Evaluating the impact of accounting for coral cover in large‐scale marine conservation prioritizations

Abstract

Aim: Mega-diverse coral reef ecosystems are declining globally, necessitating conservation prioritizations to protect biodiversity and ecosystem services of sites with high functional integrity to promote persistence. In practice however, the design of marine-protected area (MPA) systems often relies on broad classifications of habitat class and size, making the tacit assumption that all reefs are of comparable condition.We explored the impact of this assumption through a novel, pragmatic approach for incorporating variability in coral cover in a large-scale regional spatial prioritization plan.Location: The Coral Triangle. Methods:We developed a spatially explicit predictive model of hard coral cover based on freely available macro-ecological data to generate a complete regional map of coral cover as a proxy for reef condition. We then incorporate this information in spatial conservation prioritization software Marxan to design an MPA system that meets specific conservation objectives. Results:We discover prioritizations using area-based representation of reef habitat alone may overestimate the conservation benefit, defined as the amount of hard coral cover protected, by up to 64%. We find substantial differences in conservation priorities and an overall increase in habitat quality metrics when accounting for predicted coral cover.Main conclusions: This study shows that including habitat condition in a large-scale marine spatial prioritization is feasible within time and resource constraints, and calls for increased implementation, and evaluation, of such ecologically relevant planning approaches to enhance potential conservation effectiveness. K E Y W O R D S coral cover, Coral Triangle, Marxan, reef health, spatial prioritization, systematic conservation planning | 1565 VERCAMMEN Et Al.

Environmental Variability and Threshold Model’s Predictions for Coral Reefs

“…Two other key variables of TMs are the mean summer temperature and rate of SST rise, with pH also being a core part of future predictions (Camp et al, 2018). SST rise and pH did not predict the state of coral cover in our empirical study but pH was a significant variable in the Coral Triangle model (Vercammen et al, 2019). Additionally, while mean SST was the 3rd strongest predictor, the relationship found here was u-shaped rather than a decline in cover as mean temperatures increased.…”

“…Cover declined as SST distribution tails became thinner and right skewed, as would be predicted where there is poor acclimation to moderate chronic stress. In some cases, other related proxies, such as daily, seasonal, and annual temperature ranges were good predictors of bleaching and coral cover (Safaie et al, 2018;Vercammen et al, 2019). The maximum and range of SSTs are among the Bio-Oracle SST data options and found to be the 2nd and 3rd strongest environmental variables in predicting coral cover in the Coral Triangle (Vercammen et al, 2019).…”

“…As empirical data accumulates specific to each region or SST cluster, the accuracy of predictions should increase beyond those provided by the current largerscale options. For example, ecoregion has been shown to be strong predictor of coral sensitivity to exposure, even stronger than dissolved oxygen when examined for the Coral Triangle (Vercammen et al, 2019;McClanahan et al, 2020b). Our study was hampered by incomplete and non-random sampling biases at the ecoregion level, which prevented us from using ecoregion as a predictive variable.…”

“…The importance of these variables was not peculiar to the WIO. For example, a large modelling study of coral cover in 24 ecoregions of the Coral Triangle found dissolved oxygen to be the single strongest environmental predictor of cover and calcite to be 6 th among the 17 variables evaluated (Vercammen et al, 2019). Thus, these variables exhibit similar influences in both regions and are likely to be globally influential rather spatially-restricted drivers of coral cover.…”

“…To broaden the scope of the potential impacts of the environment on coral cover beyond SST, we extracted a number of abiotic variables previously found to influence the distribution and abundance of hard scleractinian corals (Vercammen et al, 2019). Variables extracted from Bio-ORACLE 2 (Tyberghein et al, 2012;Assis et al, 2018) included surface photosynthetically active radiation (PAR), diffuse water-penetration attenuation coefficient at 490nm, calcite concentration, dissolved oxygen, and pH (Supplementary Table 2).…”