2014
DOI: 10.1111/aec.12160
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Genetic inference as a method for modelling occurrence: A viable alternative to visual surveys

Abstract: Management and conservation require a comprehensive understanding of species distributions and habitat requirements. Reliable species occurrence data are critical in the face of climate change and other anthropogenic activity, but are often difficult to obtain, particularly for wide ranging species. This directly affects ecological models of occurrence and habitat suitability and, in turn, conservation and management decisions. We used generalized linear mixed-effects models to identify ecological determinants… Show more

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Cited by 5 publications
(5 citation statements)
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“…Nevertheless, the costs and time effort depend on the approach the noninvasive genetic assessment is being compared with, the type of study, and the research design (Table S1). For instance, field visual or acoustic survey used for population size estimation or species detection could be both less expensive [107,108] or more expensive [13,78,[109][110][111] than noninvasive genetic sampling and analysis. Similarly, one study reported lower costs of camera traps for population size estimation [38], while two studies reported the opposite [112,113].…”
Section: Cost and Time Effort Advantagesmentioning
confidence: 99%
See 1 more Smart Citation
“…Nevertheless, the costs and time effort depend on the approach the noninvasive genetic assessment is being compared with, the type of study, and the research design (Table S1). For instance, field visual or acoustic survey used for population size estimation or species detection could be both less expensive [107,108] or more expensive [13,78,[109][110][111] than noninvasive genetic sampling and analysis. Similarly, one study reported lower costs of camera traps for population size estimation [38], while two studies reported the opposite [112,113].…”
Section: Cost and Time Effort Advantagesmentioning
confidence: 99%
“…Genetic monitoring in particular can be a powerful research tool, as it is capable of providing the same information as other methods, for instance, population size estimates [10,11], species detection [12,13], individual identification [14,15], or diet composition [16][17][18]. Moreover, DNA analyses can deliver multitude of data that might be difficult or impossible to obtain with other methods, e.g., on relatedness among individual animals [19,20], population structure [21][22][23], origin of invasive species [24][25][26][27], hybridization [28][29][30][31], past and present population sizes [7,32,33], or gene flow [26,27,31,[34][35][36][37][38][39].…”
Section: Introductionmentioning
confidence: 99%
“…We used a two-phased analytical approach to select the best model (e.g., Wadley, Austin, & Fordham, 2014). We used a two-phased analytical approach to select the best model (e.g., Wadley, Austin, & Fordham, 2014).…”
Section: Model Construction and Evaluationmentioning
confidence: 99%
“…To determine the "best" model and to avoid over-parametrization, we first constructed a set of candidate models based on expert knowledge, representing different biological processes (and their combination) likely to define the rabbit distribution in Australia (Supporting Information S4). We used a two-phased analytical approach to select the best model (e.g., Wadley, Austin, & Fordham, 2014). We first constructed a candidate set of models with only climatic and another with nonclimatic covariates and used multimodel inference to select the best models for each group.…”
Section: Model Construction and Evaluationmentioning
confidence: 99%
“…Similarly, for large marsupials, marked variation in faecal morphology (e.g. clumping or unsegmented cylinders) relating to seasonal variability in diet is known to lead to challenges in the morphological differentiation of faeces among the eastern grey kangaroo (Macropus giganteus), swamp wallaby (Wallabia bicolor) and common wombat (Vombatus ursinus) [10] and between or among other marsupial species [14][15][16].…”
Section: Introductionmentioning
confidence: 99%