Partitioning Detectability Components in Populations Subject to Within-Season Temporary Emigration Using Binomial Mixture Models

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model’s potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3–5 surveys each spring and fall 2010–2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability.     

Predicting species distributions from checklist data using site‐occupancy models

Aim (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how ‘cheap’ checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site‐occupancy models. Location Switzerland. Methods We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1‐ha pixels to derive ‘detection histories’ and apply site‐occupancy models to estimate the ‘true’ species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site‐occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site‐occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence–elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell‐shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site‐occupancy models applied to replicated detection/non‐detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of ‘cheap’ checklist data greatly enhances the scope of applications of this useful class of models.     

Spatially explicit estimation of occupancy,detection probability and survey effort needed to inform conservation planning

Aim It is increasingly recognized the importance of accounting for imperfect detection in species distribution modelling and conservation planning. However, the integration of detectability into a spatially explicit frame has received little attention. We aim (1) to show how to develop distribution maps of both detection probability and survey effort required to reliably determine a species presence/absence and (2) to increase awareness of the spatial variation of detection error inherent in studies of species occurrence. Location North‐western Spain. Methods  We registered the presence/absence of the endangered Egyptian vulture (Neophron percnopterus) in 213 surveys performed in 40 of 104 territories once known to be occupied. We model simultaneously both detection probability and occurrence, using site occupancy modelling. With the resulting regression equations, we developed distribution maps of both detection probability and required sampling effort throughout the area. Results Of the studied territories, 72.5% were detected as occupied, but after accounting for imperfect detection, the proportion of sites truly occupied was 79%. Detectability decreased in territories with higher topographical irregularity and increased with both the time of day of the survey and the progress of the season. Spatial distribution of detectability showed a mainly north–south gradient following the distribution of slope in the area. The likelihood of occupancy increased with rockier, less forested surface and less topographical irregularity within the territory. A minimum of five surveys, on average, are needed to assess, with 95% probability, the occupancy status of a site, ranging from ≤ 3 to > 24 visits/territory depending on survey‐ and site‐specific features. Main conclusions Accounting for detectability and its sources of variation allows us to elaborate distribution maps of detectability‐based survey effort. These maps are useful tools to reliably assess (e.g. with 95% probability) occupancy status throughout a landscape and provide guidance for species conservation planning.     

Trends in forest fragment research in Madagascar: Documented responses by lemurs and other taxa

The rise in research investigating fragmentation and its impact on primates and other taxa reflects the growing presence of fragmented landscapes themselves. Although numerous studies report the negative effects of fragmentation on biodiversity, it is difficult to generalize responses to fragmentation for specific taxonomic groups, such as non-human primates, when studies have not employed a definitive concept of fragmentation or fragments themselves. Madagascar's high degree of fragmentation, wealth of endemic taxa, and extensive history of ecological research provide the opportunity to compare fragmentation studies across similar contexts. We conducted a literature search of peer-reviewed articles on fragmentation in Madagascar to characterize its trends. A total of 70 articles, 46 of which concentrated on lemurs, tested the impacts of fragmentation on Malagasy taxa, while additional sources conducted research in one or more fragments without testing its effects (n = 112 total, 79 on lemurs). Studies on lemurs most frequently tested fragmentation's impacts on genetics and biodiversity metrics (n = 16 and 15 studies, respectively), although health, modeling, behavioral, and cross-disciplinary techniques were also reported. Responses to fragmentation were reported for 49 lemur species, with most studies concentrated in eastern Madagascar (87%). Although there was variation in the metrics reported in studies testing the effects of fragmentation on Malagasy species, the most common measures were fragment area, isolation, or comparison to a control site. Landscape-scale approaches and examination of fragmentation per se were rarely employed. Characterizing trends of fragmentation research in Madagascar emphasizes the challenges of documenting fragmentation's effects while highlighting the benefits of research within fragmented landscapes, particularly when combined with consideration for how the matrix within human-modified landscapes may impact primate populations.     

Associations between anuran tadpoles and salinity in a landscape mosaic of wetlands impacted by secondary salinisation

1. The secondary salinisation of wetlands is a global problem that poses a great threat to most freshwater biodiversity, including amphibians. We examined tadpole diversity in relation to wetland conductivity (our proxy for salinity) in wetlands in south‐eastern Australia to better understand (i) how salinity and amphibian diversity interact and (ii) the threat posed by secondary salinisation. 2. Six tadpole species were trapped in 56 wetlands that reflected a typical salinity gradient for the study region. We developed Bayesian models to examine the relationships between conductivity and both the probability of species occupancy and expected number of species with the imperfect detection probability of species accounted for in the models. 3. The probability of occupancy for all species and expected species number was negatively associated with wetland conductivity. Our results predict that conductivity should not limit tadpole presence below about 3000 μS cm⁻¹ at 25 °C (approximately 6% seawater) in the region, but will largely exclude amphibian larvae beyond about 6000 μS cm⁻¹ at 25 °C (approximately 12% seawater). 4. We also detected subtle among‐species differences in salinity tolerance. The results reported here show that tadpoles in the study region are likely to be negatively affected by projected future increases in salinisation.     

Replication levels,false presences and the estimation of the presence/absence from eDNA metabarcoding data

Environmental DNA (eDNA) metabarcoding is increasingly used to study the present and past biodiversity. eDNA analyses often rely on amplification of very small quantities or degraded DNA. To avoid missing detection of taxa that are actually present (false negatives), multiple extractions and amplifications of the same samples are often performed. However, the level of replication needed for reliable estimates of the presence/absence patterns remains an unaddressed topic. Furthermore, degraded DNA and PCR/sequencing errors might produce false positives. We used simulations and empirical data to evaluate the level of replication required for accurate detection of targeted taxa in different contexts and to assess the performance of methods used to reduce the risk of false detections. Furthermore, we evaluated whether statistical approaches developed to estimate occupancy in the presence of observational errors can successfully estimate true prevalence, detection probability and false‐positive rates. Replications reduced the rate of false negatives; the optimal level of replication was strongly dependent on the detection probability of taxa. Occupancy models successfully estimated true prevalence, detection probability and false‐positive rates, but their performance increased with the number of replicates. At least eight PCR replicates should be performed if detection probability is not high, such as in ancient DNA studies. Multiple DNA extractions from the same sample yielded consistent results; in some cases, collecting multiple samples from the same locality allowed detecting more species. The optimal level of replication for accurate species detection strongly varies among studies and could be explicitly estimated to improve the reliability of results.     

Accounting for Imperfect Detection Is Critical for Inferring Marine Turtle Nesting Population Trends

Assessments of population trends based on time-series counts of individuals are complicated by imperfect detection, which can lead to serious misinterpretations of data. Population trends of threatened marine turtles worldwide are usually based on counts of nests or nesting females. We analyze 39 years of nest-count, female-count, and capture-mark-recapture (CMR) data for nesting loggerhead turtles (Caretta caretta) on Wassaw Island, Georgia, USA. Annual counts of nests and females, not corrected for imperfect detection, yield significant, positive trends in abundance. However, multistate open robust design modeling of CMR data that accounts for changes in imperfect detection reveals that the annual abundance of nesting females has remained essentially constant over the 39-year period. The dichotomy could result from improvements in surveys or increased within-season nest-site fidelity in females, either of which would increase detection probability. For the first time in a marine turtle population, we compare results of population trend analyses that do and do not account for imperfect detection and demonstrate the potential for erroneous conclusions. Past assessments of marine turtle population trends based exclusively on count data should be interpreted with caution and re-evaluated when possible. These concerns apply equally to population assessments of all species with imperfect detection.     

Rabies epidemiology,prevention and control in Nigeria: Scoping progress towards elimination

BackgroundHuman rabies remains a significant public health problem in Africa with outbreaks reported in most countries. In Nigeria–the most populous country in Africa–rabies causes a significant public health burden partly due to perennial obstacles to implementing a national prevention and control program.MethodsWe conducted a scoping review using standard Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify and select published articles from Nigeria during 1978–2020 reporting on rabies virus infections (human, canine, livestock, and wildlife), canine bites, knowledge, attitudes and practices (KAP) surveys on rabies and canine ecology studies. We extracted information on study location, year and additional details of each study such as rabies prevalence, general characteristics of offending dogs, dog vaccination status and health-seeking behaviours.FindingsBetween 1978 and 2020, 90 published articles met our inclusion criteria. The prevalence of rabies virus antigen detection varied between 3% and 28%, with more studies in the north. Most bites were unprovoked from dog bite studies (36.4%-97%), by dogs with low vaccination rates (12–38%). A more significant proportion of biting dogs were owned (31–90%). Laboratory confirmation for biting was available for only a small proportion of studies (6%; n = 2/32). Of the dogs surveyed during ecology studies, indigenous dogs accounted for the majority (62–98%), used mostly for security purposes (52–98%), with the vaccination rate between 15% and 38% in most states. Studies conducted in areas distant from rabies diagnostic facilities accounted for more human rabies cases and fewer dog rabies cases.ConclusionSignificant improvements are necessary to achieve the elimination of human rabies mediated via dogs by 2030.     

Imperfect detection and the determination of environmental flows for fish: challenges,implications and solutions

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The Optimal Number of Surveys when Detectability Varies

The survey of plant and animal populations is central to undertaking field ecology. However, detection is imperfect, so the absence of a species cannot be determined with certainty. Methods developed to account for imperfect detectability during surveys do not yet account for stochastic variation in detectability over time or space. When each survey entails a fixed cost that is not spent searching (e.g., time required to travel to the site), stochastic detection rates result in a trade-off between the number of surveys and the length of each survey when surveying a single site. We present a model that addresses this trade-off and use it to determine the number of surveys that: 1) maximizes the expected probability of detection over the entire survey period; and 2) is most likely to achieve a minimally-acceptable probability of detection. We illustrate the applicability of our approach using three practical examples (minimum survey effort protocols, number of frog surveys per season, and number of quadrats per site to detect a plant species) and test our model''s predictions using data from experimental plant surveys. We find that when maximizing the expected probability of detection, the optimal survey design is most sensitive to the coefficient of variation in the rate of detection and the ratio of the search budget to the travel cost. When maximizing the likelihood of achieving a particular probability of detection, the optimal survey design is most sensitive to the required probability of detection, the expected number of detections if the budget were spent only on searching, and the expected number of detections that are missed due to travel costs. We find that accounting for stochasticity in detection rates is likely to be particularly important for designing surveys when detection rates are low. Our model provides a framework to do this.     

Generalization of Mimics Imperfect in Colour Patterns: The Point of View of Wild Avian Predators

Current research of imperfect mimicry brings ambiguous results. Experiments simulating more natural conditions rather than laboratory experiments show lower willingness of avian predators to attack less perfect mimics. We decided to simulate a natural situation by testing responses of wild‐caught adult avian predators (Great tit – Parus major) to variously perfect mimics of the red firebug (Pyrrhocoris apterus), which were in previous studies shown to elicit avoidance in Great tits. Presented mimics were perfect in all traits (firebug with its own colour pattern), imperfect in colour pattern (firebug with modified colour pattern), perfect in colour pattern, but imperfect in other visual traits (cockroach with firebug colour pattern), and imperfect in colour pattern as well as in other visual traits (cockroach with modified colour patterns). Modification of the pattern focused on the rounded spots on firebug's hemielytra, which is a conspicuous trait within the pattern. The pattern modification had no influence on the number of birds attacking the prey; nevertheless, birds spent more time observing the cockroaches that displayed the perfect firebug colour pattern than in the case of any other prey. Moreover, firebugs that displayed the perfect firebug colour pattern were observed for the shortest time (equal to that of the model – unmodified firebug). Cockroaches were attacked more often than firebugs, which suggest that birds were able to use additional visual cues (shape of legs and antennae) in prey recognition. Given these result, we conclude that differences in morphological traits characteristic for used prey taxa (true bugs, cockroaches) seem to be more important in the prey's protection than its colour pattern.     

Good-genes effects in sexual selection

The magnitude of the effect of good genes as a viability benefit accruing to choosy females remains a controversial theoretical and empirical issue. We collected all available data from the literature to estimate the magnitude of good-genes viability effects, while adjusting for sample size. The average correlation coefficient between male traits and offspring survival in 22 studies was 0.122, which differed highly significantly from zero. This implies that male characters chosen by females reveal on average 1.5% of the variance in viability. The studies demonstrated considerable heterogeneity in effect size; some of this heterogeneity could be accounted for by differences among taxa (birds demonstrating stronger effects), and by differences in the degree of mating skew in the species (high skew reflecting stronger effects). Although these results suggest that viability-based sexual selection is widespread across taxa, they indicate that the effect is relatively minor. Finally, there was also an effect of publication year in that the more recent studies reported reduced effects. This may reflect publication biases during paradigm shifts of this debated issue, but it should also be recalled that the studies have only partly estimated the full fitness consequences of mate choice for offspring.     

Optimal taxonomic groups for biodiversity assessment: a meta‐analytic approach

A fundamental decision in biodiversity assessment is the selection of one or more study taxa, a choice that is often made using qualitative criteria such as historical precedent, ease of detection, or available technical or taxonomic expertise. A more robust approach would involve selecting taxa based on the a priori expectation that they will provide the best possible information on unmeasured groups, but data to inform such hypotheses are often lacking. Using a global meta‐analysis, we quantified the proportion of variability that each of 12 taxonomic groups (at the Order level or above) explained in the richness or composition of other taxa. We then applied optimization to matrices of pairwise congruency to identify the best set of complementary surrogate groups. We found that no single taxon was an optimal surrogate for both the richness and composition of unmeasured taxa if we used simple methods to aggregate congruence data between studies. In contrast, statistical methods that accounted for well‐known drivers of cross‐taxon congruence (spatial extent, grain size, and latitude) lead to the prioritization of similar surrogates for both species richness and composition. Advanced statistical methods were also more effective at describing known ecological relationships between taxa than simple methods, and show that congruence is typically highest between taxonomically and functionally dissimilar taxa. Birds and vascular plants were most frequently selected by our algorithm as surrogates for other taxonomic groups, but the extent to which any one taxon was the ‘optimal’ choice of surrogate for other biodiversity was highly context‐dependent. In the absence of other information – such as in data‐poor areas of the globe, and under limited budgets for monitoring or assessment – ecologists can use our results to assess which taxa are most likely to reflect the distribution of the richness or composition of ‘total’ biodiversity.     

Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep

Aerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)-collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.     

The importance of parentage in assessing temperature effects on fish early life history: a review of the experimental literature

Climate change and human development are altering aquatic thermal regimes, highlighting the need to understand how fish fitness may be impacted across a generational boundary. We reviewed experimental temperature studies investigating the links between parents and progeny, asking questions regarding the taxa studied, broodfish used, offspring traits examined, experimental durations and research motivations. We identified forty-one peer-reviewed articles examining the effects of pre-spawning adult temperature holding on offspring. These studies showed a strong focus on the order Salmoniformes (46% of studies) and aquaculturally driven research (66%). The use of wild broodfish was rare (12%) and the majority of experiments (83%) did not examine offspring consequences beyond hatch. We also identified 56 articles investigating how incubation temperature and parental influences affect embryonic and larval development. We demonstrate that these studies are not common in comparison to the majority of incubation thermal experiments that do not employ controlled parental breeding designs. However, 52 out of 56 studies we reviewed reported maternal, paternal or family identity influenced offspring responses to temperature. In characterizing these studies, Salmoniformes were the most studied order (52%), wild broodfish were more commonly used (55%), aquaculture motivations were less evident (23%), and few studies investigated offspring performance or traits beyond endogenous yolk stages. Overall, we suggest it is beneficial to experimentally examine temperature with consideration to parent-progeny relationships. To broaden our current understanding of intergenerational temperature effects, we recommend an increased focus on wild populations, offspring physiological and performance measures, later offspring development stages, and expanding research in non-salmonid species.     

Is There a Size Limit for Cosmopolitan Distribution in Free-Living Microorganisms? A Biogeographical Analysis of Testate Amoebae from Polar Areas

A long-standing debate in microbial ecology is the extent to which free-living microorganisms exhibit cosmopolitan distributions. We use a comparison of testate amoebae communities in cold “polar” locations (Arctic, Antarctic, and Tibet) to investigate how a microorganism’s size affects its probability of having a cosmopolitan distribution. We show that the probability a given taxa being reported in all three locations increases as testate size decreases. Likewise, excluding those testates found only in Tibet, very small testates (<20 μm) are more likely to occur in both the Arctic and Antarctic than in either of these poles alone. Attempting to correct for phylogeny reduces the number of statistically significant relationships—both because of decreased sample size and potentially real phylogenetic patterns, although some size-dependent effects were still apparent. In particular, taxa found in both the Arctic and Antarctic poles were significantly smaller than congeneric taxa found only in Tibet. This pattern may in part be due to habitat effects, with the Tibetan samples being more likely to have come from aquatic sites which may be more suitable for larger taxa. Overall, our analysis suggests that, at least within testate amoebae, a cosmopolitan distribution becomes increasingly common as median taxon size decreases.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Investigating detection success: lessons from trials using decoy rare plants

Imperfect detection leads to underestimates of species presence and decreases the reliability of survey data. Imperfect detection has not been examined in detail for boreal forest understory plants, despite widespread use of surveys for rare plants prior to development. We addressed this issue using detectability trials conducted in Alberta, Canada with decoy vascular plants. Volunteer observers searched in survey plots for species while unaware of their true presence or abundance. Our findings indicate that the detection of cryptic species is very low when abundance is low (0–35%) and plot size is large (<?50% in?≥?100 m²). Plant density (individuals per unit area) was the most important determinant of detection probability, where more abundant species were detected more often and with less survey effort. When abundance was held constant, diffusely arranged species were twice as likely to be detected compared to those in clumps. Detection of cryptic species can be low even when individuals are flowering, and even morphologically distinct species can go unnoticed in small plots. We suggest that future decoy trials investigate search strategies that could improve detection and that field surveys for vascular plants address imperfect detection through careful consideration of plot size, characteristics of the target species, and survey effort, both in terms of time expenditure within an area and the number of observers employed.     

Modelling occurrence and abundance of species when detection is imperfect

Relationships between species abundance and occupancy are of considerable interest in metapopulation biology and in macroecology. Such relationships may be described concisely using probability models that characterize variation in abundance of a species. However, estimation of the parameters of these models in most ecological problems is impaired by imperfect detection. When organisms are detected imperfectly, observed counts are biased estimates of true abundance, and this induces bias in stated occupancy or occurrence probability. In this paper we consider a class of models that enable estimation of abundance/occupancy relationships from counts of organisms that result from surveys in which detection is imperfect. Under such models, parameter estimation and inference are based on conventional likelihood methods. We provide an application of these models to geographically extensive breeding bird survey data in which alternative models of abundance are considered that include factors that influence variation in abundance and detectability. Using these models, we produce estimates of abundance and occupancy maps that honor important sources of spatial variation in avian abundance and provide clearly interpretable characterizations of abundance and occupancy adjusted for imperfect detection.     

Habitat occupancy of sloth bear Melursus ursinus in Chitwan National Park,Nepal

Mammals have experienced a massive decline in their populations and geographic ranges worldwide. The sloth bear, Melursus ursinus (Shaw, 1791), is one of many species facing conservation threats. Despite being endangered in Nepal, decades of inattention to the situation have hindered their conservation and management. We assessed the distribution and patterns of habitat use by sloth bears in Chitwan National Park (CNP), Nepal. We conducted sign surveys from March to June, 2020, in 4 × 4 km grids (n = 45). We collected detection/non‐detection data along a 4‐km trail that was divided into 20 continuous segments of 200 m each. We obtained environmental, ecological, and anthropogenic covariates to understand determinants of sloth bear habitat occupancy. The data were analyzed using the single‐species single‐season occupancy method, with a spatially correlated detection. Using repeated observations, these models accounted for the imperfect detectability of the species to provide robust estimates of habitat occupancy. The model‐averaged occupancy estimate for the sloth bear was 69% and the detection probability was 0.25. The probability of habitat occupancy by sloth bears increased with the presence of termites and fruits and in rugged, dry, open, undisturbed habitats. Our results indicate that the sloth bear is elusive, functionally unique, and widespread in CNP. Future conservation interventions and action plans aimed at sloth bear management must adequately consider their habitat requirements.