Pin-Hsin Hu

While it is clear that vegetation takes part in shaping terrestrial climate through various interactions with the atmosphere, it is not so obvious what role plant functional diversity plays here. So far a tool for investigating this question in land-atmosphere simulations was missing. The new tool JeDi-BACH (version 1.0), described here, closes this gap by combining the Jena Diversity Model (JeDi) with the land component JSBACHv4 of the ICON Earth System Model (version 1.0). In practice, the low-diversity plant parametrization of JSBACH employing plant functional types (PFTs) was replaced by the trait based high-diversity vegetation description of JeDi. The key novelty introduced by the implementation of JeDi into JSBACH is that the composition of terrestrial ecosystems emerges dynamically from environmental filtering based on functional trade-offs. Thereby, in contrast to the PFT approach, a richer set of plant strategies adapted to the ruling environmental conditions is obtained without a priori knowledge of the vegetation distribution. Besides documentation of this new implementation of JeDi, the paper also presents results from first exploratory simulations with interactive land-atmosphere coupling. We find a systematic dependence of simulated terrestrial climate on potential diversity in our experiments. Moreover, when investigating the reaction to changes in trait parameters, we find that at low diversity, simulated local climate varies with the particular composition of vegetation, while at high diversity simulated terrestrial climate proves to be rather insensitive due to a dynamic re-organization of the plant community structure. Apparently, the many more dynamic degrees of freedom of the highly diverse vegetation in JeDi-BACH make this model behave very differently (less tunable) than conventional land components based on only a few PFTs. Besides fundamental research on the relation between diversity and climate, JeDi-BACH may be useful for the investigation of non-analogue climates (e.g., paleoclimate) where we lack knowledge on the structure and distribution of vegetation.

Rising atmospheric CO2 enhances the land carbon (C) uptake, providing a negative feedback mechanism for atmospheric CO2. At the same time, CO2-driven warming of land and air temperature tends to weaken land carbon storage, providing a primarily positive feedback on climate (i.e. intensifying climate change). The magnitude of these effects is, beside others, mediated by the nitrogen (N) content in land, which attenuates the land C response to atmospheric CO2 and climate [Kou-Giesbrecht et al., 2025]. Comprehensive Earth System Models (ESMs) have been developed to project effects from different feedbacks on Earth’s climate change, but to date not all ESMs take into account effects from the coupled C-N cycles.ICON is a state of the art ESM [Jungclaus et al., 2022], yet its initial land surface model (LSM) implementation JSBACHv4.3 [Schneck et al., 2022] does not include a representation of the N-cycle. Recently, the QUINCY model [Thum et al., 2019] was integrated into the ICON framework. While the geophysical processes of the initial LSM JSBACHv4.3 are taken over, the new QUINCY configuration provides an alternative representation of the vegetation and biogeochemical processes, including a more realistically representation of vegetation structure (e.g. by coupling the LAI to the available carbon) and a comprehensive representation of the terrestrial N-cycle processes.In the current study, we apply ICON in its ICON-XPP configuration [Müller et al. 2025] and with QUINCY as configuration for ICON-Land to evaluate the N-effect on land C uptake under conditions of 1%CO2 increase in the atmosphere. For this purpose, two numerical AMIP experiments (sea surface temperature and sea ice are prescribed) were carried out for the period of 1850-2019. In one experiment only C cycle was considered, in another - C and N cycles. The modelling results will be analysed to evaluate a possible N limitation effect under the conditions of increasing atmospheric CO2.

Observations of drought-driven damage to vegetation are widespread but, until recently, large-scale terrestrial models used to study climate-vegetation interactions did not capture the contrasting sensitivities of plants to drought. This is changing with the advent of a generation of models that consider plant hydraulics. Plant hydraulics link plant water status to pedoclimatic conditions; as such, explicit consideration of plant hydraulics should make models more mechanistic and predictive. Models, however, diverge in how they represent the plant water transport pathway and relate it to other plant functions (e.g., photosynthesis), so they further diverge in their parameterisation approach for hydraulic processes. Only at the most basic level do plant hydraulic implementations converge on a common set of measurable traits or parameters: two that describe a hydraulic vulnerability curve (e.g., P12 and P50, the water potentials at which 12% and 50% of a plant’s hydraulic conductivity are lost, respectively), and one that quantifies the efficiency of water movement within the plant (e.g., maximum hydraulic conductance). Regrettably, we do not yet know how to obtain regional- or global-scale hydraulic parameters from local-scale measurements, nor how to connect them to other plant traits. In this study, we propose strategies to leverage cross-species hydraulic diversity when scaling traits from the species level into model parameters. We also emphasise the importance of accounting for (i) within-species trait variability across space (e.g., interactions between hydraulic traits and their environment) and (ii) cross-functional trait covariation (i.e., interactions – or lack thereof – among traits that characterise different functional axes). Beyond advancing regional and global plant hydraulic modelling, efforts to address the suggested strategies would ready models for simulations that capture the resilience of vegetation communities worldwide.

Mounting evidence from field observations has shown that high functional diversity is associated with strong ecosystem resilience and stability. However, plant ecology studies have focused on the passive response of global ecosystems to climatic changes while the impacts of plant-functional diversity on climate including its feedback are seldom addressed. Moreover, state-of-the-art climate models are insufficient to address such topics. Their land component models cover only a restricted range of present-day plant features, so that adaptation at the sub-grid scale is ignored. Based on a process-based plant functional trade-off scheme developed by Kleidon and Mooney (2000), we have set up a new vegetation model JeDi-BACH into the land component of the ICON-Earth System Model (ICON-ESM). The advantage of this new model is that the representation of global vegetation is an emergent outcome of environmental filtering following several well-known fundamental functional trade-offs that link plant functions to abiotic and biotic attributes. In such a way, plants dynamically adjust to the changing environment and meanwhile modify climate. With this new model, we present a series of sensitivity studies investigating the effect of plant trait diversity on the coupled vegetation-climate system in a coupled land-atmosphere setup. We found that high plant diversity ecosystems tend to stabilize terrestrial climate in a high water-turnover state, leading to a wet and cool climate. The enhancement in evapotranspiration with increasing diversity found in our study is consistent with the BEF (Biodiversity-Ecosystem Functioning) relationship derived from the field studies. Our modeling results demonstrate the importance of the "biodiversity-climate feedback" and highlight the role of plant functional diversity in shaping a robust climate.Kleidon, A. and Mooney, H. A.: A global distribution of biodiversity inferred from climatic constraints: Results from a process-based modelling study, Glob. Chang. Biol., 6(5), 507–523, doi:10.1046/j.1365-2486.2000.00332.x, 2000.

While it is clear that vegetation takes part in shaping terrestrial climate through various interactions with the atmosphere, it is not so obvious what role plant functional diversity plays here. So far a tool for investigating this question in land-atmosphere simulations was missing. The new tool JeDi-BACH (version 1.0), described here, closes this gap by combining the Jena Diversity Model (JeDi) with the land component JSBACHv4 of the ICON Earth System Model (version 1.0). In practice, the low-diversity plant parametrization of JSBACH employing plant functional types (PFTs) was replaced by the trait-based high-diversity vegetation description of JeDi. The novelty of JeDi is that the composition of terrestrial ecosystems emerges dynamically from environmental filtering based on functional trade-offs. Thereby, in contrast to the PFT approach, a richer set of plant strategies adapted to the ruling environmental conditions is obtained without a priori knowledge of the vegetation distribution. Besides documentation of this new implementation of JeDi, the paper also presents results from first exploratory simulations with interactive land-atmosphere coupling. We find a systematic dependence of terrestrial climate on diversity. Moreover, when investigating the reaction to changes in trait parameters, we find that at low diversity, climate depends strongly on the particular composition of vegetation, while at high diversity terrestrial climate proves to be rather resilient due to a dynamic re-organization of the plant community structure. Apparently, the many more dynamic degrees of freedom of the highly diverse vegetation in JeDi-BACH make this model behave very differently (less tunable) than conventional land components based on only a few PFTs. Besides fundamental research on the relation between diversity and climate, JeDi-BACH may be useful for the investigation of non-analogue climates (e.g., paleoclimate) where we lack knowledge on the structure and distribution of vegetation.

Climate extremes are on the rise. Impacts of extreme climate and weather events on ecosystem services and ultimately human well‐being can be partially attenuated by the organismic, structural, and functional diversity of the affected land surface. However, the ongoing transformation of terrestrial ecosystems through intensified exploitation and management may put this buffering capacity at risk. Here, we summarize the evidence that reductions in biodiversity can destabilize the functioning of ecosystems facing climate extremes. We then explore if impaired ecosystem functioning could, in turn, exacerbate climate extremes. We argue that only a comprehensive approach, incorporating both ecological and hydrometeorological perspectives, enables us to understand and predict the entire feedback system between altered biodiversity and climate extremes. This ambition, however, requires a reformulation of current research priorities to emphasize the bidirectional effects that link ecology and atmospheric processes.

To understand the interaction between vegetation and the climate, Dynamic Global Vegetation Models (DGVMs) have been coupled with Earth system models (ESMs). In DGVMs, global vegetation is commonly empirically categorized into a few discrete plant functional types (PFTs) by differentiating their phenological, morphophysiological, and bioclimatic properties. Although the PFT-approach is useful to capture the large-scale general features of plants, growing evidence from the ecology community has challenged the use of the plant-type specific parametrization in models and the omission of the intra-variation of PFTs. Modelling studies have also shown that the local climate is highly sensitive to the selection and combination of PFTs. Therefore, a less parameter-dependent approach, of which the results should be robust to the empirical selection of parameters, is critical to address vegetation-climate interaction in climate models.Based on a process-based plant functioning trade-off scheme developed by Kleidon and Mooney (2000), we have set up a new vegetation model JeDi-BACH and have implemented the new model into the land component of the ICON-Earth System Model (ICON-ESM). The advantage of this new model is to obtain plant distribution as a result of environmental filtering. Plants are represented based on several well-known fundamental functional trade-offs that link the plant functions to abiotic and biotic attributes. For example, plants which partition more biomass to roots could improve their soil-water uptake and thereby reduce the stress from water shortage. Each plant functional aspect is defined by a set of plant-trait parameters that is randomly generated for each plant species. Hence, every parameter set realizes a plant growth strategy with different functional capabilities. Using a large number of randomly generated plant growth strategies, plants are allowed to ‘grow’ everywhere; but the environment will select the survivors. In such a way, plants dynamically adjust to the changing environment and meanwhile influence climate. We have done several simulations of present-day climate with JeDi-BACH and coupled to the atmosphere component of the ICON-ESM to investigate how such an adaptive ecosystem interacts with regional and global climate. Future investigations will focus on non-analogue climates (eg. Eocene with tropical vegetation at high latitudes) where in contrast to PFT-based DGVMs the new model allows vegetation to adjust consistently with climate because of its dynamic selection of plant traits by environmental filtering.Kleidon, A. and Mooney, H. A.: A global distribution of biodiversity inferred from climatic constraints: Results from a process-based modelling study, Glob. Chang. Biol., 6(5), 507–523, doi:10.1046/j.1365-2486.2000.00332.x, 2000.