2020
DOI: 10.1016/j.jnc.2020.125896
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Habitat use by tiger prey in Thailand’s Western Forest Complex: What will it take to fill a half-full tiger landscape?

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Cited by 19 publications
(22 citation statements)
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“…investigate ecological patterns and theories (Lombardi et al, 2020;Robinson et al, 2014), interactions among native and invasive species (Dugger et al, 2016;Hegel et al, 2019;Osorio et al, 2020), Consequently, while the opportunity to apply multi-species occupancy models will likely increase, data collection procedures may not be at the correct spatial and temporal scales necessary to meet the closure assumption for many species. The simulations presented here emulated camera trapping data and the simulated level for detection was comparable to observed levels of daily detection for several carnivores (Shannon et al, 2014) F I G U R E 1 Proportion of simulations for which the estimates of (a) occupancy for Species A (Ψ A ), (b) occupancy of Species B given Species A was present (Ψ BA ) and occupancy of Species B, given that Species A was absent (Ψ Ba ) when the simulated pattern was independence (i.e., Ψ BA = Ψ Ba ), (c) Ψ BA and Ψ Ba when the simulated pattern was avoidance (i.e., Ψ BA < Ψ Ba ), and (d) Ψ BA and Ψ Ba when the simulated pattern was aggregation (i.e., Ψ BA > Ψ Ba ), was not different from the true simulated level of occupancy (based on 95% confidence intervals) when sites were closed or not closed (i. may be difficult to meet the closure assumption for some species (Mackenzie & Royle, 2005) due to logistical constraints (e.g., limited equipment or personnel) that require sampling to take longer than a period over which closure can be reasonably assumed (e.g., Johnson et al, 2020), or challenges identifying an appropriate spatial scale (e.g., Jornburom et al, 2020). Consequently, the closure assumption is often relaxed with estimates of occupancy from single-species models interpreted as the probability of 'use' (Gould et al, 2019;Mackenzie, 2005a).…”
Section: Discussionmentioning
confidence: 99%
“…investigate ecological patterns and theories (Lombardi et al, 2020;Robinson et al, 2014), interactions among native and invasive species (Dugger et al, 2016;Hegel et al, 2019;Osorio et al, 2020), Consequently, while the opportunity to apply multi-species occupancy models will likely increase, data collection procedures may not be at the correct spatial and temporal scales necessary to meet the closure assumption for many species. The simulations presented here emulated camera trapping data and the simulated level for detection was comparable to observed levels of daily detection for several carnivores (Shannon et al, 2014) F I G U R E 1 Proportion of simulations for which the estimates of (a) occupancy for Species A (Ψ A ), (b) occupancy of Species B given Species A was present (Ψ BA ) and occupancy of Species B, given that Species A was absent (Ψ Ba ) when the simulated pattern was independence (i.e., Ψ BA = Ψ Ba ), (c) Ψ BA and Ψ Ba when the simulated pattern was avoidance (i.e., Ψ BA < Ψ Ba ), and (d) Ψ BA and Ψ Ba when the simulated pattern was aggregation (i.e., Ψ BA > Ψ Ba ), was not different from the true simulated level of occupancy (based on 95% confidence intervals) when sites were closed or not closed (i. may be difficult to meet the closure assumption for some species (Mackenzie & Royle, 2005) due to logistical constraints (e.g., limited equipment or personnel) that require sampling to take longer than a period over which closure can be reasonably assumed (e.g., Johnson et al, 2020), or challenges identifying an appropriate spatial scale (e.g., Jornburom et al, 2020). Consequently, the closure assumption is often relaxed with estimates of occupancy from single-species models interpreted as the probability of 'use' (Gould et al, 2019;Mackenzie, 2005a).…”
Section: Discussionmentioning
confidence: 99%
“…We retained the variables that better explained the parameter of interest based on: ecological relevance, correspondence with earlier studies, ease in data collection across the study areas, and simplest in explanation of the model outcomes (parsimony). Prior to modelling, all continuous site covariates were scaled, (x -x ̅ )/SDx, to facilitate estimation of parameters using numerical optimization techniques and to make estimates comparable between parameters (Sunarto et al 2012;Nath et al 2019b;Jornburom et al 2020).…”
Section: Discussionmentioning
confidence: 99%
“…The presence of domestic animals, too, could influence detection since domestic animals can obliterate tracks of wild ungulates (pers. obs; Jornburom et al 2020). The presence/absence of domestic livestock was noted as a binary variable coded as "0" for absence and "1" for presence in every 100 m replicate.…”
Section: Selection Of Ecological and Anthropogenic Variablesmentioning
confidence: 99%
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