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DOE OSTI2022

Conflicts of Greens’ in Renewable Energy Landscapes: Case Studies and a Planning Framework

Reducing greenhouse gas emissions (GHG) through renewable energy deployment is a goal for many cities and nations to mitigate the effects of a rapidly changing climate while securing energy needs. Given national and state level policies on green energy to achieve GHG reduction targets, localities are considering utility-scale renewable energy (USRE) facilities on remote lands, rural areas, oceans, coastal waters and large rivers to meet the energy needs for urban residents and industries. Although these USRE facilities generate much “greener” electricity than fossil fuel power plants, locating them can pose conflicts with wildlife, including endangered, threatened and/or special status species, and the habitats that support wildlife populations (Brunette et al., 2013; Gasparatos et al. 2016; Mulvaney 2017), which lead to a “Conflict of Greens” (Ko et al., 2011). In addition to ecological impacts, conflicts over social and cultural resources in local communities lead to concerns over environmental justice, in this context “energy justice,” where negative environmental, social, and economic impacts of energy projects fall more heavily upon marginalized, vulnerable, or indigenous communities. The Pacific Rim region is a center of major and growing economies, and it has become a battlefield for competing “green” objectives. In addition to progressive renewable energy goals, such as in California, Hawaii, and Taiwan, countries around the Pacific Rim have the majority of the growth in manufacturing of wind and solar energy devices and also some of the highest levels of renewables deployment with China, India, and the US leading the way in wind and solar installations. Developing renewable energy source in the ocean such as offshore wind, tidal, and wave energy, are beginning to add to this mix. Given this challenge, the APRU SCL energy working group provides six case studies that address questions about the “Conflict of Greens” across the Pacific Rim including South Korea, Taiwan, and the United States (California, Hawaii, and Massachusetts). The literature review highlights the emerging ecological, social, and economic aspects of conflicts over siting renewables on the landscape. Using case studies, we examine the trial and errors in least-conflict spatial planning, data collection and analysis, public participation in decision-making, mitigation, social planning for energy transitions, and multi-scalar approaches. Lastly, we recommend interdisciplinary policy, planning, and design actions for sustainable energy landscapes across the Pacific Rim and beyond.

green versus green, renewable energy↗
DOE OSTI2020

Past and present disturbances generate spatial variation in seed predation

Seed survival is a key process for plant populations; variation in the activity and abundance of animals that consume seeds can lead to dramatic shifts in seed fate. Because granivores may respond to contemporary disturbance as well as to enduring changes in habitats caused by past disturbances, understanding seed fate requires studies capable of evaluating how past and present disturbances modify granivore communities, foraging activity, and ultimately, seed predation. Historic agricultural land use and contemporary canopy harvesting are widespread disturbances that could generate large-scale patterns of seed fate by modifying environmental characteristics that determine granivore identity and behavior. Here, to evaluate whether land-use history and canopy harvesting affect seed–animal interactions, we conducted an experiment distributed across 80,000 ha of longleaf pine woodlands that coupled large-scale canopy harvesting at seven 4-ha sites containing both post-agricultural land use and nonagricultural land use in South Carolina, United States. We deployed a total of 28,000 nail-tagged seeds and recovered the tags to quantify seed fate. Past agricultural land use and contemporary canopy harvesting interacted to affect the rate of seed predation. Seed predation rates in harvested sites depended on land-use history: Seed predation was 30% lower in post-agricultural plots than in nonagricultural plots. This interaction was driven by the differential effect of land-use history and canopy harvesting on rodent activity. Camera traps revealed that Sigmodon hispidus only foraged in harvested plots and was most active in nonagricultural plots. In harvested plots, seed removal increased with S. hispidus activity. In unharvested plots, seed removal increased with Sciurus niger activity, but S. niger was not affected by land-use history. In finding that land-use history and canopy harvesting determine the outcomes of seed–animal interactions, we show that understanding patterns of seed predation is contingent upon the interplay of disturbances in both the distant past and recent past. These results suggest that patterns of past land use and present land use may help reconcile the considerable variation in seed fate observed in ecological communities.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Using low volume eDNA methods to sample pelagic marine animal assemblages

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380–1800 mL) collected at depths of 0–2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Switchgrass Best Management Practices for Biofuel Production

Switchgrass is a perennial C 4 grass native to North America and broadly adaptable across the U.S. Its high productivity, low input requirements, and ability to deliver significant ecosystem services benefits, including carbon sequestration, soil conservation, and wildlife habitat, make it well-suited for cultivation on marginal lands. Achieving the U.S. Department of Energy’s projected potential of 1 billion dry tons of biomass annually by 2050 – with switchgrass contributing up to 230 million tons – will require a transition to large-scale, commercial production. This technical guide was developed to provide decision-makers with current best management practices (BMPs) for establishing, managing, and harvesting bioenergy switchgrass at scale on marginal lands across the U.S. Midwest and Great Plains. Drawing extensively on previous field research and insights from the five-year 'Next-Generation Feedstocks for the Emerging Bioeconomy' project – funded by the U.S. Department of Energy’s Bioenergy Technologies Office – this guide provides practical strategies for scaling up switchgrass production to meet the demands of the growing bioeconomy.

Lee, D.K.↗
DOE OSTI2020

Defining the Environmental Adaptations of Genus Devosia: Insights into its Expansive Short Peptide Transport System and Positively Selected Genes

Devosia are well known for their dominance in soil habitats contaminated with various toxins and are best characterized for their bioremediation potential. In this study, we compared the genomes of 27 strains of Devosia with aim to understand their metabolic abilities. The analysis revealed their adaptive gene repertoire which was bared from 52% unique pan-gene content. A striking feature of all genomes was the abundance of oligo- and di-peptide permeases (oppABCDF and dppABCDF) with each genome harboring an average of 60.7±19.1 and 36.5±10.6 operon associated genes respectively. Apart from their primary role in nutrition, these permeases may help Devosia to sense environmental signals and in chemotaxis at stressed habitats. Through sequence similarity network analyses, we identified 29 Opp and 19 Dpp sequences that shared very little homology with any other sequence suggesting an expansive short peptidic transport system within Devosia. The substrate determining components of these permeases viz. OppA and DppA further displayed a large diversity that separated into 12 and 9 homologous clusters respectively in addition to large number of isolated nodes. We also dissected the genome scale positive evolution and found genes associated with growth (exopolyphosphatase, HesB_IscA_SufA family protein), detoxification (moeB, nifU-like domain protein, alpha/beta hydrolase), chemotaxis (cheB, luxR) and stress response (phoQ, uspA, luxR, sufE) were positively selected. The study highlights the genomic plasticity of the Devosia spp. for conferring adaptation, bioremediation and the potential to utilize a wide range of substrates. The widespread toxin-antitoxin loci and ‘open’ state of the pangenome provided evidence of plastic genomes and a much larger genetic repertoire of the genus which is yet uncovered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tradeoffs between phenotypic plasticity and local adaptation influence the ecophysiology of the moss, Sphagnum magellanicum

Bryophytes are a diverse plant group and are functionally different from vascular plants. Yet, their peculiarities are rarely considered in the theoretical frameworks for plants. Currently, we lack information about the magnitude and the importance of intraspecific variability in the ecophysiology of bryophytes and how these might translate to local adaptation—a prerequisite for adaptive evolution. Capitalizing on two ecologically distinct (hummock and hollow) phenotypes of Sphagnum magellanicum, we explored the magnitude and pattern of intraspecific variability in this species and asked whether the environmental-mediated changes in shoot and physiological traits are due to phenotypic plasticity or local adaptation. Size, pigmentation, and habitat type that distinguished the phenotypes in the field did not influence the trait responses under a transplant and factorial experiment. In addition, the magnitude and pattern of trait variability (e.g., branch, stem and capitulum mass) changed with the treatments, which suggest that trait responses were due largely to phenotypic plasticity. The trait responses also suggest that the ecophysiological needs for mosses to grow in clumps, where they maintain a uniform growth may have an overriding effect over the potential for a fixed adaptive response to environmental heterogeneity, which would constrain local adaptation. In this paper, we conclude that extending the trait-based framework to mosses or making comparisons between mosses and vascular plants under any theoretical framework would only be meaningful to the extent that growth form and dispersal strategies are considered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Phoresy in animals: review and synthesis of a common but understudied mode of dispersal

Phoresy is a type of interaction in which one species, the phoront, uses another species, the dispersal host, for transportation to new habitats or resources. Despite being a widespread behaviour, little is known about the ecology and evolution of phoresy. Our goal is to provide a comprehensive review of phoretic dispersal in animals and to bring renewed attention to this subject. We surveyed literature published between 1900 and 2020 to understand the extent of known higher-level taxonomic diversity (phyla, classes, and orders) and functional aspects of animals that use phoretic dispersal. Species dispersing phoretically have been observed in at least 13 animal phyla, 25 classes, and 60 orders. The majority of known phoronts are arthropods (Phylum Euarthropoda) in terrestrial habitats, but phoronts also occur in freshwater and marine environments. Marine phoronts may be severely under-represented in the literature due to the relative difficulty of studying these systems. Phoronts are generally small with low mobility and use habitats or resources that are ephemeral and/or widely dispersed. Many phoronts are also parasites. In general, animals that engage in phoresy use a wide variety of morphological and behavioural traits for locating, attaching to, and detaching from dispersal hosts, but the exact mechanisms behind these activities are largely unknown. In addition to diversity, we discuss the evolution of phoresy including the long-standing idea that it can be a precursor to parasitism and other forms of symbioses. To conclude, we suggest several areas of future research to improve our understanding of phoresy and its ecological and evolutionary significance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Coastal Acoustic Buoy for Offshore Wind: Project Synthesis

The population of North Atlantic right whales is critically endangered and their habitat overlaps with offshore windfarm leases. It is therefore imperative that effective mitigation strategies be used to avoid impacts on right whales during the construction of offshore windfarms. The Department of Energy issued FOA Number DE-FOA-0001924 to encourage the development of technology that could monitor large exclusion zones for right whales in order to mitigate potential impact of construction noise on right whales. This report summarizes the past two years of the development and evaluation of the Coastal Acoustic Buoy for Offshore Wind (CABOW) project which aimed to develop technology to monitor large exclusion zones for North Atlantic right whales. Over the course of the project SMRU Consulting have implemented a rigorous design process including comparison of different approaches (e.g., single sensor vs multiple sensors), as well as consideration of placement and timing of acoustic monitoring. We have evaluated critical components of the CABOW system including, reliability, detection range, and bearing accuracy in areas adjacent to offshore windfarm leases in Maryland by conducting 3,536 playbacks of simulated right whale upcalls. The maximum call detection range was 7.5 km when noise was 99 dB re 1µPa rms (50-225 Hz), but this reduced to < 1 km when ambient noise levels were high. Our detection probability in the field was measured as a function of range as well as the source-to-noise level ratio allowing us to build a model to predict the probability of detection under various scenarios (sample size: 3,536 calls x 5 buoys = 17,680). The median bearing error was -0.25° but this is likely an underestimate of error due to experimental design. Using the published recall and precision of the two detectors we implemented in the CABOW system, we estimate that at a recall of 80%, our precision was > 80%, within the range of what we were aiming for in this project. To estimate our exclusion zone false negative and false positive rates, we built a simulation model using the empirical data from our field trial. We modelled three to nine CABOW units placed on the 10 km exclusion zone and estimated our false negative rate to be 1% or less (which was our project goal) and our false positive rate to be between seven and nine percent, slightly above our goal of 5%. However, we also modelled an equivalent PAM system that does not have bearing capabilities and found the false positive rates for that system to be six to eight times higher than the CABOW rate. This higher false positive rate of PAM systems with low spatial information could have significant cost repercussions for offshore wind developers by adding work shutdowns or delays without providing additional protection for right whales. The model we built allows us to explore the placement of PAM systems under various scenarios and will thus help facilitate planning of PAM mitigation systems to meet NOAA Incidental Harassment Authorizations for specific windfarms. We achieved an average system uptime of 98.3%, just below our goal of 99%. The issues that caused these short losses of data have been identified and fixed. Right whale detections and audio clips were typically transferred via radio from the buoys to the base station in two to four seconds. We therefore believe we have developed a highly robust real-time PAM system. Based on the above, we feel we have achieved the stated funding goal of developing a cost-effective and robust real-time PAM system that enables the monitoring of large exclusion zones for right whales during the constructions of offshore windfarms. This should lead to decreased costs and risks for the offshore wind sector while providing robust mitigation for right whales. It is important to state that PAM mitigation will need to be implemented with other mitigation strategies (e.g., visual observers) to provide a complete mitigation strategy to ensure that any effects on right whales from offshore windfarm construction is minimized.

17 WIND ENERGY↗
DOE OSTI2022

A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion

Abstract. Rivers and river habitats around the world are under sustained pressure from human activities and the changing global environment. Our ability to quantify and manage the river states in a timely manner is critical for protecting the public safety and natural resources. In recent years, vector-based river network models have enabled modeling of large river basins at increasingly fine resolutions, but are computationally demanding. This work presents a multistage, physics-guided, graph neural network (GNN) approach for basin-scale river network learning and streamflow forecasting. During training, we train a GNN model to approximate outputs of a high-resolution vector-based river network model; we then fine-tune the pretrained GNN model with streamflow observations. We further apply a graph-based, data-fusion step to correct prediction biases. The GNN-based framework is first demonstrated over a snow-dominated watershed in the western United States. A series of experiments are performed to test different training and imputation strategies. Results show that the trained GNN model can effectively serve as a surrogate of the process-based model with high accuracy, with median Kling–Gupta efficiency (KGE) greater than 0.97. Application of the graph-based data fusion further reduces mismatch between the GNN model and observations, with as much as 50 % KGE improvement over some cross-validation gages. To improve scalability, a graph-coarsening procedure is introduced and is demonstrated over a much larger basin. Results show that graph coarsening achieves comparable prediction skills at only a fraction of training cost, thus providing important insights into the degree of physical realism needed for developing large-scale GNN-based river network models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Potential environmental effects of deepwater floating offshore wind energy facilities

Over the last few decades, the offshore wind energy industry has expanded its scope from turbines mounted on fixed platforms driven into the seafloor and standing in less than 50 meters of water, to floating turbines moored in 120 meters of water, to prospecting the development of floating turbines moored in ~1000 meters of water. Since there are few prototype turbines and mooring systems of these deepwater, floating offshore wind energy facilities (OWFs) currently deployed, their effects on the marine environment are largely unknown. Using the available scientific literature concerning appropriate analogs, this study provides the first synthesis of the potential environmental effects of deepwater, floating OWFs during operation, as well as potential mitigation measures to some of the risks. Potential effects we identify and evaluate include changes to atmospheric and oceanic dynamics, electromagnetic fields, habitat alterations, noise, structural impediments, and changes to water quality that could affect a variety of marine species across trophic levels. Our synthesis suggests that many of these potential effects could be mitigated to pose a low risk to the marine environment if developers adopt appropriate mitigation strategies and best-practice protocols. This review takes the necessary first steps in summarizing the available information on the potential environmental effects of deepwater, floating OWFs and can serve as a valuable reference document for marine scientists and engineers, the energy industry, permitting agencies and regulators of the energy industry, project developers, and concerned stakeholders such as coastal residents, conservationists, and fisheries.

Farr, Hayley K.↗
DOE OSTI2022

Soil viruses: Understudied agents of soil ecology

Over the past couple decades there has been intense exploration of the soil microbiome using modern sequencing and bioinformatics approaches. These studies have revealed a vast diversity of microorganisms across a variety of habitats (Thompson et al., 2017) and how differences in the environment, for example with climate change, influence the soil microbial community composition (Jansson and Hofmockel, 2020). The focus of these studies has primarily been on microbial cellular organisms, including bacteria, archaea and fungi. By contrast, in depth study of soil viruses has been largely neglected, until recently. There are several reasons that soil viruses are less studied, including difficulties with extraction of viruses from soil particles, difficulties with classification of soil viruses based on microscopic imaging, and reliance on the small proportion of microbial hosts that can be cultivated. Now that comprehensive soil metagenomes are available the current trend has been to survey the metagenomes for viral sequences. This approach has revealed that soil viruses are incredibly abundant, highly diverse, and largely uncharacterized (Paez-Espino et al., 2016). This so-called ‘viral dark matter’ presents an incredible research opportunity for the future. Here I will highlight some of these potential research avenues based on what is known to date.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A comparison of cost and quality of three methods for estimating density for wild pig (Sus scrofa)

A critical element in efective wildlife management is monitoring the status of wildlife populations; however, resources to monitor wildlife populations are typically limited. We compared cost efectiveness of three common population estimation methods (i.e. non-invasive DNA sampling, camera sampling, and sampling from trapping) by applying them to wild pigs (Sus scrofa) across three habitats in South Carolina, U.S.A where they are invasive. We used mark-recapture analyses for fecal DNA sampling data, spatially-explicit capture-recapture analyses for camera sampling data, and a removal analysis for removal sampling from trap data. Density estimates were similar across methods. Camera sampling was the least expensive, but had large variances. Fecal DNA sampling was the most expensive, although this technique generally performed well. We examined how reductions in efort by method related to increases in relative bias or imprecision. For removal sampling, the largest cost savings while maintaining unbiased density estimates was from reducing the number of traps. For fecal DNA sampling, a reduction in efort only minimally reduced costs due to the need for increased lab replicates while maintaining high quality estimates. For camera sampling, efort could only be marginally reduced before inducing bias. We provide a decision tree for researchers to help make monitoring decisions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗
DOE OSTI2022

Modern analogs for understanding pollen-vegetation dynamics in a Mediterranean mosaic landscape (Balearic Islands, Western Mediterranean)

This paper presents the study of modern pollen analogs from the Balearic Islands. While similar studies have been largely applied to mainland areas, research focused on modern vegetation dynamics on Mediterranean islands remains very rare. In this research, we combine vegetation surveys, pollen analysis and multivariate statistics to understand landscape composition. The main objectives of are: (1) to examine pollen-vegetation relationships in relation to environmental and land-use variables; (2) to understand modern pollen representation in a mosaic landscape structure; and (3) to propose pollen indicators that characterize the primary vegetation types from the Balearic Islands to better interpret past pollen records in Mediterranean island environments. Pollen results and Redundancy Analysis (RDA) distinguish three major groups: (a) Holm oak and box formations; (b) maquis and garrigues; and (c) anthropogenic and open habitats. Landscape form, mean decadal rainfall, mean decadal temperature, fire activity, trampling, slope percentage, wet/flooded soil, saline soil, distance to agropastoral cells, gHM index, domestic herbivory presence, agropastoral use, and soil type are the major variables explaining modern pollen assemblage variation in our research. Poaceae undiff., Plantago sp., Apiaceae undiff., Cerealia-t, and Cichorieae are highly correlated to human activities but should be interpreted cautiously when occurring in low values. Quercus ilex-t, Hypericum, and Buxus are correlated to humid locations while Pistacia, Pinus, Juniperus-t, and Olea to high mean decadal temperatures. Our study indicates how pollen analysis and multivariate analysis are powerful tools for characterizing the mosaic landscape, with special focus on the main vegetation types of the Balearic Islands.

Geology↗
DOE OSTI2020

Artificial Intelligence and Computer Vision for Cost-Effective Benthic Habitat Characterizations

Machine learning applied to computer vision and pattern recognition is a type of artificial intelligence that has advanced rapidly in the last 10 to 15 years, spurred forward by breakthroughs in deep convolutional neural networks. These state-of-the-art methods are poised to become widely used in environmental monitoring applications as a result of the increasing abundance of data available from different imaging platforms (e.g., fixed-point cameras, drone surveys, high-resolution satellite data) that can be analyzed to observe, model, and understand environmental conditions. Computer vision and pattern recognition (CVPR) tools advance our ability to use imagery and camera-based tools in cost-effective ways for environmental monitoring. Although these techniques offer great potential, some challenges remain, such as the need for large sets of labeled images for model training and validation and optimized hardware and software to ensure that the models can be trained effectively and in a reasonable amount of time. Here, we have overcome many of these rate-limiting challenges by using a diverse image library built across multiple projects coupled with staff expertise and onsite computing resources. We are working toward a fully automated SPI processing system and also are moving to develop CVPR analytical tools for other imaging platforms and data sets.

02 PETROLEUM↗
DOE OSTI2023

A Small Warm Tributary Provides Prespawning Resources for Colorado Pikeminnow in a Cold Dam-Regulated River

Abstract Riverine habitat mosaics, including tributaries, are an important reason the Green River subbasin supports the largest remaining population of federally endangered Colorado Pikeminnow Ptychocheilus lucius in the Colorado River Basin. Upstream Colorado Pikeminnow distribution is limited by Flaming Gorge Dam and few typically occurred in the reach immediately downstream of the dam, which is the reach most affected by thermal and hydrologic alterations. However, fish captures and passive integrated transponder (PIT) antenna sampling of previously tagged individuals from 2011 to 2021 revealed seasonal congregations of up to 75 Colorado Pikeminnow annually in the mouth of Vermillion Creek, a small tributary in the regulated reach. Approximately 11% (N = 93 individuals) of the entire 2017–2018 Green River basin population were encountered in Vermillion Creek over the 11-y study, an underestimate of use considering that untagged fish were not detected by antennas. Colorado Pikeminnow used Vermillion Creek primarily when Green River spring flows from Flaming Gorge Dam were high and cold in May through mid-June when the confluence was a large, deep backwater warmer than the main channel and supported forage fishes. Intra-annual encounters revealed seasonal residence times for individual Colorado Pikeminnow up to 91 d, and multiple inter-annual encounters indicated site fidelity. Frequent detections of individual Colorado Pikeminnow in a Yampa River spawning area soon after their detections in Vermillion Creek indicate this tributary may be an important resource for reproductive adults. The intensive and basin-wide PIT tagging and detection program for Colorado Pikeminnow enhanced our understanding of the importance of small habitat nodes such as Vermillion Creek in the Green River drainage network. Understanding and protecting these seasonally available riverine habitat mosaics used for prespawning conditioning may assist with recovery of Colorado Pikeminnow.

Biodiversity & Conservation↗
DOE OSTI2022

Riverscape heterogeneity in estimated Chinook Salmon emergence phenology and implications for size and growth

Abstract Many salmonid‐bearing rivers exhibit thermal and hydrologic heterogeneity at multiple spatial and temporal scales, but how this translates into spatiotemporal patterns of fry emergence is poorly understood. Understanding this variability is important because emergence timing determines the biophysical conditions fish first experience (e.g., temperature, flow, and food supply), thereby influencing growth opportunities and survival during this critical life stage. We predicted spring Chinook Salmon ( Oncorhynchus tshawytscha ) emergence phenology across four northeastern Oregon subbasins over 5–9 years using empirical spawning and temperature data. We then related interannual emergence timing estimates to juvenile salmon size and growth rates at consistent sampling locations. There were clear longitudinal patterns of predicted emergence timing in each subbasin: The shape of these patterns was consistent among years, but not among subbasins. In two subbasins, emergence occurred progressively later with distance upstream, whereas in the other two subbasins emergence was earliest at upstream sites. Within each year, median emergence dates among sites within each subbasin ranged between 44 and 58 days. This spatial variation was comparable to interannual variation, with median emergence dates for a given location in each subbasin ranging between 47 and 74 days among years. Contrary to our expectations, juvenile salmon were not larger in years with earlier emergence, owing to slower estimated spring and summer growth rates compared to years with later emergence. Despite large interannual variation in estimated emergence dates, these results suggest that other factors (e.g., stream flow, temperature, and density‐dependence) were more important than growth duration in determining juvenile salmon growth rates and size among years. We demonstrated considerable spatial and interannual variation in emergence phenology within these subbasins. Understanding how this variation translates to spatiotemporal patterns of juvenile salmon habitat use, growth, and survival has important implications for guiding restoration efforts and understanding how climate change may impact these populations.

Kaylor, Matthew J.↗
DOE OSTI2023

Expression of macromolecular organic nitrogen degrading enzymes identifies potential mediators of soil organic N availability to an annual grass

Abstract Nitrogen (N) is frequently limiting to plant growth, in part because most soil N is present as polymeric organic compounds that are not readily taken up by plants. Microbial depolymerization of these large macromolecular N-substrates gradually releases available inorganic N. While many studies have researched and modeled controls on soil organic matter formation and bulk N mineralization, the ecological—spatial, temporal and phylogenetic—patterns underlying organic N degradation remain unclear. We analyzed 48 time-resolved metatranscriptomes and quantified N-depolymerization gene expression to resolve differential expression by soil habitat and time in specific taxonomic groups and gene-based guilds. We observed much higher expression of extracellular serine-type proteases than other extracellular N-degrading enzymes, with protease expression of predatory bacteria declining with time and other taxonomic patterns driven by the presence (Gammaproteobacteria) or absence (Thermoproteota) of live roots and root detritus (Deltaproteobacteria and Fungi). The primary chitinase chit1 gene was more highly expressed by eukaryotes near root detritus, suggesting predation of fungi. In some lineages, increased gene expression over time suggests increased competitiveness with rhizosphere age (Chloroflexi). Phylotypes from some genera had protease expression patterns that could benefit plant N nutrition, for example, we identified a Janthinobacterium phylotype and two Burkholderiales that depolymerize organic N near young roots and a Rhizobacter with elevated protease levels near mature roots. These taxon-resolved gene expression results provide an ecological read-out of microbial interactions and controls on N dynamics in specific soil microhabitats and could be used to target potential plant N bioaugmentation strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗