Effectiveness of hierarchical Bayesian models for citizen science data with missing values: A case study on the factors influencing beach litter in Shimane Prefecture, Japan-Reference-Cited by-同舟云学术

Effectiveness of hierarchical Bayesian models for citizen science data with missing values: A case study on the factors influencing beach litter in Shimane Prefecture, Japan

Published:2023-06 Issue: Volume:191 Page:114948
ISSN:0025-326X
Container-title:Marine Pollution Bulletin
language:en
Short-container-title:Marine Pollution Bulletin

Author:

Matsuba Misako,Tsujimoto Akira,Tsuchiya Masashi,Tanaka Yusuke,Nomaki Hidetaka

Publisher

Elsevier BV

Subject

Pollution,Aquatic Science,Oceanography

Reference47 articles.

1. Spatial trends and drivers of marine debris accumulation on shorelines in South Eleuthera, The Bahamas using citizen science;Ambrose;Mar. Pollut. Bull.,2019

2. From citizen science to citizen management: suggestions for a pervasive fine-grained and operational approach to biodiversity conservation;Battisti;Israel J. Ecol. Evol.,2021

3. Not just trash! Anthropogenic marine litter as a ‘charismatic threat” driving citizen-based conservation management actions’;Battisti;Anim. Conserv.,2019

4. Small environmental actions need of problem-solving approach: applying project management tools to beach litter clean-ups;Battisti;Environments,2020

5. The halophyte Cakile maritima Scop. 1772 as a trap of plastic litter on the Moroccan coast;Ben-Haddad;Mar. Pollut. Bull.,2023

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2. Quantification of Litter in Cities Using a Smartphone Application and Citizen Science in Conjunction with Deep Learning-Based Image Processing;2023