RÉSUMÉ
Fluvial fishes are threatened globally from intensive human landscape stressors degrading aquatic ecosystems. However, impacts vary regionally, as stressors and natural environmental factors differ between ecoregions and continents. To date, a comparison of fish responses to landscape stressors over continents is lacking, limiting understanding of consistency of impacts and hampering efficiencies in conserving fishes over large regions. This study addresses these shortcomings through a novel, integrative assessment of fluvial fishes throughout Europe and the conterminous United States. Using large-scale datasets, including information on fish assemblages from more than 30,000 locations on both continents, we identified threshold responses of fishes summarized by functional traits to landscape stressors including agriculture, pasture, urban area, road crossings, and human population density. After summarizing stressors by catchment unit (local and network) and constraining analyses by stream size (creeks vs. rivers), we analyzed stressor frequency (number of significant thresholds) and stressor severity (value of identified thresholds) within ecoregions across Europe and the United States. We document hundreds of responses of fish metrics to multi-scale stressors in ecoregions across two continents, providing rich findings to aid in understanding and comparing threats to fishes across the study regions. Collectively, we found that lithophilic species and, as expected, intolerant species are most sensitive to stressors in both continents, while migratory and rheophilic species are similarly strongly affected in the United States. Also, urban land use and human population density were most frequently associated with declines in fish assemblages, underscoring the pervasiveness of these stressors in both continents. This study offers an unprecedented comparison of landscape stressor effects on fluvial fishes in a consistent and comparable manner, supporting conservation of freshwater habitats in both continents and worldwide.
Sujet(s)
Écosystème , Poissons , Animaux , Humains , États-Unis , Europe , Rivières , Agriculture , BiodiversitéRÉSUMÉ
Environmental DNA (eDNA) sampling provides sensitive early detection capabilities for recently introduced taxa. However, natural resource managers struggle with how to integrate eDNA results into an early detection rapid response program because positive eDNA detections are not always indicative of an eventual infestation. We used a structured decision making (SDM) framework to evaluate appropriate response actions to hypothetical eDNA early detections of an introduced aquatic plant in Sebago Lake (Maine, USA). The results were juxtaposed to a recent study that used a similar SDM approach to evaluate response actions to hypothetical eDNA early detections of introduced mussels in Jordanelle Reservoir (Utah, USA). We found that eDNA early detections were not actionable in Sebago Lake because the plant's invasion potential was spatially constrained and the current management activities provided acceptable levels of mitigation. In Jordanelle Reservoir, eDNA detections were actionable due to high invasion potential and analyses supported management actions to contain the invasion. The divergent outcomes of the two case studies are related to the unique attributes of the habitats and species, highlighting the utility of the SDM approach when considering an eDNA monitoring program. We use these two case studies to present a general SDM framework and a set of heuristics that can be efficiently applied to eDNA early detection rapid response scenarios and other instances associated with indeterminant eDNA detections, especially when there is an imperative to make decisions as quickly as possible.
Sujet(s)
ADN environnemental , Espèce introduite , Écosystème , Surveillance de l'environnement/méthodesRÉSUMÉ
Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.
Sujet(s)
Biodiversité , Espèce introduiteRÉSUMÉ
Invasive species surveillance programs can utilize environmental DNA sampling and analysis to provide information on the presence of invasive species. Wider utilization of eDNA techniques for invasive species surveillance may be warranted. This paper covers topics directed towards invasive species managers and eDNA practitioners working at the intersection of eDNA techniques and invasive species surveillance. It provides background information on the utility of eDNA for invasive species management and points to various examples of its use across federal and international programs. It provides information on 1) why an invasive species manager should consider using eDNA, 2) deciding if eDNA can help with the manager's surveillance needs, 3) important components to operational implementation, and 4) a high-level overview of the technical steps necessary for eDNA analysis. The goal of this paper is to assist invasive species managers in deciding if, when, and how to use eDNA for surveillance. If eDNA use is elected, the paper provides guidance on steps to ensure a clear understanding of the strengths and limitation of the methods and how results can be best utilized in the context of invasive species surveillance.
RÉSUMÉ
Multiplexed deep neural networks (DNN) have engendered high-performance predictive models gaining popularity for decoding brain waves, extensively collected in the form of electroencephalogram (EEG) signals. In this paper, to the best of our knowledge, we introduce a first-ever DNN-based generalized approach to estimate reaction time (RT) using the periodogram representation of single-trial EEG in a visual stimulus-response experiment with 48 participants. We have designed a Fully Connected Neural Network (FCNN) and a Convolutional Neural Network (CNN) to predict and classify RTs for each trial. Though deep neural networks are widely known for classification applications, cascading FCNN/CNN with the Random Forest model, we designed a robust regression-based estimator to predict RT. With the FCNN model, the accuracies obtained for binary and 3-class classification were 93% and 76%, respectively, which further improved with the use of CNN (94% and 78%, respectively). The regression-based approach predicted RTs with correlation coefficients (CC) of 0.78 and 0.80 for FCNN and CNN, respectively. Investigating further, we found that the left central as well as parietal and occipital lobes were crucial for predicting RT, with significant activities in the theta and alpha frequency bands.
Sujet(s)
Algorithmes , Électroencéphalographie , , Temps de réaction , HumainsRÉSUMÉ
Despite the prevalence of damming as a global disturbance to river habitats, detailed reach-based assessments of the ecological effects of dams are lacking, particularly across large spatial extents. Using data from nearly 50,000 large dams, we assessed stream network fragmentation and flow alteration by large dams for streams of the conterminous USA. We developed 21 dam metrics characterizing a diversity of dam influences operating at both localized (e.g., distances-to-dams) and landscape scales (e.g., cumulative reservoir storage throughout stream networks) for every stream reach in the study region. We further evaluated how dams have affected stream fish assemblages within large ecoregions using more than 37,000 stream fish samples. Streams have been severely fragmented by large dams, with the number of stream segments increasing by 801% compared to free-flowing streams in the absence of dams and a staggering 79% of stream length is disconnected from their outlet (i.e., oceans and Great Lakes). Flow alteration metrics demonstrate a landscape-scale disturbance of dams, resulting in total upstream reservoir storage volumes exceeding estimated annual discharge volumes of many of the nation's largest rivers. Further, we show large-scale changes in fish assemblages with dams. Species adapted to lentic habitats increase with dams across the conterminous USA, while rheophils, lithophils, and intolerant fishes decrease with dams. Overall, fragmentation and flow alteration by dams have affected fish assemblages as much or more than other anthropogenic stressors, with dam effects generally increasing with stream size. Dam-induced stream fragmentation and flow alteration are critical natural resource issues. This study emphasizes the importance of considering dams as a landscape-scale disturbance to river habitats along with the need to assess differential effects that dams may have on river habitats and the fishes they support. Together, these insights are essential for more effective conservation of stream resources and biotic communities globally.