REVEALS-based reconstruction of Holocene vegetation abundance in temperate China: new insights on past human-induced land-cover change for climate modelling

2020 ◽  
Author(s):  
Furong Li ◽  
Marie-José Gaillard ◽  
Shinya Sugita ◽  
Xianyong Cao ◽  
Ulrike Herzschuh ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Cover ◽  
Eastern China ◽  
Plant Cover ◽  
Climate Modelling ◽  
Important Region ◽  
Open Land ◽  
Vegetation Cover Change

<p>Quantification of the effects of human-induced vegetation-cover change on past (present and future) climate is still a subject of debate. Our understanding of these effects greatly depends on the availability of empirical reconstructions of past anthropogenic vegetation cover. Such reconstructions can be used to evaluate Anthropogenic Land-Cover Change (ALCC) scenarios for the past (such as HYDE and KK), and simulated past vegetation using dynamic vegetation models such as LPJGUESS. In this context, China is an important region given that agriculture started already in early Holocene, and expanded rapidly over large areas throughout the eastern part of the country. Quantitative reconstructions of plant cover based on pollen data has long been a challenge. The REVEALS model (Sugita, 2007) is one of the approaches for quantitative reconstruction of past plant cover that has been applied, tested, and validated in many regions of the world over the last years. Relative pollen productivity (RPP) of plant taxa is a key parameter required for REVEALS applications. A synthesis of all RPP estimates available in temperate China is published in Li et al. (2018). These RPPs were used with pollen records from lakes and bogs to produce REVEALS-based estimates of Holocene regional vegetation-cover change in temperate China. In order to interpret the REVEALS reconstructions in terms of climate or anthropogenic land-cover change, we compared the REVEALS estimates of vegetation-cover change with existing palaeoclimatic data and archaeological evidences on human history and past land-use change. We also compared the REVEALS estimates with fractions of plant functional types simulated by LPJGUESS and ALCC scenarios from HYDE and KK.</p><p>The results suggest that the REVEALS-based values of plant cover strongly differ from the pollen percentages and provide new insights on past changes in plant composition and vegetation dynamics over the Holocene. Human-induced deforestation is highest in eastern China with 3 major phases at ca. 5500, 3000 and 2000 calibrated years before present. Disentangling human-induced from climate-induced pollen-based open-land cover remains a challenge. However,  thorough comparison of the REVEALS reconstructions with historical and archaeological information on settlement and land-use history, and with palaeoclimate reconstructions provide important clues to the question. This study is a contribution to PAGES LandCover6k.</p><p><em>References: Li et al., 2018. Front Plant Sci; Sugita, 2007. Holocene.</em></p>

scholarly journals Spatiotemporal water yield variations and influencing factors in the Lhasa River Basin, Tibetan Plateau

2020 ◽  
Author(s):  
Huiting Lu ◽  
Yan Yan ◽  
Jieyuan Zhu ◽  
Tiantian Jin ◽  
Guohua Liu ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Influencing Factors ◽  
River Basin ◽  
Vegetation Cover ◽  
Water Yield ◽  
Lhasa River Basin ◽  
Lhasa River ◽  
Vegetation Cover Change

<p>Climate and land use/cover changes are widely recognized as two main drivers of variations in ecosystem services including water yield. However, vegetation cover condition, which can also influence the hydrological cycle through evapotranspiration process, is seldom considered. In this study, we used the Seasonal Water Yield Model (SWYM) to assess the spatiotemporal water yield changes of Lhasa River Basin from 1990 to 2015, and analysed its influencing factors by focusing on precipitation change, land cover change, and vegetation cover change (indexed by Normalized Difference Vegetation Index, i.e. NDVI). We first examined the model through Morris Screening sensitivity analysis and validated it with observed flow data. Spatiotemporal variation of three indices of water yield, baseflow, quick flow and local recharge, were then assessed. To analyse the contribution of each factor to water yield change, three scenarios were built in which one factor was altered at a time. Results showed that, the precipitation and vegetation cover change were substantial during the study period, while land cover change was quite small. From 1990 to 2015, the baseflow, local recharge and quick flow decreased by 67.03%, 80.21% and 37.03% respectively, with the change mainly occurring during 2000-2010. The spatial pattern of water yield remained mostly unchanged. The upstream area had relatively high baseflow and local recharge, and was the main contributor of quick flow. The downstream area had relatively low or even zero baseflow, and most of its local recharge was negative due to high evapotranspiration. According to contribution analysis, precipitation and vegetation cover change were the main factors affecting water yield in the Lhasa River Basin. For baseflow, the influence of precipitation change was, on average, 7.98 times as big as vegetation cover change, and the influence of vegetation cover change was, on average, 115.45 times as big as land cover change. However, land cover change began to exert greater influence after 2010. We suggest that besides climate and land use/cover change, vegetation cover change should also be studied in greater depth to fully understand its effect on regional hydrological process and ecosystem service provision.</p>

scholarly journals Land Use and Land Cover Change in the Kailash Sacred Landscape of China

2019 ◽  
Vol 11 (6) ◽  
pp. 1788 ◽  
Author(s):  
Cheng Duan ◽  
Peili Shi ◽  
Minghua Song ◽  
Xianzhou Zhang ◽  
Ning Zong ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Cover ◽  
Driving Forces ◽  
Landscape Planning ◽  
Landscape Conservation ◽  
Climatic Warming ◽  
Sacred Landscape ◽  
Kailash Sacred Landscape

Land use and land cover change (LUCC) is an important driver of ecosystem function and services. Thus, LUCC analysis may lay foundation for landscape planning, conservation and management. It is especially true for alpine landscapes, which are more susceptible to climate changes and human activities. However, the information on LUCC in sacred landscape is limited, which will hinder the landscape conservation and development. We chose Kailash Sacred Landscape in China (KSL-China) to investigate the patterns and dynamics of LUCC and the driving forces using remote sensing data and meteorological data from 1990 to 2008. A supervised classification of land use and land cover was established based on field survey. Rangelands presented marked fluctuations due to climatic warming and its induced drought, for example, dramatic decreases were found in high- and medium-cover rangelands over the period 2000–2008. And recession of most glaciers was also observed in the study period. Instead, an increase of anthropogenic activities accelerated intensive alteration of land use, such as conversion of cropland to built-up land. We found that the change of vegetation cover was positively correlated with growing season precipitation (GSP). In addition, vegetation cover was substantially reduced along the pilgrimage routes particularly within 5 km of the routes. The findings of the study suggest that climatic warming and human disturbance are interacted to cause remarkable LUCC. Tourism development was responsible land use change in urban and pilgrimage routes. This study has important implications for landscape conservation and ecosystem management. The reduction of rangeland cover may decrease the rangeland quality and pose pressure for the carrying capacity of rangelands in the KSL-China. With the increasing risk of climate warming, rangeland conservation is imperative. The future development should shift from livestock-focus animal husbandry to service-based ecotourism in the sacred landscape.

Response of vegetation cover to drought in the northern slope of the Tianshan Mountains during 2001-2015 based on the land-use and land-cover change

2019 ◽  
Vol 39 (17) ◽  
Author(s):  
李艳菊 LI Yanju ◽  
丁建丽 DING Jianli ◽  
张钧泳 ZHANG Junyong ◽  
武鹏飞 WU Pengfei
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Cover ◽  
Tianshan Mountains ◽  
Northern Slope

scholarly journals High-resolution land-use land-cover change data for regional climate modelling applications over Europe – Part 2: Historical and future changes

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Vanessa Reinhart ◽  
Diana Rechid ◽  
Nathalie de Noblet-Ducoudré ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Changes ◽  
Regional Climate ◽  
Climate Modelling ◽  
Historical Changes ◽  
The Impact

Abstract. Anthropogenic land-use and land cover change (LULCC) is a major driver of environmental changes. The biophysical impacts of these changes on the regional climate in Europe are currently extensively investigated within the WCRP CORDEX Flagship Pilot Study (FPS) LUCAS – "Land Use and Climate Across Scales" using an ensemble of different Regional Climate Models (RCMs) coupled with diverse Land Surface Models (LSMs). In order to investigate the impact of realistic LULCC on past and future climates, high-resolution datasets with observed LULCC and projected future LULCC scenarios are required as input for the RCM-LSM simulations. To account for these needs, we generated the LUCAS LUC Version 1.0 at 0.1° resolution for Europe Hoffmann et al. (2021b,c). The plant functional type distribution for the year 2015 (i.e. LANDMATE PFT dataset) is derived from the European Space Agency Climate Change Initiative Land Cover (ESA-CCI LC) dataset. Details about the conversion method based on a cross-walking procedure and the evaluation of the LANDMATE PFT dataset are given in the companion paper by Reinhart et al. (submitted). Subsequently, we applied the land-use change information from the Land-Use Harmonization 2 (LUH2) dataset, provided at 0.25° resolution as input for CMIP6 experiments, to derive realistic LULC distribution at high spatial resolution and at annual timesteps from 1950 to 2100. In order to convert land use and land management change information from LUH2 into changes in the PFT distribution, we developed a Land Use Translator (LUT) specific to the needs of RCMs. The annual PFT maps for Europe for the period 1950 to 2015 are derived from the historical LUH2 dataset by applying the LUT backward from 2015 to 1950. Historical changes in the forest type changes are considered using an additional European forest species dataset. The historical changes in the PFT distribution of LUCAS LUC follow closely the land use changes given by LUH2 but differ in some regions compared to remotely-sensed PFT time series. From 2016 onward, annual PFT maps for future land use change scenarios based on LUH2 are derived for different Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) combinations used in the framework of the Coupled Modelling Intercomparison Project Phase 6 (CMIP6). The resulting LULCC maps can be applied as land use forcing to the next generation of RCM simulations for downscaling of CMIP6 results. The newly developed LUT is transferable to other CORDEX regions world-wide.

Analysis of Land Use/Land Cover Change in Yangzhou City Based on CLUE-S Model

2011 ◽  
Vol 13 (5) ◽  
pp. 695-700
Author(s):  
Zhihua TANG ◽  
Xianlong ZHU ◽  
Cheng LI
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Land Cover ◽  
S Model
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