SBIR Phase II: Assessing Status and Trends of Threatened Species from Uncertain Monitoring Data: Methodology and Software
Small Business Information
Appl Biomathematics Inc
100 North Country Road, Setauket, NY, 11733
AbstractThis Small Business Innovation Research (SBIR) Phase II project aims to develop and implement as software methods for entering, processing, and analyzing species distribution monitoring data, which is one of the most basic forms of biological information that comes from surveys, censuses, and other routine assessments. These methods will use basic monitoring data to (1) assess the status and trends of the monitored species at the population-level, and (2) estimate the input parameters for the more advanced quantitative models, thereby increasing the use of these models, which include population viability analysis models, habitat models and other GIS-based methods, and quantitative risk criteria, such those used by the World Conservation Union (IUCN) and the NatureServe. One of the major innovations of the proposed software will be its treatment of uncertainty. Ecological data are often scarce and uncertain, including spatial and temporal variation, measurement and sampling errors, and demographic variance. The methods to be implemented in the proposed software will account for this uncertainty and incorporate it into the assessment of status and other outputs produced. Broader impacts of the project will include standardization of the monitoring process for a broad spectrum of species, significantly reducing the cost of processing and analyzing monitoring data and increasing the use of advanced quantitative models in relation to environmental issues. This will, in turn, increase the use of scientific information in environmental decision-making and policy formulation. The methods developed in this project will also allow incorporating data uncertainties in an objective, transparent, and credible way, thereby providing scientifically credible and sound summary of the status and trends of the species monitored. The proposed methods will be implemented as software. Expected commercial applications include software sales and contracts for specific applications of the software.
* information listed above is at the time of submission.