Fundamental knowledge of mortality during the planktonic phase of the typical marine life cycle is essential to understanding population dynamics and managing marine resources. However, estimating larval mortality is extremely challenging, because the fate of microscopic larvae cannot be tracked as they develop for weeks in ocean currents. We used a two-pronged approach to provide reliable estimates of larval mortality: (1) frequent, long-term sampling where the combination of larval behaviors and recirculation greatly reduces larval transport to and from the study area, and (2) an improved method of calculating larval mortality that consists of a vertical life table with a negative binomial distribution to account for the notorious patchiness of plankton. Larval mortality rates of our study species (barnacles and crabs) were ≤0.14 larvae/d, which produce survivorships over an order of magnitude higher than commonly determined for marine larvae. These estimates are reliable because they were similar for species with similar dispersal patterns. They are conservative because they were conducted in a highly advective upwelling system, and they may be even lower in other systems using our approach. Until other systems can be tested, our improved estimates should be used to inform future models of population dynamics and the evolution of life histories in the sea.

INTRODUCTION:To fill the void created by insufficient dental terminologies, a multi-institutional workgroup was formed among members of the Consortium for Oral Health Research and Informatics to develop the Dental Diagnostic System (DDS) in 2009. The adoption of dental diagnosis terminologies by providers must be accompanied by rigorous usability and validity assessments to ensure their effectiveness in practice. OBJECTIVES:The primary objective of this study was to describe the utilization and correct use of the DDS over a 4-y period. METHODS:Electronic health record data were amassed from 2013 to 2016 where diagnostic terms and Current Dental Terminology procedure code pairs were adjudicated by calibrated dentists. With the resultant data, we report on the 4-y utilization and validity of the DDS at 5 dental institutions. Utilization refers to the proportion of instances that diagnoses are documented in a structured format, and validity is defined as the frequency of valid pairs divided by the number of all treatment codes entered. RESULTS:Nearly 10 million procedures ( n = 9,946,975) were documented at the 5 participating institutions between 2013 and 2016. There was a 1.5-fold increase in the number of unique diagnoses documented during the 4-y period. The utilization and validity proportions of the DDS had statistically significant increases from 2013 to 2016 ( P < 0.0001). Academic dental sites were more likely to document diagnoses associated with orthodontic and restorative procedures, while the private dental site was equally likely to document diagnoses associated with all procedures. Overall, the private dental site had significantly higher utilization and validity proportions than the academic dental sites. CONCLUSION:The results demonstrate an improvement in utilization and validity of the DDS terminology over time. These findings also yield insight into the factors that influence the usability, adoption, and validity of dental terminologies, raising the need for more focused training of dental students. KNOWLEDGE TRANSFER STATEMENT:Ensuring that providers use standardized methods for documentation of diagnoses represents a challenge within dentistry. The results of this study can be used by clinicians when evaluating the utility of diagnostic terminologies embedded within the electronic health record.

Demographic connectivity is fundamental to the persistence and resilience of metapopulations, but our understanding of the link between reproduction and recruitment is notoriously poor in open-coast marine populations. We provide the first evidence of high local retention and limited connectivity among populations spanning 700 km along an open coast in an upwelling system. Using extensive field measurements of fecundity, population size and settlement in concert with a Bayesian inverse modelling approach, we estimated that, on average, Petrolisthes cinctipes larvae disperse only 6.9 km (±25.0 km s.d.) from natal populations, despite spending approximately six weeks in an open-coast system that was once assumed to be broadly dispersive. This estimate differed substantially from our prior dispersal estimate (153.9 km) based on currents and larval duration and behaviour, revealing the importance of employing demographic data in larval dispersal estimates. Based on this estimate, we predict that demographic connectivity occurs predominantly among neighbouring populations less than 30 km apart. Comprehensive studies of larval production, settlement and connectivity are needed to advance an understanding of the ecology and evolution of life in the sea as well as to conserve ecosystems. Our novel approach provides a tractable framework for addressing these questions for species occurring in discrete coastal populations.

Marine Protected Areas (MPAs) are increasingly established globally as a spatial management tool to aid in conservation and fisheries management objectives. Assessing whether MPAs are having the desired effects on populations requires effective monitoring programs. A cornerstone of an effective monitoring program is an assessment of the statistical power of sampling designs to detect changes when they occur. We present a novel approach to power assessment that combines spatial point process models, integral projection models (IPMs) and sampling simulations to assess the power of different sample designs across a network of MPAs. We focus on the use of remotely operated vehicle (ROV) video cameras as the sampling method, though the results could be extended to other sampling methods. We use empirical data from baseline surveys of an example indicator fish species across three MPAs in California, USA as a case study. Spatial models simulated time series of spatial distributions across sites that accounted for the effects of environmental covariates, while IPMs simulated expected trends over time in abundances and sizes of fish. We tested the power of different levels of sampling effort (i.e., the number of 500-m ROV transects) and temporal replication (every 1-3 yr) to detect expected post-MPA changes in fish abundance and biomass. We found that changes in biomass are detectable earlier than changes in abundance. We also found that detectability of MPA effects was higher in sites with higher initial densities. Increasing the sampling effort had a greater effect than increasing sampling frequency on the time taken to achieve high power. High power was best achieved by combining data from multiple sites. Our approach provides a powerful tool to explore the interaction between sampling effort, spatial distributions, population dynamics, and metrics for detecting change in previously fished populations.

Acute environmental stressors such as short-term exposure to pollutants can have lasting effects on organisms, potentially impacting future generations. Parental exposure to toxicants can result in changes to the epigenome (e.g., DNA methylation) that are passed down to subsequent, unexposed generations. However, it is difficult to gauge the cumulative population-scale impacts of epigenetic effects from laboratory experiments alone. Here, we developed a size- and age-structured delay-coordinate population model to evaluate the long-term consequences of epigenetic modifications on population sustainability. The model emulated changes in growth, mortality, and fecundity in the F0, F1, and F2 generations observed in experiments in which larval Menidia beryllina were exposed to environmentally relevant concentrations of bifenthrin (Bif), ethinylestradiol (EE2), levonorgestrel (LV), or trenbolone (TB) in the parent generation (F0) and reared in clean water up to the F2 generation. Our analysis suggests potentially dramatic population-level effects of repeated, chronic exposures of early-life stage fish that are not captured by models not accounting for those effects. Simulated exposures led to substantial declines in population abundance (LV and Bif) or near-extinction (EE2 and TB) with the exact trajectory and timeline of population decline dependent on the combination of F0, F1, and F2 effects produced by each compound. Even acute one-time exposures of each compound led to declines and recovery over multiple years due to lagged epigenetic effects. These results demonstrate the potential for environmentally relevant concentrations of commonly used compounds to impact the population dynamics and sustainability of an ecologically relevant species and model organism.

California responded to concerns about overfishing in the 1990s by implementing a network of marine protected areas (MPAs) through two science-based decision-making processes. The first process focused on the Channel Islands, and the second addressed California's entire coastline, pursuant to the state's Marine Life Protection Act (MLPA). We review the interaction between science and policy in both processes, and lessons learned. For the Channel Islands, scientists controversially recommended setting aside 30-50% of coastline to protect marine ecosystems. For the MLPA, MPAs were intended to be ecologically connected in a network, so design guidelines included minimum size and maximum spacing of MPAs (based roughly on fish movement rates), an approach that also implicitly specified a minimum fraction of the coastline to be protected. As MPA science developed during the California processes, spatial population models were constructed to quantify how MPAs were affected by adult fish movement and larval dispersal, i.e., how population persistence within MPA networks depended on fishing outside the MPAs, and how fishery yields could either increase or decrease with MPA implementation, depending on fishery management. These newer quantitative methods added to, but did not supplant, the initial rule-of-thumb guidelines. In the future, similar spatial population models will allow more comprehensive evaluation of the integrated effects of MPAs and conventional fisheries management. By 2011, California had implemented 132 MPAs covering more than 15% of its coastline, and now stands on the threshold of the most challenging step in this effort: monitoring and adaptive management to ensure ecosystem sustainability.

Adaptive management of marine protected areas (MPAs) requires developing methods to evaluate whether monitoring data indicate that they are performing as expected. Modeling the expected responses of targeted species to an MPA network, with a clear timeline for those expectations, can aid in the development of a monitoring program that efficiently evaluates expectations over appropriate time frames. Here, we describe the expected trajectories in abundance and biomass following MPA implementation for populations of 19 nearshore fishery species in California. To capture the process of filling in the age structure truncated by fishing, we used age-structured population models with stochastic larval recruitment to predict responses to MPA implementation. We implemented both demographically open (high larval immigration) and closed (high self-recruitment) populations to model the range of possible trajectories as they depend on recruitment dynamics. From these simulations, we quantified the time scales over which anticipated increases in abundance and biomass inside MPAs would become statistically detectable. Predicted population biomass responses range from little change, for species with low fishing rates, to increasing by a factor of nearly seven, for species with high fishing rates before MPA establishment. Increases in biomass following MPA implementation are usually greater in both magnitude and statistical detectability than increases in abundance. For most species, increases in abundance would not begin to become detectable for at least 10 years after implementation. Overall, these results inform potential indicator metrics (biomass), potential indicator species (those with a high fishing : natural mortality ratio), and time frame (>10 yr) for MPA monitoring assessment as part of the adaptive management process.