Integrated ocean observing systems for assessing marine protected areas across California

Marine protected areas (MPAs) have been established as a tool to improve sustainability of fisheries, habitats, and their socio-economic value. MPAs face many pressures, from resource use to climate variations and long-term change. These factors operate from local to global spatial scales over daily to decadal timescales. This wide range of variance in space and time presents serious challenges to understanding how ocean weather, climate, MPA management practices, and other factors converge to shape MPA conditions. Given the range of possible influences and their scales, there is risk of interacting factors becoming indistinguishable without sufficient context (e.g. aliasing). In addition to issues with measuring such phenomena, big challenges remain in improving the timeliness and reproducibility of assessments. This presentation will introduce objectives and preliminary results from a newly funded California Ocean Protection Council and California Sea Grant project that aims to leverage existing capacity at the IOOS Regional Associations for California to employ: 1) large scale satellite data and models to develop regularly updating curated data views and products that quantify relationships between large scale phenomena, features, and variations and conditions at selected MPA and reference locations across the state, and 2) fine-scale models nested in larger scale simulations to develop regularly updating information products that quantify changing conditions, including MPA connectivity, at finer scales, and integrate results into our products and our multi-scale curated data views. We will also describe our plan to work with others collecting MPA relevant data to: 1) format and assemble in situ MPA monitoring data for inclusion in the multi-scale curated data views, including data for key performance measures and metrics, and 2) evaluate an emerging suite of operational, ecological models that can be synthesize data into a multivariate, multi-stressor description of regional ecosystem state to produce statewide quantitative, indicator-based assessments.