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Abstract Federal and state land agencies lack diversity at the natural resource manager level, in turn limiting the agencies' capacity for creative problem solving needed for complex and wicked environmental problems. Diverse representation is imperative to increase public support and trust in natural resource management.We used an online survey method to examine the relationship and experiences between independent demographic variables (e.g. gender, ethnicity and years worked in natural resources) and two dependent variables: (1) perceived public support and (2) sense of belonging for resource management professionals in the Pacific Northwest, USA.We find in general, that gender is associated with how one progresses through a career in natural resource management. As years in natural resource management increases, sense of belonging decreases for women and remains constant for men. Similarly, as years in natural resource management increases, perceived public support increases for men and remains constant for women.Given that ample past research suggests strong links between sustainable management and diverse perspectives, this study has implications for addressing our current and future natural resource management challenges. Read the freePlain Language Summaryfor this article on the Journal blog. 

ABSTRACT MotivationHere, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables IncludedThe database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and GrainSampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and GrainThe earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of MeasurementThe database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Formatcsv and. SQL. 

Abstract Increasing wildfire activity can impact the global carbon cycle, aquatic ecosystem health, and drinking water treatment through alterations in aquatic dissolved organic matter (DOM) composition. However, uncertainty remains about the spatial and temporal variability in wildfire effects on DOM composition. We sought to improve understanding of how burn severity affects stream DOM and how weather, hydrology, and landscape factors contribute to variability in post‐fire DOM responses across space and time. Following a large 2020 wildfire in Oregon, USA, we collected water samples to quantify dissolved organic carbon and DOM optical properties at 129 stream sites across the fire‐affected stream network. Sampling was repeated across seasonal hydrologic conditions to capture variation in hydrologic pathways and organic matter sources. We developed a PARAFAC model using excitation‐emission matrices (EEMs) and used spatial stream network (SSN) models to determine how DOM composition changed across the stream network with burn severity. The greatest shifts in DOM composition were observed during the dry and wetting seasons, with an increase in aromatic DOM at higher burn severities. In contrast, an increase in protein‐like DOM was observed during the wet season at higher burn severities. Drainage area, 31‐day and 1‐day antecedent precipitation, and baseflow index impacted the relationship between DOM composition and burn severity, which could partially explain the variability in post‐fire DOM responses. Our study contributes a mechanistic understanding of how wildfire impacts DOM sources and composition, which is critical to predicting wildfire effects on aquatic biogeochemical cycling and preserving ecosystem health and source water quality. 

Abstract Hyporheic exchange is critical to river corridor biogeochemistry, but decameter‐scale flowpaths (∼10‐m long) are understudied due to logistical challenges (e.g., sampling at depth, multi‐day transit times). Some studies suggest that decameter‐scale flowpaths should have initial hot spots followed by transport‐limited conditions, whereas others suggest steady reaction rates and secondary reactions that could make decameter‐scale flowpaths important and unique. We investigated biogeochemistry along a 12‐m hyporheic mesocosm that allowed for controlled testing of seasonal and spatial water quality changes along a flowpath with fixed geometry and constant flow rate. Water quality profiles of oxygen, carbon, and nitrogen were measured at 1‐m intervals along the mesocosm over multiple seasons. The first 6 m of the mesocosm were always oxic and a net nitrogen source to mobile porewater. In winter, oxic conditions persisted to 12 m, whereas the second half of the flowpath became anoxic and a net nitrogen sink in summer. No reactive hot spots were observed in the first meter of the mesocosm. Instead, most reactions were zeroth‐order over 12 m and 54 hr of transit time. Influent chemistry had less impact on hyporheic biogeochemistry than expected due to large amounts of in situ reactant sources compared to stream‐derived reactant sources. Sorbed or buried carbon likely fueled reactions with rates controlled by temperature and redox conditions. Each reactant showed different hyporheic Damköhler numbers, challenging the characterization of flowpaths being intrinsically reaction‐ or transport‐limited. Future research should explore the prevalence and biogeochemical contributions of decameter‐scale flowpaths in diverse field settings. 

Abstract The body size of aquatic vertebrates is declining across populations and ecosystems worldwide owing to warmer water temperature and changing streamflow. In freshwaters, the effects of stream network position and density‐dependent factors on body size are less understood. We used an extensive dataset spanning 41 stream sites over 7 years to evaluate how density‐dependent and density‐independent factors influence the size of two top predators in small watersheds, Coastal Cutthroat TroutOncorhynchus clarkii clarkiiand Coastal Giant SalamandersDicamptodon tenebrosus. We tested three hypotheses of body‐size variation for trout and salamanders, including intraspecific density dependence, interspecific density dependence, and resource availability, using empirical observations in hierarchical linear mixed models in a model‐selection framework. In our best‐supported models, the strongest predictors of size were conspecific negative density dependence, as expected, suggesting greater intraspecific interactions probably owing to conspecific individuals having similar requirements. We reveal a biogeographic pattern in which body size peaks in middle stream‐network positions and plateaus or declines at lower and upper locations, proposing that stream network position also plays a role in determining body size in small watersheds. Salamander density also has a quadratic effect on adult trout size, with salamanders having a greater overall effect on the body size of both species than trout, suggesting that salamanders might be more dominant than trout in some interactions. Collectively, we found that biotic interactions, mainly conspecific but also interspecific, and stream‐network position affect trout and salamander body sizes in small watersheds. 

Abstract The biodiversity crisis necessitates spatially extensive methods to monitor multiple taxonomic groups for evidence of change in response to evolving environmental conditions. Programs that combine passive acoustic monitoring and machine learning are increasingly used to meet this need. These methods require large, annotated datasets, which are time‐consuming and expensive to produce, creating potential barriers to adoption in data‐ and funding‐poor regions. Recently released pre‐trained avian acoustic classification models provide opportunities to reduce the need for manual labelling and accelerate the development of new acoustic classification algorithms through transfer learning. Transfer learning is a strategy for developing algorithms under data scarcity that uses pre‐trained models from related tasks to adapt to new tasks.Our primary objective was to develop a transfer learning strategy using the feature embeddings of a pre‐trained avian classification model to train custom acoustic classification models in data‐scarce contexts. We used three annotated avian acoustic datasets to test whether transfer learning and soundscape simulation‐based data augmentation could substantially reduce the annotated training data necessary to develop performant custom acoustic classifiers. We also conducted a sensitivity analysis for hyperparameter choice and model architecture. We then assessed the generalizability of our strategy to increasingly novel non‐avian classification tasks.With as few as two training examples per class, our soundscape simulation data augmentation approach consistently yielded new classifiers with improved performance relative to the pre‐trained classification model and transfer learning classifiers trained with other augmentation approaches. Performance increases were evident for three avian test datasets, including single‐class and multi‐label contexts. We observed that the relative performance among our data augmentation approaches varied for the avian datasets and nearly converged for one dataset when we included more training examples.We demonstrate an efficient approach to developing new acoustic classifiers leveraging open‐source sound repositories and pre‐trained networks to reduce manual labelling. With very few examples, our soundscape simulation approach to data augmentation yielded classifiers with performance equivalent to those trained with many more examples, showing it is possible to reduce manual labelling while still achieving high‐performance classifiers and, in turn, expanding the potential for passive acoustic monitoring to address rising biodiversity monitoring needs. 

ABSTRACT Mast seeding, the synchronous and highly variable production of seed crops by perennial plants, is a population‐level phenomenon and has cascading effects in ecosystems. Mast seeding studies are typically conducted at the population/species level. Much less is known about synchrony in mast seeding between species because the necessary long‐term data are rarely available. To investigate synchrony between species within communities, we used long‐term data from seven forest communities in the U.S. Long‐Term Ecological Research (LTER) network, ranging from tropical rainforest to boreal forest. We focus on cross‐species synchrony and (i) quantify synchrony in reproduction overall and within LTER sites, (ii) test for relationships between synchrony with trait and phylogenetic similarity and (iii) investigate how climate conditions at sites are related to levels of synchrony. Overall, reproductive synchrony between woody plant species was greater than expected by chance, but spanned a wide range of values between species. Based on 11 functional and reproductive traits for 103 species (plus phylogenetic relatedness), cross‐species synchrony in reproduction was driven primarily by trait similarity with phylogeny being largely unimportant, and synchrony was higher in sites with greater climatic water deficit. Community‐level synchrony in masting has consequences for understanding forest regeneration dynamics and consumer‐resource interactions. 

Abstract Plants display a range of temporal patterns of inter‐annual reproduction, from relatively constant seed production to “mast seeding,” the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long‐lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community‐level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long‐Term Ecological Research (LTER) or long‐term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community‐level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent‐scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license. 

Abstract Despite much interest in relationships among carbon and water in forests, few studies assess how carbon accumulation scales with water use in forested watersheds with varied histories. This study quantified tree growth, water use efficiency, and carbon‐water tradeoffs of young versus mature/old‐growth forest in three small (13–22 ha) watersheds in the H.J. Andrews Experimental Forest, Oregon, USA. To quantify and scale carbon‐water tradeoffs from trees to watersheds, tree‐ring records and greenness and wetness indices from remote sensing were combined with long‐term vegetation, climate, and streamflow data from young forest watersheds (trees ∼45 years of age) and from a mature/old‐growth forest watershed (trees 150–500 years of age). Biomass production was closely related to water use; water use efficiency (basal area increment per unit of evapotranspiration) was lower; and carbon‐water tradeoffs were steeper in young forest plantations compared with old‐growth forest for which the tree growth record begins in the 1850s. Greenness and wetness indices from Landsat imagery were not significant predictors of streamflow or tree growth over the period 1984 to 2017, and soil C and N did not differ significantly among watersheds. Multiple lines of evidence show that mature and old‐growth forest watersheds store and accumulate more carbon, are more drought resistant, and better sustain water availability compared to young forests. These results provide a basis for reconstructions and predictions that are potentially broadly applicable, because first‐order watersheds occupy 80%–90% of large river basins and study watersheds are representative of forest history in the Pacific Northwest region. 

IntroductionLogging impacts millions of hectares of forests globally every year, and not only affects tree cover, but also disrupts below-ground soil communities that are essential for forest ecosystems. Soil fungi are particularly vulnerable to such disturbances due to their reliance upon plant hosts as their source of carbon. Fluctuations within the major guilds of fungi important for forest function can have ramifications for plant communities and biogeochemical processes. We addressed questions about soil fungal communities in temperate forest stands with varying logging histories: (1) Do assembly patterns of soil fungal communities and functional guilds reflect historical differences in logging legacies? (2) Does sequencing of below-ground communities of fungi resemble the composition of surveys of fungal fruiting bodies? (3) How do fungal communities in the litter layer differ from those in the soil and do these assembly patterns change with logging history? MethodsOur study took place in the H. J. Andrews Experimental Forest in western Oregon, USA. We sampled soil and litter (Oi—Oe) in three sites with different logging histories: one clear cut in 1974, one selectively logged and thinned three times between 1974 and 2001, and one unlogged. We sequenced soil fungi separately for mineral soil samples and litter samples. Additionally, we compiled fruiting-body studies from 1972 through the present to compare with our eDNA samples. ResultsWe found that four decades after logging had ceased there were detectable signatures within the soil fungal communities that distinguished logged from unlogged sites, indicating a legacy that affects many generations of fungi (PERMANOVA;p< 0.001 for both soil and litter fungi). There were also significant differences between litter and mineral soil communities (PERMANOVA;p< 0.001) with higher relative abundances of pathogens within the litter layer and a greater proportion of mycorrhizal fungi in the soil. DiscussionThese results highlight the importance of including forest litter in studies, as entire guilds of fungi can be underestimated when considering a single fraction. Together, these results have repercussions for the regeneration of forests following logging, as the composition of fungal guilds important to plant functions do not fully recover even after decades of cessation.