As the threats to coral reefs mount, scientists and managers are looking for innovative ways to increase the scope, scale, and efficiency of coral reef monitoring. Monitoring changes in coral communities and demographic features provides key information about ecosystem function and resilience of reefs. While most monitoring programs continue to rely on in-water visual survey methods, scientists are exploring 3D imaging technologies such as photogrammetry, also known as Structure-from-Motion (SfM), to enhance precision of monitoring, increase logistical efficiency in the field, and generate a permanent record of the reef. Here, we quantitatively compare data generated from in-water surveys to SfM-derived metrics for assessing coral demography, bleaching, and diversity in the main Hawaiian Islands as part of NOAA’s National Coral Reef Monitoring Program. Our objectives were to compare between-method error to within-method error, test for bias between methods, and identify strengths and weaknesses of both methods. Colony density, average colony diameter, average partial mortality, prevalence of bleaching, species richness, and species diversity were recorded using both methods within the same survey areas. For all metrics, the magnitude of between-method error was comparable to the within-method error for the in-water method and between method error was significantly higher than within-method error for SfM for one of the seven metrics. Our results also reveal that a majority of the metrics do not vary significantly between methods, nor did we observe a significant interaction between method and habitat type or method and depth. Exceptions include estimates of partial mortality, bleaching prevalence, and Porites juvenile density–though differences between methods are generally small. Our study also highlights that SfM offers a unique opportunity to more rigorously quantify and mitigate inter-observer error by providing observers unlimited “bottom time” and the opportunity to work together to resolve difficult annotations. However, the necessary investment in equipment and expertise does present substantial up-front costs, and the time associated with curating imagery, photogrammetric modeling, and manual image annotation can reduce the timeliness of data reporting. SfM provides a powerful tool to reimagine how we study and manage coral reefs, and this study provides the first quantified methodological comparison to validate the transition from standard in-water methods to SfM survey methods for estimates of coral colony-level surveys.

Ecosystem-based Fisheries Management is a holistic management approach that integrates the dynamics of an entire ecosystem, including societal dimensions. However, this approach seldom lives up to its promise because economic and social objectives are rarely specified. To fill this gap, we explored how an ecosystem model could better integrate economic and social objectives, using the coral reef ecosystem around Hawai`i as a case study. After meeting with stakeholders and conducting a literature review of policy/strategy documents, we identified societal and ecological objectives and associated performance indicators for which data existed. We developed a social–ecological system conceptual framework to illustrate the relationships between ecological and social state components. This framework was the foundation for the development of the final social–ecological system model which we simulated using an Ecopath with Ecosim model. We simulated four gear/species restrictions for the reef-based fishery, two fishing scenarios associated with the opening of hypothetical no-take Marine Protected Areas for the deepwater-based fishery, and a Constant Effort (No Action) scenario. Despite limitations in the model, our approach shows that when social and economic objectives and social–ecological relationships are defined, we can quantify the trade-offs among the identified societal objectives to support managers in choosing among alternative interventions.