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Cover Data (cover + data)
Kinds of Cover Data Selected AbstractsCan distribution models help refine inventory-based estimates of conservation priority?DIVERSITY AND DISTRIBUTIONS, Issue 4 2010A case study in the Eastern Arc forests of Tanzania, Kenya Abstract Aim, Data shortages mean that conservation priorities can be highly sensitive to historical patterns of exploration. Here, we investigate the potential of regionally focussed species distribution models to elucidate fine-scale patterns of richness, rarity and endemism. Location, Eastern Arc Mountains, Tanzania and Kenya. Methods, Generalized additive models and land cover data are used to estimate the distributions of 452 forest plant taxa (trees, lianas, shrubs and herbs). Presence records from a newly compiled database are regressed against environmental variables in a stepwise multimodel. Estimates of occurrence in forest patches are collated across target groups and analysed alongside inventory-based estimates of conservation priority. Results, Predicted richness is higher than observed richness, with the biggest disparities in regions that have had the least research. North Pare and Nguu in particular are predicted to be more important than the inventory data suggest. Environmental conditions in parts of Nguru could support as many range-restricted and endemic taxa as Uluguru, although realized niches are subject to unknown colonization histories. Concentrations of rare plants are especially high in the Usambaras, a pattern mediated in models by moisture indices, whilst overall richness is better explained by temperature gradients. Tree data dominate the botanical inventory; we find that priorities based on other growth forms might favour the mountains in a different order. Main conclusions, Distribution models can provide conservation planning with high-resolution estimates of richness in well-researched areas, and predictive estimates of conservation importance elsewhere. Spatial and taxonomic biases in the data are essential considerations, as is the spatial scale used for models. We caution that predictive estimates are most uncertain for the species of highest conservation concern, and advocate using models and targeted field assessments iteratively to refine our understanding of which areas should be prioritised for conservation. [source] The implications of data selection for regional erosion and sediment yield modellingEARTH SURFACE PROCESSES AND LANDFORMS, Issue 15 2009Joris de Vente Abstract Regional environmental models often require detailed data on topography, land cover, soil, and climate. Remote sensing derived data form an increasingly important source of information for these models. Yet, it is often not easy to decide what the most feasible source of information is and how different input data affect model outcomes. This paper compares the quality and performance of remote sensing derived data for regional soil erosion and sediment yield modelling with the WATEM-SEDEM model in south-east Spain. An ASTER-derived digital elevation model (DEM) was compared with the DEM obtained from the Shuttle Radar Topography Mission (SRTM), and land cover information from the CORINE database (CLC2000) was compared with classified ASTER satellite images. The SRTM DEM provided more accurate estimates of slope gradient and upslope drainage area than the ASTER DEM. The classified ASTER images provided a high accuracy (90%) land cover map, and due to its higher resolution, it showed a more fragmented landscape than the CORINE land cover data. Notwithstanding the differences in quality and level of detail, CORINE and ASTER land cover data in combination with the SRTM DEM or ASTER DEM allowed accurate predictions of sediment yield at the catchment scale. Although the absolute values of erosion and sediment deposition were different, the qualitative spatial pattern of the major sources and sinks of sediments was comparable, irrespective of the DEM and land cover data used. However, due to its lower accuracy, the quantitative spatial pattern of predictions with the ASTER DEM will be worse than with the SRTM DEM. Therefore, the SRTM DEM in combination with ASTER-derived land cover data presumably provide most accurate spatially distributed estimates of soil erosion and sediment yield. Nevertheless, model calibration is required for each data set and resolution and validation of the spatial pattern of predictions is urgently needed. Copyright © 2009 John Wiley & Sons, Ltd. [source] Ground beetle species (Coleoptera, Carabidae) associations with land cover variables in northern England and southern ScotlandECOGRAPHY, Issue 4 2004M. D. Eyre Distribution data concerning 172 ground beetle species derived from 1145 pitfall trap sites in northern England and southern Scotland were used to assess the relationship between species distribution and 12 satellite-derived land cover variables at the regional scale. A number of species were strongly associated with one cover type and negatively with others. The major variation was for preferences for covers in upland or lowland parts of the region. Other distinct preferences for some species were covers such as those at the coast whilst a number of common species showed no strong preference for any cover variable. The synthesis of ground beetle species distribution and satellite-derived cover data is discussed in relation to environmental assessment and change. [source] Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchmentsHYDROLOGICAL PROCESSES, Issue 4 2007J. Parajka Abstract We examine the value of additional information in multiple objective calibration in terms of model performance and parameter uncertainty. We calibrate and validate a semi-distributed conceptual catchment model for two 11-year periods in 320 Austrian catchments and test three approaches of parameter calibration: (a) traditional single objective calibration (SINGLE) on daily runoff; (b) multiple objective calibration (MULTI) using daily runoff and snow cover data; (c) multiple objective calibration (APRIORI) that incorporates an a priori expert guess about the parameter distribution as additional information to runoff and snow cover data. Results indicate that the MULTI approach performs slightly poorer than the SINGLE approach in terms of runoff simulations, but significantly better in terms of snow cover simulations. The APRIORI approach is essentially as good as the SINGLE approach in terms of runoff simulations but is slightly poorer than the MULTI approach in terms of snow cover simulations. An analysis of the parameter uncertainty indicates that the MULTI approach significantly decreases the uncertainty of the model parameters related to snow processes but does not decrease the uncertainty of other model parameters as compared to the SINGLE case. The APRIORI approach tends to decrease the uncertainty of all model parameters as compared to the SINGLE case. Copyright © 2006 John Wiley & Sons, Ltd. [source] Statistical characterization of the spatial variability of soil moisture in a cutover peatlandHYDROLOGICAL PROCESSES, Issue 1 2004Richard M. Petrone Abstract Soil moisture is a significant variable in its importance to the validation of hydrological models, but it is also the one defining variable that ties in all components of the surface energy balance and as such is of major importance to climate models and their surface schemes. Changing the scale of representation (e.g. from the observation to modelling scale) can further complicate the description of the spatial variability in any hydrological system. We examine this issue using soil moisture and vegetation cover data collected at two contrasting spatial scales and at three different times in the snow-free season from a cutover peat bog in Cacouna, Québec. Soil moisture was measured using Time Domain Reflectometry (TDR) over 90 000 m2 and 1200 m2 grids, at intervals of 30 and 2 m respectively. Analyses of statistical structure, variance and spatial autocorrelation were conducted on the soil moisture data at different sampling resolutions and over different grid sizes to determine the optimal spatial scale and sampling density at which these data should be represented. Increasing the scale of interest without adequate resolution in the measurement can lead to significant inconsistency in the representation of these variables. Furthermore, a lack of understanding of the nature of the variability of soil moisture at different scales may produce spurious representation in a modelling context. The analysis suggests that in terms of the distribution of soil moisture, the extent of sampling within a grid is not as significant as the density, or spacing, of the measurements. Both the scale and resolution of the sampling scheme have an impact on the mean of the distribution. Only approximately 60% of the spatial pattern in soil moisture of both the large and small grid is persistent over time, suggesting that the pattern of moisture differs for wetting and drying cycles. Copyright © 2003 John Wiley & Sons, Ltd. [source] Relationship between snow cover variability and Arctic oscillation index on a hierarchy of time scalesINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 2 2003A. S. Bamzai Abstract Based on satellite-derived global snow cover data on weekly time scales, the climatology and interannual variability of snow onset day-of-year, snowmelt day-of-year and number of snow-free days in a year are presented. Trends for snow onset day-of-year, snowmelt day-of-year and number of snow-free days in a year indicate that there has been an increase in number of snow-free days in recent decades. The relationship between snow cover and the Arctic oscillation (AO) index is examined on a hierarchy of time scales using lagged correlation and composite analysis. On weekly time scales, composite snow extent anomalies are maximum when AO leads snow cover by 1 week. These composite differences are maintained several weeks thereafter, particularly in the negative phase of the AO. Maps of composite snow cover anomalies when AO leads snow cover by 1 week delineate the spatial structure of these snow anomalies. On monthly time scales, lead,lag correlation between monthly snow cover and AO index indicates that the AO index during January, February and March is significantly correlated with snow cover in concurrent and subsequent spring months, particularly over Eurasia. Finally, on seasonal time scales, it is shown that winter season AO and winter/spring season snow cover are significantly correlated. Copyright © 2003 Royal Meteorological Society. [source] A new land-cover map of Africa for the year 2000JOURNAL OF BIOGEOGRAPHY, Issue 6 2004Philippe Mayaux Abstract Aim, In the framework of the Global Land Cover 2000 (GLC 2000), a land-cover map of Africa has been produced at a spatial resolution of 1 km using data from four sensors on-board four different Earth observing satellites. Location, The map documents the location and distribution of major vegetation types and non-vegetated land surface formations for the entire African continent plus Madagascar and the other surrounding islands. Methods, The bulk of these data were acquired on a daily basis throughout the year 2000 by the VEGETATION sensor on-board the SPOT-4 satellite. The map of vegetation cover has been produced based upon the spectral response and the temporal profile of the vegetation cover. Digital image processing and geographical information systems techniques were employed, together with local knowledge, high resolution imagery and expert consultation, to compile a cartographic map product. Radar data and thermal sensors were also used for specific land-cover classes. Results, A total of 27 land cover categories are documented, which has more thematic classes than previously published land cover maps of Africa contain. Systematic comparison with existing land cover data and 30-m resolution imagery from Landsat are presented, and the map is also compared with other pan-continental land cover maps. The map and digital data base are freely available for non-commercial uses from http://www.gvm.jrc.it/tem/africa/products.htm Main conclusions, The map improves our state of knowledge of the land-cover of Africa and presents the most spatially detailed view yet published at this scale. This first version of the map should provide an important input for regional stratification and planning purposes for natural resources, biodiversity and climate studies. Résumé Objet, Dans le cadre du projet Global Land Cover 2000 (GLC 2000), une carte d'Afrique d'occupation du sol a été produite à la résolution spatiale de 1 km à partir de données satellitales de 4 capteurs différents. Localisation, La carte représente la distribution des principaux types de végétation et des surfaces non-végétales du continent africain plus Madagascar et les autres îles voisines du continent. Méthodes, La plupart des données fut acquise durant l'année 2000 par le capteur VEGETATION, embarquéà bord du satellite SPOT-4. La réponse spectrale et le profil temporel des formations végétales ont permis la production de la carte d'occupation du sol. Des techniques de traitement d'image et de systèmes d'information géographique ont été combinées à la consultation d'experts locaux et à l'utilisation de cartes nationales et de données à haute résolution spatiale. Des images radar et thermiques ont servi à cartographier des classes spécifiques. Résultats, Un total de 27 classes est cartographié, ce qui est plus que les précédentes cartes basées sur l'imagerie satellitale. Une comparaison systématique avec les cartes publiées et des images Landsat à 30 m est présentée. Les données sont libres d'accès pour un usage non-commercial à l'adresse http://www.gvm.jrc.it/tem/africa/products.htm Conclusion, Cette carte accroît notre connaissance de l'occupation du sol de l'Afrique et présente la vue la plus détaillée jamais publiée à cette échelle. La première version de la carte devrait fournir une base importante pour une stratification régionale et pour la planification d'études sur les ressources naturelles, la biodiversité et le climat. [source] 16 Comparisons of macrophyte cover and community primary productivity on two southern california shoresJOURNAL OF PHYCOLOGY, Issue 2003A. M. Bullard Light-saturated net photosynthetic rates and cover of rocky intertidal macrophytes were determined between January and March 2003 at two southern California sites characterized by different macrophyte standing stocks. Overall macrophyte cover at Little Corona del Mar was low (75.4%) and was dominated by articulated corallines, and small, turf-forming crustose algae that provide little habitat structure. Macrophyte cover was higher at Dana Point (99.4%), where larger, frondose seaweeds were more abundant (34% vs < 5% cover). Our light-saturated photosynthetic rates for Little Corona del Mar and Dana Point macrophytes were similar to values for the same species obtained during the 1970s and 1980s. Highest photosynthetic rates were obtained for thinner, sheet-like, and branched, frondose seaweeds, while lowest rates were found for articulated coralline and crustose algae. We estimated the net community productivity of the two sites using photosynthetic rates (calculated as mg C m,2 · h,1) and percent cover data for the most abundant populations. We also compared our community productivity estimates for Little Corona del Mar and Dana Point with values for the same sites calculated using macrophyte cover values obtained during the mid-1970s. Re-sampling studies of these and other regional sites reveal that lower-producing, crustose and coralline algae have become increasingly abundant while the cover of higher-producing, frondose algae has declined on many southern California shores. Our studies at Little Corona del Mar and Dana Point, indicate that changing macrophyte abundances can have significant effects on the primary productivity of rocky intertidal communities. [source] WATERSHED WEIGHTING OF EXPORT COEFFICIENTS TO MAP CRITICAL PHOSPHOROUS LOADING AREAS,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 1 2003Theodore A. Endreny ABSTRACT: The Export Coefficient model (ECM) is capable of generating reasonable estimates of annual phosphorous loading simply from a watershed's land cover data and export coefficient values (ECVs). In its current form, the ECM assumes that ECVs are homogeneous within each land cover type, yet basic nutrient runoff and hydrological theory suggests that runoff rates have spatial patterns controlled by loading and filtering along the flow paths from the upslope contributing area and downslope dispersal area. Using a geographic information system (GIS) raster, or pixel, modeling format, these contributing area and dispersal area (CADA) controls were derived from the perspective of each individual watershed pixel to weight the otherwise homogeneous ECVs for phosphorous. Although the CADA-ECM predicts export coefficient spatial variation for a single land use type, the lumped basin load is unaffected by weighting. After CADA weighting, a map of the new ECVs addressed the three fundamental criteria for targeting critical pollutant loading areas: (1) the presence of the pollutant, (2) the likelihood for runoff to carry the pollutant offsite, and (3) the likelihood that buffers will trap nutrients prior to their runoff into the receiving water body. These spatially distributed maps of the most important pollutant management areas were used within New York's West Branch Delaware River watershed to demonstrate how the CADA-ECM could be applied in targeting phosphorous critical loading areas. [source] INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 4 2002Scott N. Miller ABSTRACT: Significant land cover changes have occurred in the watersheds that contribute runoff to the upper San Pedro River in Sonora, Mexico, and southeast Arizona. These changes, observed using a series of remotely sensed images taken in the 1970s, 1980s, and 1990s, have been implicated in the alteration of the basin hydrologic response. The Cannonsville subwatershed, located in the Catskill/Delaware watershed complex that delivers water to New York City, provides a contrast in land cover change. In this region, the Cannonsville watershed condition has improved over a comparable time period. A landscape assessment tool using a geographic information system (GIS) has been developed that automates the parameterization of the Soil and Water Assessment Tool (SWAT) and KINEmatic Runoff and EROSion (KINEROS) hydrologic models. The Automated Geospatial Watershed Assessment (AGWA) tool was used to prepare parameter input files for the Upper San Pedro Basin, a subwatershed within the San Pedro undergoing significant changes, and the Cannonsville watershed using historical land cover data. Runoff and sediment yield were simulated using these models. In the Cannonsville watershed, land cover change had a beneficial impact on modeled watershed response due to the transition from agriculture to forest land cover. Simulation results for the San Pedro indicate that increasing urban and agricultural areas and the simultaneous invasion of woody plants and decline of grasslands resulted in increased annual and event runoff volumes, flashier flood response, and decreased water quality due to sediment loading. These results demonstrate the usefulness of integrating remote sensing and distributed hydrologic models through the use of GIS for assessing watershed condition and the relative impacts of land cover transitions on hydrologic response. [source] Soil state and surface hydrology diagnosis based on MOSES in the Met Office Nimrod nowcasting systemMETEOROLOGICAL APPLICATIONS, Issue 2 2006R. N. B. Smith Abstract A system has been developed and made operational at the Met Office for the real-time diagnosis of soil state and surface hydrology. It is based on the Met Office Surface Exchanges Scheme (MOSES) modified to take account of unresolved soil and topographic heterogeneity when calculating surface runoff by incorporating a Probability Distributed Moisture (PDM) scheme developed by the Centre for Ecology and Hydrology. The implementation of MOSES-PDM in the Met Office's Nimrod nowcasting system is described. High resolution soil characteristics and land cover data, together with Nimrod's analyses of precipitation amount and type, cloud cover and near-surface atmospheric variables are used to drive MOSES-PDM. Hourly values of snowmelt, runoff, net surface radiation, evaporation, potential evaporation, soil temperature, soil moisture and soil moisture deficit are calculated on a 5 km grid. Copyright © 2006 Royal Meteorological Society. [source] Modelling the distribution of palsas in Finnish Lapland with logistic regression and GISPERMAFROST AND PERIGLACIAL PROCESSES, Issue 1 2002Miska Luoto Abstract The location of palsas (peat mounds with a perennially frozen core) was mapped in an area of 3370 km2 in Finnish Lapland by interpreting aerial digital photographs. Using environmental variables derived from digital land cover data and an elevation model, the distribution of palsas was modelled using geographic information system (GIS) techniques and multiple logistic regression. The relative roles of eight environmental variables potentially affecting the distribution of the palsas were studied in a spatial grid system with 3370 grid squares of 1.0 km2, of which 172 were found to contain palsas. The altitudes of the palsas varied from 180 m to 390 m. In the logistic regression model the probability of the presence of a palsa in a 1.0 km2 square increased with 1) the area of mire, 2) the proportion of flat topography, 3) water cover and 4) elevation of the lowest point in the 1.0 km2 analysis square. The palsa distribution model was validated by fitting it to an independent test area of 300 squares bordering on the main study area: the overall classification rate was 97.67%. The application of GIS data and techniques with logistic regression modelling has potential for wide use in studies on distribution patterns in periglacial processes and landforms. Copyright © 2002 John Wiley & Sons, Ltd. [source] Soil Nitrogen Pools Associated with Revegetation of Disturbed Sites in the Lake Tahoe AreaRESTORATION ECOLOGY, Issue 2 2002V. P. Claassen Abstract Thin, poorly developed soils in the high elevation, summer-dry environment near Lake Tahoe, California are easily disturbed by anthropogenic impacts. Subsoils and parent materials that are exposed by vegetation removal and topsoil erosion or by burial during construction activities are difficult to revegetate and may continue to erode for decades after disturbance. The resulting sediment loads contribute to decreased water quality in local watersheds and to the loss of clarity in Lake Tahoe. Field observations suggest that soil disturbance often results in depletion of soil nitrogen (N) reserves and that the remaining substrates may be unable to provide adequate N for revegetation. To quantify the levels of soil N that are associated with higher levels of percent plant cover on previously disturbed soils in the Lake Tahoe area, a basin-wide survey and a second paired site study were conducted. Results indicate that extractable ammonium and nitrate levels correlate poorly with percent vegetative cover, whereas the correlations of anaerobically mineralizable N and total N are stronger and account for nearly 50% of the variability in plant cover data. Sites with plant cover measuring greater than 40% are associated with total soil N levels of about 1,200 kg N/ha and anaerobic mineralizable N levels of about 26 kg N/ha. Despite high concentrations of N in the surface soils, a large fraction of the N in the 0- to 50-cm profile occurs below 30 cm, when measured on a landscape basis. [source] Land Transitions in the Tropics: Going Beyond the Case StudiesBIOTROPICA, Issue 1 2010María Uriarte ABSTRACT Estimates of the percent of Earth's land surface that has either been transformed or degraded by human activity range between 39 and 50 percent, with agriculture accounting for the vast majority of these changes. Although much of the focus of research on land use and cover change in the tropics has been on deforestation, ongoing socioeconomic changes both locally and globally have made land transitions in the tropics extremely fluid. In addition, feedbacks between land cover change and human behavior constrain the extent and trajectories of land transitions. The sustainability of land use systems in the tropics depends on an understanding of coupled human,natural systems that can lead to general frameworks for management and prediction. The unprecedented availability of land use/cover data together with ecological data collected at large spatial scales offer exciting opportunities for advancing our understanding of socioecological systems. We rely on six studies of land transitions in the tropics to illustrate some promising approaches and pose critical questions to guide this body of research. [source] | |||||||||||||||||||