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Models of Suitable Habitat for Corals for a Better Planning of Offshore Activities in Newfoundland

Models of Suitable Habitat for Corals for a Better Planning of Offshore Activities in Newfoundland
珊瑚适宜栖息地模型,以更好地规划纽芬兰近海活动
批准号:
524515-2018
负责人:
Roncal, Julissa
金额:
$1.82万
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
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英文摘要
One of the most challenging aspects of undertaking environmental impact statements (EIS) is determining the**distribution and abundance of aquatic organisms such as corals, for which there is limited survey data on their**occurrence. In particular, understanding how the specific environmental conditions of a particular geographical**area - potentially being approved for natural resource extraction - may or may not support corals and other**marine biota. Wood Environment & Infrastructure Solutions conducts EIS guided by surveys from Fisheries**and Oceans Canada (DFO) and provides an estimation of the type and density of corals and other aquatic**species likely to be found within its client's proposed oil and gas project area. In order to make appropriate**management recommendations and to suggest suitable mitigation actions, Wood requires a better**understanding of the ecology and distribution of corals offshore Newfoundland. Therefore, this proposal aims**to develop unique probability models of suitable habitats for corals. The new knowledge generated will include**predicted areas of high coral density and the identification of the most important environmental variables that**determine coral suitable habitat. This new information will be incorporated within Wood's EIS which will**permit the targeting of offshore activities more efficiently to avoid interactions with corals.**Following recommendations from Wood we will select three coral species for which species distribution**models will be estimated: a shallow water, a deep-sea specialist, and a species with a wide depth range. With**the technical help of Wood professionals, we will obtain occurrence data from DFO in a format suitable for**modelling. Using environmental data such as depth, slope of the seabed, velocity of tidal currents, temperature,**wave height, and substrate type, these distribution models will be able to predict the location of the most**suitable habitats to sustain them. This work will fill a knowledge gap that results in sometimes-inappropriate**management recommendations, therefore Wood will benefit from the research outcomes, as well as the natural**resource sector, and government regulatory agencies responsible for approving natural resource extraction.
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