2010
DOI: 10.1890/09-0470.1
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Two‐species occupancy models: a new parameterization applied to co‐occurrence of secretive rails

Abstract: Two-species occupancy models that account for false absences provide a robust method for testing for evidence of competitive exclusion, but previous model parameterizations were inadequate for incorporating covariates. We present a new parameterization that is stable when covariates are included: the conditional two-species occupancy model, which can be used to examine alternative hypotheses for species' distribution patterns. This new model estimates the probability of occupancy for a subordinate species cond… Show more

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Cited by 255 publications
(389 citation statements)
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“…We fit conditional two‐species occupancy models (Richmond et al., 2010), which estimates the probability of occupancy for a subordinate species conditional upon the presence of a dominant species, which allow for differences in occupancy and detection probabilities of P. shenandoah conditional on the presence and/or detection of P. cinereus . We tested models which represented whether the occupancy of P. shenandoah was conditional [ψ SC different than ψ Sc ] or unconditional [ψ S ; i.e., setting ψ SC  = ψ Sc ] on the presence of P. cinereus [ψ C ] and whether occupancy of either species was influenced by site covariates.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…We fit conditional two‐species occupancy models (Richmond et al., 2010), which estimates the probability of occupancy for a subordinate species conditional upon the presence of a dominant species, which allow for differences in occupancy and detection probabilities of P. shenandoah conditional on the presence and/or detection of P. cinereus . We tested models which represented whether the occupancy of P. shenandoah was conditional [ψ SC different than ψ Sc ] or unconditional [ψ S ; i.e., setting ψ SC  = ψ Sc ] on the presence of P. cinereus [ψ C ] and whether occupancy of either species was influenced by site covariates.…”
Section: Methodsmentioning
confidence: 99%
“…There are two related processes that influence the observation of a range edge: an ecological process where a population responds to a biotic or abiotic gradient, and a statistical process where variation in abundance of individuals across space is only partially observed (e.g., Grant, 2014). Ignoring the issue of partial observability may induce bias in the detection of range limits and species interactions, as the presence of one species may influence both the detection and the occurrence of another (Richmond, Hines, & Beissinger, 2010). …”
Section: Introductionmentioning
confidence: 99%
“…prey, hosts). Twospecies occupancy models [99] could be applied to test for the impacts of these and other types of interspecific interactions. Identifying the particular interactions that are responsible for climate-related extinctions may be challenging, given the diversity of interactions and species that may be involved.…”
Section: Approaches For Finding the Proximate Causes Of Climate-relatmentioning
confidence: 99%
“…The rarity of a species also influences detectability and the probability of detecting a species is positively related to its abundance [15][16][17]. Less appreciated is that the local abundance of another species (e.g., a competitor or predator) can influence the behavior of the focal species, resulting in either positive or negative changes in detectability [18][19][20]. Substantial heterogeneity in detection among individuals can also occur within species.…”
Section: Origins Of Imperfect Detectionmentioning
confidence: 99%