Search NASA⌕ Search

SEARCH · Search NASA

Results for “Soil erosion”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Vegetation heterogeneity reflects soil thermal state and surface soil displacement in a thawing permafrost landscape

Thawing permafrost has the potential to dramatically alter the physical and ecological structure of northern landscapes. Warming of the Arctic and subsequent degradation of permafrost have created a need to assess the stability and movement of soils on hillslopes and the potential impacts on ecosystem structure. In this work, we explore the relationships among vegetation heterogeneity, soil temperature, and soil surface displacements observed from 2019 to 2022 in a watershed in the discontinuous permafrost region on the Seward Peninsula of Alaska. Vegetation heterogeneity was measured as the standard deviation (SD) of the normalized difference vegetation index (NDVI) from 3 m PlanetScope satellite imagery around each soil temperature and active layer thickness observation. Locations of observations were clustered into three soil thermal groups, warm, intermediate, and cold, based on soil temperature and active layer thickness. Average annual horizontal surface displacements were significantly lower for soils within the warm thermal group (median = 0.033 m yr −1 ) compared to soils within the cold thermal group (median = 0.090 m yr −1 ; p < 0.001). Conversely, vegetation heterogeneity was significantly higher in the warm (median = 0.014 SD NDVI; p = 0.002) and intermediate (median = 0.015 SD NDVI; p = 0.002) groups compared with the cold thermal group (median = 0.012 SD NDVI), suggesting a warming-induced shift in vegetation community complexity. Because of the observed associations of ground surface displacement rates and vegetation heterogeneity with soil thermal state, we hypothesize that warming soil conditions induce changes in the rates and patterns of hillslope erosion due to an increase in surface movement as near-surface permafrost thaws, followed by a decrease as the permafrost table deepens and excess ice content diminishes. The transition to warm soils promotes surface ecosystem transformation, shifting the dominant vegetation at the site, given the warming climatic conditions of the region. We integrated our observations of soil temperature, vegetation heterogeneity, and soil surface displacements into a conceptual model that describes the co-evolution of hillslopes and vegetation in warming permafrost environments, which is currently unrepresented in earth system models.

54 ENVIRONMENTAL SCIENCES↗

A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services

More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.

54 ENVIRONMENTAL SCIENCES↗

Water use and radiation balance of miscanthus and corn on marginal land in the coastal plain region of North Carolina

Abstract Miscanthus is a perennial grass that can yield substantial amounts of biomass in land areas considered marginal. In the Coastal Plain region of North Carolina, marginal lands are typically located in coarse‐textured soils with low nutrient retention and water‐holding capacity, and high erosivity potential. Little is known about miscanthus water use under these conditions. We conducted a study to better understand the efficiency with which miscanthus uses natural resources such as water and radiant energy to produce harvestable dry biomass in comparison to corn, a typical commodity crop grown in the region. We hypothesized that under non‐limiting soil water conditions, miscanthus would have greater available energy and water use rates owing to its greater leaf area, thus leading to greater agronomic yields. Conversely, these effects would be negated under drought conditions. Our measurements showed that miscanthus intercepted more radiant energy than corn, which led to greater albedo (by 0.05), lower net radiation (by 4% or 0.4 MJ m −2 day −1 ), and lower soil heat flux (by 69% or 1.0 MJ m −2 day −1 ) than corn on average. Consequently, miscanthus had greater available energy (by 7% or 0.6 MJ m −2 day −1 ) and water use rates (by 14% or 0.5 mm day −1 ) than corn throughout the growing season on average, which partially confirmed our hypothesis. Greater water use rates and radiation interception by miscanthus did not translate to greater water‐use (1.5 g kg −1 vs. 1.6 g kg −1 ) and radiation‐use (0.9 g MJ −1 vs. 1.1 g MJ −1 ) efficiencies than corn. Compared to literature values, our data indicated that water and radiation availability were not limiting at our study site. Thus, it is likely that marginal land features present at the Coastal Plain region such as low soil fertility and high air temperatures throughout the growing season may constrain agronomic yields even if soil water and radiant energy are non‐limiting.

Carvalho, Henrique D. R.↗

Enabling Sustainable Landscape Design for Continual Improvement of Operating Bioenergy Supply Systems

This unique and highly effective project catalyzed collaboration among government, university, and private sector partners through a multi-state research and technology transfer project designed to support continuous improvement of bioenergy feedstock supply systems. Conceived and built upon the foundation created by prior DOE investments in the Billion Ton Study, Sun Grant Regional Project, and many other feedstock production, harvest, storage and transportation studies, this project addressed seven tasks with more than 29 subtasks. All goals were met with key accomplishments being: (1) on-farm establishment of potential perennial plant mixtures that could not only become sustainable feedstock sources but also enhance soil health, (2) a reduction in potential wind and water erosion by improving corn stover harvest techniques and incorporating cover crops into current row-crop production systems, (3) reduced potential for surface and groundwater contamination while also increasing potential biodiversity and sustainability of Midwestern USA landscapes, and (4) development of site-specific land management, data visualization, and sustainability assessment tools. Twenty-two Case Studies highlighting accomplishments and lessons learned through this public-private partnership investment are incorporated into this final report. On-farm and replicated field plot studies were used to provide the real-world data needed to verify baseline assumptions for extensive feedstock logistic modeling and greenhouse gas (GHG) assessments needed to develop sustainable bioenergy and bio-product industries at national and international scales.

09 BIOMASS FUELS↗

Phosphorus and cover crop management practices affect phosphorus speciation in soils and eroded sediments

Abstract Agricultural runoff often contains P in dissolved and sediment‐bound forms, decreasing surface water quality. No‐till and cover cropping conservation practices have been recommended for reducing erosion and nutrient loss from cropping systems. The overall aims of this study were to characterize and evaluate the effects of fertilizer (placement and source) and cover crop management on P speciation in surface runoff sediments and source soil. In 2014, a field‐scale experiment was established in a no‐till, corn (Zea maysL.)–soybean (Glycine maxL.) cropping system with two cover crop treatments (with and without a winter crop; winter wheat [Triticum aestivumL.], rapeseed [Brassica napusL.], hairy vetch [Vicia villosaRoth], winter triticale [×Triticosecale Wittm.], and cereal rye [Secale cerealeL.]) and three P fertilizer management treatments (no P, fall broadcast diammonium phosphate, and spring subsurface injected ammonium polyphosphate). Phosphorus fractionation in the source soil collected in the fall of 2019 and sediment samples collected throughout 2020 were analyzed using a modified sequential P extraction method to evaluate the cumulative effects of imposing the treatment factors over 5 years. The direct P speciation was done using X‐ray absorption near edge structure spectroscopy. The indirect P speciation (fractionation) results showed that the management practices affected the exchangeable, organic matter‐associated, and Fe‐bound P fractions in sediments and the exchangeable and residual fractions in source soil. Direct P speciation results showed a depletion of Fe‐associated P in soil and sediment from cover crop treatment, suggesting that Fe‐associated P species were affected by cover crops. Changes in soil and runoff sediment P speciation would change the proportions and forms of soluble and particulate P in runoff sediments and may influence P bioavailability in aquatic ecosystems. Developing P fertilizer and cropping system management options with an understanding of soil P transformations helps maintain environmental sustainability.

Environmental Sciences & Ecology↗

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗

Meteoric 10Be Flux Calibration Data for the East River Watershed, Colorado, USA

This data package contains tabular and geospatial data used to quantify and model meteoric beryllium-10 fluxes in the East River watershed, Colorado, USA. The tabular component includes calibration-site data from five glacial moraine sites and includes environmental variables used to evaluate spatial controls on meteoric 10Be delivery, including elevation, mean annual precipitation (MAP), mean snow depth, and mean snow water equivalent (SWE). These site-level data were used to compare observed fluxes with environmental gradients across the watershed and to evaluate the effects of erosion correction on flux estimates. The package also includes supporting slope and curvature values used to assess topographic inputs to the erosion analysis. A second component of the data package contains updated manuscript tables and regression outputs used to summarize the relationships between meteoric 10Be flux and environmental predictors. These tables include meteoric 10Be sample information and AMS results, site-level environmental values, site-level meteoric 10Be inventory and flux values, watershed-averaged predicted fluxes, soil bulk density measurements, fine-fraction values, soil pH measurements, and regression statistics including slope, intercept, coefficient of determination, and p-value. The regression products include both standard linear regressions and regressions in which the intercept is constrained to pass through zero, and they support the analyses presented in the companion manuscript. Together, these tabular files provide the numerical basis for the manuscript tables and the regression-based interpretation of meteoric 10Be flux variability in a snow-dominated mountain watershed. The geospatial component of the package consists of GeoTIFF raster files used to generate the map products presented in Figures 2 and 6 of the companion manuscript. These rasters represent watershed-scale spatial layers for environmental variables and regression-based predictions of meteoric 10Be flux. This dataset contains comma-separated values files (.csv), Microsoft Excel files (.xlsx), GeoTIFF raster files (.tif), and upporting metadata files, including CSV data dictionaries and readme text files (.csv, .txt). The tabular files can be opened with standard spreadsheet software, and the raster files can be viewed and analyzed in GIS software such as ArcGIS Pro or QGIS. Together, these files document the numerical and spatial datasets used to calibrate and predict meteoric 10Be delivery in the East River watershed.

East River↗

Idaho National Laboratory Site Natural Resources: Wildland Fire Recovery Framework

As pressures from invasive species, climate change, and anthropogenic impacts increase across the landscape in the western U.S., managing wildland fire recovery to promote healthy sagebrush steppe becomes an increasingly important stewardship responsibility. The Idaho National Laboratory (INL) has developed and implemented wildland fire recovery plans to hasten desirable vegetation re-establishment on several individual fires, but lacks an overarching wildland fire recovery strategy, or framework. The intent of this document is to develop the technical approach and scientific basis for wildland fire recovery at the INL Site and to evaluate the tools available to support it in a comprehensive and broadly applicable format. This wildland fire recovery framework will outline the process of assessing the potential impacts of wildland fire on natural resources, present a range of post-fire recovery options, outline an approach for post-fire monitoring, and provide a template for post-fire recovery plans designed to addresses the specific conditions of each wildland fire. There are numerous benefits to developing a wildland fire recovery framework for the INL Site. The first is streamlining the development of post-fire recovery plans for individual fires. A second benefit is more closely aligning INL’s post-fire planning processes with those of other federal agencies. The development of an INL Site fire recovery framework will also allow resource professionals to consider a broader set of recovery tools than they have before because all proposed tools included in the framework were vetted through the process of scoping and stakeholder review. Finally, this framework is a publicly available document that can be used as a basis for communicating and discussing post-fire natural resource recovery objectives with agency collaborators, conservation partners, and other stakeholders. Through the proactive land stewardship principles outlined in this framework, current INL sustainability initiatives can be enhanced, and future INL mission flexibility will be maintained.

99 GENERAL AND MISCELLANEOUS↗

Coastal typologies and surface and subsurface characteristics of the Alaskan Beaufort Sea Coast

This dataset was generated to classify the Alaskan Beaufort Sea Coast (ABSC) into a set of distinct coastal typologies, to understand the surface and subsurface characteristics and variability of the ABSC, and to quantify relationships between these characteristics and historical rates of shoreline change. This geospatial dataset contains two csv files of points along the ABSC at a 50 m spacing, one for points sheltered by a barrier island and one for points exposed to the open ocean. Each point has a lat/lon location, and we have attributed to each point average values for elevation, historical long-term shoreline change rates, shoreline orientation, landcover, mean annual ground temperature, geomorphic unit, lithology, geology, ecological landscape unit, maximum thaw settlement potential, massive ice content, and segregated ice content. Each point is also assigned to one of 16 coastal typologies, determined by a hierarchical clustering algorithm on the elevation, shoreline change, orientation, and ground temperature data. There are 9 sheltered typologies and 7 exposed typologies, identified by an integer label in the last column of each csv file. The other two csv files contain the integer IDs and classes for the landcover and geomorphology datasets.

54 ENVIRONMENTAL SCIENCES↗

Eroding Permafrost Coastlines Release Biodegradable Dissolved Organic Carbon to the Arctic Ocean

Coastal erosion mobilizes large quantities of organic matter (OM) to the Arctic Ocean where it may fuel greenhouse gas emissions and marine production. While the biodegradability of permafrost-derived dissolved organic carbon (DOC) has been extensively studied in inland soils and freshwaters, few studies have examined dissolved OM (DOM) leached from eroding coastal permafrost in seawater. To address this knowledge gap, we sampled three horizons from bluff exposures near Drew Point, Alaska: seasonally thawed active layer soils, permafrost containing Holocene terrestrial and/or lacustrine OM, and permafrost containing late-Pleistocene marine-derived OM. Samples were leached in seawater to compare DOC yields, DOM composition (chromophoric DOM, Fourier transform ion cyclotron resonance mass spectrometry), and biodegradable DOC (BDOC). Holocene terrestrial permafrost leached the most DOC compared to active layer soils and Pleistocene marine permafrost. However, DOC from Pleistocene marine permafrost was the most biodegradable (33 ± 6% over 90 days), followed by DOC from active layer soils (23 ± 5%) and Holocene terrestrial permafrost (14 ± 3%). Permafrost leachates contained relatively more aliphatic and peptide-like formulae, whereas active layer leachates contained relatively more aromatic formulae. BDOC was positively correlated with nitrogen-containing and aliphatic formulae, and negatively correlated with polyphenolic and condensed aromatic formulae. Using estimates of eroding OM, we scale our results to estimate DOC and BDOC inputs to the Alaska Beaufort Sea. While DOC inputs from coastal erosion are relatively small compared to rivers, our results suggest that erosion may be an important source of BDOC to the Beaufort Sea when river inputs are low.

Bristol, Emily M.↗

Permafrost Landscape History Shapes Fluvial Chemistry, Ecosystem Carbon Balance, and Potential Trajectories of Future Change

Intensifying permafrost thaw alters carbon cycling by mobilizing large amounts of terrestrial substrate into aquatic ecosystems. Yet, few studies have measured aquatic carbon fluxes and constrained drivers of ecosystem carbon balance across heterogeneous Arctic landscapes. Here, we characterized hydrochemical and landscape controls on fluvial carbon cycling, quantified fluvial carbon fluxes, and estimated fluvial contributions to ecosystem carbon balance across 33 watersheds in four ecoregions in the continuous permafrost zone of the western Canadian Arctic: unglaciated uplands, ice-rich moraine, and organic-rich lowlands and till plains. Major ions, stable isotopes, and carbon speciation and fluxes revealed patterns in carbon cycling across ecoregions defined by terrain relief and accumulation of organics. In previously unglaciated mountainous watersheds, bicarbonate dominated carbon export (70% of total) due to chemical weathering of bedrock. In lowland watersheds, where soil organic carbon stores were largest, lateral transport of dissolved organic carbon (50%) and efflux of biotic CO 2 (25%) dominated. In watersheds affected by thaw-induced mass wasting, erosion of ice-rich tills enhanced chemical weathering and increased particulate carbon fluxes by two orders of magnitude. From an ecosystem carbon balance perspective, fluvial carbon export in watersheds not affected by thaw-induced wasting was, on average, equivalent to 6–16% of estimated net ecosystem exchange (NEE). Finally, in watersheds affected by thaw-induced wasting, fluvial carbon export approached 60% of NEE. Because future intensification of thermokarst activity will amplify fluvial carbon export, determining the fate of carbon across diverse northern landscapes is a priority for constraining trajectories of permafrost region ecosystem carbon balance.

54 ENVIRONMENTAL SCIENCES↗

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet. Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction. Plain Language Summary: Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions. Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

54 ENVIRONMENTAL SCIENCES↗

A Dose Assessment Model for Radioactive Waste Exposed by Gully Erosion at West Valley - 20513

The Western New York Nuclear Service Center (WNYNSC), located approximately 48 km south of Buffalo, New York, is the site of a former nuclear fuel reprocessing and radioactive waste disposal facility. Spent nuclear fuel was processed there from 1966 to 1972, leaving behind radioactive and chemical wastes in two disposal areas and a waste tank farm. Site operations also resulted in releases of radioactivity to site soils, groundwater, and to surface waters draining the site. The New York State Energy Research and Development Authority (NYSERDA) and the U.S. Department of Energy (DOE) are collaborating in a process of decision making for decommissioning those facilities remaining at the WNYNSC following the completion of Phase 1 decommissioning. Neptune and Company, Inc. (Neptune) was contracted to develop a probabilistic performance assessment (PPA) computer model to assist the agencies in this process. The PPA Model includes a contaminant transport component focusing on the movement of contaminants within and among environmental media including groundwater and surface water transport, contaminant translocation by plants and animals, diffusion, and erosion. The model also includes evaluation of potential exposure and health effects for a Resident Farmer exposure scenario, where the Resident Farmer represents a critical group, described as that group of individuals reasonably expected to receive the greatest exposure to residual radioactivity for any applicable set of circumstances. The West Valley Site is located in the glaciated Allegheny Plateau region of western New York State. The waste reprocessing and disposal areas were constructed on a relatively fat area of plateau dissected by drainages of Buttermilk Creek, including Erdman Brook, Franks Creek, and Quarry Creek. An important aspect of the contaminant transport component of the PPA model is consideration of erosive processes such as slumping of the stream slopes and the advance of gullies from these streams. These erosion processes remove material from the plateau, growing the size of the creek valleys and making them wider and deeper. Of particular interest for the impact of erosion is radioactive waste contained in the Nuclear Regulatory Commission (NRC)-Licensed Disposal Area (NDA), the New York State-Licensed Disposal Area (SDA), and residual radiological inventory in the underground storage tanks at the Waste Tank Farm (WTF). The PPA Model is organized around geographically-defined facilities which were constructed upon the plateau, including the NDA, SDA, and WTF. Ongoing stream erosion processes will potentially transfer radioactive waste and residual inventory from these facilities to the ground surface on adjacent hillslope areas where erosion has breached the facility. Hence, it is important to evaluate the consequences of potential exposures to a Resident Farmer on the hillslopes below a breached facility. Two interrelated aspects of the dose assessment model related to hillslope exposure are discussed: 1) representation of the physical processes related to transport of radionuclides from facilities onto the hillslopes, and from the hillslopes into adjoining creeks where contaminated material migrates downstream with surface water and sediment, and; 2) adaptation of the activities associated with the Resident Farmer scenario to assess potential exposures to contamination in the hillslope areas. This discussion will cover the conceptual basis of the hillslope exposure and transport models, and also implementation in the PPA computer model. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Hurricanes and turbulent floods threaten arsenic-contaminated coastal soils and vulnerable communities

Coastal environments, particularly those adjacent to Superfund sites, are at increased risk of contaminant release during natural disasters, posing serious threats to nearby communities. To investigate this issue, we employed an advanced laboratory flood simulator to impose arsenic-contaminated sediments to turbulent flooding events. We further monitored changes in arsenic collocation and solid-phase speciation using advanced synchrotron radiation-based techniques to understand the impacts of flooding on arsenic mobility. Our results demonstrate that turbulent conditions significantly enhance the resuspension of arsenic-rich sediments, resulting in increased arsenic release into the water. This mobilization is driven by the erosion of the reduced sediments and the redox-mediated transformation and dissolution of Fe and Mn (oxyhydr) oxides, which promote the release of As(III). We found that arsenic speciation on resuspended particles is closely tied to shear stress, with As(V) prevailing at low stress and the more toxic As(III) dominating at higher stress levels. In the post-erosion phase, solid-phase As(III) decreased while dissolved As(III) increased, indicating ongoing desorption. The persistence of multiple arsenic species on resuspended particles marks them as potential long-range transport vectors. Thus, the environmental impact of flooding and sediment resuspension extends beyond the event itself, raising longer-term concerns for arsenic mobility. Our comprehensive geospatial analysis revealed substantial overlap between arsenic-contaminated soils and regions at high risk of flooding and hurricanes across the conterminous United States. This overlap disproportionately impacts economically disadvantaged and marginalized communities. Approximately 40 million Americans reside within 10 kilometers of these high-risk contaminated zones, with nearly 28 million exposed to hurricane threats and around 18 million vulnerable to flooding risks. Alarmingly, over 40% of those affected by hurricanes and 33% of those impacted by flooding belong to underrepresented minority and low-income populations. These findings highlight the urgent need for targeted mitigation strategies to protect public health and address environmental justice concerns.

54 ENVIRONMENTAL SCIENCES↗

Climate-driven tradeoffs between landscape connectivity and the maintenance of the coastal carbon sink

Abstract Ecosystem connectivity tends to increase the resilience and function of ecosystems responding to stressors. Coastal ecosystems sequester disproportionately large amounts of carbon, but rapid exchange of water, nutrients, and sediment makes them vulnerable to sea level rise and coastal erosion. Individual components of the coastal landscape (i.e., marsh, forest, bay) have contrasting responses to sea level rise, making it difficult to forecast the response of the integrated coastal carbon sink. Here we couple a spatially-explicit geomorphic model with a point-based carbon accumulation model, and show that landscape connectivity, in-situ carbon accumulation rates, and the size of the landscape-scale coastal carbon stock all peak at intermediate sea level rise rates despite divergent responses of individual components. Progressive loss of forest biomass under increasing sea level rise leads to a shift from a system dominated by forest biomass carbon towards one dominated by marsh soil carbon that is maintained by substantial recycling of organic carbon between marshes and bays. These results suggest that climate change strengthens connectivity between adjacent coastal ecosystems, but with tradeoffs that include a shift towards more labile carbon, smaller marsh and forest extents, and the accumulation of carbon in portions of the landscape more vulnerable to sea level rise and erosion.

54 ENVIRONMENTAL SCIENCES↗

Riverbank temperatures on the Selawik River, Alaska 2010-2012, and Koyukuk River, Alaska June to July 2018.

The data package includes temperature measurements from riverbanks along the Selawik and Koyukuk Rivers in northwest Alaska. The Selawik River data also includes meteorological data collected locally and the Koyukuk River includes bulk density and ice content data from the riverbanks. The Selawik River data was collected between 2010 and 2013 with meteorological data collected for the entire time period and riverbank temperatures collected in shorter time intervals between 2010 to 2012. All of the Selawik River data were collected a single river bend. The Koyukuk River temperature data was collected from late June to early July 2018 at a total of five locations on three riverbanks. Ice content measurements on the Koyukuk were made at five riverbank locations. The data collection on both rivers was done in support of studies on the influence of permafrost on riverbank erosion. The temperature data was collected to monitor the thermal conditions of the river banks both seasonally and during periods of erosion. The ice content of the banks was measured to better understand how bank erosion rates are influenced by ice in the frozen riverbanks.

54 ENVIRONMENTAL SCIENCES↗