When do plant hydraulics matter in terrestrial biosphere modelling?

The ascent of water from the soil to the leaves of vascular plants, described by the study of plant hydraulics, regulates ecosystem responses to environmental forcing and recovery from stress periods. Several approaches to model plant hydraulics have been proposed. In this study, we introduce four different versions of plant hydraulics representations in the terrestrial biosphere model T&C to understand the significance of plant hydraulics to ecosystem functioning. We tested representations of plant hydraulics, investigating plant water capacitance, and long-term xylem damages following drought. The four models we tested were a combination of representations including or neglecting capacitance and including or neglecting xylem damage legacies. Using the models at six case studies spanning semiarid to tropical ecosystems, we quantify how plant xylem flow, plant water storage and long-term xylem damage can modulate overall water and carbon dynamics across multiple time scales. We show that as drought develops, models with plant hydraulics predict a slower onset of plant water stress, and a diurnal variability of water and carbon fluxes closer to observations. Plant water storage was found to be particularly important for the diurnal dynamics of water and carbon fluxes, with models that include plant water capacitance yielding better results. Models including permanent damage to conducting plant tissues show an additional significant drought legacy effect, limiting plant productivity during the recovery phase following major droughts. However, when considering ecosystem responses to the observed climate variability, plant hydraulic modules alone cannot significantly improve the overall model performance, even though they reproduce more realistic water and carbon dynamics. This opens new avenues for model development, explicitly linking plant hydraulics with additional ecosystem processes, such as plant phenology and improved carbon allocation algorithms.

Aerodynamic effects cause higher forest evapotranspiration and water yield reductions after wildfires in tall forests.

Wildfires are increasing in frequency, intensity, and extent globally due to climate change and they can alter forest composition, structure, and function. The destruction and subsequent regrowth of young vegetation can modify the ecosystem evapotranspiration and downstream water availability. However, the response of forest recovery on hydrology is not well known with even the sign of evapotranspiration and water yield changes following forest fires being uncertain across the globe. Here, we quantify the effects of forest regrowth after catastrophic wildfires on evapotranspiration and runoff in the world's tallest angiosperm forest (Eucalyptus regnans) in Australia. We combine eddy covariance measurements including pre- and post-fire periods, mechanistic ecohydrological modeling and then extend the analysis spatially to multiple fires in eucalypt-dominated forests in south-eastern Australia by utilizing remote sensing. We find a fast recovery of evapotranspiration which reaches and exceeds pre-fire values within 2 years after the bushfire, a result confirmed by eddy covariance data, remote sensing, and modeling. Such a fast evapotranspiration recovery is likely generalizable to tall eucalypt forests in south-eastern Australia as shown by remote sensing. Once climate variability is discounted, ecohydrological modeling shows evapotranspiration rates from the recovering forest which reach peak values of +20% evapotranspiration 3 years post-fire. As a result, modeled runoff decreases substantially. Contrary to previous research, we find that the increase in modeled evapotranspiration is largely caused by the aerodynamic effects of a much shorter forest height leading to higher surface temperature, higher humidity gradients and therefore increased transpiration. However, increases in evapotranspiration as well as decreases in runoff caused by the young forest are constrained by energy and water limitations. Our result of an increase in evapotranspiration due to aerodynamic warming in a shorter forest after wildfires could occur in many parts of the world experiencing forest disturbances.

Economic valuation of temperature-related mortality attributed to urban heat islands in European cities.

As the climate warms, increasing heat-related health risks are expected, and can be exacerbated by the urban heat island (UHI) effect. UHIs can also offer protection against cold weather, but a clear quantification of their impacts on human health across diverse cities and seasons is still being explored. Here we provide a 500 m resolution assessment of mortality risks associated with UHIs for 85 European cities in 2015-2017. Acute impacts are found during heat extremes, with a 45% median increase in mortality risk associated with UHI, compared to a 7% decrease during cold extremes. However, protracted cold seasons result in greater integrated protective effects. On average, UHI-induced heat-/cold-related mortality is associated with economic impacts of €192/€ - 314 per adult urban inhabitant per year in Europe, comparable to air pollution and transit costs. These findings urge strategies aimed at designing healthier cities to consider the seasonality of UHI impacts, and to account for social costs, their controlling factors, and intra-urban variability.

Satellite-based evidence highlights a considerable increase of urban tree cooling benefits from 2000 to 2015.

Tree planting is a prevalent strategy to mitigate urban heat. Tree cooling efficiency (TCE), defined as the temperature reduction for a 1% tree cover increase, plays an important role in urban climate as it regulates the capacity of trees to alter the surface energy and water budget. However, the spatial variation and more importantly, temporal heterogeneity of TCE in global cities are not fully explored. Here, we used Landsat-based tree cover and land surface temperature (LST) to compare TCEs at a reference air temperature and tree cover level across 806 global cities and to explore their potential drivers with a boosted regression tree (BRT) machine learning model. From the results, we found that TCE is spatially regulated by not only leaf area index (LAI) but climate variables and anthropogenic factors especially city albedo, without a specific variable dominating the others. However, such spatial difference is attenuated by the decrease of TCE with tree cover, most pronounced in midlatitude cities. During the period 2000-2015, more than 90% of analyzed cities showed an increasing trend in TCE, which is likely explained by a combined result of the increase in LAI, intensified solar radiation due to decreased aerosol content, increase in urban vapor pressure deficit (VPD) and decrease of city albedo. Concurrently, significant urban afforestation occurred across many cities showing a global city-scale mean tree cover increase of 5.3 ± 3.8% from 2000 to 2015. Over the growing season, such increases combined with an increasing TCE were estimated to on average yield a midday surface cooling of 1.5 ± 1.3°C in tree-covered urban areas. These results are offering new insights into the use of urban afforestation as an adaptation to global warming and urban planners may leverage them to provide more cooling benefits if trees are primarily planted for this purpose.

Modeling distributed metal pollution transport in a mine impacted catchment: Short and long-term effects.

A spatially distributed trace metal transport and transformation module was developed and implemented within the hydrological model TOPKAPI-ETH. The new module can be used to better understand, at high spatial and temporal resolution, the transport and reactions of trace metals as they move through a catchment from upland sources to downstream areas and water bodies. The newly developed module takes into consideration solid metal in multiple chemical phases with different reactivity and simulates their mutual transformation over time, which gives the possibility to analyze the fraction of different solid metal phases present in the river suspended sediment. The characteristics and potential of the model are demonstrated by simulating Zinc (Zn) and Cadmium (Cd) dynamics in a headwater catchment of the Xiang River in South China, which has been highly perturbed by mining activities. The developed module is shown to reasonably reproduce the observed dynamics of dissolved and total trace metals flux for 14 months at two monitoring stations. The distributed solute transport model was proved to be capable of explaining the reasons underlying the spatial variability of C-Q relationships that are driven by the combined effect of point and non-point pollution sources, as well as identifying the spatiotemporal hotspots of trace metal pollution. By means of synthetic numerical experiments, a limited impact of slow reactions on dissolved Cd transport from upland to river over short-temporal scales was demonstrated, while for longer scales, e.g. >5 years, this effect becomes more relevant, highlighting potential long-lasting sources of trace metal pollution and their impacts.

Gross primary productivity and water use efficiency are increasing in a high rainfall tropical savanna.

Despite their size and contribution to the global carbon cycle, we have limited understanding of tropical savannas and their current trajectory with climate change and anthropogenic pressures. Here we examined interannual variability and externally forced long-term changes in carbon and water exchange from a high rainfall savanna site in the seasonal tropics of north Australia. We used an 18-year flux data time series (2001-2019) to detect trends and drivers of fluxes of carbon and water. Significant positive trends in gross primary productivity (GPP, 15.4 g C m2  year-2 ), ecosystem respiration (Reco , 8.0 g C m2  year-2 ), net ecosystem productivity (NEE, 7.4 g C m2  year-2 ) and ecosystem water use efficiency (WUE, 0.0077 g C kg H2 O-1  year-1 ) were computed. There was a weaker, non-significant trend in latent energy exchange (LE, 0.34 W m-2  year-1 ). Rainfall from a nearby site increased statistically over a 45-year period during the observation period. To examine the dominant drivers of changes in GPP and WUE, we used a random forest approach and a terrestrial biosphere model to conduct an attribution experiment. Radiant energy was the dominant driver of wet season fluxes, whereas soil water content dominated dry season fluxes. The model attribution suggested that [CO2 ], precipitation and Tair accounting for 90% of the modelled trend in GPP and WUE. Positive trends in fluxes were largest in the dry season implying tree components were a larger contributor than the grassy understorey. Fluxes and environmental drivers were not significant during the wet season, the period when grasses are active. The site is potentially still recovering from a cyclone 45 years ago and regrowth from this event may also be contributing to the observed trends in sequestration, highlighting the need to understand fluxes and their drivers from sub-diurnal to decadal scales.

An ecohydrological journey of 4500 years reveals a stable but threatened precipitation-groundwater recharge relation around Jerusalem.

Groundwater is a key water resource in semiarid and seasonally dry regions around the world, which is replenished by intermittent precipitation events and mediated by vegetation, soil, and regolith properties. Here, a climate reconstruction of 4500 years for the Jerusalem region was used to determine the relation between climate, vegetation, and groundwater recharge. Despite changes in air temperature and vegetation characteristics, simulated recharge remained linearly related to precipitation over the entire analyzed period, with drier decades having lower rates of recharge for a given annual precipitation due to soil memory effects. We show that in recent decades, the lack of changes in the precipitation­groundwater recharge relation results from the compensating responses of vegetation to increasing CO2, i.e., increased leaf area and reduced stomatal conductance. This multicentury relation is expected to be modified by climate change, with changes up to −20% in recharge for unchanged precipitation, potentially jeopardizing water resource availability.

Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO2.

Atmospheric carbon dioxide concentration ([CO2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2 ] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2 ] (iCO2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Persistent decay of fresh xylem hydraulic conductivity varies with pressure gradient and marks plant responses to injury.

Defining plant hydraulic traits is central to the quantification of ecohydrological processes ranging from land-atmosphere interactions, to tree mortality and water-carbon budgets. A key plant trait is the xylem specific hydraulic conductivity (Kx ), that describes the plant's vascular system capacity to transport water. While xylem's vessels and tracheids are dead upon maturity, the xylem is neither inert nor deadwood, various components of the sapwood and surrounding tissue remaining alive and functional. Moreover, the established definition of Kx assumes linear relations between water flux and pressure gradient by tacitly considering the xylem as a "passive conduit". Here, we re-examine this notion of an inert xylem by systematically characterizing xylem flow in several woody plants using Kx measurements under constant and cyclic pressure gradients. Results show a temporal and pressure gradient dependence of Kx . Additionally, microscopic features in "living branches" are irreversibly modified upon drying of the xylem, thus differentiating the macroscopic definition of Kx for living and dead xylem. The findings highlight the picture of the xylem as a complex and delicate conductive system whose hydraulic behaviour transcends a passive gradient-based flow. The study sheds new light on xylem conceptualization, conductivity measurement protocols, in situ long-distance water transport and ecosystem modelling.

Seasonal hysteresis of surface urban heat islands.

Temporal dynamics of urban warming have been extensively studied at the diurnal scale, but the impact of background climate on the observed seasonality of surface urban heat islands (SUHIs) remains largely unexplored. On seasonal time scales, the intensity of urban-rural surface temperature differences ([Formula: see text]) exhibits distinctive hysteretic cycles whose shape and looping direction vary across climatic zones. These observations highlight possible delays underlying the dynamics of the coupled urban-biosphere system. However, a general argument explaining the observed hysteretic patterns remains elusive. A coarse-grained model of SUHI coupled with a stochastic soil water balance is developed to demonstrate that the time lags between radiation forcing, air temperature, and rainfall generate a rate-dependent hysteresis, explaining the observed seasonal variations of [Formula: see text] If solar radiation is in phase with water availability, summer conditions cause strong SUHI intensities due to high rural evaporative cooling. Conversely, cities in seasonally dry regions where evapotranspiration is out of phase with radiation show a summertime oasis effect controlled by background climate and vegetation properties. These seasonal patterns of warming and cooling have significant implications for heat mitigation strategies as urban green spaces can reduce [Formula: see text] during summertime, while potentially negative effects of albedo management during winter are mitigated by the seasonality of solar radiation.

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Soil structure is an important omission in Earth System Models.

Most soil hydraulic information used in Earth System Models (ESMs) is derived from pedo-transfer functions that use easy-to-measure soil attributes to estimate hydraulic parameters. This parameterization relies heavily on soil texture, but overlooks the critical role of soil structure originated by soil biophysical activity. Soil structure omission is pervasive also in sampling and measurement methods used to train pedotransfer functions. Here we show how systematic inclusion of salient soil structural features of biophysical origin affect local and global hydrologic and climatic responses. Locally, including soil structure in models significantly alters infiltration-runoff partitioning and recharge in wet and vegetated regions. Globally, the coarse spatial resolution of ESMs and their inability to simulate intense and short rainfall events mask effects of soil structure on surface fluxes and climate. Results suggest that although soil structure affects local hydrologic response, its implications on global-scale climate remains elusive in current ESMs.

Magnitude of urban heat islands largely explained by climate and population.

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime differences between urban and rural surface temperatures (ΔTs) worldwide and find a nonlinear increase in ΔTs with precipitation that is controlled by water or energy limitations on evapotranspiration and that modulates the scaling of ΔTs with city size. We introduce a coarse-grained model that links population, background climate, and UHI intensity, and show that urban-rural differences in evapotranspiration and convection efficiency are the main determinants of warming. The direct implication of these nonlinearities is that mitigation strategies aimed at increasing green cover and albedo are more efficient in dry regions, whereas the challenge of cooling tropical cities will require innovative solutions.

A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change.

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

Globally consistent influences of seasonal precipitation limit grassland biomass response to elevated CO2.

Rising atmospheric carbon dioxide concentration should stimulate biomass production directly via biochemical stimulation of carbon assimilation, and indirectly via water savings caused by increased plant water-use efficiency. Because of these water savings, the CO2 fertilization effect (CFE) should be stronger at drier sites, yet large differences among experiments in grassland biomass response to elevated CO2 appear to be unrelated to annual precipitation, preventing useful generalizations. Here, we show that, as predicted, the impact of elevated CO2 on biomass production in 19 globally distributed temperate grassland experiments reduces as mean precipitation in seasons other than spring increases, but that it rises unexpectedly as mean spring precipitation increases. Moreover, because sites with high spring precipitation also tend to have high precipitation at other times, these effects of spring and non-spring precipitation on the CO2 response offset each other, constraining the response of ecosystem productivity to rising CO2. This explains why previous analyses were unable to discern a reliable trend between site dryness and the CFE. Thus, the CFE in temperate grasslands worldwide will be constrained by their natural rainfall seasonality such that the stimulation of biomass by rising CO2 could be substantially less than anticipated.

Modelling carbon sources and sinks in terrestrial vegetation.

Contents Summary 652 I. Introduction 652 II. Discrepancy in predicting the effects of rising [CO2 ] on the terrestrial C sink 655 III. Carbon and nutrient storage in plants and its modelling 656 IV. Modelling the source and the sink: a plant perspective 657 V. Plant-scale water and Carbon flux models 660 VI. Challenges for the future 662 Acknowledgements 663 Authors contributions 663 References 663 SUMMARY: The increase in atmospheric CO2 in the future is one of the most certain projections in environmental sciences. Understanding whether vegetation carbon assimilation, growth, and changes in vegetation carbon stocks are affected by higher atmospheric CO2 and translating this understanding in mechanistic vegetation models is of utmost importance. This is highlighted by inconsistencies between global-scale studies that attribute terrestrial carbon sinks to CO2 stimulation of gross and net primary production on the one hand, and forest inventories, tree-scale studies, and plant physiological evidence showing a much less pronounced CO2 fertilization effect on the other hand. Here, we review how plant carbon sources and sinks are currently described in terrestrial biosphere models. We highlight an uneven representation of complexity between the modelling of photosynthesis and other processes, such as plant respiration, direct carbon sinks, and carbon allocation, largely driven by available observations. Despite a general lack of data on carbon sink dynamics to drive model improvements, ways forward toward a mechanistic representation of plant carbon sinks are discussed, leveraging on results obtained from plant-scale models and on observations geared toward model developments.

Partitioning direct and indirect effects reveals the response of water-limited ecosystems to elevated CO2.

Increasing concentrations of atmospheric carbon dioxide are expected to affect carbon assimilation and evapotranspiration (ET), ultimately driving changes in plant growth, hydrology, and the global carbon balance. Direct leaf biochemical effects have been widely investigated, whereas indirect effects, although documented, elude explicit quantification in experiments. Here, we used a mechanistic model to investigate the relative contributions of direct (through carbon assimilation) and indirect (via soil moisture savings due to stomatal closure, and changes in leaf area index) effects of elevated CO2 across a variety of ecosystems. We specifically determined which ecosystems and climatic conditions maximize the indirect effects of elevated CO2 The simulations suggest that the indirect effects of elevated CO2 on net primary productivity are large and variable, ranging from less than 10% to more than 100% of the size of direct effects. For ET, indirect effects were, on average, 65% of the size of direct effects. Indirect effects tended to be considerably larger in water-limited ecosystems. As a consequence, the total CO2 effect had a significant, inverse relationship with the wetness index and was directly related to vapor pressure deficit. These results have major implications for our understanding of the CO2 response of ecosystems and for global projections of CO2 fertilization, because, although direct effects are typically understood and easily reproducible in models, simulations of indirect effects are far more challenging and difficult to constrain. Our findings also provide an explanation for the discrepancies between experiments in the total CO2 effect on net primary productivity.

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes.

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the "most active hours/days" (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

Environmental stochasticity controls soil erosion variability.

Understanding soil erosion by water is essential for a range of research areas but the predictive skill of prognostic models has been repeatedly questioned because of scale limitations of empirical data and the high variability of soil loss across space and time scales. Improved understanding of the underlying processes and their interactions are needed to infer scaling properties of soil loss and better inform predictive methods. This study uses data from multiple environments to highlight temporal-scale dependency of soil loss: erosion variability decreases at larger scales but the reduction rate varies with environment. The reduction of variability of the geomorphic response is attributed to a 'compensation effect': temporal alternation of events that exhibit either source-limited or transport-limited regimes. The rate of reduction is related to environment stochasticity and a novel index is derived to reflect the level of variability of intra- and inter-event hydrometeorologic conditions. A higher stochasticity index implies a larger reduction of soil loss variability (enhanced predictability at the aggregated temporal scales) with respect to the mean hydrologic forcing, offering a promising indicator for estimating the degree of uncertainty of erosion assessments.

Modeling terrestrial carbon and water dynamics across climatic gradients: does plant trait diversity matter?

Plant trait diversity in many vegetation models is crudely represented using a discrete classification of a handful of 'plant types' (named plant functional types; PFTs). The parameterization of PFTs reflects mean properties of observed plant traits over broad categories ignoring most of the inter- and intraspecific plant trait variability. Taking advantage of a multivariate leaf-trait distribution (leaf economics spectrum), as well as documented plant drought strategies, we generate an ensemble of hypothetical species with coordinated attributes, rather than using few PFTs. The behavior of these proxy species is tested using a mechanistic ecohydrological model that translates plant traits into plant performance. Simulations are carried out for a range of climates representative of different elevations and wetness conditions in the European Alps. Using this framework we investigate the sensitivity of ecosystem response to plant trait diversity and compare it with the sensitivity to climate variability. Plant trait diversity leads to highly divergent vegetation carbon dynamics (fluxes and pools) and to a lesser extent water fluxes (transpiration). Abiotic variables, such as soil water content and evaporation, are only marginally affected. These results highlight the need for revising the representation of plant attributes in vegetation models. Probabilistic approaches, based on observed multivariate whole-plant trait distributions, provide a viable alternative.