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

Contrasting effects of intensified dry-season drought and extended dry-season length on soil greenhouse gas emissions in a subtropical forest

Over two-thirds of the Earth's land surface is subjected to seasonal precipitation changes along with climate warming, including the subtropical forests that represent one of the Earth's most important carbon sink and source. However, few experiments have been conducted to understand the response of soil greenhouse gas (GHGs) emissions from these forests to seasonal changes in precipitation. Herein, we conducted a field experiment in a subtropical forest of southern China including two precipitation seasonality treatments: an intensified dry-season (Oct-Mar) drought and wetter wet-season (Jun-Sep) treatment (ID) and an extended dry-season (Apr-May) length and wetter wet-season treatment (ED); for both ID and ED, the annual precipitation amount was kept the same as under ambient control (AC). Compared to AC, the decreased annual CO2 emissions for ID were mainly due to decreased WFPS in Oct-Mar of 2013-2014 and increased WFPS during Jun-Sep of 2013; the increased annual CH4 uptake for ID was predominantly attributed to decreased WFPS in Oct-Mar of 2013-2014; the decreased annual N2O emissions for ID were mainly due to decreased WFPS in Oct-Mar of 2013; the increased annual N2O emissions for ID in 2014 were mainly attributed to increased WFPS in Jun-Sep (p < 0.05). Relative to AC, the increased annual CO2 and N2O emissions from ED were predominantly attributed to decreased WFPS in Apr-May and increased WFPS in Jun-Sep during 2013-2014, respectively (p < 0.05). The average annual CO2-equivalent CH4 and N2O emissions increased under ED but decreased under ID compared to AC (p < 0.05). Although our two precipitation manipulation scenarios simulated seasonal drought impacts without changing annual precipitation amount, ED and ID had distinct impacts on soil GHGs emissions, which have important implications for modeling the subtropical forests GHG emissions and managing the forests to mitigate climate change.

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.

Increased photosynthesis during spring drought in energy-limited ecosystems

Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

The ecosystem wilting point defines drought response and recovery of a Quercus-Carya forest

Soil and atmospheric droughts increasingly threaten plant survival and productivity around the world. Yet, conceptual gaps constrain our ability to predict ecosystem-scale drought impacts under climate change. Here, we introduce the ecosystem wilting point (Ψ_EWP ), a property that integrates the drought response of an ecosystem's plant community across the soil-plant-atmosphere continuum. Specifically, Ψ_EWP defines a threshold below which the capacity of the root system to extract soil water and the ability of the leaves to maintain stomatal function are strongly diminished. We combined ecosystem flux and leaf water potential measurements to derive the Ψ_EWP of a Quercus-Carya forest from an "ecosystem pressure-volume (PV) curve," which is analogous to the tissue-level technique. When community predawn leaf water potential (Ψ_pd ) was above Ψ_EWP (=-2.0 MPa), the forest was highly responsive to environmental dynamics. When Ψ_pd fell below Ψ_EWP , the forest became insensitive to environmental variation and was a net source of carbon dioxide for nearly 2 months. Thus, Ψ_EWP is a threshold defining marked shifts in ecosystem functional state. Though there was rainfall-induced recovery of ecosystem gas exchange following soaking rains, a legacy of structural and physiological damage inhibited canopy photosynthetic capacity. Although over 16 growing seasons, only 10% of Ψ_pd observations fell below Ψ_EWP , the forest is commonly only 2-4 weeks of intense drought away from reaching Ψ_EWP , and thus highly reliant on frequent rainfall to replenish the soil water supply. We propose, based on a bottom-up analysis of root density profiles and soil moisture characteristic curves, that soil water acquisition capacity is the major determinant of Ψ_EWP , and species in an ecosystem require compatible leaf-level traits such as turgor loss point so that leaf wilting is coordinated with the inability to extract further water from the soil.

When things get MESI: The Manipulation Experiments Synthesis Initiative-A coordinated effort to synthesize terrestrial global change experiments

Responses of the terrestrial biosphere to rapidly changing environmental conditions are a major source of uncertainty in climate projections. In an effort to reduce this uncertainty, a wide range of global change experiments have been conducted that mimic future conditions in terrestrial ecosystems, manipulating CO₂ , temperature, and nutrient and water availability. Syntheses of results across experiments provide a more general sense of ecosystem responses to global change, and help to discern the influence of background conditions such as climate and vegetation type in determining global change responses. Several independent syntheses of published data have yielded distinct databases for specific objectives. Such parallel, uncoordinated initiatives carry the risk of producing redundant data collection efforts and have led to contrasting outcomes without clarifying the underlying reason for divergence. These problems could be avoided by creating a publicly available, updatable, curated database. Here, we report on a global effort to collect and curate 57,089 treatment responses across 3644 manipulation experiments at 1145 sites, simulating elevated CO₂ , warming, nutrient addition, and precipitation changes. In the resulting Manipulation Experiments Synthesis Initiative (MESI) database, effects of experimental global change drivers on carbon and nutrient cycles are included, as well as ancillary data such as background climate, vegetation type, treatment magnitude, duration, and, unique to our database, measured soil properties. Our analysis of the database indicates that most experiments are short term (one or few growing seasons), conducted in the USA, Europe, or China, and that the most abundantly reported variable is aboveground biomass. We provide the most comprehensive multifactor global change database to date, enabling the research community to tackle open research questions, vital to global policymaking. The MESI database, freely accessible at doi.org/10.5281/zenodo.7153253, opens new avenues for model evaluation and synthesis-based understanding of how global change affects terrestrial biomes. We welcome contributions to the database on GitHub.

Accuracy, realism and general applicability of European forest models

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world

Responses of terrestrial ecosystems to climate change have been explored in many regions worldwide. While continued drying and warming may alter process rates and deteriorate the state and performance of ecosystems, it could also lead to more fundamental changes in the mechanisms governing ecosystem functioning. Here we argue that climate change will induce unprecedented shifts in these mechanisms in historically wetter climatic zones, towards mechanisms currently prevalent in dry regions, which we refer to as 'dryland mechanisms'. We discuss 12 dryland mechanisms affecting multiple processes of ecosystem functioning, including vegetation development, water flow, energy budget, carbon and nutrient cycling, plant production and organic matter decomposition. We then examine mostly rare examples of the operation of these mechanisms in non-dryland regions where they have been considered irrelevant at present. Current and future climate trends could force microclimatic conditions across thresholds and lead to the emergence of dryland mechanisms and their increasing control over ecosystem functioning in many biomes on Earth.

Characterizing the Response of Vegetation Cover to Water Limitation in Africa Using Geostationary Satellites

Hydrological interactions between vegetation, soil, and topography are complex, and heterogeneous in semi-arid landscapes. This along with data scarcity poses challenges for large-scale modeling of vegetation-water interactions. Here, we exploit metrics derived from daily Meteosat data over Africa at ca. 5 km spatial resolution for ecohydrological analysis. Their spatial patterns are based on Fractional Vegetation Cover (FVC) time series and emphasize limiting conditions of the seasonal wet to dry transition: the minimum and maximum FVC of temporal record, the FVC decay rate and the FVC integral over the decay period. We investigate the relevance of these metrics for large scale ecohydrological studies by assessing their co-variation with soil moisture, and with topographic, soil, and vegetation factors. Consistent with our initial hypothesis, FVC minimum and maximum increase with soil moisture, while the FVC integral and decay rate peak at intermediate soil moisture. We find evidence for the relevance of topographic moisture variations in arid regions, which, counter-intuitively, is detectable in the maximum but not in the minimum FVC. We find no clear evidence for wide-spread occurrence of the "inverse texture effect" on FVC. The FVC integral over the decay period correlates with independent data sets of plant water storage capacity or rooting depth while correlations increase with aridity. In arid regions, the FVC decay rate decreases with canopy height and tree cover fraction as expected for ecosystems with a more conservative water-use strategy. Thus, our observation-based products have large potential for better understanding complex vegetation-water interactions from regional to continental scales.

Timing outweighs magnitude of rainfall in shaping population dynamics of a small mammal species in steppe grassland

Disentangling the effects of rainfall timing and magnitude on animal and plant populations is essential to reveal the biological consequence of diverse climate change scenarios around the world. We conducted a 10-y, large-scale, manipulative experiment to examine the bottom-up effects of changes in rainfall regime on the population dynamics of Brandt’s voles in the steppe grassland of Inner Mongolia, China. We found that a moderate rainfall increase during the early growing season could produce marked increases in vole population size by increasing the biomass of preferred plant species, whereas large increases in rainfall produced no additional increase in vole population growth. Our study highlights the importance of rainfall magnitude and timing on the nonlinear population dynamics of herbivores.

Climate change–induced shifts in species phenology differ widely across trophic levels, which may lead to consumer–resource mismatches with cascading population and ecosystem consequences. Here, we examined the effects of different rainfall patterns (i.e., timing and amount) on the phenological asynchrony of population of a generalist herbivore and their food sources in semiarid steppe grassland in Inner Mongolia. We conducted a 10-y (2010 to 2019) rainfall manipulation experiment in 12 0.48-ha field enclosures and found that moderate rainfall increases during the early rather than late growing season advanced the timing of peak reproduction and drove marked increases in population size through increasing the biomass of preferred plant species. By contrast, greatly increased rainfall produced no further increases in vole population growth due to the potential negative effect of the flooding of burrows. The increases in vole population size were more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide experimental evidence for the fitness consequences of phenological mismatches at the population level and highlight the importance of rainfall timing on the population dynamics of small herbivores in the steppe grassland environment.

Divergent responses of primary production to increasing precipitation variability in global drylands

Interannual variability in precipitation has increased globally as climate warming intensifies. The increased variability impacts both terrestrial plant production and carbon (C) sequestration. However, mechanisms driving these changes are largely unknown. Here, we examined mechanisms underlying the response of aboveground net primary production (ANPP) to interannual precipitation variability in global drylands with mean annual precipitation (MAP) <500 mm year^-1 , using a combined approach of data synthesis and process-based modeling. We found a hump-shaped response of ANPP to precipitation variability along the MAP gradient. The response was positive when MAP < ~300 mm year^-1 and negative when MAP was higher than this threshold, with a positive peak at 140 mm year^-1 . Transpiration and subsoil water content mirrored the response of ANPP to precipitation variability; evaporation responded negatively and water loss through runoff and drainage responded positively to precipitation variability. Mean annual temperature, soil type, and plant physiological traits all altered the magnitude but not the pattern of the response of ANPP to precipitation variability along the MAP gradient. By extrapolating to global drylands (<500 mm year^-1  MAP), we estimated that ANPP would increase by 15.2 ± 6.0 Tg C year^-1 in arid and hyper-arid lands and decrease by 2.1 ± 0.5 Tg C year^-1 in dry sub-humid lands under future changes in interannual precipitation variability. Thus, increases in precipitation variability will enhance primary production in many drylands in the future.

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.

Annual precipitation explains variability in dryland vegetation greenness globally but not locally

Dryland vegetation productivity is strongly modulated by water availability. As precipitation patterns and variability are altered by climate change, there is a pressing need to better understand vegetation responses to precipitation variability in these ecologically fragile regions. Here we present a global analysis of dryland sensitivity to annual precipitation variations using long-term records of normalized difference vegetation index (NDVI). We show that while precipitation explains 66% of spatial gradients in NDVI across dryland regions, precipitation only accounts for <26% of temporal NDVI variability over most (>75%) dryland regions. We observed this weaker temporal relative to spatial relationship between NDVI and precipitation across all global drylands. We confirmed this result using three alternative water availability metrics that account for water loss to evaporation, and growing season and precipitation timing. This suggests that predicting vegetation responses to future rainfall using space-for-time substitution will strongly overestimate precipitation control on interannual variability in aboveground growth. We explore multiple mechanisms to explain the discrepancy between spatial and temporal responses and find contributions from multiple factors including local-scale vegetation characteristics, climate and soil properties. Earth system models (ESMs) from the latest Coupled Model Intercomparison Project overestimate the observed vegetation sensitivity to precipitation variability up to threefold, particularly during dry years. Given projections of increasing meteorological drought, ESMs are likely to overestimate the impacts of future drought on dryland vegetation with observations suggesting that dryland vegetation is more resistant to annual precipitation variations than ESMs project.

Precipitation Variability Affects Aboveground Biomass Directly and Indirectly via Plant Functional Traits in the Desert Steppe of Inner Mongolia, Northern China

Clarifying the response of community and dominance species to climate change is crucial for disentangling the mechanism of the ecosystem evolution and predicting the prospective dynamics of communities under the global climate scenario. We examined how precipitation changes affect community structure and aboveground biomass (AGB) according to manipulated precipitation experiments in the desert steppe of Inner Mongolia, China. Bayesian model and structural equation models (SEM) were used to test variation and causal relationship among precipitation, plant diversity, functional attributes, and AGB. The results showed that the responses of species richness, evenness, and plant community weighted means traits to precipitation changes in amount and year were significant. The SEM demonstrated that precipitation change in amount and year has a direct effect on richness, evenness, and community-weighted mean (CWM) for height, leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), and leaf carbon content (LCC) and AGB; there into CWM for height and LDMC had a direct positive effect on AGB; LA had a direct negative effect on AGB. Three dominant species showed diverse adaptation and resource utilization strategies in response to precipitation changes. A. polyrhizum showed an increase in height under the precipitation treatments that promoted AGB, whereas the AGB of P. harmala and S. glareosa was boosted through alterations in height and LA. Our results highlight the asynchronism of variation in community composition and structure, leaf functional traits in precipitation-AGB relationship. We proposed that altered AGB resulted from the direct and indirect effects of plant functional traits (plant height, LA, LDMC) rather than species diversity, plant functional traits are likely candidate traits, given that they are mechanistically linked to precipitation changes and affected aboveground biomass in a desert steppe.

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.