Balancing detection probability and survey effort in multistate occupancy models: A camera trap simulation analysis
Sign Up to like & getrecommendations! Published in 2025 at "Ecosphere"
DOI: 10.1002/ecs2.70402
Abstract: Camera trapping has become crucial in wildlife research, enabling detailed observations of elusive and nocturnal species with limited human interference. The use of occupancy modeling to analyze camera trap data is rapidly increasing, aiding in… read more here.
Keywords: detection; occupancy models; occupancy; multistate occupancy ... See more keywords
Variation in herpetofauna detection probabilities: implications for study design
Sign Up to like & getrecommendations! Published in 2021 at "Environmental Monitoring and Assessment"
DOI: 10.1007/s10661-021-09424-0
Abstract: Population monitoring is fundamental for informing management decisions aimed at reducing the rapid rate of global biodiversity decline. Herpetofauna are experiencing declines worldwide and include species that are challenging to monitor. Raw counts and associated… read more here.
Keywords: detection; herpetofauna; detection probabilities; pitfall traps ... See more keywords
Net overboard: Comparing marine eDNA sampling methodologies at sea to unravel marine biodiversity
Sign Up to like & getrecommendations! Published in 2022 at "Molecular Ecology Resources"
DOI: 10.1111/1755-0998.13722
Abstract: Environmental DNA (eDNA) analyses are powerful for describing marine biodiversity but must be optimized for their effective use in routine monitoring. To maximize eDNA detection probabilities of sparsely distributed populations, water samples are usually concentrated… read more here.
Keywords: edna sampling; net overboard; marine biodiversity; biodiversity ... See more keywords
Moose calf detection probabilities: quantification and evaluation of a ground-based survey technique
Sign Up to like & getrecommendations! Published in 2020 at "Wildlife Biology"
DOI: 10.2981/wlb.00599
Abstract: Survey data improve population management, yet those data often have associated bias. We quantified one source of bias in moose survey data (observer detection probability, p), by using repeated ground-observations of calves-at-heel of radio-collared moose… read more here.
Keywords: detection; ground based; survey; detection probabilities ... See more keywords