Prediction of Suitable Regions for Danxiaorchis yangii Combined with Pollinators Based on the SDM Model
- PMID: 39520019
- PMCID: PMC11548668
- DOI: 10.3390/plants13213101
Prediction of Suitable Regions for Danxiaorchis yangii Combined with Pollinators Based on the SDM Model
Abstract
Danxiaorchis yangii, a newly discovered fully mycoheterotrophic orchid. It relies on Lysimachia alfredii and Dufourea spp. for pollination, and environmental factors closely influence the growth and distribution of these pollinators, which in turn directly affects the growth and reproduction of D. yangii. Climate change threatens the suitable habitats for these three species, emphasizing the need to understand D. yangii's response. This study comprehensively utilized the field distribution of D. yangii and related climatic data, along with future climate predictions from global models, to predict the climate suitability areas of D. yangii under two greenhouse gas emission scenarios (SSP245 and SSP370) using species distribution models (SDMs), which encompassed a random forest (RF) model. Additionally, we selected the optimal ensemble model (OEM) for Dufourea spp. and applied generalized boosted models (GBMs) and RF for L. alfredii in our predictions. The study found that precipitation of the driest quarter plays a pivotal role in determining the distribution of D. yangii, with an optimal range of 159 to 730 mm being most conducive to its growth. Comparative analysis further indicated that precipitation exerts a greater influence on D. yangii than temperature. Historically, D. yangii has been predominantly distributed across Jiangxi, Hunan, Zhejiang, and the Guangxi Zhuang Autonomous Region, with Jiangxi Province containing the largest area of highly suitable habitat, and this distribution largely overlaps with the suitable regions of its pollinators.
Keywords: Danxiaorchis yangii; Dufourea spp.; Lysimachia alfredii; suitable region.
Conflict of interest statement
The authors declare no conflict of interest.
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References
-
- Eliseev A.V., Mokhov I.I. Influence of volcanic activity on climate change in the past several centuries: Assessments with a climate model of intermediate complexity. Izv. Atmos. Ocean. Phys. 2008;44:671–683. doi: 10.1134/S0001433808060017. - DOI
-
- Smallwood P.A., Trapnell D.W. Species distribution modeling reveals recent shifts in suitable habitat for six north American Cypripedium spp. (Orchidaceae) Diversity. 2022;14:694. doi: 10.3390/d14090694. - DOI
-
- Franklin J., Miller J.A. Mapping Species Distributions: Spatial Inference and Prediction. Cambridge University Press; Cambridge, UK: 2009.
-
- Franklin J. Species distribution modelling supports the study of past, present and future biogeographies. J. Biogeogr. 2023;50:1533–1545. doi: 10.1111/jbi.14617. - DOI
-
- Zhang H., Zhao H.X., Wang H. Potential geographical distribution of Populus euphratica in China under future climate change scenarios based on Maxent model. Acta Ecol. Sin. 2020;40:6552–6563.
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