957 resultados para Land cover change
Resumo:
Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.
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Deforestation often occurs as temporal waves and in localized fronts termed 'deforestation hotspots' driven by economic pulses and population pressure. Of particular concern for conservation planning are 'biodiversity hotspots' where high concentrations of endemic species undergo rapid loss and fragmentation of habitat. We investigate the deforestation process in Caqueta, a biodiversity hotspot and major colonization front of the Colombian Amazon using multi-temporal satellite imagery of the periods 1989-1996-1999-2002. The probabilities of deforestation and regeneration were modeled against soil fertility, accessibility and neighborhood terms, using logistic regression analysis. Deforestation and regeneration patterns and rates were highly variable across the colonization front. The regional average annual deforestation rate was 2.6%, but varied locally between -1.8% (regeneration) and 5.3%, with maximum rates in landscapes with 40-60% forest cover and highest edge densities, showing an analogous pattern to the spread of disease. Soil fertility and forest and secondary vegetation neighbors showed positive and significant relationships with the probability of deforestation. For forest regeneration, soil fertility had a significant negative effect while the other parameters were marginally significant. The logistic regression models across all periods showed a high level of discrimination power for both deforestation and forest regeneration, with ROC values > 0.80. We document the effect of policies and institutional changes on the land clearing process, such as the failed peace process between government and guerillas in 1999-2002, which redirected the spread of deforestation and increased forest regeneration. The implications for conservation in biologically rich areas, such as Caqueta are discussed. (c) 2005 Elsevier B.V All rights reserved.
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Increasingly erratic flow in the upper reaches of the Mara River, has directed attention to land use change as the major cause of this problem. The semi-distributed hydrological model SWAT and Landsat imagery were utilized in order to 1) map existing land use practices, 2) determine the impacts of land use change on water flux; and 3) determine the impacts of climate change scenarios on the water flux of the upper Mara River. This study found that land use change scenarios resulted in more erratic discharge while climate change scenarios had a more predictable impact on the discharge and water balance components. The model results showed the flow was more sensitive to the rainfall changes than land use changes but land use changes reduce dry season flows which is a major problem in the basin. Deforestation increased the peak flows which translated to increased sediment loading in the Mara River.
Resumo:
With the flow of the Mara River becoming increasingly erratic especially in the upper reaches, attention has been directed to land use change as the major cause of this problem. The semi-distributed hydrological model Soil and Water Assessment Tool 5 (SWAT) and Landsat imagery were utilized in the upper Mara River Basin in order to 1) map existing field scale land use practices in order to determine their impact 2) determine the impacts of land use change on water flux; and 3) determine the impacts of rainfall (0%, ±10% and ±20%) and air temperature variations (0% and +5%) based on the Intergovernmental Panel on Climate Change projections on the water flux of the 10 upper Mara River. This study found that the different scenarios impacted on the water balance components differently. Land use changes resulted in a slightly more erratic discharge while rainfall and air temperature changes had a more predictable impact on the discharge and water balance components. These findings demonstrate that the model results 15 show the flow was more sensitive to the rainfall changes than land use changes. It was also shown that land use changes can reduce dry season flow which is the most important problem in the basin. The model shows also deforestation in the Mau Forest increased the peak flows which can also lead to high sediment loading in the Mara River. The effect of the land use and climate change scenarios on the sediment and 20 water quality of the river needs a thorough understanding of the sediment transport processes in addition to observed sediment and water quality data for validation of modeling results.
Resumo:
Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5–10 %) accompanied by increases in temperature (2.5–3.5 °C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (−3 %) and high (+25 %) extremes of projected precipitation changes, but under median projections (+7 %) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned largely to increased evapotranspiration. Overall, model results support the existing efforts of Mara water resource managers to protect headwater forests and indicate that additional emphasis should be placed on improving land management practices that enhance infiltration and aquifer recharge as part of a wider program of climate change adaptation.
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This work contributed to The input of PS and PCW contributes to the Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1) and for PS also contributes to the EU FP7 SmartSoil project (Project number: 289694)
Resumo:
This work contributed to The input of PS and PCW contributes to the Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1) and for PS also contributes to the EU FP7 SmartSoil project (Project number: 289694)
Resumo:
Across North America, grassland songbirds have undergone steep population declines over recent decades, commonly attributed to agricultural intensification. Understanding the potential interactions between the impacts of climate change on the future distributions of these species and the availability of suitable vegetation for nesting can support improved risk assessments and conservation planning for this group of species. We used North American bioclimatic niche models to examine future changes in suitable breeding climate for 15 grassland songbird species at their current northern range limits along the boreal forest–prairie ecotone in Alberta, Canada. Our climate suitability projections, combined with the current distribution of native and tame pasture and cropland in Alberta, suggest that some climate-mediated range expansion of grassland songbirds in Alberta is possible. For six of the eight species projected to experience expansions of suitable climate area in Alberta, this suitable climate partly overlaps the current distribution of suitable land cover. Additionally, for more than half of the species examined, most of the area of currently suitable climate was projected to remain suitable to the end of the century, highlighting the importance of Alberta for the long-term persistence of these species. Some northern prairie-endemic species exhibited substantial projected northward shifts of both the northern and southern edges of the area of suitable climate. Baird’s Sparrow (Ammodramus bairdii) and Sprague’s Pipit (Anthus spragueii), both at-risk grassland specialists, are predicted to have limited climate stability within their current ranges, and their expansion into new areas of suitable climate may be limited by the availability of suitable land cover. Our results highlight the importance of the preservation and restoration of remaining suitable grassland habitat within areas of projected climate stability and beyond current northern range limits for the long-term persistence of many grassland songbird species in the face of climate change.
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Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.
Resumo:
Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.
Resumo:
Global environmental changes (GEC) such as climate change (CC) and climate variability have serious impacts in the tropics, particularly in Africa. These are compounded by changes in land use/land cover, which in turn are driven mainly by economic and population growth, and urbanization. These factors create a feedback loop, which affects ecosystems and particularly ecosystem services, for example plant-insect interactions, and by consequence agricultural productivity. We studied effects of GEC at a local level, using a traditional coffee production area in greater Nairobi, Kenya. We chose coffee, the most valuable agricultural commodity worldwide, as it generates income for 100 million people, mainly in the developing world. Using the coffee berry borer, the most serious biotic threat to global coffee production, we show how environmental changes and different production systems (shaded and sun-grown coffee) can affect the crop. We combined detailed entomological assessments with historic climate records (from 1929-2011), and spatial and demographic data, to assess GEC's impact on coffee at a local scale. Additionally, we tested the utility of an adaptation strategy that is simple and easy to implement. Our results show that while interactions between CC and migration/urbanization, with its resultant landscape modifications, create a feedback loop whereby agroecosystems such as coffee are adversely affected, bio-diverse shaded coffee proved far more resilient and productive than coffee grown in monoculture, and was significantly less harmed by its insect pest. Thus, a relatively simple strategy such as shading coffee can tremendously improve resilience of agro-ecosystems, providing small-scale farmers in Africa with an easily implemented tool to safeguard their livelihoods in a changing climate.
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Tropical ecosystems play a large and complex role in the global carbon cycle. Clearing of natural ecosystems for agriculture leads to large pulses of CO(2) to the atmosphere from terrestrial biomass. Concurrently, the remaining intact ecosystems, especially tropical forests, may be sequestering a large amount of carbon from the atmosphere in response to global environmental changes including climate changes and an increase in atmospheric CO(2). Here we use an approach that integrates census-based historical land use reconstructions, remote-sensing-based contemporary land use change analyses, and simulation modeling of terrestrial biogeochemistry to estimate the net carbon balance over the period 1901-2006 for the state of Mato Grosso, Brazil, which is one of the most rapidly changing agricultural frontiers in the world. By the end of this period, we estimate that of the state`s 925 225 km(2), 221 092 km(2) have been converted to pastures and 89 533 km(2) have been converted to croplands, with forest-to-pasture conversions being the dominant land use trajectory but with recent transitions to croplands increasing rapidly in the last decade. These conversions have led to a cumulative release of 4.8 Pg C to the atmosphere, with similar to 80% from forest clearing and 20% from the clearing of cerrado. Over the same period, we estimate that the residual undisturbed ecosystems accumulated 0.3 Pg C in response to CO2 fertilization. Therefore, the net emissions of carbon from Mato Grosso over this period were 4.5 Pg C. Net carbon emissions from Mato Grosso since 2000 averaged 146 Tg C/yr, on the order of Brazil`s fossil fuel emissions during this period. These emissions were associated with the expansion of croplands to grow soybeans. While alternative management regimes in croplands, including tillage, fertilization, and cropping patterns promote carbon storage in ecosystems, they remain a small portion of the net carbon balance for the region. This detailed accounting of a region`s carbon balance is the type of foundation analysis needed by the new United Nations Collaborative Programmme for Reducing Emissions from Deforestation and Forest Degradation (REDD).
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The Brazilian Amazon is one of the most rapidly developing agricultural areas in the world and represents a potentially large future source of greenhouse gases from land clearing and subsequent agricultural management. In an integrated approach, we estimate the greenhouse gas dynamics of natural ecosystems and agricultural ecosystems after clearing in the context of a future climate. We examine scenarios of deforestation and postclearing land use to estimate the future (2006-2050) impacts on carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) emissions from the agricultural frontier state of Mato Grosso, using a process-based biogeochemistry model, the Terrestrial Ecosystems Model (TEM). We estimate a net emission of greenhouse gases from Mato Grosso, ranging from 2.8 to 15.9 Pg CO(2)-equivalents (CO(2)-e) from 2006 to 2050. Deforestation is the largest source of greenhouse gas emissions over this period, but land uses following clearing account for a substantial portion (24-49%) of the net greenhouse gas budget. Due to land-cover and land-use change, there is a small foregone carbon sequestration of 0.2-0.4 Pg CO(2)-e by natural forests and cerrado between 2006 and 2050. Both deforestation and future land-use management play important roles in the net greenhouse gas emissions of this frontier, suggesting that both should be considered in emissions policies. We find that avoided deforestation remains the best strategy for minimizing future greenhouse gas emissions from Mato Grosso.
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Biogeochemistry is hosting this special thematic issue devoted to studies of land-water interactions, as part of the Large-scale Biosphere-Atmosphere Experiment in Amaznia (LBA). This compilation of papers covers a broad range of topics with a common theme of coupling land and water processes, across pristine and impacted systems. Findings highlighted that hydrologic flowpaths are clearly important across basin size and structure in determining how water and solutes reach streams. Land-use changes have pronounced impacts on flowpaths, and subsequently, on stream chemistry, from small streams to large rivers. Carbon is produced and transformed across a broad array of fluvial environments and wetlands. Surface waters are not only driven by, but provide feedback to, the atmosphere.
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Stream discharge-concentration relationships are indicators of terrestrial ecosystem function. Throughout the Amazon and Cerrado regions of Brazil rapid changes in land use and land cover may be altering these hydrochemical relationships. The current analysis focuses on factors controlling the discharge-calcium (Ca) concentration relationship since previous research in these regions has demonstrated both positive and negative slopes in linear log(10)discharge-log(10)Ca concentration regressions. The objective of the current study was to evaluate factors controlling stream discharge-Ca concentration relationships including year, season, stream order, vegetation cover, land use, and soil classification. It was hypothesized that land use and soil class are the most critical attributes controlling discharge-Ca concentration relationships. A multilevel, linear regression approach was utilized with data from 28 streams throughout Brazil. These streams come from three distinct regions and varied broadly in watershed size (< 1 to > 10(6) ha) and discharge (10(-5.7)-10(3.2) m(3) s(-1)). Linear regressions of log(10)Ca versus log(10)discharge in 13 streams have a preponderance of negative slopes with only two streams having significant positive slopes. An ANOVA decomposition suggests the effect of discharge on Ca concentration is large but variable. Vegetation cover, which incorporates aspects of land use, explains the largest proportion of the variance in the effect of discharge on Ca followed by season and year. In contrast, stream order, land use, and soil class explain most of the variation in stream Ca concentration. In the current data set, soil class, which is related to lithology, has an important effect on Ca concentration but land use, likely through its effect on runoff concentration and hydrology, has a greater effect on discharge-concentration relationships.