Urgent need for coral demography in a world where corals are disappearing

Coral reefs have long attracted attention because of their biological and economic importance, but this interest now has turned to examining the possibility of functional extirpation. Widespread declines in coral abundances have fueled the shift in motivation for studying reefs and catalyzed the proliferation of monitoring to record the changes underway. Despite appreciation of monitoring as a scientific endeavor, its primary use has continued to be the quantification of cover of coral, macroalgae, and a few other space holders. The limitations of coral cover in evaluating the consequences of changing coral abundance were highlighted decades ago. Yet neglect of the tools most appropriate for this task (demographic approaches) and continuing emphasis on a tool (coral cover) that is not ideal, indicates that these limitations are not widely appreciated. Reef monitoring therefore continues to underperform with respect to its potential, thus depriving scientists of the approaches necessary to project the fate of coral reefs and test hypotheses focused on the proximal causes of declining coral cover. We make the case that the coral reef crisis creates a need for coral demography that is more acute now than 4 decades ago. Modern demographic approaches are well suited to meet this need, but to realize their potential, consideration will need to be given to the possibility of expanding ecological monitoring of coral reefs to provide the data necessary for demographic analyses of their foundation taxon, the Scleractinia

Coral community structure at Yawazi Point and Tektite in St. John before and after five hurricanes from 1988–2017

Dataset: yawzi point and tektiteThese files contain data that support an analysis of the effects of two major hurricanes on coral reefs that have been extensively studied for more than three decades. Major tropical storms are destructive phenomena with large effects on the community dynamics of multiple biomes. On coral reefs, their impacts have been described for decades, leading to the expectation that future storms should have effects similar to those recorded in the past. This expectation relies on the assumption that storm intensities will remain unchanged, and the impacted coral reef communities are similar to those of the recent past; neither assumption is correct. These data support a study quantifying the effects of two category five hurricanes on the reefs of St. John, US Virgin Islands, where 31 y of time-series analyses reveal chronic coral mortality, increasing macroalgal abundance, and five major hurricanes that caused acute coral mortality. Contextualized by these trends, the effects of the most recent storms, Hurricanes Irma and Maria (September 2017), on coral cover were modest. While mean absolute coral cover declined 1–4% depending on site, these effects were not statistically discernable. Following decades of increasing abundance of macroalgae, this functional group responded to the recent hurricanes with large increases in abundance on both absolute and relative scales. Decades of chronic mortality have changed the coral assemblages of St. John to create degraded communities that are resistant to severe storms. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/750060National Science Foundation (NSF) DEB-0841441, National Science Foundation (NSF) DEB-0343570, NSF Division of Environmental Biology (NSF DEB) DEB-1350146, NSF Division of Ocean Sciences (NSF OCE) OCE-180133

Coral community structure at pooled random sites between Cabritte Horn and White Point in St. John before and after five hurricanes from 1988–2017

Dataset: pooled random sites (PRS)These files contain data that support an analysis of the effects of two major hurricanes on coral reefs that have been extensively studied for more than three decades. Major tropical storms are destructive phenomena with large effects on the community dynamics of multiple biomes. On coral reefs, their impacts have been described for decades, leading to the expectation that future storms should have effects similar to those recorded in the past. This expectation relies on the assumption that storm intensities will remain unchanged, and the impacted coral reef communities are similar to those of the recent past; neither assumption is correct. These data support a study quantifying the effects of two category five hurricanes on the reefs of St. John, US Virgin Islands, where 31 y of time-series analyses reveal chronic coral mortality, increasing macroalgal abundance, and five major hurricanes that caused acute coral mortality. Contextualized by these trends, the effects of the most recent storms, Hurricanes Irma and Maria (September 2017), on coral cover were modest. While mean absolute coral cover declined 1–4% depending on site, these effects were not statistically discernable. Following decades of increasing abundance of macroalgae, this functional group responded to the recent hurricanes with large increases in abundance on both absolute and relative scales. Decades of chronic mortality have changed the coral assemblages of St. John to create degraded communities that are resistant to severe storms. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/750092National Science Foundation (NSF) DEB-0841441, National Science Foundation (NSF) DEB-0343570, NSF Division of Environmental Biology (NSF DEB) DEB-1350146, NSF Division of Ocean Sciences (NSF OCE) OCE-180133

Measurements of rainfall and surface light intensity (PAR) in St. John, US Virgin Islands from 2014-2017.

Dataset: Rainfall and surface light intensityData supporting publication through measurements of rainfall on St. John and surface light adjacent to Lameshur Bay. These data describe rainfall on the north shore of St. John as measured by R. Boulon using a manual rain gauge. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/739601NSF Division of Ocean Sciences (NSF OCE) OCE-1332915, NSF Division of Environmental Biology (NSF DEB) DEB-135014

Measurements of light intensity (PAR) underwater (19 m depth) in St. John, US Virgin Islands from 2014-2017.

Dataset: Light intensity at depthLight measured at depth (19 m) in Great Lameshur Bay, St. John using a cosine-corrected sensor with wiper. These data describe the core data in the manuscript and come from an Alec (brand) light sensor installed at 19 m depth. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/739892NSF Division of Ocean Sciences (NSF OCE) OCE-1332915, NSF Division of Environmental Biology (NSF DEB) DEB-135014

Summed coral cover along the four accessory transects in St. John from 1989 to 2017

Dataset: accessory transectsThese files contain data that support an analysis of the effects of two major hurricanes on coral reefs that have been extensively studied for more than three decades. Major tropical storms are destructive phenomena with large effects on the community dynamics of multiple biomes. On coral reefs, their impacts have been described for decades, leading to the expectation that future storms should have effects similar to those recorded in the past. This expectation relies on the assumption that storm intensities will remain unchanged, and the impacted coral reef communities are similar to those of the recent past; neither assumption is correct. These data support a study quantifying the effects of two category five hurricanes on the reefs of St. John, US Virgin Islands, where 31 y of time-series analyses reveal chronic coral mortality, increasing macroalgal abundance, and five major hurricanes that caused acute coral mortality. Contextualized by these trends, the effects of the most recent storms, Hurricanes Irma and Maria (September 2017), on coral cover were modest. While mean absolute coral cover declined 1–4% depending on site, these effects were not statistically discernable. Following decades of increasing abundance of macroalgae, this functional group responded to the recent hurricanes with large increases in abundance on both absolute and relative scales. Decades of chronic mortality have changed the coral assemblages of St. John to create degraded communities that are resistant to severe storms. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/750265National Science Foundation (NSF) DEB-0841441, National Science Foundation (NSF) DEB-0343570, NSF Division of Environmental Biology (NSF DEB) DEB-1350146, NSF Division of Ocean Sciences (NSF OCE) OCE-180133

Tank seawater conditions from Coral/Temperature/pCO2 Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_Corals project)

Dataset: MarBio. 2016: tank conditionsSummary of conditions in the eight tanks assigned randomly to create four treatments of ambient or high temperature and ambient or high CO2. These tanks were used to examine the responses of four species of calcifying coral to temperature and CO2 concentration. The experiments took place in Moorea, French Polynesia in January and April, 2011. These data were published in Brown & Edmunds (2016) Marine Biology, Table 1. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/641759NSF Ocean Sciences (NSF OCE) OCE-0417412, NSF Ocean Sciences (NSF OCE) OCE-1041270, NSF Ocean Sciences (NSF OCE) OCE-102685

Kd averages calculated by month from studies conducted in St. John, US Virgin Islands from 2014-2017.

Dataset: Kd averagesDiffuse attenuation coefficient (Kd) for light in reef water of Great Lameshur Bay. These data describe how light is attenuated with depth in seawater in Lameshur Bay, with the coefficient calculated using standard procedures constrain (as described in the ms) by using surface light instead of immediately sub surface For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/739882NSF Division of Ocean Sciences (NSF OCE) OCE-1332915, NSF Division of Environmental Biology (NSF DEB) DEB-135014

Calcification Rates and Biomass of 4 Coral Species, 2 Temperatures and 2 pCO2 Levels from Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_Corals project)

Dataset: MarBio. 2016: calcification and biomassThis dataset contains area-normalized calcification (mg cm-2 d-1) and biomass normalized calcification (mg mg-1) for Pocillopora meandrina, massive Porites spp., Acropora pulchra and Millepora platyphylla, as a function of pCO2 (408 µatm versus 913 µatm) and temperature (28.0°C and 30.1°C), collected and measured in Moorea in 2011. These data were published in Brown & Edmunds (2016) Marine Biology, Fig. 1. For a complete list of measurements, refer to the supplemental document 'Field_names.pdf', and a full dataset description is included in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: http://www.bco-dmo.org/dataset/641479NSF Ocean Sciences (NSF OCE) OCE-0417412, NSF Ocean Sciences (NSF OCE) OCE-1041270, NSF Ocean Sciences (NSF OCE) OCE-102685

Scaling the Effects of Ocean Acidification on Coral Growth and Coral-Coral Competition on Coral Community Recovery

Ocean acidification (OA) is negatively affecting calcification in a wide variety of marine organisms. These effects are acute for many tropical scleractinian corals under short-term experimental conditions, but it is unclear how these effects interact with ecological processes, such as competition for space, to impact coral communities over multiple years. This study sought to test the use of individual-based models (IBMs) as a tool to scale up the effects of OA recorded in short-term studies to community-scale impacts, combining data from field surveys and mesocosm experiments to parameterize an IBM of coral community recovery on the fore reef of Moorea, French Polynesia. Focusing on the dominant coral genera from the fore reef, Pocillopora, Acropora, Montipora and Porites, model efficacy first was evaluated through the comparison of simulated and empirical dynamics from 2010-2016, when the reef was recovering from sequential acute disturbances (a crown-of-thorns seastar outbreak followed by a cyclone) that reduced coral cover to ~0% by 2010. The model then was used to evaluate how the effects of OA (1,100-1,200 µatm pCO2) on coral growth and competition among corals affected recovery rates (as assessed by changes in % cover y-1) of each coral population between 2010-2016. The model indicated that recovery rates for the fore reef community was halved by OA over 7 years, with cover increasing at 11% y-1 under ambient conditions and 4.8% y-1 under OA conditions. However, when OA was implemented to affect coral growth and not competition among corals, coral community recovery increased to 7.2% y-1, highlighting mechanisms other than growth suppression (i.e., competition), through which OA can impact recovery. Our study reveals the potential for IBMs to assess the impacts of OA on coral communities at temporal and spatial scales beyond the capabilities of experimental studies, but this potential will not be realized unless empirical analyses address a wider variety of response variables representing ecological, physiological and functional domains