Experimenting With the Past to Improve Environmental Monitoring
Long-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical power, site selection, or the full costs and benef...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-01-01
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| Series: | Frontiers in Ecology and Evolution |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fevo.2020.572979/full |
| _version_ | 1818822169967198208 |
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| author | Easton R. White Easton R. White Christie A. Bahlai |
| author_facet | Easton R. White Easton R. White Christie A. Bahlai |
| author_sort | Easton R. White |
| collection | DOAJ |
| description | Long-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical power, site selection, or the full costs and benefits of monitoring. Key considerations can be incorporated into the optimal design of a management program with simulations and experiments. Here, we advocate for the expanded use of a third approach: non-random resampling of previously-collected data. This approach conducts experiments with available data to understand the consequences of different monitoring approaches. We first illustrate non-random resampling in determining the optimal length and frequency of monitoring programs to assess species trends. We then apply the approach to a pair of additional case studies, from fisheries and agriculture. Non-random resampling of previously-collected data is underutilized, but has the potential to improve monitoring programs. |
| first_indexed | 2024-12-18T23:19:49Z |
| format | Article |
| id | doaj.art-5ba470defe11407cb105edd4cd860b62 |
| institution | Directory Open Access Journal |
| issn | 2296-701X |
| language | English |
| last_indexed | 2024-12-18T23:19:49Z |
| publishDate | 2021-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Ecology and Evolution |
| spelling | doaj.art-5ba470defe11407cb105edd4cd860b622022-12-21T20:48:01ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2021-01-01810.3389/fevo.2020.572979572979Experimenting With the Past to Improve Environmental MonitoringEaston R. White0Easton R. White1Christie A. Bahlai2Department of Biology, University of Vermont, Burlington, VT, United StatesGund Institute for Environment, University of Vermont, Burlington, VT, United StatesDepartment of Biological Sciences, Kent State University, Kent, OH, United StatesLong-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical power, site selection, or the full costs and benefits of monitoring. Key considerations can be incorporated into the optimal design of a management program with simulations and experiments. Here, we advocate for the expanded use of a third approach: non-random resampling of previously-collected data. This approach conducts experiments with available data to understand the consequences of different monitoring approaches. We first illustrate non-random resampling in determining the optimal length and frequency of monitoring programs to assess species trends. We then apply the approach to a pair of additional case studies, from fisheries and agriculture. Non-random resampling of previously-collected data is underutilized, but has the potential to improve monitoring programs.https://www.frontiersin.org/articles/10.3389/fevo.2020.572979/fullstatistical powerpopulation trendsdata-poor fisheriesspecies monitoringresampling |
| spellingShingle | Easton R. White Easton R. White Christie A. Bahlai Experimenting With the Past to Improve Environmental Monitoring Frontiers in Ecology and Evolution statistical power population trends data-poor fisheries species monitoring resampling |
| title | Experimenting With the Past to Improve Environmental Monitoring |
| title_full | Experimenting With the Past to Improve Environmental Monitoring |
| title_fullStr | Experimenting With the Past to Improve Environmental Monitoring |
| title_full_unstemmed | Experimenting With the Past to Improve Environmental Monitoring |
| title_short | Experimenting With the Past to Improve Environmental Monitoring |
| title_sort | experimenting with the past to improve environmental monitoring |
| topic | statistical power population trends data-poor fisheries species monitoring resampling |
| url | https://www.frontiersin.org/articles/10.3389/fevo.2020.572979/full |
| work_keys_str_mv | AT eastonrwhite experimentingwiththepasttoimproveenvironmentalmonitoring AT eastonrwhite experimentingwiththepasttoimproveenvironmentalmonitoring AT christieabahlai experimentingwiththepasttoimproveenvironmentalmonitoring |