The terrestrial vegetation carbon balance is controlled not just by photosynthesis, but by respiration, carbon allocation, turnover (comprising litterfall, background mortality and disturbances) and wider vegetation dynamics. Observed, and likely future, changes in vegetation structure and functioning are the result of interactions of these processes with atmospheric carbon dioxide concentration, climate and human activities. The quantification and assessment of such changes has proven extremely challenging because of a lack of observations at large scales and over the long time periods required to evaluate trends.
Thus, our current understanding of the environmental controls on vegetation dynamics and properties, and, in turn, their impact on carbon stocks in biomass and soils, is limited. The behaviour of vegetation models regarding many of the processes mentioned above remains under-constrained at scales from landscape to global. This gives rise to high uncertainty as to whether the terrestrial vegetation will continue to act as a carbon sink under future environmental changes, or whether increases in autotrophic respiration or carbon turnover might counteract this negative feedback to climate change. For instance, accelerated background tree mortality or more frequent and more severe disturbance events (e.g. drought, fire, insect outbreaks) might turn vegetation into carbon sources. Likewise, understanding how these shifts in dynamics will influence forest composition is crucial for long-term carbon cycle projections.
Uncertainties and/or data gaps in large-scale empirical products of vegetation dynamics, carbon fluxes and stocks may be overcome by extensive collections of field data and new satellite retrievals of forest biomass and other vegetation properties. Such novel datasets may be used to evaluate, develop and parametrize global vegetation models and hence to constrain present and future simulations of vegetation dynamics. Where no observations exist, exploratory modelling can investigate realistic responses and identify necessary measurements. We welcome contributions that make use of observational approaches, vegetation models, or model-data integration techniques to advance understanding of the effects of environmental change on vegetation dynamics, tree mortality and carbon stocks and fluxes at local, regional or global scales and/or at long time scales.
vPICO presentations: Fri, 30 Apr
Tree mortality has been pointed out as a key factor to quantify global forests carbon stocks and turnover. While there have been recent developments on observational studies aiming at detection and attribution of tree mortality using remote sensing data in temperate forests, the spatial and temporal distribution of tropical forests mortality is still poorly understood. Tropical forests pose a challenge for mortality detection due to its rich diversity of plant species and heterogeneous canopy structure, which also leads to the occurrence of very frequent and localized mortality events rather than widespread mortality as seen in some temperate forests. Here, we report on recent developments on estimates of spatialized forest dynamics over tropical forests leveraging large datasets of airborne lidar and a newly established link between canopy gaps and canopy mortality. Using multi-temporal lidar datasets collected at five Brazilian Amazon forests with varied forest structure, we linked static gaps, i.e. holes in the forest observed at one date, to dynamic gaps, i.e. gaps that opened from one date to another. Using 610 flight lines of airborne lidar data covering an area >2,300 km² across the Brazilian Amazon, we mapped the static gaps and used them to analyze potential natural and human-induced drivers using generalized linear models. Finally, we produced estimates of annual dynamic gap rates (% yr-1) for the whole Amazon using the combination of the environmental-climate model and the static-dynamic gaps relationship. Our findings show well-defined spatial patterns of dynamic gaps over the Amazon, with 20-35% faster dynamics in the west and southeast than in the central-east and north. Higher gap fractions were more often found at southern and eastern Brazilian Amazon, bordering the ‘deforestation arch’, i.e. regions with increased human influence. Dynamic gaps showed a significant relationship with field mortality rates (R² = 0.40), but with 60% lower magnitude. In fact, what we have detected is very likely mortality with the predominant emphasis of lidar on detecting uprooted and broken mode of death. The analysis also provided new insights on the dynamics of remote areas where we have never visited before. New challenges include testing the gap-method over other sites with multi-temporal data, developing methods to detect standing dead trees, and mapping other drivers such as liana-infested forests. Merging improved regional quantification of dynamic gap estimates with vegetation modelling offers potential to explore how forest dynamics is influencing carbon stocks and turnover, and how they may evolve in the future.
How to cite: Dalagnol, R., Wagner, F. H., Galvão, L. S., Streher, A. S., Phillips, O. L., Gloor, E., Ometto, J. P. H. B., and Aragão, L. E. O. C.: Mind the gap: New insights on large-scale forest dynamics over Amazonian forests from airborne lidar and canopy gap data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11046, https://doi.org/10.5194/egusphere-egu21-11046, 2021.
The land surface is absorbing carbon from the atmosphere. Tropical forests play a key role in this carbon uptake. Recent analyses of 565 long-term forest inventory plots across Africa and Amazonia show that structurally intact tropical forest are a large carbon sink, but that this sink has recently saturated and is projected to be in long-term decline. Here we compare these results with estimates from the two most recent generations of Earth System Models, CMIP5 (19 models) and CMIP6 (17 models). We show that, while CMIP5 and CMIP6 are of similar skill, they do not reproduce the observed 1985-2014 carbon dynamics. The pan-tropical net sink from inventory data is 0.99 Pg C yr-1 (95% CI 0.7–1.3) between 2000–2010, the best sampled decade, double the CMIP6 multimodel-mean of 0.45 Pg C yr-1 (95% CI 0.35–0.55) over the same decade. The observed saturating and declining sink beginning in Amazonia in the 1990s and Africa in the 2010s is not captured by the models, which show modest increases in sink strength. The future pan-tropical net sink from the statistical model decreases by 0.23 Pg C per decade (95% CI 0.09–0.39) until the 2030s, while CMIP6 multimodel-means project an increasing carbon sink under all scenarios (0.01–0.03 Pg C per decade; 95% CI 0.00–0.06) except the low-CO2 scenario (-0.02 Pg C per decade; 95% CI -0.01–0.03). CMIP models balance positive CO2 fertilisation with negative responses to higher temperatures and droughts on carbon gains from tree growth similarly to observations, but the modelling of carbon losses from tree mortality does not correspond well to the inventory data. Reason for the model-observation differences is the treatment of mortality in models. Integrated research programs combining continued tropical forest monitoring and targeted experiments are needed to reduce the uncertainties in this key carbon cycle feedback in next-generation models.
How to cite: Koch, A., Hubau, W., and Lewis, S. L.: Earth System Models are not capturing observed tropical forest carbon dynamics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-764, https://doi.org/10.5194/egusphere-egu21-764, 2021.
Grasslands cover ca. 7% (2,100,000 km2) of the African continent. They provide a wide range of ecosystem services (e.g., forage, water, recreational spaces, carbon sequestration), and host large wildlife communities. Despite their importance, African grasslands are reported to be suffering from degradation and, perhaps more worryingly, have received little consideration within international policies (e.g., United Nations Sustainable Development Goals). A key issue at present is widespread woody plant encroachment (WPE), which it is shifting African grassland from a grassy- to a (less palatable) woody-dominated biome. However, the way climatic (e.g., precipitation, soil moisture) and non-climatic disturbances (e.g., fire, population density) affect WPE is still poorly understood, particularly at large spatiotemporal scales. Here we identified grasslands in sub-Saharan Africa according to the ESA Climate Change Initiative (CCI) land cover product and use vegetation optical depth (VOD) from passive microwave observations as a proxy for woody vegetation change between 1992 and 2011. We then use independent climatic (precipitation and soil moisture) and non-climatic (burn intensity, population change) data to assess how both spatiotemporal variations and interactions between climatic and non-climatic drivers controlled rates of VOD increase during 1992-2011. We consider not only annual precipitation, soil moisture, fire, and population data, but also integrated and lagged precipitation data (both up to five years ahead of VOD) in these models. Preliminary results reveal a large overall increase in woody vegetation in sub-Saharan Africa grasslands as well as considerable spatiotemporal variation in VOD change that is not due to climatic factors alone.
How to cite: D'Adamo, F., Spake, R., Bullock, J., Ogutu, B., Dash, J., and Eigenbrod, F.: Continental-scale modelling of the effects of climatic and non-climatic disturbances on woody plant encroachment in the grasslands of Africa, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7425, https://doi.org/10.5194/egusphere-egu21-7425, 2021.
Australia plays an important role in the global terrestrial carbon cycle on inter-annual timescales. While the Australian continent is included in global assessments of the carbon cycle, the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations of net biome productivity (NBP) and the carbon stored in vegetation between 1901 to 2018 from 13 DGVMs (TRENDY v8 ensemble). The TRENDY models simulated differing magnitudes of NBP on inter-annual timescales, leading to marked differences in carbon accumulation in the vegetation on decadal to centennial timescales. We showed that the spread in carbon storage resulted from differences in simulated carbon residence time rather than differences in net carbon uptake. Differences in simulated long-term accumulated NBP between models were mostly due to model responses to land-use change. The DGVMs also simulated different sensitivities to atmospheric CO2 concentration. Notably, models with nutrient cycles did not simulate the smallest response. While our results suggested that changes in the climate forcing do not have a large impact on the carbon cycle on long timescales, the inter-annual variability in precipitation drives the year-to-year variability in NBP. We analysed the impact of key modes of climate variability, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). While the DGVMs agreed on sign of the response of NBP to El Niño and La Niña, and to positive and negative IOD events, the magnitude of inter-annual variability in NBP differs strongly between models. In addition, we identified simulated phenology and fire as associated with high model uncertainty, indicating differences in simulated vegetation composition and process representation. Model disagreement in simulated vegetation carbon, phenology and carbon residence time imply different types of vegetation cover across Australia between models, whether prescribed or resulting from model assumptions. Our study highlights the need to evaluate parameter assumptions and key processes that drive vegetation dynamics, such as phenology, mortality and fire, in an Australian context to reduce uncertainty across models.
How to cite: Teckentrup, L., De Kauwe, M., Pitman, A., Bastrikov, V., Goll, D., Haverd, V., Jain, A., Joetzjer, E., Kato, E., Lienert, S., Lombardozzi, D., McGuire12, P., Melton, J., Nabel, J., Pongratz, J., Sitch, S., Walker, A., Wiltshire, A., and Zaehle, S.: Assessing the representation of the Australian carbon cycle in global vegetation models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3620, https://doi.org/10.5194/egusphere-egu21-3620, 2021.
Over the last decades, the vegetation dynamics have been severely disturbed due to the increasing intensity and occurrence of extreme events. The activity of terrestrial ecosystems is particularly susceptible to the climate variability, and their recently regional changes, mainly linked to the occurrence of extreme climatic events, are leading to rapid changes on natural vegetation cycle, plants productivity and terrestrial carbon cycle.
Droughts have been broadly recognized, among a wide range of extreme events, as playing a central role on the carbon cycle. Dry conditions contribute to the occurrence of high hydrological stress on vegetation, generating disturbances on the regular photosynthesis and vegetation mechanisms. Furthermore, they may increase the risk of fires, enhancing the losses on carbon stocks and plants productivity and inhibiting the ecosystems to regenerate and recover for a long time.
A wide range of works have recently shown that Europe, and in particular, the Mediterranean region, has been affected by severe droughts and large fires in the last decades. Therefore, we propose to assess the impact of a set of the severest droughts and large fires, between 2001 and 2019, over three different regions of Mediterranean basin, in order to assess their influence on vegetation, by evaluating the persistency of soil dry conditions and the observation of the number of months that vegetation’s activity is disturbed. This analysis allowed the quantification of the carbon losses occurred due to the referred extreme events, and also, the observation of the time response and recovery process of vegetation during the following months. In this study, we used remote sense products to monitor the vegetation production and activity (MODIS GPP and PSNet), to assess the soil moisture (ESA CCI SM) and to detect burned areas (FIRE CCI51).
This work was supported by FCT through projects IMPECAF (PTDC/CTA-CLI/28902/2017), FIRECAST (PCIF/GRF/0204/2017) and by IDL (UIDB/50019/2020).
How to cite: Silva, T. E., Russo, A., and Gouveia, C. M.: The Impact of Mediterranean Droughts and Large Fires on the Carbon Balance of Vegetation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11135, https://doi.org/10.5194/egusphere-egu21-11135, 2021.
In the past, terrestrial ecosystems have largely functioned as carbon sinks, capturing nearly 30% of anthropogenic carbon dioxide emissions (Le Quéré et al. 2009). Forest ecosystems, which cover roughly 30% of the land surface, play a fundamental role in maintaining this sink by storing nearly half of all terrestrial carbon (Pan et al. 2011; Bonan 2008). Over large parts of Europe, these forest ecosystems are dominated by European beech. Consequently, the reaction of beech to climate extremes is central to the ability of European forests to act as carbon sinks. Disconcertingly, the projected – and indeed already observed – increase in frequency and severity of drought across Europe threatens to shift forest ecosystems from carbon sinks to carbon sources (Ciais et al. 2005). Concurrently, the incidence of late-spring frost events in Europe is on the rise. While these events are considerably more localized and do not result in the same widespread reduction of ecosystem productivity as droughts, the damage to the photosynthetic apparatus of affected trees forces the mobilization of non-structural carbohydrates (NSC) to ensure tree survival. We analyze high-resolution historical (E-OBS 0.1°) and projected (EURO-CORDEX RCP 2.6 & RCP 8.5 0.11°) climate data to identify localized changes in the frequency of sequentially occurring drought and late-spring frost events across Europe. Subsequently, we use a modified version of the standalone NSC-model SUGAR (Jones et al. 2020) to ascertain the effect of sequentially occurring climate extremes on the carbon reserves of European beech forests. Here, we identify differences in the impact of isolated extremes (either frost or drought) and sequential extremes (frost followed by drought and vice versa) on the regulation of the NSC pool. Through the integration of SUGAR with the LPJ-GUESS DGVM (Smith et al. 2014; Sitch et al. 2003) we further quantify the effect of sequentially occurring climate extremes on the productivity of beech forest ecosystems in central Europe.
How to cite: Meyer, B. F., Rammig, A., Buras, A., and Zang, C. S.: Shifts in the frequency of sequentially occurring late-spring frost and drought impact the dynamics of non-structural carbohydrates in European beech, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9444, https://doi.org/10.5194/egusphere-egu21-9444, 2021.
Boreal forests are located at latitudes that are predicted to experience some of the greatest warming on the planet. Forests growing on permafrost may be particularly vulnerable, with accelerated soil warming and permafrost degradation linked to changes in woody net primary productivity (NPPw). Recent evidence suggests that the responses of NPPw to permafrost thaw are mixed, with both increases and decreases in productivity observed following the onset of permafrost degradation. What determines these contrasting responses is currently poorly understood. This leads to uncertainties in predicting the future vegetation and carbon dynamics in permafrost regions, which propagate to climate projections in Earth System Models. Here, we propose a framework, and a set of hypotheses to explain the observed differences in the response of NPPw to permafrost thaw. We argue that the relationship between permafrost thaw and NPPw is non-linear and determined by a set of climatic and environmental variables. On this basis, we partition ecosystems into classes, and describe their relationships between permafrost thaw and NPPw.
How to cite: Kulawska, A., MacKenzie, A. R., Kettridge, N., Ullah, S., and A. M. Pugh, T.: On thin ice: contrasting responses of woody NPP to permafrost thaw, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1579, https://doi.org/10.5194/egusphere-egu21-1579, 2021.
Tundra-taiga ecotone dynamics play a relevant role in the global carbon cycle. However, it is rather uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. This knowledge gap stems from the complex permafrost-vegetation interactions, not yet fully understood. Consequently, shedding light on the role of current and future active layer dynamics is crucial for an accurate prediction of treeline dynamics, and thus for aboveground forest biomass and carbon stock developments.
We make use of a coupled model version combining CryoGrid, a one-dimensional permafrost land-surface model, with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.) in Siberia. Following a parametrization against an extensive field data set of 100+ forest inventories conducted along the Siberian treeline (97-169° E), we run simulations for the upcoming centuries forced by climatic change scenarios.
The coupled model setup benefits from the detailed process implementation gained while developing the individual models. Therefore, we can reproduce the energy transfer and thermal regime in permafrost ground as well as the radiation budget, nitrogen and photosynthetic profiles, canopy turbulence, and leaf fluxes, while at the same time, predicting the expected establishment, die-off, and treeline movements of larch forests. In our analyses, we focus on vegetation and permafrost dynamics and reveal the magnitudes of different feedback processes between permafrost, vegetation, and current and future climate in Northern Siberia.
How to cite: Kruse, S., Stünzi, S. M., Langer, M., Boike, J., and Herzschuh, U.: Assessing the impact of permafrost-vegetation interaction on treeline dynamics in Siberia with the individual-based, spatially explicit treeline model LAVESI coupled to the permafrost land-surface model CryoGrid, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14119, https://doi.org/10.5194/egusphere-egu21-14119, 2021.
Changes in future above-ground biomass (AGB) of terrestrial ecosystems is one of the current interests in the light of climate change and essential to forecast for predicting potential climate feedbacks such as influence on the carbon balance. The tundra-taiga ecotone is a region that is prone to notable above-ground biomass changes, in the first instance due to the treeline advance. Forest is expected to occupy non-polygonal tundra. Our study region in central Chukotka (Northeastern Siberia) is a mountainous area on the northern border of the tundra-taiga ecotone that covers a wide range of vegetation types on a density gradient starting with lichen communities via open graminoid tundra to forest tundra. There is only one tree species – a deciduous conifer Larix cajanderi. We applied the individual-based spatially explicit model LAVESI to simulate larch AGB change from nowadays to 3000 AD under different climate scenarios, depending on Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5 and RCP 8.5. We implemented in the model topographical parameters, as well as region-specific individual larch AGB equations, biological parameters of the tree growth and climate variables. We validated the new version of the model against field and Landsat satellite-based data, as well as a high spatial resolution image with distinctive trees visible, provided by ESRI (ArcGIS/World_imagery). Our first results are indicating mostly densification of existing tree stands before 2200 AD and forest expansion in the study region after 2200 AD even under the mildest RCP 2.6 scenario. First evaluations of the average tree AGB increase rates from present to 2200 AD are ranges from 0.007 (RCP 2.6) to 0.01 (RCP 8.5) kg*m-2*yr-1. Obtained rates of tree AGB change and its future distribution on the landscape can be particularly useful for conservation measures and modelling of future above-ground carbon stock dynamics.
How to cite: Shevtsova, I., Herzschuh, U., Heim, B., and Kruse, S.: Tree above-ground biomass dynamics in the Northeast Siberian tundra-taiga from nowadays to 3000 AD, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15109, https://doi.org/10.5194/egusphere-egu21-15109, 2021.
Net terrestrial carbon uptake is primarily driven by increases in net primary productivity (NPP) and/or the residence time of carbon in vegetation and soil. As such, it is of critical importance to accurately quantify spatio-temporal variation in both terms and determine their drivers. Both NPP and residence times are modulated by changing environmental conditions, including climate change and variability, atmospheric CO2, and Land Use and Land Cover Changes (LULCC). For the historical period, 1901-2019, outputs from a suite of Dynamic Global Vegetation Models (DGVMs) from the TRENDY consortium, driven with observed changes in climate, CO2, and LULCC are analysed. Changes in global and regional carbon fluxes, stocks, and residence times are quantified, as well as an attribution to the underlying drivers. We find that over the historical period the majority of models simulate an increase in NPP, predominantly driven by enhanced atmospheric CO2 concentrations. This generally leads to increased carbon storage in both vegetation and soils, however there is no agreement across models on the partitioning between vegetation and soils. This increased storage also acts to reduce soil carbon residence times due to a relative increase in carbon allocated in the faster decomposing soil pools. LULCC over this period has acted to reduce carbon inputs to the system and reduce vegetation carbon residence times due to conversion of forests to shorter vegetation. We find there is a large variation in simulated global and regional fluxes, stocks, and residence times in resonse to changes in climate, implying there are considerable uncertainties in current DGVMs. We therefore use long-term global observations of productivity and biomass change to constrain model estimates and provide insight into a process attribution for biospheric change as well as highlighting areas for future model improvement.
How to cite: O'Sullivan, M., Friedlingstein, P., and Sitch, S.: Where is the carbon going? - A multi-model comparison, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12422, https://doi.org/10.5194/egusphere-egu21-12422, 2021.
Quantifying the responses of forest dynamics to fluctuations in the atmosphere, hydrosphere and land surface conditions at global scales have been rather challenging. Despite the understanding that favourable environmental conditions promote forest growth, the effects have been challenging to observe across different ecosystems and climate gradients. Based on a global annual time series of aboveground biomass (AGB) from 1992 to 2018, we present forest carbon changes and provide insights on the controls of atmospheric (e.g., climate), hydrosphere (e.g., soil water availability) and land surface (e.g., changes in forest cover) conditions on forest carbon changes from local to global scales. Our findings indicate a gradient of forest gains and losses across AGB classes, with regions with carbon stocks of 50-100 MgC ha-1 depicting both the highest forest gains and losses. Furthermore, we observe that changes in forest carbon stocks were systematically positively correlated with changes in forest cover, while it was not necessarily the case with other environmental variables, such as air temperature and water availability at the uni-variate level. We also used a gradient boosted decision tree model and a variable importance metric (i.e., SHAP values) to demonstrate that atmospheric conditions largely dictate forest carbon changes followed by land surface and hydrosphere conditions. Interestingly, the observed functional relationships indicate a strong sensitivity of forest carbon changes to recent-past carbon stocks and both recent-past and concurrent atmospheric water demand. Regionally, we find evidence that carbon gains from long-term forest growth covary with long-term carbon sink inferred from atmospheric inversions at the ecosystem level. Our study quantifies the contributions from the atmosphere, hydrosphere, and land surface conditions to forest carbon changes and provides new insights into the underlying mechanisms of forest growth on the global carbon cycle.
How to cite: Besnard, S., Santoro, M., Cartus, O., Fan, N., Linscheid, N., Nair, R., Weber, U., Koirala, S., and Carvalhais, N.: Global sensitivities of forest carbon changes to environmental conditions , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15550, https://doi.org/10.5194/egusphere-egu21-15550, 2021.
Belowground or ‘soil’ autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but uncertain components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil is rarely measured directly and has not been fully examined at the global scale. To fill this knowledge gap, the spatio-temporal patterns of RAsoil with a spatial resolution of half degree from 1981 to 2017 were predicted by Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; carbon allocation from photosynthesis to RAsoil (CAsoil), was calculated as the ratio of RAsoil to gross primary production (GPP); and its temporal and spatial patterns were assessed in global forest ecosystems. We found strong temporal and spatial variabilities of RAsoil with an increasing trend from boreal forests to tropical forests. Globally, mean RAsoil from forests was 8.9 ± 0.08 Pg C yr-1 (mean ± standard deviation) from 1981 to 2017 increasing at a rate of 0.0059 Pg C yr-2, paralleling broader soil respiration changes and indicating an increasing carbon loss respired by roots. Mean CAsoil was 0.243 ± 0.016 and showed a decreasing trend over time, although there were interannual variabilities, indicating that CAsoil was sensitive to environmental changes. The temporal trend of CAsoil varied greatly in space, reflecting uneven responses of CAsoil to environmental changes. The spatio-temporal variability of carbon allocation should be considered in global biogeochemical models to accurately predict belowground carbon cycling in an era of ongoing climate change.
How to cite: Tang, X., Shi, Y., Luo, X., Liu, L., Jian, J., Bond-Lamberty, B., Hao, D., Olchev, A., Zhang, W., Gao, S., and Li, J.: Spatial variability of carbon allocation to soil autotrophic respiration in global forest ecosystems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9154, https://doi.org/10.5194/egusphere-egu21-9154, 2021.
Accurately representing historical soil and vegetation carbon stocks in land data systems is important when evaluating outcomes of land use change decisions (e.g. land use change emissions). Moreover, carbon stocks (especially soil carbon stocks) are subject to uncertainty and vary significantly based on assumptions used by different data sets. For this reason, when representing carbon stocks in data systems, it is important to present a range of values based on the distribution of carbon stock observations for a given unit (region/country/basin) at the grid cell level.
We updated the moirai land data system (LDS) to generate historical estimates of soil carbon stocks (at a depth of 0-30 cms) and vegetation carbon stocks (broken down into above ground and below ground biomass) at the sub-national (basin) level based on global fine resolution raster input data. The LDS has also been programmed to calculate soil carbon stock values based on multiple data sets (such as SoilGrids database maintained by the ISRIC and the harmonized world soil database maintained by the FAO) to enable efficient comparisons of carbon stock estimates by end users between data sets. Moreover, to account for uncertainty, carbon stocks are calculated for 6 “states” based on 5 arcmin grid cell level observations of carbon stocks (The states are -weighted average, median, minimum, maximum, quartile 1 and quartile 3). This provides a robust representation of soil and vegetation carbon stocks at the sub-national level which are differentiated by data sources and the above-mentioned states, which can be used to represent more realistic outcomes from land use change decisions. To demonstrate the utility of this data, we also implemented the same in the land module of a multi sector dynamics model, Global Change Analysis Model (GCAM) to observe the impacts on land use change decision outcomes with different initializations of carbon stock data.
How to cite: Narayan, K., Vernon, C., and Di Vittorio, A.: Improving the representation of soil and vegetation carbon stocks at the sub-national scale in a global land data system., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6604, https://doi.org/10.5194/egusphere-egu21-6604, 2021.
How to cite: Padrón, R. S., Gudmundsson, L., Humphrey, V., and Seneviratne, S. I.: The relevance of soil moisture for land carbon sink projections, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15469, https://doi.org/10.5194/egusphere-egu21-15469, 2021.
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 CO2. 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 projected environmental change.
This problem can be tackled by theoretical modelling and 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 drivers of GPP independent of 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 (EVI from MODIS) that allows spatial estimates of the fraction of incident light absorbed by green vegetation. Matching soil moisture data were 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 explored additive models (incorporating multiple explanatory factors) that support non-linear responses. Recognising that our longitudinal data lack independence, we controlled for the hierarchical nature of the dataset through a variance structure that nests measurement year within site location.
In arriving at a preferred 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. As a model-comparison exercise, we used that portion of our dataset which overlaps the North American Carbon Program to apply our empirical model structure to site-based estimates of GPP generated by 19 discrete Terrestrial Biosphere Models (TBMs). The comparative analysis reveals wide variation between the TBMs in the shape, strength and even sign of the environmental effects on modelled GPP.
This empirical analysis suggests it is feasible to predict GPP using a single model structure, common across vegetation categories. And the appeal of such universal approaches is highlighted by inconsistent relationships with key environmental drivers within extant terrestrial models.
How to cite: Bloomfield, K., Stocker, B., Keenan, T., and Prentice, C.: Predictions of Gross Primary Production from a suite of Terrestrial Biome Models display divergent relationships with key environmental variables, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5177, https://doi.org/10.5194/egusphere-egu21-5177, 2021.
Terrestrial ecosystems have accounted for more than half of the global carbon sink during the past decades and offset 25%-30% of current anthropogenic CO2 emissions. The projected increase in CO2 concentration will depend on the magnitude of terrestrial plants’ feedback to CO2: i.e. the sensitivity of plant carbon uptake in response to elevated CO2, and the strength of the CO2 fertilization effect (CFE) in a changing (and warming) environment. Projecting vegetation responses to future increases in CO2 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 CO2 under idealized conditions, in comparison with other vegetation models and field experiments. We investigate the impact of two central parameters, the ratio of Jmax to Vcmax (at a common temperature) and the curvature of the light response curve, on the sensitivity of GPP to CO2. 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 CO2 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.
How to cite: Cai, W. and Prentice, I. C.: Sensitivity of global gross primary production to elevated CO2, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1744, https://doi.org/10.5194/egusphere-egu21-1744, 2021.
The role of nitrogen and phosphorus in terrestrial ecosystems has been shown to be critical in the regulation of the terrestrial carbon cycle. Therefore, the implementation of nutrient limitation in Earth System Models should be considered in order to have a more accurate representation of carbon fluxes, vegetation distribution and the response of the biosphere to climate change. Previous attempts to introduce the terrestrial nitrogen cycle and nutrient limitation in the UVic ESCM resulted in an incomplete project that was not added to the regular structure of the model. Here, we intend to improve the current state of the terrestrial nitrogen cycle and to develop a new terrestrial phosphorus cycle that will be coupled to the carbon cycle. The most prominent changes in the N cycle are the enforcement of N mass conservation and the merge with a deep land surface and a new wetland model. The N and P cycles estimates the fluxes between three organic pools: litter, soil and vegetation compartments (leaf, root and wood), two N pools (NH4+, NO3-) and one inorganic P pool. The basic structure of the N cycle was left in place, it estimates the inputs via biological nitrogen fixation and outputs via leaching, furthermore, with the merger with the new wetland model denitrification was added to the N loss of the system. The P cycle accounts the inputs from estimations of rock weathering and losses from occlusion and leaching. Both cycles regulate the vegetation system in 2 ways: (1) by controlling vegetation biomass if nutrient is limiting, reducing the amount of carbon in the plant compartments until the C:N or C:P ratio is met and (2) directly regulating the primary productivity by taking into account the relationship between leaf N and P and the maximum carboxylation rate (Vcmax). We aim to improve projections of the future CO2 fertilization feedback, and thus carbon budgets and ZEC.
How to cite: De Sisto, M. and MacDougall, A.: MODELLING THE TERRESTRIAL NITROGEN AND PHOSPHORUS CYCLE IN THE UVic ESCM , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7801, https://doi.org/10.5194/egusphere-egu21-7801, 2021.
Plants not only acquire carbon to sustain biomass production, autotrophic respiration, and the production of non-structural compounds, but also require nitrogen to support carboxylation and growth. However, available observations have not fully been integrated and used for modelling growth, carbon allocation to different compartments, and how different compartments’ nitrogen-to-carbon ratio vary across large climatic and soil gradients. This leaves substantial uncertainty in estimates of the global distribution of growth and nitrogen uptake by plants.
Here, we used the P-model, a first principles-derived and remote sensing-driven model for terrestrial gross primary production (GPP) to simulate the global distribution of GPP. Using comprehensive datasets with locally measured covariates for climatic and edaphic conditions and vegetation structure, we modelled the fractional allocation of GPP to biomass production (BP), aboveground net primary production (ANPP), and leaf NPP based on linear mixed-effects regression models. We defined BP as the sum of NPP in leaves, wood and roots. It thus does not include additional components such as exudates and labile carbon to mycorrhizae. Leaf nitrogen-to-carbon was modelled based on the maximum rate of carboxylation at 25 degrees Celsius (Vcmax25) and leaf mass per area (LMA). We then used global gridded data for the covariates that entered as predictors in site-level empirical models to simulate global C and N allocated to each component. We finally validated our global simulation results with an extended set of globally distributed GPP, BP and nitrogen-to-carbon ratio observations.
GPP was well predicted (R2 = 0.61). In forests, ratios of BP/GPP and ANPP/GPP decreased with soil C/N and stand-age but increased with humidity and with the fraction of absorbed photosynthetically active radiation (fAPAR). The ratio of leaf NPP to ANPP, increased with light availability and growth temperature, but decreased with vapor pressure deficit. Leaf nitrogen-to-carbon ratio was positively related to the ratio of Vcmax25 to LMA. Leaf nitrogen resorption efficiency (NRE) was increased in drier and colder environments. Through our data validation at the end, we have shown a prediction for NPP (R2 = 0.26), ANPP (R2 = 0.28), leaf NPP (R2 = 0.39), NRE (R2 = 0.30), leaf N/C (R2 = 0.26) and leaf N flux (R2 = 0.35).
Simulated global total GPP is 125 Pg C yr-1. Based on these statistical models, global mean carbon-use-efficiency (BP/GPP) was estimated to be 40%. The ratio of ANPP/BP was 72%, and ANPP was further split with 46% to leaf NPP and 54% to wood NPP. Simulated global total nitrogen acquisition (total of uptake from the soil and symbiotic N fixation) was 860 Tg N yr-1. Growth in the leaf, wood and root compartment accounted for 39%, 23% and 38% of global N acquisition, respectively. We suggest that plant adaptations result in higher ANPP, leaf NPP and finally leaf N flux under warmer, wetter, more abundant light and N-rich soil conditions, which aims to support higher rate of photosynthesis with greater nitrogen investment in the leaf.
How to cite: Peng, Y., Prentice, C., Bloomfield, K., Campioli, M., Guo, Z., Sun, Y., Tian, D., Wang, X., Vicca, S., and Stocker, B.: Combining diverse data for the quantification of terrestrial carbon and nitrogen allocations, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8252, https://doi.org/10.5194/egusphere-egu21-8252, 2021.
Aerosols have a dimming and cooling effect and change hydrological regimes, thus affecting carbon fluxes, which are sensitive to climate. Aerosols also scatter sunlight, which increases the fraction of diffuse radiation, increasing photosynthesis. Although previous studies have quantified the impacts of some of these factors separately, there remains no clear conclusion whether the physical impacts of aerosols on land carbon fluxes is larger through diffuse radiation change than through changes in other climate variables. In this study, we quantified the overall physical impacts of anthropogenic aerosols on land C fluxes and explored the contribution from each factor using a set of factorial simulations driven by climate and aerosol data from the IPSL-CM6A-LR experiments from 1850 to 2014. A newly-developed land surface model which distinguishes diffuse and direct radiation in canopy radiation transmission, ORCHIDEE_DF, was used. Specifically, a sub-grid scheme was developed to distinguish the cloudy and clear sky conditions. We found that anthropogenic aerosol emissions since 1850 cumulatively enhanced the land C sink by 22.6 PgC. 78% of this C sink enhancement is contributed by aerosol-induced increase in the diffuse radiation fraction, which is much larger than the effect of the aerosol-induced dimming. The cooling of anthropogenic aerosols increases the C sink in low latitudes but decreases the C sink in high latitudes and overall slightly increases the global land C sink. Compared with radiation and temperature changes, aerosol-induced precipitation changes have limited impacts. The dominant role of diffuse radiation changes in affecting historical land C fluxes found in this study implies that future aerosol emissions may have a much stronger impacts on the C cycle through changing radiation quality than through changing climate alone. Earth system models need to take into account the diffuse radiation fertilization effect, in order to better evaluate the impacts of climate change mitigation scenarios.
How to cite: Zhang, Y., Ciais, P., Boucher, O., Maignan, F., Bastos, A., Goll, D., Lurton, T., Viovy, N., Bellouin, N., and Li, L.: Disentangling the impacts of anthropogenic aerosols on terrestrial carbon cycle during 1850-2014, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14841, https://doi.org/10.5194/egusphere-egu21-14841, 2021.
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