Skip to main content
WCS
Menu
Library
Library Catalog
eJournals & eBooks
WCS Research
Archives
Research Use
Finding Aids
Digital Collections
WCS History
WCS Research
Research Publications
Science Data
Services for WCS Researchers
Archives Shop
Bronx Zoo
Department of Tropical Research
Browse By Product
About Us
FAQs
Intern or Volunteer
Staff
Donate
Search WCS.org
Search
search
Popular Search Terms
WCS History
Library and Archives
Library and Archives Menu
Library
Archives
WCS Research
Archives Shop
About Us
Donate
en
fr
Title
Using machine learning to advance synthesis and use of conservation and environmental evidence
Author(s)
Cheng, S. ;Augustin, C. ;Bethel, A. ;Gill, D. ;Anzaroot, S. ;Brun, J. ;DeWilde, B. ;Minnich, R. ;Garside, R. ;Masuda, Y. ;Miller, D. ;Wilkie, D. ;Wongbusarakum, S. ;McKinnon, M.
Published
2018
Publisher
Conservation Biology
Published Version DOI
https://doi.org/10.1111/cobi.13117
Abstract
Rapid growth in environmental research (Li & Zhao 2015) presents a potential wealth of information for conservation decision‐making. Evidence synthesis methods (e.g. systematic maps, reviews, meta‐analyses) (Pullin & Knight 2009) are critical for garnering actionable insight from published research, yet come with high resource demands (time and funding) that are prohibitive for meeting short policy windows (Elliott et al. 2014) and balancing trade‐offs between conservation planning and implementation.
Access Full Text
A full-text copy of this article may be available. Please email the
WCS Library
to request.
Back
PUB23939