Muñoz, ManuelFernández, Francisco J.Ponce Oliva, RobertoVásquez Lavín, FelipeGelcich, Stefan2021-12-222021-12-222021Muñoz, Manuel; Fernández, Francisco J.; Ponce Oliva, Roberto; Vásquez-Lavín, Felipe; Gelcich, Stefan(2021). Gaps, biases, and future directions in research on the impacts of anthropogenic land-use change on aquatic ecosystems: a topic-based bibliometric analysis. Environmental Science and Pollution Research (2021) 28:43173–43189. https://doi.org/10.1007/s11356-021-15010-1https://doi.org/10.1007/s11356-021-15010-1http://hdl.handle.net/11447/5270Anthropogenic land use change (ALUC) satisfies human needs but also impacts aquatic ecosystems. Aquatic ecosystems are intrinsically linked with terrestrial landscapes, an association that is already recognized as a key factor to address future research and effective governance. However, the complexity and range of the impact of ALUC in aquatic ecosystems have been fundamental challenges and have implicitly routed the analysis to particular segments, drivers, management, or effects of the theme. In this study, we present an attempt to frame the subject in a broader context through a topic-based bibliometric analysis. Our aim is to identify possible biases and gaps in the current scientific literature and detect the main topics that have characterized the theme. Our results show an unequal distribution of articles by country when we analyzed the authors’ affiliation and also a slight increase in contributions from social and economic disciplines, although they are still underrepresented. Moreover, we distinguish topics whose prevalence seems to change, especially those topics where the use of scenario analysis and multistressors are considered. We discuss the main biases and gaps revealed by our results, concluding that future studies on the impact of ALUC on aquatic ecosystems should better integrate social and economic disciplines and expand geographic frontiersenAnthropogenic land use changeAquatic ecosystemsWater qualityLand use change impactsBibliometric analysisTopic modelingArticle