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At least 253 records · Page 14Linked to original sources

Organizing environmental flow frameworks to meet hydropower mitigation needs

The global recognition of the importance of natural flow regimes to sustain the ecological integrity of river systems has led to increased societal pressure on the hydropower industry to change plant operations to improve downstream aquatic ecosystems. However, a complete reinstatement of natural flow regimes is often unrealistic when balancing water needs for ecosystems, energy production, and other human uses. Thus, stakeholders must identify a prioritized subset of flow prescriptions that meet ecological objectives in light of realistic constraints. Yet, isolating aspects of flow regimes to restore downstream of hydropower facilities is among the greatest challenges of environmental flow science due, in part, to the sheer volume of available environmental flow tools in conjunction with complex negotiation-based regulatory procedures. Herein, we propose an organizational framework that structures information and existing flow paradigms into a staged process that assists stakeholders in implementing environmental flows for hydropower facilities. The framework identifies areas where regulations fall short of the needed scientific process, and provide suggestions for stakeholders to ameliorate those situations through advanced preparation. We highlight the strengths of existing flow paradigms in their application to hydropower settings and suggest when and where tools are most applicable. Our suggested framework increases the effectiveness and efficiency of the e-flow implementation process by rapidly establishing a knowledge base and decreasing uncertainty so more time can be devoted to filling knowledge gaps. Lastly, the framework provides the structure for a coordinated research agenda to further the science of environmental flows related to hydropower environments.

Environmental Management

Assessment and monitoring of recreation impacts and resource conditions on mountain summits: Examples from the Northern Forest, USA

Mountain summits present a unique challenge to manage sustainably: they are ecologically important and, in many circumstances, under high demand for recreation and tourism activities. This article presents recent advances in the assessment of resource conditions and visitor disturbance in mountain summit environments, by drawing on examples from a multiyear, interdisciplinary study of summits in the northeastern United States. Primary impact issues as a consequence of visitor use, such as informal trail formation, vegetation disturbance, and soil loss, were addressed via the adaption of protocols from recreation ecology studies to summit environments. In addition, new methodologies were developed that provide measurement sensitivity to change previously unavailable through standard recreation monitoring protocols. Although currently limited in application to the northeastern US summit environments, the methods presented show promise for widespread application wherever summits are in demand for visitor activities.

Maine, Vermont, New Hampshire, New York, Massachus

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

A new groundwater energy transport model for the MODFLOW hydrologic simulator

Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.

Groundwater

USGS ecosystem research for the next decade: advancing discovery and application in parks and protected areas through collaboration

Ecosystems within parks and protected areas in the United States and throughout the world are being transformed at an unprecedented rate. Changes associated with natural hazards, greenhouse gas emissions, and increasing demands for water, food, land, energy and mineral resources are placing urgency on sound decision making that will help sustain our Nation’s economic and environmental well-being (Millennium Ecosystem Assessment, 2005). In recognition of the importance of science in making these decisions, the U.S. Geological Survey (USGS) in 2007 identified ecosystem science as one of six science directions included in a comprehensive decadal strategy (USGS 2007). The Ecosystems Mission Area was identified as essential for integrating activity within the USGS and as a key to enhanced integration with other Federal and private sector research and management organizations (Myers at al., 2007). This paper focuses on benefits to parks and protected areas from the USGS Ecosystems Mission Area plan that expanded the scope of the original 2007 science strategy, to identify the Bureau’s work in ecosystem science over the next decade (Williams et al., 2013). The plan describes a framework that encompasses both basic and applied science and allows the USGS to continue to contribute meaningfully to conservation and management issues related to the Nation’s parks and ecological resources. This framework relies on maintaining long-standing, collaborative relationships with partners in both conducting science and applying scientific results. Here we summarize the major components of the USGS Ecosystems Science Strategy, articulating the vision, goals and strategic approaches, then outlining some of the proposed actions that will ultimately prove useful to those managing parks and protected areas. We end with a discussion on the future of ecosystem science for the USGS and how it can be used to evaluate ecosystem change and the associated consequences to management of our Nation’s natural resources.

The George Wright Forum

Evolutionary history predicts high-impact invasions by herbivorous insects

A long‐standing goal of invasion biology is to identify factors driving highly variable impacts of non‐native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense‐free space hypothesis), predicting the impact of non‐native herbivorous insects has eluded scientists for over a century. Using a census of all 58 non‐native conifer‐specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects). We discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non‐native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non‐native herbivorous insects. Our novel, integrated model predicts whether a non‐native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R2 = 0.91) Synthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.

Ecology and Evolution

Hierarchical computing for hierarchical models in ecology

Bayesian hierarchical models allow ecologists to account for uncertainty and make inference at multiple scales. However, hierarchical models are often computationally intensive to fit, especially with large datasets, and researchers face trade-offs between capturing ecological complexity in statistical models and implementing these models. We present a recursive Bayesian computing (RB) method that can be used to fit Bayesian models efficiently in sequential MCMC stages to ease computation and streamline hierarchical inference. We also introduce transformation-assisted RB (TARB) to create unsupervised MCMC algorithms and improve interpretability of parameters. We demonstrate TARB by fitting a hierarchical animal movement model to obtain inference about individual- and population-level migratory characteristics. Our recursive procedure reduced computation time for fitting our hierarchical movement model by half compared to fitting the model with a single MCMC algorithm. We obtained the same inference fitting our model using TARB as we obtained fitting the model with a single algorithm. For complex ecological statistical models, like those for animal movement, multi-species systems, or large spatial and temporal scales, the computational demands of fitting models with conventional computing techniques can limit model specification, thus hindering scientific discovery. Transformation-assisted RB is one of the most accessible methods for reducing these limitations, enabling us to implement new statistical models and advance our understanding of complex ecological phenomena.

Article

Assessing contaminants of emerging concern in the Great Lakes Ecosystem: A decade of method development and practical application

Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+- year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State-of-the-science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer-reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management . Environ Toxicol Chem 2023;42:2506–2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Environmental Toxicology and Chemistry

Fish Bioenergetics 4.0: An R-based modeling application

Bioenergetics modeling is a widely used tool in fisheries management and research. Although popular, currently available software (i.e., Fish Bioenergetics 3.0) has not been updated in over 20 years and is incompatible with newer operating systems (i.e., 64‐bit). Moreover, since the release of Fish Bioenergetics 3.0 in 1997, the number of published bioenergetics models has increased appreciably from 56 to 105 models representing 73 species. In this article, we provide an overview of Fish Bioenergetics 4.0 (FB4), a newly developed modeling application that consists of a graphical user interface (Shiny by RStudio) combined with a modeling package used in the R computing environment. While including the same capabilities as previous versions, Fish Bioenergetics 4.0 allows for timely updates and bug fixes and can be continuously improved based on feedback from users. In addition, users can add new or modified parameter sets for additional species and formulate and incorporate modifications such as habitat‐dependent functions (e.g., dissolved oxygen, salinity) that are not part of the default package. We hope that advances in the new modeling platform will attract a broad range of users while facilitating continued application of bioenergetics modeling to a wide spectrum of questions in fish biology, ecology, and management.

Fisheries Magazine

Temporal variability of exchange between groundwater and surface water based on high-frequency direct measurements of seepage at the sediment-water interface

Seepage at the sediment-water interface in several lakes, a large river, and an estuary exhibits substantial temporal variability when measured with temporal resolution of 1 min or less. Already substantial seepage rates changed by 7% and 16% in response to relatively small rain events at two lakes in the northeastern USA, but did not change in response to two larger rain events at a lake in Minnesota. However, seepage at that same Minnesota lake changed by 10% each day in response to withdrawals from evapotranspiration. Seepage increased by more than an order of magnitude when a seiche occurred in the Great Salt Lake, Utah. Near the head of a fjord in Puget Sound, Washington, seepage in the intertidal zone varied greatly from −115 to +217 cm d−1 in response to advancing and retreating tides when the time-averaged seepage was upward at +43 cm d−1. At all locations, seepage variability increased by one to several orders of magnitude in response to wind and associated waves. Net seepage remained unchanged by wind unless wind also induced a lake seiche. These examples from sites distributed across a broad geographic region indicate that temporal variability in seepage in response to common hydrological events is much larger than previously realized. At most locations, seepage responded within minutes to changes in surface-water stage and within minutes to hours to groundwater recharge associated with rainfall. Likely implications of this dynamism include effects on water residence time, geochemical transformations, and ecological conditions at and near the sediment-water interface.

Water Resources Research

Climate-induced changes in lake ecosystem structure inferred from coupled neo- and paleoecological approaches

Over the 20th century, surface water temperatures have increased in many lake ecosystems around the world, but long-term trends in the vertical thermal structure of lakes remain unclear, despite the strong control that thermal stratification exerts on the biological response of lakes to climate change. Here we used both neo- and paleoecological approaches to develop a fossil-based inference model for lake mixing depths and thereby refine understanding of lake thermal structure change. We focused on three common planktonic diatom taxa, the distributions of which previous research suggests might be affected by mixing depth. Comparative lake surveys and growth rate experiments revealed that these species respond to lake thermal structure when nitrogen is sufficient, with species optima ranging from shallower to deeper mixing depths. The diatom-based mixing depth model was applied to sedimentary diatom profiles extending back to 1750 AD in two lakes with moderate nitrate concentrations but differing climate settings. Thermal reconstructions were consistent with expected changes, with shallower mixing depths inferred for an alpine lake where treeline has advanced, and deeper mixing depths inferred for a boreal lake where wind strength has increased. The inference model developed here provides a new tool to expand and refine understanding of climate-induced changes in lake ecosystems.

Ecology

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials

Vulnerability of riparian ecosystems to elevated CO 2 and climate change in arid and semiarid western North America

Riparian ecosystems, already greatly altered by water management, land development, and biological invasion, are being further altered by increasing atmospheric CO 2 concentrations ([CO 2 ]) and climate change, particularly in arid and semiarid (dryland) regions. In this literature review, we (1) summarize expected changes in [CO 2 ], climate, hydrology, and water management in dryland western North America, (2) consider likely effects of those changes on riparian ecosystems, and (3) identify critical knowledge gaps. Temperatures in the region are rising and droughts are becoming more frequent and intense. Warmer temperatures in turn are altering river hydrology: advancing the timing of spring snow melt floods, altering flood magnitudes, and reducing summer and base flows. Direct effects of increased [CO 2 ] and climate change on riparian ecosystems may be similar to effects in uplands, including increased heat and water stress, altered phenology and species geographic distributions, and disrupted trophic and symbiotic interactions. Indirect effects due to climate-driven changes in streamflow, however, may exacerbate the direct effects of warming and increase the relative importance of moisture and fluvial disturbance as drivers of riparian ecosystem response to global change. Together, climate change and climate-driven changes in streamflow are likely to reduce abundance of dominant, native, early-successional tree species, favor herbaceous species and both drought-tolerant and late-successional woody species (including many introduced species), reduce habitat quality for many riparian animals, and slow litter decomposition and nutrient cycling. Climate-driven changes in human water demand and associated water management may intensify these effects. On some regulated rivers, however, reservoir releases could be managed to protect riparian ecosystem. Immediate research priorities include determining riparian species' environmental requirements and monitoring riparian ecosystems to allow rapid detection and response to undesirable ecological change.

Global Change Biology

Overwintering behavior of juvenile sea turtles at a temperate foraging ground

Most freshwater and terrestrial turtle species that inhabit temperate environments hibernate to survive extreme cold periods. However, for sea turtles, the question of whether these species use hibernation as an overwintering strategy has not been resolved (Ultsch 2006 ). Felger et al. ( 1976 ) suggested that sea turtles bury themselves in mud on the seafloor and remain dormant throughout the winter, presumably not surfacing during that time. Additional researchers have described sea turtles in temperatures <15°C as lethargic, mud‐covered and buried in bottom sediment (Carr et al. 1980 , Mendonça 1983 , Ogren and McVea 1995 ). However, more recent studies suggest that sea turtles may not be as dormant in cold temperatures as previously suggested (Hochscheid et al. 2007 ). Resolving this question is difficult due to the unpredictability of winter weather patterns and the cost of advanced tracking tools required to assess these fine‐scale behaviors. However, in January 2018, unusually calm and clear marine conditions coupled with exceptionally cold weather provided us the opportunity to observe and film turtle behavior at a foraging ground in the northern Gulf of Mexico. These images, combined with previously gathered data from vessel‐based surveys and water temperature loggers, have enabled us to piece together one of the most comprehensive views of sea turtle overwintering behavior to date.

Ecology

Broadening the ecology of fear: Non-lethal effects arise from diverse responses to predation and parasitism

Research on the ‘ecology of fear’ posits that defensive prey responses to avoid predation can cause non-lethal effects across ecological scales. Parasites also elicit defensive responses in hosts with associated non-lethal effects, which raises the longstanding, yet unresolved question of how non-lethal effects of parasites compare with those of predators. We developed a framework for systematically answering this question for all types of predator–prey and host–parasite systems. Our framework reveals likely differences in non-lethal effects not only between predators and parasites, but also between different types of predators and parasites. Trait responses should be strongest towards predators, parasitoids and parasitic castrators, but more numerous and perhaps more frequent for parasites than for predators. In a case study of larval amphibians, whose trait responses to both predators and parasites have been relatively well studied, existing data indicate that individuals generally respond more strongly and proactively to short-term predation risks than to parasitism. Apart from studies using amphibians, there have been few direct comparisons of responses to predation and parasitism, and none have incorporated responses to micropredators, parasitoids or parasitic castrators, or examined their long-term consequences. Addressing these and other data gaps highlighted by our framework can advance the field towards understanding how non-lethal effects impact prey/host population dynamics and shape food webs that contain multiple predator and parasite species.

Proceedings of the Royal Society B

Methylmercury exposure in wildlife: A review of the ecological and physiological processes affecting contaminant concentrations and their interpretation

Exposure to methylmercury (MeHg) can result in detrimental health effects in wildlife. With advances in ecological indicators and analytical techniques for measurement of MeHg in a variety of tissues, numerous processes have been identified that can influence MeHg concentrations in wildlife. This review presents a synthesis of theoretical principals and applied information for measuring MeHg exposure and interpreting MeHg concentrations in wildlife. Mercury concentrations in wildlife are the net result of ecological processes influencing dietary exposure combined with physiological processes that regulate assimilation, transformation, and elimination. Therefore, consideration of both physiological and ecological processes should be integrated when formulating biomonitoring strategies. Ecological indicators, particularly stable isotopes of carbon, nitrogen, and sulfur, compound-specific stable isotopes, and fatty acids, can be effective tools to evaluate dietary MeHg exposure. Animal species differ in their physiological capacity for MeHg elimination, and animal tissues can be inert or physiologically active, act as sites of storage, transformation, or excretion of MeHg, and vary in the timing of MeHg exposure they represent. Biological influences such as age, sex, maternal transfer, and growth or fasting are also relevant for interpretation of tissue MeHg concentrations. Wildlife tissues that represent current or near-term bioaccumulation and in which MeHg is the predominant mercury species (such as blood and eggs) are most effective for biomonitoring ecosystems and understanding landscape drivers of MeHg exposure. Further research is suggested to critically evaluate the use of keratinized external tissues to measure MeHg bioaccumulation, particularly for less-well studied wildlife such as reptiles and terrestrial mammals. Suggested methods are provided to effectively use wildlife for quantifying patterns and drivers of MeHg bioaccumulation over time and space, as well as for assessing the potential risk and toxicological effects of MeHg on wildlife.

Science of the Total Environment

Advances and applications of occupancy models

Summary: The past decade has seen an explosion in the development and application of models aimed at estimating species occurrence and occupancy dynamics while accounting for possible non-detection or species misidentification. We discuss some recent occupancy estimation methods and the biological systems that motivated their development. Collectively, these models offer tremendous flexibility, but simultaneously place added demands on the investigator. Unlike many mark&ndash;recapture scenarios, investigators utilizing occupancy models have the ability, and responsibility, to define their sample units (i.e. sites), replicate sampling occasions, time period over which species occurrence is assumed to be static and even the criteria that constitute &lsquo;detection&rsquo; of a target species. Subsequent biological inference and interpretation of model parameters depend on these definitions and the ability to meet model assumptions. We demonstrate the relevance of these definitions by highlighting applications from a single biological system (an amphibian&ndash;pathogen system) and discuss situations where the use of occupancy models has been criticized. Finally, we use these applications to suggest future research and model development.

Methods in Ecology and Evolution

Understanding abundances and behaviors of shorebirds in coastal Louisiana

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.

BioRxiv