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At least 1,027 records · Page 57Linked to original sources
USGS2017

Enhanced coal-dependent methanogenesis coupled with algal biofuels: Potential water recycle and carbon capture

Many coal beds contain microbial communities that can convert coal to natural gas (coalbed methane). Native microorganisms were obtained from Powder River Basin (PRB) coal seams with a diffusive microbial sampler placed downhole and used as an inoculum for enrichments with different nutrients to investigate microbially-enhanced coalbed methane production (MECoM). Coal-dependent methanogenesis more than doubled when yeast extract (YE) and several less complex components (proteins and amino acids) were added to the laboratory microcosms. Stimulated coal-dependent methanogenesis with peptone was 86% of that with YE while glutamate-stimulated activity was 65% of that with YE, and a vitamin mix had only 33% of the YE stimulated activity. For field application of MECoM, there is interest in identifying cost-effective alternatives to YE and other expensive nutrients. In laboratory studies, adding algal extract (AE) with lipids removed stimulated coal-dependent methanogenesis and the activity was 60% of that with YE at 27 d and almost 90% of YE activity at 1406 d. Analysis of British Thermal Unit (BTU) content of coal (a measure of potential energy yield) from long-term incubations indicated > 99.5% of BTU content remained after coalbed methane (CBM) stimulation with either AE or YE. Thus, the coal resource remains largely unchanged following stimulated microbial methane production. Algal CBM stimulation could lead to technologies that utilize coupled biological systems (photosynthesis and methane production) that sustainably enhance CBM production and generate algal biofuels while also sequestering carbon dioxide (CO 2 ).

International Journal of Coal Geology↗
USGS2022

Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA

Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due to their limited availability and high demand in a wide range of applications and especially in high-technology products. The increased demand and geopolitical pressures motivate the search for alternative sources of REYs, and coal, coal waste, and coal ash are considered as new sources for these critical elements. This research evaluates the REY potential of coals from Indiana (USA). However, although coal data revealed REY potential, it suffered from sparse samples with complete REY measurements. Therefore, we explore the applicability of machine learning (ML) models and data augmentation techniques to demonstrate their applicability to evaluate REY potential in Indiana, and other areas in coal basins, using selected coal parameters (Al2O3, Fe2O3, C, Ash, S, P, Mo, Zn, and As contents) as covariates (indicators). Due to the relatively small sample size with complete REY data in the Indiana Coal Database, two data augmentation techniques (Random Over-Sampling Examples and Synthetic Minority Over-Sampling Technique) were used. Four machine learning algorithms (linear discriminate analysis, support vector machine, random forest, and artificial neural networks) were applied for modeling REY potential as a classification problem. The results show that application of Synthetic Minority Over-Sampling Technique prior to development of the support vector machine (SVM) models generated the best REY classification with an accuracy of 95%. The encouraging results based on Indiana coal data may suggest that a similar approach can be used for other coal basins for screening the locations with REY potential. Those locations then can be targeted for more detailed geochemical surveys to identify most promising areas and evaluate overall REY resources.

Indiana↗
USGS2023

Scanning electron microscopic evaluation of broad ion beam milling effects to sedimentary organic matter: Sputter-induced artifacts or naturally occurring porosity?

Research examining organic-matter hosted porosity has significantly increased during the last decade due to greater focus on understanding hydrocarbon migration and storage in source-rock reservoirs, and technological advances in scanning electron microscopy (SEM) capabilities. The examination of nanometer-scale organic-matter hosted porosity by SEM requires the preparation of exceptionally flat geologic samples beyond the abilities of traditional mechanical polishing, which can deform or otherwise obscure organic surfaces. To meet this demand, broad ion beam (BIB) milling was introduced as a sample preparation technique for SEM petrographic analysis of geologic samples. As with any sample preparation technique, there can be unintended consequences. In this study, we examined the development of nanometer-scale sputter-induced voids caused by BIB milling of thermoset plastic binder material [poly(methyl methacrylate), PMMA] used for the mounting of geologic samples, and artifact sputter-induced voids in the organic matter of Green River Formation and Kimmeridge Clay Formation source rocks. Development of artifact sputter-induced voids was evaluated in relation to variations in the slope of the sample examination surface (0.0–4.9% slope), effectively varying the angle of ion incidence. The results indicate that only minor variations in the angle of ion incidence can generate sputter-induced voids in both PMMA (10.0–386.2 nm diameter sputter-induced voids) and sample sedimentary organic matter (solid bitumen; 12.2–103.6 nm diameter sputter-induced voids). Overall, average artifact pore diameters increased with increasing ion incidence angle within PMMA. Although sputter-induced voids within solid bitumen in the Green River Formation sample were only found in limited extent, the size of these void artifacts falls within the same size range as naturally occurring meso-macroporosity. That is, the pore-like artifacts could easily be misconstrued as naturally developed organic porosity, which is a major concern for SEM-based porosity evaluation methods. This study describes the factors that contribute to the creation of artifact sputter-induced voids, their distinguishing characteristics, and best practices for avoiding the creation of ion-induced artifacts.

International Journal of Coal Geology↗
USGS2024

Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA

Rare earth elements and yttrium (REEs) have a wide range of applications in high- and low-carbon technologies. The strategic significance of REEs has grown due to their expanding applications in manufacturing industries and the constrained availability of these essential resources. This research explores the applicability of machine learning models and their uncertainty for assessing the REE potential in coal beds using various coal parameters as inputs. The work focuses on developing a predictive model based on geological variables, excluding considerations related to potential shifts in the commodities market. The Indiana Coal Quality Database was used as the data source. The promising and unpromising indicators derived from the outlook coefficient of samples from the database were used as the REE potential indicator for machine learning classification models. The filter-based approach with bootstrap was used to evaluate the importance of the coal parameters and their prediction uncertainties. Four machine learning methods (linear discriminant analysis (LDA), random forest (RF), support vector machine (SVM), and artificial neural networks (ANN), a data balancing and augmentation approach (Synthetic Minority Over-sampling Technique), and bootstrap resampling techniques were used for building the models and evaluating their prediction capabilities under uncertainty. It was determined that the SVM bootstrap model with ten-times balanced and augmented data provided superior results compared with other models. Finally, stochastic spatial maps of the REE potential within the coal basin were generated using sequential indicator simulation. The spatial maps of the REE potential showed that a 29% area of the Indiana section of the Illinois coal basin has economic potential of REEs, with 90% confidence.

Indiana↗
USGS2024

Structure and morphology of chars and activated carbons obtained from thermal treatment of coal and biomass origin materials, including their wastes: Results from the ICCP Microscopy of Carbon Materials Working Group

This paper describes the evaluation of petrographic textures in char and activated carbon derived from coal, coal by-products and biomass, formed during carbonization and activation processes. This work represents the results of interlaboratory exercises from 2016 to 2022 of the Microscopy of Carbon Materials Working Group in Commission III of the International Committee for Coal and Organic Petrology. The interlaboratory exercises were run on photomicrograph samples. For textural characterization of carbon materials, the existing American Society for Testing and Materials (ASTM) classification system for metallurgical coke was applied. Morphological differences were evaluated in 29 carbon material types, including 22 char samples, and 7 activated carbon (AC) samples obtained experimentally using conventional direct/indirect and microwave heating technologies. This approach gives an extended view on the identification of microporous carbons, and how a certain heat treatment develops a certain optical texture and structure in a raw material. The requested evaluation of carbon materials was related to their porosity, origin, extent, and characteristics, which are particular to each carbon material type. Because carbon matrices can form a wide range of optical textures during heat treatment it is important to demonstrate which carbon occurrences will have a crucial role in industrial applications dominated by adsorption phenomena. The interlaboratory exercises included 17 participants from 14 laboratories. Four sets of digital black and white and colour photomicrographs were distributed, which in total comprised 184 fields of different types of carbon material. The results were evaluated based on four levels: (i) optical texture (isotropic/anisotropic), (ii) optical type and size (punctiform, mosaic, fiber, ribbon, domain), iii) morphology (porous, non-porous/massive), and (iv) particle origin (precursor type). The statistical method applied to evaluate the results was based on “raw agreement indices”. Comparative analyses of the average values of the level of overall agreement showed homogeneity in the results, the mean value was 89%, with a minimum value of 87% and a maximum value of 91% for those who participated in at least three out of four exercises.

International Journal of Coal Geology↗
USGS2026

Genetic biocontrol strategy considerations for mosquito control in the Pacific Island Countries and Territories

Mosquito-borne diseases pose an existential threat to the health, economies, and unique ecosystems of Pacific Island Countries and Territories (PICTs). The remoteness of these islands, combined with the presence of highly competent mosquito vectors, complicates disease surveillance and vector control efforts. In response, the PICTs have become a focal point for the development and application of Genetic BioControl (GBC) technologies designed to break vector-borne disease transmission cycles. However, the application of GBC tools in this region warrants careful consideration of its unique history, including a legacy of colonialism, and challenges associated with logistic hurdles. Through meaningful community engagement and authentic collaborations, drawing from local knowledge, and building local capacity, the sustainable, efficient, and effective deployment of GBC tools may be achieved.

Current Opinion in Insect Science↗
USGS2022

New frontiers in bird migration research

Bird migrations are impressive behavioral phenomena, representing complex spatiotemporal strategies to balance costs of living while maximizing fitness. The field of bird migration research has made great strides over the past decades, yet fundamental gaps remain. Technologies have sparked a transformation in the study of bird migration research by revealing remarkable insights into the underlying behavioral, cognitive, physiological and evolutionary mechanisms of these diverse journeys. Here, we aim to encourage broad discussions and promote future studies by highlighting research fields that are characterized by major knowledge gaps or conflicting evidence, namely the fields of navigation, social learning, individual development, energetics and conservation. We approach each topic by summarizing the current state of knowledge and provide a future outlook of ideas and state-of-the-art methods to further advance the field. Integrating knowledge across these disciplines will allow us to understand the adaptive abilities of different species and to develop effective conservation strategies in a rapidly changing world.

Current Biology↗
USGS2006

Aquifer composition and the tendency toward scale-deposit formation during reverse osmosis desalination - Examples from saline ground water in New Mexico, USA

Desalination is expected to make a substantial contribution to water supply in the United States by 2020. Currently, reverse osmosis is one of the most cost effective and widely used desalination technologies. The tendency to form scale deposits during reverse osmosis is an important factor in determining the suitability of input waters for use in desalination. The tendency toward scale formation of samples of saline ground water from selected geologic units in New Mexico was assessed using simulated evaporation. All saline water samples showed a strong tendency to form CaCO3 scale deposits. Saline ground water samples from the Yeso Formation and the San Andres Limestone showed relatively stronger tendencies to form CaSO4 2H2O scale deposits and relatively weaker tendencies to form SiO2(a) scale deposits than saline ground water samples from the Rio Grande alluvium. Tendencies toward scale formation in saline ground water samples from the Dockum Group were highly variable. The tendencies toward scale formation of saline waters from the Yeso Formation, San Andres Limestone, and Rio Grande alluvium appear to correlate with the mineralogical composition of the geologic units, suggesting that scale-forming tendencies are governed by aquifer composition and water-rock interaction. ?? 2006 Elsevier B.V. All rights reserved.

Desalination↗
USGS2017

Gene transcription patterns in response to low level petroleum contaminants in Mytilus trossulus from field sites and harbors in southcentral Alaska

The 1989 Exxon Valdez oil spill damaged a wide range of natural resources, including intertidal communities, and post-spill studies demonstrated acute and chronic exposure and injury to an array of species. Standard toxicological methods to evaluate petroleum contaminants have assessed tissue burdens, with fewer assays providing indicators of health or physiology, particularly when contaminant levels are low and chronic. Marine mussels are a ubiquitous and crucial component of the nearshore environment, and new genomic technologies exist to quantify molecular responses of individual mussels to stimuli, including exposure to polycyclic aromatic hydrocarbons (PAHs). We used gene-based assays of exposure and physiological function to assess chronic oil contamination using the Pacific blue mussel, Mytilus trossulus . We developed a diagnostic gene transcription panel to investigate exposure to PAHs and other contaminants and its effects on mussel physiology and health. During 2012–2015, we analyzed mussels from five field sites in western Prince William Sound, Alaska, with varying oil histories from the 1989 Exxon Valdez oil spill, and from three boat harbors in the area. Gene transcription patterns of mussels from harbors were consistent with elevated exposure to PAHs or other contaminants, whereas transcription patterns of mussels sampled from shorelines in areas affected by the oil spill indicated no PAH exposure.

Alaska↗
USGS2015

Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review

The study of mass and energy transfer across landscapes has recently evolved to comprehensive considerations acknowledging the role of biota and humans as geomorphic agents, as well as the importance of small-scale landscape features. A contributing and supporting factor to this evolution is the emergence over the last two decades of technologies able to acquire high resolution topography (HRT) (meter and sub-meter resolution) data. Landscape features can now be captured at an appropriately fine spatial resolution at which surface processes operate; this has revolutionized the way we study Earth-surface processes. The wealth of information contained in HRT also presents considerable challenges. For example, selection of the most appropriate type of HRT data for a given application is not trivial. No definitive approach exists for identifying and filtering erroneous or unwanted data, yet inappropriate filtering can create artifacts or eliminate/distort critical features. Estimates of errors and uncertainty are often poorly defined and typically fail to represent the spatial heterogeneity of the dataset, which may introduce bias or error for many analyses. For ease of use, gridded products are typically preferred rather than the more information-rich point cloud representations. Thus many users take advantage of only a fraction of the available data, which has furthermore been subjected to a series of operations often not known or investigated by the user. Lastly, standard HRT analysis work-flows are yet to be established for many popular HRT operations, which has contributed to the limited use of point cloud data. In this review, we identify key research questions relevant to the Earth-surface processes community within the theme of mass and energy transfer across landscapes and offer guidance on how to identify the most appropriate topographic data type for the analysis of interest. We describe the operations commonly performed from raw data to raster products and we identify key considerations and suggest appropriate work-flows for each, pointing to useful resources and available tools. Future research directions should stimulate further development of tools that take advantage of the wealth of information contained in the HRT data and address the present and upcoming research needs such as the ability to filter out unwanted data, compute spatially variable estimates of uncertainty and perform multi-scale analyses. While we focus primarily on HRT applications for mass and energy transfer, we envision this review to be relevant beyond the Earth-surface processes community for a much broader range of applications involving the analysis of HRT.

Earth-Science Reviews↗
USGS2013

Capacity, pressure, demand, and flow: A conceptual framework for analyzing ecosystem service provision and delivery

Ecosystem services provide an instinctive way to understand the trade-offs associated with natural resource management. However, despite their apparent usefulness, several hurdles have prevented ecosystem services from becoming deeply embedded in environmental decision-making. Ecosystem service studies vary widely in focal services, geographic extent, and in methods for defining and measuring services. Dissent among scientists on basic terminology and approaches to evaluating ecosystem services create difficulties for those trying to incorporate ecosystem services into decision-making. To facilitate clearer comparison among recent studies, we provide a synthesis of common terminology and explain a rationale and framework for distinguishing among the components of ecosystem service delivery, including: an ecosystem's capacity to produce services; ecological pressures that interfere with an ecosystem's ability to provide the service; societal demand for the service; and flow of the service to people. We discuss how interpretation and measurement of these four components can differ among provisioning, regulating, and cultural services. Our flexible framework treats service capacity, ecological pressure, demand, and flow as separate but interactive entities to improve our ability to evaluate the sustainability of service provision and to help guide management decisions. We consider ecosystem service provision to be sustainable when demand is met without decreasing capacity for future provision of that service or causing undesirable declines in other services. When ecosystem service demand exceeds ecosystem capacity to provide services, society can choose to enhance natural capacity, decrease demand and/or ecological pressure, or invest in a technological substitute. Because regulating services are frequently overlooked in environmental assessments, we provide a more detailed examination of regulating services and propose a novel method for quantifying the flow of regulating services based on estimates of ecological work. We anticipate that our synthesis and framework will reduce inconsistency and facilitate coherence across analyses of ecosystem services, thereby increasing their utility in environmental decision-making.

Ecological Complexity↗
USGS2007

Accumulation of metals in fish from lead-zinc mining areas of southeastern Missouri, USA

The potential effects of proposed lead-zinc mining in an ecologically sensitive area were assessed by studying a nearby mining district that has been exploited for about 30 yr under contemporary environmental regulations and with modern technology. Blood and liver samples representing fish of three species (largescale stoneroller, Campostoma oligolepis, n=91; longear sunfish, Lepomis megalotis, n=105; and northern hog sucker, Hypentelium nigricans, n=20) were collected from 16 sites representing a range of conditions relative to lead-zinc mining and ore beneficiation in southeastern Missouri. Samples were analyzed for lead, zinc, and cadmium, and for a suite of biomarkers (reported in a companion paper). A subset of the hog sucker (n=9) representing three sites were also analyzed for nickel and cobalt. Blood and liver lead concentrations were highly correlated (r=0.84-0.85, P < 0.01) in all three species and were significantly (ANOVA, P < 0.01) greater at sites < 10 km downstream of active lead-zinc mines and mills and in a historical lead-zinc mining area than at reference sites, including a site in the area proposed for new mining. Correlations between blood and liver cadmium concentrations were less evident than for lead but were nevertheless statistically significant (r=0.26-0.69, P < 0.01-0.07). Although blood and liver cadmium concentrations were highest in all three species at sites near mines, within-site variability was greater and mining-related trends were less evident than for lead. Blood and liver zinc concentrations were significantly correlated only in stoneroller (r=0.46, P < 0.01) and mining-related trends were not evident. Concentrations of cobalt and nickel in blood and liver were significantly higher (ANOVA, P < 0.01) at a site near an active mine than at a reference site and a site in the historical lead-zinc mining area. These findings confirm previous studies indicating that lead and other metals are released to streams from active lead-zinc mines and are available for uptake by aquatic organisms. ?? 2006 Elsevier Inc. All rights reserved.

Ecotoxicology and Environmental Safety↗
USGS2017

AnimalFinder: A semi-automated system for animal detection in time-lapse camera trap images

Although the use of camera traps in wildlife management is well established, technologies to automate image processing have been much slower in development, despite their potential to drastically reduce personnel time and cost required to review photos. We developed AnimalFinder in MATLAB® to identify animal presence in time-lapse camera trap images by comparing individual photos to all images contained within the subset of images (i.e. photos from the same survey and site), with some manual processing required to remove false positives and collect other relevant data (species, sex, etc.). We tested AnimalFinder on a set of camera trap images and compared the presence/absence results with manual-only review with white-tailed deer ( Odocoileus virginianus ), wild pigs ( Sus scrofa ), and raccoons ( Procyon lotor ). We compared abundance estimates, model rankings, and coefficient estimates of detection and abundance for white-tailed deer using N-mixture models. AnimalFinder performance varied depending on a threshold value that affects program sensitivity to frequently occurring pixels in a series of images. Higher threshold values led to fewer false negatives (missed deer images) but increased manual processing time, but even at the highest threshold value, the program reduced the images requiring manual review by ~ 40% and correctly identified > 90% of deer, raccoon, and wild pig images. Estimates of white-tailed deer were similar between AnimalFinder and the manual-only method (~ 1–2 deer difference, depending on the model), as were model rankings and coefficient estimates. Our results show that the program significantly reduced data processing time and may increase efficiency of camera trapping surveys.

Ecological Informatics↗
USGS2019

Comparison of attraction, entrance and passage of downstream migrant American eels (Anguilla rostrata) through airlift and siphon deep entrance bypass systems

Downstream migrating anguillid eels face many barriers including turbines and pumps at impoundments for water abstraction, power generation and water level control, when attempting to exit the freshwater catchment to reach spawning grounds. Multiple eel species worldwide are facing different levels of endangerment and alleviating the impacts of barriers to migration is essential to allow completion of the life cycle. Deep bypass systems with entrances located near the riverbed hold some promise for increased effectiveness compared to traditional downstream guidance and bypass facilities with entrances near the surface, as eels typically occupy the bottom of the water column. Here we evaluate two deep entrance bypass designs; an airlift (the Conte Airlift) and a conventional gravity siphon of the same entrance dimensions. Tests were performed using migratory silver-phase American eels ( Anguilla rostrata ), at night, in a simulated forebay environment. Passage performance was monitored over a 3 h test period using both PIT (passive integrated transponder) tag and video recording equipment. Entrance velocity was fixed at 1.2 m s −1 in each of 8 test runs with cohort size fixed in six runs at 14 and in two runs at 42. Test eels readily located, entered and passed both bypass designs. Differences in performance metrics between the airlift and siphon were not statistically significant ( P > 0.05) with linked mean values of 74.5%, 90.5% and 100%, respectively. Eel length did not affect passage speed ( P > 0.05) or slip ratio, i.e., the measured eel velocity relative to fluid velocity. The slip ratio was, however, greater in the siphon than in the airlift ( P < 0.01) within identical vertical upflow sections of the test equipment. Siphon slip ratios in the upflow vertical section were comparable to those established for the horizontal and downflow sections. Fish density did not affect attraction and passage through the airlift or siphon. No mortality or signs of injury were observed on any of the test eels through a 48 h post-test observation period. Both airlift and siphon downstream bypass systems show promise as effective technologies for protection of downstream migrating eels at a variety of water diversion or hydroelectric sites that pose threats of impingement, entrainment, and turbine mortality.

Massachusetts↗
USGS2017

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources

Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking water sources because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection. In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentinel-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 ha in area. Results from this study show that 5.6% of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7% of waterbodies were resolvable when a three by three pixel (3 × 3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3 × 3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization’s (WHO) high threshold for risk of 100,000 cells mL −1 . The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1%) and Grand Lake St. Marys, OH (83%) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.

Florida, Ohio↗
USGS2020

Acoustic space occupancy: Combining ecoacoustics and lidar to model biodiversity variation and detection bias across heterogeneous landscapes

There is global interest in quantifying changing biodiversity in human-modified landscapes. Ecoacoustics may offer a promising pathway for supporting multi-taxa monitoring, but its scalability has been hampered by the sonic complexity of biodiverse ecosystems and the imperfect detectability of animal-generated sounds. The acoustic signature of a habitat, or soundscape, contains information about multiple taxa and may circumvent species identification, but robust statistical technology for characterizing community-level attributes is lacking. Here, we present the Acoustic Space Occupancy Model, a flexible hierarchical framework designed to account for detection artifacts from acoustic surveys in order to model biologically relevant variation in acoustic space use among community assemblages. We illustrate its utility in a biologically and structurally diverse Amazon frontier forest landscape, a valuable test case for modeling biodiversity variation and acoustic attenuation from vegetation density. We use complementary airborne lidar data to capture aspects of 3D forest structure hypothesized to influence community composition and acoustic signal detection. Our novel analytic framework permitted us to model both the assembly and detectability of soundscapes using lidar-derived estimates of forest structure. Our empirical predictions were consistent with physical models of frequency-dependent attenuation, and we estimated that the probability of observing animal activity in the frequency channel most vulnerable to acoustic attenuation varied by over 60%, depending on vegetation density. There were also large differences in the biotic use of acoustic space predicted for intact and degraded forest habitats, with notable differences in the soundscape channels predominantly occupied by insects . This study advances the utility of ecoacoustics by providing a robust modeling framework for addressing detection bias from remote audio surveys while preserving the rich dimensionality of soundscape data, which may be critical for inferring biological patterns pertinent to multiple taxonomic groups in the tropics. Our methodology paves the way for greater integration of remotely sensed observations with high-throughput biodiversity data to help bring routine, multi-taxa monitoring to scale in dynamic and diverse landscapes.

Mato Grosso↗
USGS2023

Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data

The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl ( Strix occidentalis caurina ) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km 2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl ( Strix varia ), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.

Oregon↗
USGS2017

Simulating the effects of management practices on cropland soil organic carbon changes in the Temperate Prairies Ecoregion of the United States from 1980 to 2012

Understanding the effects of management practices on soil organic carbon (SOC) is important for designing effective policies to mitigate greenhouse gas emissions in agriculture. In the Midwest United States, management practices in the croplands have been improved to increase crop production and reduce SOC loss since the 1980s. Many studies of SOC dynamics in croplands have been performed to understand the effects of management, but the results are still not conclusive. This study quantified SOC dynamics in the Midwest croplands from 1980 to 2012 with the General Ensemble Biogeochemical Modelling System (GEMS) and available management data. Our results showed that the total SOC in the croplands decreased from 1190 Tg C in 1980 to 1107 TgC in 1995, and then increased to 1176 TgC in 2012. Continuous cropping and intensive tillage may have driven SOC loss in the early period. The increase of crop production and adoption of conservation tillage increased the total SOC so that the decrease in the total SOC stock after 32 years was only 1%. The small change in average SOC did not reflect the large spatial variations of SOC change in the region. Major SOC losses occurred in the north and south of the region, where SOC baseline values were high and cropland production was low. The SOC gains took place in the central part of the region where SOC baseline values were moderate and cropland production was higher than the other areas. We simulated multiple land-use land-cover (LULC) change scenarios and analyzed the results. The analysis showed that among all the LULC changes, agricultural technology that increased cropland production had the greatest impact on SOC changes, followed by the tillage practices, changes in crop species, and the conversions of cropland to other land use. Information on management practice induced spatial variation in SOC can be useful for policy makers and farm managers to develop long-term management strategies for increasing SOC sequestration in different areas.

Ecological Modelling↗