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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

On the influence of ENSO complexity on Pan-Pacific coastal wave extremes

Significance This study demonstrates how the main wave regimes in the Pacific, in particular related to tropical and extratropical storm activity, are activated by different El Niño/Southern Oscillation (ENSO) teleconnections patterns. By combining these robust relationships with the latest theoretical advances in ENSO research, a mathematical model of wave energy modulation is derived. It allows a better representation of wave extremes over a range of time scales wider than previously possible with the previous baseline understanding of ENSO’s influence on coastal impacts. This paves the way for unprecedented seasonal to monthly forecasts of coastal hazards around the densely populated Pacific basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Kim et al., "Variations in the optical and molecular composition of dissolved organic matter exported from coastal wetlands"

Knowledge about sources and composition of marsh-derived dissolved organic matter (DOM) is critical for understanding the role of marshes in coastal biogeochemical cycling and the fate of marsh-derived DOM in the ocean. To investigate tidal variability in composition of marsh-derived DOM, Kim et al. examined the optical and molecular characteristics of hourly surface water samples at three tidal creeks in the Chesapeake Bay. Groundwater samples along the terrestrial landscape gradient as well as estuarine water from the adjacent estuary at each site were also collected to help resolve sources of surface water DOM. Samples were collected in summer 2024 at three sites – SWH: Sweet Hall Marsh, GCW: Kirkpatrick Marsh, and GWI: Goodwin Islands – which are part of synoptic sites in the Chesapeake Bay region of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales - Field, Measurements, and Experiments) project. Surface water samples were collected hourly over a 48-hour period at each site. Groundwater and estuarine water samples were collected once. This dataset includes- Surface water depth and salinity- Dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) concentrations- Optical indices and relative composition of parallel factor analysis (PARAFAC) components- High resolution mass spectrometry data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Geometric and Material Variability Influences Stress States Relevant to Coastal Permafrost Bluff Failure

Scientific knowledge and engineering tools for predicting coastal erosion are largely confined to temperate climate zones that are dominated by non-cohesive sediments. The pattern of erosion exhibited by the ice-bonded permafrost bluffs in Arctic Alaska, however, is not well-explained by these tools. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is needed. We conducted physics-based numerical simulations of mechanical response that focus on the impact of geometric and material variability on permafrost bluff stress states for a coastal setting in Arctic Alaska that is prone to toppling mode block failure. Our three-dimensional geomechanical boundary-value problems output static realizations of compressive and tensile stresses. We use these results to quantify variability in the loci of potential instability. We observe that niche dimension affects the location and magnitude of the simulated maximum tensile stress more strongly than the bluff height, ice wedge polygon size, ice wedge geometry, bulk density, Young's Modulus, and Poisson's Ratio. Our simulations indicate that variations in niche dimension can produce radically different potential failure areas and that even relatively shallow vertical cracks can concentrate displacement within ice-bonded permafrost bluffs. These findings suggest that stability assessment approaches, for which the geometry of the failure plane is delineated a priori, may not be ideal for coastlines similar to our study area and could hamper predictions of erosion rates and nearshore sediment/biogeochemical loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Estimation of Aerosol Columnar Size Distribution from Spectral Extinction Data in Coastal and Maritime Environment

Aerosol columnar size distributions (SDs) are commonly provided by aerosol inversions based on measurements of both spectral extinction and sky radiance. These inversions developed for a fully clear sky offer few SDs for areas with abundant clouds. Here, we estimate SDs from spectral extinction data alone for cloudy coastal and maritime regions using aerosol refractive index (RI) obtained from chemical composition data. Our estimation involves finding volume and mean radius of lognormally distributed modes of an assumed bimodal size distribution through fitting of the spectral extinction data. We demonstrate that vertically integrated SDs obtained from aircraft measurements over a coastal site have distinct seasonal changes, and these changes are captured reasonably well by the estimated columnar SDs. We also demonstrate that similar seasonal changes occur at a maritime site, and columnar SDs retrieved from the combined extinction and sky radiance measurements are approximated quite well by their extinction only counterparts (correlation exceeds 0.9) during a 7-year period (2013–2019). The level of agreement between the estimated and retrieved SDs depends weakly on wavelength selection within a given spectral interval (roughly 0.4–1 µm). Since the extinction-based estimations can be performed frequently for partly cloudy skies, the number of periods where SDs can be found is greatly increased.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

An Overview of the IGOS Coastal Theme

The Integrated Global Observing Strategy (IGOS) Coastal Observation Theme seeks to develop a strategy for integrated global observations that will provide improved understanding of earth system variability and change in the coastal zone, with a particular emphasis on the land-sea-air interface. The program's representatives, expected benefits, milestones, priorities and observing requirements are outline in this presentation.

oceanography↗
NASA NTRS2017

Atmospheric Correction for Hyperspectral Ocean Color Retrieval with Application to the Hyperspectral Imager for the Coastal Ocean (HICO)

The classical multi-spectral Atmospheric Correction (AC) algorithm is inadequate for the new generation of spaceborne hyperspectral sensors such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and scattering by aerosols from the measured top-of-atmosphere (TOA) radiance, compensate for the absorption by atmospheric gases, and correct for reflection and refraction of the air-sea interface. In this work, we present and evaluate an improved AC for hyperspectral sensors developed within NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System software package (SeaDAS). The improvement is based on combining the classical AC approach of multi-spectral capabilities to correct for the atmospheric path radiance, extended to hyperspectral, with a gas correction algorithm to compensate for absorbing gases in the atmosphere, including water vapor. The SeaDAS-hyperspectral version is capable of operationally processing the AC of any hyperspectral airborne or spaceborne sensor. The new algorithm development was evaluated and assessed using the Hyperspectral Imager for Coastal Ocean (HICO) scenes collected at the Marine Optical BuoY (MOBY) site, and other SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and AERosol Robotic NETwork - Ocean Color (AERONET-OC) coastal sites. A hyperspectral vicarious calibration was applied to HICO, showing the validity and consistency of HICO's ocean color products. The hyperspectral AC capability is currently available in SeaDAS to the scientific community at https://oceancolor.gsfc.nasa.gov/.

Ocean Color↗
NASA NTRS2020

Robust Algorithm for Estimating Total Suspended Solids (TSS) in Inland and Nearshore Coastal Waters

One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP) -based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N > 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (R(sub rs)), (b) retrieval of particulate backscattering (b(sub bp)) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from b(sub bp) via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m (exp 3)], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e., from 10 to > 100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in Rrs leads to < 20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads.

Total suspended solids↗
NASA NTRS2020

Enhancing New York City's resilience to sea level rise and increased coastal flooding

Accelerating Greenland and Antarctic Ice Sheet ice mass losses and potential West Antarctic Ice Sheet instability may lead to higher than previously anticipated future sea levels. The New York City Panel on Climate Change Antarctic Rapid Ice Melt (ARIM) upper-end, low probability sea level rise (SLR) scenario, which incorporates recent ice loss trends, improved ice sheet-ocean-atmosphere modeling, and potential ice sheet destabilization, projects SLR of up to 2.1 m by the 2080s and up to 2.9 m by 2100, at high greenhouse gas emissions (NPCC, 2019). These results exceed previous high-end SLR projections (90th percentile) of 1.5 m by the 2080s and 1.9 m by 2100, relative to 2000–2004 (NPCC, 2015). By 2100, the 1% annual chance (100-year) floodplain could cover 1/3 of the city's total area under ARIM; around 1/5 of the area could be flooded during monthly high tides. Some low-lying locations could become permanently inundated by late century. Will New York City coastal resiliency initiatives, guided, in part by NPCC findings, suffice for very high sea levels? Additional research is needed to determine technological, environmental, or economic limitations to coastal protection and to decide when and where strategic relocation may become necessary.

Sea level rise↗
NASA NTRS2024

Expanded Signal to Noise Ratio Estimates for Validating Next-Generation Satellite Sensors in Oceanic, Coastal, and Inland Waters

The launch of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) and the Surface Biology and Geology (SBG) satellite sensors will provide increased spectral resolution compared to existing platforms. These new sensors will require robust calibration and validation datasets, but existing field-based instrumentation is limited in its availability and potential for geographic coverage, particularly for coastal and inland waters, where optical complexity is substantially greater than in the open ocean. The minimum signal-to-noise ratio (SNR) is an important metric for assessing the reliability of derived biogeochemical products and their subsequent use as proxies, such as for biomass, in aquatic systems. The SNR can provide insight into whether legacy sensors can be used for algorithm development as well as calibration and validation activities for next-generation platforms. We extend our previous evaluation of SNR and associated uncertainties for representative coastal and inland targets to include the imaging sensors PRISM and AVIRIS-NG, the airborne-deployed C-AIR radiometers, and the shipboard HydroRad and HyperSAS radiometers, which were not included in the original analysis. Nearly all the assessed hyperspectral sensors fail to meet proposed criteria for SNR or uncertainty in remote sensing reflectance (R rs ) for some part of the spectrum, with the most common failures (>20% uncertainty) below 400 nm, but all the sensors were below the proposed 17.5% uncertainty for derived chlorophyll-a. Instrument suites for both in-water and airborne platforms that are capable of exceeding all the proposed thresholds for SNR and R rs uncertainty are commercially available. Thus, there is a straightforward path to obtaining calibration and validation data for current and next-generation sensors, but the availability of suitable high spectral resolution sensors is limited.

signal-to-noise ratio↗
DOE OSTI2025

Impact of Salinity on Ground Ice Distribution Across an Arctic Coastal Polygonal Tundra Environment

The heterogeneous distribution of ground ice in the Arctic is a key driver of uneven ground subsidence as permafrost thaws, significantly impacting infrastructure and surface/subsurface hydrology. These topographic and hydrological changes contribute to major uncertainties in energy and carbon fluxes and storage in a warming Arctic. This study aims to improve our understanding of the controls on ground ice and organic matter distribution within the top 3 m of permafrost in coastal polygonal tundra near Utqiagvik, Alaska. To this end, we apply a neural network approach to bulk density distributions derived from nondestructive X-ray tomography of soil cores, trained with laboratory analyses, to improve the resolution and spatial coverage of estimates of dry bulk density, ice content, and organic matter content. In addition, we use capacitively coupled geophysical imaging to map soil electrical conductivity and salinity variations. The results show that sedimentary deposits from ocean transgressions, along with subsequent ice wedge polygon geomorphological processes, jointly influence the distribution of ice content at various scales. The impact of the latter decreases with depth, whereas the influence of salinity and sedimentary history increases. Although the controls on the distribution of soil organic matter content (g/cm 3 ) remain unclear, the pronounced heterogeneity in bulk density strongly influences its calculation from laboratory mass fraction measurements (g/g). From a methodological perspective, the interdependencies among soil components and the need for increased data coverage underscore the value of high-resolution density measurements, such as using X-ray tomography. Overall, this study emphasizes the importance of considering salinity constraints on ice content distribution in coastal permafrost regions. The results are expected to aid in the development of data products and process representations in geomorphological and ecosystem models.

Dafflon, Baptiste [Lawrence Berkeley National Labo↗
DOE OSTI2026

Alternating salt and freshwater floods of coastal soils impact soil structure, hydraulic properties, and oxygen dynamics

Coastal soils are increasingly impacted by hydrologic intensification in the form of rising sea level and flooding from storm surges and precipitation. Alternating saltwater (SW) and freshwater (FW) exposure has the potential to disperse colloids, which can lead to disintegration of soil structure, clogging of pore spaces, and reduction in ecologically and biogeochemically important functions like infiltration or gas exchange. To investigate how hydrologic intensification affects soil structure and oxygen dynamics, we conducted a series of laboratory-based flood simulations. Intact soil cores of the A and B horizons (22 total) from the toe slope of an upland coastal forest along the western shore of Chesapeake Bay. We subjected the cores to 24 h of saturation with either FW or alternating brackish SW and FW, with a 24-h draining event in between flood events. Oxygen diffusion into soil during draining was reduced by up to 30% for soils flooded alternating SW-FW compared to soils flooded only with FW. We attributed the reduced oxygen diffusion to clogging of smaller pores by colloids, with colloid redistribution observed as an increase in specific surface area down the core profile of up to 59%. After three SW-FW floods (six floods total), there were significant changes in pore size distribution, significant redistribution of colloids, and the A horizon became sodic. We concluded that a small number of SW flooding events can induce a measurable change in soil physical properties that directly impacts the biogeochemical dynamics.

Rod, Kenton A. [Pacific Northwest National Laborat↗
DOE OSTI2024

Simulated plant-mediated oxygen input has strong impacts on fine-scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands

Methane (CH 4 ) emissions from wetland ecosystems are controlled by redox conditions in the soil, which are currently underrepresented in Earth system models. Plant-mediated radial oxygen loss (ROL) can increase soil O 2 availability, affect local redox conditions, and cause heterogeneous distribution of redox-sensitive chemical species at the root scale, which would affect CH 4 emissions integrated over larger scales. In this study, we used a subsurface geochemical simulator (PFLOTRAN) to quantify the effects of incorporating either spatially homogeneous ROL or more complex heterogeneous ROL on model predictions of porewater solute concentration depth profiles (dissolved organic carbon, methane, sulfate, sulfide) and column integrated CH 4 fluxes for a tidal coastal wetland. From the heterogeneous ROL simulation, we obtained 18% higher column averaged CH 4 concentration at the rooting zone but 5% lower total CH 4 flux compared to simulations of the homogeneous ROL or without ROL. This difference is because lower CH 4 concentrations occurred in the same rhizosphere volume that was directly connected with plant-mediated transport of CH 4 from the rooting zone to the atmosphere. Sensitivity analysis indicated that the impacts of heterogeneous ROL on model predictions of porewater oxygen and sulfide concentrations will be more important under conditions of higher ROL fluxes or more heterogeneous root distribution (lower root densities). Despite the small impact on predicted CH 4 emissions, the simulated ROL drastically reduced porewater concentrations of sulfide, an effective phytotoxin, indicating that incorporating ROL combined with sulfur cycling into ecosystem models could potentially improve predictions of plant productivity in coastal wetland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

Here, the objective of this work is to evaluate GOES-R based fog conditions occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. C-FOG is designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve its predictability. The project took place along coastlines and open water environments of Eastern Canada (Nova Scotia, NS and the Island of Newfoundland, NL) during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. During the C-FOG field campaign, instruments were located at the Ferryland Supersite, NL, with 2 main sites, and five satellite sites, as well as on the Research Vessel (R/V) Hugh R. Sharp. Key measurement instruments included a Gondola carrying a CDP (cloud droplet probe) and a BCP (backscatter cloud probe) was used for measuring droplet spectra from 1-75 µm on the R/V. A LPM (laser precipitation monitor) with 100 µm-1 cm size range and an OPC (optical particle counter) with 0.3-17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms (e.g. profiling microwave radiometer, PMWR), Ceilometer, Lidar), meteorological towers, tethered balloons, and GOES-R products (e.g. fog coverage and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and PMWR were comparable to ground based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short term local fog predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Improving coastal water level estimation by merging nadir-only satellite altimetry data into a hydrodynamic model

Providing robust real time flood warnings is of paramount importance to coastal communities. Although state-of-the-art hydrodynamic models are capable of robustly predicting Coastal Water Levels (CWL), unresolved drivers affecting level fluctuations are often not represented by the model governing equations. This work evaluates a novel method to improve the performance of the ADvanced CIRCulation (ADCIRC) hydrodynamic model by assimilating observations from four nadir-only satellite altimetry missions against a set of National Oceanic and Atmospheric Administration (NOAA) gauge stations located across the entire U.S. East Coast. Two different types of simulations were performed – Open Loop (OL) and Data Assimilation (DA). Five different simulations were performed where four different satellite altimetry observations were assimilated individually and combined with two different scenarios – with and without considering the data quality flags. Results indicate that, despite their limited spatial coverage, merging nadir-only observations into ADCIRC from the newly launched Surface Water and Ocean Topography (SWOT)’s nadir altimeter can improve the model performance at 76% of the gauge locations, whereas Sentinel-6 improves 73% of the total locations, Jason-3 74%, and SARAL 21%. Furthermore, combining observations from SWOT-nadir, Jason-3, and Sentinel-6 can improve the ADCIRC performance at more than 80% of the gauge locations for 107-day simulation. Nadir-only satellite altimetry observations can be useful for improving the model performance even if flagged as “poor quality” near the coast. When the flagged data are disregarded, SWOT can improve ADCIRC at 78%, Sentinel-6 at 73%, Jason-3 at 53%, and SARAL at 21% of the gauge locations. The ability to improve the model simulations largely depends on the availability of a satellite overpass nearby. Therefore, model performance can be further enhanced if satellite observations are available during a storm surge event, stressing the importance of frequent satellite overpasses.

Aafnan Bhuiyan, Soelem↗
DOE OSTI2024

Effects of Warming and Elevated CO2 on Stomatal Conductance and Chlorophyll Fluorescence of C3 and C4 Coastal Wetland Species

Abstract Coastal wetland communities provide valuable ecosystem services such as erosion prevention, soil accretion, and essential habitat for coastal wildlife, but are some of the most vulnerable to the threats of climate change. This work investigates the combined effects of two climate stressors, elevated temperature (ambient, + 1.7 °C, + 3.4 °C, and 5.1 °C) and elevated CO 2 ( e CO 2 ), on leaf physiological traits of dominant salt marsh plant species. The research took place at the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX) at the Smithsonian Environmental Research Center, which includes two plant communities: a C 3 sedge community and a C 4 grass community. Here we present data collected over five years on rates of stomatal conductance (g s ), quantum efficiency of PSII photochemistry ( F v / F m ), and rates of electron transport (ETR max ). We found that both warming and e CO 2 caused declines in all traits, but the warming effects were greater for the C 3 sedge. This species showed a strong negative stomatal response to warming in 2017 and 2018 (28% and 17% reduction, respectively in + 5.1 °C). However, in later years the negative response to warming was dampened to < 7%, indicating that S. americanus was able to partially acclimate to the warming over time. In 2022, we found that sedges growing in the combined + 5.1 °C e CO 2 plots exhibited more significant declines in g s , F v /F m , and ETR max than in either treatment individually. These results are important for predicting future trends in growth of wetland species, which serve as a large carbon sink that may help mitigate the effects of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Salinity exposure affects lower-canopy specific leaf area of upland trees in a coastal deciduous forest

Sea level rise and increasing storm surges are likely to affect the canopy physiology, ecology, and structure of coastal forests, even well in advance of tree mortality. Laboratory and greenhouse studies have documented that saltwater exposure can trigger changes in leaf-level physiology and morphology, but few in situ studies have examined how tree-specific leaf area (SLA), the ratio of leaf area to mass and a crucial trait and model parameter, is affected by saline soils. We conducted an observational study of SLA in a mid-Atlantic (USA) coastal deciduous forest, taking advantage of a natural gradient in salinity along a tidal creek. Measured SLA of the 239 trees and seven species sampled ranged from Carya glabra (N = 6 trees, mean SLA = 277.9±36.3cm 2 /g) to Fagus grandifolia (N=60, 321.9±62.9cm 2 g); as expected, trees species and canopy position (sun versus shade) significantly affected SLA. For trees (N=100) directly exposed to the tidal creek, salinity was highly significant after accounting for species (P<0.001), with trees in the lower reaches of the creek having lower SLA. Leaf area index (LAI), computed from SLA and litter traps, ranged from 4.8 to 15.8 and was inversely related to salinity exposure; the spatial variability in leaf litter production contributed much more to LAI uncertainty than did SLA variability. These in situ results are correlative but consistent with the hypothesis, based on previous greenhouse studies, that the stress of chronic salinity exposure changes species’ leaf morphology. Our findings are useful for understanding the growing effects of saltwater intrusion into upland forests, as well as parameterizing and testing ecosystem-scale models simulating forest stressors and disturbances at the terrestrial-aquatic interface.

54 ENVIRONMENTAL SCIENCES↗