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Context: Coral reef resilience is the product of multiple interacting processes that occur across various interacting scales. This complexity presents challenges for identifying solutions to the ongoing worldwide decline of coral reef ecosystems that are threatened by both local and global human stressors. Objectives: We highlight how coral reef resilience is studied at spatial, temporal, and functional scales, and explore emerging technologies that are bringing new insights to our understanding of reef resilience. We then provide a framework for integrating insights across scales by using new and existing technological and analytical tools. We also discuss the implications of scale on both the ecological processes that lead to declines of reefs, and how we study those mechanisms. Methods: To illustrate, we present a case study from Kāneʻohe Bay, Hawaiʻi, USA, linking remotely sensed hyperspectral imagery to within-colony symbiont communities that show differential responses to stress. Results: In doing so, we transform the scale at which we can study coral resilience from a few individuals to entire ecosystems. Conclusions: Together, these perspectives guide best practices for designing management solutions that scale from individuals to ecosystems by integrating multiple levels of biological organization from cellular processes to global patterns of coral degradation and resilience. [ABSTRACT FROM AUTHOR]

Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs. Randomised controlled experiments are the gold standard for scientific inference, but environmental and social scientists often rely on different study designs. Here the authors analyse the use of six common study designs in the fields of biodiversity conservation and social intervention, and quantify the biases in their estimates. [ABSTRACT FROM AUTHOR]

Following the recent 2014–2017 global coral bleaching event, managers are seeking interventions to promote long-term resilience beyond monitoring coral decline. Here, we applied a spatial approach to investigate one potential intervention, mapping areas where local management could build coral reef resilience using herbivore management. Although herbivore management is a top recommendation in resilience-based management, site-specific attributes are thought to affect its success, and thus strategizing placement and design of these areas are crucial. Using Marxan, we mapped and prioritized potential Herbivore Management Areas (HMAs), where herbivores are protected but other types of fishing are allowed, in the main Hawaiian Islands. Through four scenarios, we found multiple hotspots along the west coast of Hawai'i Island and around the islands of Moloka'i, Lana'i, Maui, and Kaho'olawe where HMAs may have the best chance for success based on habitat, ecologically critical areas, life history, and social considerations. We further analyzed top results and found that a subset of characteristics including habitat types, biomass of herbivore functional groups, and temperature variability were significantly different from surrounding areas and thus contain potential drivers for selection. This unique approach can serve as an example for coral reef management in Hawai'i, on other Pacific Islands, and beyond, as it provides practical guidance on how to apply a resilience-building tool at a local level, incorporating site-specific biological and socioeconomic considerations. [ABSTRACT FROM AUTHOR]

Coral reefs worldwide face an uncertain future with many reefs reported to transition from being dominated by corals to macroalgae. However, given the complexity and diversity of the ecosystem, research on how regimes vary spatially and temporally is needed. Reef regimes are most often characterised by their benthic components; however, complex dynamics are associated with losses and gains in both fish and benthic assemblages. To capture this complexity, we synthesised 3,345 surveys from Hawai'i to define reef regimes in terms of both fish and benthic assemblages. Model-based clustering revealed five distinct regimes that varied ecologically, and were spatially heterogeneous by island, depth and exposure. We identified a regime characteristic of a degraded state with low coral cover and fish biomass, one that had low coral but high fish biomass, as well as three other regimes that varied significantly in their ecology but were previously considered a single coral dominated regime. Analyses of time series data reflected complex system dynamics, with multiple transitions among regimes that were a function of both local and global stressors. Coupling fish and benthic communities into reef regimes to capture complex dynamics holds promise for monitoring reef change and guiding ecosystem-based management of coral reefs. [ABSTRACT FROM AUTHOR]

Finding potentially varying scaling relations that link ecosystem services with LULC at different levels of the urban hierarchy, the authors speculate that scaling relations may have a role to play in conservation and planning policy. B Correction to: Landsc Ecol b https://doi.org/10.1007/s10980-022-01591-w In the original publication of the article we neglected to include a summary of the contribution by Sun et al. (2022) - I Spatial scaling of land use/land cover and ecosystem services across urban hierarchical levels: patterns and relationships i . We provide a brief summary and discussion of this article in this correction. [Extracted from the article]