A Predictive Model for Geographic Distributions of Mangroves
- URL: http://arxiv.org/abs/2101.00967v2
- Date: Sun, 10 Jan 2021 18:42:49 GMT
- Title: A Predictive Model for Geographic Distributions of Mangroves
- Authors: Lynn Wahab, Ezzat Chebaro, Jad Ismail, Amir Nasrelddine, Ali El-Zein
- Abstract summary: Mangroves are especially relevant to oceanic ecosystems because of their protective nature towards other marine life.
The change in global distribution was studied based on global distributions of the previous year.
The best performing predictive model was a support vector regressor, which yielded a correlation coefficient of 0.9998.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Climate change is an impending disaster which is of pressing concern more and
more every year. Countless efforts have been made to study the long-term
effects of climate change on agriculture, land resources, and biodiversity.
Studies involving marine life, however, are less prevalent in the literature.
Our research studies the available data on the population of mangroves (groups
of shrubs or small trees living in saline coastal intertidal zones) and their
correlations to climate change variables, specifically, temperature, heat
content, various sea levels, and sea salinity. Mangroves are especially
relevant to oceanic ecosystems because of their protective nature towards other
marine life, as well as their high absorption rate of carbon dioxide, and their
ability to withstand varying levels of salinity of our coasts. The change in
global distribution was studied based on global distributions of the previous
year, as well as ocean heat content, salinity, temperature, halosteric sea
level, thermosteric sea level, and total steric sea level. The best performing
predictive model was a support vector regressor, which yielded a correlation
coefficient of 0.9998.
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