The Distribution and Abundance of an Island Population of Koalas (Phascolarctos cinereus) in the Far North of Their Geographic Range

Koalas are an iconic species of charismatic megafauna, of substantial social and conservation significance. They are widely distributed, often at low densities, and individuals can be difficult to detect, making population surveys challenging and costly. Consequently, koala population estimates have been limited and the results inconsistent. The aims of this study were to estimate the distribution, relative abundance and population size of the koalas on Magnetic Island, far north Queensland. Population densities were estimated in 18 different vegetation types present on the island using a Fecal Standing Crop Method. Koala density ranged from 0.404 ha⁻¹, recorded in forest red gum and bloodwood woodland, to absence from eight of the vegetation types surveyed. The second highest density of 0.297 koalas ha⁻¹ was recorded in mixed eucalypt woodland, which covers 45% of the island. The total abundance of koalas on Magnetic Island, not including those present in urban areas, was estimated at 825±175 (SEM). The large variation in koala density across vegetation types reinforces the need for sampling stratification when calculating abundance over large areas, as uniformity of habitat quality cannot be assumed. In this context, koala populations also occur in low densities in areas generally regarded as poor quality koala habitat. These results highlight the importance of protecting vegetation communities not traditionally considered to have high conservation value to koalas, as these habitats may be essential for maintaining viable, widespread, low-density populations. The results from this study provide a baseline to assess future trends in koala distribution, density and abundance on Magnetic Island.     

Influences on koala habitat selection across four local government areas on the far north coast of NSW

Conserving habitats crucial for threatened koala (Phascolarctos cinereus) populations requires rating habitat quality from a fine spatial scale to patches, landscapes and then regions. The koala has a specialized diet focused on the leaves of a suite of Eucalyptus species. We asked: what are the key regional influences on habitat selection by koalas in the far north coast of New South Wales? We addressed this question by investigating the multi-scale factors, and within-scale and cross-scale interactions, that influence koala habitat selection and distribution across four local government areas on the far north coast of New South Wales. We assembled and analysed a large data set of tree selection, identified by the presence of scats, in a wide range of randomly selected 5 × 5 km grids across the region. This resulted in more than 9000 trees surveyed for evidence of koala use from 302 field sites, together with associated biophysical site features. The dominant factor influencing habitat use and koala occurrence was the distribution of five Eucalyptus species. Koalas were more likely to use medium-sized trees of these species where they occurred on soils with high levels of Colwell phosphorous. We also identified new interactions among the distribution of preferred tree species and soil phosphorous, and their distribution with the amount of suitable habitat in the surrounding landscape. Our study confirmed that non-preferred species of eucalypts and non-eucalypts are extensively used by koalas and form important components of koala habitat. This finding lends support to restoring a mosaic of koala-preferred tree species and other species recognized for their value as shelter. Our study has provided the ecological foundation for developing a novel regional-scale approach to the conservation of koalas, with adaptability to other wildlife species.     

Difficulties of assessing the impacts of the 2019–2020 bushfires on koalas

The 2019–2020 Australian bushfires were unprecedented both in extent and severity, impacting wildlife through direct mortality as well as habitat damage. More than 10% of koala habitat is estimated to have been affected by fires. Estimating the number of koalas lost is crucial to assess koala conservation status and to determine the appropriate management actions required. However, this is not a trivial task, as accurate data on koala distribution and population density before the fires is patchy. Acknowledging this weakness, we sought to estimate fire impact on koalas at specific sites, by comparing habitat areas affected by the fire with habitat areas that were unaffected by the fire, pairing closely related study sites (based on geography and vegetation). To compare koala density, we deployed two koala detection methods; drone-acquired thermal imagery and detection dogs coupled with genetic fingerprinting, in four fire-affected sites paired with four control sites in New South Wales and Queensland. Through drone surveys, we detected 140 koalas in 5,240 ha in New South Wales. The detection dogs found 144 scat samples corresponding to 79 unique koalas in 77 ha of transects in Queensland. Our preliminary results show many koalas were still present in fire-affected areas after the 2019–2020 bushfire season. Koala density was 24 to 71% lower in fire-affected sites compared with control sites in three of the habitat pairs, whereas unexpectedly, in the fourth pair, we observed a 317% higher koala density in the fire-affected site. This underlined that koalas can be present in fire-affected areas and that monitoring their health could be critical for months after the fires.     

Reliable genotyping of the koala (Phascolarctos cinereus) using DNA isolated from a single faecal pellet

The koala, an Australian icon, has been added to the threatened species list. Rationale for the listing includes proposed declines in population size, threats to populations (e.g. disease) and loss and fragmentation of habitat. There is now an urgent need to obtain accurate data to assess the status of koala populations in Australia, to ensure the long‐term viability of this species. Advances in genetic techniques have enabled DNA analysis to study and inform the management of wild populations; however, sampling of individual koalas is difficult in tall, often remote, eucalypt forest. The collection of faecal pellets (scats) from the forest floor presents an opportunistic sampling strategy, where DNA can be collected without capturing or even sighting an individual. Obtaining DNA via noninvasive sampling can be used to rapidly sample a large proportion of a population; however, DNA from noninvasively collected samples is often degraded. Factors influencing DNA quality and quantity include environmental exposure, diet and methods of sample collection, storage and DNA isolation. Reduced DNA quality and quantity can introduce genotyping errors and provide inaccurate DNA profiles, reducing confidence in the ability of such data to inform management/conservation strategies. Here, we present a protocol that produces a reliable individual koala genotype from a single faecal pellet and highlight the importance of optimizing DNA isolation and analysis for the species of interest. This method could readily be adapted for genetic studies of mammals other than koalas, particularly those whose diet contains high proportions of volatile materials that are likely to induce DNA damage.     

Multiresistant Enterobacteriaceae in yellow‐legged gull chicks in their first weeks of life

Wild animal species living in anthropogenic areas are commonly carriers of antimicrobial‐resistant bacteria (AMRB), but their role in the epidemiology of these bacteria is unclear. Several studies on AMRB in wildlife have been cross‐sectional in design and sampled individual animals at only one point in time. To further understand the role of wildlife in maintaining and potentially transmitting these bacteria to humans and livestock, longitudinal studies are needed in which samples are collected from individual animals over multiple time periods. In Europe, free‐ranging yellow‐legged gulls (Larus michahellis) commonly live in industrialized areas, forage in landfills, and have been found to carry AMRB in their feces. Using bacterial metagenomics and antimicrobial resistance characterization, we investigated the spatial and temporal patterns of AMRB in a nesting colony of yellow‐legged gulls from an industrialized area in southern France. We collected 54 cloacal swabs from 31 yellow‐legged gull chicks in 20 nests on three dates in 2016. We found that AMRB in chicks increased over time and was not spatially structured within the gull colony. This study highlights the complex occurrence of AMRB in a free‐ranging wildlife species and contributes to our understanding of the public health risks and implications associated with ARMB‐carrying gulls living in anthropogenic areas.     

Translocation of overabundant species: Implications for translocated individuals

Effective management of overabundant animal populations is a difficult challenge for wildlife managers around the globe. Translocation is often considered a viable management tool, whereby individual animals are removed from areas of high population density and released in areas where densities are lower. Typically, the success of a translocation program is measured at the population source, with little attention given to the fate of translocated individuals. Here we use a koala (Phascolarctos cinereus) translocation program from southeastern Australia as a case study to investigate the effects of translocation on individual animals. The koala is an iconic species that occurs at high densities in some parts of its southern range, leading to numerous conservation and animal welfare issues. Between 1997 and 2007 over 3,000 koalas from a high-density island population were captured, surgically sterilized, and translocated to the mainland. Annual post-translocation surveys at release sites revealed densities of ≤0.4 koalas/ha, despite release densities of 1.0 koala/ha. Radiotracking studies indicate that low densities were because of both mortality and high dispersal of translocated individuals. We observed a mortality rate of 37.5% for translocated koalas in the first 12 months post-release. No deaths occurred among animals that were not sterilized and translocated. Translocated koalas moved greater distances than non-translocated animals. Monitoring of translocated individuals should be performed routinely during translocation programs for overabundant species. Due consideration must be given to what is an acceptable level of mortality for translocated individuals. Although often considered an ethically acceptable management technique (especially for iconic and charismatic species), translocation may not always be the best option from an animal welfare perspective. © 2012 The Wildlife Society.     

Modelling Chlamydia–koala interactions: coexistence, population dynamics and conservation implications

1. Considerable research has been conducted on koala Phascolarctos cinereus population dynamics and the epidemiology of Chlamydia psittaci infection in koalas, but the impact of Chlamydia on koala populations has been difficult to assess.
2. I developed a model of koala and Chlamydia population dynamics to examine interactions between Chlamydia transmission and pathogenicity, koala mating behaviour and demography, and koala population persistence.
3. Simulations based on sexual and parent–offspring parasite transmission demonstrate that stable Chlamydia–koala coexistence is possible in a small population for a broad range of demographic, behavioural, pathogenicity and transmission parameter estimations. Koala population persistence was most sensitive to reduced annual survivorship of adults (4–10-year-old males and 2–12-year-old females), highlighting the need for accurate field estimates of adult survivorship in order to assess Chlamydia 's impact on specific populations.
4. If koalas become less resistant to disease in fragmented, high-stress habitats (i.e. experience increased Chlamydia -induced mortality and sterility rates), Chlamydia is not predicted to cause koala extinctions under most conditions. Extinctions are only predicted if Chlamydia transmission rates also increase (e.g. due to new transmission pathways or increased mating frequency), or other non-disease factors change birth and mortality rates to reduce the koala population's intrinsic rate of increase below 0·1.
5. The most important predicted effect of habitat fragmentation and other forms of human disturbance on this unique host–parasite relationship is the extinction of Chlamydia in populations where koala resistance to disease decreases.     

The importance of fine‐scale predictors of wild boar habitat use in an isolated population

1. Predicting the likelihood of wildlife presence at potential wildlife–livestock interfaces is challenging. These interfaces are usually relatively small geographical areas where landscapes show large variation over small distances. Models of wildlife distribution based on coarse data over wide geographical ranges may not be representative of these interfaces. High‐resolution data can help identify fine‐scale predictors of wildlife habitat use at a local scale and provide more accurate predictions of species habitat use. These data may be used to inform knowledge of interface risks, such as disease transmission between wildlife and livestock, or human–wildlife conflict.
2. This study uses fine‐scale habitat use data from wild boar (Sus scrofa) based on activity signs and direct field observations in and around the Forest of Dean in Gloucestershire, England. Spatial logistic regression models fitted using a variant of penalized quasi‐likelihood were used to identify habitat‐based and anthropogenic predictors of wild boar signs.
3. Our models showed that within the Forest of Dean, wild boar signs were more likely to be seen in spring, in forest‐type habitats, closer to the center of the forest and near litter bins. In the area surrounding the Forest of Dean, wild boar signs were more likely to be seen in forest‐type habitats and near recreational parks and less likely to be seen near livestock.
4. This approach shows that wild boar habitat use can be predicted using fine‐scale data over comparatively small areas and in human‐dominated landscapes, while taking account of the spatial correlation from other nearby fine‐scale data‐points. The methods we use could be applied to map habitat use of other wildlife species in similar landscapes, or of movement‐restricted, isolated, or fragmented wildlife populations.

     

Optimizing trilateration estimates for tracking fine‐scale movement of wildlife using automated radio telemetry networks

A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal‐borne radio transmitters. However, the use of RSS‐based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high‐quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS‐based localization estimates for a node network designed to track fine‐scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS‐based localization estimates. Overall, the use of signal strength and distance‐based filters resulted in a 3‐ to 9‐fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS‐based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.     

Genetic structure and diversity of the koala population in South Gippsland,Victoria: a remnant population of high conservation significance

In the Australian state of Victoria, the history of koalas and their management has resulted in the homogenisation and reduction of genetic diversity in many contemporary populations. Decreased genetic diversity may reduce a species’ ability to adapt to future environmental pressures such as climate change or disease. The South Gippsland koala population is considered to be unique in Victoria, as it is believed to be a remnant population, not originating from managed populations that have low genetic variation. This study investigated genetic structure and diversity of koalas in South Gippsland, with comparison to other populations in Victoria (French Island/Cape Otway, FI and Raymond Island, RI), New South Wales and south east Queensland. Population analyses were undertaken using both microsatellite genotype and mitochondrial DNA sequence data. Non-invasive sampling of koala scats was used to source koala DNA, allowing 222 South Gippsland koalas to be genotyped. Using nuclear data the South Gippsland koala population was found to be significantly differentiated (D_jost 95% CI SG–RI?=?0.03–0.06 and SG–FI?=?0.08–012) and more diverse (A_R 95% CI SG?=?4.7–5.6, RI?=?3.1–3.3, FI?=?3.0–3.3; p?=?0.001) than other Victorian koala populations, supporting the premise that koalas in the South Gippsland region are part of a remnant population, not derived from translocated island stock. These results were also supported by mitochondrial data where eight haplotypes (Pc4, Pc17, Pc26, Pc27, and Pc56–Pc59) were identified in South Gippsland while a single haplotype (Pc27) was found in all island koalas tested. Compared to other Victorian koala populations, greater genetic diversity found in South Gippsland koalas, may provide this population with a greater chance of survival in the face of future environmental pressures. The South Gippsland koala population is, therefore, of high conservation significance, warranting the implementation of strategies to conserve this population and its diversity into the future.     

Genetic variation and structuring in the threatened koala populations of Southeast Queensland

Habitat fragmentation can act to cause reproductive isolation between conspecifics and undermine species’ persistence, though most studies have reported the genetic condition of populations that have already declined to a very small size. We examined genetic diversity within the vulnerable, declining koala (Phascolarctos cinereus) population in Southeast Queensland, Australia to determine the genetic impact of ongoing threatening processes. Five hundred and twelve koalas from ten Southeast Queensland Local Government Areas on the mainland and one island were genotyped at six polymorphic microsatellite loci. Based on Bayesian cluster analysis incorporating spatial data, the regional koala population was subdivided into six clusters, with location of major roads and rivers appearing to be consistent with being barriers to gene flow. The distribution of mtDNA control region haplotypes identified distinct coastal and inland clades suggesting that historically there was gene flow between koalas along the coast (though little interchange between coastal and inland animals). In contrast, koalas from the Koala Coast (Brisbane City, Logan City and Redland Shire) were shown by microsatellite analysis to be genetically distinct from adjacent areas. It is likely, therefore, that more recent reductions in population size and restricted gene flow through urbanisation have contributed to the genetic differentiation of koalas in the Koala Coast region.     

An open spatial capture–recapture model for estimating density,movement, and population dynamics from line‐transect surveys

The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line‐transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture–recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture–recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture–recapture model that can be applied to line‐transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line‐transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line‐transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.     

Predicted declines in suitable habitat for greater one‐horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios

Rapidly changing climate is likely to modify the spatial distribution of both flora and fauna. Land use change continues to alter the availability and quality of habitat and further intensifies the effects of climate change on wildlife species. We used an ensemble modeling approach to predict changes in habitat suitability for an iconic wildlife species, greater one‐horned rhinoceros due to the combined effects of climate and land use changes. We compiled an extensive database on current rhinoceros distribution and selected nine ecologically meaningful environmental variables for developing ensemble models of habitat suitability using ten different species distribution modeling algorithms in the BIOMOD2 R package; and we did this under current climatic conditions and then projected them onto two possible climate change scenarios (SSP1‐2.6 and SSP5‐8.5) and two different time frames (2050 and 2070). Out of ten algorithms, random forest performed the best, and five environmental variables—distance from grasslands, mean temperature of driest quarter, distance from wetlands, annual precipitation, and slope, contributed the most in the model. The ensemble model estimated the current suitable habitat of rhinoceros to be 2610 km², about 1.77% of the total area of Nepal. The future habitat suitability under the lowest and highest emission scenarios was estimated to be: (1) 2325 and 1904 km² in 2050; and (2) 2287 and 1686 km² in 2070, respectively. Our results suggest that over one‐third of the current rhinoceros habitat would become unsuitable within a period of 50 years, with the predicted declines being influenced to a greater degree by climatic changes than land use changes. We have recommended several measures to moderate these impacts, including relocation of the proposed Nijgad International Airport given that a considerable portion of potential rhinoceros habitat will be lost if the airport is constructed on the currently proposed site.     

Fresh is best: Accurate SNP genotyping from koala scats

Maintaining genetic diversity is a crucial component in conserving threatened species. For the iconic Australian koala, there is little genetic information on wild populations that is not either skewed by biased sampling methods (e.g., sampling effort skewed toward urban areas) or of limited usefulness due to low numbers of microsatellites used. The ability to genotype DNA extracted from koala scats using next‐generation sequencing technology will not only help resolve location sample bias but also improve the accuracy and scope of genetic analyses (e.g., neutral vs. adaptive genetic diversity, inbreeding, and effective population size). Here, we present the successful SNP genotyping (1272 SNP loci) of koala DNA extracted from scat, using a proprietary DArTseq^? protocol. We compare genotype results from two‐day‐old scat DNA and 14‐day‐old scat DNA to a blood DNA template, to test accuracy of scat genotyping. We find that DNA from fresher scat results in fewer loci with missing information than DNA from older scat; however, 14‐day‐old scat can still provide useful genetic information, depending on the research question. We also find that a subset of 209 conserved loci can accurately identify individual koalas, even from older scat samples. In addition, we find that DNA sequences identified from scat samples through the DArTseq^? process can provide genetic identification of koala diet species, bacterial and viral pathogens, and parasitic organisms.     

Non‐invasive monitoring of multiple wildlife health factors by fecal microbiome analysis

Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body‐fat). We paired a feature‐selection algorithm with an LDA‐classifier trained on elk differential bacterial abundance (16S‐rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave‐one‐out cross‐validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body‐fat, sex, and age‐class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non‐invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome‐based monitoring of wildlife populations and supports hypothetical expectations found in host‐microbiome theory.     

Testing the precision and sensitivity of density estimates obtained with a camera‐trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The random encounter model (REM) is a camera‐trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e., average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera‐trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture–recapture estimator based on hair‐snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture–recapture model, was 2.87 individuals/10km² [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km² depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow‐moving species had more influence on REM density estimates than for fast‐moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, that is, using GPS telemetry locations with large fix‐rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture–recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.     

Multi‐surveyor capture‐mark‐recapture as a powerful tool for butterfly population monitoring in the pre‐imaginal stage

For many elusive insect species, which are difficult to cover by standard monitoring schemes, innovative survey methods are needed to gain robust data on abundance and population trends. We suggest a monitoring of overwintering larvae for the endangered nymphalid butterfly Limenitis reducta. We tested different removal and capture‐mark‐recapture (CMR) approaches in a field study in the “Alb‐Donau” region, Germany. Classical removal and CMR studies require movement of the organisms under study, but in our approach, we replaced movement of the study organisms by random movement of multiple different surveyors. We tested the validity of the approach by comparing detection frequencies from our field data with simulated detections. Our results indicate that multi‐surveyor removal/CMR techniques are suitable for estimating abundance of overwintering L. reducta larvae. Depending on surveyor experience, the average detection probability ranged between 16% for novices and 35% for experts. The uncertainty of population estimates increased with a decrease in personnel expenditure. Estimated larval densities on a spruce clear‐cut varied between one and three individuals per 100 m², probably related to habitat conditions. We suggest a CMR approach with three to four trained surveyors for the monitoring of L. reducta populations in the overwintering stage. Compared with previous sampling methods, our approach is a powerful tool with clear advantages: long survey period, estimates of the absolute population size accompanied by uncertainty measures, and estimates of overwinter mortality. The proposed method can be adapted and used for several different butterfly species, other insect taxa with specific immobile life stages, and some sessile organisms, for example, elusive plants, fungi, or corals.     

Potential risk zone for anthropogenic mortality of carnivores in Gandaki Province,Nepal

Anthropogenic pressures in human‐dominated landscapes often contribute to wildlife mortality. Carnivores are especially vulnerable to human‐induced mortality due to the perceived threat to livestock and humans. Despite having widespread conservation implications, carnivore mortality data have been largely underutilized within Nepal. This study utilized Maxent to identify high‐risk areas and explore the contribution of habitat attributes associated with carnivore mortality using the casualty database within the Gandaki province of central Nepal. We categorized the risk to carnivore species in three taxonomic groups, Felid, Viverridae, and Herpestidae, and identified a 3704‐km² area within the province at high risk for carnivore casualty. The middle mountains were the riskiest physiographic zone, and the Annapurna Conservation Area represented the largest risk zone among the four protected areas. Agricultural land was the most problematic area in terms of carnivore casualty. The human population was positively associated with high‐risk areas and the number of casualties, whereas protected area cover had a negative association. This study identified that the common leopard was at the highest risk of mortality and therefore would benefit from the implementation of an action plan and species‐specific conservation strategies, especially within identified high‐risk zones. An expansion of protected areas in the middle mountain region would serve to greatly reduce carnivore casualty. Species distribution modeling can be further used with national‐level spatial and temporal mortality data to identify the most prominent casualty times and pinpoint potential casualty locations throughout the country.     

Inbreeding and disease avoidance in a free‐ranging koala population

Habitat destruction and fragmentation are increasing globally, forcing surviving species into small, isolated populations. Isolated populations typically experience heightened inbreeding risk and associated inbreeding depression and population decline; although individuals in these populations may mitigate these risks through inbreeding avoidance strategies. For koalas, as dietary specialists already under threat in the northern parts of their range, increased habitat fragmentation and associated inbreeding costs are of great conservation concern. Koalas are known to display passive inbreeding avoidance through sex‐biased dispersal, although population isolation will reduce dispersal pathways. We tested whether free‐ranging koalas display active inbreeding avoidance behaviours. We used VHF tracking data, parentage reconstruction, and veterinary examination results to test whether free‐ranging female koalas avoid mating with (a) more closely related males; and (b) males infected with sexually transmitted Chlamydia pecorum. We found no evidence that female koalas avoid mating with relatively more related available mates. In fact, as the relatedness of potential mates increases, so did inbreeding events. We also found no evidence that female koalas can avoid mating with males infected with C. pecorum. The absence of active inbreeding avoidance mechanisms in koalas is concerning from a conservation perspective, as small, isolated populations may be at even higher risk of inbreeding depression than expected. At risk koala populations may require urgent conservation interventions to augment gene flow and reduce inbreeding risks. Similarly, if koalas are not avoiding mating with individuals with chlamydial disease, populations may be at higher risk from disease than anticipated, further impacting population viability.