Detecting population trends for US marine mammals
Abstract Trend analysis can provide valuable information about marine mammal population dynamics, potentially revealing the influence of environmental factors and inform conservation and management decisions. We reviewed the marine mammal stock assessment reports (SARs) published by the US National...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-03-01
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| Series: | Conservation Science and Practice |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/csp2.611 |
| _version_ | 1819004243920551936 |
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| author | Easton R. White Zachary Schakner Amber Bellamy Mridula Srinivasan |
| author_facet | Easton R. White Zachary Schakner Amber Bellamy Mridula Srinivasan |
| author_sort | Easton R. White |
| collection | DOAJ |
| description | Abstract Trend analysis can provide valuable information about marine mammal population dynamics, potentially revealing the influence of environmental factors and inform conservation and management decisions. We reviewed the marine mammal stock assessment reports (SARs) published by the US National Marine Fisheries Service and found that 80% of the selected 244 marine mammal stocks with SARs lack assessment for trends in population abundance. We compared trend analysis with another common management tool, potential biological removal (PBR), a measure of the maximum human‐caused mortality that can still result in positive population growth. We found that, generally, estimates of PBR were lower for declining stocks than for increasing or stable stocks and varied by life history characteristics. As a case study, we used a resampling approach on three well‐studied stocks, killer whale (Orcinus orca—Northern Resident), beluga (Delphinapterus leucas—Cook Inlet), and humpback whale (Megaptera novaeangliae—CA/OR/WA), to test the minimal amount of time and sampling necessary to detect population trends with high statistical power. We found seven sampling events over more than 10 years were needed for a high statistical power level for all three stocks. Altogether, these findings suggest that well‐studied stocks can provide crucial information on the statistical requirements for detecting trends. Furthermore, our proposed resampling approach might enable more frequent trend analysis, even with limited time series available for many stocks. |
| first_indexed | 2024-12-20T23:33:48Z |
| format | Article |
| id | doaj.art-0cc5b5af23dc4b75af6c6f9360595b0e |
| institution | Directory Open Access Journal |
| issn | 2578-4854 |
| language | English |
| last_indexed | 2024-12-20T23:33:48Z |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Conservation Science and Practice |
| spelling | doaj.art-0cc5b5af23dc4b75af6c6f9360595b0e2022-12-21T19:23:14ZengWileyConservation Science and Practice2578-48542022-03-0143n/an/a10.1111/csp2.611Detecting population trends for US marine mammalsEaston R. White0Zachary Schakner1Amber Bellamy2Mridula Srinivasan3Department of Biological Sciences University of New Hampshire Durham New Hampshire USAOffice of Science and Technology, National Marine Fisheries Service, National Oceanic and Atmospheric Administration Silver Spring Maryland USAOffice of Science and Technology, National Marine Fisheries Service, National Oceanic and Atmospheric Administration Silver Spring Maryland USAOffice of Science and Technology, National Marine Fisheries Service, National Oceanic and Atmospheric Administration Silver Spring Maryland USAAbstract Trend analysis can provide valuable information about marine mammal population dynamics, potentially revealing the influence of environmental factors and inform conservation and management decisions. We reviewed the marine mammal stock assessment reports (SARs) published by the US National Marine Fisheries Service and found that 80% of the selected 244 marine mammal stocks with SARs lack assessment for trends in population abundance. We compared trend analysis with another common management tool, potential biological removal (PBR), a measure of the maximum human‐caused mortality that can still result in positive population growth. We found that, generally, estimates of PBR were lower for declining stocks than for increasing or stable stocks and varied by life history characteristics. As a case study, we used a resampling approach on three well‐studied stocks, killer whale (Orcinus orca—Northern Resident), beluga (Delphinapterus leucas—Cook Inlet), and humpback whale (Megaptera novaeangliae—CA/OR/WA), to test the minimal amount of time and sampling necessary to detect population trends with high statistical power. We found seven sampling events over more than 10 years were needed for a high statistical power level for all three stocks. Altogether, these findings suggest that well‐studied stocks can provide crucial information on the statistical requirements for detecting trends. Furthermore, our proposed resampling approach might enable more frequent trend analysis, even with limited time series available for many stocks.https://doi.org/10.1111/csp2.611marine mammalspopulation dynamicstrend analysispopulation monitoring |
| spellingShingle | Easton R. White Zachary Schakner Amber Bellamy Mridula Srinivasan Detecting population trends for US marine mammals Conservation Science and Practice marine mammals population dynamics trend analysis population monitoring |
| title | Detecting population trends for US marine mammals |
| title_full | Detecting population trends for US marine mammals |
| title_fullStr | Detecting population trends for US marine mammals |
| title_full_unstemmed | Detecting population trends for US marine mammals |
| title_short | Detecting population trends for US marine mammals |
| title_sort | detecting population trends for us marine mammals |
| topic | marine mammals population dynamics trend analysis population monitoring |
| url | https://doi.org/10.1111/csp2.611 |
| work_keys_str_mv | AT eastonrwhite detectingpopulationtrendsforusmarinemammals AT zacharyschakner detectingpopulationtrendsforusmarinemammals AT amberbellamy detectingpopulationtrendsforusmarinemammals AT mridulasrinivasan detectingpopulationtrendsforusmarinemammals |