Hide and seek: extended camera-trap session lengths and autumn provide best parameters for estimating lynx densities in mountainous areas

Weingarth, Kirsten; Zeppenfeld, Thorsten; Heibl, Christoph; Heurich, Marco; Bufka, Luděk; Daniszová, Kristina; Müller, Jörg

doi:10.1007/s10531-015-0986-5

Cited by 26 publications

(32 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The trap array covered a minimum convex polygon of 414 km 2 . A sampling of 71 days (from 20 June to 28 August 2014) was chosen as a trade-off between the need to maximize the number of recaptures and that of assuming a demographically closed population [ 54 ]. A second session was carried out in 2015, increasing the number of camera points to 48, subdividing the study area into two blocks of 25 and 23 locations and enlarging the trap array to cover 560 km 2 .…”

Section: Methodsmentioning

confidence: 99%

Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring

Mattioli¹,

Canu

Passilongo

et al. 2018

Front Zool

View full text Add to dashboard Cite

BackgroundDensity estimation is a key issue in wildlife management but is particularly challenging and labour-intensive for elusive species. Recently developed approaches based on remotely collected data and capture-recapture models, though representing a valid alternative to more traditional methods, have found little application to species with limited morphological variation. We implemented a camera trap capture-recapture study to survey wolf packs in a 560-km2 area of Central Italy. Individual recognition of focal animals (alpha) in the packs was possible by relying on morphological and behavioural traits and was validated by non-invasive genotyping and inter-observer agreement tests. Two types (Bayesian and likelihood-based) of spatially explicit capture-recapture (SCR) models were fitted on wolf pack capture histories, thus obtaining an estimation of pack density in the area.ResultsIn two sessions of camera trapping surveys (2014 and 2015), we detected a maximum of 12 wolf packs. A Bayesian model implementing a half-normal detection function without a trap-specific response provided the most robust result, corresponding to a density of 1.21 ± 0.27 packs/100 km2 in 2015. Average pack size varied from 3.40 (summer 2014, excluding pups and lone-transient wolves) to 4.17 (late winter-spring 2015, excluding lone-transient wolves).ConclusionsWe applied for the first time a camera-based SCR approach in wolves, providing the first robust estimate of wolf pack density for an area of Italy. We showed that this method is applicable to wolves under the following conditions: i) the existence of sufficient phenotypic/behavioural variation and the recognition of focal individuals (i.e. alpha, verified by non-invasive genotyping); ii) the investigated area is sufficiently large to include a minimum number of packs (ideally 10); iii) a pilot study is carried out to pursue an adequate sampling design and to train operators on individual wolf recognition. We believe that replicating this approach in other areas can allow for an assessment of density variation across the wolf range and would provide a reliable reference parameter for ecological studies.Electronic supplementary materialThe online version of this article (10.1186/s12983-018-0281-x) contains supplementary material, which is available to authorized users.

show abstract

Section: Methodsmentioning

confidence: 99%

Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring

Mattioli¹,

Canu

Passilongo

et al. 2018

Front Zool

View full text Add to dashboard Cite

show abstract

“…In addition, closure tests are limited in obtaining reliable estimates when small sample sizes are used [ 29 ]. In general, studies that focus on elusive species, such as the Indochinese leopard, have low sample sizes, and thus these tests might not be appropriate for revealing robust values [ 30 ]. Similarly, no specific population closure test for spatially explicit capture–recapture (SECR) models is available, given that violation of population closure cannot be distinguished from the violation of other model assumptions [ 31 ].…”

Section: Methodsmentioning

confidence: 99%

An adaptable but threatened big cat: density, diet and prey selection of the Indochinese leopard (Panthera pardus delacouri) in eastern Cambodia

Rostro‐García

Kamler

Crouthers³

et al. 2018

R. Soc. open sci.

View full text Add to dashboard Cite

We studied the Indochinese leopard (Panthera pardus delacouri) in eastern Cambodia, in one of the few potentially remaining viable populations in Southeast Asia. The aims were to determine the: (i) current leopard density in Srepok Wildlife Sanctuary (SWS) and (ii) diet, prey selection and predation impact of leopard in SWS. The density, estimated using spatially explicit capture–recapture models, was 1.0 leopard/100 km2, 72% lower than an estimate from 2009 at the same site, and one of the lowest densities ever reported in Asia. Dietary analysis of 73 DNA confirmed scats showed leopard consumed 13 prey species, although ungulates comprised 87% of the biomass consumed (BC). The overall main prey (42% BC) was banteng (Bos javanicus), making this the only known leopard population whose main prey had adult weight greater than 500 kg. Consumption of wild pig (Sus scrofa) was also one of the highest ever reported (22% BC), indicating leopard consistently predated on ungulates with some of the largest adult weights in SWS. There were important differences in diet and prey selection between sexes, as males consumed mostly banteng (62% BC) in proportion to availability, but few muntjac (Muntiacus vaginalis; 7% BC), whereas females selectively consumed muntjac (56% BC) and avoided banteng (less than 1% BC). Predation impact was low (0.5–3.2% of populations) for the three ungulate species consumed. We conclude that the Indochinese leopard is an important apex predator in SWS, but this unique population is declining at an alarming rate and will soon be eradicated unless effective protection is provided.

show abstract

“…An intensive cheetah survey was conducted during a three-month period from 1 st August 2014 to 31 st October 2014. Based on other studies, we believe that this was short enough so not to seriously violate the assumption of closure but long enough to collect sufficient data [ 9 , 17 , 31 ]. The survey involved a maximum of five vehicles traveling within the study area with the objective of adequately covering the entire study area spatially.…”

Section: Methodsmentioning

confidence: 99%

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

Broekhuis

Gopalaswamy

2016

PLoS ONE

View full text Add to dashboard Cite

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

show abstract

Hide and seek: extended camera-trap session lengths and autumn provide best parameters for estimating lynx densities in mountainous areas

Cited by 26 publications

References 56 publications

Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring

Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring

An adaptable but threatened big cat: density, diet and prey selection of the Indochinese leopard (Panthera pardus delacouri) in eastern Cambodia

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

Contact Info

Product

Resources

About