BG3.7 | Plant traits, adaptation, and biogeochemical cycles – from measurements to models
EDI
Plant traits, adaptation, and biogeochemical cycles – from measurements to models
Convener: Jens Kattge | Co-conveners: Michael Bahn, Oskar Franklin, Julia JoswigECSECS
Orals
| Fri, 19 Apr, 14:00–15:45 (CEST)
 
Room N1
Posters on site
| Attendance Thu, 18 Apr, 10:45–12:30 (CEST) | Display Thu, 18 Apr, 08:30–12:30
 
Hall X1
Posters virtual
| Attendance Thu, 18 Apr, 14:00–15:45 (CEST) | Display Thu, 18 Apr, 08:30–18:00
 
vHall X1
Orals |
Fri, 14:00
Thu, 10:45
Thu, 14:00
Plant traits extend the range of earth observations to the level of individual organisms, providing a link to ecosystem function and modelling in the context of rapid global changes. However, overcoming the differences in temporal and spatial scales between plant trait data and biogeochemical cycles remains challenging.

This session will address the role of plant traits, biodiversity, acclimation, and adaptation in the biogeochemical cycles of water, carbon, nitrogen, and phosphorus. We welcome conceptual, observational, experimental and modelling approaches and studies from the local to the global scale, including in-situ or remote sensing observations.

Orals: Fri, 19 Apr | Room N1

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Jens Kattge, Michael Bahn, Oskar Franklin
14:00–14:10
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EGU24-6476
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BG3.7
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On-site presentation
Alvaro Moreno-Martínez, Jordi Muñoz-Marí, Jose E. Adsuara, Benjamin Dechant, Jens Katge, Teja Kattenborn, Francesco Maria Sabatini, Ethan Butler, Peter M. van Bodegom, Fabian D. Schneider, Miguel Mahecha, Josep Peñuelas, Philip A. Townsend, Gerhard Boenisch, Emma Izquierdo-Verdiguier, Nuno Carvalhais, Gregory Duveiller, Daniel Lusk, and Gustau Camps-Valls

Plant functional traits play a crucial role in determining how terrestrial ecosystems function. However, most Earth system models (ESMs) oversimplify this information, representing it with a limited number of static, empirically fixed values assigned to a selection of plant functional types (PFTs). This results in a reduction of the diversity of plant communities into a relatively small number of categories and the loss of key variability within individual PFTs. As a result, local processes occurring within ESM grid cells are not well represented, leading to uncertainties in predicting ecosystem functions.

The TRY global plant traits database is home to the most extensive collection of in-situ trait observations for a broad spectrum of species across the globe. Nonetheless, despite the numerous species and samples included in TRY, it still falls short compared to the overall richness and diversity of species and ecosystem functions worldwide. As a result, various initiatives have emerged to create global maps of plant traits. In this study, we created maps of essential plant traits, such as specific leaf area (SLA), leaf nitrogen content (LNC), and leaf phosphorus content (LPC), at a spatial resolution of 1 km. We took an innovative approach by leveraging the use of biodiversity, trait databases, and remote sensing data as primary sources of information. Additionally, we provide ancillary data layers that indicate regions where  data gaps currently exist and  where more samples are needed to improve trait representation in TRY.

We compared our results to plot-level estimates for thousands of sites globally. The comparison demonstrated strong correlations (r > 0.5) and low relative errors (rME < 6% and rRMSE < 11%) for all considered traits despite the challenges in scaling up from local to global scales. Our results reveal the non-Gaussian nature of trait distributions at a global scale when computing community representative mean trait values and further statistical descriptors, including standard deviation, skewness, and kurtosis estimations. These higher-order moments provide a more detailed and nuanced view of plant functional diversity and distribution. Using these new data to parameterize global ecological models could lead to more accurate predictions and a better understanding of the main drivers of different ecosystem processes.

How to cite: Moreno-Martínez, A., Muñoz-Marí, J., Adsuara, J. E., Dechant, B., Katge, J., Kattenborn, T., Maria Sabatini, F., Butler, E., van Bodegom, P. M., Schneider, F. D., Mahecha, M., Peñuelas, J., Townsend, P. A., Boenisch, G., Izquierdo-Verdiguier, E., Carvalhais, N., Duveiller, G., Lusk, D., and Camps-Valls, G.: Leveraging Crowd-sourced Biodiversity Data for an Enhanced Plant Functional Trait Mapping, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6476, https://doi.org/10.5194/egusphere-egu24-6476, 2024.

14:10–14:20
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EGU24-18306
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BG3.7
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On-site presentation
Ning Dong and Iain Colin Prentice

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO2 and climate change. By extension, it has been suggested that declining carboxylation capacity (Vcmax) and leaf N content in enhanced-CO2­ experiments and satellite records signify increasing N limitation of primary production. We estimated changes in Vcmax andbased on optimality principles over decades, and the changes in leaf-level photosynthetic N assuming proportionality with leaf-level Vcmax at 25˚C. using satellite-based and predicted , and converted to annual N demand using estimated leaf turnover times.The predicted spatial pattern of Vcmax shares key features with an independent reconstruction based on remotely-sensed leaf chlorophyll content. Leaf-level responses to rising CO2, and to a lesser extent temperature, may have reduced the canopy requirement for N by more than greening has increased it. Our finding provides an alternative explanation for declining N that does not depend on increasing N limitation, also could use as evidence for recently increasing N limitation on primary production.  

How to cite: Dong, N. and Prentice, I. C.: Rising CO2 and warming reduce global canopy demand for nitrogen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18306, https://doi.org/10.5194/egusphere-egu24-18306, 2024.

14:20–14:30
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EGU24-3438
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BG3.7
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Virtual presentation
Efrat Sheffer

Plant symbiosis with dinitrogen-fixing bacteria is a plant trait that affects plant fitness directly. Indirectly, symbiotic N-fixation influences the ecosystem nitrogen cycle. However, little is known about the ecology of symbiotic nitrogen fixation and specifically its feedback with the addition and recycling of soil nitrogen. Our studies examined how the conditions that influence plant performance also influence its regulation of symbiotic nitrogen fixation at the level of individual plants, and how these two, in turn, determine whether new nitrogen enters the soil, or other components of the ecosystem.

Our findings indicate that a diversity of nitrogen fixation strategies have been adopted by ephemeral herbaceous legumes, while perennial drought-adapted legumes, which have to survive through a dry rainless summer, always downregulated their investment in fixation when provided with external nitrogen source (facultative strategy).  We found that stress conditions (such as plant-plant competition) also invoked strong downregulation of nitrogen fixation in response to nitrogen availability in the soil. Downregulation of symbiotic nitrogen fixation was stronger in juveniles compared to mature individuals, and in woody perennials compared to herbaceous annuals. These results highlight that regulation of N-fixation is influenced both by plant N-demand and by a tradeoff between N-fixation and other carbon-demanding processes.

At the level of the ecosystem nitrogen cycle we found that, contrary to expectations, there is no added nitrogen in the surrounding of our studied N-fixing shrubs. Instead, we show that fixed nitrogen is allocated to different tissues within the plant and is lost and decomposed indirectly, primarily via grazing and fruit predation.

We conclude that regulation of nitrogen fixation and nitrogen conservation, are key adaptations influencing the fitness and persistence of nitrogen-fixing plants in the community, with broader consequences on existing perceptions on how N-fixation influences the ecosystem nitrogen cycle.

How to cite: Sheffer, E.: Adaptations of symbiotic nitrogen fixation minimize its contribution to ecosystem nitrogen cycles, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3438, https://doi.org/10.5194/egusphere-egu24-3438, 2024.

14:30–14:40
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EGU24-71
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BG3.7
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On-site presentation
Sara Chebbo

Biodiversity and associated functional diversity are expected to improve ecosystem stability in response to climate change. Land surface models (LSMs), such as Dynamic Global Vegetation Models (DGVMs), currently represent each plant functional type (PFT) as a "mean" plant, characterized by a set of global-scale average parameters that are static in space and time. However, this approach neglects to consider the diversity of traits observed in natural populations. To address this limitation, we incorporated the functional biogeography in the ORCHIDEE model, one of the most known DGVMs.  In this study, we aim to refine the representation of trait-based models to better capture the complexity of natural ecosystems.

We used a 5 km map of French permanent grasslands (FPGs) generated as part of the DIVGRASS project.  In this study, we focused on the case of FPGs for the 1960-2019 period. First, trait data were collected, and the distribution of traits was analysed at the national scale in France. The primary objective is to introduce the concept of Community-Weighted Means (CWM) of two key traits,  namely the specific leaf area (SLA) and the maximum rate of carboxylation (VCMAX) to better capture trait diversity within communities. We calculated the leaf lifespan (LLS), one of the traits represented in the model by a constant value. Five different experiments were performed using the ORCHIDEE model in order to simulate the net primary productivity (NPP) in each scenario. Furthermore, this study emphasizes the need to examine not only the productivity of grasslands in France but also the stability of grassland productivity. The choice of which stability productivity component to consider is pivotal for understanding the ecosystem functioning. Thus, we focused on the temporal invariability (constancy) and the maximum deviation from the average level of functioning baseline (resistance) of grassland productivity over time. Subsequently, we established relationships between productivity, constancy and resistance when all grasslands are combined on one hand and across four distinct grassland habitats with a contrasting floristic composition on another hand.  Finally, we used the satellite observations to assess the spatial similarity with the simulated NPP by the ORCHIDEE model in each of the 5 experimental cases. 

This study underscores the importance of incorporating community-weighted metrics and trait diversity in order to enhance the ecological relevance and accuracy of DGVMs. Understanding how trait values affect productivity and its stability is vital, especially when considering land surface models such as ORCHIDEE. 

 

Keywords:  C3 permanent grasslands, functional biogeography, biodiversity, ecoinformatics, land surface model,  plant traits, community weighted mean, constancy, resistance, dynamic global vegetation model, ORCHIDEE model, productivity, climate change, satellite observations

 

How to cite: Chebbo, S.: Functional biogeography integration in a land surface model: Spatial trait variability impact on productivity and stability of permanent grasslands in France, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-71, https://doi.org/10.5194/egusphere-egu24-71, 2024.

14:40–14:50
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EGU24-16900
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BG3.7
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ECS
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On-site presentation
Bárbara Rocha Cardeli, David Montenegro Lapola, Thomas Hickler, and Mateus Dantas de Paula

Climate change is impacting all regions of the world, particularly tropical ecosystems like the Amazon rainforest. The Amazon rainforest, being the largest tropical forest globally, plays a crucial role in acting as a carbon sink and mitigating the effects of climate change. However, studies indicate that the increasing levels of CO2 in the atmosphere can disrupt the ability of ecosystems to act as effective carbon sinks. The use of vegetation models, known as Dynamic Global Vegetation models (DGVMs), has become increasingly frequent in understanding the impact of climate change on vegetation through computer simulation of ecological and physiological processes. Some DGVM models, referred to as trait-based vegetation models, also allow the representation of different plant functional strategies within an ecological unit. Given the immense influence of mega-diverse ecosystems like the Amazon rainforest on the global carbon cycle and atmosphere CO2 concentrations, it is crucial to study the connections between the forest's ecosystem functioning and climate change. For this, we present a novel approach called “inverse modeling”. Conventional vegetation modeling approaches treat traits as parameters (i.e. independent variables) and carbon storage and productivity as outputs (i.e. dependent variables), however, in this approach, we will invert this arrangement. So, through the development of an inverse modeling framework we aim to identify the combination of functional traits that best maintain the Amazon forest's capacity as a carbon sink and ensure essential processes such as evapotranspiration, which impacts rainfall and the water cycle at the local level under climate change scenarios. The inverse algorithm will be developed using two trait-based DGVMs to ensure reproducibility and enhance the algorithm's robustness: CAETÊ (Carbon and Ecosystem functional Trait Evaluation model) and the LPJ-GUESS-NTD (Nutrient-Trait Dynamics). The main input data of this algorithm will be the values of the processes of (i) net primary productivity (NPP), (ii) biomass, and (iii) evapotranspiration rates. Three functional traits, related to productivity, carbon stock and evapotranspiration processes, will be considered to evaluate the functional composition: Specific Leaf Area (SLA, m²/g), Wood Density (WD, g/cm³), Specific Root Length (SRL, cm/g), and the parameter that describes the plant water use strategy related to CO2 assimilation rates (g1). And, simulations will be made under the climate change predicted according to the IPCC Sixth Assessment Report (2021; increase [CO2] and average temperature and reduces precipitation to Amazon region). Therefore, we will present to the scientific community an innovative approach to applying ecosystem modeling that allows testing and elucidating new hypotheses about climate change and its impacts on terrestrial ecosystems of global relevance, such as the Amazon. Highlighting the significance of plant functional traits in sustaining ecosystem functioning and resilience, and contributing to discussions on effective management and restoration techniques and methods of modeling.

How to cite: Rocha Cardeli, B., Montenegro Lapola, D., Hickler, T., and Dantas de Paula, M.: A new modeling approach to evaluate the effects of climate change on plant functional diversity in the Amazon rainforest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16900, https://doi.org/10.5194/egusphere-egu24-16900, 2024.

14:50–15:00
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EGU24-8983
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BG3.7
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ECS
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On-site presentation
Lucía Laorden-Camacho, Elena Tello-García, Karl Grigulis, Marie-Pascale Colace, Christiane Gallet, Ursula Peintner, Ulrike Tappeiner, Georg Leitinger, and Sandra Lavorel

In the context of climate change, shrub encroachment is expected to advance in temperature-sensitive ecosystems such as arctic and alpine grasslands. In mountain regions, shrub encroachment is further triggered by grassland management changes (i.e., land abandonment or extensification). Shrub encroachment is expected to significantly impact ecosystem properties and functions like carbon stocks in both aboveground and belowground compartments, nutrient concentrations, and to slow down biogeochemical cycles. While studies of shrub encroachment processes and their effects on plant and soil functioning have increased our understanding of underpinning processes, there is still a lack of integrated studies and knowledge gaps on the interaction between plant-soil changes and their cascading effects. Our study focuses on understanding these effects on plant community traits and soil properties, and whether these changes are linear. We took herbaceous, shrub and soil samples along gradients of encroachment in sub-alpine grassland communities at two sites in the Alps: Lautaret (France) and the Stubai Valley (Austria). We used a trait-based approach to analyze hypothesized nonlinear functional changes in communities, using community-weighted means (CWM) to scale herbaceous and shrub functional traits and plant allometries. Structural equation models (SEM) support our hypothesis that changing CWM with increasing shrub biomass flows on to changes in soil properties. Dwarf shrub encroachment leads to more conservative and less nutrient-rich plant communities, resulting in an accumulation of recalcitrant organic matter and nutrient-poor soils. Nevertheless, contrary to our expectations, decreased nitrogen in plant communities along the encroachment gradient did not lead to decreased soil available nitrogen. Our results generally suggest it is possible to characterize shrub encroached ecosystems in the Alps using well-studied traits of the global plant economic spectrum, like nitrogen content or dry matter content. With these findings, we are confident that well-researched trait-based models are also applicable for dwarf shrubs, allowing to scale-up from plant traits to the delivery of ecosystem services. This research provides a novel understanding of shrub encroached ecosystems and is a first step in understanding the patterns and mechanisms underpinning their provision of ecosystem services.

How to cite: Laorden-Camacho, L., Tello-García, E., Grigulis, K., Colace, M.-P., Gallet, C., Peintner, U., Tappeiner, U., Leitinger, G., and Lavorel, S.: Cascading effects of shrub encroachment in sub-alpine grasslands from a trait-based perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8983, https://doi.org/10.5194/egusphere-egu24-8983, 2024.

15:00–15:10
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EGU24-5255
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BG3.7
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ECS
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On-site presentation
Lijuan Sun, Tonghui Wu, and Xinyao Yang

Plants manipulate the activities of microbial decomposition in the rhizosphere, i.e. the so-called rhizosphere effects (REs). The more nutrient-acquisitive plants seem to allocate more carbon (C) to the rhizosphere to meet their nutrient demands. Alternatively, it is probably the fast-growing species are more C leaky. In this study, we induced plant regulation processes on C release and nutrient acquisition to the biogeochemical model of microbial decomposition. We simply increased two parameters, namely root exudation and plant competition capacity  against microbes for available nitrogen. Our model showed that C investment to the rhizosphere and plant nutrient-acquisition capacity with decomposers together determine the cost-benefit balance of rhizosphere effects. For each specific species with a specific nutrient-acquisition capacity, there is an optimal exudation invest for the plant’s best interests. Furthermore, co-existing species can have similar efficiency of C cost against N benefit by optimal pairs of exudation and competition capacity. Our model not only give mathematical explanation why acquisitive plants release more root exudation but also show promising tools to modeling rhizosphere effects at ecosystem levels.      

How to cite: Sun, L., Wu, T., and Yang, X.: Why do acquisitive fine-roots exude more carbon: A cost-benefit model simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5255, https://doi.org/10.5194/egusphere-egu24-5255, 2024.

15:10–15:20
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EGU24-1292
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BG3.7
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ECS
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On-site presentation
Magdalena Held, Tuula Jyske, and Anna Lintunen

Ensuring sufficient water transport to the leaves is crucial for trees to survive under varying water availability. Both hydraulic efficiency and safety depend highly on the anatomical structure of the conduits and particularly of their connections, the pits. On the one hand, wider conduits and pits enable higher water flow. On the other hand, air seeding (hydraulic failure) occurs through the pits, and wider pits and conduits (with more and/or larger pits) have a lower hydraulic safety, i. e., they are more susceptible to air seeding under stressed conditions. Conduits widen with distance from the treetop to counterbalance the resistance to water transport that accumulates with tree height. Although pits represent the main resistance to water transport in the xylem, we know little about the widening of pits or the coordination of conduit and pit dimensions. Trees exposed to stressful conditions may adjust the conduit- and potential pit-widening pattern to increase their hydraulic safety, otherwise they need to grow shorter. Our study aims to a) shed new light onto the coordination of conduit and pit dimensions at different distances from the treetop, and b) study if trees adjust the widening pattern of their conduits and particularly their pits to environmental conditions.

For our study, we sampled Scots pines (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) Karst) on two sites with different environmental conditions (forest types) and thus different tree growth rates. We took wood samples along the water transport pathway from the treetops to the roots. Then, we prepared light microscopical images from cross sections and analyzed the mean conduit diameter, mean hydraulic diameter, and cell wall reinforcement. Furthermore, we prepared tangential sections for scanning electron microscopy to measure the diameter of the margo (pit membrane), torus (central thickening of the pit membrane), and pit aperture. With those dimensions, we calculated the following pit functional properties: the margo flexibility, torus overlap, and valve effect, as well as the absolute torus overlap.

In both species, we found that the conduit and pit dimensions increase, whereas cell wall reinforcement decreases from the treetop towards the base of the tree. Roots do not necessarily follow the scaling pattern. In general, trees coordinated pit dimensions with the mean hydraulic diameter of conduits. The pit functional properties behaved differently in the two species. For example, the valve effect, which is strongly associated with hydraulic safety, increased in pine with distance from the treetop, whereas in spruce it decreased. Furthermore, torus overlap, valve effect, and absolute torus overlap increased in pine and decreased in spruce with mean hydraulic diameter. We detected no differences between the sites so far, but statistical analysis is still ongoing.

We conclude from the preliminary analyses, that the studied trees widen their conduit and pit dimensions with distance from the treetop to maintain a sufficient water flow through their stems while they grow in height. Overall, conifers seem to coordinate their conduit and pit dimensions well.

How to cite: Held, M., Jyske, T., and Lintunen, A.: Conduits and interconduit pits of Pinus sylvestris and Picea abies scale with water transport distance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1292, https://doi.org/10.5194/egusphere-egu24-1292, 2024.

15:20–15:30
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EGU24-6445
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BG3.7
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ECS
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On-site presentation
Thomas Guzman, Pierre Petriacq, Yves Gibon, Josep Valls-Fonayet, Thomas Dussarrat, Nicolas Devert, Cédric Cassan, Amélie Flandin, and Lisa Wingate

Mycorrhizal symbiosis is a ubiquitous plant-fungal association widespread across the plant kingdom. Considering the different characteristics and distributions of arbuscular (AM) and ectomycorrhizal (EM) fungal types across biomes, mycorrhizal types can be associated with different climatic and edaphic conditions, reinforced by feedback between soil conditions and plant traits. Although it is becoming clear that AM and EM trees differ in leaf litter quality and nutrient acquisition strategies, studies investigating how leaf traits differ across mycorrhizal associations have led to contrasting results. Here for the first time, we used a combination of quantitative targeted measurements and an untargeted metabolomic approach on 32 European tree species to demonstrate that AM and EM-associated tree species show distinct leaf metabolic fingerprints. Finally, we discuss the link between AM and EM function with key leaf metabolites that emerged from our integrated metabolomic approach.

How to cite: Guzman, T., Petriacq, P., Gibon, Y., Valls-Fonayet, J., Dussarrat, T., Devert, N., Cassan, C., Flandin, A., and Wingate, L.: Do leaf phytochemical fingerprints vary with mycorrhizal association?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6445, https://doi.org/10.5194/egusphere-egu24-6445, 2024.

15:30–15:45

Posters on site: Thu, 18 Apr, 10:45–12:30 | Hall X1

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 12:30
Chairpersons: Jens Kattge, Michael Bahn, Oskar Franklin
X1.28
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EGU24-2477
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BG3.7
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ECS
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Daniel Lusk, Sophie Wolf, Álvaro Moreno Martínez, Jens Kattge, Francesco Maria Sabatini, and Teja Kattenborn

The acceleration of global environmental change underscores the pressing need for a comprehensive understanding of how the biosphere interacts with its environment. To reliably examine these connections across diverse ecosystems, having extensive and spatially comprehensive data on plant functional traits is imperative. The TRY database boasts an extensive repository of plant trait measurements for thousands of species, and, while previous approaches have attempted to spatially extrapolate these traits using environmental predictors and remote sensing data, the scarcity of the original data leads to significant uncertainty in the extrapolations. Meanwhile, citizen scientists have been actively gathering dense observations of species occurrences worldwide, and when matched with trait data, can adequately represent global trait patterns. Here, we explore the use of citizen science and Earth observation data to generate global maps of 31 ecologically relevant plant functional traits. The study utilizes sparse spatial grids created by linking species occurrences from the Global Biodiversity Information Facility (GBIF) with the TRY gap-filled database to generate continuous global trait maps as a function of climate, soil, and remote sensing data. We first evaluated model performance using spatial cross-validation, and they demonstrated up to R2 = 0.53 with a normalized RMSE = 0.21. We then compared mean trait values from the GBIF-based extrapolations to community-weighted mean traits from sPlotOpen, a global, environmentally balanced dataset of vegetation plot data. Our results show correlations between the two datasets of up to r = 0.73 with particular resilience to decreasing map resolution. When compared to similar extrapolations based on sPlotOpen alone, we found that GBIF-based extrapolations increased global spatial applicability for all maps by up to 12%. Additionally, we show that GBIF-based extrapolations have higher correlations to sPlotOpen-derived maps than the majority of previously published trait maps. Despite the inherent noise and biases of their crowd-sourced origins, GBIF-based models are remarkably capable of producing even closer approximations of the trait distributions of scientifically controlled vegetation plots than their own sparse reference data. Considering the rapid growth and availability of crowd-sourced data, the capacity of models to overcome their noisy and opportunistic nature further affirms the potential of databases such as GBIF to complement more scientifically rigorous data collections.

How to cite: Lusk, D., Wolf, S., Moreno Martínez, Á., Kattge, J., Maria Sabatini, F., and Kattenborn, T.: Combining citizen science and Earth observation data to produce global maps of 31 plant traits, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2477, https://doi.org/10.5194/egusphere-egu24-2477, 2024.

X1.29
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EGU24-4475
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BG3.7
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ECS
Roxanne Lai, Tatsuro Nakaji, Tomoko Kawaguchi Akitsu, Fujio Hyodo, Hibiki Noda, and Hideki Kobayashi

Rapid and large-scale characterizations of forest canopies using remote sensing and modelling techniques are necessary, but the extent to which leaf-level traits and spectra can be upscaled to validate larger scale remote sensing data and vice versa is still not well understood. For one, spatial variations of leaf-level traits across tree crowns and canopies can bias results. While differences in extreme crown variations (e.g., shade and sun leaves) have been observed, across crown variation (i.e., sunlit leaves from top and sides of crown), which is of particular importance to increasingly higher resolution optical airborne and satellite remote sensing applications, have not been as widely documented.

Here, we investigated the across-crown and canopy variations of leaf-level plant functional traits and spectral reflectances and transmittances in a temperate forest in northern Japan. Our study period spanned the growing and senescence periods from July to October 2023 as well as deciduous broadleaf and evergreen conifer tree species. For each tree, we collected and processed sunlit leaves from two different crown positions visible to overhead aircraft: the top of the tree crown (TC) and at the tree crown periphery (CP).

We found differences in certain trait values (e.g., carbon (C) concentration,  d13C, leaf mass per area (LMA), chlorophyll, and total carotenoids) and spectra between TC (average height of 16.7 m above ground level) and CP (average height of 12.5 m above ground level) positions. We also show that differences between trait values and spectra between crown positions varied across tree species and over the growing and senescence periods. Overall reflectance and transmittance spectra across species showed increasing difference between TC and CP, especially in the near-infrared (NIR) region, from the growing to the senescence periods. Collectively, results suggest that crown sampling positions should be considered in the estimation of functional traits from spectral information, reflecting the dynamics of crown architecture. Particularly in spectral regions such as the NIR or short-wave infrared (SWIR), as well as during periods of senescence, where greater difference between crown positions were found.

How to cite: Lai, R., Nakaji, T., Akitsu, T. K., Hyodo, F., Noda, H., and Kobayashi, H.: Across-crown and canopy variations of plant functional traits and spectra for deciduous broadleaf and evergreen coniferous species in a temperate forest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4475, https://doi.org/10.5194/egusphere-egu24-4475, 2024.

X1.30
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EGU24-15797
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BG3.7
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ECS
Benjamin Dechant, Ryan Pavlick, Jens Kattge, Fabian Schneider, Francesco M. Sabatini, Alvaro Moreno-Martinez, Teja Kattenborn, Helge Bruehlheide, and Philip A. Townsend

Relationships between plant functional traits and environmental variables have been intensively studied in the ecological community due to their importance for applications such as generating upscaled trait maps and predicting trait responses due to climate change. However, such relationships have been found to be relatively weak for various potential reasons.

We analyzed global-scale trait-environment relationships using plot-level trait estimates based on the sPlotOpen and TRY databases. In addition to the commonly used community weighted mean (CWM), we considered a top-of-canopy weighted mean (TWM) metric that excludes understory vegetation. For both trait metrics, we quantified the change in trait-environment relationships when considering the dominant plant functional type (PFT) of the plot. 

We found that, overall, TWM combined with PFT had the strongest correlations to environmental variables and TWM also had the strongest increase in correlation when adding PFTs. CWM, in contrast, tended to show slightly higher correlations than TWM when not adding PFTs, but the correlations for CWM combined with PFTs were also substantially higher than CWM without PFTs. Overall, we found stronger trait-environment relationships compared to the existing literature. Our findings confirm the relevance of considering PFT-specific trait-environment relationships and demonstrate the considerable impact of different plot-level trait metrics. The choice of the most suitable trait metric depends on the application and the availability of ancillary data that can be used as weighting factors in CWM.

How to cite: Dechant, B., Pavlick, R., Kattge, J., Schneider, F., Sabatini, F. M., Moreno-Martinez, A., Kattenborn, T., Bruehlheide, H., and Townsend, P. A.: Global-scale plant trait-environment relationships based on sPlotOpen and TRY data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15797, https://doi.org/10.5194/egusphere-egu24-15797, 2024.

X1.31
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EGU24-5574
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BG3.7
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ECS
Mateus Dantas de Paula and Thomas Hickler

Exploring the intricate interplay between global biodiversity patterns and the looming impact of climate change stands as a paramount inquiry within the realm of earth system science. Furthermore, the acknowledgment of shifts in plant functional diversity emerges as a key catalyst, wielding substantial influence over pivotal ecosystem processes like the carbon cycle. Various essential plant traits, intricately tied to vegetation function—ranging from photosynthesis to carbon storage and water/nutrient uptake—underscore the significance of comprehensive global trait maps. These maps prove indispensable for unraveling environmental interactions, identifying threats to the biosphere, and fostering a profound understanding of our planet's intricacies. However, the sparse and non-representative nature of current trait observations poses a formidable challenge. Presently, global maps of vegetation traits are constructed by bridging observational gaps, primarily relying on empirical or statistical relationships between trait observations, climate and soil data, and remote sensing information. However, these approaches exhibit limited explanatory power, struggle to encompass a myriad of traits, and face constraints in ensuring ecological consistency in their extrapolations.

The VESTA (Vegetation Spatialization of Traits Algorithm) project emerges as a groundbreaking initiative aimed at refining our grasp on global above and belowground plant traits. This endeavor involves integrating a trait-based dynamic global vegetation model (DGVM) with Earth observation (EO) data. Trait-based DGVMs, rooted in a process-based foundation, forge a direct nexus between the environment, plant ecology, and emerging vegetation patterns. Leveraging insights from contemporary global trait databases, the model is initialized to mirror real-world conditions. Subsequently, EO data enters the equation to fine-tune the model through a calibration process, adjusting trait relationship curves having as reference satellite measurements of vegetation structure and productivity.

Drawing parallels to prior methods used in climate reanalysis, EO-constrained trait-based DGVMs yield a multivariate, spatially comprehensive, and coherent record of global vegetation traits. The resultant dataset encapsulates trait distributions, offering detailed insights into plant functional diversity metrics—mean, variance, skewness, and kurtosis—at specific locations. Notably, these trait maps extend beyond mere snapshots, evolving into a temporal series that affords a nuanced comprehension of the prevailing state of functional diversity and its temporal shifts. Ultimately, the fruition of this project manifests as an invaluable EO product, showcasing leaf, wood, and root traits and their change through time.

How to cite: Dantas de Paula, M. and Hickler, T.: Towards global maps of vegetation trait change - the VESTA project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5574, https://doi.org/10.5194/egusphere-egu24-5574, 2024.

X1.32
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EGU24-22186
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BG3.7
Carolina C. Blanco, Bianca F. Rius, João Paulo Darela-Filho, Barbara Cardeli, Izabela Aleixo, Simon Scheiter, Liam Langan, Jaideep Joshi, Florian Hofhansl, Shipra Singh, Mateus Dantas De Paula, Thomas Hickler, Shasank Ongole, Steven Higgins, Katrin Fleischer, Anja Rammig, Jeremy Lichstein, and David M. Lapola

The continuous rising of atmospheric carbon dioxide (CO2) concentration is undoubtedly affecting the resilience of tropical forests worldwide. However, the magnitude of such effects is poorly known, limiting our capacity to assess the vulnerability of tropical forests and to improve their representation by models. Functional diversity (FD) is an important component of biodiversity enhancing ecosystem resilience, as high FD can provide higher response diversity and capacity to buffer against climate change. How FD is represented by different Dynamic Global Vegetation Models (DGVMs) may affect how such models predict the impacts of environmental changes on hyperdiverse ecosystems. We compared simulations of five trait-based DGVMs (i.e., with flexible, variable traits) constrained with data from the Amazon rainforest in the scope of the AmazonFACE project. Simulations were conducted considering initial high or low diversity scenarios under ambient and elevated CO2 (400 ppm and 600 ppm, respectively). We searched for correspondence between the functional identity of simulated plant strategies and their ecophysiological performances under elevated CO2. As models take different approaches to simulating functional trait distributions and they differ in their structure and in the trade-offs implemented, we found important intermodel differences in simulated results. Nevertheless, we took advantage of these differences in order to assess the most likely scenarios in terms of functional composition under elevated CO2, as well as to give feedback for better harmonization of model inputs and outputs and future model improvements. In the face of the pessimistic scenarios that project a continuous increase in CO2 levels, resolving the divergent responses among model predictions is critical, given the global importance of the Amazon rainforest's biodiversity and climate regulation, as well as the approximately 30 million people that directly or indirectly depend on the forest for their well-being.

How to cite: Blanco, C. C., Rius, B. F., Darela-Filho, J. P., Cardeli, B., Aleixo, I., Scheiter, S., Langan, L., Joshi, J., Hofhansl, F., Singh, S., De Paula, M. D., Hickler, T., Ongole, S., Higgins, S., Fleischer, K., Rammig, A., Lichstein, J., and Lapola, D. M.: Non-matching predictions from different models simulating the effects of elevated atmospheric CO2 on the Amazon forest’s functional diversity, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22186, https://doi.org/10.5194/egusphere-egu24-22186, 2024.

X1.33
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EGU24-8705
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BG3.7
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ECS
Yanghang Ren, Han Wang, Sandy Harrison, Colin Prentice, Giulia Mengoli, Long Zhao, and Kun Yang

Leaf photosynthetic and respiratory processes are important for the terrestrial carbon cycle. Leaf physiological traits, such as the maximum carboxylation rate and leaf respiration rate at 25˚C (Vcmax,25, R25), the key parameters affecting photosynthesis and respiration rate, acclimate to environmental changes. However, many land surface models (LSMs) assume a constant R25 and Vcmax,25 by plant functional types (PFTs) due to limited understanding of plant acclimation processes. Here, we incorporated the acclimation of photosynthesis and leaf respiration into a land surface model (Noah MP) using the Eco-Evolutionary Optimality principle (Noah MP-EEO), and evaluated the performances of the EEO and standard schemes to simulate photosynthesis and respiration using global plant trait measurements and data from FLUXNET. We demonstrate that R25 and Vcmax,25 varied temporally and spatially within the same PFT (C.V. >20%). This behaviour is captured by the EEO scheme (R2 =0.69 and 0.62 for temporal and spatial variations) but ignored by the standard scheme. At the FLUXNET sites, the standard scheme underestimates gross primary production (GPP) but this is reduced in the EEO scheme. The EEO scheme explains 66% of the variation of site-annual GPP compared to 55% in the standard scheme. The EEO scheme also simulates the variation of leaf respiration (Rleaves) better than the standard scheme (R2 increases from 0.45 to 0.77). The EEO scheme shows less temperature sensitivity than the standard scheme because of acclimation. This study indicates that adopting EEO approaches that do not require PFT-specific parameters improves carbon cycle predictions and could be used in Earth system models for better understanding the climate-carbon feedback.

How to cite: Ren, Y., Wang, H., Harrison, S., Prentice, C., Mengoli, G., Zhao, L., and Yang, K.: Incorporating the acclimation of photosynthesis and leaf respiration in the Noah-MP land surface model: model development and evaluation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8705, https://doi.org/10.5194/egusphere-egu24-8705, 2024.

X1.34
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EGU24-17097
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BG3.7
Karin Rebel, Astrid Odé, Jan Lankhorst, and Hugo de Boer

Quantifying leaf transpiration and photosynthesis is crucial for modeling global vegetation in a changing climate, but deriving general relationships and responses to environmental drivers across time scales remains challenging. A promising new approach to predict general leaf trait responses is the P-model (Prentice et al., 2014), which is based on eco-evolutionary optimality (EEO) theory. Leaf-level optimality is defined as the optimal ratio of leaf internal CO2 partial pressure to ambient CO2 partial pressure, resulting in maximum assimilation while minimizing respiration and transpiration costs. This process is coordinated via changes in both stomatal conductance and photosynthetic biochemistry, and results in a fundamental model with a strong dependency on climatic variables including temperature, relative humidity, CO2 levels, and light quantity. The P-model currently predicts instantaneous changes in leaf-level traits of photosynthesis and gas exchange without explicitly considering timescales of adaptation and acclimation, and the associated ranges of phenotypic plasticity of individual plants. It is also limited/confined to leaf-level traits, without considering whole-plant processes, like resource allocation. Thus, it is uncertain how leaf-level optimality and their related costs translate to organ level carbon and nitrogen allocation.

Our work focuses on further developing and evaluating the P-model by incorporating time scales of acclimation and adaptation, as well as upscaling leaf-level traits to whole-plant traits. To achieve these aims, we first developed a theoretical framework which allows the distinction of different timescales. Using a literature review, we identified and highlighted the tight relationship between leaf traits across timescales, and we also identified constraints on key leaf-level EEO optimality traits, and the timescales at which these constraints occur. We then propose a new framework to separate these responses at physiological, developmental, and evolutionary timescales. Second, we performed experimental work in order to evaluate the link between leaf-level optimality and whole-plant acclimation. Our experiments showed a strong response in whole-plant resource allocation to nutrient availability while leaf-level optimality was unresponsive to the nutrient treatments. This indicates that while leaf-level optimality is regulated mainly by climatic variables, whole-plant performance is strongly influenced by below-ground resource availability.

This research is a way forward in bridging plant ecophysiology and vegetation modeling, while acknowledging timescales and plasticity ranging from meteorology to deep time climate research. This work can be used to further develop EEO-modeling, and specifically the P-model.

How to cite: Rebel, K., Odé, A., Lankhorst, J., and de Boer, H.: Temporal and plant-structural constraints for eco-evolutionary optimality models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17097, https://doi.org/10.5194/egusphere-egu24-17097, 2024.

X1.35
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EGU24-2371
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BG3.7
|
ECS
Daniel Palchan, Anton Lokshin, Elnatan Golan, Ran Erel, and Stephen Fox

While roots have long been considered the sole pathway for plant nutrient uptake, a surprising discovery reveals a hidden source: foliar dust. This study demonstrates that plants can directly acquire crucial minerals like P, Fe, and Ni from deposited dust particles, bypassing the root system altogether. In our experiments, we had applied two types of dust on plant foliage and examined biomass, P content, and ionome. Remarkably, utilizing radiogenic Nd isotopes, we show that this foliar pathway surpasses root uptake in just weeks, contributing over 60% of a plant's nutrient profile under elevated CO2 conditions.

These findings shed light on a previously unrecognized adaptation that could be critical for plant survival in a CO2-rich world. As eCO2 levels are predicted to decrease soil nutrient availability, the dust-as-nutrient phenomenon offers a potential lifeline for plants and ecosystems. Moreover, understanding this alternative pathway could pave the way for novel agricultural strategies to combat "hidden hunger" malnutrition triggered by CO2-induced nutrient deficiencies.

How to cite: Palchan, D., Lokshin, A., Golan, E., Erel, R., and Fox, S.: Beyond roots: Foliar dust as a vital nutrient source for plants under elevated CO2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2371, https://doi.org/10.5194/egusphere-egu24-2371, 2024.

X1.36
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EGU24-5264
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BG3.7
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ECS
Gabriela Sophia, Silvia Caldararu, Benjamin Stocker, and Sönke Zaehle

Nutrient resorption from senescing leaves is a critical process of plant nutrient cycling that can significantly affect plant nutrient status and growth, making it essential for land surface models in order to predict long-term primary productivity. Most models assume leaf resorption to be a fixed value of 50% for N and P partially because we lack the knowledge of what drives this process, being unknown its implications when simulating nutrient cycling. Based on our own analysis of global patterns of nutrient resorption from trait data, we developed a dynamic scheme of nutrient resorption for nitrogen and phosphorus driven by leaf structure, longevity and environmental factors, to be implemented in the QUINCY model. We present the concept behind this novel scheme through ecophysiological traits trade-offs, as well as first implications for ecosystem functioning. We show that we can better predict plant and soil nutrient dynamics at steady state and crucially, under altered climate and CO2 conditions. Plant internal nutrient cycling has cascading implications for ecosystem nutrient pools and fluxes, being an essential process in ecosystem models, that allows us to improve our predictions of the future and furthers our understanding of nutrient cycling processes.

How to cite: Sophia, G., Caldararu, S., Stocker, B., and Zaehle, S.: Ecological trade-offs between leaf structure and plant nutrient demand to predict nutrient resorption in a terrestrial biosphere model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5264, https://doi.org/10.5194/egusphere-egu24-5264, 2024.

X1.37
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EGU24-5592
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BG3.7
|
ECS
Fabio Berzaghi and David Makowski

Plant nutritional traits (or nutritional values) are a fundamental property of the food web and also important for human beings' health. Much research on nutritional values has focused on a small selected group of plants and primarily crops, but their broader importance for wild animals has been neglected. In particular, the effect of climate change on the nutritional quality of plants is poorly understood even though it may have major implications for the food web and ecosystems. Here we use a dataset covering > 1450 plant species to identify the factors driving plants nutritional properties and develop global projections. We reveal that plant type, CO2, and solar radiation are major drivers controlling nutritional properties. Projections for 2050 show a decline in nutritional quality (-8%, on average at the global scale), measured as the protein to fiber ratio, a strong decrease in minerals (-18%), and a small decrease in digestibility (-3%). Plants in arid and tropical areas will experience the largest decline in quality, which will decline minimally in temperate areas and improve in cold, and polar regions. Quality trends will be opposite in grasses. These results have important implications for human's health, livestock management, and wildlife conservation.

How to cite: Berzaghi, F. and Makowski, D.: Better integration of nutritional quality of plants in ecological research, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5592, https://doi.org/10.5194/egusphere-egu24-5592, 2024.

X1.38
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EGU24-5706
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BG3.7
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ECS
Tania L. Maxwell, Elisa Stefaniak, Florian Hofhansl, and Jaideep Joshi

To predict the response of forest ecosystems and how projected climate change will shift plant species composition, we need models that can account for adaptations encompassing multiple temporal and organizational scales. Recently, eco-evolutionary optimality-based models have emerged, which need fewer parameters than their empirical counterparts, i.e. standard dynamic global vegetation models. The new Plant-FATE (Plant Functional Acclimation and Trait Evolution) model embodies functional diversity through the representation of species across trait space. It integrates ecosystem adaptations across three distinct levels: firstly, it captures the acclimation of plastic traits in individual plants by harnessing the principles of eco-evolutionary optimality. Secondly, to simulate shifts in species composition through demographic changes and species immigration, a trait-size-structured demographic vegetation model is implemented. Lastly, the model addresses the long-term genetic evolution of species by incorporating novel evolutionary theory tailored for trait-size-structured communities. Currently, Plant-FATE implements fine roots by scaling these to total leaf area, and coarse roots as a fraction of stem mass. Thus, rooting structures, plant root traits, and belowground trade-offs are not represented.

To expand the modelling framework, we are implementing fine roots in a similar way as the crown, as a function of the root length profile and the root projection area. We are maintaining the current model structure so that total fine root mass is related to total leaf mass, which reduces the additional parameters needed to model. Instead, we are incorporating one additional trait, specific root length (SRL), which will determine the rooting profile, and which can evolve by natural selection in response to environmental changes. This allows for a depth distribution of fine roots, and for the plant water uptake to be dependent on both soil water potential and root distribution. At a community level, this implementation now means that changes in soil water content, e.g., during drought, can influence belowground competition and trade-offs between above- and below-ground biomass for different species. By modelling rooting strategies of deep-rooted vs shallow-rooted species, or evergreen vs deciduous species, the new root implementation in Plant-FATE will enable correct prediction of differential drought and climate response of coexisting plant species in line with the observed trade-offs in relative investment in above- and belowground tissues in association with their life-history strategy. It will thus allow to create a continuum of plants and their eco-evolutionary niches, which will allow us to predict plant functional diversity in response to environmental cues. Ultimately, incorporating roots in Plant-FATE will better represent ecosystem adaptation and community shifts in response to a changing climate.

How to cite: Maxwell, T. L., Stefaniak, E., Hofhansl, F., and Joshi, J.: Incorporating roots into Plant-FATE, a dynamic eco-evolution trait-based vegetation model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5706, https://doi.org/10.5194/egusphere-egu24-5706, 2024.

X1.39
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EGU24-17600
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BG3.7
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ECS
Robert Caine, Peter Berry, Kate Storer, and Holly Croft

Understanding how crops contribute to carbon, water and nitrogen cycling under different fertiliser regimes will be crucial for improving ecosystem models and predicting future yields. Synthetic fertilisers hugely boost crop yields, but excessive application often leads to negative environmental impacts including increased nitrous oxide emissions (about c. 300x more potent than CO2). To maximise crop yields and optimise fertiliser and water application, rapid retrieval of plant traits and fluxes will be critical. Here, we explore the effectiveness of optical (trait-based) and thermal (flux-based) remotely-sensed data collected from ground-based and drone platforms for quantifying differences in plant physiological performance and overall yield in field-grown wheat under different nitrogen, sulphur and or sugar treatments.

Research was undertaken at a winter wheat variable nutrient field trial in North Yorkshire, UK during June, 2021. Across 24 treatment plots (3 plot replicates per treatment), leaf level hyperspectral reflectance data was obtained using a Spectral Evolution PSR+ 3500 Spectroradiometer which was paired with stomatal conductance (gsw) measurements (collected using a LI-COR LI-600 porometer) and photosynthetic capacity (Vcmax) measurements (collected using a Li-6800 portable infra-red gas analyser). Plant thermal images were captured using a handheld FLIR T650-C thermal imaging camera (640x480). Field-assessed leaves were destructively harvested for leaf chlorophyll and nitrogen content analysis. Drone flights were conducted using a DJI Matrice M200 with a MicaSense RedEdge-Mx multispectral imaging sensor (1456 x 1088) and a Parrot Analfi thermal drone (160 x 120) at a 10 m altitude above ground.

Results show that plants fertilised with sulphur and nitrogen had the highest or equal-highest leaf chlorophyll values (c. 60-70 µg/cm2), followed by plants that only received nitrogen (c. 40-55 µg/cm2), with unfertilised controls having the lowest chlorophyll values (c. 15-20 µg/cm2). Sugar did not significantly affect leaf chlorophyll values but an interaction was detectable between sugar and fertiliser at the plot level (Two-way ANOVA, p < 0.05). Strong relationships were found between the MERIS terrestrial chlorophyll index (MTCI) spectral vegetation index, calculated from drone-acquired optical reflectance, and both leaf chlorophyll content (R2 = 0.76; p < 0.0001) and crop yield (R2= 0.90; p < 0.0001). Vcmax assessment also revealed a strong relationship with chlorophyll across fertiliser treatments (R2 = 0.77, p < 0.0001), with sulphur and nitrogen application again producing the highest trait values. Plants receiving nitrogen or nitrogen and sulphur had c. 50% higher gsw, with leaf temperatures that were c. 1-3 °C cooler than unfertilised controls. Sugar did not significantly affect leaf gsw or temperature. Using ground-based and drone-mounted thermal cameras, strong correlations were shown between leaf temperature and gsw (R2 = 0.64; p < 0.0001  and R2 = 0.6; p < 0.001 respectively).  Data captured during the drone flights enabled the production of spatial maps of Vcmax (~3 cm spatial resolution) across the field trails to reveal clear differences in photosynthetic capacity both across and within nutrient treatments. Overall, remote sensing data accurately captured subtle differences in plant traits and water fluxes paving the way for field-scale mapping of crop physiological, biochemical and structural traits.

How to cite: Caine, R., Berry, P., Storer, K., and Croft, H.: Modelling crop productivity, water fluxes and yield in winter wheat from remotely-sensed drone data under differential sulphur, nitrogen and or sugar application., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17600, https://doi.org/10.5194/egusphere-egu24-17600, 2024.

X1.40
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EGU24-1697
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BG3.7
Anton Lokshin

Dusty secrets: REE unveil hidden trends in foliar plant nutrition under rising CO2

 

Anton Lokshin1,2, Avner Gross2, Daniel Palchan1

 

1Department of Civil Engineering, Ariel University, Ariel 40700, Israel

2 Department of Geography and Environmental Development, Ben Gurion University of the Negev, Beer Sheva 8410501, Israel

 

The emerging phenomenon of direct foliar nutrient uptake, where dust deposits replenish plant ionome under stress, holds potential as a significant adaptation in a changing world. Dust's rapid leaf deposition, bypassing soil contact, offers a unique nutrient source, particularly relevant in soils of limited fertility. Rising CO2, known to hinder root nutrient uptake, along with an expected decrease in soil fertility, further underscores the potential importance of this pathway. Here, we present findings from laboratory experiments in which chickpea plants were treated with atmospheric particles used as natural fertilizers. These particles, including fire ash, volcanic ash, and desert dust, were applied to plant foliage under ambient and elevated CO2 conditions. We examined the foliar nutrient pathway from the Rare Earth Elements (REE) perspective and demonstrated that REEs serve as an excellent tool for its exploration. Analysis of the REE within the treated plants showed enrichment in Light REE compared to Heavy REE concurrent with higher biomass and improved carbon assimilation – proving the nutrients were assimilated into the plant rather than just surface retention. Finally, our results elucidate a couple of trends in the foliar nutrient uptake pathway: (1) under elevated CO2 levels, the foliar uptake is larger, and (2) nutrient transport from dust to plant is in the following order- volcanic ash > desert dust > fire ash. Analysis of REE patterns and ratios, alongside other biological parameters, provides novel insights into the extent and dynamics of foliar nutrient uptake across dust types and CO2 levels, shedding light on previously unexplored aspects of this crucial adaptation.

How to cite: Lokshin, A.: Dusty secrets: REE unveil hidden trends in foliar plant nutrition under rising CO2, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1697, https://doi.org/10.5194/egusphere-egu24-1697, 2024.

X1.41
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EGU24-4927
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BG3.7
Xiang Song, Jinxu Li, and Xiaodong Zeng

The tree height–diameter at breast height (H–DBH) and crown radius–DBH (CR–DBH) relationships as well as wood density are key for forest carbon/biomass estimation, parameterization in vegetation models and vegetation–atmosphere interactions. Although the H–DBH relationship has been widely investigated on site or regional scales, and a small amount of studies have involved CR–DBH relationships based on plot-level data, few studies have quantitatively verified the universality of these two relationships on a global scale. Moreover, in current Earth System Models/Dynamic Global Vegetation Models (ESMs/DGVMs), wood density is also oversimplified, being defined either as a uniform constant or as plant functional type-dependent (PFT-dependent) constants worldwide. Such oversimplifications may lead to simulation biases in morphology of woody PFTs, ecosystem transition and vegetation-atmosphere interactions.

In our study, the ability of 29 functions to fit the H–DBH and CR–DBH relationships for six different plant functional types (PFTs) are evaluated on a global scale, based on a global plant trait database. Then, the relationships between H-DBH, CR-DBH, wood density and climate are investigated. This work provides a valuable foundation for parameterization improvements in vegetation models, and some clues to forest field investigations.

How to cite: Song, X., Li, J., and Zeng, X.: Adaptions of tree individual morphology and stem wood density to multiple climate and soil characteristics gradients, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4927, https://doi.org/10.5194/egusphere-egu24-4927, 2024.

X1.42
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EGU24-16156
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BG3.7
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ECS
Songwei Wang, Günter Hoch, Sven Hopf, and Ansgar Kahmen

During drought, when trees have lost access to soil moisture, the survival time of trees is intimately linked to leaf minimum water conductance (gmin), which determines the residual water loss after a tree has fully closed its stomates. Large differences in gmin are known among different tree species from contrasting climates. In addition, gmin typically exhibits strong and highly species-specific thermal sensitivity (T) with rising temperatures. Within a species, the genetic variability (G) and phenotypic plasticity (P) of gmin, and especially the G and P of the thermal sensitivity, in natural tree populations remains unknown. Here we examined the thermal sensitivity of four tree species (Acer pseudoplatanus, Fagus sylvatica, Picea abies, and Pseudotsuga menziesii) and assessed G, P, and the interaction of G x P of gmin and T in a provenience trial. Additionally, we determined the relative distance plasticity index (RDPI) among populations for each species and how leaf cuticular and stomatal traits are related to the intraspecific variation in gmin. The trees that we investigated were grown in three trials with different hydroclimatic conditions in Switzerland. Our results show a strong effect of T on gmin, which increased by a factor of two to seven when the temperature increased from 30 to 50 °C for all studied species. Importantly, gmin in two deciduous broadleaf tree species displayed strong G, with gmin values being higher for genotypes originating from wet climates than those of trees originating from dry climates. In contrast, there was little G in gmin for two evergreen conifers. On the other hand, significant P of gmin was found in all tested tree species, with higher gmin values for trees grown in wet rather than dry environments. RDPI was typically low across provenances for all studied tree species, suggesting the limited absolute P of gmin. Interestingly, there was a dramatic interaction of P x T for Fagus, showing stronger temperature responses under wet growing conditions rather than dry growing conditions. Interestingly, G and P of gmin could not be simply explained by leaf stomatal and cuticular traits. Our study provides novel insights into the long-term evolution and short-term adaptation of gmin, suggesting that gmin may be capable of acclimating to future hotter and drier environments in some but not all species. Our findings provide practical measurements for improving European forest management in the context of global-change-type drought.

How to cite: Wang, S., Hoch, G., Hopf, S., and Kahmen, A.: Genotypic variability and phenotypic plasticity of leaf minimum conductance, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16156, https://doi.org/10.5194/egusphere-egu24-16156, 2024.

X1.43
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EGU24-7732
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BG3.7
Understanding and Managing Plant Species Invasiveness: Unraveling Vegetation Type-Specific Correlations with Species Traits and Indicators
(withdrawn)
Kristina Blennow and Cecilia Palmér
X1.44
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EGU24-17553
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BG3.7
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ECS
Mengdi Gao

Terrestrial climate and vegetation exhibit distinct zonal patterns in relation to longitude, latitude, and altitude, a phenomenon known as three-dimensional zonality. Accelerated warming rates since the industrial revolution, along with changes in latitude and altitude, have the potential to influence the geographical distribution of vegetative phenology. To comprehend and accurately predict changes in terrestrial ecosystems, it is critical to understand the three-dimensional zonal variations in global vegetation phenology. Using the PEP725, USA-NPN, and CPON phenological network datasets, we examined and compared the spatiotemporal dynamics of longitudinal, latitudinal, and elevational gradients at the beginning (SOS) and end (EOS) of the growing season over the last forty years in different regions and identified the potential mechanisms underlying these variations. It is revealed that the changes in latitudinal, longitudinal, and altitudinal gradients of SOS vary by location. Between 1980-1990 and 2008-2018, the latitudinal gradient of SOS in Europe decreased threefold, from 1.38 days/degree to 0.37 days/degree. In China, the longitudinal, latitudinal, and altitudinal gradients of SOS have all decreased, indicating that SOS is becoming more synchronized across longitude, latitude, and elevation. Unlike SOS, the latitudinal, longitudinal, and altitudinal gradients of EOS differ from species. For example, in Europe, the correlation between EOS and latitude has weakened for Aesculus hippocastanum and Betula pendula, indicating a reduced latitudinal gradient in EOS for these two tree species. In contrast, the correlation between latitude and EOS for Fagus sylvatica has strengthened, suggesting an increased latitudinal gradient in EOS for this species. In North America, due to the limited observation period, the changes in latitudinal gradients of plant phenological periods are not yet clear. These findings of mixed three-dimensional zonal variations in global vegetation phenology pose challenges for mitigating the possible adverse impacts of climate change.

How to cite: Gao, M.: Mixed three-dimensional zonal variations in vegetation phenology based on global site observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17553, https://doi.org/10.5194/egusphere-egu24-17553, 2024.

Posters virtual: Thu, 18 Apr, 14:00–15:45 | vHall X1

The posters scheduled for virtual presentation are visible in Gather.Town. Attendees are asked to meet the authors during the scheduled attendance time for live video chats. If authors uploaded their presentation files, these files are also linked from the abstracts below, but only on the day of the poster session. The button to access Gather.Town appears just before the time block starts. Onsite attendees can also visit the virtual poster sessions at the PICO spot in the corresponding on-site poster hall (e.g. virtual posters of vHall X4 are visible at PICO spot 4).
Display time: Thu, 18 Apr 08:30–Thu, 18 Apr 18:00
Chairperson: Jens Kattge
vX1.1
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EGU24-11473
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BG3.7
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ECS
Wanying Yu, Congwen Wang, Zhenying Huang, Deli Wang, and Guofang Liu

Woody plants are an important component of dryland vegetation. Research on wood decomposition in drylands has still been scarce compared with mesic ecosystems. Disentangling climate, position, and wood traits on decomposition rates is vital for understanding the carbon cycle in drylands. We studied the relative importance of economic traits including wood nitrogen, density, dry matter content (DMC) and bark weight ratio and the size trait of wood diameter class (<2, 2–4, 4–8, 8–13 and 13–20 mm) of plant species (four to five local species and one standard plant material) and position (aboveground and belowground) on wood litter decomposition rates along a precipitation gradient from 37 to 369 mm covering five sites. Decomposition rate of woody litter in buried condition was significantly higher than that on soil surface, which the position did not affect wood decomposition rates in extremely arid site. The decomposition rates of woody litters with first- and second-class diameter were higher than those of other-class diameter. The wood economics spectrum, and wood DMC and diameter were the most important drivers regulating wood decomposition rates. Woody litters with a larger size or in drier sites were characterized by higher wood DMC and density. The accelerating effect of soil burial increased with increasing annual precipitation or increasing woody litter diameter. Precipitation and wood diameter regulated woody litter decomposition rates directly and indirectly by modulating wood DMC or bark weight ratio. Our findings highlight a dual role of precipitation and stem diameter on aboveground and belowground woody litter decomposition and the effects of position on wood decomposition rates depend on precipitation and woody litter quality in drylands. Accurately measuring the wood decomposition rate in drylands and its sensitivity to macroclimate and position-mediated microenvironment would help improve the global carbon cycle models.

How to cite: Yu, W., Wang, C., Huang, Z., Wang, D., and Liu, G.: Disentangling the effects of precipitation, position, and economic and size traits on wood decomposition rates across drylands, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11473, https://doi.org/10.5194/egusphere-egu24-11473, 2024.