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Physiological Responses of Forests to Drought.
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Drought Conditions Maximize the Impact of High-Frequency Flow Variations on Thermal Regimes and Biogeochemical Function in the Hyporheic Zone.
Anthropogenic activities, such as dam operations, often induce larger and more frequent stage fluctuations than those occurring in natural rivers. However, the long-term impact of such flow variations on thermal and biogeochemical dynamics of the associated hyporheic zone (HZ) is poorly understood. A heterogeneous, two-dimensional thermo-hydro-biogeochemical model revealed an important interaction between high-frequency flow variations and watershed-scale hydrology. High-frequency stage fluctuations had their strongest thermal and biogeochemical impacts when the mean river stage was low during fall and winter. An abnormally thin snowpack in 2015, however, created a low river stage during summer and early fall, whereby high frequency stage fluctuations caused the HZ to be warmer than usual. This study provided the scientific basis to assess the potential ecological consequences of the high-frequency flow variations in a regulated river, as well as guidance on how to maximize the potential benefits—or minimize the drawbacks—of river regulation to river ecosystems.
Accounting for Renewable Resource Droughts in Energy Infrastructure Planning for California, Part II: Nodal Capacity Expansion Planning
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Identifying Differences in Abiotic Stress Gene Networks between Lowland and Upland Ecotypes of Switchgrass (DE-SC0008338)
Switchgrass (Panicum virgatum) is a warm-season C4 grass that is a target lignocellulosic biofuel species for use in the United States due to its local adaption capabilities and high biomass accumulation. Two ecotypes of switchgrass have been described. Members of the lowland ecotype are taller, have narrower leaf blades and generate more biomass compared to individuals from the upland ecotype. Additionally, lowland plants are generally found in the southern United States while upland switchgrass is more typically present in the northern United States. These differences are important as it is envisioned that switchgrass for biofuel production will typically be grown on marginal lands in the northern United States to supplement and diversify farmers' traditional crop incomes. While lowland switchgrass is more productive, it has poor winter survivability in northern latitudes where upland switchgrass is expected to be grown for biofuel use. Abiotic stresses likely to be encountered by switchgrass include drought and salinity. Despite initially being described as preferring wetter environments, members of the lowland ecotype have been characterized as being more drought tolerant than plants of the upland ecotype. Nonetheless, direct trials have indicated that variation for drought tolerance exists in both ecotypes, but prior to this project, only a relatively small number of switchgrass lines had been tested for drought responses. Similarly, switchgrass cultivars have not been widely tested for salt tolerance, but a few studies have shown that even mild salt stress can inhibit growth. The effects of drought and salt stress on plant growth are complex. Both drought and salinity affect the osmotic potential of plant cells and negatively affect plant growth due to reduced water potential and reduced photosynthesis that results from lower stomatal conductance of CO 2 . Plants respond to drought and salt stress by activating genes that directly attempt to reduce the stress (e.g., transmembrane pumps that partition Na + ) and mitigate the effects of the stress (e.g., synthesis of osmoprotectant metabolites and stress-related signaling compounds). Prior to the start of this project, no gene expression analysis had been performed on switchgrass under conditions of drought or salt stress, and therefore, relevant gene networks responding to drought and salt stress were unknown in switchgrass. In this project, we performed drought, salt and alkali-salt screens on 49 switchgrass cultivars (Liu et al 2014; Liu et al 2015; Hu et al 2015; Kim et al 2016). These experiments demonstrated that a wide range of variation exists within switchgrass for drought, salt and alkali-salt tolerance and that, while the lowland ecotype of switchgrass is often considered more tolerant of abiotic stresses, there are some upland switchgrass lines that are also very tolerant of drought, salt and alkali-salt stress. We also conducted drought and salt time course experiments with Alamo and Dacotah. We have identified modules of coexpressed genes that differentiate Alamo and Dacotah drought responses. We are continuing to analyze these results and plan to submit manuscripts describing this work in early 2017. In an effort to show how drought- and salt-related gene modules could be dissected, we generated transgenic switchgrass overexpressing either PvGTγ-1 or ZmDREB2. Increased expression of PvGTγ-1 does confer increased salt tolerance, and we were able to identify genes that are induced and suppressed by PvGTγ-1. Overexpression of ZmDREB2 increases drought tolerance in switchgrass. Analysis of the PvGTγ-1 and ZmDREB2 overexpression work is ongoing, and we plan to prepare manuscripts about these experiments for submission in early 2017.
Quantitative proteome profile of water deficit stress responses in eastern cottonwood ( Populus deltoides ) leaves
Drought stress is a recurring feature of world climate and the single most important factor influencing agricultural yield worldwide. Plants display highly variable, species-specific responses to drought and these responses are multifaceted, requiring physiological and morphological changes influenced by genetic and molecular mechanisms. Moreover, the reproducibility of water deficit studies is very cumbersome, which significantly impedes research on drought tolerance, because how a plant responds is highly influenced by the timing, duration, and intensity of the water deficit. Despite progress in the identification of drought-related mechanisms in many plants, the molecular basis of drought resistance remains to be fully understood in trees, particularly in poplar species because their wide geographic distribution results in varying tolerances to drought. Herein, we aimed to better understand this complex phenomenon in eastern cottonwood ( Populus deltoides ) by performing a detailed contrast of the proteome changes between two different water deficit experiments to identify functional intersections and divergences in proteome responses. We investigated plants subjected to cyclic water deficit and compared these responses to plants subjected to prolonged acute water deficit. In total, we identified 108,012 peptide sequences across both experiments that provided insight into the quantitative state of 22,737 Populus gene models and 8,199 functional protein groups in response to drought. Together, these datasets provide the most comprehensive insight into proteome drought responses in poplar to date and a direct proteome comparison between short period dehydration shock and cyclic, post-drought re-watering. Altogether, this investigation provides novel insights into drought avoidance mechanisms that are distinct from progressive drought stress. Additionally, we identified proteins that have been associated as drought-relevant in previous studies. Importantly, we highlight the RD26 transcription factor as a gene regulated at both the transcript and protein level, regardless of species and drought condition, and, thus, represents a key, universal drought marker for Populus species.
Long-Term Studies Reveal Differential Responses to Climate Change for Trees Under Soil- or Herbivore-Related Stress
Worldwide, trees are confronting increased temperature and aridity, exacerbating susceptibility to herbivory. Long-term studies comparing patterns of plant performance through drought can help identify variation among and within populations in vulnerability to climate change and herbivory. We use long-term monitoring data to examine our overarching hypothesis that the negative impacts of poor soil and herbivore susceptibility would be compounded by severe drought. We studied pinyon pine, Pinus edulis, a widespread southwestern tree species that has suffered extensive climate-change related mortality. We analyzed data on mortality, growth, male reproduction, and herbivory collected for 14–32 years in three areas with distinct soil-types. We used standardized precipitation-evapotranspiration index (SPEI) as a climate proxy that summarizes the impacts of drought due to precipitation and temperature variation on semi-arid forests. Several key findings emerged: (1) Plant performance measurements did not support our hypothesis that trees growing in stressful, coarse-textured soils would suffer more than trees growing in finer-textured soils. Stem growth at the area with coarse, young cinder soils (area one) responded only weakly to drought, while stem growth on more developed soils with sedimentary (area two) and volcanic (area three) substrates, was strongly negatively affected by drought. Male reproduction declined less with drought at area one and more at areas two and three. Overall mortality was 30% on coarse cinder soils (area one) and averaged 55% on finer soil types (areas two and three). (2) Although moth herbivore susceptible trees were hypothesized to suffer more with drought than moth resistant trees, the opposite occurred. Annual stem growth was negatively affected by drought for moth resistant trees, but much less strongly for moth susceptible trees. (3) In contrast to our hypothesis, moths declined with drought. Overall, chronically water-stressed and herbivore-susceptible trees had smaller declines in performance relative to less-stressed trees during drought years. These long-term findings support the idea that stressed trees might be more resistant to drought since they may have adapted or acclimated to resist drought-related mortality.
Hydraulic architecture explains species moisture dependency but not mortality rates across a tropical rainfall gradient
Aim Intensified droughts are affecting tropical forests across the globe. However, the underlying mechanisms of tree drought response and mortality are poorly understood. Hydraulic traits and especially hydraulic safety margins (HSMs), i.e. the extent to which plants buffer themselves from thresholds of water stress, provide insights into species-specific drought vulnerability. Methods We investigated hydraulic traits during an intense drought triggered by the 2015-2016 El Niño on 27 canopy trees across three tropical forest sites with differing precipitation. We capitalized on the drought event as a time when plant water status might approach or exceed thresholds of water stress. We investigated the degree to which these traits varied across the rainfall gradient, as well as relationships amongst hydraulic traits and species-specific optimal moisture and mortality rates. Results There were no differences among sites for any measured trait. There was strong coordination among traits, with a network analysis revealing two major groups of coordinated traits. In one group there were water potentials, turgor loss point, sapwood capacitance and density, HSMs, and mortality rate. In the second group there was leaf mass per area, leaf dry matter content, hydraulic architecture (leaf area to sapwood area ratio), and species-specific optimal moisture. Conclusion These results demonstrated that while species with greater safety from turgor loss had lower mortality rates, hydraulic architecture was the only trait that explained species’ moisture dependency. Species with a greater leaf area to sapwood area ratio were associated with drier sites and reduced their transpirational demand during the dry season via deciduousness.
A trait-based framework for linking microbial communities with carbon transformations under precipitation change
Droughts are common throughout the world. As the climate changes, droughts may become more frequent and intense. Still, scientists are uncertain about how drought will affect the natural world, particularly the bacteria, fungi, and other microbes that live in soils. These tiny life forms are crucial because they control the Earth’s flows of carbon and essential nutrients. Researchers at the University of California, Irvine, and Lawrence Berkeley National Laboratory teamed up to study how the microbiome, or collection of bacteria and fungi in the soil, deals with drought. Since 2007, the researchers have used shelters with retractable roofs to prevent nearly half of normal rainfall from reaching grass and shrub ecosystems, and their soil microbiomes, in Southern California. The study team discovered that microbes have some clever tricks up their sleeve for surviving drought. When growing on dead grass as a food source, microbes ramp up production of specialized chemicals called osmolytes that keep their cells from drying out. But microbes growing on dead shrubs face another problem. Unlike grass, shrub leaves are a lousy food source. To digest and consume shrub leaves, microbes have to exude more enzymes, which act like biochemical chef knives that chop complex leaf molecules into bite-sized pieces. Carbon is the coin of the microbial realm, earned via enzyme action or slurping up dead plant juices. Microbes growing under normal conditions on tasty dead grass have it easy: they can spend most of their carbon currency on growth. With drought, life gets harder as microbes need to pay up for osmolytes and ramp down their growth. It gets worse with shrub leaves because microbes have to multi-task among growth, enzyme secretion, and osmolyte production. When drought hits, microbes on shrub leaves forgo the osmolytes, probably because losing the carbon revenue from enzyme investment would be a deal-breaker for survival. The next question tackled by the researchers asked how the genes controlling microbial lifestyles sort out across the tree of life. Most microbiologists thought these lifestyles would correspond to rather large branches on the tree. But the study team found that in fact, very closely related microbes differ in important and interesting ways. For example, bacteria that have nearly identical housekeeping genes respond distinctively to warming, rainfall, and plant chemistry. As a result, soil microbiomes are much richer in diversity than originally thought. And studying microbial diversity in much greater detail could open up many more possibilities for how microbial life deals with changing environmental conditions. Trying to understand microbial life without the fine details of genetic diversity is like trying to stream Netflix on a dial-up connection. By looking across the landscape, the researchers revealed that microbial diversity is absolutely critical for maintaining the planet’s flows of carbon and nutrients. The study team designed a new technology—microbial cages—for transplanting intact microbiomes. With the cages, the researchers could move microbiomes to novel environments and compare their ability to cycle carbon and nutrients. In some cases, performance tailed off when microbiomes found themselves in a new environment, but in other cases, performance rivaled or even exceeded that of the resident microbiome. And even the low performers eventually caught up to the native microbiomes if given sufficient time. These findings mean that microbiomes—at least in Southern California—may be resilient to climate shifts due to a high diversity of microbial lifestyles. Coping with heat and drought may literally be in their DNA. The last piece of the research puzzle, and a “Holy Grail” for microbial ecologists, is to forecast the behavior of diverse microbiomes. To meet this challenge, the study team developed new theory and computer models. For the first time, these models account for hundreds of different microbes and how their intricate lifestyles cope with drought. The models are starting to connect the tiniest microbes with the global cycles that sustain Earth’s farms, fields, and forests. With that connection, it will be easier for society to plan for a world with more droughts and other climate disruptions.
Bridging the Divide: Linking Genomics to Ecosystem Responses to Climate Change: Final Report
Over the project period, we have addressed the following objectives: 1) assess the effects of altered precipitation patterns (i.e., increased variability in growing season precipitation) on genetic diversity of the dominant C4 grass species, Andropogon gerardii, and 2) experimentally assess the impacts of extreme climatic events (heat wave, drought) on responses of the dominant C4 grasses, A. gerardii and Sorghastrum nutans, and the consequences of these response for community and ecosystem structure and function. Below is a summary of how we have addressed these objectives. Objective 1 After ten years of altered precipitation, we found the number of genotypes of A. gerardii was significantly reduced compared to the ambient precipitation treatments (Avolio et al., 2013a). Although genotype number was reduced, the remaining genotypes were less related to one another indicating that the altered precipitation treatment was selecting for increasingly dissimilar genomes (based on mean pairwise Dice distance among individuals). For the four key genotypes that displayed differential abundances depending on the precipitation treatment (G1, G4, and G11 in the altered plots and G2 in the ambient plots), we identified phenotypic differences in the field that could account for ecological sorting (Avolio & Smith, 2013a). The three altered rainfall genotypes also have very different phenotypic traits in the greenhouse in response to different soil moisture availabilities (Avolio and Smith, 2013c). Two of the genotypes that increased in abundance in the altered precipitation plots had greater allocation to root biomass (G4 and G11), while G1 allocated more biomass aboveground. These phenotypic differences among genotypes suggests that changes in genotypic structure between the altered and the ambient treatments has likely occurred via niche differentiation, driven by changes in soil moisture dynamics (reduced mean, increased variability and changes in the depth distribution of soil moisture) under a more variable precipitation regime, rather than reduced population numbers (A. gerardii tiller densities did not differ between altered and ambient treatments; p = 0.505) or a priori differences in genotype richness (Avolio et al.2013a). This ecological sorting of genotypes, which accounts for 40% of all sampled individuals in the altered plots, is an important legacy of the press chronic climate changes in the RaMPs experiment. Objective 2 In May 2010, we established the Climate Extremes Experiment at the Konza Prairie Biological Station. For the experiment, a gradient of temperatures, ranging from ambient to extreme, were imposed in 2010 and 2011 as a mid-season heat wave under well-watered or severe drought conditions. This study allowed us for the first time to examine species-specific thresholds of responses to climate extremes and assess how these phenotypic responses may impact selection of particular genotypes, with the ultimate goal of linking alterations in individual performance and genetic diversity to ecosystem structure and functioning. We found that tallgrass prairie was resistant to heat waves, but it was not resistant to extreme drought, which reduced aboveground net primary productivity (ANPP) below the lowest level measured in this grassland in almost thirty years (Hoover et al. in press(a)). This extreme reduction in ecosystem function was a consequence of reduced productivity of both C4 grasses and C3 forbs. This reduction in biomass of the C4 grasses (Andropogon gerardii and Sorghastrum nutans) was, in part, due to significant reductions in photosynthesis, leaf water potential and productivity with drought in the dominant grasses species, with S. nutans was more sensitive than A. gerardii to drought (Hoover et al. in press(b)). However, the dominant forb was negatively impacted by the drought more than the dominant grasses, and this led to a reordering of species abundances within the plant community. Although this change in community composition persisted post-drought, ANPP recovered completely the year after drought due to rapid demographic responses by the dominant grass, compensating for loss of the dominant forb. Overall, our results show that an extreme reduction in ecosystem function attributable to a climate extreme (e.g., low resistance) does not preclude rapid ecosystem recovery. Given that dominance by a few species is characteristic of most ecosystems, knowledge of the traits of these species and their responses to climate extremes will be key for predicting future ecosystem dynamics and function. In addition, our research suggests that water stress will dominate photosynthetic and productivity responses caused by discrete drought and heat wave events, rather than direct or additive effects of heat stress, with differential sensitivity in these grasses altering future ecosystem function.
West African monsoon decadal variability and surface-related forcings: second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II)
The Sahel climate system had experienced one of the strongest interdecadal climate variabilities and the longest drought on the planet in the twentieth century. Most modeling studies on the decadal variability of the Sahel climate so far have focused on the role of anomalies in either sea surface temperature (SST), land surface processes, or aerosols concentration. The Second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedback of SST, land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The WAMME II strategy is to apply observationally based anomaly forcing, i.e., “idealized but realistic” forcing, in simulations by general circulation models’ (GCMs) and regional climate models’ (RCMs) to test the relative impacts of such forcings in producing/amplifying the Sahelian seasonal and decadal climate variability, including the 20th century drought. To test individual ocean’s SST effect, a special approach in the experimental design is taken to avoid undermine its effect. This is the first multi-model experiment specifically designed to simultaneously evaluate relative contributions of multiple-external forcings to the Sahel drought. This paper presents the major results and preliminary findings of the WAMME II SST experiment, including each ocean’s contribution to the global SST effect, as well as comparison of the SST effect with the LULCC effect. The common empirical orthogonal functions and other analyses are applied to assess and comprehend the discrepancies among the models. In general, the WAMME II models have reached a consensus on SST’s major contribution to the great Sahel drought and show that with the maximum possible SST forcing, it can produce up to 60% of the absolute amount of precipitation difference between the 1980s and the 1950s. This paper has 3 also delineated the role of SSTs in triggering and maintaining the Sahel drought, suggesting a potential predictability of WAM development linked to SST. Among different ocean basins, the Pacific and Indian Ocean SSTs have the greatest impact on the 1980s drought. The WAMME II, however, fails to reach a consensus on the role of the Mediterranean Sea SST. The changes in circulation, moisture flux convergence, and associated surface energy balances are the main mechanisms for the SST effect. The paper also compares the SST effect with the LULCC effects. It is shown that the prescribed land forcing produces about 40% of the precipitation difference between the 1980s and the 1950s, which is less than SST contribution but still of first order in the Sahel climate system. The role of land surface processes in responding to and amplifying the drought has also been identified. The results demonstrate that catastrophic consequences likely occur in the regional climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. Due to limited ensemble members, aerosol effects are not compared. Since the SST and land forcing in the real world are likely smaller than specified in this study, further investigations on the effects of aerosols as well as of other external forcings, such as greenhouse gases, and of atmospheric internal variability, are necessary. Moreover, although the WAMEE II models support a general consensus on SST and LULCC effects, there are still large discrepancies in how these models produce the Sahel drought in the 1980s. Better atmospheric observational and analysis data including more processes and components are necessary to validate and constrain models, and to guide further model development and improvement.
Vegetation Monitoring Optimization with Normalized Difference Vegetation Index and Evapotranspiration Using Remote Sensing Measurements and Land Surface Models Over East Africa
The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration(ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.
Using Machine Learning to Identify Novel Hydroclimate States
Anthropogenic climate change is expected to alter drought risk in the future. However, droughts are not uncommon or unprecedented, as documented in tree-ring-based reconstructions of the summer average Palmer drought severity index (PDSI). Using an unsupervised machine-learning method trained on these reconstructions of pre-industrial climate, we identify outliers: years in which the spatial pattern of PDSI is unusual relative to ‘normal' variability. We show that in many regions, outliers are more frequently identified in the twentieth and twenty-first centuries. This trend is more pronounced when the regional drought atlases are combined into a single global dataset. By definition, outlier patterns at the 10% level are expected to occur once per decade, but from 1950 to 2000 more than 6 years per decade are identified as outliers in the global drought atlas (GDA). Extending the GDA through 2020 using an observational dataset suggests that anomalous global drought conditions are present in 80% of years in the twenty-first century. Our results indicate, without recourse to climate models, that the world is more frequently experiencing drought conditions that are highly unusual in the context of past natural climate variability.
Microbial community response to a decade of simulated global changes depends on the plant community
Global changes such as increased drought and atmospheric nitrogen deposition perturb both the microbial and plant communities that mediate terrestrial ecosystem functioning. However, few studies consider how microbial responses to global changes may be influenced by interactions with plant communities. To begin to address the role of microbial–plant interactions, we tested the hypothesis that the response of microbial communities to global change depends on the plant community. We characterized bacterial and fungal communities from 395 plant litter samples taken from the Loma Ridge Global Change Experiment, a decade-long global change experiment in Southern California that manipulates rainfall and nitrogen levels across two adjacent ecosystems, a grassland and a coastal sage scrubland. The differences in bacterial and fungal composition between ecosystems paralleled distinctions in plant community composition. In addition to the direct main effects, the global change treatments altered microbial composition in an ecosystem-dependent manner, in support of our hypothesis. The interaction between the drought treatment and ecosystem explained nearly 5% of the variation in bacterial community composition, similar to the variation explained by the ecosystem-independent effects of drought. Unexpectedly, we found that the main effect of drought was approximately four times as strong on bacterial composition as that of nitrogen addition, which did not alter fungal or plant composition. Overall, the findings underscore the importance of considering plant–microbe interactions when considering the transferability of the results of global change experiments across ecosystems.
Climate and the Global Famine of 1876-78
From 1875 to 1878, concurrent multiyear droughts in Asia, Brazil, and Africa, referred to as the Great Drought, caused widespread crop failures, catalyzing the so-called Global Famine, which had fatalities exceeding 50 million people and long-lasting societal consequences. Observations, paleoclimate reconstructions, and climate model simulations are used 1) to demonstrate the severity and characterize the evolution of drought across different regions, and 2) to investigate the underlying mechanisms driving its multiyear persistence. Severe or record-setting droughts occurred on continents in both hemispheres and in multiple seasons, with the "Monsoon Asia" region being the hardest hit, experiencing the single most intense and the second most expansive drought in the last 800 years. The extreme severity, duration, and extent of this global event is associated with an extraordinary combination of preceding cool tropical Pacific conditions (1870-76), a record-breaking El Nino (1877-78), a record strong Indian Ocean dipole (1877), and record warm North Atlantic Ocean (1878) conditions. Composites of historical analogs and two sets of ensemble simulations - one forced with global sea surface temperatures (SSTs) and another forced with tropical Pacific SST - were used to distinguish the role of the extreme conditions in different ocean basins. While the drought in most regions was largely driven by the tropical Pacific SST conditions, an extreme positive phase of the Indian Ocean dipole and warm North Atlantic SSTs, both likely aided by the strong El Nino in 1877-78, intensified and prolonged droughts in Australia and Brazil, respectively, and extended the impact to northern and southeastern Africa. Climatic conditions that caused the Great Drought and Global Famine arose from natural variability, and their recurrence, with hydrological impacts intensified by global warming, could again potentially undermine global food security.
An improved daily standardized precipitation index dataset for mainland China from 1961 to 2018
The standardized precipitation index (SPI), one of the most commonly used drought indicators, is widely used in the research areas of drought analysis and drought prediction in different fields such as meteorology, agriculture, and hydrology. However, its main disadvantage is the relatively coarse time resolution of one month. To improve the time resolution of SPI to identify flash droughts, we have refined the traditional SPI calculation method and developed a new multi-scale daily SPI dataset based on data from 484 meteorological stations in mainland China from 1961 to 2018. SPI data from three different sites (located in Henan, Yunnan, and Fujian Provinces) at the three-month timescale were analyzed by comparing with historically recorded drought events. We found that the new multi-scale daily SPI can effectively capture drought events in different periods and locations and identify the specific start and end times of drought events. In short, our SPI dataset appears reasonable and capable of facilitating drought research in different fields.
Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request
Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.
Data for EMSL Project 60929 from August 2023: PI Goemann MONet Request
Just as humans rely on a healthy gut microbiome for resilience to illness, plants rely on a healthy root microbiome for resilience to environmental abiotic stress (heat, drought). To achieve a healthy root microbiome, plants release carbon (C)-rich compounds as root exudates to stimulate microbial activity and increase local nutrient mineralization. However, the enhanced performance comes at a cost: up to 44% of a plant’s C can be lost to root exudates, diverting C from plant growth and respiration. Critical knowledge gaps include how the ‘C cost’ is managed and how root exudates alter the microbiome under different environmental conditions. In addition, historical climate conditions, particularly mean annual precipitation, is known to shape local soil microbiomes and alter their sensitivity to drought. Therefore, studies that better characterize the plant-microbe responses to environmental stress will aid in efforts to harness the microbiome to improve crop resilience. However, current knowledge gaps make it challenging to engineer beneficial plant-microbe interactions to improve plant productivity in agricultural systems and to predict how increased climate variability will alter terrestrial C fluxes and climate feedbacks. To fill this knowledge gap our research group at Montana State University – Bozeman is currently studying blue grama (Bouteloua gracilis), a prairie grass native across the Northern Great Plains, as a model for drought tolerance. Our goal is to investigate the above- and belowground responses of blue grama to drought and heat stress to improve our understanding of stress-induced carbon allocation and plant-microbe interactions. Most recently, we investigated the influence of climate history on the blue grama drought response. We collected soil from three blue grama-dominated sites (those proposed to sample here) across a 150 mm mean annual precipitation gradient in SW Montana, USA, to use as inoculum for a greenhouse drought experiment. Preliminary results indicate that soil climate history has a strong influence on the blue grama physiological response to drought as well as on the chemical composition of root exudates and rhizosphere microbiome composition. Metabarcoding data from this experiment is scheduled to be submitted to public databases within the next year. Having in-depth analyses of the soil biogeochemistry and metagenomic composition through the MONet project at each of the field sites associated with this experiment will allow us to link underlying ecological processes with observed patterns of plant growth and productivity at each site. In addition, we plan to utilize the MONet database for future meta-analyses to compare the genomic and biogeochemical signatures of our field sites to others across a wider precipitation gradient throughout the native range of blue grama. This will further provide critical insights into the mechanisms that drive ecosystem functioning and resilience to drought stress.