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At least 613 records · Page 34Linked to original sources
USGS2021

Rapid monitoring of the abundance and spread of exotic annual grasses in the western United States using remote sensing and machine learning

Exotic annual grasses (EAG) are one of the most damaging agents of change in western North America. Despite known socio-environmental effects of EAG there remains a need to enhance monitoring capabilities for better informing conservation and management practices. Here, we integrate field observations, remote sensing and climate data with machine-learning techniques to estimate and assess patterns of historical (1985–2019; R 2 = 0.86 ± 0.05; MAE = 6.7 ± 1.4%), present (2020), and future (2025–2040) EAG abundance (30-m) across much of the western United States. Trend analysis revealed that ∼8% and 1% of the landscape experienced significant rises and declines in historical EAG cover, respectively, with hotspots of invasion generally occurring near roads and along low-to-mid elevation gradients with warmer and drier conditions. Accurate simulations of the response of EAG to changing environmental conditions, disturbances and management treatments indicate that ecosystem resistance to invasion is largely controlled by long-term EAG abundance (surrogate for seed bank), time since and frequency of wildfire, and plant community interactions. Ecological thresholds associated with enhanced probabilities of wildfire occurrence and invasion rates indicate that relatively little (10%) EAG cover is needed to heighten these risks. Climate change is expected to push 8% of the landscape across invasion thresholds by 2040, impacting 6% of existing sage-grouse habitat, and we identify where fuel breaks may be placed to reduce wildfire risks and invasion. Spatially detailed, timely, and accurate depictions of past, present, and future EAG abundance are vital for the protection of life and property and the continued stewardship of sagebrush ecosystems.

California, Colorado, Idaho, Nevada, Oregon, Utah,↗
USGS1991

Great lakes embryo mortality, edema, and deformities syndrome (glemeds) in colonial fish-eating birds: Similarity to chick-edema disease

Several species of colonial fish-eating birds nesting in the Great Lakes basin Includ-ing herring gulls, common terns and double-crested cormorants, have exhibited chronic impairment of reproduction. In addition to eggshell thinning caused by high levels of DDT and metabolites, the reproductive impairment is characterized by high embryonic and chick mortality , edema, growth retardation, and deformities, hence the name Great Lakes embryo mortality , edema, and deformities syndrome (GLEMEDS). The hypothesis has been advanced that GLEMEDS in colonial fish-eating birds resembles chick-edema disease of poultry and has been caused by exposure to chick- edema active compounds that have a common mode of action through the cytochrome P-448 system. Detailed evidence has been collected from the following three groups of studies on herring gulls in the lower Great Lakes during the early 1970s; Forster’s terns in Green Bay, Wisconsin in 1983; and double-crested cormorants and Caspian terns in various locations in the upper Great Lakes from 1986 onwards. It has proved difficult to establish not only the onset of the disease in the various species at various locations but also the period in which chick-edema active compounds were released. Anecdotal evidence suggested that serious egg mortality . © 1988 by Hemisphere Publishing Corporation.

Illinois, Indiana, Michigan, Wisconsin, Minnesota,↗
USGS2022

Mapping benthic algae and cyanobacteria in river channels from aerial photographs and satellite images: A proof-of-concept investigation on the Buffalo National River, AR, USA

Although rivers are of immense practical, aesthetic, and recreational value, these aquatic habitats are particularly sensitive to environmental changes. Increasingly, changes in streamflow and water quality are resulting in blooms of bottom-attached (benthic) algae, also known as periphyton, which have become widespread in many water bodies of US national parks. Because these blooms degrade visitor experiences and threaten human and ecosystem health, improved methods of characterizing benthic algae are needed. This study evaluated the potential utility of remote sensing techniques for mapping variations in algal density in shallow, clear-flowing rivers. As part of an initial proof-of-concept investigation, field measurements of water depth and percent cover of benthic algae were collected from two reaches of the Buffalo National River along with aerial photographs and multispectral satellite images. Applying a band ratio algorithm to these data yielded reliable depth estimates, although a shallow bias and moderate level of precision were observed. Spectral distinctions among algal percent cover values ranging from 0 to 100% were subtle and became only slightly more pronounced when the data were aggregated to four ordinal levels. A bagged trees machine learning model trained using the original spectral bands and image-derived depth estimates as predictor variables was used to produce classified maps of algal density. The spatial and temporal patterns depicted in these maps were reasonable but overall classification accuracies were modest, up to 64.6%, due to a lack of spectral detail. To further advance remote sensing of benthic algae and other periphyton, future studies could adopt hyperspectral approaches and more quantitative, continuous metrics such as biomass.

Arkansas↗
USGS2008

Canopy structure and atmospheric flows in relation to the δ13C of respired CO 2 in a subalpine coniferous forest

Stable isotopes provide insight into ecosystem carbon cycling, plant physiological processes, atmospheric boundary-layer dynamics, and are useful for the integration of processes over multiple scales. Of particular interest is the carbon isotope content (δ 13 C) of nocturnal ecosystem-respired CO 2 ( δ R ). Recent advances in technology have made it possible to continuously examine the variation in δ R within a forest canopy over relatively long time-scales (months–years). We used tunable diode laser spectroscopy to examine δ R at within- and below-canopy spatial locations in a Colorado subalpine forest (the Niwot Ridge AmeriFlux site). We found a systematic pattern of increased δ R within the forest canopy ( δ R-c ) compared to that near the ground ( δ R-g ). Values of δ R-c were weakly correlated with the previous day's mean maximum daytime vapor pressure deficit (VPD). Conversely, there was a negative but still weak correlation between δ R-g and time-lagged (0–5 days) daily mean soil moisture. The topography and presence of sustained nightly drainage flows at the Niwot Ridge forest site suggests that, on nights with stable atmospheric conditions, there is little mixing of air near the ground with that in the canopy. Atmospheric stability was assessed using thresholds of friction velocity, stability above the canopy, and bulk Richardson number within the canopy. When we selectively calculated δ R-g and δ R-c by removing time periods when ground and canopy air were well mixed, we found stronger correlations between δ R-c and VPD, and δ R-g and soil moisture. This suggests that there may be fundamental differences in the environmental controls on δ R at sub-canopy spatial scales. These results may help explain the wide variance observed in the correlation of δ R with different environmental parameters in other studies.

Colorado↗
USGS2022

Diatoms.org: Supporting taxonomists, connecting communities

Consistent identification of diatoms is a prerequisite for studying their ecology, biogeography, and successful application as environmental indicators. However, taxonomic consistency among observers has been difficult to achieve because taxonomic information is scattered across numerous literature sources, presenting challenges to the diatomist. Firstly, literature is often inaccessible because of cost or its location in journals that are not widely circulated. Secondly, taxonomic revisions of diatoms are taking place faster than floras can be updated. Finally, taxonomic information is often contradictory across literature sources. These issues can be addressed by developing a content creation community dedicated to making taxonomic, ecological, and image-based data freely available for diatom researchers. Diatoms.org represents such a content curation community, providing open, online access to a vast amount of recent and historical information on North American diatom taxonomy and ecology. The content curation community aggregates existing taxonomic information, creates new content, and provides feedback in the form of corrections and notices of literature with nomenclatural changes. The website not only addresses the needs of experienced diatom scientists for consistent identification but is also designed to meet users at their level of expertise, including engaging the lay public in the importance of diatom science. The website now contains over 1000 species pages contributed by over 100 content contributors, from students to established scientists. The project began with the intent to provide accurate information on diatom identification, ecology, and distribution using an approach that incorporates engaging design, user feedback, and advanced data access technology. In retrospect, the project that began as an ‘extended electronic book’ has emerged not only as a means to support taxonomists, but for practitioners to communicate and collaborate, expanding the size of and benefits to the content curation community. In this paper, we outline the development of diatoms.org , document key elements of the project, examine ongoing challenges and consider the unexpected emergent properties, including the value of diatoms.org as a source of data. Ultimately, if the field of diatom taxonomy, ecology, and biodiversity is to be relevant, a new generation of taxonomists needs to be trained and employed using new tools. We propose that diatoms.org is in a key position to serve as a hub of training and continuity for the study of diatom biodiversity and aquatic conditions.

Diatom Research↗
USGS2025

Integrating theory and empirical patterns: Fish body size distributions, life history traits, and environmental flows in streams

Individual size distributions (ISDs) are prominent in ecological research and may support resource managers with ecosystem-scale objectives. We use a database of individual size measurements for US stream fishes to test for direct and indirect effects of traits, flow regimes, and land use on the interspecific ISD exponent. Path analysis indicates that traits have strong, direct effects on ISD. Flow and land use effects on the exponent are largely indirectly mediated by their influences on species traits. ISD exponents increase (abundances of larger-bodied individuals increase, relative to smaller-bodied) when environments favor higher trophic levels, warmer thermal tolerances, and periodic life histories. Alternatively, ISD exponents decrease in systems that favor opportunistic life histories. Our flexible modeling framework that includes direct and indirect effects of traits, flow regimes, and land use on ISD could be expanded to incorporate additional variables that interact with flow (e.g., temperature and physical habitat) to assess of effects of multiple stressors on aquatic ecosystem functioning.

Science Advances↗
USGS2007

Advances and opportunities in assessing contaminant sensitivity of freshwater mussel (unionidae) early life stages

Freshwater mussels (family Unionidae, also referred to as freshwater pearly mussels, unionids, or naiades) are one of North America’s most endangered faunal groups. Near unanimity exists in characterizations of the imperilment of these ecologically, economically, and culturally important bivalve mollusks. Freshwater mussels are a renewable resource supporting a shell industry in the United States valued at $40–50 million annually [1]. In addition to being a food source for aquatic and terrestrial vertebrates, this diverse fauna helps stabilize sediment [2] and provides critical nutrient and energy cycling in streams and lakes by filtering phytoplankton, bacteria, and particulate organic matter from the water column [3]. Thirty-five species of freshwater mussels are extinct [4], 70 species are listed as threatened or endangered under the U.S. Endangered Species Act (www.fws.gov/endangered/wildlife.html), and nearly 180 species are identified as critically imperiled or vulnerable (www.natureserve.org/explorer). Declines in freshwater mussels are not unique to North America [5], but because the taxon reaches its greatest richness here, impacts are especially noteworthy.

Environmental Toxicology and Chemistry↗
USGS2017

Response of bird community structure to habitat management in piñon-juniper woodland-sagebrush ecotones

Piñon ( Pinus spp.) and juniper ( Juniperus spp.) woodlands have been expanding their range across the intermountain western United States into landscapes dominated by sagebrush ( Artemisia spp.) shrublands. Management actions using prescribed fire and mechanical cutting to reduce woodland cover and control expansion provided opportunities to understand how environmental structure and changes due to these treatments influence bird communities in piñon-juniper systems. We surveyed 43 species of birds and measured vegetation for 1–3 years prior to treatment and 6–7 years post-treatment at 13 locations across Oregon, California, Idaho, Nevada, and Utah. We used structural equation modeling to develop and statistically test our conceptual model that the current bird assembly at a site is structured primarily by the previous bird community with additional drivers from current and surrounding habitat conditions as well as external regional bird dynamics. Treatment reduced woodland cover by >5% at 80 of 378 survey sites. However, habitat change achieved by treatment was highly variable because actual disturbance differed widely in extent and intensity. Biological inertia in the bird community was the strongest single driver; 72% of the variation in the bird assemblage was explained by the community that existed seven years earlier. Greater net reduction in woodlands resulted in slight shifts in the bird community to one having ecotone or shrubland affinities. However, the overall influence of woodland changes from treatment were relatively small and were buffered by other extrinsic factors. Regional bird dynamics did not significantly influence the structure of local bird communities at our sites. Our results suggest that bird communities in piñon-juniper woodlands can be highly stable when management treatments are conducted in areas with more advanced woodland development and at the level of disturbance measured in our study.

Forest Ecology and Management↗
USGS2023

Improving ecological data science with workflow management software

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

Methods in Ecology and Evolution↗
USGS2013

Bactericidal efficacy of elevated pH on fish pathogenic and environmental bacteria

Ship ballast water is a recognized medium for transfer and introductions of nonindigenous species. There is a need for new ballast water treatment methods that effectively and safely eliminate or greatly minimize movements of these species. The present study employed laboratory methods to evaluate the bactericidal efficacy of increased pH (pH 10.0–12.0) for exposure durations of up to 72 h to kill a variety of Gram-negative and Gram-positive bacteria including fish pathogens (Aeromonas spp., Yersinia ruckeri, Edwardsiella ictaluri, Serratia liquefaciens, Carnobacterium sp.), other common aquatic-inhabitant bacteria (Serratia marcescens, Pseudomonas fluorescens, Staphylococcus sp., Bacillus sp.) and indicators listed in International Maritime Organization D2 Standards; namely, Vibrio cholera (an environmental isolate from fish), Escherichia coli and Enterococcus faecalis. Volumes of 5 N NaOH were added to tryptic soy broth to obtain desired pH adjustments. Viable cells were determined after 0, 4, 12, 24, 48, and 72 h. Initial (0 h) cell numbers ranged from 3.40 × 10 4 cfu/mL for Bacillus sp. to 2.44 × 10 7 cfu/mL for E. faecalis. The effective endpoints of pH and treatment duration necessary to realize 100% bactericidal effect varied; however, all bacteria tested were killed within 72 h at pH 12.0 or lower. The lowest parameters examined, 4 h at pH 10.0, were bactericidal to V. cholera, E. ictaluri, three of four isolates of E. coli, and (three of four) Aeromonas salmonicida subsp. salmonicida. Bactericidal effect was attained at pH 10.0 within 12 h for the other A. salmonicida subsp. salmonicida, and within 24 h for P. fluorescens, and the remaining E. coli.

Journal of Advanced Research↗
USGS2012

Guidelines for a graph-theoretic implementation of structural equation modeling

Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for an updated definition of the SEM process that subsumes the historical matrix approach under a graph-theory implementation. The implementation is also designed to permit complex specifications and to be compatible with various estimation methods. Finally, they are meant to foster the use of probabilistic reasoning in both retrospective and prospective considerations of the quantitative implications of the results.

Ecosphere↗
USGS2009

Biological community structure on patch reefs in Biscayne National Park, FL, USA

Coral reef ecosystem management benefits from continual quantitative assessment of the resources being managed, plus assessment of factors that affect distribution patterns of organisms in the ecosystem. In this study, we investigate the relationships among physical, benthic, and fish variables in an effort to help explain the distribution patterns of organisms on patch reefs within Biscayne National Park, FL, USA. We visited a total of 196 randomly selected sampling stations on 12 shallow (<10 m) patch reefs and measured physical variables (e.g., substratum rugosity, substratum type) and benthic and fish community variables. We also incorporated data on substratum rugosity collected remotely via airborne laser surveying (Experimental Advanced Airborne Research Lidar—EAARL). Across all stations, only weak relationships were found between physical, benthic cover, and fish assemblage variables. Much of the variance was attributable to a “reef effect,” meaning that community structure and organism abundances were more variable at stations among reefs than within reefs. However, when the reef effect was accounted for and removed statistically, patterns were detected. Within reefs, juvenile scarids were most abundant at stations with high coverage of the fleshy macroalgae Dictyota spp., and the calcified alga Halimeda tuna was most abundant at stations with low EAARL rugosity. Explanations for the overwhelming importance of “reef” in explaining variance in our dataset could include the stochastic arrangement of organisms on patch reefs related to variable larval recruitment in space and time and/or strong historical effects due to patchy disturbances (e.g., hurricanes, fishing), as well as legacy effects of prior residents (“priority” effects).

Florida↗
USGS2012

Toxicity of carbon nanotubes to freshwater aquatic invertebrates

Carbon nanotubes (CNTs) are hydrophobic in nature and thus tend to accumulate in sediments if released into aquatic environments. As part of our overall effort to examine the toxicity of carbon-based nanomaterials to sediment-dwelling invertebrates, we have evaluated the toxicity of different types of CNTs in 14-d water-only exposures to an amphipod ( Hyalella azteca ), a midge ( Chironomus dilutus ), an oligochaete ( Lumbriculus variegatus ), and a mussel ( Villosa iris ) in advance of conducting whole-sediment toxicity tests with CNTs. The results of these toxicity tests conducted with CNTs added to water showed that 1.00g/L (dry wt) of commercial sources of CNTs significantly reduced the survival or growth of the invertebrates. Toxicity was influenced by the type and source of the CNTs, by whether the materials were precleaned by acid, by whether sonication was used to disperse the materials, and by species of the test organisms. Light and electron microscope imaging of the surviving test organisms showed the presence of CNTs in the gut as well as on the outer surface of the test organisms, although no evidence was observed to show penetration of CNTs through cell membranes. The present study demonstrated that both the metals solubilized from CNTs such as nickel and the "metal-free" CNTs contributed to the toxicity.

Environmental Toxicology and Chemistry↗
USGS2014

A comparison of selected diversity, similarity, and biotic indices for detecting changes in benthic-invertebrate community structure and stream quality

Implementation of advanced wastewater treatment at the two municipal wastewater-treatment plants for Indianapolis, Indiana, resulted in substantial improvement in the quality of the receiving stream and significant changes in the benthic-invertebrate community. Diversity, similarity, and biotic indices were compared to determine which indices best reflected changes in the composition of the biota in the river. None of the indices perfectly reflected the changes in river quality or community structure. Similarity indices, especially percentage similarity, exhibit the most promise of the three classes of indices. Diversity indices were least useful, wrongly indicating that water quality deteriorated after the upgrade of the wastewater-treatment plants. The most descriptive tool in analyzing the data was the percentage of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa present. Using a mixture of indices and other analytical tools, such as EPT, in the analysis of biological data will ensure the most effective investigations of water quality.

Archives of Environmental Contamination and Toxico↗
USGS2019

Process-guided deep learning predictions of lake water temperature

The rapid growth of data in water resources has created new opportunities to accelerate knowledge discovery with the use of advanced deep learning tools. Hybrid models that integrate theory with state‐of‐the art empirical techniques have the potential to improve predictions while remaining true to physical laws. This paper evaluates the Process‐Guided Deep Learning (PGDL) hybrid modeling framework with a use‐case of predicting depth‐specific lake water temperatures. The PGDL model has three primary components: a deep learning model with temporal awareness (long short‐term memory recurrence), theory‐based feedback (model penalties for violating conversation of energy), and model pretraining to initialize the network with synthetic data (water temperature predictions from a process‐based model). In situ water temperatures were used to train the PGDL model, a deep learning (DL) model, and a process‐based (PB) model. Model performance was evaluated in various conditions, including when training data were sparse and when predictions were made outside of the range in the training data set. The PGDL model performance (as measured by root‐mean‐square error (RMSE)) was superior to DL and PB for two detailed study lakes, but only when pretraining data included greater variability than the training period. The PGDL model also performed well when extended to 68 lakes, with a median RMSE of 1.65 °C during the test period (DL: 1.78 °C, PB: 2.03 °C; in a small number of lakes PB or DL models were more accurate). This case‐study demonstrates that integrating scientific knowledge into deep learning tools shows promise for improving predictions of many important environmental variables.

Minnesota, Wisconsin↗
USGS2023

Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20

Loss and degradation of sagebrush ( Artemisia spp.) rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western U.S. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (hereinafter, “Needs”) for informing the actions proposed under the five topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse ( Centrocercus urophasianus ), Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.” Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts. This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed four Needs identified under the Climate and Weather topic in the Plan. The topic outlined research Needs broadly focused on understanding the potential effects of climate change on vegetative resilience to inform restoration of sagebrush rangelands. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (hereinafter, “Next Steps”) were either addressed well, partially addressed or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 92 science products that at least partially addressed a Need identified in the Climate and Weather topic. The Needs that were well and partially addressed included: studies of the complex set of climatic relationships that influence sagebrush rangeland restoration and seeding success; the identification of seed collection areas across the range of environmental variability inhabited by target restoration species; and develop predictive models to assess targeted restoration species’ responses to mid-century climatic conditions. The Need addressed poorly was the identification of native plant species, genotypes and ecotypes, and seed mixes that may be resilient to a changing climate. The information provided in this assessment will assist updating the Plan, and can inform updates of other relevant science planning documents as needed.

Open-File Report↗
USGS2026

Hyperspectral narrowband imaging spectroscopy: A new paradigm for Earth observation

This editorial introduces the Special Issue entitled “Hyperspectral Narrowband Imaging Spectroscopy: A New Paradigm for Earth Observation” in the August 2026 issue of Photogrammetric Engineering & Remote Sensing (PE&RS), the flagship journal of the American Society for Photogrammetry and Remote Sensing (ASPRS). This volume represents the fourth dedicated hyperspectral special issue published in PE&RS, following earlier contributions by Thenkabail et al. (2025, 2024a, 2024b), and continues ASPRS’s commitment to advancing cutting‑edge imaging spectroscopy research and its applications across Earth system science. Remote sensing is undergoing one of the most profound transformations in its history. The emergence of hyperspectral narrowband (HNB) imaging spectroscopy data, capable of acquiring hundreds of contiguous, narrow spectral bands, has shifted the discipline from observing Earth in a handful of broad spectral windows to capturing continuous spectral signatures of the Planet. This transition marks a decisive break from the multispectral paradigm that has dominated satellite remote sensing for nearly five decades, driven by the advent of new orbital imaging spectrometers such as EnMAP, PRISMA, and NASA’s EMIT, and by the forthcoming Surface Biology and Geology (SBG) mission ((Pires Silva et al., 2026; Bourriz et al., 2025; Thenkabail et al., 2025; Chabrillat et al., 2024; Aneece et al., 2024; Dave et al., 2024; Thenkabail et al., 2024a; Thenkabail et al., 2024b; Thenkabail, 2024a; Thenkabail, 2024b; Thompson et al., 2022; Kokaly et al., 2022; Aneece & Thenkabail, 2022; Cawse Nicholson et al., 2021; Guanter et al., 2021; Vangi et al., 2021; Thenkabail et al., 2021). These missions (e.g., Table 1) deliver unprecedented spectral fidelity, improved signal to noise ratios, and global coverage capabilities, enabling a new era of quantitative, spectroscopy based Earth observation. Where multispectral broadbands (MBBs) provide only a few discrete measurements along the electromagnetic spectrum, HNB systems deliver rich, diagnostic information that enables scientists to characterize Earth’s surface with unprecedented biochemical, biophysical, and structural detail (Figure 1a, 1b). The implications for environmental monitoring, agriculture, water resources, and mineral exploration are profound. Several overarching themes emerge: • Spectral fidelity matters. The ability to preserve subtle absorption features is essential for mineral mapping, vegetation trait retrieval, and biochemical modeling. • AI and deep learning are indispensable. From destriping to classification, modern analytics must be scalable, label‑efficient, and capable of exploiting the full spectral–spatial richness of HNB data. • Physics‑based and data‑driven approaches must converge. Radiative transfer models such as PROSAIL, enhanced with localized soil parameterizations, remain foundational for biophysical retrievals and model‑based inference. • Dimensionality reduction and feature extraction are critical. Techniques such as L1‑ISOMAP demonstrate that intelligent manifold learning can unlock the structure of fused, high‑dimensional datasets. • Next‑generation architectures must be interactive and multimodal. ICTNet exemplifies the future of hyperspectral classification: hybrid, synergistic, and capable of modeling both local textures and global spectral dependencies.

Photogrammetric Engineering and Remote Sensing (PE↗
USGS2018

Climate Assessments and Scenario Planning (CLASP)

The NE CASC boasts an interdisciplinary array of scientists, from ecologists to biologists, hydrologists to climatologists, each contributing new, original academic research to advance our understanding of the impacts of climate change on wildlife and other natural resources in the Northeast. Needed was an outreach specialist who would interface directly with the management agencies who benefited from this research to aid the integration of this research into their management planning as part of adapting to climate change. A climatologist was preferred to address queries about climate modeling, climate change uncertainties, and other areas of climate science outside the expertise of NE CASC ecologists, biologists, and hydrologists. This person’s activities would include responding to inquiries, presenting climate science concepts at management workshops, gathering managers’ climate science needs, contributing to the climate portion of synthesis reports and other resources for managers, and collaborating with ecologists on interdisciplinary studies of climate change by providing climate data and guidance on interpretation. The objective was to relay and interpret the scientific findings most relevant to managers’ resources of concern and management activities around those resources to guide adjustments to their activities toward better protecting their resources of concern. As an outcome, managers often relied on synthesized climate science to be able to consider how climate trends affect their work, especially those thinking about climate change for the first time in the context of their work. This lays the groundwork for more detailed management-driven science delivery that can aid eventual implementation. Management groups reached by this project include land managers with the National Park Service, state fish and game departments and DNRs, and tribal environmental coordinators.

Report↗