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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.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Native bee Pollination Ecosystem Services in Agricultural Wetlands and Riparian Protected Lands

Abstract Many freshwater wetlands and riparian systems are protected within agricultural landscapes. Yet, pollinator ecosystem services are seldom considered key ecosystem services provided by these conservation easements. The purpose of this study is to explore the extent of protected aquatic lands to provide pollination ecosystem services by assessing pollinator abundances, crop yield changes, and value estimations of increased soybean yields from a subset of common native solitary bees. We created a novel geodatabase of United States Department of Agriculture (USDA) conservation easements and used this database in the InVEST crop pollination model to model wild solitary bee pollination. We then estimated the monetary value of yield increases provided by pollinators. We found that wetland uplands provided the greatest potential for pollination services for ground nesting bees, followed by herbaceous and forested riparian respectively. Stem nesters preferred forested riparian, then upland habitats. In soybeans fields, we found wild pollinators can provide up to 5.5% yield response from current private aquatic conservation lands. The current landscape is not optimized to use wetlands and riparian conservation lands as pollinator habitat, but these results suggest protected aquatic lands can sustainably increase wild pollination services to agricultural crops if landscapes are managed, protected, and optimized with pollinator services as co-benefit.

Hinson, Audra L. (ORCID:0000000242314820)↗
DOE OSTI2023

Intensification differentially affects the delivery of multiple ecosystem services in subtropical and temperate grasslands

Intensification, the process of intensifying land management to enhance agricultural goods, results in “intensive” pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO 2 and CH 4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO 2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH 4 emissions from subtropical pastures and reduced CH 4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Enhanced water use efficiency in global terrestrial ecosystems under increasing aerosol loadings

Aerosols play a crucial role in the climate system, affecting incoming radiation and cloud formation. Based on a modelling framework that couples ecosystem processes with the atmospheric transfer of radiation, we analyze the effect of aerosols on surface incoming radiation, gross primary productivity (GPP), water losses from ecosystems through evapotranspiration (ET) and ecosystem water use efficiency (WUE, defined as GPP/ET) for 2003–2010 and validate them at global FLUXNET sites. The total diffuse radiation increases under relatively low or intermediate aerosol loadings, but decreases under more polluted conditions. We find that aerosol-induced changes in GPP depend on leaf area index, aerosol loading and cloudiness. Specifically, low and moderate aerosol loadings cause increases in GPP for all plant types, while heavy aerosol loadings result in enhancement (decrease) in GPP for dense (sparse) vegetation. On the other hand, ET is mainly negatively affected by aerosol loadings due to the reduction in total incoming radiation. Finally, WUE shows a consistent rise in all plant types under increasing aerosol loadings. Overall, the simulated daily WUE compares well with observations at 43 eddy-covariance tower sites (R 2 =0.84 and RMSE=0.01gC (kg H 2 O) -1 ) with better performance at forest sites. In addition to the increasing portions of diffuse light, the rise in WUE is also favored by the reduction in radiation- and heat-stress caused by the aerosols, especially for wet and hot climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hydrometeorological sensitivities of net ecosystem carbon dioxide and methane exchange of an Amazonian palm swamp peatland

Here, we report ecosystem-scale CO 2 and CH 4 flux observations for an Amazonian palm swamp peatland over a two-year period in relation to hydrometeorological forcings. Seasonal and short-term variations in hydrometeorological forcing had a strong effect on carbon dioxide and methane fluxes. High air temperature and vapor pressure deficit exerted an important limitation on photosynthesis during the dry season, while latent heat flux appeared to be insensitive to these climate drivers. Evidence from light-response analyses and flux partitioning support that photosynthetic activity was downregulated during dry conditions, while ecosystem respiration was either inhibited or enhanced depending on water table position. The cumulative net ecosystem carbon dioxide exchange indicated that the peatland was a significant carbon dioxide sink ranging from –465 (–279 to –651) g C m -2 y -1 in 2018 to –462 (–277 to –647) g C m -2 y -1 in 2019. The forest was a methane source of 22 (20 to 24) g C m -2 y -1 , similar in magnitude to other tropical peatlands and larger than boreal and arctic peatlands. Furthermore, the annual carbon budget of this Amazonian palm swamp peatland appears to be a major carbon sink under current hydrometeorological conditions, but evidence indicates that the sink strength is vulnerable to future climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration

Plant hydraulics substantially affects terrestrial water and carbon cycles by modulating water transport and carbon assimilation. Despite improved drought simulations in certain ecosystems through their integration into land surface models (LSMs), the broader application of plant hydraulics in diverse ecosystems and hydroclimates is still underexplored. Here, in this study, we implemented the recently developed Noah-Multiparameterization Land Surface Model (Noah-MP LSM) equipped with a plant hydraulics scheme (Noah-MP-PHS) across 40 FLUXNET sites globally. Employing the Shuffled Complex Evolution-University of Arizona (SCE-UA) auto-calibration algorithm, we optimized key plant hydraulics parameters for these sites spanning eight vegetation types in both arid and humid climates. Noah-MP-PHS significantly improves the simulation of evapotranspiration (ET) and gross primary production (GPP) by better representing atmospheric and soil water stress compared to traditional soil hydraulic schemes (SHSs, such as Noah and CLM). The augmented Noah-MP-PHS models reduce surface flux overestimation and underestimation, exhibiting an average increase of 0.14 and 0.15 in Kling-Gupta Efficiency (KGE) compared to Noah and CLM, respectively. The explicit consideration of plant capacitance in PHS reveals substantial deep-layer and nocturnal root water uptake especially under dry conditions. We employed eXplainable Machine learning (XML) to quantify the model’s relative sensitivity to newly introduced leaf-, stem and root-related parameters in PHS. The sensitivity analysis reveals a rise in root parameter importance and a decline in leaf and stem parameters as conditions shift from humid to arid. These findings indicate that as aridity states vary, the most influential parameters affecting surface fluxes variation may change in parameter calibration for PHS applications. Our findings underscore the importance of incorporating plant hydraulics into LSMs to enhance simulations of terrestrial water and carbon dynamics. These findings are crucial for understanding ecosystem responses to global climate changes and guide the broader application of PHS at larger scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Improving water quality in the Chesapeake Bay using payments for ecosystem services for perennial biomass for bioenergy and biofuel production

Replacing row crops with perennial bioenergy crops may reduce nitrogen (N) loading to surface waters. We estimated the benefits, costs, and potential for replacing maize with switchgrass to meet required N loading reduction targets for the Chesapeake Bay (CB) of 26.9 Gg -1 . After subtracting the potential reduction in N loading due to improved N fertilizer practices for maize, a further 22.8 Gg reduction is required. Replacing maize with fertilized switchgrass could reduce N loading to the CB by 18 kg ha -1 y -1 , meeting 31% of the N reduction target. The break-even price of fertilized switchgrass to provide the same profit as maize in the CB is 111 $Mg -1 (oven-dry basis throughout). Growers replacing maize with switchgrass could receive an ecosystem service payment of 148 ha -1 based on the price paid in Maryland for planting a rye cover crop. For our estimated average switchgrass yield of 9.9 Mg ha -1 , and the greater N loading reduction of switchgrass compared to a cover crop, this equates to 24 dollars Mg -1 . The annual cost of this ecosystem service payment to induce switchgrass planting is 13.29 dollars kg -1 of N. Using the POLYSYS model to account for competition among food, feed, and biomass markets, we found that with the ecosystem service payment for switchgrass of 25 $ Mg -1 added to a farm-gate price of 111 dollars Mg -1 , 11% of the N loading reduction target could be met while also producing 1.3 Tg of switchgrass, potentially yielding 420 dam 3 y -1 of ethanol.

09 BIOMASS FUELS↗
DOE OSTI2017

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States

Spring phenology of temperate ecosystems is highly sensitive to climate change, generating various impacts on many important terrestrial surface biophysical processes. Although various prognostic models relying on environmental variables of temperature and photoperiod have been developed for spring phenology, comprehensive ecosystem-scale evaluations over large landscapes and long-time periods remain lacking. Further, environmental variables other than temperature and photoperiod might also importantly constrain spring phenology modelling but remain under-investigation. To address these issues, we leveraged around 20-years datasets of environmental variables (from Daymet and GLDAS products) and the spring phenology metric (i.e., the greenup date) respectively derived from MODIS and PhenoCams across 108 sites in the Northern and Eastern United States. We firstly cross-compared MODIS-derived greenup date with official PhenoCams product with high accuracy (R 2 = 0.70). Then, we evaluated the three prognostic models (i.e., Growing Degree Date (GDD), Sequential (SEQ) and optimality-based (OPT)) with MODIS-derived spring phenology, assessed the model residuals and their associations with soil moisture, rainfall, and solar radiation, and revised the two photoperiod-relevant models (SEQ, OPT) by replacing the daylength variable with solar radiation, which was found to contribute the most to model residuals. We found that 1) all models demonstrated good capability in characterizing spring phenology, with OPT performing the best (RMSE = 8.04 ± 5.05 days), followed by SEQ (RMSE = 10.57 ± 7.77 days) and GDD (RMSE = 10.84 ± 8.42 days), 2) all models displayed high model residuals showing tight correlation with solar radiation (r = 0.45–0.75), and 3) the revised models that included solar radiation significantly performed better with an RMSE reduction by 22.08%. Such results are likely because solar radiation better constrains early growing season plant photosynthesis than photoperiod, supporting the hypothesis of spring phenology as an adaptive strategy to maximize photosynthetic carbon gain (approximated by solar radiation) while minimizing frost damage risk (captured by temperature). Collectively, our study here reveals the underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems, and suggests ways to improve spring phenology modelling and other phenology-related ecological processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH 4 ) fluxes from riparian forests is available. Here, in this work, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH 4 fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH 4 fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH 4 consuming 0.24 kg CH 4 -C ha –1 y –1 . Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH 4 fluxes between the wet and dry periods. During the wet period, 83% of CH 4 was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH 4 was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH 4 sink. Our results together with past measurements of CH 4 fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH 4 sinks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exposure pathways and bioaccumulation of per- and polyfluoroalkyl substances in freshwater aquatic ecosystems: Key considerations

We report that due to the bioaccumulative behavior, toxicity, and recalcitrance to degradation, per- and polyfluoroalkyl substances (PFAS) are a focus for many researchers investigating freshwater aquatic ecosystems. PFAS are a diverse set of chemicals that accumulate and transport quite differently in the environment depending on the length of their fluoroalkyl chains and their functional groups. This diversity in PFAS chemical characteristics combined with varying environmental factors also impact the bioaccumulation of these compounds in different organisms. In this review, we evaluate environmental factors (such as organic carbon, proteins, lipids, and dissolved cations) as well as PFAS characteristics (head group, chain-length, and concentration) that contribute to the significant variation seen in the literature of bioaccumulation metrics reported for organisms in aquatic ecosystems. Of the factors evaluated, it was found that PFAS concentration, dissolved organic matter, sediment organic matter, and biotransformation of precursor PFAS tended to significantly impact reported bioaccumulation metrics the most. Based on this review, it is highly suggested that future studies provide sufficient details of important environmental factors, specific organism traits/ behavior, and PFAS concentrations/compounds when reporting on bioaccumulation metrics to further fill data gaps and improve our understanding of PFAS in aquatic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Plant and microbial biomarkers suggest mechanisms of soil organic carbon accumulation in a Mojave Desert ecosystem under elevated CO 2

We ireport on how properties of soil organic matter (SOM) were altered after 10 years exposure to elevated atmospheric CO 2 concentration ([CO 2 ]) in a Mojave Desert ecosystem, using plant and microbial biomarkers. We focused on roles of Larrea tridentata, the dominant evergreen shrub which form islands of fertility, and biological soil crusts which have extensive cover in plant interspace. Soils to 5 cm in depth were collected under L. tridentata and plant interspace, and biological soil crusts to 0.5 cm in depth under three cover types, Pleuraphis rigida , a C 4 grass, shrubs and plant interspace. Soil organic carbon contents were not significantly different between elevated and ambient [CO 2 ]. Yet, significantly higher abundance of n-alkanes, a major constituent of foliage wax material, occurred in the elevated compared to ambient [CO 2 ] plots in the soils collected under L. tridentata , but no such difference was found in the soils at plant interspace or the biological soil crusts. There was no critical difference in abundance of microbial phospholipid fatty acids between the CO 2 treatments in the soils of either cover types. However, neutral lipid fatty acid abundance was significantly higher under elevated than ambient [CO 2 ] in the soils under L. tridentata , whereas no such significant difference was observed at plant interspace. These results emphasize important roles of the dominant shrubs in SOM formation under elevated [CO 2 ] in arid ecosystems. Elevated [CO 2 ] stimulated growth of L. tridentata in wet years, and aboveground litter deposition via senescence contributed to SOM formation in islands of fertility. In addition, elevated [CO 2 ] stimulated soil microbial turnover rates in rhizosphere of L. tridentata , which left more soil microbial necromass, a major SOM source. We concluded that responses of dominant shrubs to elevated [CO 2 ] can stimulate SOM formation in arid ecosystems, but biological soil crusts may have limited capacity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Climatic Controls on Soil Carbon Accumulation and Loss in a Dryland Ecosystems

Arid and semiarid ecosystems drive year-to-year variability in the strength of the terrestrial carbon (C) sink, yet there is uncertainty about how soil C gains and losses contribute to this variation. For this work, to address this knowledge gap, we embedded C-depleted soil mesocosms, containing litter or biocrust C inputs, within an in situ dryland ecosystem warming experiment. Over the course of one year, changes in microbial biomass and total soil organic C pools were monitored alongside hourly measurements of soil CO 2 flux. We also developed a biogeochemical model to explore the mechanisms that gave rise to observed soil C dynamics. Field data and model simulations demonstrated that water exerted much stronger control on soil biogeochemistry than temperature, with precipitation events triggering large CO 2 pulses and transport of litter- and biocrust-derived C into the soil profile. We expected leaching of organic matter would result in steady accumulation of C within the mineral soil over time. Instead, the size of the total organic C pool fluctuated throughout the year, largely in response to microbial growth: increases in the size of microbial biomass were negatively correlated with the quantity of C residing in the top 2 cm, where most biogeochemical changes were observed. Our data and models suggest that microbial responses to precipitation events trigger rapid metabolism of dissolved organic C inputs, which strongly limit accumulation of autotroph-derived C belowground. Accordingly, changes in the magnitude and/or frequency of precipitation events in this dryland ecosystem could have profound impacts on the strength of the soil C sink.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Soil Respiration Responses to Throughfall Exclusion Are Decoupled From Changes in Soil Moisture for Four Tropical Forests, Suggesting Processes for Ecosystem Models

Abstract Climatic drying is predicted for many tropical forests yet models remain poorly parameterized for these ecosystems, hampering predictions of forest‐climate interactions. We applied an integrated model–experiment approach, parameterizing an ecosystem model with tropical forest observational data and comparing model predictions to a field drying manipulation. We hypothesized that drying suppresses soil CO 2 fluxes (i.e., respiration) in relatively dry tropical forests but increases CO 2 fluxes in wetter tropical forests by alleviating anaerobiosis. We measured soil CO 2 fluxes during wet‐dry cycles from 2015 to 2022 in four Panamanian forests that vary in rainfall and soil fertility. Measured soil CO 2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in lower soil moisture optima for respiration than previously modeled. We then parameterized the model using field data and the new moisture‐respiration response functions. The updated model predicted increased soil CO 2 fluxes with drying in wetter and fertile forests and suppressed fluxes in drier, infertile forests. In contrast to model predictions, a chronic throughfall exclusion experiment initially suppressed soil respiration across forests, with sustained suppression for four years in the wettest forest only (−28% ± 4% during the dry season). In the fertile forest, drying eventually elevated CO 2 fluxes over this period (+75% ± 28% during the late wet season). The unexpected negative drying effect in the wettest, infertile forest could have resulted from reduced vertical flushing of nutrients into soils. Including hydro‐nutrient interactions in ecosystem models could improve predictions of tropical forest‐climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems

Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO 2 ) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO 2 increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Freshwater Biogeochemical Hotspots: High Primary Production and Ecosystem Respiration in Shallow Waterbodies

Abstract Ponds, wetlands, and shallow lakes (collectively “shallow waterbodies”) are among the most biogeochemically active freshwater ecosystems. Measurements of gross primary production (GPP), respiration (R), and net ecosystem production (NEP) are rare in shallow waterbodies compared to larger and deeper lakes, which can bias our understanding of lentic ecosystem processes. In this study, we calculated GPP, R, and NEP in 26 small, shallow waterbodies across temperate North America and Europe. We observed high rates of GPP (mean 8.4 g O 2 m −3 d −1 ) and R (mean −9.1 g O 2 m −3 d −1 ), while NEP varied from net heterotrophic to autotrophic. Metabolism rates were affected by depth and aquatic vegetation cover, and the shallowest waterbodies had the highest GPP, R, and the most variable NEP. The shallow waterbodies from this study had considerably higher metabolism rates compared to deeper lakes, stressing the importance of these systems as highly productive biogeochemical hotspots.

Geology↗
DOE OSTI2026

Investigating Coastal Vegetation Dynamics and Ecosystem Impacts Under Elevated CO 2 and Temperature: A Process‐Based Approach

Coastal forests are increasingly vulnerable to climate change and sea-level rise, with flooding and salinity driving transitions to marsh-dominated ecosystems. Using the coastal version of FATES-Hydro, we conducted 30-year simulations at two coastal forest sites—a broadleaf swamp white oak stand at Lake Erie and a conifer loblolly pine stand at Chesapeake Bay—under historical climate and elevated CO 2 (+100 ppm) and temperature (+1.5°C) scenarios. Elevated CO 2 increased net primary productivity at both sites, while warming alone intensified hydraulic stress and accelerated mortality, particularly in the conifer stand. Simulations show that elevated temperatures intensify vapor pressure deficit and hydraulic stress on trees already experiencing salinity- and submersion-driven water stress, increasing tree mortality beyond what would be expected in a non-water-limited environment. Marsh expansion partially compensated for tree loss at the Lake Erie site but reduced ecosystem productivity in the conifer forest at Chesapeake Bay. In conclusion, our results highlight how differences in stand structure, phenology, and local hydrology modulate ecosystem trajectories under climate change, emphasizing the importance of demographic and community-level processes for predicting the fate of coastal forests.

Ding, Junyan [Barcelona Supercomputing Center (BSC↗
DOE OSTI2025

A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial‐Aquatic Interfaces

Interconnected landscape features such as terrestrial‐aquatic interfaces play an outsized role in biogeochemical cycles as ecosystem control points, but it is notoriously challenging to characterize these. Here, we document a synoptic sensor network design that is (a) flexible to accommodate diverse ecosystem interfaces and gradients, (b) adaptable to monitoring and modeling needs of small and large projects alike, (c) standardized for intercomparability across sites and field experiments, and (d) adequately replicated to capture heterogeneity of each parameter monitored. This real‐time monitoring of surface water, groundwater, soil, and vegetation supports configuration and evaluation of models that span upland, wetland, open water strata, and transitions between them. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including large‐scale flood manipulation experiments in both regions. A central design element is “one data logger program to rule them all”—a collection of sensor‐specific modules deployed on 40 loggers controlling ∼2,000 sensors, with the goal of streamlining maintenance, debugging, and reproducible data processing. The network generates ∼6 M observations per month, capturing system dynamics at the broad spatial and fine temporal scales needed to initialize and benchmark models; measurement frequency can be modified remotely to capture events. This network design has also revealed behaviors not represented in Earth system models, such as transient groundwater oxygen pulses. Completely documented and open source, this standardized, flexible, and efficient sensor network design can reduce barriers to understanding environmental changes and ecosystem responses across systems and scales.

Ward, Nicholas D. [Pacific Northwest National Labo↗
DOE OSTI2015

Using Ecosystem Experiments to Improve Vegetation Models

Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.

54 ENVIRONMENTAL SCIENCES↗