New Zealand has a considerable body of experience creating spatial classifications of the marine environment, and applying them for management. We assert that recent innovations in multivariate statistical modeling have made possible the combined use of spatially comprehensive environmental data and discontinuous biological data to generate rigorous, objective, data-driven classifications of the Southern Ocean sensitive to ecologically important contrasts, consistent with CCAMLR’s ecosystem management mandate. This paper considers a range of methodological options for data-driven marine classification, and reviews the results of three New Zealand classifications to draw methodological and practical lessons relevant to CCAMLR’s Bioregionalisation of the Southern Ocean.
We offer the following explicit recommendations to the CCAMLR Bioregionalisation process: 1) Use biological data; 2) Model species individually; 3) Generate a classification based on abundance, not presence-absence; 4) Use the most powerful statistical methods available, such as BRT and GDM; 5) Use a hierarchical algorithm; 6) Focus on an environment or community of interest; 7) Include information representing uncertainty.
We also highlight some of the inherent limitations of all attempts to represent spatially and temporally dynamic ecosystems using static representations such as produced by marine classifications. We identify important ecosystem processes that may not be captured by even the best classifications, and warn against uncritical or misinformed application of marine classifications in the management stage. Finally we highlight some practical steps to make marine classifications more ‘management-friendly’.
Abstract:
Phytoplankton production during the austral summer in the Southern Ocean is known to be limited by iron and light. Distributions of satellite-detected chlorophyll-a (Chl-a) show very complex and time-variable patterns that are hard to explain. We analysed covariance between satellite-detected and modelled variables and show that this covariance in time between the mixed layer depth (MLD), sea surface temperature (SST) and Chl-a can be used to map areas where different factors control phytoplankton production. Statistically significant spatial patterns in the covariance between MLD, SST and Chl-a show that the physical factors controlling phytoplankton production in the Southern Ocean change in a predictable manner. Well-defined areas exist where phytoplankton is light-limited in the summer due to insufficient stratification and where phytoplankton is clearly limited by nutrients (probably iron). The boundary between light limitation and nutrient limitation can be sharp and may be associated with the main hydrographic fronts (e.g. the Subantarctic Front).
