Potential Biodiversity Connectivity in the Network of Marine Protected Areas in Western Africa

Abstract

Marine Protected Areas (MPAs) must function as networks with sufficient stepping-stone continuity between suitable habitats to ensure the conservation of naturally connected regional pools of biodiversity in the long-term. For most marine biodiversity, population connectivity is mediated by passively dispersed planktonic stages with contrasting dispersal periods, ranging from a few hours to hundreds of days. These processes exert a major influence on whether threatened populations should be conserved as either isolated units or linked metapopulations. However, the distance scales at which individual MPAs are connected are insufficiently understood. Here, we use a biophysical model integrating high-resolution ocean currents and contrasting dispersal periods to predict connectivity across the Network of MPAs in Western Africa. Our results revealed that connectivity differs sharply among distinct ecological groups, from highly connected (e.g., fish and crustacea) to predominantly isolated ecosystem structuring species (e.g., corals, macroalgae and seagrass) that might potentially undermine conservation efforts because they are the feeding or nursery habitats required by many other species. Regardless of their dispersal duration, all ecological groups showed a common connectivity gap in the Bijagós region of Guinea-Bissau, highlighting the important role of MPAs there and the need to further support and increase MPA coverage to ensure connectivity along the whole network. Our findings provide key insights for the future management of the Network of MPAs in Western Africa, highlighting the need to protect and ensure continuity of isolated ecosystem structuring species and identifying key regions that function as stepping-stone connectivity corridors.

Coastal oceanographic connectivity estimates at the global scale

“…The simulations involved the daily release of passive Lagrangian particles from the centers of hexagon-shaped coastal sites (Figure 1), each side measuring 8.45 km, over a 21-year period from 2000 to 2020. These particles were subjected to horizontal advection by the ocean velocity fields for a maximum duration of 180 days, a period that encompasses the pelagic phase of the vast majority of marine species 7,15 . The position of each particle was calculated hourly through bilinear interpolation, in compliance with the Courant-Friedrichs-Lewy condition, until they either reached designated sink sites or got lost to the open ocean.…”

“…By simulating the movement of particles advected by oceanographic processes, biophysical models can predict dispersal pathways between populations and final settlement locations 15,16 . Importantly, when coupled with graph theory, biophysical models recurrently yield estimates of connectivity that mirror the observed patterns of marine biodiversity, from demography to genetics 2,3,14,17,18 .…”

“…Specific graph algorithms can compute multigenerational stepping-stone connectivity 12 or identify critical connectivity components with higher centrality that can bridge populations across large water masses 19 . Despite the significant advancements made through biophysical modeling in understanding the role of coastal oceanographic connectivity on marine biodiversity patterns 2,3,14,20 , and its implications for marine conservation and management 7,15,19 , research is hindered by the lack of a globally ready-to-use connectivity database. This limitation is impaired by the technical and computational requirements associated with the development of such complex modeling tools.…”

Biophysical modelling and graph theory identify key connectivity hubs in the Mediterranean marine reserve network

“…Estimates of connectivity between the Mediterranean marine reserves were inferred with a bio-physical numerical model (Assis et al, 2015;Buonomo et al, 2017;Assis et al, 2021a) that simulated the spatial and temporal distribution of drifting propagules (i.e., planktonic dispersal stages such as larvae, spores, gametes, seeds and drifting fragments) with information on ocean currents derived from the Hybrid Coordinate Ocean Model (HYCOM), a high-resolution hindcast of three-dimensional velocity fields (spatial resolution of 0.08°, approximately 7 km in the Mediterranean Sea, with 40 depth levels). The HYCOM model is forced by wind stress, wind speed, precipitation, and heat flux (Chassignet et al, 2007) and assimilates data from an array of satellites, bathythermographs, Argo floats and moored buoys (for additional information please refer to Chassignet et al, 2007; see Supplementary Figure S1 for a representation of the surface circulation in the Mediterranean Sea).…”

Seascape connectivity: ontogenetic migration model for Haemulon flavolineatum

“…Functional connectivity, on the other hand, describes the response of genes, gametes, propagules, or individuals to the landscape structure, as re ected in survival, reproduction, dispersal, migration, and settlement/recruitment (Crooks and Sanjayan 2006;Weeks 2017). Whereas real functional connectivity directly quanti es the movements of organisms, potential functional connectivity uses indirect knowledge about the dispersal or migration ability of the organisms (Fagan and Calabrese 2006;Assis et al 2021) and the species' life history data to simulate, model, and predict its connectivity in a seascape, particularly useful in remote areas with limited access to species ecological information.…”