A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Prediction and assessment of marine fisheries carbon sink in China based on a novel nonlinear grey Bernoulli model with multiple optimizations. | LitMetric

The vigorous development of marine fisheries carbon sinks (MFCS) has become a momentous pathway to mitigate global warming and effectively cope with the climate crisis. Deservedly, based on clarifying mechanism of carbon sequestration, this paper designs a research paradigm for predicting and evaluating the potential of MFCS. Specifically, a novel nonlinear grey Bernoulli model, namely MFCSNGBM(1,1), is proposed by innovatively mining the original data law through adaptive cumulative series and introducing the compound Simpson formula to optimize background values. More precisely, we utilize a heuristic Grey Wolf Optimization algorithm to find the best power index, which enhances the adaptability. To prove usefulness and robustness of MFCSNGBM(1,1) model, yields of seven common shellfishes (oyster, clam, mussel, scallop, razor clam, bloody clam, and snail) and three main algae (kelp, pinnatifid undaria, and laver) are predicted and compared with six competing models. Based on prediction results, new model has the most accurate predictions, with all prediction errors being <10 %, and thus can achieve effective prediction of shellfish and algae production from 2022 to 2025. Further, the capacity and potential of MFCS in China are scientifically evaluated using a removable carbon sink model, considering various yield levels and biological parameters of shellfish and algae. The assessment results show that during the sample period, China's marine fisheries carbon sinks steadily increased with an annual growth rate of 57,000 tons. From 2022 to 2025, with support of policy of MFCS and improvement of disaster prevention and mitigation capacity, the potential of MFCS will be further released. The growth rate of MFCS will be increased to 94,000 tons per year, and its overall scale is expected to reach 2,198,245 tons by 2025, equivalent to fixing 8.06 million tons of CO2. The carbon sink's economic value is significantly estimated to be over 400 billion yuan.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.scitotenv.2023.169769DOI Listing

Publication Analysis

Top Keywords

marine fisheries
8
fisheries carbon
8
novel nonlinear
8
nonlinear grey
8
grey bernoulli
8
bernoulli model
8
prediction assessment
4
assessment marine
4
carbon sink
4
sink china
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!