HS10.3

Optimality concepts have been used to successfully infer ecophysiological properties and functioning of terrestrial vegetation from the leaf- to ecosystem scale.  In many cases this implies, roughly speaking, that vegetation is as productive as it can possibly be.  However, when vegetation activity is looked at in terms of its energy conversion from the radiant energy in sunlight to the chemical energy stored in carbohydrates, it has a very low conversion efficiency of about 1% or less.  This is much less than what would be expected from thermodynamics applied to the photochemical conversion process.  How do these two seemingly contradictory views fit together?  Here I suggest that thermally-driven gas exchange between vegetation canopies and the lower atmosphere represents the major bottleneck, explaining the low thermodynamic efficiency of carbon uptake and setting a strong constraint to any form of vegetation optimality.  Gas exchange intimately links the carbon taken up by vegetation from the atmosphere for photosynthesis during the day with the water loss by evaporation, with evaporation being a major component of the surface energy balance.  The magnitude of this exchange is, however, not externally set by atmospheric conditions, but predominantly determined by the local heating of the surface, creating buoyancy and thus this exchange.  Thermodynamics sets a strong constraint on the magnitude of this locally generated exchange by the maximum power that can be derived from the absorption of solar radiation to generate the associated kinetic energy.  I use global, observation-based radiation and precipitation datasets and this thermodynamic constraint to quantify surface energy balance partitioning over land as well as the associated rate of evaporation at the climatological scale.  I then use a typical value for the water use efficiency observed in vegetation to convert this evaporative flux to a carbon uptake flux by vegetation and show that the derived fluxes of water and carbon compare very well to observation-based estimates across regions.  This means that the low thermodynamic efficiency of terrestrial carbon uptake should not be attributed to an inefficient use of light, but rather to the low efficiency by which radiative heating generates gas exchange that is needed to supply canopies with carbon dioxide and that maintains evaporation.  This interpretation has broad implications for the role of vegetation in the Earth system.  It implies that physically-driven gas exchange with the atmosphere - and not energy directly - is a major constraint on vegetation activity, shaping its geographic patterns.  Given this constraint, vegetation may then maximize its carbon uptake for the given evaporative flux, but it has comparatively little control over evaporation and surface energy balance partitioning if sufficient water is available.  Applied to global warming, this then implies that the response of evaporation is mostly determined by changes in the radiative forcing and water availability, and not by stomatal responses.

How to cite: Kleidon, A.: Why is the thermodynamic efficiency of carbon uptake by terrestrial vegetation so low despite its optimal functioning?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1382, https://doi.org/10.5194/egusphere-egu21-1382, 2021.

Ecohydrological systems are a result of long-term co-evolution of soils, biota and atmospheric conditions, and often respond to perturbations in non-intuitive ways. Their short-term responses can be explained and sometimes predicted if we understand the underlying dynamic processes and if we can observe the initial state precisely enough. However, how do they co-evolve in the long-term after a change in the boundary conditions? In 1922, Alfred Lotka hypothesised that the natural selection governing the evolution of biota and composition of ecosystems may be obeying some thermodynamic principles related to maximising energy flow through these systems. Similar thoughts have been formulated for various components of the Earth system and individual processes, such as heat transport in the atmosphere and oceans, erosion and sediment transport in river systems and estuaries, the formation of vegetation patterns, and many others. Different thermodynamic optimality principles have been applied to predict or explain a given system property or behaviour, of which the maximum entropy production and the maximum power principles are most widespread. However, the different studies did not use a common systematic approach for the formulation of the relevant system boundaries, state variables and exchange fluxes, resulting in considerable ambiguity about the application of thermodynamic optimality principles in the scientific community. Such a systematic framework has been developed recently and can be tested online at:

https://renkulab.io/projects/stanislaus.schymanski/thermodynamic_optimality_blueprint

In the present study, we illustrate how such a common framework can be used to classify and compare different applications of thermodynamic optimality principles in the literature, and discuss the insights gained and key criteria for a more rigorous testing of such principles.

How to cite: Schymanski, S. J., Dewals, B., Dijkstra, H. A., Ozawa, H., and Zehe, E.: Thermodynamic optimality principles in Earth sciences, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4188, https://doi.org/10.5194/egusphere-egu21-4188, 2021.

In the Bramke valley (western Harz mountains, North Germany), three forested headwater catchments have been monitored since decades. A broad range of observables relevant to forestry, hydrology, hydrochemistry and ecosystem research allows to compare different approaches to environmental monitoring; each of them has its own set of relevant observables. The basic temporal resolution is daily for hydrometeorology and bi-weekly for streamwater chemistry; standing biomass of the Norway spruce stands is measured every couple of years.

Tree growth (site index) has changed between and within rotation periods (of up to 129 years); changes in soil nutrient pools are typical variables used to explain this nonstationary forest growth when the spatial-temporal scales match. In hydrology, transport mechanisms of water and solutes through catchment soils are used to model and predict runoff and its chemistry. Given the homogeneity of the area in terms of geology, soils and topography as well as climate, differences between the catchments in the Bramke valley are mostly related to forestry variables. The catchments exhibit long-term changes and spatial gradients related to atmospheric deposition, management and changing climate. After providing a short multivariate summary of the dataset, we present several nonlinear metrics suitable to detect and quantify subtle changes and to describe different behavior, both between different variables from the same catchment, as well as for the same variable across catchments.

Soil water potential and solution chemistry are further links between forestry and hydrology. However, at Lange Bramke, similar to other catchment studies, the evaluation of these data sets has not converged to a consistent, realistic model at the catchment scale. We hypothesize that this lack of model integration is due to theoretical rather than technical limits. A possible representation of these limits might be phrased in a category theory approach.

How to cite: Hauhs, M., Meesenburg, H., and Lange, H.: Long-term monitoring of vegetation and hydrology in headwater catchments and the difficulties to embrace data-oriented and process-oriented approaches, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7684, https://doi.org/10.5194/egusphere-egu21-7684, 2021.

The Budyko-framework is widely used to assess the water balance of catchments, with large catchments worldwide converging to a constrained set of empirical curves. Ongoing research focuses on explaining deviations of catchments from the Budyko-curve, implying that local characteristics, such as hydrological settings and land use, determine an individual curve for each catchment, along which the catchment travels in response to climatic variability. Here we use vegetation optimality to explain convergence on the Budyko-curve and assess if the Vegetation Optimality Model (VOM, Schymanski et al., 2009) and three conceptual hydrological models support the assumption that catchments follow individual Budyko-curves as climate varies.

The VOM optimizes vegetation properties, such as rooting depths and vegetation cover, for maximum Net Carbon Profit (NCP), i.e. the difference between the total amount of CO₂ assimilated from the atmosphere and the carbon costs for maintenance and respiration of plants. In this sense, the VOM represents vegetation water use as the result of ecological adaptation, while the conceptual hydrological models lump water use into a set of calibration parameters. The following research questions were investigated:

- Does vegetation optimality lead to convergence of catchments on the Budyko-curve?

- Does modelled catchment response to changing precipitation follow a catchment-specific Budyko-curve?

The VOM was applied at five flux tower sites, as well as 36 additional points, along the North Australian Tropical Transect, following a strong precipitation gradient from north to south, and six other catchments in Australia. Beside the VOM, three conceptual hydrological models were applied to the Australian catchments for comparison. In a final step, these hydrological models were run for a selection of catchments in the contiguous United States to generalize the results from Australia.

For each site, the vegetation parameters of the VOM were optimized for maximum NCP, while the conceptual models were calibrated to reproduce observed streamflow. The simulated water balances were used to generate individual Budyko-curves for each site and model run. Subsequently, rainfall was stepwise increased or decreased and the models were re-run to test if each site would stay on its curve. In a second step, the vegetation was re-optimized in the VOM to simulate vegetation response to the new precipitation and the resulting water balance was again plotted on the Budyko-curve.

The individual Budyko-curves were consistently different for the different precipitation amounts, indicating that modelled responses do not follow a catchment-specific curve. Conversely, if vegetation was re-optimized in the VOM for each rainfall scenario, the different scenarios converged to a single curve for each study site. In other words, adjusting the vegetation to maximize the NCP made the study sites converge back to the initial Budyko-curve. This indicates that convergence onto a Budyko-curve and tracking along a catchment-specific Budyko-curve may not be due to physical constraints, as commonly assumed, but the result of biological adaptation to the environment.

References

Schymanski, S.J., Sivapalan, M., Roderick, M.L., Hutley, L.B., Beringer, J., 2009. An optimality‐based model of the dynamic feedbacks between natural vegetation and the water balance. Water Resources Research 45. https://doi.org/10.1029/2008WR006841

How to cite: Nijzink, R. C. and Schymanski, S.: The role of vegetation optimality in the Budyko-framework, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1300, https://doi.org/10.5194/egusphere-egu21-1300, 2021.

The future Earth is projected to experience elevated rainfall variability, with more frequent and intense droughts, as well as high-rainfall events. Increasing CO₂ concentrations are expected to raise terrestrial gross primary productivity (GPP), whereas water stress is expected to lower GPP. Plant responses to water stress vary strongly with timescale, and plants adapted to different environmental conditions differ in their functional responses. Here, we embed a unified optimality-based theory of stomatal conductance and biochemical acclimation of leaves we have recently developed [Joshi, J. et al. (2020) Towards a unified theory of plant photosynthesis and hydraulics. bioRxiv 2020.12.17.423132] in an eco-evolutionary vegetation-modelling framework, with the goal to investigate emergent functional diversity and associated GPP impacts under different rainfall regimes.

The model of photosynthesis used here simultaneously predicts the stomatal responses and biochemical acclimation of leaves to atmospheric and soil-moisture conditions. Using three hydraulic traits and two cost parameters, it successfully predicts the simultaneous declines in CO₂ assimilation rate, stomatal conductance, and leaf photosynthetic capacity caused by drying soil. It also correctly predicts the responses of CO₂ assimilation rate, stomatal conductance, leaf water potential, and leaf photosynthetic capacity to vapour pressure deficit, temperature, ambient CO₂, light intensity, and elevation. Our model therefore captures the synergistic effects of atmospheric and soil drought, as well as of atmospheric CO₂ changes, on plant photosynthesis and transpiration.

We embed this model of photosynthesis and transpiration in a trait-height-patch structured eco-evolutionary vegetation model. This model accounts for allometric carbon allocation, height-structured competition for light, patch-structured successional dynamics, and coevolution of plant functional traits. It predicts functional species mixtures and emergent ecosystem properties under different environmental conditions. Using this model, we investigate the evolution of plant hydraulic strategies under different regimes of drought and rainfall variability. Our approach provides an eco-evolutionarily consistent framework to scale up the responses of plant communities from individual plants to ecosystems to provide ecosystem-level predictions of functional diversity, primary production, and plant water use, and could thus be used for reliable projections of the global carbon and water cycles under future climate scenarios.

How to cite: Joshi, J., Stocker, B., Hofhansl, F., Zhou, S., Brännström, Å., Prentice, I. C., and Dieckmann, U.: Eco-evolutionary responses of plant communities to drought and rainfall variability, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11142, https://doi.org/10.5194/egusphere-egu21-11142, 2021.

The emergent spatial organization of ecosystems in elevational gradients suggest that some ecosystem processes, important enough to shape morphological traits, must show similar patterns.

The most important of these processes, gross primary production (GPP), usually (albeit with some exceptions) decreases with elevation. This was previously thought to be a direct consequence either of the decrease in temperature, or the decrease of incident light due to cloud cover. However, some recent developments in photosynthetic theory, plus the unprecedented availability of ecophysiological data, support the hypothesis that plants acclimate (optimize) their photosynthetic traits to the environment. In this new theoretical context, the temperature is no longer considered as a major constraining factor, except when either freezing or excessively high temperatures inhibit plant function generally.

Two of the most important photosynthetic traits, the maximum rate of carboxylation (V_CMAX) and the intrinsic quantum efficiency (φ_o), vary in opposite directions with increasing elevation. Plants tend to increase V_CMAX to compensate for a decrease in the ratio leaf-internal to ambient partial pressures of CO₂, while φ_o increases with temperature up to a plateau. To explore how these different responses, documented at leaf level, converge in emergent spatial patterns at ecosystem scale we considered how elevation shape light use efficiency (defined as the ratio of CO₂ assimilated over light absorbed) over mountain regions worldwide. We used data from eddy-covariance flux towers, from different networks, located in mountain regions around the world, adding up to 618 station-years of record. To complement our analysis, we included theoretical predictions using an optimality model (P-model) and evaluated changes in the spatial pattern with simulation experiments.

Empirically we found an asymptotic response of LUE to the average daytime temperature during the growing season with increasing elevation, and a small, but globally consistent effect of elevation on LUE. We propose a theoretical explanation for the observation that temperature differences have little impact on the biogeographical pattern of LUE, but we also find that different assumptions on the acclimation of the maximum rate of electron transport (J_MAX) and φ_o change this pattern.

How to cite: Sandoval, D. and Prentice, I. C.: Biogeographical Patterns of Light Use efficiency?, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3254, https://doi.org/10.5194/egusphere-egu21-3254, 2021.

How to cite: Dong, N., Prentice, I. C., Wright, I., Luo, X., and Smith, N.: Rising CO2 and warming lead to declining global canopy demand for nitrogen, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10540, https://doi.org/10.5194/egusphere-egu21-10540, 2021.

Optimal stomatal control models have shown great potential in predicting stomatal behavior and improving carbon cycle modeling. Basic stomatal optimality theory posits that stomatal regulation maximizes the carbon gain relative to a penalty of stomatal opening. Many optimization models take a similar approach to calculate instantaneous carbon gain from stomatal opening. But stomatal optimization models often diverge in how they calculate the corresponding penalty of stomatal opening. We will present our recent work on this penalty function, the conditions that influence the penalty function, and compare and evaluate 10 different optimization models in how they quantify the penalty and how well they predict stomatal responses to the environment. We quantitatively tested different models against multiple leaf gas-exchange datasets. The optimization models with better predictive skills have penalty functions that meet seven key criteria and use fitting parameters that are both few in number and physiology based. The most skilled models are those with a penalty function based on stress-induced hydraulic damage. We conclude by examining the key uncertainties in these optimization models for improving predictions of carbon and water fluxes, as well as demographic rates like drought-induced tree mortality.

How to cite: Anderegg, W., Kerr, K., Sperry, J., Todd, H., Trugman, A., Venturas, M., Wang, Y., and Zenes, N.: Advancing carbon cycle projections with stomatal optimality models linked to plant hydraulics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6375, https://doi.org/10.5194/egusphere-egu21-6375, 2021.