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Abstract The efficacy of marine protected areas (MPAs) may be reduced when climate change disrupts the ecosystems and human communities around which they are designed. The effects of ocean warming on MPA functioning have received attention but less is known about how multiple climatic stressors may influence MPAs efficacy. Using a novel dataset incorporating 8.8 million oceanographic observations, we assess exposure to potentially stressful temperatures, dissolved oxygen concentrations, and pH levels across the California MPA network. This dataset covers more than two-thirds of California’s 124 MPAs and multiple biogeographic domains. However, spatial-temporal and methodological patchiness constrains the extent to which systematic evaluation of exposure is possible across the network. Across a set of nine well-monitored MPAs, the most frequently observed combination of stressful conditions was hypoxic conditions (<140 umol/kg) co-occurring with low pH (<7.75). Conversely, MPAs exposed most frequently to anomalously warm conditions were less likely to experience hypoxia and low pH, although exposure to hypoxia varied throughout the 2014–2016 marine heatwaves. Finally, we found that the spatial patterns of exposure to hypoxia and low pH across the MPA network remained stable across years. This multiple stressor analysis both confirms and challenges prior hypotheses regarding MPA efficacy under global environmental change. 

The prevalence of disease-driven mass mortality events is increasing, but our understanding of spatial variation in their magnitude, timing and triggers are often poorly resolved. Here, we use a novel range-wide dataset comprised 48 810 surveys to quantify how sea star wasting disease affected Pycnopodia helianthoides , the sunflower sea star, across its range from Baja California, Mexico to the Aleutian Islands, USA. We found that the outbreak occurred more rapidly, killed a greater percentage of the population and left fewer survivors in the southern half of the species's range. Pycnopodia now appears to be functionally extinct (greater than 99.2% declines) from Baja California, Mexico to Cape Flattery, Washington, USA and exhibited severe declines (greater than 87.8%) from the Salish Sea to the Gulf of Alaska. The importance of temperature in predicting Pycnopodia distribution rose more than fourfold after the outbreak, suggesting latitudinal variation in outbreak severity may stem from an interaction between disease severity and warmer waters. We found no evidence of population recovery in the years since the outbreak. Natural recovery in the southern half of the range is unlikely over the short term. Thus, assisted recovery will probably be required to restore the functional role of this predator on ecologically relevant time scales. 

Numerical simulations present challenges because they generate petabyte-scale data that must be extracted and reduced during the simulation. We demonstrate a seamless integration of feature extraction for a simulation of turbulent fluid dynamics. The simulation produces on the order of 6 TB per timestep. In order to analyze and store this data, we extract velocity data from a dilated volume of the strong vortical regions and also store a lossy compressed representation of the data. Both reduce data by one or more orders of magnitude. We extract data from user checkpoints in transit while they reside on temporary burst buffer SSD stores. In this way, analysis and compression algorithms are designed to meet specific time constraints so they do not interfere with simulation computations. Our results demonstrate that we can perform feature extraction on a world-class direct numerical simulation of turbulence while it is running and gather meaningful scientific data for archival and post analysis. 

The apparent clustering in longitude of perihelionϖand ascending node Ω of extreme trans-Neptunian objects (ETNOs) has been attributed to the gravitational effects of an unseen 5–10 Earth-mass planet in the outer solar system. To investigate how selection bias may contribute to this clustering, we consider 14 ETNOs discovered by the Dark Energy Survey, the Outer Solar System Origins Survey, and the survey of Sheppard and Trujillo. Using each survey's published pointing history, depth, and TNO tracking selections, we calculate the joint probability that these objects are consistent with an underlying parent population with uniform distributions inϖand Ω. We find that the mean scaled longitude of perihelion and orbital poles of the detected ETNOs are consistent with a uniform population at a level between 17% and 94% and thus conclude that this sample provides no evidence for angular clustering.