Resurrection genomics provides molecular and phenotypic evidence of rapid adaptation to salinization in a keystone aquatic species.

Ecologists and evolutionary biologists are increasingly cognizant of rapid adaptation in wild populations. Rapid adaptation to anthropogenic environmental change is critical for maintaining biodiversity and ecosystems services into the future. Anthropogenic salinization of freshwater ecosystems is quickly emerging as a primary threat, which is well documented in the northern temperate ecoregion. Specifically, many northern temperate lakes have undergone extensive salinization because of urbanization and the associated increase in impervious surfaces causing runoff, and the extensive use of road deicing salts (e.g., NaCl). It remains unclear whether increasing salinization will lead to extirpation of species from these systems. Using a "resurrection genomics" approach, we investigated whether the keystone aquatic herbivore, Daphnia pulicaria, has evolved increased salinity tolerance in a severely salinized lake located in Minnesota, USA. Whole-genome resequencing of 54 Daphnia clones from the lake and hatched from resting eggs that represent a 25-y temporal contrast demonstrates that many regions of the genome containing genes related to osmoregulation are under selection in the study population. Tolerance assays of clones revealed that the most recent clones are more tolerant to salinity than older clones; this pattern is concomitant with the temporal pattern of stabilizing salinity in this lake. Together, our results demonstrate that keystone species such as Daphnia can rapidly adapt to increasing freshwater salinization. Further, our results indicate that rapid adaptation to salinity may allow lake Daphnia populations to persist in the face of anthropogenic salinization maintaining the food webs and ecosystem services they support despite global environmental change.

Recent Advances in the Crosstalk between Brassinosteroids and Environmental Stimuli.

Due to their sessile lifestyle, plants need to optimize their growth in order to adapt to ever-changing environments. Plants receive stimuli from the environment and convert them into cellular responses. Brassinosteroids (BRs), as growth-promoting steroid hormones, play a significant role in the tradeoff between growth and environmental responses. Here, we provide a comprehensive summary for understanding the crosstalk between BR and various environmental stresses, including water availability, temperature fluctuations, salinization, nutrient deficiencies and diseases. We also highlight the bottlenecks that need to be addressed in future studies. Ultimately, we suppose to improve plant environmental adaptability and crop yield by excavating natural BR mutants or modifying BR signaling and its targets.

Timing determines zooplankton community responses to multiple stressors.

Human activities and climate change cause abiotic factors to fluctuate through time, sometimes passing thresholds for organismal reproduction and survival. Multiple stressors can independently or interactively impact organisms; however, few studies have examined how they interact when they overlap spatially but occur asynchronously. Fluctuations in salinity have been found in freshwater habitats worldwide. Meanwhile, heatwaves have become more frequent and extreme. High salinity pulses and heatwaves are often decoupled in time but can still collectively impact freshwater zooplankton. The time intervals between them, during which population growth and community recovery could happen, can influence combined effects, but no one has examined these effects. We conducted a mesocosm experiment to examine how different recovery times (0-, 3-, 6-week) between salt treatment and heatwave exposure influence their combined effects. We hypothesized that antagonistic effects would appear when having short recovery time, because previous study found that similar species were affected by the two stressors, but effects would become additive with longer recovery time since fully recovered communities would respond to heatwave similar to undisturbed communities. Our findings showed that, when combined, the two-stressor joint impacts changed from antagonistic to additive with increased recovery time between stressors. Surprisingly, full compositional recovery was not achieved despite a recovery period that was long enough for population growth, suggesting legacy effects from earlier treatment. The recovery was mainly driven by small organisms, such as rotifers and small cladocerans. As a result, communities recovering from previous salt exposure responded differently to heatwaves than undisturbed communities, leading to similar zooplankton communities regardless of the recovery time between stressors. Our research bolsters the understanding and management of multiple-stressor issues by revealing that prior exposure to one stressor has long-lasting impacts on community recovery that can lead to unexpected joint effects of multiple stressors.

Wastewaters Coproduced with Shale Gas Drive Slight Regional Salinization of Groundwater.

While unconventional oil and gas (UOG) development is changing the world economy, processes that are used during UOG development such as high-volume hydraulic fracturing ("fracking") have been linked with water contamination. Water quality risks include leaks of gas and salty fluids (brines) that are coproduced at wellpads. Identifying the cause of contamination is difficult, however, because UOG wells are often colocated with other contaminant sources. We investigated the world's largest shale gas play with publicly accessible groundwater data (Marcellus Shale in Pennsylvania, U.S.A. with ∼29,000 analyses) and discovered that concentrations of brine-associated barium ([Ba]) and strontium ([Sr]) show small regional increases within 1 km of UOG development. Higher concentrations in groundwaters are associated with greater proximity to and density of UOG wells. Concentration increases are even larger when considering associations with the locations of (i) spill-related violations and (ii) some wastewater impoundments. These statistically significant relationships persist even after correcting for other natural and anthropogenic sources of salts. The most likely explanation is that UOG development slightly increases salt concentrations in regional groundwaters not because of fracking but because of the ubiquity of wastewater management issues. These results emphasize the need for stringent wastewater management practices across oil and gas operations.

Predictive Understanding of Stream Salinization in a Developed Watershed Using Machine Learning.

Stream salinization is a global issue, yet few models can provide reliable salinity estimates for unmonitored locations at the time scales required for ecological exposure assessments. Machine learning approaches are presented that use spatially limited high-frequency monitoring and spatially distributed discrete samples to estimate the daily stream-specific conductance across a watershed. We compare the predictive performance of space- and time-unaware Random Forest models and space- and time-aware Recurrent Graph Convolution Neural Network models (KGE: 0.67 and 0.64, respectively) and use explainable artificial intelligence methods to interpret model predictions and understand salinization drivers. These models are applied to the Delaware River Basin, a developed watershed with diverse land uses that experiences anthropogenic salinization from winter deicer applications. These models capture seasonality for the winter first flush of deicers, and the streams with elevated predictions correspond well with indicators of deicer application. This result suggests that these models can be used to identify potential salinity-impaired streams for winter best management practices. Daily salinity predictions are driven primarily by land cover (urbanization) trends that may represent anthropogenic salinization processes and weather at time scales up to three months. Such modeling approaches are likely transferable to other watersheds and can be applied to further understand salinization risks and drivers.

The influence of soil salinization, induced by the backwater effect of the Yellow River, on microbial community dynamics and ecosystem functioning in arid regions.

Irrigation practices and groundwater levels are critical factors contributing to soil salinization in arid and semi-arid regions. However, the impact of soil salinization resulting from Yellow River water irrigation and recharge on microbial communities and their functions in the Huinong District has not been thoroughly documented. In this study, high-throughput sequencing technology was employed to analyze the diversity, composition, and structure of bacterial and fungal communities across a gradient of salinized soils. The results indicated that the alpha diversity of bacterial communities was significantly higher in slightly saline soils compared to highly saline soils. Soil salinization notably influenced the composition of both bacterial and fungal communities. Highly salinized soils were enriched with bacterial taxa such as Halomonas, Salinimicrobium, Pseudomonas, Solibacillus, and Kocuria, as well as fungal taxa including Emericellopsis, Alternaria, and Podospora. In these highly saline soils, bacterial taxa associated with iron respiration, sulfur respiration, and hydrocarbon degradation were more prevalent, whereas fungal taxa linked to functions such as soil animal pathogens, arbuscular mycorrhizal symbiosis, endophytes, dung saprotrophy, leaf saprotrophy, soil saprotrophy, fungal parasitism, and plant pathogenicity were less abundant. Random forest analysis identified nine bacterial and eighteen fungal taxa as potential biomarkers for salinity discrimination in saline soils. Symbiotic network analysis further revealed that soil salinization pressure reduced the overall complexity and stability of bacterial and fungal communities. Additionally, bacterial community assembly showed a tendency shift from stochastic to deterministic processes in response to increasing salinity, while fungal community assembly remained dominated by deterministic processes. provide robust evidence that soil salinity is a major inhibitor of soil biogeochemical processes in the Huinong District and plays a critical role in shaping bacterial and fungal communities, their symbiotic networks, and their assembly processes.

Long-term surface composts application enhances saline-alkali soil carbon sequestration and increases bacterial community stability and complexity.

Organic composts could remediate saline-alkali soils on agricultural land by amending soil micro-environment which is one of the main strategies for resourceful treatment and recycling of livestock manure. However, it was still unknown how long-term surface application of organic composts affects the microhabitat and bacterial community characteristics and assembly processes on the profile. We examined the features of the soil properties, bacterial community, and assembly models after 7-years composts application. Physicochemical indicators, enzyme activities, and bacterial diversity of the saline-alkali farmland were all enhanced by the surface composts application, particularly in the 0-20 cm. The network analysis showed that the surface application of composts significantly enhanced the robustness and topological characteristics of the bacterial community and that bacteria from Acidobacteriota were the keystone of the saline-alkali soils improvement. Composts also greatly increased the ecological niche of the bacterial community, while stochastic processes (mainly dispersal limitation) significantly shaped the bacterial community compared to the control. Structural equation modeling indicated that composts application promoted bacterial community succession, which in turn promoted elevated total organic carbon and improved saline-alkali soils properties. Overall, the study linked the ecological characteristics of soil microhabitats and bacterial communities during the restoration of saline-alkali soils by long-term surface application of composts, providing the management and remediation of saline-alkali agricultural soil with a theoretical foundation and technological support.

Tapping into haloalkaliphilic bacteria for sustainable agriculture in treated wastewater: insights into genomic fitness and environmental adaptation.

The increasing salinity and alkalinity of soils pose a global challenge, particularly in arid regions such as Tunisia, where about 50% of lands are sensitive to soil salinization. Anthropogenic activities, including the use of treated wastewater (TWW) for irrigation, exacerbate these issues. Haloalkaliphilic bacteria, adapted to TWW conditions and exhibiting plant-growth promotion (PGP) and biocontrol traits, could offer solutions. In this study, 24 haloalkaliphilic bacterial strains were isolated from rhizosphere sample of olive tree irrigated with TWW for more than 20 years. The bacterial identification using 16S rRNA gene sequencing showed that the haloalkaliphilic isolates, capable of thriving in high salinity and alkaline pH, were primarily affiliated to Bacillota (Oceanobacillus and Staphylococcus). Notably, these strains exhibited biofertilization and enzyme production under both normal and saline conditions. Traits such as phosphate solubilization, and the production of exopolysaccharide, siderophore, ammonia, and hydrogen cyanide were observed. The strains also demonstrated enzymatic activities, including protease, amylase, and esterase. Four selected haloalkaliphilic PGPR strains displayed antifungal activity against Alternaria terricola, with three showing tolerances to heavy metals and pesticides. The strain Oceanobacillus picturea M4W.A2 was selected for genome sequencing. Phylogenomic analyses indicated that the extreme environmental conditions probably influenced the development of specific adaptations in M4W.A2 strain, differentiating it from other Oceanobacillus picturae strains. The presence of the key genes associated with plant growth promotion, osmotic and oxidative stress tolerance, antibiotic and heavy metals resistance hinted the functional capabilities might help the strain M4W.A2 to thrive in TWW-irrigated soils. By demonstrating this connection, we aim to improve our understanding of genomic fitness to stressed environments. Moreover, the identification of gene duplication and horizontal gene transfer events through mobile genetic elements allow the comprehension of these adaptation dynamics. This study reveals that haloalkaliphilc bacteria from TWW-irrigated rhizosphere exhibit plant-growth promotion and biocontrol traits, with genomic adaptations enabling their survival in high salinity and alkaline conditions, offering potential solutions for soil salinization issues.

Impacts of sequential salinity and heat stress are recovery time-specific in freshwater crustacean, Daphnia pulicaria.

Stressors can interact to affect animal fitness, but we have limited knowledge about how temporal variation in stressors may impact their combined effect. This limits our ability to predict the outcomes of pollutants and future dynamic environmental changes. Elevated salinity in freshwater ecosystems has been observed worldwide. Meanwhile, heatwaves have become more frequent and intensified as an outcome of climate change. These two stressors can jointly affect organisms; however, their interaction has rarely been explored in the context of freshwater ecosystems. We conducted lab experiments using Daphnia pulicaria, a key species in lakes, to investigate how elevated salinity and heatwave conditions collectively affect freshwater organisms. We also monitored the impacts of various recovery times between the two stressors. Daphnia physiological conditions (metabolic rate, Na+-K+-ATPase (NKA) activity, and lipid peroxidation level) and life history traits (survival, fecundity, and growth) in response to salt stress as well as mortality in heat treatment were examined. We found that Daphnia responded to elevated salinity by upregulating NKA activity and increasing metabolic rate, causing a high lipid peroxidation level. Survival, fecundity, and growth were all negatively affected by this stressor. These impacts on physiological conditions and life history traits persisted for a few days after the end of the exposure. Heat treatments caused mortality in Daphnia, which increased with rising temperature. Results also showed that individuals that experienced salt exposure were more susceptible to subsequent heat stress, but this effect decreased with increasing recovery time between stressors. Findings from this work suggest that the legacy effects from a previous stressor can reduce individual resistance to a subsequent stressor, adding great difficulties to the prediction of outcomes of multiple stressors. Our work also demonstrates that cross-tolerance/susceptibility and the associated mechanisms remain unclear, necessitating further investigation.

Spatial, temporal, and biological factors influencing plant responses to deicing salt in roadside bioinfiltration basins.

Plants are arguably the most visible components of stormwater bioretention basins and play key roles in stabilizing soils and removing water through transpiration. In regions with cold winters, bioretention basins along roadways can receive considerable quantities of deicing salt, much of which migrates out of the systems prior to the onset of plant growth but the rest remains in the soil. The resulting effects on plants presumably vary with time (due to annual weather patterns), space (because stormwater exposure is location-dependent), and biology (because plant taxa differ in their salt tolerance). The goal of this study was to investigate the magnitude of deicing salt's effects on bioretention plants and how it varies with spatial, temporal, and biological factors. The study took place in a set of five bioretention basins in Philadelphia, USA that receive runoff from a major highway. Over a five-year period, the electrical conductivity (EC) of influent stormwater frequently exceeded 1 mS cm-1 in winter, and occasionally surpassed that of seawater (∼50 mS cm-1). In both of the years when soil EC was measured as well, it remained elevated through all spring months, especially near basin inlets and centers. Mortality of nine plant taxa ranged widely after three years (0-90%), with rankings largely corresponding to salt tolerances. Moreover, leaf areas and/or crown volumes were strongly reduced in proportion to stormwater exposure in seven of these taxa. In the three taxa evaluated for tissue concentrations of 14 potentially toxic elements (Hemerocallis 'Happy Returns', Iris 'Caesar's Brother', and Cornus sericea 'Cardinal'), only sodium consistently exceeded the toxicity limit for salt intolerant plants (500 mg kg-1). However, exceedance of the sodium toxicity limit was associated with plants' topographic positions, with median concentrations greatest in the bottom of basins and least on basin rims. This study demonstrates that deicing salts can have detrimental effects on plants in bioretention basins, with the strongest effects likely to occur in years with the greatest snowfall (and therefore deicing salt use), in portions of basins with greatest stormwater exposure (typically around inlets and centers), and in plants with minimal salinity tolerance. Our results therefore underscore the value of installing salt-tolerant taxa in basins likely to experience any frequency of deicing salt exposure.

Uncertainty-based saltwater intrusion prediction using integrated Bayesian machine learning modeling (IBMLM) in a deep aquifer.

Data-driven machine learning approaches are promising to substitute physically based groundwater numerical models and capture input-output relationships for reducing computational burden. But the performance and reliability are strongly influenced by different sources of uncertainty. Conventional researches generally rely on a stand-alone machine learning surrogate approach and fail to account for errors in model outputs resulting from structural deficiencies. To overcome this issue, this study proposes a flexible integrated Bayesian machine learning modeling (IBMLM) method to explicitly quantify uncertainties originating from structures and parameters of machine learning surrogate models. An Expectation-Maximization (EM) algorithm is combined with Bayesian model averaging (BMA) to find out maximum likelihood and construct posterior predictive distribution. Three machine learning approaches representing different model complexity are incorporated in the framework, including artificial neural network (ANN), support vector machine (SVM) and random forest (RF). The proposed IBMLM method is demonstrated in a field-scale real-world "1500-foot" sand aquifer, Baton Rouge, USA, where overexploitation caused serious saltwater intrusion (SWI) issues. This study adds to the understanding of how chloride concentration transport responds to multi-dimensional extraction-injection remediation strategies in a sophisticated saltwater intrusion model. Results show that most IBMLM exhibit r values above 0.98 and NSE values above 0.93, both slightly higher than individual machine learning, confirming that the IBMLM is well established to provide better model predictions than individual machine learning models, while maintaining the advantage of high computing efficiency. The IBMLM is found useful to predict saltwater intrusion without running the physically based numerical simulation model. We conclude that an explicit consideration of machine learning model structure uncertainty along with parameters improves accuracy and reliability of predictions, and also corrects uncertainty bounds. The applicability of the IBMLM framework can be extended in regions where a physical hydrogeologic model is difficult to build due to lack of subsurface information.

Effects of groundwater level changes on soil characteristics and vegetation response in arid and semiarid coal mining areas.

Coal mining in arid and semiarid regions often leads to numerous ecological and environmental problems, such as aquifer depletion, lake shrinkage, vegetation degradation, and surface desertification. The drainage from coal mining activities is a major driving force in the evolution of the groundwater-soil-vegetation system. In order to explore the effect of groundwater level fluctuation on soil properties and the response mechanism of surface vegetation in coal mining areas, this study is based on hydrogeological and ecological vegetation investigations in the Bojianghaizi Basin, and soil and vegetation samples are collected in the areas with different groundwater levels, and soil and vegetation indexes are analyzed with the aid of methods such as numerical statistics, linear regression, and correlation analysis with the aid of the Origin software. The results show that there is a significant negative correlation between groundwater table (GWT) and soil water content (SWC), soil conductivity, soil organic matter (SOM), soil available nitrogen (SAN), and soil available potassium (SAK). Mining activities have led to the destruction of the soil structure, greatly reducing its ability to retain water and fertilizer. The contents of SWC, SOM, and SAN in the mining area are significantly reduced, which are at least 49.73%, 47.56% and 59.90% lower than those around the mining area. On the northern and southern sides of the lake, serious soil salinization exists in the lakeshore zone where the depth to the water table is <0.5 m, and the water required for the growth of vegetation here mainly comes from the groundwater, so there are only a few water-loving and saline-resistant plants; when the depth to the water table is 0.5-7 m, the growth of surface vegetation is influenced by the double impacts of the water table and atmospheric precipitation with a high degree of species richness; when the depth to the water table is >7 m, the surface vegetation is only dependent on the limited atmospheric precipitation for water. When the depth of groundwater is >7 m, the surface vegetation only relies on limited atmospheric precipitation for water, and drought-tolerant plants mainly grow in these areas. This study not only provides a scientific basis for the sustainable development and environmental protection of similar mines in the world, but also has important significance in guiding the ecological management and rational utilization of water resources in coal mine areas. What is more, This study provides valuable insights into sustainable water resource management in arid and semi-arid regions, crucial for mitigating the ecological impacts of coal mining activities.

Characteristics of soil salinity and water-salt transport in the vadose zone of salt-impacted regions with variable permeability.

Soil salinization poses a significant ecological challenge, emerging as a critical constraint to agricultural development in the arid and semi-arid regions of China, especially in southern Xinjiang. In particular, Yuepuhu County, situated in Kashgar, faces a distinctive issue. Impermeable thin clay layers within the vadose zone impede year-round leaching of salts, significantly impacting the growth of cotton. Through a combination of indoor testing, experiments, and statistical analyses, this study elucidated the varying permeability of soil layers at different depths and explored the forms and accumulation characteristics of soil salts in Yuepuhu County. It unveiled patterns of water and salt movement in soils with variable permeability layers, identifying key influencing factors. The research also proposed an irrigation regime suitable for cultivating vadose zone soils in the local context. The findings revealed a progression of increasing soil complexity and decreasing burial depth of clay layers from northwest to southeast, aligned with the direction of groundwater flow. With increasing depth, a noticeable reduction in soil saturated hydraulic conductivity was observed, indicating significant variability in permeability. Predominantly chloride-sulfate type saline soils in Yuepuhu County contained potassium (K+) and sodium (Na+) as the main cations in surface soils. Salinity strongly correlated with calcium (Ca2+) and magnesium (Mg2+). Chloride (Cl-), sulfate (SO42-), K+, Na+, and bicarbonate (HCO3-) reflected the degree of soil salinization in Yuepuhu County. The clay interlayers in variable permeability zones significantly impeded water and salt movement in the vadose zone. Moving from west to east, thicker and shallower clay interlayers hindered downward water movement, increasing the difficulty of salt leaching. Additionally, the irrigation regime influenced water and salt movement in the vadose zone. Under the same soil structure, flood irrigation with a higher water flux resulted in more significant salt leaching, and lower total dissolved solids (TDS) in irrigation water were more favorable for effective salt leaching. Collectively, our findings provided a theoretical foundation for improving and managing local saline soils, as well as guiding the implementation of rational agricultural irrigation practices.

Potential of land degradation index for soil salinity mapping in irrigated agricultural land in a semi-arid region using Landsat-OLI and Sentinel-MSI data.

Irrigated agricultural lands in arid and semi-arid regions are prone to soil degradation. Remote sensing technology has proven useful for mapping and monitoring the extent of this issue. To accurately discern soil salinity, it is essential to choose appropriate spectral wavelengths. This study evaluated the potential of the land degradation index (LDI) using the visible and near infrared (VNIR) and the short wavelength infrared (SWIR) spectral bands compared to that of soil salinity indices by integrating only the VNIR wavelengths. Landsat-OLI and Sentinel-MSI data, acquired 2 weeks apart, were rigorously preprocessed and used. This research was conducted over irrigated agricultural land in Morocco, which is well known for its semi-arid climate and moderately saline soil. Furthermore, a field soil survey was conducted and 42 samples with variable electrical conductivity (EC) were collected for index calibration and validation of the results. The results showed that the visual analysis of the derived maps based on the examined indices exhibited a clear spatial pattern of gradual soil salinity changes extending from the elevated upstream plateau to the downstream of the plain, which limits agricultural activities in the southwestern sector of the study area. The results of this study show that LDI is effective in identifying soil salinity, as indicated by a coefficient of determination (R2) of 0.75 when using Sentinel-MSI and 0.72 with Landsat-OLI. The R2 value of 0.89 and root mean square error (RMSE) of 0.87 dS/m for soil salinity maps generated from LDI with Sentinel-MSI demonstrate high accuracy. In contrast, the R2 value of 0.83 and RMSE of 1.24 dS/m for maps produced from Landsat-OLI indicate lower accuracy. These findings indicate that high-resolution Sentinel-MSI data significantly improved the prediction of salinity-affected soils. Furthermore, this study highlights the benefits of using VNIR and SWIR bands for precise soil salinity mapping.

Longitudinal stream synoptic (LSS) monitoring to evaluate water quality in restored streams.

Impervious surface cover increases peak flows and degrades stream health, contributing to a variety of hydrologic, water quality, and ecological symptoms, collectively known as the urban stream syndrome. Strategies to combat the urban stream syndrome often employ engineering approaches to enhance stream-floodplain reconnection, dissipate erosive forces from urban runoff, and enhance contaminant retention, but it is not always clear how effective such practices are or how to monitor for their effectiveness. In this study, we explore applications of longitudinal stream synoptic (LSS) monitoring (an approach where multiple samples are collected along stream flowpaths across both space and time) to narrow this knowledge gap. Specifically, we investigate (1) whether LSS monitoring can be used to detect changes in water chemistry along longitudinal flowpaths in response to stream-floodplain reconnection and (2) what is the scale over which restoration efforts improve stream quality. We present results for four different classes of water quality constituents (carbon, nutrients, salt ions, and metals) across five watersheds with varying degrees of stream-floodplain reconnection. Our work suggests that LSS monitoring can be used to evaluate stream restoration strategies when implemented at meter to kilometer scales. As streams flow through restoration features, concentrations of nutrients, salts, and metals significantly decline (p < 0.05) or remain unchanged. This same pattern is not evident in unrestored streams, where salt ion concentrations (e.g., Na+, Ca2+, K+) significantly increase with increasing impervious cover. When used in concert with statistical approaches like principal component analysis, we find that LSS monitoring reveals changes in entire chemical mixtures (e.g., salts, metals, and nutrients), not just individual water quality constituents. These chemical mixtures are locally responsive to restoration projects, but can be obscured at the watershed scale and overwhelmed during storm events.

Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment-bound bacterial communities in agricultural streams.

Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy-stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.

Host exposure to a common pollutant can influence diversity-disease relationships.

Hosts and parasites are embedded in communities where species richness and composition can influence disease outcomes (diversity-disease relationships). The direction and magnitude of diversity-disease relationships are influenced by variation in competence (ability to support and transmit infections) of hosts in a community. However, host susceptibility to parasites, which mediates host competence, is not static and is influenced by environmental factors, including pollutants. Despite the role that pollutants can play in augmenting host susceptibility, how pollutants influence diversity-disease dynamics is not well understood. Using an amphibian-trematode model, we tested how NaCl influences diversity-disease dynamics. We predicted that NaCl exposure can alter relative susceptibility of host species to trematodes, leading to cascading effects on the diversity-disease relationship. To test these predictions, we exposed hosts to benign or NaCl environments and generated communities that differed in number and composition of host species. We exposed these communities to trematodes and measured disease outcomes at the community (total infections across all hosts within a community) and species levels (average number of infections per host species within a community). Host species differed in their relative susceptibility to trematodes when exposed to NaCl. Consequently, at the community level (total infections across all hosts within a community), we only detected diversity-disease relationships (dilution effects) in communities where hosts were exposed to NaCl. At the species level, disease outcomes (average number of infections/species) and whether multi-species communities supported lower number of infections relative to single-species communities depended on community composition. Notably, however, as with overall community infection, diversity-disease relationships only emerged when hosts were exposed to NaCl. Synthesis. Pollutants are ubiquitous in nature and can influence disease dynamics across a number of host-parasite systems. Here, we show that NaCl exposure can alter the relative susceptibility of host species to parasites, influencing the relationship between biodiversity and disease at both community and species levels. Collectively, our study contributes to the limited knowledge surrounding environmental mediators of host susceptibility and their influence on diversity-disease dynamics.

Sodium as a subsidy in the spring: evidence for a phenology of sodium limitation.

Understanding the factors that mediate carbon (C) cycling is increasingly important as anthropogenic activities and climate change alter ecosystems. Decomposition rates mediate C cycling and are in part regulated by sodium (Na) where Na is limiting up to some threshold after which Na becomes stressful and reduces decomposition rates (i.e., the Sodium Subsidy-Stress hypothesis). An overlooked pathway by which decomposers encounter increased salts like NaCl is through plants, which often take up Na in proportion to soil concentrations. Here we tested the hypothesis that Na addition through litter (detritus) and water and their interaction would impact detrital processing and leachate chemistry. Laboratory riparian soil mesocosms received either artificial litter (100% cellulose sponges) soaked in 0.05% NaCl (NaClL) or just H2O (H2OL: control) and half of each litter treatment received weekly additions of 150 ml of either 0.05% NaCl water (NaClW) or just H2O (H2OW: control). After 8 weeks decomposition was higher in NaCl addition treatments (both NaClL and NaClW and their combo) than controls (H2OL + H2OW) but reflected a unimodal relationship where the saltiest treatment (NaClL + NaClW) was only marginally higher than controls indicating a subsidy-stress response. Previous studies in this system found that Na addition in either water or litter decreased decomposition. However, differences may reflect a phenology of Na demand where Na-limitation increases in the spring (this study). These results indicate that our understanding of how Na impacts detrital processes, C cycling, and aquatic-terrestrial linkages necessitates incorporation of temporal dynamics.

Soil salinization disrupts plant-plant signaling effects on extra-floral nectar induction in wild cotton.

Plant-plant interactions via volatile organic compounds (VOCs) have received much attention, but how abiotic stresses affect these interactions is poorly understood. We tested the effect of VOCs exposure from damaged conspecifics on the production of extra-floral nectar (EFN) in wild cotton plants (Gossypium hirsutum), a coastal species in northern Yucatan (Mexico), and whether soil salinization affected these responses. We placed plants in mesh cages, and within each cage assigned plants as emitters or receivers. We exposed emitters to either ambient or augmented soil salinity to simulate a salinity shock, and within each group subjected half of the emitters to no damage or artificial leaf damage with caterpillar regurgitant. Damage increased the emission of sesquiterpenes and aromatic compounds under ambient but not under augmented salinity. Correspondingly, exposure to VOCs from damaged emitters had effect on receiver EFN induction, but this effect was contingent on salinization. Receivers produced more EFN in response to damage after being exposed to VOCs from damaged emitters when the latter were grown under ambient salinity, but not when they were subjected to salinization. These results suggest complex effects of abiotic factors on VOC-mediated plant interactions.

Selenium-induced rhizosphere microorganisms endow salt-sensitive soybeans with salt tolerance.

Soil salinization is a prevalent abiotic stress that adversely affects soybean production. Rhizosphere microorganisms have been shown to modulate the rhizosphere microenvironment of plants, leading to improved stress resistance. Selenium is known to optimize the rhizosphere microbial community, however, it remains uncertain whether selenium-induced rhizosphere microorganisms can enhance plant salt tolerance. In this study, we selected two soybean varieties, including salt-tolerant and salt-sensitive, and conducted pot experiments to explore the impact of selenium application on the structure and composition of the rhizosphere microbial community of soybean plants under salt stress. Four salt-tolerant bacteria from salt-tolerant soybean rhizosphere soil fertilized with selenium under salt stress were isolated, and their effects on improving salt tolerance in salt-sensitive soybean were also investigated. Our results showed that selenium application enhanced soybean salt tolerance by optimizing the structure of the plant rhizosphere microbial community and improving soil enzyme activities in both salt-tolerant and salt-sensitive varieties. Moreover, compared with salt-only treatment, inoculation of the four bacteria led to a significant increase in the plant height (7.2%-19.8%), aboveground fresh weight (57.3%-73.5%), SPAD value (8.4%-30.3%), and K+ content (4.5%-12.1%) of salt-sensitive soybean, while reducing the content of proline (84.5%-94%), MDA (26.5%-49.3%), and Na+ (7.1%-21.3%). High-throughput sequencing of the 16 S ribosomal RNA gene indicated that the four bacteria played a crucial role in changing the community structure of salt-sensitive soybean and mitigating the effects of salt stress. This study highlighted the importance of selenium combined with beneficial microorganisms in the plant rhizosphere in alleviating salinity stress.