Evidence map›Paper›PMID 37608034›Full record

ArticleScientific reports2023

Modelling the effects of topographic heterogeneity on distribution of Nitraria tangutorum Bobr. species in deserts using LiDAR-data.

Huoyan Zhou, Linyan Feng, Liyong Fu, Ram P Sharma, Xiao Zhou, Xiaodi Zhao

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Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Huoyan ZhouSchool of Ecology and Environment Science, Yunnan University, Kunming, 650031, Yunnan Province, People's Republic of China.
Linyan FengInstitute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China.
Liyong FuInstitute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China.
Ram P SharmaInstitute of Forestry, Tribhuvan University, Kritipur, Kathmandu, 44600, Nepal.
Xiao ZhouInternational Center for Bamboo and Rattan, Key Laboratory of National Forestry and Grassland Administration, Beijing, 100091, China.
Xiaodi ZhaoResearch Institute of Forestry Policy and Information, Chinese Academy of Forestry, Beijing, 100091, People's Republic of China. zhaoxiaodi@caf.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microclimate ecology is attracting renewed attention because of its fundamental importance in understanding how organisms respond to climate change. Many hot issues can be investigated in desert ecosystems, including the relationship between species distribution and environmental gradients (e.g., elevation, slope, topographic convergence index, and solar insolation). Species Distribution Models (SDMs) can be used to understand these relationships. We used data acquired from the important desert plant Nitraria tangutorum Bobr. communities and desert topographic factors extracted from LiDAR (Light Detection and Ranging) data of one square kilometer in the inner Mongolia region of China to develop SDMs. We evaluated the performance of SDMs developed with a variety of both the parametric and nonparametric algorithms (Bioclimatic Modelling (BIOCLIM), Domain, Mahalanobi, Generalized Linear Model, Generalized Additive Model, Random Forest (RF), and Support Vector Machine). The area under the receiver operating characteristic curve was used to evaluate these algorithms. The SDMs developed with RF showed the best performance based on the area under curve (0.7733). We also produced the Nitraria tangutorum Bobr. distribution maps with the best SDM and suitable habitat area of the Domain model. Based on the suitability map, we conclude that Nitraria tangutorum Bobr. is more suited to southern part with 0-20 degree slopes at an elevation of approximately 1010 m. This is the first attempt of modelling the effects of topographic heterogeneity on the desert species distribution on a small scale. The presented SDMs can have important applications for predicting species distribution and will be useful for preparing conservation and management strategies for desert ecosystems on a small scale.

Indexed as

EcosystemMagnoliopsidaAlgorithmsChinaClimate ChangeEcology

Identifiers

PMID37608034
PMCPMC10444836

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