ESTIMATING ABUNDANCE FROM REPEATED PRESENCE–ABSENCE DATA OR POINT COUNTS

By J. Andrew Royle, James D. Nichols. 2003

1,356 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/e155e52089b6c723464d2d1b6df2249cfdce059a

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In Ecology

In Nature and Landscape Conservation

Citations in the corpus

WAS IT THERE? DEALING WITH IMPERFECT DETECTION FOR SPECIES PRESENCE/ABSENCE DATA † (2005, background): “Alternatively, Royle & Nichols (2003) suggest a modification of the single season model that allows for heterogeneity caused by varying levels of abundance, and also enables abundance to be estimated.”
Abundance, Density and Relative Abundance: A Conceptual Framework (2011, background): “Under these circumstances, estimates of N i may be poor, but the estimate of total or average point abundance, N̂, at the trap sites may be good (Royle and Nichols 2003).”
Imperfect detection is the rule rather than the exception in plant distribution studies (2013, methodology): “Via the abundance– detection relationship exploited formally in the heterogeneity site-occupancy model of Royle & Nichols (2003), abundance is probably at the root of such elevation patterns in detection probability.”
EXPERIMENTAL ANALYSIS OF THE AUDITORY DETECTION PROCESS ON AVIAN POINT COUNTS (2007, methodology): “…sampling (Buckland et al. 2001), multipleobserver methods (Nichols et al. 2000, Alldredge et al. in press a), time-ofdetection methods (Farnsworth et al. 2002, Alldredge et al. in press b), double sampling (Bart and Earnst 2002) and repeated count methods (Royle and Nichols 2003, Kery et al. 2005).”
Estimating animal population density using passive acoustics (2012, methodology): “(e) Other model-based approaches Methods based on presence-absence (Royle & Nichols, 2003) or counts (Royle, 2004) of a given species over repeated visits to a given number of sites have also been used to estimate abundance.”
Best practice guidelines for surveys and monitoring of great ape populations (2008, methodology): “If certain assumptions are met, occupancy methods can also be used to estimate abundance (e.g., Royle and Nichols 2003).”
Using camera trapping and hierarchical occupancy modelling to evaluate the spatial ecology of an African mammal community (2016, background): “A species’ abundance can significantly affect detection probabilities, often resulting in strong, positive correlations between occupancy and detection (Royle & Nichols 2003).”
Assessing global patterns in mammalian carnivore occupancy and richness by integrating local camera trap surveys (2017, background): “In many cases, the density of a species is related to both the overall occupancy probability and the average site-specific detection probability, resulting in strong, positive correlations between occupancy and detection among species (Royle & Nichols, 2003).”
Camera Trapping of Carnivores: Trap Success Among Camera Types and Across Species, and Habitat Selection by Species, on Salt Pond Mountain, Giles County, Virginia (2008, background): “…can allow us to use presence-absence data obtained from sequential, repeated, remote camera surveys to generate detection probabilities and produce more reliable estimates of species’ relative abundance or areas occupied (MacKenzie and Royle 2005, MacKenzie et al. 2003, Royle and Nichols 2003).”
Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models (2004, background): “Few studies have been conducted to examine factors affecting probability of detection (but see Mckenzie et al., 2002; Royle and Nichols, 2003).”
unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance (2011, background): “Another related model was described by Royle and Nichols (2003) and can be fit with the occuRN function.”
A picture is worth a thousand words: the application of camera trapping to the study of birds (2008, methodology): “Sanderson and Trolle (2005) trace the first use of a camera trap to George Shiras III, a pioneer of wildlife photography.”
INCORPORATING AVAILABILITY FOR DETECTION IN ESTIMATES OF BIRD ABUNDANCE (2007, methodology): “Availability of Birds for DetectionJanuary 2007] 97 I , methods have been developed for estimating the associated detection probability of count statistics from bird surveys to make inferences about bird abundance (Nichols et al. 2000, Farnsworth et al. 2002, Royle and Nichols 2003).”
Inference About Species Richness and Community Structure Using Species-Specific Occupancy Models in the National Swiss Breeding Bird Survey MHB (2009, background): “Modelling this correlation can easily be justified on grounds of the expected relationships between quadrat-specific abundance and occupancy on the one hand and abundance-induced heterogeneity in quadrat-specific detection probability on the other (Royle and Nichols 2003; Dorazio and Royle 2005).”
Differential responses of large mammals to logging and edge effects (2015, methodology): “Third, we use an occupancy modeling based approach (cf. Royle and Nichols, 2003) that allows us to assess the relative habitat use of different species in adjacent logged and primary forest while explicitly accounting for potentially different detection probabilities between the two habitats.”
Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities (2017, methodology): “A related model extension describes site heterogeneity in species detection/non-detection data by linking it to detectability of individuals and variations in the (unknown) local abundance (Royle and Nichols 2003, Stanley and Royle 2005).”