Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Relating populations to habitats using resource selection functions.

Boyce, McDonald

    Trends in Ecology & Evolution
    |June 17, 1999
    PubMed
    Summary

    Resource selection functions (RSFs) can now estimate animal population density. New methods integrate RSF models with geographical information systems (GIS) to map habitat use probability across landscapes.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Influence of Alcohol.

    Buffalo medical and surgical journal·2023
    Same author

    Correspondence.

    Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland·2013
    Same author

    A case of canine S. typhimurium infection with notes on other Salmonella infections in animals.

    The Indian veterinary journal·2010
    Same author

    Survey of the Free and Conjugated Myricetin and Quercetin Content of Red Wines of Different Geographical Origins.

    Journal of agricultural and food chemistry·2001
    Same author

    The incidence of intraductal papillary mucinous tumors of the pancreas(1).

    Current surgery·2000
    Same author

    Transient Ischemic Attack and Secondary Stroke.

    Current treatment options in neurology·2000

    Area of Science:

    • Ecology
    • Wildlife Biology
    • Conservation Science

    Background:

    • Resource selection functions (RSFs) quantify habitat use probability.
    • Linking RSFs to population density is crucial for wildlife management.
    • Geographical Information Systems (GIS) offer powerful spatial analysis tools.

    Purpose of the Study:

    • To present novel procedures for relating RSFs to population density.
    • To demonstrate the integration of RSF models with GIS for landscape-level analysis.
    • To enhance the application of RSFs in ecological research and conservation.

    Main Methods:

    • Utilized two recently developed procedures to connect RSFs with population density estimates.
    • Integrated RSF models with GIS for spatial mapping of habitat use probability.
    • Considered species-specific practical field procedures for data collection.

    Main Results:

    • Successfully established methods to link RSF models with population density.
    • Demonstrated the capability to map probability of use across landscapes using GIS.
    • Provided a framework for mapping animal populations based on habitat selection.

    Conclusions:

    • RSF models can be effectively interfaced with GIS for landscape-scale population estimation.
    • These advancements offer improved tools for wildlife research and conservation planning.
    • The integration facilitates a more comprehensive understanding of habitat use and its relation to population dynamics.

    Related Experiment Videos