Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?

VanDerWal, Jeremy; Shoo, Luke P.; Graham, Catherine H.; Williams, Stephen E.

doi:10.1016/j.ecolmodel.2008.11.010

Cited by 712 publications

(622 citation statements)

References 18 publications

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“…The selection of an appropriate extent which is relevant for all correlative SDMs employing background, pseudo-absence, or absence data (Bahn and McGill 2007;Barve et al 2011;Chefaoui and Lobo 2008) may help resolve debates regarding model generality/transferability across space and time (e.g., Duncan et al 2009). Our results support the hypothesis that SDMs predict differently when different methods of defining the extent are used (Anderson and Raza 2010;Barve et al 2011;VanDerWal et al 2009). Of the two methods applied here, Anderson and Raza (2010) found that method 2 performed better than method 1; models using method 2 at narrower extents predicted larger suitable areas which were less concentrated in regions surrounding species' localities, as well as higher interpredictivity.…”

Section: Effects Of the Extent Of The Study Region On Predicted Distrsupporting

confidence: 86%

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

Jiang

2012

Naturwissenschaften

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Species distribution modeling (SDM) is increasingly used to reveal biogeographical relationships, for example the sympatric range for species coexistence, and fundamental questions about niche evolution between related species. We explored the sympatric ranges between three Procapra species (Procapra przewalskii, Procapra Picticaudata, and Procapra gutturosa) via two methods of defining the study region (method 1, in which models were developed in a larger region including the whole geographic range of Procapra, and method 2 in which a smaller region surrounding focal species' localities was used and then projected to the larger region). We also quantified environmental niche divergence between gazelles across the whole range in Procapra. Models for gazelles generally performed well. Compared with method 2, method 1 led to larger predicted areas with high suitability and was less concentrated around known localities. Clamping, which deals with variables outside the training range, varied between gazelles and occurred primarily in regions unsuitable for respective species. For all gazelle pairs, models revealed an overlap zone where more than one species should occur, while the estimates varied between the two methods. Moreover, we found that the niche overlap was closely associated with geographic distance but not with phylogenetic distance among gazelles. Our findings indicate that SDM is a useful tool for testing whether related species tend to be in sympatry at large scales, with method 1 leading to more realistic predictions for Procapra. This study provides evidence of a distinct niche divergence among related species and supports the theory that ecological speciation plays a significant role in lineage generation.

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Section: Effects Of the Extent Of The Study Region On Predicted Distrsupporting

confidence: 86%

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

Jiang

2012

Naturwissenschaften

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“…We calibrated models within a region bounded by the Americas and 348 W longitude, and 488 N and 448 S latitude (figure 1). We sought the union of the area sampled by researchers and most likely to be accessible to the species across spatial and temporal dimensions [13,64,65]. We used all spatially explicit data points for each species/time slice, running 100 bootstrap replicates with a 10% random test percentage.…”

Section: (D) Modelling Algorithmmentioning

confidence: 99%

Macroevolutionary consequences of profound climate change on niche evolution in marine molluscs over the past three million years

et al. 2014

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“…This approach has shown to be one of the best performing models in predicting species distributions with presence-only data (Elith et al, 2006;Hijmans and Graham, 2006), and it has been extensively applied to project species range and vegetation shifts under climate change (Rebelo et al, 2010;Ponce-Reyes et al, 2012;Wong et al, 2013). The full extent of the study area was used to extract background (pseudo-absence) data to improve model performance (VanderWal et al, 2009). We performed 10 replications for each bamboo species and a maximum of 500 iterations for the giant panda, using a cross-validation procedure where we divided our dataset using 75% of the data for model calibration and retaining 25% of the data for evaluation.…”

Section: Species Distribution Modeling and Testingmentioning

confidence: 99%

Climate change threatens giant panda protection in the 21st century

Wong

et al. 2015

Biological Conservation

111

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a b s t r a c tIt is increasingly recognized that biotic interactions could play a significant role in species distribution modelling. To assess the conservation effectiveness of the giant panda (Ailuropoda melanoleuca) reserves in a changing climate, we combined both biotic variables (food availability) and abiotic (climatic and geographic) to project the potential changes of distribution and quality of giant panda habitats using the most recent IPCC-CMIP5 climate scenarios. Our results suggested that climate change would adversely affect giant pandas through habitat degradation, in that: (1) 52.9-71.3% of the current habitats could be lost; (2) the giant panda habitats could become more fragmented and isolated; and (3) both the quantity and quality of habitats in the current giant panda reserves could substantially contract, and approximately 20% of the reserves could lose all habitat representations in this century. Additionally, we found that climate change would make it increasingly necessary to translocate small populations of pandas from the southwestern to the northwestern part of the current distribution range to ensure population viability. Our results suggest the need for immediate change in current conservation policies and formulating adaptation plans for giant panda conservation in a changing climate.

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Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?

Cited by 712 publications

References 18 publications

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra

Macroevolutionary consequences of profound climate change on niche evolution in marine molluscs over the past three million years

Climate change threatens giant panda protection in the 21st century

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