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Morro manzanita Arctostaphyos morroensis (Ericaceae) is a long-lived, shrub endemic to San Luis Obispo County, southern California, USA. It was listed as threatened under the U.S. Endangered Species Act in 1994, with identified threats being residential and urban development, including lack of protection on private land and lack of management on public lands, competition with invasive non-native plants, and risks of extinction associated with small and isolated populations. Our goal in this paper is to summarize and supplement the current knowledge of Morro manzanita. We review the literature on the species' description, reproductive ecology, germination cues, short-term response to fire. and distribution. We conducted field surveys to report on long-term response to fire, resampling the previously studied prescribed burn site 25 yr post-fire. Finally, we summarize the current land management of sites that support Morro manzanita and threats faced by this species. We conclude with specific recommendations for management and future study towards supporting conservation of this species and its maritime chaparral community. [ABSTRACT FROM AUTHOR]

The substantial threat of concurrent air pollutants to public health is increasingly severe under climate change. To identify the common drivers and extent of spatiotemporal similarity of PM 2.5 and ozone (O 3), this paper proposed a log Gaussian–Gumbel Bayesian hierarchical model allowing for sharing a stochastic partial differential equation and autoregressive model of order one (SPDE-AR(1)) spatiotemporal interaction structure. The proposed model, implemented by the approach of integrated nested Laplace approximation (INLA), outperforms in terms of estimation accuracy and prediction capacity for its increased parsimony and reduced uncertainty, especially for the shared O 3 sub-model. Besides the consistently significant influence of temperature (positive), extreme drought (positive), fire burnt area (positive), gross domestic product (GDP) per capita (positive), and wind speed (negative) on both PM 2.5 and O 3 , surface pressure and precipitation demonstrate positive associations with PM 2.5 and O 3 , respectively. While population density relates to neither. In addition, our results demonstrate similar spatiotemporal interactions between PM 2.5 and O 3 , indicating that the spatial and temporal variations of these pollutants show relatively considerable consistency in California. Finally, with the aid of the excursion function, we see that the areas around the intersection of San Luis Obispo and Santa Barbara counties are likely to exceed the unhealthy O 3 level for USG simultaneously with other areas throughout the year. Our findings provide new insights for regional and seasonal strategies in the co-control of PM 2.5 and O 3. Our methodology is expected to be utilized when interest lies in multiple interrelated processes in the fields of environment and epidemiology. [Display omitted] • PM 2.5 and O 3 pollutants are jointly analysed in California through a log Gaussian–Gumbel Bayesian hierarchical joint model. • Distinct spatiotemporal interactions are revealed with a shared SPDE-AR structure; common drivers of PM 2.5 and O 3 are identified. • Hotspots at risk of simultaneously exceeding unhealthy O 3 levels are identified. [ABSTRACT FROM AUTHOR]