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

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

Managing plant population spread: prediction and analysis using a simple model

Models can be used to direct the management of population spread for the control of invasives or to encourage species of conservation value. Analytical models are attractive because of their theoretical basis and limited data requirements, but there is concern that their simplicity may limit their practical utility. We address the applied use of simple models in a study of a declining annual herb, Rhinanthus minor. We parameterized a population-spread model using field data on demography and dispersal for four management systems: grazed only (GR), hay-cut once (H1), hay-cut twice (H2), and hay-cut with autumn grazing (HG). Within a replicated experiment we measured spread rates of introduced R. minor populations over eight years. The modeled and measured spread rates were very similar in terms of both patterns of management effects and absolute values, so that in both cases HG > H2, H1 > GR. The treatments affected both dispersal and demography (establishment and survival) and so we used decomposition approaches to analyze the major causes of differences in population spread. Increased dispersal under hay-cutting was more important than demographic changes and accounted for approximately 70% of the differences in spread rate between the hay-cut and grazed-only treatments. Furthermore, management effects on the tail of the dispersal curve were by far the most critical in governing spread. This study suggests that simple models can be used to inform practical conservation management, and we demonstrate straightforward uses of our model to predict the impacts of different management strategies. While simple models can give accurate projections, we emphasize that they must be parameterized with high-quality data gathered at the appropriate spatial scale.     

Improving Habitat Models and Their Utility in Koala Conservation

Abstract: Models of what makes good koala habitat are a key to developing effective conservation policy and practices. Koala habitat models are based on (1) ecological studies of high-density koala populations in limited areas, (2) physiological studies of koala nutrition and characteristics of food plants, and (3) surveys of koala geographic distribution and biophysical features of forests and woodlands. The role of models in koala conservation varies because legislators, decisionmakers, land managers, and citizens have different expectations and uses for models. Although current habitat models address many of these needs, overall they lack sufficient certainty and authority to resolve disputes and develop policy. Unpublished and inadequately peer-reviewed data and models add to misinterpretation and argument. Improvements are needed in the decision-making process to increase the constructive involvement of all interest groups and to focus on the koala conservation problem, thereby reducing use of the popular media and courts of law to achieve objectives.     

Managing the Koala Problem: Interdisciplinary Perspectives

Abstract: There is a complex scientific, ethical, and cultural debate in Australia about how best to conserve koalas and their habitat. Despite the diverse array of management and research options promoted by scientists, wildlife agency staff, and koala advocates, there remains a gap in our acknowledgment of the social factors influencing decision making about koala conservation. Koala management research has generated valuable scientific knowledge about koala biology and ecology but has been weak about organizational and policy processes and about the cultures within which we produce, disseminate, and legitimize this kind of knowledge. We suggest that more effective koala conservation will result from making the political and cultural influences on decision making regarding the koala more explicit in research, management, and policy-making forums. Research must be conducted in the context of the cultural significance of the koala. The koala's survival depends on preserving the valuable lands that these creatures (and many others) inhabit. Ultimately, the koala symbolizes conflicting land-use values and illustrates the need for greater collaboration, cooperation, and trust among social and natural scientists in the conduct of koala conservation research, management, and policy.     

Forecasting extinction risk with nonstationary matrix models.

Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.     

Modeling Species' Distributions to Improve Conservation in Semiurban Landscapes: Koala Case Study

Abstract:  Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (  Phascolarctos cinereus ) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however, anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity.     

Population Trends and the Koala Conservation Debate

Abstract: A critical issue affecting the long-term management of koalas is their perceived conservation status. Koalas still occur in many areas throughout their historical range, but numbers of animals are estimated to vary from <100,000 to at least one order of magnitude higher. Complex factors limit free-ranging koala populations, including food tree preferences, history of disturbance, and Chlamydia infection, all of which make longer-term population trends of many populations difficult to predict. Lack of consensus regarding the size and viability of remaining populations and regarding the extent of and reasons for decline, overabundance or in some instances, hinders the conservation task. A reappraisal of population trends suggests that, notwithstanding localized management issues in Victoria and South Australia, overall the species is "vulnerable" on the basis of current World Conservation Union criteria. Recommendations for more effective conservation of koalas include (1) acknowledging the legitimacy of differing perspectives, (2) recognizing the uncertainty and assumptions inherent in population estimates and trends, (3) applying greater rigor and developing better standards for monitoring population trends, and (4) being cautious in assigning conservation status to national, state, and regional populations.     

Landscape evaluation in conservation: molecular sampling and habitat modeling for the Iberian lynx.

Conservation of endangered species requires comprehensive understanding of their distribution and habitat requirements, in order to implement better management strategies. Unfortunately, this understanding is often difficult to gather at the short term required by rapidly declining populations of many rare vertebrates. We present a spatial habitat modeling approach that integrates a molecular technique for species detection with landscape information to assess habitat requirements of a critically endangered mammalian carnivore, the Iberian lynx (Lynx pardinus), in a poorly known population in Spain. We formulated a set of model hypotheses for habitat selection at the spatial scale of home ranges, based on previous information on lynx requirements of space, vegetation, and prey. To obtain the required data for model selection, we designed a sampling protocol based on surveys of feces and their molecular analysis for species identification. After comparing candidate models, we selected a parsimonious one that allowed (1) reliable assessment of lynx habitat requirements at the scale of home ranges, (2) prediction of lynx distribution and potential population size, and (3) identification of landscape management priorities for habitat conservation. This model predicted that the species was more likely to occur in landscapes with a higher percentage of rocky areas and higher cover of bushes typical of mature mediterranean shrubland mosaics. Its accuracy for discriminating lynx presence was approximately 85%, indicating high predictive performance. Mapping model predictions showed that only 16% of the studied areas constitute potential habitat for lynx, even though the region is dominated by large extents of well-preserved native vegetation with low human interference. Habitat was mostly clumped in two nearby patches connected by vegetation adequate for lynx dispersal and had a capacity for 28-62 potential breeding territories. The lynx population in Sierra Morena is probably the largest persisting today, but it is still critically small for optimism about its long-term persistence. Model results suggest habitat conservation and restoration actions needed for preserving the species, including reconciliation of hunting management with preservation of mature shrubland over large areas (particularly in rocky landscapes). The approach presented here can be applied to many other species for which the ecological information needed to develop sound habitat conservation strategies is lacking.     

Conservation of Fragmented Populations

In this paper we argue that landscape spatial structure is of central importance in understanding the effects of fragmentation on population survival. Landscape spatial structure is the spatial relationships among habitat patches and the matrix in which they are embedded. Many general models of subdivided populations make the assumptions that (1) all habitat patches are equivalent in size and quality and (2) all local populations (in the patches) are equally accessible by dispersers. Models that gloss over spatial details of landscape structure can be useful for theoretical developments but will almost always be misleading when applied to real-world conservation problems. We show that local extinctions of fragmented populations are common. From this it follows that recolonization of local extinctions is critical for regional survival of fragmented populations. The probability of recolonization depends on (1) spatial relationships among landscape elements used by the population, including habitat patches for breeding and elements of the inter-patch matrix through which dispersers move, (2) dispersal characteristics of the organism of interest, and (3) temporal changes in the landscape structure. For endangered species, which are typically restricted in their dispersal range and in the kinds of habitat through which they can disperse, these factors are of primary importance and must be explicitly considered in management decisions.     

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     

The contribution of community wisdom to conservation ecology

Scientists have traditionally collected data on whether a population is increasing, decreasing, or staying the same, but such studies are often limited by geographic scale and time frame. This means that for many species, understanding of trends comes from only part of their ranges at particular periods. Working with citizen scientists has the potential to overcome these limits. Citizen science has the added benefit of exposing citizens to the scientific process and engaging them in management outcomes. We examined a different way of using citizen scientists (instead of data collection). We asked community members to answer a question directly and thus examined whether community wisdom can inform conservation. We reviewed the results of 3 mail‐in surveys that asked community members to say whether they thought koala populations were increasing, decreasing, or staying the same. We then compared the survey results with population trends derived from more traditional research. Population trends identified through community wisdom were similar to the trends identified by traditional research. The community wisdom surveys, however, allowed the question to be addressed at much broader geographical scales and time frames. Studies that apply community wisdom have the benefit of engaging a broad section of the community in conservation research and education and therefore in the political process of conserving species.     

Dispersal, competition, and shifting patterns of diversity in a degraded oak savanna

Diversity is a balance between processes that add and limit species (e.g., dispersal vs. competition), but reconciling their contributions remains a challenge. Recruit-ment-based models predict that dispersal barriers are most limiting for diversity, while competition-based models predict that dispersal matters only when competition is minimized. Testing these models is difficult because their influence varies with scale and site productivity. In a degraded oak savanna, we used plot-level (seed additions, burning) and site-level (proportions of regional functional groups found locally) analyses in areas with variable soil depth to examine how dispersal and competition influence diversity. At the plot level, added species persisted where they were formerly absent, but few established naturally despite fire-induced resource enrichment and nearby populations, revealing the importance of dispersal limitation for diversity. This result did not vary with soil depth or standing crop. Although competition could not prevent establishment in unburned plots, it significantly lowered survival, indicating that resource limitations exacerbate dispersal inefficiencies. At the site level, the concordance between regional and local diversity for native species was associated with soil depth heterogeneity, not dispersal or competition. This suggests that persistence is determined primarily by the influence of the environment on population demographics. Given that the formation of new populations is unlikely, those remaining appear to be confined to optimal habitat where they resist competitive or stochastic displacement, possibly explaining why species loss is rare despite substantial habitat loss and invasion. For exotics, there was no relationship between diversity and soil depth heterogeneity. Annuals with presumed dispersal capabilities were significantly overrepresented in all sites while perennial forbs, the largest regional functional group, were significantly underrepresented. We interpret the native-exotic discrepancies as reflecting the recent arrival of exotics (150 years ago), suggesting that local establishment occurs slowly even for species with regional prevalence. The accumulation lag may be explained by the need for founder populations to be demographically stable; otherwise persistence requires continual immigration favoring overrepresentation by dispersers. Our findings support the view that dispersal limitation restricts diversity within plant communities, but suggests that the impacts of environment on demographic performance ultimately determine the pattern and rate of community assembly.     

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.     

Effect of Vegetation Matrix on Animal Dispersal: Genetic Evidence from a Study of Endangered Skinks

Abstract:  Maintaining connectivity in fragmented landscapes is a key principle of biological conservation. Although corridors are a widely accepted approach to connecting populations, their merits are still debated, and they may be impractical in many situations. A focus on management of the vegetation matrix between populations has been advocated as an alternative way to deal with habitat fragmentation and has theoretical support. We combined microsatellite DNA and demographic data to provide an empirical account of how two forms of agricultural land use affect the connectivity of insular populations of an endangered skink in southern New Zealand. The grand skink ( Oligosoma grande ) lives in small populations (approximately 20 individuals) on rock outcrops separated from one another by 50–150 m of inhospitable matrix vegetation (either native tussock grassland or exotic pasture). Skinks typically dispersed short distances, and the nature of the matrix both quantitatively and qualitatively affected dispersal dynamics. Skink populations in pasture were significantly more genetically structured and had less genetic variation than similar populations in tussock, implying less dispersal between populations in pasture than tussock. Furthermore, although female-biased dispersal was a feature of populations in tussock, no sex bias was evident in pasture. In addition, Bayesian individual-based genetic assignment tests that incorporated prior mark-recapture information revealed that some populations produced many emigrants but received few immigrants, whereas other populations were relatively insular. Patterns of dispersal and response to matrix vegetation were complex, and the causes of these patterns deserve attention in future studies of habitat fragmentation. Managing the vegetation matrix may be a practical way to connect animal populations in some situations.     

Designing a Conservation Landscape for Tigers in Human-Dominated Environments

Abstract:  Wildlife populations in small, isolated reserves face genetic and demographic threats to their survival. To increase the probability of long-term persistence, biologists promote metapopulation management, in which breeding subpopulations are protected as source pools. Animals that disperse from the source pools increase the probability of persistence of the metapopulation across the greater landscape. We used a geographic information system (GIS)–based, cost-distance model to design a conservation landscape along the Himalayan foothills for managing a metapopulation of Asia's largest predator, the tiger ( Panthera tigris ). The model is based on data from 30 years of field research on tigers, recent satellite imagery, and a decade of buffer-zone restoration in this region. We used the model to (1) identify potential dispersal corridors for tigers; (2) identify strategic transit refuges; and (3) make recommendations for off-reserve land management and restoration to enhance the potential of corridors for tigers. This tool can aid the design of conservation landscapes for other endangered, wide-ranging species in human-dominated environments.     

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     

Wild Dog Demography in Hluhluwe-Umfolozi Park, South Africa

Abstract: Wild dogs (   Lycaon pictus ) are highly threatened carnivores, and conservation of their dwindling numbers is needed. Isolated populations contribute little to these conservation efforts, so linking populations of dogs is a necessary goal to prevent extinction. I gathered demographic information from a small population of wild dogs in Hluhluwe-Umfolozi Park, KwaZulu-Natal, South Africa. Photographs and archive records from 1981 to 1996 were used to compile information on this population. Demographic parameters from the released population were compared with information on wild dogs elsewhere. Most demographic parameters of the Hluhluwe-Umfolozi Park population were similar to published information from other populations. The main difference was the effect of a single pack on population performance: pack formation was unlikely, unrelated animals were rare, and major losses (emigration and mortalities) occurred. Increasing the number of packs by introducing more dogs would be useful but would be only a short-term solution. Increasing the local population size and artificially linking populations in southern Africa appears to be the only longer-term solution to ensure the viability of wild dogs on the subcontinent.     

Increasing the Accuracy of Productivity and Survival Estimates in Assessing Landbird Population Status

Abstract:  The conservation of species with declining populations requires information on population demography and identification of factors that limit population growth. For landbird species, an understanding of large-scale population declines often requires assessment of local population processes, including the production of offspring, the survival of those offspring, and adult survival. Population growth has been modeled for several species of landbirds to date, and these studies have provided important information on relationships between population status and population-limiting factors. Several recent studies have illuminated field methods and analytical techniques that can aid in increasing the accuracy of productivity and survival estimates for population models. We reviewed these methods and recommend their implementation, including quantification of the season-long productivity of individuals, collection of empirical data on juvenile survival during the postfledging and overwintering periods, and incorporation of adult breeding dispersal into annual adult survival estimates. Such methods will allow for more accurate assessment of population status and provide a better understanding of the factors on which to focus our conservation efforts.