Knowing the baseline state of a reef ecosystem requires time-series data that describes the ecosystem before degradation. However, datasets with this type of information are rare. Alternatively, expectations about recovery can be estimated spatiotemporally by characterizing reef health along a gradient of human-impacted habitat. Using 717 fisheries-independent reef monitoring surveys in the main Hawaiian Islands from 2012 and 2015, the authors created a hierarchical, linear Bayesian model to develop spatially explicit and locally relevant total biomass and potential recovery baselines. These baselines were used to characterize spatial variability in herbivorous and total reef fish biomass, and are relevant to coral reef resiliency planning. Areas with the highest capacity to support reef fish and herbivore biomass were identified, as well as areas with high recovery potential.

Inbreeding is prevalent in the small population of the endangered Southern Resident killer whale (Orcinus orca). Characterizing inbreeding is important for evaluating population viability and recovery potential. Building on previous work with 68-94 nuclear loci from 105 individuals, the authors evaluated the degree of inbreeding in the population, quantified the relationship between inbreeding, heterozygosity and fitness, and evaluated trends in the effective number of breeders. They found that two males sired 52% of the sampled progeny since 1990 and that male reproductive success increased with age. The effective number of breeders is currently 26, which is similar to historic trends of <25 breeders in the population. The authors attempted to evaluate relationships between survival or fecundity and inbreeding; while weak negative relationships with survival were found, this question will be addressed in more detail with ongoing work. The degree of inbreeding in Southern Residents highlights the need to better understand the effects of inbreeding in killer whales and other cetaceans more globally.

 Journal article 

Photo courtesy of NWFSC; Permit No. 16163-01

Skeletochronology offers the dual benefit of measuring annual longitudinal growth rates and detecting important growth spurts in sea turtles. The authors counted growth spurts in 267 humeri of deceased stranded Hawaiian green sea turtles (Chelonia mydas) to improve estimates of annual growth rates, growth spurt frequency, age at first reproduction, life stage, and time to grow from the interior-most line of arrested growth to the stranding date (representing the time of death). The authors found that sea turtles may actually experience faster lifetime growth rates and earlier age at first reproduction than previously estimated from traditional mark-recapture methods that are unable to detect growth spurts. This study estimated the age at first reproduction to be at 37.5 years. Also, growth spurts may occur throughout the turtle’s lifetime with peaks for males from 50 to 59.9 cm and females from 70 to 79.9 cm SCL.

New technology and methods for aerial cetacean surveys are constantly emerging and need to be compared to existing, accepted methods for efficiency, cost-effectiveness, and efficacy. The authors compared visual data collected using three methods: 1) marine mammal observers aboard a manned aircraft, 2) autonomously collected imagery from the manned aircraft, and 3) autonomously collected imagery from a ScanEagle unmanned aircraft system (UAS). These data were used to calculate ten different performance metrics evaluating the precision and uncertainty in abundance estimates, species identification, and cost. Results suggest that visual data collected by marine mammal observers required the least post-processing, were a fraction of the cost to collect and interpret, and provided estimates of cetacean density with lower uncertainty than the other two methods. The study concluded that the use of UAS for conducting broad scale, beyond line-of-sight surveys to estimate cetacean density and distribution holds promise, but it is premature to implement them at this time due to safety concerns, limitations in collecting and processing data, and cost.