The impact of global warming on the potential suitable planting area of Pistacia chinensis is limited

Guo, Yuxue; Zhao, Zefang; Zhu, Fuxin; Gao, Bei

doi:10.1016/j.scitotenv.2022.161007

Cited by 4 publications

(4 citation statements)

References 55 publications

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“…Variables with a correlation coefficient greater than 0.75 were considered highly correlated, and only those with high importance and interpretability were retained for species distribution modeling. The method of evaluating and selecting variables based on their importance using ensemble models allows for a more comprehensive consideration of each variable’s contribution to model predictions compared to other approaches for addressing multicollinearity [ 50 , 51 ]. Consequently, this method facilitates the selection of important variables, thereby enhancing the interpretability of the model.…”

Section: Methodsmentioning

confidence: 99%

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Impacts of Climate Change on the Biogeography and Ecological Structure of Zelkova schneideriana Hand.-Mazz. in China

Wang,

Zhang,

Sheng

et al. 2024

Plants

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This study utilized the platform for ensemble forecasting of species distributions, biomod2, to predict and quantitatively analyze the distribution changes of Zelkova schneideriana Hand.-Mazz. under different climate scenarios (SSP1-2.6 and SSP5-8.5) based on climate and land-use data. This study evaluated the geographic range changes in future distribution areas and the results indicated that, under both SSP1-2.6 and SSP5-8.5 scenarios, the distribution area of Zelkova schneideriana would be reduced, showing a trend towards migration to higher latitudes and elevations. Particularly, in the more extreme SSP5-8.5 scenario, the contraction of the distribution area was more pronounced, accompanied by more significant migration characteristics. Furthermore, the ecological structure within the distribution area of Zelkova schneideriana also experienced significant changes, with an increasing degree of fragmentation. The variables of Bio6 (minimum temperature of the coldest month), Bio2 (mean diurnal temperature range), Bio15 (precipitation seasonality), and elevation exhibited important influences on the distribution of Zelkova schneideriana, with temperature being particularly significant. Changes in land use, especially the conversion of cropland, had a significant impact on the species’ habitat. These research findings highlight the distributional pressures faced by Zelkova schneideriana in the future, emphasizing the crucial need for targeted conservation measures to protect this species and similar organisms.

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Section: Methodsmentioning

confidence: 99%

“…Default parameters were used for all models. The use of multiple modeling techniques can reduce the prediction bias caused by individual models, and ensemble modeling has been widely used in species distribution prediction [16,51]. The data were divided into training data (75%) and testing data (25%) [56].…”

Section: Species Distribution Modelmentioning

confidence: 99%

Impacts of Climate Change on the Biogeography and Ecological Structure of Zelkova schneideriana Hand.-Mazz. in China

Wang,

Zhang,

Sheng

et al. 2024

Plants

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“…The main emphasis lies in the characteristics of short duration, simplified operation, minimal sample size requirement, and superior performance. As a result, MaxEnt is widely used to predict the geographical distributions of endangered animals, plants, and invasive species colonization [ 7 , 23 – 25 ].…”

Section: Introductionmentioning

confidence: 99%

Predicting the global potential distribution of Bursaphelenchus xylophilus using an ecological niche model: expansion trend and the main driving factors

Xiao,

Guo,

Xie

et al. 2024

BMC Ecol Evo

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Bursaphelenchus xylophilus (Steiner&Buhrer) Nickle is a global quarantine pest that causes devastating mortality in pine species. The rapid and uncontrollable parasitic spread of this organism results in substantial economic losses to pine forests annually. In this study, we used the MaxEnt model and GIS software ArcGIS10.8 to predict the distribution of B. xylophilus based on collected distribution points and 19 environmental variables (with a correlation coefficient of|R| > 0.8) for the contemporary period (1970–2000), 2041–2060 (2050s), 2061–2080 (2070s), and 2081–2100 (2090s) under four shared socioeconomic pathways (SSPs). We conducted a comprehensive analysis of the key environmental factors affecting the geographical distribution of B. xylophilus and suitable distribution areas. Our results indicate that in current prediction maps B. xylophilus had potential suitable habitats in all continents except Antarctica, with East Asia being the region with the most highly suitable areas and the most serious epidemic area currently. Precipitation of the warmest quarter, temperature seasonality, precipitation of the wettest month, and maximum temperature of the warmest month were identified as key environmental variables that determine the distribution of B. xylophilus. Under future climatic conditions, the potential geographic distribution of B. xylophilus will expand relative to current conditions. In particular, under the SSP5-8.5 scenario in 2081–2100, suitable areas will expand to higher latitudes, and there will be significant changes in suitable areas in Europe, East Asia, and North America. These findings are crucial for future prevention and control management and monitoring.

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“…Notably, MaxEnt, in accordance with the principle of maximum entropy [19,22,26], is frequently regarded as outperforming other species distribution models (SDMs) due to its strong toleration and precise forecasting in many model intercomparisons [27][28][29]. Researchers worldwide in the last decade have achieved significant success in applying species distribution models to issues such as protecting the diversity of rare animals and plants [30][31][32][33], estimating the dangers of invasive species [34][35][36], protecting marine ecosystem [37,38], predicting disaster distribution [39], and disease propagation [40,41], employing the MaxEnt model.…”

Section: Introductionmentioning

confidence: 99%

Modeling Climate Change Indicates Potential Shifts in the Global Distribution of Orchardgrass

Yan

Zhao

et al. 2023

Agronomy

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Orchardgrass (Dactylis glomerata L.) is highly tolerant of shade, cold, and overwintering, making it an ideal species for grassland ecological restoration and livestock production. However, the genetic diversity of orchardgrass may be threatened by climate change. Using a Maximum Entropy (MaxEnt) model with the BCC-CSM2-MR global climate database and the Harmonized World Soil Database, we projected the current and future distribution of orchardgrass suitable areas globally. The predicted ecological thresholds for vital environmental factors were determined to be a temperature seasonality range of 411.50–1034.37 °C, a mean diurnal range of −0.88–10.69 °C, a maximum temperature of the warmest month of 22.21–35.45 °C, and precipitation of the coldest quarter of 116.56–825.40 mm. A range of AUC values from 0.914 to 0.922, indicating the accuracy of the prediction model. Our results indicate that the total area of current suitable habitats for orchardgrass was estimated to be 2133.01 × 104 km2, it is dispersed unevenly over six continents. Additionally, the suitable areas of habitats increased in higher latitudes while decreasing in lower latitudes as greenhouse gas emissions increased. Therefore, efforts should be made to save places in the southern hemisphere that are in danger of becoming unsuitable, with the possibility of using northern America, China, and Europe in the future for conservation and extensive farming.

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The impact of global warming on the potential suitable planting area of Pistacia chinensis is limited

Cited by 4 publications

References 55 publications

Impacts of Climate Change on the Biogeography and Ecological Structure of Zelkova schneideriana Hand.-Mazz. in China

Impacts of Climate Change on the Biogeography and Ecological Structure of Zelkova schneideriana Hand.-Mazz. in China

Predicting the global potential distribution of Bursaphelenchus xylophilus using an ecological niche model: expansion trend and the main driving factors

Modeling Climate Change Indicates Potential Shifts in the Global Distribution of Orchardgrass

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