Reliability of Absolute and Relative Predictions of Population Persistence Based on Time Series

Abstract:  Conventional population viability analysis (PVA) is often impractical because data are scarce for many threatened species. For this reason, simple count-based models are being advocated. The simplest of these models requires nothing more than a time series of abundance estimates, from which variance and autocorrelation in growth rate are estimated and predictions of population persistence are generated. What remains unclear, however, is how many years of data are needed to generate reliable estimates of these parameters and hence reliable predictions of persistence. By analyzing published and simulated time series, we show that several decades of data are needed. Predictions based on short time series were very unreliable mainly because limited data yielded biased, unreliable estimates of variance in growth rate, especially when growth rate was strongly autocorrelated. More optimistically, our results suggest that count-based PVA is sometimes useful for relative risk assessment (i.e., for ranking populations by extinction risk), even when time series are only a decade long. However, some conditions consistently lead to backward rankings. We explored the limited conditions under which simple count-based PVA may be useful for relative risk assessment.     

Using Population Viability Criteria to Assess Strategies to Minimize Disease Threats for an Endangered Carnivore

Outbreaks of infectious disease represent serious threats to the viability of many vertebrate populations, but few studies have included quantitative evaluations of alternative approaches to the management of disease. The most prevalent management approach is monitoring for and rapid response to an epizootic. An alternative is vaccination of a subset of the free‐living population (i.e., a “vaccinated core”) such that some individuals are partially or fully immune in the event of an epizootic. We developed a simulation model describing epizootic dynamics, which we then embedded in a demographic simulation to assess these alternative approaches to managing rabies epizootics in the island fox (Urocyon littoralis), a species composed of only 6 small populations on the California Channel Islands. Although the monitor and respond approach was superior to the vaccinated‐core approach for some transmission models and parameter values, this type of reactive management did not protect the population from rabies under many disease‐transmission assumptions. In contrast, a logistically feasible program of prophylactic vaccination for part of the wild population yielded low extinction probabilities across all likely disease‐transmission scenarios, even with recurrent disease introductions. Our use of a single metric of successful management—probability of extreme endangerment (i.e., quasi extinction)—to compare very different management approaches allowed an objective assessment of alternative strategies for controlling the threats posed by infectious disease outbreaks. Utilización de Criterios de Viabilidad Poblacional para Evaluar Estrategias para Minimizar Amenazas de Enfermedades para un Carnívoro en Peligro     

Using Scalar Models for Precautionary Assessments of Threatened Species

Abstract:  Scalar population models, commonly referred to as count-based models, are based on time-series data of population sizes and may be useful for screening-level ecological risk assessments when data for more complex models are not available. Appropriate use of such models for management purposes, however, requires understanding inherent biases that may exist in these models. Through a series of simulations, which compared predictions of risk of decline of scalar and matrix-based models, we examined whether discrepancies may arise from different dynamics displayed due to age structure and generation time. We also examined scalar and matrix-based population models of 18 real populations for potential patterns of bias in population viability estimates. In the simulation study, precautionary bias (i.e., overestimating risks of decline) of scalar models increased as a function of generation time. Models of real populations showed poor fit between scalar and matrix-based models, with scalar models predicting significantly higher risks of decline on average. The strength of this bias was not correlated with generation time, suggesting that additional sources of bias may be masking this relationship. Scalar models can be useful for screening-level assessments, which should in general be precautionary, but the potential shortfalls of these models should be considered before using them as a basis for management decisions.     

Habitat Change and Plant Demography: Assessing the Extinction Risk of a Formerly Common Grassland Perennial

Abstract:  An important aim of conservation biology is to understand how habitat change affects the dynamics and extinction risk of populations. We used matrix models to analyze the effect of habitat degradation on the demography of the declining perennial plant Trifolium montanum in 9 calcareous grasslands in Germany over 4 years and experimentally tested the effect of grassland management. Finite population growth rates (λ) decreased with light competition, measured as leaf-area index above T. montanum plants. At unmanaged sites λ was <1 due to lower recruitment and lower survival and flowering probability of large plants. Nevertheless, in stochastic simulations, extinction of unmanaged populations of 100 flowering plants was delayed for several decades. Clipping as a management technique rapidly increased population growth because of higher survival and flowering probability of large plants in managed than in unmanaged plots. Transition-matrix simulations from these plots indicated grazing or mowing every second year would be sufficient to ensure a growth rate ≥1 if conditions stayed the same. At frequently grazed sites, the finite growth rate was approximately 1 in most populations of T. montanum . In stochastic simulations, the extinction risk of even relatively small grazed populations was low, but about half the extant populations of T. montanum in central Germany are smaller than would be sufficient for a probability of survival of >95% over 100 years. We conclude that habitat change after cessation of management strongly reduces recruitment and survival of established individuals of this perennial plant. Nevertheless, our results suggest extinction processes may take a long time in perennial plants, resulting in an extinction debt. Even if management is frequent, many remnant populations of T. montanum may be at risk because of their small size, but even a slight increase in size could considerably reduce their extinction risk.     

生态恢复对退化河岸植物群落的作用 ——以重庆九龙外滩河岸带生态恢复为例

河岸带是陆地生态系统与水生生态系统之间的过渡地带,受人类干扰的威胁较大.长江是流经重庆都市区的主要河流,主城区两江四岸部分河岸硬化,河岸生态功能退化或丧失,生物多样性降低.本文以重庆主城区九龙外滩的河岸带为研究区域,通过调查,采用Ward最小方差法对植物群落类型进行划分,比较了生态恢复区域和自然区域的植物群落特征及优势...     

Effects of Road Fencing on Population Persistence

Abstract:  Roads affect animal populations in three adverse ways. They act as barriers to movement, enhance mortality due to collisions with vehicles, and reduce the amount and quality of habitat. Putting fences along roads removes the problem of road mortality but increases the barrier effect. We studied this trade-off through a stochastic, spatially explicit, individual-based model of population dynamics. We investigated the conditions under which fences reduce the impact of roads on population persistence. Our results showed that a fence may or may not reduce the effect of the road on population persistence, depending on the degree of road avoidance by the animal and the probability that an animal that enters the road is killed by a vehicle. Our model predicted a lower value of traffic mortality below which a fence was always harmful and an upper value of traffic mortality above which a fence was always beneficial. Between these two values the suitability of fences depended on the degree of road avoidance. Fences were more likely to be beneficial the lower the degree of road avoidance and the higher the probability of an animal being killed on the road. We recommend the use of fences when traffic is so high that animals almost never succeed in their attempts to cross the road or the population of the species of concern is declining and high traffic mortality is known to contribute to the decline. We discourage the use of fences when population size is stable or increasing or if the animals need access to resources on both sides of the road, unless fences are used in combination with wildlife crossing structures. In many cases, the use of fences may be beneficial as an interim measure until more permanent measures are implemented.     

The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot

Abstract:  Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot ( Isoodon obesulus ) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.     

Effects of an Invasive Plant on Population Dynamics in Toads

When populations decline in response to unfavorable environmental change, the dynamics of their population growth shift. In populations that normally exhibit high levels of variation in recruitment and abundance, as do many amphibians, declines may be difficult to identify from natural fluctuations in abundance. However, the onset of declines may be evident from changes in population growth rate in sufficiently long time series of population data. With data from 23 years of study of a population of Fowler's toad (Anaxyrus [ = Bufo] fowleri) at Long Point, Ontario (1989–2011), we sought to identify such a shift in dynamics. We tested for trends in abundance to detect a change point in population dynamics and then tested among competing population models to identify associated intrinsic and extrinsic factors. The most informative models of population growth included terms for toad abundance and the extent of an invasive marsh plant, the common reed (Phragmites australis), throughout the toads’ marshland breeding areas. Our results showed density‐dependent growth in the toad population from 1989 through 2002. After 2002, however, we found progressive population decline in the toads associated with the spread of common reeds and consequent loss of toad breeding habitat. This resulted in reduced recruitment and population growth despite the lack of significant loss of adult habitat. Our results underscore the value of using long‐term time series to identify shifts in population dynamics coincident with the advent of population decline. Efectos de una Planta Invasora sobre las Dinámica Poblacional de Sapos     

Modeling the Effects of Trophy Selection and Environmental Disturbance on a Simulated Population of African Lions

Abstract:  Tanzania is a premier destination for trophy hunting of African lions (Panthera leo) and is home to the most extensive long-term study of unhunted lions. Thus, it provides a unique opportunity to apply data from a long-term field study to a conservation dilemma: How can a trophy-hunted species whose reproductive success is closely tied to social stability be harvested sustainably? We used an individually based, spatially explicit, stochastic model, parameterized with nearly 40 years of behavioral and demographic data on lions in the Serengeti, to examine the separate effects of trophy selection and environmental disturbance on the viability of a simulated lion population in response to annual harvesting. Female population size was sensitive to the harvesting of young males (≥3 years), whereas hunting represented a relatively trivial threat to population viability when the harvest was restricted to mature males (≥6 years). Overall model performance was robust to environmental disturbance and to errors in age assessment based on nose coloration as an index used to age potential trophies. Introducing an environmental disturbance did not eliminate the capacity to maintain a viable breeding population when harvesting only older males, and initially depleted populations recovered within 15–25 years after the disturbance to levels comparable to hunted populations that did not experience a catastrophic event. These results are consistent with empirical observations of lion resilience to environmental stochasticity .     

Quantitative tools for implementing the new definition of significant portion of the range in the U.S. Endangered Species Act

In 2014, the Fish and Wildlife Service (FWS) and National Marine Fisheries Service announced a new policy interpretation for the U.S. Endangered Species Act (ESA). According to the act, a species must be listed as threatened or endangered if it is determined to be threatened or endangered in a significant portion of its range (SPR). The 2014 policy seeks to provide consistency by establishing that a portion of the range should be considered significant if the associated individuals’ “removal would cause the entire species to become endangered or threatened.” We reviewed 20 quantitative techniques used to assess whether a portion of a species’ range is significant according to the new guidance. Our assessments are based on the 3R criteria—redundancy (i.e., buffering from catastrophe), resiliency (i.e., ability to withstand stochasticity), and representation (i.e., ability to evolve)—that the FWS uses to determine if a species merits listing. We identified data needs for each quantitative technique and considered which methods could be implemented given the data limitations typical of rare species. We also identified proxies for the 3Rs that may be used with limited data. To assess potential data availability, we evaluated 7 example species by accessing data in their species status assessments, which document all the information used during a listing decision. In all species, an SPR could be evaluated with at least one metric for each of the 3Rs robustly or with substantial assumptions. Resiliency assessments appeared most constrained by limited data, and many species lacked information on connectivity between subpopulations, genetic variation, and spatial variability in vital rates. These data gaps will likely make SPR assessments for species with complex life histories or that cross national boundaries difficult. Although we reviewed techniques for the ESA, other countries require identification of significant areas and could benefit from this research.     

Population Viability Analysis with Species Occurrence Data from Museum Collections

Abstract: The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi‐extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.     

Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

Predicting Recovery Criteria for Threatened and Endangered Plant Species on the Basis of Past Abundances and Biological Traits

Recovery plans for species listed under the U.S. Endangered Species Act are required to specify measurable criteria that can be used to determine when the species can be delisted. For the 642 listed endangered and threatened plant species that have recovery plans, we applied recursive partitioning methods to test whether the number of individuals or populations required for delisting can be predicted on the basis of distributional and biological traits, previous abundance at multiple time steps, or a combination of traits and previous abundances. We also tested listing status (threatened or endangered) and the year the recovery plan was written as predictors of recovery criteria. We analyzed separately recovery criteria that were stated as number of populations and as number of individuals (population‐based and individual‐based criteria, respectively). Previous abundances alone were relatively good predictors of population‐based recovery criteria. Fewer populations, but a greater proportion of historically known populations, were required to delist species that had few populations at listing compared with species that had more populations at listing. Previous abundances were also good predictors of individual‐based delisting criteria when models included both abundances and traits. The physiographic division in which the species occur was also a good predictor of individual‐based criteria. Our results suggest managers are relying on previous abundances and patterns of decline as guidelines for setting recovery criteria. This may be justifiable in that previous abundances inform managers of the effects of both intrinsic traits and extrinsic threats that interact and determine extinction risk. Predicción de Criterios de Recuperación para Especies de Plantas en Peligro y Amenazadas con Base en Abundancias Pasadas y Atributos Biológicos     

Using Coral Disease Prevalence to Assess the Effects of Concentrating Tourism Activities on Offshore Reefs in a Tropical Marine Park

Abstract: Concentrating tourism activities can be an effective way to closely manage high‐use parks and minimize the extent of the effects of visitors on plants and animals, although considerable investment in permanent tourism facilities may be required. On coral reefs, a variety of human‐related disturbances have been associated with elevated levels of coral disease, but the effects of reef‐based tourist facilities (e.g., permanent offshore visitor platforms) on coral health have not been assessed. In partnership with reef managers and the tourism industry, we tested the effectiveness of concentrating tourism activities as a strategy for managing tourism on coral reefs. We compared prevalence of brown band disease, white syndromes, black band disease, skeletal eroding band, and growth anomalies among reefs with and without permanent tourism platforms within the Great Barrier Reef Marine Park. Coral diseases were 15 times more prevalent at reefs with offshore tourism platforms than at nearby reefs without platforms. The maximum prevalence and maximum number of cases of each disease type were recorded at reefs with permanently moored tourism platforms. Diseases affected 10 coral genera from 7 families at reefs with platforms and 4 coral genera from 3 families at reefs without platforms. The greatest number of disease cases occurred within the spatially dominant acroporid corals, which exhibited 18‐fold greater disease prevalence at reefs with platforms than at reefs without platforms. Neither the percent cover of acroporids nor overall coral cover differed significantly between reefs with and without platforms, which suggests that neither factor was responsible for the elevated levels of disease. Identifying how tourism activities and platforms facilitate coral disease in marine parks will help ensure ongoing conservation of coral assemblages and tourism.     

Ability of Matrix Models to Explain the Past and Predict the Future of Plant Populations

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage‐based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts’ 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data‐collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk‐averse decisions than to expect precise forecasts from models. Habilidad de los Modelos Matriciales para Explicar el Pasado y Predecir el Futuro de las Poblaciones de Plantas     

Using ensemble modeling to predict the impacts of assisted migration on recipient ecosystems

Assisted migration is a controversial conservation measure that aims to protect threatened species by moving part of their population outside its natural range. Although this could save species from extinction, it also introduces a range of risks. The magnitude of the threat to recipient ecosystems has not been investigated quantitatively, despite being the most common criticism leveled at the action. We used an ensemble modeling framework to estimate the risks of assisted migration to existing species within ecosystems. With this approach, we calculated the consequences of an assisted migration project across a very large combination of translocated species and recipient ecosystems. We predicted the probability of a successful assisted migration and the number of local extinctions would result from establishment of the translocated species. Using an ensemble of simulated 15-species recipient ecosystems, we estimated that translocated species will successfully establish in 83% of cases if introduced to stable, high-quality habitats. However, assisted migration projects were estimated to cause an average of 0.6 extinctions and 5% of successful translocations triggered 4 or more local extinctions. Quantifying the impacts to species within recipient ecosystems is critical to help managers weigh the benefits and negative consequences of assisted migration.