Mapping the global distribution of C4 vegetation using observations and optimality theory.

Plants with the C4 photosynthesis pathway typically respond to climate change differently from more common C3-type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C4 and C3 vegetation distributions. However, current C4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C4 vegetation. We find that global C4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C4 natural grass cover due to elevated CO2 favoring C3-type photosynthesis, and an increase in C4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18-23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C4 plants in the contemporary global carbon cycle.

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.

Accelerating effects of growing-season warming on tree seasonal activities are progressively disappearing.

The phenological changes induced by climate warming have profound effects on water, energy, and carbon cycling in forest ecosystems. In addition to pre-season warming, growing-season warming may drive tree phenology by altering photosynthetic carbon uptake. It has been reported that the effect of pre-season warming on tree phenology is decreasing. However, temporal change in the effect of growing-season warming on tree phenology is not yet clear. Combining long-term ground observations and remote-sensing data, here we show that spring and autumn phenology were advanced by growing-season warming, while the accelerating effects of growing-season warming on tree phenology were progressively disappearing, manifesting as phenological events converted from being advanced to being delayed, in the temperate deciduous broadleaved forests across the Northern Hemisphere between 1983 and 2014. We further observed that the effect of growing-season warming on photosynthetic productivity showed a synchronized decline over the same period. The responses of phenology and photosynthetic productivity had a strong linear relationship with each other, and both showed significant negative correlations with the elevated temperature and vapor pressure deficit during the growing season. These findings indicate that warming-induced water stress may drive the observed decline in the responses of tree phenology to growing-season warming by decelerating photosynthetic productivity. Our results not only demonstrate a close link between photosynthetic carbon uptake and tree seasonal activities but also provide a physiological perspective of the nonlinear phenological responses to climate warming.

Soil nitrogen fertilization reduces relative leaf nitrogen allocation to photosynthesis.

The connection between soil nitrogen availability, leaf nitrogen, and photosynthetic capacity is not perfectly understood. Because these three components tend to be positively related over large spatial scales, some posit that soil nitrogen positively drives leaf nitrogen, which positively drives photosynthetic capacity. Alternatively, others posit that photosynthetic capacity is primarily driven by above-ground conditions. Here, we examined the physiological responses of a non-nitrogen-fixing plant (Gossypium hirsutum) and a nitrogen-fixing plant (Glycine max) in a fully factorial combination of light by soil nitrogen availability to help reconcile these competing hypotheses. Soil nitrogen stimulated leaf nitrogen in both species, but the relative proportion of leaf nitrogen used for photosynthetic processes was reduced under elevated soil nitrogen in all light availability treatments due to greater increases in leaf nitrogen content than chlorophyll and leaf biochemical process rates. Leaf nitrogen content and biochemical process rates in G. hirsutum were more responsive to changes in soil nitrogen than those in G. max, probably due to strong G. max investments in root nodulation under low soil nitrogen. Nonetheless, whole-plant growth was significantly enhanced by increased soil nitrogen in both species. Light availability consistently increased relative leaf nitrogen allocation to leaf photosynthesis and whole-plant growth, a pattern that was similar between species. These results suggest that the leaf nitrogen-photosynthesis relationship varies under different soil nitrogen levels and that these species preferentially allocated more nitrogen to plant growth and non-photosynthetic leaf processes, rather than photosynthesis, as soil nitrogen increased.

Environmental heterogeneity modulates the effect of plant diversity on the spatial variability of grassland biomass.

Plant productivity varies due to environmental heterogeneity, and theory suggests that plant diversity can reduce this variation. While there is strong evidence of diversity effects on temporal variability of productivity, whether this mechanism extends to variability across space remains elusive. Here we determine the relationship between plant diversity and spatial variability of productivity in 83 grasslands, and quantify the effect of experimentally increased spatial heterogeneity in environmental conditions on this relationship. We found that communities with higher plant species richness (alpha and gamma diversity) have lower spatial variability of productivity as reduced abundance of some species can be compensated for by increased abundance of other species. In contrast, high species dissimilarity among local communities (beta diversity) is positively associated with spatial variability of productivity, suggesting that changes in species composition can scale up to affect productivity. Experimentally increased spatial environmental heterogeneity weakens the effect of plant alpha and gamma diversity, and reveals that beta diversity can simultaneously decrease and increase spatial variability of productivity. Our findings unveil the generality of the diversity-stability theory across space, and suggest that reduced local diversity and biotic homogenization can affect the spatial reliability of key ecosystem functions.

Warming-induced increase in carbon uptake is linked to earlier spring phenology in temperate and boreal forests.

Under global warming, advances in spring phenology due to rising temperatures have been widely reported. However, the physiological mechanisms underlying the advancement in spring phenology still remain poorly understood. Here, we investigated the effect of temperature during the previous growing season on spring phenology of current year based on the start of season extracted from multiple long-term and large-scale phenological datasets between 1951 and 2018. Our findings indicate that warmer temperatures during previous growing season are linked to earlier spring phenology of current year in temperate and boreal forests. Correspondingly, we observed an earlier spring phenology with the increase in photosynthesis of the previous growing season. These findings suggest that the observed warming-induced earlier spring phenology is driven by increased photosynthetic carbon assimilation in the previous growing season. Therefore, the vital role of warming-induced changes in carbon assimilation should be considered to accurately project spring phenology and carbon cycling in forest ecosystems under future climate warming.

Daytime warming triggers tree growth decline in the Northern Hemisphere.

Global warming has been linked to declines in tree growth. However, it is unclear how the asymmetry in daytime and nighttime warming influences this response. Here, we use 2947 residual tree-ring width chronologies covering 32 species at 2493 sites, between 1901 and 2018, across the Northern Hemisphere, to analyze the effects of daytime and nighttime temperatures, precipitation, and drought stress on the radial growth of trees. We show that drought stress was primarily triggered by daytime rather than nighttime warming. The radial growth of trees was more sensitive to drought stress in warm regions than in cold regions, especially for angiosperms. Our study provides robust evidence that daytime warming is the primary driver of the observed declines in forest productivity related to drought stress and that daytime and nighttime warming should be considered separately when modelling forest-climate interactions and feedbacks in a future, warmer world.

Rising CO2 and warming reduce global canopy demand for nitrogen.

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO2 and climate change. By extension, it has been suggested that declining carboxylation capacity (Vcmax ) and leaf N content in enhanced-CO2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis and estimated changes in leaf-level photosynthetic N for 1982-2016 assuming proportionality with leaf-level Vcmax at 25°C. The whole-canopy photosynthetic N was derived using satellite-based leaf area index (LAI) data and an empirical extinction coefficient for Vcmax , and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of Vcmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr-1 , while observed leaf (total) N declined by 0.2-0.25% yr-1 . Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf-level responses to rising CO2 , and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation.

Leaf nitrogen from the perspective of optimal plant function.

Leaf dry mass per unit area (LMA), carboxylation capacity (V cmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and V cmax at 25°C (V cmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to V cmax25 and LMA. Relationships of observed V cmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and V cmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean V cmax25, 43% in LMA and 31% in Narea. Predicted V cmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils. Synthesis. Global patterns of variation in observed site-mean Narea can be explained by climate-induced variations in optimal V cmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of V cmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole-plant carbon allocation, rather than via leaf-level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.

Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model.

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change, and broadening the impact of ecological research.

Delaying effect of humidity on leaf unfolding in Europe.

Understanding the drivers of plant phenology is critical to predict the impact of future warming on terrestrial ecosystem carbon cycling and feedbacks to climate. Using indoor growth chambers, air humidity is reported to influence spring phenology in temperate trees. However, previous studies have not investigated the effect of air humidity on the spring phenology using long-term and large-scale ground observations. Therefore, the role of humidity in spring phenology in temperate trees still remains poorly understood. Here, we synthesized 229,588 records of leaf unfolding dates in eight temperate tree species, including four early-successional and four late-successional species, at 1716 observation sites during 1951-2015 in Europe, and comprehensively analyzed the effect of humidity on the spring phenology. We found that rising humidity significantly delayed spring leaf unfolding for all eight temperate tree species. Leaf unfolding was more sensitive to humidity in early-successional species compared to late-successional species. In addition, the delaying effect of humidity on leaf unfolding increased as temperature warmed over the past 65 years. Our results provide evidence that spring leaf unfolding of temperate trees was significantly delayed by rising humidity. The delaying effect of humidity may restrict earlier spring phenology induced by warming, especially for early-successional species, under future climate warming scenarios in temperate forests.

Global variation in the fraction of leaf nitrogen allocated to photosynthesis.

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.

Contrasting temporal variations in responses of leaf unfolding to daytime and nighttime warming.

Earlier spring phenological events have been widely reported in plants under global warming. Recent studies reported a slowdown in the warming-induced advanced spring phenology in temperate regions. However, previous research mainly focused on daily mean temperature, thus neglecting the asymmetric phenological responses to daytime and nighttime temperature. Using long-term records of leaf unfolding in eight deciduous species at 1300 sites across central Europe, we assessed and compared the effects of daytime temperature, nighttime temperature, and photoperiod on leaf unfolding during 1951-1980 and 1981-2013. Although leaf unfolding was advanced by daytime warming during 1951-2013, the advancing responses of leaf unfolding significantly decreased from 1951-1980 to 1981-2013 due to a lower accumulation of chilling units by daytime warming. Nighttime warming delayed leaf unfolding during 1951-1980 but advanced it during 1981-2013 due to a higher accumulation of chilling units by nighttime warming. In contrast, critical daylength and plasticity of leaf unfolding dates remained unchanged between 1951 and 2013. Our study provided evidence that daytime warming instead of nighttime warming accounts for the slowdown in the advancing spring phenology and implied that nighttime warming-induced earlier spring phenology may be buffering the slowdown of the advanced spring phenology by daytime warming. The response of spring phenology to nighttime temperature may override that to daytime temperature under the actual trends in global warming.

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.

Root mass carbon costs to acquire nitrogen are determined by nitrogen and light availability in two species with different nitrogen acquisition strategies.

Plant nitrogen acquisition requires carbon to be allocated belowground to build roots and sustain microbial associations. This carbon cost to acquire nitrogen varies by nitrogen acquisition strategy; however, the degree to which these costs vary due to nitrogen availability or demand has not been well tested under controlled conditions. We grew a species capable of forming associations with nitrogen-fixing bacteria (Glycine max) and a species not capable of forming such associations (Gossypium hirsutum) under four soil nitrogen levels to manipulate nitrogen availability and four light levels to manipulate nitrogen demand in a full-factorial greenhouse experiment. We quantified carbon costs to acquire nitrogen as the ratio of total root carbon to whole-plant nitrogen within each treatment combination. In both species, light availability increased carbon costs due to a larger increase in root carbon than whole-plant nitrogen, while nitrogen fertilization generally decreased carbon costs due to a larger increase in whole-plant nitrogen than root carbon. Nodulation data indicated that G. max shifted relative carbon allocation from nitrogen fixation to direct uptake with increased nitrogen fertilization. These findings suggest that carbon costs to acquire nitrogen are modified by changes in light and nitrogen availability in species with and without associations with nitrogen-fixing bacteria.

Invasion-induced root-fungal disruptions alter plant water and nitrogen economies.

Despite widespread evidence that biological invasion influences both the biotic and abiotic soil environments, the extent to which these two pathways underpin the effects of invasion on plant traits and performance remains unknown. Leveraging a long-term (14-year) field experiment, we show that an allelochemical-producing invader affects plants through biotic mechanisms, altering the soil fungal community composition, with no apparent shifts in soil nutrient availability. Changes in belowground fungal communities resulted in high costs of nutrient uptake for native perennials and a shift in plant traits linked to their water and nutrient use efficiencies. Some plants in the invaded community compensate for the disruption of nutritional symbionts and reduced nutrient provisioning by sanctioning more nitrogen to photosynthesis and expending more water, which demonstrates a trade-off in trait investment. For the first time, we show that the disruption of belowground nutritional symbionts can drive plants towards alternative regions of their trait space in order to maintain water and nutrient economics.

Mechanisms underlying leaf photosynthetic acclimation to warming and elevated CO2 as inferred from least-cost optimality theory.

The mechanisms responsible for photosynthetic acclimation are not well understood, effectively limiting predictability under future conditions. Least-cost optimality theory can be used to predict the acclimation of photosynthetic capacity based on the assumption that plants maximize carbon uptake while minimizing the associated costs. Here, we use this theory as a null model in combination with multiple datasets of C3 plant photosynthetic traits to elucidate the mechanisms underlying photosynthetic acclimation to elevated temperature and carbon dioxide (CO2 ). The model-data comparison showed that leaves decrease the ratio of the maximum rate of electron transport to the maximum rate of Rubisco carboxylation (Jmax /Vcmax ) under higher temperatures. The comparison also indicated that resources used for Rubisco and electron transport are reduced under both elevated temperature and CO2 . Finally, our analysis suggested that plants underinvest in electron transport relative to carboxylation under elevated CO2 , limiting potential leaf-level photosynthesis under future CO2 concentrations. Altogether, our results show that acclimation to temperature and CO2 is primarily related to resource conservation at the leaf level. Under future, warmer, high CO2 conditions, plants are therefore likely to use less nutrients for leaf-level photosynthesis, which may impact whole-plant to ecosystem functioning.

When and where soil is important to modify the carbon and water economy of leaves.

Photosynthetic 'least-cost' theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate-related costs for both resources increase. Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci /Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets. The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit-costs are presumably higher. Higher values of soil silt and depth increased Ci /Ca , likely by providing greater H2 O supply, alleviating biophysical photosynthetic limitation when soil water is scarce. Climate is important in controlling the optimal balance of H2 O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate-demand driven predictions of Ci /Ca by up to 30% at a global scale.