A key challenge in the effective management of marine ecosystems is translating from small scale studies of distribution and dynamics to the regional scale of management action. In many marine ecosystems, including the Hawaiian Archipelago, there are extensive survey data of nearshore communities from multiple investigators, representing a huge investment of resources. Often, these data are underutilized and remain of limited use to managers. In the Hawaiian Archipelago, at least seven separate entities are engaged in surveys of coral reef communities, with varying degrees of coordination. The synthesis of these data requires integrated modeling approaches at multiple scales. This study builds on an existing database and extends two existing models: the Coral Recovery Model (CRM) of stochastic coral recovery after disturbance and the COMBO model of the synergistic impacts of increasing acidification and temperature on coral reefs. Extending from this prior work is the application of two innovative modeling approaches (scale transition theory and fundamental niche modeling) to predict coral community composition and dynamics at the regional scale. Fundamental niche modeling uses multiple data fitting approaches (regression, machine learning, etc) to describe the relationship between species and their environments, using a split dataset for training and validation. This approach can generate a predictive and validated spatially continuous model of species distribution from discrete data points. The scale transition modeling will use the completed database of species distributions as the landscape on which species interactions occur. These interactions are described by a local model, here, based on recruitment, growth, and mortality from the Coral Recovery Model. In scale transition theory, the local model plus landscape information on the distribution and co-distribution of organisms and their environments predicts how a species assemblage responds (locally and regionally) to changes in biotic and abiotic factors on the landscape.
This project will generate four products relevant to ecosystem-based management of the Hawaiian Archipelago, resulting in significant impacts beyond the research community: (1) A Hawaiian Archipelago-wide GIS database of coral distribution, benthic community data, fish surveys, and other data gathered by CRAMP, NPS (National Park Service), various divisions in NOAA, the Hawaii Division of Aquatic Resources, and other sources into a single GIS database; (2) Validated, predictive, and spatially continuous maps of coral species distribution throughout the Archipelago; (3) A validated Coral Recovery Model for coral reef mitigation in the Main Hawaiian Islands; (4) Prediction of coral community response to climate change throughout the Hawaiian Archipelago, based on known and predicted coral distributions and the COMBO model.
The Hawaiian Archipelago is the most geographically isolated island chain in the world, and the coral reefs of the Hawaiian Archipelago comprise the majority of coral reefs in the United States. Anthropogenic threats to coral reef ecosystems have historically occurred at local scales, such as overfishing, sedimentation and nutrient loading through terrestrial run-off, and habitat destruction. These local risks are now compounded by risks at the global scale of climate change, where increasing atmospheric carbon dioxide is influencing the temperature, pH, and circulation patterns of the global oceans. Even as our understanding of these risks has increased, so has our understanding of the services provided by coral reef ecosystems, including seafood, recreation, nutrient cycling, and protection of shores from erosion and storm damage. The first hurdle in effective ecosystem management is the assessment of current condition. In many marine ecosystems, including the Hawaiian Archipelago, there are extensive survey data of nearshore communities from multiple investigators, including state and federal agencies, representing a huge investment of resources. Often, these data are underutilized or inaccessible and remain of limited use to scientists and managers. Therefore, the first achievement of this project was to synthesize and share archipelago-wide data from the many surveys of coral reef communities of the Hawaiian Archipelago into a single database of >15,000 records. Using this new database, we developed and validated statistical models to predict the distribution of coral throughout Hawai‘i. These models can be visualized as a continuous map of coral distribution and abundance for the dominant corals in Hawaii. These maps have been shared with local resource managers to better understand the impacts of management decisions and are available at the PacIOOS Voyager geographic information server (oos.soest.hawaii.edu). Coral distributions are net result of individual coral colonies changing through time. Individual colonies change through recruitment (establishment of a new coral colony), growth (the expansion of a coral colony), partial mortality (the death of part of a coral colony), fission (when a single colony breaks into smaller colonies), fusion (when multiple colonies fuse into a single colony), and colony death (the death of an entire colony). The way that these processes differ between sites can help us understand the environmental and anthropogenic factors that are impacting coral population growth. Ongoing monitoring efforts in Hawai‘i include permanent photo quadrats, in which the same small area of reef is photographed year after year. Using these photographs, we measured the changes in individual coral colonies through time, to compare differences across species and across sites. We found distinct differences in recruitment, growth, and partial mortality at sites around Maui will help managers identify the features at each of these sites that put corals at risk. Predicting the future condition of coral reefs in a changing climate is a fundamental challenge of our time. This project has made two revisions to the modeling assumptions that are currently used to predict the future fate of coral reefs. Assumption 1: Current models use shifts in aragonite saturation state to predict the response of coral reefs to ocean acidification. Instead, coral calcification is driven primarily by photosynthetic rate (available light) and limited by the efflux of protons from the corals. Assumption 2: Current models generally assume that coral reef calcification rate is equivalent to coral calcification rate; however, coral reefs communities include both corals and other calcifiers, such as crustose coralline algae, which are more sensitive than coral to increasing ocean acidity. In addition, coral reef calcification is measured chemically, while coral calcification is measured biologically, and these measures are not directly comparable. These flawed assumptions have limited the predictive capacity of current models for understanding reef response to climate change.
