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At least 973 records · Page 54

Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution

Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. Furthermore, these outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10 3 tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.

13 HYDRO ENERGY↗

Computational studies of hydraulic stressors for biological performance assessment in a hydropower plant with Kaplan turbine

We report Hydropower is currently one of the preeminent sources of renewable energy in the United States and globally. Hydropower plants also have detrimental impacts on the environment and ecology, including direct impacts to anadromous fish populations. The computational fluid dynamics (CFD) – based Biological Performance Assessment (BioPA) toolset is used for biological evaluations of fish passage through hydropower plants. The hydraulic environment of a hydropower plant was evaluated using CFD coupled with discrete element method (DEM) simulations. The predicted flow field and particle collision rate were validated against the experimental data in a water flume that has an idealized hydroturbine distributor geometry. Flow simulations were conducted to evaluate the hydraulic stressors, such as nadir pressure, fluid shear, runner collision, in a physical scale in a hydropower plant with Kaplan turbine which are responsible for injury and mortality of fish in a downstream migration. The cumulative exposure probability for the nadir pressure and collision with turbine runner was found to decrease with increased discharge rate. The lowest discharge rate shows the higher value of cumulative shear exposure probability. The maximum value of collision velocity increases with increased discharge rate. We offer the conclusions that will help in understanding various hydraulic stressors for biological assessment for environmentally sustainable hydroturbine passage.

13 HYDRO ENERGY↗

Exploring the Potential of Rainwater Harvesting for Cooling Towers: A Systematic Review and Regional Feasibility Assessment

Water scarcity has driven interest in rainwater harvesting, especially for U.S. industries like power and manufacturing, which dedicate a large percentage of their water needs to cooling towers. This paper provides a comprehensive systematic review of studies on the use of rainwater in cooling tower applications, along with an assessment of the regional feasibility of integrating RWH in U.S. manufacturing cooling towers. The systematic review examines the technical, economic, environmental, and policy feasibility of utilizing harvested rainwater, and the regional feasibility analysis evaluates the practical implementation of RWH in manufacturing cooling towers, considering factors such as regional RWH potential, water costs, state policies, and the industrial water use of manufacturing facilities per state. This study supports the hypothesis that RWH for cooling towers is technically feasible, economically viable, and environmentally beneficial. Harvested rainwater is naturally less conductive and soft, and rainwater reuse minimizes the ecological footprint. Supportive state policies, regional RWH potential, and rising water costs across the U.S. are important variables that may impact RWH adoption. The review highlights rooftop RWH as the most studied method and notes that implementing RWH requires infrastructure changes and filtration techniques. While initial investment costs may be high, operational and maintenance costs are low, making RWHS economically feasible over time. Regions with higher water costs and supportive policies are more likely to benefit from RWH adoption. The study provides a foundation for understanding the potential for using RWH in industrial cooling towers.

Cooling towers↗

Satellite remote sensing for environmental sustainable development goals: A review of applications for terrestrial and marine protected areas

With few years left to achieve the vital United Nations Sustainable Development Goals (SDGs), member nations must urgently leverage technological advancements in environmental monitoring to succeed. Remote sensing now provides decades of global observations at a variety of spatio-temporal scales and a litany of data products to guide comprehensive measures for climate action, and aquatic and terrestrial biota preservation. Protected areas, such as national parks and wildlife preserves, represent largely untapped resources for both applying robust conservation measures and testing ambitious new approaches to sustainable development that could jumpstart the much-needed adoption of strategies to efficiently pursue global sustainability. This review summarizes recent demonstrated utilities of remotely sensed data applied to protected areas for research related to SDG goals 13, 14, and 15: “Climate Action”, “Life below Water”, and “Life on Land”. We identify successful uses of such data for each SDG, identify areas for improvement, and provide recommendations from the literature on how to expand what others have done to achieve lofty goals with global impact. We demonstrate that remote sensing provides a valuable tool for achieving SDGs as it facilitates monitoring vegetation health, water quality and condition, and climate variables at large spatial and fine temporal scales, while also evaluating the effectiveness of management and conservation practices. Issues remain, however, in that there is currently no reference from which to relate goal progress to human livelihoods. Further, the current relationship between remotely sensed indices and ecological services that determine sustainable development omit steps that would establish this connection.

54 ENVIRONMENTAL SCIENCES↗

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "Designated Targeted Observable" (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380 - 2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3-5 µm; TIR: 8-12 µm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. Finally, this effort synthesizes the findings of more than 130 scientists.

54 ENVIRONMENTAL SCIENCES↗

Studying drought-induced forest mortality using high spatiotemporal resolution evapotranspiration data from thermal satellite imaging

Drought can have pervasive and wide-spread impacts to forest health, as evidenced in several severe events occurring over the recent decades. Extensive forest die-off due to drought can impair the ecological functioning of forests, impacting habitat, water yield and quality from forested lands, and altering forest fire dynamics and intensity. Satellite remote sensing provides an effective means for detecting and monitoring spatial patterns of forest mortality over large areas, exploiting free and open long-term image archives available at a range in spatial and temporal resolutions. While remotely sensed surface reflectances and vegetation indices have been widely used to study optical response of forest canopies to drought events, retrievals of evapotranspiration (ET) derived from thermal satellite imagery – particularly at resolutions approaching crown scale - can provide insights into cumulative tree stresses that can incite disease and trigger mortality. In this study, we applied a multi-sensor satellite data fusion approach to estimate daily 30-m resolution ET and an associated Evaporative Stress Index (ESI) to study drought-induced mortality in a temperate forest at the Missouri Ozark AmeriFlux (MOFLUX) site, located in the central United States. The study covered the period from 2010 to 2014, including an exceptional drought year of 2012. Modeled ET agreed well with eddy flux measurements from the MOFLUX tower, with average monthly relative errors of 15%. Plot-scale ESI, describing temporal anomalies in the ratio of actual-to-reference ET, was used as an index of relative forest health to investigate relationships between forest mortality and drought severity. ESI showed good agreement with observed predawn leaf water potential, especially during the drought year. Furthermore, plot-scale ESI was also correlated with the subsequent year's tree mortality, suggesting the importance of considering the forest health condition prior to drought when studying drought-induced forest impacts. This study demonstrates the utility of multi-year ET remote sensing data at the stand or plot scale as an indicator of forest health and as a predictor of future mortality due to drought.

54 ENVIRONMENTAL SCIENCES↗

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

Next generation Arctic vegetation maps: Aboveground plant biomass and woody dominance mapped at 30 m resolution across the tundra biome

The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m −2 ) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ∼6000 g m −2 (mean ≈ 350 g m −2 ), while predicted values ranged from 0 to ∼4000 g m −2 (mean ≈ 275 g m −2 ), resulting in model validation root-mean-squared-error (RMSE) ≈ 400 g m −2 and R 2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling.

Climate change↗

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

Estimation of intensity, footprint, and capacity of surface urban heat islands using a direction-enhanced adaptive synchronous extraction (DEASE) method

Here, the surface urban heat island (SUHI) effect, assessed through remotely sensed land surface temperature (LST), remains a focal point in urban climate research. Conventional indicators like SUHI intensity (SUHII) and footprint (SUHIF) capture peak values and spatial extent but fail to account for the cumulative thermal load—a critical dimension reflecting the total heat exposure imposed by spatially continuous warming, which directly limits a holistic assessment of ecological and societal impacts of the SUHI effect. Therefore, this study introduces an indicator termed SUHI capacity (SUHIC), designed to quantify the aggregated SUHI effect by integrating the magnitude of the warming signal across all affected areas, thereby enabling a more comprehensive evaluation of urban thermal environments. Furthermore, a direction-enhanced adaptive synchronous extraction (DEASE) method is proposed for the quantification of SUHIC. This method can dynamically identify the optimal background reference area based on the urban-rural LST gradients in various directions within the city, without relying on predefined mathematical models as previously. The results from 102 European cities first confirm that the directional variations in urban-rural LST gradients, and the DEASE method can effectively capture these distinctions for the simultaneous estimation of SUHII, SUHIF, and SUHIC. Secondly, the spatial patterns of absolute SUHIC values show strong associations with those of SUHIF (R2>0.86), while its relative values (normalized by the area of urban) align more closely with SUHII (R2 > 0.64). More importantly, SUHIC can serve as a crucial reference for assessing the urban thermal signal when SUHII and SUHIF diverge. The proposed method and framework contribute to standardizing the quantification of the SUHI effect.

Indicator↗

Analysis of alternative climate datasets and evapotranspiration methods for the Upper Mississippi River Basin using SWAT within HAWQS

This study reports the application of Soil andWater Assessment Tool (SWAT) within the Hydrologic andWater Quality System(HAWQS) on-line platform, for the UpperMississippi River Basin (UMRB). TheUMRB is an important ecosystem located in the north central U.S. that is experiencing a range of ecological stresses. Specifically, testing of SWAT was performed for: (1) Hargreaves (HG) and Penman-Monteith (PM) PET methods, and (2) Livneh, National Climatic Data Center (NCDC) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate datasets. The Livneh-PM combination resulted in the highest average annual water yield of 380.6 mm versus the lowest estimated water yield of 193.9 mm for the Livneh-HG combination, in response to 23-year uncalibrated simulations. Higher annual ET and PET values were predicted with HG method versus the PM method for all three weather datasets in response to the uncalibrated simulations, due primarily to higher HG-based estimates during the growing season. Based on these results, it was found that the HG method is the preferred PET option for the UMRB. Initial calibration of SWAT was performed using the Livneh data and HGmethod for threeMississippi Rivermain stem gauge sites, which was followed by spatial validation at 10 other gauge sites located within the UMRB streamnetwork. Overall satisfactory results were found for the calibration and validation gauge sites, with the majority of R2 values ranging between 0.61 and 0.82, Nash- Sutcliffe modeling efficiency (NSE) values ranging between 0.50 and 0.79, and Kling-Gupta efficiency (KGE) values ranging between 0.61 and 0.84. The results of an additional experimental suite of six scenarios,which represented different combinations of climate data sets and calibrated parameters, revealed that suggested statistical criteria were again satisfied by the different scenario combinations. Overall, the PRISM data exhibited the strongest reliability for the UMRB.

54 ENVIRONMENTAL SCIENCES↗

Black carbon enriches short-range-order ferrihydrite in Amazonian Dark Earth: Interplay mechanism and environmental implications

Our study underpins the mechanism of organo-mineral interaction between black carbon (BC, biochar) and associated minerals in the historical BC-rich Amazonian Dark Earth (ADE) by using synchrotron-based microscopic (TXM), microspectroscopic (μFTIR) and spectroscopic (XAS and μ-diffraction) approaches. The BC-rich ADE contained over 100% more poorly crystalline minerals than the adjacent tropical soil. Linear combination fitting of k-spacing in the X-ray Absorption Spectra (XAS) revealed that ferrihydrite contributed to 81.1% of the Fe-minerals in BC. A small but distinct peak was observed at 5.7 Å –1 in the extended X-ray absorption fine structure k oscillation of BC, revealing the presence of Fe—C (including Fe-O-C) covalent bonds. No Fe—C path was yielded by the XAS fitting when an obvious peak downshift of the first (Fe—Fe 1 ) shell was observed, suggesting that the availability of inner-sphere Fe—C complexation was limited to the BC surface and interphase region. In this study, the main minerals for organo-mineral complexation were short-range-order (SRO) ferrihydrite on BC instead of corner-sharing FeO 6 octahedra. Compared to ADE, the coordination number of the first (Fe—Fe 1 ) and second (Fe—Fe 2 ) shell was higher in BC, revealing a higher degree of order in coordination between the neighboring Fe mineral crystals. Black C limited the progressive aging of amorphous Fe phases and greatly enriched SRO ferrihydrite in the redox-fluctuating and high-leaching environment. The transformation of SRO ferrihydrite into the more crystalline Fe oxides was controlled by the local pH environment. A strong signal from the complexed phenolic group (aryl-OH, 1241 cm –1 ) and a distinct band of inner-sphere complexation (Fe-aryl C, 1380–1384 cm –1 ) were identified in the FTIR spectra. The enrichment of poorly crystalline minerals can have positive feedback on the long-term stabilization of BC. The scale-up application of biochar to agricultural and ecological systems may have a long-lasting impact on the enrichment and transformation of the SRO minerals in the soil.

54 ENVIRONMENTAL SCIENCES↗

Interplay of microbial communities with mineral environments in coralline algae

Coralline algae are worldwide carbonate builders, considered to be foundational species and biodiversity hotspots. Coralline habitats face increasing pressure from human activities and effects related to Global Change, yet their ecological properties and adaptive responses remain poorly understood. The relationships of the algal microbiota with the mineral bioconstructions, as well as plasticity and resilience of coralline holobionts in a changing environment, are of particular interest. In the Gulf of California, Neogoniolithon trichotomum (Rhodophyta) is the main carbonate builder in tidal pools. We performed a multi-disciplinary assessment of the N. trichotomum microstructure using XRD, SEM microscopy and SR-FTIR spectromicroscopy. In the algal perithallus, magnesium-calcite and aragonite were spatially segregated and embedded in a polysaccharide matrix (rich in sulfated polysaccharides). Mg-calcites (18-19 mol% Mg) were the main mineral components of the thallus overall, followed by iron carbonates related to dolomite (ankerite) and siderite. Minerals of late evaporitic sequences (sylvite and bischofite) were also present, suggesting potential halophilic microenvironments within the algal thalli. The diverse set of abundant halophilic, halotolerant and oligotrophic taxa, whose abundance increase in the summer, further suggests this condition. We created an integrated model, based on environmental parameters and the microbiota distribution, that identified temperature and nutrient availability (particularly nitrate and silicate) as the main parameters related to specific taxa patterns. Among these, Hahella, Granulossicoccus, Ferrimonas, Spongiibacteraceae and cyanobacterial Xenococcaceae and Nostocaceae change significantly between seasons. These bacterial components might play relevant roles in algal plasticity and adaptive responses to a changing environment. This study contributes to the understanding of the interplay of the prokaryotic microbiota with the mineral microenvironments of coralline algae. Because of their carbonates with potential resistance to dissolution in a higher pCO 2 world and their seasonally dynamic bacteria, coralline algae are relevant targets to study coastal resilience and carbonated systems responses to changing environments.

54 ENVIRONMENTAL SCIENCES↗

Influence of shrub willow buffers strategically integrated in an Illinois corn-soybean field on soil health and microbial community composition

We report soil serves many important ecological functions and is an integral part of our existence as a society. However, concerns for soil health are growing globally, in part due to the negative impacts of agricultural management on soil resources. The production of perennial bioenergy crops on marginal land in row-crop production systems is one solution that could improve land-use efficiency and address the sustainability of cropland management. Because the relationship between crop management and the environment is complex, more research is needed to evaluate the potential benefits perennial bioenergy crop production has on soil health, as well as other ecosystem services. In this study, shrub willow buffers were strategically integrated into a corn-soybean cropping system with the main objective of reducing nitrate-N leaching from grain crop production while producing biomass for bioenergy. Two buffer systems (defined by landscape positions) were included for comparison, one on marginal land with exposure to nitrate-N leaching from upslope grain (southern plots) and one on fertile soils with less nitrate-N leaching potential (northern plots). Evaluation of soil (chemistry, bulk density, microbial community) and shrub willow vegetation properties ( fine roots, leaf litter decomposition, and nutrient uptake dynamics), showed that landscape position plays an important role in (1) the dynamics of soil chemical properties, (2) shrub willow's influence and productivity, and (3) the provision of additional ecosystem services such as reductions in nitrous oxide emissions and nitrate-N leaching. In addition, the combination of crop type and landscape position (N-grain, N-willow, S-grain, and S-willow) influenced the species composition of the soil microbial community, resulting in unique and identifiable communities. These results highlight the potential application of shrub willow buffers for ecosystem service provision and support of ecosystem processes; however, understanding the relationship between the microbial community, crop type, and landscape is important for understanding the sustainability of the design.

54 ENVIRONMENTAL SCIENCES↗

A review of transformative strategies for climate mitigation by grasslands

Grasslands can significantly contribute to climate mitigation. However, recent trends indicate that human activities have switched their net cooling effect to a warming effect due to management intensification and land conversion. This indicates an urgent need for strategies directed to mitigate climate warming while enhancing productivity and efficiency in the use of land and natural (nutrients, water) resources. Here, in this work, we examine the potential of four innovative strategies to slow climate change including: 1) Adaptive multi-paddock grazing that consists of mimicking how ancestral herds roamed the Earth; 2) Agrivoltaics that consists of simultaneously producing food and energy from solar panels on the same land area; 3) Agroforestry with a reverse phenology tree species, Faidherbia (Acacia) albida, that has the unique trait of being photosynthetically active when intercropped herbaceous plants are dormant; and, 4) Enhanced Weathering, a negative emission technology that removes atmospheric CO 2 from the atmosphere. Further, we speculate about potential unknown consequences of these different management strategies and identify gaps in knowledge. We find that all these strategies could promote at least some of the following benefits of grasslands: CO 2 sequestration, non-CO 2 GHG mitigation, productivity, resilience to climate change, and an efficient use of natural resources. However, there are obstacles to be overcome. Mechanistic assessment of the ecological, environmental, and socio-economic consequences of adopting these strategies at large scale are urgently needed to fully assess the potential of grasslands to provide food, energy and environmental security.

54 ENVIRONMENTAL SCIENCES↗

Year-around survey and manipulation experiments reveal differential sensitivities of soil prokaryotic and fungal communities to saltwater intrusion in Florida Everglades wetlands

Global sea-level rise is transforming coastal ecosystems, especially freshwater wetlands, in part due to increased episodic or chronic saltwater exposure, leading to shifts in biogeochemistry, plant- and microbial communities, as well as ecological services. Yet, it is still difficult to predict how soil microbial communities respond to the saltwater exposure because of poorly understood microbial sensitivity within complex wetland soil microbial communities, as well as the high spatial and temporal heterogeneity of wetland soils and saltwater exposure. To address this, we first conducted a two-year survey of microbial community structure and bottom water chemistry in submerged surface soils from 14 wetland sites across the Florida Everglades. We identified ecosystem-specific microbial biomarker taxa primarily associated with variation in salinity. Bacterial, archaeal and fungal community composition differed between freshwater, mangrove, and marine seagrass meadow sites, irrespective of soil type or season. Especially, methanogens, putative denitrifying methanotrophs and sulfate reducers shifted in relative abundance and/or composition between wetland types. Methanogens and putative denitrifying methanotrophs declined in relative abundance from freshwater to marine wetlands, whereas sulfate reducers showed the opposite trend. A four-year experimental simulation of salt-water intrusion in a pristine freshwater site and a previously saltwater-impacted site corroborated the highest sensitivity and relative increase of sulfate reducers, as well as taxon-specific sensitivity of methanogens, in response to continuously pulsing of saltwater treatment. Collectively, these results suggest that besides increased salinity, saltwater-mediated increased sulfate availability leads to displacement of methanogens by sulfate reducers even at low or temporal salt exposure. In conclusion, these changes of microbial composition could affect organic matter degradation pathways in coastal freshwater wetlands exposed to sea-level rise, with potential consequences, such as loss of stored soil organic carbon.

54 ENVIRONMENTAL SCIENCES↗

The effects of mixed-species root zones on the resistance of soil bacteria and fungi to long-term experimental and natural reductions in soil moisture

Mixed forest stands tend to be more resistant to drought than species-specific stands partially due to complementarity in root ecology and physiology. For this work, we asked whether complementary differences in the drought resistance of soil microbiomes might contribute to this phenomenon. We experimented on the effects of reduced soil moisture on bacterial and fungal community composition in species-specific (single species) and mixed-species root zones of Norway spruce and European beech forests in a 5-year-old throughfall-exclusion experiment and across seasonal (spring-summer-fall) and latitudinal moisture gradients. Bacteria were most responsive to changes in soil moisture, especially members of Rhizobiales, while fungi were largely unaffected, including ectomycorrhizal fungi (EMF). Community resistance was higher in spruce relative to beech root zones, corresponding with the proportions of drought-favored (more in spruce) and drought-sensitive bacterial taxa (more in beech). The spruce soil microbiome also exhibited greater resistance to seasonal changes between spring (wettest) and fall (driest). Mixed-species root zones contained a hybrid of beech- and spruce-associated microbiomes. Several bacterial populations exhibited either enhanced resistance or greater susceptibility to drought in mixed root zones. Overall, patterns in the relative abundances of soil bacteria closely tracked moisture in seasonal and latitudinal precipitation gradients and were more predictive of soil water content than other environmental variables. We conclude that complementary differences in the drought resistance of soil microbiomes can occur and the likeliest form of complementarity in mixed-root zones coincides with the enrichment of drought-tolerant bacteria associated with spruce and the sustenance of EMF by beech.

54 ENVIRONMENTAL SCIENCES↗

The impact of sampling scale: A comparison of methods for estimating external contaminant exposure in free-ranging wildlife

The impacts of contaminants on wildlife are dose dependent, and thus being able to track or predict exposure following contamination events is important for monitoring ecosystem health. However, the ability to track exposure in free-ranging wildlife is often severely limited. Consequently, researchers have predominantly relied on simple methods for estimating contaminant exposures in wildlife with little regard for spatial contaminant heterogeneity or an animal’s use of diverse habitats. We evaluated the influence sampling scale (i.e., how finely contaminant distribution and organism’s spatial use of the landscape is mapped) has on (1) realism and (2) conservativeness of exposure estimates. To do this, we monitored the actual exposure of wild boar (Sus scrofa) in Fukushima, Japan to radioactive contamination using GPS27 coupled contaminant monitors placed on individual animals. We compared empirical exposures to estimates generated by combining varying amounts of information about an individual boar’s location and/or movement, with the distribution of contamination on the landscape. Here we found that the most realistic exposure estimates were produced when finer-scale contaminant distribution surveys (e.g., airborne surveys) were combined with more accurate estimates of an individual’s space use (e.g., home ranges or core areas). Importantly, estimates of exposure based on single point surveys at a trap site (a simple method commonly used in the literature), did not correlate with actual exposure rates, suggesting dose-effects studies using this method may result in spurious conclusions. These results suggest that researchers seeking realistic estimates of exposure, such as in dose-effect studies, should ensure they have adequately accounted for fine-scale contaminant distribution patterns and areas of higher use by study organisms. However, conservative estimates of exposure i.e., intentionally over-predicting exposure as is done in initial tiers of ecological risk analyses) were not as scale sensitive and could be achieved with a single known location and coarse contaminant distribution maps.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗