Bernard Kettlewell

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18‐years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast).Butterflies shifted their centroids at a mean rate of 4.87 km year−1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges.Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity.Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges.We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges.This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.

Despite large numbers of reintroduction projects taking place and the high cost involved, there is a generally low success rate. Insects in particular are understudied within reintroduction ecology, with guidelines focusing on more iconic vertebrate taxa. Species distribution models (SDMs) examine the associations between species observations and environmental variables to find the conditions in which populations could survive. This study utilises two frequently used SDM approaches, a regression model (general linear model (GLM)) and a machine learning method (MaxEnt) to model habitat suitability for Chequered Skipper,  Carterocephalus palaemon, butterflies, which are being reintroduced to Northamptonshire following extinction in England. We look at how SDMs using widespread remotely sensed variables could be used to inform the reintroduction process by finding areas of suitable habitat that were previously overlooked. These remotely sensed variables have the potential to inform reintroductions without extensive on the ground research as they cover huge areas and are widely available. We found that both models are successful in discriminating between presences and absences, using only a limited number of explanatory variables. We conclude that these wide-scale SDMs are useful as a first step in the decision-making process in determining appropriate sites for reintroductions, but that they are less accurate when establishing precisely where species should be placed. The rates of failure among species reintroductions are very high despite the large costs involved in these projects. By better utilising SDMs and remote sensing variables that cover huge areas, an increased rate of success and cost efficiency in insect reintroductions could be established.

Climate is a main driver of species distributions, but all species are not equally affected by climate change, and their differential responses to similar climatic constraints might dramatically affect the local species composition. In the context of climate warming, a better knowledge of the ability of dispersal-limited and habitat-specialist species to track climate change at local scale is urgently needed. Comparing the population genetic and demographic impacts of past climate cycles in multiple co-distributed species with similar ecological requirements help predicting the community-scale response to climate warming, but such comparative studies remain rare. Here, we studied the relationship between demographic history and past changes in spatial distribution of three protected peatland butterfly species (Boloria aquilonaris, Coenonympha tullia, Lycaena helle) in the Jura massif (France), using a genomic approach (ddRAD sequencing) and species distribution modeling (SDM). We found a similar and narrow thermal niche among species, and shared demographic histories of post-glacial decline and recent fragmentation of populations. Each species functions as a single metapopulation at the regional scale, with a North-South gradient of decreasing genetic diversity that fits the local dynamics of the ice cover over time. However, we found no correlation between changes in the quantity or the quality of suitable areas and changes in effective population size over time. This suggests that species ranges moved beyond the Jura massif during the less favorable climatic periods, and/or that habitat loss and deterioration are major drivers of the current dramatic decline observed in the three species. Our findings allow better understanding how history events and contemporary dynamics shape local biodiversity, providing valuable knowledge to identify appropriate conservation strategies.

The black vanilla orchid (Nigritella nigra s.l.) is a perennial plant found in the main European mountain ranges. It occurs in large numbers in the Alps, but it has become a rare and endangered species in Scandinavia due to the loss of suitable habitats. Here we present occurrence data on the occurr…

Aim: Biogeographical studies on the entire ranges of widely distributed species can change our perception of species’ range dynamics. We studied the effects of Pleistocene glacial cycles on current butterfly species distributions, aiming to uncover complex biogeographic patterns in the Holarctic, a …