Spatiotemporal variability in kelp forest and seagrass ecosystems : can local biogeochemical modification combat acidification stress?
Keywords: Environmental Earth System Science.

Anthropogenic carbon dioxide (CO2) emissions have driven widespread ocean acidification (OA). OA has reduced surface ocean pH by at least 0.1 pH units since the beginning of the industrial era and global models forecast a further decrease of 0.3 to 0.4 pH units by the end of the century. Submerged aquatic vegetation, such as kelp forests and seagrass beds, has the potential to locally ameliorate OA by removing CO2 during photosynthesis and storing it as fixed carbon. Thus, understanding the contribution of these habitats to local biogeochemistry is essential to inform coastal management and policy, especially as the impacts of anthropogenic climate change become more prevalent. The following work describes high resolution spatiotemporal variability in seagrass and kelp forest biogeochemistry (Chapters 1 and 2) and in the surface canopy extent of a giant kelp forest (Chapter 3). In order to understand the contributions of kelp forest and seagrass metabolism to their respective local biogeochemistry, we must determine the natural variability in these systems and disentangle the physical and biological drivers of local biogeochemical variability. In Chapter 1, I deployed an extensive instrument array in Monterey Bay, CA, inside and outside of a kelp forest to assess the degree to which kelp locally ameliorates present-day acidic conditions, which we expect to be further exacerbated by OA. Interactions between upwelling exposure, internal bores, and biological production shaped the local biogeochemistry inside and outside of the kelp forest. Significantly elevated pH, attributed to kelp canopy productivity, was observed at the surface inside the kelp forest. This modification was largely limited to a narrow band of surface water, implying that while kelp forests have the potential to locally ameliorate ocean acidification stress, this benefit may largely be limited to organisms living in the upper part of the canopy. In Chapter 2, I quantified net community production (NCP) over a mixed seagrass-coral community on Ngeseksau Reef, Ngermid Bay, Republic of Palau. We observed a net heterotrophic diel signal over the deployment, but dissolved oxygen (O2) fluxes during the day were largely positive, illustrating daytime autotrophy. pH, O2, and temperature followed a clear diel pattern with maxima typically occurring in the afternoon. The relationship between tidal regime and time of day drove the magnitude of the signals observed. The case studies described in Chapters 1 and 2 emphasize the importance of high-resolution measurements (high temporal frequency as well as high horizontal and vertical spatial resolution) and consideration of the multiple drivers responsible for shaping the observed biogeochemical variability. In addition to the photosynthetic biomass (kelp and seagrass) at the center of these studies, the physical environment played an important role in dictating the signals observed, in particular water circulation and residence time. Biogeochemical studies rarely look beyond a few deployment sites, but the ecosystem contributing to the local biogeochemical variability includes influences from beyond those discrete points. Describing the area around these discrete points is important for accurate assessment of factors driving the signals observed at those points. Remote sensing can help us capture and describe the spatial patterns of biomass contributing to changes observed in our chemical records. In Chapter 3, I established a low altitude unmanned aerial vehicle (UAV) record of giant kelp surface areal extent over 18 months on the wave-protected side of Cabrillo Point (Hopkins Marine Station) in Monterey Bay, CA. This was the same canopy responsible for elevating pH in Chapter 1; however, in this case, the kelp canopy mapping did not overlap in time with biogeochemical measurements in the kelp forest. I compared the UAV kelp classification to canopy cover determined from Landsat satellite images obtained over the same period. There was a linear relationship between the drone kelp ratio and Landsat kelp canopy fraction for spatially-matched pixels; a Landsat kelp fraction of 0.64 was equivalent to 100% kelp cover in the drone data. The level of resolution provided by UAV, compared with Landsat images, could allow more detailed mapping of kelp responses to environmental change. Future studies should pair mapping flights with biogeochemical measurements to quantify the relationship between changes in canopy area and the relative surface canopy modification of pH.