Abstract
Although we spend millions annually monitoring marine resources, these efforts are uncoordinated and have major information gaps. We developed a scalable and transferable Marine Biodiversity Observation Network (MBON) in the Santa Barbara Channel (SBC), one of the most monitored areas of the world, that we are expanding throughout the Southern California Bight. SBC MBON is connecting existing monitoring efforts and continues to fill remaining information gaps. Our overall objective is to provide a complete picture of biodiversity in SBC using a transferable system that integrates and augments existing monitoring programs including the National Science Foundation’s (NSF) Long Term Ecological Research (LTER) program, Channel Islands National Park, California Cooperative Oceanic Fisheries Investigations (CalCOFI), and NASA Plumes and Blooms (PnB). Broad goals were to:
A. Integrate biodiversity data to enable inferences about regional biodiversity: Synthesizing information relevant to biodiversity requires integrating highly heterogeneous data collected at widely different temporal and spatial scales. We employed advanced techniques in spatial statistics for this synthesis and provide multiple biodiversity-related data products, including indices that provide measures of ecosystem diversity and health.
B. Develop advanced methods in optical and acoustic imaging and genomics for monitoring biodiversity in partnership with ongoing monitoring and research programs to begin filling the gaps in our knowledge: A key element we employed was a ‘pincer movement’ using two classes of methods approaching diversity observation from opposite directions: optical and acoustic imagery from the ecosystem scale down to the species level, and molecular biology from the genetic scale up through community level.
C. Implement a tradeoff framework that optimizes allocation of sampling effort: An effective MBON requires targeted sampling to address key data gaps, while making best use of existing sampling efforts, thereby gaining a complete description of biodiversity while minimizing cost. Optimal decisions about data collection require a framework for balancing costs and benefits of alternative sampling. Such a framework can be used to make recommendations for how resources should be allocated in a full-scale MBON as a function of the program’s goals and anticipated funding level.