Combining financial costs and statistical power to optimize monitoring to detect recoveries of species after megafire.
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| Title: | Combining financial costs and statistical power to optimize monitoring to detect recoveries of species after megafire. |
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| Authors: | Smart, Adam1,2 (AUTHOR) adam.steven.smart@gmail.com, Southwell, Darren1,2 (AUTHOR), Geary, William3 (AUTHOR), Buchan, Anne3 (AUTHOR), Wintle, Brendan1,2 (AUTHOR) |
| Source: | Global Ecology & Biogeography. Oct2022, Vol. 31 Issue 10, p2147-2157. 11p. |
| Subjects: | Statistical power analysis, Electricity pricing, Species distribution, Biodiversity monitoring, Budget, Building material testing |
| Geographic Terms: | Victoria |
| Abstract: | Aim: Megafire plays a crucial role in driving the distribution of biodiversity around the world. Long‐term monitoring is vital for understanding how species are impacted immediately by megafire and subsequently respond over time. However, monitoring should be designed with sufficient statistical power to detect impact and recovery. In this study, we developed a simulation framework for optimizing the design of biodiversity monitoring programmes to detect population recoveries after megafire. Location: Victoria, Australia. Time period: 2019–2020. Major taxa studied: Vertebrates. Methods: We collated species distribution models for 45 priority vertebrates most likely to respond to management after the 2019–2020 megafires in Victoria, Australia. We combined these models with fire severity maps to optimize the location of monitoring sites in and around the fire footprint. We simulated the impact of the megafires on species distributions and modelled plausible recoveries over the next 10 years. Using estimates of detectability for a suite of preferred sampling methods, we simulated monitoring at pairs of burnt and unburnt sites to evaluate the statistical power to detect the modelled recoveries. We tested the sensitivity of power to alternative monitoring designs, rates of recovery and monitoring budgets. Results: Priority regions to establish monitoring sites varied by taxonomic group. Power to detect population recoveries increased as the monitoring budget increased, as the recovery rate increased and when the proportion of sites in burnt compared with unburnt habitat increased. According to the optimal monitoring design, an AUD $9M budget could detect 90% of recoveries to pre‐fire levels in 40% of species with >80% power. Power was highest for mammals, followed by birds, reptiles and amphibians. Main conclusions: Our simulation approach allowed us to test the relative performance of alternative post‐fire monitoring designs ahead of time. Although we focused on megafire, our approach could easily be applied to detect population recoveries after any large‐scale catastrophic disturbance. [ABSTRACT FROM AUTHOR] |
| Copyright of Global Ecology & Biogeography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 159294852 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Combining financial costs and statistical power to optimize monitoring to detect recoveries of species after megafire. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Smart%2C+Adam%22">Smart, Adam</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> adam.steven.smart@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Southwell%2C+Darren%22">Southwell, Darren</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Geary%2C+William%22">Geary, William</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Buchan%2C+Anne%22">Buchan, Anne</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wintle%2C+Brendan%22">Wintle, Brendan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Global+Ecology+%26+Biogeography%22">Global Ecology & Biogeography</searchLink>. Oct2022, Vol. 31 Issue 10, p2147-2157. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Statistical+power+analysis%22">Statistical power analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Electricity+pricing%22">Electricity pricing</searchLink><br /><searchLink fieldCode="DE" term="%22Species+distribution%22">Species distribution</searchLink><br /><searchLink fieldCode="DE" term="%22Biodiversity+monitoring%22">Biodiversity monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Budget%22">Budget</searchLink><br /><searchLink fieldCode="DE" term="%22Building+material+testing%22">Building material testing</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Victoria%22">Victoria</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Aim: Megafire plays a crucial role in driving the distribution of biodiversity around the world. Long‐term monitoring is vital for understanding how species are impacted immediately by megafire and subsequently respond over time. However, monitoring should be designed with sufficient statistical power to detect impact and recovery. In this study, we developed a simulation framework for optimizing the design of biodiversity monitoring programmes to detect population recoveries after megafire. Location: Victoria, Australia. Time period: 2019–2020. Major taxa studied: Vertebrates. Methods: We collated species distribution models for 45 priority vertebrates most likely to respond to management after the 2019–2020 megafires in Victoria, Australia. We combined these models with fire severity maps to optimize the location of monitoring sites in and around the fire footprint. We simulated the impact of the megafires on species distributions and modelled plausible recoveries over the next 10 years. Using estimates of detectability for a suite of preferred sampling methods, we simulated monitoring at pairs of burnt and unburnt sites to evaluate the statistical power to detect the modelled recoveries. We tested the sensitivity of power to alternative monitoring designs, rates of recovery and monitoring budgets. Results: Priority regions to establish monitoring sites varied by taxonomic group. Power to detect population recoveries increased as the monitoring budget increased, as the recovery rate increased and when the proportion of sites in burnt compared with unburnt habitat increased. According to the optimal monitoring design, an AUD $9M budget could detect 90% of recoveries to pre‐fire levels in 40% of species with >80% power. Power was highest for mammals, followed by birds, reptiles and amphibians. Main conclusions: Our simulation approach allowed us to test the relative performance of alternative post‐fire monitoring designs ahead of time. Although we focused on megafire, our approach could easily be applied to detect population recoveries after any large‐scale catastrophic disturbance. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Global Ecology & Biogeography is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/geb.13554 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 2147 Subjects: – SubjectFull: Statistical power analysis Type: general – SubjectFull: Electricity pricing Type: general – SubjectFull: Species distribution Type: general – SubjectFull: Biodiversity monitoring Type: general – SubjectFull: Budget Type: general – SubjectFull: Building material testing Type: general – SubjectFull: Victoria Type: general Titles: – TitleFull: Combining financial costs and statistical power to optimize monitoring to detect recoveries of species after megafire. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Smart, Adam – PersonEntity: Name: NameFull: Southwell, Darren – PersonEntity: Name: NameFull: Geary, William – PersonEntity: Name: NameFull: Buchan, Anne – PersonEntity: Name: NameFull: Wintle, Brendan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 1466822X Numbering: – Type: volume Value: 31 – Type: issue Value: 10 Titles: – TitleFull: Global Ecology & Biogeography Type: main |
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