Predicting the Impact of Climate Change on the Distribution of a Neglected Arboviruses Vector (Armigeres subalbatus) in China

Abstract

The geographic boundaries of arboviruses continue to expand, posing a major health threat to millions of people around the world. This expansion is related to the availability of effective vectors and suitable habitats. Armigeres subalbatus (Coquillett, 1898), a common and neglected species, is of increasing interest given its potential vector capacity for Zika virus. However, potential distribution patterns and the underlying driving factors of Ar. subalbatus remain unknown. In the current study, detailed maps of their potential distributions were developed under both the current as well as future climate change scenarios (SSP126 and SSP585) based on CMIP6 data, employing the MaxEnt model. The results showed that the distribution of the Ar. subalbatus was mainly affected by temperature. Mean diurnal range was the strongest predictor in shaping the distribution of Ar. subalbatus, with an 85.2% contribution rate. By the 2050s and 2070s, Ar. subalbatus will have a broader potential distribution across China. There are two suitable expansion types under climate change in the 2050s and 2070s. The first type is continuous distribution expansion, and the second type is sporadic distribution expansion. Our comprehensive analysis of Ar. subalbatus’s suitable distribution areas shifts under climate change and provides useful and insightful information for developing management strategies for future arboviruses.

The Ginkgo biloba L. in China: Current Distribution and Possible Future Habitat

“…Moreover, the land use change and human disturbance factors are not taken into account in the modeling process, and these limitations can cause bias in the simulation results. Despite the many assumptions and uncertainties in species distribution simulations, the MaxEnt model is still an important data source tool for species distribution simulation predictions of future suitable areas, which is useful for proposing and developing scientific adaptation strategies based on predicted species distributions to cope with future climate change impacts on species, as well as ecosystem-level biota [67,68].…”

“…According to the output results of MaxEnt (Figure 4), using the presence probability of 0.23 as the critical condition for the Ginkgo biloba suitable area, the threshold values of the dominant environmental variables are: Bio6, −12.86-6.60 °C; Bio13, 120. 68…”

Multi-Model Analysis to Predict the Potential Suitable Habitat for Quercus oblongata D. Don (Fagaceae) in the Western Himalayan Region

“…The variables used for niche modeling were at a spatial resolution of 0.5 arcminutes (~1 km 2 ). Multi-collinearity among the bioclimatic variables may affect the prediction analysis, as they are mainly derived from temperature and precipitation (Wang et al 2022). Therefore, to avoid multi-collinearity among the variables, a Pearson correlation test was performed using ENMTools v1.4.4 (Warren et al 2010).…”

Potential Global Distribution of the Invasive Mosquito Aedes koreicus under a Changing Climate

“…The maximum entropy model (MaxEnt) is based on the maximum entropy theory, which treats species and their growing environment as a system, determines the stable relationship between species and the environment by calculating the state parameters when the system has maximum entropy, and estimates the distribution of species [27]. Several scholars [28][29][30] have demonstrated that the MaxEnt model is a successful tool for analyzing the potential distribution areas of species, and some have also used species distribution models to predict the potential distribution areas of mosquitoes.…”