Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics
Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these iss...
Ausführliche Beschreibung
Autor*in: |
Husband, E. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2022 |
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Schlagwörter: |
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Anmerkung: |
© The Author(s) 2022 |
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Übergeordnetes Werk: |
Enthalten in: Coral reefs - Berlin : Springer, 1982, 41(2022), 4 vom: 14. Apr., Seite 1199-1209 |
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Übergeordnetes Werk: |
volume:41 ; year:2022 ; number:4 ; day:14 ; month:04 ; pages:1199-1209 |
Links: |
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DOI / URN: |
10.1007/s00338-022-02247-6 |
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Katalog-ID: |
SPR047687835 |
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520 | |a Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. | ||
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10.1007/s00338-022-02247-6 doi (DE-627)SPR047687835 (SPR)s00338-022-02247-6-e DE-627 ger DE-627 rakwb eng Husband, E. verfasserin (orcid)0000-0002-4062-2600 aut Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 Perry, C. T. aut Lange, I. D. aut Enthalten in Coral reefs Berlin : Springer, 1982 41(2022), 4 vom: 14. Apr., Seite 1199-1209 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:41 year:2022 number:4 day:14 month:04 pages:1199-1209 https://dx.doi.org/10.1007/s00338-022-02247-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 41 2022 4 14 04 1199-1209 |
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10.1007/s00338-022-02247-6 doi (DE-627)SPR047687835 (SPR)s00338-022-02247-6-e DE-627 ger DE-627 rakwb eng Husband, E. verfasserin (orcid)0000-0002-4062-2600 aut Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 Perry, C. T. aut Lange, I. D. aut Enthalten in Coral reefs Berlin : Springer, 1982 41(2022), 4 vom: 14. Apr., Seite 1199-1209 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:41 year:2022 number:4 day:14 month:04 pages:1199-1209 https://dx.doi.org/10.1007/s00338-022-02247-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 41 2022 4 14 04 1199-1209 |
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10.1007/s00338-022-02247-6 doi (DE-627)SPR047687835 (SPR)s00338-022-02247-6-e DE-627 ger DE-627 rakwb eng Husband, E. verfasserin (orcid)0000-0002-4062-2600 aut Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 Perry, C. T. aut Lange, I. D. aut Enthalten in Coral reefs Berlin : Springer, 1982 41(2022), 4 vom: 14. Apr., Seite 1199-1209 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:41 year:2022 number:4 day:14 month:04 pages:1199-1209 https://dx.doi.org/10.1007/s00338-022-02247-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 41 2022 4 14 04 1199-1209 |
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10.1007/s00338-022-02247-6 doi (DE-627)SPR047687835 (SPR)s00338-022-02247-6-e DE-627 ger DE-627 rakwb eng Husband, E. verfasserin (orcid)0000-0002-4062-2600 aut Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 Perry, C. T. aut Lange, I. D. aut Enthalten in Coral reefs Berlin : Springer, 1982 41(2022), 4 vom: 14. Apr., Seite 1199-1209 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:41 year:2022 number:4 day:14 month:04 pages:1199-1209 https://dx.doi.org/10.1007/s00338-022-02247-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 41 2022 4 14 04 1199-1209 |
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10.1007/s00338-022-02247-6 doi (DE-627)SPR047687835 (SPR)s00338-022-02247-6-e DE-627 ger DE-627 rakwb eng Husband, E. verfasserin (orcid)0000-0002-4062-2600 aut Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 Perry, C. T. aut Lange, I. D. aut Enthalten in Coral reefs Berlin : Springer, 1982 41(2022), 4 vom: 14. Apr., Seite 1199-1209 (DE-627)268756112 (DE-600)1472576-9 1432-0975 nnns volume:41 year:2022 number:4 day:14 month:04 pages:1199-1209 https://dx.doi.org/10.1007/s00338-022-02247-6 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 41 2022 4 14 04 1199-1209 |
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At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). 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Husband, E. misc Coral misc Coral morphology misc Carbonate production misc ReefBudget misc Historical ecology Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics |
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Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics Coral (dpeaa)DE-He213 Coral morphology (dpeaa)DE-He213 Carbonate production (dpeaa)DE-He213 ReefBudget (dpeaa)DE-He213 Historical ecology (dpeaa)DE-He213 |
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estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics |
title_auth |
Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics |
abstract |
Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. © The Author(s) 2022 |
abstractGer |
Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. © The Author(s) 2022 |
abstract_unstemmed |
Abstract Recent interest in assessing coral reef functions has raised questions about how carbonate production rates have altered over the past few decades of ecological change. At the same time, there is growing interest in quantifying carbonate production on larger reef-scales. Resolving these issues is challenging because carbonate production estimates require three-dimensional survey data, which are typically collected in-situ over small spatial scales. In contrast, data that can be extracted from archive photograph or video imagery and high-resolution aerial imagery are generally planar. To address this disconnect, we collected data on the relationship between linear planar and 3D contour lengths of 62 common Indo-Pacific hard coral genera-morphotypes to establish appropriate conversion metrics (i.e. coral class rugosity values, hereafter termed Rcoral). These conversion values allow planar colony dimensions to be converted to estimates of 3D colony contour length, which can be employed within existing census budget methodologies like ReefBudget to estimate coral carbonate production (G, in kg $ CaCO_{3} $ $ m^{−2} $ $ yr^{−1} $). We tested this approach by comparing in-situ carbonate production data collected using the ReefBudget methodology against estimates derived from converted colony length data from video imagery. The data show a high level of consistency with an error of ~ 10%. We then demonstrate potential applications of the conversion metrics in two examples, the first using time-series (2006 to 2018) photo-quadrat imagery from Moorea, and the second using high-resolution drone imagery across different reef flat habitats from the Maldives. Whilst some degree of error must necessarily be accepted with such conversion techniques, the approach presented here offers exciting potential to calculate coral carbonate production: (1) from historical imagery to constrain past coral carbonate production rates; (2) from high quality aerial imagery for spatial up-scaling exercises; and (3) for use in rapid photograph or video-based assessments along reef systems where detailed surveys are not possible. © The Author(s) 2022 |
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container_issue |
4 |
title_short |
Estimating rates of coral carbonate production from aerial and archive imagery by applying colony scale conversion metrics |
url |
https://dx.doi.org/10.1007/s00338-022-02247-6 |
remote_bool |
true |
author2 |
Perry, C. T. Lange, I. D. |
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Perry, C. T. Lange, I. D. |
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doi_str |
10.1007/s00338-022-02247-6 |
up_date |
2024-07-03T14:20:40.763Z |
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|
score |
7.399665 |