Uncovering the spatio-temporal dynamics of land cover change and fragmentation of mangroves in the Ca Mau peninsula,Vietnam using multi-temporal SPOT satellite imagery (2004–2013)

Mangrove forests provide vital ecosystem services for millions of people living in coastal communities. The expansion of aquaculture production and urbanization have been identified as major causes of mangrove clearance in South-East Asia. The Ca Mau peninsula in Vietnam is leading the country in shrimp aquaculture and at the same time, the region is home to the largest remaining mangrove forests. This study aims to assess the spatial and temporal mangrove forest dynamics in Ngoc Hien district in Ca Mau. Land cover change and fragmentation are quantified using remote sensing imagery consisting of a series of SPOT5 scenes from 2004, 2009 and 2013. The results indicate a high turnover of land cover change, with close to half of the mangrove forests being affected by land cover changes between 2004 and 2014. Net changes in mangrove forest are found to average −0.34% annually, characterized by deforestation between 2004 and 2009 and afforestation of between 2009 and 2013. Fragmentation remains a plausible threat; approximately 35.4% of the mangrove forests in Ngoc Hien are part of interior ‘core’ forests. Forest zones with different regulation regimes play a significant role in shaping the geographic distribution of mangrove forest changes. The insights into recent mangrove forest dynamics facilitate the informed discussion on improving future protection of the mangrove forests abiding anthropogenic pressures.     

中国不同气候带各类型森林的生物量和净第一性生产力

根据<中国植被>的区划,将收集的全国984个样点的森林数据归并到5种气候带类型中,计算了各类型森林以及同一类型森林(分人工林和天然林)的生物量和净第一性生产力,还计算了不同气候带森林各器官的平均生物量和净第一性生产力.结果表明,从寒温带到热带各类型森林的生物量和净第一性生产力逐渐增加,天然林的生物量大于人工林生物量;除热带林外,人工林的净第一性生产力大于天然林净第一性生产力.     

Forest transitions in tropical landscapes: A test in the Atlantic Forest biodiversity hotspot

Analyzing temporal changes in forest amount and configuration is paramount to better design future forest management interventions. Such analyses are especially required for tropical biomes, which are usually subject to dynamic and heterogeneous land uses. Recent studies have suggested that many tropical biomes are passing through the process of “forest transition”, i.e. an overall change from forest loss to forest gain. However, this hypothesis remains scarcely tested, due to the difficulty of obtaining detailed, quantitative historical records of forest cover. In this study, we investigate 38 years of land use change in Brazil's Atlantic Forest, a biodiversity hotspot, from 1976 to 2014, using multitemporal datasets from aerial photographs and satellite images. We classified the historical series to produce land use maps and calculated a set of landscape metrics, including total forest cover, patch size, patch shape and patch connectivity. Our results indicated non-linear changes through time in forest loss and gain and also in landscape structure, which can be classified into two distinct periods. The first period (1976–1996) was marked by expressive forest loss and fragmentation, whereas the second (1996–2014) was characterized by a much less intense forest dynamics, with little deforestation being balanced by forest regeneration. We attribute the forest dynamics observed to temporal changes in socioeconomic factors, such as increasing human settlements and changes in environmental protection policies. Our results show that current forests are a heterogeneous mosaic of forests with different ages, and support the hypothesis that forest transition is occurring in Atlantic Forest landscapes.     

全球森林固碳潜力巨大(英文)

森林是重要的陆地生态系统碳汇。1990–2007年间全球森林平均每年从大气中吸收固定2.4±0.4PgC,但对全球森林未来固碳量的评价多是基于气候因素的过程模型的模拟结果,很少有基于森林调查样地数据评价全球森林固碳潜力的研究。我们收集整理野外调查和已发表的成熟林生物量数据728条,建立全球成熟林生物量数据库。根据成熟林地上生物量碳储量空间插值,得到全球森林地上生物量碳容量,进而评估全球森林地上生物量的固碳潜力。结果显示:(1)全球成熟林地上生物量自赤道向两极整体呈递减趋势,但最大值出现在中纬度区;(2)气温和降水是影响成熟林地上生物量的重要因素;(3)全球森林地上生物量碳容量约为586.2±49.3PgC,其地上生物量固碳潜力为313.4PgC。因此,充分发挥现有森林的碳吸存能力,减少对现有森林碳库的干扰,是土地利用变化之外减缓温室气体排放的又一可选途径。     

Paraguay's Atlantic Forest cover loss – Satellite-based change detection and fragmentation analysis between 2003 and 2013

The subtropical Atlantic Forest is a highly diverse ecosystem in South America and one of the most endangered rain forests in the world. The present study focuses specifically on the Paraguayan part of the tri-national Atlantic Forest. Over the last decades, the Paraguayan Atlantic Forest presented one of the highest deforestation rates in the world, and today, only a small share remains. Hence, forest loss in Paraguay's Atlantic Forest was detected and analysed through remote sensing and GIS methodologies based on Landsat images obtained in 2003 and 2013. The objective of this study was to examine the spatial impact of forest loss in Paraguay's Atlantic Forest over the past decade with a special focus on biodiversity conservation. Classifications results obtained overall accuracies above 83% and revealed that over 6000 km² of forest was cleared during the study period. The forest landscape and its fragmentation level were characterised through a set of landscape metrics, in particular the proximity analysis which support the identification of forest priority areas for nature conservation and potential biological corridors. In summary, the study revealed that deforestation and fragmentation of the Atlantic Forest area continued, but at a slower pace than that in the previous decade. Protected areas were conserved very effectively; however, forest core areas without any protection status require further attention. Intact forest patches and their connectivity are a crucial prerequisite to biodiversity conservation in a highly fragmented forest area. The combination of different remote sensing and GIS methods provides valuable information for sustainable forest management in the region.     

The tropical forest in south east Asia: Monitoring and scenario modeling using synthetic aperture radar data

Tropical forests play a major role in storing large carbon stocks and regulating energy, and water fluxes, but such forest cover is decreasing rapidly in spite of the policy attention on reducing deforestation. High-resolution spatiotemporal maps are unavailable for the forests in majority of the tropical regions in Asia because of the persistent cloud cover and haze cover. Recent advances in radar remote sensing have provided weather-independent data of earth surface, thus offering an opportunity to monitor tropical forest change processes with relatively high spatiotemporal resolutions. In this research, we aim to examine the tropical deforestation process and develop a spatial model to simulate future forest patterns under various scenarios. Riau Province from central Sumatra of Indonesia is selected as the study area; this province has received much attention worldwide because the highest CO₂ emission resulting from tropical deforestation has been recorded. Annual time series PALSAR data from 2007 to 2010 were analyzed for forest mapping and detecting land cover changes. A spatial model was calibrated using the Bayesian method. Modeling parameters were customized for the local subregions that allocate deforestation on the basis of their empirical relationships to physical and socioeconomic drivers. The model generated landscape spatial patterns mirrored the possible locations and extent of deforested areas by 2030 and provided time-series crucial information on forest landscape under various scenarios for future landscape management projects. The results suggested that the current deforestation process is in a critical stage where some subregions may face unprecedented stress on primary forest costing rivers and forest ecosystems by the end of 2020. The perspective views of Riau Province generated by the model highlighted the need for forest/environmental planning controls for the conservation of environmentally sensitive areas.     

Effects of Thinning Intensity on Carbon Stocks and Changes in Larch Forests in China Northeast Forest Region

Thinning represents an important and frequently used silvicultural technique that improves forest wood products and has obvious effects on forest carbon stocks and stock changes. Here, we used the carbon budget model CBM-CFS3 to simulate the effects of thinning on carbon storage and changes in larch forest ecosystems under thirteen thinning scenarios. Simulation results demonstrate that strong thinning greatly reduces the biomass carbon density of larch forests compared to non-thinning forests. The minimum and maximum average biomass carbon density, respectively, were 30.3 tC ha^-1 and 47.8 tC ha^-1, a difference of 58% under set scenarios in the simulated time scale. The dead organic matter (including soil) carbon density increased in all thinned larch forests stands, compared with non-thinning stands, and the pattern of variation was opposite to that found for biomass carbon density. However, the total ecosystem carbon density of larch forests declined with thinning because the increase in dead organic matter carbon is insufficient to offset the loss of biomass carbon caused by thinning. Thus, strong thinning can transform larch forest ecosystems from carbon sinks into carbon sources. Future work should consider the carbon sequestered in wood materials acquired via thinning and their use as substitutes for other construction materials with less favorable lifecycle carbon footprints, such as steel, cement, aluminum and PVC.     

Sensitivity of the backscatter intensity of ALOS/PALSAR to the above-ground biomass and other biophysical parameters of boreal forest in Alaska

We investigated the potential of ALOS/PALSAR for estimating the above-ground biomass (AGB) and other biophysical parameters (tree height, diameter at breast height (DBH), and tree stand density) in the boreal forest of Alaska. In July 2007, forest surveys were conducted along a south–north transect (150°W) to profile the ecotone from boreal forest to tundra in Alaska. In situ parameters were measured in 29 forests by a combination of the Bitterlich angle-count sampling method and the sampled-tree measuring method. These in situ values were compared with the backscatter intensity of ALOS/PALSAR. A strong positive logarithmic correlation was found between the backscatter intensity and the forest AGB, with the correlation being stronger in the HV than in the HH polarization mode. No obvious saturation was found in the sensitivity of the HV mode backscatter intensity to the forest AGB up to 120.7 Mg ha^?1. Similarly, a robust sensitivity was found in the HV backscatter intensity to both tree height and DBH, but weak sensitivity was observed for tree density. The regression curve of HV backscatter intensity to the forest AGB appeared to be intensified by the uneven forest floor, particularly for forests with small AGB. The geographical distribution of the forest AGB was mapped, demonstrating a generally south-rich and north-poor forest AGB gradient.     

Carbon Sequestration Potential of the Forest Ecosystems in the Western Ghats,a Global Biodiversity Hotspot

Global warming with the burgeoning anthropogenic greenhouse gas (GHG) emissions (400 parts per million from 280 ppm CO₂ emissions of pre-industrial era) has altered climate, eroding the ecosystem productivity and sustenance of water, affecting the livelihood of people. The anthropogenic activities such as burning fossil fuel, power generation, agriculture, industry, polluting water bodies and urban activities are responsible for increasing GHG footprint of which 72% constitute CO₂. GHG footprint needs to be in balance with sequestration of carbon to sustain ecosystem functions. Forests are the major carbon sinks (about 45%) that aid in mitigating global warming. The current research focusses on the carbon budgeting through quantification of emissions and sinks in the forest ecosystems and changes in climatic conditions of Western Ghats. This would help in evolving appropriate mitigation strategies toward sustainable management of forests and mitigate impacts of global warming. The land-use land-cover (LULC) dynamics are the prime driver of climate change due to the loss of carbon sequestration potential as well as emissions. The Western Ghats are one among 36 global biodiversity hotspots and forests in this region sequester atmospheric carbon, which aid in moderating the global climate and sustaining water to ensure water and food security in the peninsular India. Assessment of LULC dynamics using temporal remote sensing data shows the decline of evergreen forest by 5% with an increase in agriculture, plantations and built-up area. The interior or intact forests have declined by 10%, and they are now confined to protected areas. The simulation of likely changes indicates that the region will have only 10% evergreen cover and 17% agriculture, 40% plantations and 5% built-up. Quantification of carbon reveals that the WG forest ecosystem holds 1.23 MGg (million gigagrams or Gt) in vegetation and soils. The annual incremental carbon is about 37,507.3 Gg, (or 37.5 million tons, Mt) and the highest in the forests of Karnataka part of WG. Simulation of the likely changes in carbon content indicates the loss of 0.23 MGg (2018–2031) carbon sequestration potential under business as usual scenario. The conservation scenario depicts an increase in carbon sequestration potential of WG forests with the protection. Sequestered carbon in WG is about INR 100 billion ($1.4 billion) at carbon trading of INR 2142 ($30) per tonne. Large-scale land-cover changes leading to deforestation has contributed to an increase in mean temperature by 0.5°C and decline in rainy days, which necessitates evolving prudent landscape management strategies involving all stakeholders for conservation of ecologically fragile WG. This will enhance the ability of forests to sequester atmospheric carbon and climate moderation, with the sustenance of ecosystem goods and services.

     

Spatial patterns of subsistence extraction of forest products – An indirect approach for estimation of forest degradation in dry forest

Successful implementation of a forest based climate change mitigation mechanism such as REDD + depends on robust and available methods for measurement and estimation of forest degradation. Currently available methods are for application in single-hit degradation incidents in high density humid forests. However, it has been suggested that gradual degradation, especially in dry forests, is more widespread and that methods are needed for measuring and estimating associated emissions. We assess the applicability of an indirect remote sensing approach for monitoring forest degradation: infrastructure and other indicators of human activities are mapped and used for spatial prediction of degradation activities. For proxy variables we tested distance to forest edge, distance to roads, and population pressure calculated as the sum of inhabitants per pixel in the Landscan 2010 population raster dataset multiplied by an inverse power distance decay function. Wood extraction incidents were counted in 160 plots in two dry forests in Tanzania with infrastructural entry from one side only. We analyzed the spatial pattern of forest degradation as a function of the chosen proxy variables using zero inflated count models which allows for an excess of zero counts. A jack-knife bootstrap using 10,000 runs was applied to optimize the population distance decay function. We found that the impact of forest degradation is highest near high population concentration, above 1000 individuals. Furthermore, distance to nearest forest edge or road was a significant proxy for estimation of the number of wood extraction incidents (p < 0.001), where degradation incidents decreased with increasing distance to forest edge or road. At 3000 m from the forest edge towards the forest core the probability of wood extraction is 20% and dropping. The population distance decay function was found to have a steep decline indicating a relative small impact on forest degradation. Further, and perhaps larger, studies are needed to be able to recommend a distance decay function for general application in Tanzania. However, the results are useful for understanding spatial patterns of wood harvesting as a function of distance to nearest forest edge or road in dry Miombo woodland areas with average population pressure at 1685 ± 101 persons within a radius of 4000 m from the wood extraction sites.     

How landscapes change: Integration of spatial patterns and human processes in temperate landscapes of southern Chile

A comprehensive understanding of the patterns that occur as human processes transform landscapes is necessary for sustainable development. We provide new evidence on how landscapes change by analysing the spatial patterns of human processes in three forest landscapes in southern Chile at different states of alteration (40%-90% of old-growth forest loss). Three phases of landscape alteration are distinguished. In Phase I (40%-65% of old-growth forest loss), deforestation rates are < 1% yr⁻¹, forests are increasingly degraded, and clearance for pastureland is concentrated on deeper soils. In Phase II (65%-80%), deforestation reaches its maximum rate of 1-1.5% yr⁻¹, with clearance for pastureland being the main human process, creating a landscape dominated by disturbed forest and shrubland. In this phase, clearance for pastureland is the primary driver of change, with pastures expanding onto poorer soils in more spatially aggregated patterns. In Phase III (80%-90%), deforestation rates are again relatively low (<1% yr⁻¹) and forest regrowth is observed on marginal lands. During this phase, clearance is the dominant process and pastureland is the main land cover. As a forest landscape is transformed, the extent and intensity of human processes vary according to the existing state of landscape alteration, resulting in distinctive landscape patterns in each phase. A relationship between spatial patterns of land cover and human-related processes has been identified along the gradient of landscape alteration. This integrative framework can potentially provide insights into the patterns and processes of dynamic landscapes in other areas subjected to intensifying human use.     

Spatiotemporal patterns of tropical deforestation and forest degradation in response to the operation of the Tucuruí hydroelectric dam in the Amazon basin

The planned construction of hundreds of hydroelectric dams in the Amazon basin has the potential to provide invaluable ‘clean’ energy resources for aiding in securing future regional energy needs and continued economic growth. These mega-structures, however, directly and indirectly interfere with natural ecosystem dynamics, and can cause noticeable tree loss. To improve our understanding of how hydroelectric dams affect the surrounding spatiotemporal patterns of forest disturbances, this case study integrated remote sensing spectral mixture analysis, GIS proximity analysis and statistical hypothesis testing to extract and evaluate spatially-explicit patterns of deforestation (clearing of entire forest patch) and forest degradation (reduced tree density) in the 80,000 km² neighborhoods of the Brazil's Tucuruí Dam, the first large-scale hydroelectric project in the Amazon region, over a period of 25 years from 1988 to 2013. Results show that the average rates of deforestation were consistent during the first three time periods 1988–1995 (620 km² per year), 1995–2001 (591 km² per year), and 2001–2008 (660 km² per year). However, such rate dramatically fell to half of historical levels after 2008, possibly reflecting the 2008 global economic crisis and enforcement of the Brazilian Law of Environmental Crimes. The rate of forest degradation was relatively stable from 1988 to 2013 and, on average, was 17.8% of the rate of deforestation. Deforestation and forest degradation were found to follow similar spatial patterns across the dam neighborhoods, upstream reaches or downstream reaches at the distances of 5 km–80 km, suggesting that small and large-scale forest disturbances may have been influencing each other in the vicinity of the dam. We further found that the neighborhoods of the Tucuruí Dam and the upstream region experienced similar degrees of canopy loss. Such loss was mainly attributed to the fast expansion of the Tucuruí town, and the intensive logging activities alongside major roads in the upstream reservoir region. In contrast, a significantly lower level of forest disturbance was discovered in the downstream region.     

Monitoring deforestation with MODIS Active Fires in Neotropical dry forests: An analysis of local-scale assessments in Mexico,Brazil and Bolivia

The detection of vegetation fires using remote sensing has proven useful for highlighting areas undergoing rapid conversion in humid forests, but not in tropical dry forest (TDF). To further understand this relationship, we explored the correlation between MODIS Active Fires and forest cover change at local scales using 3 × 3 km sampling grids in three TDF landscapes in Bolivia; Mexico, and Brazil. Our analysis showed no single overall correlation among sites between the frequency of fires reported by the MODIS Active Fire Mapping product and forest cover change. Also, aggregated patterns of fire occurrence in Brazil and Bolivia did not correspond to areas with high percentage of forest loss, which indicates that the fire/deforestation relationship in TDF is not apparent in a simple fire frequency map. However, statistically significant correlations were found in sampling boxes with 50–60%, 50–70%, 50–95% forest cover at “initial state” of the time series in the Mexican site, Bolivian site and Brazilian site, respectively. Our findings suggest that complex interactions between anthropogenic fire-use, satellite-detected fires, and deforestation in highly fragmented TDF landscapes are difficult to describe at regional scales and might only be possible to analyze using finer resolution sampling grids.     

The use of Landsat imagery to assess large-scale forest cover changes in space and time,minimizing false-positive changes

A new approach, based on the application of multi-spectral remote sensing data of Landsat imagery, is introduced to determine large-scale spatiotemporal variations of forest cover changes quantitatively and with a high degree of precision. The test area covers about 837,330.5 ha of a mountainous region in Central Italy. The approach employs several multi-temporal Landsat acquisitions to account for forest cover changes larger than 0.5 ha for the period from March 2002 to July 2011. In contrast to automated approaches that strongly curtail mapping time, the approach introduced here allowed us to map only the real forest cover change, based on a robust validation and rectification of the detected forest change. Derived high spatial resolution data of forest change estimates indicate that about 5.7% (47,670.5 ha) of the observed forest area was subject to human-induced change between 2002 and 2011. Moreover, the detected forest cover changes, most of which are identifiable as timber harvesting, are considerably larger than those reported in the official statistics and often fall within the perimeter of restricted areas (i.e., national parks and natural reserves).     

Drivers of forest change in Hoa Binh,Vietnam in the context of integration and globalization

This study identified spatial patterns of forest change in Hoa Binh, Vietnam, from 2005 to 2017 by integrating Landsat data and Geographic Information System (GIS) data. A Multiple Logistic Regression (MLR) model was adapted to analyse drivers of three types of forest change, including (i) deforestation and forest degradation, (ii) forest regrowth and (iii) plantation expansion. The results reveal that accessibility and local economic development were determinants of forest cover dynamics during the integration and globalization period and that increased population pressure and poverty were no longer the main factors in forest cover transition. Several key policies in this time period positively affected forest cover change, triggering private sector participation in developing the forest economy by including households and small and medium enterprises in particular. The findings of this study can provide learning points for the implementation of sustainable forest management policies in other Vietnamese provinces or in neighbouring countries. This research has provided an effective tool for visualizing human‐forest ecosystem interaction, and this tool can be applied to subsequent studies to determine causes of forest cover change at the provincial level in Vietnam.     

The contribution of two common shrub species to aboveground and belowground carbon stock in Iberian dehesas

Shrubs play an important role in water-limited agro-silvo-pastoral systems by providing shelter and forage for livestock, for erosion control, to maintain biodiversity, diversifying the landscape, and above all, facilitating the regeneration of trees. Furthermore, the carbon sink capacity of shrubs could also help to mitigate the effects of climate change since they constitute a high proportion of total plant biomass. The contribution of two common extensive native shrub species (Cistus ladanifer L. and Retama sphaerocarpa (L.) Boiss.) to the carbon pool of Iberian dehesas (Mediterranean agro-silvo-pastoral systems) is analyzed through biomass models developed at both individual (biovolume depending) and community level (height and cover depending).The total amount of carbon stored in these shrubs, including above- and belowground biomass, ranges from 1.8 to 11.2 Mg C ha⁻¹ (mean 6.8 Mg C ha⁻¹) for communities of C. ladanifer and from 2.6 to 8.6 Mg C ha⁻¹ (mean 4.5 Mg C ha⁻¹) for R. sphaerocarpa. These quantities account for over 20–30% of the total plant biomass in the system. The potential for carbon sequestration of these shrubs in the studied system ranges 0.10–1.32 Mg C ha⁻¹ year⁻¹ and 0.25–1.25 Mg C ha⁻¹ year⁻¹ for the C. ladanifer and R. sphaerocarpa communities' respectively.     

Preliminary Estimation of Soil Carbon Sequestration of China’s Forests during 1999-2008

The National Forest Inventory (NFI) is an important resource for estimating the national carbon balance (These data were unpublished data, and we could only obtain the data before 2008 through data search by now). Based on the data from sample plots, the literature, and NFI, as well as the relationships between volume, biomass, annual litterfall and soil respiration of different forest types, the net ecosystem production (NEP), changes in forest biomass carbon storage (△Cbiomass) and non-respiratory losses (NR) of China’s forests during 1999-2008 were estimated, and the forest soil carbon sequestration (△Csoil) was assessed according to the carbon balance principle of the forest ecosystem (△Csoil = NEP - NR - △Cbiomass). The results showed that the total NEP, △Cbiomass, NR and △Csoil values for China’s forests were 157.530, 48.704, 31.033 and 77.793 Tg C yr^-1 respectively, and average NEP, △Cbiomass, NR, and △Csoil values were 101.247, 31.303, 19.945 and 49.999 g C m^-2 yr^-1 respectively. There were large spatial differences in forest soil carbon sequestration in different parts of China. The forest soil in Jiangxi, Hunan, Zhejiang, Fujian, Anhui, Shanxi, Shaanxi, Guangxi and Liaoning served as carbon sources and the carbon released was about 25.507 Tg C yr^-1. The other 22 provinces served as carbon sinks and the average carbon sequestration by forest soil came to 103.300 Tg C yr^-1. This research established a method for evaluating soil carbon sequestration by China’s forests based on the NFI, which is a useful supplement to current statistical data-based studies on the forest ecosystem carbon cycle, and can promote comparable studies on forest soil carbon sequestration with consistent research methods at the regional scale.     

Quantifying the variability and allocation patterns of aboveground carbon stocks across plantation forest types,structural attributes and age in sub-tropical coastal region of KwaZulu Natal,South Africa using remote sensing

Quantifying the variability and allocation patterns of aboveground carbon stocks across plantation forests is central in deriving accurate and reliable knowledge and understanding of the extent to which these species contribute to the global carbon cycle and towards minimizing climate change effects. The principal objective of this study was to quantify the variability and allocation patterns of aboveground carbon stocks across Pinus and Eucalyptus plantation forests, tree-structural attributes (i.e. stems, barks, branches and leaves) and age groups, using models developed based on remotely sensed data. The results of this study demonstrate that aboveground carbon stocks significantly (α = 0.05) vary across different plantation forest species types, structural attributes and age. Pinus taeda and Eucalyptus grandis species contained aboveground carbon stocks above 110 t C ha⁻¹, and Eucalyptus dunii had 20 t C ha⁻¹. Across plantation forest tree structural attributes, stems contained the highest aboveground carbon stocks, when compared to barks, branches and leaves. Aboveground carbon stock estimates also varied significantly (α = 0.05) with stand age. Mature plantation forest species (i.e. between 7 and 20 years) contained the highest aboveground carbon stock estimates of approximately 120 t C ha⁻¹, when compared to younger species (i.e. between 3 and 6 years), which had approximately 20 t C ha⁻¹. The map of aboveground carbon stocks showed distinct spatial patterns across the entire study area. The findings of this study are important for understanding the contribution of different plantation forest species, structural attributes and age in the global carbon cycle and possible climate change moderation measures. Also, this study demonstrates that data on vital tree structural attributes, previously difficult to obtain, can now be easily derived from cheap and readily-available satellite data for inventorying carbon stocks variability.     

Land use dynamics and land cover structure change in Thailand (as exemplified by mountainous Nan Province

Changes in the land use pattern and in the land cover structure for the time interval 1995–2012 in Thailand are considered by using, as an example, Nan Province located in the northern mountainous part of the country. Interpretation of satellite images and vector data that were provided by the Land Development Department (Thailand) revealed the main directions of change in the region’s land use: deforestation, expansion of areas under crops, transition from slash and burn cultivation to permanent cultivation, and intensive utilization of agrochemicals. In spite of a decrease in the deforestation rate across Thailand in general, it is shown that for the period under review the proportion of natural forests in Nan Province decreased by nearly one half. On the other hand, the agricultural lands increased for the same period by more than 50%. The highest deforestation rates were recorded during 2009–2012. It was found that the changes in the land use pattern disturbed the existing centuries-old balance of man–natural environment interaction within the framework of the traditional system of slash and burn agriculture which is well adapted to local conditions. The study revealed the chief causes for such changes: an ineffective monitoring of forests; an unclear character of the boundaries separating lands of rural communities and protected territories, and possibilities for sales of commercial products (maize, cassava, etc.) cultivated in illegal fields. It is shown that rapid changes in land cover due to deforestation and plowing of mountainous areas for cultivation of commercial crops led to an intensification of slope processes (landslides and solifluction), an increase in overland runoff, and to an enhanced hazard of heavy floods during the monsoon season. To keep track of deforestation and deal with nature management conflicts requires a continuous monitoring of the land cover dynamics.     

Modelling the integrated effects of land use and climate change scenarios on forest ecosystem aboveground biomass,a case study in Taihe County of China

Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change (ABM/LUCC), an ecosystem process model (PnET-II), and a forest dynamic landscape model (LANDIS-II) to simulate the change of forest aboveground biomass (AGB) which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that: (1) land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County. (2) Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7% (RCP2.6 + land use), 57.2% (RCP4.5 + land use), and 56.9% (RCP8.5 + land use) by 2050, which is in comparison to the results under separate RCPs without land use disturbance. (3) The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function, and developing measures for sustainable forest management.