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

At least 955 records · Page 53Linked to original sources

USGS2026

Efficiency of down-looking cameras for detecting round goby (Neogobius melanostomus) over varying substrates in laboratory microcosms

Since invading the Laurentian Great Lakes in the late 1980s, round goby Neogobius melanostomus have become a dominant benthic prey species, resulting in a need to accurately monitor their population abundance to inform fisheries management. Camera-based methods for assessing round goby abundances have gained popularity, but their efficiencies for detecting round goby are poorly understood. We evaluated the efficiency of down-looking color monocular cameras for detecting round goby presence in microcosm enclosures with known numbers of fish. Detection efficiencies were compared between sand and cobble substrate during daylight hours using a generalized linear mixed-effects model. After accounting for trial effects, enclosure placement, and within-replicate temporal autocorrelation, round goby detection efficiency was 98.6% over sand (95% confidence limit (CL): 98.0–99.0%), and 55.3% over a single layer of cobble substrate (CL: 48.6–61.8%). The large difference in detectability between cobble and sand suggests that camera-based estimates of round goby abundances are likely to be biased low and have lower relative precision in high-structure habitats, but may be largely unbiased in low-structure habitats. Despite much lower relative detection efficiencies of cameras in high-structure cobble habitats, the efficiencies reported here still compare favorably to conventional methods like otter and beam trawling. Our results provide initial quantitative bounds on the possible degree of negative bias in camera-based estimates of round goby abundances in different substrates, but require further field verification across the diversity of substrates, interstitial infilling, and other structural attributes of habitat found in the Great Lakes.

Michigan↗

USGS2026

Loma salmonae and related species

Loma salmonae is a microsporidium that infects Pacific salmon and causes a gill inflammatory syndrome known as microsporidial gill disease of salmon. This disease has been mostly associated with netpen-farmed Chinook salmon ( Oncorhynchus tshawytscha ) in British Columbia, Canada. Clinical, diagnostic, pathological aspects of disease, as well as approaches for disease avoidance in salmon aquaculture are discussed. A laboratory infection model in rainbow trout was used to determine life cycle-stages, transmission dynamics, pathophysiology, influence of temperature, and to test therapeutics applicable to aquaculture. This experimental model has been informative on various approaches of disease control, including the development of a promising vaccine. In addition to improving fish health in salmon farming in North America, this L. salmonae model will be applicable to other microsporidial diseases that may be encountered in emerging aquaculture regions.

Book chapter↗

USGS2026

Stacked machine learning for timber identification with laser-induced breakdown spectroscopy (LIBS)

This study presents a new approach to wood species identification using laser-induced breakdown spectroscopy (LIBS) combined with stacked machine learning techniques. The research analyzed 700 samples comprising nine Dalbergia species and nine additional tropical timber species, utilizing a handheld LIBS analyzer. A stacking methodology was developed by integrating three support vector machine (SVM) models with different kernel functions (linear, polynomial, and radial) in a one-versus-all (OVA) configuration. These SVM outputs were then combined using a partial least squares discriminant analysis (PLS-DA) meta-learner. Through PCA-based variable selection, the dimensionality was reduced from 23 401 to wavelengths while maintaining classification accuracy. The stacking approach achieved a Cohen's kappa value of 0.8671 in the validation set, significantly outperforming traditional flat classifiers. Variable importance analysis revealed calcium, magnesium, and barium as crucial elements for species differentiation, with their concentrations reflecting environmental conditions and geographical origins. This research demonstrates the potential of combining LIBS spectroscopy with advanced machine learning techniques for rapid, non-invasive timber identification, which can support efforts against illegal logging and enforcement of international trade regulations.

Applied Spectroscopy↗

USGS2026

Using structured decision-making to develop a communications strategy for the U.S. Geological Survey Cooperative Research Units Program

Communication regarding the mission of the U.S. Geological Survey (USGS) Cooperative Research Units Program (CRU) can take many forms, yet clear and concise messaging for various audiences is critical to highlight program accomplishments and increase visibility. Before the work described in this report, CRU did not have a communication strategy; therefore, CRU leadership supported a structured decision-making (SDM) workshop to develop a comprehensive strategy for multiple audiences. The workshop was conducted in November 2024, in Nebraska City, Nebraska. The working group for this SDM process included CRU Program leadership, the CRU Communications Team lead, Unit scientists, a Unit administrative assistant, a representative of the Wildlife Management Institute (WMI), a member of the USGS Ecosystems Mission Area (EMA), Office of Communications and Publishing (OCAP) team, and the team lead for the CRU Program strategic planning process, as well as three facilitators who were also unit scientists as well as experts in SDM. Over the course of a week, the SDM team followed the PrOACT framework which identified the problem, objectives, alternatives, consequences, and tradeoffs to guide us toward a strategy for implementation of a set of actions for CRU communications. Results of the SDM workshop included the development of a problem statement, an objectives hierarchy, a suite of alternatives that were evaluated using a consequences table and a clear process for assessing tradeoffs among alternative communication actions and strategies. Through the evaluation of consequences of each action or campaign, the team developed both the assessment tool (for the future) and an immediate plan for communication product development and distribution. The consequences table for this problem was meant to be flexible to accommodate changes in CRU thematic priorities and can be easily updated with new objectives, measures, and alternatives. In addition, the weight placed on objectives may change as the Team moves forward; the ranking and scoring system used in the workshop can be easily updated. Overall, the working group identified three different actions or campaigns—Fact Sheets, Who Are We Campaign, and Alumni Campaign—that scored high in the prototype decision framework. However, the tradeoffs analysis indicated that each action(s) performed better on some objectives than others. The working group identified a need to therefore develop an implementation plan that is composed of individual actions that each target different objectives to potentially create a holistic and feasible communications strategy that performs well for all objectives. In addition, the SDM prototype developed a scalable, objective-based framework for effectively communication of the value and accomplishments of the CRU program.

Preprints.org↗

USGS2026

Characterizing the long-term (1981–2023) temperature and precipitation dynamics in the Trans-Mountain regions of Kazakhstan, Central Asia

Mountain regions are highly climate-sensitive, yet long-term observational evidence of elevation and seasonal climate dynamics in Central Asia remains limited. This study examines spatiotemporal trends in temperature (Tmean, Tmax, Tmin, and diurnal temperature range [DTR]) and precipitation across Kazakhstan’s transmountain regions using 74 meteorological stations (1981–2023). Data were analyzed using the Mann–Kendall test and Sen’s slope estimator, stratified across six elevation zones from lowlands (<400 m) to high mountains (>1500 m). Results reveal a robust, spatially coherent warming signal across all zones. Annual Tmean increased at a median rate of ~0.30 °C decade −1 , peaking at 0.36 °C decade −1 above 1500 m, corresponding to an absolute increase exceeding 1.5 °C. Warming exhibited strong seasonal and diurnal asymmetries. Spring warmed most rapidly, with Tmean increasing >0.60 °C decade −1 (approaching 3 °C total). Winter warming was driven by Tmin increases (up to 0.44 °C decade −1 ), causing widespread DTR contraction, whereas summer warming was driven by Tmax increases, expanding DTR at higher elevations. Tmin showed the strongest elevation amplification overall. In stark contrast, precipitation trends were weak, spatially heterogeneous, and largely non-significant. Annual changes ranged from −6.63 to +14.35 mm decade −1 , with seasonal tendencies indicating modest, non-significant winter/spring wetting and summer drying. Ultimately, the results demonstrate a profound decoupling between strong, elevation-dependent warming and weak precipitation changes. The acute amplification of temperature, particularly during spring and summer at high elevations, has severe implications for snowmelt timing, glacier mass balance, evapotranspiration demand, and long-term water security in Kazakhstan.

Water↗

USGS2026

Indirect mineral import reliance and provenance

Mineral commodity supply chain analyses rely on international trade data reported by individual countries as quantities of a mineral commodity form imported from (or exported to) a partner. However, export quantities frequently exceed a country’s domestic production, or occur when no production data are reported, suggesting that the trade partner is merely an intermediary in a transshipment. These discrepancies can result in misleading conclusions regarding supply chain vulnerabilities and dependencies. We present a two-stage methodology to reconcile gaps between reported material sources and actual producers. First, we construct trade networks for specific mineral forms, treating production as a type of import to distinguish producing nations from entrepôts. By tracing flows through these networks, we attribute a target country’s imports to original producers via both direct (in a single trade link) and indirect (transferring through intermediaries) pathways. Second, these production-attributed flows are incorporated into multi-stage supply chains to determine the upstream provenance of feedstock for domestic refining and processing. This approach provides a more representative picture of trade reliance. For example, while the United States (U.S.) Geological Survey reports no imports of unwrought antimony metal from Russia in 2022 (U.S. Geological Survey (2025). Mineral Commodity Summaries 2025. 10.3133/mcs2025), our analysis reveals that over 16% of U.S. imports can be traced back to Russian mining through intermediate processing in countries such as China, India, and Vietnam. Additionally, our analysis of the aluminum supply chain shows that while the U.S. is reported as 52% net import reliant on aluminum materials in 2022, it is 100% reliant on foreign bauxite, 7% of which arrived indirectly. This unreported reliance, which is predominantly tied to bauxite mined in Brazil (43%) and Jamaica (28%), highlights our methods ability to capture the supply chain’s dependence on foreign feedstock that may be missing in single-stage trade data.

Mineral Economics↗

USGS2026

Rethinking seed selection based on climate matching during restoration: Geography, soils and climate explain species-specific mortality

Implicit in the construction of seed transfer zones (STZs) are the assumptions that plant populations are adapted to their home climates and that transferring native seed across climate gradients risks maladaptation and poor performance. However, plants are adapted to multiple aspects of their environments that are often excluded from STZ development. Here, we used models integrating geographic distance, climate distance and soil metrics to predict plant mortality in an experimental garden for three restoration-relevant species in the southwestern United States: Bouteloua curtipendula , Heterotheca villosa and Sporobolus cryptandrus . Overall, climate distance explained mortality better than geographic distance, but increasing climate distance was not consistently associated with higher mortality. In contrast, mortality always increased with geographic distance. Species responded idiosyncratically to environmental gradients such as soil texture and pH, indicating that incorporating site-specific variables beyond climate can improve predictions of survival. Finally, seed sources of H. villosa from hotter, drier climates exhibited improved survival during abnormally hot, dry conditions at the experimental site, whereas no consistent pattern emerged for the two grass species. Collectively, our results suggest that seeding strategies extending beyond climate matching alone may better support restoration outcomes when species-specific guidance is unavailable.

Arizona, Colorado, New Mexico, Utah↗

USGS2026

Engaging adult R3 outdoor educational program design to strengthen participation in hunting and fishing

Declining participation in hunting and fishing has been slowed by women who are learning numerous outdoor skills through recruitment, retention, and reactivation [R3] programs. R3 programs are hosted by state agencies, non-governmental organizations, and businesses that take a variety of approaches to develop participant skills and confidence. To understand how R3 program design influences hunting and fishing participation, we conducted 11 focus group interviews with 72 participants at women’s R3 programs to identify program design components that women appreciate when learning to hunt and fish. Well-designed programs offered customized educational approaches to align with participants’ needs, created a supportive environment to foster a sense of belonging, and streamlined participation through event logistics. Programs that incorporated these design components promoted skill development, boosted self-confidence, and helped participants build a supportive network to independently hunt and fish. Program leaders can apply these findings to bolster participation in hunting and fishing.

Human Dimensions of Wildlife↗

USGS2026

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan↗

USGS2026

3D semantic mapping of surface geological features

Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.

Computers & Geosciences↗

USGS2026

Case report: Observations on expulsions from 20 years of radiotransmitter implantation in adult Burmese pythons

Background Radiotelemetry as a research tool has advanced our understanding of snake behavior and ecology. However, surgical transmitter implantation can lead to health complications for study animals, including expulsion, which may also interfere with research objectives. Two implantation methods include intramuscular and coelomic placements, and we evaluate expulsion rates of transmitters using these methods in Burmese pythons ( Python bivittatus ) in southern Florida. Results From 2005 to 2024, we implanted 305 transmitters in 142 adult Burmese pythons, primarily using intramuscular implantation ( n = 221), then transitioning to include coelomic placement ( n = 84). There were no observations of transmitter-related mortality. Overall, 98.7% of transmitters were retained, with a 1.3% expulsion rate ( n = 4 transmitters). Expelled transmitters were only observed in intramuscularly implanted transmitters from 4 of 13 gravid females. Conclusions We observed no mortality related to transmitter implantation and few instances of transmitter expulsion, indicating that both intramuscular and coelomic implantation techniques are effective for monitoring adult pythons in the wild. However, there is some risk that females may expel transmitters when gravid, and this risk may be reduced when implanting transmitters intracoelomically. Our findings may be useful for studies of other large-bodied snake populations worldwide where radiotransmitter implantation is appropriate and logistically feasible.

Florida↗

USGS2026

Cumulative effects of multiple stressors on marine mammals: Elephant seals as a model system

Noise exposure is a potential stressor for free-ranging marine mammals and is often studied in the absence of other environmental factors. Here, a multi-investigator, interdisciplinary effort was undertaken to examine the response of elephant seals to multiple stressors. An integrated physiological and ecological approach was taken, including immunology, stress physiology, toxicology, animal behavior, population biology, and life history theory, to examine the cumulative effects of exposure to multiple stressors in elephant seals. While we measured the response of individual animals, a population response can be predicted by incorporating these results into the long-term data on elephant seal demographics.

Book chapter↗

USGS2026

Population structure and genetic stock identification in southeastern United States loggerhead sea turtles (Caretta caretta) using genome-wide SNPs

Characterizing the genetic structure and connectivity between populations of endangered species can be used to inform management actions. In vagile species with high gene flow or recently established populations, such characterizations can be difficult to undertake using traditional genetic markers, and genetic stock identification (GSI) may be confounded by allele-sharing between populations. Loggerhead sea turtles ( Caretta caretta ) in the southeastern United States comprise seven management units (MUs) based on female philopatry inferred via mitochondrial DNA sequences, yet nuclear microsatellite data do not reflect divergence. Further, loci for accurate GSI are not currently known. To address this, we generated genome-wide single nucleotide polymorphism (SNP) data from 146 females nesting at individual sites representative of each southeastern United States MU. We found weak (F ST =0.001–0.003) but significant divergence among all MUs, with more notable divergence between the Gulf Coast and Atlantic Ocean MUs, and amongst the Atlantic Ocean MUs. We then used an iterative leave-one-out approach to identify candidate loci for GSI. This approach identified loci that could assign individuals to natal ocean basins (i.e., to the Gulf Coast or to the Atlantic Ocean), and to individual MUs within the Atlantic Ocean, with high (≥90%) success and accuracy. Analyses of genome-wide SNPs refined our understanding of the magnitude and scale of population connectivity in loggerhead turtles in the southeastern United States, and provided a foundation for the development of SNP panels for accurate, fine-scale GSI in sea turtles.

Alabama, Florida, Georgia↗

USGS2026

Spatial and temporal drivers of variability in abundance of two stream fishes

An understanding of how and why animal populations vary in space and time informs effective conservation and management. We used spatial and temporal flow metrics to explore flow-ecology relationships for two fish species, Mountain Sucker Pantosteus platyrhynchus (Cope, 1874) and Mottled Sculpin Cottus bairdii Girard, 1850, across 64 sites and 8 years in Wyoming, U.S.A. We found variation in Mottled Sculpin and Mountain Sucker abundance was driven to a greater extent by spatial flow metrics (e.g., drainage area, median summer flow) with differing direction of response between species. The opposing responses to spatial variation in median summer flow could reflect the ability of Mountain Sucker to persist in non-perennial habitats, likely due to their relatively high mobility and recolonization capacity. Responses to temporal flow metrics (e.g., previous year spring flow, previous year autumn flow) were weaker but consistent across species likely due to similar reproductive strategies and timing. The lack of stronger flow effects on population variability in both species likely corresponds to high variability in local habitat characteristics that are mediating population response. These findings underscore how considering spatial context informs conservation planning and suggest that flow-ecology relationships may be mediated by species-specific traits and local habitat conditions.

Wyoming↗

USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗

USGS2026

Improving the use of expert opinion in disease risk analysis for conservation translocations

Conservation translocations are subject to considerable uncertainty and risk, of which disease is one of the most recognized. To address disease risks, several protocols for qualitative disease risk analysis (qDRA) exist and are used for responsible conservation translocation planning. Existing qDRA protocols usually rely on expert judgment, but they lack quantitative aggregation of elicited estimates, transparent treatment of uncertainty, and explicit comparison of alternative disease risk management pathways. We added these factors to a qDRA for translocation of a charismatic species that is extinct in the wild, the sihek (Guam kingfisher) ( Todiramphus cinnamominus ). We asked a panel of seven independent experts to quantify their judgment of risks of pathogen release, exposure, and consequences for seven pathogen hazards under three translocation management scenarios. Experts suggested that implementing a full biosecurity protocol would reduce risk for several pathogen hazards but would have variable effectiveness (11–65% depending on the hazard). There was substantial uncertainty associated with individual experts and noise among different experts, showing the potential for error if decisions are based on single-point judgments (i.e., providing judgment of a central tendency without accounting for uncertainty) from one expert or on collaborative consensus of multiple experts, as is current practice.

Conservation Biology↗

USGS2026

Peak-, mean-, and low-streamflow regional-regression equations for natural streamflow in central and western Colorado, 2019

The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed peak-, mean-, and low-streamflow regional-regression equations for estimating various statistics for natural streamflow in hydrologic regions of central and western Colorado. The peak-streamflow regression equations were developed using data from 418 streamgages, consisting of 15,202 years of record and a mean of approximately 36 years of record per streamgage. The mean- and low-streamflow regional-regression equations were developed using data from 323 streamgages where daily streamflow data were collected year-round. The annual exceedance-probability discharges for each streamgage were computed using the USGS software program PeakFQ. Mean monthly and 7-day minimum and maximum streamflows were computed using the USGS software program SWToolbox. Streamflow-duration values were computed using an R script. The regional-regression equations were determined using data for the period of record for a given streamgage through water year 2019. Geographic information systems datasets were used to develop 55 basin and 42 climatic characteristics, which were evaluated as candidate explanatory variables in the regression analysis. For the peak-streamflow regional-regression equations, the study area was divided into four hydrologic regions based on mean basin elevation, including the Plateau (less than 8,014 feet), Mid-Elevation (8,015 feet to 9,492 feet), Sub-Alpine (9,493 feet to 10,490 feet), and Alpine (greater than 10,490 feet) regions. For the peak-streamflow equations, the selection of basin and climatic characteristics was based on the 1-percent annual exceedance-probability discharge for each hydrologic region. For the mean streamflow, streamflow-duration values, and 7-day minimum and maximum streamflows, the study area was divided into four hydrologic regions based on river basin, including the (1) Colorado-East Slope Headwaters, (2) Green River, (3) Rio Grande, and (4) San Juan-Dolores. For mean streamflows, basin and climatic characteristics were evaluated separately for the annual period and each month for each hydrologic region. Regional regression equations published in this report are available for use in the USGS web-based program StreamStats.

Colorado↗

USGS2026

The future for reptiles: Advances and challenges in the Anthropocene

The future for the Reptilia will be one of continued discovery of the extant diversity of species in every group and continued challenges for their conservation. Most species will persist, albeit in smaller and increasingly fragmented geographic ranges, and active conservation measures can help to ensure survival of highly vulnerable species. There are more than 12,440 documented species of reptiles, up from 10,500 only seven years ago. Transfer of laboratory techniques, computational resources, and access to literature to herpetologists throughout the world is fueling the increase in systematic studies of reptiles. The bulk of reptiles are the squamates, lizards and snakes, with impressive diversity on most continents. Habitat loss, landscape fragmentation, exploitation, invasive species, environmental contamination, and global warming are persistent challenges to all biodiversity, including reptiles. Endemism, ecological specialization, and restricted ranges generally make species more vulnerable to anthropogenic disturbances. Moreover, the natural history information that is so important for informing conservation aims is lacking for most newly described forms, whether they represent completely novel discoveries or result from taxonomic revisions. The major lineages of reptiles exhibit enormous variation in life history traits, ranging from extremely long-lived species with low fecundity to those with short generation times and high fecundity. Reptiles vary in their degree of ecological specialization, and many live in difficult-to-sample habitats. It is implausible, if not impossible, to gather detailed information on thousands of species of reptiles, many of which are secretive and difficult to study. However, evaluating where species are likely to fit along life history gradients of time to maturity, brood size, and frequency of reproduction reveals much about their abilities to persist in the face of anthropogenic disturbance. Combined with information on geographic distribution and the severity of anthropogenic pressures, consideration of life history strategies reveals important implications for conservation of reptile species. Modern approaches to conservation of reptiles, including conservation translocations, regulation of the international trade in reptiles, management of imperiled species in the context of landscapes, progress in confronting emerging diseases, and resolving human-wildlife conflict in all its forms can help ensure the persistence of the great diversity of the Reptilia in the Anthropocene.

Book chapter↗