摘要：Tropical coral reefs cover ca. 0.1% of the Earth’s surface but host an outstanding biodiversity and provide important ecosystem services to millions of people living nearby. However, they are currently threatened by both local (e.g. nutrient enrichment and chemical pollution of coastal reefs, arising from poor land management, agriculture and industry) and global stressors (mainly seawater warming and acidification, i.e. climate change). Global and local stressors interact together in different ways, but the presence of one stressor often reduces the tolerance to additional stress. While global stressors cannot be halted by local actions, local stressors can be reduced through ecosystem management, therefore minimizing the impact of climate change on reefs. To inform decision-makers, we propose here to systematically map the evidence of impacts of chemicals arising from anthropogenic activities on tropical reef-building corals, which are the main engineer species of reef ecosystems. We aim to identify the combinations of chemical and coral responses that have attracted the most attention and for which evidence can be further summarized in a systematic review that will give practical information to decision-makers. The systematic map will follow the Collaboration for Environmental Evidence Guidelines and Standards for Evidence Synthesis in Environmental Management. We will search the relevant literature using English terms combined in a tested search string in two publication databases (Web Of Science Core Collection and Scopus). The search string will combine terms describing the population (tropical reef-building corals) and the exposure (chemicals). We will supplement this literature with some more obtained through search engines, specialist websites, and through a call to local stakeholders. Titles, abstracts, and full-texts will then be successively screened using pre-defined eligibility criteria. A list of pre-defined variables will then be extracted from full-texts. Finally, a database of all studies included in the map with coded metadata will be produced. The evidence will be described in a map report with text, figures and tables, and a matrix showing the distribution and frequency of included study into types of exposure and types of outcomes will be computed to identify potential knowledge gaps and knowledge clusters.
