Basin-wide Impacts of Climate Change on Ecosystem Services in the Lower Mekong Basin.

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 water yield under near- and long-term climate scenarios and assess the potential impacts on rice cultivation. The InVEST model (Integrated Valuation of Ecosystem Services and Tradeoffs) forecasted water yield, and land evaluation was used to 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 (average 1986-2005) runoff. In contrast, increased seasonality and wetter rainfall scenarios increased annual runoff by 6-26%. Extreme drought decreased 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. Rice production in the LMB appears sufficient to feed the LMB population in 2030, while rice production in Lao PDR and Cambodia are not expected to be sufficient for domestic consumption, largely due to steep topography and sandy soils as well as drought. Four adaptation measures to minimize climate impacts (i.e., irrigation, changing the planting calendar, new rice varieties, and alternative crops) are discussed.

Integrating land use and climate change scenarios and models into assessment of forested watershed services in Southern Thailand.

The Thadee watershed, covering 112km(2), is the main source of water for agriculture and household consumption in the Nakhon Srithammarat Province in Southern Thailand. As the natural forests upstream have been largely degraded and transformed to fruit tree and rubber plantations, problems with landslides and flooding have resulted. This research attempts to predict how further land-use/land-cover changes during 2009-2020 and conceivable changes in rainfall may influence the future levels of water yield and sediment load in the Thadee River. Three different land use scenarios (trend, development and conservation) were defined in collaboration with the local stakeholders, and three different rainfall scenarios (average rainfall, climate change and extreme wet) were determined on the basis of literature sources. Spatially explicit empirical modelling was employed to allocate future land demands and to assess the contributions of land use and rainfall changes, considering both their separate and combined effects. The results suggest that substantial land use changes may occur from a large expansion of rubber plantations in the upper sub-watersheds, especially under the development land use scenario. The reduction of the current annual rainfall by approximately 30% would decrease the predicted water yields by 38% from 2009. According to the extreme rainfall scenario (an increase of 36% with respect to current rainfall), an amplification of 50% of the current runoff could result. Sensitivity analyses showed that the predicted soil loss is more responsive to changes in rainfall than to the compared land use scenarios alone. However, very high sediment load and runoff levels were predicted on the basis of combined intensified land use and extreme rainfall scenarios. Three conservation activities-protection, reforestation and a mixed-cropping system-are proposed to maintain the functional watershed services of the Thadee watershed region.

Vulnerability to climate change of species in protected areas in Thailand.

Although 23% of Thailand's land is in protected areas, these are vulnerable to climate change. We used spatial distribution modelling for 866 vertebrate and 591 plant species to understand potential climate change impacts on species in protected areas. Most mammals, birds, and plants were projected to decline by 2070, but most amphibians and reptiles were projected to increase. By 2070 under RCP8.5, 54% of modeled species will be threatened and 11 nationally extinct. However, SDMs are sensitive to truncation of the climate space currently occupied by habitat loss and hunting, and apparent truncation by data limitations. In Thailand, lowland forest clearance has biased records for forest-dependent species to cooler uplands (> 250 m a.s.l.) and hunting has confined larger vertebrates to well-protected areas. In contrast, available data is biased towards lowland non-forest taxa for amphibians and reptiles. Niche truncation may therefore have resulted in overestimation of vulnerability for some mammal and plant species, while data limitations have likely led to underestimation of the threat to forest-dependent amphibians and reptiles. In view of the certainty of climate change but the many uncertainties regarding biological responses, we recommend regular, long-term monitoring of species and communities to detect early signals of climate change impacts.

Projecting land-use change and its consequences for biodiversity in northern Thailand.

Rapid deforestation has occurred in northern Thailand over the last few decades and it is expected to continue. The government has implemented conservation policies aimed at maintaining forest cover of 50% or more and promoting agribusiness, forestry, and tourism development in the region. The goal of this paper was to analyze the likely effects of various directions of development on the region. Specific objectives were (1) to forecast land-use change and land-use patterns across the region based on three scenarios, (2) to analyze the consequences for biodiversity, and (3) to identify areas most susceptible to future deforestation and high biodiversity loss. The study combined a dynamic land-use change model (Dyna-CLUE) with a model for biodiversity assessment (GLOBIO3). The Dyna-CLUE model was used to determine the spatial patterns of land-use change for the three scenarios. The methodology developed for the Global Biodiversity Assessment Model framework (GLOBIO 3) was used to estimate biodiversity intactness expressed as the remaining relative mean species abundance (MSA) of the original species relative to their abundance in the primary vegetation. The results revealed that forest cover in 2050 would mainly persist in the west and upper north of the region, which is rugged and not easily accessible. In contrast, the highest deforestation was expected to occur in the lower north. MSA values decreased from 0.52 in 2002 to 0.45, 0.46, and 0.48, respectively, for the three scenarios in 2050. In addition, the estimated area with a high threat to biodiversity (an MSA decrease >0.5) derived from the simulated land-use maps in 2050 was approximately 2.8% of the region for the trend scenario. In contrast, the high-threat areas covered 1.6 and 0.3% of the region for the integrated-management and conservation-oriented scenarios, respectively. Based on the model outcomes, conservation measures were recommended to minimize the impacts of deforestation on biodiversity. The model results indicated that only establishing a fixed percentage of forest was not efficient in conserving biodiversity. Measures aimed at the conservation of locations with high biodiversity values, limited fragmentation, and careful consideration of road expansion in pristine forest areas may be more efficient to achieve biodiversity conservation.

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

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.

Applying gap analysis and a comparison index to evaluate protected areas in Thailand.

Protected areas in Thailand were first established 40 years ago. The total area of existing protected areas covers 18.2% of the country's land area and the Class 1 Watershed, another form of protection, encompasses 18.1%. The government of Thailand intends to increase protected area systems to 25% of the country in 2006 and 30% in 2016. There are always questions arising about how much is enough protected areas to effectively protect biodiversity. The objective of this article is to assess the representation of ecosystems in the protected area network. This article also recommends which underrepresented ecosystems should be added to fill the gaps in representativeness. The research applies a gap analysis and a comparison index to assess the representation of ecosystems within the protected area network. The spatial analyses were applied to measure three aspects of representativeness, namely forest type, altitude, and natural land system. The analyses indicate that the existing protected area system covers 24.4% of the country's land area, nearly meeting the 25% target proposed by the National Forest Policy; and 83.8% of these areas are under forest cover. Most protected areas are situated in high altitudes, where biological diversity is less than in lowlands. Mangrove forest and riparian floodplain are extremely underrepresented in the existing system. Peat swamp forest, dry dipterocarp forest, and beach forest are relatively well represented. In addition, these five ecosystems are threatened by human pressures and natural disasters; therefore, they should be targeted as high priorities for the selection of new reserves. Future research should incorporate aquatic and marine ecosystems, as well as animal distributions, which were not included in this research due to data unavailabilities.