Current and future predicting habitat suitability map of Cunninghamia konishii Hayata using MaxEnt model under climate change in Northern Vietnam

Nguyen, Thanh Tuan; Gliottone, Ilaria; Pham, Mai Phuong

doi:10.17161/eurojecol.v7i2.15079

Cited by 8 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, climate change has brought far-reaching impacts on the distribution patterns of plant species in recent decades, constituting a primary cause of their decline and loss 6 . Temperature and precipitation changes brought by climate change modify plant physiological processes, affecting growth, development, reproduction, stability, and geographical distribution 7 , 8 . Notable and fast climate change can induce serious degradation or loss of species habitats.…”

Section: Introductionmentioning

confidence: 99%

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Wei,

Wang,

Xie

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Climate change has significantly influenced the growth and distribution of plant species, particularly those with a narrow ecological niche. Understanding climate change impacts on the distribution and spatial pattern of endangered species can improve conservation strategies. The MaxEnt model is widely applied to predict species distribution and environmental tolerance based on occurrence data. This study investigated the suitable habitats of the endangered Ormosia microphylla in China and evaluated the importance of bioclimatic factors in shaping its distribution. Occurrence data and environmental variables were gleaned to construct the MaxEnt model, and the resulting suitable habitat maps were evaluated for accuracy. The results showed that the MaxEnt model had an excellent simulation quality (AUC = 0.962). The major environmental factors predicting the current distribution of O. microphylla were the mean diurnal range (bio2) and precipitation of the driest month (bio14). The current core potential distribution areas were concentrated in Guangxi, Fujian, Guizhou, Guangdong, and Hunan provinces in south China, demonstrating significant differences in their distribution areas. Our findings contribute to developing effective conservation and management measures for O. microphylla, addressing the critical need for reliable prediction of unfavorable impacts on the potential suitable habitats of the endangered species.

show abstract

Section: Introductionmentioning

confidence: 99%

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Wei,

Wang,

Xie

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…The fundamental abiotic alterations disturb or damage species' habitats by changing the cardinal environmental attributes of temperature and precipitation [3,4]. Nature responds by modifying the structure, function and composition of biological communities and species distribution patterns at different scales [5,6]. In extreme cases, the diversity and stability of local and regional ecosystems could be disrupted and endangered [7].…”

Section: Introductionmentioning

confidence: 99%

Predicting Suitable Habitats for China’s Endangered Plant Handeliodendron bodinieri (H. Lév.) Rehder

Wang,

Xie,

Wei

et al. 2023

Diversity

View full text Add to dashboard Cite

Demarcating a plant species’ actual and potential biogeographical distribution is crucial for understanding the key environmental variables shaping its habitat conditions. We used MaxEnt and species distribution modeling to predict the likely range of China’s endangered species, Handeliodendron bodinieri (H. Lév.) Rehder, based on forty-four validated distribution records and eight selected environmental variables. Combined with percentage contribution and permutation importance, the jackknife statistical method was applied to test and evaluate pertinent factors restricting the potential distribution of H. bodinieri. The response curves of critical bioclimatic factors were employed to determine the potential species range. The generated MaxEnt model was confirmed to have excellent simulation accuracy. The current core potential distribution areas are concentrated in the Guangxi and Guizhou provinces of Southwest China, with a significant inter-regional difference. The precipitation of the warmest quarter (Bio18) and minimum temperature of the coldest month (Bio6) had the greatest impact on the distribution area of H. bodinieri. The findings could provide useful information and a reasonable reference for managers to enhance the protection of this declining species.

show abstract

“…Compared to other SDM tools, a maximum entropy algorithm can develop a good model with small number of occurrences (Harapan et al 2020). Because of this reason, many studies on threatened plants, which typically have small amounts of occurrence data, use MaxEnt to model species distributions (Adhikari et al 2012;Yang et al 2013;Padalia et al 2014;Pradhan 2015;Remya et al 2015;Yuan et al 2015;Yi et al 2016;Pranata et al 2019;Ito et al 2020;Anand et al 2021;Du et al 2021;Felix et al 2021;Liu et al 2021;Mahatara et al 2021;Nguyen et al 2021;Purohit and Rawat 2021;Su et al 2021;Yang et al 2021;Ye et al 2021). With effective conservation planning focused on ensuring redundancy and resiliency for sustainable future populations (Redford et al 2011), SDMs are a valuable tool for the conservation community (Mcshea 2014).…”

Section: Introductionmentioning

confidence: 99%

Identifying the potential geographic distribution for Castanopsis argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area Network, Indonesia

et al. 2022

View full text Add to dashboard Cite

Abstract. Harapan TS, Nurainas, Syamsuardi, Taufiq A. 2022. Identifying the potential geographic distribution for Castanopsis argentea and Castanopsis tungurrut (Family: Fagaceae) in the Sumatra Conservation Area Network, Indonesia. Biodiversitas 23: 1726-1733. Recently, Castanopsis argentea (Blume) A.DC. and Castanopsis tungurrut (Blume) A.DC. have been listed as endangered species by the International Union for the Conservation of Nature (IUCN). For conservation planning, it is important to know the full distribution of species. This study aimed to predict the potential distribution of C. argentea and C. tungurrut using MaxEnt, and understand key factors responsible for the distribution of these species. A total of 53 occurrences and six environmental variables were used to model their distribution. The AUC values of C. argentea and C. tungurrut were 0.86 and 0.91, respectively, and the models suggest the distribution of both species is mainly influenced by elevation, and temperature seasonality for C. tungurrut. The predicted distributions of the species are in the mountains of the western part of Sumatra, and their range includes 12 conservation areas that have highly suitable habitats for both species. After generating the MaxEnt prediction map, we conducted field validation to validate the model predictions. Field surveys in two predicted areas showed that the predicted distribution maps accurately estimated the distribution of C. argentea and C. tungurrut at those localities.

show abstract

Current and future predicting habitat suitability map of Cunninghamia konishii Hayata using MaxEnt model under climate change in Northern Vietnam

Cited by 8 publications

References 25 publications

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Predicting suitable habitat for the endangered tree Ormosia microphylla in China

Predicting Suitable Habitats for China’s Endangered Plant Handeliodendron bodinieri (H. Lév.) Rehder

Identifying the potential geographic distribution for Castanopsis argentea and C. tungurrut (Fagaceae) in the Sumatra Conservation Area Network, Indonesia

Contact Info

Product

Resources

About