Edouard Janmoulle

(no abstract available)

Climate warming is expected to substantially impact the global landscape of mosquito‐borne disease, but these impacts will vary across disease systems and regions. Understanding which diseases, and where within their distributions, these impacts are most likely to occur is critical for preparing public health interventions. While research has centered on potential warming‐driven expansions in vector transmission, less is known about the potential for vectors to experience warming‐driven stress or even local extirpations. In conservation biology, species risk from climate warming is often quantified through vulnerability indices such as thermal safety margins—the difference between an organism's upper thermal limit and its habitat temperature. Here, we estimated thermal safety margins for 8 mosquito species that are the vectors of malaria, dengue, chikungunya, Zika, West Nile and other major arboviruses, across their known ranges to investigate which mosquitoes and regions are most and least vulnerable to climate warming. We find that several of the most medically important mosquito vector species, including Ae. aegypti and An. gambiae, have positive thermal safety margins across the majority of their ranges when realistic assumptions of mosquito behavioral thermoregulation are incorporated. On average, the lowest climate vulnerability, in terms of both the magnitude and duration of thermal safety, was just south of the equator and at northern temperate range edges, and the highest climate vulnerability was in the subtropics. Mosquitoes living in regions including the Middle East, the western Sahara, and southeastern Australia, which are largely comprised of desert and xeric shrubland biomes, have the highest climate vulnerability across vector species.

The global threat of invasive alien species (IAS) being introduced into new habitats is concerning, particularly in agricultural crops as invasive insect species are continuing to expand their distribution through anthropogenic activities and climate changes. Pea aphids (Acyrthosiphon pisum Harris) are an economic threat to numerous legume crops as they can reproduce parthenogenetically, damage crops directly, and vector over 30 plant viruses as the insect's distribution continues to spread. There are no existing pea aphid-specific risk maps that identify the habitat suitability of pea aphids at either a regional or global scale. Here, we used Species Distribution Models (SDMs) to evaluate which climatic variables influence pea aphid distribution, identify regions of potential distribution, and analyze the global distribution of pea aphids under current and future climate change scenarios (SSP 126, 245, and 370) by utilizing presence-only SDMs based on Maximum Entropy (MaxEnt). The modeling results indicate suitable conditions are relevant for pea aphid establishment in six out of seven continents, with significant range expansion in western Canada, the United States of America, and across Europe. We identified human influence to be the most prominent predictor in determining the distribution of pea aphids, supporting the fact that invasive species distributions are heavily impacted by human activities.

Background Arthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim We aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output. Method s: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes. Results As of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet’s impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Climate change will cause drastic fluctuations in agricultural ecosystems, which in turn may affect global food security. We used ecological niche modeling to predict the potential distribution for four cereal aphids (i.e., Sitobion avenae, Rhopalosiphum padi, Schizaphis graminum, and Diurphis noxia…

The aim of this study was to evaluate the impact of global warming on suitable niches of montane orchid, Traunsteinera globosa, using ecological niche modelling approach. Additionally, the effect of various climate change scenarios on future changes in the distribution and overlap of the orchid magn…

Protected areas are the cornerstone of biodiversity conservation. However, alien species invasion is an increasing threat to biodiversity, and the extent to which protected areas worldwide are resistant to incursions of alien species remains poorly understood. Here, we investigate establishment by 8…

Aim: The aim of this study was to test the hypothesis that the global latitudinal diversity gradient pattern in spiders is pear‐shaped, with maximum species diversity shifted south of the Equator, rather than egg‐shaped, centred on the equator, this study infers the gradient using two large datasets…