compare inferences from various connectivity models to traditional demographic-based models, and to incidence functions models parameterized by extensive survey data.

Incorporating Stochasticity and Uncertainty into Population Viability Analysis. RUSSELL LANDE*, Dept. of Biology, Univ. Oregon, Eugene, OR, STEINAR ENGEN, Dept. of Mathematics & Statistics, Norwegian Univ. Science & Technology, Trondheim, Norway, and BERNT-ERIK SÆTHER, Dept. of Zoology, Norwegian Univ. Science & Technology, Trondheim, Norway.

Because population viability is generally expressed as a probability of persistence (above a certain level) for a specified time, stochastic demographic and genetic factors should be incorporated along with deterministic factors into PVA. Deterministic factors include the population effects of habitat destruction and fragmentation, introduced species, overexploitation, and pollution. Stochastic demographic factors include demographic and environmental stochasticity, random catastrophes, and local extinction and colonization in metapopulations. Stochastic genetic factors include random genetic drift and fixation of deleterious mutations. All genetic factors influencing population viability are expressed through demographic factors that affect population dynamics. Uncertainty in estimates of demographic parameters often greatly reduces the statistical confidence that a population achieves any given level of viability, and should cause management to be much more conservative.

Metapopulation Dynamics in Oregon Coastal Natural Coho Salmon Oncorhynchus kisutch: A Buffer against Extended periods of Poor Marine Survival. PETER. W. LAWSON*, Northwest Fisheries Science Center, National Marine Fisheries Service, Newport, OR, and THOMAS E. NICKELSON, Oregon Dept. of Fish and Wildlife, Corvallis, OR.

A habitat-based life-cycle model of Oregon coastal natural (OCN) coho salmon Oncorhynchus kisutch was developed using freshwater production dynamics of individual stream reaches estimated from habitat survey data. Within a river basin, populations in reaches were independent except for straying of five percent of returning spawners. In this sense, each reach represented a population within the basin metapopulation. Monte Carlo simulations showed that during periods of poor marine survival populations in reaches with higher-quality habitat persisted, while those in reaches with low-quality habitat went extinct. When marine survival improved, strays from the persistent populations gradually recolonized unpopulated reaches. Repopulation took several generations, suggesting that OCN coho abundance and distribution may adjust to changes in marine survival over periods of five to ten generations. In healthy metapopulations this time lag could provide resilience against prolonged periods of poor marine survival. Distributions of spawners should be considered along with abundance in evaluating the status of stocks.

A Computer-Intensive Method for Inferring Population Persistence Based on Time Series Data. DANNY C. LEE, Sierra Nevada Conservation Framework, Sacramento, CA..

Population viability analyses often rely on time series data. One approach to modeling such data is use simplistic statistical models to estimate demographic parameters. While analytically elegant, such approaches can overlook important biological factors, including age structure and the interplay between demographic and environmental stochasticity. An alternative approach is to build complex life-history models. Such models simulate population dynamics more mechanistically, but lose the analytical elegance and relations to data of the statistical models. The PopVANC model (Population Viability Analysis based on Nest Counts), uses a hybrid approach to estimating population persistence that relies on the capability of modern computers to readily simulate and analyze millions of synthetic time series. The approach has seven steps: (1) Fit observed time series data using linear regression. (2) Develop a population profile using a fixed life-history structure and observed regression coefficients. (3) Simulate synthetic time series using the predetermined life-history structure and random grid of l (expected replacement rate) and s (environmental noise). (4) Search synthetic data base for observations matching population profile. (5) Build likelihood surface for l and s. (6) Simulate future abundance starting with observed time series and probabilistic draws of l and s. (7) Summarize results as a persistence profile. This approach allows complex life histories, yet provides a rigorous tie to data through the generated likelihood surfaces. The model is illustrated using Pacific salmon redd counts.

Fitting PVA into Adaptive Management. DONALD LUDWIG*, Dept. of Mathematics, Univ. British Columbia, Vancouver, BC, Canada, and CARL WALTERS, Fisheries Centre, Univ. British Columbia, Vancouver, BC, Canada.

Adaptive management initially involves two stages: (1) A modeling stage to identify the main ingredients in understanding the problem and to identify important gaps in existing knowledge, and (2) Design of experiments to try to fill some of these gaps and improve policies. PVA suffers from an apparent requirement for detailed and accurate knowledge in the face of numerous complications due to biological complexity, the complexity of human responses and motivations, and the inherent complexity of the problem of inference. If we underestimate these difficulties in the first stage, we may be led to strategies for the second stage that appear to be cost-effective, but actually impede prudent and practical responses to the problem.

A Reassessment of Florida Panther Population Viability Analysis and Recovery Efforts from Multiple Perspectives. DAVID S. MAEHR*, Dept. of Forestry, Univ. Kentucky, Lexington, KY, ROBERT C. LACY, Chicago Zoological Society, Brookfield, IL, E. DARRELL LAND, Florida Game and Fresh Water Fish Commission, Naples, FL, ORON L. BASS, Everglades National Park, Homestead, FL, and THOMAS S. HOCTOR, Univ. Florida, Gainesville, FL.

We used Vortex (Lacy et al. 1995) to model Florida panther (Puma concolor coryi) population viability from four perspectives. Independent analyses were based on demographic inputs provided by a federal field biologist, a state field biologist, a university conservation biologist, and an NGO population biologist. Despite a lack of full consensus regarding the inputs and results of earlier modeling efforts (Seal et al. 1989, Seal and Lacy 1992), management of this endangered subspecies moved forward first with a plan for captive breeding (which has yet to be implemented) and more recently with genetic restoration. Since 1994, 8 female cougars, introduced from Texas, have produced at least 12 hybrid kittens. Eight may nearly equal the breeding female segment of the population where N_e/N may be as low as 0.26. Because PVAs can use best guesses for model inputs, and because the collection of accurate demographic data from small populations can be a slow, painstaking process, PVA results can easily outpace the collection of data needed to properly drive the model. Panther recovery has been controversial, with the genetic restoration efforts being questioned by analyses which suggest demographic stability of the population may obviate the need for such a radical approach to small population management (Maehr and Caddick 1995). By analyzing the most recent information from different perspectives, we attempt to clarify the status of the panther to increase consensus among managers and to provide guidance as to the most useful recovery actions in the future.

The Demographic and Genetic Contributions of Immigrants in an Insular Song Sparrow Population, AMY B. MARR*, Dept. of Wildlife Ecology, Univ. Wisconsin, Madison, WI, and PETER ARCESE, Dept. of Wildlife Ecology, Univ. Wisconsin, Madison, WI.

Few studies have assessed the true genetic and demographic contributions of immigrants to a population because of practical limits on monitoring effort. This lack of information makes it difficult for conservation biologists to determine objectively how to incorporate the effects of dispersal and inbreeding into Population Viability Analysis models. We used longterm data from a study of an insular song sparrow population to examine the effect of occasional immigration on the genetic composition and fitness of individuals in a small population. Our analysis involved 18 years of data on 313 females for which all breeding attempts were recorded and all offspring were color-banded. Over this period, 16 immigrant females bred and genetic work shows that these individuals introduced novel alleles to subsequent generations. We used our complete pedigree from 1981 to describe the turnover of matrilines and spread of immigrant nuclear genes in the population. Logistic regression was used to determine the consequences of inbreeding, matriline association, and immigrant ancestry for fitness. Our analysis allowed us to estimate directly the genetic and demographic contributions of immigrants, and to suggest how our results might be generalized for inclusion into PVA.

Methods for Testing PVA Models. MICHAEL A. MCCARTHY*, Centre Res. Env. Studies, Aust. Nat. Univ., Canberra, ACT, Australia, HUGH P. POSSINGHAM, Dept. of Env. Sci. and Manag., Univ. Adelaide, Adelaide, SA, Australia, DAVID B. LINDENMAYER, Centre Res. Env. Studies, Aust. Nat. Univ., Canberra, ACT, Australia, and LINDA S. BROOME, NSW Nat. Parks & Wildl. Serv., Queanbeyan, NSW, Australia.

Despite being first developed approximately 20 years ago, the predictions of PVA models have rarely been tested. We present several different methods for testing PVA models, which aim at identifying their weakest aspects. The different methods require different sorts of data, such as presence/absence data in patches and time series data of population size. Both graphical and statistical methods are used. The methods are illustrated with examples of PVA models of mountain pygmy-possums, arboreal marsupials and Australian treecreepers. Three different types of model are analyzed: single population models; patch-occupancy metapopulation models; and metapopulation models that include local dynamics. In most cases, there is at least reasonable congruence between the predictions of the models and the observed data.

Population Viability Analysis of an Endangered Passerine: Computer-modeling Results for a Translocated Metapopulation. ANDREW MCCLUNG*, Dept. of Zoology, Univ. Hawaii at Manoa, Honolulu, HI, MARIE MORIN, Dept. of Zoology, Univ. Hawaii at Manoa, Honolulu, HI, and SHEILA CONANT, Dept. of Zoology, Univ. Hawaii at Manoa, Honolulu, HI.

Population Viability Analysis (PVA) has proven useful in assessing management options for endangered species, especially when the biology of the species is well-known. Most studies to date have focused on continental species and habitat fragmentation, but few have addressed management options for relict species in island ecosystems. The Northwest Hawaiian Islands contain several passerine birds that could be so described, and formerly contained many others since gone extinct. Our research, using the VORTEX PVA modeling program, indicates that one of these birds, the Laysan Finch, may be in the process of losing a group of populations at Pearl & Hermes Reef (PHR). Translocated to PHR in 1967 as insurance against catastrophic events at Laysan, the PHR finches face environmental stochasticity comparable to that affecting their parent population, but patch sizes and effective population sizes at PHR are much smaller. Also, local population extinctions remain problematic due to low inter-islet migration rates and consequent lack of population replenishment. Furthermore, the vegetation composition has changed significantly over the last 20 years, creating a severe limitation on nest sites and shifts in behavior that may be affecting breeding success. Preliminary VORTEX results suggest that inbreeding is much more a problem at PHR than at Laysan, and in concert with earlier genetic studies, indicate that the PHR populations provide neither a sufficient reserve of genetic diversity nor of demographic stability. Whether to respond to this decline by attempting an additional translocation at a more stable island habitat remains to be answered.

Linking the Human Animal with Endangered Species Risk Assessment: Case Studies of an Expanded PVA Process. PHILIP S. MILLER*, IUCN/SSC Conservation Breeding Specialist Group, Apple Valley, MN, FRANCES WESTLEY, IUCN/SSC Conservation Breeding Specialist Group, Apple Valley, MN, and ANN P. BYERS, IUCN/SSC Conservation Breeding Specialist Group, Apple Valley, MN.

The use of demographic and genetic models of the extinction process has become an increasingly valuable component of endangered species management. However, due in large part to great consternation amongst biologists concerning the conceptual foundations and detailed mechanics of these methods for population viability analysis (PVA), we neglect to concern ourselves with perhaps the most important element in applying PVA to real conservation action: the link between human population processes (demographic, economic, and socio-political) and the risks of wildlife population extinction. Just as these human processes are the principal agents of wildlife population endangerment, so too must they be the subjects of rigorous analysis as part of a broader risk assessment. Through the Population and Habitat Viability Assessment workshop process, we are attempting to augment the standard PVA approach by working to expand stakeholder involvement and to incorporate quantitative estimates of human population growth and land use projections into the modeling process. We have implemented this expanded process in four countries representing a diverse array of socio-cultural domains. Two specific case studies are described in some detail: the mountain gorilla (Gorilla gorilla beringei), where parameterizing and simulating the effects of disease outbreak and violent civil unrest around the Virunga volcanoes region formed the bulk of the modeling effort; and the tree kangaroos of Papua New Guinea (Dendrolagus sp.) in which considerable semantic knowledge from local villagers was assembled to evaluate the impacts of hunting on locally fragmented populations. Lessons learned from these initial experiments with an expanded process are discussed.

Sensitivity Analysis to Evaluate the Consequences of Conservation Actions. L. SCOTT MILLS, Wildlife Biology Program, Univ. Montana, Missoula, MT.

Sensitivity analysis is a critical component of PVA, because instead of merely flagging low persistence probability it helps us identify specific activities that are most likely to improve population growth or persistence. The three main methods for conducting sensitivity analysis include: a) elasticities and LTRE approaches; b) life-stage simulation analysis; c) approaches based on PVA analysis. I will address the potential and pitfalls of each of these, emphasizing the problems that arise when "best guess" or mean estimates are used without accounting for variation in birth and death rates. To date, sensitivity analysis has not yet been extended to multiple populations, although levels of connectivity (or dispersal rates) are considered to be key parameters in demographic and genetic analyses of metapopulations. As an example using real field data, I use a simple model based on lesser snow geese to demonstrate how ignoring connectivity, or ignoring a plausible range of variation in vital rates, can lead to misleading management recommendations of the importance of particular conservation actions for metapopulations. The pivotal role of variance in evaluating the importance of within and among-population vital rates illuminates the need for field estimates that separate process variation from sampling variation.

Regional-scale Habitat Modeling When Data are Insufficient for Population Viability Analysis. REED NOSS*, Conservation Biology Institute, Corvallis, OR, CARLOS CARROLL, Conservation Biology Institute, Corvallis, OR, PAUL PAQUET, Conservation Biology Institute, Corvallis, OR, and JAMES STRITTHOLT, Conservation Biology Institute, Corvallis, OR.

Developing conservation plans for wide-ranging species, such as large carnivores, requires information on the distribution of suitable habitat over large regions, from which inferences about population persistence can be made. Typically, in such cases, the demographic information necessary for credible population viability analysis is lacking. Furthermore, existing conceptual models of habitat suitability, based on fine-scale habitat attributes, are not useful for regional-scale modeling. We are developing empirical GIS-based models of habitat quality for 12 species of carnivores in the Rocky Mountains of the U.S. and Canada based on "found" distributional data such as trappings and sightings, as well as regional-scale attributes predicted to be important to long-term persistence. Although dynamic simulation models may offer the strongest mechanistic insights, the poor knowledge base for most of these species is inconsistent with these models' sensitivity to error-propagation. The use of static spatial models, such as the autologistic, allows analysis of habitat requirements across multiple scales in the absence of detailed demographic data. Commonalities among species in their response to habitat attributes facilitates the development of multi-species models and conservation strategies. Our modeling approach is iterative, with initial models offering information for short-term land-use and conservation decisions, as well as helping to identify key knowledge gaps and prioritize future studies. An "adaptive monitoring" approach allows initial empirical models to be validated and revised using new field data.

The Use of PVA to Compare the Relative Effects of Alternative Proposed Hydrologic Scenarios on the Everglades' Cape Sable Seaside Sparrow. PHIL NOTT, Institute for Environmental Modeling, Univ. Tennessee, Knoxville, TN.

SIMSPAR is a spatially-explicit individual based model designed as a management tool for the Cape Sable Seaside Sparrow (Ammodramus maritimus mirabilis) of the Florida Everglades. It represents one of the models within the Across Trophic Level System Simulation (ATLSS) Program of the U.S. Geological Survey, Biological Resources Division, an Everglades ecosystem-wide model. The model includes landscape layers of habitat and topography at 500-m resolution upon which individuals in a small population respond to the changing landscape and encounters with other individuals. The life history and behavioral characteristics of model individuals are based on field observations of the species. Spatial and temporal patterns of breeding success are mainly determined by historical daily water levels affecting the availability of breeding habitat. The model was validated using historical daily water levels as input and comparing the resultant temporal and spatial patterns of breeding with those known from field surveys over a 15-year period. The model is now used to predict the impact of proposed alternative hydrologic scenarios on Cape Sable Seaside Sparrow populations. The processes of mortality, mate choice, and dispersal are expressed stochastically; hence the model is implemented as Monte Carlo simulations. Population viability analyses are applied to the variable results to determine population variability and the risk of explosion or extinction. This allows comparison of the relative merits of one or other management scenarios.

Wolves, Deer, and Logging: Population Viability and Predator-prey Dynamics in a Disturbed Insular Landscape. DAVID K. PERSON*, Alaska Dept. of Fish and Game, Ketchikan, AK, and R. TERRY BOWYER, Institute of Arctic Biology, Univ. Alaska Fairbanks, Fairbanks, AK.

Analysis of population viability typically examines the demography and habitat relations associated with a single species. The population dynamics of obligate predators such as wolves (Canis lupus) are inextricably linked with those of their prey, and viability analyses for these carnivores should address influences on the predator-prey system rather than simply focusing on the predator population. We describe a population viability analysis for wolves that employs a predator-prey model to predict the effects of the revised Tongass National Forest Management Plan on the persistence of the wolf-deer-human system on Prince of Wales Island in southeastern Alaska. We conclude that it is unlikely that the current plan for the Tongass National Forest will result in the extinction of wolves from Prince of Wales Island in the next century. Nevertheless, the wolf population may decline 30-40% over the next 100 years and deer populations will likely decline disproportionately to the decay of carrying capacity. Prior to the initiation of industrial-scale timber harvesting in 1954, carrying capacity was sufficiently high to enable wolf and deer populations to rebound after severe winters. Long periods in which deer numbers are suppressed by predation will likely occur in the future because of the loss of carrying capacity for deer. Declining populations of deer will result in conflicts between hunters and wolves.

Model Choice in Population Viability Analysis. CATHERINE A. PFISTER, Dept. of Ecology and Evolution, Univ. Chicago, Chicago, IL.

All modeling techniques that we use to examine population viability require we decide what level of detail will be included in the model. Should individual data be used or should we use aggregate descriptors for our populations? We often decide based on the quantity and quality of data available for the species we are studying, rather than a knowledge of how the model formulation will affect our predictions. Using a series of analyses that compares the outcome of individual based models (IBMs) with models that aggregate individuals into size classes (matrix projection models), I have found features of natural populations that cause matrix models to deviate from IBMs. In both density dependent and independent scenarios, populations composed of individuals with strongly size-dependent performance and the tendency for individuals to have positive correlations in performance through time were always poorly described by matrix models. While the dynamics of populations reduced to small size were also better described by IBMs, high levels of stochasticity did not favor the use of a particular model. These results provide guidance for how we might better match the characteristics of a species of concern and the model needed to accurately describe it.

Decision Theory and Population Viability Analysis. HUGH POSSINGHAM, Dept. of Applied & Molecular Ecology, Univ. Adelaide, Australia and National Center for Ecological Analysis and Synthesis, Santa Barbara, CA .

The science in our conservation journals has limited application to applied managers because it has not been developed within a decision theory framework. Population Viability Analysis is a classical example of a theoretical tool developed with the limited (if not flawed) purpose of estimating the viability of populations. The real benefits of PVA arise when we use it to explicitly evaluate decisions and/or rank management options. Costs, benefits and trade-offs should be the cornerstones of our thinking. In this paper I will briefly review some applications of PVA in a decision support role. I then explore the potential application of more formal decision-making tools, like stochastic dynamic programming, for finding state-dependent management regimes for threatened species. Relatively simple stochastic population models are all that is needed to make fairly robust decisions. Using this approach we can explore questions in conservation ecology like: Where should habitat be restored - adding to existing patches or making corridors? When should an endangered species be brought in to captivity? How should fire be managed? What forest management strategies minimize extinction probabilities for low cost? Answers to these questions will lead us to a theory of applied conservation, not more theory.

Extinction Probabilities of a Rare Species under Variable Fire Regimes PEDRO F. QUINTANA-ASCENCIO*. Archbold Biological Station, Lake Placid, FL and El Colegio de la Frontera Sur, San Cristóbal de Las Casas, Chiapas, 29200, México and ERIC S. MENDES, El Colegio de la Frontera Sur, San Cristóbal de Las Casas, Chiapas, 29200, México.

We used matrix population models to compare Hypericum cumulicola demography and extinction probability in Florida scrub under different fire scenarios. Demographic data were obtained from five-year census of 15 populations (1994-1998; 3300 plants), field observations, and experiments. Projected finite rates of increase ranged between 0.597 and 3.69. Time-since-fire and finite rates of increase showed a significant inverse relationship. Expanding populations were predicted mostly in recently burned patches. Growth was the most important elasticity component in recently burned patches while soil seed bank survival had the largest elasticity in sites a decade postfire and in long-unburned patches. Simulations of population trajectories after an initial fire indicated that in the absence of migration and additional fires, even large populations may become locally extirpated within 200 years. Fire return intervals less than 20 years and variation in fire return intervals are recommended as appropriate management for this rosemary scrub endemic.

Guidelines for Using PVA for Endangered Species Management. KATHERINE RALLS*, National Zoological Park, Smithsonian Institution, Washington, DC, STEVEN BEISSINGER, Dept. of Environmental Science, Policy, and Management, Univ. of California, Berkeley, CA, JEAN FITTS COCHRANE, Dept. of Ecology, Evolution, and Behavior, Univ. Minnesota, St. Paul, MN, and ANTHONY M. STARFIELD, Dept. of Ecology, Evolution, and Behavior, Univ. Minnesota, St. Paul, MN.

PVA models use a wide variety of approaches to understand past population trends, evaluate likely threats to a population, and project future population trends. However, the formal population models used in PVA are not the only useful approach to recovery planning. PVA is widely used to gain a better understanding of an endangered species and its problems and to estimate the relative risk of alternative management options. There are no consensus guidelines on why, when, or how PVA should be used in endangered species management. We describe PVA and alternative approaches to gaining understanding, estimating risk, and making decisions. It is crucial to define objectives before choosing a specific technique. We provide guidelines to help decision-makers decide whether or not a PVA would be helpful for a given species, choose or develop an appropriate model, conduct the analysis, and interpret the results. We also develop criteria for judging the quality of a completed PVA. Although many PVA's are conducted during brief workshops and never revisited, PVA is more useful as a long-term, iterative process coupled with an adaptive management approach to species recovery.

The Use of Demographic Data and a Spatially Explicit Population Model to Analyze Effects of Habitat Management on Persistence of Northern Spotted Owls on the Olympic Peninsula, WA. MARTIN G. RAPHAEL*, U.S. Forest Service, Pacific Northwest Research Station, Olympia, WA, RICHARD S. HOLTHAUSEN, U.S. Forest Service, Rocky Mountain Research Station, Flagstaff, AZ, and KEVIN McKELVEY, U.S. Forest Service, Rocky Mountain Research Station, Missoula, MT.

We analyzed likely patterns of distribution and persistence of northern spotted owls (Strix occidentalis caurina) on the Olympic Peninsula, WA. We used a spatially explicit population simulation model for northern spotted owls for the analysis and also reviewed current information on demographics and likely owl population numbers on the peninsula. Where there was uncertainty surrounding the values of input parameters, such as the relationship between habitat quality and survival and fecundity rates, we looked at the sensitivity of model results to variation in parameter values. Analysis focused on the effects of Federal habitat under provisions of the Northwest Forest Plan; additional benefits to the owl population of different levels of habitat retention on non-Federal lands; effects of establishing a habitat connection between the Olympic Peninsula and other parts of the owl's range; the likely rate of habitat regrowth in the National Forest and its effect on the owl population; and the likely effect of a worst-case fire. We concluded that the retention of non-Federal habitat would make a biologically significant contribution to the maintenance of the population on the peninsula. We also concluded that a habitat connection across Southwest Washington, based on a design suggested by the Northern Spotted Owl Recovery Team, would have little effect on the status of the owl population on the peninsula. This analysis demonstrated the value of spatially explicit population modeling based on locally-collected demographic information. However, even with a long-term data base and powerful analytical models, significant uncertainty remained concerning future projections, and we had to resort to professional judgment to decide which analytical scenarios were most likely.

Determining Viable Stream Networks for Persistence of the Lahontan Cutthroat Trout. CHRIS RAY*, Dept. of Biology, Univ. Nevada, Reno, NV, MARY PEACOCK, Dept. of Biology, Univ. Nevada, Reno, NV, and JASON DUNHAM, Dept. of Biology, Univ. Nevada, Reno, NV.

Once found in cold streams and lakes throughout the north-central Great Basin, Lahontan cutthroat trout have experienced a 90% range reduction in the last century. Most contemporary populations are isolated in minor tributaries, due to the degradation of lake and mainstem stream habitats. Stream flows in the Great Basin are extremely variable in space and time, and previous analyses suggest that historic populations persisted through frequent redistribution within stream networks. Here we develop models to predict the viability of networked populations, using data from long-term studies of age-structured recruitment. Data were gathered from several isolated populations and from one of the few remaining population systems connected by a functional mainstem. Lacking specific data on dispersal, we adopt two approaches to modeling network dynamics. 1) We incorporate dispersal implicitly by using data from the observed network to determine relationships between network 'state' (average demographic and environmental variables) and the growth of individual populations. The dynamics of arbitrary networks are predicted by linking populations that obey these relationships. 2) We use data from isolated populations to determine relationships between population state and growth. Larger networks are modeled by linking populations that obey these relationships and adding hypothetical levels of dispersal. We compare assumptions and predictions between approaches, and discuss the potential for persistent trout networks in watersheds throughout the Great Basin.

Application of Population Viability Analysis in the Development of the Wisconsin Wolf Management Plan. ROBERT E. ROLLEY*, Wisc. Dept. Nat. Res., Monona, WI, ADRIAN P. WYDEVEN, Wisc. Dept. Nat. Res., Park Falls, WI, and BRUCE E. KOHN, Wisc. Dept. Nat. Res., Rhinelander, WI.

The gray wolf (Canis lupus) was extirpated in Wisconsin in the 1950s but recolonized in the mid 1970s. The Wisconsin Department of Natural Resources (WDNR) listed wolves as state endangered in 1975 and implemented a recovery plan in 1989. By 1997, the wolf population had met the recovery goal of 80 or more wolves for 3 consecutive years. The WDNR is currently proposing to reclassify wolves as a threatened species, and is developing a plan for their management as a threatened and eventually as a delisted species. We analyzed the viability of the Wisconsin gray wolf population using VORTEX software to aid in plan development. Radio-telemetry studies provided estimates of mean reproduction and mortality rates. We evaluated several environmental variability and catastrophic event scenarios because data on these parameters were limited. Virtually all simulations with delisting criteria of 100+ wolves resulted in population persistence when we assumed low to moderate environmental variability and <5% probability of catastrophic event. Estimates of risk of wolves declining below the recovery goal varied little among delisting criteria of 200-500, but were very sensitive to magnitude of environmental variability and the probability of catastrophic events assumed. Our analysis emphasizes the importance of continued monitoring in the development of an adaptive management program for Wisconsin's wolves. The long- term persistence of wolves in Wisconsin depends on finding the proper balance between wolf protection and control to address public concerns about livestock and pet depredations.

Population Viability of a Small, but Rapidly Increasing Arctic Goose Population. MARCUS ROWCLIFFE*, Inst. of Zool., Zoological Soc. London, London, UK, RICHARD PETTIFOR, Inst. of Zool., Zoological Soc. London, London, UK, and JEFFREY M. BLACK, Dept. of Wildlife, Humboldt State Univ., Arcata, CA.

Use of Population Viability Analyses (PVA) for predicting population stability can lead to unrealistic conclusions if models are based on poor-quality demographic data. Because data from small, endangered populations are often meager, it is difficult to assess the usefulness of the PVA approach as a conservation tool. We attempt to validate the PVA approach by utilizing data from an intensively studied small population of Barnacle Geese Branta leucopsis. This population is among the most celebrated wildlife management and conservation success stories in the United Kingdom and Norway It was through proactive wildlife policy and the establishment of well-managed refuges that the population recovered from critically low numbers; i.e. 300 in 1947 to 24,000 in 1997. Based on the 25-year dataset of individually marked birds (i.e. their survival and reproductive success) and other population parameters, we assess the risk of extinction and potential growth within a given time span. We consider a range of range of population responses based on potential management scenarios (e.g. further improving refuge management policy, allowing harvesting etc.) while considering the severe stochastic nature of the arctic breeding grounds. We conclude that the PVA approach is indeed a useful conservation/management tool when appropriately detailed data is available.

Understanding the Importance of Stochastic Processes in PVA: Estimates of Some Essential Parameters. BERNT-ERIK SÆTHER*, Dept. of Zoology, Norwegian Univ. Science and Technology, Trondheim, Norway and STEINAR ENGEN, Dept. of Mathematical Sciences, Norwegian Univ. Science and Technology, Trondheim, Norway.

Fluctuations of small populations are likely to be strongly influenced by different forms of stochasticities. A problem in making reliable predictions from population viability analysis is to obtain estimates of the stochastic parameters in the model. Here we will present formal definitions of demographic and environmental variances. Based on methods derived from these definitions, we will present estimates of these two parameters in three populations of small temperate passerines (great tit, European dipper and song sparrow) where longterm data on both population fluctuations and individual variation in recruitment success were available. We will then calculate the expected time to extinction, applying a diffusion approximation, and examine which demographic factors most likely to affect the probability of extinction in these three populations. We will then discuss the applicability of these results for viability analysis of rare or endangered species where such long-term data are rarely available.

Reintroduced Population Viability Analyses: What Can Be Done? FRANÇOIS SARRAZIN*, Lab. of Ecology, CNRS -UMR 7625, Univ. Pierre & Marie Curie, Paris, France, and STEPHANE LEGENDRE, Lab. of Ecology, CNRS -UMR 7625, Ecole Normale Superieure, Paris, France.

Reintroductions are more and more often used for conservation but they remain too rarely successful. Since the aim of any reintroduction is to restore a self-sustaining population, this is mainly a matter of extinction avoidance. In that context, Population Viability Analyses may be useful in two ways. First they may help to compare a priori reintroduction strategies. However, since the quality of data available for species candidate to reintroduction is often questionable, PVA have to be considered as formal approaches providing qualitative results Missing data can nevertheless be inferred from life cycle and habitat quality scenarios. Second, once the reintroduction is running, PVA may help to assess the success of the project and to plan the management of the reintroduced population. These models have to consider both life history traits and release parameters (number and duration of releases, origin and age class of individuals, habitat quality). They therefore necessitate highly plastic modeling tools. Using the software ULM, we developed two-sex models including demographic stochasticity to assess the consequence of breeding systems on reintroduced populations viability for different release parameters. Furthermore, we compared the relative efficiency of releasing juveniles or adults for a given life cycle. This family of models accounted for possible reduction of survival and fertility of released adults . Such a model was applied to the case of the reintroduction of Griffon vultures Gyps fulvus in Southern France for which accurate monitoring allowed us to estimate demographic rates and consequences of releases.

The Implications of Territorial Clustering on the Demography and Dispersion Patterns of Small Populations of Birds. THOMAS SCOTT, Dept. of Environmental Science, Policy,. and Management, Univ. California, Berkeley, CA..

The San Clemente Loggerhead Shrike remains the one of the rarest North American subspecies of passerine. By any measure, the subspecies persists at the conventional limits of population viability (7 to 18 pairs during the 15 years of our study). Nevertheless, the persistence of this population and its isolation on San Clemente Island (southern California) have provided an opportunity to study long-term demography and dispersion patterns of small populations without the confounding influence of immigration. Many parameters of the population seem driven by the longevity of breeding males and their use of life-long territories rather than individual variance in reproductive success. Female survivorship, emigration, and movement (among territories) appear to be strong contributors to male territorial clustering in shrikes. In general the viability of the population has been most strongly influenced by males longevity and female choice of mate/breeding territory. Nesting pairs were more clustered than would be predicted by habitat quality, with strong implications for meta-population structure and landscape-level dispersion patterns of other passerines. The spatial pattern can either be viewed as a manifestation of declining populations or as an intrinsic nesting pattern magnified by island isolation. In either case, clustering may play a substantive role in the survival or extirpation of small populations of birds.

Estimating the Magnitude of Environmental and Demographic Stochasticity in Survivorship Data for a Nearctic-Neotropical Migrant Songbird. T. SCOTT SILLETT*, Dept. of Biological Sciences, Dartmouth College, Hanover, NH, SCOTT A. MORRISON, Dept. of Biological Sciences, Dartmouth College, Hanover, NH, KATHRYN L. COTTINGHAM, Dept. of Biological Sciences, Dartmouth College, Hanover, NH, RICHARD T. HOLMES, Dept. of Biological Sciences, Dartmouth College, Hanover, NH.

An explicit accounting of stochastic effects on survivorship is critical to sound population viability analysis. Annual variation in survival is typically attributed to environmental factors. However, assuming that all variation in survivorship is a result of environmental stochasticity can lead to overly pessimistic predictions of population viability. We used the method of Kendall (1998: Ecol. App. 8:184) to separate demographic and environmental stochasticity in survivorship of a Nearctic - Neotropical migrant songbird, the black-throated blue warbler (Dendroica caerulescens). Data were gathered from 1986-1998 on two warbler populations: one in the breeding grounds in New Hampshire, USA, and one in the non-breeding quarters in Jamaica, West Indies. The black-throated blue warbler is representative of many migrant passerines in its life history and demography, and our sample sizes are as large as those from most published bird studies. Based on our analyses, all variation in survivorship could be attributed to demographic stochasticity, despite wide variation in annual survivorship (0.3 - 1.0) for both populations. Simulations to explore the role of sample size and variance in survivorship on the statistical results indicate that our power to detect environmental stochasticity, if it existed, was low (<0.3 for both populations). This suggests that very large sample sizes or more extreme variation may be needed to produce meaningful results. We therefore recommend caution in applying Kendall's (1998) method, especially to smaller datasets typically available for species of conservation concern, where policy decisions might not wait for longer-term data collection.

Error Propagation, Population Viability Analysis, and the Natural Boundaries of Knowability. DAVID SMITH*, Dept. of Biology, Univ. Maryland, College Park, MD, JON PAUL RODRIGUEZ, Dept. of Ecology and Evolutionary Biology, Princeton Univ., Princeton, NJ, and STEVE PACALA, Dept. of Ecology and Evolutionary Biology, Princeton Univ., Princeton, NJ.

Population viability analyses (PVA) depend on estimates of basic demographic parameters, but measurement errors are often ignored. We collected published life-tables and used several methods to generate pseudo-data. We investigated the effect of measurement errors on risk assessment by bootstrapping the data and propagating the errors through a stochastic, demographic model. The risk from error propagation was compared to the risk from demographic stochasticity by repeating the stochastic, demographic simulation using the estimates as if they were true values. Error propagation had a larger impact than demographic stochasticity when populations were small and had growth rates close to zero--in other words, those populations where a PVA could be the method of choice for assessing the relative value of alternative conservation strategies. Because studies of small populations must have small sample sizes, there are limits on what can be known about small populations. We identify the bounds to the unknowable region in terms of population size, longevity, growth, and several other aspects of the demography. This study has implications on an important question--should developers or conservationists have the burden of proof in a conflict over a small population?

Desensitizing and Constraining Dispersal in an Individual Based Model. BRADLEY M. STITH*, Dept. of Wildlife Ecology and Conservation, Univ. Florida, Gainesville, FL, JOHN W. FITZPATRICK, Cornell Laboratory of Ornithology, Ithaca, NY; and GLEN E. WOOLFENDEN, Archbold Biological Station, Lake Placid, FL.

We examined the sensitivity of an individual based model for the Florida Scrub-Jay (Aphelocoma coelurescens) within artificial landscapes configured to maximize the influence of dispersal on population persistence. We compared the relative importance of total metapopulation size, local patch size, interpatch distance, and dispersal ability. Local patch size was much more important than the other 3 factors, even though maximum patch size was small, supporting no more than 8 pairs of jays. In contrast to several recent studies, our model was relatively insensitive to substantial differences in dispersal parameter settings, even where dispersal should be maximally important. We attribute this model robustness to design features of the dispersal module and increased model realism. We also describe how different types of field data can be used to place effective constraints on plausible parameter settings. Long term research at Archbold Biological Station provided data that model output could be tested against. Radiotracking provided rough estimates of disperser movement ability and survival. Knowledge of where colonizations should NOT occur placed further constraints on dispersal parameters. We suggest that PVA models are not all overly sensitive to dispersal parameters, and often can be constrained by a variety of field data. Moreover, increasing model realism may further constrain model behavior; error propagation can actually decrease with increasing model complexity.

Genetic Based Effective Population Sizes: Are They? BRADLEY J. SWANSON, Dept. of Biological Sciences, Purdue Univ., W. Lafayette, IN.

One component required for long term population viability is maintenance of genetic variation. The rate of loss of genetic variation is controlled by genetic drift, the strength of which can be estimated by Wright’s effective population size (N_e). N_e can be directly measured with genetic markers such as allozymes and microsatellites. In this paper I examine how N_e varies when estimated from allozyme heterozygosity or microsatellite heterozygosity. N_es were estimated from published reports of heterozygosity using the infinite allele model for allozymes and the stepwise mutation model for microsatellites with mutation rates of 10^-7 and 10^-3 respectively. I found that the average allozyme-based estimate of N_e (151,000 + 26.3 SD) based on 682 populations from 152 mammalian species was significantly greater than the average N_e for microsatellites (550 + 1.14) based on 132 populations from 36 species. In paired species comparisons the ratio of allozyme estimates to microsatellite estimates was greater by 3 orders of magnitude. In an intraspecific comparison of 72 populations of white-footed mice (Peromyscus leucopus) the average allozyme estimate of N_e (912,000 + 2.34), was 200 times greater than the microsatellite estimate of N_e (5750 + 2.4). The average N_e/N ratio for populations with allozyme data and census sizes was 829 (+ 1376). N_es estimated from allozymes seem too high to be accurate. Results were robust to changing both mutation model and mutation rate. Estimates of N_e based on allozymes were also several orders of magnitude greater than those estimated from temporal change in heterozygosity and demographic methods. This work suggests that temporal methods are most appropriate when estimating N_e over the time periods important for population viability.

Use of PVA Models for Ranking Species Vulnerability. BARBARA L. TAYLOR*, Southwest Fisheries Science Center, La Jolla, CA, PAUL WADE, National Marine Mammal Laboratory, Alaska Fisheries Science Center, Seattle, WA, UMA RAMAKRISHNAN, Dept. of Biology, Univ. California, San Diego, CA, and MICHAEL GILPIN, Dept. of Biology, Univ. California, San Diego, CA..

We use simulations to evaluate two types of Population Viability Analysis (PVA) for risk classification of species. We perform an experiment where one author creates multiple data sets at varying levels of risk and submits these data to the other authors for analysis and risk classification. We contrast two analytical techniques: the typical single model approach which uses single estimates for all parameters and a Bayesian approach which incorporates the uncertainties of model choice and parameter estimation. We also consider two classification schemes. The current IUCN scheme, which classifies populations/species according to an X% chance of extinction in Y years (like the Endangered criterion: a 20% chance of extinction in 20 years). Including model and parameter uncertainty results in a probability distribution for each time. For example, a model assuming density dependent dispersal might have a very different probability of extinction in 100 years than a model assuming constant dispersal. Similarly, models using rates of decline of 2% or 4%/year, which may both be plausible given the data, will have different probabilities of extinction for a set period of time. Thus, more appropriate classification criteria would be phrased in terms of assuming a high probability of correctly classifying an endangered population. For example, the endangered criterion might be a 90% chance of correctly classifying a population which was truly endangered (e.g., had a 20% chance of extinction, or greater, in 20 years). We contrast the performance of these criteria and PVA techniques using our simulations where the actual level of risk is known.

Population Viability Assessment Using Monte-Carlo Life-Table Simulations. M. K. TAYLOR*, Fisheries and Wildlife, RWED/GNWT, Iqaluit, NT, Canada, M. KUC, ESSA Technologies, Richmond Hill, Ontario, M. A. OBBARD, Wildlife and Natural Heritage, Ontario MNR, Peterborough, Ontario, B. POND, Wildlife and Natural heritage, Ontario MNR, Peterborough, Ontario, and D. CLUFF, Regional Biologist, RWED/GNWT, Yellowknife, NT, Canada.

Population viability is essentially a question of demographic performance. One approach is demographic simulations based on life-history models of population dynamics. Estimates of population number, sex and age distribution, survival, recruitment, and harvest (if any) may be used in age-structured birth-pulse models to estimate population trend or status, number at some future time, and to explore the demographic consequences of some particular set of circumstances. Models may allow unlimited exponential growth or contain density effect feedback mechanisms. Harvest may be incorporated in a variety of ways, ranging from detailed simulation of actual sex and age selectivity/vulnerability, to simple apportionment of the kill according to the relative abundance of the population sex and age categories. A Windows compatible program named "RISKMAN" (RISK MANagement) was developed for the full range of options described above. RISKMAN provides a stochastic option that is based on the variance of input parameters, and the structure identified by the simulation options that are selected. Monte Carlo techniques are used to generate a distribution of results, and that distribution is used to estimate the variance of summary parameters such as number at some future time or population growth at some future time. RISKMAN utilizes the correct distributions of the population and rate variance estimates to provide accurate estimates of the uncertainty of summary parameters. Parameters may co-vary or be independent, and RISKMAN allows the user to set the correlation to one or zero to bound the co-variance possibilities.

Effects of Inbreeding on Population Viability, Modeling, and Management. DAVID W. TONKYN, Dept. of Biol. Sciences, Clemson Univ., Clemson, SC.

Inbreeding is inevitable in small, isolated populations, and is associated with reduced juvenile survival in many captive populations of endangered vertebrates. However, earlier studies likely underestimated the full effects of inbreeding, both to individuals, in reduced survival and fecundity, and to populations, in increased risk of extinction from low viability, disease, or environmental change. Among other concerns, these studies have not used the full information on living animals, often the most abundant and inbred in the data sets, and have ignored possible additional mortality among adults. Using more powerful statistical models, we have shown that inbreeding reduces survival in endangered Asian leopards and other species, and not only among the young, as was known, but continuously and therefore cumulatively throughout life. As a result, both individual survival to reproductive age and population growth rates decline faster with inbreeding than previously thought, increasing the risk of extinction. In this talk, I shall review these results, discuss specific implications for conservation of the endangered Amur leopard, and then conclude with general remarks on the management of both captive and wild endangered species. If many species exhibit a similar interaction between demography and genetics, this will change our basic understanding of inbreeding, require further integration of demographic and genetic models for accurate PVAs, and perhaps even influence views on breeding strategies for captive populations, and on what constitutes a minimum viable population in nature.

Viability of Feral Horse Populations on Atlantic Coastal Barrier Islands: Implications for Management. H. BRIAN UNDERWOOD, USGS Patuxent Wildlife Research Center, College of Environmental Science & Forestry, Syracuse, NY.

Feral and free-ranging horses have a long and illustrious legacy common to many Atlantic coastal barrier islands. I analyzed the population dynamics of the horses of Assateague Island National Seashore. Using population reconstruction methods and computer simulation of feral horse life-history, I developed a demographic PVA for this population for the expressed purpose of assessing the impacts of fertility control, disease epidemics, and catastrophic storm events on population persistence. Partial pedigrees were constructed to examine lineage-specific effects on population demography and heterozygosity. The reconstructed population varied from a low of 35 horses in 1975 to a high of 171 in 1988. Two-hundred forty-seven observations of survival histories (58 uncensored) of horses demonstrated that reconstructed March population size added significant prognostic value to the prediction of hazards for AINS horses. There were no statistically detectable differences in survival between the sexes and no dramatic differences in the age at first foaling over time. Analysis of the inter-birth interval revealed a strong population size influence, however. There was a pronounced change in the early-age hazards as population size increased, while adult survival changed very little and remained quite high over a wide range in population sizes. The levels of adult mortality due to storms, diseases and accidents, which are impossible to predict, had the most profound effect on population viability. The simulation also suggested that management directed at specific matrilines exerts a disproportionate effect on rate of increase, population viability and heterozygosity.

Mathematical Models as a Basis for Managing Goose Populations in Scotland. MICHAEL B. USHER*, Scottish Natural Heritage, Edinburgh, and ANDREW DOUSE, Scottish Natural Heritage, Edinburgh.

Population viability analyses (PVAs) are being performed on five goose populations in Scotland - the Icelandic population of the greylag goose (Anser anser), the pink-footed goose (Anser brachyrhyncus), the Greenland white-fronted goose (Anser albifrons flavirostris), and the barnacle goose (Branta leucopsis, both Greenland and Svalbard populations). During the last 50 years the population sizes of these wintering geese have increased dramatically; for example, that of the Svalbard population of the barnacle goose has increased from a few hundred in the late 1940s to over 23,000 in the late 1990s. Population sizes are continuing to increase, except that of the greylag goose which has apparently declined by about 20% since the mid-1980s. Increasing goose population sizes can be viewed either as a conservation success or as an agricultural nightmare. Farmers blame restrictive conservation legislation for damage to their pastures and winter cereal crops. Conservationists disagree and blame the change in land management practices that makes these fields far more suitable for goose grazing. The Scottish National Goose Forum, established in 1997 to explore options for goose management, is using PVA for each population to explore its security in the long term, especially the impact of infrequent catastrophes. A focus has been to explore the probability that the population size could fall below some pre-determined quasi-extinction level. From a conservation perspective, such probabilities must be extremely low. From an agricultural perspective, it is difficult to accept that the goose population sizes will continue to increase year after year. The PVA models are being used to explore the implications of increasing the mortality rate as a result of a limited program of culling. The paper will present results from these PVAs, and will approach, but not answer, the question 'when is a population sufficiently large?

Population Variability and Viability: Resolving the Conflict between Theory and Observation. JOHN A. VUCETICH*, School of Forestry, Michigan Tech. Univ., Houghton, MI, and THOMAS A. WAITE, Dept.of Evol., Ecol. & Organismal Biol., Ohio State Univ., Columbus, OH.

Population viability models routinely predict increased extinction risk (ER) with increased population variability (PV), yet empirical tests of this fundamental prediction have provided contradictory findings. We contend that the lack of clear-cut support for this prediction stems from a statistical artifact. If the true underlying relationship between PV and ER is positive (as expected), then measured relationships are likely to be negative simply because PV tends to be underestimated for populations with short persistence times. Beyond providing this basic insight, we use simulations to identify the specific properties of population count data minimizing this bias and thereby permitting meaningful tests of the relationship between PV and ER. For an existing dataset that fulfills these properties, our reanalysis provides the first statistically valid evidence of a significant positive correlation between PV and ER. Likewise, our experimental study of extinction risk in laboratory populations of the cowpea weevil (Callosobruchus maculatus) provides support for the predicted positive relationship between PV and ER. As expected, this relationship strengthened with increased persistence time. Consistent with our general claim, when these experimental data were treated as though they were observational data, underestimates of PV caused the measured relationship between ER and PV to become spuriously negative. Thus, our simulation results, reanalysis of published data, and new experimental findings all suggest that previous findings of negative or equivocal relationships between PV and ER were misleading outcomes of a statistical artifact.

Using Bayesian Techniques to Incorporate Uncertainty into PVA Analyses for Risk Classification of Species. PAUL R. WADE, National Marine Mammal Laboratory, Alaska Fisheries Science Center, Seattle, WA.

Population Viability Analysis (PVA) models are used to estimate the probability of extinction of a population. Although these estimates have many uses, I address use of extinction estimates to categorize species according to risk, which requires estimates of extinction to be absolute rather than relative. Current PVAs, particularly as reflected in available software, require specification of a single value for each parameter. Even though sensitivity analyses can examine the effects of uncertainty, the actual calculation of extinction probability ignores uncertainty in both parameter estimation and model structure. Bayesian statistics provide a method to directly incorporate parameter uncertainty into the results. Rather than using best estimates for parameters, Bayesian methods use distributions for each parameter. These distributions can either result from data where uncertainty can be quantified or can be specified for parameters for which no data are available. Uncertainty in model structure can also be incorporated. Once the definition of an endangered species is defined (e.g., an endangered species is one that truly has a 20% chance of extinction, or greater, in 20 years), a Bayesian analysis can estimate the probability a species is endangered. This probability can then be used for classification, once a risk level is specified (e.g., classify as endangered if there is a probability of X% or greater that it is truly endangered). This classification criterion directly incorporates parameter uncertainty: classification will be more conservative where our level of ignorance about a species is high, and will be appropriately less conservative for species with better knowledge.

Viability of Oregon Coast Coho Salmon, Oncorhynchus kisutch: A Bayesian Meta-analytic Approach. THOMAS C. WAINWRIGHT*, Northwest Fisheries Science Center, National Marine Fisheries Service, Newport, OR, and PAUL SPENCER, Alaska Fisheries Science Center, National Marine Fisheries Service, Seattle, WA.

We present a Bayesian risk analysis model for assessing extinction risk for salmon populations. The model combines a stochastic population dynamics model with Bayesian parameter estimates using meta-analytic priors on production parameters. The model provides a risk analysis tool incorporating both population stochasticity and parameter uncertainty. We apply the model to multiple populations of coho salmon (Oncorhynchus kisutch) from coastal Oregon, currently listed as a threatened species under the U.S. Endangered Species Act. Results indicate a north-south cline in population risk, with northern Oregon populations at higher risk than central and southern Oregon populations.

Erosion of Heterozygosity in Fluctuating Populations. THOMAS A. WAITE*, Dept .of Evol., Ecol. & Organismal Biol., Ohio State Univ., Columbus, OH, and JOHN A. VUCETICH, School of Forestry, Michigan Tech. Univ., Houghton, MI.

Demographic, environmental, and genetic stochasticity threaten the persistence of isolated populations. The relative importance of these factors remains unresolved, but a widely held view is that random demographic and environmental events will usually drive small populations toward extinction before genetic deterioration poses a serious threat. To evaluate the potential importance of genetic factors, we analyzed a model linking demographic and environmental conditions to the loss of genetic diversity in isolated populations undergoing natural levels of fluctuation. Nongenetic population processes were modeled as a bounded diffusion process. Genetic processes were modeled by quantifying the rate of drift as predicted by the effective population size, which was predicted from the same parameters used to describe the nongenetic processes. We joined these two models to predict the heterozygosity expected to remain at the mean time to extinction. Our model predicts that many populations will lose most or all of their neutral genetic diversity before nongenetic random events lead to extinction. Given the abundant evidence for inbreeding depression and recent evidence for elevated extinction rates of inbred populations, our findings suggest that inbreeding may be a greater general threat to population persistence than generally recognized. Conservationists should thus consider the genetic component of extinction risk when assessing species endangerment and developing recovery plans.

Applications of Individual-based Models to PVA. JEFFREY R. WALTERS*, Dept. of Biology, Virginia Tech, Blacksburg, VA, and LARRY B. CROWDER, Duke Univ. Marine Laboratory, Beaufort, NC.

Spatially-explicit, individual-based models are more complex than the stochastic matrix models frequently used in PVA. They are often superior to more aggregated models when individuals differ in their effects on vital rates, when populations are small and when spatial proximity among individuals influences their probability of survival or growth. For endangered species, several of these conditions frequently apply. Individual-based models allow us to incorporate important details of the biology rather than make simplifying assumptions, and to simulate vital processes at the level of the individual (where space matters). But the gap between the data available and data required for these models typically is large, sometimes leading to questionable applications of the individual-based approach. The motivation for applying spatially-explicit models in most of the cases we review is the vital importance of habitat distribution to conservation. Ultimately, the available data limit which models are most appropriate to use. We focus especially on a species with complex social structure whose population dynamics cannot be modeled accurately with other approaches, the red-cockaded woodpecker. When we applied our spatially-explicit population model for red-cockaded woodpeckers to theoretical populations, we found that the spatial distribution of individuals can have as large an effect on population viability as population size. Comparisons to results from a stochastic, stage-based matrix model indicate that ignoring known spatial constraints on dispersal can have a pronounced effect on assessing population viability. Recently, we have applied our model to real landscapes to assess the relative effectiveness of alternative locations of new territories in improving population viability.

Issues Associated with the Definition and Estimation of Effective Population Size in the Conservation of Endangered Species. ROBIN S. WAPLES, Conservation Biology Division, National Marine Fisheries Service, Seattle, WA.

Effective population size (N_e) is widely acknowledged to be one of the most fundamental evolutionary parameters of biological systems. Nevertheless, application of the concept has not been fully integrated into management of endangered species in general or to PVA in particular. A variety of factors have contributed to this situation, including (1) difficulty in obtaining ecological information to compute N_e; (2) concerns regarding precision and bias of indirect genetic methods for estimating N_e; (3) lack of clarity in defining the temporal scale of interest (annual vs. generational vs. long-term N_e); (4) confusion regarding the magnitude (and meaning) of the ratio N_e/N; (5) failure to adequately account for spatial and metapopulation structure and their effects on N_e; and (6) limitations of existing models relating N_e to persistence times and extinction probabilities. I will discuss these factors and suggest approaches to more fully integrate effective size considerations into endangered species management.

Use of Marked Animals for Estimating Parameters in PVA Models. GARY C. WHITE*, Dept. of Fishery and Wildlife Biology, Colorado State Univ., Fort Collins, CO, and ALAN B. FRANKLIN, Dept. of Fishery and Wildlife Biology, Colorado State Univ., Fort Collins, CO.

Population viability analysis examines the question of whether a biological population of a given size will persist (remain viable) for some specified time period. To develop useful estimates of population viability, stochastic population models must be developed that incorporate demographic, temporal, and individual variation. A re-parameterization of the Jolly-Seber model by Pradel (Pradel, R. 1996. Utilization of capture-mark-recapture for the study of recruitment and population growth rate. Biometrics 52:703-709) incorporated into Program MARK allows the estimation of survival and recruitment rates, or alternatively, finite rate of population change. Pradel's model has been recently implemented into Program MARK, a comprehensive software package for analysis of data from marked animals. Also incorporated into MARK are procedures to separate sampling variance of estimates from variation inherent in the population growth process. Most previous population viability analyses have not removed sampling variation from parameter estimates, so these studies underestimate population persistence. Program MARK also allows inclusion of individual covariates, allowing some determination of the importance of individual heterogeneity in the population growth process. As a final step, the uncertainty (sampling variance) of parameter estimates must be incorporated into estimates and confidence intervals of persistence.

Facing a World of Sparse and Messy Data: Lessons from an Individual-based Model for Assessing the Risk of Extinction for Brown Bears (Ursus arctos) in Northern Spain. THORSTEN WIEGAND*, Dept. of Ecological Modelling, Centre for Environmental Research, Leipzig, Germany, and JAVIER NAVES, Dept. of Zoology, Univ. Oviedo, Spain.

The poor quality of data and difficulties in parameter estimation are serious limitations for applying demographic models in Population Viability Analysis (PVA). Here we propose orientation towards real patterns observed in nature as one way to estimate population parameters from incomplete data sets. We exemplify our approach for an endangered brown bear population in northern Spain. The individual-based simulation model, based on long-term field investigations on this population, includes detailed life history data and information on environmental variations in food abundance. We use the 1982-1995 time pattern of observed number of females with cubs of the year (COY) to determine current population parameters. We systematically compare the patterns produced by the model with the observed pattern for a high number of parameter combinations. The observed pattern acts as a "filter" that sorts out implausible parameter sets. The model simulations with the best adjustment of the COY index facilitate a detailed reconstruction and analysis of the population size development during the 1982-1995 period. We estimated that the population currently consist of 25 or 26 independent females and a total of 50-60 individuals. However, our viability analysis showed that the population does not satisfy the criterion of a Minimum Viable Population (MVP) if mortalities remain at the level of the last few years of 1988-1995. The "salvation" of at least one independent female every three years is required.

The Effect of Life History Strategy and Variation on Diffusion Approximations for Extinction Probabilities. CHRIS WILCOX*, Dept. of Environmental Studies, Univ. California, Santa Cruz, CA, and HUGH POSSINGHAM, Dept. of Environmental Science and Management, Univ. Adelaide, Australia.

Diffusion theory approximations have been very influential in the area of population management for threatened species. They have been widely used to calculate mean time to extinction for populations, and have been extended to cases with catastrophic mortality and harvesting. These models have been championed over simulation models due to their simplicity and the possibility of analytical results. However, diffusion models only approximate the actual changes in population size and may vary from the results obtained using a random walk model that simulates the biology of a species more closely. We explore the deviations between the diffusion approximation and simulation results across a range of life-history parameters, including variance in mortality and fecundity rates and catastrophes. We compare deviations for three general life history strategies: annual species with very high reproduction typical of invertebrates and many plants, short-lived perennial species with intermediate reproduction typical of amphibians and small mammals, and long-lived species with low reproduction typical of large mammals. By comparing the accuracy of the approximation across these life history strategies we are able to suggest circumstances where using a simple diffusion approximation may not be preferable to the more complex and idiosyncratic simulation model approach. Our results indicate that there are significant deviations, both qualitative and quantitative, between the diffusion approximation and the simulation model. Given that these types of predictions are used for management decisions, our results could qualitatively change the basis for conservation activities for threatened populations.

Implications of Dispersal for Five Populations of Stripe-Backed Wrens in the Venezuelan Savanna. M. CAROLINA YABER* Dept. of Biol. Science, Purdue Univ., West Lafayette, IN, and KERRY N. RABENOLD. Dept. of Biol. Science, Purdue Univ., West Lafayette, IN.

Five populations of stripe-backed wrens (Campylorhynchus nuchalis) with study histories of 6-20 years make it possible to: 1) use behavioral and demographic data to test the hypothesis that patterns of dispersal in a naturally fragmented population make it necessary to study birth, death and dispersal on a large spatial scale encompassing multiple interacting populations in order to assess viability; 2) evaluate the applicability of a variety of metapopulation models, contrasting source-sink models with those in which populations are more mutually interdependent; 3) evaluate the importance of dispersal in the rescue of declining populations; and 4) evaluate how the social systems of stripe-backed wrens affect dispersal among the populations. The five populations are independent in their demographic dynamics. Neither survival nor fecundity is correlated among these populations nor are they autocorrelated or density-dependent. Dispersal among these populations is strongly affected by the social system. Effective, within-population dispersal occurs more than expected to groups containing four or more adults. Field experiments have shown that dispersers choose large groups where reproductive success is high, and that proximity of natal group confers a competitive advantage. Because of these constraints, effective interpopulation dispersal is uncommon, except when the recipient population is at very low density.

POSTERS

The Implications of Environmental Variability, Disease and Catastrophes for Management of African Elephants. SANDY J. ANDELMAN*, National Center for Ecological Analysis & Synthesis, Santa Barbara, CA, and IAIN DOUGLAS-HAMILTON, Save the Elephants, Nairobi, Kenya.

Historically, elephants ranged nearly continuously throughout much of sub-Saharan Africa. However, elephant populations today are greatly reduced, and increasingly restricted to protected areas. Historically, elephant populations were probably relatively open over large geographic scales. Conflicts with humans now necessitate that, increasingly, elephants are and will be managed within a series of relatively isolated protected areas, with limited opportunities for movement from one park to another. Here we use stochastic, density-dependent population models, in conjunction with long-term data on a population of elephants in Lake Manyara National Park, Tanzania, as well as elsewhere, to evaluate the implications of environmental variability, disease, and catastrophic poaching episodes for long-term management of elephants in protected areas throughout Africa.

Time Frames for Population Viability Analysis of Species with Long Generations: An Example with Asian Elephants. PETER ARMBRUSTER*, Institute of Zoology, Zoological Society of London, Regent's Park, London, UK, PRITHIVARA J. FERNANDO, Center for Environmental Research and Conservation, Columbia Univ., New York, NY, and RUSSELL LANDE, Dept. of Biology, Univ. Oregon, Eugene, OR.

We extend an earlier population viability analysis (PVA) of the Asian elephant (Elephas maximus) conducted by Sukumar and Santiapillai (1993) in order to examine how conclusions about viability can depend upon the time frame examined. We find that there is an approximately 200 year lag period before extinction events begin to occur in slowly declining populations of E. maximus. Therefore, examining population persistence over a 100 year time frame seriously underestimates the risk of population extinction over a longer, 1,000 year period. These results are supported by the use of both a species-specific model of elephant demography, ELEPHANT, and a generic PVA package, VORTEX. For populations with long generations, a 100 year time period will often not be sufficient to evaluate demographic processes leading to extinction. These results have important implications for how investigators conduct PVAs, and for the listing of endangered species by the World Conservation Union (IUCN).

Is PVA Useful for the Management of Threatened Coho Salmon Populations? MIKE BRADFORD, Fisheries and Oceans Canada, and Resource and Environmental Mgmt., Simon Fraser Univ., Burnaby, BC.

A large complex of coho salmon populations from the interior of British Columbia has declined dramatically (>90% reduction) in the last 3-4 generations. To provide management advice for the conservation of these populations I conducted 2 analyses following Caughley's (1994) paradigms: (1) the analyses of the causes of the declines, and (2) the viability of these populations in the short and medium term under different harvest rate scenarios. The cause of the declines can be attributed to a combination of overfishing and continuously declining survival of juvenile salmon in the sea. Results of forward simulations used to determine the risk of extinction for these populations were very dependent what was assumed about the sea survival rates. Because we do not know the mechanism for the decline in sea survival rates, we cannot predict whether they will continue to decline, stabilize, or return to previous higher levels. When this uncertainty is admitted in the PVA, risk of extinction estimates are extremely imprecise and provide little utility to managers. Instead, the PVA model was collapsed to a very simple form to provide qualitative information about the relative ranking of different management options. This information was expressed as likely population trends (increasing or decreasing)rather than probabilities of extinction. The coho salmon example illustrates how our inability to predict trending environmental factors may limit the utility of PVA for predicting the fate of small populations.

Expert Judgments in Population Viability Analysis: Experiences from Ecoregion Assessments. DAVE CLEAVES*, USDA Forest Service, Washington, DC; RICHARD HOLTHAUSEN, USDA Forest Service, Flagstaff, AZ; and Bruce Marcot, USDA Forest Service, Portland, OR.

Expert inferences and predictions are important components of species population viability analysis (PVA). These expert judgments can take the form of choices about model structure, interpretations of model output, or predictions of habitat or population conditions. Some challenges to the validity and usefulness of PVA have been directed at the quality of its expert judgment components and the processes through which the judgments are elicited and analyzed. Problems noted have included unexplainable differences in predictions given the same data, rationales that are difficult to understand, and scant or ambiguous interpretation of the sensitivity of the output to variation in the data or assumptions. This paper will review the experiences of the Forest Service in eliciting, organizing, and using expert judgment in population viability and wildlife habitat assessment. It will provide a rationale for improving judgment quality and outline the basic issues in eliciting and analyzing expert judgment, including: (1) judgment (causal relationship) modeling, (2)biases—task, cognitive, and motivational, (3) endpoint definition and specification, (4) response scale design, (5) process options for eliciting judgments, (6) interpreting outputs to decision makers, and (7) acceptance in the scientific community. Case material will be taken from large-scale analyses. Based on these experiences and on findings from the decision sciences, the paper will propose the design of a protocol for expert judgment elicitation. The protocol would make use of structured process, objective analysts/facilitators, bias awareness and correction procedures, and incentives for candor and introspection. Its objective would be to make it easier for experts, individually or in panels, to more clearly and accurately express their opinions and uncertainties. The paper will encourage the adoption of government-wide guidelines for eliciting or using expert opinion and will outline how the scientific community can contribute by better articulating the role of scientists and scientific opinion in PVA modeling for management decision making.

Logistic Regression as a Method of Sensitivity Analysis in a Stochastic Population Model of African Wild Dogs. PAUL C. CROSS, Dept. of Environmental Science, Policy, & management, Univ. California, Berkeley, CA.

The strength of population viability analysis lies in the ability to test hypotheses, identify the relative importance of model parameters, and assess alternative management actions. Yet few studies of population viability conduct a formal sensitivity analysis. I used logistic regression to determine the relative importance of 11 parameters in a three-stage stochastic population model of African wild dog (Lycaon pictus) dynamics. Year-to-year variability in survival and litter size were relatively unimportant parameters regardless of density dependence or carrying capacity. The percent of females that bred per year, adult survival and disease probability were the most important parameters in predicting extinction probability. Logistic regression did not reveal that the severity and probability of a disease outbreak affected the ending population distribution in different ways. High disease severity caused a bimodal distribution of ending population size that alluded to a threshold value, below which a population was likely to go extinct during periods of high disease severity. This analysis does not indicate whether the extinction of wild dogs in the Serengeti ecosystem was caused by increased stress due to researcher handling. However, the logistic regression indicated that disease outbreak and adult survival were relatively important parameters to the survival of African wild dogs. Extrinsic factors which affect the probability and severity of disease outbreaks as well as adult survival may have a large impact upon wild dog populations.

A Generic Metapopulation Program for Conservation, Planning and Teaching: META-X. KARIN FRANK*, Dept. Ecological Modelling,Centre for Environmental Research, Leipzig, Germany, VOLKER GRIMM, Dept. Ecological Modelling,Centre for Environmental Research, Leipzig, Germany, CHRISTIAN WISSEL, Dept. Ecological Modelling,Centre for Environmental Research, Leipzig, Germany, and HELMUT LOREK, Offis, University of Oldenburg, Germany

A program is presented, META-X, which implements a generic metapopulation model. The aim of the program is to enable non-modellers to perform PVA of metapopulations. The model is a spatially explicit patch occupancy model. Patch characteristics, connections between patches, dispersal probabilities and probabilities of correlated extinctions on different patches can be specified. The main difference to other generic metapopulation models is that local population dynamics is not modelled explicitly. This means that local extinction risk has to determined with other models or has to be estimated based on the knowledge available. The program which implements the model is designed to guide users to perform comparative experiments, i.e. not to assess extinction risk per se but to assess how extinction risk changes due to changes in models parameters or if different management scenarios are chosen. In this way the program may help to base management decision more on understanding than on mere numbers. The program makes use of modern features provided by Windows. We present sample analyses performed using META-X. Potential users of META-X are field ecologists who want to test ideas, planners and managers, and teachers.

Population Viability Assessment for Two Tiger Beetles, Cincindela dorsalis dorsalis and C. puritana, based on Analyses of Population Counts. JAMES P. GIBBS*, College of Environmental Science and Forestry, State Univ. New York, Syracuse, NY, C. BARRY KNISLEY, Dept. of Biology, Randolph-Macon College, Ashland, VA, and SCOTT M. MELVIN, Mass. Div. Of Fish and Wildlife, Westboro, MA.

Population viability analyses for insects typically involve stage-based population models that require estimation of stage-specific transition and survival probabilities and fecundity rates. Such information simply is not available for most endangered insects. As an alternative to conventional viability modeling, we used statistical patterns observed in the population dynamics in two federally listed, beach dwelling tiger beetles, Cincindela puritana and C. dorsalis dorsalis, to provide an empirical basis for viability modeling. Given an initial population size, the expected growth rate of a population in a subsequent year was modeled from the slope and intercept of known density-dependent relationships between population size and growth rate in these species. "Noise" observed in the density-growth relationship provided stochasticity in population projections. This modeling approach has been used to examine issues of minimum population size, metapopulation structure, and potential levels of "harvest" for use in beetle translocations. The approach's simplicity and strict reliance on empirical patterns observed in population counts implies that the method should produce reliable predictions. Nevertheless the method is dependent on accurate estimation of the parameters describing the density-growth patterns in tiger beetle populations.

Persistence Times in Predator-prey Communities Undergoing Multiple Introductions. LAURA HARTT, Dept. of Zoology, Univ. of Toronto, Toronto, Ontario.

I randomly assemble native predator-prey communities and subject them to multiple species introductions in order to examine factors influencing persistence times for both exotic and native species. I compare the persistence times for predators and prey as a function of (a) exotic propagule size, (b) pattern of introduction, (c) ratio of predator to prey exotics, and (d) community structure. In most cases, prey persist longer than predators, and natives persist longer than exotics. Furthermore, increasing either the frequency or the intensity of introduction reduces native persistence times, but the effects of introduction pattern on exotic persistence time are more variable. Increasing exotic predator propagule size reduces both native and exotic persistence times, especially when introductions are of high frequency. Exotic prey propagule size has little effect on persistence time. In general, decreasing the predator to prey ratio of exotics increases prey persistence times. Exotic trophic ratio has variable effects on exotic persistence times. Finally, increasing species number within the native community decreases persistence times, but the degree of generalization may modify this effect somewhat. My findings suggest: (1) multiple introductions may impact native predators more than prey, (2) exotic predators may have a greater negative effect on native persistence times than exotic prey do, (3) increasing either the intensity or the frequency of introductions reduces persistence time for exotics as well as natives, and (4) a community's trophic structure modifies the impact of exotics on native persistence times.

Simulating Viability of a Spadefoot Toad (P. fuscus) Metapopulation in a Landscape Fragmented by a Road. TOVE HELS*, Dept. of Landscape Ecol., Natl. Env. Res. Inst., Denmark, and GÖSTA NACHMAN, Dept. of Pop. Biol., Univ. Copenhagen, Copenhagen, Denmark.

A population based stochastic simulation model including demographic and environmental stochasticity was developed in order to predict the development of a P. fuscus metapopulation. The metapopulation (consisting of about 1,000 adult individuals) was intensively studied in the field for a period of four years and the simulation model was parameterised (sex ratio, age-specific survival rates, fecundity, and dispersal between subpopulations) in accordance with field data. A sensitivity analysis revealed that a relative change in the juvenile yearly survival rate had a larger effect on population persistence than adult survival rate and fecundity rate had. Varying dispersal rate showed that four of the five subpopulations were dependent on the last one for persistence, indicating a source-sink structure of the metapopulation. The subpopulation with the highest estimated juvenile survival had a far higher persistence probability than the others; they in turn would go extinct were it not for the input from the stable subpopulation. The source-sink structure was also apparent when simulating the isolation effect of the road: persistence of the subpopulation isolated by the road decreased markedly with only a 20% decrease in the number of individuals dispersing to this pond. Environmental stochasticity decreased persistence probability of the stable subpopulation and increased persistence probability of the unstable ones. This is probably due to the density-dependent regulation of the subpopulations and to the more general effect of stochasticity: It may temporarily change reproduction and mortality rates, increasing time to extinction for unstable subpopulations and decreasing time to extinction for stable subpopulations.

Developing a Spatially Explicit PHVA for Grizzly Bears in the Central Rockies Ecosystem (CRE). STEPHEN HERRERO*, Environmental Science Program, EVDS, Univ. Calgary, Calgary, AB, and MICHAEL L. GIBEAU, Committee on Resources and Environment, Univ. of Calgary, Calgary, AB.

The Eastern Slopes Grizzly Bear Research Project (ESGBP) now has 5 years of radio-telemetry locations (7000 data points), vital rate and habitat data for about 50 grizzly bears in a 40,000 sq. km area surrounding and including Banff National Park (the CRE). There are nearly one million people within 100 km of the project area, making this one of the most developed landscapes in North America where grizzly bears survive. There is also extensive forestry, oil and gas, and recreational activity. The project is multi-stakeholder and is university based, and involves federal and provincial governments, business and industry, and conservation groups. Project research direction and funding are facilitated by a Steering Committee of major stakeholders. The project goal is to scientifically understand and to contribute to managing the cumulative effects of development on the regional grizzly bear population and habitat. A population estimate was generated in a 4000 sq. km. portion of the project area in 1996 using hair snagging and DNA analysis in a capture/recapture design. The confidence limits were not acceptable. We are now working toward calculating lambda using female reproductive, and population survivorship data, and bootstrapping. In January of 1999 the ESGBP is hosting a major workshop on linking PVA and habitat conditions. Our intent is to generate a spatially explicit PHVA and to use this as one tool in understanding the cumulative effects of development on grizzly bears in our region. While the ESGBP does not have formal policy, planning or management responsibility, we have influenced decisions regarding grizzly bear mortality and habitat because of the participation of decision makers on the project Steering Committee.

Modeling Equilibrium Population Size and Life-stage Structure for Site-dependent Species. W. GRAINGER HUNT*, Predatory Bird Research Group, Univ. of California, Santa Cruz, CA, and PETER R. LAW, Predatory Bird Research Group, Univ. of California, Santa Cruz, CA.

Spatial partitioning by pairs of territorial birds restricts cohort size per unit area of landscape, setting an upper limit to an equilibrium size range for the total population deriving from any defined area. Floaters maintain the lower limit by filling territorial vacancies. This phenomenon, known as Moffat's equilibrium, provides the basis for modeling age- and stage structure either under the assumption of annual constancy in vital rates or with variation thereof. The floater-to-breeder ratio at equilibrium is a more informative indicator of population health and stability than a growth rate estimate. Another useful parameter, the floater-to-breeder transition rate, can be directly estimated from field data. The existence of floaters implies an adaptive threshold of site suitability that underscores the importance of identifying and conserving the elements of high quality breeding areas for threatened or endangered species of territorial birds.

Population Viability Analysis of Northern Goshawks in East-central Arizona. MICHAEL F. INGRALDI*, Research Branch, Arizona Game and Fish Dept., Phoenix, AZ, and PAUL BEIER, School of Forestry, Northern Arizona Univ., Flagstaff, AZ.

We developed a population viability analysis model to project the future population status for northern goshawks in east-central Arizona. The northern goshawk is an Arizona Game and Fish Department Species of Special Concern, a U.S. Forest Service sensitive species and has recently received a status review by the U.S. Fish and Wildlife Service for potential listing under the Endangered Species Act. To parameterize the model, we monitored demographic rates (activity rate, fecundity, sex ratio at fledging, and survivorship of age classes) at 44 breeding territories on the Sitgreaves National Forest for six years (1993-1998). Our stage-structured stochastic model suggests that with the current parameter values (fledgling sex ratio of 2 males to 1 female, low adult survivorship rate), the Sitgreaves National Forest acts as a "sink" habitat for northern goshawks. Sensitivity analysis shows that varying adult survivorship has the greatest effect on the stability of the population.

Limitations of Population Viability Analysis in the Absence of Evidence, Case Study of the Eskimo Curlew (Numenius borealis). EVE IVERSON, Dept. of Agronomy & Range Science, Univ. California, Davis, CA.

Population analysis does not work with highly migratory species that exist in low numbers. The Eskimo curlew (Numenius borealis) is one of the rarest birds in North America. The curlews’ migration route from Arctic Canada to the pampas of Argentina, and its still undetermined return route, make direct observation and study problematic. The historic breeding grounds are remote and difficult to survey. The wintering habitat is unknown. The complete migration route has not been established. The timing of migration can only be estimated from specimen records. Today birds do not appear at any location consistently making a census impossible. All of the sightings since 1945 have been of single birds, pairs, or small groups. There is no way to determine if a bird seen in one location is the same one seen later in another place. There is no system to evaluate these scattered reports and determine if the identification is correct. This makes population estimation more guesswork than science. Determining if a population is viable depends on solid data. The lack of reliable data on the population and distribution of the Eskimo curlew makes the application of any statistical analysis technique unsupportable. The Eskimo curlew is a species that does not lend itself to modeling in any form.

Viability Analysis of White Sturgeon Populations in a Fragmented River Habitat. HENRIETTE I. JAGER*, Oak Ridge National Laboratory, Oak Ridge, TN, WEBB VAN WINKLE, Oak Ridge, TN, KEN B. LEPLA, Idaho Power Co., Boise, ID, and JIM A. CHANDLER, Idaho Power Co., Boise, ID

We are conducting a population viability analysis (PVA) for white sturgeon (Acipenser transmontanus) populations in the Snake River, Idaho. Concerns for the viability of this ancient fish species are based on its delayed maturation (13 to 25 years) and anadromy. Population declines have been attributed to: (1) habitat fragmentation, (2) genetic isolation, (3) degraded water quality, (4) loss of spawning habitat, (5) entrainment mortality, (6) reduced prey availability, (7) contaminant exposure, and (8) hooking mortality. We developed an individual-based PVA model. As a first step in our hierarchical PVA process we summarized the simulated likelihood of persistence to 1000 years as a logistic function of survival during three life stages, without regard to mechanistic factors. In the second step, we focused in on the first five mechanistic factors listed above. First, we simulated a 200-km river reach divided by 1 to 10 dams and quantified the effects of fragmentation alone on persistence. Next, we estimated the length of remaining free-flowing river and considered two hypothesized forms of density-dependent habitat limitation associated with fragmentation. In another scenario, we evaluated the effects of various policies that would alter migration. In each simulated scenario, we separately evaluated the effects on population viability and on neutral genetic diversity. Predicted viability declined faster with habitat loss than with fragmentation alone. Our migration experiments identified downstream migration without upstream movement as a potential demographic and genetic threat to land-locked upstream populations.

The Effect of Fire on the Population Viability of an Endangered Prairie Plant. THOMAS N. KAYE*, Dept. Botany and Plant Pathology, Oregon State Univ., Corvallis, OR, KATHY L. PENDERGRASS, Bureau of Land Management, Eugene, OR, KAREN FINLEY, Corvallis, OR and DAVID A. PYKE, USGS, Forest & Rangeland Ecosystem Science Center, Corvallis, OR.

We examine the effects of fire on population growth rate and extinction probability of a rare plant. Lomatium bradshawii (Apiaceae) is an endangered species of western Oregon and Washington prairies that were frequently burned by Native Americans prior to 1850. We used transition matrix models and observed stochasticity to evaluate the effects of controlled burns on the viability of two populations. Unburned plots had population growth rates (lambda) of 0.928-0.943. Burning twice in six years increased growth rates to 0.976-1.110, and three burns yielded growth rates of 1.014-1.190. Stochastic growth rates were lower but showed similar trends. The risk of extinction (100 yr, extinction =<10 individuals) was calculated by incorporating stochasticity through randomly shuffling whole annual matrices (using POPPROJ), or selecting each matrix element from a normal distribution with observed mean and variance (with RAMAS/stage). Extinction probability (EP) was very high (97-99%) in the absence of fire for both methods and sites, but with two burns declined to 60% and 73% for matrix selection and element selection, respectively at one site, and 1% (both methods) at the other. EP was very low (<=1%) for both methods and sites after three burns. Although different methods of incorporating stochasticity gave slightly different quantitative results (especially in short-term projections), they were qualitatively similar. Fire is an effective tool for maintaining viable populations of this species.

Estimating the Magnitude of Environmental Stochasticity in Demographic Processes. BRUCE E. KENDALL, Donald Bren School of Environmental Science & Management, Univ. California, Santa Barbara, CA.

Small populations are subject to both demographic and environmental stochasticity. If populations are modeled with explicit demographic processes (survival, reproduction, dispersal) instead of with aggregate population growth rates, then it is conceptually possible to separate these sources of variability in biologically defensible ways. Indeed, most modern PVA software makes this distinction. How does one empirically estimate the magnitude of these variabilities? Most studies based on long-term demographic data have assumed that all of the variation in observed demography (such as percent survival) is due to environmental stochasticity. Much of this variation can in fact be caused by demographic stochasticity. The resulting inflated estimates of the magnitude of environmental stochasticity can lead to overly pessimistic predictions of population viability. Here I demonstrate a likelihood approach for acquiring a less biased estimate of the magnitude of environmental stochasticity. This requires explicit models of demographic stochasticity (for example, within a year survivorship is binomially distributed) and environmental stochasticity (a distribution describing how the survival probability varies among years). These models can incorporate additional biological detail such as density dependence. This approach also provides confidence intervals, giving an estimate of uncertainty in the environmental stochasticity parameters. The consequences of this uncertainty for viability analysis can be explored through simulation modeling.

Hippo Critical Issues: A Population Viability Analysis for the Hippopotamus (Hippopotamus amphibius ). REBECCA LEWISON, Dept. of Wildlife, Fish & Conservation Biology Univ. California, Davis, CA.

The distribution of the hippopotamus is declining across the African continent. The most prominent threat that remaining hippopotamus populations face is habitat disruption or destruction, which occurs as a result of natural rainfall variation and human-induced water reduction related to farming and other human activities. Changes in water conditions can dramatically impact mortality and conception rates. Since hippo population dynamics are extremely sensitive to changing habitat conditions, determining the probability of persistence for future hippopotamus populations requires the development of population monitoring tools which incorporate environmental change. Here, I present an environmental state PVA (sensu Beissinger 1995) for hippopotamus populations within a representative protected area in East Africa. The model uses four rainfall states which each correspond to a set of demographic parameters. Transition between states will be based on probabilities derived from a 50 year rainfall record for the model area. This PVA will allow an evaluation of the effect of both natural rainfall fluctuations and human-induced habitat destruction on a hippopotamus population. The model will provide a template which can be used to estimate the likelihood of persistence of remaining hippopotamus populations across East Africa and provide land managers crucial information on the need for protective measures.

Density Dependence at Low Densities in Spawner-recruit Models. MARTIN LIERMANN, National Marine Fisheries Service, Seattle, WA.

In spawner-recruit (SR) analysis attention has tended to focus at intermediate densities where maximum sustainable yield (MSY) occurs. However, as conservation has become more of an issue in fisheries management the development of models that more realistically portray low density dynamics has begun to receive more attention. One of the most commonly used SR models, the Beverton-Holt, is based on the biological assumption that instantaneous per-capita mortality is linearly dependent on the density of the pre-recruits. A simple generalization of this assumption produces a three parameter SR model with much more general low density characteristics. The various shapes of this curve can be loosely associated with different types of competition. Because SR data tends be very noisy it is difficult to determine how density dependence is occurring, especially at low densities. However, using this as a reason to rely on simpler models may result in overestimation of population resilience. This is demonstrated using simulations.

Reproductive Ecology and Population Viability of British Columbia's Endangered Brewer's Sparrow (Spizella breweri breweri). NANCY A. MAHONY*, Centre for Applied Conservation Biology, Faculty of Forestry, Univ. British Columbia, Vancouve,r BC, and PAM G. KRANNITZ Pacific Wildlife Research Centre, Canadian Wildlife Service, Delta, BC.

Brewer's Sparrows (Spizella breweri breweri) are red-listed in B.C. due to their restricted breeding range and threatened shrubsteppe breeding habitat. North American Breeding Bird Survey data indicate that this species has declined significantly throughout its entire range, by 3.9% per year for the last 30 years. The spatial pattern of this decline indicates that it may be most severe in the core of the range with more stable populations at the range periphery. This patterns shows that B.C.'s population, at the northern range edge, may not only be provincially significant, but, if stable or increasing, could be an important conservation refuge for this species. We are studying the reproductive ecology and population viability of Brewer's Sparrows at four sites in southern B.C. to determine population dynamics and to examine how reproductive success is related to habitat quality and food availability. In 1997 and 1998 we color-banded 101 and 125 adults, and 26 and 225 fledglings respectively. We also followed nest, hatching, and fledging success for 115 and 258 nests in 1997 and 1998 respectively. We will use Population Viability Analysis (PVA) to investigate which life history stages are key to population dynamics, the rate of population change, and the relative risk of extinction at the four sites. Field work will continue in 1999 and 2000 to collect further demographic data. Examining the factors that affect reproduction and determining population viability will allow us to make management recommendations for this provincially endangered and possibly, globally significant population.

A Graphical Approach to the Visual Representation of Avian Population Viability. ROBERT H. MELTON*, U. S. Army Construction Engineering Research Laboratories, Champaign, IL, LESLIE A. JETTE, U. S. Army Construction Engineering Research Laboratories, Champaign, IL, and TIMOTHY J. HAYDEN, U. S. Army Construction Engineering Research Laboratories, Champaign, IL.

We present a population viability analysis of the Red-cockaded Woodpecker on Fort Stewart, GA. The analysis employs a single-sex Lefkovitch population matrix, modified to include the effects of population carrying capacity, demographic and environmental variation in vital rates, and annual immigration and emigration. The state of the population is presented as a point in a 3-dimensional space with axes representing mean annual seasonal fecundity, juvenile (hatch-year) survival rate, and adult (post-hatch-year) survival rate. Graphically, this is presented in three 2-dimensional graphs. Also presented in each graph are three lines, each line representing combinations of vital rates denoting thresholds for each of three levels of population viability (vulnerable, endangered, and critical) as defined in Mace & Lande (1991, Conservation Biology 5: 148-157). A fourth line is shown representing the threshold level for attainment of a user-defined population target density at the end of 100 years, with a given degree of probability. Thus, the state of the population is presented in a rich visual context of potential population viability states related to survival and fecundity. This facilitates a holistic visual assessment of the population's present viability, and of the relative effects of potential changes in vital rates due to environmental disturbance, population management, or revised Army training procedures. The model is meant as a first-approximation to population viability, and is suited to avian populations for which limited basic demographic data have been collected, and for which a rapid, readily intuitable approximation of viability status and management options is needed.

Modeling California Condor Demography to Assess Condor Release Programs. VICKY J. MERETSKY*, School of Public and Environmental Affairs, Indiana Univ., Bloomington, IN, NOEL F.R. SNYDER, Wildlife Preservation Trust International, Portal, AZ, and STEVEN R. BEISSINGER, Dept. Environmental Science, Policy, and Management, Univ. California, Berkeley, CA.

In April 1987, the last wild California condor was brought into captivity to join 26 others - all that remained of the species. Earlier studies of condors in the wild provide estimates of nest success, sex ratio, proportion of population paired, probability of renesting following a failed nest, and mortality that can be used as expectations to evaluate the level of survivorship required for reintroductions to be successful. Releases of captive-reared California condors to the wild began in southern California in 1992. Currently, release programs are in place in southern and central California and in northern Arizona. Released condors have been reared by parents or by puppets, and some have been aversively conditioned to avoid humans and human structures. Annual mortality among release cohorts has ranged from 0 to 64% and may be linked to rearing strategy; effects are confounded by mixing of parent- and puppet-reared birds in most instances. We use stage-based matrix models to determine mortality rates that would allow populations to persist under various estimates of reproductive success. We also examine alternative strategies for modeling uncertainty in input parameters. Our results suggest that parent rearing may be a more successful strategy for release birds, and we encourage release programs to conduct releases in such a way that analysis of release success is not continually confounded.

Effects of Carrying Capacity and Age-Specific Mortality on Hawaiian Tree-Snail Populations. STEPHEN E. MILLER*, U.S. Fish and Wildlife Service, Honolulu, HI, MICHAEL G. HADFIELD, Dept. of Zoology, Univ. Hawaii, Honolulu, HI.

The Hawaiian Islands contain one of the most endangered animal and plant assemblages on earth. Hawaiian tree snails on the island of Oahu are listed as endangered and most other native Hawaiian snails are equally endangered but have not received formal protection under the Endangered Species Act. Long term life-history studies of tree snail populations on Oahu and Molokai have provided longitudinal data on age-specific survivorship and growth. Field observations and laboratory studies have provided estimates of annual fecundity. Using these parameters, population viability analyses of show that carrying capacity can set a threshold for recovery, below which mean population size decreases to an initially low but stable level until stochastic extinction. Above the carrying capacity threshold, mean population sizes increase to higher stable levels with a decreasing change of extinction. Small decreases across all age-specific mortalities result in more stable populations at larger mean sizes than can be achieve by larger decreases in adult mortality alone. These results indicate that conservation of Hawaiian tree snails should focus on reducing age-specific mortalities and reversing habitat degradation to a point that allows for increased carrying capacity beyond a recovery threshold. Habitat restoration is probably achievable and will require weed control and regeneration of native vegetation. Reductions in snail mortality require controlling field populations of rats and alien predatory snails, which will be a costly and long term at significant landscape levels. Population data for these predators are lacking but may indicate the level of actions required to achieve the recovery of Hawaiian tree snails.

Predicting the Occurrence of Flying Squirrels with Landscape Data. MIKKO MÖNKKÖNEN*, Dept. Biology, Univ. Oulu, Oulu, Finland, PASI REUNANEN, Dept. Biology, Univ. Oulu, Oulu, Finland, and ARI NIKULA, Finnish Forest Research Institute, Rovaniemi Research Station, Rovaniemi, Finland.

Flying squirrel Pteromys volans is a forest specialist species, whose populations have declined dramatically during the past few decades in Finland, and are considered prone to regional extinction in northern Finland. Comparisons between occupied and unoccupied sites by the species have shown that flying squirrel home ranges are characterized by old spruce forest with a high proportion of deciduous trees. At the landscape scale, occupied sites differ from random sites by a high degree of connectivity between suitable forest sites. We use these data to make predictions about the occurrence of the species in northern Finland. We exploit Finnish Forest Inventory data, which is based on satellite image and field reference sites, as background information. Using GIS we first surveyed northern Finland for potential home ranges based on the information of home range size and on the occurrence of specified forest characteristics within that area. We then applied connectivity criteria to pick out only the sites where probability of flying squirrel occurrence is high. We applied several options in these criteria to yield qualitatively different predictions. We test the success of this predictive model by field surveys. The sites selected by the model and respective number of random suitable sites will be visited to determine occupation. If the model turns out to be successful, we can use it as a first step toward PVA before adequate demographic data become available. Based on the model forest management recommendations can also be made and alternative management options compared.

Klamath River Chinook Population Viability with Variations in Salmon Harvest Model Parameters. ANNE MULLAN, Dept. Environmental Studies, Univ. California, Santa Cruz, CA.

The population viability under changes in freshwater and marine survival rates used in salmon harvest management models are explored. Seasons for California and Oregon chinook (Oncorhynchus tshawytscha ) fisheries are based on models which employ fixed survival rates and projected harvest mortality rates. Deterministic matrix models were employed for Klamath chinook model parameters to examine the effects on lambda of increased harvest mortality and decreased marine survival. Lambda was greater than or equal to one, increasing to 1.24 in the best case. Stochastic simulations incorporating density dependence in freshwater stages were performed with variations in key rates. Cumulative probabilities of obtaining current or lower population levels in 100 years were obtained by incorporating random environmental variation in 1000 iteration Monte Carlo simulations. For both deterministic and stochastic models, the decreases in marine survival resulted in steeper declines of the population than the scenarios with harvest rate increases. Populations at lower survival levels never return to the starting size and the possibility of declining to fifteen percent of the starting population is greater than 90%.

Formulating a Model and Choosing Experiments for the Puritan Tiger Beetle. KRISTIAN SHAWN OMLAND , Dept. Ecology & Evolutionary Biol., Univ. Connecticut, Storrs, CT.

The range of the Puritan tiger beetle (Cincindela puritana ) was tremendously reduced by human activity in the last hundred years, and the species was listed as Threatened in 1990. Stewardship of the species requires sound scientific information. Population viability analysis is a response to that need involving incremental model building and field studies. The process involves 1) assembling existing information, 2) formulating a model, 3) identifying knowledge gaps, 4) conducting field studies to fill those gaps, 5) testing the performance of the model, 6) improving the model, and ultimately 7) assessing extinction risk, and the response of that risk to alternative management actions. Steps 3-6 can be iterated cyclically, but the number of iterations before executing step 7 is constrained by time and other resources. Therefore, selection of field studies requires setting priorities. Prioritization involves intuition and feasibility constraints, but it also should be informed by model sensitivity analysis. Here I present a model for the Puritan tiger beetle that incorporates the patchiness of the species' beach habitat, its biennial life cycle, habitat- and density-dependent relations, movement of adult beetles among patches, and the possibility of local extinction. Gaps in our knowledge include: survivorship of eggs, first instar larvae, and pupae; larval microhabitat relations; the form and strength of density dependent and trophic relations; interpatch movement rates; and the frequency and consequences of catastrophic events. Among feasible studies addressing those gaps, I have assigned high priority to field studies that describe larval microhabitat relations, larval density dependent relations, and source-sink dynamics involving adult movement.

Population and Habitat Viability Assessment of the Indian Gharial. R. J. RAO, School of Studies in Zoology, Jiwaji Univ., Gwalior, India.

A Population and Habitat Viability Assessment (PHVA) focuses on the species level of the hierarchy and provides a forum to bring all required expertise together to ensure a balanced integrated approach to species conservation. A workshop on PHVA for Indian Gharial was organized in India during January 1995. This is the first such workshop on world crocodiles. In the workshop issues and concerns of gharial were discussed in a combination of small working group sessions alternating with plenary discussions. Various aspects of gharial conservation like census and distribution, habitat, population modeling, threats, trade, captive management and disease, reintroduction and education were discussed. In the past two decades about 4000 gharial have been released into 12 rivers in four states under the "Grow and Release" programs in which eggs were collected and hatched and hatchlings reared to sizes which increased the probability of their survival. While there is every indication that this program has made the species secure in certain areas, there was a conspicuous lack of information in other areas. It is recommended that the annual census be done in every area, using a more standardized methodology, and taking the help of local people and other volunteers. It was also recommended that a central coordinating unit be established which would provide a mechanism for better interaction between the different states and agencies involved in conservation activities of gharial.

Can Quasi-stationarity be Detectable in the Field? OLIVIER RENAULT, Lab. of Ecology, Univ. Pierre & Marie Curie, Paris, France, and FRANÇOIS SARRAZIN*, Lab. of Ecology, Univ. Pierre & Marie Curie, Paris, France.

Population extinction does not always follow an exponential decrease. It has been shown that due to demographic stochasticity, a population can reach, before its extinction, a plateau known as the Quasi-Stationary Phase (QSP). At this time, the population size is extremely low, while the extinction risk is maximized. The properties of such populations have already been studied theoretically. In the QSP, the instantaneous extinction probability is given by 1 - lambda, where lambda is the asymptotic growth rate of the population. Then, the population behaves like a single individual, whose survival probability is lambda. So, despite a lambda lower than 1, the population can potentially persist for a fairly long time. In the field, a quasi-stationary population shows an apparent stability. Consequently, the underlying problem for the conservationist is to differentiate a small population regulated by biodemographic processes from a quasi-stationary population. Indeed, extinction probabilities strongly differ in both situations, and management possibilities are divergent as well. In order to investigate this question, we used the software ULM. We constructed an age-structured model accounting for demographic stochasticity. Considering only trajectories presenting a QSP, we regenerated capture-recapture histories to estimate survival rates with MARK software. In the same way, we estimated mean fecundity rates. We then compared these estimates with the ones that had been put into the model. We also compared the value of lambda computed from the estimated parameters. Globally, the results showed a trend to overestimate demographic parameters, leading to a possible underestimate of extinction probabilities.

The PATCH Model: Linking Population Viability Analysis to Landscape Change. NATHAN H. SCHUMAKER, U.S. Environmental Protection Agency, Corvallis, OR.

PVA models are frequently criticized as either unrealistic or overly complex. Practitioners of PVA often insist that models be spatially explicit, thus permitting direct examination of the consequences of management actions. And demands for realism dictate that models be stochastic and provide a variety of inputs and outputs. Not surprisingly, the result has been a trend towards complicated models that defy parameterization or validation. The PATCH model was designed specifically to counter this trend. PATCH is a parsimonious individually-based, spatially explicit, life history simulator that links population viability analysis and landscape change. PATCH's life history simulations are conducted within digital habitat maps, and these maps can change as the model runs. PATCH produces a range of analyses depending on data quality and availability. Users can quantify landscape pattern, study the partitioning of landscapes into arrays of breeding sites, perform source-sink analyses, study dispersal success and failure, and conduct sophisticated demographic simulations. PATCH's pattern analysis module facilitates the identification of habitat-based indicators of landscape quality. PATCH's life history simulator is based on a population projection matrix and it incorporates demographic and environmental stochasticity. The model produces an array of both tabular and map-based outputs that will be useful to many population and conservation biologists. PATCH is animated, and it can easily perform simulations on entire states or multi-state regions. The PATCH model and manual were completed in September 1988, and are available (along with sample habitat maps) free of charge.

Rethinking Rare Plant Monitoring with Mark-Recapture Analysis: The Case of a Midwestern Orchid. RICHARD P. SHEFFERSON, Dept. Environmental Science, Policy, & Management, Univ. California, Berkeley, CA.

I applied mark-recapture statistics in a 4-yr study of a rare, perennial plant, the small yellow lady’s slipper (Cypripedium calceolus var. parviflorum (Salisb.) Fernald). I evaluated the use of this method to separate adult dormancy from mortality. Apparent survival (phi) and reshooting rates (p) were calculated and compared to conventional aboveground persistence rates that did not account for adult dormancy. Further analyses were performed to determine whether microclimatic covariates and management histories could account for trends in apparent survival and reshooting rates. A final analysis examined whether the exclusion of unidentifiable orchids leads to significant effects on apparent survival and reshooting rate. Results indicated that aboveground persistence rates underestimated apparent survival rates by 0 42.9% (mean = 20.0%). Microclimatic covariates accounted for variation in apparent survival and reshooting rate, but management histories accounted for little variation. The exclusion of unidentifiable orchids from analyses can lead to significant impacts on apparent survival and reshooting rate. This technique worked well to describe trends in demographic parameters and to suggest possible cause-and-effect relationships for future experimentation.

Applying Individual Based Modeling to Explore the Effects of Changing Ecological Parameters on the Population Dynamics of the Endangered Largest Malagasy Rodent (Hypogeomys antimena, Nesomyinae). SIMONE SOMMER*, Institute of Zoology, Ecology & Conservation, Univ. Hamburg, Germany, and UDO HOMMEN, Ecological Modelling & Statistics, Alsdorf, Germany.

The geographic range of the largest endemic rodent of Madagascar, Hypogeomys antimena, was recently restricted to less than 20 x 40 km of dry deciduous forest at the western coast of Madagascar. Continuous field studies since 1992 indicate that H. antimena lives in obligate monogamy. A male and a female defend an exclusive territory throughout the year. The reproduction is very low (1-2 offspring/couple/year). Male offspring disperse earlier than female offspring which stay together with their parents for one more reproductive period. Adult and offspring mortality rates were mainly depending on the predation impact by two top predator species. The population size in the 100 ha study area was constant until 1996 (55 animals/100ha), however it declined about 40% in 1997 and 1998. We designed an individual based simulation model to explore the effects of changing reproductive rates, offspring- and adult mortality and habitat size on the population size and persistence of H. antimena. Further habitat fragmentation and degradation might change these parameters. Simulations showed that the population can persist for the next 100 years with high probability at the given ecological conditions. However, slight changes in each single factor will increase the extinction risk of local populations considerably. Thus, the maintenance of habitat connectivity is important to reduce the risk of extinction of H. antimena.

The Sensitivity of a Simple Spatial Population Model to Different Representations of Dispersal Behavior. ANDY B. SOUTH*, CLUWRR, Univ. Newcastle upon Tyne, UK, STEVE P. RUSHTON, CLUWRR, Univ. Newcastle upon Tyne, UK

The incorporation of spatial structure into population models has become increasingly common and is an important component of a number of published Population Viability Analyses. Recently, concern has been expressed at the lack of data and understanding upon which these models are based. Dispersal, the process that links spatially separated habitat patches, has been highlighted as an area in which there is a particular paucity of knowledge. Published population models have represented dispersal in a wide range of ways. Dispersal can be classified into 3 phases: leaving, movement and arrival, and models including dispersal can differ in the way that each phase is represented. There have been few attempts to look at the effect of alternative representations of dispersal on the same model. We use a simple, spatially explicit population model to investigate how different representations of dispersal behavior can effect model predictions. We consider this in the context of uncertainty in quantitative parameter values relating to both within patch demography and between patch dispersal. We use the results to investigate methods of summarizing the effect on model predictions of uncertainty in the representation of dispersal behavior. T he methods presented here provide a means of assessing the regions of parameter space for which differences in the representation of dispersal are likely to have a large impact on population model predictions.

Leopard Frogs in Southwestern U.S.A.: Insights into Conservation and Reconstruction of Historical Dynamics. MICHAEL J. SREDL*, Arizona Game and Fish Dept., Phoenix, AZ, and LINDA J. ALLISON, Arizona Game and Fish Dept., Phoenix, AZ.

Along with populations of amphibians worldwide, Arizona leopard frog populations have declined. During these declines, earthen cattle tanks and other small wetland systems have become important habitats. One of us (MJS) has been developing a local approach to conservation of remaining populations. To accommodate these changes in landscape and population structure, local conservation zones could be enhanced by increasing the number of small wetland populations or renovating existing sites to create larger core populations. These approaches can be examined using PVA models; however, these models are not often used to examine amphibian populations. We used VORTEX, equating metamorphosis with birth, to gain insight into changes in population structure as populations have become fragmented. In addition, we used model populations to gain insight into reserve design that would stabilize populations and perhaps mimic historical demographic and genetic structure. We used data from our (MJS) field studies and from literature on related frogs to build four types of model populations. Our first model population, mimicking very large populations in large river systems, was stable over a 20-year period and had very high heterozygosity. Our second population, modeling addition of cattle tanks near riverine habitats did not differ significantly in behavior. Not surprisingly, loss of large river core populations and dependence strictly on cattle tank habitats resulted in increased chance of extinction and loss of heterozygosity. This situation was improved most by enlarging one cattle tank population, but not by adding small cattle tank populations. With the addition of a larger core population, the resulting population fluctuations decreased and heterozygosity increased. Stability and genetic variability did not mimic that of modeled historical populations.

The Influence of Different Habitat Quality Zones on the Survival of the Northern Shrike. THOMAS STEPHAN*, Dept. of Ecological Modelling, Centre for Environmental Research, Leipzig, Germany, and GERHARD ROTHHAUPT, Dept. of Zoology, Univ. Goettingen, Goettingen, Germany.

Population sizes of northern shrike (Lanius excubitor) in Germany have decreased in recent years, due to habitat fragmentation and destruction. This study uses own field observations (data from 1990-1995, district of Neustadt/Aisch, Bavaria) as a basis for stochastic simulations of the population dynamics. We include the influence of environmental fluctuations on survival and reproduction. Additionally, we take into account that reproduction is mainly determined by the quality of habitats. Data about breeding success from 1990-1995 allow us to distinguish between three different habitat quality stages (4 optimal, 24 suboptimal, 38 marginal habitats). The whole variety of simulations—particularly as different scenarios for environmental fluctuations are tested—shows an overwhelming influence of the optimal habitats. Taking a standard parameter set, the extinction probability within the next 100 years equals approximately 10%. Removal of two optimal habitats has about the same effect as the removal of twelve suboptimal habitats—extinction probability increases up to approximately 25%. Removal of marginal habitats does not have any significant effect on extinction probabilities. The importance of differences in habitat quality is underlined by the fact that neglecting these differences results in a substantial overestimation of the extinction risk. A similar model with average reproduction in only one habitat quality zone leads to an extinction risk of 90% after 100 years for the standard parameter set. The presence of optimal habitats acts as an insurance against such high extinction risks—conservation efforts should focus on preserving them.

Population Projections for the Endangered Southwestern Willow Flycatcher: Uncertain Inference from Incomplete Data. SCOTT H. STOLESON*, Rocky Mountain Research Station, Albuquerque, NM, MARY J. WHITFIELD, Kern River Preserve, Weldon, CA, MARK K. SOGGE, USGS Forest and Rangeland Ecosystem Science Center, Colorado Plateau Field Station, Flagstaff, AZ, and WILLIAM E. HAAS, Varanus Biological Services, San Diego, CA.

Currently about 500 pairs of the Southwestern Willow Flycatcher (Empidonax traillii extimus) occur in about 100 remnant patches of dense riparian habitat in the Southwest. We report on the results and limitations of a simple population model for the flycatcher. Because data on vital rates exist for very few subpopulations, we lacked adequate knowledge of variance in rates or what rates might be considered typical. Also it was unclear whether subpopulations are discrete, comprise a metapopulation, or are simply parts of a fragmented single population. Therefore we constructed a simple stage-based deterministic model for a hypothetical population of 100 pairs under three scenarios: (1) an optimistic scenario using the maximum productivity and survivorship estimates available from current studies; (2) a conservative scenario using minimum estimates; and (3) an intermediate scenario using the means of optimistic and conservative estimates. Population trajectories varied from exponential growth to rapid extinction. An elasticity analysis indicated that the relative effects of different demographic parameters on population growth rate varied among the three scenarios. Thus, we could not identify a particular critical parameter for management focus. It is likely that a spatial component is needed to understand of population dynamics in the Willow Flycatcher. For example, a rescue effect would mitigate against tendencies towards rapid extinction and more accurately reflect the continued persistence of subpopulations with low fecundity in real life. Ongoing recovery efforts are exploring more advanced modeling techniques including metapopulation analysis, spatially explicit models and incidence functions.

Viability Analysis of Endangered Gulf Coast Beach Mice Populations. MICHAEL C. WOOTEN*, Dept. of Zoology, Auburn Univ., Auburn AL, MADAN OLI, Dept. of Zoology, Auburn Univ., Auburn AL, and NICHOLAS R. HOLLER, AL Cooperative Fish and Wildlife Research Unit, USGS, Auburn University, Auburn AL.

Endangered Alabama (Peromyscus polionotus ammobates) and Perdido Key (P. p. trissyllepsis) beach mice occur in isolated populations along the Gulf Coast of Alabama and Florida. Ongoing development continues to reduce habitat, exacerbating the already precarious existence of these mice. We conducted population viability analyses, through demographic modeling, for two populations of Alabama beach mice and two populations of Perdido Key beach mice, using data collected during 7-8 years of study. In the absence of catastrophic events, the probability that the populations would decline to one mouse ranged from 0.002 for the population of Alabama beach mice at the Perdue unit of Bon Secour National Wildlife Refuge (BSPU) to 1.00 for the Perdido Key beach mouse population at Gulf Island National Seashore. Modal time to extinction, for paths reaching extinction, ranged from 5 to 21 years. When the BSPU data set was extended to include data collected following Hurricane Opal, the probability of extinction increased to 0.479. If catastrophic events, which are frequent in the Gulf Coast habitats, are considered, virtually all populations of beach mice appear in substantial danger of extinction, unless the current trend in habitat destruction and fragmentation is reversed.

The Good and Bad of Conservation Without Population Viability Analysis: The Case of a Well Studied Insect, the Bay Checkerspot Butterfly. DAVID H. WRIGHT, Endangered Species Division, U.S. Fish and Wildlife Service, Sacramento, CA.

The bay checkerspot butterfly (Euphydryas editha bayensis) may be the world's most studied wild, non-pest insect; certainly it is the most studied endangered invertebrate. Yet a PVA for this taxon, listed since 1987, is still remote. Aspects of the butterfly's biology that would go into many PVAs but are incompletely known include long-distance dispersal, intraspecific interactions, and variances in some demographic rates and their relation to environment. Factors uncommonly incorporated into PVAs such as grazing management, anthropogenically induced climate change, and nitrogen deposition may also affect the butterfly's chances of survival. I prepared the 1997 USFWS draft recovery plan for the bay checkerspot, a plan that builds on many tenets of modern conservation biology as well as on the voluminous published and gray literature on the subspecies, but that lacks a PVA. Proceeding with conservation efforts in the absence of a PVA will be practical necessity for most rare species, so that existing threats to their survival can be immediately addressed. PVAs may also lend a false sense of understanding or controlling a species' future. In their favor, PVAs allow objective evaluation of the relative impacts of alternative scenarios on population trends, and may provide useful insight or guidance for management, research, or policy. In many cases, research to support a PVA could be approached stepwise, incrementally providing biological information useful to ongoing conservation management before a PVA is possible.