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At least 37 records · Page 2Linked to original sources
USGS2012

Applications of mineral surface chemistry to environmental problems

Environmental surface chemistry involves processes that occur at the interface between the regolith, hydrosphere and atmosphere. The more limited scope of the present review addresses natural and anthropogenically-induced inorganic geochemical reactions between solutes in surface and ground waters and soil and aquifer substrates. Important surficial reactions include sorption, ion exchange, dissolution, precipitation and heterogeneous oxidation/reduction processes occurring at the solid/aqueous interface. Recent research advances in this field have addressed, both directly and indirectly, societal issues related to water quality, pollution, biogeochemical cycling, nutrient budgets and chemical weathering related to long term global climate change. This review will include recent advances in the fundamental and theoretical understanding of these surficial processes, breakthroughs in experimental and instrumental surface characterization, and development of methodologies for field applications.

Reviews of Geophysics↗
USGS2021

Climate-mediated changes to linked terrestrial and marine ecosystems across the northeast Pacific coastal temperate rainforest margin

Coastal margins are important areas of materials flux that link terrestrial and marine ecosystems. Consequently, climate-mediated changes to coastal terrestrial ecosystems and hydrologic regimes have high potential to influence nearshore ocean chemistry and food web dynamics. Research from tightly coupled, high-flux coastal ecosystems can advance understanding of terrestrial–marine links and climate sensitivities more generally. In the present article, we use the northeast Pacific coastal temperate rainforest as a model system to evaluate such links. We focus on key above- and belowground production and hydrological transport processes that control the land-to-ocean flow of materials and their influence on nearshore marine ecosystems. We evaluate how these connections may be altered by global climate change and we identify knowledge gaps in our understanding of the source, transport, and fate of terrestrial materials along this coastal margin. Finally, we propose five priority research themes in this region that are relevant for understanding coastal ecosystem links more broadly.

BioScience↗
USGS1995

Seasonal land-cover regions of the United States

Global-change investigations have been hindered by deficiencies in the availability and quality of land-cover data. The U.S. Geological Survey and the University of Nebraska-Lincoln have collaborated on the development of a new approach to land-cover characterization that attempts to address requirements of the global-change research community and others interested in regional patterns of land cover. An experimental 1 -kilometer-resolution database of land-cover characteristics for the coterminous U.S. has been prepared to test and evaluate the approach. Using multidate Advanced Very High Resolution Radiometer (AVHRR) satellite data complemented by elevation, climate, ecoregions, and other digital spatial datasets, the authors define 152, seasonal land-cover regions. The regionalization is based on a taxonomy of areas with respect to data on land cover, seasonality or phenology, and relative levels of primary production. The resulting database consists of descriptions of the vegetation, land cover, and seasonal, spectral, and site characteristics for each region. These data are used in the construction of an illustrative 1:7,500,000-scaIe map of the seasonal land-cover regions as well as of smaller-scale maps portraying general land cover and seasonality. The seasonal land-cover characteristics database can also be tailored to provide a broad range of other landscape parameters useful in national and global-scale environmental modeling and assessment.

Conterminous United States↗
USGS2019

The landscape of soil carbon data: Emerging questions, synergies and databases

Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.

Progress in Physical Geography: Earth and Environm↗
USGS2025

Spatial regimes provide ample early warning of tipping points

Accelerating global change is a hallmark of the Anthropocene, and the interaction of rapid change in climate, land use and land cover makes understanding the response of social-ecological systems to global change difficult to predict. Global change directly and indirectly affects both social-ecological systems and the landscapes in which they are embedded. Spatial heterogeneity in the location, manifestation of, and responses to global change makes spatially explicit approaches to management and conservation necessary. Spatial regimes, a concept derived from resilience theory, are at the forefront of attempts to operationalize and quantify resilience of dynamic landscapes. Spatial regimes are defined as dynamic landscape units that are shaped by a self-organizing set of processes and structures. They have identifiable spatial extents with discrete boundaries at a given scale that exhibit relative homogeneity in process, structure and composition maintained by feedback mechanisms. Here, we describe the concept of, evidence for, and applications of spatial regimes and how spatial regimes relate to scale and telecoupling of change across social-ecological systems. We emphasize the utility of the concept as an early warning of regime change, one that can provide ample early warning. We discuss methods that can be used to detect spatial regimes and uses of the concept for understanding and managing the spatio-temporal response of social-ecological systems to global change.

Advances in Ecological Research↗
USGS2005

The carbon dioxide cycle

The seasonal CO2 cycle on Mars refers to the exchange of carbon dioxide between dry ice in the seasonal polar caps and gaseous carbon dioxide in the atmosphere. This review focuses on breakthroughs in understanding the process involving seasonal carbon dioxide phase changes that have occurred as a result of observations by Mars Global Surveyor.

Advances in Space Research↗
USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗
USGS2011

Seeing the forest and the trees: USGS scientist links local changes to global scale

The recent recipient of two major awards, Craig D. Allen, a research ecologist with the U.S. Geological Survey Fort Collins Science Center, has loved trees since childhood. He is now considered an expert of world renown on the twin phenomena of forest changes and tree mortality resulting from climate warming and drought, and in 2010 was twice recognized for his scientific contributions. In December 2010, Dr. Allen was named a 2010 Fellow of the American Association for the Advancement of Science “for outstanding leadership in the synthesis of global forest responses to climate change, built from worldwide collaboration and a deep understanding of the environmental history of the southwestern United States.” In March 2010, he was honored with the Meritorious Service Award from the U.S. Department of the Interior (DOI) in recognition of his outstanding vision, initiative, and scientific contributions to the USGS, DOI, and U.S. Department of Agriculture in establishing a model science program to support adaptive land management at the new Valles Caldera National Preserve in north-central New Mexico. Dr. Allen has authored more than 85 publications on landscape ecology and landscape change, from fire history and ecology to ecosystem responses to climate change. He has appeared on NOVA discussing fire ecology and on The Discovery Channel and Discovery Canada explaining the links between drought-induced tree mortality and climate warming, in addition to being interviewed and quoted in innumerable newspaper articles on both topics. But how did this unassuming scientist grow from nurturing maple saplings on 40 acres in Wisconsin to understanding forest system stress worldwide?

Report↗
USGS2025

Second Integrated Hydro-Terrestrial Modeling (IHTM 2.0) workshop: USGCRP federal agency perspectives

U.S. federal leadership, mobilizing close interagency coordination across sectors, is key to tackling compound climate and human impacts on our nation’s water resources. Recognizing this need, federal agencies and academic collaborators conducted a series of workshops to advance Integrated Hydro-Terrestrial Modeling (IHTM). IHTM is focused on supporting a multiscale framework to accelerate research insights, better integrate operational and planning perspectives, and bridge national-to-regional capabilities to address major interdependent societal water challenges. This framework leverages the capabilities of different agencies and institutional partners across sectors to advance a shared vision for use-inspired modeling and open science. The IHTM conceptual framework has developed over several community workshops in recent years: ● In September 2019, a community coordinating group on IHTM hosted an interagency workshop (“IHTM 1.0”) with support from NSF, DOE, and USGS. The resulting report identified the need for agencies to invest resources in designing pilot use cases, setting the stage for an integrated national IHTM capability. ● In November 2020, the U.S. Global Change Research Program (USGCRP) held a virtual Coastal-IHTM (C-IHTM) workshop in collaboration with the MultiSector Dynamics Community of Practice, which engages researchers across universities and national labs. Building on IHTM 1.0, this workshop aimed to identify coastal modeling capabilities and appropriate coastal applications of the IHTM framework. The workshop report detailed needs for open science, geographical or topical use cases, integrated modeling frameworks, and linking communities of practice. ● From October 31 to November 2, 2023, USGCRP hosted a hybrid IHTM 2.0 community workshop that brought together 160 scientists and managers from nine federal departments/agencies (DHS-FEMA, DOC-NOAA, DoD-USACE, DOE, DOI [U.S. Bureau of Reclamation (USBR), USGS], EPA, NASA, NSF, USDA [ARS, FS, NRCS]) and 32 non-federal academic, non-profit, and private institutions and consortiums. The workshop was organized by a federal Interagency Steering Committee with representatives from DOE, USGS, NSF, NASA, and NOAA, as well as a Scientific Organizing Committee comprising experts from academia and additional federal agency technical experts. The IHTM 2.0 workshop focused on moving the IHTM 1.0 concepts to action by making advances in designing national and regional integrated modeling experiments in five geographic testbeds. These modeling testbeds seek to facilitate collaborative water resources research and assessment that responds to societal needs, extending from basic research to resource management operations, including the assessment of water quantity, quality, and use at national and regional scales. Ultimately, we envision that the IHTM testbeds will improve our ability to provide water resources assessment scenarios to decision-makers and the public. This document summarizes USGCRP and member agencies’ perspectives of the IHTM 2.0 workshop. Sections 2 and 3 build on the work of the IHTM 2.0 workshop Scientific Organizing Committee to outline the importance of IHTM, summarize the workshop, and propose near- and medium-term IHTM priorities. Section 4 presents select ongoing and potential interagency activities that could help realize the IHTM 2.0 vision and align with three of USGCRP’s strategic goals for this decade: Advancing Science, Informing Decisions, and Engaging the Nation. Finally, Section 5 summarizes this report and offers information about how to connect with USGCRP’s IHTM activities. USGCRP and its member agencies are well-positioned to coordinate federal efforts to enhance IHTM capabilities in the coming years.

Conference Paper↗
USGS2025

​​Integrated Hydro-terrestrial Modeling 2.0: Progress and path forward on building a national capability​

Growing societal pressures on U.S. water resources and the challenges inherent in understanding how future water risks may evolve are driving major investments to improve our knowledge of the integrated water cycle. This improved understanding as captured in innovations in our data, knowledge, and modeling capabilities, needs to be accelerated through better integration and coordination across scientific disciplines, programs, and U.S. agencies. The Integrated Hydro-Terrestrial Modeling (IHTM) community holds promise to accelerate the progress required to manage the U.S. water resources sustainably, equitably, and effectively. The U.S. Global Change Research Program (USGCRP) coordinates research on the impacts of global change on the water cycle through interagency collaboration. USGCRP agencies and their partners jointly held the IHTM 2.0 workshop for U.S. federal and non-federal scientists and managers in fall 2023, aiming to advance community modeling and integrated water resources management capabilities following open science principles. This workshop focused on developing both national and regional testbeds that employ state-of-the-art modeling approaches to explore gaps and opportunities for improving the representation and extensibility of hydrologic processes and modeling. Integrated regional testbeds in Mid-Atlantic, Great Lakes, Colorado River Basin, and Gulf Coast/Mississippi regions were proposed to leverage existing investments and seek actionable collaboration on issues such as water extremes, water quality, water use, and urbanization. Collaborations focused on advancing iterative cycles of model development and testing offer a means for regional scale studies to inform national scale modeling applications and yield nationally consistent modeling frameworks that are also locally relevant. This presentation will highlight key takeaways, findings, and future directions for the IHTM community that have been laid out in the IHTM 2.0 workshop report.

Report↗
USGS2014

Methane hydrates in nature - Current knowledge and challenges

Recognizing the importance of methane hydrate research and the need for a coordinated effort, the United States Congress enacted the Methane Hydrate Research and Development Act of 2000. At the same time, the Ministry of International Trade and Industry in Japan launched a research program to develop plans for a methane hydrate exploratory drilling project in the Nankai Trough. India, China, the Republic of Korea, and other nations also have established large methane hydrate research and development programs. Government-funded scientific research drilling expeditions and production test studies have provided a wealth of information on the occurrence of methane hydrates in nature. Numerous studies have shown that the amount of gas stored as methane hydrates in the world may exceed the volume of known organic carbon sources. However, methane hydrates represent both a scientific and technical challenge, and much remains to be learned about their characteristics and occurrence in nature. Methane hydrate research in recent years has mostly focused on: (1) documenting the geologic parameters that control the occurrence and stability of methane hydrates in nature, (2) assessing the volume of natural gas stored within various methane hydrate accumulations, (3) analyzing the production response and characteristics of methane hydrates, (4) identifying and predicting natural and induced environmental and climate impacts of natural methane hydrates, (5) analyzing the methane hydrate role as a geohazard, (6) establishing the means to detect and characterize methane hydrate accumulations using geologic and geophysical data, and (7) establishing the thermodynamic phase equilibrium properties of methane hydrates as a function of temperature, pressure, and gas composition. The U.S. Department of Energy (DOE) and the Consortium for Ocean Leadership (COL) combined their efforts in 2012 to assess the contributions that scientific drilling has made and could continue to make to advance our understanding of methane hydrates in nature. COL assembled a Methane Hydrate Project Science Team with members from academia, industry, and government. This Science Team worked with COL and DOE to develop and host the Methane Hydrate Community Workshop, which surveyed a substantial cross section of the methane hydrate research community for input on the most important research developments in our understanding of methane hydrates in nature and their potential role as an energy resource, a geohazard, and/or as an agent of global climate change. Our understanding of how methane hydrates occur in nature is still growing and evolving, and it is known with certainty that field, laboratory, and modeling studies have contributed greatly to our understanding of hydrates in nature and will continue to be a critical source of the information needed to advance our understanding of methane hydrates.

Journal of Chemical and Engineering Data↗
USGS2017

A mosaic-based approach is needed to conserve biodiversity in disturbed freshwater ecosystems

Conserving native biodiversity in the face of human‐ and climate‐related impacts is a challenging and globally important ecological problem that requires an understanding of spatially connected, organismal‐habitat relationships. Globally, a suite of disturbances (e.g., agriculture, urbanization, climate change) degrades habitats and threatens biodiversity. A mosaic approach (in which connected, interacting collections of juxtaposed habitat patches are examined) provides a scientific foundation for addressing many disturbance‐related, ecologically based conservation problems. For example, if specific habitat types disproportionately increase biodiversity, these keystones should be incorporated into research and management plans. Our sampling of fish biodiversity and aquatic habitat along ten 3‐km sites within the Upper Neosho River subdrainage, KS, from June‐August 2013 yielded three generalizable ecological insights. First, specific types of mesohabitat patches (i.e., pool, riffle, run, and glide) were physically distinct and created unique mosaics of mesohabitats that varied across sites. Second, species richness was higher in riffle mesohabitats when mesohabitat size reflected field availability. Furthermore, habitat mosaics that included more riffles had greater habitat diversity and more fish species. Thus, riffles (<5% of sampled area) acted as keystone habitats. Third, additional conceptual development, which we initiate here, can broaden the identification of keystone habitats across ecosystems and further operationalize this concept for research and conservation. Thus, adopting a mosaic approach can increase scientific understanding of organismal‐habitat relationships, maintain natural biodiversity, advance spatial ecology, and facilitate effective conservation of native biodiversity in human‐altered ecosystems.

Kansas↗
USGS2025

One-hundred fundamental, open questions to integrate methodological approaches in lake ice research

The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.

Water Resources Research↗
USGS2022

Lacunarity as a tool for assessing landscape configuration over time and informing long-term monitoring: An example using seagrass

Context Seagrasses are submerged marine plants that have been declining globally at increasing rates. Natural resource managers rely on monitoring programs to detect and understand changes in these ecosystems. Technological advancements are allowing for the development of patch-level seagrass maps, which can be used to explore seagrass meadow spatial patterns. Objectives Our research questions involved comparing lacunarity, a measure of landscape configuration, for seagrass to assess cross-site differences in areal coverage and spatial patterns through time. We also discussed how lacunarity could help natural resource managers with monitoring program development and restoration decisions and evaluation. Methods We assessed lacunarity of seagrass meadows for various box sizes (0.0001 ha to 400.4 ha) around Cat Island and Ship Island, Mississippi (USA). For Cat Island, we used seagrass data from 2011 to 2014. For Ship Island, we used seagrass data for seven dates between 1963 and 2014. Results Cat Island, which had more continuous seagrass meadows, had lower lacunarity (i.e., denser coverage) compared to Ship Island, which had patchier seagrass beds. For Ship Island, we found a signal of disturbance and path toward recovery from Hurricane Camille in 1969. Finally, we highlighted how lacunarity curves could be used as one of multiple considerations for designing monitoring programs, which are commonly used for seagrass monitoring. Conclusions Lacunarity can help quantify spatial pattern dynamics, but more importantly, it can assist with natural resource management by defining fragmentation and potential scales for monitoring. This approach could be applied to other environments, especially other coastal ecosystems.

Mississippi↗
USGS2006

USGS science in Menlo Park -- a science strategy for the U.S. Geological Survey Menlo Park Science Center, 2005-2015

In the spring of 2004, the U.S. Geological Survey (USGS) Menlo Park Center Council commissioned an interdisciplinary working group to develop a forward-looking science strategy for the USGS Menlo Park Science Center in California (hereafter also referred to as "the Center"). The Center has been the flagship research center for the USGS in the western United States for more than 50 years, and the Council recognizes that science priorities must be the primary consideration guiding critical decisions made about the future evolution of the Center. In developing this strategy, the working group consulted widely within the USGS and with external clients and collaborators, so that most stakeholders had an opportunity to influence the science goals and operational objectives. The Science Goals are to: Natural Hazards: Conduct natural-hazard research and assessments critical to effective mitigation planning, short-term forecasting, and event response. Ecosystem Change: Develop a predictive understanding of ecosystem change that advances ecosystem restoration and adaptive management. Natural Resources: Advance the understanding of natural resources in a geologic, hydrologic, economic, environmental, and global context. Modeling Earth System Processes: Increase and improve capabilities for quantitative simulation, prediction, and assessment of Earth system processes. The strategy presents seven key Operational Objectives with specific actions to achieve the scientific goals. These Operational Objectives are to: Provide a hub for technology, laboratories, and library services to support science in the Western Region. Increase advanced computing capabilities and promote sharing of these resources. Enhance the intellectual diversity, vibrancy, and capacity of the work force through improved recruitment and retention. Strengthen client and collaborative relationships in the community at an institutional level. Expand monitoring capability by increasing density, sensitivity, and efficiency and reducing costs of instruments and networks. Encourage a breadth of scientific capabilities in Menlo Park to foster interdisciplinary science. Communicate USGS science to a diverse audience.

Circular↗
USGS2017

The U.S. Geological Survey Flagstaff Science Campus—Providing expertise on planetary science, ecology, water resources, geologic processes, and human interactions with the Earth

T he U.S. Geological Survey’s Flagstaff Science Campus is focused on interdisciplinary study of the Earth and solar system, and has the scientific expertise to detect early environmental changes and provide strategies to minimize possible adverse effects on humanity. The Flagstaff Science Campus (FSC) is located in Flagstaff, Arizona, which is situated in the northern part of the State, home to a wide variety of landscapes and natural resources, including (1) young volcanoes in the San Francisco Volcanic Field, (2) the seven ecological life zones of the San Francisco Peaks, (3) the extensive geologic record of the Colorado Plateau and Grand Canyon, (4) the Colorado River and its perennial, ephemeral, and intermittent tributaries, and (5) a multitude of canyons, mountains, arroyos, and plains. More than 200 scientists, technicians, and support staff provide research, monitoring, and technical advancements in planetary geology and mapping, biology and ecology, Earth-based geology, hydrology, and changing climate and landscapes. Scientists at the FSC work in collaboration with multiple State, Federal, Tribal, municipal, and academic partners to address regional, national, and global environmental issues, and provide scientific outreach to the general public.

Arizona↗
USGS2017

Engaging the user community for advancing societal applications of the Surface Water Ocean Topography mission

Scheduled for launch in 2021, the Surface Water and Ocean Topography (SWOT) mission will be a truly unique mission that will provide high-temporal-frequency maps of surface water extents and elevation variations of global water bodies (lakes/reservoirs, rivers, estuaries, oceans, and sea ice) at higher spatial resolution than is available with current technologies (Biancamaria et al. 2016; Alsdorf et al. 2007). The primary instrument on SWOT is based on a Ka-band radar interferometer (KaRIN), which uses radar interferometery technology. The satellite will fly two radar antennas at either end of a 10-m (33 ft) mast, allowing it to measure the elevation of the surface along a 120-km (75 mi)-wide swath below. The availability of high-frequency and high-resolution maps of elevations and extents for surface water bodies and oceans will present unique opportunities to address numerous societally relevant challenges around the globe (Srinivasan et al. 2015). These opportunities may include such diverse and far-ranging applications as fisheries management, flood inundation mapping/risk mitigation/forecasting, wildlife conservation, global data assimilation for improving forecast of ocean tides and weather, reservoir management, climate change impacts and adaptation, and river discharge estimation, among others. Although SWOT is a research mission and not scheduled for launch for another 4 years, there is a need to build engagement within the application community now and to explore how best to advance the societal relevance and benefits of the SWOT mission from concept to reality. The SWOT Applications Working Group organized a workshop on 5–6 April 2017 at the U.S. Geological Survey (USGS) headquarters in Reston, Virginia. The goal of the workshop was to understand and communicate how the applications community can use SWOT data to address problems of profound societal relevance.

Bulletin of the American Meteorological Society↗
USGS2025

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗