Nonparametric spatial regression of survival probability: visualization of population sinks in Eurasian woodcock

Both evolutionary ecologists and wildlife managers make inference based on how fitness and demography vary in space. Spatial variation in survival can be difficult to assess in the wild because (1) multisite study designs are not well suited to populations that are continuously distributed across a large area and (2) available statistical models accounting for detectability less than 1.0 do not easily cope with geographical coordinates. Here we use penalized splines within a Bayesian state-space modeling framework to estimate and visualize survival probability in two dimensions. The approach is flexible in that no parametric form for the relationship between survival and coordinates need be specified a priori. To illustrate our method, we study a game species, the Eurasian Woodcock Scolopax rusticola, based on band recovery data (5000 individuals) collected over a > 50 000-km2 area in west-central France with contrasted habitats and hunting pressures. We find that spatial variation in survival probability matches an index of hunting pressure and creates a mosaic of population sources and sinks. Such analyses could provide guidance concerning the spatial management of hunting intensity or could be used to identify pathways of spatial variation in fitness, for example, to study adaptation to changing landscape and climate.     

Predator-prey spatial game as a tool to understand the effects of protected areas on harvester-wildlife interactions

No-take reserves are sometimes implemented for sustainable population harvesting because they offer opportunities for animals to spatially avoid harvesters, whereas harvesters can benefit in return from the reserve spillover. Here, we used the framework of predator-prey spatial games to understand how protected areas shape spatial interactions between harvesters and target species and determine animal mortality. In these spatial games, the "predator" searches for "prey" and matches their habitat use, unless it meets spatial constraints offering the opportunity for prey to avoid the mortality source. However, such prey refuges could attract predators in the surroundings, which questions the potential benefits for prey. We located, in the Geneva Basin (France), hunting dogs and wild boar Sus scrofa L. during hunting seasons with global positioning systems and very-high-frequency collars. We quantified how the proximity of the reserve shaped the matching between both habitat uses using multivariate analyses and linked these patterns to animals' mortality with a Cox regression analysis. Results showed that habitat uses by both protagonists disassociated only when hunters were spatially constrained by the reserve. In response, hunters increased hunting efforts near the reserve boundary, which induced a higher risk exposure for animals settled over the reserve. The mortality of adult wild boar decreased near the reserve as the mismatch between both habitat uses increased. However the opposite pattern was determined for younger individuals that suffered from the high level of hunting close to the reserve. The predator-prey analogy was an accurate prediction of how the protected area modified spatial relationships between harvesters and target species. Prey-searching strategies adopted by hunters around reserves strongly impacted animal mortality and the efficiency of the protected area for this harvested species. Increasing reserve sizes and/or implementing buffer areas with harvesting limitations can dampen this edge effect and helps harvesters to benefit durably from source populations of reserves. Predator-prey spatial games therefore provide a powerful theoretical background for understanding wildlife-harvester spatial interactions and developing substantial application for sustainable harvesting.     

Exploring alternative states in ecological systems with a qualitative analysis of community feedback

Demonstrating and predicting the existence of alternative states in natural communities remains a challenge for ecologists and is essential for resource managers. Positive feedback is often presented as central in maintaining alternative ecosystem states, but no formal approach relates this part of theory to real world applications. Through qualitative modelling of community response to long-term perturbations, we define generic mechanistic links between positive feedback and the occurrence of alternative states. Positive feedback diminishes a system's overall resistance to change, and can create and maintain correlations in the relative abundance of variables that coincide with alternative states.Through specific models of the dynamics of Tasmanian rocky-reef communities, which are affected by climate and fishing and persist within alternative states, we demonstrate the ability of our theoretical framework to predict alternative states in ecosystems and inform management intervention. A qualitative knowledge of community structure permits a thorough analysis of system feedback and an assessment of the potential for an ecosystem to exhibit alternative states. We illustrate the usefulness of the approach to inform management priorities, and to focus monitoring and field research on the key drivers of ecosystem dynamics.     

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.     

Uncertainty analysis of transient population dynamics

Two types of demographic analyses, perturbation analysis and uncertainty analysis, can be conducted to gain insights about matrix population models and guide population management. Perturbation analysis studies how the perturbation of demographic parameters (survival, growth, and reproduction parameters) may affect the population projection, while uncertainty analysis evaluates how much uncertainty there is in population dynamic predictions and where the uncertainty comes from. Previously, both perturbation analysis and uncertainty analysis were conducted on the long-term population growth rate. However, the population may not reach its equilibrium state, especially when there is management by harvesting or hunting. Recently, there has been an increased interest in short-term transient dynamics, which can differ from asymptotic long-term dynamics. There are currently techniques to conduct perturbation analyses of short-term transient dynamics, but no techniques have been proposed for uncertainty analysis of such dynamics. In this study, we introduced an uncertainty analysis technique, the general Fourier Amplitude Sensitivity Test (FAST), to study uncertainties in transient population dynamics. The general FAST is able to identify the amount of uncertainty in transient dynamics and contributions by different demographic parameters. We applied the general FAST to a mountain goat (Oreamnos americanus) matrix population model to give a clear illustration of how uncertainty analysis can be conducted for transient dynamics arising from matrix population models.     

A bio-inspired computing model as a new tool for modeling ecosystems: The avian scavengers as a case study

The models used for ecosystems modeling are generally based on differential equations. However, in recent years new computational models based on biological processes, or bioinspired models, have arisen, among which are P systems. These are inspired by the functions of cells and present important advantages with respect to traditional models, such as a high computational efficiency, modularity and their ability to work in parallel. They are simple, individual-based models that use biological parameters that can be obtained experimentally. In this work, we present the framework for a model based on P systems applied to the study of an ecosystem in which three avian scavengers (predators) interact with 10 wild and domestic ungulates (preys). The computation time for 100 repetitions, corresponding to 14 simulation years each, with an initial population composed of 385,422 individuals, was 30 min. Our results suggest that the model presented, based on P systems, correctly simulates the population dynamics in the period of time analyzed. We discuss the usefulness of this tool in simulating complex ecosystems dynamics to aid managers, conservationists and policy-makers in making appropriate decisions for the improvement of management and conservation programs.     

Climate influences the demography of three dominant sagebrush steppe plants

Climate change could alter the population growth of dominant species, leading to profound effects on community structure and ecosystem dynamics. Understanding the links between historical variation in climate and population vital rates (survival, growth, recruitment) is one way to predict the impact of future climate change. Using a unique, long-term data set from eastern Idaho, USA, we parameterized integral projection models (IPMs) for Pseudoroegneria spicata, Hesperostipa comata, and Artemisia tripartita to identify the demographic rates and climate variables most important for population growth. We described survival, growth, and recruitment as a function of genet size using mixed-effect regression models that incorporated climate variables. Elasticites for the survival + growth portion of the kernel were larger than the recruitment portion for all three species, with survival + growth accounting for 87-95% of the total elasticity. The genet sizes with the highest elasticity values in each species were very close to the genet size threshold where survival approached 100%. We found strong effects of climate on the population growth rate of two of our three species. In H. comata, a 1% decrease in previous year's precipitation would lead to a 0.6% decrease in population growth. In A. tripartita, a 1% increase in summer temperature would result in a 1.3% increase in population growth. In both H. comata and A. tripartita, climate influenced population growth by affecting genet growth more than survival or recruitment. Late-winter snow was the most important climate variable for P. spicata, but its effect on population growth was smaller than the climate effects we found in H. comata or A. tripartita. For all three species, demographic responses lagged climate by at least one year. Our analysis indicates that understanding climate effects on genet growth may be crucial for anticipating future changes in the structure and function of sagebrush steppe vegetation.     

Modelling volatility of growth rate in atmospheric carbon dioxide concentrations in a Bayesian approach

Atmospheric gases, such as carbon dioxide, ozone, methane, nitrous oxide, and etc., create a natural greenhouse effect and cause climate change. Therefore, modelling behavior of these gases could help policy makers to control greenhouse effects. In a Bayesian framework, we analyse and model conditional variance of growth rate in atmospheric carbon dioxide concentrations (ACDC) using monthly data from a subset of the well known Mauna Loa atmosphere carbon dioxide record. The conditional variance of ACDC monthly growth rate is modelled using the autoregressive conditional heteroscedasticity (ARCH), generalized ARCH model (GARCH) and a few variants of stochastic volatility (SV) models. Smooth transition ARCH and GARCH models are shown to be able to capture the dynamics in the conditional variance in ACDC level growth rate and to improve the forecast performance of ACDC growth rate.     

Estimating wild boar density in hunting areas by a probabilistic sampling of drive counts

Environmental and Ecological Statistics - The evaluation of wild boar density in a hunting district can be performed by accurate drive counts of boars within the drive areas assigned to each...     

Effect of Hunting in Source-Sink Systems in the Neotropics

Abstract: Previous studies of the sustainability of wildlife hunting in the Neotropics have not considered the potential dispersal of animals into hunted areas. A literature review of studies of subsistence hunting in the Neotropics suggests that hunting is often conducted in areas adjacent to relatively undisturbed habitat that may act as sources of animals for the hunted sites. We compared studies of tapir (   Tapirus terrestris ) hunting at different sites to illustrate the potential bias of sustainability evaluations based on local productivity. The limited information available suggests that dispersal could have a key role in rebuilding animal populations depleted by hunting. Thus, factors that strongly affect dispersal—such as spatial distribution and size of areas with and without hunting, population size in source areas, and social behavior—should be considered when the sustainability of hunting is evaluated in areas with heterogeneous hunting pressure. We suggest the application of two models that use spatial controls (recognizing the potential source-sink nature of some hunted systems and protecting unhunted refugia) to avoid wildlife overexploitation when biological data and enforcement capabilities to regulate harvests are limited. This approach may produce more reliable evaluations of sustainability, provide information on the dynamics of hunting systems, and help local communities and policymakers conserve key areas (including protected areas) that may act as game sources.     

Application of the Anthropogenic Allee Effect Model to Trophy Hunting as a Conservation Tool

Trophy hunting can provide economic incentives to conserve wild species, but it can also involve risk when rare species are hunted. The anthropogenic Allee effect (AAE) is a conceptual model that seeks to explain how rarity may spread the seeds of further endangerment. The AAE model has increasingly been invoked in the context of trophy hunting, increasing concerns that such hunting may undermine rather than enhance conservation efforts. We question the appropriateness of uncritically applying the AAE model to trophy hunting for 4 reasons. First, the AAE assumes an open‐access resource, which is a poor characterization of most trophy‐hunting programs and obscures the potential for state, communal, or private‐property use rights to generate positive incentives for conservation. Second, study results that show the price of hunting increases as the rarity of the animal increases are insufficient to indicate the presence of AAE. Third, AAE ignores the existence of biological and behavioral factors operating in most trophy‐hunting contexts that tend to regulate the effect of hunting. We argue that site‐specific data, rather than aggregated hunting statistics, are required to demonstrate that patterns of unsustainable exploitation can be well explained by an AAE model. Instead, we suggest that conservation managers seeking to investigate and identify constraints that limit the potential conservation role of trophy hunting, should focus on the critical governance characteristics that shape the potential conservation role of trophy hunting, such as corruption, insecure property rights, and inadequate sharing of benefits with local people. Aplicación del Modelo Antropogénico del Efecto Allee sobre la Caza de Trofeos como una Herramienta de Conservación     

An individual based model of bearded pig abundance

We develop an individual based model of bearded pig abundance which predicts population dynamics based on the processes of energy accumulation and expenditure, reproduction and mortality of individual pigs. Because fatness is a key indicator of condition and reproductive potential in bearded pigs, processes are represented in terms of a fatness index variable. Only a small number of parameters are used in this simple model; these were chosen on the basis of fatness index data and qualitative observations of bearded pig population dynamics. The model was found to be accurate in predicting the timing of observed pig eruptions, and robust in that model results were unaffected by moderate variation in parameter values. There was insufficient quantitative data to obtain precise predictions of fatness and abundance, but qualitative insights about the effects of the size and timing of fruiting events on pig abundance were obtained. The results showed that a single fruiting peak will not produce a bearded pig eruption, no matter how large the fruiting event is, because the duration of the fruiting is too short to allow exponential growth of the population. Consecutive masting events are necessary for an eruption, because if events are separated by more than 1 year, the population will decline to its minimum fatness and abundance levels. It is also necessary for at least one of the fruiting events in a consecutive sequence to be a large event, as consecutive small fruiting events do not increase the fatness enough to cause an eruption. These insights help to explain and predict the effects of changes in mast fruiting patterns on bearded pig populations, such as the predicted increase in frequency and reduction in size of masting fruiting events as a result of climate change.     

Demography, Hunting Ecology, and Pathogen Exposure of Domestic Dogs in the Isoso of Bolivia

Abstract:  Disease is increasingly recognized as a threat to the conservation of wildlife, and in many cases the source of disease outbreaks in wild carnivores is the domestic dog. For disease to spill over from a domestic to a wild population, three conditions must be satisfied: susceptibility of the wild species, presence of the disease agent in the domestic population, and contact between the two populations of interest. We investigated the potential for disease spillover from the domestic dog population to the wild carnivore population in the Isoso of Bolivia, an area of tropical dry forest contiguous with a national park. Using questionnaires and discussions with residents, we gathered data on the demography of dogs in the Isoso, including adult and neonatal mortality, litter size, and hunting frequency. We analyzed a large data set containing self-recorded information on hunting in various communities of the Isoso to determine the extent of dog participation in hunting and the duration of hunting trips. Finally, we took blood samples from dogs in the Isoso for a serosurvey of common canine pathogens. More than 95% of dogs had positive titers to canine distemper virus and canine parvovirus. There was also a high seroprevalence in dogs for other pathogens, a high population turnover of dogs (which may allow diseases to be maintained endemically), and frequent opportunities for contact between domestic and wild carnivores. Based on our results and the susceptibility of wild species previously reported in the literature, domestic dogs represent a disease risk for wildlife in the Bolivian Isoso.     

Cryptic herbivores mediate the strength and form of ungulate impacts on a long-lived savanna tree

Plant populations are regulated by a diverse array of herbivores that impose demographic filters throughout their life cycle. Few studies, however, simultaneously quantify the impacts of multiple herbivore guilds on the lifetime performance or population growth rate of plants. In African savannas, large ungulates (such as elephants) are widely regarded as important drivers of woody plant population dynamics, while the potential impacts of smaller, more cryptic herbivores (such as rodents) have largely been ignored. We combined a large-scale ungulate exclusion experiment with a five-year manipulation of rodent densities to quantify the impacts of three herbivore guilds (wild ungulates, domestic cattle, and rodents) on all life stages of a widespread savanna tree. We utilized demographic modeling to reveal the overall role of each guild in regulating tree population dynamics, and to elucidate the importance of different demographic hurdles in driving population growth under contrasting consumer communities. We found that wild ungulates dramatically reduced population growth, shifting the population trajectory from increase to decline, but that the mechanisms driving these effects were strongly mediated by rodents. The impact of wild ungulates on population growth was predominantly driven by their negative effect on tree reproduction when rodents were excluded, and on adult tree survival when rodents were present. By limiting seedling survival, rodents also reduced population growth; however, this effect was strongly dampened where wild ungulates were present. We suggest that these complex interactions between disparate consumer guilds can have important consequences for the population demography of long-lived species, and that the effects of a single consumer group are often likely to vary dramatically depending on the larger community in which interactions are embedded.     

Estimating age from recapture data: integrating incremental growth measures with ancillary data to infer age-at-length

Estimating the age of individuals in wild populations can be of fundamental importance for answering ecological questions, modeling population demographics, and managing exploited or threatened species. Significant effort has been devoted to determining age through the use of growth annuli, secondary physical characteristics related to age, and growth models. Many species, however, either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age. Length-at-age models are well represented in the fisheries and other wildlife management literature. Many of these models overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual-specific random effects. Here, we describe hierarchical models in which growth curves vary as individual-specific stochastic processes, and we show how these models can be fit using capture-recapture data for animals of unknown age along with data for animals of known age. We combine these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. We illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models. The analysis provides the means of predicting crocodile age, given a single measurement of head length. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, reproductive maturity was estimated to be at nine years. These size benchmarks are believed to represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. The modeling approach that we present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.     

Modelling coral reef ecosystems with limited observational data

Ecosystem models represent potentially powerful tools for coral reef ecosystem managers. They can provide insight into ecosystem dynamics not achievable through alternative means allowing coral reef managers to assess the potential outcome of any given management decision. One of the main limitations in the applicability of ecosystem models is that they often require detailed empirical data and this can restrict their applicability to ecosystems that are either currently well studied or have the resources available to collect the required data. This study describes the development of a coral reef ecosystem model that can be calibrated to an ecosystem with limited empirical data. Based on the assumption that coral reef ecological structure is generic across all tropical coral reefs and that the magnitude of the interactions between ecological components is reef specific, the dynamics of the ecosystem can be replicated based on limited empirical data. The model successfully replicated the dynamics of three individual reef systems including an inshore and oceanic reef within the Great Barrier Reef and a Caribbean reef system. It highlighted the importance of understanding the specific dynamics of a given reef and that a positive management intervention in one system may result in a negative outcome for another. The model was also used to assess the importance of various interactions within coral reef ecosystems. It identified the interactions between hard corals and other non-algal benthic components as being an important (but currently understudied) facet of coral reef ecology. The development of this modelling approach provides access to ecosystem modelling tools for coral reef managers previously excluded due to a lack of resources or technical expertise.     

Demographic Models and Reality in Reintroductions: Persian Fallow Deer in Israel

Abstract:  Because most reintroduced species are rare, data on their dynamics are scarce. Consequently, reintroduction programs often rely on data from other species or captive populations to project the performance of the reintroduced population in the wild. We compared the reproductive success and survival of a Persian fallow deer ( Dama mesopotamica ) population reintroduced in Israel over the first 5 years of the project with the survival and reproduction parameters estimated while planning the reintroduction. In addition, we compared the actual growth of the wild population with the growth originally projected by a computer model in the original reintroduction program. We monitored 74 radio-collared individuals (57 females and 17 males) released semiannually 1996–2001. Survival during the first year after release was lower than later years (0.90 and 0.82 versus 0.95 and 0.88, for females and males, respectively). Such an impact was not anticipated in the original plan, but overall survival was higher than originally projected. As assumed in the reintroduction program, reproductive success improved significantly with time since release and overall, was higher than expected. The mean number of animals released annually was lower than planned. Overall, the growth of the reintroduced population was slower than projected, but the deviation was close to confidence limits and the pattern similar. After 5 years it appears that the original time frame of 8–10 years for project completion can be met or at worst will cause a 1-year delay. Over the short term of 5 years, projection models in reintroduction programs are useful tools for assessing the sustained use of the breeding core, depicting the dynamics of the population in the wild, providing a relatively accurate time frame for the successful completion of the project, and assessing project success.     

Hunting for Sustainability in Tropical Secondary Forests

Abstract:  The interaction between land-use change and the sustainability of hunting is poorly understood but is critical for sustaining hunted vertebrate populations and a protein supply for the rural poor. We investigated sustainability of hunting in an Amazonian landscape mosaic, where a small human population had access to large areas of both primary and secondary forest. Harvestable production of mammals and birds was calculated from density estimates. We compared production with offtake from three villages and used catch-per-unit-effort as an independent measure of prey abundance. Most species were hunted unsustainably in primary forest, leading to local depletion of the largest primates and birds. The estimated sustainable supply of wild meat was higher for primary (39 kg · km⁻²· yr⁻¹) than secondary forest (22 kg · km⁻²· yr⁻¹) because four species were absent and three species at low abundance in secondary forests. Production of three disturbance-tolerant mammal species was 3 times higher in secondary than in primary forest, but hunting led to overexploitation of one species. Our data suggest that an average Amazonian smallholder would require ≥3.1 km² of secondary regrowth to ensure a sustainable harvest of forest vertebrates. We conclude that secondary forests can sustainably provide only 2% of the required protein intake of Amazonian smallholders and are unlikely to be sufficient for sustainable hunting in other tropical forest regions.