Abstract
Metasequoia glyptostroboides Hu & W. C. Cheng, which is a remarkable rare relict plant, has gradually been reduced to its current narrow range due to climate change. Understanding the comprehensive distribution of M. glyptostroboides under climate change on a large spatio-temporal scale is of great significance for determining its forest adaptation. In this study, based on 394 occurrence data and 10 bioclimatic variables, the global potential distribution of M. glyptostroboides under eight different climate scenarios (i.e., the past three, the current one, and the next four) from the Quaternary glacial to the future was simulated by a random forest model built with the biomod2 package. The key bioclimatic variables affecting the distribution of M. glyptostroboides are BIO2 (mean diurnal range), BIO1 (annual mean temperature), BIO9 (mean temperature of driest quarter), BIO6 (min temperature of coldest month), and BIO18 (precipitation of warmest quarter). The result indicates that the temperature affects the potential distribution of M. glyptostroboides more than the precipitation. A visualization of the results revealed that the current relatively suitable habitats of M. glyptostroboides are mainly distributed in East Asia and Western Europe, with a total area of approximately 6.857 × 106 km2. With the intensification of global warming in the future, the potential distribution and the suitability of M. glyptostroboides have a relatively non-pessimistic trend. Whether under the mild (RCP4.5) and higher (RCP8.5) emission scenarios, the total area of suitable habitats will be wider than it is now by the 2070s, and the habitat suitability will increase to varying degrees within a wide spatial range. After speculating on the potential distribution of M. glyptostroboides in the past, the glacial refugia of M. glyptostroboides were inferred, and projections regarding the future conditions of these places are expected to be optimistic. In order to better protect the species, the locations of its priority protected areas and key protected areas, mainly in Western Europe and East Asia, were further identified. Our results will provide theoretical reference for the long-term management of M. glyptostroboides, and can be used as background information for the restoration of other endangered species in the future.
Highlights
Climate is a crucial driver of physiological processes related to the species survival [1]
In terms of the distribution details, we found that the potential distribution of M. glyptostroboides was more similar to the current distribution in Europe, while the significant change mainly occurred in Asia, especially in China
The results showed that the refugia where the suitability will increase/decrease under future climate change are known as glacial refugia of M. glyptostroboides covers approximately 6.45 × 10 km, of which nearly 41.03% have a positive trend in habitat suitability, and 6.17% need to be treated with caution in the future
Summary
Climate is a crucial driver of physiological processes related to the species survival [1]. SDMs, known as ecological niche modeling (ENM), aim to predict species geographic distribution in projected range and threat levels through a set of statistical methods based on limited species records and corresponding environmental variables [7]. The RF model is an ensemble machine learning approach [17], which can build a large number of regression trees for classification and regression by selecting multiple sub-samples from the total data. This algorithm avoids the shortcomings of previous machine learning models that are prone to overfitting and has received increasing attention for the prediction of species potential distribution in recent years [18,19]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
