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At least 595 records · Page 33Linked to original sources

Spatial nonlinearities: Cascading effects in the earth system

Nonlinear behavior is prevalent in all aspects of the Earth System, including ecological responses to global change (Gallagher and Appenzeller 1999; Steffen et al. 2004). Nonlinear behavior refers to a large, discontinuous change in response to a small change in a driving variable (Rial et al. 2004). In contrast to linear systems where responses are smooth, well-behaved, continuous functions, nonlinear systems often undergo sharp or discontinuous transitions resulting from the crossing of thresholds. These nonlinear responses can result in surprising behavior that makes forecasting difficult (Kaplan and Glass 1995). Given that many system dynamics are nonlinear, it is imperative that conceptual and quantitative tools be developed to increase our understanding of the processes leading to nonlinear behavior in order to determine if forecasting can be improved under future environmental changes (Clark et al. 2001).

Book chapter↗

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. In this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

Nature Reviews Earth & Environment↗

Persistence of coral reef structures into the twenty-first century

Coral reefs provide important socioecological services but are vulnerable to climate change, which shifts the balance between the production and erosion of calcium carbonate (CaCO 3 ). In this Review, we summarize understanding of reef accretion, describe the mechanisms of carbonate production and erosion, and consider the effects of future ocean warming and acidification on key reef-building and eroding taxa. The combined stressors of climate change substantially reduce net carbonate production, with a more pronounced effect on calcifying algae than corals. However, declining coral cover driven by marine heatwaves and mass bleaching will probably be the dominant determinant of future reef carbonate budgets, and thus only reefs with thermally adapted populations are predicted to maintain the ability to sustain positive CaCO 3 production under climate change, even if calcareous algal cover increases. As carbonate budgets become net negative in the future, the longevity of pre-existing reef frameworks remains unknown and understudied owing to the timescales required to meaningfully assess framework removal rates. Improving estimates of the rates of biologically driven framework loss and chemical dissolution will also be important in better predicting future reef persistence. Key knowledge gaps exist in understanding the effects of deoxygenation on coral reefs, as well as the influence of climate change on understudied sediment-producing taxa such as foraminifera and tropical molluscs.

Nature Reviews Earth & Environment↗

Terrestrial lidar datasets of New Orleans, Louisiana, levee failures from Hurricane Katrina, August 29, 2005

Hurricane Katrina made landfall with the northern Gulf Coast on August 29, 2005, as one of the strongest hurricanes on record. The storm damage incurred in Louisiana included a number of levee failures that led to the inundation of approximately 85 percent of the metropolitan New Orleans area. Whereas extreme levels of storm damage were expected from such an event, the catastrophic failure of the New Orleans levees prompted a quick mobilization of engineering experts to assess why and how particular levees failed. As part of this mobilization, civil engineering members of the United States Geological Survey (USGS) performed terrestrial lidar topographic surveys at major levee failures in the New Orleans area. The focus of the terrestrial lidar effort was to obtain precise measurements of the ground surface to map soil displacements at each levee site, the nonuniformity of levee height freeboard, depth of erosion where scour occurred, and distress in structures at incipient failure. In total, we investigated eight sites in the New Orleans region, including both earth and concrete floodwall levee breaks. The datasets extend from the 17th Street Canal in the Orleans East Bank area to the intersection of the Gulf Intracoastal Waterway (GIWW) with the Mississippi River Gulf Outlet (MRGO) in the New Orleans East area. The lidar scan data consists of electronic files containing millions of surveyed points. These points characterize the topography of each levee’s postfailure or incipient condition and are available for download through online hyperlinks. The data serve as a permanent archive of the catastrophic damage of Hurricane Katrina on the levee systems of New Orleans. Complete details of the data collection, processing, and georeferencing methodologies are provided in this report to assist in the visualization and analysis of the data by future users.

Louisiana↗

Summer of Applied Geophysical Experience (SAGE): Training for our future geoscientists

Energy and natural resources are crucial to the sustainability of worldwide economies, security, and overall well-being. However, the future workforce in the energy and natural-resources sector is at risk, and meeting the challenges of this dwindling workforce requires well-educated geoscientists in exploration and applied geophysics and related geoscience and technology disciplines. Programs such as geophysical field courses that are supported by SEG and industry, in partnership with academic institutions and government laboratories, are important approaches to maintaining and enhancing expertise in exploration geophysics. One example of a geophysical field course devoted to educating our future workforce is the Summer of Applied Geophysical Experience (SAGE), a four-week program based in Santa Fe, New Mexico, designed to actively engage students in all phases of applied geophysical research. SAGE is a unique educational experience that combines teaching and research as a partnership among universities, industry, government agencies, and professional societies. SAGE teaches the principles and applications of refraction and reflection seismology, magnetics, gravity, GPS, heat flow, several electromagnetic (EM) methods, and ground-penetrating radar (GPR) in a field-based, hands-on setting. More than 850 students and qualified professionals have attended SAGE, many of whom have gone on to become leaders in academia, industry, and government. SAGE students are exposed to the exciting challenges that face earth scientists today, and they develop skills that are necessary to address the world's growing energy demands. Examples of SAGE research projects include mapping archaeological sites and tectonic structure and investigating water and geothermal resources in the Rio Grande rift.

Leading Edge (Tulsa, OK)↗

Selected annotated bibliography of the geology of uraniferous and radioactive native bituminous substances, exclusive of coals, in the United States

Native bituminous substances are divided into two groups, 1) bitumens and, 2) pyrobitumens. Bitumens are composed principally of hydrocarbons substantially free from oxygenated bodies, are fusible, and are soluble in carbon disulfide. Native bitumens occur in liquid and solid forms. The native liquid bitumens include all petroleums or crude oils. Native solid bitumens include native waxes such as ozocerite, asphalts or petroleum tars, and asphaltites such as gilsonite and grahamite. Pyrobitumens are composed principally of hydrocarbons which may contain oxygenated bodies. They are infusible and are insoluble, or nearly insoluble, in carbon disulfide. Native pyrobitumens are divided into an oxygen-containing group including peats, lignites, and coals, and an essentially oxygen-free, asphaltic group including such substances as wurtzilite, albertite, impsonite, and ingramite. Thucholites, which are carbonaceous substances that may contain uranium, thorium, and rare earths, commonly are considered to be pyrobitumens. Their compositions are variable and may fall into either the oxygen-containing or oxygen-free group. All varieties of native bituminous substances may be associated with mineral matter. The nomenclature of bitumens and pyrobitumens is used very loosely in the literature. This circumstance arises from the difficulty in recognizing many of these substances by visual examination, and because many of them can be identified accurately only by chemical methods. Inasmuch as some of the chemical procedures are time-consuming and satisfactory analytical methods have not been devised for all these substances, geologists generally have not obtained precise identifications but rather have used names that appeared most appropriate to the circumstances. It is expected that future research will show many substances called "asphaltite," "thucholite," etc., to be incorrectly identified. The nomenclature used by the authors of the various references of this bibliography is followed without deviation or further discussion. The stratigraphic nomenclature also is that used by the authors. In this bibliography emphasis is placed on reports dealing with the uranium contents and radioactivity of native bituminous substances rather than on mineralogical and chemical studies of these substances. The distribution of the substances described in the references is shown on the accompanying map. The indicated presence of these substances does not infer that they contain sufficient radioactive elements to constitute ores.

Trace Elements Investigations↗

Unmanned aircraft systems (UAS) activities at the Department of the Interior

The U.S. Department of the Interior (DOI) is responsible for protecting and managing the natural resources and heritage on almost 20% of the land in the United States. The DOI’s mission requires access to remotely sensed data over vast lands, including areas that are remote and potentially dangerous to access. Unmanned Aircraft Systems (UAS) technology has the potential to enable the DOI to be a better steward of the land by: (1) Improving natural hazard forecasting and the analysis of the impacts. (2) Improving the understanding of climate change to better plan for likely impacts. (3) Developing precipitation and evaporation forecasting to better manage water resources. (4) Monitoring Arctic ice change and its impacts on ecosystems, coasts, and transportation. (5) Increasing safety and effectiveness of wildland fire management. (6) Enhancing search and rescue capabilities. (7) Broadening the abilities to monitor environmental or landscape conditions and changes. (8) Better understanding and protecting the Nation’s ecosystems. The initial operational testing and evaluations performed by the DOI have proven that UAS technology can be used to support many of the Department’s activities. UAS technology provides scientists a way to look longer, closer and more frequently at some of Earth’s most remote areas—places that were previously too dangerous or expensive to monitor in detail. The flexibility of operations and relative low cost to purchase and operate Small Unmanned Aerial System (sUAS) enhances the ability to track long-term landscape and environmental change. The initial testing indicates the operational costs are approximately 10% of traditional manned aircraft. In addition, users can quickly assess landscape-altering events such as wildland fires, floods and volcanoes. UAS technology will allow the DOI to do more with less and in the process enhance the Department’s ability to provide unbiased scientific information to help stakeholders make informed decisions. It will also provide a digital baseline record that can be archived and used when monitoring future events or conditions. One possible future scenario has scientists carrying sUAS into the field allowing quick deployment and operation to observe the environment or for emergency response. This scenario could also include a persistent monitoring capability provided by a UAS that can stay airborne over a small geographic area for days or weeks, or possibly longer. While the DOI focus is on sUAS, the Department recognizes that larger UAS systems will also play a role in meeting its mission. The Department anticipates meeting long-duration or specialized acquisition commitments, such as state or national aerial photography, by collaboration with other agencies or through commercial contracts. Even though the DOI continues to evaluate UAS and sensor technology to meet the Department’s mission, some of its bureaus are already moving towards an operational capability. The authors fully anticipate that by 2020 UAS will emerge as one of the primary platforms for DOI remote sensing applications.

Photogrammetric Engineering and Remote Sensing↗

Physics‐based evaluation of the maximum magnitude of potential earthquakes induced by the Hutubi (China) underground gas storage

The world’s largest underground gas storage facility in Hutubi (HUGS), China, is a unique case where cyclic gas injection‐extraction induced both seismicity and ground deformation. To assess the potential for future induced seismicity, we develop a framework physically based on a well‐constrained hydro‐geomechanical model and on fully coupled poroelastic simulations. We first interpret the spatiotemporal distribution and focal mechanisms of induced earthquakes and use these to estimate the magnitude and location of the largest potential earthquake. The sharp increase in seismicity was controlled by poroelastic loading on secondary southwest‐dipping thrust faults with spatial scales too small to be resolved by 3D seismic surveys. Both operational and local geological factors affect the seismic productivity at the HUGS site, distinguishing it from most cases of seismicity induced by wastewater disposal and hydraulic fracturing. We then conduct slip tendency analyses for major faults imaged by the seismic data, including the largest reservoir‐bounding Hutubi fault hydraulically connected to injection wells. The reactivation potentials of these imaged faults are estimated to be extremely low. Accordingly, future seismicity would most likely occur on failure‐prone secondary faults in regions with positive stress perturbation due to poroelastic loading. The maximum magnitude likely depends on the spatial scales of the secondary faults. As the occurrence of detected earthquakes is spatially and temporally consistent with the simulated evolution of Coulomb stress perturbation, the location of the largest potential earthquake probably depends on the sizes of the poroelastic stressing regions.

Hutubi↗

The plumbotectonic model for Pb isotopic systematics among major terrestrial reservoirs: A case for bi-directional transport

Version IV of plumbotectonics expands and refines the original model of Doe and Zartman (1979) and Zartman and Doe (1981) for explaining Pb (Sr, and Nd) isotopic systematics among major terrestrial reservoirs. A case for bi-directional transport among reservoirs is based on the observed isotopic compositions for different tectonic settings, and finds a rationale in the kinetics of plate tectonics. Chemical fractionation and radioactive decay create isotopic differences during periods of isolation of one reservoir from another, whereas dynamic processes allowing mixing between reservoirs tend to reduce these differences. Observed isotopic characteristics reflect a balance between these opposing tendencies and provide constraints on the extent and timing of fractionation and mixing processes. Plumbotectonics does not require interaction with a lower mantle or core reservoir over most of the Earth's lifetime, and, in fact, achieves a material balance consistent with no such exchange of material. Important evidence of the amount and timing of crustal recycling, and of the residence times of mantle heterogeneities lies in the coupled 207 Pb 204 Pb- 206 Pb 204 Pb "> 207 Pb 204 Pb- 206 Pb 204 Pb systematics. We believe that examination of the published data base fully supports our contention of significant bi-directional transport of material among terrestrial reservoirs. Plumbotectonics allows us to explore many aspects of reservoir interaction, and to identify parameters that provide meaningful constraints on mantle-crust differentiation. We put forth a compromise fit to many of the model variables in version IV, which can serve as a reference for future work.

Geochimica et Cosmochimica Acta↗

Fifty years of Landsat science and impacts

Since 1972, the Landsat program has been continually monitoring the Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, Landsat data were crucial for many scientific and technical advances. Prior to the Landsat program, detailed, synoptic depictions of the Earth's surface were rare, and the ability to acquire and work with large datasets was limited. The early years of the Landsat program delivered a series of technological breakthroughs, pioneering new methods, and demonstrating the ability and capacity of digital satellite imagery, creating a template for other global Earth observation missions and programs. Innovations driven by the Landsat program have paved the way for subsequent science, application, and policy support activities. The economic and scientific value of the knowledge gained through the Landsat program has been long recognized, and despite periods of funding uncertainty, has resulted in the program's 50 years of continuity, as well as substantive and ongoing improvements to payload and mission performance. Free and open access to Landsat data, enacted in 2008, was unprecedented for medium spatial resolution Earth observation data and substantially increased usage and led to a proliferation of science and application opportunities. Here, we highlight key developments over the past 50 years of the Landsat program that have influenced and changed our scientific understanding of the Earth system. Major scientific and programmatic impacts have been realized in the areas of agricultural crop mapping and water use, climate change drivers and impacts, ecosystems and land cover monitoring, and mapping the changing human footprint. The introduction of Landsat collection processing, coupled with the free and open data policy, facilitated a transition in Landsat data usage away from single images and towards time series analyses over large areas and has fostered the widespread use of science-grade data. The launch of Landsat-9 on September 27, 2021, and the advanced planning of its successor mission, Landsat-Next, underscore the sustained institutional support for the program. Such support and commitment to continuity is recognition of both the historic impact the program, and the future potential to build upon Landsat's remarkable 50-year legacy.

Remote Sensing of Environment↗

Estimated global nitrogen deposition using NO 2 column density

Global nitrogen deposition has increased over the past 100 years. Monitoring and simulation studies of nitrogen deposition have evaluated nitrogen deposition at both the global and regional scale. With the development of remote-sensing instruments, tropospheric NO 2 column density retrieved from Global Ozone Monitoring Experiment (GOME) and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) sensors now provides us with a new opportunity to understand changes in reactive nitrogen in the atmosphere. The concentration of NO 2 in the atmosphere has a significant effect on atmospheric nitrogen deposition. According to the general nitrogen deposition calculation method, we use the principal component regression method to evaluate global nitrogen deposition based on global NO2 column density and meteorological data. From the accuracy of the simulation, about 70% of the land area of the Earth passed a significance test of regression. In addition, NO2 column density has a significant influence on regression results over 44% of global land. The simulated results show that global average nitrogen deposition was 0.34 g m −2 yr −1 from 1996 to 2009 and is increasing at about 1% per year. Our simulated results show that China, Europe, and the USA are the three hotspots of nitrogen deposition according to previous research findings. In this study, Southern Asia was found to be another hotspot of nitrogen deposition (about 1.58 g m −2 yr −1 and maintaining a high growth rate). As nitrogen deposition increases, the number of regions threatened by high nitrogen deposits is also increasing. With N emissions continuing to increase in the future, areas whose ecosystem is affected by high level nitrogen deposition will increase.

International Journal of Remote Sensing↗

Simulations of historical and future trends in snowfall and groundwater recharge for basins draining to Long Island Sound

A regional watershed model was developed for watersheds contributing to Long Island Sound, including the Connecticut River basin. The study region covers approximately 40 900 km 2 , extending from a moderate coastal climate zone in the south to a mountainous northern New England climate zone dominated by snowmelt in the north. The input data indicate that precipitation and temperature have been increasing for the last 46 years (1961– 2006) across the region. Minimum temperature has increased more than maximum temperature over the same period (1961–2006). The model simulation indicates that there was an upward trend in groundwater recharge across most of the modeled region. However, trends in increasing precipitation and groundwater recharge are not significant at the 0.05 level if the drought of 1961–67 is removed from the time series. The trend in simulated snowfall is not significant across much of the region, although there is a significant downward trend in southeast Connecticut and in central Massachusetts. To simulate future trends, two input datasets, one assuming high carbon emissions and one assuming low carbon emissions, were developed from GCM forecasts. Under both of the carbon emission scenarios, simulations indicate that historical trends will continue, with increases in groundwater recharge over much of the region and substantial snowfall decreases across Massachusetts, Connecticut, southern Vermont, and southern New Hampshire. The increases in groundwater recharge and decreases in snowfall are most pronounced for the high emission scenario.

Connecticut, Massachusetts, New Hampshire, Rhode I↗

Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

Scientific Investigations Report↗

Operational nowcasting of electron flux levels in the outer zone of Earth's radiation belt

We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. ( 2004 , https://doi.org/10.1029/2003SW000036 ), we turn to a time‐varying linear filter of previous flux levels and K p . We train and test this model on data gathered from the 2.10 MeV channel of the Relativistic Electron‐Proton Telescope sensor onboard the Van Allen probes. Dynamic linear models are a specific case of state space models and can be made flexible enough to emulate the nonlinear behavior of particle fluxes within the radiation belts. Real‐time estimation of the parameters of the model is done using a Kalman filter, where the state of the model is exactly the parameters. Nowcast performance is assessed against several baseline interpolation schemes. Our model demonstrates significant improvements in performance over persistence nowcasting. In particular, during times of high geomagnetic activity, our model is able to attain performance substantially better than a persistence model. In addition, residual analysis is conducted in order to assess model fit and to suggest future improvements to the model.

Space Weather↗

Fires and landscape conservation in mediterranean ecosystems

Protected areas are some of the last remaining areas on Earth where fire can play its natural role at a landscape-scale. The International Union for Conservation of Nature (IUCN) has developed a system for categorizing protected areas. The role fire can play in the various categories depends on the management objectives of the category, the size of the individual units, and the laws and policies of the country in which the unit is located. An analysis of all the IUCN protected areas showed that 505 areas had the potential for conserving landscape fire. Areas in Europe, Africa, South America, Australia, and North America show promise for being able to include fire in the conservation of landscapes. Examples from South Africa, Australia, and the United States show how fire can be incorporated at the landscape scale. Future challenges include increasing urban encroachment, climate change, and air pollution. Society will have to deal with these challenges if fire is to continue its essential ecological role in Mediterranean ecosystems.

Book chapter↗

Evaluation of debris-flow building damage forecasts

Reliable forecasts of building damage due to debris flows may provide situational awareness and guide land and emergency management decisions. Application of debris-flow runout models to generate such forecasts requires combining hazard intensity predictions with fragility functions that link hazard intensity with building damage. In this study, we evaluated the performance of building damage forecasts for the 9 January 2018 Montecito postfire debris-flow runout event, in which over 500 buildings were damaged. We constructed forecasts using either peak debris-flow depth or momentum flux as the hazard intensity measure and applied each approach using three debris-flow runout models (RAMMS, FLO-2D, and D-Claw). Generated forecasts were based on averaging multiple simulations that sampled a range of debris-flow volume and mobility, reflecting typical sources and magnitude of pre-event uncertainty. We found that only forecasts made with momentum flux and the D-Claw model could correctly predict the observed number of damaged buildings and the spatial patterns of building damage. However, the best forecast only predicted 50 % of the observed damaged buildings correctly and had coherent spatial patterns of incorrectly predicted building damage (i.e., false positives and false negatives). These results indicate that forecasts made at the building level reliably reflect the spatial pattern of damage but do not support interpretation at the individual building level. We found the event size strongly influences the number of damaged buildings and the spatial pattern of debris-flow depth and velocity. Consequently, future research on the link between precipitation and the volume of sediment mobilized may have the greatest effect on reducing uncertainty in building damage forecasts. Finally, because we found that both depth and velocity are needed to predict building damage, comparing debris-flow models against spatially distributed observations of building damage is a more stringent test for model fidelity than comparison against the extent of debris-flow runout.

Natural Hazards and Earth System Sciences↗

Heat flow in the Arctic

Defines heat flow as the flux at the earth's solid surface of heat conducted from the interior; the heat-flow-unit (hfu) is on the order of 1-millionth calorie through each sq cm of the surface/sec, which is enough to melt a 4-mm layer of ice over the earth's surface/yr. Earth heat originates from radioactive decay of U, Th and K in the crust and mantle. Although land heat-flow measurements in the Arctic are too few for regional interpretation, those from Cape Thompson, Barrow and Cape Simpson, Northern Alaska are discussed and figured to show what they contribute to understanding of permafrost, climatic change and shoreline movements. Measuring thermal conductivity and gradient is much simpler in ocean basins than on land. Locations of such measurements are mapped, the results for the Alaskan quadrant in more detail. The sharp change in heat flow at the edge of the Alpha Cordillera, shown in a geothermal model, suggests that this feature is a huge accumulation of basalt, rather than mantle material or remnant of a foundering continent as previously postulated. Future Arctic heat flow studies are discussed.

Arctic↗

Integrating subsistence practice and species distribution modeling: assessing invasive elodea’s potential impact on Native Alaskan subsistence of Chinook salmon and whitefish

Alaska has one of the most rapidly changing climates on earth and is experiencing an accelerated rate of human disturbance, including resource extraction and transportation infrastructure development. Combined, these factors increase the state’s vulnerability to biological invasion, which can have acute negative impacts on ecological integrity and subsistence practices. Of growing concern is the spread of Alaska’s first documented freshwater aquatic invasive plant Elodea spp. (elodea). In this study, we modeled the suitable habitat of elodea using global and state-specific species occurrence records and environmental variables, in concert with an ensemble of model algorithms. Furthermore, we sought to incorporate local subsistence concerns by using Native Alaskan knowledge and available statewide subsistence harvest data to assess the potential threat posed by elodea to Chinook salmon ( Oncorhynchus tshawytscha ) and whitefish ( Coregonus nelsonii ) subsistence. State models were applied to future climate (2040–2059) using five general circulation models best suited for Alaska. Model evaluations indicated that our results had moderate to strong predictability, with area under the receiver-operating characteristic curve values above 0.80 and classification accuracies ranging from 66 to 89 %. State models provided a more robust assessment of elodea habitat suitability. These ensembles revealed different levels of management concern statewide, based on the interaction of fish subsistence patterns, known spawning and rearing sites, and elodea habitat suitability, thus highlighting regions with additional need for targeted monitoring. Our results suggest that this approach can hold great utility for invasion risk assessments and better facilitate the inclusion of local stakeholder concerns in conservation planning and management.

Alaska↗