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DOE OSTI2025

Human–Earth system interactions under climate change

This special issue, titled ‘Focus on human–Earth system interactions under climate change,’ compiles cutting-edge research that deepens our understanding of the complex feedback mechanisms between anthropogenic activities and Earth system processes in the context of a changing climate (figure 1). The featured articles employ a diverse array of methodologies—including field studies, remote sensing, modeling, and socio-ecological analyses—to explore these interconnections. A unifying theme across these contributions is the imperative to bridge disciplinary divides, integrating physical Earth sciences with social sciences to fully capture the spectrum of human-Earth system interactions. Key topics addressed the impacts of human activities on natural systems, encompassing land-use change and water resource management on biogeochemistry, climate dynamics, and feedback on the climate system and socioeconomics from local to global scales under a changing climate.

Li, Huidong [Vanderbilt Univ., Nashville, TN (Unit↗

DOE OSTI2022

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S ppt with different satellite products: S ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S ppt . Our finding of the overall decline in S ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

Leaf trait relationships are widely used to predict ecosystem function in Terrestrial Biosphere Models (TBMs), in which leaf maximum carboxylation capacity (V c,max ), an important trait for modelling photosynthesis, can be inferred from other easier- to-measure traits. However, whether trait-V c,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V c,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V c,max and the four morphological and biochemical traits (R 2 ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. In contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V c,max relationships across three forest biomes into a single robust model for V c,max (R 2 = 0.77), and also accurately estimated the four traits (R 2 = 0.75-0.94). Furthermore, these findings challenge the traditional use of empirical trait-V c,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterizing V c,max and multi-trait variability, with critical insights into ecosystem modeling and functional trait ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Electromagnetic Induction (EMI) Data, 2024, Trail Creek, Colorado

This dataset contains Electromagnetic Induction (EMI) data collected at Trail Creek, Colorado, in 2024. EMI surveys were conducted to investigate the spatial distribution of electrical conductivity in the subsurface, providing insights into soil moisture and subsurface geological features. The surveys were performed along multiple transects to capture variations in conductivity influenced by changes in soil composition, moisture content, and underlying geological structures. This dataset complements other geophysical data collected in the region, including Electrical Resistivity Tomography (ERT) and Terrestrial LiDAR Scanning (TLS), providing a detailed understanding of the subsurface and its impact on surface vegetation and hydrological processes. The data are valuable for environmental geophysics, ecological research, and hydrological modeling in mountainous ecosystems. The files include: - data.zip: the raw EMI data (.csv) - inversion.zip: the inverted resistivity model (.csv and .kml) - kriging.zip: the kriging resistivity model (.csv, .tif, .kmz) - flmd.csv: file level metadata file describing all files within this dataset - dd.csv: data dictionary file describing the column headers within CSV files This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

CMD Mini-Explorer↗

DOE OSTI2022

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Determining the biogeochemical transformations of organic matter composition in rivers using molecular signatures

Inland waters are hotspots for biogeochemical activity, but the environmental and biological factors that govern the transformation of organic matter (OM) flowing through them are still poorly constrained. Here we evaluate data from a crowdsourced sampling campaign led by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to investigate broad continental-scale trends in OM composition compared to localized events that influence biogeochemical transformations. Samples from two different OM compartments, sediments and surface water, were collected from 97 streams throughout the Northern Hemisphere and analyzed to identify differences in biogeochemical processes involved in OM transformations. By using dimensional reduction techniques, we identified that putative biogeochemical transformations and microbial respiration rates vary across sediment and surface water along river continua independent of latitude (18°N–68°N). In contrast, we reveal small- and large-scale patterns in OM composition related to local (sediment vs. water column) and reach (stream order, latitude) characteristics. These patterns lay the foundation to modeling the linkage between ecological processes and biogeochemical signals. We further showed how spatial, physical, and biogeochemical factors influence the reactivity of the two OM pools in local reaches yet find emergent broad-scale patterns between OM concentrations and stream order. OM processing will likely change as hydrologic flow regimes shift and vertical mixing occurs on different spatial and temporal scales. As our planet continues to warm and the timing and magnitude of surface and subsurface flows shift, understanding changes in OM cycling across hydrologic systems is critical, given the unknown broad-scale responses and consequences for riverine OM.

rivers↗

DOE OSTI2024

Exploring Ecological, Morphological, and Environmental Controls on Coastal Foredune Evolution at Annual Scales Using a Process-Based Model

Coastal communities commonly rely upon foredunes as the first line of defense against sea-level rise and storms, thus requiring management guidance to optimize their protective services. Here, we use the AeoLiS model to simulate wind-driven accretion and wave-driven erosion patterns on foredunes with different morphologies and ecological properties under modern-day conditions. Additional sets of model runs mimic potential future climate changes to inform how both morphological and ecological properties may have differing contributions to net dune changes under evolving environmental forcing. This exploratory study, applied to represent the morphological, environmental, and ecological conditions of the northern Outer Banks, North Carolina, USA, finds that dunes experiencing minimal wave collision have similar net volumetric growth rates regardless of beach morphology, though the location and density of vegetation influence sediment deposition patterns across the dune profile. The model indicates that high-density, uniform planting strategies trap sediment close to the dune toe, whereas low-density plantings may allow for accretion across a broader extent of the dune face. The initial beach and dune shape generally plays a larger role in annual-scale dune evolution than vegetation cover. For steeper beach slopes and/or low dune toe elevations, the model generally predicts wave-driven dune erosion at the annual scale.

Environmental Sciences & Ecology↗

DOE OSTI2021

Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change

In September of 2020, Arctic sea ice extent was the second-lowest on record. State of the art climate prediction uses Earth system models (ESMs), driven by systems of differential equations representing the laws of physics. Previously, these models have tended to underestimate Arctic sea ice loss. The issue is grave because accurate modeling is critical for economic, ecological, and geopolitical planning. We use machine learning techniques, including random forest regression and Gini importance, to show that the Energy Exascale Earth System Model (E3SM) relies too heavily on just one of the ten chosen climatological quantities to predict September sea ice averages. Furthermore, E3SM gives too much importance to six of those quantities when compared to observed data. Finally, identifying the features that climate models incorrectly rely on should allow climatologists to improve prediction accuracy.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Weak-form inference for hybrid dynamical systems in ecology

Species subject to predation and environmental threats commonly exhibit variable periods of population boom and bust over long timescales. Understanding and predicting such behaviour, especially given the inherent heterogeneity and stochasticity of exogenous driving factors over short timescales, is an ongoing challenge. A modelling paradigm gaining popularity in the ecological sciences for such multi-scale effects is to couple short-term continuous dynamics to long-term discrete updates. We develop a data-driven method utilizing weak-form equation learning to extract such hybrid governing equations for population dynamics and to estimate the requisite parameters using sparse intermittent measurements of the discrete and continuous variables. The method produces a set of short-term continuous dynamical system equations parametrized by long-term variables, and long-term discrete equations parametrized by short-term variables, allowing direct assessment of interdependencies between the two timescales. We demonstrate the utility of the method on a variety of ecological scenarios and provide extensive tests using models previously derived for epizootics experienced by the North American spongy moth ( Lymantria dispar dispar ).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Plankton energy flows using a global size-structured and trait-based model

Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Optimising response to an introduction of African swine fever in wild pigs

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the United States, invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on the size of the control areas required to rapidly eliminate the ASFv in wild pigs and how this area should change with management constraints and local ecology is needed to optimize response planning. We developed a spatially explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in Southeastern United States. We simulated ASFv spread and determined the optimal response area (reported as the radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv was detected relative to the true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly) and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions, the ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within 1 year. The results highlight the importance of adjusting response plans based on local ecology and show that wild pig movement is a better predictor of the optimal response area than the number of ASFv cases early in the outbreak trajectory. Furthermore, our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Organic molecules are deterministically assembled in variably inundated river sediments, but drivers remain unclear

Dissolved organic matter (DOM) is central to ecosystem function. A fundamental challenge is understanding the processes leading to variation in the chemistry of organic molecules that comprise DOM. Here we study these processes in variably inundated riverbed sediments, as an understudied, yet ubiquitous component of rivers. Using null-model approaches adopted from community ecology, we found that within-site variation in environmental conditions caused non-random (i.e., deterministic) shifts in DOM chemistry. Deterministic shifts were observed across diverse biomes, though the strength of determinism varied substantially. We found that the strength of determinism decreased with increasing sediment moisture, but in the form of a constraint space. Many systems fell below the upper constraint boundary, however. We propose a conceptual model based on our results and other publications in which DOM assemblages are hypothesized to be increasingly deterministic across the continuum from the river water column to saturated sediment pore spaces to unsaturated and dry soils/sediments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Mapping the Path Forward to Next Generation Algal Technologies: Workshop on Understanding the Rules of Life and Complexity in Algal Systems

Algal technology offers enormous potential as a source of renewable biomass and bioproducts for fuels, biochemicals, nutrients, and numerous other applications. While tremendous opportunities exist, significant challenges are also present in harnessing and utilizing this valuable and potentially sustainable bioproduction platform. Funded by a joint partnership between the Bioenergy Technologies Office (BETO) at the Department of Energy (DOE) and the National Science Foundation (NSF), the recent virtual workshop, "Understanding the Rules of Life: Complexity in Algal Systems Workshop," was organized to bring together thought leaders from academia, national laboratories and other government agencies, and industry to identify key challenges and propose research strategies to overcome these barriers. Two parallel sessions were undertaken: 1) algae strain and toolkit development and 2) algal ecosystem and microbiome dynamics, in order to advance algae engineering and cultivation efforts. In each session, attendees discussed the most pressing challenges from the perspective of model systems and omics analysis. Themes such as genetic engineering toolboxes, translation from the laboratory to outdoor cultivation, functional genomics, metabolomics, algal ecology, consortial design, microbiome dynamics, mathematical models, and data analytics emerged from the discussion. Overall, this workshop has served to elucidate the key hurdles and many opportunities present as we continue to advance algal science and technology from the laboratory and into the commercial realm.

09 BIOMASS FUELS↗

DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗

DOE OSTI2023

Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge

Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

Abstract To predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Choi, Jang‐Geun↗