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Canid species are highly adaptable, including to urban and peri-urban areas, where they can come into close contact with people. Understanding the mechanisms of wild canid population persistence in these areas is key to managing any negative impacts. The resource dispersion hypothesis predicts that animal density increases and home range size decreases as resource concentration increases, and may help to explain how canids are distributed in environments with an urban-natural gradient. In Australia, dingoes have adapted to human presence, sometimes living in close proximity to towns. Using a targeted camera trap survey and spatial capture-recapture models, we estimated spatial variation in the population density and detection rates of dingoes on Worimi Country in the Great Lakes region of the NSW coast. We tested whether dingo home range and population densities varied across a gradient of human population density, in a mixed-use landscape including, urban, peri-urban, and National Park environs. We found human population density to be a strong driver of dingo density (ranging from 0.025 to 0.433 dingoes/km2 across the natural-urban gradient), and to have a negative effect on dingo home range size. The spatial scale parameter changed depending on survey period, being smaller in the peak tourism period, when human population increases in the area, than in adjacent survey periods, potentially indicating reduced home range size when additional resources are available. Our study highlights the potential value of managing anthropogenic resource availability to manage carnivore densities and potential risk of human-carnivore interactions.

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Edge effects result from the penetration to varying depths and intensities, of abiotic and biotic conditions from the surrounding non-forest matrix into the forest interior. Although 70% of the world's forests are within 1 km of a forest edge, making edge effects a dominant feature of most forest habitats, there are few empirical data on inter-site differences in edge responses in primates. We used spatially explicit capture-recapture (SECR) models to determine spatial patterns of density for two species of mouse lemurs (Microcebus murinus and Microcebus ravelobensis) in two forest landscapes in northwestern Madagascar. The goal of our study was to determine if mouse lemurs displayed spatially variable responses to edge effects. We trapped animals using Sherman live traps in the Mariarano Classified Forest (MCF) and in the Ambanjabe Forest Fragment Site (AFFS) site within Ankarafantsika National Park. We trapped 126 M. murinus and 79 M. ravelobensis at MCF and 78 M. murinus and 308 M. ravelobensis at AFFS. For M. murinus, our top model predicted a positive edge response, where density increased towards edge habitats. In M. ravelobensis, our top model predicted a negative edge response, where density was lower near the forest edges and increased towards the forest interior. At regional and landscape-specific scales, SECR models estimated different density patterns between M. murinus and M. ravelobensis as a result of variation in edge distance. The spatial variability of our results using SECR models indicate the importance of studying the population ecology of primates at varying scales that are appropriate to the processes of interest. Our results lend further support to the theory that some lemurs exhibit a form of ecological flexibility in their responses to forest loss, forest fragmentation, and associated edge effects.

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Landscape structure affects animal movement. Differences between landscapes may induce heterogeneity in home range size and movement rates among individuals within a population. These types of heterogeneity can cause bias when estimating population size or density and are seldom considered during analyses. Individual heterogeneity, attributable to unknown or unobserved covariates, is often modelled using latent mixture distributions, but these are demanding of data, and abundance estimates are sensitive to the parameters of the mixture distribution. A recent extension of spatially explicit capture-recapture models allows landscape structure to be modelled explicitly by incorporating landscape connectivity using non-Euclidean least-cost paths, improving inference, especially in highly structured (riparian & mountainous) landscapes. Our objective was to investigate whether these novel models could improve inference about black bear (Ursus americanus) density. We fit spatially explicit capture-recapture models with standard and complex structures to black bear data from 51 separate study areas. We found that non-Euclidean models were supported in over half of our study areas. Associated density estimates were higher and less precise than those from simple models and only slightly more precise than those from finite mixture models. Estimates were sensitive to the scale (pixel resolution) at which least-cost paths were calculated, but there was no consistent pattern across covariates or resolutions. Our results indicate that negative bias associated with ignoring heterogeneity is potentially severe. However, the most popular method for dealing with this heterogeneity (finite mixtures) yielded potentially unreliable point estimates of abundance that may not be comparable across surveys, even in data sets with 136-350 total detections, 3-5 detections per individual, 97-283 recaptures, and 80-254 spatial recaptures. In these same study areas with high sample sizes, we expected that landscape features would not severely constrain animal movements and modelling non-Euclidian distance would not consistently improve inference. Our results suggest caution in applying non-Euclidean SCR models when there is no clear landscape covariate that is known to strongly influence the movement of the focal species, and in applying finite mixture models except when abundant data are available.

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Insect diversity and abundance are in drastic decline worldwide, but quantifying insect populations to better conserve them is a difficult task. Mark-release-recapture (MRR) is widely used as an ecological indicator for insect populations, but the accuracy of MRR estimates can vary with factors such as spatial scale, sampling effort and models of inference. We conducted a 3-year MRR study of B. thaidina in Yanzigou valley, Mt. Gongga but failed to obtain sufficient data for a robust population estimate. This prompted us to integrate B. thaidina life history information to parameterize agent-based models and evaluate the conditions under which successful MRR studies could be conducted. We evaluated: (1) the performance of MRR models under different landscape types, and (2) the influence of experimental design on the accuracy and variance of MRR-based estimates. Our simulations revealed systematic underestimates of true population parameters by MRR models when sampling effort was insufficient. In a total of 2772 simulations, subjective decisions in sampling protocol (e.g., frequency, number of sampling locations, use of spatially explicit models, type of estimands) accounted for nearly half of the variation in estimates. We conclude that MRR-based estimates could be improved with the addition of more field-specific parameters.

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The conservation of large carnivores often requires precise and accurate estimates of their populations. Being cryptic and occurring at low population densities, obtaining an unbiased population estimate is difficult in large carnivores. To overcome the uncertainties in the conventional capture-recapture (CR) methods used to estimate large carnivore densities, more robust methods such as spatially explicit capture-recapture (SECR) framework are now widely used. We modeled the CR data of tiger (Panthera tigris tigris) and leopard (Panthera pardus fusca) in the SECR framework with biotic and abiotic covariates likely believed to influence their densities. An effort of 2,211 trap nights resulted in the capture of 33 and 38 individual tigers and leopards. A total of 95 and 74 detections of tigers and leopards were achieved using 35 pairs of camera traps. Tiger and leopard density were estimated at 4.71 ± 1.20 (3.05-5.11) and 3.03 ± 0.78 (1.85-4.99) per 100 km2. Our results show that leopard density increased with high road density, high terrain ruggedness and habitats with high percentage of cropland and natural vegetation. The tiger density was positively influenced by the mosaic of cropland and natural vegetation. This study provides the first robust density estimates of tiger and leopard within the study area. Our results support the notion that large carnivores can attain moderate densities within human-dominated regions around protected areas relying on domestic livestock. Broader management strategies aimed at maintaining wild prey in the human-dominated areas around protected areas are necessary for large and endangered carnivores' sustenance in the buffer zones around protected areas.

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BACKGROUND: Lethal removal of invasive species, such as wild pigs (Sus scrofa), is often the most efficient approach for reducing their negative impacts. Wild pigs are one of the most widespread and destructive invasive mammals in the USA. Lethal management techniques are a key approach for wild pigs and can alter wild pig spatial behavior, but it is unclear how wild pigs respond to the most common removal technique, trapping. We investigated the spatial behavior of wild pigs following intensive removal of conspecifics via trapping at three sites within the Savannah River Site, SC, USA. We evaluated changes in wild pig densities, estimated temporal shifts in home-range properties, and evaluated fine-scale movement responses of wild pigs to removal. RESULTS: We observed a significant reduction in the density of wild pigs in one site following removal via trapping while a qualitative reduction was observed in another site. We found little evidence of shifts in pig home-ranging behavior following removal. However, we did observe a nuanced response in movement behavior of wild pigs to the removal at the scale of the GPS locations (4 h), including increased movement speed and reduced selection for vegetation rich areas. CONCLUSION: Our work provides a better understanding of the impact of removal via trapping on wild pig movement and its implications for management. The lack of shift in home-range characteristics observed illustrates how targeted trapping could be used to provide temporary relief for species sensitive to wild pig consumption such as ground nesting birds or agricultural crops.

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Australia is currently free of canine rabies. Spatio-ecological knowledge about dingoes in northern Australia is currently a gap that impedes the application of disease spread models and our understanding of the potential transmission of rabies, in the event of an incursion. We therefore conducted a one-year camera trap survey to monitor a dingo population in equatorial northern Australia. The population is contiguous with remote Indigenous communities containing free-roaming dogs, which potentially interact with dingoes. Based on the camera trap data, we derived dingo density and home range size estimates using maximum-likelihood, spatially explicit, mark-resight models, described dingo movements and evaluated spatial correlation and temporal overlap in activities between dingoes and community dogs. Dingo density estimates varied from 0.135 animals/km2 (95% CI = 0.127-0.144) during the dry season to 0.147 animals/km2 (95% CI = 0.135-0.159) during the wet season. The 95% bivariate Normal home range sizes were highly variable throughout the year (7.95-29.40 km2). Spatial use and daily activity patterns of dingoes and free-roaming community dogs, grouped over ~3 month periods, showed substantial temporal activity overlap and spatial correlation, highlighting the potential risk of disease transmission at the wild-domestic interface in an area of biosecurity risk in equatorial northern Australia. Our results have utility for improving preparedness against a potential rabies incursion.

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Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide-ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3-month survey and adapted a Bayesian spatially explicit capture-recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture-recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km2 , and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.

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Ocelots play a key role in ecological communities as mesopredators affecting the lower trophic level and other mesopredators. They show great variability in ecological traits across their distribution, but knowledge of this species is missing in several regions where it occurs. Here, we present the first study of ocelot in the Brazilian semiarid of Caatinga. Arid habitats might keep carnivore population density low and therefore vulnerable to environmental shocks and to human-induced changes, at risk of local extinction. To assess their population status, we used camera traps between September 2009 and January 2010. We estimated the density of ocelots using a spatially explicit capture-recapture method (SECR) to be 3.16 ± 0.46 individuals per 100 km2. This is a low-density estimate for ocelots, which might reflect the harsh conditions of the arid habitat. A longer population study of the ocelot can answer if this low population density is enough for a long-term persistence of this species in this and other arid environments.

Jaguatiricas possuem um papel fundamental em comunidades ecológicas como mesopredadores, afetando níveis tróficos inferiores e também outros mesopredadores. Esta espécie possui uma grande variabilidade em suas características ecológicas em toda a sua distribuição, no entanto, o conhecimento desta espécie possui lacunas em vários locais onde ela ocorre. Neste trabalho, nós apresentamos o primeiro estudo desta espécie no semiárido brasileiro da Caatinga. Ambientes áridos podem afetar negativamente as espécies carnívoras e, aliado a alterações antrópicas, esta espécie pode ser levada a extinção local se sua densidade populacional é baixa. Portanto, para verificar o nível populacional da jaguatirica em uma região protegida da Caatinga, instalamos armadilhas fotográficas, entre setembro de 2009 e janeiro de 2010. Com os dados obtidos, calculamos a densidade desta espécie através de métodos espacialmente explícitos (SECR). A densidade estimada da jaguatirica foi de 3.16 ± 0.46 indivíduos por 100 km2. Esta estimativa é muito baixa para esta espécie, o que pode ser um reflexo das condições áridas deste ambiente. Um estudo populacional de maior duração pode ajudar a responder se esta baixa densidade é o suficiente para a persistência desta espécie a longo prazo tanto neste, quanto em outros ambientes áridos onde ela ocorre.

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Tropical evergreen forests in northeast India are a biological hot spot for conservation of flora and fauna. Little is known, however, about tiger abundance, which is a flagship species for tropical evergreen forests. Our objective was to document the capture rate and population density of tigers based on spatial explicit capture-recapture (SECR) approaches using camera trap data in an intensive study area (ISA) of 158 km(2) in Pakke Tiger Reserve (PTR) during March to May 2006. The Reserve lies in the foothills of the Eastern Himalayan Mountains, northeast India. We monitored 38 camera traps in ISA for 70 days and documented 10 photo-captures of tigers (5 left and 5 right flanks) with an average trap success rate of 1.3 captures/100 trap days. The overall capture probability was 0.05. The tiger density estimated using a SECR model was 0.97 ± 0.23 individuals/100 km(2). This is the first systematic sampling study in tropical semi evergreen forests of India, and information on capture rate and population density of tigers provides baseline data from which to determining changes in the future to assist conservation.