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At least 433 records · Page 24

Functional but not taxonomic diversity increases productivity of Populus in the southeastern United States

Plant interactions like competition and facilitation impact ecosystem function and resilience. Improving our understanding of the relationships between these interactions and community productivity has important implications for managers of production systems in forestry and agriculture as well as conservation science. Populus spp. are an excellent model system for exploring how inter‐ and intraspecific interactions impact ecosystem functions, such as productivity, in forest plantations. In this study, we compared aboveground productivity of six Populus clones from three different taxa grown in monoclonal and mixed‐clonal plots. The different mixture treatments were intended to experimentally test aboveground biomass response to contrasting levels of taxonomic diversity and functional diversity based on nitrogen use characteristics of Populus clones. We hypothesize that functional diversity would be more important than taxonomic diversity in increasing aboveground productivity of mixed‐clonal plantings compared to monocultures. In addition, a subset of treatments was carried out on additional sites representing a productivity gradient in order to determine if the relationship between biodiversity and productivity in these systems diminished at more productive sites as suggested by the stress‐gradient hypothesis. We found that functionally diverse mixtures of clones had greater yield of aboveground biomass than the average of their constituent monocultures, while more taxonomically diverse mixes of clones did not differ from the average of their constituent monocultures. However, when reestablished on sites with extremely high or low productivity, the best performing clone mixture also did not differ from the average of its constituent monocultures. Our results suggest that intimate clone mixtures of Populus have the potential to significantly increase productivity, but results vary by mixture and by site. To capitalize on positive biodiversity effects on yield in production systems, targeted mixtures based on divergent functional traits linked to different use and acquisition strategies for site‐specific limiting resources are most likely to be successful.

BEF↗

Machine-learning based approach to examine ecological processes influencing the diversity of riverine dissolved organic matter composition

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes ( 2 H and 18 O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Evidence and attribution of the enhanced land carbon sink

Climate change has been partially mitigated by an increasing net land carbon sink in the terrestrial biosphere; understanding the processes that drive this sink is thus essential for protecting, managing and projecting this important ecosystem service. In this Review, we examine evidence for an enhanced land carbon sink and attribute the observed response to drivers and processes. This sink has doubled from 1.2 ± 0.5 PgC yr -1 in the 1960s to 3.1 ± 0.6 PgC yr -1 in the 2010s. This trend results largely from carbon dioxide fertilization increasing photosynthesis (driving an increase in the annual land carbon sink of >2 PgC globally since 1900), mainly in tropical forest regions, and elevated temperatures reducing cold limitation, mainly at higher latitudes. Continued long-term land carbon sequestration is possible through the end of this century under multiple emissions scenarios, especially if nature-based climate solutions and appropriate ecosystem management are used. In conclusion, a new generation of globally distributed field experiments is needed to improve understanding of future carbon sink potential by measuring belowground carbon release, the response to carbon dioxide enrichment, and long-term shifts in carbon allocation and turnover.

54 ENVIRONMENTAL SCIENCES↗

The Emergence and Promise of Functional Chemogeography of Organic Matter

Organisms in ecosystems continuously release a myriad of organic matter molecules that undergo microbial and abiotic transformation, processes that critically influence carbon storage and climate feedbacks. Yet, a systematic understanding of what determines the transformation and persistence of organic matter across spatiotemporal scales remains elusive. We propose an emerging framework, termed “functional chemogeography,” to understand transformation and persistence of organic matter based on the chemical traits of molecules. This framework extends beyond a sole focus on intrinsic traits, which remain relatively constant across spatiotemporal scales, to emphasize extrinsic traits such as biochemical transformations and environmental responses, which vary spatiotemporally and are shaped by both intrinsic traits and the environment. When upscaled to the assemblage level using functional diversity indices, these extrinsic traits reveal a significant, and in some cases superior, capacity than intrinsic traits to explain biogeochemical processes, as demonstrated through a case study of dissolved organic matter in China's lakes. In conclusion, by integrating trait-based perspectives into predictive models, this framework helps bridge chemical complexity with ecosystem biogeochemistry, thereby advancing our ability to predict the fate of global organic carbon under environmental change.

chemical traits↗

Leaf-cutting ant (Atta cephalotes) nests may be hotspots of methane and carbon dioxide emissions in tropical forests

Leaf-cutting ants of the genus Atta are widely distributed throughout the American tropics and subtropics and rival other herbivores in the consumption of surrounding foliage. Although numerous studies have been conducted on the role these insects play in herbivory and organic matter dynamics, only a handful of studies have examined their impacts on soil greenhouse gas emissions. Our study investigated fluxes of carbon dioxide (CO 2 ) and methane (CH 4 ) from three nests of Atta cephalotes using a portable greenhouse gas analyzer, and measured CO 2 and CH 4 emissions from soils containing nest holes that ranged 5.2–152.1 g CO 2 -C and –1.1 to 15,264.7 mg CH 4 -C m -2 day -1 , respectively. Fluxes of CO 2 and CH 4 were positively correlated above nest holes, but not in patches of soil away from leaf-cutting ant nests. Nearby non-nest soil emissions were significantly lower, ranging from 0.6 to 6.0 g CO 2 -C and –1.3 to 0.77 mg CH 4 -C m -2 day -1 . Fluxes of both gases among nests and among holes within a single nest were highly variable. This preliminary dataset is small in scale both temporarily and geographically, but the discovery of substantial greenhouse gas fluxes from Atta cephalotes nests may have important implications for carbon budgets of tropical and subtropical American forests. Further work will be necessary to determine the mechanisms behind enhanced greenhouse gas emissions from leaf-cutting ant nests, and how this may alter ecosystem-scale CO 2 emissions and CH 4 sink strength in tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗

ToPolyAgent: AI agents for coarse-grained bead-spring topological polymer simulations

We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions. By integrating large language models (LLMs) with domain-specific computational tools, ToPolyAgent supports both interactive and autonomous simulation workflows across diverse polymer architectures, including linear, ring, brush, and star polymers, as well as dendrimers. The system consists of four LLM-powered agents: a Config Agent for generating initial polymer–solvent configurations, a Simulation Agent for executing LAMMPS-based MD simulations and conformational analyses, a Report Agent for compiling markdown reports, and a Workflow Agent for streamlined autonomous operations. Interactive mode incorporates user feedback loops for iterative refinements, while autonomous mode enables end-to-end task execution from detailed prompts. We demonstrate ToPolyAgent's versatility through case studies involving diverse polymer architectures under varying solvent conditions, thermostats, and simulation lengths. Furthermore, we highlight its potential as a research assistant by directing it to investigate the effect of interaction parameters on the linear polymer conformation, and the influence of grafting density on the persistence length of the brush polymer. By coupling natural language interfaces with rigorous simulation tools, ToPolyAgent lowers barriers to complex computational workflows and advances AI-driven materials discovery in polymer science. It lays the foundation for autonomous and extensible multi-agent scientific research ecosystems.

Ding, Lijie [Oak Ridge National Laboratory (ORNL),↗

How to improve scaling from traits to ecosystem processes

Scaling approaches in ecology assume that traits are the main attributes by which organisms influence ecosystem functioning. However, several recent empirical papers have found only weak links between traits and ecosystem functioning, questioning the usefulness of trait-based ecology (TBE). Here, we argue that these studies often suffer from one or more widespread misconceptions. Specifically, these studies often (i) conflict with the conceptual foundations of TBE, (ii) lack theory- or hypothesis-driven selection and use of traits, (iii) tend to ignore intraspecific variation, and (iv) use experimental or study designs that are not well suited to make strong tests of TBE assumptions. Addressing these aspects could significantly improve our ability to scale from traits to ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗

Programs Enabling Deep Technology Transfer from National Labs

To maximize the technology transfer potential, it is important to create an ecosystem for the inventors to adapt the technologies developed for basic science to successful commercial ventures. In this white paper we present a brief overview of technology transfer programs at high energy physics (HEP) laboratories with a focus on the programs at Fermilab and KEK, and identify opportunities and recommendations for increasing partnerships and commercialization at HEP-centric laboratories.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Ecological Monitoring and Compliance Program 2023 Report

Annual report of activities conducted under the EMAC program including biological surveys, desert tortoise compliance, ecosystem monitoring, sensitive and protected/regulated plant and animal monitoring, and habitat restoration implementation and monitoring.

60 APPLIED LIFE SCIENCES↗

Early Career Perspectives to Broaden the Scope of Critical Zone Science

Abstract Critical Zone (CZ) scientists have advanced understanding of Earth's surface through process‐based research that quantifies water, energy, and mass fluxes in predominantly undisturbed systems. However, the CZ is being increasingly altered by humans through climate and land use change. Expanding the scope of CZ science to include both human‐ and non‐human controls on the CZ is important for understanding anthropogenic impacts to Earth's surface processes and ecosystem services. Here, we share perspectives from predominantly U.S.‐based, early career CZ scientists centered around broadening the scope of CZ science to focus on societally relevant science through a transdisciplinary science framework. We call for increased training on transdisciplinary methods and collaboration opportunities across disciplines and with stakeholders to foster a scientific community that values transdisciplinary science alongside physical science. Here, we build on existing transdisciplinary research frameworks by highlighting the need for institutional support to include and educate graduate students throughout the research processes. We also call for graduate‐student‐led initiatives to increase their own exposure to transdisciplinary science through activities such as transdisciplinary‐focused seminars and symposiums, volunteering with local conservation groups, and participating in internships outside academia.

Warix, Sara [University of Utah Department of Geol↗

Evidence for multi-decadal fuel buildup in a large California wildfire from smoke radiocarbon measurements

In recent decades, there has been a significant increase in annual area burned in California's Sierra Nevada mountains. This rise in fire activity has prompted the need to understand how historical forest management practices affect fuel composition and emissions. Here we examined the total carbon (TC) concentration and radiocarbon abundance (Δ 14 C) of particulate matter (PM) emitted by the KNP Complex Fire, which occurred during California's 2021 wildfire season and affected several groves of giant sequoia trees in the southern Sierra Nevada. During a 26 h sampling period, we measured concentrations of fine airborne PM (PM 2.5 ), as well as dry air mole fractions of carbon monoxide (CO) and methane (CH 4 ), using a ground-based mobile laboratory. We also collected filter samples of PM 2.5 for analysis of TC concentration and Δ 14 C. High correlation among PM 2.5 , CO, and CH 4 time series confirmed that our PM 2.5 measurements captured variability in wildfire emissions. Using a Keeling plot approach, we determined that the mean Δ 14 C of PM 2.5 was 111.6 ± 7.7‰ (n = 12), which was considerably enriched relative to atmospheric carbon dioxide in the northern hemisphere in 2021 (-3.2 ± 1.4‰). Combining these Δ 14 C data with a steady-state one-box ecosystem model, we estimated that the mean age of fuels combusted in the KNP Complex Fire was 40 years, with a range of 29–57 years. These results provide evidence for emissions originating from woody biomass, larger-diameter fine fuels, and coarse woody debris that have accumulated over multiple decades. This is consistent with independent field observations that indicate high fire intensity contributed to widespread giant sequoia mortality. With the expanded use of prescribed fires planned over the next decade in California to mitigate wildfire impacts, our measurement approach has the potential to provide regionally-integrated estimates of the effectiveness of fuel treatment programs.

54 ENVIRONMENTAL SCIENCES↗

Basic Research Needs for Communicating Basic Science

Basic science—also known as discovery or foundational research—is the fuel that powers our innovation ecosystem and the global economy. Despite this critical role, public awareness for how and where basic research is done, how it is funded, and its need for sustainable support over the long term is negligible. The ability to engage broader publics in awareness and understanding of basic science is paramount if we are to maintain the research enterprise that has transformed the modern world. Communicating how the federal government stewards taxpayer dollars for basic science is also incumbent on the agencies and scientists who use public dollars for their research. However, science communication is a complex activity that requires advanced planning, resources, and skill. Therefore, it is important to understand what we know about communicating basic science to the broader publics, as well as what we do not know, to be strategic and better equipped for effective, meaningful engagement. To identify and explore knowledge gaps in our understanding of basic science communication, the Science Public Engagement Partnership (SciPEP), a public-private partnership of the U.S. Department of Energy (DOE) Office of Science and The Kavli Foundation, carried out a two-part landscape analysis: literature surveys of social science scholarship and a basic research needs conference.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.

60 APPLIED LIFE SCIENCES↗

Carbon cycling across ecosystem succession in a north temperate forest: Controls and management implications

Despite decades of progress, much remains unknown about successional trajectories of carbon (C) cycling in north temperate forests. Drivers and mechanisms of these changes, including the role of different types of disturbances, are particularly elusive. To address this gap, we synthesized decades of data from experimental chronosequences and long-term monitoring at a well-studied, regionally representative field site in northern Michigan, USA. Our study provides a comprehensive assessment of changes in above- and belowground ecosystem components over two centuries of succession, links temporal dynamics in C pools and fluxes with underlying drivers, and offers several conceptual insights to the field of forest ecology. Our first advance shows how temporal dynamics in some ecosystem components are consistent across severe disturbances that reset succession and partial disturbances that slightly modify it: both of these disturbance types increase soil N availability, alter fungal community composition, and alter growth and competitive interactions between short-lived pioneer and longer-lived tree taxa. Further, these changes in turn affect soil C stocks, respiratory emissions, and other belowground processes. Second, we show that some other ecosystem components have effects on C cycling that are not consistent over the course of succession. For example, canopy structure does not influence C uptake early in succession but becomes important as stands develop, and the importance of individual structural properties changes over the course of two centuries of stand development. Third, we show that in recent decades, climate change is masking or overriding the influence of community composition on C uptake, while respiratory emissions are sensitive to both climatic and compositional change. In synthesis, we emphasize that time is not a driver of C cycling; it is a dimension within which ecosystem drivers such as canopy structure, tree and microbial community composition change. Changes in those drivers, not in forest age, are what control forest C trajectories, and those changes can happen quickly or slowly, through natural processes or deliberate intervention. Stemming from this view and a whole-ecosystem perspective on forest succession, we offer management applications from this work and assess its broader relevance to understanding long-term change in other north temperate forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Strategic roadmap to assess forest vulnerability under air pollution and climate change

Abstract Although it is an integral part of global change, most of the research addressing the effects of climate change on forests have overlooked the role of environmental pollution. Similarly, most studies investigating the effects of air pollutants on forests have generally neglected the impacts of climate change. We review the current knowledge on combined air pollution and climate change effects on global forest ecosystems and identify several key research priorities as a roadmap for the future. Specifically, we recommend (1) the establishment of much denser array of monitoring sites, particularly in the South Hemisphere; (2) further integration of ground and satellite monitoring; (3) generation of flux‐based standards and critical levels taking into account the sensitivity of dominant forest tree species; (4) long‐term monitoring of N, S, P cycles and base cations deposition together at global scale; (5) intensification of experimental studies, addressing the combined effects of different abiotic factors on forests by assuring a better representation of taxonomic and functional diversity across the ~73,000 tree species on Earth; (6) more experimental focus on phenomics and genomics; (7) improved knowledge on key processes regulating the dynamics of radionuclides in forest systems; and (8) development of models integrating air pollution and climate change data from long‐term monitoring programs.

54 ENVIRONMENTAL SCIENCES↗

Annual carbon sequestration and loss rates under altered hydrology and fire regimes in southeastern USA pocosin peatlands

Peatlands drained for agriculture or forestry are susceptible to the rapid release of greenhouse gases (GHGs) through enhanced microbial decomposition and increased frequency of deep peat fires. We present evidence that rewetting drained subtropical wooded peatlands (STWPs) along the southeastern USA coast, primarily pocosin bogs, could prevent significant carbon (C) losses. To quantify GHG emissions and storage from drained and rewetted pocosin we used eddy covariance techniques, the first such estimates that have been applied to this major bog type, on a private drained (PD) site supplemented by static chamber measurements at PD and Pocosin Lakes National Wildlife Refuge. Net ecosystem exchange measurements showed that the loss was 21.2 Mg CO2 ha –1 year –1 (1 Mg = 10 6 g) in the drained pocosin. Under a rewetted scenario, where the annual mean water table depth (WTD) decreased from 60 to 30 cm, the C loss was projected to fall to 2 Mg CO 2 ha –1 year –1 , a 94% reduction. If the WTD was 20 cm, the peatlands became a net carbon sink (–3.3 Mg CO2 ha –1 year –1 ). Hence, net C reductions could reach 24.5 Mg CO 2 ha –1 year –1 , and when scaled up to the 4000 ha PD site nearly 100,000 Mg CO 2 year –1 of creditable C could be amassed. We conservatively estimate among the 0.75 million ha of southeastern STWPs, between 450 and 770 km 2 could be rewet, reducing annual GHG emissions by 0.96–1.6 Tg (1 Tg = 10 12 g) of CO 2 , through suppressed microbial decomposition and 1.7–2.8 Tg via fire prevention, respectively. Despite covering <0.01% of US land area, rewetting drained pocosin can potentially provide 2.4% of the annual CO 2 nationwide reduction target of 0.18 Pg (1 Pg = 10 15 g). Finally, suggesting pocosin restoration can contribute disproportionately to the US goal of achieving net-zero emission by 2050.

58 GEOSCIENCES↗

Rock-Sourced Nitrogen in Semi-Arid, Shale-Derived California Soils

Models suggest that rock-derived nitrogen (N) inputs are of global importance to ecosystem N budgets; however, field studies demonstrating the significance of rock N inputs are rare. We examined rock-derived N fluxes in soils derived from sedimentary rocks along a catena formed under a semi-arid climate. Our measurements demonstrate that there are distinct and traceable pools of N in the soil and bedrock and that the fraction of rock-derived N declines downslope along the catena. We used geochemical mass balance weathering flux measurements to estimate a rock-derived N flux of 0.145 to 0.896 kg ha -1 yr -1 at the ridgecrest. We also developed independent N flux estimates using a 15 N-based isotope mixing model. While geochemical mass-balance-based estimates fell within the 95% confidence range derived from the isotope mixing model (-1.1 to 44.3 kg ha -1 yr -1 ), this range was large due to uncertainty in values for atmospheric 15 N deposition. Along the catena, N isotopes suggest a diminishing effect of rock-derived N downslope. Overall, we found that despite relatively large N pools within the saprolite and bedrock, slow chemical weathering and landscape denudation limit the influence of rock-derived N, letting atmospheric N deposition (7.1 kg ha -1 yr -1 ) and N fixation (0.9-3.1 kg ha -1 yr -1 ) dominate N inputs to this grassland ecosystem.

54 ENVIRONMENTAL SCIENCES↗