Temporal patterns of deforestation and fragmentation in lowland Bolivia: implications for climate change

The lowlands of eastern and northeastern Bolivia are characterized by a transition between the humid evergreen forests of the Amazon Basin and the deciduous thorn-scrub vegetation of the Gran Chaco. Within this landscape lies one of the world’s best preserved areas: the ecoregion known as the Chiquitano dry forest, where deforestation patterns over a 30 year period were analyzed. Results indicate that the area of the natural cover was reduced from 97.21 % before 1976 to 82.10 % in 2008, causing significant change in the landscape, especially in the spatial configuration of forest cover. The density of forest fragments increased from 0.073 patches per 100 ha before 1976 to 0.509 in 2008, with a mean distance between patches of 151 and 210 m over the same period, leading to a considerable reduction in the fragment sizes, from 1,204 ha before 1976 to a mere 54 in 2008. This pattern, observed in forests, does not occur in the savannas because, on one hand the savanna area is much lower compared to that of forests, and on the other because the deforestation process tended to be concentrated within forested areas. Based on the observed patterns, it is possible that in the future the natural landscapes will be substituted principally by anthropic landscapes, if there is no change in the economic and land distribution policies. If this process continues, it will stimulate the expansion of mechanized agriculture and the colonization of new areas, which will lead to further deforestation and landscape fragmentation.     

Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India – analysis from remote sensing datasets

Summary Leaf phenology describes the seasonal cycle of leaf functioning and is essential for understanding the interactions between the biosphere, the climate and the atmosphere. In this study, we characterized the spatial patterns in phenological variations in eight contrasting forest types in an Indian region using coarse resolution NOAA AVHRR satellite data. The onset, offset and growing season length for different forest types has been estimated using normalized difference vegetation index (NDVI). Further, the relationship between NDVI and climatic parameters has been assessed to determine which climatic variable (temperature or precipitation) best explain variation in NDVI. In addition, we also assessed how quickly and over what time periods does NDVI respond to different precipitation events. Our results suggested strong spatial variability in NDVI metrics for different forest types. Among the eight forest types, tropical dry deciduous forests showed lowest values for summed NDVI (SNDVI), averaged NDVI (ANDVI) and integrated NDVI (I-NDVI), while the tropical wet evergreen forests of Arunachal Pradesh had highest values. Within the different evergreen forest types, SNDVI, ANDVI and INDVI were highest for tropical wet evergreen forests, followed by tropical evergreen forests, tropical semi-evergreen forests and were least for tropical dry evergreen forests. Differences in the amplitude of NDVI were quite distinct for evergreen forests compared to deciduous ones and mixed deciduous forests. Although, all the evergreen forests studied had a similar growing season length of 270 days, the onset and offset dates were quite different. Response of vegetative greenness to climatic variability appeared to vary with vegetation characteristics and forest types. Linear correlations between mean monthly NDVI and temperature were found to yield negative relationships in contrast to precipitation, which showed a significant positive response to vegetation greenness. The correlations improved much for different forest types when the log of cumulative rainfall was correlated against mean monthly NDVI. Of the eight forest types, the NDVI for six forest types was positively correlated with the logarithm of cumulative rainfall that was summed for 3–4 months. Overall, this study identifies precipitation as a major control for vegetation greenness in tropical forests, more so than temperature.     

Evaluating the influence of different vegetation biomes on the global climate

The participation of different vegetation types within the physical climate system is investigated using a coupled atmosphere-biosphere model, CCM3-IBIS. We analyze the effects that six different vegetation biomes (tropical, boreal, and temperate forests, savanna, grassland and steppe, and shrubland/tundra) have on the climate through their role in modulating the biophysical exchanges of energy, water, and momentum between the land-surface and the atmosphere. Using CCM3-IBIS we completely remove the vegetation cover of a particular biome and compare it to a control simulation where the biome is present, thereby isolating the climatic effects of each biome. Results from the tropical and boreal forest removal simulations are in agreement with previous studies while the other simulations provide new evidence as to their contribution in forcing the climate. Removal of the temperate forest vegetation exhibits behavior characteristic of both the tropical and boreal simulations with cooling during winter and spring due to an increase in the surface albedo and warming during the summer caused by a reduction in latent cooling. Removal of the savanna vegetation exhibits behavior much like the tropical forest simulation while removal of the grassland and steppe vegetation has the largest effect over the central United States with warming and drying of the atmosphere in summer. The largest climatic effect of shrubland and tundra vegetation removal occurs in DJF in Australia and central Siberia and is due to reduced latent cooling and enhanced cold air advection, respectively. Our results show that removal of the boreal forest yields the largest temperature signal globally when either including or excluding the areas of forest removal. Globally, precipitation is most affected by removal of the savanna vegetation when including the areas of vegetation removal, while removal of the tropical forest most influences the global precipitation excluding the areas of vegetation removal.     

Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets

This paper addresses the use of radar remote sensing to map forest above-ground biomass, and discusses the use of biomass maps to test a dynamic vegetation model that identifies carbon sources and sinks and predicts their variation over time. For current radar satellite data, only the biomass of young/sparse forests or regrowth after disturbances can be recovered. An example from central Siberia illustrates that biomass can be measured by radar at a continental scale, and that a significant proportion of the Siberian forests have biomass values less than 50 tonnes/ha. Comparison between the radar map and calculations by the Sheffield Dynamic Global Vegetation Model (SDGVM) indicates that the model considerably overestimates biomass; under-representation of managed areas, disturbed areas and areas of low site quality in the model are suggested reasons for this effect. A case study carried out at the Büdingen plantation forest in Germany supports the argument that inadequate representations of site quality and forest management may cause model overestimates of biomass. Comparison of the calculated biomass of stands planted after 1990 with biomass estimates by radar allows identification of forest stands where the growth conditions assumed by the model are not valid. This allows a quality check on model calculations of carbon fluxes: only calculations for stands where there is good agreement between the data and the model predictions should be accepted. Although the paper only uses the SDGVM model, similar effects are likely in other dynamic vegetation models, and the results show that model calculations attempting to quantify the role of forests as carbon sources or sinks could be qualified and potentially improved by exploiting remotely sensed measurements of biomass.     

Relating Radar Remote Sensing of Biomass to Modelling of Forest Carbon Budgets

This paper addresses the use of radar remote sensing to map forest above-ground biomass, and discusses the use of biomass maps to test a dynamic vegetation model that identifies carbon sources and sinks and predicts their variation over time. For current radar satellite data, only the biomass of young/sparse forests or regrowth after disturbances can be recovered. An example from central Siberia illustrates that biomass can be measured by radar at a continental scale, and that a significant proportion of the Siberian forests have biomass values less than 50 tonnes/ha. Comparison between the radar map and calculations by the Sheffield Dynamic Global Vegetation Model (SDGVM) indicates that the model considerably overestimates biomass; under-representation of managed areas, disturbed areas and areas of low site quality in the model are suggested reasons for this effect. A case study carried out at the Büdingen plantation forest in Germany supports the argument that inadequate representations of site quality and forest management may cause model overestimates of biomass. Comparison of the calculated biomass of stands planted after 1990 with biomass estimates by radar allows identification of forest stands where the growth conditions assumed by the model are not valid. This allows a quality check on model calculations of carbon fluxes: only calculations for stands where there is good agreement between the data and the model predictions should be accepted. Although the paper only uses the SDGVM model, similar effects are likely in other dynamic vegetation models, and the results show that model calculations attempting to quantify the role of forests as carbon sources or sinks could be qualified and potentially improved by exploiting remotely sensed measurements of biomass.     

气候与植被覆盖变化对中国西南亚高山区流域碳水循环的影响模拟

正确认识气候变化对流域森林植被和水文的影响对于林业经营管理与流域生态修复具有重要意义。为了揭示气候与植被覆盖变化对西南亚高山区流域碳水循环过程的影响,用生物物理/动态植被模型SSiB4/TRIFFID（Simplified Simple Biosphere model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics model）与流域地形指数水文模型TOPMODEL（Topographic Index Model）的耦合模型（以下记为SSiB4T/TRIFFID）模拟了不同气候情景下西南亚高山区的梭磨河流域植被演替和碳水循环过程。结果表明,所有试验流域植被经历了从C3到苔原灌木最后到森林的变化;控制试验流域蒸散在流域植被主要为苔原灌木时达到最大而径流深最小;增温5 ℃并且增雨40%试验[记为T+5, (1+40%) P试验]流域蒸散在流域为森林覆盖时达到最大而径流深最小。随着温度增加,森林蒸腾、冠层截留蒸发和蒸散的增加幅度明显大于草和苔原灌木,导致森林从控制试验的增加径流量变为减小径流量。从控制试验到T+5, (1+40%) P试验,温度增加使森林净初级生产力有所增加,但对草和苔原灌木的净初级生产力影响很小;植被水分利用效率随温度增加明显减小。西南山区随着海拔高度降低（温度升高）,森林从增加径流量转变为减少径流量,植被水分利用效率也相应明显减小。西南山区气候的垂直地带性对森林—径流关系和水分利用效率的空间变化有着重要的影响。     

National assessments of forest fragmentation in the US

Because of the linkages among ecological pattern, function and process, policy makers and land managers have increasingly sought measures of landscape pattern that may be used to quantify and monitor changes in forest cover associated with forest fragmentation at national or multinational scales. In this paper, I provide a brief overview of the processes and initiatives driving interest in national assessments of forest fragmentation (e.g., the Montréal Process) and review the results of recent assessments of landscape pattern (and by proxy, fragmentation) conducted at the US national level. Despite widespread recognition that spatial pattern and continuity of forests is important for biodiversity conservation, many international processes and conventions as well as most national forest assessments still focus solely on the extent of forest loss without concern for its spatial pattern, likely due to greater uncertainty over the ecological effects of fragmentation, questions associated with indicator selection, the ill-defined nature of “fragmentation” as an indicator, and confusion over scale and data issues. I thus conclude with a discussion of how experiences gained from recent US assessments may provide insights useful for addressing most or all of these issues when conducting similar assessments in other countries or globally.     

Using Remote Sensing to Assess Russian Forest Fire Carbon Emissions

Russian boreal forests are subject to frequent wildfires. The resulting combustion of large amounts of biomass not only transforms forest vegetation, but it also creates significant carbon emissions that total, according to some authors, from 35–94 Mt C per year. These carbon emissions from forest fires should be considered an important part of the forest ecosystem carbon balance and a significant influence on atmospheric trace gases. In this paper we discuss a new method to assess forest fire damage. This method is based on using multi-spectral high-resolution satellite images, large-scale aerial photography, and declassified images obtained from the space-borne national security systems. A normalized difference vegetation index (NDVI) difference image was produced from pre- and post-fire satellite images from SPOT/HRVIR and RESURS-O/MSU-E images. A close relationship was found between values of the NDVI difference image and forest damage level. High-resolution satellite data and large-scale aerial-photos were used to calibrate the NDVI-derived forest damage map. The method was used for mapping of forest fire extent and damage and for estimating carbon emissions from burned forest areas.     

Mesoscale moisture transport effects on forest edges in a fragmented landscape in Amazonia

This work explores the dry season micrometeorology of fragmented forests in Amazonia. Numerical simulations with a coupled atmosphere-vegetation model show that mesoscale moisture transport leads to a significant drying and vegetation stress at the forest edges. Increased evaporation cannot fully compensate for the drying. Typical convective precipitation events that occur in the dry season have a localized impact and do not affect the drying trend in the long term. Availability of soil moisture can partially mitigate the drying effect and consequent vegetation stress. Edge effects can dominate the vegetation dynamics and fire susceptibility of forest fragments as a whole. Hence, understanding the dynamics and drivers of edge effects is crucial for understanding the ecology and future of tropical forests in a changing climate.     

The role of soybean production as an underlying driver of deforestation in the South American Chaco

South America’s tropical dry forests and savannas are under increasing pressure from agricultural expansion. Cattle ranching and soybean production both drive these forest losses, but their relative importance remains unclear. Also unclear is how soybean expansion elsewhere affects deforestation via pushing cattle ranching to deforestation frontiers. To assess these questions, we focused on the Chaco, a 110 million ha ecoregion extending into Argentina, Bolivia, and Paraguay, with about 8 million ha of deforestation in 2000–2012. We used panel regressions at the district level to quantify the role of soybean expansion in driving these forest losses using a wide range of environmental and socio-economic control variables. Our models suggest that soybean production was a direct driver of deforestation in the Argentine Chaco only (0.08 ha new soybean area per ha forest lost), whereas cattle ranching was significantly associated with deforestation in all three countries (0.02 additional cattle per hectare forest loss). However, our models also suggested Argentine soybean cultivation may indirectly be linked to deforestation in the Bolivian and Paraguayan Chaco. We furthermore found substantial time-delayed effects in the relationship of soybean expansion in Argentina and Paraguay (i.e., soybean expansion in one year resulted in deforestation several years later) and deforestation in the Chaco, further suggesting that possible displacement effects within and between Chaco countries may at least partly drive forest loss. Altogether, our study showed that deforestation in the Chaco appears to be mainly driven by the globally surging demand for soybean, although regionally other proximate drivers are sometimes important. Steering agricultural production in the Chaco and other tropical dry forests onto sustainable pathways will thus require policies that consider these scale effects and that account for the regional variation in deforestation drivers within and across countries.     

Effects of Climate Change on Carbon Storage in Boreal Forests of China: A Local Perspective

The BIOME3 model was used to simulate the distribution patterns and carbon storage of the horizontal, zonal boreal forests in northeast and northwest China using a mapping system for vegetation patterns combined with carbon density estimates from vegetation and soils. The BIOME3 prediction is in reasonable good agreement with the potential distribution of Chinese boreal forests. The effects of changing atmospheric CO₂ concentration had a nonlinear effect on boreal forest distribution, with 3.5–10.8% reduced areas for both increasing and decreasing CO₂. In contrast, the increased climate together with and without changing CO₂ concentration showed dramatic changes in geographic patterns, with 70% reduction in area and disappearance of almost boreal forests in northeast China. The baseline carbon storage in boreal forests of China is 4.60 PgC (median estimate) based on the vegetation area of actual boreal forest distribution. If taking the large area of agricultural crops into account, the median value of potential carbon storage is 6.92 PgC. The increasing (340–500 ppmv) and decreasing CO₂ concentration (340–200 ppmv) led to decrease of carbon storage, 0.33 PgC and 1.01 PgC respectively compared to BIOME3 potential prediction under present climate and CO₂ conditions. Both climate change alone and climate change with CO₂ enrichment (340–500 ppmv) reduced largely the carbon stored in vegetation and soils by ca. 6.5 PgC. The effect of climate change is more significant than the direct physiological effect of CO₂ concentration on the boreal forests of China, showing a large reduction in both distribution area and carbon storage.     

西北地区MODIS-NDVI指数饱和问题分析

为了了解西北地区MODIS-NDVI和MODIS-EVI两种植被指数的特点,本文利用美国NASA LP DAAC(Land Process Distributed Active Archive Center)2004年1~12月的250 m分辨率16天植被指数合成的MOD13 Q1数据集,对西北地区不同类型植被NDVI和EVI的特征进行分析,并对西北地区MODIS-NDVI饱和问题进行了初步研究。结果表明:NDVI和EVI对干旱—半干旱气候区植被覆盖度不高的植被类型描述能力相似,月际变化趋势一致。西北地区各种植被类型NDVI比EVI高,NDVI与EVI的差异总体上呈现从半荒漠、草原、农区到林区,随NDVI值的增加而增大的规律。对植被度覆盖度高的阔叶林和针叶林,在植被生长旺盛期,NDVI总在0.8附近波动,NDVI随植被的生长增加的很小,一直维持在一个高且平的范围内,不再能看出植被生长变化的现象,即饱和现象严重;而EVI表现良好,随着植被的生长而增加,能明显地反映出植被生长的季节变化。西北高寒草甸和陕西关中农业区NDVI也出现有不同程度的饱和,饱和时间因植被的不同从1~2月不等。0.8可作为NDVI饱和的阈值。NDVI饱和问题对卫星监测植被的研究和应用会产生误差,EVI能较好地解决NDVI的饱和问题。     

Assessing potential impacts of climatic change on subalpine forests on the eastern Tibetan Plateau

Forest gap models have been used widely in the study of forest dynamics, including predicting long-term succession patterns and assessing the potential impacts of climate change on forest structure and composition. However, little effort is devoted to predict forest dynamics in the high elevation areas, although they have the sensitive response to global climate change. In the present study, based on a modified height-diameter function, we developed a new version (FAREAST-GFSM) of the forest patch model, FAREAST for simulating the changes of subalpine forests. The observed data from the Gongga Mt. Alpine Station were also used to test model precision. With the improved performance of FAREAST-GFSM, we explored the impact of three warming scenarios on subalpine forest on the eastern Tibetan plateau within a 100-year period. The study result indicates that the effects of climate change were evident on subalpine forests in the high elevation areas. The response of different species to the warming climate might eventually transform the subalpine Abies fabric forest into Betula utilis forest similar to that which is now widely distributed in the eastern Tibetan Plateau mountainous areas with the relatively lower elevation. Subalpine forests could move to higher and colder areas, which are currently tundra.     

2000-2013年新疆植被覆盖变化多尺度遥感分析

基于中等分辨率成像光谱仪(MODIS)8 d 500 m分辨率地表反射率数据生成归一化植被指数(NDVI)时间序列,利用线性回归、转折点检测和Mann-Kendall趋势分析方法,分析2000—2013年新疆地区植被覆盖时空变化格局,并结合Landsat数据分析典型区域植被变化。研究结果表明：近14 a来,新疆地区植被覆盖整体呈波动型上升的趋势,植被改善区面积占全区的34.02%,恶劣区的占3.20%,其中2000—2003年植被明显增长、2003—2009年的波动下降及2009—2013年的逐渐回升,植被增长显著的区域主要分布在准噶尔盆地南部和塔里木盆地北部绿洲;大多数植被类型NDVI呈增长趋势,其中增长率最高的是作物、开放灌丛和混交林,6种主要植被类型常绿针叶林、混交林、开放灌丛、多树草原、草原、作物呈现出相似的NDVI变化趋势;在植被覆盖变化显著的4个典型区,NDVI变化受土地覆盖类型变化的影响,荒漠、草地被开垦成农田导致NDVI增加,城市建成区扩张导致NDVI降低。     

Development of the IAP Dynamic Global Vegetation Model

ABSTRACT The lAP Dynamic Global Vegetation Model （IAP-DGVM） has been developed to simulate the distribution and structure of global vegetation within the framework of Earth System Models. It incorporates our group＇s recent developments of major model components such as the shrub sub-model, establishment and competition parameterization schemes, and a process-based fire parameterization of intermediate complexity. The model has 12 plant functional types, including seven tree, two shrub, and three grass types, plus bare soil. Different PFTs are allowed to coexist within a grid cell, and their state variables are updated by various governing equations describing vegetation processes from fine-scale biogeophysics and biogeochemistry, to individual and population dynamics, to large-scale biogeography. Environmental disturbance due to fire not only affects regional vegetation competition, but also influences atmospheric chemistry and aerosol emissions. Simulations under observed atmospheric conditions showed that the model can correctly reproduce the global distribution of trees, shrubs, grasses, and bare soil. The simulated global dominant vegetation types reproduce the transition from forest to grassland （savanna） in the tropical region, and from forest to shrubland in the boreal region, but overestimate the region of temperate forest.     

Evaluation of coupled ocean–atmosphere simulations of the mid-Holocene using palaeovegetation data from the northern hemisphere extratropics

We have used the BIOME4 biogeography–biochemistry model and comparison with palaeovegetation data to evaluate the response of six ocean–atmosphere general circulation models to mid-Holocene changes in orbital forcing in the mid- to high-latitudes of the northern hemisphere. All the models produce: (a) a northward shift of the northern limit of boreal forest, in response to simulated summer warming in high-latitudes. The northward shift is markedly asymmetric, with larger shifts in Eurasia than in North America; (b) an expansion of xerophytic vegetation in mid-continental North America and Eurasia, in response to increased temperatures during the growing season; (c) a northward expansion of temperate forests in eastern North America, in response to simulated winter warming. The northward shift of the northern limit of boreal forest and the northward expansion of temperate forests in North America are supported by palaeovegetation data. The expansion of xerophytic vegetation in mid-continental North America is consistent with palaeodata, although the extent may be over-estimated. The simulated expansion of xerophytic vegetation in Eurasia is not supported by the data. Analysis of an asynchronous coupling of one model to an equilibrium-vegetation model suggests vegetation feedback exacerbates this mid-continental drying and produces conditions more unlike the observations. Not all features of the simulations are robust: some models produce winter warming over Europe while others produce winter cooling. As a result, some models show a northward shift of temperate forests (consistent with, though less marked than, the expansion shown by data) and others produce a reduction in temperate forests. Elucidation of the cause of such differences is a focus of the current phase of the Palaeoclimate Modelling Intercomparison Project.     

Assessing impacts of climate change on forests: The state of biological modeling

Models that address the impacts of climate change on forests are reviewed at four levels of biological organization: global, regional or landscape, community, and tree. The models are compared for their ability to assess changes in fluxes of biogenic greenhouse gases, land use, patterns of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models have been used to consider more impacts than the other models. The development of landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research needing additional effort are identified: (1) linking socioeconomic and ecologic models; (2) interfacing forest models at different scales; (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes; and (4) relating information from different scales.The U.S. Government right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.Managed by Martin Marietta Energy Systems, Inc., for the U.S. Department of Energy under contract DE-AC05-84OR21400.     

Legacies of 19th century land use shape contemporary forest cover

Historic land use can exert strong land-use legacies, i.e., long-lasting effects on ecosystems, but the importance of land-use legacies, alongside other factors, for subsequent forest-cover change is unclear. If past land use affects rates of forest disturbance and afforestation then this may constrain land use planning and land management options, and legacies of current land management may constrain future land use. Our goal was to assess if and how much land-use legacies affect contemporary forest disturbance, and the abundance of different forest types in the Carpathian region in Eastern Europe (265,000 km², encompassing parts of Poland, Slovakia, Ukraine, Romania, Hungary, and Czech Republic). We modeled contemporary forest disturbance (based on satellite image analysis from 1985 to 2010) as a function of historic land use (based on digitized topographic maps from 1860 and 1960). Contemporary forest disturbance was strongly related to historic land use even when controlling for environmental, accessibility and socio-political variation. Across the Carpathian region, the odds of forest disturbance were about 50% higher in areas that were not forested in 1860 (new forests) compared to areas that were forested then (old forests). The forest disturbance in new forests was particularly high in Poland (88% higher odds), Slovakia (69%) and Romania (67%) and persisted across the entire range of environmental, accessibility and socio-political variation. Reasons for the observed legacy effects may include extensive plantations outside forest ranges, predominantly spruce, poplar, and black locust, which are prone to natural disturbances. Furthermore, as plantations reach harvestable age of about 70 years for pulp and 120 year for saw-timber production, these are likely to be clear-cut, producing the observed legacy effects. Across the Carpathians, forest types shifted towards less coniferous cover in 2010 compared to the 1860s and 1960s likely due to extensive historic conifer harvest, and to recent natural disturbance events and clear-cuts of forest plantations. Our results underscore the importance of land-use legacies, and show that past land uses can greatly affect subsequent forest disturbance for centuries. Given rapid land use changes worldwide, it is important to understand how past legacies affect current management and what the impact of current land management decisions may be for future land use.     

International wood trade and forest change: A global analysis

Throughout history, humans have transformed natural forests into agricultural land, settlement areas and managed forests. Studies on the dynamics of forest change are one of the mainstays in land change science. The forest transition theory offers a powerful tool to analyze changes in human interference with forests. At the national level, a range of factors have been found to influence a country's forest change. The role of international wood product trade has, however, rarely been studied based on empirical data. We offer a global assessment of how this trade helps shape observed forest change, by relating forest stock change to net trade of wood products for the period 1997-2007 and by localizing the origin of wood consumed in a given nation. For many nations, traded wood products have a relevant impact on the course of ongoing forest transitions. We develop a general typology of how wood product trade can influence forest change and place various nations within this framework. We find that many wealthy nations with returning forests seem to accelerate this return by importing wood products. These imports appear to be provided by two main types of wood exporters: (a) by wealthy countries with low population densities and stable forests and (b) by relatively poor countries with declining forests, employing increasing population and welfare levels. We discuss these findings in the light of general theories on land use transitions and forest change and conclude by highlighting implications for national forest policies and global environmental governance, aiming at reducing negative impacts of wood products and enhancing the positive role they can play in replacing more fossil fuel intensive products.     

Responses of Grassland and Forest to Temperature and Precipitation Changes in Northeast China

Using the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth, we explored the characteristics and differences in the response to drought of five vegetation biomes in Northeast China, including typical steppe, desert steppe, meadow steppe, deciduous coniferous forest and deciduous broad-leaved forest during the period 1982-2009. The results indicate that growing season precipitation may be the primary vegetation growth-limiting factor in grasslands. More than 70% of the temporal variations in NDVI can be explained by the amount of precipitation during the growing season in typical and desert steppes. During the same period, the mean temperature in the growing season could explain nearly 43% of the variations in the mean growing season NDVI and is therefore a dominant growth-limiting factor for forest ecosystems. Therefore, the NDVI trends differ largely due to differences in the vegetation growth-limiting factors of the different vegetation biomes. The NDVI responses to droughts vary in magnitude and direction and depend on the drought-affected areas of the five vegetation types. Specifically, the changes in NDVI are consistent with the variations in precipitation for grassland ecosystems. A lack of precipitation resulted in decreases in NDVI, thereby reducing vegetation growth in these regions. Conversely, increasing precipitation decreased the NDVI of forest ecosystems. The results also suggest that grasslands under arid and semi-arid environments may be more sensitive to drought than forests under humid environments. Among grassland ecosystems, desert steppe was most sensitive to drought, followed by typical steppe; meadow steppe was the least sensitive.