Science Inventory

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

Citation:

Trisurat, Y., H. Shirakawa, AND J. Johnston. Land-Use/Land-Cover Change from Socio-Economic Drivers and Their Impact on Biodiversity in Nan Province, Thailand. Sustainability. MDPI AG, Basel, Switzerland, 11(3):649, (2019). https://doi.org/10.3390/su11030649

Impact/Purpose:

Water resources support more than 60 million people in the Lower Mekong Basin (LMB) and are important for food security– especially rice production–and economic security. This study aims to quantify current water yield under short- and long-term climate scenarios and assess the potential impacts on rice cultivation. A spatially-explicit watershed hydrology model forecasted water yield, and land evaluation was used delineate suitability classes. Pattern downscaled climate data were specially generated for the LMB. Predicted annual water yields for 2030 and 2060, derived from a drier overall scenario in combination with medium and high greenhouse gas emissions, indicated a reduction of 9-24% from baseline runoff. In contrast, increased seasonality and wetter rainfall scenarios increased annual runoff by 6-26%. Extreme drought decreases suitability of transplanted rice cultivation by 3% and rice production would be reduced by 4.2% and 4%, with and without irrigation projects, relative to baseline. Greatest rice reduction was predicted for Thailand, followed by Lao PDR and Cambodia, and was stable for Vietnam. It was also expected that rice production in the LMB would be sufficient to feed the LMB population in 2030, while rice production in Lao PDR and Cambodia are not expected to be enough for domestic consumption, largely due to steep topography and sandy soil as well as drought. Four adaptation measures to minimize climate impacts (i.e., irrigation system, changing the planting calendar, new rice varieties, and alternative crops) are discussed.

Description:

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 the majority of 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 45, 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.

Record Details:

Record Type: DOCUMENT ( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date: 01/26/2019
Record Last Revised: 10/21/2019
OMB Category: Other
Record ID: 347091