Potential natural vegetation dynamics driven by future long-term climate change and its hydrological impacts in the Hanjiang River basin, China

2012 ◽  
Vol 43 (1-2) ◽  
pp. 73-90 ◽  
Author(s):  
Fei Yuan ◽  
Liliang Ren ◽  
Zhongbo Yu ◽  
Yonghua Zhu ◽  
Jing Xu ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
21St Century ◽  
Land Surface ◽  
Natural Vegetation ◽  
Potential Natural Vegetation ◽  
Area Index ◽  
Hanjiang River ◽  
Ipcc Sres

Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via the Lund-Potsdam-Jena dynamic global vegetation model. Subsequently, predicted PFTs and LAIs were employed in the Xinanjiang vegetation-hydrology model for rainfall–runoff simulations. Results reveal that future long-term changes in precipitation, air temperature and atmospheric CO2 concentration would remarkably affect the spatiotemporal distribution of PFTs and LAIs. These climate-driven vegetation changes would further influence regional water balance. With the decrease in forest cover in the 21st century, plant transpiration and evaporative loss of intercepted canopy water will tend to fall while soil evaporation may rise considerably. As a result, total evapotranspiration may increase moderately with a slight increase in annual runoff depth. This indicates that, for long-term hydrological prediction, climate-induced changes in terrestrial vegetation cannot be neglected as the terrestrial biosphere plays an important role in land-surface hydrological responses.

scholarly journals Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO<sub>2</sub>

2021 ◽  
Vol 18 (17) ◽  
pp. 4985-5010 ◽  
Author(s):  
Alexander J. Winkler ◽  
Ranga B. Myneni ◽  
Alexis Hannart ◽  
Stephen Sitch ◽  
Vanessa Haverd ◽  
...  
Keyword(s):  
Climate Change ◽  
Leaf Area ◽  
Carbon Emissions ◽  
Land Surface ◽  
Carbon Sink ◽  
Natural Vegetation ◽  
Climate Projections ◽  
Co2 Fertilization ◽  
Area Index ◽  
Anthropogenic Carbon

Abstract. Satellite data reveal widespread changes in Earth's vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change, and consequent disturbances such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at the biome level that can be scaled to a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies for vegetation changes and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying causal counterfactual theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). The probabilistic attribution method clearly identifies the CO2 fertilization effect as the dominant driver in only two biomes, the temperate forests and cool grasslands, challenging the view of a dominant global-scale effect. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last 2 decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slowdown in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.

scholarly journals Slow-down of the greening trend in natural vegetation with further rise in atmospheric CO<sub>2</sub>

2021 ◽  
Author(s):  
Alexander J. Winkler ◽  
Ranga B. Myneni ◽  
Alexis Hannart ◽  
Stephen Sitch ◽  
Vanessa Haverd ◽  
...  
Keyword(s):  
Climate Change ◽  
Leaf Area ◽  
Carbon Emissions ◽  
Land Surface ◽  
Scale Effects ◽  
Natural Vegetation ◽  
Climate Projections ◽  
Co2 Fertilization ◽  
Area Index ◽  
Anthropogenic Carbon

Abstract. Satellite data reveal widespread changes of Earth's vegetation cover. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO2 fertilization, climate change and consequent disturbances, such as fires and droughts, are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at biome-level that can be scaled into a global picture of what is behind the observed changes is currently lacking. Here we analyze different datasets of decades-long satellite observations of global leaf area index (LAI, 1981–2017) as well as other proxies of vegetation changes, and identify several clusters of significant long-term changes. Using process-based model simulations (Earth system and land surface models), we disentangle the effects of anthropogenic carbon emissions on LAI in a probabilistic setting applying Causal Counterfactual Theory. The analysis prominently indicates the effects of climate change on many biomes – warming in northern ecosystems (greening) and rainfall anomalies in tropical biomes (browning). Our results do not support previously published accounts of dominant global-scale effects of CO2 fertilization. Altogether, our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last two decades. Most models substantially underestimate the emerging vegetation browning, especially in the tropical rainforests. Leaf area loss in these productive ecosystems could be an early indicator of a slow-down in the terrestrial carbon sink. Models need to account for this effect to realize plausible climate projections of the 21st century.

scholarly journals Slow-down of the greening trend in natural vegetation with further rise in atmospheric CO2

2020 ◽  
Author(s):  
Alexander J. Winkler ◽  
Ranga B. Myneni ◽  
Alexis Hannart ◽  
Victor Brovkin
Keyword(s):  
Climate Change ◽  
Leaf Area ◽  
Land Surface ◽  
Scale Effects ◽  
Carbon Sink ◽  
Global Scale ◽  
Natural Vegetation ◽  
Earth System ◽  
Area Index ◽  
Probabilistic Setting

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;Satellite data reveal widespread changes in vegetation cover of Earth&amp;#8217;s land surfaces. Regions intensively attended to by humans are mostly greening due to land management. Natural vegetation, on the other hand, is exhibiting patterns of both greening and browning in all continents. Factors linked to anthropogenic carbon emissions, such as CO&lt;sub&gt;2 &lt;/sub&gt;fertilization, climate change and consequent episodic disturbances (&lt;em&gt;e.g. &lt;/em&gt;fires and droughts) are hypothesized to be key drivers of changes in natural vegetation. A rigorous regional attribution at biome-level that can be scaled into a global picture of what is behind the observed changes is currently lacking.&lt;/p&gt; &lt;p&gt;Therefore, we analyze here the longest available satellite record of global leaf area index (LAI, 1981-2017) and identify several clusters of significant long-term changes at the biome scale. Using process-based model simulations (fully-coupled MPI-M Earth system model and 13 stand-alone land surface models), we disentangle the effects of rising CO&lt;sub&gt;2 &lt;/sub&gt;on LAI in a probabilistic setting applying Causal Counterfactual Theory.&lt;/p&gt; &lt;p&gt;Our analysis reveals a slowing down of greening and strengthening of browning trends, particularly in the last two decades (2000-2017). The decreases in LAI are primarily concentrated in regions of high LAI (&lt;em&gt;i.e. &lt;/em&gt;tropical forests), whereas the increases are in low LAI regions (&lt;em&gt;i.e. &lt;/em&gt;northern and arid lands). These opposing trends are reducing the LAI texture of natural vegetation at the global scale. The analysis prominently indicates the effects of climate change on many biomes &amp;#8211; warming in northern ecosystems and rainfall anomalies in tropical biomes. Our results do not support previously published accounts of dominant global-scale effects of CO&lt;sub&gt;2 &lt;/sub&gt;fertilization. Most models largely underestimate vegetation browning, especially in the tropical rainforests. The leaf area loss in these productive ecosystems could be an early indicator of a slow-down in the terrestrial carbon sink. Models need to better account for this effect to realize plausible Earth system projections of the 21&lt;sup&gt;st &lt;/sup&gt;century.&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;

Variations in land surface phenology and their response to climate change in Yangtze River basin during 1982–2015

2018 ◽  
Vol 137 (3-4) ◽  
pp. 1659-1674 ◽  
Author(s):  
Moxi Yuan ◽  
Lunche Wang ◽  
Aiwen Lin ◽  
Zhengjia Liu ◽  
Sai Qu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Land Surface ◽  
Yangtze River ◽  
Yangtze River Basin ◽  
Land Surface Phenology

scholarly journals Projecting marine fish production and catch potential in Bangladesh in the 21st century under long-term environmental change and management scenarios

2015 ◽  
Vol 73 (5) ◽  
pp. 1357-1369 ◽  
Author(s):  
Jose A. Fernandes ◽  
Susan Kay ◽  
Mostafa A. R. Hossain ◽  
Munir Ahmed ◽  
William W. L. Cheung ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Low Income ◽  
Nutrient Loading ◽  
Global Climate Model ◽  
Productive Capacity ◽  
Fish Production ◽  
Management Scenarios ◽  
Bombay Duck

Abstract The fisheries sector is crucial to the Bangladeshi economy and wellbeing, accounting for 4.4% of national gross domestic product and 22.8% of agriculture sector production, and supplying ca. 60% of the national animal protein intake. Fish is vital to the 16 million Bangladeshis living near the coast, a number that has doubled since the 1980s. Here, we develop and apply tools to project the long-term productive capacity of Bangladesh marine fisheries under climate and fisheries management scenarios, based on downscaling a global climate model, using associated river flow and nutrient loading estimates, projecting high-resolution changes in physical and biochemical ocean properties, and eventually projecting fish production and catch potential under different fishing mortality targets. We place particular interest on Hilsa shad (Tenualosa ilisha), which accounts for ca. 11% of total catches, and Bombay duck (Harpadon nehereus), a low price fish that is the second highest catch in Bangladesh and is highly consumed by low-income communities. It is concluded that the impacts of climate change, under greenhouse emissions scenario A1B, are likely to reduce the potential fish production in the Bangladesh exclusive economic zone by &lt;10%. However, these impacts are larger for the two target species. Under sustainable management practices, we expect Hilsa shad catches to show a minor decline in potential catch by 2030 but a significant (25%) decline by 2060. However, if overexploitation is allowed, catches are projected to fall much further, by almost 95% by 2060, compared with the Business as Usual scenario for the start of the 21st century. For Bombay duck, potential catches by 2060 under sustainable scenarios will produce a decline of &lt;20% compared with current catches. The results demonstrate that management can mitigate or exacerbate the effects of climate change on ecosystem productivity.

scholarly journals Effects of Forest Changes on Summer Surface Temperature in Changbai Mountain, China

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1551
Author(s):  
Jiaqi Zhang ◽  
Xiangjin Shen ◽  
Yanji Wang ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Changbai Mountain ◽  
Vegetation Coverage ◽  
Area Index ◽  
Forest Coverage ◽  
Cooling Effects

The area and vegetation coverage of forests in Changbai Mountain of China have changed significantly during the past decades. Understanding the effects of forests and forest coverage change on regional climate is important for predicting climate change in Changbai Mountain. Based on the satellite-derived land surface temperature (LST), albedo, evapotranspiration, leaf area index, and land-use data, this study analyzed the influences of forests and forest coverage changes on summer LST in Changbai Mountain. Results showed that the area and vegetation coverage of forests increased in Changbai Mountain from 2003 to 2017. Compared with open land, forests could decrease the summer daytime LST (LSTD) and nighttime LST (LSTN) by 1.10 °C and 0.07 °C, respectively. The increase in forest coverage could decrease the summer LSTD and LSTN by 0.66 °C and 0.04 °C, respectively. The forests and increasing forest coverage had cooling effects on summer temperature, mainly by decreasing daytime temperature in Changbai Mountain. The daytime cooling effect is mainly related to the increased latent heat flux caused by increasing evapotranspiration. Our results suggest that the effects of forest coverage change on climate should be considered in climate models for accurately simulating regional climate change in Changbai Mountain of China.

The «rainfall-runoff» system and its long-term fluctuations in the Siverskyi Donets River Basin (Ukraine)

2021 ◽  
Author(s):  
Hanna Bolbot ◽  
Vasyl Grebin
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
River Basin ◽  
Air Temperature ◽  
River Runoff ◽  
Annual Runoff ◽  
Annual Precipitation ◽  
Spring Flood ◽  
Current Period

&lt;p&gt;The current patterns estimation of the water regime under climate change is one of the most urgent tasks in Ukraine and the world. Such changes are determined by fluctuations in the main climatic characteristics - precipitation and air temperature, which are defined the value of evaporation. These parameters influence on the annual runoff distribution and long-term runoff fluctuations. In particular, the annual precipitation redistribution is reflected in the corresponding changes in the river runoff.&lt;br&gt;The assessment of the current state and nature of changes in precipitation and river runoff of the Siverskyi Donets River Basin was made by comparing the current period (1991-2018) with the period of the climatological normal (1961-1990).&lt;br&gt;In general, for this area, it was defined the close relationship between the amount of precipitation and the annual runoff. Against the background of insignificant (about 1%) increase of annual precipitation in recent decades, it was revealed their redistribution by seasons and separate months. There is a decrease in precipitation in the cold period (November-February). This causes (along with other factors) a decrease in the amount of snow and, accordingly, the spring flood runoff. There are frequent cases of unexpressed spring floods of the Siverskyi Donets River Basin. The runoff during March-April (the period of spring flood within the Ukrainian part of the basin) decreased by almost a third.&lt;br&gt;The increase of precipitation during May-June causes a corresponding (insignificant) increase in runoff in these months. The shift of the maximum monthly amount of precipitation from May (for the period 1961-1990) to June (in the current period) is observed.&lt;br&gt;There is a certain threat to water supply in the region due to the shift in the minimum monthly amount of precipitation in the warm period from October to August. Compared with October, there is a higher air temperature and, accordingly, higher evaporation in August, which reduces the runoff. Such a situation is solved by rational water resources management of the basin. The possibility of replenishing water resources in the basin through the transfer runoff from the Dnieper (Dnieper-Siverskyi Donets channel) and the annual runoff redistribution in the reservoir system causes some increase in the river runoff of summer months in recent decades. This is also contributed by the activities of the river basin management structures, which control the maintenance water users' of minimum ecological flow downstream the water intakes and hydraulic structures in the rivers of the basin.&lt;br&gt;Therefore, in the period of current climate change, the annual runoff distribution of the Siverskyi Donets River Basin has undergone significant changes, which is related to the annual precipitation redistribution and anthropogenic load on the basin.&lt;/p&gt;

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