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As the global demand for renewable energy sources intensifies amid the urgent fight against climate change [1] , offshore wind energy has emerged as a promising and crucial component of the sustainable energy portfolio. Fixed-bottom offshore wind farms have already demonstrated their potential; however, they are limited to relatively shallow waters, typically no deeper than 60 m.
Abstract Understanding how biodiversity and interaction networks change across environmental gradients is a major challenge in ecology. We integrated metacommunity and metanetwork perspectives to test species’ functional roles in bird–plant frugivory interactions in a fragmented forest landscape in Southwest China, with consequences for seed dispersal. Availability of fruit resources both on and under trees created vertical feeding stratification for frugivorous birds. Bird–plant interactions involving birds feeding only on‐the‐tree or both on and under‐the‐tree (shared) had a higher centrality and contributed more to metanetwork organisation than interactions involving birds feeding only under‐the‐tree. Moreover, bird–plant interactions associated with large‐seeded plants disproportionately contributed to metanetwork organisation and centrality. Consequently, on‐the‐tree and shared birds contributed more to metanetwork organisation whereas under‐the‐tree birds were more involved in local processes. We would expect that species’ roles in the metanetwork will translate into different conservation values for maintaining functioning of seed‐dispersal networks.
Inland waters serve as important hydrological connections between the terrestrial landscape and oceans but are often overlooked in global carbon (C) budgets and Earth System Models. Terrestrially derived C entering inland waters from the watershed can be transported to oceans but over 83% is either buried in sediments or emitted to the atmosphere before reaching oceans. Anthropogenic pressures such as climate and landscape changes are altering the magnitude of these C fluxes in inland waters. Here, we synthesize the most recent estimates of C fluxes and the differential contributions across inland waterbody types (rivers, streams, lakes, reservoirs, and ponds), including recent measurements that incorporate improved sampling methods, small waterbodies, and dried areas. Across all inland waters, we report a global C emission estimate of 4.40 Pg C/year (95% confidence interval: 3.95–4.85 Pg C/year), representing a 13% increase from the most recent estimate. In this work, we also review the mechanisms by which the most globally widespread anthropogenically driven climate and landscape changes influence inland water C fluxes. The majority of these drivers are expected to influence terrestrial C inputs to inland waters due to alterations in terrestrial C quality and quantity, hydrological pathways, and biogeochemical processing. We recommend four research priorities for the future study of anthropogenic alterations to inland water C fluxes: (1) before-and-after measurements of C fluxes associated with climate change events and landscape changes, (2) better quantification of C input from land, (3) improved assessment of spatial coverage and contributions of small inland waterbodies to C fluxes, and (4) integration of dried and drawdown areas to global C flux estimates. Improved measurements of inland water C fluxes and quantification of uncertainty in these estimates will be vital to understanding both terrestrial C losses and the “moving target” of inland water C emissions in response to rapid and complex anthropogenic pressures.
Ectomycorrhizal symbiosis is essential for the nutrition of most temperate forest trees and helps regulate the movement of carbon and nitrogen through forested ecosystems. The factors governing the exchange of plant carbon for fungal nitrogen, however, remain obscure. Because competition and soil resources may influence ectomycorrhizal resource movement, we performed a ten month split-root microcosm study using Pinus muricata seedlings with Thelephora terrestris, Suillus pungens, or no ectomycorrhizal fungus, under two nitrogen levels in artificial soil. Fungi competed directly with roots, and indirectly with each other. We used stable isotope enrichment to track plant photosynthate and fungal nitrogen. For Thelephora, plants received N commensurate with the C given to their fungal partners. Thelephora was a superior mutualist under high nitrogen. For Suillus, plant C and fungal N exchange were not coupled. However, in low nitrogen, plants preferentially allocated C to Suillus rather than Thelephora. Our results suggest that ectomycorrhizal resource transfer depends on competitive and nutritional context. Plants can exchange C for fungal N, but coupling of these resources can depend on the fungal species and soil N. Here, understanding the diversity of fungal strategies, and how they change with environmental context, reveals mechanisms driving this important symbiosis.
Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Here, two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability – and possibly the preventability – of the ongoing extinction of plant species.
The rhizosphere is a critical interface between plant roots and soil, harboring diverse microbial communities that are essential to plant and ecosystem health. Although these communities exhibit stark temporal dynamics, their dormancy/activity transitions remain poorly understood. Such transitions may enable microbes to rapidly adjust functional contributions faster than community turnover alone would allow. Here, we used RNA metabarcoding to characterize the active fraction of microbial communities on the roots of quaking aspen (Populus tremuloides) in a time-series study across a natural environmental gradient. We explore cryptic temporal microbial community dynamics of rhizosphere communities at the ecosystem scale. The active rhizosphere bacterial and fungal communities were more temporally dynamic than total communities, while total communities exhibited a stronger response to site-specific conditions. Notably, some core microbiome members were often inactive, yielding a smaller “active core” subset. The fungal endophyte Hyaloscypha finlandica was the only microbe that was both present and active in all plots across all timepoints. Soil temperature strongly influenced both total and active community composition, with the fungal class Eurotiomycetes showing a temperature-dependent seasonal decline in abundance. Together, these results reveal that modulation of microbial activity levels is a key mechanism by which the plant root holobiont responds to environmental variation, and that even dominant symbionts may frequently persist in dormancy within the rhizosphere.
Sustaining a robust metabolic network requires a balanced and fully functioning proteome. In addition to amino acids, many enzymes require cofactors (coenzymes and engrafted prosthetic groups) to function properly. Extensively validated resource allocation models, such as genome-scale models of metabolism and gene expression (ME-models), have the ability to compute an optimal proteome composition underlying a metabolic phenotype, including the provision of all required cofactors. Here we apply the ME-model for Escherichia coli K-12 MG1655 to computationally examine how environmental conditions change the proteome and its accompanying cofactor usage. We found that: (1) The cofactor requirements computed by the ME-model mostly agree with the standard biomass objective function used in models of metabolism alone (M-models); (2) ME-model computations reveal non-intuitive variability in cofactor use under different growth conditions; (3) An analysis of ME-model predicted protein use in aerobic and anaerobic conditions suggests an enrichment in the use of peroxyl scavenging acids in the proteins used to sustain aerobic growth; (4) The ME-model could describe how limitation in key protein components affect the metabolic state of E . coli . Genome-scale models have thus reached a level of sophistication where they reveal intricate properties of functional proteomes and how they support different E . coli lifestyles.
This dataset comprises radiocarbon and geochemical measurements from peat and porewater samples collected across various depths at a site in Bocas del Toro, Panama. The study focuses on carbon cycling dynamics in tropical peatlands by examining carbon isotopic signatures (¹⁴C and ¹³C) and elemental compositions of bulk peat, dissolved organic carbon (DOC), carbon dioxide (CO₂), and methane (CH₄). Key parameters include radiocarbon ages and isotopic ratios (δ¹³C) of bulk peat, concentrations of carbon (%C) and nitrogen (%N), and radiocarbon content of porewater gases and dissolved organic carbon (DOC). The data provide insights into the vertical and spatial distribution of carbon sources and possible preservation and decomposition processes within tropical peat profiles, offering critical information for understanding carbon storage and greenhouse gas emissions in these ecosystems.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) carbon isotopic signatures (¹⁴C and ¹³C); (5) concentrations of carbon (%C) and nitrogen (%N); (6) radiocarbon content of porewater carbon dioxide (CO₂), and methane (CH₄) ; (7) porewater DOC; (8) bulk peat sampling protocol; (9) porewater sampling protocol; (10) porewater gas collection methods; and (11) gas extraction methods. All files are in .csv format and can be opened with any software that supports this file types.
Photosynthetic CO2 response curves (ACi curves), light response curves (AQ curves), dark adapted dark respiration, conductance curves, and survey measurements for leaves measured in the Parque Natural Metropolitano (PNM) and Gamboa, Panama, from January to April 2022 are presented. Measurements were made on leaves from 46 different tree, shrub and liana species, from sunlit canopy and understory locations. Leaf area index from 8 vertical profiles at PNM are also included. The aim of this measurement campaign was three-fold: (i) to improve our understanding of the vertical variation in leaf-level water use efficiency; (ii) to develop an understanding of the sensitivity of stomata to changes in environmental conditions, especially light, humidity, and temperature; (iii) to improve models which can predict leaf traits from leaf contact spectral measurements. All the gas exchange data and metadata are presented in .csv files and complete instrument output are included in .zip folders. Data and metadata meet the ESS-DIVE leaf-level gas exchange reporting format requirements. The protocol details are provided as pdf documents. In addition to gas exchange data reported here these samples were also used for measurement of leaf optical properties, carbon and nitrogen content, and leaf mass per unit leaf area (LMA). These data can be cross linked using the unique sample ID and are provided in separate data packages.
Underserved communities in the United States often experience the negative impacts of climate change and environmental degradation but enjoy few of the benefits of technological and environmental advances. The White House has addressed this inequity through the Justice40 initiative, which requires 40% of the benefits of select federal investments to be directed to underserved communities (The White House, 2022). Clean energy and energy efficiency are two highlighted investment categories, so the U.S. Department of Energy will guide implementation of the Justice40 initiative by, among other things, decreasing energy burdens, increasing parity in clean energy technology access and adoption, and increasing energy resiliency. A strategy for reaching these goals is to evaluate and validate new energy efficiency technologies in commercial buildings in underserved communities, where buildings may be older, smaller, and have deferred maintenance due to historical underinvestment. This paper develops guidance for researchers pursuing field validations with underserved communities. Historical redlining and past negative experiences with government and large institutions may make residents wary of participating in these field validations. Researchers, therefore, may need to spend more time building relationships and matching technologies to buildings. In this paper, we analyzed technical reports to identify common field validation building characteristics and conducted semi-structured expert conversations to identify key stages and major themes of engaging underserved communities. Results indicate there may be flexibility in site selection and there are steps researchers can take to support collaboration with communities. Results also suggest benefits to both the community and energy efficiency research.
This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>
U.S. Department of Energy (DOE), Office of Science, Award DE-SC0023215, Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region, supported capacity and partnership building between researchers at Central Michigan University (CMU) and scientists at DOE laboratories. The work involved identifying potential collaborations both internal to CMU and between CMU researchers and DOE staff, developing collaborative research proposals, and partnering on pilot-scale research projects focused on enhancing resilience of Great Lakes communities, ecosystems, and infrastructure to global change and environmental stressors. DOE funds supported travel, time to develop collaborations, investigate new research pathways, and draft grant proposals, and a loan of DOE equipment to collect pilot data in support of future work. The project achieved its goal of strengthening research collaborations between interdisciplinary researchers at CMU and establishing new collaborations and partnerships between CMU and DOE scientists. These collaborations resulted in 5 pre-applications and 4 full applications for funding to DOE BER Funding Opportunities, a successfully funded DOE BER award (DE-SC0025260), a new pilot project that leveraged DOE resources (AquaBOT) to improve understanding of water quality conditions in Michigan rivers, and two presentations of preliminary results at national scientific conferences. This project’s outcomes will benefit the Great Lakes Region via new lines of collaborative research focused on improving the resilience of Michigan communities, ecosystems, and infrastructure.
This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.
Field measurements have shown that cold-season methane (CH 4 ) and carbon dioxide (CO 2 ) emissions contribute a substantial portion to the annual net carbon emissions in permafrost regions. However, most earth system land models do not accurately reproduce cold-season CH 4 and CO 2 emissions, especially over the shoulder (i.e., thawing and freezing) seasons. Here we use the Energy Exascale Earth System Model (E3SM) land model version 1 (ELMv1-ECA) to tackle this challenge and fill the knowledge gap of how cold-season CH 4 and CO 2 emissions contribute to the annual totals at Alaska Arctic tundra sites. Specifically, we improved the ELMv1-ECA soil water phase-change scheme, environmental controls on microbial activity, and the methane module. Results demonstrate that both soil temperature and the duration of zero-curtain periods (i.e., the fall period when soil temperatures linger around 0°C) simulated by the updated ELMv1-ECA were greatly improved; e.g., the mean absolute error (MAE) in zero-curtain durations at 12 cm depth was reduced by 62 % on average. Furthermore, the MAEs of simulated cold-season carbon emissions at three tundra sites were improved by 72 % and 70 % on average for CH 4 and CO 2 , respectively. Overall, CH 4 emitted during the early cold season (September and October), which often includes most of the zero-curtain period in Arctic tundra, accounted for more than 50 % of the total emissions throughout the entire cold season (September to May) in the model, compared with around 49.4 % (43 %–58 %) in observations. From 1950 to 2017, both CO 2 emissions during the zero-curtain period and during the entire cold season showed increasing trends, for example, of 0.17 and 0.36 gC m -2 yr -1 at Atqasuk. This study highlights the importance of zero-curtain periods in facilitating cold-season CH 4 and CO 2 emissions from tundra ecosystems.
Previous research has demonstrated that tropical cyclone-related precipitation and flooding have been increased by anthropogenic global warming. Our work aims to quantify the contribution of climate change to the deadly flooding from the remnants of Hurricane Ida (2021) and its impact on human society. We developed an analysis framework that combines lessons from climate change attribution science, two-dimensional hydrodynamic modeling, and flood impact evaluation, including a social inequality index, to estimate remnants of Ida flooding and consequences responding to current (locally 1°C warmer) and future (another 1°C warmer) climate change. We find that an additional quarter to a half million people were exposed to flooding due to current and future climate change. The human influence on flood impacts was larger with deeper flood water depth (≥ 1 m) than with shallow depths. Socially vulnerable populations were found to be disproportionately more affected, and climate change exacerbates this inequality
A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. By ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.
Underserved communities in the United States often experience the negative impacts of climate change and environmental degradation but enjoy few of the benefits of technological and environmental advances. The White House has addressed this inequity through the Justice40 initiative, which requires 40% of the benefits of select federal investments to be directed to underserved communities (The White House, 2022). Clean energy and energy efficiency are two highlighted investment categories, so the U.S. Department of Energy will guide implementation of the Justice40 initiative by, among other things, decreasing energy burdens, increasing parity in clean energy technology access and adoption, and increasing energy resiliency. A strategy for reaching these goals is to evaluate and validate new energy efficiency technologies in commercial buildings in underserved communities, where buildings may be older, smaller, and have deferred maintenance due to historical underinvestment. This paper assesses the proficiency of the technologies under these conditions and increases awareness of the benefits to the communities. In addition, historical redlining and past negative experiences with government and large institutions may make residents wary of participating in these field validations. Researchers, therefore, may need to spend more time building relationships and matching technologies to buildings. In this paper, we analyzed technical reports to identify common required and desired field validation building characteristics, and conducted semi-structured expert conversations to identify key stages and major themes of engaging underserved communities. Our results indicate that the benefits to both the community and energy efficiency research justify the effort. The White House. (2022). Justice40. https://www.whitehouse.gov/environmentaljustice/justice40/