Fisheries conservation requires accurate knowledge of species identities and distributions. Fisheries are typically assessed via capture‐based sampling, but managers frequently are unable to conduct extensive surveys due to budgetary constraints. Sampling of environmental DNA (eDNA) released by fish is a potentially cost‐effective approach that could improve species detection per unit effort. However, eDNA methods have not been widely adopted, in part because the cost and effort of eDNA versus traditional sampling are often unclear to managers. We compared the monetary costs and sampling effort required to assess the distribution of Brook Trout Salvelinus fontinalis in a Wisconsin watershed using both electrofishing and eDNA. We detected Brook Trout via both electrofishing and eDNA. The eDNA analysis required lower sampling effort and 67% less cost than triple‐pass electrofishing. However, eDNA was more expensive than presence–absence electrofishing, and no population structure information was obtained. Our study illustrates the potential of eDNA to complement traditional sampling methods during fish surveys.

The expansion of the wind energy industry has had benefits in terms of increased renewable energy production but has also led to increased mortality of migratory bats due to interactions with wind turbines. A key question that could guide bat-related management activities is identifying the geographic origin of bats killed at wind-energy facilities. Generating this information requires developing new methods for identifying the geographic sources of individual bats. Here we explore the viability of assigning geographic origin using trace element analyses of fur to infer the summer molting location of eastern red bats (Lasiurus borealis). Our approach is based on the idea that the concentration of trace elements in bat fur is related through the food chain to the amount of trace elements present in the soil, which varies across large geographic scales. Specifically, we used inductively coupled plasma–mass spectrometry to determine the concentration of fourteen trace elements in fur of 126 known-origin eastern red bats to generate a basemap for assignment throughout the range of this species in eastern North America. We then compared this map to publicly available soil trace element concentrations for the U.S. and Canada, used a probabilistic framework to generate likelihood-of-origin maps for each bat, and assessed how well trace element profiles predicted the origins of these individuals. Overall, our results suggest that trace elements allow successful assignment of individual bats 80% of the time while reducing probable locations in half. Our study supports the use of trace elements to identify the geographic origin of eastern red and perhaps other migratory bats, particularly when combined with data from other biomarkers such as genetic and stable isotope data.

Significance Only an estimated 1 to 10% of Earth’s species have been formally described. This discrepancy between the number of species with a formal taxonomic description and actual number of species (i.e., the Linnean shortfall) hampers research across the biological sciences. To explore whether the Linnean shortfall results from poor taxonomic practice or not enough taxonomic effort, we applied machine-learning techniques to build a predictive model to identify named species that are likely to contain hidden diversity. Results indicate that small-bodied species with large, climatically variable ranges are most likely to contain hidden species. These attributes generally match those identified in the taxonomic literature, indicating that the Linnean shortfall is caused by societal underinvestment in taxonomy rather than poor taxonomic practice.

Understanding seasonal variation in the distribution and movement patterns of migratory species is essential to monitoring and conservation efforts. While there are many species of migratory bats in North America, little is known about their seasonal movements. In terms of conservation, this is important because the bat fatalities from wind energy turbines are significant and may fluctuate seasonally. Here we describe seasonally resolved distributions for the three species that are most impacted by wind farms (Lasiurus borealis (eastern red bat), L. cinereus (hoary bat) and Lasionycteris noctivagans (silver-haired bat)) and use these distributions to infer their most likely migratory pathways. To accomplish this, we collected 2,880 occurrence points from the Global Biodiversity Information Facility over five decades in North America to model species distributions on a seasonal basis and used an ensemble approach for modeling distributions. This dataset included 1,129 data points for L. borealis, 917 for L. cinereus and 834 for L. noctivagans. The results suggest that all three species exhibit variation in distributions from north to south depending on season, with each species showing potential migratory pathways during the fall migration that follow linear features. Finally, we describe proposed migratory pathways for these three species that can be used to identify stop-over sites, assess small-scale migration and highlight areas that should be prioritized for actions to reduce the effects of wind farm mortality.