Sensitivity of global gross primary production to environmental drivers

2020 ◽  
Author(s):  
Wenjia Cai ◽  
Iain Colin Prentice
Keyword(s):  
Primary Production ◽  
Vegetation Cover ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Vapour Pressure Deficit ◽  
Terrestrial Ecosystems ◽  
Environmental Drivers ◽  
Generic Model ◽  
Terrestrial Plants ◽  
Green Vegetation

<p>Terrestrial Gross Primary Production (GPP), the total amount of carbon taken up by terrestrial plants, is one of the largest fluxes in the global carbon cycle – and a key process governing the capacity of terrestrial ecosystems to partly offset continuing anthropogenic CO<sub>2</sub> emissions. Accurate simulation of land carbon uptake and its response to environmental change is therefore essential for reliable future projections of the terrestrial carbon sink. However, there are still large uncertainties in the sensitivity of global GPP to environmental drivers. Here we use a recently developed and extensively tested generic model of GPP (the ‘P-model’), which uses satellite-derived green vegetation cover as an input, to simulate (a) trends in site-level GPP, as observed at eddy-covariance flux sites; (b) trends in global GPP, for comparison with independent geophysical estimates; and (c) quantitative spatial patterns of the sensitivity of grid-based GPP to green vegetation cover, vapour pressure deficit, temperature, solar radiation, soil moisture and atmospheric CO<sub>2.</sub></p>

Sensitivity of global gross primary production to elevated CO2

2021 ◽  
Author(s):  
Wenjia Cai ◽  
Iain Colin Prentice
Keyword(s):  
Field Experiments ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Light Response ◽  
Terrestrial Ecosystems ◽  
Percentage Increase ◽  
Terrestrial Plants ◽  
Fertilization Effect ◽  
Vegetation Models ◽  
The Impact

<p>Terrestrial ecosystems have accounted for more than half of the global carbon sink during the past decades and offset 25%-30% of current anthropogenic CO<sub>2</sub> emissions. The projected increase in CO<sub>2</sub> concentration will depend on the magnitude of terrestrial plants’ feedback to CO<sub>2</sub>: i.e. the sensitivity of plant carbon uptake in response to elevated CO<sub>2</sub>, and the strength of the CO<sub>2</sub> fertilization effect (CFE) in a changing (and warming) environment. Projecting vegetation responses to future increases in CO<sub>2</sub> concentration under climate change is a major uncertainty, as ecosystem models, field experiments and satellite-based models show large disagreements. In this study, using a recently developed, parameter-sparse model (the ‘P model’), we assess the sensitivity of GPP to increasing CO<sub>2</sub> under idealized conditions, in comparison with other vegetation models and field experiments. We investigate the impact of two central parameters, the ratio of J<sub>max </sub>to V<sub>cmax</sub> (at a common temperature) and the curvature of the light response curve, on the sensitivity of GPP to CO<sub>2</sub>. We also quantified the spatial-temporal trend of CFE using the β factor, defined as the percentage increase in GPP in response to a 100-ppm increase in atmospheric CO<sub>2</sub> concentration over a defined period. We show how modelled β has changed over the satellite era, and infer the possible effect of climatic variables on changes of CFE from spatial patterns of the modelled trend in β.</p>

scholarly journals Biophsyical constraints on gross primary production by the terrestrial biosphere

2014 ◽  
Vol 11 (20) ◽  
pp. 5987-6001 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
T. W. Davis
Keyword(s):  
Primary Production ◽  
Optimality Theory ◽  
Vegetation Cover ◽  
Gross Primary Production ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Water Shortage ◽  
C3 Plants ◽  
Environmental Controls ◽  
Green Vegetation

Abstract. Persistent divergences among the predictions of complex carbon-cycle models include differences in the sign as well as the magnitude of the response of global terrestrial primary production to climate change. Such problems with current models indicate an urgent need to reassess the principles underlying the environmental controls of primary production. The global patterns of annual and maximum monthly terrestrial gross primary production (GPP) by C3 plants are explored here using a simple first-principles model based on the light-use efficiency formalism and the Farquhar model for C3 photosynthesis. The model is driven by incident photosynthetically active radiation (PAR) and remotely sensed green-vegetation cover, with additional constraints imposed by low-temperature inhibition and CO2 limitation. The ratio of leaf-internal to ambient CO2 concentration in the model responds to growing-season mean temperature, atmospheric dryness (indexed by the cumulative water deficit, Δ E) and elevation, based on an optimality theory. The greatest annual GPP is predicted for tropical moist forests, but the maximum (summer) monthly GPP can be as high, or higher, in boreal or temperate forests. These findings are supported by a new analysis of CO2 flux measurements. The explanation is simply based on the seasonal and latitudinal distribution of PAR combined with the physiology of photosynthesis. By successively imposing biophysical constraints, it is shown that partial vegetation cover – driven primarily by water shortage – represents the largest constraint on global GPP.

Moisture and heat advection as drivers of global ecosystem productivity

2020 ◽  
Author(s):  
Dominik L. Schumacher ◽  
Jessica Keune ◽  
Diego G. Miralles
Keyword(s):  
Primary Production ◽  
Interannual Variability ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Ecosystem Productivity ◽  
Climate Conditions ◽  
Source Regions ◽  
Heat And Moisture ◽  
The Impact

<p>Terrestrial ecosystems play a key role in climate by dampening the increasing atmospheric CO<sub>2</sub> concentrations primarily caused by anthropogenic fossil fuel emissions. The capability of the land biosphere to act as a carbon sink largely depends on climate conditions, which determine the energy and water availability required by plants to grow. Even though only a small part of the global land area is covered by vegetation, the impact of extreme dry and wet seasons has been shown to largely drive the global interannual variability of gross primary production. The climate in a certain area can be seen as the balance of different heat and moisture fluxes: local surface–atmosphere fluxes from below, entrainment of heat and moisture from aloft, and ‘horizontal’ advection of heat and moisture from upwind regions. The latter provides a mechanism for remote regions to impact gross primary production downwind, and has received less scientific attention. Here, advection is inferred from a bird’s eye perspective, focussing on the five ecoregions with the largest interannual variability in peak productivity around the globe. Employing the atmospheric Lagrangian trajectory model FLEXPART, driven by ERA-Interim reanalysis data, we track the air residing over ecoregions back in time to deduce the origins of heat and moisture that affect ecosystem gross primary production. Utilizing the evaporative source regions supplying water for precipitation to these ecosystems, as well as the analogous source regions of advected heat, we estimate the contribution of advection to gross primary production. Our findings show that source regions of heat and moisture are not congruent: upwind land surfaces typically supply most of the advected heat, whereas upwind oceans tend to provide more moisture. Moreover, low gross primary production in heat-stressed and water-limited ecosystems is often accompanied by enhanced heat and reduced moisture advection from land regions, exacerbated by upwind land–atmosphere feedbacks. These results demonstrate that anomalies in atmospheric advection can cause ecosystem productivity extremes. Particularly in light of ongoing climate change, we emphasize the potentially detrimental effects of upwind areas that may cause long-lasting impacts on the terrestrial carbon budget, thereby further affecting the climate.</p>

scholarly journals Biophysical constraints on gross primary production by the terrestrial biosphere

2014 ◽  
Vol 11 (2) ◽  
pp. 3209-3240 ◽  
Author(s):  
H. Wang ◽  
I. C. Prentice ◽  
T. W. Davis
Keyword(s):  
Primary Production ◽  
Optimality Theory ◽  
Vegetation Cover ◽  
Gross Primary Production ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Water Shortage ◽  
C3 Plants ◽  
Environmental Controls ◽  
Green Vegetation

Abstract. Persistent divergences among the predictions of complex carbon cycle models include differences in the sign as well as the magnitude of the response of global terrestrial primary production to climate change. This and other problems with current models indicate an urgent need to re-assess the principles underlying the environmental controls of primary production. The global patterns of annual and maximum monthly terrestrial gross primary production (GPP) by C3 plants are explored here using a simple first-principles model based on the light-use efficiency formalism and the Farquhar model for C3 photosynthesis. The model is driven by incident photosynthetically active radiation (PAR) and remotely sensed green vegetation cover, with additional constraints imposed by low-temperature inhibition and CO2 limitation. The ratio of leaf-internal to ambient CO2 concentration in the model responds to growing-season mean temperature, atmospheric dryness (indexed by the cumulative water deficit, ΔE) and elevation, based on optimality theory. The greatest annual GPP is predicted for tropical moist forests, but the maximum (summer) monthly GPP can be as high or higher in boreal or temperate forests. These findings are supported by a new analysis of CO2 flux measurements. The explanation is simply based on the seasonal and latitudinal distribution of PAR combined with the physiology of photosynthesis. By successively imposing biophysical constraints, it is shown that partial vegetation cover – driven primarily by water shortage – represents the largest constraint on global GPP.

A decreasing trend in global soil water storage from 1981 to 2017

2021 ◽  
Author(s):  
XinRui Luo ◽  
Shaoda Li ◽  
Wunian Yang ◽  
Liang Liu ◽  
Xiaolu Tang
Keyword(s):  
Soil Water ◽  
Water Loss ◽  
Root Zone ◽  
Carbon Sink ◽  
Temporal Trends ◽  
Water Storage ◽  
Terrestrial Ecosystems ◽  
Environmental Drivers ◽  
Soil Water Storage ◽  
Soil Drought

<p>Soil water storage serves as a vital resource of the terrestrial ecosystems, and it can significantly influence water cycle and carbon cycling with the frequent occurrence of soil drought induced by land-atmosphere feedbacks. However, there are high variations and uncertainties of root zone soil water storage. This study applied comparison map profile (CMP), Mann-Kendall test, Theil-Sen estimate and partial correlation analysis to (1) estimate the global root zone (0~1 m) soil water storage, (2) and investigate the spatial and temporal patterns from 1981 to 2017 at the global scale, (3) and their relationships with environmental drivers (precipitation, temperature, potential evaportranspiration) using three soil moisture (SM) products – ERA-5, GLDAS and MERRA-2. Globally, the average annual soil water storage from 1981 to 2017 varied significantly, ranging from 138.3 (100 Pg a<sup>-1</sup>, 1 Pg = 10<sup>15</sup> g) in GLDAS to 342.6 (100 Pg a<sup>-1</sup>) in ERA-5. Soil water storage of the three SM products consistently showed a decreasing trend. However, the temporal trend of soil water storage among different climate zones was different, showing a decreasing trend in tropical, temperate and cold zones, but an increasing trend in polar regions. On the other hand, temporal trends in arid regions differed from ERA-5, GLDAS and MERRA-2. Spatially, the SM products differed greatly, particularly for boreal areas with D value higher for 2500 Mg ha<sup>-1</sup> a<sup>-1</sup> and CC value lower for -0.2 between GLDAS and MERRA-2. Over 1981 to 2017, water storage of more than 50% of the global land area suffered from a decreasing trend, especially in Africa and Northeastern of China. Precipitation was the main dominated driver for variation of soil water storage, and distribution varied in different SM products. In conclusion, a global decreasing trend in soil water storage indicate a water loss from soils, and how the water loss affecting carbon sink in terrestrial ecosystems under ongoing climate change needs further investigation.</p>

Incorporating non-stomatal limitation improves the performance of leaf and canopy models at high vapour pressure deficit

2019 ◽  
Author(s):  
J Yang ◽  
R A Duursma ◽  
M G De Kauwe ◽  
D Kumarathunge ◽  
M Jiang ◽  
...  
Keyword(s):  
Gas Exchange ◽  
Primary Production ◽  
Vapour Pressure ◽  
Leaf Gas Exchange ◽  
Gross Primary Production ◽  
Vapour Pressure Deficit ◽  
Stomatal Limitation ◽  
Flow Measurements ◽  
Hydraulic Limitation ◽  
The Future

Abstract Vapour pressure deficit (D) is projected to increase in the future as temperatures rise. In response to increased D, stomatal conductance (gs) and photosynthesis (A) are reduced, which may result in significant reductions in terrestrial carbon, water, and energy fluxes. It is thus important for gas exchange models to capture the observed responses of gs and A with increasing D. We tested a series of coupled A-gs models against leaf gas exchange measurements from the Cumberland Plain Woodland (Australia), where D regularly exceeds 2 kPa and can reach 8 kPa in summer. Two commonly used A-gs models (Leuning 1995 and Medlyn et al. 2011) were not able to capture the observed decrease in A and gs with increasing D at the leaf scale. To explain this decrease in A and gs, two alternative hypotheses were tested: hydraulic limitation (i.e., plants reduce gs and/or A due to insufficient water supply) and non-stomatal limitation (i.e., downregulation of photosynthetic capacity). We found that the model that incorporated a non-stomatal limitation captured the observations with high fidelity and required the fewest number of parameters. While the model incorporating hydraulic limitation captured the observed A and gs, it did so via a physical mechanism that is incorrect. We then incorporated a non-stomatal limitation into the stand model, MAESPA, to examine its impact on canopy transpiration and gross primary production. Accounting for a non-stomatal limitation reduced the predicted transpiration by ~19%, improving the correspondence with sap flow measurements, and gross primary production by ~14%. Given the projected global increases in D associated with future warming, these findings suggest that models may need to incorporate non-stomatal limitation to accurately simulate A and gs in the future with high D. Further data on non-stomatal limitation at high D should be a priority, in order to determine the generality of our results and develop a widely applicable model.

Testing across vegetation types for common environmental dependencies of Gross Primary Production

2020 ◽  
Author(s):  
Keith Bloomfield ◽  
Benjamin Stocker ◽  
Colin Prentice
Keyword(s):  
Soil Moisture ◽  
Primary Production ◽  
Eddy Covariance ◽  
Empirical Analysis ◽  
Gross Primary Production ◽  
Incident Light ◽  
Vapour Pressure Deficit ◽  
Additive Models ◽  
Theoretical Modelling ◽  
Wide Range

<p>Accurate simulations of gross primary production (GPP) are vital for Earth System Models that must inform public policy decisions.  The instantaneous controls of leaf-level photosynthesis, which can be measured in manipulative experiments, are well established.  At the canopy scale, however, there is no consensus on how GPP depends on (a) light or (b) other aspects of the physical environment such as temperature and CO<sub>2</sub>.  Models of GPP make a variety of different assumptions when ‘scaling-up’ the standard model of photosynthesis.  As a troublesome consequence, they make a variety of different predictions about how GPP responds to contemporary environmental change.</p><p>This problem can be tackled by theoretically based modelling, or by empirical analysis of GPP as reconstructed from eddy-covariance flux measurements.  Theoretical modelling has provided an explanation for why ‘light-use efficiency’ (LUE) models work well at time scales of a week or longer.  The same logic provides a justification for the use of LUE as a key metric in an empirical analysis.  By focusing on LUE, we can isolate the controls of GPP that are distinct from its over-riding control by absorbed light.  We have used open-access eddy covariance data from over 100 sites, collated over 20 years (the number of sites has grown with time).  These sites, located in a wide range of biomes and climate zones, form part of the FLUXNET network.  We have combined the flux data with a satellite product (FPAR from MODIS) that provides spatial estimates of the fraction of incident light absorbed by green vegetation.  Soil moisture at flux sites was estimated using the SPLASH model, with appropriate meteorological inputs, and soil water-holding capacity derived using SoilGrids.  LUE was then calculated as the amount of carbon fixed per unit of absorbed light.  We then considered additive models (incorporating multiple explanatory factors) that support non-linear responses, including a peaked response to temperature.  Recognising that our longitudinal data are not fully independent, we controlled for the hierarchical nature of the dataset through a variance structure that nests measurement year within site location.</p><p>In arriving at a final parsimonious model, we show that daytime air temperature and vapour pressure deficit, and soil moisture content, are all salient predictors of LUE.  The same explanatory terms are retained in iterations of this analysis run at timescales from weeks to months.  Model performance was not significantly improved by inclusion of additional variables such as rainfall, site elevation or vegetation category (e.g. Plant Functional Type, PFT).  This empirical analysis supports the notion that GPP is predictable using a single model structure that is common to different PFTs.</p>

Response of tropical terrestrial gross primary production to the super El Niño event in 2015

2020 ◽  
Author(s):  
Jiawen Zhu ◽  
Minghua Zhang ◽  
Yao Zhang ◽  
Xiaodong Zeng ◽  
Xiangming Xiao
Keyword(s):  
Carbon Cycle ◽  
Primary Production ◽  
Tropical Forests ◽  
Gross Primary Production ◽  
Critical Role ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Climate Feedback ◽  
Test Case ◽  
Climate Data

<p>The Gross Primary Production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multi-year mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in non-forests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in non-forests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and non-forest ecosystems, and provide a test case for carbon cycle parameterization and carbon-climate feedback simulation in models.</p>

Inferring non-steady-state terrestrial vegetation carbon turnover times from multi-decadal space-borne observations on global scale

2020 ◽  
Author(s):  
Naixin Fan ◽  
Simon Besnard ◽  
Maurizio Santoro ◽  
Oliver Cartus ◽  
Nuno Carvalhais
Keyword(s):  
Climate Change ◽  
Steady State ◽  
Carbon Fixation ◽  
Carbon Sink ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Turnover Time ◽  
Terrestrial Vegetation ◽  
Time Step

<p>The global biomass is determined by the vegetation turnover times (τ) and carbon fixation through photosynthesis. Vegetation turnover time is a central parameter that not only partially determines the terrestrial carbon sink but also the response of terrestrial vegetation to the future changes in climate. However, the change of magnitude, spatial patterns and uncertainties in τ as well as the sensitivity of these processes to climate change is not well understood due to lack of observations on global scale. In this study, we explore a new dataset of annual above-ground biomass (AGB) change from 1993 to 2018 from spaceborne scatterometer observations. Using the long-term, spatial-explicit global dynamic dataset, we investigated how τ change over almost three decades including the uncertainties. Previous estimations of τ under steady-state assumption can now be challenged acknowledging that terrestrial ecosystems are, for the most of cases, not in balance. In this study, we explore this new dataset to derive global maps of τ in non-steady-state for different periods of time. We used a non-steady-state carbon model in which the change of AGB is a function of Gross Primary Production (GPP) and τ (ΔAGB = α*GPP-AGB/ τ). The parameter α represents the percentage of incorporation of carbon from GPP to biomass. By exploring the AGB change in 5 to 10 years of time step, we were able to infer τ and α from the observations of AGB and GPP change by solving the linear equation. We show how τ changes after potential disturbances in the early 2000s in comparison to the previous decade. We also show the spatial distributions of α from the change of AGB. By accessing the change in biomass, τ and α as well as their associated uncertainties, we provide a comprehensive diagnostic on the vegetation dynamics and the potential response of biomass to disturbance and to climate change.   </p><p></p><p></p><p></p><p></p><p></p><p></p>

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