Knowledge from non‐English‐language studies broadens contributions to conservation policy and helps to tackle bias in biodiversity data

Abstract Local ecological evidence is key to informing conservation. However, many global biodiversity indicators often neglect local ecological evidence published in languages other than English, potentially biasing our understanding of biodiversity trends in areas where English is not the dominant language. Brazil is a megadiverse country with a thriving national scientific publishing landscape. Here, using Brazil and using a species abundance indicator as an example, we assess how well bilingual literature searches can both improve data coverage for a country where English is not the primary language and help tackle current biases in biodiversity datasets. We conducted a comprehensive screening of articles containing abundance data for vertebrates published in 59 Brazilian journals (articles in Portuguese or English) and 79 international English‐only journals. These were grouped into three datasets according to journal origin and article language (Brazilian‐Portuguese, Brazilian‐English and International). We analysed the taxonomic, spatial and temporal coverage of the datasets, compared their average abundance trends and investigated predictors of such trends with a modelling approach. Our results showed that including data published in Brazilian journals, especially those published in Portuguese, strongly increased the representation of Brazilian vertebrate species (by 10 times) and populations (by 7.6 times) in the dataset. Meanwhile, international journals featured a higher proportion of threatened species. There were no marked differences in spatial or temporal coverage between datasets, in spite of different biases towards infrastructures. Overall, while country‐level trends in relative abundance did not substantially change with the addition of data from Brazilian journals, uncertainty considerably decreased. We found that population trends in international journals showed stronger and more frequent decreases in average abundance than those in national journals, regardless of whether the latter were published in Portuguese or English. Policy implications . Collecting data from local sources markedly further strengthens global biodiversity databases by adding species not previously included in international datasets. Furthermore, the addition of these data helps to understand spatial and temporal biases that potentially influence abundance trends at both national and global levels. We show how incorporating non‐English‐language studies in global databases and indicators could provide a more complete understanding of biodiversity trends and therefore better inform global conservation policy.