Gender bias in ecosystem restoration: from science to practice
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Date
2022-01-01Author
Cruz-Alonso, V.
Martínez-Baroja, L.
Marqués, L.
Rodríguez-Uña, A.
Rohrer, Z.
Monteagudo, N.
Velado-Alonso, E.
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Restoration Ecology (2022)
Abstract
The declaration of the United Nations Decade on Ecosystem Restoration 2020–2030 has established the need to focus on human rights in restoration initiatives, including gender equality. Although this goal raises a need to monitor gender biases on ecosystem restoration, we still lack basic gender information and evaluations on the current situation. The main purpose of this study is to analyze gender bias in ecosystem restoration covering three dimensions: research, outreach, and practice. We used scientific publications from the Restoration Ecology journal, mentions of these articles in Altmetric Explorer and Twitter, and projects from the Society for Ecological Restoration's database. First, we study gender bias among people leading ecosystem restoration initiatives in the three dimensions. Second, we assessed factors that could influence gender bias, including year, target ecosystem, and socioeconomic country development. Third, we analyzed whether the impact of scientific knowledge in society depends on the gender of the scientific team. Our results indicate that men were primary leaders in research, outreach, and practice initiatives in ecosystem restoration. There seems to be a trend over time toward equality in research, but gender inequality is still present in most types of ecosystems, with women leading more projects in more developed countries. The impact of scientific knowledge is independent of the author's gender, but research of male senior authors seems to reach society more easily. This broad perspective of inequality in the three dimensions can evolve toward gender equality, by applying gender approaches in restoration policies and initiatives. © 2022 Society for Ecological Restoration. Raw data is publicly available thanks to Web of Science, Altmetrics, Twitter and SER. Data and scripts used for the analysis are available via Figshare (Cruz‐Alonso et al. 2022 ). Funding: V.C.‐A.—Real Colegio Complutense postdoc fellowship; A.R.‐U.—Spanish State Research Agency through María de Maeztu Excellence Unit accreditation 2018–2022 (MDM‐2017‐0714); L.M.—Swiss National Science Foundation (PCEFP2_181115) and a Margarita Salas Postdoctoral Fellowship from Universidad de Alcalá; L.M.‐B.—Ministerio de Ciencia e Innovación (PID2019‐106806GB‐I00) and a Margarita Salas Postdoctoral Fellowship from Universidad de Alcalá; N.M.—predoctoral grant from Universidad de Alcalá; E.V.‐A.—European Commission (project SHOWCASE, H2020: 862480). We appreciate the support of the FIRE Foundation and the comments of M. Almaraz, M. Pajares, A. S. Moya, and D. Rohrer to improve the manuscript.