Bioclimatic envelope models of species' responses to climate change are used to predict how species will respond to increasing temperatures. These models are frequently based on the assumption that the northern and southern boundaries of a species' range define its thermal niche. However, this assumption may be violated if populations are adapted to local temperature regimes and have evolved po...

Aim To analyse the effects of nine species trait variables on the accuracy of bioclimatic envelope models built for 98 butterfly species. Location Finland, northern Europe. Methods Data from a national butterfly atlas monitoring scheme (NAFI) collected from 1991–2003 with a resolution of 10 × 10 km were used in the analyses. Generalized additive models (GAMs) were constructed for 98 butterfly s...

Drought will reduce global crop production by >10% in 2050 substantially worsening global malnutrition. Breeding for resistance to drought will require accessing crop genetic diversity found in the wild accessions from the driest high stress ecosystems. Genome-environment associations (GEA) in crop wild relatives reveal natural adaptation, and therefore can be used to identify adaptive variatio...

Environmental change in terms of land use and climatic changes are posing a serious threat to species distributions and extinctions. Thus in order to predict and mitigate against the effects of environmental change both drivers should be accounted for. Two endemic plant species in the Mediterranean island of Cyprus, Crocus cyprius and Ophrys kotschyi, were used as a case study. We have coupled ...

Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation. In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a dataset containing more than 700,000 random observations at the extent of Europe. The dataset includes spatial attributes such as: distance to road...

Species distribution models (SDMs) are an effective way of predicting the potential distribution of species and their response to environmental change. Most SDMs apply presence data to a relatively generic set of predictive variables such as climate. However, this weakens the modelling process by overlooking the responses to more cryptic predictive variables. In this paper we demonstrate a mean...