Predicting bird distributions and identifying important influences on bird distribution and abundance

2007 Impact statement

abstract

This project is the third facet of the creation of the Avian Knowledge Network (URL: www.avianknowledge.net), an initiative to: (1) bring together all available bird monitoring data into a single, easily accessible repository and; (2) produce exploratory analyses of these data in order to identify environmental features that have a high likelihood of affecting birds` distribution and abundance; and (3) create mechanisms for extracting from these analyses the patterns and relationships most relevant to an individual wishing to use analysis output. In order to predict bird distributions and understand the environmental factors that control these distributions we are introducing new techniques for data analysis to ecologists. These techniques are both existing (machine-learning) methods from the computer sciences, as well as creating new techniques that merge the strengths of data analysis techniques from the computer and statistical sciences.

submitted by

issue being addressed

In order to effectively manage North America`s wildlife in the face of ever increasing human impact on our environment, managers and conservation biologists need to be able to: (1) know where each species occurs; and (2) understand the environmental features that cause each species to be present in some areas but not others. While all of the needed information is known for a few, intensively studied species, little is known about many other species, which hampers management efforts.

response

Our work provides wildlife managers an initial screening of hundreds of environmental features that potentially impact species`, thus providing the initial knowledge with which to guide efficiently focused research and management efforts. We are designing processes for automated analysis of all major sources of bird monitoring data in North America, creating a web site that allows interested parties access to the raw data and analyses, and methods for exploring the results from analyses in order to identify the patterns of greatest interest to anyone interested.

impact assessment

The analysis and Web output parts of the Avian Knowledge Network are still under development, and as such impacts are only starting to be apparent. Currently, the most obvious impact is that we have started altering "best practices" for t"e use of exist"ng data resources by introducing a suite of analysis techniques unfamiliar to most ecologists. These novel (to ecologists) techniques have the advantage of being more likely to identify important influences on birds, and hence identifying appropriate targets for management action.

academic priority area

has geographic focus

funding source description

  • Leon Levy Foundation
  • National Science Foundation

collaborators

  • Cornell Department of Computer Science
  • USDA Forest Service Redwood Sciences Laboratory
  • Rocky Mountain Bird Observatory
  • Institute for Bird Populations
  • Avian Science Center at The University of Montana
  • PRBO Conservation Science
  • Bird Studies Canada
  • Cornell Department of Statistical Sciences

key personnel

  • Daria Sorokina
  • Ben Shaby
  • Mirek Riedewald
  • Denis Lapage
  • Art Munson
  • David Hanni
  • Rich Caruana
  • Danial Fink
  • Steve Kelling
  • Nadav Nur

mission focus

From CALS annual faculty reporting. Imported on August 5, 2008