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Range bagging: a new method for ecological niche modelling from presence-only data.

ABSTRACT: The ecological niche is the set of environments in which a population of a species can persist without introduction of individuals from other locations. A good mathematical or computational representation of the niche is a prerequisite to addressing many questions in ecology, biogeography, evolutionary biology and conservation. A particularly challenging question for ecological niche modelling is the problem of presence-only modelling. That is, can an ecological niche be identified from records drawn only from the set of niche environments without records from non-niche environments for comparison? Here, I introduce a new method for ecological niche modelling from presence-only data called range bagging. Range bagging draws on the concept of a species' environmental range, but was inspired by the empirical performance of ensemble learning algorithms in other areas of ecological research. This paper extends the concept of environmental range to multiple dimensions and shows that range bagging is computationally feasible even when the number of environmental dimensions is large. The target of the range bagging base learner is an environmental tolerance of the species in a projection of its niche and is therefore an ecologically interpretable property of a species' biological requirements. The computational complexity of range bagging is linear in the number of examples, which compares favourably with the main alternative, Qhull. In conclusion, range bagging appears to be a reasonable choice for niche modelling in applications in which a presence-only method is desired and may provide a solution to problems in other disciplines where one-class classification is required, such as outlier detection and concept learning.

SUBMITTER: Drake JM

PROVIDER: S-EPMC4590497 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Range bagging: a new method for ecological niche modelling from presence-only data.

Drake John M JM

Journal of the Royal Society, Interface 20150601 107

The ecological niche is the set of environments in which a population of a species can persist without introduction of individuals from other locations. A good mathematical or computational representation of the niche is a prerequisite to addressing many questions in ecology, biogeography, evolutionary biology and conservation. A particularly challenging question for ecological niche modelling is the problem of presence-only modelling. That is, can an ecological niche be identified from records ...[more]

PMID: 25948612

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Project description:In an era of anthropocene, threatened and endemic species with small population sizes and habitat specialists experience a greater global conservation concern in view of being at higher risk of extinction. Predicting and plotting appropriate potential habitats for such species is a rational method for monitoring and restoring their dwindling populations in expected territories. Ecological niche modelling (ENM) coalesces species existence sites with environmental raster layers to construct models that describe possible distributions of plant species. The present study is aimed to study the potential distribution and cultivation hotspots for reintroducing the high value, vulnerable medicinal herb (Rheum webbianum) in the Union territories of Jammu and Kashmir and Ladakh using population attributes and ecological niche modelling approach. Sixty-three populations inventoried from twenty-eight areas display a significant change in the phytosociological attributes on account of various anthropogenic threats. The current potential habitats coincide with actual distribution records and the mean value of Area Under Curve (AUC) was 0.98 and the line of predicted omission was almost adjacent to omission in training samples, thus validating a robustness of the model. The potential habitat suitability map based on the current climatic conditions predicted a total of 103760 km2 as suitable area for the growth of Rheum webbianum. Under the future climatic conditions, there is a significant reduction in the habitat suitability ranging from -78531.34 Km2 (RCP 4.5 for 2050) to -77325.81 (RCP 8.5 for 2070). Furthermore, there is a slight increase in the suitable habitats under future climatic conditions, ranging from +21.99 Km2 under RCP 8.5 (2050) to +3.14 Km2 under RCP 4.5 (2070). The Jackknife tests indicated Precipitation of Driest Month (BIO14) as the most contributing climatic variable in governing the distribution of R. webbianum. Therefore, scientifically sound management strategies are urgently needed to save whatever populations are left in-situ to protect this species from getting extinct. Present results can be used by conservationists for mitigating the biodiversity decline and exploring undocumented populations of R. webbianum on one hand and by policymakers in implementing the policy of conservation of species with specific habitat requirements by launching species recovery programmes in future on the other.

Dataset Information

Range bagging: a new method for ecological niche modelling from presence-only data.

Publications

Range bagging: a new method for ecological niche modelling from presence-only data.

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