Extreme drought impacts have been underestimated in grasslands and shrublands globally.

Climate change is increasing the frequency and severity of short-term (~1 y) drought events-the most common duration of drought-globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function-aboveground net primary production (ANPP)-was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Global environmental changes more frequently offset than intensify detrimental effects of biological invasions.

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.

Land surface conductance linked to precipitation: Co-evolution of vegetation and climate in Earth system models.

Vegetation and precipitation are known to fundamentally influence each other. However, this interdependence is not fully represented in climate models because the characteristics of land surface (canopy) conductance to water vapor and CO2 are determined independently of precipitation. Working within a coupled atmosphere and land modelling framework (CAM6/CLM5; coupled Community Atmosphere Model v6/Community Land Model v5), we have developed a new theoretical approach to characterizing land surface conductance by explicitly linking its dynamic properties to local precipitation, a robust proxy for moisture available to vegetation. This will enable regional surface conductance characteristics to shift fluidly with climate change in simulations, consistent with general principles of co-evolution of vegetation and climate. Testing within the CAM6/CLM5 framework shows that climate simulations incorporating the new theory outperform current default configurations across several error metrics for core output variables when measured against observational data. In climate simulations for the end of this century the new, adaptive stomatal conductance scheme provides a revised prognosis for average and extreme temperatures over several large regions, with increased primary productivity through central and east Asia, and higher rainfall through North Africa and the Middle East. The new projections also reveal more frequent heatwaves than originally estimated for the south-eastern US and sub-Saharan Africa but less frequent heatwaves across east Europe and northeast Asia. These developments have implications for evaluating food security and risks from extreme temperatures in areas that are vulnerable to climate change.

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

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

Combining local, landscape, and regional geographies to assess plant community vulnerability to invasion impact.

Invasive species science has focused heavily on the invasive agent. However, management to protect native species also requires a proactive approach focused on resident communities and the features affecting their vulnerability to invasion impacts. Vulnerability is likely the result of factors acting across spatial scales, from local to regional, and it is the combined effects of these factors that will determine the magnitude of vulnerability. Here, we introduce an analytical framework that quantifies the scale-dependent impact of biological invasions on native richness from the shape of the native species-area relationship (SAR). We leveraged newly available, biogeographically extensive vegetation data from the U.S. National Ecological Observatory Network to assess plant community vulnerability to invasion impact as a function of factors acting across scales. We analyzed more than 1000 SARs widely distributed across the USA along environmental gradients and under different levels of non-native plant cover. Decreases in native richness were consistently associated with non-native species cover, but native richness was compromised only at relatively high levels of non-native cover. After accounting for variation in baseline ecosystem diversity, net primary productivity, and human modification, ecoregions that were colder and wetter were most vulnerable to losses of native plant species at the local level, while warmer and wetter areas were most susceptible at the landscape level. We also document how the combined effects of cross-scale factors result in a heterogeneous spatial pattern of vulnerability. This pattern could not be predicted by analyses at any single scale, underscoring the importance of accounting for factors acting across scales. Simultaneously assessing differences in vulnerability between distinct plant communities at local, landscape, and regional scales provided outputs that can be used to inform policy and management aimed at reducing vulnerability to the impact of plant invasions.

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.

Links across ecological scales: Plant biomass responses to elevated CO2.

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.

Community Response to Extreme Drought (CRED): a framework for drought-induced shifts in plant-plant interactions.

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.

Combined impacts of prolonged drought and warming on plant size and foliar chemistry.

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. METHODS: Plant size and metabolite profiles were assessed on naturally occurring Plantago lanceolata plants growing under different precipitation (ambient, 50 % less than ambient = drought) and temperature (ambient, +0.8, +2.4 and +4.0 °C above ambient) treatments at the Boston Area Climate Experiment (constructed in 2007). KEY RESULTS: The analysis of primary and secondary metabolites revealed pronounced effects of drought, and a precipitation × temperature interaction. Strikingly, the effects of precipitation were minimal at the two lower temperatures but marked at the two higher temperatures. Compared with the ambient condition, plants in the drought plots had lower concentrations of foliar nitrogen, amino acids and most sugars, and higher concentrations of sorbitol, citrate and malate, common stress-induced metabolites. This pattern was especially evident at high temperatures. Moreover, drought-exposed plants showed lower concentrations of catalpol, an iridoid glycoside. CONCLUSIONS: While the effect of warming on the metabolite profiles was less pronounced, differences were marked when combined with drought. Given the interactive effect of environmental variables on leaf chemistry, and the fact that woody and herbaceous plants seem to differ in their responses to temperature and precipitation, future studies should account for the direct and indirect effects of the community response to multifactorial field conditions.

Temperature response of soil respiration largely unaltered with experimental warming.

The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of ∼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.

Drivers of leaf carbon exchange capacity across biomes at the continental scale.

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.

A roadmap for improving the representation of photosynthesis in Earth system models.

Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO2 assimilation (A) to key environmental variables: light, temperature, CO2 concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models.

LCE: leaf carbon exchange data set for tropical, temperate, and boreal species of North and Central America.

Leaf canopy carbon exchange processes, such as photosynthesis and respiration, are substantial components of the global carbon cycle. Climate models base their simulations of photosynthesis and respiration on an empirical understanding of the underlying biochemical processes, and the responses of those processes to environmental drivers. As such, data spanning large spatial scales are needed to evaluate and parameterize these models. Here, we present data on four important biochemical parameters defining leaf carbon exchange processes from 626 individuals of 98 species at 12 North and Central American sites spanning ~53° of latitude. The four parameters are the maximum rate of Rubisco carboxylation (Vcmax ), the maximum rate of electron transport for the regeneration of Ribulose-1,5,-bisphosphate (Jmax ), the maximum rate of phosphoenolpyruvate carboxylase carboxylation (Vpmax ), and leaf dark respiration (Rd ). The raw net photosynthesis by intercellular CO2 (A/Ci ) data used to calculate Vcmax , Jmax , and Vpmax rates are also presented. Data were gathered on the same leaf of each individual (one leaf per individual), allowing for the examination of each parameter relative to others. Additionally, the data set contains a number of covariates for the plants measured. Covariate data include (1) leaf-level traits (leaf mass, leaf area, leaf nitrogen and carbon content, predawn leaf water potential), (2) plant-level traits (plant height for herbaceous individuals and diameter at breast height for trees), (3) soil moisture at the time of measurement, (4) air temperature from nearby weather stations for the day of measurement and each of the 90 d prior to measurement, and (5) climate data (growing season mean temperature, precipitation, photosynthetically active radiation, vapor pressure deficit, and aridity index). We hope that the data will be useful for obtaining greater understanding of the abiotic and biotic determinants of these important biochemical parameters and for evaluating and improving large-scale models of leaf carbon exchange.

Short-term acclimation to warmer temperatures accelerates leaf carbon exchange processes across plant types.

While temperature responses of photosynthesis and plant respiration are known to acclimate over time in many species, few studies have been designed to directly compare process-level differences in acclimation capacity among plant types. We assessed short-term (7 day) temperature acclimation of the maximum rate of Rubisco carboxylation (Vcmax ), the maximum rate of electron transport (Jmax ), the maximum rate of phosphoenolpyruvate carboxylase carboxylation (Vpmax ), and foliar dark respiration (Rd ) in 22 plant species that varied in lifespan (annual and perennial), photosynthetic pathway (C3 and C4 ), and climate of origin (tropical and nontropical) grown under fertilized, well-watered conditions. In general, acclimation to warmer temperatures increased the rate of each process. The relative increase in different photosynthetic processes varied by plant type, with C3 species tending to preferentially accelerate CO2 -limited photosynthetic processes and respiration and C4 species tending to preferentially accelerate light-limited photosynthetic processes under warmer conditions. Rd acclimation to warmer temperatures caused a reduction in temperature sensitivity that resulted in slower rates at high leaf temperatures. Rd acclimation was similar across plant types. These results suggest that temperature acclimation of the biochemical processes that underlie plant carbon exchange is common across different plant types, but that acclimation to warmer temperatures tends to have a relatively greater positive effect on the processes most limiting to carbon assimilation, which differ by plant type. The acclimation responses observed here suggest that warmer conditions should lead to increased rates of carbon assimilation when water and nutrients are not limiting.

Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years.

Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multiyear droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity, suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here, we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of 'Drought-Net', a relatively low-cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites - a common approach to standardization in CDEs. This is because precipitation variability varies >fivefold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process-level understanding of ecosystem sensitivity to precipitation extremes.

Rainfall variability counteracts N addition by promoting invasive Lonicera maackii and extending phenology in prairie.

Although encroaching woody plants have reduced the global extent of grasslands, continuing increases in soil nitrogen availability could slow this trend by favoring resident herbaceous species. At the same time, projected increases in rainfall variability could promote woody encroachment by aligning spatiotemporal patterns of soil moisture availability with the needs of woody species. We evaluated the responses of two deciduous woody species to these simulated environmental changes by planting seedlings of Quercus palustris and Lonicera maackii into tallgrass prairie communities grown under a factorial combination of increased rainfall variability and nitrogen addition. Lonicera maackii growth was reduced 20% by nitrogen addition, and increased rainfall variability led to 33% larger seedlings, despite greater competition for light and soil resources. In contrast, Q. palustris growth showed little response to either treatment. Increased rainfall variability allowed both species to retain their leaves for an additional 6.5 d in autumn, potentially in response to wetter end-of-season shallow soils. Our findings suggest increases in rainfall variability will counteract the inhibitory effect of nitrogen deposition on growth of L. maackii, extend autumn phenology, and promote the encroachment of some woody species into grasslands.

Global patterns and substrate-based mechanisms of the terrestrial nitrogen cycle.

Nitrogen (N) deposition is impacting the services that ecosystems provide to humanity. However, the mechanisms determining impacts on the N cycle are not fully understood. To explore the mechanistic underpinnings of N impacts on N cycle processes, we reviewed and synthesised recent progress in ecosystem N research through empirical studies, conceptual analysis and model simulations. Experimental and observational studies have revealed that the stimulation of plant N uptake and soil retention generally diminishes as N loading increases, while dissolved and gaseous losses of N occur at low N availability but increase exponentially and become the dominant fate of N at high loading rates. The original N saturation hypothesis emphasises sequential N saturation from plant uptake to soil retention before N losses occur. However, biogeochemical models that simulate simultaneous competition for soil N substrates by multiple processes match the observed patterns of N losses better than models based on sequential competition. To enable better prediction of terrestrial N cycle responses to N loading, we recommend that future research identifies the response functions of different N processes to substrate availability using manipulative experiments, and incorporates the measured N saturation response functions into conceptual, theoretical and quantitative analyses.

Rising atmospheric CO2 is reducing the protein concentration of a floral pollen source essential for North American bees.

At present, there is substantive evidence that the nutritional content of agriculturally important food crops will decrease in response to rising levels of atmospheric carbon dioxide, Ca However, whether Ca-induced declines in nutritional quality are also occurring for pollinator food sources is unknown. Flowering late in the season, goldenrod (Solidago spp.) pollen is a widely available autumnal food source commonly acknowledged by apiarists to be essential to native bee (e.g. Bombus spp.) and honeybee (Apis mellifera) health and winter survival. Using floral collections obtained from the Smithsonian Natural History Museum, we quantified Ca-induced temporal changes in pollen protein concentration of Canada goldenrod (Solidago canadensis), the most wide spread Solidago taxon, from hundreds of samples collected throughout the USA and southern Canada over the period 1842-2014 (i.e. a Ca from approx. 280 to 398 ppm). In addition, we conducted a 2 year in situtrial of S. Canadensis populations grown along a continuous Ca gradient from approximately 280 to 500 ppm. The historical data indicated a strong significant correlation between recent increases in Ca and reductions in pollen protein concentration (r(2)= 0.81). Experimental data confirmed this decrease in pollen protein concentration, and indicated that it would be ongoing as Ca continues to rise in the near term, i.e. to 500 ppm (r(2)= 0.88). While additional data are needed to quantify the subsequent effects of reduced protein concentration for Canada goldenrod on bee health and population stability, these results are the first to indicate that increasing Ca can reduce protein content of a floral pollen source widely used by North American bees.

Do maize models capture the impacts of heat and drought stresses on yield? Using algorithm ensembles to identify successful approaches.

Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models.