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.     

Ecological Implications of Changes in Drought Patterns: Shifts in Forest Composition in Panama

CO₂ concentration is increasing, temperature is likely to rise, and precipitation patterns might change. Of these potential climatic shifts, it is precipitation that will have the most impact on tropical forests, and seasonal patterns of rainfall and drought will probably be more important than the total quantity of precipitation. Many tree species are limited in distribution by their inability to survive drought. In a 50 ha forest plot at Barro Colorado Island in Panama (BCI), nearly all tree and shrub species associated with moist microhabitats are declining in abundance due to a decline in rainfall and lengthening dry seasons. This information forms the basis for a simple, general prediction: drying trends can rapidly remove drought-sensitive species from a forest. If the drying trend continues at BCI, the invasion of drought-tolerant species would be anticipated, but computer models predict that it could take 500 or more years for tree species to invade and become established. Predicting climate-induced changes in tropical forest also requires geographic information on tree distribution relative to precipitation patterns. In central Panama, species with the most restricted ranges are those from areas with a short dry season (10–14 weeks): 26–39% of the tree species in these wet regions do not occur where it is drier. In comparison, just 11–19% of species from the drier side of Panama (18 week dry season) are restricted to the dry region. From this information, I predict that a four-week extension of the dry season could eliminate 25% of the species locally; a nine-week extension in very wet regions could cause 40% extinction. Since drier forests are more deciduous than wetter forests, satellite images that monitor deciduousness might provide a way to assess long-term forest changes caused by changes in drought patterns. I predict that increasing rainfall and shorter dry seasons would not cause major extinction in tropical forest, but that drying trends are a much greater concern. Longer dry seasons may cause considerable local extinction of tree species and rapid forest change, and they will also tend to exacerbate direct human damage, which tends to favor drought-adapted and invasive tree species in favor of moisture-demanding ones.     

The sensitivity of some high-latitude boreal forests to climatic parameters

A gap model of environmental processes and vegetation patterns in boreal forests was used to examine the sensitivity of permafrost and permafrostfree forests in interior Alaska to air temperature and precipitation changes. These analyses indicated that in the uplands of interior Alaska, the effect of climatic warming on the ecology of boreal forests may not be so much a direct response to increased air temperature as it may be a response to the increased potential evapotranspiration demands that will accompany climatic warmings. On poorlydrained north slopes with permafrost, the drier forest floor reduced the flux of heat into the soil profile. This was offset by increased fire severity, which by removing greater amounts of the forest floor increased the depth of soil thawing and converted the cold black spruce forests to warmer mixed hardwood-spruce forests. On well-drained south slopes, the increased potential water loss reduced available soil moisture, converting these mesic sites to dry aspen forests, or if too dry to steppe-like vegetation. Increases in precipitation offset the effects of increased potential evapotranspiration demands and mitigated these forest changes.     

Possible climatic impacts of tropical deforestation

Large-scale conversion of tropical forests into pastures or annual crops will likely lead to changes in the local microclimate of those regions. Larger diurnal fluctuations of surface temperature and humidity deficit, increased surface runoff during rainy periods and decreased runoff during the dry season, and decreased soil moistrue are to be expected.It is likely that evapotranspiration will be reduced because of less available radiative energy at the canopy level since grass presents a higher albedo than forests, also because of the reduced availability of soil moisture at the rooting zone primarily during the dry season. Recent results from general circulation model (GCM) simulations of Amazonian deforestation seem to suggest that the equilibrium climate for a grassy vegetation in Amazonia would be one in which regional precipitation would be significantly reduced.Global climate changes probably will occur if there is a marked change in rainfall patterns in tropical forest regions as a result of deforestation. Besides that, biomass burning of tropical forests is likely adding CO₂ into the atmosphere, thus contributing to the enhanced greenhouse warming.     

Modeling soil thermal and hydrological dynamics and changes of growing season in Alaskan terrestrial ecosystems

Abundant evidence indicates the growing season has been changed in the Alaskan terrestrial ecosystems in the last century as climate warms. Reasonable simulations of growing season length, onset, and ending are critical to a better understanding of carbon dynamics in these ecosystems. Recent ecosystem modeling studies have been slow to consider the interactive effects of soil thermal and hydrological dynamics on growing season changes in northern high latitudes. Here, we develop a coupled framework to model these dynamics and their effects on plant growing season at a daily time step. In this framework, we (1) incorporate a daily time step snow model into our existing hydrological and soil thermal models and (2) explicitly model the moisture effects on soil thermal conductivity and heat capacity and the effects of active layer depth and soil temperature on hydrological dynamics. The new framework is able to well simulate snow depth and soil temperature profiles for both boreal forest and tundra ecosystems at the site level. The framework is then applied to Alaskan boreal forest and tundra ecosystems for the period 1923–2099. Regional simulations show that (1) for the historical period, the growing season length, onset, and ending, estimated based on the mean soil temperature of the top 20 cm soils, and the annual cycle of snow dynamics, agree well with estimates based on satellite data and other approaches and (2) for the projected period, the plant growing season length shows an increasing trend in both tundra and boreal forest ecosystems. In response to the projected warming, by year 2099, (1) the snow-free days will be increased by 41.0 and 27.5 days, respectively, in boreal forest and tundra ecosystems and (2) the growing season lengths will be more than 28 and 13 days longer in boreal forest and tundra ecosystems, respectively, compared to 2010. Comparing two sets of simulations with and without considering feedbacks between soil thermal and hydrological dynamics, our analyses suggest coupling hydrological and soil thermal dynamics in Alaskan terrestrial ecosystems is important to model ecosystem dynamics, including growing season changes.     

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.     

Evapotranspiration of deforested areas in central and southwestern Amazonia

Considering the high rates of evapotranspiration of Amazonian forests, understanding the impacts of deforestation on water loss rates is important for assessing those impacts on a regional and global scale. This paper quantifies evapotranspiration rates in two different pasture sites in Amazonia and evaluates the differences between the sites. In both places, measured evapotranspiration varies seasonally, decreasing during the dry season. The decrease is higher at the southwestern Amazonia site, while at the central Amazonia site, the decrease is less pronounced. During the dry season, average values of evapotranspiration are around 2.2?±?0.6?mm?day^?1 in central Amazonia and 2.4?±?0.6?mm?day^?1 in southwestern Amazonia, while during the wet season, those values are 2.1?±?0.6?mm?day^?1 in central Amazonia and 3.5?±?0.8?mm?day^?1 in southwestern Amazonia. On an annual basis, the pasture in southwestern Amazonia has higher evapotranspiration than in central Amazonia. We conclude that the main reason for this difference is the lower available energy in the wet season at the central Amazonian site, combined with a lower leaf area index at this site during the whole year. Still, the evapotranspiration is significantly controlled by the vegetation, which is well coupled with the local moisture conditions in the dry season.     

Determining Effects of Area Burned and Fire Severity on Carbon Cycling and Emissions in Siberia

The Russian boreal forest contains about 25% of the global terrestrial biomass, and even a higher percentage of the carbon stored in litter and soils. Fire burns large areas annually, much of it in low-severity surface fires – but data on fire area and impacts or extent of varying fire severity are poor. Changes in land use, cover, and disturbance patterns such as those predicted by global climate change models, have the potential to greatly alter current fire regimes in boreal forests and to significantly impact global carbon budgets. The extent and global importance of fires in the boreal zone have often been greatly underestimated. For the 1998 fire season we estimate from remote sensing data that about 13.3 million ha burned in Siberia. This is about 5 times higher than estimates from the Russian Aerial Forest Protection Service (Avialesookhrana) for the same period. We estimate that fires in the Russian boreal forest in 1998 constituted some 14–20% of average annual global carbon emissions from forest fires. Average annual emissions from boreal zone forests may be equivalent to 23–39% of regional fossil fuel emissions in Canada and Russia, respectively. But the lack of accurate data and models introduces large potential errors into these estimates. Improved monitoring and understanding of the landscape extent and severity of fires and effects of fire on carbon storage, air chemistry, vegetation dynamics and structure, and forest health and productivity are essential to provide inputs into global and regional models of carbon cycling and atmospheric chemistry.     

Observed changes of drought/wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index

Monthly precipitation data of 42 rain stations over the Pearl River basin for 1960–2005 were analyzed to classify anomalously wet and dry conditions by using the standardized precipitation index (SPI) and aridity index (I) for the rainy season (April–September) and winter (December–February). Trends of the number of wet and dry months decided by SPI were detected with Mann-Kendall technique. Furthermore, we also investigated possible causes behind wet and dry variations by analyzing NCAR/NCEP reanalysis dataset. The results indicate that: (1) the Pearl River basin tends to be dryer in the rainy season and comes to be wetter in winter. However, different wetting and drying properties can be identified across the basin: west parts of the basin tend to be dryer; and southeast parts tend to be wetter; (2) the Pearl River basin is dominated by dry tendency in the rainy season and is further substantiated by aridity index (I) variations; and (3) water vapor flux, moisture content changes in the rainy season and winter indicate different influences of moisture changes on wet and dry conditions across the Pearl River basin. Increasing moisture content gives rise to an increasing number of wet months in winter. However, no fixed relationships can be observed between moisture content changes and number of wet months in the rainy season, indicating that more than one factor can influence the dry or wet conditions of the study region. The results of this paper will be helpful for basin-scale water resource management under the changing climate.     

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.     

Impacts of summer warming on the energy and water balance of wetland tundra

Measurements, made at a high subarctic, maritime, wetland tundra site, are presented for three different growing seasons. These are divided into hot-dry, normal-dry and normal-wet years and the behaviour of their surface energy and water balances is examined within the framework of a combination model. For periods of comparable energy availability, evapotranspiration during hot-dry conditions can be larger than during cooler and wetter periods. This results from small stomatal resistance in the sparse canopy of well-rooted sedges, and from the ability of peat soils to supply water under conditions of large atmospheric demand. This demand is expressed in terms of the vapour pressure deficit and it counteracts the large surface resistances which develop during dry periods. In many respects, the energy balance of a subarctic wetland tundra is comparable to observations and models for temperate agricultural and forest lands, in spite of the fact that the soils are organic, the vegetation canopy is sparse and there is continuous permafrost. A dry year promotes deeper thaw depths in the permafrost soils, during the growing season, than does a wet one. This is due to larger ground heat fluxes and larger soil thermal diffusivities. We concluded that maritime, wetland tundra, growing on peat soils, displays feedback mechanisms, which can offset the effects of moisture stress, caused by summer climate warming of a similar magnitude to that simulated by General Circulation Models for a 2 × CO₂ scenario.     

利用TRMM/TMI资料反演青藏高原中部土壤湿度

用辐射传输理论提出的地表微波辐射极化指数PI的定义,分别指出了PI对土壤湿度、地面粗糙度、植被层和大气层的影响。用热带降水测量(TRMM—Tropical Rainfall Measuring Mission)卫星上携带的微波辐射仪(TMI—TRMM Microwave Imager)的1B11的6年亮温数据,统计得到青藏高原中部地区PI值月平均分布。并用归一化距平,反演得到了该区域年、季以及干湿季土壤湿度变化的空间图像。结果表明,PI距平分布图可以很好地表征土壤湿度的变化,从而为大尺度评估高原土壤湿度变化提供了理论依据。另外,在同一时间段内,在已知区域平均PI值与平均土壤湿度的条件下,用归一化距平的方法可以定量反演该区域的土壤湿度。     

Climate Change and Tropical Forests in India

India has 64 Mha under forests, of which 72% are tropical moist deciduous, dry deciduous, and wet evergreen forest. Projected changes in temperature, rainfall, and soil moisture are considered at regional level for India under two scenarios, the first involving greenhouse gas forcing, and the second, sulphate aerosols. Under the former model, a general increase in temperature and rainfall in all regions is indicated. This could potentially result in increased productivity, and shift forest type boundaries along attitudinal and rainfall gradients, with species migrating from lower to higher elevations and the drier forest types being transformed to moister types. The aerosol model, however, indicates a more modest increase in temperature and a decrease in precipitation in central and northern India, which would considerably stress the forests in these regions.Although India seems to have stabilized the area under forest since 1980, anthropogenic stresses such as livestock pressure, biomass demand for fuelwood and timber, and the fragmented nature of forests will all affect forest response to changing climate. Thus, forest area is unlikely to expand even if climatically suitable, and will probably decrease in parts of northeast India due to extensive shifting cultivation and deforestation. A number of general adaptation measures to climate change are listed.     

Climate change alters growing season flux dynamics in mesic grasslands

Changing climate could affect the functioning of grassland ecosystems through variation in climate forcings and by altering the interactions of forcings with ecological processes. Both the short and long-term effects of changing forcings and ecosystem interactions are a critical part of future impacts to ecosystem ecology and hydrology. To explore these interactions and identify possible characteristics of climate change impacts to mesic grasslands, we employ a low-dimensional modeling framework to assess the IPCC A1B scenario projections for the Central Plains of the United States; forcings include increased precipitation variability, increased potential evaporation, and earlier growing season onset. These forcings are also evaluated by simulations of vegetation photosynthetic capacity to explore the seasonal characteristics of the vegetation carbon assimilation response for species at the Konza Prairie in North Central Kansas, USA. The climate change simulations show decreases in mean annual soil moisture and and carbon assimilation and increased variation in water and carbon fluxes during the growing season. Simulations of the vegetation response show increased variation at the species-level instead of at a larger class scale, with important heterogeneity in how individual species respond to climate forcings. Understanding the drivers and relationships behind these ecosystem responses is important for understanding the likely scale of climate change impacts and for exploring the mechanisms shaping growing season dynamics in grassland ecosystems.     

Modelling Regional Climate Change Effects On Potential Natural Ecosystems in Sweden

This study aims to demonstrate the potential of a process-based regional ecosystem model, LPJ-GUESS, driven by climate scenarios generated by a regional climate model system (RCM) to generate predictions useful for assessing effects of climatic and CO₂ change on the key ecosystem services of carbon uptake and storage. Scenarios compatible with the A2 and B2 greenhouse gas emission scenarios of the Special Report on Emission Scenarios (SRES) and with boundary conditions from two general circulation models (GCMs) – HadAM3H and ECHAM4/OPYC3 – were used in simulations to explore changes in tree species distributions, vegetation structure, productivity and ecosystem carbon stocks for the late 21st Century, thus accommodating a proportion of the GCM-based and emissions-based uncertainty in future climate development. The simulations represented in this study were of the potential natural vegetation ignoring direct anthropogenic effects. Results suggest that shifts in climatic zones may lead to changes in species distribution and community composition among seven major tree species of natural Swedish forests. All four climate scenarios were associated with an extension of the boreal forest treeline with respect to altitude and latitude. In the boreal and boreo-nemoral zones, the dominance of Norway spruce and to a lesser extent Scots pine was reduced in favour of deciduous broadleaved tree species. The model also predicted substantial increases in vegetation net primary productivity (NPP), especially in central Sweden. Expansion of forest cover and increased local biomass enhanced the net carbon sink over central and northern Sweden, despite increased carbon release through decomposition processes in the soil. In southern Sweden, reduced growing season soil moisture levels counterbalanced the positive effects of a longer growing season and increased carbon supply on NPP, with the result that many areas were converted from a sink to a source of carbon by the late 21st century. The economy-oriented A2 emission scenario would lead to higher NPP and stronger carbon sinks according to the simulations than the environment-oriented B2 scenario.     

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。     

Deep Soil Moisture Storage and Transpiration in Forests and Pastures of Seasonally-Dry Amazonia

To assess the impacts of land-use changes on plant-available water (PAW) and evapotranspiration (ET), volumetric water content (VWC) was measured to 8 m beneath three, adjacent ecosystems for four years (1991–1994). Estimates of PAW, ET, and deep drainage were generated for mature evergreen forest, adjacent pasture, and capoeira (second-growth forest on abandoned pasture land). PAW between 0 and 8 m depth for forest, pasture, and capoeira ranged from a low of 56, 400, and 138 mm at the end of the 1992 dry season to a high of 941, 1116, and 1021 mm during the 1994 wet season. We found significant differences in deep (4–8 m) stocks of PAW when comparing pasture with both forest types. In contrast, mature forest and capoeira PAW were not significantly different from one another at any depth during the experiment. In all three ecosystems available soil moisture from 4–8 m was depleted during the 1991 dry season by plant water uptake and was not recharged to 1991 levels until 1994 due to an intervening 2-year, El Niño Southern Oscillation event. Water balance estimates (based on measurements to 8 m) showed an average 10% decrease in ET from pasture compared to mature forest. Less than 15 years after pasture abandonment, ET in second-growth forest recovered to rates nearly equaling the mature forest rate. In seasonally dry environments annual and interannual cycles of deep soil moisture recharge and depletion influence rates of transpiration and drainage. These deep cycles are not currently incorporated in models of regional and global moisture flux.     

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.     

Changes in Area and Carbon in Forests of the Middle Zavolgie: A Regional Case Study of Russian Forests

We studied forest land-use and carbon storage over a 40-year period in the Middle Zavolgie region of Russia, an area of approximately 287,000 km². Data were obtained from state forest inventories for 1958 and 1995. In spite of the effects of disturbances and uncontrolled harvesting between 1958 and 1990, the forests of the Middle Zavolgie Region remained a considerable pool of ecosystem carbon (C). Over the study period the total area of forest lands decreased by approximately 2%, while the growing stock increased by 8%. There were significant changes in the age class structure of these forest ecosystems toward a larger proportion of young and middle aged stands. The total amount of carbon in the stem biomass of forests in all regions of Middle Zavolgie increased over the 40-year period and was equal to about 307 TgC in 1995. A regional approach for estimating the C dynamics of forest ecosystems in response to land use in the Middle Zavolgie region can contribute to understanding the potential role of Russian forests in C sequestration. This information is important for implementation of international conventions concerning national carbon budgets and reducing the potential negative impacts of climate change.     

Climate variability attributable to terrestrial and oceanic forcing in the NCAR CAM3-CLM3 Models

Based on numerical experiments using the NCAR CAM3-CLM3 models, this paper examines the impact of soil moisture, vegetation, and sea surface temperature (SST) on the inter-annual variability of climate over land. For each element, two experiments are carried out, with the inter-annual variability preserved in one experiment and eliminated in the other. Differences in the standard deviation of the precipitation and air temperature at the inter-annual time scale are used to quantify the impacts from soil moisture dynamics, vegetation dynamics, and oceanic forcing. The impact of oceanic forcing is mainly limited to the Tropics, with the strongest signal in the equatorial zone, and moisture convergence is the key linkage between SST forcing and tropical precipitation. Soil moisture plays a significant role in climate variability during the rainy seasons of all semi-arid regions (which is consistent with many previous studies), and during the dry seasons of the humid Amazon. Evapotranspiration is identified as the main mechanism linking precipitation variability to soil moisture. Amazon is the only region where vegetation dynamics has a significant influence on precipitation variability. However, the impact of vegetation dynamics on temperature is strong over the US Great Plains in all four seasons and in the Amazon region during the dry and dry-to-wet transition seasons.