Realistic representations of plant carbon exchange processes are necessary to reliably simulate biosphere-atmosphere feedbacks. These processes are known to vary over time and space, though the drivers of the underlying rates are still widely debated in the literature. Here, we measured leaf carbon exchange in >500 individuals of 98 species from the Neotropics to high boreal biomes to determine the drivers of photosynthetic and dark respiration capacity. Covariate abiotic (long- and short-term climate) and biotic (plant type, plant size, ontogeny, water status) data were used to explore significant drivers of temperature-standardized leaf carbon exchange rates. Using model selection, we found the previous week's temperature and soil moisture at the time of measurement to be a better predictor of photosynthetic capacity than long-term climate, with the combination of high recent temperatures and low soil moisture tending to decrease photosynthetic capacity. Non-trees (annual and perennials) tended to have greater photosynthetic capacity than trees, and, within trees, adults tended to have greater photosynthetic capacity than juveniles, possibly as a result of differences in light availability. Dark respiration capacity was less responsive to the assessed drivers than photosynthetic capacity, with rates best predicted by multi-year average site temperature alone. Our results suggest that, across large spatial scales, photosynthetic capacity quickly adjusts to changing environmental conditions, namely light, temperature, and soil moisture. Respiratory capacity is more conservative and most responsive to longer-term conditions. Our results provide a framework for incorporating these processes into large-scale models and a data set to benchmark such models.

Climate change has increased global mean surface temperatures and altered hydrological processes, and projections suggest that these changes will accelerate. As seasonal precipitation patterns change, so will the soil resources available for plants. In the midwestern United States, winter temperatures and precipitation are expected to increase, while snowfall is expected to be reduced. Reduced snowpack could lead to greater frost damage and alter the timing and amount of plant available resources at the start of the growing season. In the summer, precipitation is expected to decrease, and variability is expected to increase, creating longer and more frequent dry periods. In temperate forests, herbaceous understory plants and woody plants in early developmental stages are expected to be highly sensitive to changes in abiotic conditions. Here, we study how seasonal changes in precipitation affect the timing and availability of resources in a temperate deciduous forest. Further, we examine how changes in abiotic conditions influence understory composition and woody plant recruitment. We established a fully factorial experiment that manipulated winter snowfall and summer precipitation to create wet, dry, and control (ambient) conditions in a temperate deciduous forest near West Lafayette, Indiana, USA. We found that large changes in winter and summer precipitation appeared to affect forest processes independently of one another, and changes in seasonal precipitation altered understory composition minimally and had little to no effect on mineralization rates. The recruitment of woody plant species may be more sensitive to altered precipitation, as snow removal lowered germination rates and wet summer conditions lowered relative growth of a woody plant species, Lindera benzoin. In general, though, ecological processes in this forest understory were relatively resistant to change, at least in the short timeframe of this experiment.

Global warming, in combination with altered precipitation patterns, is accelerating global soil respiration, which could in turn accelerate climate change. The biological mechanisms through which soil carbon (C) responds to climate are not well understood, limiting our ability to predict future global soil respiration rates. As part of a climate manipulation experiment, we tested whether differences in soil heterotrophic respiration (R-H) driven by season or climate treatment are linked to (1) relative abundances of microbes in active and dormant metabolic states, (2) net changes in microbial biomass and/or (3) changes in the relative abundances of microbial groups with different C-use strategies. We used a flow-cytometric single-cell metabolic assay to quantify the abundance of active and dormant microbes, and the phospholipid fatty acid method to determine microbial biomass and ratios of fungi:bacteria and Gram-positive:Gram-negative bacteria. R-H did not respond to climate treatments but was greater in the warm and dry summer than in the cool and less-dry fall. These dynamics were better explained when microbial data were taken into account compared to when only physical data (temperature and moisture) were used. Overall, our results suggest that R-H responses to temperature are stronger when soil contains more active microbes, and that seasonal patterns of R-H can be better explained by shifts in microbial activity than by shifts in the relative abundances of fungi and Gram-positive and Gram-negative bacteria. These findings contribute to our understanding of how and under which conditions microbes influence soil C responses to climate.

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

The role of plant diversity in reducing invasions has generated decades of debate. Diverse communities might be more resistant to invasion because the communities contain resident species that are functionally similar to the invader (limiting similarity), or multiple species use the range of available resources more effectively (complementarity) than single species. However, the correlation of native and exotic diversity often reverses, becoming positive, with increasing spatial and temporal scale, in a phenomenon called the invasion paradox. We addressed two groups of hypotheses related to this paradox, broadly that (1) functional diversity and identity resist invasion initially, via complementarity or limiting similarity; and (2) disturbance and propagule pressure weaken the effects of functional diversity and identity on invader success through time. Using long-term data from experimental serpentine grassland assemblages in California, we examined how the abundance of a high impact invader, yellow starthistle (Centaurea solstitialis), related to functional diversity, functional dissimilarity, pocket gopher disturbance, and propagule pressure. We also conducted a single-season experiment in which we seeded disturbed and undisturbed areas and quantified invader success the following year. Neither diversity, nor dissimilarity, nor disturbance significantly impacted the success of C. solstitialis during the years of this study. Instead, propagule pressure was the single most important predictor of C. solstitialis abundance. We consolidated these findings into a novel conceptual model of invader success to illustrate how propagule input may outweigh community resistance through time, and what implications these dynamics have for the invasion paradox.

Triose phosphate utilization (TPU)-limited photosynthesis occurs when carbon export from the Calvin-Benson cycle cannot keep pace with carbon inputs and processing. This condition is poorly constrained by observations but may become an increasingly important driver of global carbon cycling under future climate scenarios. However, the consequences of including or omitting TPU limitation in models have seldom been quantified. Here, we assess the impact of changing the representation of TPU limitation on leaf-and global-scale processes. At the leaf scale, TPU limits photosynthesis at cold temperatures, high CO2 concentrations, and high light levels. Consistent with leaf-scale results, global simulations using the Community Land Model version 4.5 illustrate that the standard representation of TPU limits carbon gain under present day and future conditions, most consistently at high latitudes. If the assumed TPU limitation is doubled, further restricting photosynthesis, terrestrial ecosystem carbon pools are reduced by 9 Pg by 2100 under a business-as-usual scenario. The impact of TPU limitation on global terrestrial carbon gain suggests that CO2 concentrations may increase more than expected if models omit TPU limitation, and highlights the need to better understand when TPU limitation is important, including variation among different plant types and acclimation to temperature and CO2.

Background and Aims Future shifts in precipitation regimes and temperature are expected to affect plant traits dramatically. To date, many studies have explored the effects of acute stresses, but few have investigated the consequences of prolonged shifts in climatic conditions on plant growth and chemistry.

As climate changes, many regions of the world are projected to experience more intense droughts, which can drive changes in plant community composition through a variety of mechanisms. During drought, community composition can respond directly to resource limitation, but biotic interactions modify the availability of these resources. Here, we develop the Community Response to Extreme Drought framework (CRED), which organizes the temporal progression of mechanisms and plant-plant interactions that may lead to community changes during and after a drought. The CRED framework applies some principles of the stress gradient hypothesis (SGH), which proposes that the balance between competition and facilitation changes with increasing stress. The CRED framework suggests that net biotic interactions (NBI), the relative frequency and intensity of facilitative (+) and competitive (-) interactions between plants, will change temporally, becoming more positive under increasing drought stress and more negative as drought stress decreases. Furthermore, we suggest that rewetting rates affect the rate of resource amelioration, specifically water and nitrogen, altering productivity responses and the intensity and importance of NBI, all of which will influence drought-induced compositional changes. System-specific variables and the intensity of drought influence the strength of these interactions, and ultimately the system's resistance and resilience to drought.

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot-scale climate data from 15 active-warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 circle C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 circle C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2 circle C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non-temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species' responses.

Thermal acclimation of plant respiration is highly relevant to climate projections; when included in models, it reduces the future rate of atmospheric CO2 rise. Although all living plant tissues respire, few studies have examined differences in acclimation among tissues, and leaf responses have received greater attention than stems and roots. Here, we examine the short-term temperature acclimation of leaf, stem and root respiration within individuals of eight disparate species acclimated to five temperatures, ranging from 15 to 35 degrees C. To assess acclimation, we measured instantaneous tissue temperature response curves (14-50 degrees C) on each individual following a 7-day acclimation period. In leaves and photosynthetic stems, the acclimation temperature had little effect on the instantaneous tissue temperature response of respiration, indicating little to no thermal acclimation in these tissues. However, respiration did acclimate in non-photosynthetic tissues; respiratory rates measured at the acclimation temperature were similar across the different acclimation temperatures. Respiratory demand of photosynthetic tissue increased with acclimation temperature as a result of increased photosynthetic demands, resulting in rates measured at the acclimation temperature that increased with increasing acclimation temperature. In non-photosynthetic tissue, the homeostatic response of respiration suggests that acclimation temperature had little influence on respiratory demand. Our results indicate that respiratory temperature acclimation differs by tissue type and that this difference is the consequence of the coupling between photosynthesis and respiration in photosynthetic, but not non-photosynthetic tissue. These insights provide an avenue for improving the representation of respiratory temperature acclimation in large-scale models.