Socio-ecological patterns of citizens science programs: The case of forestry observations in 3 central Mexico states
Citizen science programs have been used to identify and address socio-environmental issues. Environmental participatory monitoring has been particularly effective in providing useful information for forest management and decision-making processes directed at formulating policy. However, recent studi...
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Published in | Urban forestry & urban greening Vol. 70; p. 127513 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier GmbH
01.04.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Citizen science programs have been used to identify and address socio-environmental issues. Environmental participatory monitoring has been particularly effective in providing useful information for forest management and decision-making processes directed at formulating policy. However, recent studies have identified a recurrent participation pattern: citizen science appears to concentrate on affluent municipalities while excluding highly marginalized regions. For this research, a non-parametric analysis of the distribution of observations collected via iNaturalist, a citizens science app for participatory monitoring, is presented. Spearman correlations and a Kruskal-Wallis test were conducted for plant species observations in three states of central Mexico. Results suggest that participatory monitoring patterns are influenced by the marginalization degree of municipalities. Percentage of natural protected areas and forested surface per municipality were also analyzed as variables useful to explain the spatial concentration of participation. Evidence shows that, contrary to observed patterns of exclusion, marginalized municipalities with a designated natural protected area concentrate more participation. Participatory monitoring via citizen science programs is discussed as a valuable tool for developing countries challenged with restricted budgets for environmental management. |
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ISSN: | 1618-8667 1610-8167 |
DOI: | 10.1016/j.ufug.2022.127513 |