Can Video Traps Reliably Detect Animals? Implications for the Density Estimation of Animals without Individual Recognition DOI

Gota Yajima,

Yoshihiro Nakashima

Mammal Study, Journal Year: 2021, Volume and Issue: 46(3)

Published: June 2, 2021

Several statistical models have recently been developed to estimate animal density using camera trappings without individual recognition. However, most assume that detection by traps of animals passing a specific area the view is perfect. A REST model (Nakashima et al. 2018; Journal Applied Ecology 55: 735–744) also depends on trapping rates and staying times within area. We tested whether commercial provided unbiased estimates these parameters conducting an experimental trial domestic dog in city park Japan. Additionally, we effects angle estimation Bushnell camera. The captured 96% time, while Ltl-Acorn missed about half his passes. time was underestimated 4% overestimated 25% bias < 10% Camera did not affect probability, downward-angled cameras due delayed trigger. hope share results with manufacturers make more suitable for estimation.

Language: Английский

Monitoring the effectiveness of fauna sensitive infrastructure along the Peak Downs Highway in Central Queensland reveals mixed results for koala conservation DOI Creative Commons
Rolf Schlagloth, Flavia Santamaria, Michael Hewson

et al.

Australasian Journal of Environmental Management, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 30

Published: Sept. 24, 2024

Language: Английский

Citations

1
Motion vectors and deep neural networks for video camera traps DOI Creative Commons

Miklas Riechmann,

Ross Gardiner,

Kai Waddington

et al.

Ecological Informatics, Journal Year: 2022, Volume and Issue: 69, P. 101657 - 101657

Published: May 13, 2022

Commercial camera traps are usually triggered by a Passive Infra-Red (PIR) motion sensor necessitating delay between triggering and the image being captured. This often seriously limits ability to record images of small fast moving animals. It also results in many "empty" images, e.g., owing foliage against background different temperature. In this paper we detail new mechanism based solely on sensor. is intended for use citizen scientists deployment an affordable, compact, low-power Raspberry Pi computer (RPi). Our system introduces video frame filtering pipeline consisting movement image-based processing. makes Machine Learning (ML) feasible live stream RPi. We describe our free open-source software implementation system; introduce suitable ecology efficiency measure that mediates specificity recall; provide ground-truth clip collection from traps; evaluate effectiveness thoroughly. Overall, trap turns out be robust effective.

Language: Английский

Citations

5
A camera trap appraisal of species richness and community composition of medium and large mammals in a Miombo woodland reserve DOI
Sally Jean Reece, Frans G.T. Radloff, Alison J. Leslie

et al.

African Journal of Ecology, Journal Year: 2021, Volume and Issue: 59(4), P. 898 - 911

Published: Aug. 9, 2021

Abstract Biological monitoring in protected areas is essential for making management decisions, especially small (<1000 km 2 ), fenced reserves which require intensive intervention to maintain core habitat characteristics. Estimates of species richness and community structure provide important information planning evaluating conservation strategies. Majete Wildlife Reserve (MWR) a (691 isolated reserve southern Malawi the Miombo Woodland Ecoregion. We investigated terrestrial medium large mammals at MWR through standardised camera trap survey. During 2018 dry season, 140 locations were sampled 40 days each. Thirty‐five mammal detected Chao 2, ICE Jackknife 1 estimators indicated between 36–41 present aligns closely with historic accounts. Non‐detection some attributed specialised requirements not catered systematic survey design. Mammal structure, calculated from species’ relative abundance indices (RAI), was atypical woodland, an underrepresentation elephants. Camera trap‐derived RAI positively related aerial census encounter data. These results can assist refining techniques act as baseline monitor efforts.

Language: Английский

Citations

7
Increased population density and behavioural flexibility of African clawless otters (Aonyx capensis) in specific anthropogenic environments DOI
Tshepiso L. Majelantle, André Ganswindt, Rowan K. Jordaan

et al.

Urban Ecosystems, Journal Year: 2020, Volume and Issue: 24(4), P. 691 - 699

Published: Oct. 21, 2020

Language: Английский

Citations

6
Can Video Traps Reliably Detect Animals? Implications for the Density Estimation of Animals without Individual Recognition DOI

Gota Yajima,

Yoshihiro Nakashima

Mammal Study, Journal Year: 2021, Volume and Issue: 46(3)

Published: June 2, 2021

Several statistical models have recently been developed to estimate animal density using camera trappings without individual recognition. However, most assume that detection by traps of animals passing a specific area the view is perfect. A REST model (Nakashima et al. 2018; Journal Applied Ecology 55: 735–744) also depends on trapping rates and staying times within area. We tested whether commercial provided unbiased estimates these parameters conducting an experimental trial domestic dog in city park Japan. Additionally, we effects angle estimation Bushnell camera. The captured 96% time, while Ltl-Acorn missed about half his passes. time was underestimated 4% overestimated 25% bias < 10% Camera did not affect probability, downward-angled cameras due delayed trigger. hope share results with manufacturers make more suitable for estimation.

Language: Английский

Citations

6