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Terms modified by NDVI

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  • Selected Abstracts

    Where do Swainson's hawks winter?

    Satellite images used to identify potential habitat
    ABSTRACT During recent years, predictive modelling techniques have been increasingly used to identify regional patterns of species spatial occurrence, to explore species,habitat relationships and to aid in biodiversity conservation. In the case of birds, predictive modelling has been mainly applied to the study of species with little variable interannual patterns of spatial occurrence (e.g. year-round resident species or migratory species in their breeding grounds showing territorial behaviour). We used predictive models to analyse the factors that determine broad-scale patterns of occurrence and abundance of wintering Swainson's hawks (Buteo swainsoni). This species has been the focus of field monitoring in its wintering ground in Argentina due to massive pesticide poisoning of thousands of individuals during the 1990s, but its unpredictable pattern of spatial distribution and the uncertainty about the current wintering area occupied by hawks led to discontinuing such field monitoring. Data on the presence and abundance of hawks were recorded in 30 × 30 km squares (n = 115) surveyed during three austral summers (2001,03). Sixteen land-use/land-cover, topography, and Normalized Difference Vegetation Index (NDVI) variables were used as predictors to build generalized additive models (GAMs). Both occurrence and abundance models showed a good predictive ability. Land use, altitude, and NDVI during spring previous to the arrival of hawks to wintering areas were good predictors of the distribution of Swainson's hawks in the Argentine pampas, but only land use and NDVI were entered into the model of abundance of the species in the region. The predictive cartography developed from the models allowed us to identify the current wintering area of Swainson's hawks in the Argentine pampas. The highest occurrence probability and relative abundances for the species were predicted for a broad area of south-eastern pampas that has been overlooked so far and where neither field research nor conservation efforts aiming to prevent massive mortalities has been established. [source]

    A Geostatistical Analysis of Soil, Vegetation, and Image Data Characterizing Land Surface Variation

    Sarah E. Rodgers
    The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites. [source]

    Debating the greening vs. browning of the North American boreal forest: differences between satellite datasets

    Abstract A number of remote sensing studies have evaluated the temporal trends of the normalized difference vegetation index (NDVI or vegetation greenness) in the North American boreal forest during the last two decades, often getting quite different results. To examine the effect that the use of different datasets might be having on the estimated trends, we compared the temporal trends of recently burned and unburned sites of boreal forest in central Canada calculated from two datasets: the Global Inventory, Monitoring, and Modeling Studies (GIMMS), which is the most commonly used 8 km dataset, and a new 1 km dataset developed by the Canadian Centre for Remote Sensing (CCRS). We compared the NDVI trends of both datasets along a fire severity gradient in order to evaluate the variance in regeneration rates. Temporal trends were calculated using the seasonal Mann,Kendall trend test, a rank-based, nonparametric test, which is robust against seasonality, nonnormality, heteroscedasticity, missing values, and serial dependence. The results showed contrasting NDVI trends between the CCRS and the GIMMS datasets. The CCRS dataset showed NDVI increases in all recently burned sites and in 50% of the unburned sites. Surprisingly, the GIMMS dataset did not capture the NDVI recovery in most burned sites and even showed NDVI declines in some burned sites one decade after fire. Between 50% and 75% of GIMMS pixels showed NDVI decreases in the unburned forest compared with <1% of CCRS pixels. Being the most broadly used dataset for monitoring ecosystem and carbon balance changes, the bias towards negative trends in the GIMMS dataset in the North American boreal forest has broad implications for the evaluation of vegetation and carbon dynamics in this region and globally. [source]

    Evaluating the impacts of climate and elevated carbon dioxide on tropical rainforests of the western Amazon basin using ecosystem models and satellite data

    Abstract Forest inventories from the intact rainforests of the Amazon indicate increasing rates of carbon gain over the past three decades. However, such estimates have been questioned because of the poor spatial representation of the sampling plots and the incomplete understanding of purported mechanisms behind the increases in biomass. Ecosystem models, when used in conjunction with satellite data, are useful in examining the carbon budgets in regions where the observations of carbon flows are sparse. The purpose of this study is to explain observed trends in normalized difference vegetation index (NDVI) using climate observations and ecosystem models of varying complexity in the western Amazon basin for the period of 1984,2002. We first investigated trends in NDVI and found a positive trend during the study period, but the positive trend in NDVI was observed only in the months from August to December. Then, trends in various climate parameters were calculated, and of the climate variables considered, only shortwave radiation was found to have a corresponding significant positive trend. To compare the impact of each climate component, as well as increasing carbon dioxide (CO2) concentrations, on evergreen forests in the Amazon, we ran three ecosystem models (CASA, Biome-BGC, and LPJ), and calculated monthly net primary production by changing a climate component selected from the available climate datasets. As expected, CO2 fertilization effects showed positive trends throughout the year and cannot explain the positive trend in NDVI, which was observed only for the months of August to December. Through these simulations, we demonstrated that the positive trend in shortwave radiation can explain the positive trend in NDVI observed for the period from August to December. We conclude that the positive trend in shortwave radiation is the most likely driver of the increasing trend in NDVI and the corresponding observed increases in forest biomass. [source]

    Are local weather, NDVI and NAO consistent determinants of red deer weight across three contrasting European countries?

    Abstract There are multiple paths via which environmental variation can impact herbivore ecology and this makes the identification of drivers challenging. Researchers have used diverse approaches to describe the association between environmental variation and ecology, including local weather, large-scale patterns of climate, and satellite imagery reflecting plant productivity and phenology. However, it is unclear to what extent it is possible to find a single measure that captures climatic effects over broad spatial scales. There may, in fact, be no a priori reason to expect populations of the same species living in different areas to respond in the same way to climate as their population may experience limiting factors at different times of the year, and the forms of regulation may differ among populations. Here, we examine whether the same environmental indices [seasonal Real Bioclimatic Index (RBI), seasonal Normalized Difference Vegetation Index (NDVI) and winter North Atlantic Oscillation (NAO)] influence body size in different populations of a large ungulate living in Mediterranean Spain, Western Scotland and Norway. We found substantial differences in the pattern of weight change over time in adult female red deer among study areas as well as different environmental drivers associated with variation in weight. The lack of general patterns for a given species at a continental scale suggest that detailed knowledge regarding the way climate affects local populations is often necessary to successfully predict climate impact. We caution against extrapolation of results from localized climate,population studies to broad spatial scales. [source]

    Postfire response of North American boreal forest net primary productivity analyzed with satellite observations

    Jeffrey A. Hicke
    Abstract Fire is a major disturbance in the boreal forest, and has been shown to release significant amounts of carbon (C) to the atmosphere through combustion. However, less is known about the effects on ecosystems following fire, which include reduced productivity and changes in decomposition in the decade immediately following the disturbance. In this study, we assessed the impact of fire on net primary productivity (NPP) in the North American boreal forest using a 17-year record of satellite NDVI observations at 8- km spatial resolution together with a light-use efficiency model. We identified 61 fire scars in the satellite observations using digitized fire burn perimeters from a database of large fires. We studied the postfire response of NPP by analyzing the most impacted pixel within each burned area. NPP decreased in the year following the fire by 60,260 g C m,2 yr,1 (30,80%). By comparing pre- and postfire observations, we estimated a mean NPP recovery period for boreal forests of about 9 years, with substantial variability among fires. We incorporated this behavior into a carbon cycle model simulation to demonstrate these effects on net ecosystem production. The disturbance resulted in a release of C to the atmosphere during the first 8 years, followed by a small, but long-lived, sink lasting 150 years. Postfire net emissions were three times as large as from a model run without changing NPP. However, only small differences in the C cycle occurred between runs after 8 years due to the rapid recovery of NPP. We conclude by discussing the effects of fire on the long-term continental trends in satellite NDVI observed across boreal North America during the 1980s and 1990s. [source]

    Human modification of the landscape and surface climate in the next fifty years

    R. S. Defries
    Abstract Human modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land-cover changes in response to demographic and economic activity. We use the land-cover scenario as a surface boundary condition in a biophysically-based land-surface model coupled to a general circulation model for a 15-years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land-cover change relative to the sensitivity to decadal-scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982,83) and high (1989,90) years to describe the seasonal phenology of the vegetation. In the past several centuries, large-scale land-cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land-cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land-cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land-cover change is generally within the range induced by decadal-scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics. [source]

    Land-use impact on ecosystem functioning in eastern Colorado, USA

    J. M. Paruelo
    Abstract Land-cover change associated with agriculture has had an enormous effect on the structure and functioning of temperate ecosystems. However, the empirical evidence for the impact of land use on ecosystem functioning at the regional scale is scarce. Most of our knowledge on land-use impact has been derived from simulation studies or from small plot experiments. In this article we studied the effects of land use on (i) the seasonal dynamics and (ii) the interannual variability of the Normalized Difference Vegetation Index (NDVI), a variable linearly related to the fraction of the photosynthetically active radiation (PAR) intercepted by the canopy. We also analysed the relative importance of environmental factors and land use on the spatial patterns of NDVI. We compared three cultivated land-cover types against native grasslands. The seasonal dynamics of NDVI was used as a descriptor of ecosystem functioning. In order to reduce the dimensionality of our data we analysed the annual integral (NDVI-I), the date of maximum NDVI (DMAX) and the quarterly average NDVI. These attributes were studied for 7 years and for 346 sites distributed across eastern Colorado (USA). Land use did modify ecosystem functioning at the regional level in eastern Colorado. The seasonal dynamics of NDVI, a surrogate for the fraction of PAR intercepted by the canopy, were significantly altered by agricultural practices. Land use modified both the NDVI integral and the seasonal dynamics of this spectral index. Despite the variability within land-cover categories, land use was the most important factor in explaining regional differences of the NDVI attributes analysed. Within the range of environmental conditions found in eastern Colorado, land use was more important than mean annual precipitation, mean annual temperature and soil texture in determining the seasonal dynamics of NDVI. [source]

    The greening and browning of Alaska based on 1982,2003 satellite data

    GLOBAL ECOLOGY, Issue 4 2008
    David Verbyla
    Abstract Aim To examine the trends of 1982,2003 satellite-derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982,2003 data set with 64-km2 pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100-km climate station buffers. The 1982,2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results, At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west-to-east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982,2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers. [source]

    Predicting and quantifying the structure of tropical dry forests in South Florida and the Neotropics using spaceborne imagery

    GLOBAL ECOLOGY, Issue 3 2006
    Thomas W. Gillespie
    ABSTRACT Aim, This research examines environmental theories and remote sensing methods that have been hypothesized to be associated with tropical dry forest structure. Location, Tropical dry forests of South Florida and the Neotropics. Methods, Field measurements of stand density, basal area and tree height were collected from 22 stands in South Florida and 30 stands in the Neotropics. In South Florida, field measurements were compared to climatic (temperature, precipitation, hurricane disturbance) and edaphic (rockiness, soil depth) variables, spectral indices (NDVI, IRI, MIRI) from Landsat 7 ETM+, and estimates of tree height from the Shuttle Radar Topography Mission (SRTM) and the National Elevation Dataset (NED). Environmental variables associated with tropical dry forest structure in South Florida were compared to tropical dry forest in other Neotropical sites. Results, There were significant correlations among temperature and precipitation, and stand density and tree height in South Florida. There were significant correlations between (i) stand density and mean NDVI and standard deviation of NDVI, (ii) MIRI and stand density, basal area and mean tree height, and (iii) estimates of tree height from SRTM with maximum tree height. In the Neotropics, there were no relationships between temperature or precipitation and tropical dry forest structure, however, Neotropical sites that experience hurricane disturbance had significantly shorter tree heights and higher stand densities. Main conclusions, It is possible to predict and quantify the forest structure characteristics of tropical dry forests using climatic data, Landsat 7 ETM+ imagery and SRTM data in South Florida. However, results based on climatic data are region-specific and not necessarily transferable between tropical dry forests at a continental spatial scale. Spectral indices from Landsat 7 ETM+ can be used to quantify forest structure characteristics, but SRTM data are currently not transferable to other regions. Hurricane disturbance has a significant impact on forest structure in the Neotropics. [source]

    Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

    GLOBAL ECOLOGY, Issue 5 2004
    José M. Paruelo
    ABSTRACT Aims, 1. To characterize ecosystem functioning by focusing on above-ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location, Western portion of the Patagonian steppes in Argentina (39°30, S to 45°27, S). Methods, We used remotely-sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM-derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results, PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions, Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely-sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification. [source]

    Use of multi-platform, multi-temporal remote-sensing data for calibration of a distributed hydrological model: an application in the Arno basin, Italy

    Lorenzo Campo
    Abstract Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS-2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring,summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat-ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd. [source]

    The North Atlantic Oscillation and European vegetation dynamics

    Célia Gouveia
    Abstract The relationship between vegetation greenness and the North Atlantic Oscillation (NAO) is assessed over Europe. The study covers the 21-year period from 1982 to 2002 and is based on monthly composites of the Normalised Difference Vegetation Index (NDVI) and Brightness Temperature from the Global Inventory Monitoring and Modelling System (GIMMS) as well as on monthly precipitation from the Global Precipitation Climatology Centre (GPCC). A systematic analysis is first performed of point correlation fields over the 21-year period between the winter NAO index and spring and summer NDVI, followed by an assessment of the vegetation response to precipitation and temperature conditions in winter, over two contrasting regions, namely the Iberian Peninsula and Northeastern Europe. Finally, the impact of NAO on vegetation dynamics over the two regions is evaluated by studying the corresponding annual cycles of NDVI and comparing their behaviour for years associated with opposite NAO phases. Over the Iberian Peninsula there is strong evidence that positive (negative) values of winter NAO induce low (high) vegetation activity in the following spring and summer seasons. This feature is mainly associated with the impact of NAO on winter precipitation, together with the strong dependence of spring and summer NDVI on water availability during the previous winter. Northeastern Europe shows a different behaviour, with positive (negative) values of winter NAO inducing high (low) values of NDVI in spring, but low (high) values of NDVI in summer. This behaviour mainly results from the strong impact of NAO on winter temperature, associated with the critical dependence of vegetation growth on the combined effect of warm conditions and water availability during the winter season. Copyright © 2008 Royal Meteorological Society [source]

    Global analyses of satellite-derived vegetation index related to climatological wetness and warmth

    Rikie Suzuki
    Abstract Wetness and warmth are the principal factors that control global vegetation distribution. This paper investigates climate,vegetation relationships at a global scale using the normalized difference vegetation index (NDVI), warmth index (WAI), and wetness index (WEI). The NDVI was derived from a global, 20-year Advanced Very High Resolution Radiometer (AVHRR) dataset with 4-min resolution. The WEI was defined as the ratio of precipitation to potential evaporation. The WAI was defined as the cumulative monthly mean temperature that exceeds 5 °C annually. Meteorological data from the International Satellite Land-Surface Climatology Project Initiative II (ISLSCP II) dataset were used to calculate the WEI and WAI. All analyses used annual values based on averages from 1986 to 1995 at 1 × 1 degree resolution over land. Relationships among NDVI, WEI, and WAI values were examined using a vegetation-climate diagram with the WEI and WAI as orthogonal coordinates. The diagram shows that large NDVI values correspond to areas of tropical and temperate forests and large WEI and WAI values. Small WEI and WAI values are associated with small NDVI values that correspond to desert and tundra, respectively. Two major regimes are revealed by the NDVI vegetation-climate diagram: wetness dominant and warmth dominant. Wetness dominates mid- and low latitudes. Warmth dominates high latitudes north of 60°N or elevated land such as the Tibetan Plateau. The boundary between the two regimes roughly corresponds to the vegetation boundary between taiga forest and southern vegetation. Over northern Eurasia, the boundary occurs in areas where the NDVI is large and the maximum monthly temperature is around 18 °C. Copyright © 2006 Royal Meteorological Society. [source]

    Spatial distribution and its seasonality of satellite-derived vegetation index (NDVI) and climate in Siberia

    Rikie Suzuki
    Abstract The Normalized Difference Vegetation Index (NDVI) distribution and its seasonal cycle were investigated in relation to temperature and precipitation over Siberia and its surrounding regions. The analyses used 5-year (1987,1991) monthly means. The monthly mean NDVI was calculated from the third-generation monthly Global Vegetation Index (GVI) product; monthly temperature and precipitation at 611 stations were calculated from Global Daily Summary (GDS) data. The 611 stations were classified by cluster analysis into 10 classes based on the NDVI seasonal cycle (March,October). The geographical distribution characteristics of the NDVI cycle were described using temperature, precipitation and Olson's land-cover type. In northern regions, where tundra vegetation prevails and temperatures and precipitation are low, the amplitude of the NDVI seasonal cycle is small. In southern regions, where temperatures are high and there is little precipitation, the seasonal amplitude of the NDVI is small because of the arid land type. Forested regions were split into six classes, each characterized by large amplitudes in the NDVI seasonal cycle. The phenological characteristics of the forest classes were noted. For example, a forest-class localized near Lake Baikal shows higher NDVI values, even with the presence of snow cover in March, compared with other regions. This high NDVI value suggests that the exposed green canopy of the coniferous forest can be observed even when snow is present. In addition, the NDVI peaks at stations near 60°N, where the maximum monthly temperature is around 18°C. This result suggests that the optimum temperature-precipitation environment coincides to the area in Siberia where the maximum monthly temperature is 18°C. Copyright © 2001 Royal Meteorological Society [source]

    Managing heterogeneity in elephant distribution: interactions between elephant population density and surface-water availability

    Summary 1Concerns over the ecological impacts of high African elephant Loxodonta africana densities suggest that it may be necessary to control their numbers locally, although the best management approach is still widely debated. Artificial water supply is believed to be a major cause of local overabundance, and could be used as a potential tool to regulate elephant distribution and impact across landscapes, but its effect on elephants at the population scale has never been studied. 2We assessed how dry-season surface-water availability constrained the distribution of an entire elephant population, using aerial and waterhole census data from Hwange National Park, Zimbabwe. The study was initiated in 1986, when the population was released from culling. We studied how artificial waterholes, holding water throughout the dry season, and vegetation production, estimated from a normalized difference vegetation index (NDVI), influenced the long-term distribution of elephant densities. We also investigated how the elephant distribution responded to changes in population density and annual rainfall, a driver of surface-water availability. 3Long-term dry-season elephant densities across the park tended to increase with vegetation production, and increased asymptotically with the density of artificial waterholes. 4Since the culling stopped, dry-season elephant densities have increased in most areas of the park, except in areas of low vegetation production and low water availability. Interannual fluctuations in elephant distribution are linked to rainfall variability through its effect on surface-water availability. During dry years elephants concentrated in areas where artificial pumping maintained surface-water availability during the dry season. 5During dry years elephant numbers at waterholes increased because of reduced surface-water availability, and elephants were distributed more evenly across waterholes, although active waterholes were unevenly distributed across the park. 6Synthesis and applications. Surface-water availability drives the distribution and abundance of elephants within Hwange National Park, and therefore appears to be at the heart of the trade-off between elephant conservation and the extent of their impact on ecosystems. Artificial manipulation of surface water is one of the tools available for the management of elephant populations and should not be overlooked when considering options for controlling elephant numbers in places where they are considered to be overabundant. [source]

    Predicting time-specific changes in demographic processes using remote-sensing data

    Summary 1Models of wildlife population dynamics are crucial for sustainable utilization and management strategies. Fluctuating ecological conditions are often key factors influencing both carrying capacity, mortality and reproductive rates in ungulates. To be reliable, demographic models should preferably rely on easily obtainable variables that are directly linked to the ecological processes regulating a population. 2We compared the explanatory power of rainfall, a commonly used proxy for variability in ecological conditions, with normalized differential vegetation index (NDVI), a remote-sensing index value that is a more direct measure of vegetation productivity, to predict time-specific conception rates of an elephant population in northern Kenya. Season-specific conception rates were correlated with both quality measures. However, generalized linear logistic models compared using Akaike's information criteria showed that a model based on the NDVI measure outperformed models based on rainfall measures. 3A predictive model based on coarse demographic data and the maximum seasonal NDVI value was able to trace the large variation in observed season-specific conception rates (Range 0,0·4), with a low median deviation from observed values of 0·07. 4By combining the model of season-specific conception rates with the average seasonal distribution of conception dates, the monthly number of conceptions (range 0,22) could be predicted within ±3 with 80% confidence. 5Synthesis and applications. The strong predictive power of the normalized differential vegetation index on time-specific variation in a demographic variable is likely to be generally applicable to resource-limited ungulate species occurring in ecologically variable ecosystems, and could potentially be a powerful factor in demographic population modelling. [source]

    Loop migration in adult marsh harriers Circus aeruginosus, as revealed by satellite telemetry

    Raymond H. G. Klaassen
    Loop migration among birds is characterized by the spring route lying consistently west or east of the autumn route. The existence of loops has been explained by general wind conditions or seasonal differences in habitat distribution. Loop migration has predominantly been studied at the population level, for example by analysing ring recoveries. Here we study loop migration of individual marsh harriers Circus aeruginosus tracked by satellite telemetry. We show that despite a generally narrow migration corridor the harriers travelled in a distinct clockwise loop through Africa and southern Europe, following more westerly routes in spring than in autumn. We used the Normalized Difference Vegetation Index (NDVI) to identify potential feeding habitat in Africa. Suitable habitat seemed always more abundant along the western route, both in spring and autumn, and no important stopover site was found along the eastern route. Observed routes did thus not coincide with seasonal variation in habitat availability. However, favourable habitat might be more important during spring migration, when the crossing of the Sahara seems more challenging, and thus habitat availability might play an indirect role in the harriers' route choice. Grid-based wind data were used to reconstruct general wind patterns, and in qualitative agreement with the observed loop marsh harriers predominantly encountered westerly winds in Europe and easterly winds in Africa, both in autumn and in spring. By correlating tail- and crosswinds with forward and perpendicular movement rates, respectively, we show that marsh harriers are partially drifted by wind. Thus, we tentatively conclude that wind rather than habitat seems to have an overriding effect on the shape of the migration routes of marsh harriers. General wind conditions seem to play an important role also in the evolution of narrow migratory loops as demonstrated for individual marsh harriers. [source]

    Patterns of density, diversity, and the distribution of migratory strategies in the Russian boreal forest avifauna

    Russell Greenberg
    Abstract Aim, Comparisons of the biotas in the Palaearctic and Nearctic have focused on limited portions of the two regions. The purpose of this study was to assess the geographic pattern in the abundance, species richness, and importance of different migration patterns of the boreal forest avifauna of Eurasia from Europe to East Asia as well as their relationship to climate and forest productivity. We further examine data from two widely separated sites in the New World to see how these conform to the patterns found in the Eurasian system. Location, Boreal forest sites in Russia and Canada. Methods, Point counts were conducted in two to four boreal forest habitats at each of 14 sites in the Russian boreal forest from near to the Finnish border to the Far East, as well as at two sites in boreal Canada. We examined the abundance and species richness of all birds, and specific migratory classes, against four gradients (climate, primary productivity, latitude, and longitude). We tested for spatial autocorrelation in both dependent and independent variables using Moran's I to develop spatial correlograms. For each migratory class we used maximum likelihood to fit models, first assuming uncorrelated residuals and then assuming spatially autocorrelated residuals. For models assuming unstructured residuals we again generated correlograms on model residuals to determine whether model fitting removed spatial autocorrelation. Models were compared using Akaike's information criterion, adjusted for small sample size. Results, Overall abundance was highest at the eastern and western extremes of the survey region and lowest at the continent centre, whereas the abundance of tropical and short-distance migrants displayed an east,west gradient, with tropical migrants increasing in abundance in the east (and south), and short-distance migrants in the west. Although overall species richness showed no geographic pattern, richness within migratory classes showed patterns weaker than, but similar to, their abundance patterns described above. Overall abundance was correlated with climate variables that relate to continentality. The abundances of birds within different migration strategies were correlated with a second climatic gradient , increasing precipitation from west to east. Models using descriptors of location generally had greater explanatory value for the abundance and species-richness response variables than did those based on climate data and the normalized difference vegetation index (NDVI). Main conclusions, The distribution patterns for migrant types were related to both climatic and locational variables, and thus the patterns could be explained by either climatic regime or the accessibility of winter habitats, both historically and currently. Non-boreal wintering habitat is more accessible from both the western and eastern ends than from the centre of the boreal forest belt, but the tropics are most accessible from the eastern end of the Palaearctic boreal zone, in terms of distance and the absence of geographical barriers. Based on comparisons with Canadian sites, we recommend that future comparative studies between Palaearctic and Nearctic faunas be focused more on Siberia and the Russian Far East, as well as on central and western Canada. [source]

    Breeding bird species richness in Taiwan: distribution on gradients of elevation, primary productivity and urbanization

    Pei-Fen Lee
    Abstract Aim, To examine the richness of breeding bird species in relation to elevation, primary productivity and urbanization. Location, The island of Taiwan (120°,122° E, 22°,25° N). Methods, We arranged bird species richness (BSR) data from 288 bird censuses undertaken in Taiwan into a 2 × 2 km quadrat system and calculated average values of elevation, primary productivity [surrogated by normalized difference vegetation index (NDVI)], and urbanization (surrogated by road density and percentage of built area) for each 2 × 2 km quadrat. Results, Bird species richness showed a hump-shaped relationship with elevation. It increased with elevation from sea level (10,64 species per 2 × 2 km quadrat), peaked around 2000 m (43,76 species), and then decreased with elevation towards its minimum at the highest elevation. Road density and percentage of built area decreased with elevation, and NDVI showed a hump-shaped relationship with elevation and inverse relationships with road density and percentage of built area. BSR increased with NDVI and decreased with road density and percentage of built area. Linear and cubic terms of elevation together explained 31.3% of the variance in BSR, and road density explained additional 3.4%. The explanatory power of NDVI on BSR was insignificant after the effects of elevation and road density had been justified. Main conclusions, We argue that urbanization plays an important role in the BSR of Taiwan. Urbanization might indirectly decrease BSR through decreasing primary productivity and therefore change the hypothetical inverse relationship between BSR and elevation into a hump-shaped relationship. We also propose a time hypothesis that the biotic communities in the mid-elevation zone of Taiwan had relatively longer periods of existence during the Pleistocene glacial cycles, which might be one underlying process of the observed hump-shaped relationship between species diversity and elevation. [source]

    Impact of climate variability on vegetative cover in the Butana area of Sudan

    Muna Elhag
    Abstract Climate variability has an impact on the renewable natural resources. This impact is strong in regions with a delicate balance between climate and ecosystem, like the Sahelian regions. Rainfall is the most important climatic factor influencing livelihoods in Butana, north-eastern part of Sudan. All people and their livestock depend on the amount of rainfall that falls and supports plant growth. Butana area experienced severe drought in 1984, 1990 and 2000. Linear relationships between the long-term rainfall and AVHRR/NDVI data were developed for four separate zones in the Butana area. There is a significant correlation between peak NDVI (beginning of September) and cumulative rainfall for July and August, but weak relationships resulted when annual rainfall and cumulative NDVI were used. This is because the NDVI reached a plateau as the rainfall increased, then it remained constant despite further increases in rainfall. The departure from the long-term average of NDVI for each pixel was calculated using the departure average vegetation method. The area had a high percentage of departure during the drought years and the NDVI recovered during the following year when the rainfall was above the average. It can be noted that the area adjacent to the irrigated scheme showed considerable decrease in NDVI. This may be due to overexploitation by the nomads during the drought year. [source]

    Climate variability and change over southern Africa: impacts and challenges

    Alec Sithole
    Abstract In this paper, the influence of climate variability and change on the environment was studied over southern Africa using ground-based and remotely sensed data. A time series analysis of rainfall and temperature anomalies indicated that there was a high rainfall and temperature variability in the region. The influence of global teleconnections on rainfall patterns over southern Africa showed that in some areas there was a spatial variation in their strength, increasing from west to east. Maps of NDVI, from 1982 to 2004, showed that changes in vegetation cover were more apparent during the dry season than during the wet season. The study also revealed that climate variability and change are linked to decreasing rainfall and hence, decreasing regional water resources and biodiversity and increasing environmental degradation. With the regional population expected increase, this depletion of resources poses the greatest regional environmental challenge to humankind. [source]

    Simulating the East African wildebeest migration patterns using GIS and remote sensing

    Douglas E. Musiega
    Abstract The Serengeti,Mara ecosystem in East Africa is a spectacular natural heritage endowed with diverse fauna and flora. The presence of the seasonally migrating wildebeest (Connochaetes taurinus) is a major boost for tourism. This migration however has enormous impacts to the ecosystem. Consequently efforts at monitoring the herd's migration trends and patterns remain a challenge to wildlife managers and ecologists in the region. In this paper, the relative influence of vegetation (normalized difference vegetation index), landscape and relief on herds migration routes are investigated and the migration routes simulated using GIS and remote sensing techniques. The results are compared with the annual mean route taken by the herds, as determined by radio tracking over the 1995,1997 period. Green vegetation availability is shown to be the major criterion in route choice. It is also shown that during the dry season phases of the migration (western trek, western corridor), the herd endures complex relief (complexity quantified based on slope and inter-visibility) in the search for greener grass. During the season of abundance (southern trek), relief becomes critical in making route choices, with herds avoiding difficult terrain, notwithstanding their relatively more abundant vegetation. The method proposed in this paper is viable for rapid prediction of approximate routes for the migrating wildebeest in different climatic conditions. Résumé L'écosystème Serengeti,Mara en Afrique Occidental est un patrimoine naturel spectaculaire, doté des divers variétés de flore et de faune. La présence du gnou migrateur (Connochaetes taurinus) représente un atout majeur pour le tourisme. Néanmoins, cette migration a un impact énorme sur l'écosystème. Par conséquence, la surveillance des tendances migratoires du troupeau est un défi constant pour les gérants et les écologistes dans la région. Dans cette enquête, l'influence relative de la végétation (NDVI), le paysage et le relief, sur les routes du migration prises par le troupeau ont étéétudiés, et simulés utilisant le Système d'Information Géographique (SIG) et des techniques de perception à distance. Les résultats sont comparés à la moyenne annuelle des routes prises par les troupeaux, déterminée par le repérage radio pendant la période allant de 1995 a 1997. Le disponibilité de végétation verte s'avère le déterminant majeur dans le choix du chemin. Il est aussi démontré que pendant les phases du migration en saison sèche (périple vers l'ouest, couloir vers l'ouest) le troupeau subit des reliefs complexes (complexité calculée sur la pente et inter visibilité) à la recherche de l'herbe la plus verte. Pendant la saison d'abondance (périple vers le sud), l'impact du relief sur le choix des routes devient critique, les troupeaux évitant le terrain difficile, malgré sa végétation relativement abondante. La méthode présentée dans cette étude permet de prédire de façon rapide et valable la route approximative des gnous en cours de migration dans des conditions climatiques diverses. [source]

    Leaf green-up in a semi-arid African savanna -separating tree and grass responses to environmental cues

    S. Archibald
    Abstract Question: Can satellite time series be used to identify tree and grass green-up dates in a semi-arid savanna system, and are there predictable environmental cues for green-up for each life form? Location: Acacia nigrescens /Combretum apiculatum savanna, Kruger National Park, South Africa (25° S, 31° E). Methods: Remotely-sensed data from the MODIS sensor were used to provide a five year record of greenness (NDVI) between 2000 and 2005. The seasonal and inter-annual patterns of leaf display of trees and grasses were described, using additional ecological information to separate the greening signal of each life form from the satellite time series. Linking this data to daily meteorological and soil moisture data allowed the cues responsible for leaf flush in trees and grasses to be identified and a predictive model of savanna leaf-out was developed. This was tested on a 22-year NDVI dataset from the Advanced Very High Resolution Radiometer. A day length cue for tree green-up predicted 86% of the green-ups with an accuracy better than one month. A soil moisture and day length cue for grass green-up predicted 73% of the green-ups with an accuracy better than a month, and 82% within 45 days. This accuracy could be improved if the temporal resolution of the satellite data was shortened from the current two weeks. Conclusions: The data show that at a landscape scale savanna trees have a less variable phenological cycle (within and between years) than grasses. Realistic biophysical models of savanna systems need to take this into account. Using climatic data to predict these dynamics is a feasible approach. [source]

    Remote sensing of protected areas to derive baseline vegetation functioning characteristics

    Martín F. Garbulsky
    Abstract: Question: How can we derive baseline/reference situations to evaluate the impact of global change on terrestrial ecosystem functioning? Location: Main biomes (steppes to rain forests) of Argentina. Methods: We used AVHRR/NOAA satellite data to characterize vegetation functioning. We used the seasonal dynamics of the Normalized Difference Vegetation Index (NDVI), a linear estimator of the fraction of the photosynthetic active radiation intercepted by vegetation (fPAR), and the surface temperature (Ts), for the period 1981,1993. We extracted the following indices: NDVI integral (NDVI -I), NDVI relative range (Rrel), NDVI maximum value (Vmax), date of maximum NDVI (Dmax) and actual evapotranspiration. Results: fPAR varied from 2 to 80%, in relation to changes in net primary production (NPP) from 83 to 1700 g.m- 2.yr -1. NDVI -I, Vmax and fPAR had positive, curvilinear relationships to mean annual precipitation (MAP), NPP was linearly related to MAP. Tropical and subtropical biomes had a significantly lower seasonality (Rrel) than temperate ones. Dmax was not correlated with the defined environmental gradients. Evapotranspiration ranged from 100 to 1100 mm.yr -1. Interannual variability of NDVI attributes varied across the temperature and precipitation gradients. Conclusions: Our results may be used to represent baseline conditions in evaluating the impact of land use changes across environmental gradients. The relationships between functional attributes and environmental variables provide a way to extrapolate ecological patterns from protected areas across modified habitats and to generate maps of ecosystem functioning. [source]

    The tick Ixodes ricinus: distribution and climate preferences in the western Palaearctic

    Abstract In this study, multivariate spatial clustering on monthly normalized difference vegetation index (NDVI) maps is used to classify ecological regions over the western Palaearctic. This classification is then used to delineate the distribution and climate preferences of populations (clades) of the tick Ixodes ricinus L. (Acari: Ixodidae) from a geographically extensive dataset of tick records and a gridded 2.5-km resolution climate dataset. Using monthly layers of the NDVI, regions of similar ecological attributes were defined and nine populations with significant differences in critical climate parameters (P < 0.005) were detected. Grouping of tick records according to other categories, such as political divisions, a 4°× 4° grid overlying the study area, or the CORINE) and USGS) vegetation classification schemes did not provided significantly separated populations (P= 0.094,0.304). Factor analysis and hierarchical tree clustering provided an ecological overview of these tick clades: two Mediterranean and one Scandinavian (western) clades are clearly separated from a node that includes clades of different parts of central Europe and the British Isles, with contrasting affinities between the different clades. The capture records of these ecologically separated clades produce a clear bias when bioclimate envelope modelling is applied to the mapping of habitat suitability for the tick in the western Palaearctic. The best-performing methods (Cohen's kappa = 0.834,0.912) use partial models developed with data from each ecoregion, which are then overlapped over the region of study. It is concluded that the use of ecologically derived ecoregions is an objective step in assessing the presence of ecologically different clades, and provides a guide in the development of data partitioning for habitat suitability modelling. [source]

    Modelling the distributions of Culicoides bluetongue virus vectors in Sicily in relation to satellite-derived climate variables

    B. V. Purse
    Abstract., Surveillance data from 268 sites in Sicily are used to develop climatic models for prediction of the distribution of the main European bluetongue virus (BTV) vector Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and of potential novel vectors, Culicoides pulicaris Linnaeus, Culicoides obsoletus group Meigen and Culicoides newsteadi Austen. The models containing the ,best' climatic predictors of distribution for each species, were selected from combinations of 40 temporally Fourier-processed remotely sensed variables and altitude at a 1 km spatial resolution using discriminant analysis. Kappa values of around 0.6 for all species models indicated substantial levels of agreement between model predictions and observed data. Whilst the distributions of C. obsoletus group and C. newsteadi were predicted by temperature variables, those of C. pulicaris and C. imicola were determined mainly by normalized difference vegetation index (NDVI), a variable correlated with soil moisture and vegetation biomass and productivity. These models were used to predict species presence in unsampled pixels across Italy and for C. imicola across Europe and North Africa. The predicted continuous presence of C. pulicaris along the appenine mountains, from north to south Italy, suggests BTV transmission may be possible in a large proportion of this region and that seasonal transhumance (seasonal movement of livestock between upland and lowland pastures) even in C. imicola -free areas should not generally be considered safe. The predicted distribution of C. imicola distribution shows substantial agreement with observed surveillance data from Greece and Iberia (including the Balearics) and parts of mainland Italy (Lazio, Tuscany and areas of the Ionian coast) but is generally much more restricted than the observed distribution (in Sardinia, Corsica and Morocco). The low number of presence sites for C. imicola in Sicily meant that only a restricted range of potential C. imicola habitats were included in the training set and that predictions could only be made within this range. Future modelling exercises will use abundance data collected according to a standardized protocol across the Mediterranean and, for Sicily in particular, should include non-climatic environmental variables that may influence breeding site suitability such as soil type. [source]

    Survival in a long-lived territorial migrant: effects of life-history traits and ecological conditions in wintering and breeding areas

    OIKOS, Issue 4 2009
    Juan M. Grande
    Despite its key role in population dynamics and evolutionary ecology, little is known about factors shaping survival in long-lived territorial species. Here, we assessed several hypotheses that might explain variability in survival in a migratory Spanish population of a long-lived territorial species, the Egyptian vulture Neophron percnopterus, using a 16-year monitoring period and live-encounter histories of 835 individually marked birds. Cormack-Jolly-Seber capture,recapture models showed no evidence for effects of sex or nestling body condition on survival. However, the normalized difference vegetation index (NDVI; an indicator of primary productivity) of natal territories had positive effects on juvenile survival, indicating that environmental conditions experienced early in life can determine survival prospects. Survival increased with age (0.73±0.02 in the first 2 years to 0.78±0.03 in years 3 and 4) to later decrease when birds were five years old (0.60±0.05), the age at which they acquire the adult plumage, abandon the communal lifestyle of juveniles, and may look for a breeding territory. At older ages, survival was higher for non-breeding (0.75±0.02) and breeding adults (0.83±0.02). Among the latter, birds that recruited into better territories had higher survival prospects. Age-specific variation in survival in this species may be related to behavioural changes linked to dispersal and recruitment into the breeding population, while survival prospects of adult birds strongly depend on breeding territory selection. These results suggest a tradeoff between recruiting soon, and thus reducing mortality costs of a long and extensive dispersal period, and trying to recruit into a good quality territory. Finally, annual survival rates for birds of all age classes were positively related with the NDVI in their African wintering grounds. Although this relationship was probably mediated by food availability, further research is needed to properly identify the limiting factors that are affecting trans-Saharan migrants, especially in light of global climate change. [source]

    Spatial analysis of solifluction landforms and process rates in the Abisko Mountains, northern Sweden

    Hanna Ridefelt
    Abstract The occurrence of turf-banked solifluction landforms in the Abisko region was analysed using a grid-based approach and statistical modelling through logistic regression. Significant parameters in the model were the vegetation index NDVI, annual incoming potential radiation, wetness index, slope gradient and elevation. The model had an acceptable discrimination capacity and rather low model-fit values, but clearly showed the importance of vegetation patterns for the occurrence of solifluction at a regional scale. Solifluction movement rates measured at eight sites were combined with model parameters and the annual duration of sun hours to regionalise solifluction movement rates through an unsupervised terrain classification. For comparison, the linear relationship between the probability of solifluction occurrence and variations in movement rates was also used to regionalise movement rates. Potential geomorphic work was calculated for six different areas within the region, with the greatest being for Kärkevagge, the area with the highest precipitation. The combination of a logistic regression model of mapped landforms and field measurements of solifluction rates represents a promising methodology to assess the occurrence and activity of the process at a regional scale. Copyright © 2010 John Wiley & Sons, Ltd. [source]

    Short-term propagation of rainfall perturbations on terrestrial ecosystems in central California

    Mónica García
    Abstract Question: Does vegetation buffer or amplify rainfall perturbations, and is it possible to forecast rainfall using mesoscale climatic signals? Location: Central California (USA). Methods: The risk of dry or wet rainfall events was evaluated using conditional probabilities of rainfall depending on El Niño Southern Oscillation (ENSO) events. The propagation of rainfall perturbations on vegetation was calculated using cross-correlations between monthly seasonally adjusted (SA) normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR), and SA antecedent rainfall at different time-scales. Results: In this region, El Niño events are associated with higher than normal winter precipitation (probability of 73%). Opposite but more predictable effects are found for La Niña events (89% probability of dry events). Chaparral and evergreen forests showed the longest persistence of rainfall effects (0-8 months). Grasslands and wetlands showed low persistence (0-2 months), with wetlands dominated by non-stationary patterns. Within the region, the NDVI spatial patterns associated with higher (lower) rainfall are homogeneous (heterogeneous), with the exception of evergreen forests. Conclusions: Knowledge of the time-scale of lagged effects of the non-seasonal component of rainfall on vegetation greenness, and the risk of winter rainfall anomalies lays the foundation for developing a forecasting model for vegetation greenness. Our results also suggest greater competitive advantage for perennial vegetation in response to potential rainfall increases in the region associated with climate change predictions, provided that the soil allows storing extra rainfall. [source]