scholarly journals The Influence of Climate Change on Three Dominant Alpine Species under Different Scenarios on the Qinghai–Tibetan Plateau

Diversity ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 682
Author(s):  
Huawei Hu ◽  
Yanqiang Wei ◽  
Wenying Wang ◽  
Chunya Wang
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Potential Distribution ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Picea Crassifolia ◽  
Maxent Model ◽  
Sabina Przewalskii ◽  
Dominant Plant Species ◽  
Temperature Seasonality

The Qinghai–Tibetan Plateau (QTP) with high altitude and low temperature is one of the most sensitive areas to climate change and has recently experienced continuous warming. The species distribution on the QTP has undergone significant changes especially an upward shift with global warming in the past decades. In this study, two dominant trees (Picea crassifolia Kom and Sabina przewalskii Kom) and one dominant shrub (Potentilla parvifolia Fisch) were selected and their potential distributions using the MaxEnt model during three periods (current, the 2050s and the 2070s) were predicted. The predictions were based on four shared socio-economic pathway (SSPs) scenarios, namely, SSP2.6, SSP4.5, SSP7.0, SSP8.5. The predicted current potential distribution of three species was basically located in the northeastern of QTP, and the distribution of three species was most impacted by aspect, elevation, temperature seasonality, annual precipitation, precipitation of driest month, Subsoil CEC (clay), Subsoil bulk density and Subsoil CEC (soil). There were significant differences in the potential distribution of three species under four climate scenarios in the 2050s and 2070s including expanding, shifting, and shrinking. The total suitable habitat for Picea crassifolia shrank under SSP2.6, SSP4.5, SSP7.0 and enlarged under SSP8.5 in the 2070s. On the contrary, the total suitable habitat for Sabina przewalskii enlarged under SSP2.6, SSP4.5, SSP7.0 and shrank under SSP8.5 in the 2070s. The total suitable habitat for Potentilla parvifolia continued to increase with SSP2.6 to SSP8.5 in the 2070s. The average elevation in potentially suitable habitat for Potentilla parvifolia all increased except under SSP8.5 in the 2050s. Our study provides an important reference for the conservation of Picea crassifolia, Sabina przewalskii, Potentilla parvifolia and other dominant plant species on the QTP under future climate change.

scholarly journals Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model

2021 ◽  
Vol 13 (20) ◽  
pp. 11253
Author(s):  
Zhen Cao ◽  
Lei Zhang ◽  
Xinxin Zhang ◽  
Zengjun Guo
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Characteristic Curve ◽  
Future Climate Change ◽  
Mean Annual Temperature ◽  
Suitable Habitat ◽  
Entropy Model ◽  
Factors Affecting ◽  
Jackknife Test ◽  
Maxent Model

Hylomecon japonica is considered a natural medicinal plant with anti-inflammatory, anticancer and antibacterial activity. The assessment of climate change impact on its habitat suitability is important for the wild cultivation and standardized planting of H. japonica. In this study, the maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the current and future distribution of H. japonica species, and the contributions of variables were evaluated by using the jackknife test. The area under the receiver operating characteristic curve (AUC) value confirmed the accuracy of the model prediction based on 102 occurrence records. The predicted potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi, Chongqing, Henan, Heilongjiang and other provinces (adaptability index > 0.6). The jackknife experiment showed that the precipitation of driest month (40.5%), mean annual temperature (12.4%), the precipitation of wettest quarter (11.6%) and the subclass of soil (9.7%) were the most important factors affecting the potential distribution of H. japonica. In the future, only under the shared socioeconomic Pathway 245 (SSP 245) scenario model in 2061–2080, the suitable habitat area for H. japonica is expected to show a significant upward trend. The area under other scenarios may not increase or decrease significantly.

scholarly journals Current and future suitable habitat areas for Nasuella olivacea (Gray, 1865) in Colombia and Ecuador and analysis of its distribution across different land uses

2020 ◽  
Vol 8 ◽  
Author(s):  
Pablo Medrano-Vizcaíno ◽  
Patricia Gutiérrez-Salazar
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Wildlife Conservation ◽  
Distribution Patterns ◽  
Climatic Conditions ◽  
Future Climate ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Ecological Niche Models

Nasuella olivacea is an endemic mammal from the Andes of Ecuador and Colombia. Due to its rarity, aspects about its natural history, ecology and distribution patterns are not well known, therefore, research is needed to generate knowledge about this carnivore and a first step is studying suitable habitat areas. We performed Ecological Niche Models and applied future climate change scenarios (2.6 and 8.5 RCP) to determine the potential distribution of this mammal in Colombia and Ecuador, with current and future climate change conditions; furthermore, we analysed its distribution along several land covers. We found that N. olivacea is likely to be found in areas where no records have been reported previously; likewise, climate change conditions would increase suitable distribution areas. Concerning land cover, 73.4% of N. olivacea potential distribution was located outside Protected Areas (PA), 46.1% in Forests and 40.3% in Agricultural Lands. These findings highlight the need to further research understudied species, furthering our understanding about distribution trends and responses to changing climatic conditions, as well as informig future PA designing. These are essential tools for supporting wildlife conservation plans, being applicable for rare species whose biology and ecology remain unknown.

scholarly journals The Global Potential Distribution of Invasive Plants: Anredera cordifolia under Climate Change and Human Activity Based on Random Forest Models

2020 ◽  
Vol 12 (4) ◽  
pp. 1491
Author(s):  
Xuhui Zhang ◽  
Haiyan Wei ◽  
Zefang Zhao ◽  
Jing Liu ◽  
Quanzhong Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Random Forest ◽  
Potential Distribution ◽  
Future Climate ◽  
Eastern Africa ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Annual Range ◽  
Forest Models ◽  
Random Forest Models

The potential distribution of the invasive plant Anredera cordifolia (Tenore) Steenis was predicted by Random Forest models under current and future climate-change pathways (i.e., RCP4.5 and RCP8.5 of 2050s and the 2070s). Pearson correlations were used to select variables; the prediction accuracy of the models was evaluated by using AUC, Kappa, and TSS. The results show that suitable future distribution areas are mainly in Southeast Asia, Eastern Oceania, a few parts of Eastern Africa, Southern North America, and Eastern South America. Temperature is the key climatic factor affecting the distribution of A. cordifolia. Important metrics include mean temperature of the coldest quarter (0.3 °C ≤ Bio11 ≤ 22.9 °C), max temperature of the warmest month (17.1 °C ≤ Bio5 ≤ 35.5 °C), temperature annual range (10.7 °C ≤ Bio7 ≤ 33 °C), annual mean air temperature (6.8 °C ≤ Bio1 ≤ 24.4 °C), and min temperature of coldest month (−2.8 °C ≤ Bio6 ≤ 17.2 °C). Only one precipitation index (Bio19) was important, precipitation of coldest quarter (7 mm ≤ Bio19 ≤ 631 mm). In addition, areas with strong human activities are most prone to invasion. This species is native to Brazil, but has been introduced in Asia, where it is widely planted and has escaped from cultivation. Under the future climate scenarios, suitable habitat areas of A. cordifolia will expand to higher latitudes. This study can provide a reference for the rational management and control of A. cordifolia.

scholarly journals Predicting the Potential Distribution of Paeonia veitchii (Paeoniaceae) in China by Incorporating Climate Change into a Maxent Model

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 190 ◽  
Author(s):  
Keliang Zhang ◽  
Yin Zhang ◽  
Jun Tao
Keyword(s):  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Potential Distribution ◽  
Central Area ◽  
Background Information ◽  
Suitable Habitat ◽  
Gas Emissions ◽  
Maxent Model ◽  
Precipitation Seasonality ◽  
Temperature Seasonality

A detailed understanding of species distribution is usually a prerequisite for the rehabilitation and utilization of species in an ecosystem. Paeonia veitchii (Paeoniaceae), which is an endemic species of China, is an ornamental and medicinal plant that features high economic and ecological values. With the decrease of its population in recent decades, it has become a locally endangered species. In present study, we modeled the potential distribution of P. veitchii under current and future conditions, and evaluated the importance of the factors that shape its distribution. The results revealed a highly and moderately suitable habitat for P. veitchii that encompassed ca. 605,114 km2. The central area lies in northwest Sichuan Province. Elevation, temperature seasonality, annual mean precipitation, and precipitation seasonality were identified as the most important factors shaping the distribution of P. veitchii. Under the scenario with a low concentration of greenhouse gas emissions (RCP 2.6), we predicted an overall expansion of the potential distribution by 2050, followed by a slight contraction in 2070. However, with the scenario featuring intense greenhouse gas emissions (RCP 8.5), the range of suitable habitat should increase with the increasing intensity of global warming. The information that was obtained in the present study can provide background information related to the long-term conservation of this species.

scholarly journals Upward Shifts in Ageratina adenophora Global Distributions in Response to Future Climate Change Scenarios

2021 ◽  
Author(s):  
Changjun Gu ◽  
Tu Yanli ◽  
Linshan Liu ◽  
Wei Bo ◽  
Yili Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Future Climate ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Altitudinal Distribution ◽  
Invasive Weed ◽  
Crofton Weed ◽  
Ageratina Adenophora

Aim: Invasive alien species (IAS) threaten ecosystems and humans worldwide, and future climate change may accelerate the expansion of IAS. Predicting the suitable distributions of IAS can prevent their further expansion. Ageratina adenophora is a invasive weed over 30 countries in tropical and subtropical regions. However, the potential suitable distribution of A. adenophora remains unclear along with its response to climate change. This study explored and mapped the current and future potential distributions of Ageratina adenophora. Location: Global Taxa: Asteraceae A. adenophora (Spreng.) R.M.King & H.Rob. Commonly known as Crofton weed. Methods: Based on A. adenophora occurrence data and climate data, we predicted its potential distribution of this weed under current and future (four RCPs in 2050 and 2070) by MaxEnt model. We used ArcGIS 10.4 to explore the distribution characteristics of this weed and the ‘ecospat’ package in R to analyse its altitudinal distribution changes. Results: The area under the curve value (>0.9) indicated excelled model performance. Among environment factors, Mean Temperature of Coldest Quarter contributed most to the model. Globally, the suitable habitat for A.adenophora invasion decreased under climate change scenarios, although regional increase were observed, including in six biodiversity hotspot regions. The potential suitable habitat of A.adenophora under climate change moved toward regions with higher elevation. Main Conclusions: Temperature was the most important variable influencing the distribution of A. Adenophora. Under the background of warming climate, the potential distribution range of A.adenophora will shrink globally but increase regionally. The distribution of A.adenophora will shift toward higher elevation under climate change. Mountain ecosystems are of special concern as they are rich in biodiversity and sensitive to climate change, and increasing human activities provide more opportunities for IAS invasion.

scholarly journals Predicting The Potential Distribution of Campsis Grandiflora In China Under Climate Change

2021 ◽  
Author(s):  
Xianheng Ouyang ◽  
Jiangling Pan ◽  
Zhitao Wu ◽  
Anliang Chen
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Potential Distribution ◽  
Eastern China ◽  
Central China ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Monthly Precipitation ◽  
Mean Temperature ◽  
Diurnal Range

Abstract As the research of geographical distribution of species shows significant influence on people’s understanding of specie protection and utilization, it is important to study the influence of climate change onto the geographical distribution pattern of plants. Based on 166 distribution records as well as 11 climate and terrain variables with low correlation in China, we used MaxEnt (Maximum Entropy) model and ArcGIS software to predict the potential distribution of Campsis grandiflora under climate change and then determine the dominant climate variables which affect the geographical distribution significantly by analysis. The results show that the area under the curve (AUC) of the train is 0.939, which implies our prediction is accurate. Under the current climate condition, the area of potentially suitable habitat is 238.29×104 km2, mainly distributed in northern China, central China, southern China, and eastern China. The dominant variables affected the geographical distribution of Campsis grandiflora are mean diurnal range, range of annual temperature variation, mean temperature, mean temperature of the coldest season, the driest monthly precipitation, precipitation of the warmest quarter, as well as altitude. In the future climate change scenario, the total area of suitable habitat and highly suitable habitat will increase, whilst the area of moderately suitable habitat and poorly suitable habitat will decrease. In the meantime, the centroid of the potentially suitable area of Campsis grandiflora will migrate to higher latitude areas.

scholarly journals Event-based probabilistic risk assessment of livestock snow disasters in the Qinghai–Tibetan Plateau

2019 ◽  
Vol 19 (3) ◽  
pp. 697-713
Author(s):  
Tao Ye ◽  
Weihang Liu ◽  
Jidong Wu ◽  
Yijia Li ◽  
Peijun Shi ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
High Risk ◽  
Tibetan Plateau ◽  
Return Period ◽  
Probabilistic Risk Assessment ◽  
Future Climate Change ◽  
Tibet Autonomous Region ◽  
Event Based ◽  
Probabilistic Risk

Abstract. Understanding risk using quantitative risk assessment offers critical information for risk-informed reduction actions, investing in building resilience, and planning for adaptation. This study develops an event-based probabilistic risk assessment (PRA) model for livestock snow disasters in the Qinghai–Tibetan Plateau (QTP) region and derives risk assessment results based on historical climate conditions (1980–2015) and present-day prevention capacity. In the model, a hazard module was developed to identify and simulate individual snow disaster events based on boosted regression trees. By combining a fitted quantitative vulnerability function and exposure derived from vegetation type and grassland carrying capacity, we estimated risk metrics based on livestock mortality and mortality rate. In our results, high-risk regions include the Nyainqêntanglha Range, Tanggula Range, Bayankhar Mountains and the region between the Kailas Range and the neighbouring Himalayas. In these regions, annual livestock mortality rates were estimated as >2 % and mortality was estimated as >2 sheep unit km−1 at a return period of 20 years. Prefectures identified with extremely high risk include Guoluo in Qinghai Province and Naqu, and Shigatse in the Tibet Autonomous Region. In these prefectures, a snow disaster event with a return period of 20 years or higher can easily claim total losses of more than 500 000 sheep units. Our event-based PRA results provide a quantitative reference for preparedness and insurance solutions in reducing mortality risk. The methodology developed here can be further adapted to future climate change risk analyses and provide important information for planning climate change adaption in the QTP region.

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