Trisurat Yongyut, Shirakawa Hiroaki, Johnston John M
Faculty of Forestry, Kasetsart University, Bangkok 10900, Thailand.
Department of Urban Environment, Graduate School of Environmental Studies, Nagoya University, Nagoya 464-8601, Japan.
Sustainability. 2019 Jan 26;11(3):649. doi: 10.3390/su11030649.
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.
自2000年以来，由于经济结构从林业转型，泰国的森林砍伐率稳步下降。然而，位于泰国北部的难府并未出现这些变化。由于对林产品的高需求和农业综合企业的增加，森林砍伐预计将继续。本文的目的是：（1）根据趋势、基于市场和保护情景预测该省的土地利用变化；（2）量化生物多样性；（3）确定未来森林砍伐风险最大的生物多样性热点地区。本研究使用动态土地利用变化模型（Dyna-CLUE）为三种情景分配汇总的土地需求，并采用FRAGSTATS确定土地利用变化的空间格局。此外，利用InVEST全球生物多样性评估模型框架来估计生物多样性，以相对于原始参考条件下的丰度表示的剩余平均物种丰度（MSA）来衡量。将森林砍伐风险和MSA值相结合，以确定整个景观中风险最大的生物多样性热点地区。结果显示，到2030年，该省大部分森林覆盖将保留在该省西部和东部，这些地区地势崎岖且交通不便，以及保护区内。预计到2030年，在趋势、基于市场和保护情景下，MSA值将分别从2009年的0.41降至0.29、0.35和0.40。此外，低、中、高生物多样性区分别覆盖难府的46%、49%和6%。保护区对维持森林覆盖和更丰富的生物多样性做出了重大贡献。保护剩余森林覆盖和维持生物多样性的重要措施包括对有森林砍伐风险的地区进行巡逻、减少原始森林地区的道路扩建，以及推广激励农民恢复退化生态系统的计划。
