Distribution pattern and change prediction of Saposhnikovia divaricata suitable area in China under climate change

Chen, Bingrui; Zou, Hui; Zhang, Boyan; Zhang, Xiyuan; Jin, Xinqiao; Wang, Chen; Zhang, Xinxin

doi:10.1016/j.ecolind.2022.109311

Cited by 15 publications

(11 citation statements)

References 45 publications

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“…Spatially, consistently with the migration direction of most plant species (B. Chen, Zou, et al, 2022;W. Li et al, 2019;Yin et al, 2022;, the overall distribution areas gradually move to the northwest of the current suitable areas (high latitude and high altitude areas).…”

Section: Spatial Transformation Characteristics Of T Chinenseunder Cl...mentioning

confidence: 74%

The wild tending framework of medicinal plants constructed based on Biomod2 and PLUS model: A case study of Thesium chinense Turcz. in China

Zhang

Chen

Zhou

et al. 2023

Preprint

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Wild medicinal plants dominate the market of Traditonal Chinese Medicine (TCM). However, the intensification of human activities and ecological deterioration have caused a gradual depletion or extinction of wild medicinal plant resources in China. Scientific planning of wild tending areas is a priority to realize the sustainable utilization of wild medicinal plant resources. Thesium chinense, a known “plant antibiotic”, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we combined three atmospheric circulation models and four common socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to explore the main environmental factors affecting the distribution of T. chinense and the changes in the suitable area under the complete niche based on the Biomod2 package. The PLUS model was used to predict and analyze the land use change trend in the climate-stable areas of T. chinense in the future. And the wild tending areas of T. chinense were planned using ZONATION software. In the next hundred years, the climate-stable areas of T. chinense in China will mainly be distributed in humid and subhumid area, and the natural habitat areas of T. chinense in this region will decrease year by year. Hot spot analysis showed that Qiqihar, Chifeng, Zunyi, and other counties were the most suitable for the wild tending of T. chinense. These results can provide a comprehensive research framework for wild tending planning of T. chinense and other medicinal plants.

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Section: Spatial Transformation Characteristics Of T Chinenseunder Cl...mentioning

confidence: 74%

The wild tending framework of medicinal plants constructed based on Biomod2 and PLUS model: A case study of Thesium chinense Turcz. in China

Zhang

Chen

Zhou

et al. 2023

Preprint

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“…When converting continuous predictions into a Boolean classification of "suitable" and "unsuitable", it is crucial to choose an appropriate threshold value 36 . We used the maximum training sensitivity plus specificity threshold, which maximized the True Skill Score (TSS) and generated binary maps 37 , 38 .…”

Section: Methodsmentioning

confidence: 99%

Distribution and protection of Thesium chinense Turcz. under climate and land use change

Zhang,

Chen,

Zhou

et al. 2024

Sci Rep

Self Cite

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Wild medicinal plants are prominent in the field of Traditional Chinese Medicine (TCM), but their availability is being impacted by human activities and ecological degradation in China. To ensure sustainable use of these resources, it is crucial to scientifically plan areas for wild plant cultivation. Thesium chinense, a known plant antibiotic, has been overharvested in recent years, resulting in a sharp reduction in its wild resources. In this study, we employed three atmospheric circulation models and four socio-economic approaches (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to investigate the primary environmental factors influencing the distribution of T. chinense. We also examined changes in its suitable area using the Biomod2 package. Additionally, we utilized the PLUS model to project and analyze future land use changes in climate-stable regions for T. chinense. Our planning for wild tending areas of T. chinense was facilitated by the ZONATION software. Over the next century, the climate-stable regions for T. chinense in China is approximately 383.05 × 104 km2, while the natural habitat in this region will progressively decline. Under the current climate conditions, about 65.06% of the habitats in the high suitable areas of T. chinense are not affected by future land use changes in China. Through hotspot analysis, we identified 17 hotspot cities as ideal areas for the wild tending of T. chinense, including 6 core hotspot cities, 6 sub-hotspot cities, and 5 fringe hotspot cities. These findings contribute to a comprehensive research framework for the cultivation planning of T. chinense and other medicinal plants.

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“…The species share some similarities in bioecology and population dynamics, and therefore some overlap in habitat selection [ 3 , 4 ]. The Italian locust is often found from Ukraine to southern Siberia, eastern Kazakhstan, and northwestern China, while the Asian locust and Siberian locust have a much wider range, covering the entire temperate and steppe regions of Eurasia, causing severe damage to local steppe ecosystems and agricultural production [ 5 , 6 , 7 ]. The occurrence of locust infestations is continuous and results from a combination of environmental factors and ecological conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Locusts may enhance net primary production over the years. For example, in dry steppes and semideserts, even between outbreaks, the Italian locust can consume a significant part of the aboveground vegetation, damaging the growing points of sagebrushes and accelerating their growth [ 5 , 20 ]. In addition, the plants themselves are harmed as locusts consume seeds and sprouts, inhibiting natural regeneration.…”

Section: Introductionmentioning

confidence: 99%

“…The availability of new datasets (e.g., soil moisture), methods, and technological progress contribute to this steady improvement. Species distribution models are binary models based on machine-learning algorithms used to understand the current distribution of species [ 5 , 29 , 30 ]. Various modeling approaches and MaxEnt model predictions are widely used in species distribution studies because they can accurately simulate species distributions and maintain accuracy and robustness in small sample settings [ 30 , 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

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Predictions Based on Different Climate Change Scenarios: The Habitat of Typical Locust Species Is Shrinking in Kazakhstan and Xinjiang, China

Guan

et al. 2022

Insects

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Climate change, especially climate extremes, can increase the uncertainty of locust outbreaks. The Italian locust (Calliptamus italicus (Linnaeus, 1758)), Asian migratory locust (Locusta migratoria migratoria Linnaeus, 1758), and Siberian locust (Gomphocerus sibiricus (Linnaeus, 1767)) are common pests widely distributed in the semidesert grasslands of Central Asia and its surrounding regions. Predicting the geographic distribution changes and future habitats of locusts in the context of climate warming is essential to effectively prevent large and sudden locust outbreaks. In this study, the optimized maximum entropy (MaxEnt) model, employing a combination of climatic, soil, and topographic factors, was used to predict the potential fitness areas of typical locusts in the 2030s and 2050s, assuming four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. Modeling results showed that the mean area under the curve (AUC) and true statistical skill (TSS) of the MaxEnt model reached 0.933 and 0.7651, respectively, indicating that the model exhibited good prediction performance. Our results showed that soil surface sand content, slope, mean precipitation during the hottest season, and precipitation seasonality were the key environmental variables affecting locust distribution in the region. The three locust species were mainly distributed in the upstream region of the Irtysh River, the Alatao Mountain region, the northern slopes of the Tianshan Mountains, around Sayram Lake, the eastern part of the Alakol Lake region, the Tekes River region, the western part of Ulungur Lake, the Ili River, and the upstream region of the Tarim River. According to several climate projections, the area of potential habitat for the three most common locust species will decrease by 3.9 × 104–4.6 × 104 km2 by the 2030s and by 6.4 × 104–10.6 × 104 km2 by the 2050s. As the climate becomes more extreme, the suitable area will shrink, but the highly suitable area will expand; thus, the risk of infestation should be taken seriously. Our study present a timely investigation to add to extensive literature currently appearing regarding the myriad ways climate change may affect species. While this naturally details a limited range of taxa, methods and potential impacts may be more broadly applicable to other locust species.

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Distribution pattern and change prediction of Saposhnikovia divaricata suitable area in China under climate change

Cited by 15 publications

References 45 publications

The wild tending framework of medicinal plants constructed based on Biomod2 and PLUS model: A case study of Thesium chinense Turcz. in China

The wild tending framework of medicinal plants constructed based on Biomod2 and PLUS model: A case study of Thesium chinense Turcz. in China

Distribution and protection of Thesium chinense Turcz. under climate and land use change

Predictions Based on Different Climate Change Scenarios: The Habitat of Typical Locust Species Is Shrinking in Kazakhstan and Xinjiang, China

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