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In a changing climate, the future survival and productivity of species rely on individual populations to respond to shifting environmental conditions. Many tree species, including northern red oak (Quercus rubra), exhibit phenotypic plasticity, the ability to respond to changes in environmental conditions at within-generation time scales, through varying traits such as leaf phenology. Phenotypic plasticity of phenology may vary among populations within a species' range, and it is unclear if the range of plasticity is adequate to promote fitness. Here, we used a 58-year-old common garden to test whether northern red oak populations differed in phenological sensitivity to changes in temperature and whether differences in phenological sensitivity were associated with differences in productivity and survival (proxies of fitness). We recorded 8 years of spring leaf emergence and autumn leaf coloration and loss in 28 distinct populations from across the species' full range. Across the 28 populations, spring leaf out consistently advanced in warmer years, but fall phenology was less responsive to changes in temperature. Southern, warm-adapted populations had larger shifts in phenology in response to springtime warming but had lower long-term survival. Moreover, higher phenological sensitivity to spring warming was not strongly linked to increased productivity. Instead, fitness was more closely linked to latitudinal gradients. Although springtime phenological sensitivity to climate change is common across northern red oak populations, responses of productivity and survival, which could determine longer-term trajectories of species abundance, are more variable across the species' range.

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. ispartof: GLOBAL CHANGE BIOLOGY vol:29 issue:7 pages:1922-1938 ispartof: location:England status: accepted

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. Accepted version

The significant portion of global terrestrial biodiversity harboured in the mountains is under increasing threat from various anthropogenic impacts. Protecting fragile mountain ecosystems requires understanding how these human disturbances affect biodiversity. As roads and railways are extended further into mountain ecosystems, understanding the long-term impacts of this infrastructure on community composition and diversity gains urgency. We used railway corridors constructed across the mountainous landscapes of the Kashmir Himalaya from 1994 to 2013 to study the effects of anthropogenic disturbance on species distributions and community dynamics. In 2014 and 2017, we collected vegetation data along 31 T-shaped transects laid perpendicular to the railway line, adopting the MIREN (Mountain Invasion Research Network) road survey methodology. Plant communities shifted significantly from 2014 to 2017, potentially because of an ongoing species redistribution after railway construction, driven mainly by declines in both native and non-native species richness, and an increasing abundance of a few non-native species, especially in areas away from the railway track. These patterns indicate an advancing succession, where initially-rare-pioneer species are replaced by increasingly dominant and often non-native competitors, and potentially suggest a trend towards delayed local extinctions after the disturbance event. Native and non-native species richness was negatively correlated with elevation, but that relationship diminished over time, with the abundance of non-natives significantly increasing at higher elevations. Synthesis and applications. Transport corridors seem to facilitate the spread of non-native species to higher elevations, which has serious implications considering the warming mountain tops. Our results indicate that the plant communities next to railways do not reach equilibrium quickly after a disturbance. More than 10 years after railway establishment within Kashmir Himalaya, succession continued, and signs pointed towards a landscape increasingly dominated by non-native species. Our study indicates that the single disturbance event associated with constructing railway in this Himalayan region had large and long-lasting effects on plant communities at and around this transport corridor and suggests the need for a long-term region-wide coordinated monitoring and management program.

While all sectors of the economy can be impacted by climate variability and change, the agricultural sector is arguably the most tightly coupled to climate where changes in precipitation and temperature directly control plant growth and yield, as well as livestock production. This paper analyzes the direct and cascading effects of temperature, precipitation, and carbon dioxide (CO2) on agronomic and horticultural crops, and livestock production in Indiana through 2100. Due to increased frequency of drought and heat stress, models predict that the yield of contemporary corn and soybean varieties will decline by 8–21% relative to yield potential, without considering CO2 enhancement, which may offset soybean losses. These losses could be partially compensated by adaptation measures such as changes in cropping systems, planting date, crop genetics, soil health, and providing additional water through supplemental irrigation or drainage management. Changes in winter conditions will pose a threat to some perennial crops, including tree and fruit crops, while shifts in the USDA Hardiness Zone will expand the area suitable for some fruits. Heat stress poses a major challenge to livestock production, with decreased feed intake expected with temperatures exceeding 29 °C over 100 days per year by the end of the century. Overall, continued production of commodity crops, horticultural crops, and livestock in Indiana is expected to continue with adaptations in management practice, cultivar or species composition, or crop rotation.

The Indiana Climate Change Impacts Assessment (IN CCIA) is a collaborative effort to provide professionals, decision makers, and the public with information about how climate change affects state and local interests throughout Indiana, USA. This assessment effort has three interrelated goals: (1) analyze and document the best available climate change impacts research, (2) develop and maintain a network of stakeholders and experts, and (3) start a dialog about climate change throughout Indiana. The project adopted a process that prioritized stakeholder engagement, re-envisioned traditional dissemination approaches, and that had limited state government involvement, setting the IN CCIA apart from most other state climate assessments (SCAs) in the USA. This overview describes the motivations, principles, and processes that guided the IN CCIA development, explores how Indiana’s approach compares with those of other SCAs, and briefly summarizes the papers presented in this special issue. As interest in SCAs grows in non-coastal and politically conservative locations, the IN CCIA serves as one example of how a bottom-up assessment with limited funding can deliver credible climate science to diverse stakeholder groups in the absence of state-level mandates or direction and attract public attention over an extended period of time.

As Earth’s climate rapidly changes, species range shifts are considered key to species persistence. However, some range-shifting species will alter community structure and ecosystem processes. By adapting existing invasion risk assessment frameworks, we can identify characteristics shared with high-impact introductions and thus predict potential impacts. There are fundamental differences between introduced and range-shifting species, primarily shared evolutionary histories between range shifters and their new community. Nevertheless, impacts can occur via analogous mechanisms, such as wide dispersal, community disturbance and low biotic resistance. As ranges shift in response to climate change, we have an opportunity to develop plans to facilitate advantageous movements and limit those that are problematic. Climate change will cause species to shift their ranges to persist. This Review uses invasion ecology theory to consider the impacts of shifting species and how to manage these shifts to protect the recipient communities as well as the survival of the shifters.

Human-induced abiotic global environmental changes (GECs) and the spread of nonnative invasive species are rapidly altering ecosystems. Understanding the relative and interactive effects of invasion and GECs is critical for informing ecosystem adaptation and management, but this information has not been synthesized. We conducted a meta-analysis to investigate effects of invasions, GECs, and their combined influences on native ecosystems. We found 458 cases from 95 published studies that reported individual and combined effects of invasions and a GEC stressor, which was most commonly warming, drought, or nitrogen addition. We calculated standardized effect sizes (Hedges’ d) for individual and combined treatments and classified interactions as additive (sum of individual treatment effects), antagonistic (smaller than expected), or synergistic (outside the expected range). The ecological effects of GECs varied, with detrimental effects more likely with drought than the other GECs. Invasions were more strongly detrimental, on average, than GECs. Invasion and GEC interactions were mostly antagonistic, but synergistic interactions occurred in >25% of cases and mostly led to more detrimental outcomes for ecosystems. While interactive effects were most often smaller than expected from individual invasion and GEC effects, synergisms were not rare and occurred across ecological responses from the individual to the ecosystem scale. Overall, interactions between invasions and GECs were typically no worse than the effects of invasions alone, highlighting the importance of managing invasions locally as a crucial step toward reducing harm from multiple global changes.

Researchers use both experiments and observations to study the impacts of climate change on ecosystems, but results from these contrasting approaches have not been systematically compared for droughts. Using a meta-analysis and accounting for potential confounding factors, we demonstrate that aboveground biomass responded only about half as much to experimentally imposed drought events as to natural droughts. Our findings indicate that experimental results may underestimate climate change impacts and highlight the need to integrate results across approaches. In a meta-analysis comparing experimental versus observational studies of aboveground biomass responses to drought in grasslands, the authors show that effect sizes in experiments are 53% weaker than in observational studies, suggesting that experiments are underestimating drought responses.

The degree to which elevated CO

The degree to which elevated CO2 concentrations (e[CO2]) increase the amount of carbon (C) assimilated by vegetation plays a key role in climate change. However, due to the short-term nature of CO2 enrichment experiments and the lack of reconciliation between different ecological scales, the effect of e[CO2] on plant biomass stocks remains a major uncertainty in future climate projections. Here, we review the effect of e[CO2] on plant biomass across multiple levels of ecological organization, scaling from physiological responses to changes in population-, community-, ecosystem-, and global-scale dynamics. We find that evidence for a sustained biomass response to e[CO2] varies across ecological scales, leading to diverging conclusions about the responses of individuals, populations, communities, and ecosystems. While the distinct focus of every scale reveals new mechanisms driving biomass accumulation under e[CO2], none of them provides a full picture of all relevant processes. For example, while physiological evidence suggests a possible long-term basis for increased biomass accumulation under e[CO2] through sustained photosynthetic stimulation, population-scale evidence indicates that a possible e[CO2]-induced increase in mortality rates might potentially outweigh the effect of increases in plant growth rates on biomass levels. Evidence at the global scale may indicate that e[CO2] has contributed to increased biomass cover over recent decades, but due to the difficulty to disentangle the effect of e[CO2] from a variety of climatic and land-use-related drivers of plant biomass stocks, it remains unclear whether nutrient limitations or other ecological mechanisms operating at finer scales will dampen the e[CO2] effect over time. By exploring these discrepancies, we identify key research gaps in our understanding of the effect of e[CO2] on plant biomass and highlight the need to integrate knowledge across scales of ecological organization so that large-scale modeling can represent the finer-scale mechanisms needed to constrain our understanding of future terrestrial C storage.

Climatic extreme events are expected to occur more frequently and potentially be stronger in the future, increasing the likelihood of unprecedented climate extremes (UCEs), or record-breaking events such as prolonged droughts, to occur. To prepare for UCEs and their impacts, we need to develop a better understanding of terrestrial ecosystem responses to events such as extreme drought. We know that intense, extreme droughts can substantially affect ecosystem stability and carbon cycling through increased plant mortality and delaying ecosystem recovery. Our ability to predict such effects is limited due to the lack of experiments focusing on climatic excursions beyond the range of historical experience.We explore the response of forest ecosystems to UCEs using two dynamic vegetation demographic models (VDMs), ED2 and LPJ-GUESS, in which the abundances of different plant functional types, as well as tree size- and age-class structure, are emergent properties of resource competition. We investigate the hypothesis that ecosystem responses to UCEs (e.g., unprecedented droughts) cannot be extrapolated from ecosystem responses to milder extremes, as a result of non-linear ecosystem responses (e.g. due to plant plasticity, functional diversity, and trait combinations). We evaluate each model’s mechanisms and state variables prior, during, and after a continuum of drought intensities ultimately reaching very extreme drought scenarios (i.e., 0% to 100% reduction in precipitation for drought durations of 1-year, 2-year, and 4-year scenarios) at two dry forested sites: Palo Verde, Costa Rica (i.e. tropical) and EucFACE, Australia (i.e. temperate). Both models produce nonlinear responses to these UCEs. Due to differences in model structure and process representation, the model’s sensitivity of biomass loss diverged based on either duration or intensity of droughts, as well as different model responses at each site. Biomass losses in ED2 are sensitive to drought duration, while in LPJ-GUESS they are mainly driven by drought intensity. Elevated atmospheric CO2 concentrations alone did not buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight discrepancies in process formulations and uncertainties in models, notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes. This shows that different hypotheses of plant responses to UCEs exist in two similar models, reflecting knowledge gaps, which should be tested with gap-informed field experiments. This iterative modeling-experiment framework would help improve predictions of terrestrial ecosystem responses and climate feedbacks.

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. National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31430015, 31830012]; US NSFNational Science Foundation (NSF) [DEB-0955771]; ClimMani COST actionEuropean Cooperation in Science and Technology (COST) [ES1308] We thank J. Wang (Hebei University), S. Yang (Institute of Botany, Chinese Academy of Sciences), L. Zhou (East China Normal University), C. Qiao (Xinyang Normal University) and H. Li (Henan University) for their help in meta-analyses and interaction analyses, and H. Li, Y. Liu (Institute of Tibetan Plateau Research, Chinese Academy of Sciences) and Y. He (Peking University) for their help in plotting figures. This work was financially supported by the National Natural Science Foundation of China (grant nos. 31430015 and 31830012). This study emerged from the INTERFACE Workshop in Beijing, China (https://www.bio.purdue.edu/INTERFACE/) supported by the US NSF DEB-0955771. We also acknowledge support from the ClimMani COST action (ES1308). Public domain – authored by a U.S. government employee

In this chapter, we describe current understanding of and identify research gaps on how invasive species directly, and indirectly, affect ecosystem processes. Specifically, we focus on how invasive species can alter the terrestrial carbon, nitrogen, and hydrologic cycles and how changes to these terrestrial cycles cascade to affect water quantity and quality. While invasive species may alter other ecosystem processes, we focus on these due to their importance to policy, to the public, and to their likely interaction with climate change effects. For example, carbon sequestration and surface water supply originating from forests and grasslands (Caldwell et al. 2014) are important policy and public concerns, and drought frequency and intensity will likely increase with climate change (Vose et al. 2016a). Our goal is to draw generalizations rather than provide details on invasive species effects on a case-by-case basis. We do, however, provide case studies for illustration and draw linkages with other chapters that provide detailed coverage to disturbance regimes (Chap. 5) and types and mechanisms of ecological impact caused by invasive insects (Chap. 2).

Crops worldwide are simultaneously affected by weeds, which reduce yield, and by climate change, which can negatively or positively affect both crop and weed species. While the individual effects of environmental change and of weeds on crop yield have been assessed, the combined effects have not been broadly characterized. To explore the simultaneous impacts of weeds with changes in climate-related environmental conditions on future food production, we conducted a meta-analysis of 171 observations measuring the individual and combined effects of weeds and elevated CO2, drought or warming on 23 crop species. The combined effect of weeds and environmental change tended to be additive. On average, weeds reduced crop yield by 28%, a value that was not significantly different from the simultaneous effect of weeds and environmental change (27%), due to increased variability when acting together. The negative effect of weeds on crop yield was mitigated by elevated CO2 and warming, but added to the negative effect of drought. The impact of weeds with environmental change was also dependent on the photosynthetic pathway of the weed/crop pair and on crop identity. Native and non-native weeds had similarly negative effects on yield, with or without environmental change. Weed impact with environmental change was also independent of whether the crop was infested with a single or multiple weed species. Since weed impacts remain negative under environmental change, our results highlight the need to evaluate the efficacy of different weed management practices under climate change. Understanding that the effects of environmental change and weeds are, on average, additive brings us closer to developing useful forecasts of future crop performance

Mean surface temperatures have increased globally by ~0.7 °C per century since 1900 and 0.16 °C per decade since 1970 (Levinson and Fettig 2014). Most of this warming is believed to result from increases in atmospheric concentrations of greenhouse gases produced by human activity. Temperature increases have been greater in winter than in summer, and there is a tendency for these increases to be manifested mainly by changes in minimum (nighttime low) temperatures (Kukla and Karl 1993). Changes in precipitation patterns have also been observed, but are more variable than those of temperature. Even under conservative emission scenarios, future climatic changes are likely to include further increases in temperature with significant drying (drought) in some regions and increases in the frequency and severity of extreme weather events (IPCC 2007). For example, multimodel means of annual temperature from climate projections predict an increase of 3–9 °C in the United States over the next century combined with reductions in summer precipitation in certain areas (Walsh et al. 2014). These changes will affect invasive species in several ways. Furthermore, climate change may challenge the way we perceive and consider nonnative invasive species, as impacts to some will change and others will remain unaffected; other nonnative species are likely to become invasive; and native species are likely to shift their geographic ranges into novel habitats.

Past research has shown that plants possess the capacity to alter their instantaneous response of photosynthesis to temperature in response to a longer-term change in temperature (i.e. acclimate). This acclimation is typically the result of processes that influence net photosynthesis (Anet), including leaf biochemical processes such as the maximum rate of Rubisco carboxylation (Vcmax) and the maximum rate of photosynthetic electron transport (Jmax), stomatal conductance (gs) and dark respiration (Rd). However, these processes are rarely examined in the field or in concert with other environmental factors, such as precipitation amount. Here, we use a fully factorial warming (active heating up to +4 °C; mean = +3.1 °C) by precipitation (−50 % ambient to 150 % ambient) manipulation experiment in an old-field ecosystem in the north-eastern USA to examine the degree to which Ulmus americana saplings acclimate through biochemical and stomatal adjustments. We found that rates of Anet at ambient CO2 levels of 400 µmol mol−1 (A400) did not differ across climate treatments or with leaf temperatures from 20 to 30 °C. Canopy temperatures rarely reached above 30 °C in any treatment, suggesting that seasonal carbon assimilation was relatively homeostatic across all treatments. Assessments of the component processes of A400 revealed that decreases in gs with leaf temperature from 20 to 30 °C were balanced by increases in Vcmax, resulting in stable A400 rates despite concurrent increases in Rd. Photosynthesis was not affected by precipitation treatments, likely because the relatively dry year led to small treatment effects on soil moisture. As temperature acclimation is likely to come at a cost to the plant via resource reallocation, it may not benefit plants to acclimate to warming in cases where warming would not otherwise reduce assimilation. These results suggest that photosynthetic temperature acclimation to future warming will be context-specific and that it is important to consider assimilatory benefit when assessing acclimation responses.

Contents Summary 52 I. Introduction 52 II. The Community Response to Extreme Drought (CRED) framework 55 III. Post-drought rewetting rates: system and community recovery 61 IV. Site-specific characteristics influencing community resistance and resilience 63 V. Conclusions 64 Acknowledgements 65 References 66 SUMMARY: 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.

This paper is the result of the INTERnational Conference on AtMosphere–BIOsphere Interactions (INTERCAMBIO), held in Medellin, Colombia, in October–November 2016. INTERCAMBIO was funded by Universidad de Antioquia, Universidad Eafit, the Purdue Research Foundation (PRF), ICETEX, the Purdue Climate Change Research Center (PCCRC), the Colombia–Purdue Initiative (CPI), and the Colombian Student Association at Purdue (CSAP). Partial funding for JCV, JFS, AMR, PAA, DM‐B, and JAP was provided by Colciencias through “Programa de investigacion en la gestion de riesgo asociado con cambio climatico y ambiental en cuencas hidrograficas” convocatoria 543‐2011. Funding for LM was provided by the Ayudar Foundation from the UK University of Exeter's College Benefactors. Partial support for JSD was provided by the US Department of Agriculture's National Institute of Food and Agriculture, through Hatch project 1000026.

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.

Recent work suggests that metabolic activation and deactivation of microbes in soil strongly influences soil carbon (C) dynamics and climate feedbacks. However, few soil C models consider these transitions. We hypothesized that microbes’ capacity to enter and exit dormancy in response to unfavorable and favorable environmental conditions decreases the sensitivity of microbial biomass and cumulative respiration to environmental stress. To test this hypothesis, we collected data from a rewetting experiment and used it to design and parameterize dormancy in an existing microbe-based soil C model. Then we compared predictions of microbial biomass and soil heterotrophic respiration (RH) under simulated cycles of stressful (dryness) and favorable (wet pulses) conditions. Because the influence of moisture on microbial processes in soil generally depends on temperature, we collected data and tested predictions at different temperatures. When dormancy was not taken into account, simulated microbial biomass and cumulative microbial respiration over five years were lower and decreased faster under lengthening drying-wetting cycles. Differences due to dormancy increased with temperature and with the length of the dry periods between wetting events. We conclude that ignoring both the capacity of microbes to enter and exit dormancy in response to the environment and the consequences of these metabolic responses for soil C cycling results in predictions of unrealistically low RH under warming and drying-wetting cycles.

In the face of ongoing and projected precipitation changes, precipitation manipulation experiments (PMEs) have produced a wealth of data about the effects of precipitation changes on soils. In response, researchers have undertaken a number of synthetic efforts. Several meta-analyses have been conducted, each revealing new aspects of soil responses to precipitation changes. We synthesize the findings of 16 meta-analyses focused on the effects of decreased and increased precipitation on 42 soil response variables, covering a wide range of soil processes and examining responses of individual variables as well as more integrative responses of carbon and nitrogen cycles. We found a strong agreement among meta-analyses that decreased and increased precipitation inhibits and promotes belowground carbon and nitrogen cycling, respectively, while microbial communities are relatively resistant to precipitation changes. Much attention has been paid to fluxes and pools in carbon, nitrogen, and phosphorus cycles, such as gas emissions, soil carbon, soil phosphorus, extractable nitrogen ions, and biomass, but the rates of processes underlying these variables are less frequently covered in meta-analytic studies (e.g., rates of mineralization, fixation, and de/nitrification). Shifting scientific attention to these “processes” would, therefore, deepen the current understanding of the effects of precipitation changes on soil and provide new insights. By comparing meta-analyses focused on different variables, we provide here a quantitative and holistic view of soil responses to changes in precipitation.

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 °C. To assess acclimation, we measured instantaneous tissue temperature response curves (14–50 °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., Our study found that temperature acclimation of respiration differs by tissue type (i.e. leaves, stems and roots). Tissue that does not photosynthesize was found to have more homeostatic responses to temperature than photosynthetic tissue. This was found due to the strong linkage between photosynthetic biochemistry and respiration fluxes. These results suggest that plant respiratory responses to changing temperatures, such as future warming, will be tissue type-specific. The link to photosynthesis found in our study provides an avenue for improving the representation of these responses in carbon cycle models.

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.

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.

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° Celsius degrees (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°Celsius degrees (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2° Celsius degrees (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.