Non-English languages enrich scientific knowledge: The example of economic costs of biological invasions

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 (scie