Search

Remote aerial sensing provides a non‐invasive, large geographical‐scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mitigate this manual image processing requirement. The implementation of AI methods, however, has several challenges: (1) imbalanced (i.e., long‐tailed) data distribution, (2) annotation uncertainty in categorization, and (3) dataset discrepancies across different study sites. Here we use aerial imagery data of waterbirds around Cape Cod and Lake Michigan in the United States to examine how these challenges limit avian recognition performance. We review existing solutions and demonstrate as use cases how methods like Label Distribution Aware Marginal Loss with Deferred Re‐Weighting, hierarchical classification, and FixMatch address the three challenges. We also present a new approach to tackle the annotation uncertainty challenge using a Soft‐fine Pseudo‐Label methodology. Finally, we aim with this paper to increase awareness in the ecological remote sensing community of these challenges and bridge the gap between ecological applications and state‐of‐the‐art computer science, thereby opening new doors to future research. [ABSTRACT FROM AUTHOR]

In ecological and conservation studies, responsible researchers strive to obtain rich data while minimizing disturbance to wildlife and ecosystems. We assessed if samples collected noninvasively can be used for faecal microbiome research, comparing microbiota of noninvasively collected faecal samples to those collected from trapped common cranes at the same sites over the same periods. We found significant differences in faecal microbial composition (alpha and beta diversity), which likely did not result from noninvasive sample exposure to soil contaminants, as assessed by comparing bacterial oxygen use profiles. Differences might result from trapped birds' exposure to sedatives or stress. We conclude that if all samples are collected in the same manner, comparative analyses are valid, and noninvasive sampling may better represent host faecal microbiota because there are no trapping effects. Experiments with fresh and delayed sample collection can elucidate effects of environmental exposures on microbiota. Further, controlled tests of stressing or sedation may unravel how trapping affects wildlife microbiota. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a novel method for classifying and computing the frequencies of movement modes of intraspecific and interspecific dyads, focusing in particular on distance‐mediated approach, retreat, following and side‐by‐side movement modes.Besides distance, other factors such as time of day, season, sex or age can be included in the analysis to assess whether they cause frequencies of movement modes to deviate from random. By subdividing the data according to selected factors, our method allows us to identify those responsible for (or correlated with) significant differences in the behaviour of dyadic pairs.We demonstrate and validate our method using both simulated and empirical data. Our simulated data were obtained from a relative‐motion, biased random‐walk (RM‐BRW) model with attraction and repulsion components. Our empirical data were GPS relocation data collected from African elephants in Etosha National Park, Namibia. The simulated data were primarily used to validate our method while the empirical data were used to illustrate the types of behavioural assessment that our methodology reveals.Our method facilitates automated, observer‐bias‐free analysis of the locomotive interactions of dyads using GPS relocation data, which are becoming increasingly ubiquitous as telemetry and related technologies improve. It should open up a whole new vista of behavioural‐interaction type analyses to movement and behavioural ecologists. [ABSTRACT FROM AUTHOR]

Human activities shape resources available to wild animals, impacting diet and probably altering their microbiota and overall health. We examined drivers shaping microbiota profiles of common cranes (Grus grus) in agricultural habitats by comparing gut microbiota and crane movement patterns (GPS‐tracking) over three periods of their migratory cycle, and by analysing the effect of artificially supplemented food provided as part of a crane‐agriculture management programme. We sampled faecal droppings in Russia (nonsupplemented, premigration) and in Israel in late autumn (nonsupplemented, postmigration) and winter (supplemented and nonsupplemented, wintering). As supplemented food is typically homogenous, we predicted lower microbiota diversity and different composition in birds relying on supplementary feeding. We did not observe changes in microbial diversity with food supplementation, as diversity differed only in samples from nonsupplemented wintering sites. However, both food supplementation and season affected bacterial community composition and led to increased abundance of specific genera (mostly Firmicutes). Cranes from the nonsupplemented groups spent most of their time in agricultural fields, probably feeding on residual grain when available, while food‐supplemented cranes spent most of their time at the feeding station. Thus, nonsupplemented and food‐supplemented diets probably diverge only in winter, when crop rotation and depletion of anthropogenic resources may lead to a more variable diet in nonsupplemented sites. Our results support the role of diet in structuring bacterial communities and show that they undergo both seasonal and human‐induced shifts. Movement analyses provide important clues regarding host diet and behaviour towards understanding how human‐induced changes shape the gut microbiota in wild animals. [ABSTRACT FROM AUTHOR]

Animals generally benefit from their gastrointestinal microbiome, but the factors that influence the composition and dynamics of their microbiota remain poorly understood. Studies of nonmodel host species can illuminate how microbiota and their hosts interact in natural environments. We investigated the role of migratory behaviour in shaping the gut microbiota of free‐ranging barn swallows (Hirundo rustica) by studying co‐occurring migrant and resident subspecies sampled during the autumn migration at a migratory bottleneck. We found that within‐host microbial richness (α‐diversity) was similar between migrant and resident microbial communities. In contrast, we found that microbial communities (β‐diversity) were significantly different between groups regarding both microbes present and their relative abundances. Compositional differences were found for 36 bacterial genera, with 27 exhibiting greater abundance in migrants and nine exhibiting greater abundance in residents. There was heightened abundance of Mycoplasma spp. and Corynebacterium spp. in migrants, a pattern shared by other studies of migratory species. Screens for key regional pathogens revealed that neither residents nor migrants carried avian influenza viruses and Newcastle disease virus, suggesting that the status of these diseases did not underlie observed differences in microbiome composition. Furthermore, the prevalence and abundance of Salmonella spp., as determined from microbiome data and cultural assays, were both low and similar across the groups. Overall, our results indicate that microbial composition differs between migratory and resident barn swallows, even when they are conspecific and sympatrically occurring. Differences in host origins (breeding sites) may result in microbial community divergence, and varied behaviours throughout the annual cycle (e.g., migration) could further differentiate compositional structure as it relates to functional needs. [ABSTRACT FROM AUTHOR]

The behavioural ecology of host species is likely to affect their microbial communities, because host sex, diet, physiology, and movement behaviour could all potentially influence their microbiota. We studied a wild population of barn owls (Tyto alba) and collected data on their microbiota, movement, diet, size, coloration, and reproduction. The composition of bacterial species differed by the sex of the host and female owls had more diverse bacterial communities than their male counterparts. The abundance of two families of bacteria, Actinomycetaceae and Lactobacillaceae, also varied between the sexes, potentially as a result of sex differences in hormones and immunological function, as has previously been found with Lactobacillaceae in the microbiota of mice. Male and female owls did not differ in the prey they brought to the nest, which suggests that dietary differences are unlikely to underlie the differences in their microbiota. The movement behaviour of the owls was associated with the host microbiota in both males and females because owls that moved further from their nest each day had more diverse bacterial communities than owls that stayed closer to their nests. This novel result suggests that the movement ecology of hosts can impact their microbiota, potentially on the basis of their differential encounters with new bacterial species as the hosts move and forage across the landscape. Overall, we found that many aspects of the microbial community are correlated with the behavioural ecology of the host and that data on the microbiota can aid in generating new hypotheses about host behaviour. [ABSTRACT FROM AUTHOR]

ABSTRACT: Environmentally transmitted diseases are comparatively poorly understood and managed, and their ecology is particularly understudied. Here we identify challenges of studying environmental transmission and persistence with a six‐sided interdisciplinary review of the biology of anthrax (Bacillus anthracis). Anthrax is a zoonotic disease capable of maintaining infectious spore banks in soil for decades (or even potentially centuries), and the mechanisms of its environmental persistence have been the topic of significant research and controversy. Where anthrax is endemic, it plays an important ecological role, shaping the dynamics of entire herbivore communities. The complex eco‐epidemiology of anthrax, and the mysterious biology of Bacillus anthracis during its environmental stage, have necessitated an interdisciplinary approach to pathogen research. Here, we illustrate different disciplinary perspectives through key advances made by researchers working in Etosha National Park, a long‐term ecological research site in Namibia that has exemplified the complexities of the enzootic process of anthrax over decades of surveillance. In Etosha, the role of scavengers and alternative routes (waterborne transmission and flies) has proved unimportant relative to the long‐term persistence of anthrax spores in soil and their infection of herbivore hosts. Carcass deposition facilitates green‐ups of vegetation to attract herbivores, potentially facilitated by the role of anthrax spores in the rhizosphere. The underlying seasonal pattern of vegetation, and herbivores' immune and behavioural responses to anthrax risk, interact to produce regular ‘anthrax seasons’ that appear to be a stable feature of the Etosha ecosystem. Through the lens of microbiologists, geneticists, immunologists, ecologists, epidemiologists, and clinicians, we discuss how anthrax dynamics are shaped at the smallest scale by population genetics and interactions within the bacterial communities up to the broadest scales of ecosystem structure. We illustrate the benefits and challenges of this interdisciplinary approach to disease ecology, and suggest ways anthrax might offer insights into the biology of other important pathogens. Bacillus anthracis, and the more recently emerged Bacillus cereus biovar anthracis, share key features with other environmentally transmitted pathogens, including several zoonoses and panzootics of special interest for global health and conservation efforts. Understanding the dynamics of anthrax, and developing interdisciplinary research programs that explore environmental persistence, is a critical step forward for understanding these emerging threats. [ABSTRACT FROM AUTHOR]

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviours, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesise the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions, expanding our understanding of host-pathogen dynamics and improving our predictive capacity for wildlife and even human diseases. [ABSTRACT FROM AUTHOR]

Abstract: Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management. [ABSTRACT FROM AUTHOR]

1. Ecologists have traditionally focused on herbivore carcasses as study models in scavenging research. However, some observations of scavengers avoiding feeding on carnivore carrion suggest that different types of carrion may lead to differential pressures. Untested assumptions about carrion produced at different trophic levels could therefore lead ecologists to overlook important evolutionary processes and their ecological consequences. 2. Our general goal was to investigate the use of mammalian carnivore carrion by vertebrate scavengers. In particular, we aimed to test the hypothesis that carnivore carcasses are avoided by other carnivores, especially at the intraspecific level, most likely to reduce exposure to parasitism. 3. We take a three-pronged approach to study this principle by: (i) providing data from field experiments, (ii) carrying out evolutionary simulations of carnivore scavenging strategies under risks of parasitic infection and (iii) conducting a literature-review to test two predictions regarding parasite life-history strategies. 4. First, our field experiments showed that the mean number of species observed feeding at carcasses and the percentage of consumed carrion biomass were substantially higher at herbivore carcasses than at carnivore carcasses. This occurred even though the number of scavenger species visiting carcasses and the time needed by scavengers to detect carcasses were similar between both types of carcasses. In addition, we did not observe cannibalism. Second, our evolutionary simulations demonstrated that a risk of parasite transmission leads to the evolution of scavengers with generally low cannibalistic tendencies and that the emergence of cannibalism-avoidance behaviour depends strongly on assumptions about parasitebased mortality rates. Third, our literature review indicated that parasite species potentially able to follow a carnivore-carnivore indirect cycle, as well as those transmitted via meat consumption, are rare in our study system. 5. Our findings support the existence of a novel coevolutionary relation between carnivores and their parasites and suggest that carnivore and herbivore carcasses play very different roles in food webs and ecosystems. [ABSTRACT FROM AUTHOR]

Partial seasonal migration is ubiquitous in many species. We documented this phenomenon in plains zebra (Equus burchelli) in Etosha National Park, Namibia (ENP), and provided a cost–benefit analysis as it relates to the spatial distribution of water, vegetation, and endemic anthrax. This analysis draws upon two years of ENP zebra movement data that reveal two sub-populations: migrators and non-migrators. Migrators are shown to be behaviorally dominant in the way they utilize space and use water holes. We raise the possibility that the co-existence of these two groups reflects an evolutionary process, and the size of each group maintains evolutionary equilibrium. [ABSTRACT FROM AUTHOR]

Population viability analysis (PVA) is used to assess the probability that a biological population will persist for a specified period of time. Such models are typically cast as Markov processes that may include age, stage, sex and metapopulation structures, density-dependence and ecological interaction processes. They may also include harvesting, stocking, and thresholds that trigger interventions. Here we present a PVA web app that includes extensible user-selected options. Specifically, this PVA web app allows for the specification of one to ten age classes, one or two sexes, single population or metapopulation configurations with 2 or 3 subpopulations, as well as density-dependent settings for inducing region-specific carrying capacities. Movement among subpopulations can be influenced by age, metapopulation connectivity, and attractivity of regions based on the relative fitness of the youngest age classes in each region. Simulations can be carried out deterministically or stochastically, with a user-specified combination of demographic and environmental processes. This PVA web app is freely available at for running directly on any browser and device. It is easily modified by users familiar with the NovaModeler Software Platform. [ABSTRACT FROM AUTHOR]

Few studies have examined host-pathogen interactions in wildlife from an immunological perspective, particularly in the context of seasonal and longitudinal dynamics. In addition, though most ecological immunology studies employ serological antibody assays, endpoint titre determination is usually based on subjective criteria and needs to be made more objective., Despite the fact that anthrax is an ancient and emerging zoonotic infectious disease found world-wide, its natural ecology is not well understood. In particular, little is known about the adaptive immune responses of wild herbivore hosts against Bacillus anthracis., Working in the natural anthrax system of Etosha National Park, Namibia, we collected 154 serum samples from plains zebra ( Equus quagga), 21 from springbok ( Antidorcas marsupialis) and 45 from African elephants ( Loxodonta africana) over 2-3 years, resampling individuals when possible for seasonal and longitudinal comparisons. We used enzyme-linked immunosorbent assays to measure anti-anthrax antibody titres and developed three increasingly conservative models to determine endpoint titres with more rigourous, objective mensuration., Between 52 and 87% of zebra, 0-15% of springbok and 3-52% of elephants had measurable anti-anthrax antibody titres, depending on the model used. While the ability of elephants and springbok to mount anti-anthrax adaptive immune responses is still equivocal, our results indicate that zebra in ENP often survive sublethal anthrax infections, encounter most B. anthracis in the wet season and can partially booster their immunity to B. anthracis., Thus, rather than being solely a lethal disease, anthrax often occurs as a sublethal infection in some susceptible hosts. Though we found that adaptive immunity to anthrax wanes rapidly, subsequent and frequent sublethal B. anthracis infections cause maturation of anti-anthrax immunity. By triggering host immune responses, these common sublethal infections may act as immunomodulators and affect population dynamics through indirect immunological and co-infection effects., In addition, with our three endpoint titre models, we introduce more mensuration rigour into serological antibody assays, even under the often-restrictive conditions that come with adapting laboratory immunology methods to wild systems. With these methods, we identified significantly more zebras responding immunologically to anthrax than have previous studies using less comprehensive titre analyses. [ABSTRACT FROM AUTHOR]

Distance sampling is widely used to estimate the abundance or density of wildlife populations. Methods to estimate wildlife mortality rates have developed largely independently from distance sampling, despite the conceptual similarities between estimation of cumulative mortality and the population density of living animals. Conventional distance sampling analyses rely on the assumption that animals are distributed uniformly with respect to transects and thus require randomised placement of transects during survey design. Because mortality events are rare, however, it is often not possible to obtain precise estimates in this way without infeasible levels of effort. A great deal of wildlife data, including mortality data, are available via road-based surveys. Interpreting these data in a distance sampling framework requires accounting for the non-uniformity of sampling. In addition, analyses of opportunistic mortality data must account for the decline in carcass detectability through time. We develop several extensions to distance sampling theory to address these problems., We build mortality estimators in a hierarchical framework that integrates animal movement data, surveillance effort data and motion-sensor camera trap data, respectively, to relax the uniformity assumption, account for spatiotemporal variation in surveillance effort and explicitly model carcass detection and disappearance as competing ongoing processes., Analysis of simulated data showed that our estimators were unbiased and that their confidence intervals had good coverage., We also illustrate our approach on opportunistic carcass surveillance data acquired in 2010 during an anthrax outbreak in the plains zebra of Etosha National Park, Namibia., The methods developed here will allow researchers and managers to infer mortality rates from opportunistic surveillance data. [ABSTRACT FROM AUTHOR]

The unsustainable harvest of wildlife is a major threat to global biodiversity and to the millions of people who depend on wildlife for food and income. Past research has called attention to the fact that commonly used methods to evaluate the sustainability of wildlife hunting perform poorly, yet these methods remain in popular use today. Here, we conduct a systematic review of empirical sustainability assessments to quantify the use of sustainability indicators in the scientific literature and highlight associations between analytical methods and their outcomes. We find that indicator type, continent of study, species body mass, taxonomic group and socio-economic status of study site are important predictors of the probability of reported sustainability. The most common measures of sustainability include population growth models, the Robinson & Redford (1991) model and population trends through time. Indicators relying on population-specific biological data are most often used in North America and Europe, while cruder estimates are more often used in Africa, Latin America and Oceania. Our results highlight both the uncertainty and lack of uniformity in sustainability science. Given our urgent need to conserve both wildlife and the food security of rural peoples around the world, improvements in sustainability indicators are of utmost importance. [ABSTRACT FROM AUTHOR]

Many studies of mammalian herbivores have employed remotely sensed vegetation greenness, in the form of Normalized Difference Vegetation Index (NDVI) as a proxy for forage quality. The assumption that reflected greenness represents forage quality often goes untested, and limited data exist on the relationships between remotely sensed and traditional forage nutrient indicators. We provide the first study connecting NDVI and forage nutrient indicators within a free-ranging African herbivore ecosystem. We examined the relationships between fecal nutrient levels (nitrogen and phosphorus), forage nutrient levels, body condition, and NDVI for African buffalo ( Syncerus caffer) in a South African savanna ecosystem over a 2-year period (2001 and 2002). We used an information-theoretic approach to rank models of fecal nitrogen (Nf) and phosphorus (Pf) as functions of geology, season, and NDVI in each year separately. For each year, the highest ranked models for Nf accounted for 61% and 65% of the observed variance, and these models included geology, season, and NDVI. The top-ranked model for Pf in 2001, although capturing 54% of the variability, did not include NDVI. In 2002, we could not identify a top ranking model for phosphorus (i.e., all models were within 2 AIC c of each other). Body condition was most highly correlated ( $R_{adj}^{2} = 0.75$; P ≤ 0.001) with NDVI at a 1 month time lag and with Nf at a 3 months time lag ( $R_{adj}^{2} = 0.65$; P ≤ 0.001), but was not significantly correlated with Pf. Our findings suggest that NDVI can be used to index nitrogen content of forage and is correlated with improved body condition in African buffalo. Thus, NDVI provides a useful means to assess forage quality where crude protein is a limiting resource. We found that NDVI accounted for more than a seasonal effect, and in a system where standing biomass may be high but of low quality, understanding available nutrients is useful for management. © 2012 The Wildlife Society. [ABSTRACT FROM AUTHOR]

The dominant differential equation paradigm for modeling the population dynamics of species interacting in the framework of a food web retains at its core the basic prey-predator and competition models formulated by Alfred J. Lotka (1880-1945) and Vito Volterra (1860-1940) nearly nine decades ago. This paradigm lacks a trophic-level-independent formulation of population growth leading to ambiguities in how to treat populations that are simultaneously both prey and predator. Also, this paradigm does not fundamentally include inertial (i.e., change resisting) processes needed to account for the response of populations to fluctuating resource environments. Here I present an approach that corrects both these deficits and provides a unified framework for accounting for biomass transformation in food webs that include both live and dead components of all species in the system. This biomass transformation formulation (BTW) allows for a unified treatment of webs that include consumers of both live and dead material-both carnivores and carcasivores, herbivores and detritivores-and incorporates scavengers, parasites, and other neglected food web consumption categories in a coherent manner. I trace how BTW is an outgrowth of the metaphysiological growth modeling paradigm and I provide a general compact formulation of BTW in terms of a three-variable differential equation formulation for each species in the food web: viz., live biomass, dead biomass, and a food-intake-related measure called deficit-stress. I then illustrate the application of this new paradigm to provide insights into two-species competition in variable environments and discuss application of BTW to food webs that incorporate parasites and pathogens. [ABSTRACT FROM AUTHOR]

Summary 1. Seasonality of rainfall can exert a strong influence on animal condition and on host-parasite interactions. The body condition of ruminants fluctuates seasonally in response to changes in energy requirements, foraging patterns and resource availability, and seasonal variation in parasite infections may further alter ruminant body condition. 2. This study disentangles the effects of rainfall and gastrointestinal parasite infections on springbok ( Antidorcas marsupialis) body condition and determines how these factors vary among demographic groups. 3. Using data from four years and three study areas, we investigated (i) the influence of rainfall variation, demographic factors and parasite interactions on parasite prevalence or infection intensity, (ii) whether parasitism or rainfall is a more important predictor of springbok body condition and (iii) how parasitism and condition vary among study areas along a rainfall gradient. 4. We found that increased parasite intensity is associated with reduced body condition only for adult females. For all other demographic groups, body condition was significantly related to prior rainfall and not to parasitism. Rainfall lagged by two months had a positive effect on body condition. 5. Adult females showed evidence of a 'periparturient rise' in parasite intensity and had higher parasite intensity and lower body condition than adult males after parturition and during early lactation. After juveniles were weaned, adult females had lower parasite intensity than adult males. Sex differences in parasitism and condition may be due to differences between adult females and males in the seasonal timing of reproductive effort and its effects on host immunity, as well as documented sex differences in vulnerability to predation. 6. Our results highlight that parasites and the environment can synergistically affect host populations, but that these interactions might be masked by their interwoven relationships, their differential impacts on demographic groups, and the different time-scales at which they operate. [ABSTRACT FROM AUTHOR]

Understanding the environmental factors influencing animal movements is fundamental to theoretical and applied research in the field of movement ecology. Studies relating fine-scale movement paths to spatiotemporally structured landscape data, such as vegetation productivity or human activity, are particularly lacking despite the obvious importance of such information to understanding drivers of animal movement. In part, this may be because few approaches provide the sophistication to characterize the complexity of movement behavior and relate it to diverse, varying environmental stimuli. We overcame this hurdle by applying, for the first time to an ecological question, a finite impulse-response signal-filtering approach to identify human and natural environmental drivers of movements of 13 free-ranging African elephants (Loxodonta africana) from distinct social groups collected over seven years. A minimum mean-square error (MMSE) estimation criterion allowed comparison of the predictive power of landscape and ecological model inputs. We showed that a filter combining vegetation dynamics, human and physical landscape features, and previous movement outperformed simpler filter structures, indicating the importance of both dynamic and static landscape features, as well as habit, on movement decisions taken by elephants. Elephant responses to vegetation productivity indices were not uniform in time or space, indicating that elephant foraging strategies are more complex than simply gravitation toward areas of high productivity. Predictions were most frequently inaccurate outside protected area boundaries near human settlements, suggesting that human activity disrupts typical elephant movement behavior. Successful management strategies at the human-elephant interface, therefore, are likely to be context specific and dynamic. Signal processing provides a promising approach for elucidating environmental factors that drive animal movements over large time and spatial scales. [ABSTRACT FROM AUTHOR]

Surveys using conservation detection dogs have grown increasingly popular as an efficient means to gather monitoring data, particularly for elusive and low-density species such as carnivores. Working with dogs can greatly increase the area surveyed for wildlife and the detection rate of survey targets. Due to the confounding effects of scent dispersion and dog movement, however, it can be difficult to estimate the area searched in a survey. Additionally, although detection dogs have been used in studies under a wide range of air temperature, humidity, and wind conditions, little research has examined how environmental factors affect detection dogs' effectiveness for wildlife surveys. Between 2003 and 2005, we trained 2 dogs to assist us with surveys for mammalian carnivore scats in northern California. We conducted controlled search trials to assess how the dogs' scat detection rates were affected by the distance of scats from the transect search line, as well as variation in six environmental factors. Both dogs detected >75% of scats located within 10 m, and the dogs' detection rates decreased with increasing distance of scats from the transect line. Among environmental factors, precipitation was the most important variable explaining variation in scat detection rates for both dogs. Precipitation likely degrades or removes scats from the landscape over time, and detection rates increase as scat begins to accumulate following the last substantial (>5 mm) rain event of the year. If scat accumulation is not controlled for in ecosystems with a strong seasonal pattern of rainfall, it could lead to considerable bias in study results. We recommend that researchers report the conditions under which conservation detection dog surveys took place and analyze how detection rates vary as a function of distance, temperature, precipitation, humidity, wind, and other locally important environmental factors. [ABSTRACT FROM AUTHOR]

High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time-frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions. We introduce a novel movement model with time-varying parameters to study these methods in an animal movement context. Simulation studies show that the spectral signature given by these methods provides a useful approach for statistically detecting and characterizing temporal dependency in animal movement data. In addition, our simulations provide a connection between the spectral signatures observed in empirical data with null hypotheses about expected animal activity. Our analyses also show that there is not a specific one-to-one relationship between the spectral signatures and behavior type and that departures from the anticipated signatures are also informative. Box plots of net displacement arranged by time of day and conditioned on common spectral properties can help interpret the spectral signatures of empirical data. The first case study is based on the movement trajectory of a lion (Panthera leo) that shows several characteristic daily activity sequences, including an active-rest cycle that is correlated with moonlight brightness. A second example based on six pairs of African buffalo (Syncerus caffer) illustrates the use of wavelet coherency to show that their movements synchronize when they are within ∼1 km of each other, even when individual movement was best described as an uncorrelated random walk, providing an important spatial baseline of movement synchrony and suggesting that local behavioral cues play a strong role in driving movement patterns. We conclude with a discussion about the role these methods may have in guiding appropriately flexible probabilistic models connecting movement with biotic and abiotic covariates. [ABSTRACT FROM AUTHOR]

Knowledge of the range, behavior, and feeding habits of large carnivores is fundamental to their successful conservation. Traditionally, the best method to obtain feeding data is through continuous observation, which is not always feasible. Reliable automated methods are needed to obtain sample sizes sufficient for statistical inference. Identification of large carnivore kill sites using Global Positioning System (GPS) data is gaining popularity. We assessed performance of generalized linear regression models (GLM) versus classification trees (CT) in a multipredator, multiprey African savanna ecosystem. We applied GLMs and CTs to various combinations of distance-traveled data, cluster durations, and environmental factors to predict occurrence of 234 female African lion (Panthera leo) kill sites from 1,477 investigated GPS clusters. Ratio of distance moved 24 hours before versus 24 hours after a cluster was the most important predictor variable in both GLM and CT analysis. In all cases, GLMs outperformed our cost-complexity-pruned CTs in their discriminative ability to separate kill from nonkill sites. Generalized linear models provided a good framework for kill-site identification that incorporates a hierarchal ordering of cluster investigation and measures to assess trade-offs between classification accuracy and time constraints. Implementation of GLMs within an adaptive sampling framework can considerably increase efficiency of locating kill sites, providing a cost-effective method for increasing sample sizes of kill data. [ABSTRACT FROM AUTHOR]

Abstract. Recent developments of automated methods for monitoring animal movement, e.g., global positioning systems (GPS) technology, yield high-resolution spatiotemporal data. To gain insights into the processes creating movement patterns, we present two new techniques for extracting information from these data on repeated visits to a particular site or patch ("recursions"). Identification of such patches and quantification of recursion pathways, when combined with patch-related ecological data, should contribute to our understanding of the habitat requirements of large herbivores, of factors governing their space-use patterns, and their interactions with the ecosystem. We begin by presenting output from a simple spatial model that simulates movements of large-herbivore groups based on minimal parameters: resource availability and rates of resource recovery after a local depletion. We then present the details of our new techniques of analyses (recursion analysis and circle analysis) and apply them to data generated by our model, as well as two sets of empirical data on movements of African buffalo (Syncerus caffer): the first collected in Klaserie Private Nature Reserve and the second in Kruger National Park, South Africa. Our recursion analyses of model outputs provide us with a basis for inferring aspects of the processes governing the production. of buffalo recursion patterns, particularly the potential influence of resource recovery rate. Although the focus of our simulations was a comparison of movement patterns produced by different resource recovery rates, we conclude our paper with a comprehensive discussion of how recursion analyses can be used when appropriate ecological data are available to elucidate various factors influencing movement. Inter alia, these include the various limiting and preferred resources, parasites, and topographical and landscape factors. [ABSTRACT FROM AUTHOR]

A central problem in population ecology is to use time series data to estimate the form of density dependence in the per capita growth rate (pgr). This is often accomplished with phenomenological models such as the theta-Ricker or generalized Beverton-Holt. Using the theta-Ricker model as a simple but flexible description of density dependence, we apply theory and simulations to show how multimodality and ridges in the likelihood surface can emerge even in the absence of model misspecification or observation error. The message for model fitting of real data is to consider the likelihood surface in detail, check whether the best- fit model is located on a likelihood ridge and, if so, evaluate predictive differences of biologically plausible models along the ridge. We present a detailed analysis of a focal data set showing how multimodality and ridges emerge in practice for fits of several parametric models, including a state-space model with explicit accommodation of observation error. Best-fit models for these data are biologically dubious beyond the range of the data, and likelihood ratio confidence regions include a wide range of more biologically plausible models. We demonstrate the broad relevance of these findings by presenting analyses of 25 additional data sets spanning a wide range of taxa. The results here are relevant to information-theoretic and Bayesian methods, which also rely on likelihoods. Beyond presentation of best-fit models and confidence regions around individual parameters, effort toward understanding features of the likelihood surface will help ensure the most robust translation from statistical analysis to biological interpretation. [ABSTRACT FROM AUTHOR]

We used more than 10 years of data on buffalo herds in a Geographic Information System (GIS) of Klaserie Private Nature Reserve (KPNR) to examine ranging behavior and habitat selection at multiple temporal and geographic scales. We compared 3 methods of empirical home range estimation: minimum convex polygons (MCP); a fixed-kernel method; and a new local nearest-neighbor convex-huff construction method (LoCoH). For 3 herds over 5 years (1995-2000), the southern herd (SH) had the largest range, the focal study herd (FH) had the intermediate range, and the northern herd (NH) had the smallest range. The LoCoH method best-described the ranges because it accommodated user knowledge of known physical barriers, such as fences, whereas the MCP and kernel methods overestimated ranges. Short-term ranges of the FH over 9 years reveal that buffalo travel farther and range wider in the dry season than the wet. Habitat selection analyses on broad vegetation categories showed preference for Acacia shrub veld and Combretum-dominated woodlands. We found no significant selection of habitat at a fine geographic and temporal interval using the remotely sensed normalized difference vegetation index (NDVI), but the index was correlated to ranging behavior at a larger geographic scale. We found that buffalo selected areas within 1 km of water sources, and an isopleth analysis using the new LoCoH method showed preference for riverine areas in both seasons. This suggests that buffalo preferentially select for areas near water, but they may range farther in the dry season for higher-quality food. As KPNR has a higher density of water than the neighboring Kruger National Park (KNP), this study provides a comparison of buffalo response to water availability in a smaller reserve and important information to managing the buffalo population as part of the larger Greater Kruger Management Area (GKMA). [ABSTRACT FROM AUTHOR]

The introduction of chronic, infectious diseases by colonizing populations (invasive or reintroduced) is a serious hazard in conservation biology, threatening the original host and other spillover species. Most research on spatial invasion of diseases has pertained to established host populations, either at steady state or fluctuating through time. Within a colonizing population, however, the spread of disease may be influenced by the expansion process of the population itself. Here we explore the simultaneous expansion of a colonizing population and a chronic, nonlethal disease introduced with it, describing basic patterns in homogeneous and structured landscapes and discussing implications for disease management. We describe expected outcomes of such introductions for three qualitatively distinct cases, depending on the relative velocities at which the population and epidemic expand. (1) If transmissibility is low the disease cannot be sustained, although it may first expand its range somewhat around the point of introduction. (2) If transmissibility is moderate but the wave-front velocity for the population, vp, is higher than that for the disease, Vd, the disease wave front lags behind that of the population. (3) A highly transmissible disease, with vd > vp, will invade sufficiently rapidly to track the spread of the host. To test these elementary theoretical predictions, we simulated disease outbreaks in a spatially structured host population occupying a real landscape. We used a spatially explicit, individual-based model of Persian fallow deer (Dama mesopotamica) reintroduced in northern Israel, considering a hypothetical introduction of bovine tuberculosis. Basic patterns of disease expansion in this realistic setting were similar to our conceptual predictions for homogeneous landscapes. Landscape heterogeneity, however, induced the establishment of population activity centers and disease foci within them, leading to jagged wave fronts and causing local variation in the relative velocities at which the population and epidemic expanded. Based on predictions from simple theory and simulations of managed outbreaks, we suggest that the relative velocities at which the population and epidemic expand have important implications for the impact of different management strategies. Recognizing which of our three general cases best describes a particular outbreak will aid in planning an efficient strategy to contain the disease. [ABSTRACT FROM AUTHOR]

The article presents a model-framed evaluation of elephant effects on tree and fire dynamics in African Savannas. Savannas occupy 60% of sub-Saharan Africa. They are typified by the coexistence of woody plants and grasses, with the relative proportions of each being influenced predominantly by water availability, fire, nutrients, herbivory, and people. There is a concern that high densities of elephants in southern Africa could lead to the overall reduction of other forms of biodiversity. The article provides a grid-based model of elephant-savanna dynamics. The model projects changes in height structure and spatial pattern of trees. The vegetation component of the model produces long-term tree-grass coexistence, and the emergent fire frequencies match those reported for southern African savannas. Including elephants in the savanna model had the expected effect of reducing woody plant cover, mainly via increased adult tree mortality, although at an elephant density of 1.0 elephant/ square kilometers, woody plants still persisted for over a century.

The epidemic potential of a disease is traditionally assessed using the basic reproductive number,R0. However, in populations with social or spatial structure a chronic disease is more likely to invade than an acute disease with the sameR0, because it persists longer within each group and allows for more host movement between groups. Acute diseases‘perceive’ a more structured host population, and it is more important to consider host population structure in analyses of these diseases. The probability of a pandemic does not arise independently from characteristics of either the host or disease, but rather from the interaction of host movement and disease recovery timescales. TheR* statistic, a group-level equivalent ofR0, is a better indicator of disease invasion in structured populations than the individual-levelR0. [ABSTRACT FROM AUTHOR]

We describe a new method for estimating the area of home ranges and constructing utilization distributions (UDs) from spatial data. We compare our method with bivariate kernel and α-hull methods, using both randomly distributed and highly aggregated data to test the accuracy of area estimates and UD isopleth construction. The data variously contain holes, corners, and corridors linking high use areas. Our method is based on taking the union of the minimum convex polygons (MCP) associated with the k−1 nearest neighbors of each point in the data and, as such, has one free parameter k. We propose a “minimum spurious hole covering” (MSHC) rule for selecting k and interpret its application in terms of type I and type II statistical errors. Our MSHC rule provides estimates within 12% of true area values for all 5 data sets, while kernel methods are worse in all cases: in one case overestimating area by a factor of 10 and in another case underestimating area by a factor of 50. Our method also constructs much better estimates for the density isopleths of the UDs than kernel methods. The α-hull method does not lead directly to the construction of isopleths and also does not always include all points in the constructed home range. Finally we demonstrate that kernel methods, unlike our method and the α-hull method, does not converges to the true area represented by the data as the number of data points increase. [ABSTRACT FROM AUTHOR]

Journal of Animal Ecology (2003) 72, 909–916 [ABSTRACT FROM AUTHOR]

The Greater Yellowstone Ecosystem in the northern Rocky Mountains provides the context for a natural experiment to investigate the response of consumers to resources with differing spatial and temporal dispersion regimes. Grey wolves ( Canis lupus) and human hunters both provide resource subsidies to scavengers by provisioning them with the remains of their kills. Carrion from hunter kills is highly aggregated in time and space whereas carrion from wolf kills is more dispersed in both time and space. We estimated the total amount of carrion consumed by each scavenger species at both wolf and hunter kills over 4 years. Species with large feeding radii [bald eagles ( Haliaeetus leucocephalus) and ravens ( Corvus corax)], defined as the area over which a consumer can efficiently locate and integrate resources, dominated consumption at the highly aggregated hunter kills whereas competitively dominant species [coyotes ( Canis latrans)] dominated at the more dispersed wolf kills. In addition, species diversity and the evenness of carrion consumption between scavengers was greater at wolf kills than at hunter kills while the total number of scavengers at hunter kills exceeded those at wolf kills. From a community perspective, the top–down effect of predation is likely to be stronger in the vicinity of highly aggregated resource pulses as species with large feeding radii switch to feeding on alternative prey once the resource pulse subsides. [ABSTRACT FROM AUTHOR]

At a landscape scale, the combined influence of biotic and abiotic factors may determine the distribution patterns of large herbivores in African savanna ecosystems. Herbivores foraging in these ecosystems may become nutritionally stressed during an annual dry season when both forage quality and quantity are reduced. Additionally, the locations of water sources may impose a landscape-scale constraint on dry-season herbivore distributions. We used logistic regression to analyze 13 years of aerial census data collected in the Kruger National Park (KNP), South Africa, and evaluated hypotheses regarding the relative influences that surface water, forage quality, and forage quantity exert on the dryseason, landscape-scale distribution patterns of eight herbivore species. Hypotheses regarding the degree of correlation between species' distributions and distance to water were developed using previous observations of species' relative water dependence. We also developed hypotheses regarding species' responses to the trade-off that may occur between surface-water constraints and nutritional requirements when either forage quality or quantity is reduced. In general, we expect an increase in species' mean distance to water as a result of individuals mitigating limitations in nutritional requirements (i.e., intake quality or quantity) by foraging farther from water. Our analyses suggest that the trade-off between nutritional requirements and surface-water constraints that species face varies according to the species' water dependence, size, and gut morphology. Of the four grazers considered in our analyses, waterbuck distributions appear to be constrained primarily by surfacewater availability. Distributions of buffalo, a large ruminant grazer, suggest that individuals face a trade-off between nutritional requirements and surface-water constraints when forage quantity is reduced. Alternatively, distributions of wildebeest, a smaller ruminant grazer, suggest that individuals face this trade-off when access to high-quality forage is limited. In comparison to buffalo and wildebeest, the strength of this trade-off is moderate for zebra, a nonruminant similar in size to wildebeest, when either forage quality or quantity is reduced. Distribution patterns for browsers are characterized by a weak relationship with distance to water, as expected for these relatively water-independent species. Population densities relative to forage quality confound exploration of this trade-off for mixed feeders. [ABSTRACT FROM AUTHOR]

The article discusses the application of stochastic metapopulation model to derive optimal management decisions for endangered species. It mentions the application of discrete-time Markov chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions. It notes that SDP is a powerful tool wherein it can give the exact optimal strategy for every landscape configuration and pattern of metapopulation occupancy.

Presents a study that proposed a metaphysiological model of biological population that includes a storage component in variable environments. Difference between a metaphysiological and demographic approach; Features of the metaphysiological storage model; Application of the model in a plant-like and herbivore-like population.

Presents a population model regarding the abruptness of ecological density dependence and the growth rate of populations among animals. Density dependence; Discrete-time population model; Evolutionary state strategy analysis.