Dataset Information

Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program.

ABSTRACT: An increasing number of citizen science water monitoring programs is continuously collecting water quality data on streams throughout the United States. Operating under quality assurance protocols, this type of monitoring data can be extremely valuable for scientists and professional agencies, but in some cases has been of limited use due to concerns about the accuracy of data collected by volunteers. Although a growing body of studies attempts to address accuracy concerns by comparing volunteer data to professional data, rarely has this been conducted with large-scale datasets generated by citizen scientists. This study assesses the relative accuracy of volunteer water quality data collected by the Texas Stream Team (TST) citizen science program from 1992-2016 across the State of Texas by comparing it to professional data from corresponding stations during the same time period. Use of existing data meant that sampling times and protocols were not controlled for, thus professional and volunteer comparisons were refined to samples collected at stations within 60 meters of one another and during the same year. Results from the statewide TST dataset include 82 separate station/year ANOVAs and demonstrate that large-scale, existing volunteer and professional data with unpaired samples can show agreement of ~80% for all analyzed parameters (DO = 77%, pH = 79%, conductivity = 85%). In addition, to assess whether limiting variation within the source datasets increased the level of agreement between volunteers and professionals, data were analyzed at a local scale. Data from a single partner city, with increased controls on sampling times and locations and correction of a systematic bias in DO, confirmed this by showing an even greater agreement of 91% overall from 2009-2017 (DO = 91%, pH = 83%, conductivity = 100%). An experimental sampling dataset was analyzed and yielded similar results, indicating that existing datasets can be as accurate as experimental datasets designed with researcher supervision. Our findings underscore the reliability of large-scale citizen science monitoring datasets already in existence, and their potential value to scientific research and water management programs.

SUBMITTER: Albus KH

PROVIDER: S-EPMC6988940 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program.

Albus Kelly Hibbeler KH Thompson Ruthanne R Mitchell Forrest F Kennedy James J Ponette-González Alexandra G AG

PloS one 20200129 1

An increasing number of citizen science water monitoring programs is continuously collecting water quality data on streams throughout the United States. Operating under quality assurance protocols, this type of monitoring data can be extremely valuable for scientists and professional agencies, but in some cases has been of limited use due to concerns about the accuracy of data collected by volunteers. Although a growing body of studies attempts to address accuracy concerns by comparing volunteer ...[more]

PMID: 31995580

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Project description:Due to the COVID-19 pandemic, many universities struggle to engage students while implementing a distance-based teaching/learning approach and to provide hands-on activities to students enrolled in STEM classes. Implementing service-focused activities that can be conducted by the students remotely can overcome these struggles. The goals of this study were to 1) implement citizen science activities focused on water quality using three commercially available low-cost test strips (2:1, 5:1, and 16:1) while teaching four undergraduate engineering courses at the University of Mississippi (UM) during a pandemic event, and 2) evaluate the acceptability and validate the results obtained. Eighty-five undergraduate students (citizen scientists) and five research scientists (control group) collected two water samples (with triplicates) after receiving detailed step-by-step written guidelines and video tutorials. One hundred twenty tap water samples were collected from private households across Lafayette County and its surrounding counties and multiple buildings on campus. Five laboratory fortified blank (LBF) samples were implemented to validate the results. While the academic background of the participants did not impact the results (p > 0.05), the results obtained using the different test strips were statistically different (p < 0.05). In fact, results obtained using the 2:1 and the 5:1 test strips were close to the LFBs, while, except for the higher concentration of Total Alkalinity (40 mg/L CaCO3), results obtained using the 16:1 test strips were significantly different than the LFBs. Results (in terms of pH, Nitrate, and Total Chlorine) obtained by the citizen scientists using the 2:1 and 5:1 test strips were consistent with those reported in the annual drinking water quality reports from UM and municipalities included in the investigated region. Overall, this activity was well received by the students. Approximately 75% of them agreed that this hands-on activity was a positive experience while struggling to attend face-to-face classes.

Project description:Citizen science approaches are of great interest for their potential to efficiently and sustainably monitor wildlife populations on both public and private lands. Here we present two studies that worked with volunteers to set camera traps for ecological surveys. The photographs recorded by these citizen scientists were archived and verified using the eMammal software platform, providing a professional grade, vouchered database of biodiversity records. Motivated by managers' concern with perceived high bear activity, our first example enlisted the help of homeowners in a short-term study to compare black bear activity inside a National Historic Site with surrounding private land. We found similar levels of bear activity inside and outside the NHS, and regional comparisons suggest the bear population is typical. Participants benefited from knowing their local bear population was normal and managers refocused bear management given this new information. Our second example is a continuous survey of wildlife using the grounds of a nature education center that actively manages habitat to maintain a grassland prairie. Center staff incorporated the camera traps into educational programs, involving visitors with camera setup and picture review. Over two years and 5,968 camera-nights this survey has collected 41,393 detections of 14 wildlife species. Detection rates and occupancy were higher in open habitats compared to forest, suggesting that the maintenance of prairie habitat is beneficial to some species. Over 500 volunteers of all ages participated in this project over two years. Some of the greatest benefits have been to high school students, exemplified by a student with autism who increased his communication and comfort level with others through field work with the cameras. These examples show how, with the right tools, training and survey design protocols, citizen science can be used to answer a variety of applied management questions while connecting participants with their secretive mammal neighbors.

Dataset Information

Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program.

Publications

Accuracy of long-term volunteer water monitoring data: A multiscale analysis from a statewide citizen science program.

Similar Datasets

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