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Effects of ecological restoration measures on the distribution of Dicranopteris dichotoma at the microscale in the red soil hilly region of China

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  • Zhiqiang Chen
  • Zhibiao Chen

Abstract

Little is known about the evaluation of ecological restoration measures using species distribution models (SDMs) at the microscale. This study investigated the effect of arbor–bush–herb mixed plantation (ABHMP) on the potential distribution of D. dichotoma using SDMs in the typical microtopographies of the red soil hilly region of China. We examined D. dichotoma growth, microtopography, and environment-related factors at the microscale. The percentages of microtopographies and D. dichotoma physiology factors increased in the order from the valley to the ridge in the D. dichotoma patches. The valley had milder temperatures, higher humidity, and more fertile soil than the ridge in the gullies. Microclimate factors were the most critical environmental factors affecting the distribution of D. dichotoma, followed by soil factors, whereas the microtopography factors had only a marginal effect. The predicted potential distribution of D. dichotoma under the ABHMP scenario was nearly 3-fold higher than the current distribution, and the suitable area was located mostly in the level trenches and the valley. ABHMP had a strong effect on the potential distribution of D. dichotoma, and SDMs proved to be a valuable tool for assessing ecological restoration measures at the microscale.

Suggested Citation

  • Zhiqiang Chen & Zhibiao Chen, 2018. "Effects of ecological restoration measures on the distribution of Dicranopteris dichotoma at the microscale in the red soil hilly region of China," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0204743
    DOI: 10.1371/journal.pone.0204743
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    1. Coro, Gianpaolo & Magliozzi, Chiara & Vanden Berghe, Edward & Bailly, Nicolas & Ellenbroek, Anton & Pagano, Pasquale, 2016. "Estimating absence locations of marine species from data of scientific surveys in OBIS," Ecological Modelling, Elsevier, vol. 323(C), pages 61-76.
    2. Domisch, Sami & Kuemmerlen, Mathias & Jähnig, Sonja C. & Haase, Peter, 2013. "Choice of study area and predictors affect habitat suitability projections, but not the performance of species distribution models of stream biota," Ecological Modelling, Elsevier, vol. 257(C), pages 1-10.
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