Reduced global plant respiration due to the acclimation of leaf dark respiration coupled with photosynthesis.

Leaf dark respiration (Rd ) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that Rd and Rubisco carboxylation capacity (Vcmax ) at 25°C (Rd,25 , Vcmax,25 ) are coordinated so that Rd,25 variations support Vcmax,25 at a level allowing full light use, with Vcmax,25 reflecting daytime conditions (for photosynthesis), and Rd,25 /Vcmax,25 reflecting night-time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5-yr warming experiment, and spatially using an extensive field-measurement data set. We compared the results to three published alternatives: Rd,25 declines linearly with daily average prior temperature; Rd at average prior night temperatures tends towards a constant value; and Rd,25 /Vcmax,25 is constant. Our hypothesis accounted for more variation in observed Rd,25 over time (R2 = 0.74) and space (R2 = 0.68) than the alternatives. Night-time temperature dominated the seasonal time-course of Rd , with an apparent response time scale of c. 2 wk. Vcmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global Rd in response to rising CO2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Optimality principles explaining divergent responses of alpine vegetation to environmental change.

Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax ) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year-1 in drier regions and a browning of 0.12 ± 0.08% year-1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year-1 ) and browning (0.07 ± 0.06% year-1 ). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the mechanisms underlying recent trends in vegetation greenness and provides further insight into the response of alpine ecosystems to ongoing climate change.

Coordination of plant hydraulic and photosynthetic traits: confronting optimality theory with field measurements.

Close coupling between water loss and carbon dioxide uptake requires coordination of plant hydraulics and photosynthesis. However, there is still limited information on the quantitative relationships between hydraulic and photosynthetic traits. We propose a basis for these relationships based on optimality theory, and test its predictions by analysis of measurements on 107 species from 11 sites, distributed along a nearly 3000-m elevation gradient. Hydraulic and leaf economic traits were less plastic, and more closely associated with phylogeny, than photosynthetic traits. The two sets of traits were linked by the sapwood to leaf area ratio (Huber value, vH ). The observed coordination between vH and sapwood hydraulic conductivity (KS ) and photosynthetic capacity (Vcmax ) conformed to the proposed quantitative theory. Substantial hydraulic diversity was related to the trade-off between KS and vH . Leaf drought tolerance (inferred from turgor loss point, -Ψtlp ) increased with wood density, but the trade-off between hydraulic efficiency (KS ) and -Ψtlp was weak. Plant trait effects on vH were dominated by variation in KS , while effects of environment were dominated by variation in temperature. This research unifies hydraulics, photosynthesis and the leaf economics spectrum in a common theoretical framework, and suggests a route towards the integration of photosynthesis and hydraulics in land-surface models.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models.

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

Global ecosystems and fire: Multi-model assessment of fire-induced tree-cover and carbon storage reduction.

In this study, we use simulations from seven global vegetation models to provide the first multi-model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001-2012. Fire globally reduces the tree covered area and vegetation carbon storage by 10%. Regionally, the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to 0. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire-induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state-of-the-art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems.

Quantifying leaf-trait covariation and its controls across climates and biomes.

Plant functional ecology requires the quantification of trait variation and its controls. Field measurements on 483 species at 48 sites across China were used to analyse variation in leaf traits, and assess their predictability. Principal components analysis (PCA) was used to characterize trait variation, redundancy analysis (RDA) to reveal climate effects, and RDA with variance partitioning to estimate separate and overlapping effects of site, climate, life-form and family membership. Four orthogonal dimensions of total trait variation were identified: leaf area (LA), internal-to-ambient CO2 ratio (χ), leaf economics spectrum traits (specific leaf area (SLA) versus leaf dry matter content (LDMC) and nitrogen per area (Narea )), and photosynthetic capacities (Vcmax , Jmax at 25°C). LA and χ covaried with moisture index. Site, climate, life form and family together explained 70% of trait variance. Families accounted for 17%, and climate and families together 29%. LDMC and SLA showed the largest family effects. Independent life-form effects were small. Climate influences trait variation in part by selection for different life forms and families. Trait values derived from climate data via RDA showed substantial predictive power for trait values in the available global data sets. Systematic trait data collection across all climates and biomes is still necessary.

Multidecadal variability in Atlas cedar growth in Northwest Africa during the last 850 years: Implications for dieback and conservation of an endangered species.

Widespread forest dieback is a phenomenon of global concern that requires an improved understanding of the relationship between tree growth and climate to support conservation efforts. One priority for conservation is the Atlas cedar (Cedrus atlantica), an endangered species exhibiting dieback throughout its North African range. In this study, we evaluate the long-term context for recent dieback and develop a projection of future C. atlantica growth by exploring the periodic variability of its growth through time. First, we present a new C. atlantica tree-ring chronology (1150-2013 CE) from the Middle Atlas mountains, Morocco. We then compare the new chronology to existing C. atlantica chronologies in Morocco and use principal components analysis (PCA) to isolate the common periodic signal from the seven longest available records (PCA7, 1271-1984 CE) in the Middle and High Atlas portions of the C. atlantica range. PCA7 captures 55.7% of the variance and contains significant multidecadal (˜95 yr, ˜57 yr, ˜21 yr) periodic components, revealed through spectral and wavelet analyses. Parallel analyses of historical climate data (1901-2016 CE) suggests that the multidecadal growth signal originates primarily in growing season (spring and summer) precipitation variability, compounded by slow-changing components of summer and winter temperatures. Finally, we model the long-term growth patterns between 1271-1984 CE using a small number (three to four) of harmonic components, illustrating that suppressed growth since the 1970s - a factor implicated in the dieback of this species - is consistent with recurrent climatically-driven growth declines. Forward projection of this model suggests two climatically-favourable periods for growth in the 21st century that may enhance current conservation actions for the long-term survival of the C. atlantica in the Middle and High Atlas mountains.

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages.

The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants.

Plant functional traits provide information about adaptations to climate and environmental conditions, and can be used to explore the existence of alternative plant strategies within ecosystems. Trait data are also increasingly being used to provide parameter estimates for vegetation models. Here we present a new database of plant functional traits from China. Most global climate and vegetation types can be found in China, and thus the database is relevant for global modeling. The China Plant Trait Database contains information on morphometric, physical, chemical, and photosynthetic traits from 122 sites spanning the range from boreal to tropical, and from deserts and steppes through woodlands and forests, including montane vegetation. Data collection at each site was based either on sampling the dominant species or on a stratified sampling of each ecosystem layer. The database contains information on 1,215 unique species, though many species have been sampled at multiple sites. The original field identifications have been taxonomically standardized to the Flora of China. Similarly, derived photosynthetic traits, such as electron-transport and carboxylation capacities, were calculated using a standardized method. To facilitate trait-environment analyses, the database also contains detailed climate and vegetation information for each site. The data set is released under a Creative Commons BY license. When using the data set, we kindly request that you cite this article, recognizing the hard work that went into collecting the data and the authors' willingness to make it publicly available.

Underlying causes of Eurasian midcontinental aridity in simulations of mid-Holocene climate.

Climate model simulations uniformly show drier and warmer summers in the Eurasian midcontinent during the mid-Holocene, which is not consistent with paleoenvironmental observations. The simulated climate results from a reduction in the zonal temperature gradient, which weakens westerly flow and reduces moisture flux and precipitation in the midcontinent. As a result, sensible heating is favored over evaporation and latent heating, resulting in substantial surface-driven atmospheric warming. Thus, the discrepancy with the paleoenvironmental evidence arises initially from a problem in the simulated circulation and is exacerbated by feedback from the land surface. This region is also drier and warmer than indicated by observations in the preindustrial control simulations, and this bias arises in the same way: zonal flow and hence moisture flux into the midcontinent are too weak, and feedback from the land surface results in surface-driven warming. These analyses suggest the need to improve those aspects of climate models that affect the strength of westerly circulation.

Drought and resprouting plants.

Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21st Century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly than ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. The strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented.

Orbitally forced and internal changes in West African rainfall interannual-to-decadal variability for the last 6000 years.

Recent variability in West African monsoon rainfall (WAMR) has been shown to be influenced by multiple ocean-atmosphere modes, including the El Niño Southern Oscillation, Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. How these modes will change in response to long term forcing is less well understood. Here we use four transient simulations driven by changes in orbital forcing and greenhouse gas concentrations over the past 6000 years to examine the relationship between West African monsoon rainfall multiscale variability and changes in the modes associated with this variability. All four models show a near linear decline in monsoon rainfall over the past 6000 years in response to the gradual weakening of the interhemispheric gradient in sea surface temperatures. The only indices that show a long-term trend are those associated with the strengthening of the El Niño Southern Oscillation from the mid-Holocene onwards. At the interannual-to-decadal timescale, WAMR variability is largely influenced by Pacific-Atlantic - Mediterranean Sea teleconnections in all simulations; the exact configurations are model sensitive. The WAMR interannual-to-decadal variability depicts marked multi-centennial oscillations, with La Niña/negative Pacific Decadal Oscillation and a weakening and/or poleward shift of subtropical high-pressure systems over the Atlantic favoring wet WAMR anomalies. The WAMR interannual-to-decadal variability also depicts an overall decreasing trend throughout the Holocene that is consistent among the simulations. This decreasing trend relates to changes in the North Atlantic and Gulf of Guinea Sea Surface Temperature variability. Supplementary Information: The online version contains supplementary material available at 10.1007/s00382-023-07023-y.

Volatile isoprenoid emissions from plastid to planet.

Approximately 1-2% of net primary production by land plants is re-emitted to the atmosphere as isoprene and monoterpenes. These emissions play major roles in atmospheric chemistry and air pollution-climate interactions. Phenomenological models have been developed to predict their emission rates, but limited understanding of the function and regulation of these emissions has led to large uncertainties in model projections of air quality and greenhouse gas concentrations. We synthesize recent advances in diverse fields, from cell physiology to atmospheric remote sensing, and use this information to propose a simple conceptual model of volatile isoprenoid emission based on regulation of metabolism in the chloroplast. This may provide a robust foundation for scaling up emissions from the cellular to the global scale.

Modelling and prediction of wind damage in forest ecosystems of the Sudety Mountains, SW Poland.

Windstorms are one of the most important disturbance factors in European forest ecosystems. An understanding of the major drivers causing observed changes in forests is essential to improve prediction models and as a basis for forest management. In the present study, we use machine learning techniques in combination with data sets on tree properties, bioclimatic and geomorphic conditions, to analyse the level of forest damage by windstorms in the Sudety Mountains over the period 2004-2010. We tested four scenarios under five classification model frameworks: logistic regression, random forest, support vector machines, neural networks, and gradient boosted modelling. Gradient boosted modelling and random forest have the best predictive power. Tree volume and age are the most important predictors of windstorm damage; climate and geomorphic variables are less important. Forest damage maps based on forest data from 2020 show lower probabilities of damage compared to the end of 20th and the beginning of 21st century.

The timing, duration and magnitude of the 8.2 ka event in global speleothem records.

Abrupt events are a feature of many palaeoclimate records during the Holocene. The best example is the 8.2 ka event, which was triggered by a release of meltwater into the Labrador Sea and resulted in a weakening of poleward heat transport in the North Atlantic. We use an objective method to identify rapid climate events in globally distributed speleothem oxygen isotope records during the Holocene. We show that the 8.2 ka event can be identified in >70% of the speleothem records and is the most coherent signal of abrupt climate change during the last 12,000 years. The isotopic changes during the event are regionally homogenous: positive oxygen isotope anomalies are observed across Asia and negative anomalies are seen across Europe, the Mediterranean, South America and southern Africa. The magnitude of the isotopic excursions in Europe and Asia are statistically indistinguishable. There is no significant difference in the duration and timing of the 8.2 ka event between regions, or between the speleothem records and Greenland ice core records. Our study supports a rapid and global climate response to the 8.2 ka freshwater pulse into the North Atlantic, likely transmitted globally via atmospheric teleconnections.

Leaf morphological traits as adaptations to multiple climate gradients.

Leaf morphological traits vary systematically along climatic gradients. However, recent studies in plant functional ecology have mainly analysed quantitative traits, while numerical models of species distributions and vegetation function have focused on traits associated with resource acquisition; both ignore the wider functional significance of leaf morphology.A dataset comprising 22 leaf morphological traits for 662 woody species from 92 sites, representing all biomes present in China, was subjected to multivariate analysis in order to identify leading dimensions of trait covariation (correspondence analysis), quantify climatic and phylogenetic contributions (canonical correspondence analysis with variation partitioning) and characterise co-occurring trait syndromes (k-means clustering) and their climatic preferences.Three axes accounted for >20% of trait variation in both evergreen and deciduous species. Moisture index, precipitation seasonality and growing-season temperature explained 8%-10% of trait variation; family 15%-32%. Microphyll or larger, mid- to dark green leaves with drip tips in wetter climates contrasted with nanophyll or smaller glaucous leaves without drip tips in drier climates. Thick, entire leaves in less seasonal climates contrasted with thin, marginal dissected, aromatic and involute/revolute leaves in more seasonal climates. Thick, involute, hairy leaves in colder climates contrasted with thin leaves with marked surface structures (surface patterning) in warmer climates. Distinctive trait clusters were linked to the driest and most seasonal climates, for example the clustering of picophyll, fleshy and succulent leaves in the driest climates and leptophyll, linear, dissected, revolute or involute and aromatic leaves in regions with highly seasonal rainfall. Several trait clusters co-occurred in wetter climates, including clusters characterised by microphyll, moderately thick, patent and entire leaves or notophyll, waxy, dark green leaves. Synthesis. The plastic response of size, shape, colour and other leaf morphological traits to climate is muted, thus their apparent shift along climate gradients reflects plant adaptations to environment at a community level as determined by species replacement. Information on leaf morphological traits, widely available in floras, could be used to strengthen predictive models of species distribution and vegetation function.

A new method based on surface-sample pollen data for reconstructing palaeovegetation patterns.

Aim: Biomisation has been the most widely used technique to reconstruct past regional vegetation patterns because it does not require an extensive modern pollen dataset. However, it has well-known limitations including its dependence on expert judgement for the assignment of pollen taxa to plant functional types (PFTs) and PFTs to biomes. Here we present a new method that combines the strengths of biomisation with those of the alternative dissimilarity-based techniques. Location: The Eastern Mediterranean-Black Sea Caspian Corridor (EMBSeCBIO). Taxon: Plants. Methods: Modern pollen samples, assigned to biomes based on potential natural vegetation data, are used to characterize the within-biome means and standard deviations of the abundances of each taxon. These values are used to calculate a dissimilarity index between any pollen sample and every biome, and thus assign the sample to the most likely biome. We calculate a threshold value for each modern biome; fossil samples with scores below the threshold for all modern biomes are thus identified as non-analogue vegetation. We applied the new method to the EMBSeCBIO region to compare its performance with existing reconstructions. Results: The method captured changes in the importance of individual taxa along environmental gradients. The balanced accuracy obtained for the EMBSeCBIO region using the new method was better than obtained using biomisation (77% vs. 65%). When the method was applied to high-resolution fossil records, 70% of the entities showed more temporally stable biome assignments than obtained using biomisation. The technique also identified likely non-analogue assemblages in a synthetic modern dataset and in fossil records. Main conclusions: The new method yields more accurate and stable reconstructions of vegetation than biomisation. It requires an extensive modern pollen dataset, but is conceptually simple, and avoids subjective choices about taxon allocations to PFTs and PFTs to biomes.

The China plant trait database version 2.

Plant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of the China Plant Trait Database, which contains information on morphometric, physical, chemical, photosynthetic and hydraulic traits from 1529 unique species in 140 sites spanning a diversity of vegetation types. Version 2 has five improvements compared to the previous version: (1) new data from a 4-km elevation transect on the edge of Tibetan Plateau, including alpine vegetation types not sampled previously; (2) inclusion of traits related to hydraulic processes, including specific sapwood conductance, the area ratio of sapwood to leaf, wood density and turgor loss point; (3) inclusion of information on soil properties to complement the existing data on climate and vegetation (4) assessments and flagging the reliability of individual trait measurements; and (5) inclusion of standardized templates for systematical field sampling and measurements.

Evidence of a universal scaling relationship for leaf CO2 drawdown along an aridity gradient.

The leaf carbon isotope ratio (δ(13) C) of C3 plants is inversely related to the drawdown of CO2 concentration during photosynthesis, which increases towards drier environments. We aimed to discriminate between the hypothesis of universal scaling, which predicts between-species responses of δ(13) C to aridity similar to within-species responses, and biotic homoeostasis, which predicts offsets in the δ(13) C of species occupying adjacent ranges. The Northeast China Transect spans 130-900 mm annual precipitation within a narrow latitude and temperature range. Leaves of 171 species were sampled at 33 sites along the transect (18 at ≥ 5 sites) for dry matter, carbon (C) and nitrogen (N) content, specific leaf area (SLA) and δ(13) C. The δ(13) C of species generally followed a common relationship with the climatic moisture index (MI). Offsets between adjacent species were not observed. Trees and forbs diverged slightly at high MI. In C3 plants, δ(13) C predicted N per unit leaf area (Narea) better than MI. The δ(13) C of C4 plants was invariant with MI. SLA declined and Narea increased towards low MI in both C3 and C4 plants. The data are consistent with optimal stomatal regulation with respect to atmospheric dryness. They provide evidence for universal scaling of CO2 drawdown with aridity in C3 plants.

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.