Wood density is an emergent property resultant of tree growth strategies modulated by local edapho-climatic and stand development conditions. It is associated with the biomechanical support of trees and hydraulic conductivity or safety, directly and indirectly influencing a range of ecological processes, including, among others, tree growth, tree resistance to disturbances, and mortality. Tree wood density is also crucial for assessing vegetation carbon stocks by supporting the link between a volumetric retrieval and a mass estimate. Earlier studies based on tree-level wood density measurements have reported significant relationships between wood density, environmental conditions, and tree growth strategies. However, these were either regionally focused or suffering from data availability, lacking a representative large-scale and spatially explicit representation of factors influencing tree wood density. This study collects and collates information from several sources to construct a global database of 28,822 tree-level wood density measurements alongside with a wide set of climate, soils, topography, and Earth observation covariates to support the development of statistical models for wood density. The dataset, consisting of more than 3,000 global covariates, is used for training different machine learning models, including random forest model (RF), light gradient boosting model (LGBM), extreme gradient boosting model (XGBoost), and bagged trees models. The experimental design considers six cross-validation approaches: either random 5-fold; according to two sets of climate classifications, land cover types, ecozones, or latitudinal ranges. Model performances are assessed with the coefficient of determination (R²) and Root-mean-square errors (RMSE) when predicting an independent test subset of wood density. The top ten models show a prominent performance (R² > 0.67 and RMSE < 0.09), and their ensemble mean, and standard deviation are considered the best estimation and uncertainty in wood density predictions, respectively. Systematic underestimation biases are observed around the low northern latitudes (0º-20ºN), primarily due to the lack of wood density measurements. Further analysis of sources of uncertainties and their quantification support the generation of a global quantitative and spatially explicit representation of wood density. The ecological interpretation and quantitative assessment of global wood density, and associated uncertainties aim to contribute to improving predictions of vegetation biomass and inferring ecosystem resistance under current and future climate scenarios.

How to cite: Yang, H., Benson, V., Zhang, Y., Son, R., Wang, S., Zhang, W., Zhang, Y., Robin, C., Schepaschenko, D., Karaszewski, Z., Krzysztof, S., Moreno-Martínez, Á., Nabais, C., Ibanez, T., Vieilledent, G., Weber, U., and Carvalhais, N.: Global patterns of tree wood density, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8794, https://doi.org/10.5194/egusphere-egu23-8794, 2023.

Plant functional traits (FTs) determine the survival strategies of plants and their adaptations to the environment, which affect the structure and productivity of vegetation. However, global patterns of many FTs remain uncertain. Currently available global maps of FTs generated by different upscaling approaches show considerable divergence. Potentially different trait responses could be induced by climate change in herbaceous, evergreen and deciduous taxa. Better understanding of these variations should improve our ability to predict global trait patterns and the consequences of global environmental change for vegetation.

We compiled a global data set for 18 FTs, including 42,676 species from 89,478 natural vegetation plots. All FTs in the data set have community-weighted mean values for each plot; seven also have species-mean values. We grouped the species into non-woody, woody deciduous and woody evergreen categories according to their life form and leaf phenology. Then we calculated community-weighted mean values of the seven FTs having species-mean records for the three plant groups. We selected three bioclimatic variables: a moisture index (MI, representing plant-available moisture), mean temperature of the coldest month (MTCO, representing winter cold), and mean growing season temperature (MGST, representing summer warmth) to create a three-dimensional global climate space and define global climate classes. Principal Component Analysis (PCA) was used to estimate the main functional continua on which FTs converge for each plant group. Redundancy Analysis (RDA) was used to describe the extent to which variation in trait combinations can be explained by bioclimatic variables. Correlations between each trait and bioclimatic variables for the three plant groups were described by Generalized Additive Models (GAMs). We used the GAMs to visualise the trait distribution in global climate space for all seven FTs, group by group. We finally fitted new comprehensive GAMs considering bioclimatic variables and remotely-sensed global cover of the three plant groups in order to predict global patterns for all 18 FTs at 0.1° spatial resolution.

Bioclimatic variables explain more trait variance for woody than non-woody plants. Two trait combinations are common to all plant groups: one is plant height (H) – diaspore mass (DM), positively associated with seasonal temperatures; the other is leaf mass per unit area (LMA) – leaf nitrogen content per unit area (N_area), decreasing with moisture availability. Stem specific density (SSD) of non-woody plants is correlated with the LMA–N_area axis, but SSD of woody evergreen plants is correlated with the H–DM axis. For woody deciduous plants, SSD is correlated with leaf nitrogen content per unit mass (N_mass). Leaf area (LA) is positively correlated with all bioclimatic variables and shows variation in all plant groups that is independent of other traits. FTs within the same trait combination tend to present similar patterns in the global climate space. GAMs based on bioclimatic variables and vegetation cover explain up to three-quarters (on average about a half) of global trait variation.

Our study reveals universal relationships among traits and between traits and climates, highlights certain key differences between within non-woody, woody deciduous and woody evergreen taxa, and produces high-resolution global maps for plant functional traits.

How to cite: Li, J. and Prentice, I. C.: Global patterns of plant functional traits and their relationships to climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7428, https://doi.org/10.5194/egusphere-egu23-7428, 2023.

Whether forests are composed of evergreen or deciduous species largely affects biogeochemical cycles and the functioning, structure and biodiversity of ecosystems. These leaf phenology types may be self-promoted through positive plant-soil feedbacks, which may shift the distribution of forest types towards alternative stable states. However, we still lack empirical evidence of phenological alternative stable states and a spatial understanding of where they might be present. Here, we test the presence of alternative stable states using forest inventory data at the continental (North America and Europe) and global scale. We show that the distribution of forest leaf phenology types is bimodal, and demonstrate the presence of positive feedbacks in recruitment, growth and mortality. Data-driven simulations show that the observed positive feedbacks are sufficient and necessary to produce the alternative stable states, which also lead to hysteresis during ecosystem transition. Spatial random forest models further reveal hotspots of alternative stable states in evergreen-deciduous ecotones and the poleward range limit of forests, which appear largely driven by soil feedbacks. Given the close connection between forest leaf phenology and ecosystem biogeochemical processes, our insights on evergreen vs. deciduous alternative stable states inform our understanding of the distribution of forest biomes, allowing more accurate quantification of carbon turnover and terrestrial climate feedbacks.

How to cite: Zou, Y., Zohner, C., Averill, C., Ma, H., Merder, J., Berdugo, M., Bialic-Murphy, L., Mo, L., and Crowther, T.: The evidence and global extent of alternative stable states in forest leaf phenology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1310, https://doi.org/10.5194/egusphere-egu23-1310, 2023.

Global trait maps of specific leaf area (SLA), leaf nitrogen (N) and phosphorus (P) contents have been generated using a wide range of data-driven upscaling approaches. We comprehensively studied their consistency and agreement with sPlotOpen data at 0.5 degee grid cells. For this, we developed approaches to separate the maps into their plant functional type (PFT) components by taking into account within-grid-cell heterogeneity and stratified sPlotOpen data by PFT.

We found that despite many differences in the upscaling approaches, the maps fall into two groups: One group using remote sensing based, fractional PFT cover  in the upscaling, while the other did not. Spatially, the main differences between the two groups are located in areas of high within-grid-cell trait heterogeneity and these areas dominate global trait variations due to the combined effects of fractional PFT cover and trait differences between-PFTs.

The agreement of upscaled maps with sPlotOpen data strongly depends on the way sPlotOpen data are scaled to the grid cell. When using a similar scaling approach as the upscaling approaches a similar level of agreement can be observed for both groups of maps. However, only the maps that used PFT information could capture main features of between-PFT differences, especially the low values of SLA and N in evergreen needleleaf forests. Within-PFT trait variations of upscaled maps partly showed similar patterns as sPlotOpen data when aggregated to latitudinal averages but considerable differences remain and the evaluation is challenging without having the original maps per PFT. 

We conclude that fractional PFT cover contains essential information for capturing global, top-of-canopy trait patterns using upscaling approaches at moderate to coarse spatial resolution.

How to cite: Dechant, B., Pavlick, R., Schneider, F., and Townsend, P. and the sTRAITS working group: Comprehensive intercomparison and evaluation of global upscaled foliar trait maps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13750, https://doi.org/10.5194/egusphere-egu23-13750, 2023.

As global change accelerates, the urgency for a solid understanding of biosphere-environment interactions grows. However, we need more data on plant functional traits to test such relationships reliably across ecosystems. The TRY database contains an impressive collection of plant trait measurements for thousands of species already, and there have been some approaches to spatially extrapolate them using geospatial predictors and remote sensing data; however, the original data is spatially sparse so that extrapolations come with substantial uncertainties. At the same time, citizen scientists have collected increasingly dense observations of species occurrences around the globe. Here, we test if we can link species occurrences from the citizen science project iNaturalist with trait observations from TRY to produce global trait maps without the need for spatial extrapolation. We generated spatial grids for 18 traits, calculating a mean for each grid cell by averaging trait values associated with observations within that cell. We compared mean trait values from iNaturalist observations to community-weighted mean traits from sPlotOpen, a globally sampled dataset of vegetation plot data. 

Our results show correlations between the two datasets of up to r = 0.69, especially in biomes with higher iNaturalist observation density and those not dominated by trees. Also, we show that iNaturalist-derived maps have higher correlations to sPlotOpen-derived maps than previously published trait maps. This strong correlation between two fundamentally different datasets is astounding and unexpected. iNaturalist is noisy and heterogenous, sampled by citizen scientists who share the species they encounter and find interesting; sPlotOpen is a data collection of vegetation plots that were measured and recorded within the framework of specific research questions. The fact that these two datasets exhibit such a strong resemblance opens up a promising avenue for using the data treasure trove that is crowd-sourced data to help fill the gaps in plant trait data and demonstrates that crowd-sourced data, such as the iNaturalist observations, can be used to complement professional data collection efforts.

How to cite: Wolf, S., Mahecha, M., Sabatini, F. M., Wirth, C., Bruelheide, H., Kattge, J., Moreno Martínez, Á., Mora, K., and Kattenborn, T.: Citizen science observations capture global patterns of plant traits, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2415, https://doi.org/10.5194/egusphere-egu23-2415, 2023.

How to cite: Cranko Page, J., Abramowitz, G., De Kauwe, M. G., and Pitman, A. J.: Using Machine Learning to Reveal the Relationships Between Plant Functional Traits and Flux Regimes at Eddy-Covariance Towers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10049, https://doi.org/10.5194/egusphere-egu23-10049, 2023.

The O₂:CO₂ exchange ratio of plants is an only recently explored new plant trait and provides novel insights into the carbon cycle. Measurements of O₂ fluxes at field sites are, however, scarce due to a number of technical challenges. This work presents unique field measurements of O₂ and CO₂ mole fractions and exchange fluxes of tree branches using a custom-made fully automated chamber system for quasi-continuous, high-precision measurements between Fagus sylvatica leaves and the atmosphere. Data from the vegetation period of 2021 in a temperate beech forest in Germany are shown.

Four steady-state, open-throughflow branch chambers were part of a larger chamber measurement set-up that also included four stem and eight soil chambers that were connected via a custom-built valve switching system to a modified FC-2 Differential Oxygen Analyzer (Oxzilla, Sable Systems International), and an LI-820 analyzer (LI-COR Biogeosciences GmbH). Precision was 1.3 ppm for O₂ and 0.3 ppm for CO₂. Both analyzers were located in an air-conditioned hut. O₂ and CO₂ mole fractions were measured continuously and logged in 10-sec intervals. Chambers were measured sequentially with typical observation times of 20-45 min per chamber, i.e. long enough for the mole fractions to reach steady state and allowing for at least two full measurement cycles of all sixteen chambers per day. For data processing, a quality check routine was developed for the branch chamber measurements, where spikes and non-steady-state conditions were excluded, and finally leaf exchange fluxes were quantified.

Diel, diurnal, and day-to-day variabilities were related to environmental and meteorological conditions. Further, the O₂:CO₂ exchange ratio on leaf-level was investigated for day- and nighttime. We could observe that the O₂:CO₂ exchange ratio varied stronger during nighttime than daytime and was affected mostly by the flux magnitude, the photosynthetically active radiation, and vapor pressure deficit. The exchange ratio was usually between 0.9 and 1.0 μmol μmol^-1.

Finally, we evaluated simulated photosynthetical O₂ and CO₂ fluxes of an extended version of the one-dimensional, multi-layer atmosphere-biosphere gas exchange model CANVEG based on the obtained measurements.

How to cite: Knohl, A., Klosterhalfen, A., Muhr, J., Blei, E., Bonazza, M., Fellert, D., Manning, A., Markwitz, C., Pickers, P. A., Tiedemann, F., Tunsch, E., and Yan, Y.: Simultaneous O2 and CO2 Flux Measurements with Custom-made Branch Chambers for Fagus sylvatica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15628, https://doi.org/10.5194/egusphere-egu23-15628, 2023.

The study of plant trait variability is critical for understanding ecosystem dynamics and predicting the response of vegetation to varying climatic conditions. Understanding the factors controlling the spatial and temporal variability in vegetation traits is key for addressing the ecosystem responses and feedbacks to changes in climate. In this study, we used the adaptive dynamic global vegetation model version 2 (aDGVM2) to simulate the temporal evolution and spatial distribution of plant traits across a wide range in edapho-climatic conditions. For such, we select locations of existing different ecosystem types and where in situ meteorological and eddy covariance flux measurements are taken.

We forced the aDGVM2 with FAO soil and flux site climate data, extended until 2020 and gap-filled with ERA5 data. To ensure that the simulated vegetation had sufficient time to adapt to prevailing local environmental conditions we conducted simulations for 500 years, split into a 400-year spin-up phase and a 100-year transient phase. For the spin-up phase, we randomly sampled years of the first 30 years of daily climate. Stochasticity in the selection-driven assembly of plant communities within the model can lead to multiple potential state; therefore, 10 replicate runs were conducted for each site with same model configuration.

We examine the differences in the 25 simulated trait values across sites, replicates and time via an analysis of variance (ANOVA). The analysis shows significant differences in trait values between sites, with some traits showing higher variability than others. In particular, we find that traits related to plant structural support (height, stem counts) were highly variable across sites, while traits related to resource acquisition (e.g., specific leaf area, leaf nitrogen content) are more stable. These results provide important insights into the factors that influence trait variability in space, and will be valuable for predicting the response of terrestrial ecosystems to environmental change. Further understanding the factors driving trait variability is of essential value in the design of mitigation and adaptation strategies and guide conservation efforts in the face of a rapidly changing world.

How to cite: Kumar, D., Scheiter, S., Langan, L., Koirala, S., Pfeiffer, M., Martens, C., Weber, U., and Carvalhais, N.: Investigating the spatial and temporal variation of plants traits across flux sites using a trait-based dynamic vegetation model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6385, https://doi.org/10.5194/egusphere-egu23-6385, 2023.

Plant biodiversity can be structured into different growth forms (i.e. woody vs. herbaceous) with divergent distributions, evolutionary histories, and relationships with climate thus they should be separately analyzed to better understand plant diversity. Flowering plants (angiosperms) are the most successful group of plants and have a diversity of growth forms that differs from other groups such as gymnosperms, all of which are woody species. However, there is still a gap in current growth form databases to cover most angiosperms. To fill the gap, this study collect data on growth forms of angiosperm species from published floras, online databases, and peer-reviewed journal articles and compiled a massive database of growth forms (woody and herbaceous, 300,750 species). Combined with distributions of 332,293 species, we mapped the current global geographical patterns in woody and herbaceous species as well as their relative proportion and assess their relationship with climate. This study also reconstructed ancestral states of growth forms through the angiosperm phylogeny to demonstrate the Cenozoic evolutionary dynamics of growth forms and explore the evolutionary transitions between the two growth forms.

How to cite: Luo, A., Xu, X., Liu, Y., Li, Y., Su, X., Li, Y., Lyu, T., Dimitrov, D., Larjavaara, M., Peng, S., Chen, Y., Wang, Q., Zimmermann, N., Pellissier, L., Schmid, B., and Wang, Z.: Global biodiversity patterns of woody and herbaceous flowering plants in space and time, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15379, https://doi.org/10.5194/egusphere-egu23-15379, 2023.

Ecosystem functioning is thought to be mediated by traits of organisms living within phylogenetic constraints. Plant groups of similar traits (functional groups) are likely to fit into a similar environmental niche. Characterizing functional groups’ niche space along environmental gradients would allow us to better understand patterns of trait variation.

We aim at defining the global environmental niche, i.e. the trait space filled at a given environment, of different functional groups of plants. 

In particular, we compare the environmental functional diversity (FD) gradients of four functional plant groups. These functional groups represent major differences in size and plant economy, derived from global in situ trait data of the TRY database. We find their gradients to vary in shape and strength. For example, tall-and-slow species’ FD varies more than small-and-slow ones, with a high FD in the Mediterranean. 

This study's findings point to how global change may affect functional groups differently and may ultimately provide valuable insights into ecosystem functioning.

How to cite: Joswig, J. and Schuman, M. C.: Environmental niche characterization of plant functional groups, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13427, https://doi.org/10.5194/egusphere-egu23-13427, 2023.

Boreal ecosystems, in particular peatlands, are one of the most essential terrestrial carbon pools. Aboveground biomass (AGB) and leaf area index (LAI) are key plant traits widely used to characterise their ecosystem processes. However, it has remained poorly understood how these variables develop over seasons among different vegetation types (VTs) and plant functional types (PFTs), and how well their seasonal spatiotemporal patterns can be detected by satellite images.

To address these gaps, we carried out field measurements between May and September during one growing season to investigate the seasonal development of ground vegetation AGB and LAI in seven VTs and PFTs within three peatland and forest study areas in northern Finland. We linked field-based AGB and LAI estimations to Sentinel-2 (S2) multi-temporal images via Random Forest (RF) regressions, yielding seasonal AGB and LAI maps.

Although AGB and LAI followed a clear unimodal curve in most VTs, their seasonal trajectories were more stable in forests and fen lawns than in fen strings and flarks. AGB peaked around the first week of August in about 900 DD5 (the sum of degree days above 5 °C), and, in most cases, one to two week(s) later than LAI. Besides evergreen shrubs, other three vascular PFTs presented clear unimodal seasonal patterns in AGB and LAI, while the AGB of mosses remained steady over the season. When upscaling to the landscape-level, the R² of regressions was 24.2-50.2% (RMSE: 78.8-198.7 g*m^-2) for AGB and 48.5-56.1% (RMSE: 0.207-0.497 m²*m^-2) for LAI. The S2-estimated AGB and LAI had unimodal seasonal patterns, though peaking dates were one to three week(s) earlier than in the corresponding field-based estimates.

Our findings suggest that S2 data which has relatively high spatial and temporal resolution has potential to monitor ground vegetation seasonality in boreal landscapes, especially in areas with sparse or no tree cover.

How to cite: Pang, Y., Räsänen, A., Juselius, T., Aurela, M., Juutinen, S., Väliranta, M., and Virtanen, T.: Field and satellite-estimated seasonal ground vegetation patterns in boreal ecosystems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1469, https://doi.org/10.5194/egusphere-egu23-1469, 2023.

Arctic environments undergo important climatic changes that affect, among others, hydrology, soil processes, and plant communities of these systems. At large scale, tree-line and shrub cover have been reported to expand northward, although permafrost melting, increased snow cover and raised soil water content can promote herbaceous covers at the local scale. Our study evaluated carbon (C) and nitrogen (N) stocks in diverse environments at Abisko, northern Sweden: a mire site with palsa, bog, and fen and a shrub tundra site with a bog to broad-leaved forest gradient. Based on plant community survey and vegetation and soil C and N analysis, results showed that proportions of ligneous and herbaceous covers do not reflect the total biomass C and N stocks, with 140.1 ± 56.9 and 3.7 ± 1.5 g per square meter of ground-level vegetation on average, respectively. However, differences in the distribution of short-lived (e.g. leaves) and long-lived (e.g. woody) biomasses were found, with an increase of 1% to up to 40% of woody biomass in dryer sites. Those results were even more important in the broad-leaved forest where C and N stocks in wood, leaves and deadwood of birch trees were over thrice the stock of ground-level vegetation and represented 515.0 ± 115.9 and 17.0 ± 3.8 g.m-2, respectively. Regarding soils, C and N stocks varied mainly at large scale between the mire (47.1 ± 9.1 kgC.m-2 and 2.6 ± 0.4 kgN.m-2 for palsa; 20.2 ± 6.9 kgC.m-2 and 0.9 ± 0.4 kgN.m-2 for bog subsites) and other dryer environments (5.8 ± 1.4 kgC.m-2 and 0.21 ± 0.02 kgN.m-2 for shrub tundra and forest) with differences mostly driven by soil density, soil depth, and water content and not by the composition of the plant community. Our results suggest that plant community shrubification at a large scale is likely to increase the overall C and N stocks in these ecosystems, with more important stocks in long-lived biomass such as wood. While plant community composition and proportion of ligneous/herbaceous species seemed to be a good indicator of biomass distribution, soil stocks appeared not to be well predicted by our results. Those results could be used as a base to compute C and N stocks using remote-sensing data, to obtain information at larger scales for which extensive field measurements are harder to conduct.

How to cite: Potier, H. M. G., Raynaud, X., Agnan, Y., Allain, A., Rouelle, M., and Alexis, M. A.: Plant community changes in the arctic: effects on Carbon and Nitrogen stocks distribution in the environment., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13087, https://doi.org/10.5194/egusphere-egu23-13087, 2023.

In early stages of forest succession plants have a high nutrient demand, but it is still a matter of debate if regrowth success of pioneer species is related to plant functional traits favoring fast soil colonization and nutrient acquisition. In general, we would expect trade-offs between plant growth performance and fine root morphological properties in association with different plant life-history strategies. Hence, we hypothesized that fast growing plants should have a more efficient root system that allows them to outcompete slow-growing neighbors in a resource-limited environment.

To test our hypothesis we monitored plant successional growth dynamics in a tropical lowland rainforest reforestation experiment conducted in southwest Costa Rica. We collected absorptive roots (<2mm diameter) from plant individuals (comprising 20 tree species and 11 plant families) with different growth dynamics (as indicated by measurements of stem diameter and height). For these samples we assessed a suite of fine root morphological traits, such as legume nodulation status, and furthermore quantified fine root nutrient concentration and phosphatase activities, as well as microbial biomass and phosphatase activity in soils in the close vicinity of fine roots.

We found stark differences in fine root characteristics between the tree species investigated in this study, such that fast growing species exhibited relatively larger specific root length and higher turnover, whereas slow growing species tend to rely on mechanical resistance by increasing root tissue density and root life span. Our results suggest that the identified differences in the root trait spectrum between fast and slow growing species reflect plant functional adaptions to resource limitation, edaphic properties and soil microbial symbioses. Our findings further highlight the crucial need to foster our understanding of belowground root morphological and physiological traits during forest succession, especially so when aiming to restore forest ecosystem functioning in formerly intensified land-use systems.

How to cite: Hofhansl, F., Valverde Barrantes, O., Chacón-Madrigal, E., Hietz, P., Weissenhofer, A., Prommer, J., Wanek, W., and Fuchslueger, L.: Do fine root morphological and functional adaptations support regrowth success in a tropical forest restoration experiment?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13211, https://doi.org/10.5194/egusphere-egu23-13211, 2023.

To conserve limiting nitrogen (N) in alpine ecosystems, herbaceous plants resorb and reallocate N from senescing tissues. However, the extent of N resorption and reallocation in aboveground tissues, coarse roots, fine roots and their relative contributions to whole-plant N conservation and ecosystem N retention remain poorly understood. Utilizing N stable isotope (¹⁵N) as a tracer, we quantified N partitions and N retranslocation efficiencies (NRE, % of N changes for each N pool) during senescence among different plant organs in a Tibetan alpine system. We found that compared to the N pools at the peak biomass stage, substantial ¹⁵N infine roots (FR, 39.93%) and aboveground tissues (shoot, 50.94%) was retranslocated primarily to coarse roots (CR, an increase of 79.02% in ¹⁵N) and non-extractable soil organic matter (an increase of 37.39% in ¹⁵N), corresponding to a temporal shift of plant trait syndrome from poor conservation to strong conservation during senescence. ¹⁵N in particulate organic matter and mineral-associated organic matter fractions during the senescence stage increased by 29.80% and 24.30%, respectively, but microbial biomass ¹⁵N significantly decreased. Our results illustrate the key role of N retranslocation to coarse roots and organic matter in N retention and the dual role of plant roots and organic matter as N sink and source in the plant-microbe-soil system. These findings suggest that plant N retranslocation and seasonal trait alternation facilitate the spatial and temporal coupling between plant N demand and bioavailable N supply in N-limiting alpine systems.

How to cite: Zhao, Q., Smith, G., Wang, P., Hu, L., Ma, M., Averill, C., Crowther, T., and Hu, S.: Nitrogen reallocation during alpine plant senescence contributed to plant nutrient conservation and ecosystem nitrogen retention, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8897, https://doi.org/10.5194/egusphere-egu23-8897, 2023.

The high invasion success of Fallopia japonica in Europe and North America is related to its niche construction strategy. A hotly debated and prominent possibility is that F. japonica uses weapons for chemical niche construction, which could have considerable consequences for plant nutrition and ecosystem functioning. At least one of its phenolic compounds is capable of inhibiting nitrification and nitrification is actually lower in F. japonica invaded systems. It was assumed that F. japonica has a higher affinity for ammonium and can therefore outcompete native plants that prefer nitrate. However, the uptake of ammonium by F. japonica has only been minimally studied and it has been shown that nitrogen-use efficiency seems to be the main trait. In a lab study using stable isotope labelling we tested nitrogen and carbon uptake of F. japonica against the strongest native competitor in European riparian zones U. dioica. We hypothesized that F. japonica has a greater potential to take up ammonium and that U. dioica would take advantage of the nitrate supply, and that F. japonica would have a slightly better nitrogen-use efficiency than U. .

We performed combined ¹³C-CO2 and ¹⁵N-NO3 and -NH4 labelling on young F. japonica and U. dioica plants. They were pulse labelled with ¹³CO₂ and fertilized with ¹⁵N enriched nitrate or ammonium (44 mg N kg -¹ dry soil). Atom excess of ¹⁵N and ¹³C, was measured after seven days in non-rooted soil, rhizosphere, fine roots, transport roots, and shoots. Contrary to our expectations, F. japonica always utilized less soil mineral N independent of the type of nitrogen.Overall, our data revealed that the ability of F. japonica to inhibit nitrification is not based on an affinity for ammonium. Therefore, it appears that F. japonica constructs its biogeochemical niche in a way to benefit from nitrogen-use efficiency, which we found to be higher, by supressing nitrification in nutrient rich habitats.

How to cite: Grange, S., Girardi, J., Mendoza Lera, C., Dyckmans, J., Brunn, M., and Jungkunst, H.: The Nitrogen Games – the invasive success of Fallopia japonica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16466, https://doi.org/10.5194/egusphere-egu23-16466, 2023.

The enormous diversity of variables that come together in the functioning of ecosystems makes it very difficult to establish reliable patterns of functionality, understood as the ability of ecosystems to progress in a balanced way with their own resources. The natural colonization of spaces degraded by mining offers us the opportunity to study the construction of an ecosystem from its beginnings. The scarcity of resources and the geochemical conditions that occur in these spaces carry out a screening of species and, consequently, the communities that establish in these soils are much simpler. In a mining area close to the city of Ciudad Real (Spain), large deposits of fine material, originating from mining processes, have remained untouched for more than 70 years and have become an exceptional place to study the rate of natural colonization and soil formation on a short scale of time and space. The transition between a bare regolithic substratum and a functional soil was monitored and analyzed to find out which are the key factors on which the functionality of the ecosystem is based. The special abilities of some pioneer plant species, the collaboration between them and the climatic factors of the study area, establish a unique path towards the achievement of a viable and functional ecosystem. In our work we have studied the natural colonization process that has occurred in a mining tailings dump (6 ha), analyzing the essential role of the reed (Phragmites australis) as a colonizing plant. Indeed, this species creates a dense network of rhizomes that favors the retention of edaphic resources such as organic matter, water and clay that will help other species to settle. In this way, a process of creating a new ecosystem begins, whose evolution will be conditioned only by the restrictions imposed by climatic patterns of rainfall and extreme temperatures. Plant species specific distribution, the standing biomass the microbial composition and enzymatic activity of the soil have been monitored, as well as the standardized soil parameters such as pH, texture, organic matter characterization, etc.

How to cite: Campos, J. A., Villena, J., Moreno, M. M., and Peco, J. D.: Towards ecosystem functionality: the case of sulphide mining tailings colonization., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14748, https://doi.org/10.5194/egusphere-egu23-14748, 2023.

Extreme climate events, generally defined as inordinately hotter, drier, or wetter compared to the historical period, are showing an increasing trend in terms of their frequency, intensity, and magnitude. They can impair the recovery system of plants, and thus, there is a need to understand their effects on plants. Here, we constructed a temperature and precipitation manipulation system to simulate extreme climate events for plants in the open field in April, 2020. We applied a factorial combination of three temperature levels (control, +3 °C, and +6 °C) and three precipitation levels (control, drought, and heavy rainfall) with six replicates (i.e., 54 plots of 1.5 m × 1.0 m) from April to June, 2020. Infrared heaters were adopted for simulating extreme heat since they are able to provide a realistic heating mechanism. The targeted temperature was automatically maintained by the data loggers and relays. For the extreme drought simulation, automatic rainout shelters intercepted ambient rainfall, closing only when detecting rainfall to avoid a disturbance of light absorption and passive warming. The rainfall simulator sprayed water from a height of 1.6 m above the ground using spraying nozzles and, the spraying time and pressure were set by the hooked-up pump and control panel to generate realistic rainfall. An infrared thermometer and a soil moisture and temperature sensor per plot measured the soil surface temperature and soil water content, respectively. As a result, the infrared heaters increased the mean soil surface temperature (°C ± standard error) by 2.7 ± 0.2 and 5.7 ± 0.5 in the +3 °C and +6 °C plots, respectively, compared to that in the control. The rainout shelter and rainfall simulator successfully produced extreme drought and heavy rainfall conditions, showing higher mean soil water contents (vol. %) of 4.44 ± 0.01 in the drought plots and 8.45 ± 0.03 in the heavy rainfall plots than that in the control (7.19 ± 0.03). Our multifactor manipulation system can provide a mechanistic understanding of the combined extreme stresses on soils and plants (e.g., soil microbial activity, seed germination, and growth of seedlings) through the comparison between the impact of single and multiple factors. Furthermore, the system has the advantage of applying diverse intensities of extreme climate events without restrictions on regions and scenarios by altering the settings of data loggers or the control panel. The system in this study can aid in investigating and modeling the mechanisms between extreme climate events, and soils and plants.

Acknowledgment: This study was carried out with the support of the National Research Foundation, Republic of Korea (Project No. 2022R1A2C1011309) and Korea Forest Service (Project No. 2020181A00-2222-BB01).

How to cite: Kim, G.-J., Jo, H., Cho, M. S., Noh, N. J., Han, S. H., and Son, Y.: An open-field multifactor experiment to simulate extreme climate events for observation of soils and plants, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2530, https://doi.org/10.5194/egusphere-egu23-2530, 2023.

Today’s forest carbon stocks are threatened by climate change through many types of disturbances, including drought. State-of-the-art Dynamic Global Vegetation Models (DGVMs) have hitherto not been able to explicitly simulate the response of tree hydraulic systems to drought, which are ultimately important determinants of tree resilience during drought events. Increasingly, more detailed representations of plant hydraulics, including death by cavitation, are being included in DGVMs, but simulations at the global level have been challenging, partially due to the lack of data for parameterisation. To overcome these issues, we compiled a large dataset of hydraulics-relevant plant traits from the literature (including TRY). To overcome the sparseness of the available trait data, we used literature on the functional relationships between traits to create a hypothesis framework that functionally links multiple traits and their trade-offs together in a network. From this network of traits we can sample parameter sets that reflect coherent plant strategies. We applied these strategies in the plant-hydraulics-enabled DGVM LPJ-GUESS and show how they can be used to provide model-based hypotheses of how both strategies and individual trait values vary across different forest environments. These results provide a basis for global-scale hydraulic model parameterisation, as well as providing verifiable hypotheses for testing in the field. 

How to cite: Pugh, T. A. M., Eckes-Shephard, A., Liu, D., Esquivel-Muelbert, A., Matthews, T., Papastefanou, P., Rammig, A., and Sadler, J.: Simulating the success of plant hydraulic strategies within a global vegetation model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9142, https://doi.org/10.5194/egusphere-egu23-9142, 2023.