Trends In Vegetation Cover Research Articles

Linear and segmented linear trend detection for vegetation cover using GIMMS normalized difference vegetation index data in semiarid regions of Nigeria

Quantitative analysis of trends in vegetation cover, especially in Kogi state, Nigeria, where agriculture plays a major role in the region’s economy, is very important for detecting long-term changes in the phenological behavior of vegetation over time. This study employs the use of normalized difference vegetation index (NDVI) [global inventory modeling and mapping studies 3g (GIMMS)] data from 1983 to 2011 with detailed methodological and statistical approach for analyzing trends within the NDVI time series for four selected locations in Kogi state. Based on the results of a comprehensive study of seasonalities in the time series, the original signals are decomposed. Different linear regression models are applied and compared. In order to detect structural changes over time a detailed breakpoint analysis is performed. The quality of linear modeling is evaluated by means of statistical analyses of the residuals. Standard deviations of the regressions are between 0.015 and 0.021 with R2 of 0.22–0.64. Segmented linear regression modeling is performed for improvement and a decreasing standard deviation of 33%–40% (0.01–0.013) and R2 up to 0.82 are obtained. The approach used in this study demonstrates the added value of long-term time series analyses of vegetation cover for the assessment of agricultural and rural development in the Guinea savannah region of Kogi state, Nigeria.

Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator

There is a strong signal showing that the climate in Xinjiang, China has changed from warm-dry to warm-wet since the early 1980s, leading to an increase in vegetation cover. Based on a regression analysis and Hurst index method, this study investigated the spatial–temporal characteristics and interrelationships of the vegetation dynamics and climate variability in Xinjiang Province using the leaf area index (LAI) and a gridded meteorological dataset for the period 1982–2012. Further analysis focused on the discrimination between climatic change and human-induced effects on the vegetation dynamics, and several conclusions were drawn. (1) Vegetation dynamics differ in mountain and plains regions, with a significant increasing trend of vegetation cover in oases and decreasing trend of vegetation growth in the Tienshan and Altay Mountain. The Hurst exponent results indicated that the vegetation dynamic trend was consistent, with a sustainable area percentage of 51.18%, unsustainable area percentage of 4.04%, and stable and non-vegetated area ratio of 44.78%. (2) The warm-dry to warm-wet climatic pattern in Xinjiang Province since the 1980s mainly appeared in the western part of the Tienshan region and North Xinjiang. Temperatures increased in all seasons over the majority of Xinjiang, and precipitation showed a significant increasing trend in the mountainous regions in spring, summer and autumn, whereas the rate of precipitation change was higher in the plains region in winter compared with that in other seasons. (3) A correlation occurs between the climate variables (precipitation and temperature) and mean LAI, and this correlation varies at the seasonal and regional scales, with coniferous forest, meadow and grassland more correlated with precipitation in spring and summer and not correlated with temperature, which indicated that precipitation was the dominant factor affecting the growth of mountain vegetation. The mean LAI of vegetation in the plains exhibited significant correlation with precipitation in winter and temperature in spring and summer. (4) A residual analysis showed a human-induced change that was superimposed on the climate trend and exhibited two effects: vegetation regeneration in oases throughout Xinjiang and desertification in the meadow located in the mountainous area of the western Tienshan Mountains and Altay Mountains. (5) Grassland is the most sensitive vegetation type to short-term climatic fluctuations and is the land-use type that has been most severely degraded by human activity; thus, local governments should take full advantage of this climatic warm-wet shift and focus on protecting vegetation to improve this fragile arid environment.

Assessment of environmental changes induced by internally displaced person (IDP) camps in the Darfur region, Sudan, based on multitemporal MODIS data

Darfur’s complex conflict situation led to large-scale internal displacement of people with significant implications for the environment as well as for the conflict situation itself. Time series analyses of medium-resolution satellite data for monitoring large regions were carried out over a longer period to detect the impact of camps for internally displaced persons (IDPs) on their surrounding environment. Four regions of interest were defined in the Darfur region, Sudan, which cover the main and most dynamic IDP camps of the region and are characterized by different environmental conditions. Hotspots of anthropogenic impacts on the vegetation are revealed based on the Seasonal Kendall test applied to quality-enhanced enhanced vegetation index and normalized difference vegetation index Moderate Resolution Imaging Spectroradiometer time series. Overlaying the resulting trend pattern with the locations of IDP camps suggests significant impact on the vegetation, especially – but not exclusively – in those areas with very high population densities. A comparison of the temporal development of the detected hotspots with precipitation and population figures over the investigated period help differentiate between natural and human-induced impacts. Subsequent to the analysis of the medium resolution data, the resulting trends in vegetation cover were correlated with changes detected with very-high-resolution satellite imagery for the two areas around Zalingei and Zam Zam. Areas of decreased vegetation cover in the resulting trend pattern can be correlated with logging of trees as well as removal of shrubs and grass, while positive changes in vegetation cover are related to agricultural land expansion.

Spatio-temporal analysis of trends in seasonal vegetation productivity across Uttarakhand, Indian Himalayas, 2000–2014

Himalayan mountain system in the Indian sub-continent are among the most ecologically sensitive environments and are also a repository of biodiversity, water and ecosystem services. Over the last two decades, land transformation related to exploitative land uses is among the main drivers of changing vegetation cover and productivity in western Himalayas. In a region where field based research is challenging due to heterogenous relief and high altitude, quantifying changes in vegetation photosynthetic activity using remote sensing can provide essential information regarding trends in vegetation cover and its linkages with anthropogenic impacts. We conducted seasonal trend analysis (STA) on MODIS NDVI time-series data (2000–2014) over Uttarakhand Himalayas and examined spatio-temporal patterns in vegetation trends and its association with altitudinal gradient and land use land cover (LULC) dynamics. In STA the first step determines the annual mean and seasonal NDVI patterns and the second step analyzes the non-parametric trend in magnitude and timing of the annual mean and seasonal NDVI cycle. To provide insights on the role of changing land use to detected changes in vegetation trend, we linked MODIS derived trends to land transformation processes using multi-temporal high spatial resolution imagery in Google Earth (GE). In total 3286.82 km2 (6.9% vegetated area of Uttarakhand) showed significant trend (p < 0.01) in mean annual greenness. While areas <800 m elevation showed dominant negative trend in mean annual greenness (browning)), those between 800 and 1600 m showed mostly positive trend (greening) and majority of areas >1600 m were characterized by negative trend in mean annual greenness. Majority of intensively cultivated irrigated croplands in the Himalayan foothills as well as areas around growing urban centers showed widespread browning, which was contrastingly different from rainfed cultivation areas that showed dominant greening trend. Browning trend was observed to be consistent with increasing altitude, particularly in closed needle leaf forests and alpine shrublands, except areas where human impacts has led to more mixed patterns. Trends in the annual seasonal timing of NDVI indicated an earlier green-up for most parts of the Uttarakhand Himalayas. These results highlight fine scale spatial variations in seasonal vegetation trends and are in partial agreement with previous studies that report only increasing brownness detected at broader scale using much coarser spatial resolution time-series.

Effectiveness of black tea extract on ROS mediated oxidative stress and other inflammatory parameters production in patients with RA in an in-vitro model system: Preliminary experimental study

In this study we analyzed dust events records of surface meteorological stations on Tibetan Plateau (TP) during 1961–2010 and provided the spatial and temporal distribution of dust events. The occurrence of dust events has significantly decreased since the 1970s. We defined the Tibetan Plateau Dust Index (TPDI) for the most dust active periods, spring and winter, to characterize the large scale variability of dust events over TP. Mann–Kendall test suggested the decreasing trend was possibly an abrupt change in the 1990s. The decline of surface wind speeds could partly explain the decrease of dust events over TP. TPDI is positively correlated to the surface winds, with correlation coefficients of 0.42 for spring and 0.46 for winter, respectively. The averaged number days with strong winds (wind speed greater than 6.5 ms-1) for the 4 selected stations, which were chosen to define TPDI, are significantly correlated with TPDI for both spring (correlation coefficient = 0.69) and winter (correlation coefficient = 0.76) and also showed a deceasing trend. The upward trend of vegetation cover was indicated by the normalized difference vegetation index (NDVI), which can be attributed as another factor driving the decrease of dust events over TP. TPDI is negatively correlated to the NDVI, with correlation coefficients of −0.48 for spring and −0.29 for winter. Additionally, analysis of geopotential height fields and wind fields indicate an enhanced ridge in the north of TP and weakened westerly jet in the low-frequency years of dust events, which also drive the decline of dust events over TP.

Monitoring temporal Vegetation changes in Lao tropical forests

Studies on changes in vegetation are essential for understanding the interaction between humans and the environment. These studies provide key information for land use assessment, terrestrial ecosystem monitoring, carbon flux modelling and impacts of global climate change. The primary purpose of this study was to detect temporal vegetation changes in tropical forests in the southern part of Lao PDR from 2001-2012. The study investigated the annual vegetation phenological response of dominant land cover types across the study area and relationships to seasonal precipitation and temperature. Improved understanding of intra-annual patterns of vegetation variation was useful to detect longer term changes in vegetation. The breaks for additive season and trend (BFAST) approach was implemented to detect changes in these land cover types throughout the 2001-2012 period. We used the enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD13Q1 products) and monthly rainfall and temperature data obtained from the Meteorology and Hydrology Department, Ministry of Agriculture-Forestry, published by Lao National Statistical Centre in this research. EVI well documented the annual seasonal growth of vegetation and clearly distinguished the characteristic phenology of four different land use types; native forest, plantation, agriculture and mixed wooded/cleared area. Native forests maintained high EVI throughout the year, while plantations, wooded/cleared areas and agriculture showed greater inter-annual variation, with minimum EVI at the end of the dry season in April and maximum EVI in September-October, around two months after the wet season peak in rainfall. The BFAST analysis detected abrupt temporal changes in vegetation in the tropical forests, especially in a large conversion of mixed wooded/cleared area into plantation. Within the study area from 2001-2012 there has been an overall decreasing trend of vegetation cover for native forests and mixed wooded/cleared lands, and by contrast an increase in EVI of plantations after 2008.

2000-2012年京津风沙源治理区植被覆盖时空演变特征

Due to grassland degradation and expansion of desertification,the Northern China continuously suffered from several sandstorms in the spring of 2000. In order to control the desertification trend in Beijing and surroundings and improve the ecological condition and environment in Beijing-Tianjin Sandstorm Source Region( BTSSR),the Chinese government launched the Beijing-Tianjin Sandstorm Source Control Program in July 2000. This program has been working for thirteen years. However,it is unknown that how the vegetation and ecosystems were restored and whether or not the program functioned in the BTSSR. It is necessary to assess the effectiveness of this program. The assessment deals not only with the changes of vegetation cover in the ecological vulnerable area,but also with the effectiveness of the policy. The objective of this study was to analyze the spatiotemporal characteristics of vegetation cover changes and the factors that affect the changes in the core control area of the BTSSR using the time series of normalized difference vegetation index( NDVI)derived from a Moderate Resolution Imaging Spectro-Radiometer( MODIS) product MODIS02 B for the time period of2000—2012. Linear trend analysis,standard deviation,Hurst index and correlation analysis were employed. Resultsshowed that( 1) During the past thirteen years,although annual NDVI values fluctuated slightly,overall there was an increased trend of vegetation cover in the BTSSR with the coefficient of determination: R2= 0. 70. The NDVI value increased with 0. 01 per year. In 2012,the maximum NDVI value reached to 0. 324 and increased by 135. 62% compared to that in 2000. However,the change rate and degree varied from place to place. The greatest increase of NDVI took place in the Northern arid area( Bbghq),then in the Hsdk area( Hsdkq),and the vegetation cover was relatively stable in the agro-pastoral ecotone( Nmjcq);( 2) The annual NDVI values in the BTSSR varied spatially. It was found that as elevation increased,the average NDVI increased at the beginning,reached its maximum and then decreased. The minimum value 0.257 was mainly distributed in the areas with elevation of 1000 to 1500 m. The NDVI values also increased as the increasing slope;( 3) In the program region,the area in which vegetation growing showed improved was obviously larger than the vegetation degraded area. There was an area of 94. 31% in which the vegetation cover statistically increased significantly at a risk level of 0. 1. Hurst index analysis showed that in the sandstorm control area,overall the vegetation showed growing and the vegetation cover continuously increased. The total area of vegetation growing occupied about 64. 48%. The results of comprehensive analysis implied that in the program area the vegetation showed a tendency of healthy development. But,it had to be pointed out that there was still an area of 35. 3% in which the vegetation was continuously degraded or only slightly improved;( 4) Human activities,especially ecological restoration,were the main factor that drove the increase of vegetation cover. Among the natural factors,precipitation was critical because it limited the growth and spatial distribution of vegetation in the BTSSR. The effect of temperature was relatively weak. All the findings greatly enhanced our understanding of how human activities impacted vegetation cover in arid and semi-arid environments and provided scientific guidelines for the management of ecological restoration programs and future directions.

Vegetation cover variation in the Qilian Mountains and its response to climate change in 2000–2011

An understanding of variations in vegetation cover in response to climate change is critical for predicting and managing future terrestrial ecosystem dynamics. Because scientists anticipate that mountain ecosystems will be more sensitive to future climate change compared to others, our objectives were to investigate the impacts of climate change on variation in vegetation cover in the Qilian Mountains (QLM), China, between 2000 and 2011. To accomplish this, we used linear regression techniques on 250-m MODIS Normalized Difference Vegetation Index (NDVI) datasets and meteorological records to determine spatiotemporal variability in vegetation cover and climatic factors (i.e. temperature and precipitation). Our results showed that temperatures and precipitation have increased in this region during our study period. In addition, we found that growing season mean NDVI was mainly distributed in the vertical zone from 2,700 m to 3,600 m in elevation. In the study region, we observed significant positive and negative trends in vegetation cover in 26.71% and 2.27% of the vegetated areas. Correlation analyses indicated that rising precipitation from May to August was responsible for increased vegetation cover in areas with positive trends in growing season mean NDVI. However, there was no similar significant correlation between growing season mean NDVI and precipitation in regions where vegetation cover declined throughout our study period. Using spatial statistics, we found that vegetation cover frequently declined in areas within the 2,500–3,100 m vertical zone, where it has steep slope, and is on the sunny side of mountains. Here, the positive influences of increasing precipitation could not offset the drier conditions that occurred through warming trends. In contrast, in higher elevation zones (3,900–4,500 m) on the shaded side of the mountains, rising temperatures and increasing precipitation improved conditions for vegetation growth. Increased precipitation also facilitated vegetation growth in areas experiencing warming trends at lower elevations (2,000–2,400 m) and on lower slopes where water was more easily conserved. We suggest that spatial differences in variation in vegetation as the result of climate change depend on local moisture and thermal conditions, which are mainly controlled by topography (e.g. elevation, aspect, and slope), and other factors, such as local hydrology.

An assessment of the degree to which Landsat TM data can support the assessment of fluvial dynamics, as revealed by changes in vegetation extent and channel position, along a large river

Recent research has demonstrated the capacity of remotely sensed data to enhance our understanding of interactions between fluvial processes and riparian vegetation. Multispectral Landsat TM satellite data covering the last 30years are now freely available and have the potential to support investigations at much broader spatial and temporal scales than previously possible. This paper assesses the degree to which this data set can support the assessment of fluvial dynamics along a large gravel bed river, the Fiume Tagliamento, NE Italy. Landsat TM scenes are used to determine spatio-temporal trends in vegetation cover and channel position at six sites of contrasting environmental conditions along the river. These trends are interpreted in combination with a number of additional hydrogeomorphological data sets before comparison with known biogeomorphological characteristics of the study sites as revealed by previous field research and analyses of higher resolution remotely sensed data sets. The research highlights a number of limitations with Landsat TM data that arise as a result of its relatively low spatial resolution including geomorphic feature definition and active tract delineation. Nevertheless, the analysis demonstrates that Landsat TM data can reveal a wealth of information that could support further biogeomorphological investigations in other large rivers.

Land use change and carbon fluxes in East Africa quantified using earth observation data and field measurements

SUMMARYCarbon-based forest conservation requires the establishment of ‘reference emission levels’ against which to measure a country or region's progress in reducing their carbon emissions. In East Africa, landscape-scale estimates of carbon fluxes are uncertain and factors such as deforestation poorly resolved due to a lack of data. In this study, trends in vegetation cover and carbon for East Africa were quantified using moderate-resolution imaging spectroradiometer (MODIS) land cover grids from 2002 to 2008 (500-m spatial resolution), in combination with a regional carbon look-up table. The inclusion of data on rainfall and the distribution of protected areas helped to gauge impacts on vegetation burning (assessed using 1-km spatial resolution MODIS active fire data) and biome trends. Between 2002 and 2008, the spatial extents of forests, woodlands and scrublands decreased considerably and East Africa experienced a net carbon loss of 494 megatonnes (Mt). Most countries in the area were sources of carbon emissions, except for Tanzania and Malawi, where the areal increase of savannah and woodlands counterbalanced carbon emissions from deforestation. Both Malawi and Tanzania contain large areas of planted forest. Vegetation burning was correlated with rainfall (forest only) and differed depending on land management. Freely available global earth observation products have provided ways to achieve rapid assessment and monitoring of carbon change hotspots at the landscape scale.

Understanding the dynamic coupling between vegetation cover and climatic factors in a semiarid region—a case study of Inner Mongolia, China

ABSTRACTVegetation is sensitive to changes in the ecological environment in arid and semiarid regions, so information on the dynamics of vegetation cover changes can provide important information for ecological environmental protection and early warning of ecosystem degradation. With the SPOT/VEGETATION normalised difference vegetation index dataset of the typical semiarid land in Inner Mongolia (IM) during 1998–2008, this study applied an integrated statistical method combing asymmetric Gaussian filtering, seasonal Kendall test, R/S analysis, correlation analysis and regression analysis, to investigate the impact of climatic factors on trends in vegetation cover. The main findings are as follows: (1) Over the 1998–2008 period, the vegetation coverage is relatively stable in IM, with only 24.5% of the total area exhibiting a significant variation in cover. The spatial distribution of the vegetation cover change has the following regional characteristics: in the northeast forest region, the vegetation cover is stable; in the middle steppe region, significant changes are observed and in the southwest desert region, the vegetation exhibits significant degradation. (2) Normalised difference vegetation index time series in most regions of IM reveal a vegetation change trend. In the high vegetation covered regions, the change trend will be reversed, whereas in the low vegetation covered regions, the original change trend will be preserved. (3) Analysis of correlation coefficients and stepwise linear regression reveals relationships between vegetation change and climatic factors. Temperature and precipitation have a direct influence on vegetation change, acting as the main climatic driving forces for the regional vegetation evolution. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Developing effective sampling designs for monitoring natural resources in Alaskan national parks: An example using simulations and vegetation data

Monitoring natural resources in Alaskan national parks is challenging because of their remoteness, limited accessibility, and high sampling costs. We describe an iterative, three-phased process for developing sampling designs based on our efforts to establish a vegetation monitoring program in southwest Alaska. In the first phase, we defined a sampling frame based on land ownership and specific vegetated habitats within the park boundaries and used Path Distance analysis tools to create a GIS layer that delineated portions of each park that could be feasibly accessed for ground sampling. In the second phase, we used simulations based on landcover maps to identify size and configuration of the ground sampling units (single plots or grids of plots) and to refine areas to be potentially sampled. In the third phase, we used a second set of simulations to estimate sample size and sampling frequency required to have a reasonable chance of detecting a minimum trend in vegetation cover for a specified time period and level of statistical confidence. Results of the first set of simulations indicated that a spatially balanced random sample of single plots from the most common landcover types yielded the most efficient sampling scheme. Results of the second set of simulations were compared with field data and indicated that we should be able to detect at least a 25% change in vegetation attributes over 31 years by sampling 8 or more plots per year every five years in focal landcover types. This approach would be especially useful in situations where ground sampling is restricted by access.

Climate‐related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006

AbstractUsing Advanced Very High Resolution Radiometer data spanning 1981–2006 and calibrated for long‐term analyses of vegetation dynamics, we examine whether vegetation cover has increased across Australia and whether there has been a differential response of vegetation functional types in response to changes in climatic growing conditions. Trends in vegetation cover are interpreted within Budyko's energy – water limitation framework. Results from an Australia‐wide analysis indicate that vegetation cover (as described by the fraction of Photosynthetically Active Radiation absorbed by vegetation; fPAR) has increased, on average, by 0.0007 per year – an increase of ∼8% over the 26 years. The majority of this change is due to a 0.0010 per year increase in persistent fPAR (representing nondeciduous perennial vegetation types; up 21%). In contrast, recurrent fPAR (representing deciduous, annual and ephemeral vegetation types) decreased, on average, by 0.0003 per year (down 7%), the trends of which are highly seasonal. Over the same period, Australian average annual precipitation increased by 1.3 mm yr−2 (up 7%). A site‐based analysis using 90 long‐term meteorological stations with minimal localized land‐cover changes showed that energy‐limited sites where total fPAR increased generally experienced decreases in precipitation, and water‐limited sites that experienced decreases in cover were almost always associated with decreases in precipitation. Interestingly, where vegetation cover increased at water‐limited sites, precipitation trends were variable indicating that this is not the only factor driving vegetation response. As Australia is a generally highly water‐limited environment, these findings indicate that the effective availability of water to plants has increased on average over the study period. Results also show that persistent vegetation types have benefited more than recurrent types from recent changes in growing conditions. Regardless of what has been driving these changes, the overall response of vegetation over the past 2–3 decades has resulted in an observable greening of the driest inhabited continent on Earth.

Spatiotemporal vegetation cover variations in the Qinghai-Tibet Plateau under global climate change

Empirical Orthogonal Function (EOF) analysis and the related Principal Components (PC) analysis are used to extract valuable vegetation cover derived information from the National Oceanic and Atmos-pheric Administration (NOAA-AVHRR)’s Leaf Area Index (LAI) satellite images. Results suggest that from 1982 to 2000 global climate change has contributed to an increase in vegetation cover in the Qinghai-Tibet Plateau. The correlation between rainfall and LAI EOF PC1 and PC2 indicates that rainfall is the major climatic factor influencing interannual variations of average vegetation cover throughout the entire Plateau. However, annual mean vegetation cover trends in the Qinghai-Tibet Plateau are mainly out of phase with air temperature increasing, which is primarily responsible for nonsynchro-nous changes of vegetation cover. In the southern ridge of the Qinghai-Tibet Plateau, recent warming trends contribute to humid weather and favorable conditions for vegetation growth. By contrast, higher temperatures have led to arid conditions and insufficient rainfall in the northern part of the Plateau, leading to drought and other climatic conditions which are not conducive to increased vegetation cover.

Vegetation cover trends along the Botswana Kalahari transect

Vegetative response aspects of climate change studies include the determination of vegetation cover changes across climatic gradients. Vegetation characteristics and soil moisture measurements were obtained from four locations with decreasing rainfall along the Botswana Kalahari transect. These are referred to as Pandamatenga, (698 mm year −1), Maun (460 mm year −1), Okwa (407 mm year −1) and Tshane (365 mm year −1). Trends in major vegetative cover and soil components included species types and richness assessments which reflected certain changes southward but also showed interesting degrees of variability. This occurred despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub–woodland vegetation cover. Despite linear decreases, both in rainfall and soil moisture content, results indicated high soil moisture variability at the Okwa location which relates to unique climatic and geological factors. Also many species are unique to specific locations for instance Pandametanga is characterized by Zambesian species while the Maun location is characterized by Colophosphermum mopane. This changes southwards as Acacias become more dominant and significantly co-occur with Grewia flava. While the average total numbers of plants decreased, total numbers of different species varied little from the wetter to the drier end of the moisture gradient. The association between rainfall and woody cover is negative implying that canopy cover extents (in terms of vegetation density) increase along the gradient due to increases in bush encroachment in drier areas. Therefore, while representing a continuum in terms of species numbers, in other respects (e.g. species types and ground cover components) vegetation zones in the Kalahari may be regarded as discontinuous units. Differences between mapped vegetation zones may be accounted for in terms of relatively unique ecosystem factors which function partly in response to geological conditions and partly in response to local (as opposed to regional) climatic factors. This appears to have led to ecosystem adaptive measures (in terms of species responses) rarely mirrored elsewhere along the gradient. Hence adaptability in terms of species migrations in response to relatively rapid climate changes may not readily take place over the Kalahari in Botswana.

Retrospective studies of grazing-induced land degradation: A case study in central Crete, Greece

Although it is well known that livestock husbandry has become more prevalent in Crete, Greece, during the last two decades, it is not well understood how grazing pressure differs spatially and how it influences grazed rangelands over time. To enhance the understanding of spatio-temporal degradation processes, a 20-year time series of Landsat Thematic Mapper and Multi-Spectral Scanner data is analysed. A set of vegetation fraction images is derived, based on a rigorous pre-processing scheme and linear spectral unmixing. Patterns of vegetation degradation, stability and regeneration are subsequently mapped by means of a trend analysis. It can be concluded that about 40% of the central Cretan rangelands show a declining trend in vegetation cover between 1977 and 1996. A deeper understanding of the underlying driving forces can be achieved through integrating remote sensing-derived information with other geoinformation sources. A comparison between local stress factors and vegetation development reveals that degradation processes are most evident when boundary conditions are favourable. It is, hence, assumed that increased grazing pressure is a major driving force for decreasing vegetation cover in the long term.

Monitoring land-cover changes in semi-arid regions: remote sensing data and field observations in the Ferlo, Senegal

Dryland degradation rarely translates into linear, declining trends in vegetation cover due to interannual climatic variability. Appropriate indicators of land-cover modifications need to be defined for semi-arid regions. Our hypothesis is that degradation can be measured by: (1) a decrease in the resilience of vegetation to droughts; (2) a decrease in rain-use efficiency; and (3) a modification of floristic composition. The objective of this paper is to test the relationships between a remotely sensed indicator of vegetation, rainfall data and field measurements of biomass and floristic composition. The study was based on field measurements of vegetation conditions covering a period of 10 years, in the semi-arid region of the Ferlo in Senegal. Our results indicate that land-cover modifications in the Ferlo are best measured by changes in rain-use efficiency. No consistent trend in the relative abundance of grass species was visible at the scale of the decade, even on the two sites affected by degradation. Just after a drought, a given increase in rainfall results in less biomass production than is the case for normal years.

The national biological information infrastructure

No abstract available.

The National Biological Information Infrastructure: Present and Future

~ding the vast amounts of biorlogical data related to the management, study, and use of biological resources cached in hundreds of databases around the world is difficult at best. According to the President's Council of Advisors on Science and Technology (PCAST), most of this information sits unused because of a lack of eftlcient means to retrieve and derive comprehensible information from it. A solution is in the midst of development: The National Biological Information Infrastructure, an initiative of the US Geological Survey's Biological Resources Division (BRD), will eventually allow researchers, land and natural resource managers, students, and the general public to locate these databases, query multiple databases simultaneously, and retrieve data. But NBIl is still far from achieving this goal, and the substantial funding needed to make biological data more accessible via NBIl comes from the same dwindling pool of money for research that generates those data. When NBIl is completed, users will be able to draw from any number of databases to assess biological and environmental processes and conditions. NBIl will also provide software to help users analyze these data. For example, a property owner or manager trying to maintain good habitat for wildlife could use NBIl to track long-term trends in vegetation cover and changes in animal and plant species diversity, composition, and abundance on the property. The property owner could also search for literature to determine possible causes of observed changes and to identify restoration measures. Initiated in 1994, NBIl is still in what its creators refer to as the first generation. Described by NBIl manager Anne Frondorf as a distributed electronic federation;' NBIl, in its cur-

Analysis of soil organic carbon and vegetation cover trends along the Botswana Kalahari Transect

Determination of trends in soil organic carbon (SOC) and vegetation cover along savanna ecosystem moisture gradients is critical to the understanding of ecosystem functioning and global change. Field results from 57 sites along the Botswana Kalahari Transect (BKT) showed general increases in both SOC and vegetation cover components along the temperature/moisture gradient. However, details in both SOC and woody cover trends revealed an area of relatively declining values in the central Kalahari. Image classification using TM single band data as input values confirmed the existence of an anomalously low woody cover area in the north-central Kalahari, within an area mapped as northern Kalahari tree and shrub savanna. It is postulated that the occurrence of such a zone of low shrubs in a gradient of otherwise increasing tree height and structural complexity may result mainly from edaphic factors, because of the co-incidence of near surface calcrete. However, the effects of fire and heavy grazing also influence the extent of low above-ground biomass, at least locally. Attempts were made to examine the extent to which soil organic carbon and vegetation components can be predicted using Thematic Mapper (TM) imagery, to increase potentially the number of sites in the BKT database. As a result of correlation and regression analyses, it was determined that the imagery-based SOC indexes of the literature were not useful in the Kalahari environment because of the extremely low SOC values encountered. Results of multiple regression analysis confirmed that woody vegetation cover could be predicted mainly through the use of TM3 single band radiance values throughout the BKT even during a non-drought period. Woody vegetation cover could be predicted to a lesser extent by the Transformed Normalised Vegetation Index. As high correlation coefficients were found between woody vegetation cover and SOC, the density of woody cover as derived from TM3 data may be taken as a surrogate for relative SOC abundance. Because this method is indirect, field checking will be required to verify results.