High-quality biodiversity data are the scientific basis for understanding the origin and maintenance of biodiversity and dealing with its extinction risk. Currently, we identify at least seven knowledge shortfalls or gaps in biodiversity science, including the lack of knowledge on species descriptions, species geographic distributions, species abundance and population dynamics, evolutional history, functional traits, interactions between species and the abiotic environment, and biotic interactions. The arrival of the current era of big data offers a potential solution to address these shortfalls. Big data mining and its applications have recently become the frontier of biodiversity science and macroecology. It is a challenge for ecologists to utilize and effectively analyze the ever-growing quantity of biodiversity data. In this paper, I review several biodiversity-related studies over global, continental, and regional scales, and demonstrate how big data approaches are used to address biodiversity questions. These examples include forest cover changes, conservation ecology, biodiversity and ecosystem functioning, and the effect of climate change on biodiversity. Furthermore, I summarize the current challenges facing biodiversity data collection, data processing and data analysis, and discuss potential applications of big data approaches in the fields of biodiversity science and macroecology.
Received: 15 February 2017
Published: 20 April 2017