The Long-Term Effects of Tiger Poaching on Population Viability

Poaching tigers, primarily for their bones, has become the latest threat to the persistence of wild tiger populations throughout the world. Anecdotal information indicates the seriousness of this new threat. It is important, however, to provide a quantitative analysis of poaching as a basis for strong policy action. We therefore created a tiger simulation model to explore the effects of realistic levels of poaching on population viability. The model is an individually based, stochastic spatial model that is based on the extensive data set from Royal Chitwan National Park, Nepal. We found that as poaching continues over time, the probability of population extinction increases sigmoidally; a critical zone exists in which a small, incremental increase in poaching greatly increases the probability of extinction. The implication is that poaching may not at first be seen as a threat but could suddenly become one. Moreover, even if poaching is effectively stopped, tiger populations will still be vulnerable and could go extinct due to demographic and environmental stochasticity. Our model also shows that poaching reduces genetic variability, which could further reduce population viability due to inbreeding depression. The longer poaching is allowed to continue, the more vulnerable a population will be to these stochastic events. At currently reported rates of poaching our analysis indicates that many wild tiger populations will be extirpated during the latter half of the 1990s.     

Effective Population Size in Red-Cockaded Woodpeckers: Population and Model Differences

Loss of genetic variability in isolated populations is an important issue for conservation biology. Most studies involve only a single population of a given species and a single method of estimating rate of loss. Here we present analyses for three different Red-cockaded Woodpecker ( Picoides borealis ) populations from different geographic regions. We compare two different models for estimating the expected rate of loss of genetic variability, and test their sensitivity to model parameters. We found that the simpler model (Reed et al. 1988) consistently estimated a greater rate of loss of genetic variability from a population than did the Emigh and Pollak (1979) model. The ratio of effective population size (which describes the expected rate of loss of genetic variability) to breeder population size varied widely among Red-cockaded Woodpecker populations due to geographic variation in demography. For this species, estimates of effective size were extremely sensitive to survival parameters, but not to the probability of breeding or reproductive success. Sensitivity was sufficient that error in estimating survival rates in the field could easily mask true population differences in effective size. Our results indicate that accurate and precise demographic data are prerequisites to determining effective population size for this species using genetic models, and that a single estimate of rate of loss of genetic variability is not valid across populations.     

Erosion of Heterozygosity in Fluctuating Populations

Abstract: Demographic, environmental, and genetic stochasticity threaten the persistence of isolated populations. The relative importance of these intertwining factors remains unresolved, but a common view is that random demographic and environmental events will usually drive small populations to the brink of 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 processes—environmental stochasticity and population demography—were modeled according to a bounded diffusion process. Genetic processes were modeled by quantifying the rate of drift according to the effective population size, which was predicted from the same parameters used to describe the nongenetic processes. We combined these models to predict the heterozygosity remaining at the time of extinction, as predicted by the nongenetic portion of the model. 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 is generally recognized. Therefore, conservation biologists should not ignore the genetic component of extinction risk when assessing species endangerment and developing recovery plans.     

Effects of Social Structure and Prey Dynamics on Extinction Risk in Gray Wolves

Extinction models based on diffusion theory generally fail to incorporate two important aspects of population biology—social structure and prey dynamics. We include these aspects in an individual-based extinction model for small, isolated populations of the gray wolf (Canis lupus). Our model predicts mean times to extinction significantly longer than those predicted by more general (diffusion) models. According to our model, an isolated population of 50 wolves has a 95% chance of surviving just 9 years and only a 30% chance of surviving beyond 100 years. Reflecting the influence of social structure, a wolf population initially comprising 50 individuals is expected to persist only a few years longer, on average (71 years), than is a population initially comprising just a single reproductive pair (62 years). In contrast, substantially greater average prey abundance leads to dramatically longer expected persistence times. Autocorrelated prey dynamics result in a more complex distribution of extinction times than predicted by many extinction models. We contend that demographic stochasticity may pose the greatest threat to small, isolated wolf populations, although environmental stochasticity and genetic effects may compound this threat. Our work highlights the importance of considering social structure and resource dynamics in the development of population viability analyses.     

The Population Dynamics and Conservation of Primate Populations

Abstract: Primates are among the most threatened taxa, with more than half of all species in jeopardy. In this paper we develop population models to use the kind of data on wild primates that primatologists actually collect. Our survey of recentprimate journals suggests that the average field study uses 1.5 years of data from 50 animals The models are based on the simple Leslie-Lefkovitch matrix. They suggest a simple method that allows assessment from a few years'data, of whether a population is collapsing and requires intervention To a good approximation, populations will collapse when adult survival, per inter-birth interval, is less than 70 percent.
Modifications of the basic model incorporate more realistic assumptions about social organization and densitydependent resource limitation. These allow us to identify population densities at which potential Allee effects operate, and permit more precise estimates of the minimum population sizes and compositions required for successful reintroductions to the wild The most important result is that populations of primates that live in small family groups may be more prone to "demographic" extinction than are more promiscuous species that live in more extended groups.     

Use of Integrated Modeling to Enhance Estimates of Population Dynamics Obtained from Limited Data

Abstract:  Demographic data of rare and endangered species are often too sparse to estimate vital rates and population size with sufficient precision for understanding population growth and decline. Yet, the combination of different sources of demographic data into one statistical model holds promise. We applied Bayesian integrated population modeling to demographic data from a colony of the endangered greater horseshoe bats (Rhinolophus ferrumequinum) . Available data were the number of subadults and adults emerging from the colony roost at dusk, the number of newborns from 1991 to 2005, and recapture data of subadults and adults from 2004 and 2005. Survival rates did not differ between sexes, and demographic rates remained constant across time. The greater horseshoe bat is a long-lived species with high survival rates (first year: 0.49 [SD 0.06]; adults: 0.91 [SD 0.02]) and low fecundity (0.74 [SD 0.12]). The yearly average population growth was 4.4% (SD 0.1%) and there were 92 (SD 10) adults in the colony in year 2005. Had we analyzed each data set separately, we would not have been able to estimate fecundity, the estimates of survival would have been less precise, and the estimate of population growth biased. Our results demonstrate that integrated models are suitable for obtaining crucial demographic information from limited data.     

Population Viability Analysis for an Endangered Plant

Abstract: Demographic modeling is used to understand the population viability of Furbish's lousewort, Pedicularis furbishiae , a perennial plant species endemic to the St. John River Valley in northern Maine. Environment-specific summaries of demographic parameters (survivorship, growth, and fecundity) over four years, organized into stage-based projection matrices, provide predictions of future population dynamics given a deterministic extension of past conditions. Stochastic modeling, using (I) empirically observed variation in demographic parameters, and (2) estimated rates of natural catastrophes, leads to predictions of extinction probability.
P. furbishiae viability has varied widely over the study period Viable populations with finite rates of increase > 1 are found where cover is low, woody plants do not dominate, and disturbance does not occur. Rates of increase vary over time, suggesting that stochastic analyses would be realistic. Stochastic measures of population viability incorporating environmental variation suggest that early successional environments, especially wetter sites, can support viable populations in the absence of disturbance. However; observed rates of natural catastrophe dominate viability estimates of individual populations. Metapopulation dynamics feature extinction rates that are greater than recolonization rates, and may be affected by land use in the watershed Species management needs to consider a large-scale view of the riverine corridor.     

Interactive Effects of Harvest and Deer Herbivory on the Population Dynamics of American Ginseng

Abstract:  Few demographic models for any species consider the role of multiple, interacting ecological threats. Many forest herbs are heavily browsed by white-tailed deer ( Odocoileus virginianus ) and a number of these are also harvested for the medicinal, floral, or horticultural trades. Previous studies of the viability of American ginseng ( Panax quinquefolius ) have separately examined the effects of harvesting and deer herbivory. We followed individually marked ginseng plants in 6 populations for 8 years and documented deer browse levels, conducted helicopter surveys to estimate the deer herd size, and documented 2 ginseng harvests. We used this long-term data set to develop a stochastic demographic model that quantified the separate and interactive role of these threats to ginseng viability. Although harvesting and deer herbivory negatively affected ginseng population growth, their effects were not additive. Deer herbivory negatively affected population growth in the absence but not in the presence of harvesting. Life table response experiments revealed that in the presence of harvesting, deer herbivory had some positive effects on vital rates because browsed plants were less apparent to harvesters. Ginseng populations that were harvested responsibly (i.e., planting seeds from harvested individuals) had higher growth rates than those that were harvested irresponsibly. We concluded that both deer populations and harvesting must be managed to ensure sustainable populations of American ginseng. Our findings underscore the importance of long-term monitoring to assess threats to viability and the need for a broad ecological understanding of the complexity of ecosystem management.     

Effects of Harvest of Nontimber Forest Products and Ecological Differences between Sites on the Demography of African Mahogany

Abstract: The demographic impacts of harvesting nontimber forest products (NTFP) have been increasingly studied because of reports of potentially unsustainable harvest. Nevertheless, our understanding of how plant demographic response to harvest is altered by variation in ecological conditions, which is critical for developing realistic sustainable‐use plans, is limited. We built matrix population models to test whether and how variation in ecological conditions affects population responses to harvest. In particular, we examined the effect of bark and foliage harvest on the demography of populations of African mahogany (Khaya senegalensis) in two contrasting ecological regions of Benin, West Africa. K. senegalensis bark and foliage harvest significantly reduced its stochastic population growth rates, but ecological differences between regions had a greater effect on population growth rates than did harvest. The effect of harvest on population growth rates (Δλ) was slightly stronger in the moist than in the drier region. Life‐table response experiments revealed that the mechanism by which harvesting reduced λ differed between ecological regions. Lowered stasis (persistence) of larger life stages lead to a reduction in λ in the drier region, whereas lowered growth of all life stages lowered λ in moist region. Potential strategies to increase population growth rates should include decreasing the proportion of individuals harvested, promoting harvester‐owned plantations of African mahogany, and increasing survival and growth by promoting no‐fire zones in gallery forests. Our results show how population responses to harvest of NTFP may be altered by ecological differences across sites and emphasize the importance of monitoring populations over the climatic range in which they occur to develop more realistic recommendations for conservation.     

Exploring Population Dynamics Patterns in a Rare Fish, Zingel asper, through Capture-Mark-Recapture Methods

Abstract:  We performed a capture-mark-recapture study on one of the last populations of Zingel asper , an endemic percid species of the Rhône River basin in France. The distribution of Z. asper has decreased dramatically during the last century. We sampled three sites in suitable habitats in the Beaume River. No impact of individual tagging on survival was found. The demography of the population was analyzed using capture-recapture methods that allow the estimation of survival, recruitment, and demographic growth rates. Annual survival rates were low (0.35–0.50). The level of transience was high (5% to 25%), suggesting that a significant number of individuals were highly mobile or shifted to suboptimal habitats. Seniority rates suggested random highly variable recruitment between years. The three sites had similar variation patterns in all demographic parameters, indicating broad spatial covariation in population dynamics. We found some local differences in demographic parameters, which could be linked to local habitat quality. Individual tagging allowed for the estimation of demographic parameters that improved our understanding of Z. asper population dynamics and revealed mechanisms that may affect population persistence, such as stochastic recruitment, low survival, and frequent dispersal. The fragmentation of habitat through river damming inhibits dispersal and represents a threat to the persistence of Z. asper in the Rhône basin. Our results offer evidence of the importance of dispersal in nonmigratory fishes and confirm the usefulness of individual tagging methods in rare fish demography.     

Local Population Dynamics in Metapopulation Models: Implications for Conservation

Abstract: Habitat fragmentation and the division of populations into spatially separated units have led to the increasing use of metapopulation models to characterize these populations. One prominent model that has served as a heuristic tool was introduced by Levins and is based on a collection of simplifying assumptions that exclude information on the dynamics and spatial distribution of local populations. Levins's and similar models predict the proportion of occupied habitat patches at equilibrium and the conditions needed to avoid total extinction. There are many obvious concerns about using such models, including how realistic alterations might change the predictions and whether occupancy has any relationship to population-level processes. Although many of the assumptions of these simple models are known to be unrealistic, we do not know how the assumptions affect model predictions. We simulated a metapopulation, and our results show that assumptions such as homogeneity of habitat patches, random migration among patches, equivalent extinction probabilities in all patches, and a large number of patches can lead to large overestimations of habitat occupancy. But when we explicitly modeled the underlying population dynamics within each patch, we found (1) that there was a strong correlation between proportion of occupied patches and total metapopulation size and (2) that the distribution of individuals among patches was relatively insensitive to model assumptions. Thus, our results show that although realistic modifications will change model predictions for occupancy, occupancy and population trends will be correlated. These correlations between occupancy and population size suggest that occupancy models may have some utility in conservation applications.     

Interacting Effects of Phenotypic Plasticity and Evolution on Population Persistence in a Changing Climate

Abstract: Climate change affects individual organisms by altering development, physiology, behavior, and fitness, and populations by altering genetic and phenotypic composition, vital rates, and dynamics. We sought to clarify how selection, phenotypic plasticity, and demography are linked in the context of climate change. On the basis of theory and results of recent empirical studies of plants and animals, we believe the ecological and evolutionary issues relevant to population persistence as climate changes are the rate, type, magnitude, and spatial pattern of climate‐induced abiotic and biotic change; generation time and life history of the organism; extent and type of phenotypic plasticity; amount and distribution of adaptive genetic variation across space and time; dispersal potential; and size and connectivity of subpopulations. An understanding of limits to plasticity and evolutionary potential across traits, populations, and species and feedbacks between adaptive and demographic responses is lacking. Integrated knowledge of coupled ecological and evolutionary mechanisms will increase understanding of the resilience and probabilities of persistence of populations and species.     

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.     

Demographic Forecasting in Koala Conservation

Abstract: The koala currently needs conservation intervention. There is clear evidence of decline in many populations, but the existence of other stable or expanding populations offers the possibility of a variety of creative solutions to their conservation problems. The 1998 National Koala Conservation Strategy emphasizes the need to obtain demographic information and to use this information to assess management options for koalas. We need accurate diagnoses of the status of koala populations and forecasts of their demographic future with and without particular management actions. In a qualitative fashion, this process has been undertaken many times on a local and national scale. Quantitative demographic forecasting tools are increasingly available, and koala management could benefit from their application both at the scale of individual populations and more broadly. There is already a considerable body of suitable data on the dispersal, effects of normal and catastrophic environmental variation on reproduction and survival, and on the effects of habitat change. Demographic forecasting, however, is hampered because the full suite of information is rarely available from a single population. In two Queensland populations, retrospective population viability analyses provided forecasts that were in agreement with observed population trends. Work is needed to determine whether data from one population can be applied to other populations. Models can then be developed to make projections at a multipopulation level on the basis of local population dynamics and dispersal. Certain koala populations, because of their long history of study, offer the opportunity to test demographic models retrospectively. These tests will not only aid in fine-tuning the models for koala biology and data but will also assist with the more general process of validating the models.     

Population growth in snow geese: a modeling approach integrating demographic and survey information

There are few analytic tools available to formally integrate information coming from population surveys and demographic studies. The Kalman filter is a procedure that facilitates such integration. Based on a state-space model, we can obtain a likelihood function for the survey data using a Kalman filter, which we may then combine with a likelihood for the demographic data. In this paper, we used this combined approach to analyze the population dynamics of a hunted species, the Greater Snow Goose (Chen caerulescens atlantica), and to examine the extent to which it can improve previous demographic population models. The state equation of the state-space model was a matrix population model with fecundity and regression parameters relating adult survival and harvest rate estimated in a previous capture-recapture study. The observation equation combined the output from this model with estimates from an annual spring photographic survey of the population. The maximum likelihood estimates of the regression parameters from the combined analysis differed little from the values of the original capture-recapture analysis, though their precision improved. The model output was found to be insensitive to a wide range of coefficient of variation (CV) in fecundity parameters. We found a close match between the surveyed and smoothed population size estimates generated by the Kalman filter over an 18-year period, and the estimated CV of the survey (0.078-0.150) was quite compatible with its assumed value (approximately 0.10). When we used the updated parameter values to predict future population size, the model underestimated the surveyed population size by 18% over a three-year period. However, this could be explained by a concurrent change in the survey method. We conclude that the Kalman filter is a promising approach to forecast population change because it incorporates survey information in a formal way compared with ad hoc approaches that either neglect this information or require some parameter or model tuning.     

Allee Effect and the Uncertainty of Population Recovery

Recovery of depleted populations is fundamentally important for conservation biology and sustainable resource harvesting. At low abundance, population growth rate, a primary determinant of population recovery, is generally assumed to be relatively fast because competition is low (i.e., negative density dependence). But population growth can be limited in small populations by an Allee effect. This is particularly relevant for collapsed populations or species that have not recovered despite large reductions in, or elimination of, threats. We investigated how an Allee effect can influence the dynamics of recovery. We used Atlantic cod (Gadus morhua) as the study organism and an empirically quantified Allee effect for the species to parameterize our simulations. We simulated recovery through an individual‐based mechanistic simulation model and then compared recovery among scenarios incorporating an Allee effect, negative density dependence, and an intermediate scenario. Although an Allee effect significantly slowed recovery, such that population increase could be negligible even after 100 years or more, it also made the time required for biomass rebuilding much less predictable. Our finding that an Allee effect greatly increased the uncertainty in recovery time frames provides an empirically based explanation for why the removal of threat does not always result in the recovery of depleted populations or species. El Efecto Allee y la Incertidumbre de la Recuperación de Poblaciones     

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.     

Photographic mark-recapture analysis of local dynamics within an open population of dolphins

Identifying demographic changes is important for understanding population dynamics. However, this requires long-term studies of definable populations of distinct individuals, which can be particularly challenging when studying mobile cetaceans in the marine environment. We collected photo-identification data from 19 years (1992-2010) to assess the dynamics of a population of bottlenose dolphins (Tursiops truncatus) restricted to the shallow (<7 m) waters of Little Bahama Bank, northern Bahamas. This population was known to range beyond our study area, so we adopted a Bayesian mixture modeling approach to mark-recapture to identify clusters of individuals that used the area to different extents, and we specifically estimated trends in survival, recruitment, and abundance of a "resident" population with high probabilities of identification. There was a high probability (p= 0.97) of a long-term decrease in the size of this resident population from a maximum of 47 dolphins (95% highest posterior density intervals, HPDI = 29-61) in 1996 to a minimum of just 24 dolphins (95% HPDI = 14-37) in 2009, a decline of 49% (95% HPDI = approximately 5% to approximately 75%). This was driven by low per capita recruitment (average approximately 0.02) that could not compensate for relatively low apparent survival rates (average approximately 0.94). Notably, there was a significant increase in apparent mortality (approximately 5 apparent mortalities vs. approximately 2 on average) in 1999 when two intense hurricanes passed over the study area, with a high probability (p = 0.83) of a drop below the average survival probability (approximately 0.91 in 1999; approximately 0.94, on average). As such, our mark-recapture approach enabled us to make useful inference about local dynamics within an open population of bottlenose dolphins; this should be applicable to other studies challenged by sampling highly mobile individuals with heterogeneous space use.     

Population inertia and its sensitivity to changes in vital rates and population structure

Because the (st)age structure of a population may rarely be stable, studies of transient population dynamics and population momentum are becoming ever more popular. Yet, studies of "population momentum" are restricted in the sense that they describe the inertia of population size resulting from a demographic transition to the stationary population growth rate. Although rarely mentioned, inertia in population size is a general phenomenon and can be produced by any demographic transition or perturbation. Because population size is of central importance in demography, conservation, and management, formulas relating the sensitivity of population inertia to changes in underlying vital rates and population structure could provide much-needed insight into the dynamics of populations with unstable (st)age structure. Here, we derive such formulas, which are readily computable, and provide examples of their potential use in studies of life history and applied arenas of population study.     

Genetic diversity increases population productivity in a sessile marine invertebrate

Reductions in genetic diversity can have widespread ecological consequences: populations with higher genetic diversity are more stable, productive and resistant to disturbance or disease than populations with lower genetic diversity. These ecological effects of genetic diversity differ from the more familiar evolutionary consequences of depleting genetic diversity, because ecological effects manifest within a single generation. If common, genetic diversity effects have the potential to change the way we view and manage populations, but our understanding of these effects is far from complete, and the role of genetic diversity in sexually reproducing animals remains unclear. Here, we examined the effects of genetic diversity in a sexually reproducing marine invertebrate in the field. We manipulated the genetic diversity of experimental populations and then measured individual survival, growth, and fecundity, as well as the size of offspring produced by individuals in high and low genetic diversity populations. Overall, we found greater genetic diversity increased performance across all metrics, and that complementarity effects drove the increased productivity of our high-diversity populations. Our results show that differences in genetic diversity among populations can have pervasive effects on population productivity within remarkably short periods of time.