Darren Ward

The Argentine ant is one among the 100 worst invasive animal species of the world. It has invaded six continents, and poses significant threats to the native invertebrate fauna. Prior knowledge on the suitable ecological niches of Argentine ants may help to devise better management plans. This study delineates the niches of Argentine ants using the ecological niche modeling approach by maintaining the temporal match between the distributional information and environmental data. We used an exhaustive methodological framework to understand the niche characteristics of Argentine ants in their native and invaded ranges. The model developed using combined native and invaded range distributional information provided better habitat suitability predictions in the invaded ranges. Efforts were also made to identify the suitable niches of this invasive species globally. The current global model was projected onto two future periods (2041–2070 and 2071–2100) under two different emission scenarios (SSP126 and SSP585). Our study highlights four important features related to the ecological niches of Argentine ants: (1) large habitat preference towards permanent streams in the native ranges, (2) native ecological niche is only partly conserved across invaded ranges, (3) invaded range niches are largely differentiated, and (4) global warming induces an increase in habitat suitability in the northern hemisphere. The results of this study may provide potential insights for the effective implementation of management strategies.

The big-headed ant, Pheidole megacephala (Fabricius), has a widespread distribution across numerous regions globally. The International Union for Conservation of Nature (IUCN) has identified it as one of the 100 worst invasive alien species worldwide, given the severe ecological and economic harm it causes in invaded areas. In this study, we predicted the present and future global distribution of P. megacephala, taking into account known distribution points and bioclimatic factors. Our results indicated that temperature is the primary factor affecting the distribution of P. megacephala, with potential suitable areas currently found mainly in South America, Southern North America, Western Europe, Coastal areas of the Mediterranean and Red Seas, Southern Africa, Southern Asia, Islands in Southeast Asia, and coastal regions of Australia. The total suitable area spans 3,352.48 × 104 km2. In China, the potential suitable area for P. megacephala is 109.02 × 104 km2, representing 11.36% of China’s land area. In the future, based on different climatic conditions, the suitable area of P. megacephala generally showed a declining trend, but some newly added suitable areas showed that it had a tendency to expand to higher latitudes. Relevant agencies should implement effective measures to control P. megacephala populations to mitigate damage in invaded areas and slow down or prevent the spread of big-headed ants into noninvaded regions.

Abstract Ninetinae are a group of poorly known spiders that do not fit the image of ‘daddy long-legs spiders’ (Pholcidae), the family to which they belong. They are mostly short-legged, tiny and live in arid environments. The previously monotypic Andean genus Nerudia exemplifies our poor knowledge of Ninetinae: only seven adult specimens from two localities in Chile and Argentina have been reported in the literature. We found representatives of Nerudia at 24 of 52 localities visited in 2019, mostly under rocks in arid habitats, up to 4450 m a.s.l., the highest known record for Pholcidae. With now more than 400 adult specimens, we revise the genus, describing ten new species based on morphology (including SEM) and COI barcodes. We present the first karyotype data for Nerudia and for its putative sister-genus Gertschiola. These two southern South American genera share a X1X2X3Y sex chromosome system. We model the distribution of Nerudia, showing that the genus is expected to occur in the Atacama biogeographic province (no record so far) and that its environmental niche is phylogenetically conserved. This is the first comprehensive revision of any Ninetinae genus. It suggests that focused collecting may uncover a considerable diversity of these enigmatic spiders.

Global climate change will likely exacerbate crop losses from insect pests, reducing agricultural production and threatening food security. To predict where crop losses will occur, scientists have mainly used correlative models of species’ distributions, but such models are unreliable when extrapolated to future environments. To minimize extrapolation, we developed mechanistic and hybrid models that explicitly capture range‐limiting processes, and we explored how incorporating mechanisms altered the projected impacts of climate change for an agricultural pest, the South American locust (Schistocerca cancellata). Because locusts are generalist herbivores surrounded by food, their population growth may be limited by thermal effects on digestion more than food availability. To incorporate this mechanism into a distribution model, we measured thermal effects on the consumption and defecation of field‐captured locusts and used these data to model energy gain in current and future climates. We then created hybrid models by using outputs of the mechanistic model as predictor variables in correlative models, estimating the potential distribution of gregarious outbreaking locusts based on multiple predictor sets, modeling algorithms, and climate scenarios. Based on the mechanistic model, locusts can assimilate relatively high amounts of energy throughout temperate and tropical South America; however, correlative and hybrid modeling revealed that most tropical areas are unsuitable for locusts. When estimating current distributions, the top‐ranked model was always the one fit with mechanistic predictors (i.e., the hybrid model). When projected to future climates, top‐ranked hybrid models projected range expansions that were 23‐30 percentage points smaller than those projected by correlative models. Therefore, combining the correlative and mechanistic approaches bracketed the potential outcomes of climate change and enhanced confidence where model projections agreed. Because all models projected a poleward range expansion under climate change, agriculturists should consider enhanced monitoring and management of locusts near the southern margin of the range.

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…

Plant pest invasions cost billions of Euros each year in Europe. Prediction of likely places of pest introduction could greatly help focus efforts on prevention and control and thus reduce societal costs of pest invasions. Here, we test whether generic data-driven risk maps of pest introduction, val…

Mollusca is the largest marine phylum, comprising about 23% of all named marine organisms, Mollusca systematics are still in flux, and an increase in human activities has affected Molluscan reproduction and development, strongly impacting diversity and classification. Therefore, it is necessary to e…

MaxEnt is a machine-learning-based species distribution modeling tool that is widely used to evaluate the occurrence possibility of a species. The characteristics of the algorithm requires that bioclimatic variables are appropriately selected in order for the model to predict species occurrence as p…

Climate change is predicted to increase the risk of biological invasions by increasing the availability of climatically suitable regions for invasive species. Endemic species on oceanic islands are particularly sensitive to the impact of invasive species due to increased competition for shared resou…

An understanding of the origin and formation of biodiversity and distribution patterns can provide a theoretical foundation for biodiversity conservation. In this study, phylogeny and biogeography analyses based on mitochondrial genomes and niche modeling based on occurrence records were performed t…