Why Coordinated Distributed Experiments Should Go Global

The performance of coordinated distributed experiments designed to compare ecosystem sensitivity to global-change drivers depends on whether they cover a significant proportion of the global range of environmental variables. In the present article, we described the global distribution of climatic and soil variables and quantified main differences among continents. Then, as a test case, we assessed the representativeness of the International Drought Experiment (IDE) in parameter space. Considering the global environmental variability at this scale, the different continents harbor unique combinations of parameters. As such, coordinated experiments set up across a single continent may fail to capture the full extent of global variation in climate and soil parameter space. IDE with representation on all continents has the potential to address global scale hypotheses about ecosystem sensitivity to environmental change. Our results provide a unique vision of climate and soil variability at the global scale and highlight the need to design globally distributed networks.

A meta-epidemiological study of bias in randomized clinical trials of open and laparoscopic surgery

BACKGROUND

Blinding, random sequence generation, and allocation concealment are established strategies to minimize bias in RCTs. Meta-epidemiological studies of drug trials have demonstrated exaggerated treatment effects in RCTs where such methods were not employed. As blinding is more difficult in surgical trials it is important to determine whether this applies to them. The study aimed to investigate this using systematic meta-epidemiological methods.

METHOD

The Cochrane Database of Systematic Reviews was searched for systematic reviews of RCTs that compared laparoscopic and open abdominal surgical procedures. Each review was then scrutinized to determine whether at least one of the included trials was blinded. Eligible reviews were updated and individual RCTs retrieved. Extracted data included the primary outcomes of interest (length of stay and complications), secondary outcomes and a risk of bias assessment. A multistep meta-regression analysis was then performed to obtain an overall difference in the reported outcome differences between trials that employed each bias-minimization strategy, and those that did not.

RESULTS

Some 316 RCTs were included, reporting on eight different procedures. Patient-blinded RCTs reported a smaller difference in length of stay between laparoscopic and open groups (difference of standardized mean differences -0·36 (95 per cent c.i. -0·73 to 0·00)) and complications (ratio of odds ratios 0·76 (95 per cent c.i. 0·61 to 0·93)). Blinding of postoperative carers and outcome assessors had similar effects.

CONCLUSION

Lack of blinding significantly altered the treatment effect estimates of RCTs comparing laparoscopic and open surgery. Blinding should be implemented in surgical RCTs where possible to avoid systematic bias.

Precipitation-productivity relationships and the duration of precipitation anomalies: An underappreciated dimension of climate change

In terrestrial ecosystems, climate change forecasts of increased frequencies and magnitudes of wet and dry precipitation anomalies are expected to shift precipitation-net primary productivity (PPT-NPP) relationships from linear to nonlinear. Less understood, however, is how future changes in the duration of PPT anomalies will alter PPT-NPP relationships. A review of the literature shows strong potential for the duration of wet and dry PPT anomalies to impact NPP and to interact with the magnitude of anomalies. Within semi-arid and mesic grassland ecosystems, PPT gradient experiments indicate that short-duration (1 year) PPT anomalies are often insufficient to drive nonlinear aboveground NPP responses. But long-term studies, within desert to forest ecosystems, demonstrate how multi-year PPT anomalies may result in increasing impacts on NPP through time, and thus alter PPT-NPP relationships. We present a conceptual model detailing how NPP responses to PPT anomalies may amplify with the duration of an event, how responses may vary in xeric vs. mesic ecosystems, and how these differences are most likely due to demographic mechanisms. Experiments that can unravel the independent and interactive impacts of the magnitude and duration of wet and dry PPT anomalies are needed, with multi-site long-term PPT gradient experiments particularly well-suited for this task.

Is a drought a drought in grasslands? Productivity responses to different types of drought

Drought, defined as a marked deficiency of precipitation relative to normal, occurs as periods of below-average precipitation or complete failure of precipitation inputs, and can be limited to a single season or prolonged over multiple years. Grasslands are typically quite sensitive to drought, but there can be substantial variability in the magnitude of loss of ecosystem function. We hypothesized that differences in how drought occurs may contribute to this variability. In four native Great Plains grasslands (three C₄- and one C₃-dominated) spanning a ~ 500-mm precipitation gradient, we imposed drought for four consecutive years by (1) reducing each rainfall event by 66% during the growing season (chronic drought) or (2) completely excluding rainfall during a shorter portion of the growing season (intense drought). The drought treatments were similar in magnitude but differed in the following characteristics: event number, event size and length of dry periods. We observed consistent drought-induced reductions (28-37%) in aboveground net primary production (ANPP) only in the C₄-dominated grasslands. In general, intense drought reduced ANPP more than chronic drought, with little evidence that drought duration altered this pattern. Conversely, belowground net primary production (BNPP) was reduced by drought in all grasslands (32-64%), with BNPP reductions greater in intense vs. chronic drought treatments in the most mesic grassland. We conclude that grassland productivity responses to drought did not strongly differ between these two types of drought, but when differences existed, intense drought consistently reduced function more than chronic drought.

Temporal variability in production is not consistently affected by global change drivers across herbaceous-dominated ecosystems

Understanding how global change drivers (GCDs) affect aboveground net primary production (ANPP) through time is essential to predicting the reliability and maintenance of ecosystem function and services in the future. While GCDs, such as drought, warming and elevated nutrients, are known to affect mean ANPP, less is known about how they affect inter-annual variability in ANPP. We examined 27 global change experiments located in 11 different herbaceous ecosystems that varied in both abiotic and biotic conditions, to investigate changes in the mean and temporal variability of ANPP (measured as the coefficient of variation) in response to different GCD manipulations, including resource additions, warming, and irrigation. From this comprehensive data synthesis, we found that GCD treatments increased mean ANPP. However, GCD manipulations both increased and decreased temporal variability of ANPP (24% of comparisons), with no net effect overall. These inconsistent effects on temporal variation in ANPP can, in part, be attributed to site characteristics, such as mean annual precipitation and temperature as well as plant community evenness. For example, decreases in temporal variability in ANPP with the GCD treatments occurred in wetter and warmer sites with lower plant community evenness. Further, the addition of several nutrients simultaneously increased the sensitivity of ANPP to interannual variation in precipitation. Based on this analysis, we expect that GCDs will likely affect the magnitude more than the reliability over time of ecosystem production in the future.

Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models

Process-based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass-dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C₃ grasses and (sub)tropical C₄ grasses. Incorporation of species-level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), situated between species-level trait data and PFT-level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

We present a supercomputer-driven pipeline for in-silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. We also describe preliminary results obtained for 23 systems involving eight protein targets of the proteome of SARS CoV-2. THe MD performed is temperature replica-exchange enhanced sampling, making use of the massively parallel supercomputing on the SUMMIT supercomputer at Oak Ridge National Laboratory, with which more than 1ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to ten configurations of each of the 23 SARS CoV-2 systems using AutoDock Vina. We also demonstrate that using Autodock-GPU on SUMMIT, it is possible to perform exhaustive docking of one billion compounds in under 24 hours. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and AI methods to cluster MD trajectories and rescore docking poses.

Genetic and functional variation across regional and local scales is associated with climate in a foundational prairie grass

Global change forecasts in ecosystems require knowledge of within-species diversity, particularly of dominant species within communities. We assessed site-level diversity and capacity for adaptation in Bouteloua gracilis, the dominant species in the Central US shortgrass steppe biome. We quantified genetic diversity from 17 sites across regional scales, north to south from New Mexico to South Dakota, and local scales in northern Colorado. We also quantified phenotype and plasticity within and among sites and determined the extent to which phenotypic diversity in B. gracilis was correlated with climate. Genome sequencing indicated pronounced population structure at the regional scale, and local differences indicated that gene flow and/or dispersal may also be limited. Within a common environment, we found evidence of genetic divergence in biomass-related phenotypes, plasticity, and phenotypic variance, indicating functional divergence and different adaptive potential. Phenotypes were differentiated according to climate, chiefly median Palmer Hydrological Drought Index and other aridity metrics. Our results indicate conclusive differences in genetic variation, phenotype, and plasticity in this species and suggest a mechanism explaining variation in shortgrass steppe community responses to global change. This analysis of B. gracilis intraspecific diversity across spatial scales will improve conservation and management of the shortgrass steppe ecosystem in the future.

Weak latitudinal gradients in insect herbivory for dominant rangeland grasses of North America

Patterns of insect herbivory may follow predictable geographical gradients, with greater herbivory at low latitudes. However, biogeographic studies of insect herbivory often do not account for multiple abiotic factors (e.g., precipitation and soil nutrients) that could underlie gradients. We tested for latitudinal clines in insect herbivory as well as climatic, edaphic, and trait-based drivers of herbivory. We quantified herbivory on five dominant grass species over 23 sites across the Great Plains, USA. We examined the importance of climate, edaphic factors, and traits as correlates of herbivory. Herbivory increased at low latitudes when all grass species were analyzed together and for two grass species individually, while two other grasses trended in this direction. Higher precipitation was related to more herbivory for two species but less herbivory for a different species, while higher specific root length was related to more herbivory for one species and less herbivory for a different species. Taken together, results highlight that climate and trait-based correlates of herbivory can be highly contextual and species-specific. Patterns of insect herbivory on dominant grasses support the hypothesis that herbivory increases toward lower latitudes, though weakly, and indicates that climate change may have species-specific effects on plant-herbivore interactions.

Author Correction: Leaf nutrients, not specific leaf area, are consistent indicators of elevated nutrient inputs

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Divergent interactive impacts on productivity and functional diversity from fluctuated snowfall and continuous nitrogen pollution within Inner Mongolian

Nitrogen pollution effects on plant communities are well documented, however, most field researches on nitrogen pollution have failed to account for extraneous environmental factors and the interaction among changes in multiple stressors. In this study, we show the effect of eutrophication via nitrogen deposition and altered snowfall on the productivity and traits space of an Inner Mongolian grassland where is recovered from abandoned farmland for 13 years. This multi-year factorial experiment allowed us to test the independent and interactive effects of nitrogen and snow deposition within this ecosystem. We simulated nitrogen pollution (added nitrogen) and extremely snowfall (added snow) to each plot for three years. After the third year, only nitrogen was added for the next two years to keep a continuous N-pollution condition. We measured changes in aboveground net primary production (ANPP), occupied functional traits space (OFS), and the centroid range of OFS (spatial traits variability, STV) at community level. Our results showed that the interaction between continuous nitrogen pollution and fluctuated snow have different effects on ANPP and functional diversity (indicated by OFS and STV). In nitrogen and nitrogen combined with snow treatment, its ANPP increased, while its OFS increased in 2010 but decreased in 2012 and 2014. Increases in snow did not affect ANPP and OFS, but significantly impacted spatial traits variability. Snow addition corresponded with decreasing the spatial traits variability in 2010, followed by increasing in 2012 and 2014. The results indicate N-Pollution on grassland ecosystem cannot be interpreted only by ANPP, especially when N-pollution interacted with changes of other extremely stressors such as snowfall.

Rapid recovery of ecosystem function following extreme drought in a South African savanna grassland

Climatic extremes, such as severe drought, are expected to increase in frequency and magnitude with climate change. Thus, identifying mechanisms of resilience is critical to predicting the vulnerability of ecosystems. An exceptional drought (<first percentile) impacted much of southern Africa during the 2015 and 2016 growing seasons, including the site of a long-term fire experiment in Kruger National Park, South Africa. Prior to the drought, experimental fire frequencies (annual, triennial, and unburned) created savanna grassland plant communities that differed in composition and function, providing a unique opportunity to assess ecosystem resilience mechanisms under different fire regimes. Surprisingly, aboveground net primary productivity (ANPP) recovered fully in all fire frequencies the year after this exceptional drought. In burned sites, resilience was due mostly to annual forb ANPP compensating for reduced grass ANPP. In unburned sites, resilience of total and grass ANPP was due to subdominant annual and perennial grass species facilitating recovery in ANPP after mortality of other common grasses. This was possible because of high evenness among grass species in unburned sites predrought. These findings highlight the importance of both functional diversity and within-functional group evenness as mechanisms of ecosystem resilience to extreme drought.

Precipitation amount and event size interact to reduce ecosystem functioning during dry years in a mesic grassland

Ongoing intensification of the hydrological cycle is altering rainfall regimes by increasing the frequency of extreme wet and dry years and the size of individual rainfall events. Despite long-standing recognition of the importance of precipitation amount and variability for most terrestrial ecosystem processes, we lack understanding of their interactive effects on ecosystem functioning. We quantified this interaction in native grassland by experimentally eliminating temporal variability in growing season rainfall over a wide range of precipitation amounts, from extreme wet to dry conditions. We contrasted the rain use efficiency (RUE) of above-ground net primary productivity (ANPP) under conditions of experimentally reduced versus naturally high rainfall variability using a 32-year precipitation-ANPP dataset from the same site as our experiment. We found that increased growing season rainfall variability can reduce RUE and thus ecosystem functioning by as much as 42% during dry years, but that such impacts weaken as years become wetter. During low precipitation years, RUE is lowest when rainfall event sizes are relatively large, and when a larger proportion of total rainfall is derived from large events. Thus, a shift towards precipitation regimes dominated by fewer but larger rainfall events, already documented over much of the globe, can be expected to reduce the functioning of mesic ecosystems primarily during drought, when ecosystem processes are already compromised by low water availability.

How ecologists define drought, and why we should do better

Drought, widely studied as an important driver of ecosystem dynamics, is predicted to increase in frequency and severity globally. To study drought, ecologists must define or at least operationalize what constitutes a drought. How this is accomplished in practice is unclear, particularly given that climatologists have long struggled to agree on definitions of drought, beyond general variants of "an abnormal deficiency of water." We conducted a literature review of ecological drought studies (564 papers) to assess how ecologists describe and study drought. We found that ecologists characterize drought in a wide variety of ways (reduced precipitation, low soil moisture, reduced streamflow, etc.), but relatively few publications (~32%) explicitly define what are, and are not, drought conditions. More troubling, a surprising number of papers (~30%) simply equated "dry conditions" with "drought" and provided little characterization of the drought conditions studied. For a subset of these, we calculated Standardized Precipitation Evapotranspiration Index values for the reported drought periods. We found that while almost 90% of the studies were conducted under conditions quantifiable as slightly to extremely drier than average, ~50% were within the range of normal climatic variability. We conclude that the current state of the ecological drought literature hinders synthesis and our ability to draw broad ecological inferences because drought is often declared but is not explicitly defined or well characterized. We suggest that future drought publications provide at least one of the following: (a) the climatic context of the drought period based on long-term records; (b) standardized climatic index values; (c) published metrics from drought-monitoring organizations; (d) a quantitative definition of what the authors consider to be drought conditions for their system. With more detailed and consistent quantification of drought conditions, comparisons among studies can be more rigorous, increasing our understanding of the ecological effects of drought.

Asymmetry in above- and belowground productivity responses to N addition in a semi-arid temperate steppe

Nitrogen (N) enrichment often increases aboveground net primary productivity (ANPP) of the ecosystem, but it is unclear if belowground net primary productivity (BNPP) track responses of ANPP. Moreover, the frequency of N inputs may affect primary productivity but is rarely studied. To assess the response patterns of above- and belowground productivity to rates of N addition under different addition frequencies, we manipulated the rate (0-50 g N m^-2  year^-1 ) and frequency (twice vs. monthly additions per year) of NH₄ NO₃ inputs for six consecutive years in a temperate grassland in northern China and measured ANPP and BNPP from 2012 to 2014. In the low range of N addition rates, BNPP showed the greatest negative response and ANPP showed the greatest positive responses with increases in N addition (<10 g N m^-2  year^-1 ). As N addition increased beyond 10 g N m^-2  year^-1 , increases in ANPP dampened and decreases in BNPP ceased altogether. The response pattern of net primary productivity (combined above- and belowground; NPP) corresponded more closely to ANPP than to BNPP. The N effects on BNPP and BNPP/NPP (f_BNPP ) were not dependent on N addition frequency in the range of N additions typically associated with N deposition. BNPP was more sensitive to N addition frequency than ANPP, especially at low rates of N addition. Our findings provide new insights into how plants regulate carbon allocation to different organs with increasing N rates and changing addition frequencies. These root response patterns, if incorporated into Earth system models, may improve the predictive power of C dynamics in dryland ecosystems in the face of global atmospheric N deposition.

Demystifying dominant species

The pattern of a few abundant species and many rarer species is a defining characteristic of communities worldwide. These abundant species are often referred to as dominant species. Yet, despite their importance, the term dominant species is poorly defined and often used to convey different information by different authors. Based on a review of historical and contemporary definitions we develop a synthetic definition of dominant species. This definition incorporates the relative local abundance of a species, its ubiquity across the landscape, and its impact on community and ecosystem properties. A meta-analysis of removal studies shows that the loss of species identified as dominant by authors can significantly impact ecosystem functioning and community structure. We recommend two metrics that can be used jointly to identify dominant species in a given community and provide a roadmap for future avenues of research on dominant species. In our review, we make the case that the identity and effects of dominant species on their environments are key to linking patterns of diversity to ecosystem function, including predicting impacts of species loss and other aspects of global change on ecosystems.

Effects of the MY34/2018 Global Dust Storm as Measured by MSL REMS in Gale Crater

The Rover Environmental Monitoring Station (REMS) instrument that is onboard NASA's Mars Science Laboratory (MSL) Curiosity rover. REMS has been measuring surface pressure, air and ground brightness temperature, relative humidity, and UV irradiance since MSL's landing in 2012. In Mars Year (MY) 34 (2018) a global dust storm reached Gale Crater at L_s ~190°. REMS offers a unique opportunity to better understand the impact of a global dust storm on local environmental conditions, which complements previous observations by the Viking landers and Mars Exploration Rovers. All atmospheric variables measured by REMS are strongly affected albeit at different times. During the onset phase, the daily maximum UV radiation decreased by 90% between sols 2075 (opacity ~1) and 2085 (opacity ~8.5). The diurnal range in ground and air temperatures decreased by 35K and 56K, respectively, with also a diurnal-average decrease of ~2K and 4K respectively. The maximum relative humidity, which occurs right before sunrise, decreased to below 5%, compared with pre-storm values of up to 29%, due to the warmer air temperatures at night while the inferred water vapor abundance suggests an increase during the storm. Between sols 2085 and 2130, the typical nighttime stable inversion layer was absent near the surface as ground temperatures remained warmer than near-surface air temperatures. Finally, the frequency-domain behavior of the diurnal pressure cycle shows a strong increase in the strength of the semidiurnal and terdiurnal modes peaking after the local opacity maximum, also suggesting differences in the dust abundance inside and outside Gale.

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.

Semiarid ecosystem sensitivity to precipitation extremes: weak evidence for vegetation constraints

In semiarid regions, vegetation constraints on plant growth responses to precipitation (PPT) are hypothesized to place an upper limit on net primary productivity (NPP), leading to predictions of future shifts from currently defined linear to saturating NPP-PPT relationships as increases in both dry and wet PPT extremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing season PPT (GSP, n = 11 levels, n = 4 replicates), ranging from the driest to wettest conditions in the 75-yr climate record, within a semiarid grassland. We focused on responses of two key ecosystem processes: aboveground NPP (ANPP) and soil respiration (R_s ). ANPP and R_s both exhibited greater relative responses to wet vs. dry GSP extremes, with a linear relationship consistently best explaining the response of both processes to GSP. However, this responsiveness to GSP peaked at moderate levels of extremity for both processes, and declined at the most extreme GSP levels, suggesting that greater sensitivity of ANPP and R_s to wet vs. dry conditions may diminish under increased magnitudes of GSP extremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover as GSP transitioned to extreme wet conditions. This compositional shift increased the magnitude of ANPP responses to wet GSP extremes, as well as the slope and variability explained in the ANPP-GSP relationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes in GSP extremes.

Ambient changes exceed treatment effects on plant species abundance in global change experiments

The responses of species to environmental changes will determine future community composition and ecosystem function. Many syntheses of global change experiments examine the magnitude of treatment effect sizes, but we lack an understanding of how plant responses to treatments compare to ongoing changes in the unmanipulated (ambient or background) system. We used a database of long-term global change studies manipulating CO₂ , nutrients, water, and temperature to answer three questions: (a) How do changes in plant species abundance in ambient plots relate to those in treated plots? (b) How does the magnitude of ambient change in species-level abundance over time relate to responsiveness to global change treatments? (c) Does the direction of species-level responses to global change treatments differ from the direction of ambient change? We estimated temporal trends in plant abundance for 791 plant species in ambient and treated plots across 16 long-term global change experiments yielding 2,116 experiment-species-treatment combinations. Surprisingly, for most species (57%) the magnitude of ambient change was greater than the magnitude of treatment effects. However, the direction of ambient change, whether a species was increasing or decreasing in abundance under ambient conditions, had no bearing on the direction of treatment effects. Although ambient communities are inherently dynamic, there is now widespread evidence that anthropogenic drivers are directionally altering plant communities in many ecosystems. Thus, global change treatment effects must be interpreted in the context of plant species trajectories that are likely driven by ongoing environmental changes.