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At least 127 records · Page 7Linked to original sources
USGS2022

Adaptive problem maps (APM): Connecting data dots to build increasingly informed and defensible environmental conservation decisions

Connecting individual datasets from different projects to each other and to decisions can help manager-researcher-administrator teams build on what is known and adapt their environmental decision-making process as new information becomes available. Throughout their careers, environmental professionals often collect data on many individual projects that address similar sets of natural resource conservation problems. Consequently, the institutions, agencies, and organizations that employ these environmental professionals accumulate a large reservoir of project-specific information. However, bigger-picture opportunities to advance broader natural resource conservation goals are lost if individual projects and datasets are not integrated. Here we illustrate how our adaptive problem mapping (APM) process provides a framing and internal structure that charts relationships among pertinent information types, germane data sets, applicable concepts, and relevant decisions. In the APM process, appropriately defined problem statements and coordinated bridging questions connect data and concepts to build a network of increasingly informed and defensible decisions. Although our APM process can be applied to many environmental problems, here we focus on examples from aquatic systems in which fish are conservation priorities. Prioritizing an initial evaluation and regular modification of the relationships among datasets and decisions using the APM process helps manager-research-administrator teams envision, track, and update what is known, unknown, learned, and needed. The resulting broader point of view advances strategic planning, evaluations of progress, assessments of opportunity costs, identification of options, and justifications of decision-related actions.

Journal of Environmental Management↗
USGS2021

Preface to book: Wetland carbon and environmental management

The idea for this book, including its organization and contents, has its origin in the latest environmental and climate policy requirements in the United States, as well as science advances. In 2007, the U.S. Congress passed the Energy Independence and Security Act (EISA), from which Section 712 required U.S. Federal agencies to provide a better understanding of carbon and greenhouse gas fluxes across the United States. As a result, largescale and coordinated efforts were launched to assess carbon storage, carbon fluxes, and greenhouse gas fluxes including CO2, CH4, and N2O from all major terrestrial and freshwater aquatic ecosystems, including forest, grassland/shrub, agricultural lands, wetlands, and rivers, streams, lakes, and impoundments. The EISA assessment produced major results (Selmants et al., 2017; Zhu, 2011; Zhu & McGuire, 2016; Zhu & Reed, 2012, 2014), but recognized that wetlands remained a significant source of uncertainty, especially for those wetlands that were being actively managed. The more recent Second State of the Carbon Cycle Report by the U.S. Global Change Research Program (USGCRP), which devoted two separate chapters to inland and coastal wetlands, respectively, noted that large knowledge gaps still remain, ranging from inadequate analysis of restored and managed wetlands, and consequences of management decisions, to future wetland responses to climate change (USGCRP, 2018). In recent literature, wetland management is suggested as a potential natural solution to mitigate climate change (Fargione et al., 2018, Kroeger et al., 2017) and help offset direct losses of wetlands from sea level rise, subsidence, and coastal erosion (Wang et al., 2017). The recognition that a synthesis of wetland carbon management was urgently needed was the genesis of Wetland Carbon and Environmental Management; discerning the relationships between wetland management and carbon flux (loss or gain) is an international goal.

Geophysical Monograph Series↗
USGS2025

Insights and strategic opportunities from the USGS 2024 Per- and Polyfluoroalkyl Substances (PFAS) Interagency Workshop

Introduction In 2021, the U.S. Geological Survey (USGS) published Circular 1490 titled, “Integrated Science for the Study of Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) in the Environment: A Strategic Science Vision for the U.S. Geological Survey” (Tokranov and others, 2021). Circular 1490 was created to be a resource for USGS scientists prioritizing and planning research related to per- and polyfluoroalkyl substances (PFAS) and to be a guide for developing partnerships with other scientists, State and Federal agencies, and stakeholders engaged in PFAS research and management and mitigation of the environmental and human-health effects of PFAS. This USGS PFAS Strategic Science Vision document was intended to be the foundation for a “living strategic vision,” periodically providing updates on the state of USGS PFAS research, emerging PFAS data gaps and needs, and progress on interagency and stakeholder PFAS partnerships and priorities. To meet this objective, the USGS planned to host an Interagency and Stakeholder PFAS Workshop every 2–3 years. During September 10–12, 2024, the USGS hosted the first Interagency and Stakeholder PFAS Workshop in Reston, Virginia. The Workshop brought together experts from other Federal agencies (U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, Food and Drug Administration, Department of Defense [Air Force, Army]), State agencies (Washington Fish and Wildlife, Virginia Department of Transportation), and academia (Harvard University, University of Maryland) to address key challenges relating to the measurement and modeling of PFAS and the implications for environmental health. Participants engaged in in-depth discussions centered around six pivotal topics related to PFAS: (1) sampling protocols, methods and interpretation; (2) environmental sources, source apportionment, and occurrence; (3) environmental fate and transport; (4) human and wildlife exposure routes and risk; (5) bioconcentration, bioaccumulation, and biomagnification; and (6) ecotoxicology and effects. Each topic had three breakout sessions. A recurrent theme of workshop discussions was how data on a nationwide scale for PFAS occurrence in various environmental matrices, including air, water, food crops, biota, soil, and streambed sediment could help to advance scientific understanding. Participants noted significant geospatial data gaps, particularly in the midwestern and southern United States and the Pacific Northwest. PFAS data collection tends to be more robust along the eastern seaboard and in California. Participants stressed how enhancing the integration of large and small datasets across various agencies could help to support national scale understanding of PFAS. To address these gaps, attendees suggested leveraging datasets from Federal entities like the USGS and the U.S. Department of Defense, State agencies, and municipal utility services to develop predictive contaminant detection and transport models. Improved coordination between water quality programs and USGS research could help to facilitate access to valuable data, leading to comprehensive databases that inform PFAS point (wastewater treatment plants and landfills) and nonpoint (runoff from land, atmospheric deposition, food packaging) sources, environmental transport mechanisms, environmental detection and concentrations, potential exposure routes, and health effects on different biota, including humans. A specific request was made to develop a map demarking the depth of modern (1953 or later) groundwater, which is susceptible to surface-derived anthropogenic (that is, human-made) contamination, based on tritium-age dating. Emphasis was placed on incorporation of hydrology, groundwater flow paths, groundwater–surface water interactions, and landscape factors in predictive statistical models as a step to improve contaminant source identification and tracking. Molecular fingerprinting approaches garnered attention as techniques to link specific PFAS mixtures detected in a sample to environmental sources and levels in biota (Dávila-Santiago and others, 2022). Integrating data from abiotic (that is, water, soil, and air) and biotic (that is, living organisms) systems identified as a research opportunity. For example, understanding the composition of soils and sediments, which include a mixture of mineral, plant, and animal components, could advance understanding of exposure pathways. The discussions highlighted opportunities to explore and understand the potential redistribution and biotic exposures of PFAS from biosolid and wastewater treatment plant effluent land application practices, in addition to atmospheric releases and discharges from landfill and wastewater treatment plants. Participants identified research gaps surrounding how these sources may contribute to contamination and may affect surrounding ecosystems, including a better definition of anthropogenic background concentrations. Moving forward, the collection of co-occurrence data was noted as a means to improve understanding of complex mixtures and to leverage companion modeling efforts focused on areas with high and low contamination levels to identify areas of concern and unaffected resources. Participants emphasized how centralized USGS databases and the establishment of sample-metadata archives can help to ensure that samples are preserved and accessible for future research. In conclusion, the workshop participants identified opportunities to bridge data gaps and improve measurement techniques, modeling frameworks, databases, and communication, to enhance the understanding of PFAS and their effects on environmental and human health. Upon completion of the workshop, participants indicated an interest in developing strategic data collection, modeling, and analytical approaches to address these challenges.

Open-File Report↗
USGS2013

An automated digital imaging system for environmental monitoring applications

Recent improvements in the affordability and availability of high-resolution digital cameras, data loggers, embedded computers, and radio/cellular modems have advanced the development of sophisticated automated systems for remote imaging. Researchers have successfully placed and operated automated digital cameras in remote locations and in extremes of temperature and humidity, ranging from the islands of the South Pacific to the Mojave Desert and the Grand Canyon. With the integration of environmental sensors, these automated systems are able to respond to local conditions and modify their imaging regimes as needed. In this report we describe in detail the design of one type of automated imaging system developed by our group. It is easily replicated, low-cost, highly robust, and is a stand-alone automated camera designed to be placed in remote locations, without wireless connectivity.

Open-File Report↗
USGS2023

Landscape transcriptomics as a tool for addressing global change effects across diverse species

Landscape transcriptomics is an emerging field studying how genome-wide expression patterns reflect dynamic landscape-scale environmental drivers, including habitat, weather, climate, and contaminants, and the subsequent effects on organismal function. This field is benefitting from advancing and increasingly accessible molecular technologies, which in turn are allowing the necessary characterization of transcriptomes from wild individuals distributed across natural landscapes. This research is especially important given the rapid pace of anthropogenic environmental change and potential impacts that span levels of biological organization. We discuss three major themes in landscape transcriptomic research: connecting transcriptome variation across landscapes to environmental variation, generating and testing hypotheses about the mechanisms and evolution of transcriptomic responses to the environment, and applying this knowledge to species conservation and management. We discuss challenges associated with this approach and suggest potential solutions. We conclude that landscape transcriptomics has great promise for addressing fundamental questions in organismal biology, ecology, and evolution, while providing tools needed for conservation and management of species.

Molecular Ecology Resources↗
USGS2018

Evolving environmental and geometric controls on Columbia Glacier’s continued retreat

Geometry strongly controls the dynamic behavior of marine‐terminating (tidewater) glaciers, significantly influencing advance and retreat cycles independent of climate. Yet the recent, nearly ubiquitous retreat of tidewater glaciers suggests that changes in atmospheric and oceanic forcing may also drive dynamic change. To isolate the influence of geometry on tidewater glacier dynamics, we analyzed detailed observational time series from 2012 to 2016 for two tidewater glaciers with shared dynamic histories and environmental forcing: Columbia Glacier and its former tributary (Post Glacier) in southcentral Alaska. We find that although terminus retreat has driven decadal‐scale changes in dynamics of the Columbia‐Post system, environmental factors contribute to short‐term (i.e., seasonal) dynamic variability. In particular, analysis of force balance time series indicates that observed variations in speed result from seasonal changes to the subglacial hydrologic system and associated changes in basal drag. Variations in terminus position only drive noticeable speed change when the terminus retreats from regions of relatively high basal drag. In agreement with long‐term analyses of Columbia Glacier, we find that terminus geometry can perturb the timing of seasonal ice flow patterns. Specifically, our data support the idea that retreat of a glacier terminus into deeper water is accompanied by a shift in the primary control on frontal ablation. Although our analysis focuses on two Alaskan glaciers, our data suggest that changes in the relative importance of surface meltwater and buoyancy effects on submarine melting and/or calving may manifest as a shift in terminus change seasonality and offer a mechanism to identify frontal ablation controls.

Alaska↗
USGS2011

An adaptive decision framework for the conservation of a threatened plant

Mead's milkweed Asclepias meadii , a long-lived perennial herb of tallgrass prairie and glade communities of the central United States, is a species designated as threatened under the U.S. Endangered Species Act. Challenges to its successful management include the facts that much about its life history is unknown, its age at reproductive maturity is very advanced, certain life stages are practically unobservable, its productivity is responsive to unpredictable environmental events, and most of the known populations occur on private lands unprotected by any legal conservation instrument. One critical source of biological uncertainty is the degree to which fire promotes growth and reproductive response in the plant. To aid in its management, we developed a prototype population-level state-dependent decision-making framework that explicitly accounts for this uncertainty and for uncertainties related to stochastic environmental effects and vital rates. To parameterize the decision model, we used estimates found in the literature, and we analyzed data from a long-term monitoring program where fates of individual plants were observed through time. We demonstrate that different optimal courses of action are followed according to how one believes that fire influences reproductive response, and we show that the action taken for certain population states is informative for resolving uncertainty about competing beliefs regarding the effect of fire. We advocate the use of a model-predictive approach for the management of rare populations, particularly when management uncertainty is profound. Over time, an adaptive management approach should reduce uncertainty and improve management performance as predictions of management outcome generated under competing models are continually informed and updated by monitoring data.

Journal of Fish and Wildlife Management↗
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↗
USGS2012

Geologic and environmental characteristics of porphyry copper deposits with emphasis on potential future development in the Bristol Bay Watershed, Alaska (Appendix H)

This report is prepared in cooperation with the Bristol Bay Watershed Assessment being conducted by the U.S. Environmental Protection Agency. The goal of the assessment is to help understand how future large-scale development in this watershed may affect water quality and the salmon fishery. Mining has been identified as a potential source of future large scale development in the region, especially because of the advanced stage of activity at the Pebble prospect. The goal of this report is to summarize the geologic and environmental characteristics of porphyry copper deposits in general, largely on the basis of literature review. Data reported in the Pebble Project Environmental Baseline Document, released by the Pebble Limited Partnership in 2011, are used to enhance the relevance of this report to the Bristol Bay watershed. The geologic characteristics of mineral deposits are paramount to determining their geochemical signatures in the environment. The geologic characteristics of mineral deposits are reflected in the mineralogy of the mineralization and alteration assemblages; geochemical associations of elements, including the commodities being sought; the grade and tonnage of the deposit; the likely mining and ore-processing methods used; the environmental attributes of the deposit, such as acid-generating and acid-neutralizing potentials of geologic materials; and the susceptibility of the surrounding ecosystem to various stressors related to the deposit and its mining, among other features (Seal and Hammarstrom, 2003). Within the Bristol Bay watershed, or more specifically the Nushagak and Kvichak watersheds, the geologic setting is permissive for the occurrence of several mineral deposit types that are amenable for large-scale development. Of these deposit types, porphyry copper deposits (e.g., Pebble) and intrusion-related gold deposits (e.g., Shotgun) are the most important on the basis of the current maturity of exploration activities by the mining industry. The Pebble deposit sits astride the drainage divide between the Nushagak and Kvichak watersheds, whereas the Humble, Big Chunk, and Shotgun deposits are within the Nushagak watershed. The Humble and Big Chunk prospects are geophysical anomalies that exhibit some characteristics similar to those found at Pebble. Humble was drilled previously in 1958 and 1959 as an iron prospect on the basis of an airborne magnetic anomaly. Humble is approximately 85 miles (137 km) west of Pebble; Big Chunk is approximately 30 miles (48 km) north-northwest of Pebble; and Shotgun is approximately 110 miles (177 km) northwest of Pebble. The H and D Block prospects, west of Pebble, represent additional porphyry copper exploration targets in the watershed.

Alaska↗
USGS2022

A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty

An open-source tool has been developed to facilitate constrained single- and multi-objective optimization under uncertainty (CMOU) analyses. The tool uses the well-known PEST interface protocols to communicate with the underlying forward simulation, making it non-intrusive. The tool contains a built-in parallel run manager to make use of heterogeneous and distributed computing resources. Several popular and well-known evolutionary algorithms are implemented and can be combined with a range of approaches to represent uncertainty in model-derived constraint/objective values. These attributes serve to address the current barrier to adopt advanced CMOU analyses for a wide range of decision-support problems across the environmental modeling spectrum. We demonstrate the capabilities of the CMOU tool on a well-known analytical benchmark problem that we augmented to include uncertainty, as well as on a synthetic density-dependent coastal groundwater management benchmark problem. Both demonstrations highlight the importance of explicitly accounting for uncertainty to convey risk and reliability in pareto-optimal design.

Environmental Modelling & Software↗
USGS2018

The natural capital accounting opportunity: Let's really do the numbers

The nation’s economic accounts provide objective, regular, and standardized information routinely relied upon by public and private decision makers. But they are incomplete. The U.S. and many other nations currently do not account for the natural capital — such as the wildlife, forests, grasslands, soils, and water bodies—upon which all other economic activity rests. By creating formal natural capital accounts (NCA) and ecosystem goods and services (EGS) accounts, governments and businesses can better understand the past, peer into the future, innovate, conserve, and plan for environmental shocks. They would standardize, regularly repeat, and aggregate diverse natural resource, environmental, and social and economic data and could thereby play a significant role in advancing the science of coupled biophysical and social systems.

BioScience↗
USGS2020

Integrating airborne remote sensing and field campaigns for ecology and Earth system science

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.

Colorado↗
USGS2026

Opportunities and challenges for incorporating lithium-ion batteries into geophysical power systems

Batteries play a critical role at seismic and other geophysical stations in ensuring that the equipment receives uninterrupted power to make continuous observations of the Earth. Often sited in remote environments under a wide range of environmental conditions, these stations have almost ubiquitously used conventional lead‐acid batteries. However, recent advances in rechargeable lithium‐ion battery technology have led to the development of lithium‐iron phosphate (LFP) batteries that can replace lead‐acid batteries in energy storage systems. In the past three years, LFP battery production has grown over an order of magnitude, reducing their cost and increasing their availability. In this article, we examine the benefits and challenges associated with incorporating several types of LFP batteries into the power systems of geophysical stations. We review how fundamental differences in battery chemistry enable LFP batteries to weigh less than half of comparable lead‐acid batteries and may have longer service lives but have the added complexity of being managed by an integrated battery monitoring system (BMS) microcontroller. Through a controlled heat chamber experiment, we demonstrate that LFP batteries can be ideally suited for use in high‐temperature environments by offering longer service lives than lead‐acid batteries. However, for safety reasons, the BMS prevents most LFP batteries from being charged at temperatures <0°C, which complicates their use in colder regions and can lead to equipment damage if the charging system is not appropriately designed for this battery type. Finally, we address some of the unique challenges associated with adopting lithium batteries, including unexpected substantial (≤14 W) power consumption from the BMS, safety concerns, and shipping restrictions. It is our goal to help inform station operators and geophysicists about potential benefits and issues that can arise from using LFP batteries at seismic and geophysical stations in a range of environments.

Seismological Research Letters↗
USGS2017

Cobalt

Cobalt is a silvery gray metal that has diverse uses based on certain key properties, including ferromagnetism, hardness and wear-resistance when alloyed with other metals, low thermal and electrical conductivity, high melting point, multiple valences, and production of intense blue colors when combined with silica. Cobalt is used mostly in cathodes in rechargeable batteries and in superalloys for turbine engines in jet aircraft. Annual global cobalt consumption was approximately 75,000 metric tons in 2011; China, Japan, and the United States (in order of consumption amount) were the top three cobalt-consuming countries. In 2011, approximately 109,000 metric tons of recoverable cobalt was produced in ores, concentrates, and intermediate products from cobalt, copper, nickel, platinum-group-element (PGE), and zinc operations. The Democratic Republic of the Congo (Congo [Kinshasa]) was the principal source of mined cobalt globally (55 percent). The United States produced a negligible amount of byproduct cobalt as an intermediate product from a PGE mining and refining operation in southeastern Montana; no U.S. production was from mines in which cobalt was the principal commodity. China was the leading refiner of cobalt, and much of its production came from cobalt ores, concentrates, and partially refined materials imported from Congo (Kinshasa). The mineralogy of cobalt deposits is diverse and includes both primary (hypogene) and secondary (supergene) phases. Principal terrestrial (land-based) deposit types, which represent most of world’s cobalt mine production, include primary magmatic Ni-Cu(-Co-PGE) sulfides, primary and secondary stratiform sediment-hosted Cu-Co sulfides and oxides, and secondary Ni-Co laterites. Seven additional terrestrial deposit types are described in this chapter. The total terrestrial cobalt resource (reserves plus other resources) plus past production, where available, is calculated to be 25.5 million metric tons. Additional resources of cobalt are known to occur on the modern sea floor in aerially extensive deposits of Fe-Mn(-Ni-Cu-Co-Mo) nodules and Fe-Mn(-Co-Mo-rare-earth-element) crusts. Legal, economic, and technological barriers have prevented exploitation of these cobalt resources, which lie at water depths of as great as 6,000 meters, although advances in technology may soon allow production of these resources to be economically viable. Environmental issues related to cobalt mining concern mainly the elevated cobalt contents in soils and waters. Although at low levels cobalt is essential to human health (it is the central atom in the critical nutrient vitamin B12), overexposure to high levels of cobalt may cause lung and heart dysfunction, as well as dermatitis. The ecological impacts of cobalt vary widely and can be severe for some species of fish and plants, depending on various environmental factors.

Professional Paper↗
USGS2019

Photosynthetic and respiratory responses of two bog shrub species to whole ecosystem warming and elevated CO2 at the boreal-temperate ecotone

Peatlands within the boreal-temperate ecotone contain the majority of terrestrial carbon in this region, and there is concern over the fate of such carbon stores in the face of global environmental changes. The Spruce and Peatland Response Under Changing Environments (SPRUCE) facility aims to advance the understanding of how such peatlands may respond to such changes, using a combination of whole ecosystem warming (WEW; +0, 2.25, 4.5, 6.75, and 9°C) and elevated CO 2 (eCO 2 ; +500 ppm) treatments in an intact bog ecosystem. We examined photosynthetic and respiration responses in leaves of two ericaceous shrub species–leatherleaf [ Chamaedaphne calyculata (L.) Moench] and bog Labrador tea [ Rhododendron groenlandicum (Oeder) Kron & Judd]–to the first year of combined eCO 2 and WEW treatments at SPRUCE. We surveyed the leaf N content per area ( N area ), net photosynthesis ( A ST ) and respiration ( R D 25 ) at 25°C and 400 ppm CO 2 and net photosynthesis at mean growing conditions ( A GR ) of newly emerged, mature and overwintered leaves. We also measured leaf non-structural carbohydrate content ( NSC ) in mature leaves. The effects of WEW and eCO 2 varied by season and species, highlighting the need to accommodate such variability in modeling this system. In mature leaves, we did not observe a response to either treatment of A ST or R D 25 in R. groenlandicum , but we did observe a 50% decrease in A ST of C. calyculata with eCO 2 . In mature leaves under eCO 2 , neither species had increased A GR and both had increases in NSC , indicating acclimation of photosynthesis to eCO 2 may be related to source-sink imbalances of carbohydrates. Thus, productivity gains of shrubs under eCO 2 may be lower than previously predicted for this site by models not accounting for such acclimation. In newly emerged leaves, A ST increased with WEW in R. groenlandicum , but not C. calyculata . Overwintered leaves exhibited a decrease in R D 25 for R. groenlandicum and in A ST for C. calyculata with increasing WEW, as well as an increase of A GR with eCO 2 in both species. Responses in newly emerged and overwintered leaves may reflect physiological acclimation or phenological changes in response to treatments.

Minnesota↗
USGS1986

Applications of Landsat data and the data base approach

A generalized methodology for applying digital Landsat data to resource inventory and assessment tasks is currently being used by several bureaux and agencies within the US Department of the Interior. The methodology includes definition of project objectives and output, identification of source materials, construction of the digital data base, performance of computer-assisted analyses, and generation of output. The USGS, Bureau of Land Management, US Fish and Wildlife Service, Bureau of Indian Affairs, Bureau of Reclamation, and National Park Service have used this generalized methodology to assemble comprehensive digital data bases for resource management. Advanced information processing techniques have been applied to these data bases for making regional environmental surveys on millions of acres of public lands at costs ranging from $0.01 to $0.08 an acre.-Author

Photogrammetric Engineering and Remote Sensing↗
USGS2016

Environmental DNA mapping of Zebra Mussel populations

Environmental DNA (eDNA) has become a popular tool for detecting aquatic invasive species, but advancements have made it possible to potentially answer other questions like reproduction, movement, and abundance of the targeted organism. In this study we developed a Zebra Mussel (Dreissena polymorpha) eDNA protocol. We then determined if this assay could be used to help determine Zebra Mussel biomass in a lake with a well-established population of Zebra Mussels and a lake with an emerging population of mussels. Our eDNA assay detected DNA of Zebra Mussels but not DNA from more than 20 other species of fish and mussels, many commonly found in Minnesota waters. Our assay did not predict biomass. We did find that DNA from Zebra Mussels accumulated in softer substrates in both lakes, even though the mussels were predominately on the harder substrates. Therefore, we concluded that eDNA may be useful to detect the presence of Zebra Mussels in these lakes but our assay/approach could not predict biomass.

Report↗
USGS2021

Effect of temperature, nitrate concentration, pH and bicarbonate addition on biomass and lipid accumulation in the sporulating green alga PW95

The mixed effects of temperature (20 °C, 25 °C and 30 °C), nitrate concentration (0.5 mM and 2.0 mM), pH buffer, and bicarbonate addition (trigger) on biomass growth and lipid accumulation were investigated in the environmental alga PW95 during batch experiments in standardized growth medium. PW95 was isolated from coal-bed methane production water and classified as a Chlamydomonas -like species by morphological characterization and phylogenetic analysis (18S, ITS, rbc L). A factorial experimental design tested the mixed effects on PW95 before and after nitrate depletion to determine a low cost, high efficiency combination of treatments for biomass growth and lipid accumulation. Results showed buffer addition affected growth for most of the treatments and bicarbonate trigger had no statistically significant effect on growth and lipid accumulation. PW95 displayed the highest growth rate and chlorophyll content at 30 °C and 2.0 mM nitrate and there was an inverse relation between biomass accumulation and lipid accumulation at the extremes of nitrate concentration and temperature. The combination of higher temperature (30 °C) and lower nitrate level (0.5 mM) without the use of a buffer or bicarbonate addition resulted in maximal daily biomass accumulation (5.30 × 10 6 cells/mL), high biofuel potential before and after nitrate depletion (27% and 20%), higher biofuel productivity (16 and 15 mg/L/d, respectively), and desirable fatty acid profiles (saturated and unsaturated C16 and C18 chains). Our results indicate an important interaction between low nitrate levels, temperature, and elevated pH for trade-offs between biomass and lipid production in PW95. This work serves as a model to approach and advance the study of physiological responses of novel microalgae to diverse culture conditions that mimic environmental changes for outdoor biofuel production. The most promising conditions for growth and biofuel production were identified for PW95 and this approach can be implemented for other microalgal production systems.

Algal Research↗