We have suggested that when selecting the area of interest within which EBSAs are to be identified, available biogeographic classifications should be considered. In ocean-basin scale deliberations, a broad classification such as that of Watling et al. (2013) can Palbociclib datasheet be used. If candidate EBSAs are to be part of a global network, then it would be advantageous to conduct the analysis within each biogeographic area to generate a suite of representative EBSAs across a large region with multiple biogeographic units. Gregr et al. (2012) summarised a number of marine habitat classification methods and schemes that operate at different spatial scales, and can be useful in
helping define the location or characteristics
of EBSAs. Our method involved a simple combination of criteria using a straight-forward procedure. We used a binary outcome for each seamount against each criterion (i.e. meets or fails the criterion) without an explicit weighting of criteria in the selection process. Taranto et al. (2012) used an Ecosystem Evaluation Framework method to examine the likelihood of a seamount constituting an EBSA as well as its level of human impact. An interesting difference in the methodology applied by Taranto et al. (2012) and ours is the weighting Selleck MDV3100 that they gave to different EBSA criteria and datasets. The presence (actual or implied) of, for example, cold-water corals, was given a weight of 3, because it was applied to three EBSA criteria (C3, C4, and C6), whereas depth had a weight of 1 as it was used only as an indicator of criterion 5. In our worked example, an individual dataset was used only to evaluate a single EBSA criterion. Whether a dataset is used across criteria matters more when relative EBSA selection is based on a scoring
system (as in Taranto et al., 2012), but not if it is a yes/no categorical situation. The separation of criteria into biological and threat categories was an important step in terms of structuring the method for future management, and the phrase “in need of protection” stated in the CBD Decision IX/20 C-X-C chemokine receptor type 7 (CXCR-7) (CBD, 2008). This division also recognises that ecosystem vulnerability can be due to natural (climate) change as well as a number of direct human-induced factors. Taranto et al. (2012) also tended to separate concepts of threat from the biological attributes of an EBSA. However, they included naturalness as a biological parameter, and then separately evaluated human impacts. The latter considered the type of fishing method or mining operation, as well as the perceived relative impact to different components of the ecosystem. The worked examples provided by Taranto et al. (2012) cover 8 seamounts for which a large amount of data are available and which enable a very thorough examination.