Publication Date:
2022-05-27
Description:
© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Angulo, E., Diagne, C., Ballesteros-Mejia, L., Adamjy, T., Ahmed, D. A., Akulov, E., Banerjee, A. K., Capinha, C., Dia, C. A. K. M., Dobigny, G., Duboscq-Carra, V. G., Golivets, M., Haubrock, P. J., Heringer, G., Kirichenko, N., Kourantidou, M., Liu, C., Nuñez, M. A., Renault, D., Roiz, D., Taheri, A., Verbrugge, L. N. H., Watari, Y., Xiong, W., & Courchamp, F. Non-English languages enrich scientific knowledge: the example of economic costs of biological invasions. Science of the Total Environment, 775, (2021): 144441, https://doi.org/10.1016/j.scitotenv.2020.144441.
Description:
We contend that the exclusive focus on the English language in scientific research might hinder effective communication between scientists and practitioners or policy makers whose mother tongue is non-English. This barrier in scientific knowledge and data transfer likely leads to significant knowledge gaps and may create biases when providing global patterns in many fields of science. To demonstrate this, we compiled data on the global economic costs of invasive alien species reported in 15 non-English languages. We compared it with equivalent data from English documents (i.e., the InvaCost database, the most up-to-date repository of invasion costs globally). The comparison of both databases (~7500 entries in total) revealed that non-English sources: (i) capture a greater amount of data than English sources alone (2500 vs. 2396 cost entries respectively); (ii) add 249 invasive species and 15 countries to those reported by English literature, and (iii) increase the global cost estimate of invasions by 16.6% (i.e., US$ 214 billion added to 1.288 trillion estimated from the English database). Additionally, 2712 cost entries — not directly comparable to the English database — were directly obtained from practitioners, revealing the value of communication between scientists and practitioners. Moreover, we demonstrated how gaps caused by overlooking non-English data resulted in significant biases in the distribution of costs across space, taxonomic groups, types of cost, and impacted sectors. Specifically, costs from Europe, at the local scale, and particularly pertaining to management, were largely under-represented in the English database. Thus, combining scientific data from English and non-English sources proves fundamental and enhances data completeness. Considering non-English sources helps alleviate biases in understanding invasion costs at a global scale. Finally, it also holds strong potential for improving management performance, coordination among experts (scientists and practitioners), and collaborative actions across countries. Note: non-English versions of the abstract and figures are provided in Appendix S5 in 12 languages.
Description:
This work was supported by the French National Research Agency (ANR-14-CE02-0021) and the BNP-Paribas Foundation Climate Initiative for the InvaCost project that allowed the construction of the InvaCost database; the AXA Research Fund Chair of Invasion Biology of University Paris Saclay (EA and LBM contracts) and BiodivERsA and Belmont-Forum call 2018 on biodiversity scenarios – “Alien Scenarios” (the workshop where this work was initiated, and MG and CD contracts, BMBF/PT DLR 01LC1807C); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (Capes) (Finance code 001, GH contract); Russian Foundation for Basic Research (grant number 19-04-01028-a); InEE-CNRS who supports the network GdR 3647 ‘Invasions Biologiques’, the French Polar Institute Paul-Emile Victor (Project IPEV 136 ‘Subanteco’), and the national nature reserve of the French southern lands (RN-TAF); Portuguese National Funds through Fundação para a Ciência e a Tecnologia (grant numbers CEECIND/02037/2017; UIDB/00295/2020 and UIDP/00295/2020); Kuwait Foundation for the Advancement of Sciences (KFAS) (grant number PR1914SM-01) and the Gulf University for Science and Technology (GUST) internal seed fund (grant number 187092).
Keywords:
Ecological bias
;
Management
;
Knowledge gaps
;
InvaCost
;
Native languages
;
Stakeholders
Repository Name:
Woods Hole Open Access Server
Type:
Article
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