Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models DOI
Shiqi Chen,

Guanghui Guo,

Mei Lei

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 954, P. 176213 - 176213

Published: Sept. 18, 2024

Language: Английский

Prediction of the Potentially Risk Areas for the Invasive Plant <i>Solanum </i><i>aculeatissimum</i> <i>Jacq.</i> in China under the Background of Climate Change Based on MaxEnt Optimization Model DOI

鸿沛 韩

Open Journal of Natural Science, Journal Year: 2025, Volume and Issue: 13(02), P. 261 - 276

Published: Jan. 1, 2025

Language: Английский

Citations

0

Spatial and temporal distribution characteristics of Paris polyphylla var. yunnanensis and the prediction of steroidal saponins content DOI Creative Commons

Zhong Chen,

Li Li,

Yuanzhong Wang

et al.

Industrial Crops and Products, Journal Year: 2025, Volume and Issue: 227, P. 120840 - 120840

Published: March 11, 2025

Language: Английский

Citations

0

Climate change and medicinal plant biodiversity: conservation strategies for sustainable use and genetic resource preservation DOI
Wajid Zaman, Asma Ayaz, SeonJoo Park

et al.

Genetic Resources and Crop Evolution, Journal Year: 2025, Volume and Issue: unknown

Published: March 21, 2025

Language: Английский

Citations

0

Advancements in ecological niche models for forest adaptation to climate change: a comprehensive review DOI Creative Commons
Wenhuan Xu, Dawei Luo, Kate Peterson

et al.

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

ABSTRACT Climate change poses significant challenges to the health and functions of forest ecosystems. Ecological niche models have emerged as crucial tools for understanding impact climate on forests at population, species, ecosystem levels. These also play a pivotal role in developing adaptive conservation management strategies. Recent advancements model development led enhanced prediction accuracy broadened applications models, driven using high‐quality data, improved algorithms, application landscape genomic information. In this review, we start by elucidating concept rationale behind context forestry adaptation change. We then provide an overview occurrence‐based, trait‐based, genomics‐based contributing more comprehensive species responses addition, summarize findings from 338 studies highlight progress made tree including data sources, future scenarios used diverse applications. To assist researchers practitioners, exemplar set accompanying source code tutorial, demonstrating integration population genetics into models. This paper aims concise yet continuous refinements serving valuable resource effectively addressing posed changing climate.

Language: Английский

Citations

0

Habitat Suitability Shifts of Eucommia ulmoides in Southwest China Under Climate Change Projections DOI Creative Commons
Qi Liu, Longjiang Liu, Juan Xue

et al.

Biology, Journal Year: 2025, Volume and Issue: 14(4), P. 451 - 451

Published: April 21, 2025

As a Chinese endemic species with dual medicinal–industrial importance, Eucommia ulmoides faces habitat challenges under climate change. Using 21 bioclimatic variables and 704 occurrence records, we modeled current future (2021–2100) distributions via MaxEnt 3.4.4 ArcGIS 10.8. The results indicate the following: (1) optimal habitats cluster in mid-elevation valleys of Daba–Wuling Mountains (Guizhou–Chongqing core); (2) SSP5-8.5 projections suggest 19.2% reduction high-suitability areas by 2081–2100 versus SSP1-2.6; (3) distribution centroids migrate southward both scenarios. Our multi-temporal analysis provides actionable intelligence for ex situ conservation agroforestry planning.

Language: Английский

Citations

0

Insight into the Influence of Ecological Factors on Shaping Distribution Patterns of Camptotheca acuminata for Conservation and Management DOI Creative Commons

T. J. Wang,

Yuchen Li,

Teja Manda

et al.

Plants, Journal Year: 2025, Volume and Issue: 14(10), P. 1466 - 1466

Published: May 14, 2025

Camptotheca acuminata Decne. is an endemic and valuable tree species in China that renowned for its medicinal economic value due to secondary metabolites like camptothecin, a potent anti-cancer compound. With wild resources dwindling, it key protected species. Predicting analyzing suitable habitats under different future environmental scenarios essential conservation, introduction, development, planting strategies. This study used 1008 distribution points 32 factors, applying the MaxEnt v3.4.4 model ArcGIS v10.7 software predict C. acuminata’s potential four greenhouse gas emission (RCP2.6, RCP4.5, RCP6.0, RCP8.5) present, 2050, 2070. identifies factors influencing analyzes habitat trends various ecological scenarios. The dominant are Bio6 (contribution 23%; importance 59.8%), human activity factor 18.6%; 15.7%), Slope2 1%; 7%), Slope3 5.1%; 3.4%), elevation 0.9%; 1.7%), Bio14 41.2%; 1%). total area 1.5796 × 104 km2. Except RCP8.5, where continuously increases, shows trend of first increasing then decreasing. When considered, 1.8495 km2, with consistent decrease all except RCP8.5. Centroid migration analysis that, driven by global warming, shifting toward higher latitudes. provides theoretical support resource management, germplasm protection changes.

Language: Английский

Citations

0

Prediction of Chinese suitable habitats of Panax notoginseng under climate change based on MaxEnt and chemometric methods DOI Creative Commons

Yixin Guo,

Shiyan Zhang,

Linghui Ren

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: July 16, 2024

Abstract Notoginseng saponin R1; ginsenosides Rg1, Re, Rb1, and Rd; the sum of five saponins; underground-part fresh weight (UPFW) single plants were used as quality evaluation indices for Panax notoginseng (Burk.) F. H. Chen ( P. ). Comprehensive samples from 30 production areas was performed using that MaxEnt model. Spatial pattern changes in suitable habitats predicted current future periods (2050s, 2070s, 2090s) SSP126 SSP585 models. The results revealed temperature, precipitation, solar radiation important environmental variables. Suitable located mainly Yunnan, Guizhou, Sichuan Provinces. distribution core is to shift southeast future. content decreased northwest Yunnan Province, which contrary UPFW trend. This study provides necessary information protection sustainable utilization resources, a theoretical reference its application Chinese medicinal products.

Language: Английский

Citations

1

Ecological Security Patterns Based on Ecosystem Services and Local Dominant Species in the Kunlun Mountains DOI Creative Commons
Jianglong Yuan, Ran Wang,

Xiaohuang Liu

et al.

Diversity, Journal Year: 2024, Volume and Issue: 16(12), P. 779 - 779

Published: Dec. 23, 2024

Constructing an ecological security pattern in ecologically fragile areas is crucial for maintaining regional stability. This study focuses on the Kunlun Mountain region, identifying sources based habitat suitability assessments and ecosystem services. An resistance evaluation index system constructed, considering topography, land use, quality. The minimum cumulative model then applied to identify corridors, with exhibiting higher currents designated as nodes. By integrating spatial characteristics of services, established. results are follows: (1) source area covers approximately 11.30% area. (2) length corridors 21,111 km, mainly distributed along valleys, gentle slopes, oasis areas. (3) nodes barriers 126.75 km2 46.75 km2, respectively. Ecological both sides Mountains, while primarily located central mountainous Mountains. (4) findings recommend establishing consisting “2 horizontal 4 vertical 5 zones” ensure integration services constructing a provides valuable decision-making tools protecting ecosystems species

Language: Английский

Citations

1

Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models DOI
Shiqi Chen,

Guanghui Guo,

Mei Lei

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 954, P. 176213 - 176213

Published: Sept. 18, 2024

Language: Английский

Citations

0