Marine Pollution BulletinDr. Serge Andréfouët and Mélanie Hamel just published a new paper in Marine Pollution Bulletin on a straightforward method to perform a rapid data gap analysis at the regional scale in tropical coral reef countries with limited resources. The rapid assessment allows to quickly identify areas of high natural value where more knowledge is needed, for a minimal cost. The project was piloted for the Solomon Islands in 2010 and wrapped up in less than four months with one full-time staff.


Gap index Gsta in 0.5 by 0.5 decimal degrees cells. Gsta reflects a data gap according to habitat richness and number of stations investigated.
Gap index Gsta in 0.5 by 0.5 decimal degrees cells for the Solomon Islands. Gsta reflects a data gap in terms of number of stations investigated in relation to habitat richness. The higher the Gsta value (red cells), the greater the gap in coral reef science data considering habitat richness.


You can download the paper below or contact Dr. Serge Andréfouët to ask for a copy:

Andrefouet-&-Hamel_2014Andréfouët, S., Hamel, M.A. Tropical islands quick data gap analysis guided by coral reef geomorphological maps. Mar. Pollut. Bull (2014),

ABSTRACT: A gap analysis is the initial step towards the identification of areas where data are needed. However, often, data coverage cannot be assessed against a reference that objectively guides the identification of both gaps and priority areas for data acquisition. Here, we describe a quick, effective and reproducible spatial data gap analysis approach based on the relationship between location of available metadata and coral reef geomorphological richness. In Solomon Islands, we identified gaps defined by high richness and low biological data coverage. We collected metadata only, to avoid dealing with data ownership, availability, and formats, and to be able to identify gaps in less than two months. This fast method does not replace quantitative and comprehensive gap analysis, but provides effective identification of areas of high natural value and limited knowledge. The method is widely applicable and particularly invaluable for large and complex domains such as the Coral Triangle.