Replication Data for: Research gaps and trends in the Arctic tundra: a topic modeling approach

• Main Authors: Ancin-Murguzur, Francisco Javier, Hausner, Vera Helene
• Format: Dataset
• Language: unknown
• Published: DataverseNO 2020
• Subjects: Latent Dirichlet Allocation; Socio economic system; Climate change; Research gaps; Topic modeling; Earth and Environmental Sciences; Arctic; Tundra
• Online Access: https://search.dataone.org/view/sha256:67647b605a3a47f6db4f838496bf5de7476dac2415600c1f3b49fbe00648ca98

Climate change is affecting the biodiversity, ecosystem services and the well-being of people that live in the Arctic tundra. Understanding the societal implications and adapting to these changes depend on knowledge produced by multiple disciplines. We analysed peer-reviewed publications to identify the main research themes relating to the Arctic tundra and assessed to what extent current research build on multiple disciplines to confront the upcoming challenges of rapid environmental changes. We used a topic- modelling approach, based on the Latent Dirichlet Allocation algorithm to detect topics based on semantic similarity. We found that plant and soil ecology dominate the tundra research and are highly connected to other ecological disciplines and biophysical sciences. Despite the fivefold increase in the number of publications during the past decades, the proportion of studies that address societal implications of climate change remains low. The strong scientific interest in the tundra reflects the concern of the rapid warming of the Arctic, but few studies include the cross-disciplinary approach necessary to fully assess the implications