NDLI: Using prior information to build probabilistic invasive species risk assessments

Content Provider	Springer Nature Link
Author	Diez, Jeffrey M. Hulme, Philip E. Duncan, Richard P.
Copyright Year	2011
Abstract	Understanding why some introduced species become naturalized and invasive whereas others do not is a major focus of invasion ecology. Invasive species risk assessments address this same question, but are not typically based on the results from recent ecological studies. Applying results from the ecological literature to risk assessment is difficult, in part because there are no general explanations of invasion likelihood across taxa. Most ecological studies are also specific to a particular region and it is unclear whether outcomes in one region will necessarily apply to another. Here we show how a hierarchical Bayesian statistical framework can make better use of ecological studies for applied risk assessments. We focus on three key opportunities afforded by these models: (1) the ability to leverage information from one region to form prior expectations for other regions about which little is known, (2) the ability to quantify uncertainty of predictions, and (3) flexibility to incorporate within-group heterogeneities in probabilities of naturalization. We illustrate these principles using a case study where we predict the probability of plant taxa naturalizing in New Zealand and Australia, showing how prior information can be particularly valuable when data are limited. As more studies document invasion patterns around the world, a framework that can formally incorporate prior information will help link the accumulating data on species introductions to risk assessments.
Starting Page	681
Ending Page	691
Page Count	11
File Format	PDF
ISSN	13873547
Journal	Biological Invasions
Volume Number	14
Issue Number	3
e-ISSN	15731464
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-09-23
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Invasive species Risk assessment Bayesian Prior information Plant Sciences Freshwater & Marine Ecology Developmental Biology Ecology
Content Type	Text
Resource Type	Article
Subject	Ecology Ecology, Evolution, Behavior and Systematics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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