Geographical variability in the controls of giant kelp biomass dynamics

Abstract

Aim Coastal marine environments experience a wide range of biotic and abiotic forces that can limit and punctuate the geographical range and abundance of species through time. Determining the relative strengths and nonlinear effects of these processes is vital to understanding the biogeographical structures of species. There has been an ongoing discussion concerning the relative importance of these processes in controlling the dynamics of giant kelp, Macrocystis pyrifera, an important structure‐forming species on shallow reefs in the eastern Pacific. We used novel spatial time‐series that span nearly three decades to determine the dominant drivers of giant kelp canopy biomass and the temporal and spatial scales over which they operate across the dominant range of the giant kelp in North America. Location Near‐shore areas from Año Nuevo, California, to the USA/Mexico border. Methods We employed empirical orthogonal functions to elucidate the primary drivers of giant kelp canopy biomass across space and time and then fit generalized additive and linear models to determine the nonlinear effect and relative importance of each of these potential drivers along the c. 1500‐km study region over a 25‐year period. Results Wave disturbance, nitrate availability and the state of the North Pacific Gyre Oscillation were the most important environmental predictors of giant kelp canopy biomass, explaining 24.5%, 12.7% and 6.1% of the variance, respectively. Environmental drivers of canopy biomass exhibited profound spatial differences in relative effect sizes. Nonlinear effect shapes of each potential biomass driver were determined, which explained these spatial differences. Main conclusions These large‐scale analyses help to reconcile the local‐scale conclusions of canopy biomass dynamics across the California coastline and show that these dynamics differ predictably in space and time in accordance with local and regional differences in environmental drivers. By characterizing the nonlinear effects of these drivers, we identified spatio‐temporal patterns of processes that cannot be detected by remote sensing.

Global patterns of kelp forest change over the past half-century

“…The potential for this decline is considered more likely for species with slow postdisturbance recovery rates [e.g., corals (38)], those species that display little seasonal variability in abundance [e.g., mangroves (39)], or those species experiencing stressors of sufficiently widespread and high magnitude [e.g., fishes (1)]. However, for many taxa, globally coherent signals of change are unlikely when the identity and magnitude of drivers vary widely on local and regional scales (4,17,40), where species and ecotypes within taxonomic groups respond variably to change, or where abiotic and biotic contexts vary widely across geographic locations (41). The global average decline detected by our analysis was modest compared with the large interregional variability in the trajectories of change exhibited by kelps across their range.…”

“…Detecting future changes in kelp ecosystems at regional and global scales is best achieved by methodologically consistent, long-term monitoring efforts broadly distributed throughout all ecoregions (51). The use of aerial and satellite data to monitor changes in kelp canopies can help fill gaps in effort (17,42), but these technologies are useful only for kelps that have surface canopies, whose current geographic distribution represents only about half of the total global extent of kelps.…”

“…16) along coastlines of all continents except Antarctica. Kelps are useful sentinels of change because they are highly responsive to environmental conditions (17,18), and are directly exposed to many human activities that impact the coastal zone (e.g., harvesting, pollution, sedimentation, invasive species, fishing, recreation) (19). Kelps are among the most prolific primary producers on the planet, supporting productivity per unit area rivaling that of intensively cultivated agricultural fields and tropical rainforests (20,21).…”

“…Kelp forest declines have now been documented in many regions in response to a variety of stressors (18,(31)(32)(33)(34)(35), but kelp abundances have been stable or increasing in other areas (17,36,37). Here, we amass a global database of kelp abundances to provide a comprehensive picture of kelp forest change.…”

Extreme warming challenges sentinel status of kelp forests as indicators of climate change

“…H s represents the mean of the largest one-third of the waves recorded during a 30-min sampling period and the maximum H s has been shown to be significantly correlated with the amount of kelp biomass loss183940. H s data for the period 2001–2015 were obtained from the Coastal Data Information Program's nowcast wave-propagation model for locations nearest to each of the nine kelp forest sites40. The model provides hourly estimates of H s along a 10 m isobath at an 800 m longshore resolution.…”