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Moqanaki, Ehsan M., Cyril Milleret, Mahdieh Tourani, Pierre Dupont, and Richard Bischof. "Consequences of ignoring variable and spatially autocorrelated detection probability in spatial capture-recapture." Landscape Ecology 36, no. 10 (2021): 2879–95. http://dx.doi.org/10.1007/s10980-021-01283-x.
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Abstract Context Spatial capture-recapture (SCR) models are increasingly popular for analyzing wildlife monitoring data. SCR can account for spatial heterogeneity in detection that arises from individual space use (detection kernel), variation in the sampling process, and the distribution of individuals (density). However, unexplained and unmodeled spatial heterogeneity in detectability may remain due to cryptic factors, both intrinsic and extrinsic to the study system. This is the case, for example, when covariates coding for variable effort and detection probability in general are incomplete or entirely lacking. Objectives We identify how the magnitude and configuration of unmodeled, spatially variable detection probability influence SCR parameter estimates. Methods We simulated SCR data with spatially variable and autocorrelated detection probability. We then fitted an SCR model ignoring this variation to the simulated data and assessed the impact of model misspecification on inferences. Results Highly-autocorrelated spatial heterogeneity in detection probability (Moran’s I = 0.85–0.96), modulated by the magnitude of the unmodeled heterogeneity, can lead to pronounced negative bias (up to 65%, or about 44-fold decrease compared to the reference scenario), reduction in precision (249% or 2.5-fold) and coverage probability of the 95% credible intervals associated with abundance estimates to 0. Conversely, at low levels of spatial autocorrelation (median Moran’s I = 0), even severe unmodeled heterogeneity in detection probability did not lead to pronounced bias and only caused slight reductions in precision and coverage of abundance estimates. Conclusions Unknown and unmodeled variation in detection probability is liable to be the norm, rather than the exception, in SCR studies. We encourage practitioners to consider the impact that spatial autocorrelation in detectability has on their inferences and urge the development of SCR methods that can take structured, unknown or partially unknown spatial variability in detection probability into account.
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Lindsø, Lars K., Pierre Dupont, Lars Rød-Eriksen, et al. "Estimating red fox density using non-invasive genetic sampling and spatial capture–recapture modelling." Oecologia 198, no. 1 (2021): 139–51. http://dx.doi.org/10.1007/s00442-021-05087-3.
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AbstractSpatial capture–recapture modelling (SCR) is a powerful tool for estimating density, population size, and space use of elusive animals. Here, we applied SCR modelling to non-invasive genetic sampling (NGS) data to estimate red fox (Vulpes vulpes) densities in two areas of boreal forest in central (2016–2018) and southern Norway (2017–2018). Estimated densities were overall lower in the central study area (mean = 0.04 foxes per km2 in 2016, 0.10 in 2017, and 0.06 in 2018) compared to the southern study area (0.16 in 2017 and 0.09 in 2018). We found a positive effect of forest cover on density in the central, but not the southern study area. The absence of an effect in the southern area may reflect a paucity of evidence caused by low variation in forest cover. Estimated mean home-range size in the central study area was 45 km2 [95%CI 34–60] for females and 88 km2 [69–113] for males. Mean home-range sizes were smaller in the southern study area (26 km2 [16–42] for females and 56 km2 [35–91] for males). In both study areas, detection probability was session-dependent and affected by sampling effort. This study highlights how SCR modelling in combination with NGS can be used to efficiently monitor red fox populations, and simultaneously incorporate ecological factors and estimate their effects on population density and space use.
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Schmidt, Benedikt R., Anita Meier, Chris Sutherland, and J. Andy Royle. "Spatial capture–recapture analysis of artificial cover board survey data reveals small scale spatial variation in slow-worm Anguis fragilis density." Royal Society Open Science 4, no. 9 (2017): 170374. http://dx.doi.org/10.1098/rsos.170374.
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Vague and/or ad hoc definitions of the area sampled in monitoring efforts are common, and estimates of ecological state variables (e.g. distribution and abundance) can be sensitive to such specifications. The uncertainty in population metrics due to data deficiencies, vague definitions of space and lack of standardized protocols is a major challenge for monitoring, managing and conserving amphibian and reptile populations globally. This is especially true for the slow-worm ( Anguis fragilis ), a cryptic and fossorial legless lizard; uncertainty about spatial variation in density has hindered conservation efforts (e.g. in translocation projects). Spatial capture–recapture (SCR) methods can be used to estimate density while simultaneously and explicitly accounting for space and individual movement. We use SCR to analyse mark–recapture data of the slow-worm that were collected using artificial cover objects (ACO). Detectability varied among ACO grids and through the season. Estimates of slow-worm density varied across ACO grids (13, 45 and 46 individuals ha −1 , respectively). The estimated 95% home range size of slow-worms was 0.38 ha. Our estimates provide valuable information about slow-worm spatial ecology that can be used to inform future conservation management.
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Widodo, Febri Anggriawan, Stephanus Hanny, Eko Hery Satriyo Utomo, et al. "Tigers and Their Prey in Bukit Rimbang Bukit Baling: Abundance Baseline for Effective Wildlife Reserve Management." Jurnal Ilmu Kehutanan 11, no. 2 (2017): 118. http://dx.doi.org/10.22146/jik.28275.
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Managing the critically endangered Sumatran tiger (Panthera tigris sumatrae) needs accurate information on its abundance and availability of prey at the landscape level. Bukit Rimbang Bukit Baling Wildlife Reserve in central Sumatra represents an important area for tigers at local, regional and global levels. The area has been recognized as a long-term priority Tiger Conservation Landscape. Solid baseline information on tigers and prey is fundamentally needed for the management. The objective of this study was to produce robust estimate of tiger density and prey a vailability in the reserve. We used camera traps to systematically collecting photographic samples of tigers and prey using Spatial Capture Recapture (SCR) framework. We estimated density for tigers and calculated trap success rate (TSR; independent pictures/100 trap nights) for main prey species. Three blocks in the reserve were sampled from 2012 to 2015 accumulating a total of 8,125 effective trap nights. We captured 14 tiger individuals including three cubs. We documented the highest density of tigers (individuals/100 km2) in southern sampling block (based on traditional capture recapture (TCR) : 1.52 ± SE 0.55; based on Maximum Likelihood (ML) SCR:0.51 ± SE 0.22) and the lowest in northeastern sampling block (TCR: 0.77 ±SE 0.39; ML SCR: 0.19 ± SE 0.16). The highest TSR of main prey (large ungulates and primates) was in northeastern block (35.01 ± SD 8.67) and the lowest was in southern block (12.42 ± SD 2.91). The highest level of disturbance, as indicated by TSR of people, was in northeastern sampling block (5.45 ± SD 5.64) and the lowest in southern (1.26 ± SD 2.41). The results suggested that human disturbance strongly determine the density of tigers in the area, more than prey availability. To recover tigers, suggested strategies include controlling human disturbance and poaching to the lowest possible level in addition to maintaining main prey availability.Keywords: Capture-Mark-Recapture; closed population; habitat management; population viability; tiger recovery Harimau dan Mangsanya di Bukit Rimbang Bukit Baling: Basis Informasi Kelimpahan untuk Pengelolaan Suaka Margasatwa yang EfektifIntisariMengelola spesies kunci seperti harimau Sumatera (Panthera tigris sumatrae) yang dalam kondisi kritis, memerlukan informasi terkait populasi satwa tersebut dan ketersediaan satwa mangsanya pada tingkat lanskap. Suaka Margasatwa Bukit Rimbang Bukit Baling di Sumatera bagian tengah merupakan sebuah kawasan penting untuk harimau baik pada tingkat lokal, regional, maupun global. Kawasan ini telah diakui sebagai sebuah kawasan prioritas jangka panjang Tiger Conservation Landascapes (TCL). Informasi dasar yang sahih mengenai populasi harimau dan mangsanya sangat dibutuhkan untuk pengelolaan efektif satwa tersebut dan kawasan habitatnya. Tujuan dari studi ini adalah untuk menghasilkan perkiraan kepadatan populasi harimau dan ketersediaan mangsanya di kawasan suaka margasatwa tersebut. Kami menggunakan perangkap kamera untuk mengumpulkan sampel gambar harimau dan mangsanya secara sistematis menggunakan kerangka kerja Spatial Capture Recapture (SCR). Kami memperkirakan kepadatan harimau dan menghitung angka keberhasilan perangkap atau trap success rate (TSR: gambar independen/100 hari aktif kamera) untuk satwa mangsa utama. Tiga blok di dalam suaka margasatwa telah disurvei dari tahun 2012 hingga 2015 mengakumulasikan keseluruhan 8,125 hari kamera aktif. Kami merekam 14 individu harimau termasuk tiga anak. Kami mendokumentasikan kepadatan tertinggi harimau (individu/100 km2) di blok sampling selatan (berdasarkan pendekatan analisa capture recapture tradisional (TCR) 1.52 ± SE 0.55; berdasarkan Maximum Likelihood (ML) SCR 0.51 ± SE 0.22) dan terendah di utara-timur (TCR: 0.77 ±SE 0.39; ML SCR: 0.19 ± SE 0.16). TSR tertinggi dari mangsa utama (ungulate besar dan primata) adalah di blok sampling utara-timur (35.01 ± SD 8.67) dan terendah adalah di blok sampling selatan (12.42 ± SD 2.91). Tingkat gangguan tertinggi, sebagaimana diindikasikan oleh TSR manusia, adalah di blok sampling utara-timur (5.45 ± SD 5.64) dan terendahnya di blok sampling selatan (1.26 ± SD 2.41). Hasil studi ini mengindikasikan bahwa gangguan manusia yang sangat tinggi sangat menentukan kepadatan harimau di kawasan ini, melebihi pengaruh dari ketersediaan satwa mangsa. Untuk memulihkan populasi harimau, disarankan beberapa strategi termasuk mengendalikan gangguan manusia dan perburuan hingga ke tingkat terendah, selain tetap memastikan ketersediaan satwa mangsa utama yang memadai.
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Celva, Roberto, Barbara Crestanello, Federica Obber, et al. "Assessing Red Fox (Vulpes vulpes) Demographics to Monitor Wildlife Diseases: A Spotlight on Echinococcus multilocularis." Pathogens 12, no. 1 (2022): 60. http://dx.doi.org/10.3390/pathogens12010060.
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The assessment of red fox population density is considered relevant to the surveillance of zoonotic agents vectored by this species. However, density is difficult to estimate reliably, since the ecological plasticity and elusive behavior of this carnivore hinder classic methods of inference. In this study, red fox population density was estimated using a non-invasive molecular spatial capture-recapture (SCR) approach in two study areas: one in a known hotspot of the zoonotic cestode Echinococcus multilocularis, and another naïve to the parasite. Parasitological investigations on collected samples confirmed the presence of the parasite exclusively in the former area; the SCR results indicated a higher fox population density in the control area than in the hotspot, suggesting either that the relationship between fox density and parasite prevalence is not linear and/or the existence of other latent factors supporting the parasitic cycle in the known focus. In addition, fox spotlight count data for the two study areas were used to estimate the index of kilometric abundance (IKA). Although this method is cheaper and less time-consuming than SCR, IKA values were the highest in the areas with the lower molecular SCR density estimates, confirming that IKA should be regarded as a relative index only.
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Johnson, James T., Richard B. Chandler, L. Mike Conner, et al. "Effects of Bait on Male White-Tailed Deer Resource Selection." Animals 11, no. 8 (2021): 2334. http://dx.doi.org/10.3390/ani11082334.
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Bait is often used to increase wildlife harvest susceptibility, enhance viewing opportunities, and survey wildlife populations. The effects of baiting depend on how bait influences space use and resource selection at multiple spatial scales. Although telemetry studies allow for inferences about resource selection within home ranges (third-order selection), they provide limited information about spatial variation in density, which is the result of second-order selection. Recent advances in spatial capture-recapture (SCR) techniques allow exploration of second- and third-order selection simultaneously using non-invasive methods such as camera traps. Our objectives were to describe how short-term baiting affects white-tailed deer (Odocoileus virginianus) behavior and distribution. We fit SCR models to camera data from baited and unbaited locations in southwestern Georgia to assess the effects of short-term baiting on second- and third-order selection of deer during summer and winter surveys. We found little evidence of second-order selection during late summer or early winter surveys when camera surveys using bait are typically conducted. However, we found evidence for third-order selection, indicating that resource selection within home ranges is affected. Concentrations in space use resulting from baiting may enhance disease transmission, change harvest susceptibility, and potentially bias the outcome of camera surveys using bait.
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Marrotte, Robby R., Eric J. Howe, Kaela B. Beauclerc, Derek Potter, and Joseph M. Northrup. "Explaining detection heterogeneity with finite mixture and non-Euclidean movement in spatially explicit capture-recapture models." PeerJ 10 (June 7, 2022): e13490. http://dx.doi.org/10.7717/peerj.13490.
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Landscape structure affects animal movement. Differences between landscapes may induce heterogeneity in home range size and movement rates among individuals within a population. These types of heterogeneity can cause bias when estimating population size or density and are seldom considered during analyses. Individual heterogeneity, attributable to unknown or unobserved covariates, is often modelled using latent mixture distributions, but these are demanding of data, and abundance estimates are sensitive to the parameters of the mixture distribution. A recent extension of spatially explicit capture-recapture models allows landscape structure to be modelled explicitly by incorporating landscape connectivity using non-Euclidean least-cost paths, improving inference, especially in highly structured (riparian & mountainous) landscapes. Our objective was to investigate whether these novel models could improve inference about black bear (Ursus americanus) density. We fit spatially explicit capture-recapture models with standard and complex structures to black bear data from 51 separate study areas. We found that non-Euclidean models were supported in over half of our study areas. Associated density estimates were higher and less precise than those from simple models and only slightly more precise than those from finite mixture models. Estimates were sensitive to the scale (pixel resolution) at which least-cost paths were calculated, but there was no consistent pattern across covariates or resolutions. Our results indicate that negative bias associated with ignoring heterogeneity is potentially severe. However, the most popular method for dealing with this heterogeneity (finite mixtures) yielded potentially unreliable point estimates of abundance that may not be comparable across surveys, even in data sets with 136–350 total detections, 3–5 detections per individual, 97–283 recaptures, and 80–254 spatial recaptures. In these same study areas with high sample sizes, we expected that landscape features would not severely constrain animal movements and modelling non-Euclidian distance would not consistently improve inference. Our results suggest caution in applying non-Euclidean SCR models when there is no clear landscape covariate that is known to strongly influence the movement of the focal species, and in applying finite mixture models except when abundant data are available.
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Law, Bradley, Traecey Brassil, Roland Proud, and Joanne Potts. "Estimating density of forest bats and their long‐term trends in a climate refuge." Ecology and Evolution 13, no. 6 (2023): e10215. https://doi.org/10.5281/zenodo.14818141.
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(Uploaded by Plazi for the Bat Literature Project) For many species, estimating density is challenging, but it is important for conservation planning and understanding the functional role of species. Bats play key ecological roles, yet little is known about their free-ranging density. We used a long-term banding study of four species caught in an extensively forested climate refuge and spatial capture–recapture models (SCR) to estimate density and its change over time. Between 1999 and 2020, there were 3671 captures of four bat species, which were all edge-space foragers. Recaptures represented 16% (n = 587) of all captures, of which 89 were between-trap-cluster movements. Closed spatial mark–recapture models estimated plausible densities that varied with elevation. Preferred elevations differed between species, with density averaging 0.63 ha−1 for Vespadelus darlingtoni (high elevation), 0.43 ha−1 for V. pumilus (low elevation), 0.19 ha−1 for Chalinolobus morio (high elevation), and 0.08 ha−1 for V. regulus (high elevation). Overall, densities were higher than most previous published estimates for bats. Forest disturbance history (past timber harvesting) had no detectable effect on density. Density also varied substantially across years, and although annual maximum temperature and rainfall were not supported in models, some time periods showed an apparent relationship between density and annual rainfall (+ve) and/or annual maximum temperature (−ve). The most notable change was an increase in the density of V. pumilus after 2013, which tracked an increase in annual temperature at the site, reflecting a warming climate. Bat densities in forests outside of climate refugia are likely to be more sensitive to climate change, but more studies are needed in different habitats and continents and outside climate refugia to place the densities we estimated into a broader context.
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Jiménez, José, Raquel Godinho, Daniel Pinto, et al. "The Cantabrian capercaillie: A population on the edge." Science of The Total Environment 821 (January 29, 2022): 153523. https://doi.org/10.5281/zenodo.6352583.
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<strong>Highlights</strong> Cantabrian capercaillie population has recently been classified as "Critically Endangered" by Spanish Government. To develop management plans, information on demographic parameters are necessary to understand population dynamics. In 2019 we estimated the size of population at 191 individuals. Since the 1970s, we estimated a shrinkage of the population range by 83%. Apparent annual survival was estimated at 0.707 and per-capita recruitment at 0.233. <strong>Abstract</strong> The capercaillie <em>Tetrao urogallus</em> - the world's largest grouse - is a circumboreal forest species, which only two remaining populations in Spain: one in the Cantabrian mountains in the west and the other in the Pyrenees further east. Both have shown severe declines, especially in the Cantabrian population, which has recently been classified as “Critically Endangered”. To develop management plans, information on demographic parameters is necessary to understand and forecast population dynamics. We used spatial capture-recapture (SCR) modeling and non-invasive DNA samples to estimate the current population size in the whole Cantabrian mountain range. In addition, for the assessment of population status, we analyzed the population trajectory over the last 42 years (1978–2019) at 196 leks on the Southern slope of the range, using an integrated population model with a Dail-Madsen model at its core, combined with a multistate capture-recapture model for survival and a Poisson regression for productivity. For 2019, we estimate the size of the entire population at 191 individuals (95% BCI 165–222) for an estimated 60 (48–78) females and 131 (109–157) males. Since the 1970s, our study estimates a shrinkage of the population range by 83%. The population at the studied leks in 2019 was at about 10% of the size estimated for 1978. Apparent annual survival was estimated at 0.707 (0.677–0.735), and per-capita recruitment at 0.233 (0.207–0.262), and insufficient to maintain a stable population. We suggest work to improve the recruitment (and survival) and manage these mountain forests for capercaillie conservation. Also, in the future, management should assess the genetic viability of this population.
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F., Muammar, Abdullah, Muhibbuddin, Safrida, and Zulfikar. "Effects of Transforming Plantation Forests into Natural Forests on Elephant Habitats and Movement in Trumon-Subulussalam, Aceh." IOP Conference Series: Earth and Environmental Science 1477, no. 1 (2025): 012026. https://doi.org/10.1088/1755-1315/1477/1/012026.
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Abstract The restoration of plantation forests to natural forests had become an important approach in biodiversity conservation, especially for endangered species such as the Sumatran elephant (Elephas maximus sumatranus). This study aimed to assess the impact of the transformation of plantation forests into natural forests on the habitat and movement of Sumatran elephants in the Trumon-Subulussalam. The study population was the Sumatran elephant and the research sample was part of the elephant population in the form of evidence of the existence of elephants through purposive sampling techniques. Sample data collection was carried out by taking GPS coordinate points followed by observing the condition of the forest structure. Analysis of elephant movement data used the Spatial Capture-Recapture (SCR) approach with the Search Encounter Data model while the condition of the forest structure was analyzed by percentage. This study was conducted from January to June 2023 in Trumon Sub-district, South Aceh Regency. The results of the SCR approach provided an overview of the movement of the elephant population’s roaming area starting from the Naca Landscape, heading to Gampong Kapa Sesak and combing the riparian area of the border river between South Aceh and Subulussalam (Soraya River via Lae Kombih) and then crossing to TNGL and entering the Babur Rahmah and Leuser Districts of Southeast Aceh. The percentage of forest structure conditions based on the Type and Vegetation categories was 71% including Secondary Forest and 29% including Primary Forest; the Canopy Closure category was 67% including Very Dense (75%) and 43% including Rare (0-25%); the Food Availability category was 28% including Very Many (>75%), 29% including Many (51-75%) and 43% including Moderate (25-50%); the Mineral Source Tree Availability category was 36% including many (>3 Trees), 36% including Median (2-3 Trees) and 28% including Rare (<3 Trees). Elephant movements followed seasonal patterns, with migration occurring in April and July, influenced by food availability and mating season. These findings provided important insights for elephant conservation in the Trumon area, particularly concerning habitat management and population connectivity between regions.
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Ferreras, Pablo, José Jiménez, Francisco Díaz-Ruiz, Jorge Tobajas, Paulo Célio Alves, and Pedro Monterroso. "Integrating multiple datasets into spatially-explicit capture-recapture models to estimate the abundance of a locally scarce felid." Biodiversity and Conservation 30, no. 14 (2021): 4317–35. http://dx.doi.org/10.1007/s10531-021-02309-1.
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AbstractThe conservation of animal populations often requires the estimation of population size. Low density and secretive behaviour usually determine scarce data sources and hampers precise abundance estimations of carnivore populations. However, joint analysis of independent scarce data sources in a common modeling framework allows unbiased and precise estimates of population parameters. We aimed to estimate the density of the European wildcat (Felis silvestris) in a protected area of Spain, by combining independent datasets in a spatially-explicit capture-recapture (SCR) framework. Data from live-capture with individual identification, camera-trapping without individual identification and radio-tracking concurrently obtained were integrated in a joint SCR and count data model. Ten live captures of five wildcats were obtained with an effort of 2034 trap-days, whereas seven wildcat independent events were recorded in camera traps with 3628 camera-days. Two wildcats were radio-tagged and telemetry information on their movements was obtained. The integration of the different data sources improved the precision obtained by the standard SCR model. The mean (± SD) density estimated with the integrated model (0.038 ± 0.017 wildcats/km2, 95% highest posterior density 0.013–0.082) is among the lowest values ever reported for this species, despite corresponding to a highly protected area. Among the likely causes of such low density, low prey availability could have triggered an extinction vortex process. We postulate that the estimated low density could represent a common situation of wildcat populations in the southern Iberia, highlighting the need for further studies and urgent conservation actions in the furthermost southwestern range of this species in Europe.
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Arechavala-Lopez, P., M. Minguito-Frutos, G. Follana-Berná, and M. Palmer. "Common octopus settled in human-altered Mediterranean coastal waters: from individual home range to population dynamics." ICES Journal of Marine Science 76, no. 2 (2018): 585–97. http://dx.doi.org/10.1093/icesjms/fsy014.
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Abstract A spatially explicit capture-recapture (SCR) model was applied to estimate simultaneously population parameters and individual activity (i.e. home range size) of O. vulgaris, based on experimental mark-recapture data in a human-altered Mediterranean coastal area. Seventy-two octopuses were captured, tagged with subcutaneous PIT-tags and released. Nineteen tagged individuals were recaptured (recapture rate: 26.4%) in the same area over the study period, which spanned over 6 months. Population sizes and densities decreased over the study period, from 337 octopuses (8 ind. ha−1) in September-October to 105 octopuses (2.5 ind. ha−1) in February-March. The highest recruitment probability was estimated to occur at the beginning of the study but it clearly decreased over time, while mortality probability during a fishing period slightly increased. Mean specific growth rate was 0.82 ± 0.11 day−1. Individual home range or activity area ranged from 2.8 ha to 7.3 ha (median home range radius: 121.8 m). Overall, these results suggest that human-altered coastal habitats, which are characterized by abundant shelters, abundant food and absence of predators, can act as settlement and growth areas for juveniles and adults of O. vulgaris. Furthermore, the methodologies applied in this study are recommended as innovative tools to improve management actions of coastal resources.
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Juhasz, Claire-Cécile, Naïs Avargues, Laurence Humeau, et al. "Application of genetic and Spatially Explicit Capture-Recapture analyses to design adaptive feral cat control in a large inhabited island." NeoBiota 79 (December 23, 2022): 51–85. https://doi.org/10.3897/neobiota.79.87726.
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Faunas of oceanic islands have a high proportion of endemic species which contribute to the uniqueness of island communities. Island species are particularly naïve and vulnerable to alien predators, such as cats (Felis catus). On large, inhabited islands, where the complete eradication of feral cat populations is not considered feasible, control represents the best management option to lower their detrimental effects on native fauna. The first objective of our study was to investigate population genetics of feral cats of Réunion Island. The second objective was to understand the space use of feral cats established near the breeding colonies of the two endemic and endangered seabirds of Réunion Island, the Barau's Petrel (Pterodroma baraui) and the Mascarene Petrel (Pseudobulweria aterrima). We evaluated genetic diversity, population structure and gene flow amongst six groups of feral cats located at a maximum of 10 km from known petrel colonies. We also analysed the behaviour and space use of one of these feral cat groups using camera-trap data and Spatially Explicit Capture-Recapture (SECR) models. Genetic analyses revealed that feral cats were structured in three genetic clusters explained mostly by the island topography. Two clusters were observed at five sampled sites, suggesting high connectivity amongst these sites. The last cluster was found in only one site, suggesting high isolation. This site was a remote mountain area located in the vicinity of one of the main Barau's Petrel colonies. The behavioural study was conducted on this isolated feral cat population. Mark recapture analysis suggested that feral cats were present at low density and had large home ranges, which is probably explained by reduced food availability. Finally, we make several recommendations for refining feral cat management programmes on inhabited islands.
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Courtenay, Orin, José F. Marinho-Júnior, Maria Edileuza F. Brito, Juliana F. C. L. S. Monteiro, Jeffrey J. Shaw, and Sinval P. Brandão-Filho. "Incidence of Human and Free-Ranging Wild Rodent Infections with Leishmania (Viannia) braziliensis, Aetiological Agent of Cutaneous Leishmaniasis." Pathogens 12, no. 12 (2023): 1395. http://dx.doi.org/10.3390/pathogens12121395.
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Background. Human and wild rodent infection rates with Leishmania (Viannia) braziliensis are needed to differentiate transmission pathways in anthropogenically altered habitats. Methods. Human participants in northeast Brazil were tested by the leishmanin skin test (LST) and inspected for lesions/scars characteristic of American clinical leishmaniasis (ACL). Molecular (PCR/qPCR) test records of free-ranging rodents were available from a concurrent capture–mark–recapture study. Force of Infection (λ) and recovery (ρ) rates were estimated from cross-sectional and longitudinal datasets. Results. Cumulative prevalences of human LST+ves and ACL scar+ves were 0.343–0.563 (n = 503 participants) and 0.122–0.475 (n = 503), respectively. Active ACL lesions were not detected. Annual rates of LST conversions were λ = 0.03–0.15 and ρ = 0.02–0.07. The probability of infection was independent of sex and associated with increasing age in addition to the period of exposure. Rodents (n = 596 individuals of 6 species) showed high rates of exclusively asymptomatic infection (λ = 0.222/month) and potential infectiousness to the sand fly vector. Spatially concurrent rodent and household human infection prevalences were correlated. Conclusions. Human exposure to L. (V.) braziliensis continues to be high despite the substantial drop in reported ACL cases in recent years. Spill-over transmission risk to humans from rodents in peridomestic habitats is likely supported by a rodent infection/transmission corridor linking houses, plantations, and the Atlantic Forest.
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Kodi, Abinand Reddy, Jasmin Howard, David Louis Borchers, et al. "Ghostbusting—Reducing bias due to identification errors in spatial capture‐recapture histories." Methods in Ecology and Evolution, April 21, 2024. http://dx.doi.org/10.1111/2041-210x.14326.
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Abstract Identifying individuals is key to estimating population sizes by spatial capture–recapture, but identification errors are sometimes made. The most common identification error is the failure to recognise a previously detected individual, thus creating a ‘ghost’ Johansson. This results in positively biased abundance estimates. Ghosts typically manifest as single detection individuals (‘singletons’) in the capture history. To deal with ghosts, we develop a spatial capture–recapture method conditioned on at least detections. The standard spatial capture–recapture (SCR) model is the special case of . Ghosts can mostly be excluded by fitting a model with (SCR‐2). We investigated the effect of ‘singleton’ ghosts on the estimation of the model parameters by simulation. The SCR method increasingly overestimated abundance with increasing percentage of ghosts, with positive bias even when only 10% of the detected individuals were ghosts, and bias between 43% and 71% when 30% were ghosts. Estimates from the SCR‐2 method showed lower bias in the presence of ghosts, at the cost of a loss of precision. The mean squared error of the estimated abundance from the SCR‐2 method was lower in all scenarios with ghosts under high encounter rates and for scenarios with 30% or more ghosts with low encounter rates. We also applied our method to capture histories from camera trap surveys of snow leopards (Panthera uncia) at two sites from Mongolia and find that the SCR method produced higher abundance estimates at both sites. Capture histories are susceptible to errors when generated from passive detectors such as camera traps and genetic samples. The SCR‐2 method can remove bias from ghost capture histories, at the cost of some loss in precision. We recommend using the SCR‐2 method in cases when there may be more than 10% ghosts or surveys with a large number of single detection capture histories, except perhaps when the sample size is very low.
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Sun, Catherine, and A. Cole Burton. "The importance of independence in unmarked spatial capture–recapture analysis." Wildlife Biology, March 13, 2024. http://dx.doi.org/10.1002/wlb3.01182.
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Wildlife populations can be unmarked, meaning individuals lack distinguishing features for individual identification. Populations may also exhibit non‐independent movements, meaning individuals move together. For populations of either unmarked or non‐independent individuals, models based on spatial capture–recapture (SCR) approaches can be used to estimate abundance, density, and other parameters critical for monitoring, management, and conservation. However, when individuals are both unmarked and non‐independent, few model options are available. One approach has been to apply unmarked models and not address the non‐independence despite unquantified impacts on bias, precision, and the ability to make robust ecological inferences. We conducted a simulation study to quantify the impact of non‐independence on the performance of spatial count (SC) and spatial partial identity models (SPIM) – two SCR‐based unmarked modeling approaches – and used the performance of fully marked and independent SCR as a reference. We varied the levels of non‐independence (aggregation and cohesion), detection probability, and the number of partial identity covariates used to resolve identities in SPIM estimation. We expected abundance estimates to be increasingly biased and precise as aggregation and cohesion increased. Results showed that models indeed became less robust to increasing non‐independence, but importantly suggested that only SPIM could be reliably applied under low levels of cohesion when sufficient partial identity covariates are available. SC yielded consistently biased estimates with poor precision. SCR was consistently robust across combinations of aggregation and cohesion, as expected. We therefore advise against the use of SC models for estimating population parameters when individuals are known to be non‐independent, caution that SPIM may be used under narrow ecological conditions, and encourage continued investigations into sampling design and methods development for estimating populations of unmarked and non‐independent individuals.
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Ketwaroo, Fabian R., Eleni Matechou, Matthew Silk, and Richard Delahay. "Modeling Disease Dynamics From Spatially Explicit Capture‐Recapture Data." Environmetrics, December 2, 2024. https://doi.org/10.1002/env.2888.
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ABSTRACTOne of the main aims of wildlife disease ecology is to identify how disease dynamics vary in space and time and as a function of population density. However, monitoring spatiotemporal and density‐dependent disease dynamics in the wild is challenging because the observation process is error‐prone, which means that individuals, their disease status, and their spatial locations are unobservable, or only imperfectly observed. In this paper, we develop a novel spatially‐explicit capture‐recapture (SCR) model motivated by an SCR data set on European badgers (Meles meles), naturally infected with bovine tuberculosis (Mycobacterium bovis, TB). Our model accounts for the observation process of individuals as a function of their latent activity centers, and for their imperfectly observed disease status and its effect on demographic rates and behavior. This framework has the advantage of simultaneously modeling population demographics and disease dynamics within a spatial context. It can therefore generate estimates of critical parameters such as population size; local and global density by disease status and hence spatially‐explicit disease prevalence; disease transmission probabilities as functions of local or global population density; and demographic rates as functions of disease status. Our findings suggest that infected badgers have lower survival probability but larger home range areas than uninfected badgers, and that the data do not provide strong evidence that density has a non‐zero effect on disease transmission. We also present a simulation study, considering different scenarios of disease transmission within the population, and our findings highlight the importance of accounting for spatial variation in disease transmission and individual disease status when these affect demographic rates. Collectively these results show our new model enables a better understanding of how wildlife disease dynamics are linked to population demographics within a spatiotemporal context.
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Kendall, Katherine C., Tabitha A. Graves, J. Andrew Royle, et al. "Using bear rub data and spatial capture-recapture models to estimate trend in a brown bear population." Scientific Reports 9, no. 1 (2019). http://dx.doi.org/10.1038/s41598-019-52783-5.
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AbstractTrends in population abundance can be challenging to quantify during range expansion and contraction, when there is spatial variation in trend, or the conservation area is large. We used genetic detection data from natural bear rubbing sites and spatial capture-recapture (SCR) modeling to estimate local density and population growth rates in a grizzly bear population in northwestern Montana, USA. We visited bear rubs to collect hair in 2004, 2009—2012 (3,579—4,802 rubs) and detected 249—355 individual bears each year. We estimated the finite annual population rate of change 2004—2012 was 1.043 (95% CI = 1.017—1.069). Population density shifted from being concentrated in the north in 2004 to a more even distribution across the ecosystem by 2012. Our genetic detection sampling approach coupled with SCR modeling allowed us to estimate spatially variable growth rates of an expanding grizzly bear population and provided insight into how those patterns developed. The ability of SCR to utilize unstructured data and produce spatially explicit maps that indicate where population change is occurring promises to facilitate the monitoring of difficult-to-study species across large spatial areas.
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Murphy, Sean M., and Victor H. Luja. "Jaguar density estimation in Mexico: The conservation importance of considering home range orientation in spatial capture–recapture." Conservation Science and Practice, January 16, 2025. https://doi.org/10.1111/csp2.13301.
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AbstractAccurate estimation of population parameters for imperiled wildlife is crucial for effective conservation decision‐making. Population density is commonly used for monitoring imperiled species across space and time, and spatial capture–recapture (SCR) models can produce unbiased density estimates. However, many imperiled species are restricted to fragmented remnant habitats in landscapes severely modified by humans, which can alter animal space use in ways that violate typical SCR model assumptions, possibly cryptically biasing density estimates and misinforming conservation actions. Using data from a two‐year camera‐trapping survey in the Central Pacific Coast region, Mexico, we demonstrate the potential importance to endangered jaguar (Panthera onca) conservation of considering non‐circular home ranges when estimating population density with SCR. Strong evidence existed that jaguars had elliptical home ranges wherein movements primarily occurred along linearly arranged coastal habitats that the camera array aligned with. Accounting for this movement with the SCR anisotropic detection function transformation, density estimates were 30%–32% higher than estimates from standard SCR models that assumed circular home ranges. Given much of suitable jaguar habitat in Mexico is fragmented and linearly oriented along coastlines and mountain ranges, accommodating irregular space use in SCR may be critical for obtaining reliable density estimates to inform effective jaguar conservation.
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Choo, Yan Ru, Chris Sutherland, and Alison Johnston. "A Monte Carlo resampling framework for implementing goodness‐of‐fit tests in spatial capture‐recapture models." Methods in Ecology and Evolution, July 15, 2024. http://dx.doi.org/10.1111/2041-210x.14386.
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Abstract Spatial capture‐recapture (SCR) models provide estimates of animal density from spatially referenced encounter data and has become the most widely adopted approach for estimating density. Despite the rapid growth in the development and application of spatial capture‐recapture methods, approaches for assessing model fit have received very little attention when compared to other classes of hierarchical models in ecology. Here, we develop an approach for testing goodness‐of‐fit (GoF) for frequentist SCR models using Monte Carlo simulations. We derive probability distributions of activity centres from the fitted model. From these, we calculate the expected encounters in the capture history based on the SCR parameter estimates, propagating the uncertainty of the estimates and the activity centre locations via Monte Carlo simulations. Aggregating these test statistics result in count data, allowing us to test fit with Freeman‐Tukey tests. These tests are based on summary statistics of the total encounters of each individual at each trap (FT‐ind‐trap), total encounters of each individual (FT‐individuals) and total encounters at each trap (FT‐traps). We assess the ability of these GoF tests to diagnose lack of fit under a range of assumption violating scenarios. FT‐traps had the strongest response to unmodelled spatial and trap heterogeneity in detection probability (power = 0.53–0.56), while FT‐ind‐traps had the strongest responses to random individual variation in detectability (power = 0.88) and non‐spatial discrete variation in (power = 0.35). The tests, designed to diagnose poor fit in the detection parameters, were insensitive to unmodelled heterogeneity in density (power = <0.001). They also demonstrated low false positive rates (<0.001) when the correct models were fitted; therefore, it is very unlikely that they will provide false indications of poor model fit. We demonstrate that these GoF tests are capable of detecting lack‐of‐fit when unmodelled heterogeneity is present in the detection sub‐model. When used jointly, the combinations of test results are also able to infer the type of lack‐of‐fit in certain cases. Our Monte Carlo sampling methods may be extended to a wider range of GoF tests, thereby providing a platform for developing more GoF methods for SCR.
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Carroll, Sarah L., Greta M. Schmidt, John S. Waller, and Tabitha A. Graves. "Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models." Movement Ecology 12, no. 1 (2024). http://dx.doi.org/10.1186/s40462-023-00445-7.
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Abstract Background Improved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning. Methods We used mark-recapture data collected from 924 genetic detections of 598 American black bears (Ursus americanus) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces. Results Model results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100 km2 (95% CI 12.52–20.6) for females and 9.27 bears/100 km2 (95% CI 7.70–11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear (Ursus arctos) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity. Conclusions Density-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.
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Russell, Robin E., Daniel W. Tripp, Katherine L. D. Richgels, and Tonie E. Rocke. "3Density estimation using spatial capture‐recapture analyses: application to vaccination of prairie dogs against sylvatic plague." Journal of Wildlife Management, October 30, 2024. http://dx.doi.org/10.1002/jwmg.22685.
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AbstractPrairie dogs are notoriously difficult to enumerate, with previously methods including visual counts, mark‐resight, burrow counts, and catch per unit effort. Unlike those methods, spatial capture‐recapture (SCR) analyses allow for formal estimation of density along with associated estimates of uncertainty, detection probability, and the size of the average area over which an individual was detected during the study period (referred to as an activity center). Using SCR analyses, we compared density estimates as part of a field trial evaluating the effectiveness of an oral sylvatic plague vaccine in black‐tailed prairie dogs (Cynomys ludovicianus), Gunnison's prairie dogs (C. gunnisoni), white‐tailed prairie dogs (C. leucurus), and Utah prairie dogs (C. parvidens) at 11 study areas in the western United States. The study was designed as a matched pairs analysis that included 27 individual paired plots (54 plots), each consisting of a plot treated with vaccine baits and a plot treated with placebo baits. Overall, we captured >3,000 individuals each year on these plots, and recapture rates ranged from 5–87%. For black‐tailed prairie dogs, density estimates ranged from 2.7 individuals/ha (95% CI = 2.2–3.3/ha) to 77.3/ha (63.2–94.4/ha), and for Gunnison's prairie dogs, estimates ranged from 11.7/ha (10.6–12.8/ha) to 15.4/ha (14.4–16.7/ha). White‐tailed prairie dogs were at their lowest density (3.3/ha, 95% CI = 2.9–3.8/ha) during the first year of the study and their highest density (14.5/ha; 13.5–15.6/ha) during the last year of the study. Utah prairie dog density estimates ranged from a low of 4.0/ha (95% CI = 3.55–4.6/ha) to a high of 20.8/ha (16.8–25.8/ha). Best‐fitting models of prairie dog density indicated increasing patterns of density over time on most study plots, negative effects of plague, and positive effects of vaccination. Finally, we found low correlations between catch per unit effort estimates from previous published literature at these sites and our densities estimates. Spatial capture‐recapture estimates allowed us to consistently compare treatment effects across space and time, although some exceptions are noted where we observed significant movement between plots within a pair (3 pairs) and when trapping effort between plots or years was not consistent.
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Visagie, Marna, Robert S. Davis, Jan A. Venter, and Terry‐Lee Honiball. "Using spatial capture‐recapture models to estimate spotted hyaena (Crocuta crocuta) population density and assess the influence of sex‐specific covariates on space use and detection probability." Conservation Science and Practice, August 6, 2024. http://dx.doi.org/10.1111/csp2.13214.
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AbstractDespite being resident or reintroduced to multiple South African protected areas, spotted hyaena (Crocuta crocuta) have been subject to limited population monitoring and are not managed in the same intensive way as other large carnivores. Considering the species' significant influence on ecosystem processes, robust estimates of population density are necessary to inform conservation management. In this study, we ran a single‐season camera trap survey in the Main Camp section of Addo Elephant National Park (Addo), South Africa, and used spatial capture‐recapture (SCR) models to estimate spotted hyaena population density. Spotted hyaena density was estimated to be 11.13 (± SE 1.96) individuals/100 km2, with an estimated abundance of 37 (± SE 6.44) individuals. Using our database of sexed spotted hyaena individuals, we found no significant difference for sex‐specific SCR parameters (baseline encounter probability and spatial scale parameter), suggesting the incorporation of sex‐specific information may not be as necessary for spotted hyaena as it is for territorial felids and other species with more pronounced differences in range size. Spotted hyaena density in Addo was comparable to previous SCR studies and towards the higher end of known densities. Our estimate provides an important baseline for monitoring reintroduction success in Addo, and we advocate for increased SCR monitoring of spotted hyaena in South African protected areas to inform a metapopulation approach to the species' management.
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Martin, Marie E., David S. Green, Dustin Garrison, et al. "An integrated spatial capture–recapture approach reveals the distribution of a cryptic carnivore in a protected area." Ecosphere 14, no. 8 (2023). http://dx.doi.org/10.1002/ecs2.4634.
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AbstractQuantifying animal abundance, density, and distributions affords the opportunity to understand the effects of landscape structure and change on species of conservation interest, but estimating these parameters can be difficult for rare and cryptic species. Noninvasive sampling methods, such as remote cameras or scat DNA, can mitigate the challenges of studying rare and cryptic species while also minimizing effects on species of conservation interest or concern. Data derived from these methods can be integrated into robust, contemporary quantitative methods, including spatial capture–recapture (SCR) models, which provide a hierarchical framework for jointly estimating animal abundance, distribution, and, consequently, density. Herein, we developed an integrated SCR model to estimate the abundance, density, and distribution of a large carnivore of conservation interest, the cougar (Puma concolor), in a rugged and remote protected area, Yosemite National Park, California, USA. We combined spatial encounter data from DNA‐based individual identification of scats with detection count data derived from remote cameras to estimate cougar density and detection probability in Yosemite. We further estimated how cougar density and detection probability varied as a result of vegetation, topography, anthropogenic and natural linear features, and survey effort. Using data collected in 2019 and 2020, we estimated a median of 31 (SD = 3.96, 95% credible intervals = 24–39) cougars in Yosemite across the two years, with higher densities associated with productive, vegetated areas. We found detection probability by scent detection teams was higher for females than males and positively correlated with survey effort, proximity to trails, and distance farther from roads and streams. Our study illustrates the utility of noninvasive survey methods that yield individual identities in rugged and remote environments, where capture and handling of cryptic, low‐density animals is logistically challenging and cost prohibitive. Integrated modeling approaches, as used here, allow ecologists to leverage empirical data using a robust quantitative framework that can effectively address conservation objectives. Through this work, we demonstrate the importance of large, contiguous, and heterogeneous ecosystems to the ecology of wide‐ranging species that occur in dynamic landscapes.
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Romeu, Bianca, Fábio G. Daura‐Jorge, Philip S. Hammond, Pedro V. Castilho, and Paulo C. Simões‐Lopes. "Assessing spatial patterns and density of a dolphin population through signature whistles." Marine Mammal Science, September 15, 2023. http://dx.doi.org/10.1111/mms.13070.
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AbstractSome dolphin species produce signature whistles, which may allow the identification of individual dolphins using passive acoustic monitoring (PAM). Identifying individuals by their sounds may enhance the opportunities for monitoring and addressing biological and ecological questions about these species. Here, we explored the potential of signature whistles to investigate ecological aspects of a resident bottlenose dolphin population. Using a limited data set, with few individuals recognized by signature whistles, combined with spatial capture‐recapture (SCR) methods, we investigated how effective such approach is describing spatial use patterns and estimating density for this population. The data were collected using 4–6 stationary bottom‐moored recorders. Since only eight signature whistles were identified, our density estimate may represent a subset of the entire population. However, even with only a few signature whistles identified, our results confirmed the center of the core area used by these dolphins as the area with the highest encounter probability. In addition, our results provided evidence that these dolphins have the same spatial use pattern at night as during the day. This study shows that SCR analysis of signature whistle data can improve our ecological knowledge and understanding of dolphin populations.
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Batter, Thomas J., Russ H. Landers, Kristin Denryter, and Joshua P. Bush. "Use of aerial distance sampling to estimate abundance of tule elk across a gradient of canopy cover and comparison to a concurrent fecal DNA spatial capture-recapture survey." Proceedings of the 14th Biennial Deer and Elk Workshop 108, no. 3 (2022). http://dx.doi.org/10.51492/cfwj.108.17.
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Historically, aerial surveys have been used widely to monitor abundance of large mammals in the western United States. In California, such surveys have typically served as minimum count indices rather than true abundance estimates. Here, we evaluated the utility of aerial multiple covariate distance sampling (MCDS) to estimate abundance of three populations of tule elk (Cervus canadensis nannodes) in northern California. We also compared estimates and costs with published results from a concurrent fecal DNA spatial capture-recapture (SCR) survey. During December 2018 and 2019, we flew line transects for distance sampling of tule elk in Colusa and Lake counties. We modeled detection functions and evaluated effects of group size, canopy cover, and survey year. We averaged the top models comprising ≥0.95 of Akaike Model Weight and estimated abundance of both total and discrete populations. Detection probability increased with increasing group size and decreasing canopy cover. We estimated a two-year average total population size of N̂ = 674 elk (90% CI = 501–907) in our survey area which was similar to N̂ = 653 elk (90% CI = 573–745) from SCR estimates. Overall precision was greater (CV = 0.08; range = 0.11–0.30 by population) for SCR than for MCDS (CV = 0.18; range = 0.22–0.43 by population). Although estimates differed somewhat between methods for the individual populations, the combined estimate across the study region compared favorably. Total cost of SCR and MCDS surveys was $98,326 and $147,324, respectively. While SCR efforts were more precise and less expensive overall, our MCDS approach reduced staff time by 64% (587 person-hours) and the number of survey days by 87% (64 days). Our results suggest MCDS methods can produce reliable abundance estimates across a gradient of canopy cover, particularly when observations can be pooled across populations to decrease variance. We recommend future research to assess use of hybrid models, such as mark-recapture distance sampling or hierarchical distance sampling, to improve precision and estimation of detection probability.
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Farhadinia, Mohammad S., Brett T. McClintock, Paul J. Johnson, et al. "A paradox of local abundance amidst regional rarity: the value of montane refugia for Persian leopard conservation." Scientific Reports 9, no. 1 (2019). http://dx.doi.org/10.1038/s41598-019-50605-2.
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Abstract The population densities of leopards vary widely across their global range, influenced by prey availability, intraguild competition and human persecution. In Asia, particularly the Middle East and the Caucasus, they generally occur at the lower extreme of densities recorded for the species. Reliable estimates of population density are important for understanding their ecology and planning their conservation. We used a photographic spatial capture-recapture (SCR) methodology incorporating animal movement to estimate density for the endangered Persian leopard Panthera pardus saxicolor in three montane national parks, northeastern Iran. We combined encounter history data arising from images of bilaterally asymmetrical left- and right-sided pelage patterns using a Bayesian spatial partial identity model accommodating multiple “non-invasive” marks. We also investigated the effect of camera trap placement on detection probability. Surprisingly, considering the subspecies’ reported low abundance and density based on previous studies, we found relatively high population densities in the three national parks, varying between 3.10 ± SD 1.84 and 8.86 ± SD 3.60 individuals/100 km2. The number of leopards detected in Tandoureh National Park (30 individuals) was larger than estimated during comparable surveys at any other site in Iran, or indeed globally. Capture and recapture probabilities were higher for camera traps placed near water resources compared with those placed on trails. Our results show the benefits of protecting even relatively small mountainous areas, which accommodated a high density of leopards and provided refugia in a landscape with substantial human activity.
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Edelhoff, Hendrik, Cyril Milleret, Pierre Dupont, and Richard Bischof. "R Implementation to: Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra." Nature Communications Biology, August 21, 2023. https://doi.org/10.5281/zenodo.8245739.
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The repository contains the necessary input data, R programming code, and Nimble code to conduct Bayesian spatial capture-recapture analyses, as detailed in the research paper titled "Sexual Segregation Results in Pronounced Sex-Specific Density Gradients in the Mountain Ungulate, Rupicapra rupicapra". The R and Nimble code provided in the repository are designed to implement the complex statistical model described in the associated journal article. Researchers can utilize this code and data to replicate and extend the reported analyses, investigating the spatial patterns and sex-specific density gradients of the studied population. For a comprehensive understanding of the model, its assumptions, and the methodology, researchers are encouraged to refer to the original journal article.
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Edelhoff, Hendrik, Cyril Milleret, Cornelia Ebert, et al. "Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra." Communications Biology 6, no. 1 (2023). http://dx.doi.org/10.1038/s42003-023-05313-z.
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AbstractSex-specific differences in habitat selection and space use are common in ungulates. Yet, it is largely unknown how this behavioral dimorphism, ultimately leading to sexual segregation, translates to population-level patterns and density gradients across landscapes. Alpine chamois (Rupicapra rupicapra r.) predominantly occupy habitat above tree line, yet especially males may also take advantage of forested habitats. To estimate male and female chamois density and determinants thereof, we applied Bayesian spatial capture-recapture (SCR) models in two contrasting study areas in the Alps, Germany, during autumn. We fitted SCR models to non-invasive individual encounter data derived from genotyped feces. Sex-specific densities were modeled as a function of terrain ruggedness, forest canopy cover, proportion of barren ground, and site severity. We detected pronounced differences in male and female density patterns, driven primarily by terrain ruggedness, rather than by sex-specific effects of canopy cover. The positive effect of ruggedness on density was weaker for males which translated into a higher proportion of males occupying less variable terrain, frequently located in forests, compared to females. By estimating sex-specific variation in both detection probabilities and density, we were able to quantify and map how individual behavioral differences scale up and shape spatial patterns in population density.
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Gaya, Heather E., and Richard B. Chandler. "Individual‐level biotic interactions and species distribution models." Journal of Biogeography, June 22, 2024. http://dx.doi.org/10.1111/jbi.14972.
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AbstractAimAccounting for biotic interactions in species distribution models is complicated by the fact that interactions occur at the individual‐level at unknown spatial scales. Standard approaches that ignore individual‐level interactions and focus on aggregate scales are subject to the modifiable aerial unit problem (MAUP) in which incorrect inferences may arise about the sign and magnitude of interspecific effects.LocationGlobal (simulation) and North Carolina, United States (case study).TaxonNone (simulation) and Aves (case study).MethodsWe present a hierarchical species distribution model that includes a Markov point process in which the locations of individuals of one species are modelled as a function of both abiotic variables and the locations of individuals of another species. We applied the model to spatial capture‐recapture (SCR) data on two ecologically similar songbird species—hooded warbler (Setophaga citrina) and black‐throated blue warbler (Setophaga caerulescens)—that segregate over a climate gradient in the southern Appalachian Mountains, USA.ResultsA simulation study indicated that the model can identify the effects of environmental variation and biotic interactions on co‐occurring species distributions. In the case study, there were strong and opposing effects of climate on spatial variation in population densities, but spatial competition did not influence the two species' distributions.Main ConclusionsUnlike existing species distribution models, the framework proposed here overcomes the MAUP and can be used to investigate how population‐level patterns emerge from individual‐level processes, while also allowing for inference on the spatial scale of biotic interactions. Our finding of minimal spatial competition between black‐throated blue warbler and hooded warbler adds to the growing body of literature suggesting that abiotic factors may be more important than competition at low‐latitude range margins. The model can be extended to accommodate count data and binary data in addition to SCR data.
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Masias, Victor H., Tobias Hecking, Fernando Crespo, and H. Ulrich Hoppe. "Detecting social media users based on pedestrian networks and neighborhood attributes: an observational study." Applied Network Science 4, no. 1 (2019). http://dx.doi.org/10.1007/s41109-019-0222-4.
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Abstract This paper proposes a methodological approach to explore the ability to detect social media users based on pedestrian networks and neighborhood attributes. We propose the use of a detection function belonging to the Spatial Capture–Recapture (SCR) which is a powerful analytical approach for detecting and estimating the abundance of biological populations. To test our approach, we created a set of proxy measures for the importance of pedestrian streets as well as neighborhood attributes. The importance of pedestrian streets was measured by centrality indicators. Additionally, proxy measures of neighborhood attributes were created using multivariate analysis of census data. A series of candidate models were tested to determine which attributes are most important for detecting social media users. The results of the analysis provide information on which attributes of the city have promising potential for detecting social media users. Finally, the main results and findings, limitations and extended use of the proposed methodological approach are discussed.
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Finnegan, Shannon P., Amael Hinojo, Sarah Monod, William A. Wall, Peter Olsen, and Maximilian L. Allen. "A comparison of thermal drones and camera trap population estimates for Sitka black‐tailed deer in Alaska." Wildlife Biology, November 2024. http://dx.doi.org/10.1002/wlb3.01360.
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One of the most difficult challenges for wildlife managers is reliably estimating wildlife populations. Camera traps combined with spatial capture–recapture (SCR) models are a popular tool for population estimation. They have limitations, however, including long data processing times. Drones with thermal imagery are an emerging tool for estimating wildlife populations, but how they compare to other methods remain poorly studied. We compared the use of camera traps and SCR models to drone surveys for estimating population densities of Sitka black‐tailed deer Odocoileus hemionus sitkensis on Afognak Island, Alaska. We deployed 26 camera traps from 1 September until 6 October 2022 and individually identified males using antler characteristics, for the SCR model. At the same site we conducted three drone surveys between October and December 2022, identified sex composition and obtained deer counts. The estimated density from the SCR model was 3.7 males ± 0.8 (SE) km‐2, and 14.1 ± 3.1 adults km‐2 of clear‐cut forest. Results from the drone survey produced similar estimates with 2.1 ± 0.9 males km‐2 and 13.4 ± 1.6 adults km‐2. The similarity in estimates suggests that both methods converged on an accurate representation of the population in this habitat, but these methods diverge in levels of sampling effort, duration, and financial cost. Camera traps offer further insights on behavior and home‐range size but require longer data processing times, can be subject to malfunctions, and are difficult to deploy and maintain in remote areas. Drones are subject to legal restrictions, have difficulty in closed canopy habitat and can be initially costly, but they provide results faster and require less data analysis. Camera traps and drones are useful for determining population dynamics but are subject to their limitations. Wildlife managers should make survey decisions based on their specific goals, habitat type, focal species ecology and financial limitations.
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Palmero, Stefano, Elisa Belotti, Luděk Bufka, et al. "Demography of a Eurasian lynx (Lynx lynx) population within a strictly protected area in Central Europe." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-99337-2.
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AbstractLarge carnivores promote crucial ecosystem processes but are increasingly threatened by human persecution and habitat destruction. Successful conservation of this guild requires information on long-term population dynamics obtained through demographic surveys. We used camera traps to monitor Eurasian lynx between 2009 and 2018 in a strictly protected area in the Bohemian Forest Ecosystem, located in the core of the distribution of the Bohemian–Bavarian–Austrian lynx population. Thereby, we estimated sex-specific demographic parameters using spatial capture–recapture (SCR) models. Over 48,677 trap nights, we detected 65 unique lynx individuals. Density increased from 0.69 to 1.33 and from 1.09 to 2.35 individuals/100 km2 for open and closed population SCR models, respectively, with corresponding positive population growth rates (mean = 1.06). Estimated yearly sex-specific survival probabilities for the entire monitoring period were high (females 82%, males 90%) and per capita recruitment rate was low (females 12%, males 9%), indicating a low yearly population turnover. We ascertained an average number of recruits of 1.97 and a generation time of 2.64 years when considering resident reproducing females. We confirmed that reproduction in the study area took place successfully every year. Despite the overall increase in local lynx densities, the number of detected family groups remained constant throughout the study period. These results indicated that the strictly protected study area acts as a source for the multi-use landscapes in its surroundings. In this first open population SCR study on lynx, we provide sex-specific demographic parameters that are fundamental information for lynx management in the study area as well as in similar contexts Europe-wide.
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"Correction to ‘Critical variables and their thresholds for the precise density estimation of wild felids with camera traps and spatial capture‐recapture (SCR) methods’." Mammal Review, June 6, 2024. http://dx.doi.org/10.1111/mam.12368.
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Palmero, Stefano, Adam F. Smith, Svitlana Kudrenko, et al. "Shining a light on elusive lynx: Density estimation of three Eurasian lynx populations in Ukraine and Belarus." Ecology and Evolution 13, no. 11 (2023). http://dx.doi.org/10.1002/ece3.10688.
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AbstractThe Eurasian lynx is a large carnivore widely distributed across Eurasia. However, our understanding of population status is heterogeneous across their range, with some populations isolated that are at risk of reduced genetic variation and a complete lack of information about others. In many European countries, Eurasian lynx are monitored through demographic studies crucial for their conservation and management. Even so, there are only rough and fragmented population assessments from Ukraine and Belarus, despite strict protection in both countries and their importance for lynx connectivity across Europe. We monitored lynx from October 2020 to March 2021 and used camera trapping in combination with spatial capture–recapture (SCR) methods in a Bayesian framework to provide the first SCR density estimation of three lynx populations across Ukraine and Belarus, including the Ukrainian Chornobyl Exclusion Zone, southern Belarus and the Ukrainian Carpathians. Our density estimates varied within our study areas ranging from 0.45 to 1.54 individuals/100 km2. This work provides a substantial scientific component to the overall understanding of lynx conservation for a region where only broad information is available and opens the doors for further large‐scale monitoring and trend assessments. The crucial information we provide can greatly enhance the range‐wide assessments of the status of this protected species. We also discuss the implications for Eurasian lynx conservation, despite the geopolitical realities impacting species monitoring in the region. Our work serves as a baseline, not only for future conservation interventions but also to evaluate the effects of disturbance and threats to these protected populations.
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Nawaz, Muhammad Ali, Barkat Ullah Khan, Amer Mahmood, Muhammad Younas, Jaffar ud Din, and Chris Sutherland. "An empirical demonstration of the effect of study design on density estimations." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-92361-2.
Full textAbstract:
AbstractThe simultaneous development of technology (e.g. camera traps) and statistical methods, particularly spatially capture–recapture (SCR), has improved monitoring of large mammals in recent years. SCR estimates are known to be sensitive to sampling design, yet existing recommendations about trap spacing and coverage are often not achieved, particularly for sampling wide-ranging and rare species in landscapes that allow for limited accessibility. Consequently, most camera trap studies on large wide-ranging carnivores relies on convenience or judgmental sampling, and often yields compromised results. This study attempts to highlight the importance of carefully considered sampling design for large carnivores that, because of low densities and elusive behavior, are challenging to monitor. As a motivating example, we use two years of snow leopard camera trapping data from the same areas in the high mountains of Pakistan but with vastly different camera configurations, to demonstrate that estimates of density and space use are indeed sensitive to the trapping array. A compact design, one in which cameras were placed much closer together than generally recommended and therefore have lower spatial coverage, resulted in fewer individuals observed, but more recaptures, and estimates of density and space use were inconsistent with expectations for the region. In contrast, a diffuse design, one with larger spacing and spatial coverage and more consistent with general recommendations, detected more individuals, had fewer recaptures, but generated estimates of density and space use that were in line with expectations. Researchers often opt for compact camera configurations while monitoring wide-ranging and rare species, in an attempt to maximize the encounter probabilities. We empirically demonstrate the potential for biases when sampling a small area approximately the size of a single home range—this arises from exposing fewer individuals than deemed sufficient for estimation. The smaller trapping array may also underestimate density by significantly inflating $$\sigma$$ σ . On the other hand, larger trapping array with fewer detectors and poor design induces uncertainties in the estimates. We conclude that existing design recommendations have limited utility on practical grounds for devising feasible sampling designs for large ranging species, and more research on SCR designs is required that allows for integrating biological and habitat traits of large carnivores in sampling framework. We also suggest that caution should be exercised when there is a reliance on convenience sampling.
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Bedson, Carlos, Oliver Metcalf, Elias Symeonakis, David Mallon, and Neil Reid. "A response to Hesford & MacLeod (2022): Rejection of a model estimating high densities of mountain hares in the Peak District, England." Mammal Communications 8 (2022). http://dx.doi.org/10.59922/iowa5107.
Full textAbstract:
A recent Game and Wildlife Conservation Trust (GWCT) report (Hesford & MacLeod 2022) suggested densities of mountain hares (Lepus timidus) may reach 52 - 125/km2 in parts of the Peak District, England. These are notably higher than previous and current estimates of 5 - 33 hares/km2 (Matthews et al. 2018; Bedson et al. 2022). We review Hesford & MacLeod (2022) who based their methods on those used in a review of mountain hare survey methods in Scotland (Newey et al. 2018). This review demonstrated a weak, non-significant relationship between hare encounter rates using spotlight surveys of walked transects at night and estimated densities derived from spatial capture-recapture (SCR) methods on managed heather moorland (p=0.08). Newey et al. (2018) recommended that this relationship should not be used to estimate hare densities. We reproduce the Newey et al. (2018) linear model and confirm its poor predictive ability and show that removal of one outlier reduces an already marginal relationship to a near-flat line (p=0.80). Hesford & MacLeod (2022), nonetheless, used this relationship to estimate hare densities along non-randomly placed transects. We conclude that reportedly high mountain hare densities estimated by Hesford & MacLeod (2022) are biased and based on a model with little predictive power; more recent Distance Sampling estimates are from 37 - 96% lower (Bedson et al. 2022). It is important that wildlife monitoring methods robustly account for survey bias and error, detection probability and variation between habitats, especially if results are to inform potential population management interventions.
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Braunstein, Jessica L., Joseph D. Clark, Ben C. Augustine, Caleb R. Hickman, Justin McVey, and Joseph Yarkovich. "Spatially explicit estimates of elk population demographics in North Carolina, USA." Journal of Wildlife Management, February 19, 2025. https://doi.org/10.1002/jwmg.22733.
Full textAbstract:
AbstractIn an effort to restore extirpated elk to their historical range, 52 elk were reintroduced to Great Smoky Mountains National Park (GRSM) in North Carolina, USA, during 2001 and 2002. Since their reintroduction, elk numbers have increased, and elk have extended their range beyond GRSM boundaries. We used spatially explicit capture‐recapture (SCR) methods based on fecal DNA to identify individual elk and estimate population abundance (N), apparent survival (φ), per capita recruitment (f), and population growth rate (λ) in western North Carolina. We walked a series of transects during 3 winter field seasons (2020–2022) and collected elk pellets encountered along those transects. We created spatially explicit capture histories and incorporated those data into both closed and open population SCR models. The top performing closed SCR models for males and females estimated density by year and as a function of the scaled distance to the nearest field, with densities decreasing as the distance increased. Combined male and female N were 179 elk (95% CI = 149–215) in 2020, 220 elk (95% CI = 188–256) in 2021, and 240 elk (95% CI = 207–279) in 2022. The top open population model estimated both φ and λ as functions of sex and year. The estimate of φ for males was 0.682 (95% CI = 0.317–0.908) during 2020–2021 and 0.339 (95% CI = 0.152–0.596) during 2021–2022 and for females was 0.953 (95% CI = 0.830–1.000) during 2020–2021 and 0.829 (95% CI = 0.601–1.000) during 2021–2022. The annual population growth rate (λ) for males was 1.127 (95% CI = 0.806–1.575) during 2020–2021 and 0.811 (95% CI = 0.566–1.163) during 2021–2022 and for females was 1.559 (95% CI = 1.162–2.091) during 2020–2021 and 1.122 (95% CI = 0.876–1.437) during 2021–2022. Our elk abundance estimates in areas >300 m from fields were negligible, and we suggest that sampling only the areas in and adjacent to fields in the future will result in reliable but more cost‐efficient population estimates. Confidence intervals for vital rate parameters were wide for our 3‐year dataset, but continued annual pellet sampling will increase sample sizes for vital rate estimation and thus improve precision. If elk herd expansion on public lands is desired, we suggest habitat modification to establish open grasslands adjacent to forests.