The impacts of the changing climate on the biological world vary across latitudes, habitats and spatial scales. By contrast, the time of day at which these changes are occurring has received relatively little attention. As biologically significant organismal activities often occur at particular times of day, any asymmetry in the rate of change S U PP O RTI N G I N FO R M ATI O N Additional supporting information may be found online in the Supporting Information section. How to cite this article: Cox DTC, Maclean IMD, Gardner AS, Gaston KJ. Global variation in diurnal asymmetry in temperature, cloud cover, specific humidity and precipitation and its association with leaf area index. Glob Change Biol.

Mammalian life shows huge diversity, but most groups remain nocturnal in their activity pattern. A key unresolved question is whether mammal species that have diversified into different diel niches occupy unique regions of functional trait space. For 5,104 extant mammals we show here that daytime-active species (cathemeral or diurnal) evolved trait combinations along different gradients from those of nocturnal and crepuscular species. Hypervolumes of five major functional traits (body mass, litter size, diet, foraging strata, habitat breadth) reveal that 30% of diurnal trait space is unique, compared to 55% of nocturnal trait space. Almost half of trait space (44%) of species with apparently obligate diel niches is shared with those that can switch, suggesting that more species than currently realised may be somewhat flexible in their activity patterns. Increasingly, conservation measures have focused on protecting functionally unique species; for mammals, protecting functional distinctiveness requires a focus across diel niches.

Aim Species distribution models (SDMs) have played a pivotal role in predicting how species might respond to climate change. To generate reliable and realistic predictions from these models requires the use of climate variables that adequately capture physiological responses of species to climate and therefore provide a proximal link between climate and their distributions. Here, we examine whether the climate variables used in plant SDMs are different from those known to influence directly plant physiology. Location Global. Methods We carry out an extensive, systematic review of the climate variables used to model the distributions of plant species and provide comparison to the climate variables identified as important in the plant physiology literature. We calculate the top 10 SDM and physiology variables at 2.5° spatial resolution for the globe and use principal component analyses and multiple regression to assess similarity between the climatic variation described by both variable sets. Results We find that the most commonly used SDM variables do not reflect the most important physiological variables and differ in two main ways: (a) SDM variables rely on seasonal or annual rainfall as simple proxies of water available to plants and neglect more direct measures such as soil water content; and (b) SDM variables are typically averaged across seasons or years and overlook the importance of climatic events within the critical growth period of plants. We identify notable differences in their spatial gradients globally and show where distal variables may be less reliable proxies for the variables to which species are known to respond. Main conclusions There is a growing need for the development of accessible, fine‐resolution global climate surfaces of physiological variables. This would provide a means to improve the reliability of future range predictions from SDMs and support efforts to conserve biodiversity in a changing climate.

Aim: Climate classification systems (CCSs) can be used to predict how species' distributions might be altered by climate change and to increase the reliability of these estimates is an important goal in biogeographical research. We produce an objective, global climate classification system (CCS) at high temporal resolution based on plant physiology as a robust way to predict how climate change may impact terrestrial biomes. Location: Global Taxon: Plantae Methods: We construct ten climate variables that capture the physiological processes that determine plant distributions and use cluster analysis to present a new global CCS which accounts for variation in these aspects of climate. We use Kappa statistics to compare the distribution of climate zones in a five-and six-cluster CCS constructed using the physiology variables to the popular Köppen-Geiger and Köppen-Trewartha CCSs, respectively, and find good correlation in both cases. Results: Our CCS highlights ten climate zones for plants. We show that clustering of the physiologically relevant variables reproduces known, present-day patterns of vegetation but also indicates important areas where zone assignment in our physiological CCSs is different to that of the Köppen systems. Main conclusions: The existing Köppen CCSs do not entirely reflect the physiological processes that determine plant distributions. Predictions of climate-driven changes in plant distributions may thus be unreliable in areas where zone assignment by clustering of physiologically relevant variables is different to that of the Köppen systems. Both the physiological relevance and temporal resolution of climate variables used to construct CCSs should be considered in order to predict reliably how climate change may alter plant distributions and to support an appropriate global response to conserve plant biodiversity for the future.

The world’s warm deserts are predicted to experience disproportionately large temperature increases due to climate change, yet the impacts on global desert biodiversity remain poorly understood. Because species in warm deserts live close to their physiological limits, additional warming may induce local extinctions. Here, we combine climate change projections with biophysical models and species distributions to predict physiological impacts of climate change on desert birds globally. Our results show heterogeneous impacts between and within warm deserts. Moreover, spatial patterns of physiological impacts do not simply mirror air temperature changes. Climate change refugia, defined as warm desert areas with high avian diversity and low predicted physiological impacts, are predicted to persist in varying extents in different desert realms. Only a small proportion (<20%) of refugia fall within existing protected areas. Our analysis highlights the need to increase protection of refugial areas within the world’s warm deserts to protect species from climate change.