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Results for “Environmental Research: Ecology”

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At least 19 recordsLinked to original sources
USGS2010

QuickBird satellite imagery as a tool for restoration and rehabilitation of Lake Sevan, Armenia

Lake Sevan in Armenia is the largest freshwater lake in the Transcaucasus region and is one of the largest high-altitude freshwater lakes in Eurasia (Babayan et al., 2006 ). Armenia is a small (29,743 km 2 ), land- locked country that is comparatively poor in natural resources and nearly surrounded by borders that are blockaded by its neighbors (Babayan et al., 2006 ; Rhoades, 2008 and references therein; CIA, 2010 ). Despite these obstacles, ecological research and environmental restoration efforts continue. For the most part, ecological research in Lake Sevan during the twentieth century was restricted to Soviet-era journals, or was otherwise unavailable to western scientists.

Lake Sevan↗
USGS2011

Quantifying seascape structure: Extending terrestrial spatial pattern metrics to the marine realm

Spatial pattern metrics have routinely been applied to characterize and quantify structural features of terrestrial landscapes and have demonstrated great utility in landscape ecology and conservation planning. The important role of spatial structure in ecology and management is now commonly recognized, and recent advances in marine remote sensing technology have facilitated the application of spatial pattern metrics to the marine environment. However, it is not yet clear whether concepts, metrics, and statistical techniques developed for terrestrial ecosystems are relevant for marine species and seascapes. To address this gap in our knowledge, we reviewed, synthesized, and evaluated the utility and application of spatial pattern metrics in the marine science literature over the past 30 yr (1980 to 2010). In total, 23 studies characterized seascape structure, of which 17 quantified spatial patterns using a 2-dimensional patch-mosaic model and 5 used a continuously varying 3-dimensional surface model. Most seascape studies followed terrestrial-based studies in their search for ecological patterns and applied or modified existing metrics. Only 1 truly unique metric was found (hydrodynamic aperture applied to Pacific atolls). While there are still relatively few studies using spatial pattern metrics in the marine environment, they have suffered from similar misuse as reported for terrestrial studies, such as the lack of a priori considerations or the problem of collinearity between metrics. Spatial pattern metrics offer great potential for ecological research and environmental management in marine systems, and future studies should focus on (1) the dynamic boundary between the land and sea; (2) quantifying 3-dimensional spatial patterns; and (3) assessing and monitoring seascape change.

Marine Ecology Progress Series↗
USGS2025

Mapping ecological states in the upper Colorado River basin: Implications for fire management

Spatially explicit information on ecosystem dynamics that offers a mechanistic understanding of ecological processes can benefit environmental management. Broad-scale maps based on state-and-transition models provide valuable insight into transitions among ecological states resulting from specific drivers within areas sharing similar climatic and edaphic characteristics ecological sites (ES). We aimed to quantify ecological dynamics of two ES groups in the Upper Colorado River Basin from 1986 to 2022 through annual maps of ecological states and assess potential drivers of observed state change. This region comprises important sagebrush shrublands and pinyon-juniper woodlands affected by non-native annual grass invasion, wildfires, and drought-induced tree mortality. Using field-based and remote sensing data, we modeled vegetation states using random forest models and mapped the states annually from 1986 to 2022. To demonstrate the utility of the state maps for monitoring and management, we used this time series of maps to investigate the influences of fire and drought on state occurrence. Our findings revealed a statistically significant increase in states invaded by non-native annual species (Invaded state), which replaced Grassland and Shrubland states, while Shrubland states decreased significantly, transitioning to invaded and Woodland states. Invaded states had the highest likelihood of burning, followed by Woodlands. Drought was associated with increased area of Grassland and Bare states, but with decreased area of invaded and Shrubland states. These results indicate an accelerating fire cycle is potentially leading to ongoing regional environmental degradation. Despite increasing drought conditions during the study period, the invaded states continued to increase in area, indicating additional underlying mechanisms. Our reproducible, broad-scale, ecologically-driven state mapping process enhances understanding of how drought, fire, and invasion by non-native plants can transform semiarid landscapes of the western USA.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2025

Sentinel imagery detects the presence of live trees following large wildfires in California

Identifying live tree presence following wildfire is important for burn damage assessments and decision making, as these trees serve as seed sources for recovery. Satellite-based remote sensing offers an efficient means to assess burn severity with products representing vegetation greenness and char/ash presence and their change from pre- to post-fire imagery. While effective at assessing burn severity (e.g. ecosystem change), there remain limitations in identifying fire refugia (surviving trees), due to the difficulty of teasing apart different green vegetation types (e.g. trees, shrubs, grasses). In this paper, we use 10 m Sentinel-2 satellite data to predict live tree presence across three sites impacted by the 2021 California fire season. We used vegetation indices (VIs) from post-fire imagery (normalized difference vegetation index [NDVI], normalized burn ratio [NBR], normalized difference water index [NDWI], visible atmospherically resistant index [VARI], and burn area index [BAI]), differential VIs from pre- and post-fire imagery (dNDVI, dNBR, RdNBR, dNDWI, dVARI), and direct reflectance bands (all bands model; visible, near-infrared, and shortwave infrared; B1–B12) to predict live tree presence via random forest modeling. To calibrate and validate the random forest models, we photointerpreted ∼2300 pixels per fire region using 2022 National Agriculture Imagery Program imagery. We performed additional field-based validation using tree presence/absence data two years post-fire ( n = 296 observations across two sites). At the site level, the all bands model outperformed the vegetation index-based models (80%–85% vs 65%–79% accuracy). Errors were mainly false positives attributed to pixels with green understory vegetation but no live trees. In cross-site inference, which involved pooling two sites for model calibration to test on the third site, the all bands model retained good performance (76%–81% accuracy). Evaluation against field survey data demonstrated a larger range of performance (50%–87% accuracy) that highlights limitations based on tree isolation and crown percent greenness. Relative to differential-based VIs, our results highlight potential advantages of using post-fire Sentinel-2 imagery and random forest modeling for identifying live tree presence and scaling to full fire extents.

California↗
USGS2025

Climate change and infrastructure development drive ice-rich permafrost thaw in Point Lay (Kali), Alaska

Permafrost thaw and thermokarst development pose urgent challenges to Arctic communities, threatening infrastructure and essential services. This study examines the reciprocal impacts of permafrost degradation and infrastructure in Point Lay (Kali), Alaska, drawing on field data from ∼60 boreholes, measured and modeled ground temperature records, remote sensing analysis, and community interviews. Field campaigns from 2022–2024 reveal widespread thermokarst development and ground subsidence driven by the thaw of ice-rich permafrost. Borehole analysis confirms excess-ice contents averaging ∼40%, with syngenetic ice wedges extending over 12 m deep. Measured and modeled ground temperature data indicate a warming trend, with increasing mean annual ground temperatures and active layer thickness (ALT). Since 1949, modeled ALTs have generally deepened, with a marked shift toward consistently thicker ALTs in the 21st century. Remote sensing shows ice wedge thermokarst expanded from <5% in 1949 to >60% in developed areas by 2019, with thaw rates increasing tenfold between 1974 and 2019. In contrast, adjacent, undisturbed tundra exhibited more consistent thermokarst expansion (∼0.2% yr −1 ), underscoring the amplifying role of infrastructure, surface disturbance, and climate change. Community interviews reveal the lived consequences of permafrost degradation, including structural damage to homes, failing utilities, and growing dependence on alternative water and wastewater strategies. Engineering recommendations include deeper pile foundations, targeted ice wedge stabilization, aboveground utilities, enhanced snow management strategies, and improved drainage to mitigate ongoing infrastructure issues. As climate change accelerates permafrost thaw across the Arctic, this study highlights the need for integrated, community-driven adaptation strategies that blend geocryological research, engineering solutions, and local and Indigenous knowledge.

Alaska↗
USGS2025

Land use strategies for achieving Chile’s nationally determined contributions

Chile’s Nationally determined contributions (NDCs) commit to carbon neutrality by 2050, with measures to reduce emissions and natural hazards while enhancing water security. The Forestry and Other Land Uses (FOLU) sectors are critical to Chile’s goal of carbon neutrality, as they serve as a net carbon sink. In this paper, we conduct policy scenario analysis focusing on FOLU strategies for meeting the NDCs. We implement the Integrated Economic-Environmental Modeling framework linked with spatial Land Use-Land Cover and Ecosystem Services (ES) Modeling (IEEM + ESM) to assess impacts on economic, environmental and social indicators. Our results show that the implementation of Chile’s FOLU strategies would reduce emissions, enhance wealth and economic growth and increase future flows of ES. Carbon dioxide emissions would be reduced (by 151 million tons by 2050) to levels that would be considerably better than current Government expectations. Gross Domestic Product and wealth would be bolstered by US$16 065 million and US$22 731 million, respectively. Water-related ES would improve including the quality of potable water, while more water would be maintained within forested ecosystems, thereby reducing the future risk of natural hazards such as landslides and floods. The FOLU strategies would create 72 800 new jobs and reduce poverty by 15 586 individuals. Analysis with IEEM + ESM demonstrates that reducing wildfire-driven forest loss would have outsized impacts and be the most effective and expedient way to contribute to meeting NDC targets. The IEEM + ESM approach is an example of an analytical framework that is meeting growing demand from Government institutions and multilateral development banks for understanding the effects and transition pathways of NDC strategies on economic, social and environmental outcomes.

Environmental Research: Ecology↗
USGS2026

Initial condition uncertainty exerts a large and persistent influence on model simulations of ecosystem carbon dynamics in California

Uncertainties in terrestrial ecosystem models limit their predictive power. Efforts to reduce projection error have rarely focused on constraining uncertainty in the initial state of the ecosystem, however, despite evidence that matching model initial conditions to real-world observations reduces overall model bias. Here we use an integrated land change and carbon gain-loss model to evaluate the influence of initial condition uncertainty on simulations of California wildland ecosystems during the years 1985–2020. We generated 36 initial conditions scenarios by varying the source data used to initialize state variables and then ran simulations based on each of these scenarios under a constant set of historical conditions. We found that discrepancies in initial forest extent and initial forest age among scenarios generated wide uncertainty ranges in model estimates of terrestrial ecosystem carbon stocks and flux rates at the outset of the simulation period, but differences in initial forest composition had no impact. Over time, forest age became more homogeneous across model scenarios leading to exponential rates of decline in the uncertainty ranges of live biomass and dead wood carbon but little to no impact on uncertainties in litter and soil organic carbon. Uncertainties in individual carbon flux rates were consistent with uncertainties in their source pools. In contrast, model estimates of ecosystem carbon balance demonstrated a shift in system behavior not apparent in trends for individual carbon stocks and fluxes. Specifically, estimates of ecosystem carbon balance converged across scenarios for the first 20 years of the simulation period but then began to diverge at an accelerating rate, possibly due to weakened resilience to the increased frequency and severity of climate-driven disturbances. Our results demonstrate that uncertainty in the initial state of the system can have large and persistent impacts on the predictability of ecosystem carbon dynamics, and that ongoing shifts in external forcing by climate and climate-driven disturbances can exacerbate these impacts.

California↗
USGS2026

How Indigenous socio-cultural systems resist, accept, or direct ecological transformation: A research agenda

Anthropogenic ecological transformations are challenging conventional environmental management paradigms, as maintaining historical ecological structures and functions becomes increasingly untenable. The resist–accept–direct (RAD) framework offers a strategic tool to navigate these shifts. However, as a product of the dominant socio-cultural system, the RAD framework risks perpetuating the same patterns of thinking that have contributed to unsustainable social-ecological dynamics. Indigenous socio-cultural systems, considered here through the lens of long-term coevolution with their environments, offer valuable empirical models for adaptive responses to environmental change. Such Indigenous socio-cultural responses, grounded in narratives, governance institutions, value systems, and other cultural elements collectively referred to as Indigenous Knowledge (IK), hold relevance for addressing today’s intertwined environmental and social challenges. We provide a targeted review of existing literature at the intersection of IK and the RAD framework, along with a broader conceptual overview of relevant insights across related fields. These reveal contrasting assumptions about Indigenous responses to environmental change, such as consistently resisting to preserve cultural fidelity or uniformly accepting, reflecting deeper cultural, temporal, and ecological complexity. We propose a structured research agenda to investigate Indigenous socio-cultural responses to environmental change through empirical research, theoretical synthesis, hypothesis development, and practical application. This agenda is grounded in comprehensive collaboration, emphasizing shared power and integrating both emic and etic perspectives throughout all stages of research and implementation. By bridging the adaptive dynamics of coevolved social-ecological systems and mainstream management strategies, an IK–RAD framework could enhance the efficacy of responses to global environmental change.

Human Ecology↗
USGS2014

Linking environmental variability to population and community dynamics

Linking population and community responses to environmental variability lies at the heart of ecology, yet methodological approaches vary and existence of broad patterns spanning taxonomic groups remains unclear. We review the characteristics of environmental and biological variability. Classic approaches to link environmental variability to population and community variability are discussed as are the importance of biotic factors such as life history and community interactions. In addition to classic approaches, newer techniques such as information theory and artificial neural networks are reviewed. The establishment and expansion of observing networks will provide new long-term ecological time-series data, and with it, opportunities to incorporate environmental variability into research. This review can help guide future research in the field of ecological and environmental variability.

Book chapter↗
USGS2022

Biosafety practices when working with bats: A guide to field research considerations

Introduction: Field work with bats is an important contribution to many areas of research in environmental biology and ecology, as well as microbiology. Work with bats poses hazards such as bites and scratches, and the potential for exposure to infectious pathogens such as rabies virus. It also exposes researchers to many other potential hazards inherent to field work, such as environmental conditions, delayed emergency responses, or challenging work conditions. Methods: This article discusses the considerations for a thorough risk assessment process around field work with bats, pre- and post-occupational health considerations, and delves into specific considerations for areas related to biosafety concerns—training, personal protective equipment, safety consideration in field methods, decontamination, and waste. It also touches on related legal and ethical issues that sit outside the realm of biosafety, but which must be addressed during the planning process. Discussion: Although the focal point of this article is bat field work located in northern and central America, the principles and practices discussed here are applicable to bat work elsewhere, as well as to field work with other animal species, and should promote careful considerations of how to safely conduct field work to protect both researchers and animals.

Applied Biosafety↗
USGS2022

Bayesian applications in environmental and ecological studies with R and Stan

Modern ecological and environmental sciences are dominated by observational data. As a result, traditional statistical training often leaves scientists ill-prepared for the data analysis tasks they encounter in their work. Bayesian methods provide a more robust and flexible tool for data analysis, as they enable information from different sources to be brought into the modelling process. Bayesian Applications in Evnironmental and Ecological Studies with R and Stan provides a Bayesian framework for model formulation, parameter estimation, and model evaluation in the context of analyzing environmental and ecological data. Features: An accessible overview of Bayesian methods in environmental and ecological studies Emphasizes the hypothetical deductive process, particularly model formulation Necessary background material on Bayesian inference and Monte Carlo simulation Detailed case studies, covering water quality monitoring and assessment, ecosystem response to urbanization, fisheries ecology, and more Advanced chapter on Bayesian applications, including Bayesian networks and a change point model Complete code for all examples, along with the data used in the book, are available via GitHub The book is primarily aimed at graduate students and researchers in the environmental and ecological sciences, as well as environmental management professionals. This is a group of people representing diverse subject matter fields, who could benefit from the potential power and flexibility of Bayesian methods.

Book↗
USGS2009

Hepatic pathologies in the brackish water catfish (Chrysichthys nigrodigitatus) from contaminated locations of the Lagos lagoon complex

Several toxicological studies into the effects of aquatic pollutants on the liver of teleost fish exist in literature. The focus on the liver in these studies is predicated on its central nature in the scheme of biotransformation and excretion of xenobiotics following exposure in polluted water bodies. As a consequence of the latter primary role of the liver in these processes it is regarded as a predilective site for the sub lethal effects of xenobiotics on the organism usually detectable at histological level. Hepatic histopathology recorded in livers from feral populations of the brackish water catfish Chrysichthys nigrodigitatus from locations on the Lagos lagoon complex with significant anthropogenic inputs from denizen populations and industries are presented. Liver sections from sixty specimens from two locations on the Lagos lagoon complex (Badagry lagoon: 6°24'N, 2°56'E; and Lagos lagoon: 6°29'N, 3°22'E) were analysed. Observed pathologies included hydropic degeneration (58%), portal / sinusoidal congestion (33%), hepatic necrosis (26%), hemosiderosis (12%) and foci of cellular alterations (FCA's). No obvious oncologic features were observed; the presence of the hydropic Vacuolation lesion was taken as prelude to the development of neoplasms and discussed as such.

Badagry Lagoon, Lagos Lagoon↗
USGS2023

Improving ecological data science with workflow management software

Pressing environmental research questions demand the integration of increasingly diverse and large-scale ecological datasets as well as complex analytical methods, which require specialized tools and resources. Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor- and time-intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies. Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers. Although WMS requires familiarity with function-oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.

Methods in Ecology and Evolution↗
USGS2014

Ground level environmental protein concentrations in various ecuadorian environments: potential uses of aerosolized protein for ecological research

Large quantities of free protein in the environment and other bioaerosols are ubiquitous throughout terrestrial ground level environments and may be integrative indicators of ecosystem status. Samples of ground level bioaerosols were collected from various ecosystems throughout Ecuador, including pristine humid tropical forest (pristine), highly altered secondary humid tropical forest (highly altered), secondary transitional very humid forest (regrowth transitional), and suburban dry montane deforested (suburban deforested). The results explored the sensitivity of localized aerosol protein concentrations to spatial and temporal variations within ecosystems, and their value for assessing environmental change. Ecosystem specific variations in environmental protein concentrations were observed: pristine 0.32 ± 0.09 μg/m3, highly altered 0.07 ± 0.05 μg/m 3 , regrowth transitional 0.17 ± 0.06 μg/m 3 , and suburban deforested 0.09 ± 0.04 μg/m 3 . Additionally, comparisons of intra-environmental differences in seasonal/daily weather (dry season 0.08 ± 0.03 μg/m 3 and wet season 0.10 ± 0.04 μg/m 3 ), environmental fragmentation (buffered 0.19 ± 0.06 μg/m 3 and edge 0.15 ± 0.06 μg/m 3 ), and sampling height (ground level 0.32 ± 0.09 μg/m 3 and 10 m 0.24 ± 0.04 μg/m 3 ) demonstrated the sensitivity of protein concentrations to environmental conditions. Local protein concentrations in altered environments correlated well with satellite-based spectral indices describing vegetation productivity: normalized difference vegetation index (NDVI) (r 2 = 0.801), net primary production (NPP) (r 2 = 0.827), leaf area index (LAI) (r 2 = 0.410). Moreover, protein concentrations distinguished the pristine site, which was not differentiated in spectral indices, potentially due to spectral saturation typical of highly vegetated environments. Bioaerosol concentrations represent an inexpensive method to increase understanding of environmental changes, especially in densely vegetated ecosystems with high canopies or in areas needing high spatial and temporal resolution. Further research to expand understanding of the applicability of bioaerosol concentrations for environmental monitoring is supported by this pilot study.

Ecological Indicators↗
USGS2015

Progress and challenges in coupled hydrodynamic-ecological estuarine modeling

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review, we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a “theory of everything” for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Estuaries and Coasts↗
USGS2005

Eco-informatics for decision makers advancing a research agenda

Resource managers often face significant information technology (IT) problems when integrating ecological or environmental information to make decisions. At a workshop sponsored by the NSF and USGS in December 2004, university researchers, natural resource managers, and information managers met to articulate IT problems facing ecology and environmental decision makers. Decision making IT problems were identified in five areas: 1) policy, 2) data presentation, 3) data gaps, 4) tools, and 5) indicators. To alleviate those problems, workshop participants recommended specific informatics research in modeling and simulation, data quality, information integration and ontologies, and social and human aspects. This paper reports the workshop findings, and briefly compares these with research that traditionally falls under the emerging eco-informatics rubric. ?? Springer-Verlag Berlin Heidelberg 2005.

Conference Paper↗
USGS2017

Used-habitat calibration plots: A new procedure for validating species distribution, resource selection, and step-selection models

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations.

Ecography↗
USGS2022

Great Lakes lake trout thiamine monitoring program annual report

The U.S. Geological Survey’s Great Lakes Science Center (GLSC), Eastern Ecological Science Center, and Columbia Environmental Research Center (CERC), and the State University of New York (SUNY) Brockport have conducted in collaboration with partner agencies a cooperative program to monitor thiamine concentrations in lake trout eggs since the late 1990s. In 2021, egg thiamine concentrations were highly variable at each sampling site. No eggs samples with thiamine concentrations less than the 4 nmol/g threshold recommended for successful lake trout reproduction were collected in Lakes Superior, Huron, Erie, and Champlain. In contrast, every site in Lakes Michigan and Ontario and Cayuga Lake had some lake trout eggs below 4 nmol/g. Time series of mean lake trout egg thiamine concentrations showed high temporal and spatial variability within the Great Lakes region.

Great Lakes↗