Accuracy of Short‐Term Demographic Data in Projecting Long‐Term Fate of Populations

Short‐term surveys are useful in conservation of species if they can be used to reliably predict the long‐term fate of populations. However, statistical evaluations of reliability are rare. We studied how well short‐term demographic data (1999–2002) of tartar catchfly (Silene tatarica), a perennial riparian plant, projected the fate and growth of 23 populations of this species up to the year 2010. Surveyed populations occurred along a river with natural flood dynamics and along a regulated river. Riparian plant populations are affected by flooding, which maintains unvegetated shores, while forest succession proceeds in areas with little flooding. Flooding is less severe along the regulated river, and vegetation overgrowth reduces abundance of tartar catchfly on unvegetated shores. We built matrix models to calculate population growth rates and estimated times to population extinction in natural and in regulated rivers, 13 and 10 populations, respectively. Models predicted population survival well (model predictions matched observed survival in 91% of populations) and accurately predicted abundance increases and decreases in 65% of populations. The observed and projected population growth rates differed significantly in all but 3 populations. In most cases, the model overestimated population growth. Model predictions did not improve when data from more years were used (1999–2006). In the regulated river, the poorest model predictions occurred in areas where cover of other plant species changed the fastest. Although vegetation cover increased in most populations, it decreased in 4 populations along the natural river. Our results highlight the need to combine disturbance and succession dynamics in demographic models and the importance of habitat management for species survival along regulated rivers. Precisión de Datos Demográficos de Corto Plazo en la Proyección del Destino de Poblaciones a Largo Plazo     

Moss species benefits from breakdown of cyclic rodent dynamics in boreal forests

Bryophytes have increased in abundance in northern regions, and climate changes have been proposed to account for this change. However, changes in the population dynamics of microtine rodents may also contribute to changes in bryophyte abundance. New evidence indicates a tendency for microtine rodent population oscillations to change from periodicity of 3-5 years to become irregular or acyclic. The impact on ecosystem functioning is potentially great. We study the impact of variation in microtine rodent population characteristics, such as cycle length and amplitude, on the population dynamics of the boreal, clonal moss Hylocomium splendens. We use experimental and observational demographic data to construct 127 scenarios representing all combinations of disturbance type (gap formation and/or clipping), period (cyclic with 4, 6, 12, or 24 years between rodent peaks; or acyclic with constant or stochastically varying annual disturbance severity) and disturbance severity (fraction of individuals affected by disturbance in each year relative to the maximum disturbance carried out in the field experiment; seven levels). Population data collected in the field during 13 years were used as a baseline scenario. By subjecting all scenarios to stochastic matrix modeling, we demonstrate considerable impact of microtine rodent on the population dynamics of H. splendens, most notably when rodent populations fluctuate with short periods and high peak disturbance severities. Under the same average disturbance severity, H. splendens population growth rates are highest in acyclic scenarios and are progressively reduced with increasing peak disturbance severities (i.e., with increasing period). Stochastic elasticity analyses show that in less variable environments mature segment survival contributes more to the population growth rate, while in more variable environments the regeneration pathway (branching of older parts of the plant) plays a stronger role, inevitably leading to lower population fitness. Our results support the hypothesis that breakdown of cyclic rodent population dynamics accentuates increase in the abundance of H. splendens and other large bryophytes in boreal forests in Norway, observed empirically in recent years and primarily ascribed to climatic change.     

The effect of summer drought on the predictability of local extinctions in a butterfly metapopulation

The ecological impacts of extreme climatic events on population dynamics and community composition are profound and predominantly negative. Using extensive data of an ecological model system, we tested whether predictions from ecological models remain robust when environmental conditions are outside the bounds of observation. We observed a 10-fold demographic decline of the Glanville fritillary butterfly (Melitaea cinxia) metapopulation on the Åland islands, Finland in the summer of 2018 and used climatic and satellite data to demonstrate that this year was an anomaly with low climatic water balance values and low vegetation productivity indices across Åland. Population growth rates were strongly associated with spatiotemporal variation in climatic water balance. Covariates shown previously to affect the extinction probability of local populations in this metapopulation were less informative when populations were exposed to severe drought during the summer months. Our results highlight the unpredictable responses of natural populations to extreme climatic events.     

A Behaviorally Explicit Demographic Model Integrating Habitat Selection and Population Dynamics in California Sea Lions

Abstract: Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral‐based PVA approaches require detailed individual‐based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage‐structured matrix model that includes the costs and benefits of movement associated with 2 habitat‐selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.     

Demographic Characteristics of Extinction in a Small, Insular Population of House Sparrows in Northern Norway

Abstract:  In conservation ecology there is an urgent need for indicators that can be used to predict the risk of extinction of populations. Identifying extinction-prone populations has been difficult because few data sets on the demographic characteristics of the final stage to extinction are available and because of problems in separating out stochastic effects from changes in the expected dynamics. We documented the demographic changes that occurred during the period prior to extinction of a small island population of House Sparrows ( Passer domesticus ) after the end of permanent human settlement. A mark-recapture analysis revealed that this decline to extinction was mainly due to increased mortality after closure of the last farm that resulted in a negative long-term-specific growth rate. No change occurred in either the structural composition (breeding sex ratio and age distribution) of the population or in female recruitment. No male, however, recruits were produced on the island after the farm closure. Based on a simple, stochastic, density-dependent model we constructed a population prediction interval (PPI) to estimate the time to extinction. The 95% PPI slightly overestimated the time to extinction with large uncertainty in predictions, especially due to the influence of demographic stochasticity and parameter drift. Our results strongly emphasize the importance of access to data on temporal variation that can be used to parameterize simple population models that allow estimation of critical parameters for credible prediction of time to extinction.     

Factors Leading to Different Viability Predictions for a Grizzly Bear Data Set

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear ( Ursus arctos horribilis ) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.     

Demographic Viability of a Relict Population of the Critically Endangered Plant Borderea chouardii

Abstract:   In addition to human-caused changes in the environment, natural stochasticity may threaten species persistence, and its impact must be taken into account when priorities are established and management plans are designed. Borderea chouardii is a Tertiary relict at risk of extinction that occurs in only one location in the world, where the probability of human disturbance is low. Its persistence, therefore, is mainly linked to its response to natural threats such as stochasticity. Over 8 years I monitored up to 25% of this rupicolous small geophyte. The population had an unbalanced size structure and 90% failure in seed arrival at appropriate microhabitats, which suggests a problem with recruitment. I used matrix models to describe its population dynamics, conducted hand sowings, and performed stochastic simulations to investigate the effect of environmental stochasticity on population trend and viability. I modeled several scenarios to represent a variety of ecological situations, such as population reduction, episodic or persistent disease, and enhancement or decrease of recruitment. Population growth rate (λ) was never significantly different from unity over the study period. The risk of extinction was null over the next five centuries under current conditions. Increase of mortality and decrease of recruitment reduced stochastic population growth rate, but no factor except a persistent increase of 10% mortality resulted in extinction. These results are the consequence of the plant's extremely long life span (over 300 years) and low temporal variability of key vital rates. Even though hand sowing significantly increased the stochastic population growth rate, other approaches may be more important for the persistence of this species. The extremely slow capacity for recovery following disturbances renders habitat preservation essential. In addition, the founding of new populations would reduce the risk associated with habitat destruction.     

Regional Consequences of Local Population Demography and Genetics in Relation to Habitat Management in Gentiana pneumonanthe

Abstract:  A joint demographic and population genetics stage-based model for a subdivided population was applied to Gentiana pneumonanthe , an early successional perennial herb, at a regional (metapopulation) scale. We used numerical simulations to determine the optimal frequency of habitat disturbance (sod cutting) and the intensity of gene flow among populations of G. pneumonanthe to manage both population viability and genetic diversity in this species. The simulations showed that even small populations that initially had near-equal allele frequencies could, if managed properly through sod cutting every 6 to 7 years, sustain their high genetic variation over the long run without gene flow. The more the allele frequencies in the small populations are skewed, however, the higher the probability that in the absence of gene flow, some alleles will be lost and within-population genetic variation will decrease even under proper management. This implies that although local population dynamics should be the major target for management, regional dynamics become important when habitat fragmentation and decreased population size lead to the loss of local genetic diversity. The recommended strategy to improve genetic composition of small populations is the introduction of seeds or seedlings of nonlocal origin.     

Integral projection models for finite populations in a stochastic environment

Continuous types of population structure occur when continuous variables such as body size or habitat quality affect the vital parameters of individuals. These structures can give rise to complex population dynamics and interact with environmental conditions. Here we present a model for continuously structured populations with finite size, including both demographic and environmental stochasticity in the dynamics. Using recent methods developed for discrete age-structured models we derive the demographic and environmental variance of the population growth as functions of a continuous state variable. These two parameters, together with the expected population growth rate, are used to define a one-dimensional diffusion approximation of the population dynamics. Thus, a substantial reduction in complexity is achieved as the dynamics of the complex structured model can be described by only three population parameters. We provide methods for numerical calculation of the model parameters and demonstrate the accuracy of the diffusion approximation by computer simulation of specific examples. The general modeling framework makes it possible to analyze and predict future dynamics and extinction risk of populations with various types of structure, and to explore consequences of changes in demography caused by, e.g., climate change or different management decisions. Our results are especially relevant for small populations that are often of conservation concern.     

Reconstructing the historic demography of an endangered seabird

Reducing extinction risk for threatened species requires determining which demographic parameters are depressed and causing population declines. Museum collections may constitute a unique, underutilized resource for measuring demographic changes over long time periods using age-ratio analysis. We reconstruct the historic demography of a U.S. federally endangered seabird, the Marbled Murrelet (Brachyramphus marmoratus), from specimens collected approximately 100 years ago for comparison with predictions from comparative analyses and with results from contemporary field studies using both age-ratio analysis and conventional demographic estimators. Reproduction in the late 1800s and early 1900s matched predictions from comparative analysis, but was 8-9 times greater than contemporary estimates, whereas adult survival was unchanged. Historic reproductive rates would support stable populations, but contemporary levels should result in population declines. Contemporary demographic estimates derived from age-ratio analysis were similar to estimates from conventional estimators. Using museum specimens to reconstruct historic demography provides a unique approach to identify causes of decline and to set demographic benchmarks for recovery of endangered species that meet most assumptions of age-ratio analysis.     

Life history and viability of a long-lived marine invertebrate: the octocoral Paramuricea clavata

The red gorgonian Paramuricea clavata is a long-lived, slow-growing sessile invertebrate of ecological and conservation importance in the northwestern Mediterranean Sea. We develop a series of size-based matrix models for two Paramuricea clavata populations. These models were used to estimate basic life history traits for this species and to evaluate the viability of the red gorgonian populations we studied. As for many other slow-growing species, sensitivity and elasticity analysis demonstrate that gorgonian population growth is far more sensitive to changes in survival rates than to growth, shrinkage, or reproductive rates. The slow growth and low mortality of red gorgonians results in low damping ratios, indicating slow convergence to stable size structures (at least 50 years). The stable distributions predicted by the model did not differ from the observed ones. However, our simulations point out the fragility of this species, showing both populations in decline and high risk of extinction over moderate time horizons. These declines appear to be related to a recent increase in anthropogenic disturbances. Relative to their life span, the values of recruitment elasticity for Paramuricea clavata are lower than those reported for other marine organisms but are similar to those reported for some long-lived plants. These values and the delayed age of sexual maturity, in combination with the longevity of the species, show a clear fecundity/mortality trade-off. Full demographic studies of sessile marine species are quite scarce but can provide insight into population dynamics and life history patterns for these difficult and under-studied species. While our work shows clear results for the red gorgonian, the variability in some of our estimates suggest that future work should include data collection over longer temporal and spatial scales to better understand the long-term effects of natural and anthropogenic disturbances on red gorgonian populations.     

The triple helix of Plantago lanceolata: genetics and the environment interact to determine population dynamics

The theory of evolution via natural selection predicts that the genetic composition of wild populations changes over time in response to the environment. Different genotypes should exhibit different demographic patterns, but genetic variation in demography is often impossible to separate from environmental variation. Here, we asked if genetic variation is important in determining demographic patterns. We answer this question using a long-term field experiment combined with general linear modeling of deterministic population growth rates (lambda), deterministic life table response experiment (LTRE) analysis, and stochastic simulation of demography by paternal lineage in a short-lived perennial plant, Plantago lanceolata, in which we replicated genotypes across four cohorts using a standard breeding design. General linear modeling showed that growth rate varied significantly with year, spatial block, and sire. In LTRE analysis of all cohorts, the strongest influences on growth rate were from year x spatial block, and cohort x year x spatial block interactions. In analysis of genetics vs. temporal environmental variation, the strongest impacts on growth rate were from year and year x sire. Finally, stochastic simulation suggested different genetic composition among cohorts after 100 years, and different population growth rates when genetic differences were accounted for than when they were not. We argue that genetic variation, genotype x environment interactions, natural selection, and cohort effects should be better integrated into population ecological studies, as these processes should result in deviations from projected deterministic and stochastic population parameters.     

Genetic and demographic consequences of importing animals into a small population: a simulation model of the Texas State Bison Herd (USA)

The extant 40 bison (Bison bison) constituting the Texas State Bison Herd (TSBH; USA) are directly and exclusively descended from a bison herd assembled by Charles Goodnight in the 1880s, representing a historically and genetically valuable resource. The population currently suffers from low genetic variation, low heterozygosity, high calf mortality, and low natality rates compared with other closed bison populations. Population viability analysis using the VORTEX program previously indicated a 99% chance of population extinction within the next 41 years [J. Mamm. 85 (2004) in press]. We developed a stochastic simulation model to evaluate the genetic and demographic consequences of various management scenarios for the TSBH using genotypic data from 51 microsatellite loci and demographic information recorded over a 6-year period. Our results reveal that without the introduction of new genetic variation, approximately 37% of the representative microsatellite loci will become fixed as the TSBH continues to lose genetic variation at a staggering rate of 30–40% within the next 50 years. Furthermore, if the current trends in natality and mortality rates continue, our model indicates the TSBH faces a 99% chance of extinction in the next 51 years. With the importation of unrelated male bison into the TSBH, and under the assumption of increased fitness, the probability of population survival in the next 100 years increases to 100%, and the population will reach the approximate carrying capacity of 200 bison in 15–16 years. Furthermore, our model predicts increases in genetic diversity and heterozygosity of 24.7–48.4% and 17.5–36.5%, respectively, in the next 100 years following the addition of new genetic variation. We conclude that the importation of bison into the TSBH is necessary to prevent extinction and ensure long-term population survival.     

Developing Metapopulation Connectivity Criteria from Genetic and Habitat Data to Recover the Endangered Mexican Wolf

Restoring connectivity between fragmented populations is an important tool for alleviating genetic threats to endangered species. Yet recovery plans typically lack quantitative criteria for ensuring such population connectivity. We demonstrate how models that integrate habitat, genetic, and demographic data can be used to develop connectivity criteria for the endangered Mexican wolf (Canis lupus baileyi), which is currently being restored to the wild from a captive population descended from 7 founders. We used population viability analysis that incorporated pedigree data to evaluate the relation between connectivity and persistence for a restored Mexican wolf metapopulation of 3 populations of equal size. Decreasing dispersal rates greatly increased extinction risk for small populations (<150–200), especially as dispersal rates dropped below 0.5 genetically effective migrants per generation. We compared observed migration rates in the Northern Rocky Mountains (NRM) wolf metapopulation to 2 habitat‐based effective distance metrics, least‐cost and resistance distance. We then used effective distance between potential primary core populations in a restored Mexican wolf metapopulation to evaluate potential dispersal rates. Although potential connectivity was lower in the Mexican wolf versus the NRM wolf metapopulation, a connectivity rate of >0.5 genetically effective migrants per generation may be achievable via natural dispersal under current landscape conditions. When sufficient data are available, these methods allow planners to move beyond general aspirational connectivity goals or rules of thumb to develop objective and measurable connectivity criteria that more effectively support species recovery. The shift from simple connectivity rules of thumb to species‐specific analyses parallels the previous shift from general minimum‐viable‐population thresholds to detailed viability modeling in endangered species recovery planning. Desarrollo de Criterios de Conectividad Metapoblacional a Partir de Datos Genéticos y de Hábitat para Recuperar al Lobo Mexicano en Peligro de Extinción     

Demography of central and marginal populations of monkeyflowers (Mimulus cardinalis and M. lewisii)

Every species occupies a limited geographic area, but how spatiotemporal environmental variation affects individual and population fitness to create range limits is not well understood. Because range boundaries arise where, on average, populations are more likely to go extinct than to persist, range limits are an inherently population-level problem for which a demographic framework is useful. In this study, I compare demographic parameters and population dynamics between central and marginal populations of monkeyflowers, Mimulus cardinalis and M. lewisii, along an elevation gradient spanning both species' ranges. Central and marginal populations of both species differed in survival and fecundity. For M. lewisii, these components of fitness were higher in central than in marginal populations, but for M. cardinalis the converse was true. To assess spatiotemporal variation in population dynamics, I used transition matrix models to estimate asymptotic population growth rates (lambda) and found that population growth rates of M. lewisii were highest at the range center and reduced at the range margin. Population growth rates of M. cardinalis were highest at the range margin and greatly reduced at the range center. Life table response analysis decomposed spatiotemporal variation in lambda into contributions from each transition between life stages, finding that transitions from large nonreproductive and reproductive plants to the seed class and stasis in the reproductive class made the largest contributions to spatial differences in lambda. These transitions had only low to moderate sensitivities, indicating that differences in projected population growth rates resulted mainly from observed differences in transition matrix parameters and their underlying vital rates.     

Using demography and movement behavior to predict range expansion of the southern sea otter

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989-2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.     

Small Populations and Offspring Sex-Ratio Deviations in Eagles

Abstract:  Stochastic variation of sex ratio has long been appreciated as a potential factor driving small populations to extinction, but it is not the only source of sex-ratio bias in small populations. We examined whether some consequences of sex allocation could affect extinction risk in small populations of size-dimorphic birds such as eagles. We report variations in sex ratio at fledging from a long-term study of a declining population of Spanish Imperial Eagles ( Aquila adalberti ). Nestling sex-ratio deviation apparently was mediated by age of breeders, whereas territory quality had no obvious effect. Adult–adult pairs produced the same proportion of both sexes in high- or low-density situations, but pairs with at least one member in nonadult plumage class produced more males. As the population declined over a period of years, the proportion of breeders with immature plumage increased; consequently, the proportion of fledgling males increased. However, when population density was high, the proportion of breeders with immature plumage decreased and more female offspring were produced. This relationship between population density, composition of breeder age, and fledgling sex ratios allowed us to make predictions of extinction risk due to nonstochastic deviations of sex ratio in small, declining populations. In the study population, on the basis of the Vortex simulation results, an estimated reduction of 42.5% in predicted mean time to extinction was attributed solely to biased sex ratio.     

Demographic heterogeneity, cohort selection, and population growth

Demographic heterogeneity--variation among individuals in survival and reproduction--is ubiquitous in natural populations. Structured population models address heterogeneity due to age, size, or major developmental stages. However, other important sources of demographic heterogeneity, such as genetic variation, spatial heterogeneity in the environment, maternal effects, and differential exposure to stressors, are often not easily measured and hence are modeled as stochasticity. Recent research has elucidated the role of demographic heterogeneity in changing the magnitude of demographic stochasticity in small populations. Here we demonstrate a previously unrecognized effect: heterogeneous survival in long-lived species can increase the long-term growth rate in populations of any size. We illustrate this result using simple models in which each individual's annual survival rate is independent of age but survival may differ among individuals within a cohort. Similar models, but with nonoverlapping generations, have been extensively studied by demographers, who showed that, because the more "frail" individuals are more likely to die at a young age, the average survival rate of the cohort increases with age. Within ecology and evolution, this phenomenon of "cohort selection" is increasingly appreciated as a confounding factor in studies of senescence. We show that, when placed in a population model with overlapping generations, this heterogeneity also causes the asymptotic population growth rate lambda to increase, relative to a homogeneous population with the same mean survival rate at birth. The increase occurs because, even integrating over all the cohorts in the population, the population becomes increasingly dominated by the more robust individuals. The growth rate increases monotonically with the variance in survival rates, and the effect can be substantial, easily doubling the growth rate of slow-growing populations. Correlations between parent and offspring phenotype change the magnitude of the increase in lambda, but the increase occurs even for negative parent-offspring correlations. The effect of heterogeneity in reproductive rate on lambda is quite different: growth rate increases with reproductive heterogeneity for positive parent-offspring correlation but decreases for negative parent-offspring correlation. These effects of demographic heterogeneity on lambda have important implications for population dynamics, population viability analysis, and evolution.     

The Impact of Increased Environmental Stochasticity Due to Climate Change on the Dynamics of Asiatic Wild Ass

Abstract:  Theory proposes that increased environmental stochasticity negatively impacts population viability. Thus, in addition to the directional changes predicted for weather parameters under global climate change (GCC), the increase in variance of these parameters may also have a negative effect on biodiversity. As a case study, we assessed the impact of interannual variance in precipitation on the viability of an Asiatic wild ass ( Equus hemionus ) population reintroduced in Makhtesh Ramon Nature Reserve, Israel. We monitored the population from 1985 to 1999 to determine what environmental factors affect reproductive success. Annual precipitation during the year before conception, drought conditions during gestation, and population size determined reproductive success. We used the parameters derived from this model to assess population performance under various scenarios in a Leslie matrix type model with demographic and environmental stochasticity. Specifically, we used a change in the precipitation regime in our study area to formulate a GCC scenario and compared the simulated dynamics of the population with a no-change scenario. The coefficient of variation in population size under the global change scenario was 30% higher than under the no-change scenario. Minor die-offs (≥15%) following droughts increased extinction probability nearly 10-fold. Our results support the idea that an increase in environmental stochasticity due to GCC may, in itself, pose a significant threat to biodiversity.     

The Influence of Model Structure on Conclusions about the Viability and Harvesting of Serengeti Wildebeest

We investigate how the viability and harvestability predicted by population models are affected by details of model construction. Based on this analysis we discuss some of the pitfalls associated with the use of classical statistical techniques for resolving the uncertainties associated with modeling population dynamics. The management of the Serengeti wildebeest (Connochaetes taurinus) is used as a case study. We fitted a collection of age-structured and unstructured models to a common set of available data and compared model predictions in terms of wildebeest viability and harvest. Models that depicted demographic processes in strikingly different ways fitted the data equally well. However, upon further analysis it became clear that models that fit the data equally well could nonetheless have very different management implications. In general, model structure had a much larger effect on viability analysis (e.g., time to collapse) than on optimal harvest analysis (e.g., harvest rate that maximizes harvest). Some modeling decisions, such as including age-dependent fertility rates, did not affect management predictions, but others had a strong effect (e.g., choice of model structure). Because several suitable models of comparable complexity fitted the data equally well, traditional model selection methods based on the parsimony principle were not practical for judging the value of alternative models. Our results stress the need to implement analytical frameworks for population management that explicitly consider the uncertainty about the behavior of natural systems.