Predicting [corrected] extinction risk in spite of predator-prey oscillations.

Most population viability analyses (PVA) assume that the effects of species interactions are subsumed by population-level parameters. We examine how robust five commonly used PVA models are to violations of this assumption. We develop a stochastic, stage-structured predator-prey model and simulate prey population vital rates and abundance. We then use simulated data to parameterize and estimate risk for three demographic models (static projection matrix, stochastic projection matrix, stochastic vital rate matrix) and two time series models (diffusion approximation [DA], corrupted diffusion approximation [CDA]). Model bias is measured as the absolute deviation between estimated and observed quasi-extinction risk. Our results highlight three generalities about the application of single-species models to multi-species conservation problems. First, our collective model results suggest that most single-species PVA models overestimate extinction risk when species interactions cause periodic variation in abundance. Second, the DA model produces the most (conservatively) biased risk forecasts. Finally, the CDA model is the most robust PVA to population cycles caused by species interactions. CDA models produce virtually unbiased and relatively precise risk estimates even when populations cycle strongly. High performance of simple time series models like the CDA owes to their ability to effectively partition stochastic and deterministic sources of variation in population abundance.     

Stochastic population dynamics in populations of western terrestrial garter snakes with divergent life histories

Comparative evaluations of population dynamics in species with temporal and spatial variation in life-history traits are rare because they require long-term demographic time series from multiple populations. We present such an analysis using demographic data collected during the interval 1978-1996 for six populations of western terrestrial garter snakes (Thamnophis elegans) from two evolutionarily divergent ecotypes. Three replicate populations from a slow-living ecotype, found in mountain meadows of northeastern California, were characterized by individuals that develop slowly, mature late, reproduce infrequently with small reproductive effort, and live longer than individuals of three populations of a fast-living ecotype found at lakeshore locales. We constructed matrix population models for each of the populations based on 8-13 years of data per population and analyzed both deterministic dynamics based on mean annual vital rates and stochastic dynamics incorporating annual variation in vital rates. (1) Contributions of highly variable vital rates to fitness (lambda(s)) were buffered against the negative effects of stochastic variation, and this relationship was consistent with differences between the meadow (M-slow) and lakeshore (L-fast) ecotypes. (2) Annual variation in the proportion of gravid females had the greatest negative effect among all vital rates on lambda(s). The magnitude of variation in the proportion of gravid females and its effect on lambda(s) was greater in M-slow than L-fast populations. (3) Variation in the proportion of gravid females, in turn, depended on annual variation in prey availability, and its effect on lambda(s) was 4 23 times greater in M-slow than L-fast populations. In addition to differences in stochastic dynamics between ecotypes, we also found higher mean mortality rates across all age classes in the L-fast populations. Our results suggest that both deterministic and stochastic selective forces have affected the evolution of divergent life-history traits in the two ecotypes, which, in turn, affect population dynamics. M-slow populations have evolved life-history traits that buffer fitness against direct effects of variation in reproduction and that spread lifetime reproduction across a greater number of reproductive bouts. These results highlight the importance of long-term demographic and environmental monitoring and of incorporating temporal dynamics into empirical studies of life-history evolution.     

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.     

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.     

Identifying interactions among salmon populations from observed dynamics

A simple direct correlation analysis of individual counts between different populations often fails to characterize the true nature of population interactions; however, the most common data type available for population studies is count data, and one of the most important objectives in population and community ecology is to identify interactions among populations. Here, I examine the dynamics of the spawning abundance of fall-run chinook salmon spawning within the California Central Valley and the Klamath Basin, California, and the Columbia River Basin, Oregon. I analyzed multiple time series from each watershed using a multivariate time-series technique called maximum autocorrelation factor analysis. This technique was used for finding common underlying trends in escapement abundance within each watershed. These trends were further investigated to identify potential resource-mediated interactions among the three groups of salmon. Each group is affected by multiple trends that are likely to be affected by environmental factors. In addition, some of the trends are coherent with each other, and the differences in population dynamics originate from variations in the relative importance of these trends among the three watershed groups.     

Albatross populations in peril: a population trajectory for black-browed albatrosses at south Georgia.

Simulation modeling was used to reconstruct Black-browed Albatross (Diomedea melanophris) population trends. Close approximations to observed data were accomplished by annually varying survival rates, reproductive success, and probabilities of returning to breed given success in previous years. The temporal shift in annual values coincided with the start of longline fishing at South Georgia and potential changes in krill abundance. We used 23 years of demographic data from long-term studies of a breeding colony of this species at Bird Island, South Georgia, to validate our model. When we used annual parameter estimates for survival, reproductive success, and probabilities of returning to breed given success in previous years, our model trajectory closely followed the observed changes in breeding population size over time. Population growth rate was below replacement (lambda < 1) in most years and was most sensitive to changes in adult survival. This supports the recent IUCN uplisting of this species from "Vulnerable" to "Endangered." Comparison of pre-1988 and post-1988 demography (before and after the inception of a longline fishery in the breeding area) reveals a decrease in lambda from 0.963 to 0.910. A life table response experiment (LTRE) showed that this decline in lambda was caused mostly by declines in survival of adults. If 1988-1998 demographic rates are maintained, the model predicts a 98% chance of a population of fewer than 25 pairs within 78 years. For this population to recover to a status under which it could be "delisted," a 10% increase in survival of all age classes would be needed.     

Combining demographic and count-based approaches to identify source-sink dynamics of a threatened seabird.

Identifying source-sink dynamics is of fundamental importance for conservation but is often limited by an inability to determine how immigration and emigration influence population processes. We demonstrate two ways to assess the role of immigration on population processes without directly observing individuals dispersing from one population to another and apply these methods to a population of Marbled Murrelets (Brachyramphus marmoratus) in California (USA). In the first method, the rate of immigration (i) is estimated by subtracting local recruitment (recruitment from within the population due to reproduction) estimated with demographic data from total recruitment (f; recruitment from within the population plus recruitment from other populations) estimated using temporal symmetry mark-recapture models developed by R. Pradel. The second method compares population growth rates estimated with temporal symmetry models (lambdaTS) and/or population growth rates estimated from counts of individuals over multiple sampling periods (lambdaC) with growth estimates from a stage-structured projection matrix model (lambdaM). Both lambdaTS and lambdaC incorporate all demographic processes affecting population change (birth, death, immigration, and emigration), whereas matrix models are usually constructed without incorporating immigration. Thus, if lambdaTS and lambdaC are > or = 1 and lambdaM < 1, the population is sustained by immigration and is considered to be a sink. Using the first method, recruitment estimated with temporal symmetry models was high (f= 0.182, SE = 0.058), the mean adult birth rate, as estimated using the ratio of juveniles to > or = 1 year old individuals (observed during ship-based surveys) was low (bA = 0.039, SE = 0.014), and immigration was 0.160 (SE = 0.057). Using the second method, murrelet numbers in central California were stable (lambdaC = 1.058, SE = 0.047; lambdaTS = 1.064, SE = 0.033), but were projected to decline 9.5% annually in the absence of immigration (lambdaM = 0.905, SE = 0.053). Our results suggest that Marbled Murrelets in central California represent a sink population that is stable but would decline in the absence of immigration from larger populations to the north. However, the extent to which modeled immigration is due to permanent recruitment or temporarily dispersing individuals that simply mask population declines is uncertain.     

Postdispersal seed predation limits the abundance of a long-lived perennial forb (Lithospermum ruderale)

Loss of seeds to consumers is common in plant communities, but the degree to which these losses influence plant abundance or population growth is often unclear. This is particularly the case for postdispersal seed predation by rodents, as most studies of rodent seed predation have focused on the sources of spatiotemporal variation in seed loss but not quantified the population consequences of this loss. In previous work we showed that seed predation by deer mice (Peromyscus maniculatus) substantially reduced seedling recruitment and establishment of Lithospermum ruderale (Boraginaceae), a long-lived perennial forb. To shed light on how rodent seed predation and the near-term effects on plant recruitment might influence longer-term patterns of L. ruderale population growth, we combined experimental results with demographic data in stage-based population models. Model outputs revealed that rodent seed predation had a significant impact on L. ruderale population growth rate (lambda). With the removal of postdispersal seed predation, the projected population growth rates increased between 0.06 and 0.12, depending on site (mean deltalambda across sites = 0.08). Seed predation shifted the projected stable stage distribution of populations from one with a high proportion of young plants to one in which larger adult size classes dominate. Elasticities of vital rates also changed, with germination and growth of seedlings and young plants becoming more important with the removal of seed predation. Simulations varying the magnitude of seed predation pressure while holding other vital rates constant showed that seed predation could lower lambda even if only 40% of available seeds were consumed. These results demonstrate that rodent granivory can be a potent force limiting the abundance of a long-lived perennial forb.     

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.     

Viability Analysis of Reef Fish Populations Based on Limited Demographic Information

Abstract:  Marine protected areas (MPAs) that allow some degree of artisanal fishing have been proposed to control the overexploitation of marine resources while allowing extraction by local communities. Nevertheless, the management of MPAs is often impaired by the absence of data on the status of their resources. We devised a method to estimate population growth rates with the type of data that are usually available for reef fishes. We used 7 years of spatially explicit abundance data on the leopard grouper ( Mycteroperca rosacea ) in an MPA in the Gulf of California, Mexico, to construct a matrix population model that incorporated the effects of El Niño/La Niña Southern Oscillation on population dynamics. An environmental model that estimated different demographic estimates for El Niño and La Niña periods performed better than a single-environment model, and a single-habitat model performed better than a model that considered different depths as different habitats. Our results suggest that the population of the leopard grouper off the main island of the MPA is not viable under present conditions. Although the impact of fishing on leopard grouper populations in the MPA has not yet been established, fishing should be closed as a precautionary measure at this island if a priority of the MPA is to ensure the sustainability of its fish populations.     

DNA Fingerprinting Reveals a Lack of Genetic Variation in Northern Populations of the Western Pond Turtle (Clemmys marmorata)

I used DNA fingerprinting to provide the first analysis of the genetic composition of western pond turtle ( Clemmys marmorata ) populations in Washington, Oregon, and California. Populations of the western pond turtle in Washington and northern Oregon are rapidly approaching extinction. Genetic similarity within the largest northern populations, which are located inland, is high. An analysis of population substructure (F_st) revealed significant genetic divergence between inland populations, indicating a lack of dispersal and gene flow between sites. In contrast, northern coastal sites are not genetically distinct, but there are few if any viable populations remaining in this region. Genetic variability within southern California populations is a great deal higher than in northern inland sites. Similarly, a low F_st value indicated a lack of genetic differentiation between southern sites. An inter-regional analysis of population substructure (F_st = 0.24) revealed a significant degree of genetic divergence between geographical regions throughout the range. In addition, an estimate of western pond turtle phylogeny showed a genetic break in the species between northern and southern populations. Both population subdivision and phylogenetic analyses suggest a lack of appreciable gene flow between geographical regions for a considerable period of time. Genetic analyses support traditional subdivision based solely on the morphological variation of Clemmys marmorata into two subspecies: northern Clemmys marmorata marmorata and southern Clemmys marmorata pallida . Recovery of dwindling northern populations must combine demographic and genetic considerations. A first step should be to preserve local gene pools while augmenting population numbers, with the goal of preventing the extinction of this genetically and morphologically distinct subspecies.     

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.     

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     

Do source-sink dynamics promote the spread of an invasive grass into a novel habitat?

Models of source-sink and other spatial patch dynamics have generated a number of ideas and predictions about species range expansion, the evolution of local adaptation, and the factors influencing population persistence, but relatively few empirical studies have applied these ideas due to the difficulty of measuring both patch-specific demography and movement rates. In this study, I used a combination of mark-recapture experiments, model fitting, and demographic approaches to ask how habitat-specific differences in population growth and dispersal affect spread of the invasive grass Aegilops triuncialis into serpentine environments. A. triuncialis germinated at lower rates but exhibited equivalent survival and greater growth in edge (extreme serpentine) than in core populations, even accounting for density differences between habitats. Estimated growth rates (lambda) for four of five edge subpopulations were strongly positive, ranging from lambda = 1.32 to 2.09 without propagule input from adjacent habitat. Local dispersal was best described by an exponential kernel, with a mean dispersal distance about twice as long on the edge (0.24-0.40 m) as in the core (0.18 m). Twenty-five percent of marked spikes in the edge were not relocated within the patch, suggesting greater rates of either seed predation or long-distance dispersal that reduced population growth. These results suggest that A. triuncialis can successfully spread into extreme serpentine habitats without sustained propagule input from adjacent populations. Further, asymmetric dispersal that may be both habitat- and density-dependent could slow growth rates on the edge. This pattern may also increase the importance of harsh edge patches as a source of long-distance dispersers.     

Phylogeography of the diamond turbot (Hypsopsetta guttulata) across the Baja California Peninsula

We compared morphology and sequenced nuclear and mitochondrial genes from 11 populations of a previously genetically unstudied “Baja California disjunct” species, the diamond turbot (Hypsopsetta guttulata). This species exhibits very limited adult movement and restriction to soft-bottom habitats but has a moderately long pelagic larval duration. Therefore, if pelagic larval duration is correlated with gene flow between Gulf of California and Pacific populations, we expect a reduced level of genetic and morphological differentiation. However, if adult habitat and ecology have more effect on gene flow, we expect the populations in the two bodies of water to be more highly differentiated. We used logistic regression to compare morphological features and phylogenetic and population genetic analyses to compare nucleotide sequence data. Gulf of California H. guttulata are different from Pacific populations in morphology and both mitochondrial and nuclear gene sequences. MtDNA shows reciprocal monophyly, and nuclear sequences from the Gulf of California formed a monophyletic group. Population genetic analyses also suggest further population subdivision within the Pacific and within the Gulf of California. We argue that adult ecology has a significant effect on migration rates among populations in the Pacific Ocean and the Gulf of California.     

Dynamics of a low‐density tiger population in Southeast Asia in the context of improved law enforcement

Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture‐recapture methods. From 2006 to 2012, we sampled across 624–1026 km² with 137–200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture‐recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood‐based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km², abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture–recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82–90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low‐density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade.     

The importance of space, time, and stochasticity to the demography and management of Alliaria petiolata

As population modeling is increasingly called upon to guide policy and management, it is important that we understand not only the central tendencies of our study systems, but the consequences of their variation in space and time as well. The invasive plant Alliaria petiolata (garlic mustard) is actively managed in the United States and is the focus of a developing biological control program. Two weevils (Coleoptera: Curculionidae: Ceutorhynchus) that reduce fecundity (C. alliariae) and rosette survival plus fecundity (C. scrobicollis) are under consideration for release pending host specificity testing. We used a demographic modeling approach to (1) quantify variability in A. petiolata growth and vital rates and (2) assess the potential for single- or multiple-agent biocontrol to suppress growth of 12 A. petiolata populations in Illinois and Michigan studied over three plant generations. We used perturbation analyses and simulation models with stochastic environments to estimate stochastic growth rates (lambda(S)) and predict the probability of successful management using either a single biocontrol agent or two agent species together. Not all populations exhibited invasive dynamics. Estimates of lambda(S) ranged from 0.78 to 2.21 across sites, while annual, deterministic growth (lambda) varied up to sevenfold within individual sites. Given our knowledge of the biocontrol agents, this analysis suggests that C. scrobicollis alone may control A. petiolata at up to 63% of our study sites where lambda >1, with the combination of both agents predicted to succeed at 88% of sites. Across sites and years, the elasticity rankings were dependent on lambda. Reductions of rosette survival, fecundity, or germination of new seeds are predicted to cause the greatest reduction of lambda in growing populations. In declining populations, transitions affecting seed bank survival have the greatest effect on lambda. This contrasts with past analyses that varied parameters individually in an otherwise constant matrix, which may yield unrealistic predictions by decoupling natural parameter covariances. Overall, comparisons of stochastic and deterministic growth rates illustrate how analyses of individual populations or years could misguide management or fail to characterize complex traits such as invasiveness that emerge as attributes of populations rather than species.     

Potential effects of environmental contamination on Yuma Myotis demography and population growth.

Unplanned natural and anthropogenic disasters provide unique opportunities for investigating the influence of perturbations on population vital rates and species recovery times. We investigated the potential effects of a major pesticide spill by comparing annual survival rates using mark-recapture techniques on a riparian bat species, Yuma Myotis (Myotis yumanensis). Demography and population dynamics for most bat species remain poorly understood despite advances in mark-recapture estimation and modeling techniques. We compared survival and population growth rates of two roost populations exposed to a large chemical (metam sodium) spill in the upper Sacramento River in Northern California with two roost populations outside the contaminated area from 1992 to 1996. Hypotheses about long-term effects of the spill on female juvenile and adult survival were tested using an information-theoretic approach (AIC). Working hypotheses included effects of age, chemical spill, and time trend on survival. Female adult survival was higher than female juvenile survival across all sites, suggesting stage-specific mortality risks. Model-averaged estimates of female juvenile survival in the contaminated area (0.50-0.74) were lower than in control roosts (0.60-0.78) for each year in the study, suggesting that the spill may have reduced juvenile survival for several years. Female adult survival (0.73-0.89) did not appear to be strongly affected by the spill during the years of the study. There was an increase in survival for both stage-classes across all populations during the study period, which may have been caused by the end of an extended drought in California in the winter of 1993. The spill-affected population was in decline for the first year of the study as indicated by an estimated growth rate (lambda) < 1, but population growth rates increased during the four-year period.     

Gray Whales and the Value of Monitoring Data in Implementing the U.S. Endangered Species Act

Abstract: Many scientists lament the absence of data for endangered species and argue that more funds should be spent acquiring basic information about population trends. Using 19 years of abundance estimates for the eastern North Pacific gray whale ( Eschrichtius robustus ), we sampled subsets of the original survey data to identify the number of years of data required to remove the population from the U.S. Endangered Species Act's (ESA) list of endangered and threatened wildlife. For any given duration of monitoring, we selected all possible combinations of consecutive counts. To incorporate variability in growth rates, we extracted a maximum likelihood estimator of growth rate and confidence interval about that growth rate on the assumption that the population changes can be approximated by a simple diffusion process with drift. We then applied a new approach to determine ESA status for each subset of survey data and found that a quantitative decision to delist is unambiguously supported by 11 years of data but is precariously uncertain with fewer than 10 years of data. The data needed to produce an unequivocal decision to delist gray whales cost the National Marine Fisheries Service an estimated U.S. $660,000, a surprisingly modest expense given the fact that delisting can greatly simplify regulatory constraints. This example highlights the value of population monitoring in administering the ESA and provides a compelling example of the utility of such information in identifying both imperiled and recovered species. The economic value of such data is that they provide the foundation for delisting, which could ultimately save much more money than the collection of the data would ever cost.     

On the choice of statistical models for estimating occurrence and extinction from animal surveys

In surveys of natural animal populations the number of animals that are present and available to be detected at a sample location is often low, resulting in few or no detections. Low detection frequencies are especially common in surveys of imperiled species; however, the choice of sampling method and protocol also may influence the size of the population that is vulnerable to detection. In these circumstances, probabilities of animal occurrence and extinction will generally be estimated more accurately if the models used in data analysis account for differences in abundance among sample locations and for the dependence between site-specific abundance and detection. Simulation experiments are used to illustrate conditions wherein these types of models can be expected to outperform alternative estimators of population site occupancy and extinction.