Habitat Suitability Modeling of Bornean Orangutan (Pongo pygmaeus pygmaeus) in Betung Kerihun National Park, Danau Sentarum and Corridor, West Kalimantan

Prayogo, Hari; Thohari, Achmad Machmud; Duryadi, Dedy; Prasetyo, L B; Sugardjito, Jito

doi:10.7226/jtfm.19.2.112

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Some approaches used commonly for Species Distribution Modeling are linear regression [9], multivariate (Principal Component Analysis) [10][11][12], GLM [13][14], and Maxent [15]. The basis of SDM is located on the use of presence and absence data obtained from observation, specimens' records and literature.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Dermawan¹,

Herdiyeni²,

Prasetyo³

et al. 2018

TELKOMNIKA

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Section: Introductionmentioning

confidence: 99%

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Dermawan¹,

Herdiyeni²,

Prasetyo³

et al. 2018

TELKOMNIKA

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“…Species Distribution Models (SDMs) offers a quantitative approach to identify the relations between species and environment together with how these relations influence the geographic distributions of the species (species distribution) [8]. Some approaches used commonly for Species Distribution Modeling are linear regression [9], multivariate (Principal Component Analysis) [10][11][12], GLM [13][14], and Maxent [15]. The basis of SDM is located on the use of presence and absence data obtained from observation, specimens' records and literature.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

et al. 2018

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Acacia nilotica planted in Baluran National Park aims to prevent the spread of fire from savanna to teak forest became developed into invasive and led to a decrease in the quality and quantity of savannas. Therefore, it is required to predict the spread of A. nilotica to minimize the impacts of invasion on savanna area. The study aims to identify environmental factors which affect spread of A. nilotica. Furthermore, the spread of A. nilotica is predicted using Maximum Entropy. Maximum Entropy is efficient model since it uses presence-only data while the most of other models use presence and absence data. The experimental results reveal six environmental factors, including elevation, slope, NDMI, NDVI, distance from the river, and temperature were identified affecting the spread of A. nilotica. The most dominant environmental factors were elevation and temperature with 40% and 39.6% contributions. Maximum Entropy performed well in predicting the spread of A. nilotica, it was indicated by AUC value of 0.938.

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Simulating Agroforestry Adoption in Rural Indonesia: The Potential of Trees on Farms for Livelihoods and Environment

Nöldeke

Winter

Laumonier

et al. 2021

Land

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In recent years, agroforestry has gained increasing attention as an option to simultaneously alleviate poverty, provide ecological benefits, and mitigate climate change. The present study simulates small-scale farmers’ agroforestry adoption decisions to investigate the consequences for livelihoods and the environment over time. To explore the interdependencies between agroforestry adoption, livelihoods, and the environment, an agent-based model adjusted to a case study area in rural Indonesia was implemented. Thereby, the model compares different scenarios, including a climate change scenario. The agroforestry system under investigation consists of an illipe (Shorea stenoptera) rubber (Hevea brasiliensis) mix, which are both locally valued tree species. The simulations reveal that farmers who adopt agroforestry diversify their livelihood portfolio while increasing income. Additionally, the model predicts environmental benefits: enhanced biodiversity and higher carbon sequestration in the landscape. The benefits of agroforestry for livelihoods and nature gain particular importance in the climate change scenario. The results therefore provide policy-makers and practitioners with insights into the dynamic economic and environmental advantages of promoting agroforestry.

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Habitat Suitability Modeling of Bornean Orangutan (Pongo pygmaeus pygmaeus) in Betung Kerihun National Park, Danau Sentarum and Corridor, West Kalimantan

Abstract: Conservation areas such as national parks became the last safe area for biodiversity in

Cited by 3 publications

References 22 publications

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

Simulating Agroforestry Adoption in Rural Indonesia: The Potential of Trees on Farms for Livelihoods and Environment

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