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The past, present, and future of ecogeographic isolation between closely related Aquilegia plants

Cite this dataset

Weng, Yulin; Li, Huiqiong; Yang, Yaqin; Zhang, Zhiqiang (2023). The past, present, and future of ecogeographic isolation between closely related Aquilegia plants [Dataset]. Dryad. https://doi.org/10.5061/dryad.cnp5hqc95

Abstract

Quantifying the strength of the ecogeographic barrier is an important aspect of studies of plant speciation and a practical step to understanding the evolutionary trajectory of plants under climate change. Here, we quantified the extent of ecogeographical isolation of four closely related Aquilegia species, which radiated in the Mountains of SW China and adjacent regions and often lacked intrinsic barriers. We predicted past, present and future species potential distributions using environmental niche models, then compared them to determine the degree of overlap and ecogeographic isolation. Investigated ecogeographical isolation between species pairs, we found significant ecological differentiation in all studied species pairs except A. kansuensis and A. ecalacarata. The current strengths of ecogeographic isolation are above 0.5 in most cases. Compared with current climates, most species had an expanding range in the Last Glacial Maximum, the Mid Holocene and under four future climate scenarios. Our results suggested that ecogeographic isolation contributes to the diversification and maintenance of Aquilegia species in the Mountains of northern and SW China and would act as an essential reproductive barrier in the future.

Methods

Species occurrence data of each species were collected species occurrence from field investigations, references, the Chinese Virtual Herbarium (CVH; http://www.cvh.ac.cn/;), and the Global Biodiversity Information Facility (GBIF; https://www.gbif.org/). The occurrence records from the field investigation were collected from 2018 to 2020 under the joint efforts of our research team members. All occurrence records with incomplete data, duplicate records, ambiguous identification and irrational (on rivers, oceans, or out of range based on our knowledge) were removed from our datasets. 

Funding

National Natural Science Foundation of China, Award: 32271693