Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems

Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although...

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Vydané v:	Journal of environmental management Ročník 188; s. 108 - 119
Hlavní autori:	Tulloch, Vivitskaia J., Klein, Carissa J., Jupiter, Stacy D., Tulloch, Ayesha I.T., Roelfsema, Chris, Possingham, Hugh P.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Elsevier Ltd 01.03.2017
Predmet:	Biodiversity Conservation Conservation of Natural Resources - economics Conservation of Natural Resources - methods Coral Reefs corals Cost-effectiveness Data Accuracy data collection decision making ecosystems Fiji Fisheries Geographic Mapping Habitat classification habitat conservation Marine protected area Parks, Recreational - economics planning remote sensing reserve networks risk seagrasses Spatial planning Surrogate ISEW, Pacific, Fiji Fiji Habitat classification Marine protected area Surrogate Spatial planning Cost-effectiveness Conservation
ISSN:	0301-4797, 1095-8630, 1095-8630
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Abstract	Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data. •We evaluate spatial planning trade-offs from using coral reef habitat data of differing accuracy.•We compare reserves designed using high accuracy geomorphology vs finer detail benthic substrate.•Accounting for mapping accuracy reduces the risk of missing conservation targets.•Using fine habitat classifications with low accuracy leads to larger and more costly reserves.•Coarse classifications are most cost-effective with low data costs and reduced impacts on fishers.
AbstractList	Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data.Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data. Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data. Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data. •We evaluate spatial planning trade-offs from using coral reef habitat data of differing accuracy.•We compare reserves designed using high accuracy geomorphology vs finer detail benthic substrate.•Accounting for mapping accuracy reduces the risk of missing conservation targets.•Using fine habitat classifications with low accuracy leads to larger and more costly reserves.•Coarse classifications are most cost-effective with low data costs and reduced impacts on fishers.
Author	Possingham, Hugh P. Jupiter, Stacy D. Tulloch, Ayesha I.T. Klein, Carissa J. Tulloch, Vivitskaia J. Roelfsema, Chris
Author_xml	– sequence: 1 givenname: Vivitskaia J. surname: Tulloch fullname: Tulloch, Vivitskaia J. email: v.tulloch@uq.edu.au organization: ARC Centre of Excellence for Environmental Decisions, School of Biological Sciences, University of Queensland, St Lucia, QLD 4072, Australia – sequence: 2 givenname: Carissa J. surname: Klein fullname: Klein, Carissa J. organization: School of Geography, Planning, and Environmental Management, University of Queensland, St Lucia, QLD 4072, Australia – sequence: 3 givenname: Stacy D. surname: Jupiter fullname: Jupiter, Stacy D. organization: Wildlife Conservation Society, Melanesia Program, 11 Ma'afu St, Suva, Fiji – sequence: 4 givenname: Ayesha I.T. surname: Tulloch fullname: Tulloch, Ayesha I.T. organization: School of Geography, Planning, and Environmental Management, University of Queensland, St Lucia, QLD 4072, Australia – sequence: 5 givenname: Chris surname: Roelfsema fullname: Roelfsema, Chris organization: Biophysical Remote Sensing Group, University of Queensland, Brisbane 4072, Australia – sequence: 6 givenname: Hugh P. surname: Possingham fullname: Possingham, Hugh P. organization: ARC Centre of Excellence for Environmental Decisions, School of Biological Sciences, University of Queensland, St Lucia, QLD 4072, Australia
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/27940319$$D View this record in MEDLINE/PubMed
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CitedBy_id	crossref_primary_10_1007_s00338_020_01929_3 crossref_primary_10_1016_j_biocon_2021_108954 crossref_primary_10_1016_j_marpolbul_2021_112131 crossref_primary_10_3389_fenvs_2024_1425668 crossref_primary_10_1007_s43621_022_00116_4 crossref_primary_10_1016_j_ocecoaman_2020_105206 crossref_primary_10_3897_oneeco_10_e155166 crossref_primary_10_3897_oneeco_9_e125578 crossref_primary_10_3390_rs16050732 crossref_primary_10_1007_s10452_021_09896_9 crossref_primary_10_1111_csp2_13293 crossref_primary_10_1007_s10531_020_01947_1 crossref_primary_10_1371_journal_pone_0204569
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Snippet	Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat...
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SubjectTerms	Biodiversity Conservation Conservation of Natural Resources - economics Conservation of Natural Resources - methods Coral Reefs corals Cost-effectiveness Data Accuracy data collection decision making ecosystems Fiji Fisheries Geographic Mapping Habitat classification habitat conservation Marine protected area Parks, Recreational - economics planning remote sensing reserve networks risk seagrasses Spatial planning Surrogate
Title	Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems
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