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Land-Use/Land-Cover Change from Socio-Economic Drivers and Their Impact on Biodiversity in Nan Province, Thailand

Author

Listed:
  • Yongyut Trisurat

    (Faculty of Forestry, Kasetsart University, Bangkok 10900, Thailand)

  • Hiroaki Shirakawa

    (Department of Urban Environment, Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan)

  • John M. Johnston

    (USEPA/ORD/NERL Computational Exposure Division, Athens, GA 30605, USA)

Abstract

The rate of deforestation declined steadily in Thailand since the year 2000 due to economic transformation away from forestry. However, these changes did not occur in Nan Province located in northern Thailand. Deforestation is expected to continue due to high demand for forest products and increased agribusiness. The objectives of this paper are (1) to predict land-use change in the province based on trends, market-based and conservation scenarios, (2) to quantify biodiversity, and (3) to identify biodiversity hotspots at greatest risk for future deforestation. This study used a dynamic land-use change model (Dyna-CLUE) to allocate aggregated land demand for three scenarios and employed FRAGSTATS to determine the spatial pattern of land-use change. In addition, the InVEST Global Biodiversity Assessment Model framework was used to estimate biodiversity expressed as the remaining mean species abundance (MSA) relative to their abundance in the pristine reference condition. Risk of deforestation and the MSA values were combined to determine biodiversity hotspots across the landscape at greatest risk. The results revealed that most of the forest cover in 2030 would remain in the west and east of the province, which are rugged and not easily accessible, as well as in protected areas. MSA values are predicted to decrease from 0.41 in 2009 to 0.29, 0.35, and 0.40, respectively, under the trends, market-based and conservation scenarios in 2030. In addition, the low, medium, and high biodiversity zones cover 46, 49 and 6% of Nan Province. Protected areas substantially contribute to maintaining forest cover and greater biodiversity. Important measures to protect remaining cover and maintain biodiversity include patrolling at-risk deforestation areas, reduction of road expansion in pristine forest areas, and promotion of incentive schemes for farmers to rehabilitate degraded ecosystems.

Suggested Citation

  • Yongyut Trisurat & Hiroaki Shirakawa & John M. Johnston, 2019. "Land-Use/Land-Cover Change from Socio-Economic Drivers and Their Impact on Biodiversity in Nan Province, Thailand," Sustainability, MDPI, vol. 11(3), pages 1-22, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:649-:d:200974
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    References listed on IDEAS

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    Cited by:

    1. Meng Wang & Xiaofang Sun & Zemeng Fan & Tianxiang Yue, 2019. "Investigation of Future Land Use Change and Implications for Cropland Quality: The Case of China," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    2. Honglei Jiang & Xia Xu & Mengxi Guan & Lingfei Wang & Yongmei Huang & Yinghui Liu, 2019. "Simulation of Spatiotemporal Land Use Changes for Integrated Model of Socioeconomic and Ecological Processes in China," Sustainability, MDPI, vol. 11(13), pages 1-18, July.
    3. Zhang, Xueru & Song, Wei & Lang, Yanqing & Feng, Xiaomiao & Yuan, Quanzhi & Wang, Jingtao, 2020. "Land use changes in the coastal zone of China’s Hebei Province and the corresponding impacts on habitat quality," Land Use Policy, Elsevier, vol. 99(C).
    4. Jamroon Srichaichana & Yongyut Trisurat & Suwit Ongsomwang, 2019. "Land Use and Land Cover Scenarios for Optimum Water Yield and Sediment Retention Ecosystem Services in Klong U-Tapao Watershed, Songkhla, Thailand," Sustainability, MDPI, vol. 11(10), pages 1-22, May.
    5. Chouaib Jouf & Laté Lawson, 2021. "European farmers’ responses to higher commodity prices: cropland expansion or forestlands preservation?," EconomiX Working Papers 2021-10, University of Paris Nanterre, EconomiX.
    6. Starfinger, Marcel, 2021. "Financing smallholder tree planting: Tree collateral & Thai ‘Tree Banks’ - Collateral 2.0?," Land Use Policy, Elsevier, vol. 111(C).
    7. Penny, Jessica & Ordens, Carlos M. & Barnett, Steve & Djordjević, Slobodan & Chen, Albert S., 2023. "Small-scale land use change modelling using transient groundwater levels and salinities as driving factors – An example from a sub-catchment of Australia’s Murray-Darling Basin," Agricultural Water Management, Elsevier, vol. 278(C).

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