Understanding how species’ thermal limits have evolved across the tree of life is central to predicting species’ responses to climate change. Here, using experimentally-derived estimates of thermal tolerance limits for over 2000 terrestrial and aquatic species, we show that most of the variation in thermal tolerance can be attributed to a combination of adaptation to current climatic extremes, and the existence of evolutionary ‘attractors’ that reflect either boundaries or optima in thermal tolerance limits. Our results also reveal deep-time climate legacies in ectotherms, whereby orders that originated in cold paleoclimates have presently lower cold tolerance limits than those with warm thermal ancestry. Conversely, heat tolerance appears unrelated to climate ancestry. Cold tolerance has evolved more quickly than heat tolerance in endotherms and ectotherms. If the past tempo of evolution for upper thermal limits continues, adaptive responses in thermal limits will have limited potential to rescue the large majority of species given the unprecedented rate of contemporary climate change.

How climate affects species distributions is a longstanding question receiving renewed interest owing to the need to predict the impacts of global warming on biodiversity. Is climate change forcing species to live near their critical thermal limits? Are these limits likely to change through natural selection? These and other important questions can be addressed with models relating geographical distributions of species with climate data, but inferences made with these models are highly contingent on non-climatic factors such as biotic interactions. Improved understanding of climate change effects on species will require extensive analysis of thermal physiological traits, but such data are both scarce and scattered. To overcome current limitations, we created the GlobTherm database. The database contains experimentally derived species’ thermal tolerance data currently comprising over 2,000 species of terrestrial, freshwater, intertidal and marine multicellular algae, plants, fungi, and animals. The GlobTherm database will be maintained and curated by iDiv with the aim to keep expanding it, and enable further investigations on the effects of climate on the distribution of life on Earth.

Aim: The anthropogenic climate change and land use change are considered two of the main factors that are altering biodiversity at the global scale. An evaluation that combined both factors can be relevant to detect which species could be the most vulnerable and reveal the regions of highest stability or susceptibility to biodiversity. We aimed to: (a) assess the effect of climate change and land use on the distribution of Cerrado plant species for different countries where they occur, (b) evaluate the effectiveness of the current network of protected areas (PAs) to safeguards species under different greenhouse–gas (GHG) emissions and land use scenarios, and (c) estimate the vulnerability of species based on protection effectiveness and habitat loss.Location: Bolivia, Brazil and Paraguay.Methods: We modelled the distribution of 1,553 plant species of Cerrado and evaluated species range loss caused by present and future land use and two GHG for 2050 and 2080. We assessed species vulnerability combining the representativeness of species within conservation units with the loss of species’ ranges outside PAs.Results: We found that climate change and land use will cause great damage to Cerrado flora by 2050 and 2080, even under optimistic conditions. The greatest impacts of land use will occur in the regions where the greatest richness will be harboured. The conservation of the species will be seriously affected since the PA network is not as effective in safeguarding them under current or future conditions.Main conclusions: The low level of protection together with the losses caused by the advance of agricultural lands will lead most species being highly vulnerable. Due to the distinct impacts of climate and land use over the three countries, conservation strategies should be implemented at transboundary and national levels.

Ecological niche modeling (ENM) is a broadly used tool in different fields of plant ecology. Despite the importance of edaphic conditions in determining the niche of terrestrial plant species, edaphic data have rarely been included in ENMs of plant species perhaps because such data are not available for many regions. Recently, edaphic data has been made available at a global scale allowing its potential inclusion and evaluation on ENM performance for plant species. Here, we take advantage of such data and address the following main questions: What is the influence of distinct predictor variables (e.g. climatic vs edaphic) on different ENM algorithms? and what is the relationship between the performance of different predictors and geographic characteristics of species? We used 125 plant species distributed over the Neotropical region to explore the effect on ENMs of using edaphic data available from the SoilGrids database and its combination with climatic data from the CHELSA database. In addition, we related these different predictor variables to geographic characteristics of the target species and different ENM algorithms. The use of different predictors (climatic, edaphic, and both) significantly affected model performance and spatial complexity of the predictions. We showed that the use of global edaphic plus climatic variables generates ENMs with similar or better accuracy compared to those constructed only with climate variables. Moreover, the performance of models considering these different predictors, separately or jointly, was related to geographic properties of species records, such as number and distribution range. The large geographic extent, the variability of environments and the different species’ geographical characteristics considered here allowed us to demonstrate that global edaphic data adds useful information for plant ENMs. This is particularly valuable for studies of species that are distributed in regions where more detailed information on soil properties is poor or does not even exist.