Abstract
AbstractA Marine Protected Area (MPA) network, in which multiple reserves are designated in a region, can promote the protection of biodiversity across space. To be effective as a network, the design must consider whether MPAs are likely to be connected through the movement of individuals of species of interest. Additionally, network design may explicitly incorporate design features that promote biodiversity in unprotected habitats through the dispersal or spillover of multiple species. Patterns of dispersal and the ability of MPAs to function as an interacting network, however, are difficult to estimate at broad and transboundary spatial scales, and therefore connectivity is often not fully integrated in the design and assessment of MPA networks. Here, we model the dispersal of multiple nearshore species to estimate the potential connectivity of the existing MPAs in British Columbia, Canada, including connections to MPAs in the United States by simulating dispersal using a biophysical model with regional oceanographic currents. We found that MPAs in BC potentially meet connectivity design criteria for nearshore invertebrate species: the majority of MPAs (65-90%) are likely to exchange individuals (i.e. functional connectivity) and support persistent metapopulations, and more than half the unprotected coast (55-85%) receives a large proportion of the larvae produced in MPAs. Furthermore, we found that species’ dispersal abilities and the level of exposure of an MPA to open ocean can predict dispersal distance when we account for the random effects of dispersal location and season. Therefore, future predictions of connectivity are possible based on these core biological and physical attributes, without running new simulations. Together, these analyses provide a robust and novel assessment of multi-species connectivity that can support the design of new MPAs with transboundary connectivity on the northwest coast of North America.
Publisher
Cold Spring Harbor Laboratory
Reference67 articles.
1. Larval dispersal of intertidal organisms and the influence of coastline geography;Ecography,2014
2. Anderson SC , Ward EJ , English PA , Barnett LAK (2022) SdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv:1–17.
3. Artzy-Randrup Y , Stone L (2010) Connectivity, cycles, and persistence thresholds in metapopulation networks. PLoS Computational Biology 6.
4. Balbar AC , Daigle RM , Heaslip SG , Jeffery NW , Proudfoot B , Robb CK , Rubidge E , Stanley R (2020) Approaches for Assessing and Monitoring Representation, Replication, and Connectivity in Marine Conservation Networks Canadian Science Advisory Secretariat (CSAS) National Capital Region Approaches for As.
5. The current application of ecological connectivity in the design of marine protected areas;Global Ecology and Conservation,2019