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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.

Immense effort has been devoted to mitigating the negative effect of deforestation, one of the main factors causing global change. However, the effect of reforestation management on food-webs has been rarely studied and no study so far has investigated the effect on predator–prey interactions in forest understories. We studied predator–prey interactions in forest understories using web-building spiders in four forest types: dry evergreen forest representing a natural control and three 20–30-year-old reforestation types, namely secondary naturally regenerating dry evergreen forest, monoculture reforestation dominated by Eucalyptus camaldulensis, and mixture reforestation dominated by Acacia mangium and E. camaldulensis. We collected spiders with their prey and measured the availability of potential prey. We also measured different spider traits (web type, body size) that can be selected by various forest types and consequently affect the predator–prey interactions. The forest type influenced the predator–prey interaction in a complex way, interactively affecting spider density and prey-specific capture efficacy of spider community. The forest type also influenced the web-type and body-size distributions of spiders. Surprisingly, the prey composition caught by spider webs was related only to the web-type but not to the spider mean body size. None of the studied reforestations have yet restored the natural predator–prey interactions, which indicates that conservation management in the tropics should focus on establishing protected areas in pristine regions instead of relying on reforestation. Moreover, the food-web models need to incorporate not only body sizes but also hunting strategies of predators to improve their predictive abilities.

There is a growing concern over change in vegetation dynamics and drought patterns with the increasing climate variability and warming trends in Africa, particularly in the semiarid regions of East Africa. Here, several geospatial techniques and datasets were used to analyze the spatio-temporal vegetation dynamics in response to climate (precipitation and temperature) and drought in Eritrea from 2000 to 2017. A pixel-based trend analysis was performed, and a Pearson correlation coefficient was computed between vegetation indices and climate variables. In addition, vegetation condition index (VCI) and standard precipitation index (SPI) classifications were used to assess drought patterns in the country. The results demonstrated that there was a decreasing NDVI (Normalized Difference Vegetation Index) slope at both annual and seasonal time scales. In the study area, 57.1% of the pixels showed a decreasing annual NDVI trend, while the significance was higher in South-Western Eritrea. In most of the agro-ecological zones, the shrublands and croplands showed decreasing NDVI trends. About 87.16% of the study area had a positive correlation between growing season NDVI and precipitation (39.34%, p < 0.05). The Gash Barka region of the country showed the strongest and most significant correlations between NDVI and precipitation values. The specific drought assessments based on VCI and SPI summarized that Eritrea had been exposed to recurrent droughts of moderate to extreme conditions during the last 18 years. Based on the correlation analysis and drought patterns, this study confirms that low precipitation was mainly attributed to the slowly declining vegetation trends and increased drought conditions in the semi-arid region. Therefore, immediate action is needed to minimize the negative impact of climate variability and increasing aridity in vegetation and ecosystem services.

Tropical forests are vulnerable to climate change including increased temperatures and changes to rainfall variation. Here, we use Thailand as a case study for assessing the impacts of the shared socio-economic pathway and climate scenarios on changes to the distribution and extent of floristic regions. To address this question, we assigned floristic regions based on a structured cluster analysis of modeled species ranges, and evaluated how those regions respond under scenarios of climate change. A total of 201 plant species with sufficient occurrence data obtained from the systematic forest inventory plots across the country and global datasets were chosen for distribution modeling. Environmental variables, including soils, topography and bioclimatic variables were compiled to model both current and 2050 distributions. Potential floristic regions were classified using a clustering algorithm on the pixel-wise species compositions—resulting in 12 floristic regions representative of both current climate species compositions and projected future species assemblages. Five floristic regions are projected to experience little change in their geographic distribution, while the remainder are projected to be substantially displaced spatially. Additionally, two of the identified floristic regions are not well represented in protected areas—with less than 50% of the current geographic distribution in each region in some form of protected status.

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.

Thailand plays a central economic and policy-making role in Southeast Asia. Although climate change adaptation is being mainstreamed in Thailand, a well-organized overview of the impacts of climate change and potential adaptation measures has been unavailable to date. Here we present a comprehensive review of climate-change impact studies that focused on the Thai water sector, based on a literature review of six sub-sectors: riverine hydrology, sediment erosion, coastal erosion, forest hydrology, agricultural hydrology, and urban hydrology. Our review examined the long-term availability of observational data, historical changes, projected changes in key variables, and the availability of economic assessments and their implications for adaptation actions. Although some basic hydrometeorological variables have been well monitored, specific historical changes due to climate change have seldom been detected. Furthermore, although numerous future projections have been proposed, the likely changes due to climate change remain unclear due to a general lack of systematic multi-model and multi-scenario assessments and limited spatiotemporal coverage of the study area. Several gaps in the research were identified, and ten research recommendations are presented. While the information contained herein contributes to state-of-the-art knowledge on the impact of climate change on the water sector in Thailand, it will also benefit other countries on the Indochina Peninsula with a similar climate.

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.

The draft post-2020 Global Biodiversity Framework asks CBD parties to conserve at least 30% of the planet by 2030 ‘through a well-connected and effective system of protected areas … with the focus on areas particularly important for biodiversity’. We use Thailand as a case study for the ability of a densely populated, hyper diverse, tropical, middle-income country to meet this target at a national level. Existing protected areas (PAs) total 24.3% of Thailand’s land area. Adding forest on government land adjacent to existing PAs, plus unprotected areas of Ramsar sites, raises this to 29.5%. To assess the importance for biodiversity, we used modeled distributions of birds and mammals plus, as proxies for other biodiversity components, elevation, bioclimate, forest type, and WWF ecoregion. All modeled species occur in the current PA system but <30% meet representation targets. Expansion of the system increases the proportion of mammals and birds adequately protected and increases the protection for underrepresented bioclimatic zones and forest types. The expanded system remains fragmented and underrepresents key habitats, but opportunities for increasing protection of these are limited. It is also still vulnerable to climate change, although projected impacts are reduced. Additional protection is needed for wetland and coastal habitats, and limestone karsts.

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.

The Emerald Triangle Protected Forests Complex (ETFC) is recognized as a globally outstanding area for transboundary biodiversity conservation. Eld’s deer (Rucervus eldii) include three subspecies; R. eldii siamensis, R. eldii eldii, and R. eldii thamin. This research focused on Siamese Eld’s deer (R. eldii siamense), which is one of the 10 critically endangered vertebrates found in the ETFC. Its habitats are threatened by forest conversion to agriculture and human settlements, as well as by future climate change. The objectives of this article were to predict Siamese Eld’s deer distribution and to determine potential shifts in its suitable habitat as the results of different land use and climate change scenarios in 2030. Occurrence data for Siamese Eld’s deer were gathered from literature and field surveys. The Maximum Entropy (Maxent) and logistic regression models were used to generate suitable habitats. The model that generated the greatest accuracy was selected for distribution mapping. The results showed 142 records of Siamese Eld’s deer. The predicted distribution map generated from the logistic regression model provided greater accuracy (90%) than the Maxent (80%). The predicted habitats of Siamese Eld’s deer covered 6.0% of the ETFC landscape by 2013. They were concentrated in the protected areas of the lowland forests of Cambodia and Lao PDR. The land use change only did not affect the distribution of Siamese Eld's Deer, but climate change would impact the distribution substantially. In addition, the combination of all future land use and climate changes would significantly reduce the current habitat to approximately 2.6% of the ETFC landscape, which is a decline 58.0%. The lowest extent of 2.5% was predicted for the combination of unsustainable land use and climate change scenario. Recommendations on biodiversity conservation cooperation among the three countries, habitat protection and ex-situ conservation were proposed.