In Defense of Indices: The Case of Bird Surveys

By Douglas H. Johnson. 2008

442 citations recorded by the source corpus.

Subfields: Ecology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/681c428aaaab28cb347cd911d6f98396cfb661bc

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In Statistics and Probability

Citations in the corpus

Landscape matrix and species traits mediate responses of Neotropical resident birds to forest fragmentation in Jamaica (2010, unknown): “…on observed point counts are expected to reflect those based on true abundances, because we implemented standardized survey protocols to control for confounding detection biases due to landscape matrix effects and those due to observer, time, or sampling effort (Johnson 2008, Etterson et al. 2009).”
Management by proxy?:the use of indices in applied ecology (2015, background): “Even over short time frames, indices might be useful, as long as the variation in detectability and activity is independent of abundance and of substantially lower magnitude than the variation in population size that researchers wish to detect (Johnson 2008).”
Calibrating indices of avian density from non‐standardized survey data: making the most of a messy situation (2013, background): “These are general issues with distance sampling and removal models – field studies are much needed to evaluate the actual prevalence of these violations and the extent that they truly bias density estimators from these and also other estimators of avian abundance (Johnson 2008; Nichols, Thomas & Con”
Intrinsic heterogeneity in detection probability and its effect on N‐mixture models (2016, background): “A principle challenge has been the need to estimate the species detection probability as a way of ‘correcting’ raw count data of individual unmarked organisms that were present but not detected during the survey [although see Johnson (2008)].”
A hierarchical model combining distance sampling and time removal to estimate detection probability during avian point counts (2014, background): “Methods to adjust raw counts for incomplete detection of individuals rely on assumptions and, thus, still result in indices of population size, though the adjusted estimates should approximate the true population size of interest better than the raw counts would alone (Johnson 2008).”
As clear as mud: A critical review of evidence for the ecological roles of Australian dingoes (2013, methodology): “Many of these considerations essentially amount to issues of detection probability, and have been discussed in greater detail elsewhere (e.g. Anderson, 2001; Johnson, 2008; MacKenzie et al., 2006; Pollock et al., 2002).”
The disproportionate value of scattered trees (2010, background): “On this basis, we consider our estimates of species richness reliable indices of true species richness (Johnson, 2008).”
Influence of camera-trap sampling design on mammal species capture rates and community structures in southeastern Brazil (2013, background): “According to Johnson (2008), for the valid use of indices to detect changes in density or abundance, the variation in detectability needs to be substantially lower than the variation in population size.”
Bird population density estimated from acoustic signals (2009, background): “While an index is sufficient for some purposes (Caughley 1977;Dawson 1981; Johnson 2008), estimates of absolute density are sometimes needed (Kendeigh 1944; Nichols, Thomas & Conn 2009).”
Imperfect detection and its consequences for monitoring for conservation (2008, background): “(+* -( 8 + * a b c d detection may need to be split into further components still (Johnson 2008, Nichols et al. 2008).”
Effects of spatial autocorrelation and imperfect detection on species distribution models (2018, unknown): “In spite of this, some researchers have recommended ignoring this challenge (Banks- Leite et al., 2014; Johnson, 2008; Stephens, Pettorelli, Barlow, Whittingham, & Cadotte, 2015).”