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>

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.

scholarly journals d4PDF: large-ensemble and high-resolution climate simulations for global warming risk assessment

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Masayoshi Ishii ◽  
Nobuhito Mori
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
High Resolution ◽  
Climate Changes ◽  
Future Climate ◽  
Atmospheric Models ◽  
Large Ensemble ◽  
Past Climate ◽  
The Past ◽  
Climate Simulations

Abstract A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.

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.

scholarly journals A 90,000-year record of Afromontane forest responses to climate change

Science ◽  
2019 ◽  
Vol 363 (6423) ◽  
pp. 177-181 ◽  
Author(s):  
Anne-Marie Lézine ◽  
Kenji Izumi ◽  
Masa Kageyama ◽  
Gaston Achoundong
Keyword(s):  
Climate Changes ◽  
High Temporal Resolution ◽  
Pollen Data ◽  
Glacial Cycles ◽  
Tropical Mountains ◽  
The Past ◽  
Afromontane Forest ◽  
Afromontane Forests ◽  
Lowland Forests ◽  
African Highlands

Pollen records from African highlands are scarce; hence, the paleoecology of the Afromontane forest and its responses to glacial cycles are poorly known. Lake Bambili (Cameroon) provides a record of vegetation changes in the tropical mountains of Africa over the past 90,000 years, with high temporal resolution. Pollen data and biome reconstructions show a diverging response of forests to climate changes; the upper tree line was extremely unstable, shifting substantially in response to glacial-interglacial climate alternation, whereas the transition between the montane and lowland forests remained remarkably stable. Such ecological instability may have had a critical influence on species richness in the Afromontane forests.

Climate changes reconstructed from a glacial lake in High Central Asia over the past two millennia

2018 ◽  
Vol 487 ◽  
pp. 43-53 ◽  
Author(s):  
Jianghu Lan ◽  
Hai Xu ◽  
Enguo Sheng ◽  
Keke Yu ◽  
Huixian Wu ◽  
...  
Keyword(s):  
Central Asia ◽  
Climate Changes ◽  
Glacial Lake ◽  
The Past

scholarly journals Comparison of changes in land use and land cover in China and the USA over the past 300 years

2015 ◽  
Vol 25 (9) ◽  
pp. 1045-1057 ◽  
Author(s):  
Fanneng He ◽  
Meijiao Li ◽  
Shicheng Li ◽  
Ran Xiao
Keyword(s):  
Land Use ◽  
Land Cover ◽  
The Past ◽  
The Usa ◽  
Past 300 Years

scholarly journals Variations in ecosystem service value in response to land use/land cover changes in Central Asia over 1995-2035

2019 ◽  
Author(s):  
Jiangyue Li ◽  
Hongxing Chen ◽  
Chi Zhang ◽  
Tao Pan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Central Asia ◽  
Ecosystem Service ◽  
Water Bodies ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Ecosystem Service Value ◽  
Rapid Urbanization ◽  
Service Value

Acute farmland expansion and rapid urbanization in Central Asia have accelerated land use/land cover changes, which has significant effect onecosystemservice. However, the spatio-temporal changes in ecosystem service values in Central Asia are not well understood. Here, based on land use products with 300-m resolution for the years of 1995, 2005 and 2015 and transfer methodology, we predicted LUCC for 2025 and 2035 using CA-Markov, assessed changes in ecosystem service value in response to LUCC dynamics, and explored the elasticity for the response of ESV to LULC changes. We found significant expansions of cropland and urban and shrinking of water bodies and bare land during 1995-2035. Overall ESVs had an increasing trend from 1995-2035, which was mainly due to the increasing cropland and construction land. The combined valueofecosystemservices of cropland, grassland, water bodies accounted for over 90% of the total ESVs. However, LULC analysis showed that the area of water body reduced by 21.80% from 1995 to 2015 and continued to decrease by 21.14% from 2015 to 2035, indicating that approximately 63.37 billion US$ of ESVs lost in Central Asia. Biodiversity, food production and water regulation were major service functions, accounting for 80.52% of the total ESVs . Our results demonstrated that theeffective land-usepolicies should be made to control farmland expansion and protect water bodies, grassland and forestland for better sustainable ecosystem services.

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