Skip to main content
Advanced Search

Filters: Tags: species distribution modeling (X) > Types: Citation (X)

4 results (42ms)   

View Results as: JSON ATOM CSV
thumbnail
This data bundle contains some of the inputs, all of the processing instructions and all outputs from a single VisTrails/SAHM workflow. This model specifically includes location data for Bombina orientalis and random background locations. Predictors include climatic, topographic, and land cover rasters. The three bundle documentation files are: 1) '_archive_bundle_metadata.xml' which contains FGDC metadata describing the archive bundle. 2) '_archive_raster_inputs.csv' a list of the raster inputs that were used to generate these model results. These are not included in the archive bundle due to size constraints but are identified in this file as well as the metadata document. 3) '_archive_workflow_Final runs.vt'...
An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations....
Aim Assessing the influence of land cover in species distribution modelling is limited by the availability of fine-resolution land-cover data appropriate for most species responses. Remote-sensing technology offers great potential for predicting species distributions at large scales, but the cost and required expertise are prohibitive for many applications. We test the usefulness of freely available raw remote-sensing reflectance data in predicting species distributions of 40 commonly occurring bird species in western Oregon. Location Central Coast Range, Cascade and Klamath Mountains Oregon, USA. Methods Information on bird observations was collected from 4598 fixed-radius point counts. Reflectance data...
There is a broad consensus within the scientific community that global climate is undergoing a comparatively rapid change. Since many plants and animals depend on specific types of climate, it is imperative to understand: (1) the details of species’ climatic preferences; (2) how climates may change in the future; and (3) how species may respond to these changes. Species distribution modeling (SDM) is an increasingly important tool to address conservation biology and global change issues. As Fortini and colleagues described in their largest vulnerability assessment in the US, SDMs provide critical information on biological refuges and potential future shifts in species ranges. In addition, climate changes could alter...