Search

This paper evaluates the effect of climate change (described in terms of temperature and rainfall) on forest cover and vegetation (described in terms of Normalized Difference Vegetation Index) in the Betwa river basin, a tributary of River Yamuna in Central India. Temperature and rainfall data of 18 stations, forest cover and vegetation (derived using 5 years data from Landsat images employing ERDAS Imagine and ArcGIS) were used in the analysis. The effect of climate change was studied for both the premonsoon and post-monsoon seasons. In this study, the simple regression method was used to evaluate their relationship. In pre-monsoon season, temperature and forest cover analysis shows regression coefficient value of 0.6876 and, temperature and vegetation analysis shows regression coefficient value of 0.5751. Further, in post-monsoon season analysis rainfall and forest cover shows regression coefficient value of 0.8417 and, temperature and vegetation analysis shows regression coefficient value of 0.6854. The study reveals that, in pre-monsoon season temperature was significantly related with forest cover and vegetation. In postmonsoon season rainfall exhibited positive response to forest cover and, temperature exhibited negative response to vegetation in the Betwa river basin. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

Recent climatic changes have affected terrestrial net primary productivity (NPP). This paper presents an investigation of the impact of climatic changes on Chinese terrestrial vegetation NPP by analyzing 18 years' (1982 to 1999) climatic data and satellite observations of vegetation activity. Results indicate that climatic changes in China have eased some critical climatic constraint on plant growth. (1) From 1982 to 1999, modeled NPP increased by 1.42% · a-1 in water-limited regions of Northwest China, 1.46% · a-1 in temperature-limited regions of Northeast China and Tibet Plateau, and 0.99% · a-1 in radiation-limited regions of South China and East China. (2) NPP increased by 24.2%, i.e. 0.76 petagram of carbon (Pg C) over 18 years in China. Changes in climate (with constant vegetation) directly contributed nearly 11.5% (0.36 Pg C). Changes in vegetation (with constant climate) contributed 12.4% (0.40 Pg C), possibly as a result of climate-vegetation feedbacks, changes in land use, and growth stimulation from other mechanisms. (3) Globally, NPP declined during all three major El Niño events (1982 to 1983, 1987 to 1988, and 1997 to 1998) between 1982 and 2000, but Chinese vegetation productivity responded differently to them because of the monsoon dynamics. In the first three events (1982 to 1983, 1987 to 1988, and 1992), Chinese vegetation NPP declined, while in the later two events (1993, 1997 to 1998) increasing obviously. [ABSTRACT FROM AUTHOR]

Current predictions of how species will respond to climate change are typically based on coarse-grained climate surfaces utilizing bioclimate envelope modelling. However, the suitability of environmental conditions for a given species might result from a variety of factors including some unrelated to climate. To address this issue, we investigated whether the inclusion of topographical and soil information in bioclimatic envelope models would significantly alter predictions of climate change-induced fine-scale tree and shrub species range size changes at the tree-limit in subarctic Europe. Using generalized additive models and data on current climate and species distributions and three different climate scenarios for the period 2040-2069, we developed predictions of the currently suitable area and potential range size changes of seven tree and shrub species in an area of 1,100 km at a resolution of 1-ha. The inclusion of topography and soil information increased the predictive accuracy of climate-only models for all studied species. The predicted changes in species distribution volumes were contradictory, and the predicted occurrences varied greatly depending on the model used. Our results therefore support the arguments that vegetation responses to climate change can be influenced by local environmental conditions and that attention should be paid to the combined effects of these factors. We conclude that disregarding local topography and soil conditions in bioclimatic models may result in biased projections of range expansions and the associated colonization, extinction and turnover assessments. [ABSTRACT FROM AUTHOR]

Extensive studies have investigated the relationships between climate change and vegetation dynamics. However, the geographic controls on vegetation dynamics are rarely studied. In this study, the geographic controls on the trends and variation of vegetation greenness in middle and eastern Inner Mongolia, China (mid-eastern Inner Mongolia) were investigated. The SPOT VEGETATION 10-day period synthesis archive of normalized difference vegetation index (NDVI) from 1999 to 2007 was used for this study. First, the maximum value compositing (MVC) method was applied to derive monthly maximum NDVI (MNDVI), and then yearly mean NDVI (YMNDVI) was calculated by averaging the MNDVIs. The greenness rate of change (GRC) and the coefficient of variation (CV) were used to monitor the trends and variation in YMNDVI at each raster grid for different vegetation types, which were determined from a land use dataset at a scale of 1:100,000, interpreted from Landsat TM images in 2000. The possible effects of geographic factors including elevation, slope and aspect on GRC and CV for three main vegetation types (cropland, forest and steppe) were analyzed. The results indicate that the average NDVI values during the 9-year study period for steppe, forest and cropland were 0.26, 0.41 and 0.32, respectively; while the GRC was 0.008, 0.042 and 0.033 per decade, respectively; and CVs were 10.2, 4.8 and 7.1%, respectively. Cropland and steppe shared a similar trend in NDVI variation, with both decreasing initially and then increasing over the study period. The forest YMNDVI increased throughout the study period. The GRCs of the forest also increased, although GRCs for cropland and steppe decreased with increasing elevation. The GRCs of cropland and steppe increased with increasing slope, but the forest GRCs were not as closely related to slope. All three vegetation types exhibited the same effects in that the GRC was larger on north-facing (shady) slopes than south-facing slopes due to differences in water conditions. The CVs of the three vegetation types showed different features to the GRC. The CVs for all three vegetation types were not affected by aspect. The CVs for forest and cropland showed minor effects with changes in elevation and slope, but the CV for steppe decreased with increasing slope, and increased with increasing elevations to 1,200 m, before decreasing at higher elevations. Our findings suggest that the role of geographic factors in controlling GRC should also be considered alongside climate factors . [ABSTRACT FROM AUTHOR]

This study examines the role of vegetation dynamics in regional predictions of future climate change in western Africa using a dynamic vegetation model asynchronously coupled to a regional climate model. Two experiments, one for present day and one for future, are conducted with the linked regional climate-vegetation model, and the third with the regional climate model standing alone that predicts future climate based on present-day vegetation. These simulations are so designed in order to tease out the impact of structural vegetation feedback on simulated climate and hydrological processes. According to future predictions by the regional climate-vegetation model, increase in LAI is widespread, with significant shift in vegetation type. Over the Guinean Coast in 2084-2093, evergreen tree coverage decreases by 49% compared to 1984-1993, while drought deciduous tree coverage increases by 56%. Over the Sahel region in the same period, grass cover increases by 31%. Such vegetation changes are accompanied by a decrease of JJA rainfall by 2% over the Guinean Coast and an increase by 23% over the Sahel. This rather small decrease or large increase of precipitation is largely attributable to the role of vegetation feedback. Without the feedback effect from vegetation, the regional climate model would have predicted a 5% decrease of JJA rainfall in both the Guinean Coast and the Sahel as a result of the radiative and physiological effects of higher atmospheric CO concentration. These results demonstrate that climate- and CO-induced changes in vegetation structure modify hydrological processes and climate at magnitudes comparable to or even higher than the radiative and physiological effects, thus evincing the importance of including vegetation feedback in future climate predictions. [ABSTRACT FROM AUTHOR]

The aim of this work was to test the hypotheses that the species composition of the vegetation of one pool in Morocco change continuously along with rainfall fluctuations, that among the vegetation can be recognized Pool species and Opportunistic species with distinct dynamics in time. We expected the Pool species to show lower inter-annual variation than the Opportunistic species. This hypothesis was tested in a 10-year study of the species composition of the vegetation along two permanent transects. The results showed high cumulative species richness (95 species) with large differences between years and a predominance of annual species (77). The proportion of Pool species during these 10 years was low (39%) when compared to opportunists (61%). In dry years the Opportunistic species were dominant and declined during wet years. The number of Pool species was correlated with the amount of rainfall. A large number of these species revealed a preference for wet years. No negative interaction between annuals/perennials and pools/non-pools species was found, suggesting that competition was not a major process during the survey. The intensity of the drought and flood stress, related to climate fluctuations, seems to be the main factors controlling the species composition of the vegetation of this unstable habitat. However, beyond the inter-annual fluctuation of the species composition of the vegetation a directional change was noticed. This directional change could result from a recovery process of the vegetation during the first years of the study after a severe flood which extirpated most of the Opportunistic species of the pool. In the last years this directional change of the species composition of the vegetation is less clear and random recruitment of the Opportunistic species from the surrounding forested habitats could contribute to explain inter-annual changes. The data collected over these 10 years led to the speculation of hypotheses on the consequences of climate change. The expected reduction of humid years and of rainfall regionally may lead to important changes in the species composition of the vegetation of the temporary pools in Morocco. [ABSTRACT FROM AUTHOR]

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO2 values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO2 fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO2 and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO2 fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift. [ABSTRACT FROM AUTHOR]

The two main goals of this study are: (i) to examine the range shifts of a currently northwards expanding species, the map butterfly (Araschnia levana), in relation to annual variation in weather, and (ii) to test the capability of a bioclimatic envelope model, based on broad-scale European distribution data, to predict recent distributional changes (2000-2004) of the species in Finland. A significant relationship between annual maximum dispersal distance of the species and late summer temperature was detected. This suggests that the map butterfly has dispersed more actively in warmer rather than cooler summers, the most notable dispersal events being promoted by periods of exceptionally warm weather and southerly winds. The accuracy of the broad-scale bioclimatic model built for the species with European data using Generalized Additive Models (GAM) was good based on split-sample evaluation for a single period. However, the model's performance was poor when applied to predict range shifts in Finland. Among the many potential explanations for the poor success of the transferred bioclimatic model, is the fact that bioclimatic envelope models do not generally account for species dispersal. This and other uncertainties support the view that bioclimatic models should be applied with caution when they are used to project future range shifts of species. [ABSTRACT FROM AUTHOR]

The dynamic vegetation model (LPJ-GUESS) is used to project transient impacts of changes in climate on vegetation of the Barents Region. We incorporate additional plant functional types, i.e. shrubs and defined different types of open ground vegetation, to improve the representation of arctic vegetation in the global model. We use future climate projections as well as control climate data for 1981-2000 from a regional climate model (REMO) that assumes a development of atmospheric CO2-concentration according to the B2-SRES scenario [IPCC, Climate Change 2001: The scientific basis. Contribution working group I to the Third assessment report of the IPCC. Cambridge University Press, Cambridge (2001)]. The model showed a generally good fit with observed data, both qualitatively when model outputs were compared to vegetation maps and quantitatively when compared with observations of biomass, NPP and LAI. The main discrepancy between the model output and observed vegetation is the overestimation of forest abundance for the northern parts of the Kola Peninsula that cannot be explained by climatic factors alone. Over the next hundred years, the model predicted an increase in boreal needle leaved evergreen forest, as extensions northwards and upwards in mountain areas, and as an increase in biomass, NPP and LAI. The model also projected that shadeintolerant broadleaved summergreen trees will be found further north and higher up in the mountain areas. Surprisingly, shrublands will decrease in extent as they are replaced by forest at their southern margins and restricted to areas high up in the mountains and to areas in northern Russia. Open ground vegetation will largely disappear in the Scandinavian mountains. Also counter-intuitively, tundra will increase in abundance due to the occupation of previously unvegetated areas in the northern part of the Barents Region. Spring greening will occur earlier and LAI will increase. Consequently, albedo will decrease both in summer and winter time, particularly in the Scandinavian mountains (by up to 18%). Although this positive feedback to climate could be offset to some extent by increased CO2 drawdown from vegetation, increasing soil respiration results in NEE close to zero, so we cannot conclude to what extent or whether the Barents Region will become a source or a sink of CO2. [ABSTRACT FROM AUTHOR]

The relationship between climate change and vegetation dynamics in the southwestern karst region of China has been identified by recent studies. Based on previous researches and AVHRR (Advanced Very High Resolution Radiometer) GIMMS (Global Inventory Monitoring and Modeling Studies) NDVI (Normalized Difference Vegetation Index) (1982–2003) and AVHRR GloPEM (Global Production Efficiency Model) NPP (Net Primary Production) (1981–2000) datasets, vegetation dynamics impacted by climate change in the southwestern karst region of China were assessed. The results show that: (1) since the early 1980s, both vegetation cover density and net primary production have insignificant ascending tendencies. However, the inter-annual variation rates of vegetation indexes have apparent spatial differentiations; (2) the correlation coefficients between the inter-annual variations of vegetation indexes and the inter-annual variations of climate factors vary geographically; (3) as indicated by NDVI and NPP, various vegetation types have different responses to climate change, and the annual mean temperature variation has more significant impact on vegetation dynamics than the annual precipitation variation in the study area; (4) distribution laws of correlation coefficients between the inter-annual variations of vegetation indexes and the inter-annual variations of climate factors in different climate conditions are apparent. All these findings will enrich our knowledge of the natural forces which impact the stability of the karst ecosystems and provide scientific basis for the management of the karst ecosystems. [ABSTRACT FROM AUTHOR]

Systematic evaluation of food security throughout the Sahel has been attempted for nearly two decades. Food security analyses have used both food prices to determine the ability of the population to access food, and satellite-derived vegetation indices that measure vegetation production to establish how much food is available each year. The relationship between these two food security indicators is explored here using correspondence analysis and through the use of Markov chain models. Two sources of quantitative data were used: 8 km normalized difference vegetation index (NDVI) data from the Advanced Very High Resolution Radiometers (AVHRR) carried on the NOAA series of satellites, and monthly millet prices from 445 markets in Mali, Niger and Burkina Faso. The results show that the growing season vegetation production is related to the price of millet at the annual and the seasonal time scales. If the growing season was characterized by erratic, sparse rainfall, it resulted in higher prices, and well-distributed, abundant rainfall resulted in lower prices. The correspondence between vegetation production and millet prices is used to produce maps of millet prices for West Africa. [ABSTRACT FROM AUTHOR]

Assessing the long-term dynamics of mountain landscapes that are influenced by large-scale natural and anthropogenic disturbances and a changing climate is a complex subject. In this study, a landscape-level ecological model was modified to this end. We describe the structure and evaluation of the fire sub-model of the new landscape model LANDCLIM, which was designed to simulate climate-fire-vegetation dynamics. We applied the model to an extended elevational gradient in the Colorado Front Range to test its ability to simulate vegetation composition and the strongly varying fire regime along the gradient. The simulated sequence of forest types along the gradient corresponded to the one observed, and the location of ecotones lay within the range of observed values. The model captured the range of observed fire rotations and reproduced realistic fire size distributions. Although the results are subject to considerable uncertainty, we conclude that LANDCLIM can be used to explore the relative differences of fire regimes between strongly different climatic conditions. [ABSTRACT FROM AUTHOR]

Background: Dynamic Global Vegetation Models (DGVMs) compute the terrestrial carbon balance as well as the transient spatial distribution of vegetation. We study two scenarios of moderate and strong climate change (2.9 K and 5.3 K temperature increase over present) to investigate the spatial redistribution of major vegetation types and their carbon balance in the year 2100. Results: The world's land vegetation will be more deciduous than at present, and contain about 125 billion tons of additional carbon. While a recession of the boreal forest is simulated in some areas, along with a general expansion to the north, we do not observe a reported collapse of the central Amazonian rain forest. Rather, a decrease of biomass and a change of vegetation type occurs in its northeastern part. The ability of the terrestrial biosphere to sequester carbon from the atmosphere declines strongly in the second half of the 21st century. Conclusion: Climate change will cause widespread shifts in the distribution of major vegetation functional types on all continents by the year 2100. [ABSTRACT FROM AUTHOR]

The article reports on the facts presented by scientists regarding the contributions of plants and vegetation in regulating the levels of carbon dioxide (CO2) in the atmosphere millions of years ago. It states that fossil fuels have caused the temperature to rise, because fossil fuels produces carbon dioxide. According to M. Pagani and his colleagues, although the geological process of the dissolution of continental rocks catch carbon dioxide, vegetation also played a major role. They state that vegetation regulates the limit of carbon dioxide in the atmosphere, wherein it prevented carbon level in reaching below 200 parts per million (p.p.m.).