Interpreting coral reef monitoring data: A guide for improved management decisions |
| |
| Affiliation: | 1. Marine Biology, Ecology & Biodiversity, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium;2. Institute of Oceanography and Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia;3. The Swire Institute of Marine Science, The University of Hong Kong, Pokfulam Rd, Hong Kong, People''s Republic of China;4. School of Biological Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong Special Administrative Region;5. The Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan;6. School of Marine and Environmental Sciences, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia;7. GEOMAR Helmholtz Centre of Ocean Research Kiel, Marine Evolutionary Ecology, Düsternbrooker Weg 20, 24105 Kiel, Germany;1. School of Biological Sciences, University of Queensland, 4072 St. Lucia, QLD, Australia;2. Global Change Institute, University of Queensland, 4072 St. Lucia, QLD, Australia;3. ARC Centre for Excellence for Coral Reef Studies, University of Queensland, 4072 St. Lucia, QLD, Australia |
| |
| Abstract: | Coral reef monitoring programmes exist in all regions of the world, recording reef attributes such as coral cover, fish biomass and macroalgal cover. Given the cost of such monitoring programs, and the degraded state of many of the world’s reefs, understanding how reef monitoring data can be used to shape management decisions for coral reefs is a high priority. However, there is no general guide to understanding the ecological implications of the data in a format that can trigger a management response. We attempt to provide such a guide for interpreting the temporal trends in 41 coral reef monitoring attributes, recorded by seven of the largest reef monitoring programmes. We show that only a small subset of these attributes is required to identify the stressors that have impacted a reef (i.e. provide a diagnosis), as well as to estimate the likely recovery potential (prognosis). Two of the most useful indicators, turf algal canopy height and coral colony growth rate are not commonly measured, and we strongly recommend their inclusion in reef monitoring. The diagnosis and prognosis system that we have developed may help guide management actions and provides a foundation for further development as biological and ecological insights continue to grow. |
| |
| Keywords: | Coral reef Monitoring Diagnostic Adaptive management Stressor Reef management |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
