Biological invasions need to be assessed as spatial processes, incorporating information on introduction sites, environmental suitability, dispersal parameters and negative impacts. The above allows us to develop risk maps, which are an important tool to determine the probability and consequences of an invasion in each area. In this study, we developed species niche-based distribution models for Vespa mandarinia and V. velutina, exotic species recently discovered in North America, being V. velutina a recognized invasive alien species that has caused enormous economic impacts in Europe. Species niche-based distribution models were used as a base map to determine the risk of establishment in conjunction with information related to the introduction, economic and biodiversity risk. The models developed in this study show environmental suitability for the establishment of these species in tropical and subtropical locations of North America. In Mexico, more than 50% of the ports are at high risk especially those located in the Gulf of Mexico. The biodiversity impact risk map for V. mandarinia shows that 57 protected areas are in regions with some risk of invasion and the V. velutina analysis shows 49 protected areas at potential risk. By implementing comprehensive surveillance and monitoring programs, integrating early detection and rapid response strategy and leveraging geographic information systems, Mexico can take proactive measures to mitigate the potential impacts of invasive species. These efforts will be crucial in protecting biodiversity, preserving ecosystems and safeguarding the country’s economy from the negative consequences associated with invasive species.

The elm zigzag sawfly, Aproceros leucopoda (Hymenoptera), native to eastern Asia, is among the most concerning potential pests for elm trees ( Ulmus spp.); elms form an important component in many North Temperate forests. This sawfly species invaded Europe in 2003 and spread rapidly across much of that continent. In 2020, it was recorded in North America, and it has since become established in several parts of the eastern United States and Canada. Sawfly infestations can cause severe elm tree defoliation, branch die-back that weakens tree health, and potentially tree mortality. Sawfly invasions have the potential to further exacerbate elm decline, especially in conjunction with other pressures, including Dutch elm disease ( Ophiostoma ulmi ). We used rigorous approaches from distributional ecology to explore climatic suitability for A. leocopoda across North America, considering various sources of uncertainty in the data. We found that, without control, the elm zigzag sawfly could establish populations across eastern Canada, much of the central-eastern and northeastern United States, as well as in the Pacific Northwest. More southern areas of North America were not climatically suitable for this species. Predicted suitable areas for the sawfly overlap broadly with elm distributions, highlighting the need to control this invasion to mitigate potential economic and environmental impacts.

Several recent papers have explored methodologies for measuring evolution of ecological niches in the context of phylogenetic hypotheses. Here, we argue that flaws in the conceptual framework behind these approaches, ignoring the distinction between fundamental and realized niches of species, lead to mis-estimations of amounts of evolutionary change in environmental tolerances of lineages. After a conceptual review, using a case study drawn from the publication presenting the most recent of these approaches, we show the importance of considering different sources of uncertainty in reconstructing ecological niches, including consideration of historically accessible areas (M) for species and sampling biases in occurrence data, which also impact niche estimations. Any focus on the realized niche, either implicitly or explicitly, rather than observable parts of the fundamental niche, leads to mis-interpretation of non-evolved consequences of the environmental variation manifested across M as niche evolution. Reconstructing any niche other than the fundamental niche results in overestimation of niche evolution.

The queen conch ( Aliger gigas ) is a key native species of the Caribbean Sea and a primary source of income for thousands of fishers. Historically, it has been a highly valuable resource for the fishing sectors of countries such as the Bahamas, Turks and Caicos, Honduras, and Nicaragua. However, due to its high economic value, the species has been extensively overfished across the region. Overfishing, combined with limited larval dispersal, low recruitment, and poor population connectivity, has led to a drastic decline in population numbers of the species, resulting in its current classification as Threatened. Despite this status, likely impacts of climate change on its populations remain poorly understood, posing significant challenges to conservation efforts. To address this gap, we integrated occurrence records, climate data, and satellite-derived marine habitat data to develop ecological niche models estimating the current and future distribution of the queen conch under different climate change scenarios. We found substantial losses of suitable areas for queen conch along the northern Atlantic coast of South America and Central America, part of the Greater Antilles and the Lesser Antilles. The entire Caribbean region is projected to lose suitability entirely within 20-30 years under the moderate and most extreme climate scenarios. Conversely, our models estimate some suitable areas to persist or expand along the southeastern coast of the United States at least until sometime between 2040 and 2060. Overall, our results suggest a northward shift in the range of this species, with the magnitude of this shift closely tied to the severity of climate change impacts. This work aims to build upon and enhance existing knowledge about survival of queen conch populations in the Caribbean over time. Anticipating future habitat availability will be key to protecting this economically and ecologically important species.

The paper titled “Measuring the evolution of n-dimensional environmental niches” recently published by Sharma et al. (2024) presents a methodology that claims to measure evolution of ecological niches. Here, we argue that flaws in the conceptual framework behind this methodology, ignoring the distinction between fundamental and realized niches of species, leads to mis-estimations of amounts of evolutionary change in environmental tolerances of lineages. After a conceptual review, using one of the Sharma et al. study cases, we show the importance of considering different sources of uncertainty in reconstructing ecological niches, including consideration of historically accessible areas (M) for species and sampling biases in occurrence data, which also impact niche estimations. The Sharma et al. focus on the realized niche, rather than observable parts of the fundamental niche, leads to mis-interpretation of non-evolved consequences of the environmental variation manifested across M as niche evolution. Reconstructing any niche other than the fundamental niche results in overestimation of niche evolution.

In this study, we explore a suite of new ecological niche modeling approaches to illuminate the distributional potential and distributional dynamics of questing individuals of four tick species in the central Great Plains region. Specifically, we improve on typical approaches in distributional ecology by (1) assigning time-specific environmental values to sampling events so that repeated sampling at the same points yields additional information, (2) using both positive and negative records of the species as inputs in model development, and (3) constraining model response shapes in models to resemble the shapes of fundamental ecological niches. Model outcomes demonstrate both seasonal dynamics and differences between species in terms of the geographic potential of questing behavior by Great Plains tick species. These improved approaches in distributional ecology have considerable potential to enrich distributional understanding of vector species distributions.