Biodiversity Decision Support Tool (BIO-EST)
Abstract: BioEST predicts the distribution of species and is used to compare biomass-producing landscapes to landscapes that are reference scenarios. Thus far, the model has been used to map changes in the distributions of individual species in response to biomass production. Two approaches to representing the effects biomass production can be used. The direct method includes landscape predictors that are associated with bioenergy crop management. The indirect method uses independently-derived (e.g., literature) estimates of land-use effects based on studies that compared wildlife populations in different land uses. By combining results for multiple species, we are able to map changes in species
richness (number of species) and to interpret results in terms of species traits, i.e., wildlife species with some traits might benefit from growing some biomass crops whereas others may not benefit. The model was created to support the biodiversity chapter of the Billion Ton 2016 Volume II report, which analyzed avian biodiversity at a national (CONUS) scale. It is currently being used in an analysis focused on a broader array of wildlife taxa, including pollinators, game, and species of concern, in Iowa.
General Modeling Type:
Primary analytical purpose:
Environmental: Analysis of the environmental effects of bioenergy and bioproduct technologies or feedstocks.
Secondary analytical purpose:
Database: Database that is public or could be made public to facilitate modeling and analysis.
ORNL - Oak Ridge National Laboratory
Model start year:
Model last updated:
Level of validation/review:
External Peer Review
- Feedstock Types
- Sugar Crops
- Oil Crops
- Fiber Crops
- Cover Crops and Hay
- Herbaceous Energy Crops
- Forest Residues
- Forest Resources
- Woody Energy Crops
Model Map HelpThe below diagram shows models interlinked with the Biodiversity Decision Support Tool (BIO-EST) model. Click on a different model to view the fact sheet for the clicked model.
Information last updated: Sep. 17, 2019 13:45:46 EDT