Locustamigratoria (L.) (Orthoptera) in a warming world: unravelling the ecological consequences of climate change using GIS.

The migratory locust, Locustamigratoria (L.), a significant grasshopper species known for its ability to form large swarms and cause extensive damage to crops and vegetation, is subject to the influence of climate change. This research paper employs geographic information system (GIS) and MaxEnt ecological modelling techniques to assess the impact of climate change on the distribution patterns of L.migratoria. Occurrence data and environmental variables are collected and analysed to create predictive models for the current and future distribution of the species. The study highlights the crucial role of climate factors, particularly temperature and precipitation, in determining the locust's distribution. The MaxEnt models exhibit high-performance indicators, accurately predicting the potential habitat suitability of L.migratoria. Additionally, specific bioclimatic variables, such as mean temperature and annual precipitation, are identified as significant factors influencing the species' presence. The generated future maps indicate how this species will invade new regions especially in Europe. Such results predict the risk of this destructive species for many agriculture communities as a direct result of a warming world. The research provides valuable insights into the complex relationship between locust distribution and environmental factors, enabling the development of effective strategies for locust management and early warning systems to mitigate the impact on agriculture and ecosystems.

Modeling the potential global distribution of the Egyptian cotton leafworm, Spodoptera littoralis under climate change.

The Egyptian cotton leafworm, Spodoptera littoralis is a highly invasive insect pest that causes extensive damage to many of the primary food crops. Considering the recent challenges facing global food production including climate change, knowledge about the invasive potential of this pest is essential. In this study, the maximum entropy model (MaxEnt) was used to predict the current global spatial distribution of the pest and the future distribution using two representative concentration pathways (RCPs) 2.6 and 8.5 in 2050 and 2070. High AUC and TSS values indicated model accuracy and high performance. Response curves showed that the optimal temperature for the S. littoralis is between 10 and 28 °C. The pest is currently found in Africa and is widely distributed across the Middle East and throughout Southern Europe. MaxEnt results revealed that the insect will shift towards Northern Europe and the Americas. Further, China was seen to have a suitable climate. We also extrapolated the impact of these results on major producing countries and how this affects trade flow, which help decision makers to take the invasiveness of such destructive pest into their account.