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.     

Abundance and Survival Rates of the Hawai’i Island Associated Spinner Dolphin (Stenella longirostris) Stock

Reliable population estimates are critical to implement effective management strategies. The Hawai’i Island spinner dolphin (Stenella longirostris) is a genetically distinct stock that displays a rigid daily behavioural pattern, foraging offshore at night and resting in sheltered bays during the day. Consequently, they are exposed to frequent human interactions and disturbance. We estimated population parameters of this spinner dolphin stock using a systematic sampling design and capture–recapture models. From September 2010 to August 2011, boat-based photo-identification surveys were undertaken monthly over 132 days (>1,150 hours of effort; >100,000 dorsal fin images) in the four main resting bays along the Kona Coast, Hawai’i Island. All images were graded according to photographic quality and distinctiveness. Over 32,000 images were included in the analyses, from which 607 distinctive individuals were catalogued and 214 were highly distinctive. Two independent estimates of the proportion of highly distinctive individuals in the population were not significantly different (p = 0.68). Individual heterogeneity and time variation in capture probabilities were strongly indicated for these data; therefore capture–recapture models allowing for these variations were used. The estimated annual apparent survival rate (product of true survival and permanent emigration) was 0.97 SE±0.05. Open and closed capture–recapture models for the highly distinctive individuals photographed at least once each month produced similar abundance estimates. An estimate of 221±4.3 SE highly distinctive spinner dolphins, resulted in a total abundance of 631±60.1 SE, (95% CI 524–761) spinner dolphins in the Hawai’i Island stock, which is lower than previous estimates. When this abundance estimate is considered alongside the rigid daily behavioural pattern, genetic distinctiveness, and the ease of human access to spinner dolphins in their preferred resting habitats, this Hawai’i Island stock is likely more vulnerable to negative impacts from human disturbance than previously believed.     

Extracting spatial networks from capture–recapture data reveals individual site fidelity patterns within a marine mammal’s spatial range

1. Estimating the impacts of anthropogenic disturbances requires an understanding of the habitat‐use patterns of individuals within a population. This is especially the case when disturbances are localized within a population''s spatial range, as variation in habitat use within a population can drastically alter the distribution of impacts.
2. Here, we illustrate the potential for multilevel binomial models to generate spatial networks from capture–recapture data, a common data source used in wildlife studies to monitor population dynamics and habitat use. These spatial networks capture which regions of a population''s spatial distribution share similar/dissimilar individual usage patterns, and can be especially useful for detecting structured habitat use within the population''s spatial range.
3. Using simulations and 18 years of capture–recapture data from St. Lawrence Estuary (SLE) beluga, we show that this approach can successfully estimate the magnitude of similarities/dissimilarities in individual usage patterns across sectors, and identify sectors that share similar individual usage patterns that differ from other sectors, that is, structured habitat use. In the case of SLE beluga, this method identified multiple clusters of individuals, each preferentially using restricted areas within their summer range of the SLE.
4. Multilevel binomial models can be effective at estimating spatial structure in habitat use within wildlife populations sampled by capture–recapture of individuals, and can be especially useful when sampling effort is not evenly distributed. Our finding of a structured habitat use within the SLE beluga summer range has direct implications for estimating individual exposures to localized stressors, such as underwater noise from shipping or other activities.

     

Density‐dependent demography and movements in a cyclic brown lemming population

Theoretical modeling predicts that both direct and delayed density‐dependence are key factors to generate population cycles. Deciphering density‐dependent processes that lead to variable population growth characterizing different phases of the cycles remains challenging. This is particularly the case for the period of prolonged low densities, which is inherently data deficient. However, demographic analyses based on long‐term capture–mark–recapture datasets can help resolve this question. We relied on a 16‐year (2004–2019) live‐trapping program to analyze the summer demography and movements of a cyclic brown lemming population in the Canadian Arctic. More specifically, we examined if inversely density‐dependent processes could explain why population growth can remain low during the prolonged low phase. We found that the proportion of females in the population was inversely density‐dependent with a strong male‐biased sex ratio at low densities but not at high densities. However, survival of adult females was higher than adult males, but both had lower survival at low densities than at high ones. Distances moved by both adult males and females were density‐dependent, and proportion of females in reproductive condition was weakly density‐dependent as it tended to increase at low density. Individual body condition, measured as monthly change in body mass, was not density‐dependent. Overall, the strong male‐biased sex ratio at very low densities suggests a loss of reproductive potential due to the rarity of females and appears to be the most susceptible demographic factor that could contribute to the prolonged low phase in cyclic brown lemmings. What leads to this sex‐bias in the first place is still unclear, potentially owing to our trapping period limited to the summer, but we suggest that it could be due to high predation rate on breeding females in winter.     

Demographic responses to climate‐driven variation in habitat quality across the annual cycle of a migratory bird species

The demography and dynamics of migratory bird populations depend on patterns of movement and habitat quality across the annual cycle. We leveraged archival GPS‐tagging data, climate data, remote‐sensed vegetation data, and bird‐banding data to better understand the dynamics of black‐headed grosbeak (Pheucticus melanocephalus) populations in two breeding regions, the coast and Central Valley of California (Coastal California) and the Sierra Nevada mountain range (Sierra Nevada), over 28 years (1992–2019). Drought conditions across the annual cycle and rainfall timing on the molting grounds influenced seasonal habitat characteristics, including vegetation greenness and phenology (maturity dates). We developed a novel integrated population model with population state informed by adult capture data, recruitment rates informed by age‐specific capture data and climate covariates, and survival rates informed by adult capture–mark–recapture data and climate covariates. Population size was relatively variable among years for Coastal California, where numbers of recruits and survivors were positively correlated, and years of population increase were largely driven by recruitment. In the Sierra Nevada, population size was more consistent and showed stronger evidence of population regulation (numbers of recruits and survivors negatively correlated). Neither region showed evidence of long‐term population trend. We found only weak support for most climate–demographic rate relationships. However, recruitment rates for the Coastal California region were higher when rainfall was relatively early on the molting grounds and when wintering grounds were relatively cool and wet. We suggest that our approach of integrating movement, climate, and demographic data within a novel modeling framework can provide a useful method for better understanding the dynamics of broadly distributed migratory species.     

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.     

Integrating growth and survival models for flexible estimation of size‐dependent survival in a cryptic,endangered snake

Estimates of demographic rates for animal populations and individuals have many applications for ecological and conservation research. In many animals, survival is size‐dependent, but estimating the form of the size–survival relationship presents challenges. For elusive species with low recapture rates, individuals’ size will be unknown at many points in time. Integrating growth and capture–mark–recapture models in a Bayesian framework empowers researchers to impute missing size data, with uncertainty, and include size as a covariate of survival, capture probability, and presence on‐site. If there is no theoretical expectation for the shape of the size–survival relationship, spline functions can allow for fitting flexible, data‐driven estimates. We use long‐term capture–mark–recapture data from the endangered San Francisco gartersnake (Thamnophis sirtalis tetrataenia) to fit an integrated growth–survival model. Growth models showed that females reach longer asymptotic lengths than males and that the magnitude of sexual size dimorphism differed among populations. The capture probability and availability of San Francisco gartersnakes for capture increased with snout–vent length. The survival rate of female snakes exhibits a nonlinear relationship with snout–vent length (SVL), with survival flat between 300 mm and 550 mm SVL before decreasing for females between 550 mm and 700 mm SVL. For male snakes, survival decreased for adult males >550 mm SVL. The survival rates of the smallest and largest San Francisco gartersnakes were highly uncertain because recapture rates were very low for these sizes. By integrating growth and survival models and using penalized splines, we found support for size‐dependent survival in San Francisco gartersnakes. Our results have applications for devising management activities for this endangered subspecies, and our methods could be applied broadly to the study of size‐dependent demography among animals.     

Reduced habitat quality increases intrinsic but not ecological costs of reproduction

Although the costs of reproduction are predicted to vary with the quality of the breeding habitat thereby affecting population dynamics and life‐history trade‐offs, empirical evidence for this pattern remains sparse and equivocal. Costs of reproduction can operate through immediate ecological mechanisms or through delayed intrinsic mechanisms. Ignoring these separate pathways might hinder the identification of costs and the understanding of their consequences. We experimentally investigated the survival costs of reproduction for adult little owls (Athene noctua) within a gradient of habitat quality. We supplemented food to nestlings, thereby relieving the parents’ effort for brood provisioning. We used radio‐tracking and Bayesian multistate modeling based on marked recapture and dead recovery to estimate survival rates of adult little owls across the year as a function of food supplementation and habitat characteristics. Food supplementation to nestlings during the breeding season increased parental survival not only during the breeding season but also during the rest of the year. Thus, the low survival of parents of unfed broods likely represents both, strong ecological and strong intrinsic costs of reproduction. However, while immediate ecological costs occurred also in high‐quality habitats, intrinsic costs carrying over to the post‐breeding period occurred only in low‐quality habitats. Our results suggest that immediate costs resulting from ecological mechanisms such as predation, are high also in territories of high habitat quality. Long‐term costs resulting from intrinsic trade‐offs, however, are only paid in low‐quality habitats. Consequently, differential effects of habitat quality on immediate ecological and delayed intrinsic mechanisms can mask the increase of costs of reproduction in low‐quality breeding habitats. Intrinsic costs may represent an underrated mechanism of habitat quality affecting adult survival rate thereby considerably accelerating population decline in degrading habitats. This study therefore highlights the need for a long‐term perspective to fully assess the costs of reproduction and the role of habitat quality in modifying these costs.     

Effects of forest disturbance on the fitness of an endemic rodent in a biodiversity hotspot

Praomys delectorum occurs abundantly in both disturbed and intact forests in the Ukaguru Mountains within the Eastern Arc Mountains (EAM), Morogoro, Tanzania. While previous studies have reported that anthropogenic disturbances such as grazing, wood cutting, and harvesting have a positive effect on the population density of P. delectorum, the impact of habitat disturbance on its demographic traits is still unknown. We performed a capture–mark–recapture study in both disturbed and intact forests from June 2018 to February 2020 in order to investigate the effects of habitat disturbance on abundance and two demographic traits: survival and maturation of P. delectorum in the Ukaguru Mountains. We found no variation in abundance or maturation between intact and disturbed forests, but habitat type did affect survival. However, this effect was sex‐dependent since female survival was higher in disturbed forests, while male survival remained similar across the two forest types potentially due to differences in predation pressure or food availability between the two habitats. Continuous demographic monitoring of P. delectorum in EAM is necessary given that the increasing human population surrounding the landscape is leading to higher deforestation rates and expansion of the pine plantation in the forest reserve.     

Considering sampling bias in close‐kin mark–recapture abundance estimates of Atlantic salmon

Genetic methods for the estimation of population size can be powerful alternatives to conventional methods. Close‐kin mark–recapture (CKMR) is based on the principles of conventional mark–recapture, but instead of being physically marked, individuals are marked through their close kin. The aim of this study was to evaluate the potential of CKMR for the estimation of spawner abundance in Atlantic salmon and how age, sex, spatial, and temporal sampling bias may affect CKMR estimates. Spawner abundance in a wild population was estimated from genetic samples of adults returning in 2018 and of their potential offspring collected in 2019. Adult samples were obtained in two ways. First, adults were sampled and released alive in the breeding habitat during spawning surveys. Second, genetic samples were collected from out‐migrating smolts PIT‐tagged in 2017 and registered when returning as adults in 2018. CKMR estimates based on adult samples collected during spawning surveys were somewhat higher than conventional counts. Uncertainty was small (CV < 0.15), due to the detection of a high number of parent–offspring pairs. Sampling of adults was age‐ and size‐biased and correction for those biases resulted in moderate changes in the CKMR estimate. Juvenile dispersal was limited, but spatially balanced sampling of adults rendered CKMR estimates robust to spatially biased sampling of juveniles. CKMR estimates based on returning PIT‐tagged adults were approximately twice as high as estimates based on samples collected during spawning surveys. We suggest that estimates based on PIT‐tagged fish reflect the total abundance of adults entering the river, while estimates based on samples collected during spawning surveys reflect the abundance of adults present in the breeding habitat at the time of spawning. Our study showed that CKMR can be used to estimate spawner abundance in Atlantic salmon, with a moderate sampling effort, but a carefully designed sampling regime is required.     

Spatial capture–recapture with random thinning for unidentified encounters

1. Spatial capture–recapture (SCR) models have increasingly been used as a basis for combining capture–recapture data types with variable levels of individual identity information to estimate population density and other demographic parameters. Recent examples are the unmarked SCR (or spatial count model), where no individual identities are available and spatial mark–resight (SMR) where individual identities are available for only a marked subset of the population. Currently lacking, though, is a model that allows unidentified samples to be combined with identified samples when there are no separate classes of “marked” and “unmarked” individuals and when the two sample types cannot be considered as arising from two independent observation models. This is a common scenario when using noninvasive sampling methods, for example, when analyzing data on identified and unidentified photographs or scats from the same sites.
2. Here we describe a “random thinning” SCR model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model. Our model was fitted in a Bayesian framework using NIMBLE.
3. We investigate the improvement in parameter estimates by including the unknown identity samples, which was notable (up to 79% more precise) in low‐density populations with a low rate of identified encounters. We then applied the random thinning SCR model to a noninvasive genetic sampling study of brown bear (Ursus arctos) density in Oriental Cantabrian Mountains (North Spain).
4. Our model can improve density estimation for noninvasive sampling studies for low‐density populations with low rates of individual identification, by making use of available data that might otherwise be discarded.

     

Climate influences on female survival in a declining population of southern elephant seals (Mirounga leonina)

The Southern Ocean has been disproportionately affected by climate change and is therefore an ideal place to study the influence of changing environmental conditions on ecosystems. Changes in the demography of predator populations are indicators of broader shifts in food web structure, but long‐term data are required to study these effects. Southern elephant seals (Mirounga leonina) from Macquarie Island have consistently decreased in population size while all other major populations across the Southern Ocean have recently stabilized or are increasing. Two long‐term mark‐recapture studies (1956–1967 and 1993–2009) have monitored this population, which provides an opportunity to investigate demographic performance over a range of climatic conditions. Using a 9‐state matrix population model, we estimated climate influences on female survival by incorporating two major climatic indices into our model: The Southern Annular Mode (SAM) and the Southern Oscillation Index (SOI). Our best model included a 1 year lagged effect of SAM and an unlagged SOI as covariates. A positive relationship with SAM1 (lagged) related the previous year''s SAM with juvenile survival, potentially due to changes in local prey availability surrounding Macquarie Island. The unlagged SOI had a negative effect on both juvenile and adult seals, indicating that sea ice dynamics and access to foraging grounds on the East Antarctic continental shelf could explain the different contributions of ENSO events on the survival of females in this population.     

Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016

The Arctic Ocean is undergoing rapid transformation toward a seasonally ice‐free ecosystem. As ice‐adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food‐web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska''s SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite‐telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.     

Population and genetic outcomes 20 years after reintroducing bobcats (Lynx rufus) to Cumberland Island,Georgia USA

In 1988–1989, 32 bobcats Lynx rufus were reintroduced to Cumberland Island (CUIS), Georgia, USA, from which they had previously been extirpated. They were monitored intensively for 3 years immediately post‐reintroduction, but no estimation of the size or genetic diversity of the population had been conducted in over 20 years since reintroduction. We returned to CUIS in 2012 to estimate abundance and effective population size of the present‐day population, as well as to quantify genetic diversity and inbreeding. We amplified 12 nuclear microsatellite loci from DNA isolated from scats to establish genetic profiles to identify individuals. We used spatially explicit capture–recapture population estimation to estimate abundance. From nine unique genetic profiles, we estimate a population size of 14.4 (SE = 3.052) bobcats, with an effective population size (N _e) of 5–8 breeding individuals. This is consistent with predictions of a population viability analysis conducted at the time of reintroduction, which estimated the population would average 12–13 bobcats after 10 years. We identified several pairs of related bobcats (parent‐offspring and full siblings), but ~75% of the pairwise comparisons were typical of unrelated individuals, and only one individual appeared inbred. Despite the small population size and other indications that it has likely experienced a genetic bottleneck, levels of genetic diversity in the CUIS bobcat population remain high compared to other mammalian carnivores. The reintroduction of bobcats to CUIS provides an opportunity to study changes in genetic diversity in an insular population without risk to this common species. Opportunities for natural immigration to the island are limited; therefore, continued monitoring and supplemental bobcat reintroductions could be used to evaluate the effect of different management strategies to maintain genetic diversity and population viability. The successful reintroduction and maintenance of a bobcat population on CUIS illustrates the suitability of translocation as a management tool for re‐establishing felid populations.     

Habitat‐dependent population regulation in an irrupting population of long‐nosed bandicoots (Perameles nasuta)

We used isodars to analyse habitat‐dependent population regulation by long‐nosed bandicoots Perameles nasuta during an irruption and subsequent population crash in three habitats (heath, woodland and forest) at Booderee National Park, south‐eastern Australia. Specifically, we aimed to see whether patterns of habitat‐dependent population regulation matched a priori estimates of quantitative and qualitative differences between habitats. We also tested if habitat preference changed between the increasing and decreasing phase of the irruption as predicted by the reciprocating dispersal theory. Quantitative differences in habitat quality were indexed by the relative abundance of the main food of long‐nosed bandicoots (terrestrial invertebrates), while qualitative differences were indexed by the availability of refuge from predation (vegetation understorey density). One index of fitness, body weight, was highest in forest, and lowest in heath, suggesting an ideal despotic model of habitat selection. Over the entire course of the irruption, there was density‐dependent habitat selection with forest and woodland both quantitatively superior to heath. This reflected the overall abundance of invertebrates with highest abundance in woodland and forest and less in heath. Isodar analysis also revealed that although forest was quantitatively better than heath and equivalent to woodland it was qualitatively poorer than either habitat. Heath had a higher density of understorey than woodland and woodland having a higher density of understorey than forest giving crossover population regulation. When the increasing and declining phase of the irruption were analysed separately, no habitat was quantitatively superior to any other during either phase. The lack of switching in preference between habitats from the increasing to the declining phase of the irruption and the virtual absence of any dispersal by adults, does not support the reciprocating dispersal hypothesis.     

Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data

Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true abundance, which is common in capture–recapture settings. However, many of the models proposed to estimate abundance in the presence of capture heterogeneity lead to incomplete likelihood functions and cannot be straightforwardly included in state‐space models. We assessed the importance of estimating sampling error explicitly by taking an intermediate approach between ignoring uncertainty in abundance estimates and fully specified state‐space models for density‐dependence estimation based on autoregressive processes. First, we estimated individual capture probabilities based on a heterogeneity model for a closed population, using a conditional multinomial likelihood, followed by a Horvitz–Thompson estimate for abundance. Second, we estimated coefficients of autoregressive models for the log abundance. Inference was performed using the methodology of integrated nested Laplace approximation (INLA). We performed an extensive simulation study to compare our approach with estimates disregarding capture history information, and using R‐package VGAM, for different parameter specifications. The methods were then applied to a real data set of gray‐sided voles Myodes rufocanus from Northern Norway. We found that density‐dependence estimation was improved when explicitly modeling sampling error in scenarios with low process variances, in which differences in coverage reached up to 8% in estimating the coefficients of the autoregressive processes. In this case, the bias also increased assuming a Poisson distribution in the observational model. For high process variances, the differences between methods were small and it appeared less important to model heterogeneity.     

Strong influence of microhabitat on survival for an intertidal snail, <Emphasis Type="Italic">Nucella lima</Emphasis>

Within a population, survival can vary widely among individuals based upon numerous aspects of the phenotype, including (but not limited to) age, size, and habitat use. We examined the role of microhabitat use, individual color, and length, in explaining within-population variation in survival for an intertidal snail, Nucella lima. We used a multi-state capture–mark–recapture approach to determine survival and movement rates and found that favored models constrained survival to be a function of microhabitat. Survival estimates from the best-fit model were different between habitat types, despite the fact that habitats were immediately adjacent. Fidelity and disproportionate movement into the habitat with the highest survival suggested possible adaptive habitat choice. This study highlights the importance of small-scale variation in influencing population vital rates, as well as the need for quantifying within-population heterogeneity in survival.     

The type of leg lost affects habitat use but not survival in a non‐regenerating arthropod

Finding shelter and surviving encounters with predators are pervasive challenges for animals. These challenges may be exacerbated after individuals experience bodily damage. Certain forms of damage arise voluntarily in animals; for instance, some taxa release appendages (tails, legs, or other body parts) as a defensive strategy (“autotomy”). This behavior, however, may pose long‐term negative consequences for habitat use and survival. Additionally, these putative consequences are expected to vary according to the function of the lost body part. We tested the effects of losing different functional leg types (locomotor or sensory) on future habitat use and survival in a Neotropical species of Prionostemma harvestmen (Arachnida: Opiliones) that undergo frequent autotomy but do not regrow limbs. Daytime surveys revealed that both eight‐legged harvestmen and harvestmen missing legs roosted in similar frequencies across habitats (tree bark, mossy tree, or fern), and perched at similar heights. Mark–recapture data showed that harvestmen that lost sensory legs roosted in tree bark less frequently, but on mossy trees more frequently. On the contrary, we did not observe changes in habitat use for eight‐legged animals or animals that lost locomotor legs. This change might be related to sensory exploration and navigation. Lastly, we found that recapture rates across substrates were not affected by the type of legs lost, suggesting that leg loss does not impact survival. This potential lack of effect might play a role in why a defensive strategy like autotomy is so prevalent in harvestmen despite the lack of regeneration.     

Lions in a coexistence landscape: Repurposing a traditional field technique to monitor an elusive carnivore

Throughout Africa, lions are thought to have experienced dramatic population decline and range contraction. The greatest declines are likely occurring in human‐dominated landscapes where reliably estimating lion populations is particularly challenging. By adapting a method that has thus far only been applied to animals that are habituated to vehicles, we estimate lion density in two community areas in Kenya''s South Rift, located more than 100 km from the nearest protected area (PA). More specifically, we conducted an 89‐day survey using unstructured spatial sampling coupled with playbacks, a commonly used field technique, and estimated lion density using spatial capture‐recapture (SCR) models. Our estimated density of 5.9 lions over the age of 1 year per 100 km² compares favorably with many PAs and suggests that this is a key lion population that could be crucial for connectivity across the wider landscape. We discuss the possible mechanisms supporting this density and demonstrate how rigorous field methods combined with robust analyses can produce reliable population estimates within human‐dominated landscapes.     

Dyke demolition led to a sharp decline in waterbird diversity due to habitat quality reduction: A case study of Dongting Lake,China

Dongting Lake, an important wintering habitat for migratory waterbirds in the East Asian–Australasian Flyway, has suffered serious degradation in recent decades. To restore habitats for biodiversity conservation and flood control, 459 dykes were demolished and 14 were preserved in 2017. However, the direct impact of dyke demolition on wintering waterbirds was not comprehensively assessed. In this study, based on annual waterbird census and habitat data (2013/14–2020/21), we compared the differences in habitat areas and species composition of waterbirds in the dyke‐demolished and preserved areas, and explored whether habitat changes caused by the dyke demolition were responsible for the changes in the number of species and percentages of waterbird individuals. The results indicate that the areas of water (including shallow water) and mudflat habitats significantly decreased, but the vegetation area significantly increased in the dyke‐demolished areas. The species numbers and percentages of waterbird individuals at the community and foraging guilds levels, and the percentages of nine species, were higher in the dyke‐preserved areas than those in the dyke‐demolished areas. Changes in the numbers of species and percentages of individuals of fish eaters, insectivores, and omnivores positively correlated with drastic changes in the percentages of water habitats (including shallow water) after dyke demolition. Effective measures should be carried out to restore hydrological regimes, providing waterbirds sufficient suitable habitats with different water depths. These findings improve our understanding of the influence of dyke demolition on waterbirds and provide insights for wetland management and waterbird conservation.