MPA network design based on graph theory and emergent properties of larval dispersal

Abstract

Despite the recognised effectiveness of networks of marine protected areas (MPAs) as a biodiversity conservation instrument, MPA network design frequently disregards the importance of connectivity patterns. In the case of sedentary marine populations, connectivity stems not only from the stochastic nature of the physical environment that affects dispersal of early life stages, but also from the spawning stock attributes that affect reproductive output (e.g. passive eggs and larvae) and survivorship. Early life stages are virtually impossible to track in the ocean. Therefore, numerical ocean current simulations coupled with egg and larval Lagrangian transport models remain the most common approach for the assessment of marine larval connectivity. Inferred larval connectivity may differ depending on the type of connectivity considered; consequently, the prioritisation of sites for the conservation of marine populations might also differ. Here, we introduce a framework for evaluating and designing MPA networks based on the identification of connectivity hotspots using graph theoretic analysis. As a case study, we used a network of open-access areas and MPAs off Mallorca Island (Spain), and tested its effectiveness for the protection of the painted comber Serranus scriba. Outputs from network analysis were used to (1) identify critical areas for improving overall larval connectivity, (2) assess the impact of species’ biological parameters in network connectivity and (3) explore alternative MPA configurations to improve average network connectivity. Results demonstrate the potential of graph theory to identify non-trivial egg/larval dispersal patterns and emerging collective properties of the MPA network, which are relevant for increasing protection efficiency.

A network analysis of global cephalopod trade

“…In networks consisting of several nodes (e.g., social networks, Marine Protected Area networks, food webs, metapopulation connectivity, etc. ), some nodes play a decisive role in facilitating many network connections 22 – 26 . Such nodes are central in network organization and are often identified by a range of metrics known as centrality measures.…”

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

“…Nodes bridging clusters of MPAs have high betweenness centrality (Ospina-Alvarez et al, 2020), thus MPAs with higher betweenness values might function as stepping-stones between clusters and prevent fragmentation of the overall network. To facilitate interpretation, betweenness measures were normalized between 0 and 1, with 1 representing the highest betweenness value, proportionally to the relative importance as stepping-stones to maintain connectivity (Ospina-Alvarez et al, 2020). This normalization was performed by considering the maximum and minimum values of betweenness retrieved per cluster, in order to capture the less/more central MPAs, at the scales of each network aggregation.…”

A Graph Theory approach to assess nature’s contribution to people at a global scale

“…However, there are multiple interpretations of what makes a node important and there are therefore many measures of centrality 28 . We calculated different centrality measures and, after a first screening including 11 measured of centrality for the Instagram hashtags’ network (e.g., Degree, In-Degree, Out-Degree, Strength, HubScore; see Ospina-Alvarez et al 51 for a detailed description of the different measures), we selected betweenness and eigenvector centrality to illustrate and interpret the structure of the social networks.…”