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Boyang Huang

Bio: Boyang Huang is an academic researcher from Nanjing Agricultural University. The author has contributed to research in topics: Population. The author has co-authored 1 publications.
Topics: Population

Papers
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Journal ArticleDOI
TL;DR: In this paper, the potential biogeographical range of Rhodomyrtus tomentosa in China was predicted by Maxent and QGIS modeling under current and three future climate change scenarios.

11 citations


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TL;DR: In this paper , the authors applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate change scenarios, and found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces.
Abstract: Abstract Castanea henryi, with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate‐change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate‐change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi, assisted by a proposed three‐domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor‐made strategies.

8 citations

Journal ArticleDOI
10 Jan 2022-Forests
TL;DR: Based on combinations of climate, topography, soil variables, and the multiple model ensemble (MME) of CMIP6, this article explored the relationship between C. bungei and climate change, then constructed Maxent to predict its potential distribution under SSP126 and SSP585 and analyzed its dominant environmental factors.
Abstract: Catalpa bungei C. A. Mey. (C. bungei) is one of the recommended native species for ecological management in China. It is a fast-growing tree of high economic and ecological importance, but its rare resources, caused by anthropogenic destruction and local climatic degradation, have not satisfied the requirements. It has been widely recommended for large-scale afforestation of ecological management and gradually increasing in recent years, but the impact mechanism of climate change on its growth has not been studied yet. Studying the response of species to climate change is an important part of national afforestation planning. Based on combinations of climate, topography, soil variables, and the multiple model ensemble (MME) of CMIP6, this study explored the relationship between C. bungei and climate change, then constructed Maxent to predict its potential distribution under SSP126 and SSP585 and analyzed its dominant environmental factors. The results showed that C. bungei is widely distributed in Henan, Hebei, Hubei, Anhui, Jiangsu, and Shaanxi provinces and others where it covers an area of 2.96 × 106 km2. Under SSP126 and SSP585, its overall habitat area will increase by more than 14.2% in 2080–2100, which mainly indicates the transformation of unsuitable areas into low suitable areas. The center of its distribution will migrate to the north with a longer distance under SSP585 than that under SSP126, and it will transfer from the junction of Shaanxi and Hubei province to the north of Shaanxi province under SSP585 by 2100. In that case, C. bungei shows a large-area degradation trend in the south of the Yangtze River Basin but better suitability in the north of the Yellow River Basin, such as the Northeast Plain, the Tianshan Mountains, the Loess Plateau, and others. Temperature factors have the greatest impact on the distribution of C. bungei. It is mainly affected by the mean temperature of the coldest quarter, followed by precipitation of the wettest month, mean diurnal range, and precipitation of the coldest quarter. Our results hence demonstrate that the increase of the mean temperature of the coldest quarter becomes the main reason for its degradation, which simultaneously means a larger habitat boundary in Northeast China. The findings provide scientific evidence for the ecological restoration and sustainable development of C. bungei in China.

7 citations

Journal ArticleDOI
TL;DR: In this paper , the MaxEnt model was used to explore the relationship between the geographical distribution of S. javanica and environmental factors, and to construct the distribution pattern of Savanica under different climate scenarios.
Abstract: Sambucus javanica Blume is a Chinese native medicinal plant with high medicinal value. In this study, the MaxEnt model was used to explore the relationship between the geographical distribution of S. javanica and environmental factors, and to construct the distribution pattern of S. javanica under different climate scenarios. The results showed that the environmental conditions suitable for the distribution of S. javanica were as follows: precipitation in June ranged from 156.36 to 383.25 mm; solar radiation in December ranged from 6750.00 to 10,521.00 kJm−2day−1; isothermality ranged from 24.06 to 35.50; precipitation of warmest quarter ranged from 447.92 to 825.00 mm. Among them, precipitation and temperature were the key environmental factors affecting the distribution patterns of S. javanica. This plant could grow well mainly in two regions in China, covering a total area of 2.73 × 106 km2. The first region mainly consists of Guizhou, western Hubei, southeastern Chongqing, southwestern Hunan, northern Guangxi, and a small part of eastern Yunnan. The second region mainly consists of Zhejiang, southern Anhui, and northern Fujian. Under the future SSP126 and SSP585 scenarios, potentially suitable habitats in the eastern part of the potential distribution of S. javanica (Jiangxi, Fujian, Zhejiang, and Anhui) might be at risk of habitat fragmentation. Future climate change might have little effect on the distribution areas of S. javanica. But its suitable distribution has a tendency shift to higher altitude areas. Based on the result of this study, real-time monitoring of wild groups of S. javanica is now recommended to protect its genetic diversity. These findings are supposed to promote the effective conservation and utilization of S. javanica in the future.

3 citations

Journal ArticleDOI
TL;DR: Zhang et al. as discussed by the authors used NDVI as the vegetation greenness data, land cover data, temperature, precipitation, downgradient shortwave radiation, and CO2 data to investigate the interrelationship among vegetation, climate change, and human activities in southern China.
Abstract: Since the 21st century, China has experienced rapid development, and the spatial and temporal changes in vegetation cover have become increasingly significant. Southern China is a representative region for human activities, climate change, and vegetation change, but the current human understanding of the interactions between vegetation and its influencing factors is still very limited. In our study, we use NDVI as the vegetation greenness data, land cover data, temperature, precipitation, downgradient shortwave radiation, and CO2 data to investigate the interrelationship among vegetation, climate change, and human activities in southern China. The changes and their consistency were studied by trend analysis and Hurst exponent analysis. Then, the contribution of each influencing factor from 2001 to 2020 was quantified by random forest. The results showed that the vegetation in southern China showed an overall rising trend, and areas with a continuous changing trend were concentrated in the Pearl River Delta, western Guangdong, and eastern Guangdong, with a growth rate of 0.02∼0.04%. The vegetation in northern Guangdong did not change significantly. The main factor of NDVI spatial variation in southern China is the land-use factor, accounting for 79.4% of the variation, while climate factors produce further differences. The contributions and lagged effects of NDVI factors on different land-use types and the lagged effects of different climate factors are different and are related to the climate and vegetation background in Sourthern China. Our study is useful in estimating the contribution of NDVI change by each considered factor and formulating environmentally friendly regional development strategies and promoting human–land harmony.

1 citations