Ecography E4 awardSpecies distribution models (SDMs) have rapidly evolved into one of the most widely used tools to answer a broad range of ecological questions, from the effects of climate change to challenges for species management. Current SDMs and their predictions under anthropogenic climate change are, however, often based on free-air or synoptic temperature conditions with a coarse resolution, and thus fail to capture apparent temperature (cf. microclimate) experienced by living organisms within their habitats. Yet microclimate operates as soon as a habitat can be characterized by a vertical component (e.g. forests, mountains, or cities) or by horizontal variation in surface cover. The mismatch between how we usually express climate (cf. coarse-grained free-air conditions) and the apparent microclimatic conditions that living organisms experience has only recently been acknowledged in SDMs, yet several studies have already made considerable progress in tackling this problem from different angles. In this review, we summarize the currently available methods to obtain meaningful microclimatic data for use in distribution modelling. We discuss the issue of extent and resolution, and propose an integrated framework using a selection of appropriatelyplaced sensors in combination with both the detailed measurements of the habitat 3D structure, for example derived from digital elevation models or airborne laser scanning, and the long-term records of free-air conditions from weather stations. As such, we can obtain microclimatic data with a relevant spatiotemporal resolution and extent to dynamically model current and future species distributions.

Summary• Discrete climate events such as heat waves and droughts can have a disproportionate impact on ecosystems relative to the temporal scale over which they occur. Research oriented towards (extreme) events rather than (gradual) trends is therefore urgently needed.• Here, we imposed heat waves and droughts (50-yr return time) in a full factorial design on experimental plant communities in spring, summer or autumn. Droughts were created by removing the controlled water table (rainout shelters prevented precipitation), while heat waves were imposed with infrared heaters.• Measurements of whole-system CO 2 exchange, growth and biomass production revealed multiple interactions between treatments and the season in which they occurred. Heat waves had only small and transient effects, with infrared imaging showing little heat stress because of transpirational cooling. If heat waves were combined with drought, negative effects observed in single factor drought treatments were exacerbated through intensified soil drying, and heat stress in summer. Plant recovery from stress differed, affecting the biomass yield.• In conclusion, the timing of extreme events is critical regarding their impact, and synergisms between heat waves and drought aggravate the negative effects of these extremes on plant growth and functioning.

Seedling establishment is expected to improve in a future warmer subarctic climate, mainly by considerably earlier germination. The magnitudes of the responses are species-specific, which should be taken into account when modelling population growth and migration of subarctic species.

Extreme events such as heat waves are emerging as a key facet of climate change, but to date, experiments on the impacts on plants are scarce. Experimental simulation of heat waves requires knowledge of regional heat wave characteristics, as plant responses depend heavily on meteorological conditions. We analysed nine Western European meteorological datasets, and found that heat waves occurring during the growing season in this region encompass more sunshine ( 1 69%), lower precipitation (À78%) and a larger vapour pressure deficit (VPD) ( 1 111%) compared with normal conditions. Possible consequences for plant responses are discussed, with emphasis on the likely seasonal variation of heat wave impacts. We explain why infrared heating (which typically increases VPD) is an appropriate technique for heat wave simulation. Finally, we advocate experiments to take into account the smaller nighttime compared with daytime temperature increases observed during heat waves, and the precipitation deficits before and during heat waves.

Global warming has created a need for studies along climatic gradients to assess the effects of temperature on ecological processes. Altitudinal and latitudinal gradients are often used as such, usually in combination with air temperature data from the closest weather station recorded at 1.52 m above the ground. However, many ecological processes occur in, at, or right above the soil surface. To evaluate how representative the commonly used weather station data are for the microclimate relevant for soil surface biota, we compared weather station temperatures for an altitudinal (500900 m a.s.l.) and a latitudinal gradient (4968 degrees N) with data obtained by temperature sensors placed right below the soil surface at five sites along these gradients. The mean annual temperatures obtained from weather stations and adjusted using a lapse rate of -5.5 degrees C km-1 were between 3.8 degrees C lower and 1.6 degrees C higher than those recorded by the temperature sensors at the soil surface, depending on the position along the gradients. The monthly mean temperatures were up to 10 degrees C warmer or 5 degrees C colder at the soil surface. The within-site variation in accumulated temperature was as high as would be expected from a 300 m change in altitude or from a 4 degrees change in latitude or a climate change scenario corresponding to warming of 1.63.8 degrees C. Thus, these differences introduced by the decoupling are significant from a climate change perspective, and the results demonstrate the need for incorporating microclimatic variation when conducting studies along altitudinal or latitudinal gradients. We emphasize the need for using relevant temperature data in climate impact studies and further call for more studies describing the soil surface microclimate, which is crucial for much of the biota

Climate changes increasingly threaten plant growth and productivity. Such changes are complex and involve multiple environmental factors, including rising CO2 levels and climate extreme events. As the molecular and physiological mechanisms underlying plant responses to realistic future climate extreme conditions are still poorly understood, a multiple organizational level analysis (i.e. eco-physiological, biochemical, and transcriptional) was performed, using Arabidopsis exposed to incremental heat wave and water deficit under ambient and elevated CO2 . The climate extreme resulted in biomass reduction, photosynthesis inhibition, and considerable increases in stress parameters. Photosynthesis was a major target as demonstrated at the physiological and transcriptional levels. In contrast, the climate extreme treatment induced a protective effect on oxidative membrane damage, most likely as a result of strongly increased lipophilic antioxidants and membrane-protecting enzymes. Elevated CO2 significantly mitigated the negative impact of a combined heat and drought, as apparent in biomass reduction, photosynthesis inhibition, chlorophyll fluorescence decline, H2 O2 production, and protein oxidation. Analysis of enzymatic and molecular antioxidants revealed that the stress-mitigating CO2 effect operates through up-regulation of antioxidant defense metabolism, as well as by reduced photorespiration resulting in lowered oxidative pressure. Therefore, exposure to future climate extreme episodes will negatively impact plant growth and production, but elevated CO2 is likely to mitigate this effect.

Until now, nonnative plant species were rarely found at high elevations and latitudes. However, partly because of climate warming, biological invasions are now on the rise in these extremely cold environments. These plant invasions make it timely to undertake a thorough experimental assessment of what has previously been holding them back. This knowledge is key to developing efficient management of the increasing risks of cold-climate invasions. Here, we integrate human interventions (i.e., disturbance, nutrient addition, and propagule input) and climatic factors (i.e., temperature) into one seed-addition experiment across two continents: the subantarctic Andes and subarctic Scandinavian mountains (Scandes), to disentangle their roles in limiting or favoring plant invasions. Disturbance was found as the main determinant of plant invader success (i.e., establishment, growth, and flowering) along the entire cold-climate gradient, explaining 40-60% of the total variance in our models, with no indication of any facilitative effect from the native vegetation. Higher nutrient levels additionally stimulated biomass production and flowering. Establishment and flowering displayed a hump-shaped response with increasing elevation, suggesting that competition is the main limit on invader success at low elevations, as opposed to low-growing-season temperatures at high elevations. Our experiment showed, however, that nonnative plants can establish, grow, and flower well above their current elevational limits in high-latitude mountains. We thus argue that cold-climate ecosystems are likely to see rapid increases in plant invasions in the near future as a result of a synergistic interaction between increasing human-mediated disturbances and climate warming.

Aim Although species distribution models (SDMs) traditionally link species occurrences to free‐air temperature data at coarse spatio‐temporal resolution, the distribution of organisms might instead be driven by temperatures more proximal to their habitats. Several solutions are currently available, such as downscaled or interpolated coarse‐grained free‐air temperatures, satellite‐measured land surface temperatures (LST) or in‐situ‐measured soil temperatures. A comprehensive comparison of temperature data sources and their performance in SDMs is, however, currently lacking. Location Northern Scandinavia. Time period 1970–2017. Major taxa studied Higher plants. Methods We evaluated different sources of temperature data (WorldClim, CHELSA, MODIS, E‐OBS, topoclimate and soil temperature from miniature data loggers), differing in spatial resolution (from 1″ to 0.1°), measurement focus (free‐air, ground‐surface or soil temperature) and temporal extent (year‐long versus long‐term averages), and used them to fit SDMs for 50 plant species with different growth forms in a high‐latitudinal mountain region. Results Differences between these temperature data sources originating from measurement focus and temporal extent overshadow the effects of temporal climatic differences and spatio‐temporal resolution, with elevational lapse rates ranging from −0.6°C per 100 m for long‐term free‐air temperature data to −0.2°C per 100 m for in‐situ soil temperatures. Most importantly, we found that the performance of the temperature data in SDMs depended on the growth forms of species. The use of in‐situ soil temperatures improved the explanatory power of our SDMs (R2 on average +16%), especially for forbs and graminoids (R2 +24 and +21% on average, respectively) compared with the other data sources. Main conclusions We suggest that future studies using SDMs should use the temperature dataset that best reflects the ecology of the species, rather than automatically using coarse‐grained data from WorldClim or CHELSA.