Climate change is responsible for increased frequency, intensity, and duration of extreme events, such as marine heatwaves (MHWs). Within eastern boundary current systems, MHWs have profound impacts on temperature-nutrient dynamics that drive primary productivity. Bull kelp (Nereocystis luetkeana) forests, a vital nearshore habitat, experienced unprecedented losses along 350 km of coastline in northern California beginning in 2014 and continuing through 2019. These losses have had devastating consequences to northern California communities, economies, and fisheries. Using a suite of in situ and satellite-derived data, we demonstrate that the abrupt ecosystem shift initiated by a multi-year MHW was preceded by declines in keystone predator population densities. We show strong evidence that northern California kelp forests, while temporally dynamic, were historically resilient to fluctuating environmental conditions, even in the absence of key top predators, but that a series of coupled environmental and biological shifts between 2014 and 2016 resulted in the formation of a persistent, altered ecosystem state with low primary productivity. Based on our findings, we recommend the implementation of ecosystem-based and adaptive management strategies, such as (1) monitoring the status of key ecosystem attributes: kelp distribution and abundance, and densities of sea urchins and their predators, (2) developing management responses to threshold levels of these attributes, and (3) creating quantitative restoration suitability indices for informing kelp restoration efforts.

Presently, operational ocean color satellite sensors are designed with a legacy perspective for sampling the open ocean primarily in the visible domain, while high spatial resolution sensors such as Sentinel-2, Sentinel-3, and Landsat8 are increasingly used for observations of coastal and inland water quality. Next-generation satellites such as the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) and Surface Biology and Geology (SBG) sensors are anticipated to increase spatial and/or spectral resolution. An important consideration is determining the minimum signal-to-noise ratio (SNR) needed to retrieve typical biogeochemical products, such as biomass, in aquatic systems, and whether legacy sensors can be used for algorithm development. Here, we evaluate SNR and remote-sensing reflectance (Rrs) uncertainty for representative bright and dim targets in coastal California, USA. The majority of existing sensors fail to meet proposed criteria. Despite these limitations, uncertainties in retrieved biomass as chlorophyll or normalized difference vegetation index (NDVI) remain well below a proposed threshold of 17.5%, suggesting that existing sensors can be used in coastal systems. Existing commercially available in-water and airborne instrument suites can exceed all proposed thresholds for SNR and Rrs uncertainty, providing a path forward for collection of calibration and validation data for future satellite missions.

This study establishes an optical inversion scheme for deriving the absorption coefficient of colored (or chromophoric, depending on the literature) dissolved organic material (CDOM) at the 440 nm wavelength, which can be applied to global water masses with near-equal efficacy. The approach uses a ratio of diffuse attenuation coefficient spectral end-members, i.e., a short-and long-wavelength pair. The

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