Estimating overlap of daily activity patterns from camera trap data

By Martin S. Ridout, M. Linkie. 2009

1,376 citations recorded by the source corpus.

Subfields: Ecology, Ecology, Evolution, Behavior and Systematics, Social Psychology

View Paper: https://www.semanticscholar.org/paper/bc5e4a8866943a0dce8898a57dcff6f907400496

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In Ecology

In Ecology, Evolution, Behavior and Systematics

In Social Psychology

Citations in the corpus

camtrapR: an R package for efficient camera trap data management (2016, methodology): “Two-species activity overlaps (Ridout & Linkie 2009) are estimated and plotted with the function activ-ityOverlap .”
When carnivores roam: temporal patterns and overlap among Madagascar's native and exotic carnivores (2015, methodology): “…criterion (Akaike, 1973) and made inference from the most simple model (no variation by camera survey) and from the most parsimonious model by estimating the probability density of temporal activity distribution for each species using nonparametric kernel density analyses (Ridout & Linkie, 2009).”
Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet (2011, methodology): “In addition, we estimated the mean temporal overlap between activity distributions using a kernel density analysis (Ridout and Linkie 2009).”
Impacts of People and Tigers on Leopard Spatiotemporal Activity Patterns in a Global Biodiversity Hotspot (2015, methodology): “Specifically, we used the overlap procedure labeled as ∆̂1 in Ridout and Linkie (2009).”
Quantifying levels of animal activity using camera trap data (2014, methodology): “Ridout & Linkie (2009) point out that this model tends to have a very flat likelihood surface, withmany local minima.”
Cat coexistence in central Sumatra: ecological characteristics, spatial and temporal overlap, and implications for management (2015, methodology): “We used kernel density estimation (KDE) on circular data following Ridout & Linkie (2009) to characterize activity patterns for each species and calculated the coefficient of overlap (Δ) between pairs using their equation 3.1 with a smoothing parameter (c) of 1.0.”
Occupancy patterns and niche partitioning within a diverse carnivore community exposed to anthropogenic pressures (2013, methodology): “In general, the model proposed by Ridout and Linkie (2009) supports results from our detection probability analysis of temporal partitioning, indicating that smaller carnivores overlap with dominant carnivores, but not completely, and that temporal partitioning among species may promote coexistence.”
Puma activity patterns and temporal overlap with prey in a human‐modified landscape at Southeastern Brazil (2018, methodology): “We used the method developed by Ridout & Linkie (2009) to determine daily activity pattern of each species and measure the overlap between pumas, prey and anthropogenic factors (people, cattle and domestic dog).”
Mesopredator spatial and temporal responses to large predators and human development in the Santa Cruz Mountains of California (2015, methodology): “We used the non-parametric kernel density estimation procedure described in Ridout and Linkie (2009) and Linkie and Ridout (2011) to compare whether 10 species (pumas, bobcats, coyotes, grey foxes, opossums, striped skunks, raccoons, domestic cats, domestic dogs, and humans) offset their temporal…”