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

<div> <div> <div> <p>Satellite data reveal widespread changes in vegetation cover of Earth&#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<sub>2 </sub>fertilization, climate change and consequent episodic disturbances (<em>e.g. </em>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.</p> <p>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<sub>2 </sub>on LAI in a probabilistic setting applying Causal Counterfactual Theory.</p> <p>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 (<em>i.e. </em>tropical forests), whereas the increases are in low LAI regions (<em>i.e. </em>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 &#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<sub>2 </sub>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<sup>st </sup>century.</p> </div> </div> </div>

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

Biogeosciences ◽

10.5194/bg-18-4985-2021 ◽

2021 ◽

Vol 18 (17) ◽

pp. 4985-5010 ◽

Cited By ~ 1

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.

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

10.5194/bg-2021-37 ◽

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.

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

Hydrology Research ◽

10.2166/nh.2011.111 ◽

2012 ◽

Vol 43 (1-2) ◽

pp. 73-90 ◽

Cited By ~ 7

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.

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Ability of the land surface model ISBA-A-gs to simulate leaf area index at the global scale: Comparison with satellites products

Journal of Geophysical Research Atmospheres ◽

10.1029/2005jd006691 ◽

2006 ◽

Vol 111 (D18) ◽

Cited By ~ 94

Author(s):

Anne-Laure Gibelin ◽

Jean-Christophe Calvet ◽

Jean-Louis Roujean ◽

Lionel Jarlan ◽

Sietse O. Los

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Land Surface ◽

Land Surface Model ◽

Global Scale ◽

Surface Model ◽

Area Index

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The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics

Geoscientific Model Development ◽

10.5194/gmd-4-701-2011 ◽

2011 ◽

Vol 4 (3) ◽

pp. 701-722 ◽

Cited By ~ 509

Author(s):

D. B. Clark ◽

L. M. Mercado ◽

S. Sitch ◽

C. D. Jones ◽

N. Gedney ◽

...

Keyword(s):

Climate Change ◽

Land Surface ◽

Carbon Allocation ◽

Carbon Sink ◽

Carbon Fluxes ◽

Methane Emissions ◽

Model Description ◽

Earth System ◽

Ecological Processes ◽

Living Plant

Abstract. The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

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Projections of leaf area index in earth system models

Earth System Dynamics ◽

10.5194/esd-7-211-2016 ◽

2016 ◽

Vol 7 (1) ◽

pp. 211-229 ◽

Cited By ~ 44

Author(s):

Natalie Mahowald ◽

Fiona Lo ◽

Yun Zheng ◽

Laura Harrison ◽

Chris Funk ◽

...

Keyword(s):

Climate Change ◽

Leaf Area Index ◽

Leaf Area ◽

Climate Change Impacts ◽

Earth System ◽

Area Index ◽

System Models ◽

Clear Cut ◽

The Tropics ◽

Earth System Models

Abstract. The area of leaves in the plant canopy, measured as leaf area index (LAI), modulates key land–atmosphere interactions, including the exchange of energy, moisture, carbon dioxide (CO2), and other trace gases and aerosols, and is therefore an essential variable in predicting terrestrial carbon, water, and energy fluxes. Here our goal is to characterize the LAI projections from the latest generation of earth system models (ESMs) for the Representative Concentration Pathway (RCP) 8.5 and RCP4.5 scenarios. On average, the models project increases in LAI in both RCP8.5 and RCP4.5 over most of the globe, but also show decreases in some parts of the tropics. Because of projected increases in variability, there are also more frequent periods of low LAI across broad regions of the tropics. Projections of LAI changes varied greatly among models: some models project very modest changes, while others project large changes, usually increases. Modeled LAI typically increases with modeled warming in the high latitudes, but often decreases with increasing local warming in the tropics. The models with the most skill in simulating current LAI in the tropics relative to satellite observations tend to project smaller increases in LAI in the tropics in the future compared to the average of all the models. Using LAI projections to identify regions that may be vulnerable to climate change presents a slightly different picture than using precipitation projections, suggesting LAI may be an additional useful tool for understanding climate change impacts. Going forward, users of LAI projections from the CMIP5 ESMs evaluated here should be aware that model outputs do not exhibit clear-cut relationships to vegetation carbon and precipitation. Our findings underscore the need for more attention to LAI projections, in terms of understanding the drivers of projected changes and improvements to model skill.

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Evaluation of Land Surface Models in Reproducing Satellite Derived Leaf Area Index over the High-Latitude Northern Hemisphere. Part II: Earth System Models

Remote Sensing ◽

10.3390/rs5083637 ◽

2013 ◽

Vol 5 (8) ◽

pp. 3637-3661 ◽

Cited By ~ 50

Author(s):

Alessandro Anav ◽

Guillermo Murray-Tortarolo ◽

Pierre Friedlingstein ◽

Stephen Sitch ◽

Shilong Piao ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Northern Hemisphere ◽

High Latitude ◽

Land Surface ◽

Earth System ◽

Land Surface Models ◽

Area Index ◽

Surface Models ◽

Earth System Models

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The Joint UK Land Environment Simulator (JULES), Model description – Part 2: Carbon fluxes and vegetation

Geoscientific Model Development Discussions ◽

10.5194/gmdd-4-641-2011 ◽

2011 ◽

Vol 4 (1) ◽

pp. 641-688 ◽

Cited By ~ 29

Author(s):

D. B. Clark ◽

L. M. Mercado ◽

S. Sitch ◽

C. D. Jones ◽

N. Gedney ◽

...

Keyword(s):

Climate Change ◽

Land Surface ◽

Carbon Allocation ◽

Carbon Sink ◽

Carbon Fluxes ◽

Methane Emissions ◽

Model Description ◽

Earth System ◽

Ecological Processes ◽

Living Plant

Abstract. The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Download Full-text