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  1. Abstract

    Spatial synchrony may be tail‐dependent, that is, stronger when populations are abundant than scarce, or vice‐versa. Here, ‘tail‐dependent’ follows from distributions having a lower tail consisting of relatively low values and an upper tail of relatively high values. We present a general theory of how the distribution and correlation structure of an environmental driver translates into tail‐dependent spatial synchrony through a non‐linear response, and examine empirical evidence for theoretical predictions in giant kelp along the California coastline. In sheltered areas, kelp declines synchronously (lower‐tail dependence) when waves are relatively intense, because waves below a certain height do little damage to kelp. Conversely, in exposed areas, kelp is synchronised primarily by periods of calmness that cause shared recovery (upper‐tail dependence). We find evidence for geographies of tail dependence in synchrony, which helps structure regional population resilience: areas where population declines are asynchronous may be more resilient to disturbance because remnant populations facilitate reestablishment.

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  2. These data describe 1987-2019 time series of giant kelp (Macrocystis pyrifera) biomass and associated environmental variables (wave height, nitrate concentration, climate indices) at quarterly and annual time intervals. Data for spatially resolvable variables (giant kelp biomass, wave height, nitrate concentration) pertain to 361 coastline segments (500 m length) in southern and central California where giant kelp was persistent over the sampling period. Data are contained in 5 tables: 1) quarterly time series of giant kelp biomass, wave height, and nitrate concentrations for 361 coastline segments; 2) quarterly time series of aspatial climate indices (NPGO, MEI, PDO); 3) annual time series of giant kelp biomass, wave height, and nitrate concentrations for 361 coastline segments; 4) annual time series of aspatial climate indices (NPGO, MEI, PDO); 5) locations (latitude and longitude of center) of coastline segments. Kelp data are derived from satellite imagery using empirical relationships. Wave data are derived from an empirically validated swell propagation model. Nitrate data are derived from empirical relationships with remotely-sensed sea surface temperature. 
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