Angler Perception and Population Dynamics of the Northern Snakehead (Channa argus) in the Potomac River & Tributaries

Our research sought to address the extent to which the northern snakehead (Channa argus), an invasive fish species, represents a threat to the Potomac River ecosystem. The first goal of our research was to survey the perceptions and opinions of recreational anglers on the effects of the snakehead population in the Potomac River ecosystem. To determine angler perceptions, we created and administered 113 surveys from June – September 2014 at recreational boat ramps along the Potomac River. Our surveys were designed to expand information collected during previous surveys conducted by the U.S. Fish and Wildlife Service. Our results indicated recreational anglers perceive that abundances and catch rates of target species, specifically largemouth bass, have declined since snakehead became established in the river. The second goal of our research was to determine the genetic diversity and potential of the snakehead population to expand in the Potomac River. We hypothesized that the effective genetic population size would be much less than the census size of the snakehead population in the Potomac River. We collected tissue samples (fin clippings) from 79 snakehead collected in a recreational tournament held between Fort Washington and Wilson’s Landing, MD on the Potomac River and from electrofishing sampling conducted by the Maryland Department of Natural Resources in Pomonkey Creek, a tributary of the Potomac River. DNA was extracted from the tissue samples and scored for 12 microsatellite markers, which had previously been identified for Potomac River snakehead. Microsatellite allele frequency data were recorded and analyzed in the software programs GenAlEx and NeEstimator to estimate heterozygosity and effective genetic population size. Resampling simulations indicated that the number of microsatellites and the number of fish analyzed provided sufficient precision. Simulations indicated that the effective population size estimate would expect to stabilize for samples > 70 individual snakehead. Based on a sample of 79 fish scored for 12 microsatellites, we calculated an Ne of 15.3 individuals. This is substantially smaller than both the sample size and estimated population size. We conclude that genetic diversity in the snakehead population in the Potomac River is low because the population has yet to recover from a genetic bottleneck associated with a founder effect due to their recent introduction into the system

Time-lapse imagery from eastern Washington, U.S.

The archive comprises 9 files. 8 folders of .jpeg images corresponding to each camera site and 1 .xlsx file containing metadata related to each camera.We present a time-lapse camera dataset for snow monitoring from eastern Washington, U.S.A. Eight time-lapse cameras facing a red pole 3-5 m away from the camera were installed between December 2020 and May 2021. Cameras were set to take an image every day at 12 PM PT. The sites spread an elevational gradient and contain both in- and out-of canopy locations. The dataset is organized with one folder of .jpeg images for each camera, along with a .xlsx file for site metadata, including latitude, longitude, percent of canopy cover, elevation (m), aspect, slope, and terrain type. Snow can be converted into snow depth by finding the length of the pole in pixels in each image and converting to centimeters using a conversion from the total length of the pole in cm/pixels. The cameras coincide with a wolf home range, making this data set ideal for testing hypotheses about how snow processes may be affecting predator-prey interactions, wildlife movement, and general trends for snow in an area where observations are sparse and limited.NASA Grant #80NSSC19K167

A framework for contextualizing social‐ecological biases in contributory science data

Contributory science—including citizen and community science—allows scientists to leverage participant-generated data while providing an opportunity for engaging with local community members. Data yielded by participant-generated biodiversity platforms allow professional scientists to answer ecological and evolutionary questions across both geographic and temporal scales, which is incredibly valuable for conservation efforts. The data reported to contributory biodiversity platforms, such as eBird and iNaturalist, can be driven by social and ecological variables, leading to biased data. Though empirical work has highlighted the biases in contributory data, little work has articulated how biases arise in contributory data and the societal consequences of these biases. We present a conceptual framework illustrating how social and ecological variables create bias in contributory science data. In this framework, we present four filters—participation, detectability, sampling and preference—that ultimately shape the type and location of contributory biodiversity data. We leverage this framework to examine data from the largest contributory science platforms—eBird and iNaturalist—in St. Louis, Missouri, the United States, and discuss the potential consequences of biased data. Lastly, we conclude by providing several recommendations for researchers and institutions to move towards a more inclusive field. With these recommendations, we provide opportunities to ameliorate biases in contributory data and an opportunity to practice equitable biodiversity conservation. Read the free Plain Language Summary for this article on the Journal blog