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

Toward a metabolic theory of catchments: Scaling of water and carbon fluxes with size

Allometric scaling relations are widely used to link biological processes to body size in nature. Several studies have shown that such scaling laws hold also for natural ecosystems, including individual trees and forests, riverine metabolism, and river network organization. However, the derivation of scaling laws for catchment-scale water and carbon fluxes has not been achieved so far. Here, we focus on scaling relations of catchment green metabolism, defined as the set of ecohydrological and biogeochemical processes through which vegetation assemblages in catchments maintain their structure and react to the surrounding environment. By revising existing plant size-density relationships and integrating them across large-scale domains, we show that the ecohydrological fluxes occurring at the catchment scale are invariant with respect to the above-ground vegetation biomass per unit area of the basin, while they scale linearly with catchment size. We thus demonstrate that the sublinear scaling of plant metabolism results in an isometric scaling at catchment and regional scales. Deviations from such predictions are further shown to collapse onto a common distribution, thus incorporating natural fluctuations due to resource limitations into a generalized scaling theory. Results from scaling arguments are supported by hyperresolution ecohydrological simulations and remote sensing observations.

Temperature controls the relation between soil organic carbon and microbial carbon use efficiency

Microbial carbon use efficiency (CUE) is an important variable mediating microbial effects on soil organic carbon (SOC) since it summarizes how much carbon is used for microbial growth or is respired. Yet, the role of CUE in regulating SOC storage remains debated, with evidence for both positive and negative SOC-CUE relations. Here, we use a combination of measured data around the world and numerical simulations to explore SOC-CUE relations accounting for temperature (T) effects on CUE. Results reveal that the sign of the CUE-T relation controls the direction of the SOC-CUE relations. A negative CUE-T relation leads to a positive SOC-CUE relation and vice versa, highlighting that CUE-T patterns significantly affect how organic carbon is used by microbes and hence SOC-CUE relations. Numerical results also confirm the observed negative SOC-T relation, regardless of the CUE-T patterns, implying that temperature plays a more dominant role than CUE in controlling SOC storage. The SOC-CUE relation is usually negative when temperature effects are isolated, even though it can become positive when nonlinear microbial turnover is considered. These results indicate a dominant role of CUE-T patterns in controlling the SOC-CUE relation. Our findings help to better understand SOC and microbial responses to a warming climate.

Stochastic process drives the dissimilarity in biodiversity patterns between Pinus kwangtungensis coniferous forest and evergreen deciduous broad-leaved mixed forest in karst area

Pinus kwangtungensis is an endangered evergreen conifer tree species, and its in situ conservation has been considered one of the most critical issues. However, relative protection is limited by the lack of understanding of its community structure and underlying assembly processes. To study how the species diversity and assembly processes of Pinus kwangtungensis coniferous forest (CF) differed with regional climax community, this study established a series forest dynamic plots both in CF and evergreen deciduous broadleaved mixed forest (EDBM). By performing comparison analysis and PER-SIMPER approaches, we quantified the differences in species diversity and community assembly rules. The results showed that the species α-diversity of CF differed greatly from the EDBM both in species richness and evenness. In addition, the stochastic process acted a more important role in determining species composition, indicating the uncertainty in presence of species. The soil phosphorus and changeable calcium content were the main factors driving the differences in biodiversity, which the importance of soil nutrient factors in driving species composition. Our study highlighted that we should consider the community structure and ecological process when conducting conservation of Pinus kwangtungensis.

Tree species explain only half of explained spatial variability in plant water sensitivity

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Tree contributions to climate change adaptation through reduced cattle heat stress and benefits to milk and beef production

Cattle heat stress causes billions of dollars' worth of losses to meat and milk production globally, and is projected to become more severe in the future due to climate change. Tree establishment in pastoral livestock systems holds potential to reduce cattle heat stress and thus provide nature-based adaptation. We developed a general model for the impact of trees on cattle heat stress, which can project milk and meat production under future climate scenarios at varying spatial scales. The model incorporates the key microclimate mechanisms influenced by trees, including shade, air temperature, humidity, and wind speed. We conducted sensitivity analyses to demonstrate the relative influence of different mechanisms through which trees can impact cattle heat stress, and how tree impacts are influenced by climatic context globally. Trees hold the greatest potential to reduce cattle heat stress in higher latitudes and altitudes, with minor benefits in the lowland tropics. We projected the future contributions of current trees in mitigating climate change impacts on the dairy and beef herds of Aotearoa-New Zealand (A-NZ) in 2070-2080. Trees were simulated to contribute to A-NZ milk yields by over 491 million liters (lower CI = 112 million liters, upper CI = 850 million liters), and meat yields by over 8316 tonnes (lower CI = 2431 tonnes, upper CI = 13,668 tonnes) annually. The total economic contribution of existing trees in mitigating future cattle heat stress was valued at $US 244 million (lower CI = $US 58 million, upper CI = $US 419 million). Our findings demonstrate the importance of existing trees in pastoral landscapes and suggest that strategic tree establishment can be a valuable adaptation option for reducing cattle heat stress under climate change. Tree establishment in the next few years is critical to provide adaptation capacity and economic benefit in future decades.

Integrating field- and remote sensing data to perceive species heterogeneity across a climate gradient

Tropical forests exhibit significant diversity and heterogeneity in species distribution. Some tree species spread abundantly, impacting the functional aspects of communities. Understanding how these facets respond to climate change is crucial. Field data from four protected areas (PAs) were combined with high-resolution Airborne Visible/InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) datasets to extract large-scale plot data of abundant species and their functional traits. A supervised component generalized linear regression (SCGLR) model was used to correlate climate components with the distribution of abundant species across PAs. The recorded rainfall gradient influenced the proportion of PA-specific species in the observed species assemblages. Community weighted means (CWMs) of biochemical traits showed better correlation values (0.85-0.87) between observed and predicted values compared to biophysical traits (0.52-0.79). The model-based projection revealed distinct distribution responses of each abundant species to the climate gradient. Functional diversity and functional traits maps highlighted the interplay between species heterogeneity and climate. The appearance dynamics of abundant species in dark diversity across PAs demonstrated their assortment strategy in response to the climate gradient. These observations can significantly aid in the ecological management of PAs exposed to climate dynamics.

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.

Functional phenotypic plasticity mediated by water stress and [CO2] explains differences in drought tolerance of two phylogenetically close conifers

Forests are threatened globally by increased recurrence and intensity of hot droughts. Functionally close coexisting species may exhibit differences in drought vulnerability large enough to cause niche differentiation and affect forest dynamics. The effect of rising atmospheric [CO2], which could partly alleviate the negative effects of drought, may also differ between species. We analysed functional plasticity in seedlings of two taxonomically close pine species (Pinus pinaster Ait., Pinus pinea L.) under different [CO2] and water stress levels. The multidimensional functional trait variability was more influenced by water stress (preferentially xylem traits) and [CO2] (mostly leaf traits) than by differences between species. However, we observed differences between species in the strategies followed to coordinate their hydraulic and structural traits under stress. Leaf 13C discrimination decreased with water stress and increased under elevated [CO2]. Under water stress both species increased their sapwood area to leaf area ratios, tracheid density and xylem cavitation, whereas they reduced tracheid lumen area and xylem conductivity. Pinus pinea was more anisohydric than P. pinaster. Pinus pinaster produced larger conduits under well-watered conditions than P. pinea. Pinus pinea was more tolerant to water stress and more resistant to xylem cavitation under low water potentials. The higher xylem plasticity in P. pinea, particularly in tracheid lumen area, expressed a higher capacity of acclimation to water stress than P. pinaster. In contrast, P. pinaster coped with water stress comparatively more by increasing plasticity of leaf hydraulic traits. Despite the small differences observed in the functional response to water stress and drought tolerance between species, these interspecific differences agreed with ongoing substitution of P. pinaster by P. pinea in forests where both species co-occur. Increased [CO2] had little effect on the species-specific relative performance. Thus, a competitive advantage under moderate water stress of P. pinea compared with P. pinaster is expected to continue in the future.

Characterization of 35 Masson pine (Pinus massoniana) half-sib families from two provinces based on metabolite properties

Plant metabolism is an important functional trait, and its metabolites have physiological and ecological functions to adapt to the growth environment. However, the physiological and ecological functions of metabolites from different provinces of the same plant species are still unclear. Therefore, this study aimed to determine whether metabolites from different provinces of Masson pine (Pinus massoniana Lamb.) have the corresponding metabolic traits. The gas chromatography–mass spectrometry technique and metabonomic analysis methods were used to characterize 35 Masson pine half-sib families from two provinces. A total of 116 metabolites were putatively identified in 35 families of Masson pine, among which the average content of organic acids was the highest, followed by saccharides and alcohols, and phosphoric acids. Comparative analysis of metabolite groups showed that organic acids, amines, and others were significantly different between the Masson pine families from Guangxi and Guizhou provinces. Six differential metabolites were found between the provinces from Guizhou and Guangxi, namely caffeic acid, L-ascorbic acid, gentiobiose, xylitol, d-pinitol, and β-sitosterol. The most significantly enriched pathways among differentially expressed metabolites between the two provinces were steroid biosynthesis, phenylpropanoid biosynthesis, glutathione metabolism, pentose and glucuronate interconversions. Overall, the results showed that Masson pine half-sib families from different geographical provinces have different metabolite profiles and their metabolites are affected by geographical provenance and growth environment adaptability. This study revealed that the breeding of Masson pine families from different provinces changed the metabolite profiles, providing a reference for the multipurpose breeding of Masson pine.

Browsing herbivores improve the state and functioning of savannas: A model assessment of alternative land-use strategies

Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.

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 precipitation–groundwater 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.

Predictability of leaf traits with climate and elevation: a case study in Gongga Mountain, China

Leaf mass per area (Ma), nitrogen content per unit leaf area (Narea), maximum carboxylation capacity (Vcmax) and the ratio of leaf-internal to ambient CO2 partial pressure (χ) are important traits related to photosynthetic function, and they show systematic variation along climatic and elevational gradients. Separating the effects of air pressure and climate along elevational gradients is challenging due to the covariation of elevation, pressure and climate. However, recently developed models based on optimality theory offer an independent way to predict leaf traits and thus to separate the contributions of different controls. We apply optimality theory to predict variation in leaf traits across 18 sites in the Gongga Mountain region. We show that the models explain 59% of trait variability on average, without site- or region-specific calibration. Temperature, photosynthetically active radiation, vapor pressure deficit, soil moisture and growing season length are all necessary to explain the observed patterns. The direct effect of air pressure is shown to have a relatively minor impact. These findings contribute to a growing body of research indicating that leaf-level traits vary with the physical environment in predictable ways, suggesting a promising direction for the improvement of terrestrial ecosystem models.

Parsimony vs predictive and functional performance of three stomatal optimization principles in a big-leaf framework

Stomatal optimization models can improve estimates of water and carbon fluxes with relatively low complexity, yet there is no consensus on which formulations are most appropriate for ecosystem-scale applications. We implemented three existing analytical equations for stomatal conductance, based on different water penalty functions, in a big-leaf comparison framework, and determined which optimization principles were most consistent with flux tower observations from different biomes. We used information theory to dissect controls of soil water supply and atmospheric demand on evapotranspiration in wet to dry conditions and to quantify missing or inadequate information in model variants. We ranked stomatal optimization principles based on parameter uncertainty, parsimony, predictive accuracy, and functional accuracy of the interactions between soil moisture, vapor pressure deficit, and evapotranspiration. Performance was high for all model variants. Water penalty functions with explicit representation of plant hydraulics did not substantially improve predictive or functional accuracy of ecosystem-scale evapotranspiration estimates, and parameterizations were more uncertain, despite having physiological underpinnings at the plant level. Stomatal optimization based on water use efficiency thus provided more information about ecosystem-scale evapotranspiration compared to those based on xylem vulnerability and proved more useful in improving ecosystem-scale models with less complexity.

Comparing Evapotranspiration Estimates from the GEOframe-Prospero Model with Penman–Monteith and Priestley-Taylor Approaches under Different Climate Conditions

Evapotranspiration (ET) is a key variable in the hydrological cycle and it directly impacts the surface balance and its accurate assessment is essential for a correct water management. ET is difficult to measure, since the existing methods for its direct estimate, such as the weighing lysimeter or the eddy-covariance system, are often expensive and require well-trained research personnel. To overcome this limit, different authors developed experimental models for indirect estimation of ET. However, since the accuracy of ET prediction is crucial from different points of view, the continuous search for more and more precise modeling approaches is encouraged. In light of this, the aim of the present work is to test the efficiency in predicting ET fluxes in a newly introduced physical-based model, named Prospero, which is based on the ability to compute the ET using a multi-layer canopy model, solving the energy balance both for the sunlight and shadow vegetation, extending the recently developed Schymanski and Or method to canopy level. Additionally, Prospero is able to compute the actual ET using a Jarvis-like model. The model is integrated as a component in the hydrological modelling system GEOframe. Its estimates were validated against observed data from five Eddy covariance (EC) sites with different climatic conditions and the same vegetation cover. Then, its performances were compared with those of two already consolidated models, the Priestley–Taylor model and Penman FAO model, using four goodness-of-fit indices. Subsequently a calibration of the three methods has been carried out using LUCA calibration within GEOframe, with the purpose of prediction errors. The results showed that Prospero is more accurate and precise with respect to the other two models, even if no calibrations were performed, with better performances in dry climatic conditions. In addition, Prospero model turned to be the least affected by the calibration procedure and, therefore, it can be effectively also used in a context of data scarcity.

Disentangling climatic and anthropogenic contributions to nonlinear dynamics of alpine grassland productivity on the Qinghai-Tibetan Plateau

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models

Process-based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass-dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C₃ grasses and (sub)tropical C₄ grasses. Incorporation of species-level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), situated between species-level trait data and PFT-level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

Remote sensing and modeling fusion for investigating the ecosystem water-carbon coupling processes

The water and carbon cycles are tightly linked and play a key role in the material and energy flows between terrestrial ecosystems and the atmosphere, but the interactions of water and carbon cycles are not quite clear. The global climate change and intensive human activities could also complicate the water and carbon coupling processes. Better understanding the coupled water-carbon cycles and their spatiotemporal evolution can inform management and decision-making efforts regarding carbon uptake, food production, water resources, and climate change. The integration of remote sensing and numeric modeling is an attractive approach to address the challenge. Remote sensing can provide extensive data for a number of variables at regional scale and support models, whereas process-based modeling can facilitate investigating the processes that remote sensing cannot well handle (e.g., below-ground and lateral material movement) and backcast/forecast the impacts of environmental change. Over the past twenty years, an increasing number of studies using a variety of remote sensing products together with numeric models have examined the water-carbon interactions. This article reviewed the methodologies for integrating remote sensing data into these models and the modeling of water-carbon coupling processes. We first summarized the major remote sensing datasets and models used for studying the coupled water-carbon cycles. We then provided an overview of the methods for integrating remote sensing data into water-carbon models, and discussed their strengths and challenges. We also prospected the development of potential new remote sensing datasets, modeling methods, and their potential applications in the field of eco-hydrology.

Contrasting stomatal sensitivity to temperature and soil drought in mature alpine conifers

Conifers growing at high elevations need to optimize their stomatal conductance (g_s ) for maximizing photosynthetic yield while minimizing water loss under less favourable thermal conditions. Yet the ability of high-elevation conifers to adjust their g_s sensitivity to environmental drivers remains largely unexplored. We used 4 years of sap flow measurements to elucidate intraspecific and interspecific variability of g_s in Larix decidua Mill. and Picea abies (L.) Karst along an elevational gradient and contrasting soil moisture conditions. Site- and species-specific g_s response to main environmental drivers were examined, including vapour pressure deficit, air temperature, solar irradiance, and soil water potential. Our results indicate that maximum g_s of L. decidua is >2 times higher, shows a more plastic response to temperature, and down-regulates g_s stronger during atmospheric drought compared to P. abies. These differences allow L. decidua to exert more efficient water use, adjust to site-specific thermal conditions, and reduce water loss during drought episodes. The stronger plasticity of g_s sensitivity to temperature and higher conductance of L. decidua compared to P. abies provide new insights into species-specific water use strategies, which affect species' performance and should be considered when predicting terrestrial water dynamics under future climatic change.

The functional decoupling of processes in alpine ecosystems under climate change

Climate change may promote the decoupling of the different above-ground and below-ground compartments of high elevation ecosystems. Along elevation gradients, a trade-off between species tolerance to cold climates and metabolic rates dictates that cold adapted organisms display a lower efficiency in decomposition, growth or herbivory. As a consequence, if dispersal or evolution under climate change is systematically faster for agents of one compartment (e.g. insect herbivores, or soil microbes, respectively) compared to others, novel and more efficient functions will arise in the alpine systems and increase fluxes of elements to and through this compartment. We illustrate this potential decoupling using a mechanistic model, where the efficiency of agents in the compartments follows the metabolic theory. To detect and forecast ecosystem decoupling under climate change, we argue that the current efficiency of agents should be measured systematically along elevation gradients. In addition, future research should investigate the impact of dispersal and evolution in response to climate change on ecosystem processes.

Plant Hydraulic Trait Covariation: A Global Meta-Analysis to Reduce Degrees of Freedom in Trait-Based Hydrologic Models

Current vegetation modeling strategies use broad categorizations of plants to estimate transpiration and biomass functions. A significant source of model error stems from vegetation categorizations that are mostly taxonomical with no basis in plant hydraulic strategy and response to changing environmental conditions. Here, we compile hydraulic traits from 355 species around the world to determine trait covariations in order to represent hydraulic strategies. Simple and stepwise regression analyses demonstrate the interconnectedness of multiple vegetative hydraulic traits, specifically, traits defining hydraulic conductivity and vulnerability to embolism with wood density and isohydricity. Drought sensitivity is strongly (Adjusted R2 = 0.52, p < 0.02) predicted by a stepwise linear model combining rooting depth, wood density, and isohydricity. Drought tolerance increased with increasing wood density and anisohydric response, but with decreasing rooting depth. The unexpected response to rooting depth may be due to other tradeoffs within the hydraulic system. Rooting depth was able to be predicted from sapwood specific conductivity and the water potential at 50% loss of conductivity. Interestingly, the influences of biome or growth form do not increase the accuracy of the drought tolerance model and were able to be omitted. Multiple regression analysis revealed 3D trait spaces and tradeoff axes along which species’ hydraulic strategies can be analyzed. These numerical trait spaces can reduce the necessary input to and parameterization of plant hydraulics modules, while increasing the physical representativeness of such simulations.

Boreal tree hydrodynamics: asynchronous, diverging, yet complementary

Water stress has been identified as a key mechanism of the contemporary increase in tree mortality rates in northwestern North America. However, a detailed analysis of boreal tree hydrodynamics and their interspecific differences is still lacking. Here we examine the hydraulic behaviour of co-occurring larch (Larix laricina) and black spruce (Picea mariana), two characteristic boreal tree species, near the southern limit of the boreal ecozone in central Canada. Sap flux density (Js), concurrently recorded stem radius fluctuations and meteorological conditions are used to quantify tree hydraulic functioning and to scrutinize tree water-use strategies. Our analysis revealed asynchrony in the diel hydrodynamics of the two species with the initial rise in Js occurring 2 h earlier in larch than in black spruce. Interspecific differences in larch and black spruce crown architecture explained the observed asynchrony in their hydraulic functioning. Furthermore, the two species exhibited diverging stomatal regulation strategies with larch and black spruce employing relatively isohydric and anisohydric behaviour, respectively. Such asynchronous and diverging tree-level hydrodynamics provide new insights into the ecosystem-level complementarity in tree form and function, with implications for understanding boreal forests' water and carbon dynamics and their resilience to environmental stress.

Drought affects abortion of reproductive organs by exacerbating developmentally driven processes via expansive growth and hydraulics

Abortion of reproductive organs is a major limiting factor of yield under water deficit, but is also a trait selected for by evolutionary processes. The youngest reproductive organs must be prone to abortion so older organs can finish their development in case of limited resources. Water deficit increases natural abortion via two developmentally driven processes, namely a signal from the first fertilized ovaries and a simultaneous arrest of the expansive growth of all ovaries at a precise stage. In maize (Zea mays) subjected to water deficits typically encountered in dryland agriculture, these developmental mechanisms account for 90% of drought-associated abortion and are irreversible 3 d after silk emergence. Consistently, transcripts and enzyme activities suggest that the molecular events associated with abortion affect expansive growth in silks whereas ovaries maintain a favourable carbon status. Abortion due to carbon starvation is only observed for severe drought scenarios occurring after silking. Both kinetic and genetic evidence indicates that vegetative and reproductive structures share a partly common hydraulic control of expansive growth. Hence, the control of expansive growth of reproductive structures probably has a prominent effect on abortion for mild water deficits occurring at flowering time, while carbon starvation dominates in severe post-flowering drought scenarios.

Modelling understorey dynamics in temperate forests under global change-Challenges and perspectives

The understorey harbours a substantial part of vascular plant diversity in temperate forests and plays an important functional role, affecting ecosystem processes such as nutrient cycling and overstorey regeneration. Global change, however, is putting these understorey communities on trajectories of change, potentially altering and reducing their functioning in the future. Developing mitigation strategies to safeguard the diversity and functioning of temperate forests in the future is challenging and requires improved predictive capacity. Process-based models that predict understorey community composition over time, based on first principles of ecology, have the potential to guide mitigation endeavours but such approaches are rare. Here, we review fourteen understorey modelling approaches that have been proposed during the last three decades. We evaluate their inclusion of mechanisms that are required to predict the impact of global change on understorey communities. We conclude that none of the currently existing models fully accounts for all processes that we deem important based on empirical and experimental evidence. Based on this review, we contend new models are needed to project the complex impacts of global change on forest understoreys. Plant functional traits should be central to such future model developments, as they drive community assembly processes and provide valuable information on the functioning of the understorey. Given the important role of the overstorey, a coupling of understorey models to overstorey models will be essential to predict the impact of global change on understorey composition and structure, and how it will affect the functioning of temperate forests in the future.

Shifts in Plant Community Assembly Processes across Growth Forms along a Habitat Severity Gradient: A Test of the Plant Functional Trait Approach

Species respond to changes in their environments. A core goal in ecology is to understand the process of plant community assembly in response to a changing climate. Examining the performance of functional traits and trait-based assembly patterns across species among different growth forms is a useful way to explore the assembly process. In this study, we constructed a habitat severity gradient including several environment factors along a 2300 m wide elevational range at Taibai Mountain, central China. Then we assessed the shift on functional trait values and community assembly patterns along this gradient across species among different growth forms. We found that (1) although habitat-severity values closely covaried with elevation in this study, an examined communities along a habitat severity gradient might reveal community dynamics and species responses under future climate change. (2) the occurrence of trait values along the habitat severity gradient across different growth forms were similar, whereas the assembly pattern of herbaceous species was inconsistent with the community and woody species. (3) the trait-trait relationships of herbaceous species were dissimilar to those of the community and woody species. These results suggest that (1) community would re-assemble along habitat severity gradient through environmental filtering, regardless of any growth forms and that (2) different growth forms' species exhibiting similar trait values' shift but different trait-trait relationship by different trait combinations.

Vegetation demographics in Earth System Models: A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Risky future for Mediterranean forests unless they undergo extreme carbon fertilization

Forest performance is challenged by climate change but higher atmospheric [CO₂ ] (c_a ) could help trees mitigate the negative effect of enhanced water stress. Forest projections using data assimilation with mechanistic models are a valuable tool to assess forest performance. Firstly, we used dendrochronological data from 12 Mediterranean tree species (six conifers and six broadleaves) to calibrate a process-based vegetation model at 77 sites. Secondly, we conducted simulations of gross primary production (GPP) and radial growth using an ensemble of climate projections for the period 2010-2100 for the high-emission RCP8.5 and low-emission RCP2.6 scenarios. GPP and growth projections were simulated using climatic data from the two RCPs combined with (i) expected c_a ; (ii) constant c_a  = 390 ppm, to test a purely climate-driven performance excluding compensation from carbon fertilization. The model accurately mimicked the growth trends since the 1950s when, despite increasing c_a , enhanced evaporative demands precluded a global net positive effect on growth. Modeled annual growth and GPP showed similar long-term trends. Under RCP2.6 (i.e., temperatures below +2 °C with respect to preindustrial values), the forests showed resistance to future climate (as expressed by non-negative trends in growth and GPP) except for some coniferous sites. Using exponentially growing c_a and climate as from RCP8.5, carbon fertilization overrode the negative effect of the highly constraining climatic conditions under that scenario. This effect was particularly evident above 500 ppm (which is already over +2 °C), which seems unrealistic and likely reflects model miss-performance at high c_a above the calibration range. Thus, forest projections under RCP8.5 preventing carbon fertilization displayed very negative forest performance at the regional scale. This suggests that most of western Mediterranean forests would successfully acclimate to the coldest climate change scenario but be vulnerable to a climate warmer than +2 °C unless the trees developed an exaggerated fertilization response to [CO₂ ].

Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade-offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual-based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen-use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade-offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones.

Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs) and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

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.

The growth of vegetative and reproductive structures (leaves and silks) respond similarly to hydraulic cues in maize

The elongation of styles and stigma (silks) of maize (Zea mays) flowers is rapid (1-3 mm h(-1) ), occurs over a short period and plays a pivotal role in reproductive success in adverse environments. Silk elongation rate was measured using displacement transducers in 350 plants of eight genotypes during eight experiments with varying evaporative demand and soil water status. Measured time courses revealed that silk elongation rate closely followed changes in soil water status and evaporative demand, with day-night alternations similar to those in leaves. Day-night alternations were steeper with high than with low plant transpiration rate, manipulated via evaporative demand or by covering part of the leaf area. Half times of changes in silk elongation rate upon changes in evaporative demand or soil water status were 10-30 min, similar to those in leaves. The sensitivity of silk elongation rate to xylem water potential was genetically linked to that of leaf elongation rate. Lines greatly differed for these sensitivities. These results are consistent with a common hydraulic control of expansive growth in vegetative and reproductive structures upon changes in environmental conditions via a close connection with the xylem water potential. They have important implications for breeding, modelling and phenotyping.

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.

The 'island effect' in terrestrial global change experiments: a problem with no solution?

Most of the currently experienced global environmental changes (rising atmospheric CO2 concentrations, warming, altered amount and pattern of precipitation, and increased nutrient load) directly or indirectly affect ecosystem surface energy balance and plant transpiration. As a consequence, the relative humidity of the air surrounding the vegetation changes, thus creating a feedback loop whose net effect on transpiration and finally productivity is not trivial to quantify. Forcedly, in any global change experiment with the above drivers, we can only treat small plots, or 'islands', of vegetation. This means that the treated plots will likely experience the ambient humidity conditions influenced by the surrounding, non-treated vegetation. Experimental assessments of global change effects will thus systematically lack modifications originating from these potentially important feedback mechanisms, introducing a bias of unknown magnitude in all measurements of processes directly or indirectly depending on plant transpiration. We call this potential bias the 'island effect'. Here, we discuss its implications in various global change experiments with plants. We also suggest ways to complement experiments using modelling approaches and observational studies. Ultimately, there is no obvious solution to deal with the island effect in field experiments and only models can provide an estimate of modification of responses by these feedbacks. However, we suggest that increasing the awareness of the island effect among both experimental researchers and modellers will greatly improve the interpretation of vegetation responses to global change.