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Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps

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Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps. / Maina, Joseph M.; Jones, Kendall R.; Hicks, Christina et al.
In: Remote Sensing, Vol. 7, No. 12, 08.12.2015, p. 16571-16587.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Maina, JM, Jones, KR, Hicks, C, McClanahan, TR, Watson, JEM, Tuda, AO & Andréfouët , S 2015, 'Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps', Remote Sensing, vol. 7, no. 12, pp. 16571-16587. https://doi.org/10.3390/rs71215849

APA

Maina, J. M., Jones, K. R., Hicks, C., McClanahan, T. R., Watson, J. E. M., Tuda, A. O., & Andréfouët , S. (2015). Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps. Remote Sensing, 7(12), 16571-16587. https://doi.org/10.3390/rs71215849

Vancouver

Maina JM, Jones KR, Hicks C, McClanahan TR, Watson JEM, Tuda AO et al. Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps. Remote Sensing. 2015 Dec 8;7(12):16571-16587. doi: 10.3390/rs71215849

Author

Maina, Joseph M. ; Jones, Kendall R. ; Hicks, Christina et al. / Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps. In: Remote Sensing. 2015 ; Vol. 7, No. 12. pp. 16571-16587.

Bibtex

@article{f887db0b9f7341a88514f5f3eeb9c4b5,
title = "Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps",
abstract = "Decision making for the conservation and management of coral reef biodiversity requires an understanding of spatial variability and distribution of reef habitat types. Despite the existence of very high-resolution remote sensing technology for nearly two decades, comprehensive assessment of coral reef habitats at national to regional spatial scales and at very high spatial resolution is still scarce. Here, we develop benthic habitat maps at a sub-national scale by analyzing large multispectral QuickBird imagery dataset covering ~686 km2 of the main shallow coral fringing reef along the southern border with Tanzania (4.68°S, 39.18°E) to the reef end at Malindi, Kenya (3.2°S, 40.1°E). Mapping was conducted with a user approach constrained by ground-truth data, with detailed transect lines from the shore to the fore reef. First, maps were used to evaluate the present management system{\textquoteright}s effectiveness at representing habitat diversity. Then, we developed three spatial prioritization scenarios based on differing objectives: (i) minimize lost fishing opportunity; (ii) redistribute fisheries away from currently overfished reefs; and (iii) minimize resource use conflicts. We further constrained the priority area in each prioritization selection scenario based on optionally protecting the least or the most climate exposed locations using a model of exposure to climate stress. We discovered that spatial priorities were very different based on the different objectives and on whether the aim was to protect the least or most climate-exposed habitats. Our analyses provide a spatially explicit foundation for large-scale conservation and management strategies that can account for ecosystem service benefits.",
keywords = "Africa, climate adaptation strategies, coral and seagrass habitat, Indian Ocean, multi-stakeholder use, Marxan , scenario analysis",
author = "Maina, {Joseph M.} and Jones, {Kendall R.} and Christina Hicks and McClanahan, {Tim R.} and Watson, {James E. M.} and Tuda, {Arthur O.} and Serge Andr{\'e}fou{\"e}t",
year = "2015",
month = dec,
day = "8",
doi = "10.3390/rs71215849",
language = "English",
volume = "7",
pages = "16571--16587",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "MDPI AG",
number = "12",

}

RIS

TY - JOUR

T1 - Designing climate-resilient marine protected area networks by combining remotely sensed coral reef habitat with coastal multi-use maps

AU - Maina, Joseph M.

AU - Jones, Kendall R.

AU - Hicks, Christina

AU - McClanahan, Tim R.

AU - Watson, James E. M.

AU - Tuda, Arthur O.

AU - Andréfouët , Serge

PY - 2015/12/8

Y1 - 2015/12/8

N2 - Decision making for the conservation and management of coral reef biodiversity requires an understanding of spatial variability and distribution of reef habitat types. Despite the existence of very high-resolution remote sensing technology for nearly two decades, comprehensive assessment of coral reef habitats at national to regional spatial scales and at very high spatial resolution is still scarce. Here, we develop benthic habitat maps at a sub-national scale by analyzing large multispectral QuickBird imagery dataset covering ~686 km2 of the main shallow coral fringing reef along the southern border with Tanzania (4.68°S, 39.18°E) to the reef end at Malindi, Kenya (3.2°S, 40.1°E). Mapping was conducted with a user approach constrained by ground-truth data, with detailed transect lines from the shore to the fore reef. First, maps were used to evaluate the present management system’s effectiveness at representing habitat diversity. Then, we developed three spatial prioritization scenarios based on differing objectives: (i) minimize lost fishing opportunity; (ii) redistribute fisheries away from currently overfished reefs; and (iii) minimize resource use conflicts. We further constrained the priority area in each prioritization selection scenario based on optionally protecting the least or the most climate exposed locations using a model of exposure to climate stress. We discovered that spatial priorities were very different based on the different objectives and on whether the aim was to protect the least or most climate-exposed habitats. Our analyses provide a spatially explicit foundation for large-scale conservation and management strategies that can account for ecosystem service benefits.

AB - Decision making for the conservation and management of coral reef biodiversity requires an understanding of spatial variability and distribution of reef habitat types. Despite the existence of very high-resolution remote sensing technology for nearly two decades, comprehensive assessment of coral reef habitats at national to regional spatial scales and at very high spatial resolution is still scarce. Here, we develop benthic habitat maps at a sub-national scale by analyzing large multispectral QuickBird imagery dataset covering ~686 km2 of the main shallow coral fringing reef along the southern border with Tanzania (4.68°S, 39.18°E) to the reef end at Malindi, Kenya (3.2°S, 40.1°E). Mapping was conducted with a user approach constrained by ground-truth data, with detailed transect lines from the shore to the fore reef. First, maps were used to evaluate the present management system’s effectiveness at representing habitat diversity. Then, we developed three spatial prioritization scenarios based on differing objectives: (i) minimize lost fishing opportunity; (ii) redistribute fisheries away from currently overfished reefs; and (iii) minimize resource use conflicts. We further constrained the priority area in each prioritization selection scenario based on optionally protecting the least or the most climate exposed locations using a model of exposure to climate stress. We discovered that spatial priorities were very different based on the different objectives and on whether the aim was to protect the least or most climate-exposed habitats. Our analyses provide a spatially explicit foundation for large-scale conservation and management strategies that can account for ecosystem service benefits.

KW - Africa

KW - climate adaptation strategies

KW - coral and seagrass habitat

KW - Indian Ocean

KW - multi-stakeholder use

KW - Marxan

KW - scenario analysis

U2 - 10.3390/rs71215849

DO - 10.3390/rs71215849

M3 - Journal article

VL - 7

SP - 16571

EP - 16587

JO - Remote Sensing

JF - Remote Sensing

SN - 2072-4292

IS - 12

ER -