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Interim report on the scientific investigations in the Animas River watershed, Colorado to facilitate remediation decisions by the U.S. Bureau of Land Management and the U.S. Forest Service, March 29, 2000 meeting, Denver, Colo.

INTRODUCTION The joint U.S. Department of the Interior and U.S. Department of Agriculture Abandoned Mine Lands Initiative (AMLI) was developed as a collaborative effort between the Federal land management agencies (FLMA, that is the U.S. Bureau of Land Management and the U.S. Forest Service) and the U.S. Geological Survey (USGS) in 1996. The stated goal of the AML Initiative was to develop a strategy for gathering and communicating the scientific information needed to develop effective and cost-efficient remediation of abandoned mines within the framework of a watershed. Four primary objectives of the AMLI are to: 1. Provide the scientific information needed (in the short-term) by the FLMAs to make decisions related to the design and implementation of cleanup actions, 2. Develop a multi-disciplined, multi-division approach that integrates geologic, hydrologic, geochemical and ecological information into a knowledge base for sound decision making, 3. Transfer technologies developed within the scientific programs of the USGS to the field and demonstrate their suitability to solve real, practical problems, and 4. Establish working relationships among involved members of land management and regulatory agencies within the framework of a watershed approach to the cleanup of abandoned mines. Long-term process-based research, including development of analytical tools, is recognized as being critical to the long-term success in remediating watersheds impacted by historical mining activities (AML 5-year plan, http://amli.usgs.gov/amli). In a meeting of Federal agencies (U.S. Bureau of Land Management [BLM], U.S. Bureau of Reclamation [BOR], U.S. National Park Service [NPS], U.S. Forest Service [USFS], the U.S. Environmental Protection Agency [EPA], the U.S. Fish and Wildlife Service [F&WS]), and State agencies (Colorado Division of Public Health and Environment, Colorado Division of Mines and Geology), several watersheds were examined within the state whose water quality was presumed to be impacted by historical mining activities. The Animas River watershed (fig. 1) was selected by the State and Federal agencies as one of two watersheds in the U.S. to be studied in detail by the USGS in the AML Initiative. Beginning in October 1997, each of the four Divisions of the USGS (Water Resources, Geologic, Biological Resources, and National Mapping) initiated a collaborative integrated science study of the watershed. Funds were provided from USGS base funding to each of the four Divisions in response to the priorities set by Congressional action and within the flexibility provided by the budgetary framework funding individual research programs. The AML Initiative provides for a five-year focused scientific effort in the two watersheds with final synthesis of the scientific results from each to be published in 2001. Publications are released on the AML web site on a regular basis (http://amli.usgs.gov/amli). On March 29, 2000, the USGS hosted a meeting for the BLM and USFS to discuss remediation options that were under consideration for the summer of 2000. The purpose of this report is to provide an overview of the scientific rational provided by the USGS to meet objective one above, and to summarize our preliminary interpretations of our data. Additional information from sites on private lands have been collected by the State of Colorado, EPA, and the ARSG. Unfortunately, these data have not been fully supplied to the USGS so our conclusions are based only upon our data. These interpretations provide science-based constraints on possible remediation options to be considered by the FLMA, the State, and local property owners in the Animas River watershed. The report is presented in outline format to facilitate discussion of remediation options at the March 29, 2000 meeting. Not all historical mining sites within the watershed are on public lands. This should not be construed to be a final report of the USGS

Denver↗

NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions. Here, we present NABat ML , an automated machine-learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet-based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted-average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud-environment computing instance, the entire model training process took <16 h. Synthesis and applications . Our convolutional neural network (CNN)-based model, NABat ML , classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species-level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open-source and reproducible, enabling future implementations as software on end-user devices and cloud-based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big-data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad-scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.

Journal of Applied Ecology↗

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗

Geospatial considerations for a multiorganizational, landscape-scale program

Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.

Journal of Map & Geography Libraries↗

Subsurface controls on the development of the Cape Fear Slide Complex, central US Atlantic Margin

The Cape Fear Slide is one of the largest (>25 000 km 3 ) submarine slope failure complexes on the US Atlantic margin. Here we use a combination of new high-resolution multichannel seismic data (MCS) from the National Science Foundation Geodynamic Processes at Rifting and Subducting Margins (NSF GeoPRISMS) Community Seismic Experiment and legacy industry MCS to derive detailed stratigraphy of this slide and constrain the conditions that lead to slope instability. Limited outer-shelf and upper-slope accommodation space during the Neogene, combined with lowstand fluvial inputs and northwards Gulf Stream sediment transport, appears to have contributed to thick Miocene and Pliocene deposits that onlapped the lower slope. This resulted in burial of an upper-slope bypass zone developed from earlier erosional truncation of Paleogene strata. These deposits created a broad ramp that allowed accumulation of thick Quaternary strata across a low-gradient (<3.5°) upper slope. Upslope of one of the larger headwalls, undulating Quaternary strata appear to downlap onto a buried failure plane. Many of the nested headwalls of the upper-slope portion of slide complex are underlain by deformed strata, which may be the result of fluid migration associated with localized subsidence from salt migration. These new data and observations suggest that antecedent margin physiography, sediment loading and substrate fluid flow were key factors in preconditioning the Cape Fear slope for failure.

Geological Society of London Special Publications↗

Concerns regarding a call for pluralism of information theory and hypothesis testing

1. Stephens et al. (2005) argue for 'pluralism' in statistical analysis, combining null hypothesis testing and information-theoretic (I-T) methods. We show that I-T methods are more informative even in single variable problems and we provide an ecological example. 2. I-T methods allow inferences to be made from multiple models simultaneously. We believe multimodel inference is the future of data analysis, which cannot be achieved with null hypothesis-testing approaches. 3. We argue for a stronger emphasis on critical thinking in science in general and less reliance on exploratory data analysis and data dredging. Deriving alternative hypotheses is central to science; deriving a single interesting science hypothesis and then comparing it to a default null hypothesis (e.g. 'no difference') is not an efficient strategy for gaining knowledge. We think this single-hypothesis strategy has been relied upon too often in the past. 4. We clarify misconceptions presented by Stephens et al. (2005) . 5. We think inference should be made about models, directly linked to scientific hypotheses, and their parameters conditioned on data, Prob(Hj| data). I-T methods provide a basis for this inference. Null hypothesis testing merely provides a probability statement about the data conditioned on a null model, Prob(data |H0). 6. Synthesis and applications . I-T methods provide a more informative approach to inference. I-T methods provide a direct measure of evidence for or against hypotheses and a means to consider simultaneously multiple hypotheses as a basis for rigorous inference. Progress in our science can be accelerated if modern methods can be used intelligently; this includes various I-T and Bayesian methods.

Journal of Applied Ecology↗

U.S. Geological Survey collections—Preserving the past to inform the future: Tour three federal repositories—Core Research Center, Paleontological Collection, and the NSF National Ice Core Laboratory

This 2016 Geological Society of America (GSA) Annual Meeting trip will explore the Core Research Center, Paleontological Collection, and National Science Foundation National Ice Core Laboratory—three collections of major national signifi cance managed by the U.S. Geological Survey (USGS). Since its inception in 1879, USGS has collected, preserved, and managed physical collections for scientifi c investigations of Earth’s systems. The Core Research Center is the largest federal core repository in the United States, where over 74 million meters (242 million feet) of the subsurface are represented by the collection of rock cores and well cuttings, available for use by researchers investigating resource potential, tectonics, structures, aquifers, and more. The USGS has conducted paleontological research for more than 110 years to inform geological mapping, biostratigraphy, paleoecology, paleoclimate, and other research. Most of these paleontological samples are at the Smithsonian Institution National Museum of Natural History (NMNH) and USGS Denver facilities. The USGS Denver paleontological collection includes ~1.2 million samples. Ancillary materials consisting of handwritten ledgers, index cards, fi eld reports, maps, and other information produced by USGS investigators provide profound knowledge about the specimens and associated geological systems. The USGS is working with NMNH to systematically digitize the collection to preserve and expose samples and data to research. The National Science Foundation (NSF) National Ice Core Laboratory (NICL) is the nation’s repository for preserving, archiving, and sampling meteoric ice cores collected from the world’s ice sheets, ice caps, and glaciers, mostly from Antarctica and Greenland. NICL’s primary mission is to store and curate ice cores, primarily collected during NSF-sponsored projects, for present and future sample investigations.

Colorado↗

Use case development for earth monitoring, analysis, and prediction (EarthMAP)—A road map for future integrated predictive science at the U.S. Geological Survey

Executive Summary The U.S. Geological Survey (USGS) 21st-century science strategy 2020–30 promotes a bureau-wide strategy to develop and deliver an integrated, predictive science capability that works at the scales and timelines needed to inform societally relevant resource management and protection and public safety and environmental health decisions (U.S. Geological Survey, 2021). This is the overarching goal of the USGS Earth Monitoring, Analysis, and Prediction (EarthMAP) vision, which consists of three components: (1) integrated data and information, (2) integrated predictive science, and (3) actionable information—all designed and delivered to respond to user needs. To launch this vision and help shape the design and implementation of integrated predictive science, the USGS Regional Offices each developed a set of use cases (hereafter Use Cases)—short descriptions of potential science applications that could clearly address high priority decision-making needs of our stakeholders and that align with an integrated science focus. Use Cases are not actionable science planning documents, nor stand-alone scholarly works, but should be considered as innovative, next-generation science ideas that can be considered as potential components of science plans still under development. The goal of Use Case development was to (1) identify and characterize existing USGS scientific capacities and expertise that can support science goals and products, (2) identify opportunities to leverage current capacities for next-generation science, and (3) foster engagement across the entire Bureau to further refine the USGS strategy for EarthMAP and integrated predictive science. The Use Case development effort documented in this report was coordinated by the Use Case Development Team (UCDT), consisting of representatives from each region. The UCDT undertook five tasks: (1) develop a unified approach to engage bureau scientists consistently across all regions in aspirational thinking about what can be accomplished; (2) work with the regions and their Science Centers to generate an initial set of Use Cases, authored directly by scientists; (3) characterize, summarize, and document the initial set of Use Case submissions from authors to illuminate bureau-level demand for integrated science; (4) compare existing and needed capacities from the Use Case descriptions with preliminary results of the EarthMAP Capacity Assessment (Keisman and others, 2021); and (5) describe lessons learned from the Use Case development process and provide recommendations to inform future efforts to generate integrated science activities. This report outlines the approach the UCDT developed to solicit Use Cases from the regions and summarizes the high-level qualitative findings from this first-round effort. The UCDT received 36 Use Cases from the regions and identified potential points of convergence and commonalities considered useful in making connections among the participating scientists. The Southwest (SW) Region and the Rocky Mountain (RM) Region asked scientists to give special consideration to Use Cases with applicability to the Colorado River Basin, and seven of the Use Cases specifically named that geographic area as a focus. Coastal hazards and coastal resilience were identified in Use Cases from the Alaska (AK), Northeast (NE), and Southeast (SE) Regions. Aspects of wildfire and post-wildfire response were part of Uses Cases from AK, RM, and SW Regions. The greatest convergence of Use Case themes was related to conservation of public lands and waters, which is a powerful linkage lending strength to future collaborative efforts. The most common type of stakeholder decisions that would be informed by the Use Case science applications were related to adaptation, mitigation, and response (for example, how to increase the resilience of coastal communities to climate-related stressors and how to prevent or respond to harmful algal blooms). Other common types of decisions included water and land management decisions (including operational water management decisions such as reservoir operations and land use planning in the sagebrush biome), decisions about how to manage and conserve habitats and species, and risk management decisions (such as managing the post-wildfire flood risks). These decision types are not exclusive because many Use Cases cross categories. Use Case authors identified existing and needed science and technology capabilities required for Use Case implementation, which were then aligned to capabilities assessed in the EarthMAP Capacity Assessment (Keisman and others, 2021). Strong alignment was found for data and information integration approaches, modeling and prediction approaches, and capabilities related to delivery of actionable information. A majority of Use Cases indicated insufficient current capacity for needed data collection methods, data integration, and modeling and prediction approaches, whereas only 25 percent indicated insufficient capacity for actionable information delivery. Overall, many Use Case capacity demand gaps could potentially be met by existing bureau-wide capacity. In addition, nearly half of the Use Cases could potentially be implemented within 3 years if funding, capabilities, and personnel impediments were removed and science priorities were realigned. Several challenges emerged during the Use Case development process. The first challenge was developing an approach that was flexible enough to accommodate regional differences in planning and implementation, while also ensuring enough guidance to promote meaningful summary analyses. The UCDT encountered a strong demand for continuous communication and education to improve overall understanding of the integrated predictive science strategy. Another challenge was managing expectations about EarthMAP activities as a design effort that was not aligned to an immediate funding opportunity. Connecting the Use Cases to stakeholder needs without the opportunity for direct stakeholder engagement was also challenging. The last notable challenge was in obtaining consistent interpretation and characterization of the qualitative data housed in the narrative descriptions of Use Cases, written in different styles. Overall, the 36 Use Cases can serve as components of a road map for advancing integrated monitoring and predictive science throughout the USGS by revealing opportunities to (1) encourage cross-region initiatives that address shared interests in common themes by integrating similar Use Cases and through direct involvement of stakeholders in identifying needs and designing effective responses, (2) leverage the Use Cases to target investments that are aligned with the Bureau and Department of the Interior (DOI) priorities, (3) connect Use Cases and the results of the companion EarthMAP Capacity Assessment (Keisman and others, 2021) to identify potential priorities for capacity building investments, and (4) raise awareness of common integrated and interdisciplinary science interests within and across the regions through Use Case and Capacity Assessment summary outreach activities.

Open-File Report↗

Alternative interpretations of oil spill data

In his article "Oil, Seabirds, and Science" (BioScience 46: 587-597), John Wiens attempted to review Exxon Valdez oil spill (EVOS) damage assessment studies and the politics of EVOS science in one stroke. In my opinion, neither purpose was particularly well served.

Alaska↗

LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment

LANDFIRE is a 5-year, multipartner project producing consistent and comprehensive maps and data describing vegetation, wildland fuel, fire regimes and ecological departure from historical conditions across the United States. It is a shared project between the wildland fire management and research and development programs of the US Department of Agriculture Forest Service and US Department of the Interior. LANDFIRE meets agency and partner needs for comprehensive, integrated data to support landscape-level fire management planning and prioritization, community and firefighter protection, effective resource allocation, and collaboration between agencies and the public. The LANDFIRE data production framework is interdisciplinary, science-based and fully repeatable, and integrates many geospatial technologies including biophysical gradient analyses, remote sensing, vegetation modelling, ecological simulation, and landscape disturbance and successional modelling. LANDFIRE data products are created as 30-m raster grids and are available over the internet at www.landfire.gov , accessed 22 April 2009. The data products are produced at scales that may be useful for prioritizing and planning individual hazardous fuel reduction and ecosystem restoration projects; however, the applicability of data products varies by location and specific use, and products may need to be adjusted by local users.

International Journal of Wildland Fire↗

Availability of Groundwater Data for California, Water Year 2008

The U.S. Geological Survey, Water Resources, in cooperation with Federal, State, and local agencies, obtains a large amount of data pertaining to the groundwater resources of California each water year (October 1-September 30). These data constitute a valuable database for developing an improved understanding of the water resources of the State. This Fact Sheet serves as an index to groundwater data for water year 2008. The 2-page report contains a map of California showing the number of wells (by county) with available water-level and water-quality data for water year 2008 (fig. 1) and instructions for obtaining this and other groundwater information contained in the databases of the U.S. Geological Survey, California Water Science Center. From 1985 to 1993, data were published in the annual report 'Water Resources Data for California, Volume 5. Ground-Water Data'; prior to 1985, the data were published in U.S. Geological Survey Water-Supply Papers.

Fact Sheet↗

Availability of Groundwater Data for California, Water Year 2009

The U.S. Geological Survey, in cooperation with Federal, State, and local agencies, obtains a large amount of data pertaining to the groundwater resources of California each water year (October 1-September 30). These data constitute a valuable database for developing an improved understanding of the water resources of the State. This Fact Sheet serves as an index to groundwater data for Water Year 2009. The 2 page report contains a map of California showing the number of wells (by county) with available water-level and water-quality data for Water Year 2009 (fig. 1) and instructions for obtaining this and other groundwater information contained in the databases of the U.S. Geological Survey, California Water Science Center. From 1985 to 1993, data were published in the annual report 'Water Resources Data for California, Volume 5. Ground-Water Data'; prior to 1985, the data were published in U.S. Geological Survey Water-Supply Papers.

Fact Sheet↗

Availability of groundwater data for California, water year 2010

The U.S. Geological Survey, in cooperation with Federal, State, and local agencies, obtains a large amount of data pertaining to the groundwater resources of California each water year (October 1-September 30). These data constitute a valuable database for developing an improved understanding of the water resources of the State. This Fact Sheet serves as an index to groundwater data for Water Year 2010. It contains a map of California showing the number of wells (by county) with available water-level or water-quality data for Water Year 2010 (fig. 1) and instructions for obtaining this and other groundwater information contained in the databases of the U.S. Geological Survey, California Water Science Center. From 1985 to 1993, data were published in the annual report "Water Resources Data for California, Volume 5. Ground-Water Data"; prior to 1985, the data were published in U.S. Geological Survey Water-Supply Papers.

California↗

Applied citizen science in freshwater research

Worldwide, scientists are increasingly collaborating with the general public. Citizen science methods are readily applicable to freshwater research, monitoring, and education. In addition to providing cost-effective data on spatial and temporal scales that are otherwise unattainable, citizen science provides unique opportunities for engagement with local communities and stakeholders in resource management and decision-making. However, these methods are not infallible. Citizen science projects require deliberate planning in order to collect high data quality and sustain meaningful community partnerships. Citizen science practitioners also have an ethical responsibility to ensure that projects are not putting the safety of participants at stake. We discuss here how citizen science is being applied in freshwater research, emerging challenges in project planning and implementation, as well as how citizen science is shaping public understanding, policy, and management of freshwaters.

WIREs Water↗

Wyoming Landscape Conservation Initiative data management and integration

Six Federal agencies, two State agencies, and two local entities formally support the Wyoming Landscape Conservation Initiative (WLCI) and work together on a landscape scale to manage fragile habitats and wildlife resources amidst growing energy development in southwest Wyoming. The U.S. Geological Survey (USGS) was tasked with implementing targeted research and providing scientific information about southwest Wyoming to inform the development of WLCI habitat enhancement and restoration projects conducted by land management agencies. Many WLCI researchers and decisionmakers representing the Bureau of Land Management, U.S. Fish and Wildlife Service, the State of Wyoming, and others have overwhelmingly expressed the need for a stable, robust infrastructure to promote sharing of data resources produced by multiple entities, including metadata adequately describing the datasets. Descriptive metadata facilitates use of the datasets by users unfamiliar with the data. Agency representatives advocate development of common data handling and distribution practices among WLCI partners to enhance availability of comprehensive and diverse data resources for use in scientific analyses and resource management. The USGS Core Science Informatics (CSI) team is developing and promoting data integration tools and techniques across USGS and partner entity endeavors, including a data management infrastructure to aid WLCI researchers and decisionmakers.

Wyoming↗

Integrating airborne remote sensing and field campaigns for ecology and Earth system science

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.

Colorado↗

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

PNAS Nexus↗

Impact of a place-based role-playing exercise on student sense of classroom community and science identity in a hydrology class

Fostering a sense of classroom community in earth science classes supports students’ sense of belonging within the classroom and the broader scientific community, helping them build a sense of identity as a geoscientist. This study examines the effects of incorporating a 2-week, collaborative role-playing activity on sense of classroom community and science identity in an introductory hydrology class. Students assumed roles of residents, medical center representatives, government employees, and environmental activists to learn about flooding through a community-centered lens, focusing on a flood event in Harris County, Texas during Tropical Storm Allison. Pre-post-surveys were given immediately before and after the learning module to evaluate classroom community, science identity using Likert scales, and hydrologist identity using a pictorial scale. Qualitative analysis of a short-answer question in which students defined “hydrologist” provided context for quantitative identity data. Post-survey data on classroom community shows an increase in mean agreement as compared to the pre-survey. This increase was statistically significant for four classroom community statements. Paired science identity data show small effect size and no significant change, but pictorial identity as a hydrologist shows significant growth. Social aspects of the role-playing activity did not significantly alter student’s already high science identity but altered their conceptions of the social implications of hydrology and increased identity as hydrologists. The significant increase in classroom community has important implications for using role-playing as an active learning strategy to enhance student learning experience by creating a positive classroom climate and connecting hydrology concepts to community needs.

Journal of Geoscience Education↗