Species distribution models: A comparison of statistical approaches for livestock and disease epidemics.

ABSTRACT: In livestock industries, reliable up-to-date spatial distribution and abundance records for animals and farms are critical for governments to manage and respond to risks. Yet few, if any, countries can afford to maintain comprehensive, up-to-date agricultural census data. Statistical modelling can be used as a proxy for such data but comparative modelling studies have rarely been undertaken for livestock populations. Widespread species, including livestock, can be difficult to model effectively due to complex spatial distributions that do not respond predictably to environmental gradients. We assessed three machine learning species distribution models (SDM) for their capacity to estimate national-level farm animal population numbers within property boundaries: boosted regression trees (BRT

SUBMITTER: Hollings T 

PROVIDER: S-EPMC5570337 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature