Occupancy Estimation and Modeling. Inferring patterns and dynamics of species occurrence

By N. Yoccoz. 2006

377 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/e67255207b0ea9f6077cee714262e00feec371b8

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Citations in the corpus

Estimating Brown Hyaena Occupancy Using Baited Camera Traps (2009, methodology): “Occupancy data can now be used to make robust inferences about numerous variables such as distribution, population size, resource selection, metapopulation dynamics and species interactions (MacKenzie et al.2006).”
Detecting small changes in populations at landscape scales: a bioacoustic site-occupancy framework (2019, methodology): “…used to estimate parameters for initial occupancy, detection, extinction and colonization; as such, likelihood ratio tests (LRT) are useful for testing hypotheses regarding the relative level of support for certain parameters using nested models (MacKenzie et al., 2005; Royle and Dorazio, 2008).”
A picture is worth a thousand words: the application of camera trapping to the study of birds (2008, methodology): “Supporting this idea, we often find that trapping rates correlate significantly with abundance or density estimates (O’Brien et al. 2003, Silveira et al. 2003, O’Brien unpubl. data). Use of counts or trapping rates, however, almost always results in bias because these indices do not control for the ”
Imperfect detection is the rule rather than the exception in plant distribution studies (2013, background): “There are now a vast number of articles and books dealing with survey designs to properly accommodate detection probability in population analyses, including Williams, Nichols & Conroy (2002), MacKenzie et al. (2006), Royle & Dorazio (2008) and Kéry & Schaub (2012).”
Evaluating relative abundance indices for terrestrial herbivores from large-scale camera trap surveys (2018, background): “A large body of statistics has been developed that uses camera trap data to calculate population estimates for uniquely identifiable animals (Karanth, 1995; Kéry, 2010; MacKenzie et al., 2006; Royle & Nichols, 2003).”
Hierarchical Species Distribution Models (2016, methodology): “The hierarchical modeling framework has also been useful and widely implemented for count and presence-absence data [72, 86], but has not been readily used for presence-only data (but see [23, 31]).”
Early assessment of the impact of alien species: differential consequences of an invasive crayfish on adult and larval amphibians (2011, methodology): “We used Presence 2.4 (Hines, 2006) to estimate occupancy and evaluate the probability of occupancy of sites where we did not detect species (MacKenzie et al., 2006; Sewell et al., 2010).”
Effects of low-level culling of feral cats in open populations: a case study from the forests of southern Tasmania (2015, background): “However, an increase in the density of cameras would likely also have increased the spatial dependence between sites, making the data unsuitable for site-occupancy analyses unless the dataset was subsampled (MacKenzie et al. 2006).”
Range dynamics of small mammals along an elevational gradient over an 80‐year interval (2009, methodology): “…range endpoints is necessary for making informed inferences about distributional shifts (Shoo et al., 2006), and both subsampling (Hill et al., 2002; Wilson et al., 2007) and information-theoretic (MacKenzie et al., 2006; Moritz et al., 2008) approaches have been employed to address this issue.”