应用遥感技术研究土地利用/土地覆盖变化及其对土壤侵蚀过程的影响--以印度北部Pali Gad山地流域为例

应用遥感技术评估了印度北部Pali Gad山地流域过去几十年里土地利用／土地覆盖变化及其造成的土壤侵蚀程度,并基于摩根参数模型（Morgan Parametric Model）的方法来测定土壤的侵蚀程度;结果表明,由于不同的坡向受到太阳光照的不同可以引起土地覆盖的变迁;海拔和坡度已不再是阻碍人们获取自然资源的因素,人们的活动范围正转移到更高的海拔和更陡峭的坡度;揭示了土地利用／土地覆盖变化对土壤侵蚀进程有着直接的影响。     

Multiple Methods in the Study of Driving Forces of Land Use and Land Cover Change: A Case Study of SE Kajiado District,Kenya

This landscape-scale study combines analysis of multitemporal satellite imagery spanning 30 years and information from field studies extending over 25 years to assess the extent and causes of land use and land cover change in the Loitokitok area, southeast Kajiado District, Kenya. Rain fed and irrigated agriculture, livestock herding, and wildlife and tourism have all experienced rapid change in their structure, extent, and interactions over the past 30 years in response to a variety of economic, cultural, political, institutional, and demographic processes. Land use patterns and processes are explored through a complementary application of interpretation of satellite imagery and case study analysis that explicitly addresses the local–national spatial scale over a time frame appropriate to the identification of fundamental causal processes. The results illustrate that this combination provides an effective basis for describing and explaining patterns of land use and land cover change and their root causes.     

Stories Remote Sensing Images Can Tell: Integrating Remote Sensing Analysis with Ethnographic Research in the Study of Cultural Landscapes

Although remote sensing techniques have become important methodologies in geographical studies, their quantitative tradition and empirical strength have discouraged their use in ethnographically based research of cultural landscapes. Using Uxin Ju of Inner Mongolia in China as a case study, this paper, adopting the approach of mixed methods, explores the integration of remote sensing techniques with ethnographic research in the study of cultural landscapes. In particular, it examines how remote sensing techniques, combined with ethnographic methods, can contribute to the study of cultural change and human perceptions as they relate to the landscape. Remote sensing analysis offers additional stories about changes in the landscape–stories not told by interviewees, or stories that supplement the account of interviewees. These stories provide important insights into cultural change and culture–landscape relationships. Through this case study, I argue that remote sensing techniques can greatly enhance ethnographic research in the study of cultural landscapes.     

Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Fire, People and Pixels: Linking Social Science and Remote Sensing to Understand Underlying Causes and Impacts of Fires in Indonesia

This study in the wake of 1990s fire catastrophes identifies and analyzes underlying causes of vegetation fires in eight locations across Borneo and Sumatra. Multidisciplinary and multiscale analysis integrates geospatial technologies with varied social research approaches and participatory mapping. It helps fill a void of site-specific evidence on diverse underlying causes of the Indonesian fires, despite emerging consensus on macrolevel causes and impacts, and policy debates on preventing future fire disasters. Our most important findings include confirmation of multiple direct and underlying fire causes at each of the eight locations, no single dominant fire cause at any site, and wide differences in fire causes among sites. Conclusions emphasize the importance of location specific studies within a regional analytical context. Our “hybrid” research methods demonstrate the explanatory power of integrating geospatial and social analysis techniques, and the benefits of analyzing fire causes and impacts at multiple scales in varied locations across diverse regions.     

Temporal Heterogeneity in the Study of African Land Use

This paper introduces a set of four collaborative papers exploring temporal heterogeneity in the analysis of African land use over a decadal time period, from 10 to 50 years, in the second half of the twentieth century. The four cases were chosen amongst the seven teams of anthropologists, human geographers and remote sensing specialists who had carried out long-term research and who met to discuss their findings at a workshop in 2003. All seven teams’ work and the collective discussion—on Casamance (Senegal), Brong Ahafo (Ghana), Southern Niger/Northern Cote d’Ivoire, Oyo State (Nigeria), Maasai Mara (Kenya and Tanzania), Gwembe (Zambia), and Malawi—inform this introduction. We identify several temporal processes in all the cases, each operating on its own temporal frame: population growth and, above all, mobility; livelihood change through crop and occupational change; tenure ambiguity; powerful though “punctuated” interventions by state policy; and climate change. Conceptual and methodological implications are disussed.

GIS and Remote Sensing for Detecting Yield Loss in Cranberry Culture

The primary goal of our research is to develop key elements of a precision agriculture program applicable to high-value woody perennial crops, such as cranberries. These crop systems exhibit tremendous variability in crop yields and quality as imposed by variations in soil properties (water availability and nutrient deficiency) that lead to crop stress (disease development and weed competition). Some of the variability present in the growing environment results in persistent yield losses as well as crop-quality reductions. We are using state-of-the-art methodologies (GIS, GPS, remote sensing) to identify and map spatial variations of the crop. Through image-processing methods (NDVI and unsupervised classification), approximately 65% of the variation in yield was described using 4-m multispectral satellite data as a base image.     

Land cover dynamics of different topographic conditions in Beijing,China

Topographic conditions play an important role in controlling land cover dynamic processes.In this study,remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing,a rapidly urbanized mega city in China.The study was based on five periods of land cover maps derived from remotely sensed data:Landsat MSS for 1978,Landsat TM for 1984,"1992,1996 and 2001,and the digital elevation model (DEM) derived from 1:250,000 topographic map.The whole area was divided into ten land cover types:conifer forest,broadleaf forest,mixed forest,shrub,brushwood,meadow,farmland,built-up,water body and bare land.The results are summarized as follows.(1) Shrub,forest,farmland and builtup consist of the main land cover types of the Beijing area.The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area.Farmland decreased from 6354 to 3813 km2 in the 23 years,while the built-up area increased from 421 to 2642 km2.Meanwhile,the coverage of forest increased from 17.2% to 24.7% of the total area.The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest.(2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes.Elevation has an intensive impact on the distribution of land cover types.The area below 100 m mostly consists of farmland and built-up areas,while the area above 100 m is mainly covered by shrub and forest.Shrub has the maximum frequency in areas between 100 and 1000 m,while forest has dominance in areas above 800 m.According to the analysis of land cover changes in different ranges of elevation,the greatest change below 100 m was the process of urbanization.The process of the main land cover change occurred above 100 m was the transformation from shrub to forest.This result was consistent with the vertical change of natural vegetation distribution in Beijing.(3) Slope has a great influence on the distribution of land cover.Farmland and built-up areas are mostly distributed in fiat areas,while shrub and forest occupy steeper areas compared with other land cover types.Forest frequency increased with the increasing slope.Land cover changes differed from the slope gradients.In the plain area,the land cover change occurred as the result of urbanization.With the increasing of the slope gradient,afforestation,which converts shrub to forest,was the process of the primary land cover change.     

云南澜沧江流域土地利用和覆盖变化

由人类活动引起的土地利用和地被覆盖的变化是地球上环境变化的主要原因。上世纪90年代是云南省经济发展和环境变化的活跃时期。本文通过现代卫星遥感技术、地理信息系统和其它多学科手段相结合 ,系统调查评估了云南澜沧江流域 1990年至 1998年间土地利用和地被覆盖的变化 ,结果显示流域中林业用地面积从 1990年的 6 4 9%增长到 1998年的6 6 4 % ,但是森林有林地 (郁闭度 >30 %的天然林和人工林 )从 1990年的 5 2 6 %减少到 1998年的 35 3%。并且分析大规模商业性森林砍伐、基础建设、经济作物的种植、刀耕火种、薪材过度采集和砍伐建筑用材等引起了森林的结构的显著变化和退化 ,从而导致了生物多样性的下降。     

Land cover dynamics of different topographic conditions in Beijing, China

Topographic conditions play an important role in controlling land cover dynamic processes. In this study, remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing, a rapidly urbanized mega city in China. The study was based on five periods of land cover maps derived from remotely sensed data: Landsat MSS for 1978, Landsat TM for 1984, 1992, 1996 and 2001, and the digital elevation model (DEM) derived from 1:250,000 topographic map. The whole area was divided into ten land cover types: conifer forest, broadleaf forest, mixed forest, shrub, brushwood, meadow, farmland, built-up, water body and bare land. The results are summarized as follows. (1) Shrub, forest, farmland and builtup consist of the main land cover types of the Beijing area. The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area. Farmland decreased from 6354 to 3813 km2 in the 23 years, while the built-up area increased from 421 to 2642 km2. Meanwhile, the coverage of forest increased from 17.2% to 24.7% of the total area. The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest. (2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes. Elevation has an intensive impact on the distribution of land cover types. The area below 100 m mostly consists of farmland and built-up areas, while the area above 100 m is mainly covered by shrub and forest. Shrub has the maximum frequency in areas between 100 and 1000 m, while forest has dominance in areas above 800 m. According to the analysis of land cover changes in different ranges of elevation, the greatest change below 100 m was the process of urbanization. The process of the main land cover change occurred above 100 m was the transformation from shrub to forest. This result was consistent with the vertical change of natural vegetation distribution in Beijing. (3) Slope has a great influence on the distribution of land cover. Farmland and built-up areas are mostly distributed in flat areas, while shrub and forest occupy steeper areas compared with other land cover types. Forest frequency increased with the increasing slope. Land cover changes differed from the slope gradients. In the plain area, the land cover change occurred as the result of urbanization. With the increasing of the slope gradient, afforestation, which converts shrub to forest, was the process of the primary land cover change. __________ Translated from Journal of Plant Ecology, 2006, 30(2): 239–251 [译自: 植物生态学报]     

Identifying and quantifying uncertainty and spatial disagreement in the comparison of Global Land Cover for different applications

This paper provides a methodology for comparing global land cover maps that allows for differences in legend definitions between products to be taken into account. The legends of the two maps are first reconciled by creating a legend lookup table that shows how the legends map onto one another. Where there is overlap, the specific definitions for each legend class are used to calculate the degree of overlap between legend classes. In this way, one‐to‐many mappings are accounted for unlike in most methods where the legend definitions are often forced into place. Another advantage over previous map comparison methods is that application‐specific requirements are captured using expert input, whereby the user rates the importance of disagreement between different legend classes based on the needs of the application. This user‐defined matrix in conjunction with the degree of overlap between legend classes is applied on a pixel‐by‐pixel basis to create maps of spatial disagreement and uncertainty. The user can then highlight the areas of highest thematic uncertainty and disagreement between the different land cover maps allowing for areas that require further detailed examination to be readily identified. It would also be possible for several users to input their knowledge into the process, leading to a potentially more robust comparison of land cover products. The methodology of map comparison is illustrated using different land cover products including Global Land Cover 2000 (GLC‐2000) and the MODIS land cover data set. Two diverse applications are provided including the estimation of global forest cover and monitoring of agricultural land. In the case of global forest cover, an example was provided for Columbia, which showed that the MODIS land cover map overestimates forest cover in comparison with the GLC‐2000. The agricultural example, on the other hand, served to illustrate that for Sudan, MODIS tends to underestimate crop areas while GLC‐2000 overestimates them.     

Land use change in the Amazon estuary: Patterns of caboclo settlement and landscape management

Landsat TM scenes for 1985 and 1991 are used to produce a georeferenced map of land cover and land use for an area of the Amazon estuary inhabited by three populations of caboclos with distinct patterns of land use. This information is combined in a geographic information system with ethnographic and survey research carried out over the past 5 years to develop representative spectral signatures which permit measurement and differentiation of land uses and the detection of change even between small areas of managed floodplain forest and unmanaged forest, and between three distinct age/growth classes of secondary succession following deforestation. Implementation of these procedures permit the scaling up or down of research at different resolutions. Three distinct patterns of land use are examined with differential impact on the environment. Mechanized agriculture at one site has eliminated virtually all the mature upland forest and is now dominated by secondary successional vegetation. The more traditional system of diversified land use at the next site shows a subtle cycling of flooded forest to managed palm forest through time in response to the price of palm fruit and cycling in the use of fallow land. A third site, based on palm fruit extractivism, shows minimal changes in land cover due to persistent specialization on management of flooded forest extraction. There is little evidence that the community with the greatest impact on forest cover is any better off economically than the two communities which have minimal impact on the landscape. This study suggests how a balance between use and conservation in Amazonia may be achieved in floodplain and estuarine areas, and the effectiveness of monitoring these types of land cover from satellite platforms.     

Land Use and Land Cover Change Dynamics across the Brazilian Amazon: Insights from Extensive Time-Series Analysis of Remote Sensing Data

Throughout the Amazon region, the age of forests regenerating on previously deforested land is determined, in part, by the periods of active land use prior to abandonment and the frequency of reclearance of regrowth, both of which can be quantified by comparing time-series of Landsat sensor data. Using these time-series of near annual data from 1973–2011 for an area north of Manaus (in Amazonas state), from 1984–2010 for south of Santarém (Pará state) and 1984–2011 near Machadinho d’Oeste (Rondônia state), the changes in the area of primary forest, non-forest and secondary forest were documented from which the age of regenerating forests, periods of active land use and the frequency of forest reclearance were derived. At Manaus, and at the end of the time-series, over 50% of regenerating forests were older than 16 years, whilst at Santarém and Machadinho d’Oeste, 57% and 41% of forests respectively were aged 6–15 years, with the remainder being mostly younger forests. These differences were attributed to the time since deforestation commenced but also the greater frequencies of reclearance of forests at the latter two sites with short periods of use in the intervening periods. The majority of clearance for agriculture was also found outside of protected areas. The study suggested that a) the history of clearance and land use should be taken into account when protecting deforested land for the purpose of restoring both tree species diversity and biomass through natural regeneration and b) a greater proportion of the forested landscape should be placed under protection, including areas of regrowth.     

Land cover change and land degradation in parts of the southwest coast of Nigeria

Frequent alteration in land cover often leads to decreased stability of ecosystems which can also increase the vulnerability of rural communities to externalities of environmental change. This study carried out in parts of the coast of southwestern Nigeria utilized topographic base maps and two-time Landsat TM imageries to assess the trend in land cover changes and ecosystems degradation for the three time periods 1965, 1986 and 2001. Remote sensing, geographic information systems and landscape pattern analysis were employed for data processing and analysis. The focus of the analysis was on land cover change, land degradation, and changes in landscape pattern resulting from interplay of natural and anthropogenic drivers.
The results show increased trend in human-induced land cover change with concomitant severe negative impacts on ecosystems and livelihoods. About 98,000ha (30% of the area) was seriously degraded as at 2001. About 33,000ha (10%) was under permanent saline water inundation with about 21 communities already dislocated. Loss of fragile ecosystems including marshland (from 7.7% in 1965 to 1% in 2001) and mangrove (from 14.6% in 1965 to 3.1% in 2001) was intense, while over 300 ponds/small lakes which are important for the local fishing economy have disappeared. About eighteen communities were also dislocated by erosion in a section around the southeastern parts of the coastline. Landscape metrics generated, suggested increased ecosystems perturbation and landscape fragmentation. The paper also discussed the implications of these rapid changes for ecosystems stability, food security and sustainable rural livelihoods in the area.     

Remote sensing imagery for resource inventories in central Africa: The importance of detailed field data

The rate of rain forest clearing throughout central Africa is of national and international interest because it affects both the region's contribution to global warming and impacts the sustainable productive capacity of its natural resource base. The size and inaccessibility of much of central Africa makes remote sensing imagery the most suitable data source for regional land cover mapping and land transformation monitoring. Present image availability is poor. Most regional studies have had to rely on coarse resolution AVHRR 1 km data that fails to detect the small-scale agricultural clearings that are the primary cause of land cover change throughout the region. This study demonstrates that higher spatial resolution Landsat MSS imagery, which comprises the most available, geographically comprehensive and longest time series dataset, is too coarse to map land cover in low population density areas typical of most of central Africa. Furthermore, this study cautions that the use of high resolution imagery without detailed collateral field data on population density and land use practices while generating superficially plausible results, will most probably produce highly inaccurate estimates of land cover and land transformation. Policies for future regional remote sensing surveys of central Africa should focus on acquisition of higher spatial, spectral, and radiometric resolution imagery and must be accompanied by detailed, systematic field data collection.     

Seasonal Variation in Aboveground Production and Radiation-use Efficiency of Temperate rangelands Estimated through Remote Sensing

Aboveground net primary production (ANPP) of grasslands varies spatially and temporally. Spectral information provided by remote sensors is a promising new tool that may be able to estimate ANPP in real time and at low cost. The objectives of this study were (a) to evaluate at a seasonal scale the relationship between ANPP and the normalized difference vegetation index (NDVI), (b) to estimate seasonal variations in the coefficient of conversion of absorbed radiation into aboveground biomass (ε_a), and (c) to identify the environmental controls on such temporal changes. We used biomass-based field determinations of ANPP for two grassland sites in the Flooding Pampa, Argentina, and related them with NDVI data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR) satellites using three different models. Results were compared with data obtained from the new Moderate Resolution Imaging Spectroradiometer (MODIS) sensor at an additional site. The first model was based solely on NDVI; the second was based on the amount of photosynthetically active radiation absorbed by the green vegetation (APAR_g), which was derived from NDVI and incoming photosynthetically active radiation (PAR); the third was based on APAR_g and ε_a, which was in turn estimated from climatic variables. NDVI explained between 63 and 93% of ANPP variation, depending on the site considered. Estimates of ANPP were not improved by considering the variation in incoming PAR. At both sites, ε_a varied seasonally (from 0.2 to 1.2 g DM/MJ) and was significantly associated with combinations of precipitation and temperature. Combining ε_a variations with APAR_g increased our ability to account for seasonal ANPP variations at both sites. Our results indicate that NDVI produces good, direct estimates of ANPP only if NDVI, PAR, and ε_a are correlated throughout the seasons. Thus, in most cases, seasonal variations of ε_a associated with temperature and precipitation must be taken into account to generate seasonal ANPP estimates with acceptable accuracy.     

Effects of Land Cover on Stream Ecosystems: Roles of Empirical Models and Scaling Issues

We built empirical models to estimate the effects of land cover on stream ecosystems in the mid-Atlantic region (USA) and to evaluate the spatial scales over which such models are most effective. Predictive variables included land cover in the watershed, in the streamside corridor, and near the study site, and the number and location of dams and point sources in the watershed. Response variables were annual nitrate flux; species richness of fish, benthic macroinvertebrates, and aquatic plants; and cover of aquatic plants and riparian vegetation. All data were taken from publicly available databases, mostly over the Internet. Land cover was significantly correlated with all ecological response variables. Modeled R² ranged from 0.07 to 0.5, but large data sets often allowed us to estimate with acceptable precision the regression coefficients that express the change in ecological conditions associated with a unit change in land cover. Dam- and point-source variables were ineffective at predicting ecological conditions in streams and rivers, probably because of inadequacies in the data sets. The spatial perspective (whole watershed, streamside corridor, or local) most effective at predicting ecological response variables varied across response variables, apparently in concord with the mechanisms that control each of these variables. We found some evidence that predictive power fell in very small watersheds (less than 1–10 km²), suggesting that the spatial arrangement of landscape patches may become critical at these small scales. Empirical models can replace, constrain, or be combined with more mechanistic models to understand the effects of land-cover change on stream ecosystems. Present address for L.C. Thompson: Wildlife, Fish and Conservation Biology Department, University of California, Davis, CA 95616.     

Assessing fragmentation and disturbance of west Kenyan rainforests by means of remotely sensed time series data and landscape metrics

Biodiversity in tropical rainforests is heavily influenced by land use/cover change (LUCC), but so far there have been few LUCC studies conducted in Africa. We present several methods that make use of remotely sensed data and landscape metrics and allow for assessment of the development of land cover and thus forest fragmentation and disturbance over a substantial period of time. The study covers Kakamega Forest and its associated forest areas in western Kenya, over the last 30 years. The accuracy of a supervised multispectral classification of Landsat time series data encompassing seven time steps between 1972 and 2001 is numerically assessed using ground truth reference data considering the 2001 time step. Here, buffering the forest areas by 1 km, highest user's accuracies for the forest classes ‘near natural + old secondary forest’ (87.50%), ‘secondary forest’ (80.00%) and ‘bushland/shrubs’ (81.08%) are revealed. Images of a spatially distributed fragmentation index derived from the land cover time series by applying a three by 3 pixel‐sized moving window to determine forest pixels’ adjacency, highlight trends in forest fragmentation, e.g. the splitting into two separate forests along the Yala/Ikuywa corridor. Calculations of mean fragmentation indices for the Biodiversity Monitoring Transect Analysis in Eastern Africa (BIOTA‐East Africa) focus research areas are used to evaluate the fragmentation index and to demonstrate its potential to extrapolate (e.g. biological) field findings in space and time. Here we argue for a correlation of the fragmentation indices results not only with forest management regimes, but with population distribution and accessibility (e.g. by roads). A cluster analysis applying the isodata‐algorithm on the classification results of all seven times steps allows for a rapid visual assessment of the distinct pattern of typical land cover development trends since 1972. This reveals that parts of Kakamega Forest have experienced severe forest loss while others, especially in the north‐east, show signs of succession.     

Comparison of phenology trends by land cover class: a case study in the Great Basin, USA

Direct impacts of human land use and indirect impacts of anthropogenic climate change may alter land cover and associated ecosystem function, affecting ecological goods and services. Considerable work has been done to identify long‐term global trends in vegetation greenness, which is associated with primary productivity, using remote sensing. Trend analysis of satellite observations is subject to error, and ecosystem change can be confused with interannual variability. However, the relative trends of land cover classes may hold clues about differential ecosystem response to environmental forcing. Our aim was to identify phenological variability and 10‐year trends for the major land cover classes in the Great Basin. This case study involved two steps: a regional, phenology‐based land cover classification and an identification of phenological variability and 10‐year trends stratified by land cover class. The analysis used a 10‐year time series of Advanced Very High Resolution Radiometer satellite data to assess regional scale land cover variability and identify change. The phenology‐based regional classification was more detailed and accurate than national or global products. Phenological variability over the 10‐year period was high, with substantial shifts in timing of start of season of up to 9 weeks. The mean long‐term trends of montane land cover classes were significantly different from valley land cover classes due to a poor response of montane shrubland and pinyon‐juniper woodland to the early 1990s drought. The differential response during the 1990s suggests that valley ecosystems may be more resilient and montane ecosystems more susceptible to prolonged drought. This type of regional‐scale land cover analysis is necessary to characterize current patterns of land cover phenology, distinguish between anthropogenically driven land cover change and interannual variability, and identify ecosystems potentially susceptible to regional and global change.