A facilitator, independent of the process, was hired to ensure the working group process was meaningful to participants, that all participants’ input was obtained, concerns recognised, addressed where possible, and documented where they could not be addressed. Third, experts, including human use sector representatives, were crucial to identifying the limitations of existing human use data for use in Marxan, and data gaps. Challenges are similar for ecological and human use data. For example, some species distributions and human uses are

seasonal, and where spatially explicit seasonality data are missing, Marxan results do not capture such nuanced information. Similarly, some areas may be particularly important for some species or human uses (e.g., spawning grounds, shipping Lonafarnib price traffic to small communities, fishing areas close to communities), but this level of detail may not be represented in available data. Thus, although analyses were designed to identify areas important to ecosystems and human users, with little or no relative value information in the data sets, Marxan uses data density to determine areas of importance. Another data limitation is that the time period over which data were originally collected was not consistent. Some data are older, even

though they may be the best-available data, and data sets for different features selleckchem used in a single analysis may have been compiled for different time periods. Furthermore, data illustrated for some features may not reflect current or future reality in terms of the various measures of relative importance. Both ecological and human use features shift spatially over time due to ongoing changes in the environment and management. Thus feedback from the human use sectors was that the Marxan results

for human uses were of limited value, and may not represent actual areas of importance. Fourth, as highlighted in the Marxan Good Practices Handbook [22], the BCMCA project found that calibrating parameters in Marxan and documenting and communicating data limitations was crucial. Calibration uncovered problems with the external edges and the use of two sizes of planning units. Racecadotril Without careful calibration, the analyses would not be robust, and the results might not have represented areas of conservation value. Similarly, because such a project involves a vast amount of data and numerous data providers, clear and transparent documentation of the limitations of each dataset is very important. Without this, the integrity of the project and its results could be compromised. One of the particular strengths of the BCMCA project’s atlas is that it pairs each map with a facing page that documents details of the data sources, limitations, and any other comments noted as important by peer reviewers of the dataset(s) illustrated on the map.