Winter is a key driver of individual performance, community composition, and ecological interactions in terrestrial habitats. Although climate change research tends to focus on performance in the growing season, climate change is also modifying winter conditions rapidly.Changes to winter temperatures, the variability of winter conditions, and winter snow cover can interact to induce cold injury, alter energy and water balance, advance or retard phenology, and modify community interactions. Species vary in their susceptibility to these winter drivers, hampering efforts to predict biological responses to climate change. Existing frameworks for predicting the impacts of climate change do not incorporate the complexity of organismal responses to winter. Here, we synthesise organismal responses to winter climate change, and use this synthesis to build a framework to predict exposure and sensitivity to negative impacts, and that can be used to estimate the vulnerability of species to winter climate change. We describe the importance of relationships between winter conditions and performance during the growing season in determining fitness, and demonstrate how summer and winter processes are linked.Incorporating winter into current models will require concerted effort from theoreticians and empiricists, and the expansion of current growing season studies to incorporate winter.

One Sentence Summary: Empirical evidence from grasslands around the world demonstrates a humped-back relationship between plant species richness and biomass at the 1 m 2 plot scale.Abstract: One of the central problems of ecology is the prediction of species diversity. The humped-back model (HBM) suggests that plant diversity is highest at intermediate levels of productivity; at low productivity few species can tolerate the environmental stresses and at high productivity a small number of highly competitive species dominate. A recent study claims to have comprehensively refuted the HBM. Here we show, using the largest, most geographically diverse dataset ever compiled and specifically built for testing this model that if the conditions are met, namely a wide range in biomass at the 1 m 2 plot level and the inclusion of plant litter, the relationship between plant biomass and species richness is hump shaped, supporting the HBM. Our findings shed new light on the prediction of plant diversity in grasslands, which is crucial for supporting management practices for effective conservation of biodiversity. 4Main Text: The relationship between plant diversity and productivity is a topic of intense debate (1-6). The HBM states that plant species richness peaks at intermediate productivity, taking above-ground biomass as a proxy for annual net primary productivity (ANPP) (7-9). This diversity peak is driven by two opposing processes; in unproductive and disturbed ecosystems where there is low plant biomass, species richness is limited by either stress, such as insufficient water and mineral nutrients, or high levels of disturbance-induced removal of biomass, which few species are able to tolerate. In contrast, in the low disturbance and productive conditions that generate high plant biomass it is competitive exclusion by a small number of highly competitive species that is hypothesized to constrain species richness (7-9). Other mechanisms proposed to explain the unimodal relationship between species richness and productivity include disturbance (10), evolutionary history and dispersal limitation (11,12), and density limitation affected by plant size (13).Different case studies have supported or rejected the HBM, and three separate meta-analyses reached different conclusions (14). This inconsistency may indicate a lack of generality of the HBM, or it may reflect a sensitivity to study characteristics including the type(s) of plant communities considered, the taxonomic scope, the length of the gradient sampled, the spatial grain and extent of analyses (14,15), and the particular measure of net primary productivity (16). Although others would argue (6), we maintain that the question remains whether the HBM serves as a useful and general model for grassland ecosystem theory and management. 5 We quantified the form and strength of the richness-productivity relationship using novel data from a globally-coordinated (17), distributed, scale-standardized and consistently designed survey, in which plant richness and biomass were m...

Changes to soil freezing dynamics with climate change can modify ecosystem carbon and nutrient losses. Soil freezing is influenced strongly by both air temperature and insulation by the snowpack, and it has been hypothesized that winter climate warming may lead to increased soil freezing as a result of reduced snowpack thickness. I used weather station data to explore the relationships between winter air temperature, precipitation and soil freezing for 31 sites in Canada, ranging from the temperate zone to the high Arctic. Inter-annual climate variation and associated soil temperature variation over the last 40 years were examined and used to interpolate the effects of projected climate change on soil freezing dynamics within sites using linear regression models. Annual soil freezing days declined with increasing mean winter air temperature despite decreases in snow depth and cover, and reduced precipitation only increased annual soil freezing days in the warmest sites. Annual soil freeze-thaw cycles increased in both warm and dry winters, although the effects of precipitation were strongest in sites that experience low mean winter precipitation. Overall, it was projected that by 2050, changes in winter temperature will have a much stronger effect on annual soil freezing days and freeze-thaw cycles than changes in total precipitation, with sites close to but below freezing experiencing the largest changes in soil freezing days. These results reveal that experimental data relevant to the effects of climate changes on soil freezing dynamics and changes in associated soil physical and biological processes are lacking.

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There is a growing realization among scientists and policy makers that an increased understanding of today’s environmental issues requires international collaboration and data synthesis. Meta-analyses have served this role in ecology for over a decade, but the different experimental methodologies researchers use can limit the strength of the meta-analytic approach. Considering the global nature of many environmental issues, a new collaborative approach, which we call coordinated distributed experiments (CDEs), is needed that will control for both spatial and temporal scale, and that encompasses large geographic ranges. Ecological CDEs, involving standardized, controlled protocols, have the potential to advance our understanding of general principles in ecology and environmental science.Peer reviewe