MaxEnt Modeling to Predict the Current and Future Distribution of Pomatosace filicula under Climate Change Scenarios on the Qinghai–Tibet Plateau

Abstract

As an important Tibetan medicine and a secondary protected plant in China, Pomatosace filicula is endemic to the country and is mainly distributed in the Qinghai–Tibet Plateau (QTP). However, global climate change caused by greenhouse gas emissions might lead to the extinction of P. filicula. To understand the potential spatial distribution of P. filicula in future global warming scenarios, we used the MaxEnt model to simulate changes in its suitable habitat that would occur by 2050 and 2070 using four representative concentration pathway (RCP) scenarios and five global climate models. The results showed that the QTP currently contains a suitable habitat for P. filicula and will continue to do so in the future. Under the RCP2.6 scenario, the suitable habitat area would increase by 2050 but shrink slightly by 2070, with an average reduction of 2.7%. However, under the RCP8.5 scenario, the area of unsuitable habitat would expand by an average of 54.65% and 68.20% by 2050 and 2070, respectively. The changes in the area of suitable habitat under the RCP4.5 and RCP6.0 scenarios were similar, with the unsuitable area increasing by approximately 20% by 2050 and 2070. Under these two moderate RCPs, the total suitable area in 2070 would be greater than that in 2050. The top three environmental factors impacting the habitat distribution were altitude, annual precipitation (BIO12) and annual temperature range (BIO7). The cumulative contribution rate of these three factors was as high as 82.8%, indicating that they were the key factors affecting the distribution and adaptability of P. filicula, P. filicula grows well in damp and cold environments. Due to global warming, the QTP will become warmer and drier; thus, the growing area of P. filicula will move toward higher elevations and areas that are humid and cold. These areas are mainly found near the Three-River Region. Future climate change will aggravate the deterioration of the P. filicula habitat and increase the species’ survival risk. This study describes the distribution of P. filicula and provides a basis for the protection of endangered plants in the QTP.

Determining Effective Environmental Factors in the Distribution of Endangered Endemic Medicinal Plant Species Using the BMLR Model: The Example of Wild Celery (Kelussia odoratissima Mozaff., Apiaceae) in Zagros (Iran)

“…Based on our results, K. odoratissima grows in heights of 2450 to 3000 m within the region of study. Researchers have reported that the optimum altitude for Pomatosace filicula was 4000–4500 m [ 28 ].…”

“…In contrast, in arid and semi-arid ecosystems, studies show that soil properties play an important role in the distribution of plant species [ 37 ]. Previous studies reveal that some plant species can move to higher elevations or latitudes in response to a warming climate [ 28 , 38 , 39 ].…”

Bioclimatic projection of the ecological niche of curly mallow (Malva verticillata) based on the forecast of the dynamics of the geographical range in the context of global climate change

“…The MaxEnt method (Phillips et al, 2004) has proved to be the most effective of the many algorithms for modelling species distribution and for predicting range dynamics under the global climate change (Marcer et al, 2013). The maximum entropy model (MaxEnt) was used in this study (www.cs.princeton.edu/wschapire/MaxEnt), because it has been shown to perform better for modelling the spatial distribution of species in the present and for predicting future changes under the influence of the global climate change (Chen et al, 2022). MaxEnt (Phillips et al, 2004) and uses presence-only data to predict species distributions based on maximum entropy theory.…”

The ecological suitability area of Cirsium lineare (Thunb.) Sch.‐Bip. under future climate change in China based on MaxEnt modeling

“…Importantly, the MaxEnt model is superior to other models when the available sample size is limited (Schmidt et al, 2020;Zeng et al, 2016). For example, Chen et al (2022) used the MaxEnt model to predict the distribution of Pomatosace filicula on the Qinghai-Tibet Plateau under climate change. Their findings showed that future climate change will increase the risk posed to the survival of this species, whose habitat will be reduced further and degraded (Chen et al, 2022).…”

“…For example, Chen et al (2022) used the MaxEnt model to predict the distribution of Pomatosace filicula on the Qinghai-Tibet Plateau under climate change. Their findings showed that future climate change will increase the risk posed to the survival of this species, whose habitat will be reduced further and degraded (Chen et al, 2022). Using the MaxEnt model, Zhang et al (2022) were able to identify and locate suitable habitats of Wolfiporia cocos distributed mainly in China's Yunnan Province.…”