Using ecological null models to assess the potential for marine protected area networks to protect biodiversity

Abstract

Marine protected area (MPA) networks have been proposed as a principal method for conserving biological diversity, yet patterns of diversity may ultimately complicate or compromise the development of such networks. We show how a series of ecological null models can be applied to assemblage data across sites in order to identify non-random biological patterns likely to influence the effectiveness of MPA network design. We use fish census data from Caribbean fore-reefs as a test system and demonstrate that: 1) site assemblages were nested, such that species found on sites with relatively few species were subsets of those found on sites with relatively many species, 2) species co-occurred across sites more than expected by chance once species-habitat associations were accounted for, and 3) guilds were most evenly represented at the richest sites and richness among all guilds was correlated (i.e., species and trophic diversity were closely linked). These results suggest that the emerging Caribbean marine protected area network will likely be successful at protecting regional diversity even if planning is largely constrained by insular, inventory-based design efforts. By recasting ecological null models as tests of assemblage patterns likely to influence management action, we demonstrate how these classic tools of ecological theory can be brought to bear in applied conservation problems.

Figure 1. The geographic distribution of survey sites used in our analysis of reef fish diversity in the Caribbean basin.

The sites circled by black rings represent the 20 (∼5% of all sites) most geographically separate sites based on a maximization of the minimum Euclidean distance between all sites.

Figure 2. Maximally packed presence-absence matrix of Caribbean reef fishes, such that species are sorted in order of ubiquity (rows) and sites are sorted in order of richness (columns).

Each darkened square indicates the presence of a species at a site. The curve represents the isocline of perfect nestedness subject to the constraints of perfect occupancy at the most diverse site, and perfect vacancy at the least diverse site.

Figure 3. Reserve network performance under three selection scenarios: 1) sites selected at random (black line), 2) sites selected by choosing the single richest site from each jurisdiction (red line), and 3) sites selected by choosing the richest sites regardless of jurisdiction (blue line).

We used the 15 country designations specified in the AGRRA database as our jurisdictional units. Each line represents the proportion of all species protected as a function of the number of reserved sites under each of the three scenarios. Error bars are ±1 standard deviation. For scenarios 2 and 3, when two or more sites had the same richness, one of these sites was selected at random (thus, scenario 3 has error bars). Similarly, when selecting fewer sites than the total number of jurisdictions considered in scenario 2, we randomly identified jurisdictions to choose sites from (thus, error bars decrease as the number of reserves approaches the number of jurisdictions).

Figure 4. The average relative proportion (y-axis) of Caribbean reef fish assemblages represented by each trophic guild as a function of site richness (x-axis).

Note that both predator trophic groups were completely absent from sites with relatively few species, suggesting that different forms of diversity may be decoupled at species poor sites.