Understanding of Pest Species Distribution on Land Use, Geographic Location, and Climate Factor using Species Distribution Modelling: Case Study in Java Island, Indonesia

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AUTHOR

Usnil Khotimah
SSRS Indonesia Biodiversity Hub, SSRS Institute Indonesia, Bogor Regency, Indonesia

Muhammad Ferdiansyah
SSRS AgroInformatics Labs, SSRS Institute Indonesia, Bogor Regency, Indonesia

Abd. Malik A. Madinu
SSRS Indonesia Earth Observatory (Inarth Indonesia), SSRS Institute Indonesia, Bogor Regency, Indonesia

Aulia Ulfa
SSRS Indonesia Biodiversity Hub, SSRS Institute Indonesia, Bogor Regency, Indonesia

Danik Septianingrum
SSRS Indonesia Biodiversity Hub, SSRS Institute Indonesia, Bogor Regency, Indonesia

Salsabila Nur’Aini
SSRS Indonesia Biodiversity Hub, SSRS Institute Indonesia, Bogor Regency, Indonesia

Khairani Putri Marfi
SSRS Indonesia Tropical Ecological Observatory, SSRS Institute Indonesia, Bogor Regency, Indonesia

Nurah Anggraeni
SSRS Indonesia Biodiversity Hub, SSRS Institute Indonesia, Bogor Regency, Indonesia

Alifia Cantika Nurrahmah
SSRS AgroInformatics Labs, SSRS Institute Indonesia, Bogor Regency, Indonesia

Rahmat Asy’Ari
SSRS EarthInformatics Labs, SSRS Institute Indonesia, Bogor Regency, Indonesia

Lina Lathifah Nurazizah
Researcher Fellow in SSRS Institute Indonesia, Bogor Regency, Indonesia

Ongky Ongky
Research Fellow in SSRS Institute Indonesia, Bogor Regency, Indonesia

Mihwan Sataral
Agrotechnology Department, University of Tompotika Luwuk, Banggai Regency, Indonesia

Fahri Fahri
Biology Department, Faculty of Science, University of Tadulako, Palu City, Indonesia

Yudi Setiawan
Center for Environmental Research, IPB University, Bogor Regencym Indonesia
https://orcid.org/0000-0001-8569-7203

ABSTRACT

Pest distribution has a broad impact across sectors, including agriculture, plantations, and forestry. The impacts are predicted to continue to increase in the future, so understanding pest distribution patterns is important as a basis for more effective pest management decision-making. This study aims to analyze the distribution of pests in Java Island based on land use, geographical location, and climate factors. A total of 2,777 individuals from 14 pest families in GBIF citizen science data were analyzed using a machine-learning-based Species Distribution Modeling (SDM) approach to map habitat suitability. Modeling was conducted using 12 WorldClim bioclimate variables: temperature (bio1, bio2, bio4-bio11), thermal (bio3), and rainfall (bio12). Model accuracy was evaluated using two metrics: Area Under the Curve (AUC) and Kappa. The results showed that most pest families were distributed across three land-use types, with a dominance on agricultural land and at elevations below 500 meters above sea level. Land Surface Temperature (LST) data shows that pests are generally found at temperatures between 15°C and 35°C. Among all bioclimate variables analyzed, annual rainfall (bio12) has the highest influence on habitat suitability. The model performs well, with an average AUC of 0.88 and a Kappa of 0.64, indicating that the predicted pest distribution is accurate enough for pest management planning in the study area. Information on the spatial distribution and potential habitats is needed to target natural treatments.

CITATION

Khotimah U, Ferdiansyah M, Madinu AMA, Ulfa A, Septianingrum D, Nurrahmah AC, Asy’Ari R, Nurazizah LN, Ongky O, Sataral M, Fahri F, Katili HA, Setiawan Y. 2025. Understanding of Pest Species Distribution on Land Use, Geographic Location, and Climate Factor using Species Distribution Modelling: Case Study in Java Island, Indonesia. SSRS Journal A: Agro-Environmental Research. 3: 57 – 73 https://publishing.ssrs.or.id/ojs/index.php/ssrs-a/article/view/63