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At least 37 records · Page 2

Past and Future Drought in Mongolia

The severity of recent droughts in semiarid regions is increasingly attributed to anthropogenic climate change, but it is unclear whether these moisture anomalies exceed those of the past and how past variability compares to future projections. On the Mongolian Plateau, a recent decade-long drought that exceeded the variability in the instrumental record was associated with economic, social, and environmental change. We evaluate this drought using an annual reconstruction of the Palmer Drought Severity Index (PDSI) spanning the last 2060 years in concert with simulations of past and future drought through the year 2100 CE. We show that although the most recent drought and pluvial were highly unusual in the last 2000 years, exceeding the 900-year return interval in both cases, these events were not unprecedented in the 2060-year reconstruction, and events of similar duration and severity occur in paleoclimate, historical, and future climate simulations. The Community Earth System Model (CESM) ensemble suggests a drying trend until at least the middle of the 21st century, when this trend reverses as a consequence of elevated precipitation. Although the potential direct effects of elevated CO2 on plant water use efficiency exacerbate uncertainties about future hydroclimate trends, these results suggest that future drought projections for Mongolia are unlikely to exceed those of the last two millennia, despite projected warming.

drought projection↗

Evaluation of a Combined Drought Indicator Against Crop Yield Estimations and Simulations Over the Argentine Humid Pampas

Droughts pose serious threats to the agricultural sector, especially in rainfed-dominated agricultural regions like those in Argentina’s Humid Pampas. This region was recently impacted by slow-evolving and long-lasting droughts as well as by flash droughts, resulting in losses reaching thousands of millions of US dollars. Improvements of drought early warning systems are essential, particularly given the projected increase in drought frequency and severity over southern South America. The spatial and temporal relationship between precipitation deficits, soil moisture and vegetation health anomalies are crucial for better understanding and representation of the agricultural droughts and their impacts. In this context, the Combined Drought Indicator (CDI) considers the causal and time-lagged relationship of these three variables. The study’s objective is twofold: (1) Analyze the time-lagged response between precipitation deficits, soil moisture and satellite fAPAR anomalies; and (2) Evaluate the CDI’s capability to characterize the severity of drought events on the Humid Pampas against agricultural yield estimations and simulations, as well as agricultural emergency declarations. The correlation among the variables shows strong spatial variability. The highest Pearson correlation values (r > 0.42) are observed over parts of the Humid Pampas for time lags of 0, 10, and 20 days between the variables. Although the CDI has limitations, such as its coarse spatial resolution and monthly temporal resolution of precipitation data, it effectively tracks the progression of major drought events in the region. The CDI’s performance aligns well with estimations and simulations of soybean and corn yields, as well as official declarations of agricultural emergencies. Insights from this study also provide a basis for discussing potential improvements to the CDI. This study highlights the global and regional significance of evaluating and enhancing the CDI for effective drought monitoring, emphasizing the role of collaborative efforts for future advancements in drought early warning systems.

Combined Drought Indicator↗

Drought Prediction for Socio-Cultural Stability Project

The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture assimilation produced marginal benefits. We carried out 1-3 month lead-time forecast experiments using GEOS-5 forecasts as input to LIS/CLSM. Based on these forecast experiments, we find that the expected skill in GEOS-5 forecasts from 1-3 months is present in the soil moisture percentiles used to indicate drought. In the case of the HOA drought, the failure of the long rains in April appears in the February 1, March 1 and April 1 initialized forecasts, suggesting that for this case, drought forecasting would have provided some advance warning about the drought conditions observed in 2011. Three key recommendations for follow-up work include: (1) carry out a comprehensive analysis of droughts observed over the entire period of record for GEOS-5 forecasts; (2) continue to analyze the GEOS-5 forecasts in HOA stratifying by anomalies in long and short rains; and (3) continue to include GRACE TWS, Soil Moisture/Ocean Salinity (SMOS) and the upcoming NASA Soil Moisture Active/Passive (SMAP) soil moisture products in a routine activity building on this prototype to further quantify the benefits for drought assessment and prediction.

Peters-Lidard, Christa↗

Landfalling Droughts: Global Tracking of Moisture Deficits From the Oceans Onto Land

Abstract Droughts threaten food, energy, and water security, causing death and displacement of millions of people and billions of dollars in damages. However, there are still important gaps in the understanding of drought mechanisms and behaviors, inhibiting the accuracy of early‐warning systems designed to protect communities worldwide. We use an object‐tracking algorithm to track clusters of precipitation‐minus‐evaporation moisture deficits across land and ocean areas of the globe from 1981–2018. This analysis reveals a new type of “landfalling drought” that originates over the ocean and “migrates” onto land. We find that 16% of droughts that affected the continents worldwide from 1981–2018 were landfalling droughts. These droughts were significantly larger (220–425%) and more intense (4–30%)—and grew (253–285%) and intensified (9–28%) faster—than droughts that developed solely over the land or ocean. To identify potential underlying mechanisms, we analyze moisture transport associated with landfalling droughts over western North America. We find that landfalling droughts in this region are associated with anomalously anticyclonic atmospheric pressure patterns that reduce moisture fluxes over the Pacific Ocean toward the continent. By advancing understanding of the spatiotemporal evolution of droughts, our findings offer the potential to improve seasonal‐scale prediction and long‐term projection of global drought risks.

Herrera‐Estrada, Julio E.↗

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗

The Changing Influence of Precipitation on Soil Moisture Drought With Warming in the Mediterranean and Western North America

Abstract Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below‐normal precipitation and terminated by average or above‐normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming‐driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts.

Environmental Sciences & Ecology↗

The Changing Influence of Precipitation on Soil Moisture Drought With Warming in the Mediterranean and Western North America

Anthropogenic climate change has already affected drought severity and risk across many regions, and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below-normal precipitation and terminated by average or above-normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming-driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought. Here, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29% in the Mediterranean and 32% and 6% in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts.

drought↗

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗

Projected Changes in Early Summer Ridging and Drought Over the Central Plains

Early summer (May–June–July; MJJ) droughts over the Central Plains are often caused by atmospheric ridging, but it is uncertain if these events will increase in frequency or if their influence on drought severity will change in a warming world. Here, we use tree-ring based reconstructions (1500–2020 CE) of MJJ ridging and 0–200 cm soil moisture with six CMIP6 model ensembles to investigate the response of Central Plains drought dynamics to a moderate warming scenario (SSP2-4.5). By the end of the 21st century (2071–2100), precipitation increases in most models during the preceding months (February–March–April), especially over the northern part of the Central Plains, while changes during MJJ are non-robust. By contrast, vapor pressure deficit increases strongly in all models, resulting in five of the six models projecting robust median soil moisture drying and all six models projecting more rapid seasonal soil moisture declines during the transition into the summer. Major ridging events increase in frequency in some models, and there is strong agreement across all models that when ridging events do occur, they will cause more severe soil moisture drought and seasonal drying at the end of the 21st century. The median multi-model response also indicates, by the end of the 21st century, that the Central Plains will experience a three-fold increase in the risk of drought events equivalent to the most extreme droughts of the last 500 years. Our results demonstrate that even moderate warming is likely to increase early summer soil moisture drought severity and risk over the Central Plains, even in the absence of robust precipitation declines, and that drought responses to major atmospheric ridging events will be significantly stronger.

Drought↗

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.

54 ENVIRONMENTAL SCIENCES↗

The Legacy of Episodic Climatic Events in Shaping Temperate, Broadleaf Forests

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning approx. 840 000 sq km and 5327 tree recruitment dates spanning approx. 1.4 million sq km across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as ''heavy tailed,'' with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Climatology↗

Intra-Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data

Understanding plant hydraulic regulation is critical for predicting plant and ecosystem responses to projected increases in drought stress. Plant hydraulic regulation is controlled by observable, diverse plant hydraulic traits that can vary as much across individuals of the same species as they do across different species. Direct measurements of plant hydraulic traits from a range of ecosystems remain limited in comparison to other, more readily measured traits (e.g., specific leaf area). Furthermore, plant hydraulic trait measurements, often made at leaf or branch levels, are not easily scaled to whole-plant values that are typically used to predict plant and ecosystem fluxes. In this study, multiple whole-plant hydraulic parameters are inferred from observations of plant water use (i.e., sap flow), soil properties, and meteorological data. We use a Markov Chain Monte Carlo model inversion approach to obtain the best estimates and uncertainty of plant hydraulic parameters that capture whole-plant effective embolism resistance and stomatal sensitivity to decreasing plant water potential. We then use the inferred values in the model to estimate whole-tree water use and isohydricity. This approach reliably infers whole-plant parameter values with enough specificity to resolve inter- and intra-specific differences, and thus supplements time- and labor-intensive direct measurements of traits.

54 ENVIRONMENTAL SCIENCES↗

Remote Sensing Technologies Mitigate Drought

Ames Research Center has partnered with the California Department of Water Resources to develop satellite-based technologies to mitigate drought conditions. One project aims to help water managers adjust their irrigation to match the biological needs of each crop, and another involves monitoring areas where land is fallow so emergency relief can more quickly aid affected communities.

Source record↗

Drought and Extreme Heat Impacts to Data Centers in Northern California

Commonly, data centers are designed and operated on the assumption of stationarity of the climate. Historical weather data informs the basis of their design and operations. However, as a result of climate change, this assumption is not valid and poses a great risk for data centers. In the coming decades, Northern California’s drought and extreme heat risk is projected to increase significantly. This report provides a drought and extreme heat impacts assessment of data centers in this region. Expert solicitation of data center experts enabled a tailored approach to this report. We identify the climate variables and analytics relevant for assessing data center-specific impacts from extreme heat and drought and demonstrate how to access and understand future climate projections from climate models. We emphasize the importance of including future climate projections into data center design and planning. This report is an important first step towards building an effective extreme heat and drought adaptation strategy for data centers in Northern California. While our geographical focus in this report is Northern California, many findings in this report are broadly applicable.

58 GEOSCIENCES↗

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗

Near-term tropical cyclone risk and coupled Earth system model biases

Most current climate models predict that the equatorial Pacific will evolve under greenhouse gas–induced warming to a more El Niño-like state over the next several decades, with a reduced zonal sea surface temperature gradient and weakened atmospheric Walker circulation. Yet, observations over the last 50 y show the opposite trend, toward a more La Niña-like state. Recent research provides evidence that the discrepancy cannot be dismissed as due to internal variability but rather that the models are incorrectly simulating the equatorial Pacific response to greenhouse gas warming. This implies that projections of regional tropical cyclone activity may be incorrect as well, perhaps even in the direction of change, in ways that can be understood by analogy to historical El Niño and La Niña events: North Pacific tropical cyclone projections will be too active, North Atlantic ones not active enough, for example. Other perils, including severe convective storms and droughts, will also be projected erroneously. While it can be argued that these errors are transient, such that the models’ responses to greenhouse gases may be correct in equilibrium, the transient response is relevant for climate adaptation in the next several decades. Given the urgency of understanding regional patterns of climate risk in the near term, it would be desirable to develop projections that represent a broader range of possible future tropical Pacific warming scenarios—including some in which recent historical trends continue—even if such projections cannot currently be produced using existing coupled earth system models.

Science & Technology - Other Topics↗

Global Gridded Crop Models Underestimate Yield Responses to Droughts and Heatwaves

Extreme events can lead to crop yield declines, resulting in financial losses and threats to food security, and the frequency and intensity of such events is projected to increase. As global gridded crop models (GGCMs) are commonly used to assess climate change impacts on agricultural yields, there is a need to understand whether these models are able to reproduce the observed yield declines. We evaluated 13 GGCMs from the Inter-Sectoral Impact Model Intercomparison Project and compared observed and simulated impact of past droughts and heatwaves on yields for four crops (maize, rice, soy, wheat). We found that most models detect but underestimate the impact of droughts and heatwaves on yield. Specifically, the drought signal was detected by 12 of 13 models for maize and all models for wheat, while the heat signal was detected by eleven models for maize and six models for wheat. To investigate whether the difference between simulated and observed yield declines is due to a misrepresentation of simulated exposure to heat or water scarcity (i.e. misrepresentation of growing season), we analysed the relationship between average discrepancies between observed and simulated yield losses, and average simulated exposure to extreme weather conditions across all crop models. We found a positive correlation between simulated exposure to heat and model performance for heatwaves, but found no correlation for droughts. This suggests that there is a systematic underestimation of yield responses to heat and drought and not only a misrepresentation of exposure. Assuming that performance for the past indicates models' capacity to project future yield impacts, models likely underestimate future yield decline from climate change. High-quality temporally and spatially resolved observational data on growing seasons will be highly valuable to further improve crop models' capacity to adequately respond to extreme weather events.

extreme events↗

Fungal and bacterial growth variation due to drought and nitrogen addition experimental treatments. Loma Ridge Experimental Project. 2010-2012

Terrestrial ecosystem models assume that microbial communities respond instantaneously, or are immediately resilient, to environmental change. Here we tested this assumption by quantifying the resilience of a leaf litter community to changes in precipitation or nitrogen availability. By manipulating composition within a global change experiment, we decoupled the legacies of abiotic parameters versus that of the microbial community itself. After one rainy season, more variation in fungal composition could be explained by the original microbial inoculum than the litterbag environment (18% versus 5.5% of total variation). This compositional legacy persisted for 3 years, when 6% of the variability in fungal composition was still explained by the microbial origin. In contrast, bacterial composition was generally more resilient than fungal composition. Microbial functioning (measured as decomposition rate) was not immediately resilient to the global change manipulations; decomposition depended on both the contemporary environment and rainfall the year prior. Finally, using metagenomic sequencing, we showed that changes in precipitation, but not nitrogen availability, altered the potential for bacterial carbohydrate degradation, suggesting why the functional consequences of the two experiments may have differed. Predictions of how terrestrial ecosystem processes respond to environmental change may thus be improved by considering the legacies of microbial communities. This data package includes ten csv files (five data files and their corresponding data dictionaries) and one file-level metadata excel file. Data files contains information about which plots were exposed to treatments related to drought and nitrogen, information about litter bags reciprocal transplants manipulation for water input and nitrogen, detail information about water addition, precipitation records, and litter variables collected. Data dictionary files include detail explanation for each column in the data files. The file-level metadata file describes each file mentioned above. All the analyses were done using the R software.

54 ENVIRONMENTAL SCIENCES↗