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      Habitat Distribution Pattern of Rare and Endangered Plant Magnolia wufengensis in China under Climate Change

      , , , , ,
      Forests
      MDPI AG

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          Abstract

          Magnolia wufengensis is a newly discovered rare and endangered species endemic to China. The primary objective of this study is to find the most suitable species distribution models (SDMs) by comparing the different SDMs to predict their habitat distribution for protection and introduction in China under climate change. SDMs are important tools for studying species distribution patterns under climate change, and different SDMs have different simulation effects. Thus, to identify the potential habitat for M. wufengensis currently and in the 2050s (2041–2060) and 2070s (2061–2080) under different climate change scenarios (representative concentration pathways RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in China, four SDMs, Maxent, GARP, Bioclim, and Domain, were first used to compare the predicted habitat and explore the dominant environmental factors. The four SDMs predicted that the potential habitats were mainly south of 40° N and east of 97° E in China, with a high distribution potential under current climate conditions. The area under the receiver operating characteristic (ROC) curve (AUC) (0.9479 ± 0.0080) was the highest, and the Kappa value (0.8113 ± 0.0228) of the consistency test and its performance in predicting the potential suitable habitat were the best in the Maxent model. The minimum temperature of the coldest month (−13.36–9.84 °C), mean temperature of the coldest quarter (−6.06–12.66 °C), annual mean temperature (≥4.49 °C), and elevation (0–2803.93 m), were the dominant factors. In the current climate scenario, areas of 46.60 × 104 km2 (4.85%), 122.82 × 104 km2 (12.79%), and 96.36 × 104 km2 (10.03%), which were mainly in central and southeastern China, were predicted to be potential suitable habitats of high, moderate, and low suitability, respectively. The predicted suitable habitats will significantly change by the 2050s (2040–2060) and 2070s (2060–2080), suggesting that M. wufengensis will increase in high-elevation areas and shift northeast with future climate change. The comparison of current and future suitable habitats revealed declines of approximately 4.53%–29.98% in highly suitable habitats and increases of approximately 6.45%–27.09% and 0.77%–21.86% in moderately and lowly suitable habitats, respectively. In summary, these results provide a theoretical basis for the response to climate change, protection, precise introduction, cultivation, and rational site selection of M. wufengensis in the future.

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          Most cited references68

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          Maximum entropy modeling of species geographic distributions

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            Novel methods improve prediction of species’ distributions from occurrence data

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              Climate change. Accelerating extinction risk from climate change.

              Mark Urban (2015)
              Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change-induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions.
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                Author and article information

                Journal
                FOREGK
                Forests
                Forests
                MDPI AG
                1999-4907
                September 2023
                August 31 2023
                : 14
                : 9
                : 1767
                Article
                10.3390/f14091767
                a809ce3c-5976-441b-8460-b758cab5b50b
                © 2023

                https://creativecommons.org/licenses/by/4.0/

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