Identification of Shared Spatial Dynamics in Temperature, Salinity, and Ichthyoplankton Community Diversity in the California Current System With Empirical Dynamic Modeling
Identifying spatially shared dynamics is a key component of community ecology studies as they provide evidence of common responses to environmental factors. We apply co-prediction, an empirical dynamic modeling method (EDM), where values in one time series are predicted from another to quantify shared dynamics in the California Cooperative Fishery Oceanographic Investigation (CalCOFI) dataset composed of spatially explicit physical and biological measurements. Co-prediction can arise in the absence of correlation between two time series. The survey dates to 1951 and consists of a semi-regular, fixed-station design off the west coast of the USA. While the California Current is a dynamic system with multiple identified regimes, we found evidence of coherence measured in terms of spatially shared dynamics in salinity, temperature, Shannon index of ichthyoplankton abundance, and single-species ichthyoplankton abundance throughout the CalCOFI survey area. Leave-one-out hindcast skill, without including any knowledge of shared dynamics was significant in 27 stations for salinity data, 36 for temperature data, and 33 for Shannon index (out of 81 total stations). We then evaluated hindcast skill when including shared dynamics via composite libraries, in which correlated or co-predicted time series are concatenated to produce denser attractors. The number of correlated stations was generally higher than the number of co-predicted stations, but hindcast skill from composite libraries of correlated stations did not increase hindcast skill. Composite libraries of co-predicted stations had significant leave-one-out hindcast skill in 60 stations for salinity data, 60 for temperature, and 72 for Shannon index. Additionally, we found evidence of nonlinear relationships, as nonlinear hindcasts accounted for nearly all of these significant stations. While there were high levels of correlation among stations, co-prediction proved a more robust method of identifying shared dynamics. Shared dynamics were largely concentrated south of Point Conception, considered an oceanographic and biological breakpoint, although in some cases shared dynamics spanned this boundary. Taken together, we apply EDM to present the first, to our knowledge, evaluation of station-specific hindcast skill and provide a view of the realized spatial structure occurring in the physical and biological dynamics of the California Current system.
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