Dataset Information

Introducing BioSARN - an ecological niche model refinement tool.

ABSTRACT: Environmental niche modeling outputs a biological species' potential distribution. Further work is needed to arrive at a species' realized distribution. The Biological Species Approximate Realized Niche (BioSARN) application provides the ecological modeler with a toolset to refine Environmental niche models (ENMs). These tools include soil and land class filtering, niche area quantification and novelties like enhanced temporal corridor definition, and output to a high spatial resolution land class model. BioSARN is exemplified with a study on Fraser fir, a tree species with strong land class and edaphic correlations. Soil and land class filtering caused the potential distribution area to decline 17%. Enhanced temporal corridor definition permitted distinction of current, continuing, and future niches, and thus niche change and movement. Tile quantification analysis provided further corroboration of these trends. BioSARN does not substitute other established ENM methods. Rather, it allows the experimenter to work with their preferred ENM, refining it using their knowledge and experience. Output from lower spatial resolution ENMs to a high spatial resolution land class model is a pseudo high-resolution result. Still, it maybe the best that can be achieved until wide range high spatial resolution environmental data and accurate high precision species occurrence data become generally available.

SUBMITTER: Heap MJ

PROVIDER: S-EPMC4983593 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Introducing BioSARN - an ecological niche model refinement tool.

Heap Marshall J MJ

Ecology and evolution 20160722 16

Environmental niche modeling outputs a biological species' potential distribution. Further work is needed to arrive at a species' realized distribution. The Biological Species Approximate Realized Niche (BioSARN) application provides the ecological modeler with a toolset to refine Environmental niche models (ENMs). These tools include soil and land class filtering, niche area quantification and novelties like enhanced temporal corridor definition, and output to a high spatial resolution land cla ...[more]

PMID: 27547356

Similar Datasets

Project description:COVID-19 pandemic is a global threat to human health and economy that requires urgent prevention and monitoring strategies. Several models are under study to control the disease spread and infection rate and to detect possible factors that might favour them, with a focus on understanding the correlation between the disease and specific geophysical parameters. However, the pandemic does not present evident environmental hindrances in the infected countries. Nevertheless, a lower rate of infections has been observed in some countries, which might be related to particular population and climatic conditions. In this paper, infection rate of COVID-19 is modelled globally at a 0.5∘ resolution, using a Maximum Entropy-based Ecological Niche Model that identifies geographical areas potentially subject to a high infection rate. The model identifies locations that could favour infection rate due to their particular geophysical (surface air temperature, precipitation, and elevation) and human-related characteristics (CO 2 and population density). It was trained by facilitating data from Italian provinces that have reported a high infection rate and subsequently tested using datasets from World countries' reports. Based on this model, a risk index was calculated to identify the potential World countries and regions that have a high risk of disease increment. The distribution outputs foresee a high infection rate in many locations where real-world disease outbreaks have occurred, e.g. the Hubei province in China, and reports a high risk of disease increment in most World countries which have reported significant outbreaks (e.g. Western U.S.A.). Overall, the results suggest that a complex combination of the selected parameters might be of integral importance to understand the propagation of COVID-19 among human populations, particularly in Europe. The model and the data were distributed through Open-science Web services to maximise opportunities for re-usability regarding new data and new diseases, and also to enhance the transparency of the approach and results.

Project description:Speciation among members of the Anopheles gambiae complex is thought to be promoted by disruptive selection and ecological divergence acting on sets of adaptation genes protected from recombination by polymorphic paracentric chromosomal inversions. However, shared chromosomal polymorphisms between the M and S molecular forms of An. gambiae and insufficient information about their relationship with ecological divergence challenge this view. We used Geographic Information Systems, Ecological Niche Factor Analysis, and Bayesian multilocus genetic clustering to explore the nature and extent of ecological and chromosomal differentiation of M and S across all the biogeographic domains of Cameroon in Central Africa, in order to understand the role of chromosomal arrangements in ecological specialisation within and among molecular forms.Species distribution modelling with presence-only data revealed differences in the ecological niche of both molecular forms and the sibling species, An. arabiensis. The fundamental environmental envelope of the two molecular forms, however, overlapped to a large extent in the rainforest, where they occurred in sympatry. The S form had the greatest niche breadth of all three taxa, whereas An. arabiensis and the M form had the smallest niche overlap. Correspondence analysis of M and S karyotypes confirmed that molecular forms shared similar combinations of chromosomal inversion arrangements in response to the eco-climatic gradient defining the main biogeographic domains occurring across Cameroon. Savanna karyotypes of M and S, however, segregated along the smaller-scale environmental gradient defined by the second ordination axis. Population structure analysis identified three chromosomal clusters, each containing a mixture of M and S specimens. In both M and S, alternative karyotypes were segregating in contrasted environments, in agreement with a strong ecological adaptive value of chromosomal inversions.Our data suggest that inversions on the second chromosome of An. gambiae are not causal to the evolution of reproductive isolation between the M and S forms. Rather, they are involved in ecological specialization to a similar extent in both genetic backgrounds, and most probably predated lineage splitting between molecular forms. However, because chromosome-2 inversions promote ecological divergence, resulting in spatial and/or temporal isolation between ecotypes, they might favour mutations in other ecologically significant genes to accumulate in unlinked chromosomal regions. When such mutations occur in portions of the genome where recombination is suppressed, such as the pericentromeric regions known as speciation islands in An. gambiae, they would contribute further to the development of reproductive isolation.

Dataset Information

Introducing BioSARN - an ecological niche model refinement tool.

Publications

Introducing BioSARN - an ecological niche model refinement tool.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure