Predicting differential habitat suitability of Rhodomyrtus tomentosa under current and future climate scenarios in China

Chun-ping, Xie; Huang, Bo-Yang; Jim, Chi Yung; Han, Weidong; Liu, Dawei

doi:10.1016/j.foreco.2021.119696

Cited by 18 publications

(15 citation statements)

References 66 publications

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“…The changes in the response curve could provide helpful information on the environmental thresholds required for optimal growth (Akyol et al, 2020 ). It is generally accepted that when the distribution probability is >0.50, the corresponding environmental factor value is suitable for the species (Xie et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

“…In this study, the model's accuracy was assessed by AUC, with a larger value indicating a higher accuracy of the prediction results (Abdelaal et al, 2019 ). AUC of 0.5–0.6, 0.6–0.7, 0.7–0.8, 0.8–0.9, and >0.9 indicated failure, poor, fair, good, and excellent categories for the predicted results, respectively (Abolmaali et al, 2018 ; Xie et al, 2021 ). The survival probability of C. henryi , indicated by the probability p , was reclassified into four categories of habitat suitability categories: poor ( p < .25), fair (0.25–0.50), good (0.50–0.75), and excellent (>0.75).…”

Section: Methodsmentioning

confidence: 99%

“…MaxEnt (maximum entropy) is the most widely used SDM with a high prediction accuracy (Abolmaali et al, 2018 ; Xie et al, 2021 ). The model describes a probability distribution where each grid cell has predicted suitable conditions for a species using a collection of environmental (e.g., climatic) grids and species georeferenced occurrence locations (Steven J. Phillips & Dudík, 2008 ).…”

Section: Introductionmentioning

confidence: 99%

“…MaxEnt (maximum entropy) is the most widely used SDM with a high prediction accuracy (Abolmaali et al, 2018;Xie et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Effects of climate‐change scenarios on the distribution patterns of Castanea henryi

Chun-ping

Tian

Jim

et al. 2022

Ecology and Evolution

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…MaxEnt (maximum entropy) is the most widely used SDM with a high prediction accuracy (Abolmaali et al, 2018;Xie et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effects of climate‐change scenarios on the distribution patterns of Castanea henryi

Chun-ping

Tian

Jim

et al. 2022

Ecology and Evolution

Self Cite

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“…Woody savannas and savannas were more influenced by LULC and more influenced by temperature among the climate factors. Their vegetation is dominated by Baeckea frutescens scrub, which is a secondary scrub formed by the succession of subtropical native vegetation after repeated deforestation or fire damage [74], significantly affected by temperature and not significantly affected by precipitation [79].…”

Section: Discussionmentioning

confidence: 99%

Changes in Vegetation Greenness and Their Influencing Factors in Southern China

Zhao

et al. 2022

Remote Sensing

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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.

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“Two zones and three centers” distribution and suitable areas shift of an evergreen oak in subtropical China under climate scenarios

Zhang,

Huang,

et al. 2024

Ecology and Evolution

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Understanding the impact of climate change on the geographical distribution of species is a fundamental requirement for biodiversity conservation and resource management. Quercus oxyphylla, an evergreen oak endemic to China, plays a crucial role in maintaining the ecological stability in subtropical regions and high economic value attributed to its dark and high‐density heartwood, but the existing resources are close to endangered. Currently, limited knowledge exists regarding its distribution and potential influences of climate change on suitable areas. This study utilized 63 occurrence records and Biomod2 platform, to predict changes in suitable areas for Q. oxyphylla under future climate change. The results revealed that (1) Q. oxyphylla showed a pattern of three disjunctive geographical centers in the eastern subregion of subtropical evergreen broad‐leaved forest region (IVA): Qinling‐Daba Mountains, Nanling Mountains and Wuyi Mountains center. Currently, the highly suitable areas concentrated in two zones divided by the Yangtze River, that is, the northern subtropical evergreen and deciduous broad‐leaved forest zone (IVAii) and the mid‐subtropical evergreen broad‐leaved forest zone (IVAi). (2) The temperature‐related variables, such as annual temperature range (Bio7), the mean diurnal range (Bio2), and annual mean temperature (Bio1), were identified as the key determinants of the distribution pattern. Because of its considerable climatic variations in temperature and water conditions, Q. oxyphylla's habitat displayed a wider climate niche and strong physiological tolerance to climate change. (3) Under future climate scenarios, the suitable area of the species was expected to overall expand with significant regional differences. The suitable area in IVAi was expected to expand significantly northward while that in IVAii was expected to gradually shrink. To address the impact of climate change, it is necessary to develop conservation plans focused around the three distribution centers, implement localized and regional conservation policies, and conduct educational outreach among local people.

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Predicting differential habitat suitability of Rhodomyrtus tomentosa under current and future climate scenarios in China

Cited by 18 publications

References 66 publications

Effects of climate‐change scenarios on the distribution patterns of Castanea henryi

Effects of climate‐change scenarios on the distribution patterns of Castanea henryi

Changes in Vegetation Greenness and Their Influencing Factors in Southern China

“Two zones and three centers” distribution and suitable areas shift of an evergreen oak in subtropical China under climate scenarios

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