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DOE OSTI2024

Warming but not elevated CO 2 depletes soil organic carbon in a temperate rice paddy

In this article, global climate change has the potential to alter soil organic carbon (SOC) stocks in rice paddies, because increases in temperature and atmospheric carbon dioxide concentration ([CO 2 ]) both influence the primary input (i.e., net primary production, NPP) and output (i.e. heterotrophic respiration) of carbon (C). We used two types of open-top chambers representing present conditions (+0°C, +0 ppm CO 2 ) and projected climate change conditions (+2°C, +200 ppm CO 2 ) to investigate the net effect of climate change on SOC stock in rice paddy. Additional chambers with elevated temperature only (+2°C, +0 ppm CO 2 ) allowed us to quantify the individual effects of temperature and [CO 2 ]. We calculated changes in SOC stock using net ecosystem C balance (NECB) analysis (i.e., the balance between C inputs and outputs). Compared to present conditions, projected climate change did not change grain yield due to a trade-off between the effects of warming and [CO 2 ] on grain yield components. NPP during the fallow season significantly decreased under combined warming and CO 2 , as the impact of warming outweighed that of elevated [CO 2 ]. However, rice NPP remained unchanged during the cropping season. Warming plus elevated CO 2 increased SOC mineralization by 157–429 %, particularly through warming-induced soil CO 2 emission during the fallow season. Consequently, climate change conditions decreased (119–271 %) NECB values compared to present conditions, primarily through the response to warming. Our findings demonstrate that rice paddies represent positive feedback on climate change, because accelerated C release from warmed soils will override C gains from NPP under elevated CO 2 . Reducing SOC depletion in rice paddy agriculture under a changing climate therefore requires conservative soil management practices during the fallow season.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Dynamic risk assessment for geologic CO 2 sequestration

At a geologic CO 2 sequestration (GCS) site, geologic uncertainty usually leads to large uncertainty in the predictions of properties that influence metrics for leakage risk assessment, such as CO 2 saturations and pressures in potentially leaky wellbores, CO 2 /brine leakage rates, and leakage consequences such as changes in drinking water quality in groundwater aquifers. The large uncertainty in these risk-related system properties and risk metrics can lead to over-conservative risk management decisions to ensure safe operations of GCS sites. The objective of this work is to develop a novel approach based on dynamic risk assessment to effectively reduce the uncertainty in the predicted risk-related system properties and risk metrics. We demonstrate our framework for dynamic risk assessment on two case studies: a 3D synthetic example and a synthetic field example based on the Rock Springs Uplift (RSU) storage site in Wyoming, USA. Results show that the U.S. National Risk Assessment Partnership’s Open Source Integrated Assessment Model (NRAP-Open-IAM) coupled with a conformance evaluation can be used to effectively quantify and reduce the uncertainty in the predictions of risk-related system properties and risk metrics in GCS.

58 GEOSCIENCES↗

DOE OSTI2023

Lagrangian Characterization of Surface Transport From the Equatorial Atlantic to the Caribbean Sea Using Climatological Lagrangian Coherent Structures and Self‐Organizing Maps

Abstract This study presents an assessment of the transport of suspended material by surface ocean currents, which have a critical role in determining the connectivity and distribution of living and non‐living material. Lagrangian experiments reveal pathways from the Equatorial Atlantic to 10 strategic regions within the Caribbean Sea, determined by considering the space‐time variability of climatological Lagrangian Coherent Structures, which act as recurrent attracting pathways and transport barriers. Due to windage or Stokes drift, wind forcing is a significant factor in determining the spatial locations where particles cluster and the time needed to reach the Caribbean from the Equatorial Atlantic. Pathways shift westward within the Caribbean and take less time to arrive with increasing wind influence. Depending on the wind effect, the particles show higher confluence in different areas of the Caribbean. A case study is presented for the Mexican Caribbean nearshore area, isolated from ocean‐current trajectories. Here, wind weakens the transport barrier responsible for this isolation and causes particle confluence toward that region. Spatial patterns of the Eulerian velocity identified through Self‐Organizing Maps, with time dependence given by their best matching units, can reproduce the characteristic Lagrangian patterns of surface current climate variability. Our study demonstrates the application of tools from dynamical systems and unsupervised neural networks to understand Lagrangian patterns and identify the processes that drive them. These findings improve our understanding of transport mechanisms of suspended material by surface ocean currents in the Western Atlantic and the Caribbean Sea, which is essential for managing and conserving marine ecosystems.

Allende‐Arandía, Ma. Eugenia↗

DOE OSTI2025

Deep Learning Advances Arctic River Water Temperature Predictions

The accelerated warming in the Arctic poses serious risks to freshwater ecosystems by altering streamflow and river thermal regimes. However, limited research on Arctic River water temperatures exists due to data scarcity and the absence of robust methodologies, which often focus on large, major river basins. To address this, we leveraged the newly released, extensive AKTEMP data set and advanced machine learning techniques to develop a Long Short-Term Memory (LSTM) model. By incorporating ERA5-Land reanalysis data and integrating physical understanding into data-driven processes, our model advanced river water temperature predictions in ungauged, snow- and permafrost-affected basins in Alaska. Our model outperformed existing approaches in high-latitude regions, achieving a median Nash-Sutcliffe Efficiency of 0.95 and root mean squared error of 1.0°C. The LSTM model learned air temperature, soil temperature, solar radiation, and thermal radiation—factors associated with energy balance—were the most important drivers of river temperature dynamics. Soil moisture and snow water equivalent were highlighted as critical factors representing key processes such as thawing, melting, and groundwater contributions. Glaciers and permafrost were also identified as important covariates, particularly in seasonal river water temperature predictions. Our LSTM model successfully captured the complex relationships between hydrometeorological factors and river water temperatures across varying timescales and hydrological conditions. This scalable and transferable approach can be potentially applied across the Arctic, offering valuable insights for future conservation and management efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Multiple elements of soil biodiversity drive ecosystem functions across biomes

The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Furthermore, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Environmental RNA as a Tool for Marine Community Biodiversity Assessments

Abstract Microscopic organisms are often overlooked in traditional diversity assessments due to the difficulty of identifying them based on morphology. Metabarcoding is a method for rapidly identifying organisms where Environmental DNA (eDNA) is used as a template. However, legacy DNA is problematically detected from organisms no longer in the environment during sampling. Environmental RNA (eRNA), which is only produced by living organisms, can also be collected from environmental samples and used for metabarcoding. The aim of this study was to determine differences in community composition and diversity between eRNA and eDNA templates for metabarcoding. Using mesocosms containing field-collected communities from an estuary, RNA and DNA were co-extracted from sediment, libraries were prepared for two loci (18S and COI), and sequenced using an Illumina MiSeq. Results show a higher number of unique sequences detected from eRNA in both markers and higher α-diversity compared to eDNA. Significant differences between eRNA and eDNA for all β-diversity metrics were also detected. This study is the first to demonstrate community differences detected with eRNA compared to eDNA from an estuarine system and illustrates the broad applications of eRNA as a tool for assessing benthic community diversity, particularly for environmental conservation and management applications.

Giroux, Marissa S.↗

DOE OSTI2023

DNA metabarcoding reveals consumption of diverse community of amphibians by invasive wild pigs (Sus scrofa) in the southeastern United States

Abstract Invasive wild pigs ( Sus scrofa ) are one of the most widespread, destructive vertebrate species globally. Their success can largely be attributed to their generalist diets, which are dominated by plant material but also include diverse animal taxa. Wild pigs are demonstrated nest predators of ground-nesting birds and reptiles, and likely pose a threat to amphibians given their extensive overlap in wetland use. DNA metabarcoding of fecal samples from 222 adult wild pigs culled monthly from 2017 to 2018 revealed a diverse diet dominated by plant material, with 166 plant genera from 56 families and 18 vertebrate species identified. Diet composition varied seasonally with availability for plants and was consistent between sexes. Amphibians were the most frequent vertebrate group consumed and represented the majority of vertebrate species detected, suggesting amphibians are potentially vulnerable to predation by wild pigs in our study region. Mammal, reptile, and bird species were also detected in pig diets, but infrequently. Our results highlight the need for research on the impacts of wild pigs on amphibians to better inform management and conservation of imperiled species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Characterizing the vertical structure of forests in the Brazilian Amazon

Little is known about the structure of tropical forests despite its critical role in the provisioning of ecosystem services. Here we assess the vertical structure of forests in the Brazilian Amazon with a large-scale airborne LiDAR dataset. We show that fire has greater impact in the lowest forest strata, differently from selective logging and windthrow. We also find that secondary forests quickly recover or even exceed reference areas at the 1-10 m height stratum but that full recovery for the 20-30 m height stratum has not been achieved even after 35 years. Our modeling results suggest that proximity to roads, elevation, precipitation, soil pH, and proportion of sand in the soil are the most important predictors of forest structure. Finally, we identify 5 forest structural types (FSTs) and use them to visualize the spatial distribution of forest structure. This study provides important information for forest monitoring, management, and conservation.

Biogeography↗

DOE OSTI2022

Development of DNA methylation‐based epigenetic age predictors in loblolly pine ( Pinus taeda )

Abstract Biological ageing is connected to life history variation across ecological scales and informs a basic understanding of age‐related declines in organismal function. Altered DNA methylation dynamics are a conserved aspect of biological ageing and have recently been modelled to predict chronological age among vertebrate species. In addition to their utility in estimating individual age, differences between chronological and predicted ages arise due to acceleration or deceleration of epigenetic ageing, and these discrepancies are linked to disease risk and multiple life history traits. Although evidence suggests that patterns of DNA methylation can describe ageing in plants, predictions with epigenetic clocks have yet to be performed. Here, we resolve the DNA methylome across CpG, CHG, and CHH‐methylation contexts in the loblolly pine tree ( Pinus taeda ) and construct epigenetic clocks capable of predicting ages in this species within 6% of its maximum lifespan. Although patterns of CHH‐methylation showed little association with age, both CpG and CHG‐methylation contexts were strongly associated with ageing, largely becoming hypomethylated with age. Among age‐associated loci were those in close proximity to malate dehydrogenase, NADH dehydrogenase, and 18S and 26S ribosomal RNA genes. This study reports one of the first epigenetic clocks in plants and demonstrates the universality of age‐associated DNA methylation dynamics which can inform conservation and management practices, as well as our ecological and evolutionary understanding of biological ageing in plants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Worldwide phylogeography of rough-toothed dolphins ( Steno bredanensis ) provides evidence for subspecies delimitation

Rough-toothed dolphins (Steno bredanensis) have a global tropical and subtropical distribution with oceanic, neritic, and island-associated populations. Here, to inform conservation and management for this species, we used sequences from the mtDNA control region (n = 360), mitogenomes (n = 19), and six nuclear introns (n = 35) to provide multiple lines of evidence to critically evaluate the potential taxonomic status of rough-toothed dolphins. Using samples from the Pacific, Indian, and Atlantic Oceans, we examined the null hypothesis that rough-toothed dolphins are one panmictic species and the alternate hypothesis of oceanic subspecies. Phylogenetic analyses of mitogenomes revealed a private Atlantic clade sister to a larger cosmopolitan clade including individuals from all tropical and subtropical oceans. We dated the split between the Atlantic clade and the cosmopolitan clade to 890,000 years ago. We determined that Atlantic rough-toothed dolphins could be correctly diagnosed with 98% accuracy with the mtDNA control region and calculated the net nucleotide divergence as 0.02. Population level analyses revealed significant genetic differentiation using mtDNA among most regions, while significant differentiation using nuclear markers occurred only between the Atlantic and the Indian/Pacific regions. Therefore, the oceanic divergence and diagnosability of rough-toothed dolphins in the Atlantic and the Indian/Pacific Oceans meet proposed criteria for recognition as two subspecies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Large Game Distribution Camera Study at Los Alamos National Laboratory [Poster]

The unique habitats at the Laboratory support a diverse community of wildlife. The habitat types that include Pinon Juniper, Ponderosa Pine, and Mixed-conifer forests each provide different resources important for a variety of species. Wildlife monitoring for large game animals can be challenging because they avoid interactions with humans, and prefer undeveloped areas. This study was conducted to analyze the distribution of predators and other game animals seasonally across the Laboratory. The data gathered will be used to make recommendations regarding wildlife management for conservation and protection. Utilizing game cameras to remotely monitor wildlife was determined to be the most effective, noninvasive method to gather the necessary data. As camera technology has advanced, game cameras have become adequate for documenting individuals, and are commonly used in wildlife studies on predation, abundance, occupancy, diversity, and endangered species detection. Twenty cameras were placed across the LANL landscape using a modified systematic sampling design. They were deployed in February 2018 and retrieved in January 2019, thus each camera sampled for one full year. All images were reviewed and the species, number, age, and sex of all animals in the photo were recorded. Here we present data for the most abundant species encountered: deer, elk, coyote, bear, bobcat, mountain lion, and fox respectively. The data were summarized by species and season. Future work will include occupancy modelling for each species. This will allow the development of heat maps showing species distributions across the Laboratory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Hanford Site Bird Surveys Report for Calendar Year 2016

Resource stewardship is an integral part of the U.S. Department of Energy, Richland Operations Office (DOE-RL) responsibilities at the Hanford Site. Efficient conservation or management of any species or any population is supported through the availability of reliable information on the population in question. DOERL conducts ecological monitoring on the Hanford Site to collect and track this information. Ecological monitoring data provide baseline information about the plants, animals, and habitat under DOE-RL stewardship at Hanford that is required for decision-making under the National Environmental Policy Act (NEPA) and Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). The Hanford Site Comprehensive Land Use Plan (CLUP, DOE/EIS-0222-F), which is the Environmental Impact Statement for Hanford Site activities, helps ensure that DOE-RL, its contractors, and other entities conducting activities on the Hanford Site are in compliance with NEPA.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Identifying Whitemouth Croaker (Micropogonias furnieri) Populations along the Rio de Janeiro Coast, Brazil, through Microsatellite and Otolith Analyses

The inshore area of the Southwestern Atlantic between 22 °S and 29 °S (South Brazilian Bight) is a transitional climatic zone, where the tropical and warm temperate provinces mix. In its northern part, i.e., in the coastal waters of Rio de Janeiro, Brazil, local oceanographic conditions, such as upwelling in the north, and great bays with different degrees of anthropogenic influences in the center and south can determine the population structure of several fish stocks. The Whitemouth croaker (Micropogonias furnieri) is one the most heavily exploited fishing resources in this area, but there are still some doubts about its population structure. In this study, through combined analyses using nuclear genetic markers and morphological and geochemical signatures of otoliths, a divergence of individuals between two populations was identified using microsatellites, while a finer spatial structure with three populations (north, center and south, respectively) was found based on otolith shapes and elemental signatures. This regional population structure may have direct implications for rational fisheries management and conservation of the species.

Franco, Taynara Pontes (ORCID:0000000167381096)↗

DOE OSTI2023

PMEL Passive Acoustics Research: Quantifying the Ocean Soundscape from Whales to Wave Energy

Passive acoustic monitoring of the global ocean has increased dramatically over the last decade, providing insights into seasonal sea ice and wind/wave variability, biodiversity, geophysical hazards, and anthropogenic noise impacts. All of these phenomena are sentinels of marine ecosystem health and ocean climate change. Recognizing the utility of underwater sound, the Pacific Marine Environmental Laboratory (PMEL) formed a passive acoustic research program with the goal of quantifying deep-ocean and coastal soundscapes in support of NOAA’s mission to conserve and manage marine ecosystems. PMEL Acoustics Program researchers have built a stable of novel ocean technologies, including autonomous stationary hydrophones, mobile platforms, and near-real-time surface buoys with satellite communication capability. These passive acoustic monitoring systems have been deployed in every major ocean basin on Earth, enabling significant advancements in understanding of natural and anthropogenic sounds. This progress includes evaluation of human-made sound levels across US waters, observations of ship noise fluctuations during the COVID-19 pandemic, and evaluation of noise levels from offshore wave-energy devices. Progress in natural sound research includes assessment of seasonal variability in the presence of endangered cetacean species due to population recovery and/or changing ocean temperatures as well as early detection of the collapse of an Antarctic ice shelf.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Distribution, Ecology, Life History, and Conservation Status of the Berry Cave Salamander (Gyrinophilus gulolineatus)

The Berry Cave Salamander (Gyrinophilus gulolineatus) is a neotenic, stygobitic salamander endemic to eight cave systems and an isolated surface record in the Appalachian Valley and Ridge of eastern Tennessee. We conducted surveys for G. gulolineatus from 2017–2019 to assess the status of the species, locate new populations, and address knowledge gaps related to life history and population ecology required for conservation assessment. We confirmed G. gulolineatus presence at four historical sites, but we did not observe the species at any additional caves. At the three known sites with greatest abundance, visual counts per survey ranged 0–19 salamanders in 2017–2019. There was no apparent trend in abundance at Berry Cave. Visual counts declined 65% since the mid-2000s at Meads Quarry Cave and 80% since the early 1980s at Mudflats Cave. Mark-recapture studies in 160-m of cave stream at Berry Cave in 2017–2018 and 900-m of cave stream at Meads Quarry Cave in 2008 yielded population size estimates that ranged from 34–78 and 15–65 individuals, respectively. We identified 13 existing or potential threats to populations. Habitat degradation and groundwater contamination (associated with urbanization of the Knoxville metropolitan area and past mining operations) represent the most evident threats to long-term viability. Based on our conservation assessments, we recommend a rank of Endangered under IUCN Red List criteria and Critically Imperiled–Imperiled (G1G2) under NatureServe criteria. In opposition to the recent U.S. Fish & Wildlife Service decision, we advocate that, at minimum, G. gulolineatus remain a Candidate Species. Given the identified threats and these ranks, we offer several recommendations for research, conservation, and management of this rare salamander.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗

DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices: Preprint

advanced distribution management system↗