Predicting growth and habitat responses of Ginkgo biloba L. to climate change

Sample locations. The color gradient on the map shows the mean annual temperature (MAT) in China

We developed a climatic response function using 20-year tree height observed from 45 Ginkgo biloba plantations in China and used it to predict the growth and habitat responses to anticipated climate change. We projected northward and upward shifts in the species habitat and productive areas, but a dramatic contraction of the species distribution is unlikely to occur at least during the present century.

Context Ginkgo biloba is the only living species in the division Ginkgophyta. The species exists in small natural populations in southeastern China but is cultivated across China and the world. The species’ future under climate change is of concern.
Aims This study was initiated to model the species’ growth response to climate change and to predict its range of suitable habitat under future climates.
Methods Using height data from 45 20 years old plantations growing under a wide range of climatic conditions across China, we developed univariate and bivariate climatic response functions to identify the climate requirements of the species.
Results According to the amount of variance explained (> 70%) and the high level of agreement (> 99%) with independent species occurrence coordinates, the developed climate response function was highly accurate and credible. Projections for future periods (2011–2040, 2041–2070, and 2071–2100) under the Representative Concentration Pathway 4.5 (RCP4.5) scenario indicated that the areas of potential suitable habitat would increase (25–67 million hectares). It would also be associated with northward (0.21–0.62° in latitude) and elevational (24–75 m) shifts.
Conclusion Global climate change is projected to increase the area of potential suitable habitats for Ginkgo and shift its spatial distributions northward and upward.

Climate response function, Suitable habitat, Climate change, Growth traits, Future projections

Open-access Publication
Guo, Y., Lu, Y., El-Kassaby, Y.A. et al. Annals of Forest Science (2019) 76: 101.

Data availability
The datasets generated and/or analyzed during the current study are available in the Mendeley Data Repository (Guo et al. 2019) at

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