37 resultados para Land cover change


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The paper presents first results of a pan-boreal scale land cover harmonization and classification. A methodology is presented that combines global and regional vegetation datasets to extract percentage cover information for different vegetation physiognomy and barren for the pan-arctic region within the ESA Data User Element Permafrost. Based on the legend description of each land cover product the datasets are harmonized into four LCCS (Land Cover Classification System) classifiers which are linked to the MODIS Vegetation Continuous Field (VCF) product. Harmonized land cover and Vegetation Continuous Fields products are combined to derive a best estimate of percentage cover information for trees, shrubs, herbaceous and barren areas for Russia. Future work will concentrate on the expansion of the developed methodology to the pan-arctic scale. Since the vegetation builds an isolation layer, which protects the permafrost from heat and cold temperatures, a degradation of this layer due to fire strongly influences the frozen conditions in the soil. Fire is an important disturbance factor which affects vast processes and dynamics in ecosystems (e.g. biomass, biodiversity, hydrology, etc.). Especially in North Eurasia the fire occupancy has dramatically increased in the last 50 years and has doubled in the 1990s with respect to the last five decades. A comparison of global and regional fire products has shown discrepancies between the amounts of burn scars detected by different algorithms and satellite data.

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The overarching goal of the Yamal portion of the Greening of the Arctic project is to examine how the terrain and anthropogenic factors of reindeer herding and resource development combined with the climate variations on the Yamal Peninsula affect the spatial and temporal patterns of vegetation change and how these changes are in turn affecting traditional herding of the indigenous people of the region. The purpose of the expeditions was to collect groundobservations in support of remote sensing studies at four locations along a transect that traverses all the major bioclimate subzones of the Yamal Peninsula. This data report is a summary of information collected during the 2007 and 2008 expeditions. It includes all the information from the 2008 data report (Walker et al. 2008) plus new information collected at Kharasavey in Aug 2008. The locations included in this report are Nadym (northern taiga subzone), Laborovaya (southern tundra = subzone E of the Circumpolar Arctic Vegetation Map (CAVM), Vaskiny Dachi (southern typical tundra = subzone D), and Kharasavey (northern typical tundra = subzone C). Another expedition is planned for summer 2009 to the northernmost site at Belyy Ostrov (Arctic tundra = subzone B). Data are reported from 10 study sites - 2 at Nadym, 2 at Laborovaya, and 3 at Vaskiny Dachi and 3 at Kharasavey. The sites are representative of the zonal soils and vegetation, but also include variation related to substrate (clayey vs. sandy soils). Most of the information was collected along 5 transects at each sample site, 5 permanent vegetation study plots, and 1-2 soil pits at each site. The expedition also established soil and permafrost monitoring sites at each location. This data report includes: (1) background for the project, (2) general descriptions and photographs of each locality and sample site, (3) maps of the sites, study plots, and transects at each location, (4) summary of sampling methods used, (5) tabular summaries of the vegetation data (species lists, estimates of cover abundance for each species within vegetation plots, measured percent ground cover of species along transects, site factors for each study plot), (6) summaries of the Normalized Difference Vegetation Index (NDVI) and leaf area index (LAI) along each transect, (7) soil descriptions and photos of the soil pits at each study site, (8) summaries of thaw measurements along each transect, and (9) contact information for each of the participants. One of the primary objectives was to provide the Russian partners with full documentation of the methods so that Russian observers in future years could repeat the observations independently.

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This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).

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Soil degradation threatens agricultural production and food security in Sub-Saharan Africa. In the coming decades, soil degradation, in particular soil erosion, will become worse through the expansion of agriculture into savannah and forest and changes in climate. This study aims to improve the understanding of how land use and climate change affect the hydrological cycle and soil erosion rates at the catchment scale. We used the semi-distributed, time-continuous erosion model SWAT (Soil Water Assessment Tool) to quantify runoff processes and sheet and rill erosion in the Upper Ouémé River catchment (14500 km**2, Central Benin) for the period 1998-2005. We could then evaluate a range of land use and climate change scenarios with the SWAT model for the period 2001-2050 using spatial data from the land use model CLUE-S and the regional climate model REMO. Field investigations were performed to parameterise a soil map, to measure suspended sediment concentrations for model calibration and validation and to characterise erosion forms, degraded agricultural fields and soil conservation practices. Modelling results reveal current "hotspots" of soil erosion in the north-western, eastern and north-eastern parts of the Upper Ouémé catchment. As a consequence of rapid expansion of agricultural areas triggered by high population growth (partially caused by migration) and resulting increases in surface runoff and topsoil erosion, the mean sediment yield in the Upper Ouémé River outlet is expected to increase by 42 to 95% by 2025, depending on the land use scenario. In contrast, changes in climate variables led to decreases in sediment yield of 5 to 14% in 2001-2025 and 17 to 24% in 2026-2050. Combined scenarios showed the dominance of land use change leading to changes in mean sediment yield of -2 to +31% in 2001-2025. Scenario results vary considerably within the catchment. Current "hotspots" of soil erosion will aggravate, and a new "hotspot" will appear in the southern part of the catchment. Although only small parts of the Upper Ouémé catchment belong to the most degraded zones in the country, sustainable soil and plant management practices should be promoted in the entire catchment. The results of this study can support planning of soil conservation activities in Benin.

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Despite the importance of tropical montane cloud forest streams, studies investigating aquatic communities in these regions are rare and knowledge on the driving factors of community structure is missing. The objectives of this study therefore were to understand how land-use influences habitat structure and macroinvertebrate communities in cloud forest streams of southern Ecuador. We evaluated these relationships in headwater streams with variable land cover, using multivariate statistics to identify relationships between key habitat variables and assemblage structure, and to resolve differences in composition among sites. Results show that shading intensity, substrate type and pH were the environmental parameters most closely related to variation in community composition observed among sites. In addition, macroinvertebrate density and partly diversity was lower in forested sites, possibly because the pH in forested streams lowered to almost 5 during spates. Standard bioindicator metrics were unable to detect the changes in assemblage structure between disturbed and forested streams. In general, our results indicate that tropical montane headwater streams are complex and heterogeneous ecosystems with low invertebrate densities. We also found that some amount of disturbance, i.e. patchy deforestation, can lead at least initially to an increase in macroinvertebrate taxa richness of these streams.

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To project the future development of the soil organic carbon (SOC) storage in permafrost environments, the spatial and vertical distribution of key soil properties and their landscape controls needs to be understood. This article reports findings from the Arctic Lena River Delta where we sampled 50 soil pedons. These were classified according to the U.S.D.A. Soil Taxonomy and fall mostly into the Gelisol soil order used for permafrost-affected soils. Soil profiles have been sampled for the active layer (mean depth 58±10 cm) and the upper permafrost to one meter depth. We analyze SOC stocks and key soil properties, i.e. C%, N%, C/N, bulk density, visible ice and water content. These are compared for different landscape groupings of pedons according to geomorphology, soil and land cover and for different vertical depth increments. High vertical resolution plots are used to understand soil development. These show that SOC storage can be highly variable with depth. We recommend the treatment of permafrost-affected soils according to subdivisions into: the surface organic layer, mineral subsoil in the active layer, organic enriched cryoturbated or buried horizons and the mineral subsoil in the permafrost. The major geomorphological units of a subregion of the Lena River Delta were mapped with a land form classification using a data-fusion approach of optical satellite imagery and digital elevation data to upscale SOC storage. Landscape mean SOC storage is estimated to 19.2±2.0 kg C/m**2. Our results show that the geomorphological setting explains more soil variability than soil taxonomy classes or vegetation cover. The soils from the oldest, Pleistocene aged, unit of the delta store the highest amount of SOC per m**2 followed by the Holocene river terrace. The Pleistocene terrace affected by thermal-degradation, the recent floodplain and bare alluvial sediments store considerably less SOC in descending order.