Predicting the risk of wild boar damage to rice paddies using presence-only data in Chiba Prefecture, Japan

Autor:	Seiji Uematsu, Hiroshi Momose, Tosaku Mihira, Masayuki U. Saito
Rok vydání:	2012
Předmět:	education.field_of_study Oryza sativa biology Ecology Population Linear model Generalised additive model Wild boar Modelling methods Insect Science biology.animal Statistics Paddy field education Independent data Agronomy and Crop Science
Zdroj:	International Journal of Pest Management. 58:65-71
ISSN:	1366-5863 0967-0874
Popis:	Population sizes of wild boar (Sus scrofa) and the damage they cause to crops have been increasing in Japan. Reliable techniques are needed to estimate the potential for damage at the landscape scale. Here, we predict the risk of damage to rice (Oryza sativa) paddies by wild boar in Chiba Prefecture, Japan, by means of three different modelling methods – Maxent, generalised linear model (GLM) and generalised additive model (GAM) – using a combination of presence-only damage data obtained from a local agency and environmental information derived from publicly available databases. We used damage locations in 2007 and 2008. To validate the models, we calculated the area under the curve (AUC) and the correct classification rate (CCR) using independent data obtained in field surveys. The three methods gave similar results, indicating that we could construct a predictive model with high accuracy from presence-only data. Among these three, Maxent showed the closest fit, with 0.78 AUC and 72.6% CCR values. Becaus...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ccd3fcee0b5828e1d6b487e36ee3d7d3 https://doi.org/10.1080/09670874.2011.648230 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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