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 km 2 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.

Multicriteria estimate of coral reef fishery sustainability

“…Variation in yield estimates are typically attributable to variation in production, multiple sources of primary production (including corals, reef algae, seagrass and plankton), complexity of species life histories, temporary large biomass removals that produce short‐term high yields and the vagile, flexible and efficient behaviours of both fish and fishers (Albert, Aswani, Fisher, & Albert, ; McClanahan et al., ; Zeller, Stoute, & Russ, ). Yet, environmental and ecological variation in Kenya is likely to be small because this single fringing reef system has clear geophysical boundaries containing similar habitats, species and environmental conditions (Carreiro‐Silva & McClanahan, ; Maina et al., ). Consequently, environmental and ecological complexity is unlikely to explain much of the observed variation.…”

“…Finally, knowing B 0 and r provided key empirical information for calibrating the MSY model but high variability in r indicates that the recovery rate is the key source of the yield uncertainty (McClanahan, 2018).Variation in yield estimates are typically attributable to variation in production, multiple sources of primary production (including corals, reef algae, seagrass and plankton), complexity of species life histories, temporary large biomass removals that produce short-term high yields and the vagile, flexible and efficient behaviours of both fish and fishers(Albert, Aswani, Fisher, & Albert, 2015;McClanahan et al, 2008;Zeller, Stoute, & Russ, 2003). Yet, environmental and ecological variation in Kenya is likely to be small because this single fringing reef system has clear geophysical boundaries containing similar habitats, species and environmental conditions(Carreiro-Silva & McClanahan, 2012;Maina et al, 2015).…”

Incorporating feasibility and collaboration into large-scale planning for regional recovery of coral reef fisheries

“…It is important to note that a limitation of this model is its inability to incorporate smaller scale local influences, such as benthic cover. While detailed benthic cover data would have been informative, data are only available for a small sub-section of the WIO (Maina et al 2015), so could not be included. Time-torecovery maps were developed using fish biomass recovery rates (kg yr −1 ) to thresholds for sustainable fishing (450 kg ha −1 ) and for conservation areas (1150 kg ha −1 ).…”

Outcomes of gear and closure subsidies in artisanal coral reef fisheries

“…Prior to and during this period, we made regular measurement on fishing gear and catches among a number of the landing sites of both counties. Details of these coral reefs and study sites have been presented in a number of papers (Maina et al, 2015;McClanahan & Kosgei, 2018).…”