The Micronesia Challenge: Assessing the Relative Contribution of Stressors on Coral Reefs to Facilitate Science-to-Management Feedback

Fishing and pollution are chronic stressors that can prolong recovery of coral reefs and contribute to ecosystem decline. While this premise is generally accepted, management interventions are complicated because the contributions from individual stressors are difficult to distinguish. The present study examined the extent to which fishing pressure and pollution predicted progress towards the Micronesia Challenge, an international conservation strategy initiated by the political leaders of 6 nations to conserve at least 30% of marine resources by 2020. The analyses were rooted in a defined measure of coral-reef-ecosystem condition, comprised of biological metrics that described functional processes on coral reefs. We report that only 42% of the major reef habitats exceeded the ecosystem-condition threshold established by the Micronesia Challenge. Fishing pressure acting alone on outer reefs, or in combination with pollution in some lagoons, best predicted both the decline and variance in ecosystem condition. High variances among ecosystem-condition scores reflected the large gaps between the best and worst reefs, and suggested that the current scores were unlikely to remain stable through time because of low redundancy. Accounting for the presence of marine protected area (MPA) networks in statistical models did little to improve the models\u27 predictive capabilities, suggesting limited efficacy of MPAs when grouped together across the region. Yet, localized benefits of MPAs existed and are expected to increase over time. Sensitivity analyses suggested that (i) grazing by large herbivores, (ii) high functional diversity of herbivores, and (iii) high predator biomass were most sensitive to fishing pressure, and were required for high ecosystem-condition scores. Linking comprehensive fisheries management policies with these sensitive metrics, and targeting the management of pollution, will strengthen the Micronesia Challenge and preserve ecosystem services that coral reefs provide to societies in the face of climate change

Local Stressors, Resilience, and Shifting Baselines on Coral Reefs.

Understanding how and why coral reefs have changed over the last twenty to thirty years is crucial for sustaining coral-reef resilience. We used a historical baseline from Kosrae, a typical small island in Micronesia, to examine changes in fish and coral assemblages since 1986. We found that natural gradients in the spatial distribution of fish and coral assemblages have become amplified, as island geography is now a stronger determinant of species abundance patterns, and habitat forming Acropora corals and large-bodied fishes that were once common on the leeward side of the island have become scarce. A proxy for fishing access best predicted the relative change in fish assemblage condition over time, and in turn, declining fish condition was the only factor correlated with declining coral condition, suggesting overfishing may have reduced ecosystem resilience. Additionally, a proxy for watershed pollution predicted modern coral assemblage condition, suggesting pollution is also reducing resilience in densely populated areas. Altogether, it appears that unsustainable fishing reduced ecosystem resilience, as fish composition has shifted to smaller species in lower trophic levels, driven by losses of large predators and herbivores. While prior literature and anecdotal reports indicate that major disturbance events have been rare in Kosrae, small localized disturbances coupled with reduced resilience may have slowly degraded reef condition through time. Improving coral-reef resilience in the face of climate change will therefore require improved understanding and management of growing artisanal fishing pressure and watershed pollution

Linear regression depicting the influence of fishing access on the relative change in fish condition through time (a), and correlation depicting the relationship between the relative change in fish condition and the relative change in coral condition (b).

<p>Linear regression depicting the influence of fishing access on the relative change in fish condition through time (a), and correlation depicting the relationship between the relative change in fish condition and the relative change in coral condition (b).</p

Map of Kosrae showing the location of sites surveyed in 1986 (circles) and 2015 (squares).

<p>The four major fishing marinas are indicated by stars, which are scaled by the number of boats housed within. Overlapping sites that were surveyed in both timeframes are indiated with brackets and asterisks. Open-access geographic information systems mapping layers were obtained from <a href="http://freegisdata.rtwilson.com" target="_blank">http://freegisdata.rtwilson.com</a>.</p

Coral functional groups contributing the top 50% of coral assemblage composition in high and low wave energy in 1986 and 2015.

<p>Coral functional groups contributing the top 50% of coral assemblage composition in high and low wave energy in 1986 and 2015.</p

Depicition showing how individual metrics of fish and coral assemblages were combined to form latent variables of overall fish and coral condition, and how latent variables were used to test the influence of environmental factors on fish and coral changes through time.

<p>Depicition showing how individual metrics of fish and coral assemblages were combined to form latent variables of overall fish and coral condition, and how latent variables were used to test the influence of environmental factors on fish and coral changes through time.</p

Principal component plots of fish (a, b) and coral (c, d) assemblage structure in 1986 and 2015.

<p>Major functional groups driving community structure are shown. Wave energy and watershed size were overlaid if they were significant predictors of assemblage structure. “Large” and “small” labels correspond to large-bodied and small-bodied groups refered to in the text.</p

Fish functional groups contributing the top 50% of fish assemblage composition in high and low wave energy in 1986 and 2015.

<p>“Large” and “small” labels correspond to large-bodied and small-bodied groups refered to in the text.</p

Violin plots showing the mean Bray-Curtis similarity values for fish (a) and coral (b) assemblages in high and low wave energy zones in 1986 and 2015.

<p>The white dots indicates the median, and the black bars indicate the interquartile range. Significant differences (p<0.05) are indicated with a single asterisk.</p