Setting expected timelines of fished population recovery for the adaptive management of a marine protected area network.

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.

Long-term, high frequency in situ measurements of intertidal mussel bed temperatures using biomimetic sensors.

At a proximal level, the physiological impacts of global climate change on ectothermic organisms are manifest as changes in body temperatures. Especially for plants and animals exposed to direct solar radiation, body temperatures can be substantially different from air temperatures. We deployed biomimetic sensors that approximate the thermal characteristics of intertidal mussels at 71 sites worldwide, from 1998-present. Loggers recorded temperatures at 10-30 min intervals nearly continuously at multiple intertidal elevations. Comparisons against direct measurements of mussel tissue temperature indicated errors of ~2.0-2.5 °C, during daily fluctuations that often exceeded 15°-20 °C. Geographic patterns in thermal stress based on biomimetic logger measurements were generally far more complex than anticipated based only on 'habitat-level' measurements of air or sea surface temperature. This unique data set provides an opportunity to link physiological measurements with spatially- and temporally-explicit field observations of body temperature.

Beyond connectivity: how empirical methods can quantify population persistence to improve marine protected-area design.

Demographic connectivity is a fundamental process influencing the dynamics and persistence of spatially structured populations. Consequently, quantifying connectivity is essential for properly designing networks of protected areas so that they achieve their core ecological objective of maintaining population persistence. Recently, many empirical studies in marine systems have provided essential, and historically challenging to obtain, data on patterns of larval dispersal and export from marine protected areas (MPAs). Here, we review the empirical studies that have directly quantified the origins and destinations of individual larvae and assess those studies' relevance to the theory of population persistence and MPA design objectives. We found that empirical studies often do not measure or present quantities that are relevant to assessing population persistence, even though most studies were motivated or contextualized by MPA applications. Persistence of spatial populations, like nonspatial populations, depends on replacement, whether individuals reproduce enough in their lifetime to replace themselves. In spatial populations, one needs to account for the effect of larval dispersal on future recruitment back to the local population through local retention and other connectivity pathways. The most commonly reported descriptor of larval dispersal was the fraction of recruitment from local origin (self-recruitment). Self-recruitment does not inform persistence-based MPA design because it is a fraction of those arriving, not a fraction of those leaving (local retention), so contains no information on replacement. Some studies presented connectivity matrices, which can inform assessments of persistence with additional knowledge of survival and fecundity after recruitment. Some studies collected data in addition to larval dispersal that could inform assessments of population persistence but which were not presented in that way. We describe how three pieces of empirical information are needed to fully describe population persistence in a network of MPAs: (1) lifetime fecundity, (2) the proportion of larvae that are locally retained (or the full connectivity matrix), and (3) survival rate after recruitment. We conclude by linking theory and data to provide detailed guidance to empiricists and practitioners on field sampling design and data presentation that better informs the MPA objective of population persistence.

Organismal climatology: analyzing environmental variability at scales relevant to physiological stress.

Predicting when, where and with what magnitude climate change is likely to affect the fitness, abundance and distribution of organisms and the functioning of ecosystems has emerged as a high priority for scientists and resource managers. However, even in cases where we have detailed knowledge of current species' range boundaries, we often do not understand what, if any, aspects of weather and climate act to set these limits. This shortcoming significantly curtails our capacity to predict potential future range shifts in response to climate change, especially since the factors that set range boundaries under those novel conditions may be different from those that set limits today. We quantitatively examine a nine-year time series of temperature records relevant to the body temperatures of intertidal mussels as measured using biomimetic sensors. Specifically, we explore how a 'climatology' of body temperatures, as opposed to long-term records of habitat-level parameters such as air and water temperatures, can be used to extrapolate meaningful spatial and temporal patterns of physiological stress. Using different metrics that correspond to various aspects of physiological stress (seasonal means, cumulative temperature and the return time of extremes) we show that these potential environmental stressors do not always occur in synchrony with one another. Our analysis also shows that patterns of animal temperature are not well correlated with simple, commonly used metrics such as air temperature. Detailed physiological studies can provide guidance to predicting the effects of global climate change on natural ecosystems but only if we concomitantly record, archive and model environmental signals at appropriate scales.