scholarly journals Advances in Observation and Estimation of Land Use Impacts on Climate Changes: Improved Data, Upgraded Models, and Case Studies

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
R. B. Singh ◽  
Chenchen Shi
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Climate Changes ◽  
Research Needs ◽  
Land Use Impacts ◽  
The Past ◽  
Surface Climate ◽  
Global Land ◽  
Cover Pattern

Global land use and land cover pattern has greatly changed in the past 50 years, which exerts direct or indirect influence on the climate change remarkably at both regional and global scales. Therefore, observing and estimating the land use impacts on surface climate is essential and has been continuously promoted by researchers. This paper explores the advancement in the models, data, and application for observing and estimating the land use impacts on surface climate and points out further research needs and priorities, which hopefully will provide some references for related studies.

Response of vegetation to past climate changes in Central Asia

2020 ◽  
Author(s):  
Laurent Marquer ◽  
Andrea Seim ◽  
Anne Dallmeyer ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Central Asia ◽  
Climate Changes ◽  
Vegetation Composition ◽  
Pollen Data ◽  
Past Climate ◽  
Coniferous Trees ◽  
The Past ◽  
Climate Events

<p>Quantifying the long-term trend of climate versus land use influence on vulnerable ecosystems is of great importance to identify the threats of landscape modifications on biodiversity and ecosystem services, and therefore on societies. The evaluation of the resilience of ecosystems is particularly important considering the ongoing climate change.</p><p>As ecosystems in arid Central Asia are mainly influenced by climate and physical geography and most species are growing near their physiological limit, the predicted increased aridity for this region likely increases the threat on the ecosystems in this region.</p><p>Pollen are the main proxy to explore changes in vegetation at different spatial (local to subcontinental) and temporal (decades to millennia) scales. To quantify human- and climate-induced changes in vegetation, past land-cover (pollen-based estimates), land use (human deforestation scenarios and human population size) and climate (variables derived from climate models) data can be combined, as it has been done in Europe (e.g. Marquer et al., 2017).</p><p>This study aims at quantifying the effect of past climate changes on vegetation in Central Asia over the past millennia at century time scale. For this purpose, we use 49 pollen data from sedimentary records (lakes and mires) which were transformed into vegetation composition and diversity indices. Pollen data as point estimates and spatial grids of past vegetation are combined with available annually resolved gridded summer temperature and precipitation estimates inferred from tree-ring chronologies in this region. The reconstructed climate and vegetation trends are compared to different transient Earth System model simulations with the help of the biome-model BIOME4 (c.f. Dallmeyer et al., 2017). Statistical analyses have been performed to compare all data.</p><p>We found clear spatial pattern in the plant distribution with i) a large abundance of coniferous trees in northernmost areas and to a lesser extend in the mountains (e.g. Tian Shan), ii) steppes in the lowlands and at high plateaus, and iii) semi-deserts and steppes in the lowlands. The vegetation composition and diversity have significantly changed over the past millennia. Those changes are mainly related to modifications in composition and diversity of plant species in steppes and semi-deserts, of coniferous trees in the mountains, and changes in land use. Our results reveal that precipitation is the major driver of vegetation composition and diversity in Central Asia whereas temperature mainly explains the spatial variation, in particular during major climate events, e.g. the Little Ice Age and the Warm Medieval Period. Further studies are now in progress to quantify the relative (to climate) influence of land use (e.g. anthropogenic land-cover change; ALCC) in the region.</p><p>This study demonstrates the climate dependency of vegetation composition and diversity in Central Asia, especially during the major climate events over the last two millennia. This opens the discussion about the resilience of vulnerable ecosystems facing severe impacts of ongoing and predicted climate changes in arid Central Asia.      </p><p>Dallmeyer et al. (2017) Climate of the Past 13, 107-134. / Marquer et al. (2017) Quaternary Science Reviews 171, 20-37.</p>

Effects of climate change, land-use change, and invasive species on the ecology of the Cumberland forests

2009 ◽  
Vol 39 (2) ◽  
pp. 467-480 ◽  
Author(s):  
Virginia H. Dale ◽  
Karen O. Lannom ◽  
M. Lynn Tharp ◽  
Donald G. Hodges ◽  
Jonah Fogel
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Species Composition ◽  
General Circulation ◽  
Climate Changes ◽  
Land Use Changes ◽  
Forest Biomass ◽  
Adelges Tsugae ◽  
Forest Species

Model projections suggest that both climate and land-use changes have large effects on forest biomass and composition in the Cumberland forests of Tennessee and Kentucky. These forests have high levels of diversity, ecological importance, land-use changes, and pressures due to invasive herbivorous insects and climate change. Three general circulation models project warming for all months in 2030 and 2080 and complex patterns of precipitation change. Climate changes from 1980 to 2100 were developed from these projections and used in the forest ecosystem model LINKAGES to estimate transient changes in forest biomass and species composition over time. These projections show that climate changes can instigate a decline in forest stand biomass and then recovery as forest species composition shifts. In addition, a landscape model (LSCAP) estimates changes in land-cover types of the Cumberlands based on projected land-use changes and the demise of eastern hemlock ( Tsuga canadensis (L.) Carrière) due to the spread of the hemlock adelgid ( Adelges tsugae Annand). LSCAP suggests that land-cover changes can be quite large and can cause a decline not only in the area of forested lands but also in the size and number of large contiguous forest patches that are necessary habitat for many forest species characteristic of the Cumberlands.

scholarly journals Climate change and land use impacts on hydrologic processes of watershed systems

2017 ◽  
Vol 8 (3) ◽  
pp. 363-374 ◽  
Author(s):  
Ammara Talib ◽  
Timothy O. Randhir
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Climate Model ◽  
Global Climate Model ◽  
Transformation Model ◽  
Land Use Impacts ◽  
Hydrological Simulation ◽  
Mitigation And Adaptation ◽  
Impervious Area

Land use, land cover and climate change (CC) can significantly influence the hydrologic balance and biogeochemical processes of watershed systems. These changes can alter interception, evapotranspiration (ET), infiltration, soil moisture, water balance, and biogeochemical cycling of carbon, nitrogen, and other elements. The need to evaluate the combined effect of land use change and CC of watershed systems is a focus of this study. We simulated watershed processes in the SuAsCo River watershed in MA, USA, using a calibrated and validated Hydrological Simulation Program Fortran model. Climatic scenarios included downscaled regional projections from Global Climate Model models. The Land Transformation Model was used to project land use. Combined change in land cover and climate reduce ET with loss of vegetation. Changes in climate and land cover increase surface runoff significantly by 2100 as well as stream discharge. Combined change in land cover and climate cause 10% increase in peak volume with 7% increase in precipitation and 75% increase in effective impervious area. Climate and land use changes can intensify the water cycle and introduce seasonal changes in watershed systems. Understanding dynamic changes in watershed systems is critical for mitigation and adaptation options. We propose restoration strategies that can increase the resilience of watershed systems.

scholarly journals Evapotranspiration is resilient in the face of land cover and climate change in a humid temperate catchment

2016 ◽  
Author(s):  
S. K. Hamilton ◽  
M. Z. Hussain ◽  
C. Lowrie ◽  
B. Basso ◽  
G. P. Robertson
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Water Balance ◽  
Deciduous Forest ◽  
Local Data ◽  
Evaporative Water ◽  
The Past ◽  
Perennial Vegetation ◽  
The Face

AbstractIn temperate humid catchments, evapotranspiration returns more than half of the annual precipitation to the atmosphere, thereby determining the balance available to recharge groundwaters and support stream flow and lake levels. Changes in evapotranspiration rates and therefore catchment hydrology could be driven by changes in land use or climate. Here we examine the catchment water balance over the past 50 y for a catchment in southwest Michigan covered by cropland, grassland, forest, and wetlands. Over the study period about 27% of the catchment has been abandoned from row-crop agriculture to perennial vegetation and about 20% of the catchment has reverted to deciduous forest, and the climate has warmed by 1.14°C. Despite these changes in land use, precipitation and stream discharge, and by inference catchment-scale evapotranspiration, have been stable over the study period. The remarkably stable rates of evapotranspirative water loss from the catchment across a period of significant land cover change suggest that rainfed annual crops and perennial vegetation do not differ greatly in evapotranspiration rates, and this is supported by measurements of evapotranspiration from various vegetation types based on soil water monitoring in the same catchment. Compensating changes in the other meteorological drivers of evaporative water demand besides air temperature—wind speed, atmospheric humidity, and net radiation—are also possible, but cannot be evaluated due to insufficient local data across the 50-y period. Regardless of the explanation, this study shows that the water balance of this landscape has been resilient in the face of both land cover and climate change over the past 50 y.

scholarly journals Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Climate ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 83
Author(s):  
Geofrey Gabiri ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Constanze Leemhuis ◽  
Roderick van der Linden ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Rainy Season ◽  
Hydrological Processes ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Inland Valley ◽  
Headwater Catchment

The impact of climate and land use/land cover (LULC) change continues to threaten water resources availability for the agriculturally used inland valley wetlands and their catchments in East Africa. This study assessed climate and LULC change impacts on the hydrological processes of a tropical headwater inland valley catchment in Uganda. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze climate and LULC change impacts on the hydrological processes. An ensemble of six regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment for two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were used for climate change assessment for historical (1976–2005) and future climate (2021–2050). Four LULC scenarios defined as exploitation, total conservation, slope conservation, and protection of headwater catchment were considered. The results indicate an increase in precipitation by 7.4% and 21.8% of the annual averages in the future under RCP4.5 and RCP8.5, respectively. Future wet conditions are more pronounced in the short rainy season than in the long rainy season. Flooding intensity is likely to increase during the rainy season with low flows more pronounced in the dry season. Increases in future annual averages of water yield (29.0% and 42.7% under RCP4.5 and RCP8.5, respectively) and surface runoff (37.6% and 51.8% under RCP4.5 and RCP8.5, respectively) relative to the historical simulations are projected. LULC and climate change individually will cause changes in the inland valley hydrological processes, but more pronounced changes are expected if the drivers are combined, although LULC changes will have a dominant influence. Adoption of total conservation, slope conservation and protection of headwater catchment LULC scenarios will significantly reduce climate change impacts on water resources in the inland valley. Thus, if sustainable climate-smart management practices are adopted, the availability of water resources for human consumption and agricultural production will increase.

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

scholarly journals ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Conversion ◽  
Landsat 8 ◽  
Amazon Forest ◽  
Landsat 8 Oli ◽  
Mato Grosso ◽  
The Past ◽  
Landsat 5 Tm

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.

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