Study on the Potential Distribution of Leptinotarsa decemlineata and Its Natural Enemy Picromerus bidens Under Climate Change

The Colorado potato beetle (CPB), scientifically known as Leptinotarsa decemlineata, is a destructive quarantine pest that has invaded more than 40 countries and regions worldwide. It causes a 20–100% reduction in plant production, leading to severe economic losses. Picromerus bidens L. is a predatory insect that preys on CPB. This study used the MaxEnt model to predict the current and future potential distribution areas of CPB and P. bidens under different climatic scenarios to determine the possibility of using P. bidens as a natural enemy to control CPB. The possible introduction routes of CPB and P. bidens were subsequently predicted by combining their potential distribution with the current distribution of airports and ports. Notably, the potential distribution area of P. bidens was similar to that of CPB, suggesting that P. bidens could be used as a natural enemy to control CPB. Future changes in the suitable growth areas of CPB under different climate scenarios increased and decreased but were insignificant, while those of P. bidens decreased. Consequently, a reduction of the suitable habitats of P. bidens may cause a decrease in its population density, leading to a lack of adequate and timely prevention and control of invasive pests. Active measures should thus be enacted to minimize global warming and protect biodiversity. This study provides a theoretical basis and data support for early warning, monitoring, and control of the CPB spread.

Analysis of Potential Distribution of Spodoptera Frugiperda In Northwest

Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), a newly invaded pest that breaks out fast and severely, causes a serious threat to the national security of food production. In this study, the MaxEnt model was used to predict the potentially suitable distribution area of S. frugiperda in Northwest China. The potential distribution of S. frugiperda was predicted using meteorological factors from the correlation analysis. According to the result, a satisfactory AUC value in the MaxEnt model indicates that the prediction model has good accuracy, which is sufficient for predicting the fitness zone of S. frugiperda in Northwest China. The prediction results show that the potential distribution risk of S. frugiperda is high in western Gansu, eastern Qinghai, Shaanxi, most regions of Ningxia, and part regions of Tibetan, and it also exists in Hami, Yili, Bozhou, Urumqi, Hotan, and Aksu in Xinjiang, and more than 60% of Northwest China are suitable distribution areas for S. frugiperda. As China's major wheat and maize production area, Northwest China is a crucial prevention area for S. frugiperda. Clarifying the potential geographical distribution of S. frugiperda in Northwest China is essential for early warning as well as prevention and control.

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

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.

Simulation of air temperature and their influence on the potential distribution of Myracrodruon urundeuva, Copernicia prunifera and Cereus jamacaru in the Caatinga

Areas in the process of aridification in Caatinga phytogeographic domain in northeastern Brazil increase every year due to human intervention and increase in air temperature. The identification of long-term patterns and air temperature trends in the phytogeographic domain can express climate variability as well as a new phase of adaptation to some plant species. The temperature series from 1951 to 2018 obtained from the National Centers for Environmental Prediction data sets in four conservation areas with native vegetation, located in the North (A1), East (A2), South (A3) and West (A4) regions of this phytogeographic domain, show an increase in temperature between 0.5 and 1.4 °C over the 68-year period with the highest warming occurring in the months of March, April and May. The Maxent model is used to identify the influence of this increase on the presence potential of three species in the Caatinga, Myracrodruon urundeuva (aroeira), Copernicia prunifera (palmeira) and Cereus jamacaru DC (cactus) in the future time interval of 2041 to 2060, considering IPCC projected climate changes. The results show that climate change can lead to a reduction as well as redistribution of the potential areas of occurrence of the three species. Notable changes are: in the case of Carnauba, the high potential area reduces from 25.3% in the present state to 19.6% in 2050, and potential area for Aroeira diminishes in central Bahia and increases in Rio Grande do Norte. The projected changes for all three species are discussed.

Climate change impact on the distribution of Tossa jute using maximum entropy and educational global climate modelling

Tossa (Corchorus olitorius L.) is a significant cash crop, cultivated commercially in the lower flood plain of Bangladesh. The climatic regimes in Bangladesh are changing as well as the world does. However, this species is threatened by climate change. Occurrences of data on threatened and endangered species are frequently sparse which makes it difficult to analyse the species suitable habitat distribution using various modelling approaches. The current paper used maximum entropy (Maxent) and educational global climate model (EdGCM) modelling to predict and conserve the suitable habitat distributions for Tossa species in Bangladesh to the year 2100. Nine environmental variables, 239 occurrence data and two Representative Concentration Pathway scenarios (RCP4.5 and RCP8.5) were used for the Maxent modelling to project the impact of climate change on the Tossa distributions. Furthermore, the EdGCM was used to study the climatic space suitability for the Tossa species in the context of Bangladesh. Both of the climatic scenarios were used for the prediction to the year 2100. The Maxent model performed better than random for the Tossa species with a high AUC value of 0.86. Under the RCP scenarios, the Maxent model predicted habitat reduction for RCP4.5 is 2%, RCP8.5 is 9% and EdGCM is 10.2% from the current localities. The predictive modelling approach presented here is promising and can be applied to other important species for conservation planning, monitoring and management, especially those under the threat of extinction due to climate change.

Spatial-temporal habitat suitability for lemuru fish (Sardinella lemuru) using the Second-generation Global Imager (SGLI) and Maximum Entropy model in the Bali Strait, Indonesia

Lemuru fish (Sardinella lemuru), the most dominant fishery resource, has economic values for the fisherman fishing activities in the Bali Strait (between Jawa and Bali islands), Indonesia. Spatial and temporal prediction for the fishing location is essential information for effective fisheries management. The high spatial resolution of sea surface temperature (SST) and Chlorophyll-a (Chl-a) by the second-generation global imager (SGLI) on the global change observation mission (GCOM-C) satellite was employed for the input of the Maximum Entropy Model (MaxEnt) to predict the potential fishing area of lemuru fish in 2020. This study analyzed SST and Chl-a using the SGLI data and shows the variability of SST and Chl-a for lemuru fish-catching data. The MaxEnt model performance to predict the habitat suitability for lemuru fish in the Bali Strait has been shown in this study. As a result, the maximum average Chl-a estimated in August 2020 was around 1.62 mg m−3 and maximum SST in March 2020 around 28.12°C. The correlation between SST and Chl-a with total lemuru fish-catching were -0.209 and 0.375 for SST and Chl-a, respectively. The prediction of lemuru fishing areas using the MaxEnt model showed excellent model evaluations with a correlation value higher than 0.80.