Protection promotes energetically efficient structures in marine communities

Abstract

The sustainability of marine communities is critical for supporting many biophysical processes that provide ecosystem services that promote human well-being. It is expected that anthropogenic disturbances such as climate change and human activities will tend to create less energetically-efficient ecosystems that support less biomass per unit energy flow. It is debated, however, whether this expected development should translate into bottom-heavy (with small basal species being the most abundant) or top-heavy communities (where more biomass is supported at higher trophic levels with species having larger body sizes). Here, we combine ecological theory and empirical data to demonstrate that full marine protection promotes shifts towards top-heavy energetically-efficient structures in marine communities. First, we use metabolic scaling theory to show that protected communities are expected to display stronger top-heavy structures than disturbed communities. Similarly, we show theoretically that communities with high energy transfer efficiency display stronger top-heavy structures than communities with low transfer efficiency. Next, we use empirical structures observed within fully protected marine areas compared to disturbed areas that vary in stress from thermal events and adjacent human activity. Using a nonparametric causal-inference analysis, we find a strong, positive, causal effect between full marine protection and stronger top-heavy structures. Our work corroborates ecological theory on community development and provides a quantitative framework to study the potential restorative effects of different candidate strategies on protected areas.

Fig 1. Global distribution and attributes of study sites.

We analyzed 299 Reef Life Survey [37] sites which were surveyed more than once per year. The color of the circles corresponds to the number of species observed at a given site. The background color corresponds to the thermal stress anomalies (TSA), which are calculated as the sum of all the values of TSA between 1982 and 2019, at which the average value of TSA was above 1°C. The black lines show the borders of fully protected areas (Marine Protected Areas under IUCN Category Ia). This figure was created using www.naturalearthdata.com.

Fig 2. Theoretical predictions.

Using metabolic scaling theory (see Methods for details), Panel (A) depicts the distribution of Spearman’s rank correlation coefficients between average body size and average trophic level (ρ_{BM: TL}). Panel (B) shows an example of how simulated selective harvesting affects the body size (measured as body mass) distribution of species. Specifically, selective harvesting is expected to reduce the number of individuals and average body size of larger-bodied species. Panel (C) shows the distribution of the median predator-prey mass ratios (PPMR) in each simulated community. Panel (D) shows that protected marine communities (blue boxplots) are expected to display stronger top-heavy structures than disturbed communities (yellow boxplots). Community structure is measured by the community scaling coefficient (k_c), and higher values represent stronger top-heavy structures. Similarly, communities with higher transfer efficiency (TE_max) display stronger top-heavy structures than communities with lower efficiency. Horizontal dashed line shows the expected scaling coefficient (k_c = 0.25) based on the energetic equivalence hypothesis and lower values (light blue background) are the expected scaling coefficients accounting for trophic transfer efficiency.

Fig 3. Inferred causal graph.

Marine protection is the direct cause of community structure. Furthermore, thermal stress anomalies, coral reefs, and human density affect the placement of fully protected areas. The causal graph was inferred using a causal discovery algorithm (inductive causation) based on conditional independence testing. This figure was created using thenounproject.com.

Fig 4. Distribution of community structures across different marine and geographical properties.

The panels show the empirical distribution of community structures, measured as the regression coefficient ($k_c^e$) between log average individual body size and log population biomass. Higher values of $k_c^e$ represent stronger top-heavy structures. Human density is people per km² within 25-km radius (following Ref. [51]). High and Low categories are Distributions separated by protected communities (MPAs under IUCN Category Ia) and disturbed communities. We transform all quantitative variables into binary variables based on the median values. That is, values above the median are translated as V = 1, otherwise V = 0. We refer to V = 1 (resp. V = 0) to high (resp. low) values. Note that some variables are already binary by definition, such as the presence or absence of protection and coral reefs.