SEARCH · Search USGS

Results for “Ecology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

USGS2008

Understanding the ecology of disease in Great Lakes fish populations

Disease may be an important factor affecting wild fish population dynamics in the Great Lakes, but a lack of information on the ecology of fish disease currently precludes the prediction of risks to fish populations. Here we propose a conceptual framework for conducting ecologically-oriented fish health research that addresses the inter-relationships among fish health, fish populations, and ecosystem dysfunction in the Great Lakes. The conceptual framework describes potential ways in which disease processes and the population-level impacts of disease may relate to ecosystem function, and suggests that functional ecosystems are more likely to be resilient with respect to disease events than dysfunctional ecosystems. We suggest that ecosystem- or population-level research on the ecology of fish disease is necessary to understand the relationships between ecosystem function and fish health, and to improve prediction of population-level effects of diseases on wild fish populations in the Great Lakes. Examples of how the framework can be used to generate research questions are provided using three disease models of current interest in the Great Lakes: thiamine deficiency complex, botulism, and bacterial kidney disease.

Great Lakes↗

USGS2020

A synthesis of the biology and ecology of sculpin species in the Laurentian Great Lakes and implications for the adaptive capacity of the benthic ecosystem

The Laurentian Great Lakes have experienced recent ecosystem changes that could lead to reductions in adaptive capacity and ultimately a loss of biodiversity and production throughout the food web. Observed changes in Great Lakes benthic communities include declines of native species and widespread success of invasive species like dreissenid mussels in all but Lake Superior. Understanding the ecology of native benthic deepwater preyfish and the reasons for their declines is important for predicting future losses in adaptive capacity and diversity, as well as managing the Great Lakes ecosystem to avoid such losses. Native sculpin species ( Cottus bairdii , C. cognatus , C. ricei , Myoxocephalus thompsonii ) historically were among the most abundant of the Great Lakes native deepwater benthic preyfish community and are an important link between offshore benthic and pelagic food webs. With one exception, these species have declined in abundance throughout the Great Lakes in recent years, but relatively little is known about their biology and ecology. This review synthesizes the available knowledge for the Great Lakes sculpin species and provides suggestions for future research efforts, which include understanding reproductive ecology and spawning behavior, connectivity and dispersal of populations, early life history, and influences of interactions with native and non-native species.

Great Lakes↗

USGS2020

Small-scale water deficits after wildfires create long-lasting ecological impacts

Ecological droughts are deficits in soil–water availability that induce threshold-like ecosystem responses, such as causing altered or degraded plant-community conditions, which can be exceedingly difficult to reverse. However, 'ecological drought' can be difficult to define, let alone to quantify, especially at spatial and temporal scales relevant to land managers. This is despite a growing need to integrate drought-related factors into management decisions as climate changes result in precipitation instability in many semi-arid ecosystems. We asked whether success in restoration seedings of the foundational species big sagebrush ( Artemisia tridentata ) was related to estimated water deficit, using the SoilWat2 model and data from >600 plots located in previously burned areas in the western United States. Water deficit was characterized by: (1) the standardized precipitation-evapotranspiration index (SPEI), a coarse-scale drought index, and (2) the number of days with wet and warm conditions in the near-surface soil, where seeds and seedlings germinate and emerge (i.e. days with 0–5 cm deep soil water potential >−2.5 MPa and temperature above 0 °C). SPEI, a widely used drought index, was not predictive of whether sagebrush had reestablished. In contrast, wet-warm days elicited a critical drought threshold response, with successfully reestablished sites having experienced seven more wet-warm days than unsuccessful sites during the first March following summer wildfire and restoration. Thus, seemingly small-scale and short-term changes in water availability and temperature can contribute to major ecosystem shifts, as many of these sites remained shrubless two decades later. These findings help clarify the definition of ecological drought for a foundational species and its imperiled semi-arid ecosystem. Drought is well known to affect the occurrence of wildfires, but drought in the year(s) after fire can determine whether fire causes long-lasting, negative impacts on ecosystems.

Oregon, Idaho, Nevada, Utah↗

USGS2021

Responding to ecological transformation: Mental models, external constraints, and manager decision-making

Ecological transformation creates many challenges for public natural resource management and requires managers to grapple with new relationships to change and new ways to manage it. In the context of unfamiliar trajectories of ecological change, a manager can resist, accept, or direct change, choices that make up the resist-accept-direct (RAD) framework. In this article, we provide a conceptual framework for how to think about this new decision space that managers must navigate. We identify internal factors (mental models) and external factors (social feasibility, institutional context, and scientific uncertainty) that shape management decisions. We then apply this conceptual framework to the RAD strategies (resist, accept, direct) to illuminate how internal and external factors shape those decisions. Finally, we conclude with a discussion of how this conceptual framework shapes our understanding of management decisions, especially how these decisions are not just ecological but also social, and the implications for research and management.

BioScience↗

USGS2021

A science agenda to inform natural resource management decisions in an era of ecological transformation

Earth is experiencing widespread ecological transformation in terrestrial, freshwater, and marine ecosystems that is attributable to directional environmental changes, especially intensifying climate change. To better steward ecosystems facing unprecedented and lasting change, a new management paradigm is forming, supported by a decision-oriented framework that presents three distinct management choices: resist, accept, or direct the ecological trajectory. To make these choices strategically, managers seek to understand the nature of the transformation that could occur if change is accepted while identifying opportunities to intervene to resist or direct change. In this article, we seek to inspire a research agenda for transformation science that is focused on ecological and social science and based on five central questions that align with the resist–accept–direct (RAD) framework. Development of transformation science is needed to apply the RAD framework and support natural resource management and conservation on our rapidly changing planet.

BioScience↗

USGS2023

Evolutionary fire ecology: An historical account and future directions

The idea that fire acts as an evolutionary force contributing to shaping species traits started a century ago, but had not been widely recognized until very recently. Among the first to realize this force were E dward B . Poulton, R. D ale Guthrie, and E dwin V . Komarek in animals and W illis L . Jepson, W alter W . Hough, T om M . Harris, P hilip V . Wells, and R obert W . Mutch in plants. They were all ahead of their time in their evolutionary thinking. Since then, evolutionary fire ecology has percolated very slowly into the mainstream ecology and evolutionary biology; in fact, this topic is still seldom mentioned in textbooks of ecology or evolution. Currently, there is plenty of evidence suggesting that we cannot understand the biodiversity of our planet without considering the key evolutionary role of fire. But there is still research to be done in order to fully understand fire's contribution to species evolution and to predicting species responses to rapid global changes.

BioScience↗

USGS2014

Ecological change on California's Channel Islands from the Pleistocene to the Anthropocene

Historical ecology is becoming an important focus in conservation biology and offers a promising tool to help guide ecosystem management. Here, we integrate data from multiple disciplines to illuminate the past, present, and future of biodiversity on California's Channel Islands, an archipelago that has undergone a wide range of land-use and ecological changes. Our analysis spans approximately 20,000 years, from before human occupation and through Native American hunter–gatherers, commercial ranchers and fishers, the US military, and other land managers. We demonstrate how long-term, interdisciplinary research provides insight into conservation decisions, such as setting ecosystem restoration goals, preserving rare and endemic taxa, and reducing the impacts of climate change on natural and cultural resources. We illustrate the importance of historical perspectives for understanding modern patterns and ecological change and present an approach that can be applied generally in conservation management planning.

California↗

USGS2019

An integrated framework for ecological drought across riverscapes of North America

Climate change is increasing the severity and extent of extreme droughts events, posing a critical threat to freshwater ecosystems, particularly with increasing human demands for diminishing water supplies. Despite the importance of drought as a significant driver of ecological and evolutionary dynamics, current understanding of drought consequences for freshwater biodiversity is very limited. We describe key barriers that hinder integrative drought research and monitoring across riverscapes. The primary constraint limiting understanding of ecological drought is an existing monitoring framework focused on human water consumption and flood risk in mainstem rivers. This approach is misaligned with escalating needs for research and data collection that illuminate exposure, sensitivity, and adaptive capacity (i.e., vulnerability) of biota to drought across entire riverscapes. We present a hierarchical framework for integrated ecological drought monitoring and research that addresses drought vulnerability across riverscapes, and describe how this approach can directly inform natural-resource management.

BioScience↗

USGS2025

The role of ecology in allopatric speciation of darters in the Central Highlands, USA

Allopatric speciation is the predominant mode of speciation in riverine fishes. However, the relative importance of genetic drift versus natural selection in the allopatric speciation of these fishes remain uncertain. Here, we present a case study that demonstrates the role of ecology in the diversification of a group of imperiled freshwater fishes from the central United States. We integrate a phylogenomic dataset with analyses of streamwise distance, environmental variables, meristic and morphological traits, and diet to investigate the ecological context and outcomes of allopatric speciation within a species complex comprising the Slenderhead Darter Percina phoxocephala (Nelson), Ouachita Darter Percina brucethompsoni (Robison, Cashner, and Near), and Longnose Darter Percina nasuta (Bailey). We find that two of the species traditionally delimited based on disparity in snout length, P. phoxocephala and P. nasuta , are polyphyletic, revealing three instances of the parallel evolution of snout length disparity. We propose a revised taxonomy including the delimitation of six new species based on disparity in phenotypic traits and phylogenomic analyses. We find that morphological differences are not correlated with genetic divergence but are congruent with variations in diet and environmental niches, suggesting a role for ecological factors in allopatric speciation of riverine fishes.

Arkansas, Kansas, Missouri, Oklahoma↗

USGS2024

Ecological and social drivers of Mexican wolf home range size across spatiotemporal scales

Elucidating factors influencing home range size is fundamental to the ecology and management of wildlife species, particularly those of conservation concern, because they can provide insight into how species utilize and interact with their environment. Variation in home range size can be related to intraspecific competition and social organization, energetic requirements in relation to habitat productivity, allometric relationships, and population density. The Mexican Gray Wolf ( Canis lupus baileyi ) is an endangered subspecies of the Gray Wolf whose home range size has not yet been studied. We examined ecological and social drivers of home range size of 22 Mexican Wolf packs between 2017 and 2021 across 4 biological time frames: annual; denning; post-denning; and non-denning. We used a 95% Brownian Bridge Movement Model home range estimator and generalized linear mixed-effect models to assess these relationships. Home range size was inversely correlated with estimated ungulate biomass, which was the most influential driver of home range size at annual and post-denning time frames. Larger packs utilized larger ranges during denning and post-denning time frames, while packs with larger litters had smaller ranges during the denning season. Snow depth was inversely related to home range size during the non-denning season. Our results indicate that both ecological and social factors are important and seasonally dependent in driving Mexican Wolf home range size. Use of a multiscale approach in future home range studies could discern relevant factors for species during time frames of interest.

Journal of Mammology↗

USGS2026

Birds, breakpoints, and baselines: How citizen science data can reveal ecological boundaries in Kenya’s Upper Tana watershed

Tropical watersheds are increasingly threatened by climate change, land-use conversion, and resource extraction, yet conventional biodiversity monitoring in these systems is often spatially and temporally limited. Citizen science offers a complementary approach, enabling biodiversity data collection over large areas that can supplement professional scientific surveys. We analyzed 10 years (2012–2022) of Upper Tana Watershed bird data from the Kenya Bird Map project, covering 114 pentads (9 × 9 km) within a 17,000 km 2 watershed to assess patterns of bird community composition and distribution across this watershed and to also evaluate the effects of environmental variables, seasonality, and sampling effort to help inform improvements in future citizen science projects. Citizen (or community) scientists recorded 575 species (>50% of Kenya’s total avifauna) in 74 families. Asymptotic species accumulation indicates that most probable species present in the watershed were detected. Threshold indicator taxa analysis revealed distinct ecological boundaries along elevation (∼1,500 m), precipitation (∼1,100 mm), and mean temperature (∼19°C) gradients, corresponding to a turnover from xeric savanna to mesic montane forest assemblages. Notably, bird communities showed little seasonal differentiation between wet and dry periods, consistent with dominance by resident year-round species. Data limitations including uneven survey distribution and frequency, absence of abundance metrics, and coarse representation of local environmental conditions that likely reduced our ability to detect fine-scale species–habitat relationships. Addressing these gaps through spatially balanced sampling at greater resolution, greater survey frequency in underrepresented areas, and improved capture of habitat metrics could strengthen the use of citizen-science bird data for watershed bioassessment. Our findings demonstrate that structured citizen-science initiatives can identify ecological boundaries and inform adaptive management of tropical socio-ecological systems under rapid environmental change.

Upper Tana watershed↗

USGS2020

Spatial ecology of closely-related taxa: The case of the little shearwater complex in the North Atlantic Ocean

Seabirds inhabiting vast water masses provide numerous examples where opposing phenomena, such as natal and breeding philopatry vs. vagility have dug cryptic taxonomic boundaries among closely related taxa. The taxonomy of little shearwaters of the North Atlantic Ocean (Little–Audubon’s shearwater complex, Puffinus assimilis – lherminieri ) still remains unclear, and complementary information on non-breeding distributions and at-sea behaviour becomes essential to unravel divergent local adaptations to specific habitats. Using miniaturized light-level geolocators from seven study areas in the North Atlantic, we evaluate the spatial and habitat segregation, estimate the timing of their key life-cycle events and describe the at-sea behaviour of three taxa of these little shearwaters year-round to distinguish ecological patterns and specializations that could ultimately unravel potential lineage divergences. We also assess morphometric data from birds that were breeding at each study area to further discuss potential adaptations to specific habitats. Our results show that, while birds from different taxa segregated in space and habitats, they share ecological plasticity, similar annual phenology and diel foraging behaviour. These ecological inconsistencies, while defining the evolutionary stressors faced by these taxa, do not suggest the existence of three Evolutionary Significant Units. However, they confirm the recent evolutionary divergence among the three little shearwaters of the North Atlantic.

Zoological Journal of the Linnean Society↗

USGS2024

Ecology shapes the genomic and biosynthetic diversification of Streptomyces bacteria from insectivorous bats

Streptomyces are prolific producers of secondary metabolites from which many clinically useful compounds have been derived. They inhabit diverse habitats but have rarely been reported in vertebrates. Here, we aim to determine to what extent the ecological source (bat host species and cave sites) influence the genomic and biosynthetic diversity of Streptomyces bacteria. We analysed draft genomes of 132 Streptomyces isolates sampled from 11 species of insectivorous bats from six cave sites in Arizona and New Mexico, USA. We delineated 55 species based on the genome-wide average nucleotide identity and core genome phylogenetic tree. Streptomyces isolates that colonize the same bat species or inhabit the same site exhibit greater overall genomic similarity than they do with Streptomyces from other bat species or sites. However, when considering biosynthetic gene clusters (BGCs) alone, BGC distribution is not structured by the ecological or geographical source of the Streptomyces that carry them. Each genome carried between 19–65 BGCs (median=42.5) and varied even among members of the same Streptomyces species. Nine major classes of BGCs were detected in ten of the 11 bat species and in all sites: terpene, non-ribosomal peptide synthetase, polyketide synthase, siderophore, RiPP-like, butyrolactone, lanthipeptide, ectoine, melanin. Finally, Streptomyces genomes carry multiple hybrid BGCs consisting of signature domains from two to seven distinct BGC classes. Taken together, our results bring critical insights to understanding Streptomyces -bat ecology and BGC diversity that may contribute to bat health and in augmenting current efforts in natural product discovery, especially from underexplored or overlooked environments.

Microbial Genomics↗

USGS2024

Ecological dissimilarity matters more than geographical distance when predicting land surface indicators using machine learning

Supervised training techniques, such as those used in machine learning, use generally large sets of in situ data to train models that can, in turn, be used to make predictions (or prediction maps) about the Earth’s surface in times or places where no in situ data exist. The purpose of the present study is to investigate, using a very large set of in situ data from across the western United States (U.S.), the conditions under which training data from a different geographic region where predictions are desired may be substituted. To do this, we train models using in situ data from level IV ecoregions and test how well these models predict surface conditions in different ecoregions. We characterize the difference between the possible pairs of ecoregion in terms of geographical (centroid-to-centroid) distance and “ecological dissimilarity.” Ecological dissimilarity between pairs of ecoregions is defined in two ways: 1) as the Euclidean distance in multivariate space defined by in situ indicators designed for monitoring purposes and 2) in terms of the difference in temporal behavior from model- and remote sensing-derived datasets. Although, overall, prediction error increases with geographical distance between training and testing ecoregions, our results indicate that ecological dissimilarity can be used to predict the error expected from a model trained with data from one ecoregion when applied in a different ecoregion.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2002

A landscape ecology approach to assessing development impacts in the tropics: A geothermal energy example in Hawaii

Geographic information systems (GIS) are increasingly being used in environmental impact assessments (EIA) because GIS is useful for analysing spatial impacts of various development scenarios. Spatially representing these impacts provides another tool for landscape ecology in environmental and geographical investigations by facilitating analysis of the effects of landscape patterns on ecological processes and examining change over time. Landscape ecological principles are applied in this study to a hypothetical geothermal development project on the Island of Hawaii. Some common landscape pattern metrics were used to analyse dispersed versus condensed development scenarios and their effect on landscape pattern. Indices of fragmentation and patch shape did not appreciably change with additional development. The amount of forest to open edge, however, greatly increased with the dispersed development scenario. In addition, landscape metrics showed that a human disturbance had a greater simplifying effect on patch shape and also increased fragmentation than a natural disturbance. The use of these landscape pattern metrics can advance the methodology of applying GIS to EIA.

Singapore Journal of Tropical Geography↗

USGS2020

elfgen: A new instream flow framework for rapid generation and optimization of flow-ecology relations

Effective water resource management requires practical, data‐driven determination of instream flow needs. Newly developed, high‐resolution flow models and aquatic species databases provide enormous opportunity, but the volume of data can prove challenging to manage without automated tools. The objective of this study was to develop a framework of analytical methods and best practices to reduce costs of entry into flow–ecology analysis by integrating widely available hydrologic and ecological datasets. Ecological limit functions (ELFs) describing the relation between maximum species richness and stream size characteristics (streamflow or drainage area) were developed. Species richness is expected to increase with streamflow through a watershed up to a point where it either plateaus or transitions to a decreasing trend in larger streams. Our results show that identifying the location of this "breakpoint" is critical for producing optimal ELF model fit. We found that richness breakpoints can be estimated using automated low‐supervision methods, with high‐supervision providing negligible improvement in detection accuracy. Model fit (and predictive capability) was found to be superior in smaller hydrologic units. The ELF model ("elfgen" R package available on GitHub: https://github.com/HARPgroup/elfgen ) can be used to generate ELFs using built‐in datasets for the conterminous United States, or applied anywhere else streamflow and biodiversity data inputs are available.

Virginia↗

USGS2026

Sediment vulnerability ranking for river basins across the contiguous U.S. using integrated biophysical and social-ecological data

Nearly half of streams and rivers in the United States (U.S.) have fair to poor conditions for aquatic ecosystem health as declared by the U.S. Environmental Protection Agency, and sediment was identified as a primary factor impairing these waterbodies. We rank sediment vulnerability using physical, ecological, and socioeconomic datasets in 163 4-digit Hydrologic Unit Codes within 18 regions across the contiguous U.S. based on the National Hydrography Dataset. We refer to sediment vulnerability as the potential for excess sediment to adversely impact social-ecological aspects of streams and rivers. Metrics were organized into six variable groups: (1) geomorphic setting, (2) modeled sediment and phosphorus, (3) hydrologic conditions, (4) anthropogenic factors and land use, (5) socioeconomic considerations, and (6) measures of ecosystem sensitivity. Correlations and principal component analysis were used to reduce and select metrics that explained the highest variability across basins. Results from the regional analysis identify basins with higher sediment vulnerability in each region, whereas national results identify hotspots of highly ranked basins in the Midwest and the central U.S. with a concentration of moderately to highly ranked basins in the south-central and southwestern U.S. Indicators of socioeconomic and ecological vulnerability integrated with physical drivers of sediment production help identify important gaps in sediment monitoring and research.

contiguous United States↗

USGS2020

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↗