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Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In 2007, due to growing concerns of declines in nearshore fisheries in Hawai‘i, a ban on gillnets was implemented in designated areas around the island of O‘ahu in the main Hawaiian Islands. Utilizing a 17 year time-series of juvenile fish abundance beginning prior to the implementation of the gillnet ban, we examined the effects of the ban on the abundance of juveniles of soft-bottom associated fish species. Using a Before-After-Control-Impact (BACI) sampling design, we compared the abundance of targeted fishery species in a bay where gillnet fishing was banned (Kailua, O‘ahu), and an adjacent bay where fishing is still permitted (Waimānalo, O‘ahu). Our results show that when multiple juvenile fish species were combined, abundance declined over time in both locations, but the pattern varied for each of the four species groups examined. Bonefishes were the only species group with a significant BACI effect, with higher abundance in Kailua in the period after the gillnet ban. This study addressed a need for scientific assessment of a fisheries regulation that is rarely possible due to lack of quality data before enactment of such restrictions. Thus, we developed a baseline status of juveniles of an important fishery species, and found effects of a fishery management regulation in Hawai‘i. [ABSTRACT FROM AUTHOR]

Much of coral reef ecology has focused on how human impacts change coral reefs to macroalgal reefs. However, macroalgae may not always be a good indicator of reef decline, especially on reefs with significant sea urchin populations, as found in Kenya and Hawaii. This study tests the effects of trophic interactions ( i.e. herbivory by fishes and sea urchins) and spatial competition (between algae and coral) on algal community structure of reefs surrounding two Hawaiian Islands that vary in their level of human impacts. Reef-building organisms (corals and crustose coralline algae) were less abundant and turf algae were more abundant on Maui as compared to Lanai, where human impacts are lower. In contrast to previous studies, we found no evidence that macroalgae increased with human impacts. Instead, low turf and macroalgal abundance were best explained by the interactive effects of coral cover and sea urchin abundance. Fishing sea urchin predators appeared to have cascading effects on the benthic community. The absence of sea urchin predators and high sea urchin densities correspond to a disproportionately high abundance of turf and crustose coralline algae. We propose that high turf algal abundance is a better indicator of reef decline in Hawaii than high macroalgal abundance because turf abundance was highest on reefs with low coral cover and few fish. The results of this study emphasize that understanding changes in community composition are context-dependent and that not all degraded reefs look the same. [ABSTRACT FROM AUTHOR]