Remote sensing: generation of long‐term kelp bed data sets for evaluation of impacts of climatic variation. Issue 7 (17th April 2020) - Hamilton, Sara L.; Bell, Tom W.; Watson, James R.; Grorud‐Colvert, Kirsten A.; Menge, Bruce A.
Abstract: A critical tool in assessing ecosystem change is the analysis of long‐term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional‐scale drivers are driving kelp populations—and particularly how kelp populations are responding to climate change—requires long‐term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long‐lived, perennial, canopy‐forming species. To understand how kelp populations with different life history traits are responding to climate‐related variability, we leverage 35 yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp, Nereocystis luetkeana, across Oregon. We found high levels of interannual variability in Nereocystis canopy area and varying population trajectories over the last 35 yr. Surprisingly, Oregon Nereocystis population sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern California Nereocystis populations. Some Oregon Nereocysti s populations have even increased in area relative to pre‐2014 levels. Analysis of environmental drivers found that Nereocystis population size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelp Macrocystis pyrifera and may be related to the annual life cycle of Nereocystis . This article demonstrates (1) the value of novel remote sensing tools to create long‐term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future.