Taking climate-smart governance to the high seas.

Comprehensive spatial planning in international waters is key to achieving ocean sustainability.

Embedding the value of coastal ecosystem services into climate change adaptation planning.

Coastal habitats, such as salt marshes and dune systems, can protect communities from hazards by reducing coastline exposure. However, these critical habitats and their diverse ecosystem services are threatened by coastal development and the impacts from a changing climate. Ever increasing pressure on coastal habitats calls for coastal climate adaptation efforts that mitigate or adapt to these pressures in ways that maintain the integrity of coastal landscapes. An important challenge for decisionmakers is determining the best mitigation and adaptation strategies that not only protect human lives and property, but also safeguard the ability of coastal habitats to provide a broad suite of benefits. Here, we present a potential pathway for local-scale climate change adaptation planning through the identification and mapping of natural habitats that provide the greatest benefits to coastal communities. The methodology coupled a coastal vulnerability model with a climate adaptation policy assessment in an effort to identify priority locations for nature-based solutions that reduce vulnerability of critical assets using feasible land-use policy methods. Our results demonstrate the critical role of natural habitats in providing the ecosystem service of coastal protection in California. We found that specific dune habitats play a key role in reducing erosion and inundation of the coastline and that several wetland areas help to absorb energy from storms and provide a protective service for the coast of Marin county, California, USA. Climate change and adaptation planning are globally relevant issues in which the scalability and transferability of solutions must be considered. This work outlines an iterative approach for climate adaptation planning at a local-scale, with opportunity to consider the scalability of an iterative science-policy engagement approach to regional, national, and international levels.

The role of large wild animals in climate change mitigation and adaptation.

Two major environmental challenges of our time are responding to climate change and reversing biodiversity decline. Interventions that simultaneously tackle both challenges are highly desirable. To date, most studies aiming to find synergistic interventions for these two challenges have focused on protecting or restoring vegetation and soils but overlooked how conservation or restoration of large wild animals might influence the climate mitigation and adaptation potential of ecosystems. However, interactions between large animal conservation and climate change goals may not always be positive. Here, we review wildlife conservation and climate change mitigation in terrestrial and marine ecosystems. We elucidate general principles about the biome types where, and mechanisms by which, positive synergies and negative trade-offs between wildlife conservation and climate change mitigation are likely. We find that large animals have the greatest potential to facilitate climate change mitigation at a global scale via three mechanisms: changes in fire regime, especially in previously low-flammability biomes with a new or intensifying fire regime, such as mesic grasslands or warm temperate woodlands; changes in terrestrial albedo, particularly where there is potential to shift from closed canopy to open canopy systems at higher latitudes; and increases in vegetation and soil carbon stocks, especially through a shift towards below-ground carbon pools in temperate, tropical and sub-tropical grassland ecosystems. Large animals also contribute to ecosystem adaptation to climate change by promoting complexity of trophic webs, increasing habitat heterogeneity, enhancing plant dispersal, increasing resistance to abrupt ecosystem change and through microclimate modification.

Estimating blue carbon sequestration under coastal management scenarios.

Restoring and protecting "blue carbon" ecosystems - mangrove forests, tidal marshes, and seagrass meadows - are actions considered for increasing global carbon sequestration. To improve understanding of which management actions produce the greatest gains in sequestration, we used a spatially explicit model to compare carbon sequestration and its economic value over a broad spatial scale (2500 km of coastline in southeastern Australia) for four management scenarios: (1) Managed Retreat, (2) Managed Retreat Plus Levee Removal, (3) Erosion of High Risk Areas, (4) Erosion of Moderate to High Risk Areas. We found that carbon sequestration from avoiding erosion-related emissions (abatement) would far exceed sequestration from coastal restoration. If erosion were limited only to the areas with highest erosion risk, sequestration in the non-eroded area exceeded emissions by 4.2 million Mg CO2 by 2100. However, losing blue carbon ecosystems in both moderate and high erosion risk areas would result in net emissions of 23.0 million Mg CO2 by 2100. The removal of levees combined with managed retreat was the strategy that sequestered the most carbon. Across all time points, removal of levees increased sequestration by only an additional 1 to 3% compared to managed retreat alone. Compared to the baseline erosion scenario, the managed retreat scenario increased sequestration by 7.40 million Mg CO2 by 2030, 8.69 million Mg CO2 by 2050, and 16.6 million Mg CO2 by 2100. Associated economic value followed the same patterns, with large potential value loss from erosion greater than potential gains from conserving or restoring ecosystems. This study quantifies the potential benefits of managed retreat and preventing erosion in existing blue carbon ecosystems to help meet climate change mitigation goals by reducing carbon emissions.

Parsing human and biophysical drivers of coral reef regimes.

Coral reefs worldwide face unprecedented cumulative anthropogenic effects of interacting local human pressures, global climate change and distal social processes. Reefs are also bound by the natural biophysical environment within which they exist. In this context, a key challenge for effective management is understanding how anthropogenic and biophysical conditions interact to drive distinct coral reef configurations. Here, we use machine learning to conduct explanatory predictions on reef ecosystems defined by both fish and benthic communities. Drawing on the most spatially extensive dataset available across the Hawaiian archipelago-20 anthropogenic and biophysical predictors over 620 survey sites-we model the occurrence of four distinct reef regimes and provide a novel approach to quantify the relative influence of human and environmental variables in shaping reef ecosystems. Our findings highlight the nuances of what underpins different coral reef regimes, the overwhelming importance of biophysical predictors and how a reef's natural setting may either expand or narrow the opportunity space for management interventions. The methods developed through this study can help inform reef practitioners and hold promises for replication across a broad range of ecosystems.

Combining fish and benthic communities into multiple regimes reveals complex reef dynamics.

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.

Advancing the integration of spatial data to map human and natural drivers on coral reefs.

A major challenge for coral reef conservation and management is understanding how a wide range of interacting human and natural drivers cumulatively impact and shape these ecosystems. Despite the importance of understanding these interactions, a methodological framework to synthesize spatially explicit data of such drivers is lacking. To fill this gap, we established a transferable data synthesis methodology to integrate spatial data on environmental and anthropogenic drivers of coral reefs, and applied this methodology to a case study location-the Main Hawaiian Islands (MHI). Environmental drivers were derived from time series (2002-2013) of climatological ranges and anomalies of remotely sensed sea surface temperature, chlorophyll-a, irradiance, and wave power. Anthropogenic drivers were characterized using empirically derived and modeled datasets of spatial fisheries catch, sedimentation, nutrient input, new development, habitat modification, and invasive species. Within our case study system, resulting driver maps showed high spatial heterogeneity across the MHI, with anthropogenic drivers generally greatest and most widespread on O'ahu, where 70% of the state's population resides, while sedimentation and nutrients were dominant in less populated islands. Together, the spatial integration of environmental and anthropogenic driver data described here provides a first-ever synthetic approach to visualize how the drivers of coral reef state vary in space and demonstrates a methodological framework for implementation of this approach in other regions of the world. By quantifying and synthesizing spatial drivers of change on coral reefs, we provide an avenue for further research to understand how drivers determine reef diversity and resilience, which can ultimately inform policies to protect coral reefs.

Seascape models reveal places to focus coastal fisheries management.

To design effective marine reserves and support fisheries, more information on fishing patterns and impacts for targeted species is needed, as well as better understanding of their key habitats. However, fishing impacts vary geographically and are difficult to disentangle from other factors that influence targeted fish distributions. We developed a set of fishing effort and habitat layers at high resolution and employed machine learning techniques to create regional-scale seascape models and predictive maps of biomass and body length of targeted reef fishes for the main Hawaiian Islands. Spatial patterns of fishing effort were shown to be highly variable and seascape models indicated a low threshold beyond which targeted fish assemblages were severely impacted. Topographic complexity, exposure, depth, and wave power were identified as key habitat variables that influenced targeted fish distributions and defined productive habitats for reef fisheries. High targeted reef fish biomass and body length were found in areas not easily accessed by humans, while model predictions when fishing effort was set to zero showed these high values to be more widely dispersed among suitable habitats. By comparing current targeted fish distributions with those predicted when fishing effort was removed, areas with high recovery potential on each island were revealed, with average biomass recovery of 517% and mean body length increases of 59% on Oahu, the most heavily fished island. Spatial protection of these areas would aid recovery of nearshore coral reef fisheries.

Fish with chips: tracking reef fish movements to evaluate size and connectivity of Caribbean marine protected areas.

Coral reefs and associated fish populations have experienced rapid decline in the Caribbean region and marine protected areas (MPAs) have been widely implemented to address this decline. The performance of no-take MPAs (i.e., marine reserves) for protecting and rebuilding fish populations is influenced by the movement of animals within and across their boundaries. Very little is known about Caribbean reef fish movements creating a critical knowledge gap that can impede effective MPA design, performance and evaluation. Using miniature implanted acoustic transmitters and a fixed acoustic receiver array, we address three key questions: How far can reef fish move? Does connectivity exist between adjacent MPAs? Does existing MPA size match the spatial scale of reef fish movements? We show that many reef fishes are capable of traveling far greater distances and in shorter duration than was previously known. Across the Puerto Rican Shelf, more than half of our 163 tagged fish (18 species of 10 families) moved distances greater than 1 km with three fish moving more than 10 km in a single day and a quarter spending time outside of MPAs. We provide direct evidence of ecological connectivity across a network of MPAs, including estimated movements of more than 40 km connecting a nearshore MPA with a shelf-edge spawning aggregation. Most tagged fish showed high fidelity to MPAs, but also spent time outside MPAs, potentially contributing to spillover. Three-quarters of our fish were capable of traveling distances that would take them beyond the protection offered by at least 40-64% of the existing eastern Caribbean MPAs. We recommend that key species movement patterns be used to inform and evaluate MPA functionality and design, particularly size and shape. A re-scaling of our perception of Caribbean reef fish mobility and habitat use is imperative, with important implications for ecology and management effectiveness.