Results 71 to 80 of about 4,509 (203)

Knee height is often right: evaluating device height effects on camera trapping rate

Remote Sensing in Ecology and Conservation, EarlyView.
Camera trap deployment height can introduce systematic biases in detection trapping rates across species of different body sizes. Combining 172 paired sampling points in five experiments across Europe, North America and Africa, our results show that low cameras significantly increase detections of small‐ and medium‐sized species, whereas high cameras ...
Jorge Sereno‐Cadierno, Tim R. Hofmeester, Marcus Becker, Alice Bernard, Lizette Moolman, Hervé Fritz, Pelayo Acevedo   +6 more
wiley   +1 more source

Estimating density for species conservation: Comparing camera trap spatial count models to genetic spatial capture-recapture models

Global Ecology and Conservation, 2018
Density estimation is integral to the effective conservation and management of wildlife. Camera traps in conjunction with spatial capture-recapture (SCR) models have been used to accurately and precisely estimate densities of “marked” wildlife ...
Joanna M. Burgar, Frances E.C. Stewart, John P. Volpe, Jason T. Fisher, A. Cole Burton   +4 more
doaj   +1 more source

Estimating spatially variable and density-dependent survival using open-population spatial capture-recapture models. [PDF]

Ecology, 2023
Milleret C, Dey S, Dupont P, Brøseth H, Turek D, de Valpine P, Bischof R.   +6 more
europepmc   +1 more source

Semi‐automated seal detection on the Western Antarctic Peninsula: an unsupervised machine learning approach for detecting ice seals in aerial survey data

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a semi‐automated, rule‐based image analysis pipeline to detect ice seals in aerial surveys of the Western Antarctic Peninsula during an unusually low sea ice year. By using simple hierarchical clustering instead of deep learning, the method substantially reduced human annotation effort while achieving 82% recall, identifying 758 ...
Claire McGinnity, Connor C.G. Bamford, Nathan Fenney, Andrew Fleming, Jaume Forcada, Michael S. Tift, Luis A. Hückstädt, Daniel P. Costa, Peter T. Fretwell   +8 more
wiley   +1 more source

An integrated path for spatial capture-recapture and animal movement modeling. [PDF]

Ecology, 2022
McClintock BT, Abrahms B, Chandler RB, Conn PB, Converse SJ, Emmet RL, Gardner B, Hostetter NJ, Johnson DS.   +8 more
europepmc   +1 more source

Monitoring feral pigs (Sus scrofa): Complementarity between autonomous sensing methods increases detection probability

Remote Sensing in Ecology and Conservation, EarlyView.
Invasive alien species are a major threat for biodiversity worldwide and effective monitoring is paramount to inform management. In this study we used a multi‐season occupancy model to assess probability of detection between camera traps and passive acoustic recorders for feral pigs (Sus scrofa) during 1 year of data collection.
Marina D. A. Scarpelli, Stewart Macdonald, Maryam Golchin, Simon Linke, Jens G. Froese   +4 more
wiley   +1 more source

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture-recapture movement model. [PDF]

Ecology, 2022
Hostetter NJ, Regehr EV, Wilson RR, Royle JA, Converse SJ.   +4 more
europepmc   +1 more source

Historical remote sensing highlights long‐term persistence of Emperor Penguin (Aptenodytes forsteri) colonies

Remote Sensing in Ecology and Conservation, EarlyView.
Remote sensing can reveal population dynamics of Antarctic penguin colonies. In this study, we analyze emperor penguin (Aptenodytes forsteri) guano stains in remote sensing imagery and discover colony presence predating known records for 18 colonies across Antarctica.
Martynas Bielinis, Michelle LaRue, Benjamin M. Kraemer, Catalina Munteanu   +3 more
wiley   +1 more source

Deep learning‐based super‐resolution reconstruction and improved YOLOv9 for efficient benthos detection: a case study at Lake Hamana, Japan

Remote Sensing in Ecology and Conservation, EarlyView.
This study presents a UAV‐based framework that integrates deep learning‐based super‐resolution reconstruction and an enhanced YOLO detector to improve centimetre‐scale benthic organism monitoring. Using hermit crabs in Lake Hamana, a coastal lagoon in Japan, as a case study, the method substantially enhanced small‐object detection performance ...
Fan Zhao, Bangzhang Ma, Dianhan Xi, Jiaqi Wang, Yijia Chen, Yongying Liu, Xinlei Shao, Mowen Zhang, Guocheng Zhang, Jundong Chen, Katsunori Mizuno   +10 more
wiley   +1 more source

Evaluating and integrating spatial capture-recapture models with data of variable individual identifiability. [PDF]

Ecol Appl, 2021
Ruprecht JS, Eriksson CE, Forrester TD, Clark DA, Wisdom MJ, Rowland MM, Johnson BK, Levi T.   +7 more
europepmc   +1 more source