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Climate change poses certain threats to the World's forests. That is, tree performance declines if species-specific, climatic thresholds are surpassed. Prominent climatic changes negatively affecting tree performance are mainly associated with so-called hotter droughts. In combination with biotic pathogens, hotter droughts cause a higher tree vulnerability and thus mortality. As a consequence, global forests are expected to undergo vast changes in the course of climate change. Changed climatic conditions may on the one hand locally result in more frequent dieback of a particular tree species but on the other hand allow other-locally yet absent species-to establish themselves, thereby potentially changing local tree-species diversity. Although several studies provide valuable insights into potential risks of prominent European tree species, we yet lack a comprehensive assessment on how and to which extent the composition of European forests may change. To overcome this research gap, we here project future tree-species compositions of European forests. We combine the concept of climate analogs with national forest inventory data to project the tree-species composition for the 26 most important European tree species at any given location in Europe for the period 2061-2090 and the two most relevant CMIP5 scenarios RCP 4.5 and RCP 8.5. Our results indicate significant changes in European forests species compositions. Species richness generally declined in the Mediterranean and Central European lowlands, while Scandinavian and Central European high-elevation forests were projected an increasing diversity. Moreover, 76% (RCP 4.5) and 80% (RCP 8.5) of the investigated locations indicated a decreasing abundance of the locally yet most abundant tree species while 74 and 68% were projected an increasing tree-species diversity. Altogether, our study confirms the expectation of European forests undergoing remarkable changes until the end of the 21st century (i.e., 2061-2090) and provides a scientific basement for climate change adaptation with important implications for forestry and nature conservation.

Inter-annual crop yield variation is driven in large parts by climate variability, wherein the climate components of temperature and precipitation often play the biggest role. Nonlinear effects of temperature on yield as well as interactions among the climate variables have to be considered. Links between climate and crop yield variability have been previously studied, both globally and at regional scales, but typically with additive models with no interactions, or when interactions were included, with implications not fully explained. In this study yearly country level yields of maize, rice, soybeans, and wheat of the top producing countries were combined with growing season temperature and SPEI (standardized precipitation evapotranspiration index) to determine interaction and intensification effects of climate variability on crop yield variability during 1961-2014. For maize, soybeans, and wheat, heat and dryness significantly reduced yields globally, while global effects for rice were not significant. But because of interactions, heat was more damaging in dry than in normal conditions for maize and wheat, and temperature effects were not significant in wet conditions for maize, soybeans, and wheat. Country yield responses to climate variability naturally differed between the top producing countries, but an accurate description of interaction effects at the country scale required sub-national data (shown only for the USA). Climate intensification, that is consecutive dry or warm years, reduced yields additionally in some cases, however, this might be linked to spillover effects of multiple growing seasons. Consequently, the effect of temperature on yields might be underestimated in dry conditions: While there were no significant global effects of temperature for maize and soybeans yields for average SPEI, the combined effects of high temperatures and drought significantly decreased yields of maize, soybeans, and wheat by 11.6, 12.4, and 9.2%, respectively.

Droughts during the growing season are projected to increase in frequency and severity in Central Europe in the future. Thus, area-wide monitoring of agricultural drought in this region is becoming more and more important. In this context, it is essential to know where and when vegetation growth is primarily water-limited and whether remote sensing-based drought indices can detect agricultural drought in these areas. To answer these questions, we conducted a correlation analysis between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) within the growing season from 2001 to 2020 in Bavaria (Germany) and investigated the relationship with land cover and altitude. In the second step, we applied the drought indices Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI) to primarily water-limited areas and evaluated them with soil moisture and agricultural yield anomalies. We found that, especially in the summer months (July and August), on agricultural land and grassland and below 800 m, NDVI and LST are negatively correlated and thus, water is the primary limiting factor for vegetation growth here. Within these areas and periods, the TCI and VHI correlate strongly with soil moisture and agricultural yield anomalies, suggesting that both indices have the potential to detect agricultural drought in Bavaria.

Spring leaf unfolding has been occurring earlier in the year because of rising temperatures; however, long-term evidence in the field from 7 European tree species studied in 1,245 sites shows that this early unfolding effect is being reduced in recent years, possibly because the reducing chilling and/or insolation render trees less responsive to warming. Opposing effects of warming on tree greening Spring leaf unfolding has been occurring earlier in the year because of rising temperatures, but some experimental evidence has suggested that the effect is becoming less marked because trees are not receiving the necessary chilling required to trigger leaf unfolding. Shilong Piao and colleagues present evidence based on long-term field observations of seven European tree species studied in 1,245 locations across Europe confirming that a weakening of temperature sensitivity of leaf unfolding is indeed occurring. The authors provide model-based evidence that the chilling effect is at least partially responsible. Earlier spring leaf unfolding is a frequently observed response of plants to climate warming 1 , 2 , 3 , 4 . Many deciduous tree species require chilling for dormancy release, and warming-related reductions in chilling may counteract the advance of leaf unfolding in response to warming 5 , 6 . Empirical evidence for this, however, is limited to saplings or twigs in climate-controlled chambers 7 , 8 . Using long-term in situ observations of leaf unfolding for seven dominant European tree species at 1,245 sites, here we show that the apparent response of leaf unfolding to climate warming (S T , expressed in days advance of leaf unfolding per °C warming) has significantly decreased from 1980 to 2013 in all monitored tree species. Averaged across all species and sites, S T decreased by 40% from 4.0 ± 1.8 days °C −1 during 1980–1994 to 2.3 ± 1.6 days °C −1 during 1999–2013. The declining S T was also simulated by chilling-based phenology models, albeit with a weaker decline (24–30%) than observed in situ . The reduction in S T is likely to be partly attributable to reduced chilling. Nonetheless, other mechanisms may also have a role, such as ‘photoperiod limitation’ mechanisms that may become ultimately limiting when leaf unfolding dates occur too early in the season. Our results provide empirical evidence for a declining S T , but also suggest that the predicted strong winter warming in the future may further reduce S T and therefore result in a slowdown in the advance of tree spring phenology.

When meteorological conditions deviate from the optimal range for human well-being, the risks of illness, injury, and death increase, and such impacts are feared in particular with more frequent and intense extreme weather conditions resulting from climate change. Thermal indices, such as the universal thermal climate index (UTCI), can better assess human weather-related stresses by integrating multiple weather components. This paper quantifies and compares the seasonal and spatial association of UTCI with mortality, morbidity, and road accidents in the federal state of Bavaria, Germany. Linear regression was applied to seasonally associate daily 56 million hospital admissions and 2.5 million death counts (1995–2015) as well as approximately 930,000 road accidents and 1.7 million people injured (2002–2015) with spatially interpolated same day- and lagged- (up to 14 days) average UTCI values. Additional linear regressions were performed stratifying by age, gender, region, and district. UTCI effects were clear in all three health outcomes studied: Increased UTCI resulted in immediate (1–2 days) rises in morbidity and even more strongly in mortality in summer, and lagged (up to 14 days) decreases in fall, winter, and spring. The strongest UTCI effects were found for road accidents where increasing UTCI led to immediate decreases in daily road accidents in winter but pronounced increases in all other seasons. Differences in UTCI effects were observed e.g. between in warmer north-western regions (Franconia, more districts with heat stress-related mortality, but hospital admissions for lung, heart and external reasons decreasing with summer heat stress), the touristic alpine regions in the south (immediate effect of increasing UTCI on road accidents in summer), and the colder south-eastern regions (increasing hospital admissions for lung, heart and external reasons in winter with UTCI). Districts with high percentages of elderly suffered from higher morbidity and mortality, particularly in winter. The influences of UTCI as well as the spatial and temporal patterns of this influence call for improved infrastructure planning and resource allocation in the health sector.

Climate change is expected to exacerbate the frequency of drought-induced tree mortality world-wide. To better predict the associated change of species composition and forest dynamics on various scales and develop adequate adaptation strategies, more information on the mechanisms driving the often observed patchiness of tree die-back is needed. Although forest-edge effects may play an important role within the given context, only few corresponding studies exist. Here, we investigate the regional die-back of Scots pine in Franconia, Germany, after a hot and dry summer in 2015, thereby emphasizing possible differences in mortality between forest edge and interior. By means of dendroecological investigations and close-range remote sensing, we assess long-term growth performance and current tree vitality along five different forest-edge distance gradients. Our results clearly indicate a differing growth performance between edge and interior trees, associated with a higher vulnerability to drought, increased mortality rates, and lower tree vitality at the forest edge. Prior long-lasting growth decline of dead trees compared to live trees suggests depletion of carbon reserves in course of a long-term drought persisting since the 1990s to be the cause of regional Scots pine die-back. These findings highlight the forest edge as a potential focal point of forest management adaptation strategies in the context of drought-induced mortality.

Tree seedling resistance to and recovery from abiotic stressors such as drought and warming are crucial for forest regeneration and persistence. Selection of more resilient provenances and their use in forest management programs might alleviate pressures of climate change on forest ecosystems. Scots pine forests in particular have suffered frequent drought-induced mortality, suggesting high vulnerability to extreme events. Here, we conducted an experiment using potted Scots pine seedlings from ten provenances of its south-western distribution range to investigate provenance-specific impacts of multiple drought events. Seedlings were grown under ambient and elevated temperatures for 1.5 years and were subjected to consecutive droughts during spring and summer. Growth (height, diameter, and needle) and spring phenology were monitored during the whole study period and complemented by biomass assessments (bud, needle, wood, and needle/wood ratio) as well as measurements of chlorophyll fluorescence and of needle stable carbon isotope ratio. Phenology, growth and biomass parameters as well as carbon isotope ratio and their (direct) responses to reoccurring droughts differed between provenances, indicating genotypic adaptation. Seedling growth was plastic during drought with intra- and inter-annual compensatory growth after drought stress release (carryover effects), however, not fully compensating the initial impact. For (smaller) seedlings from southern/drier origins, sometimes greater drought resistance was observed which diminished under warmer conditions in the greenhouse. Warming increased diameter growth and advanced phenological development, which was (partly) delayed by drought in 2013, but advanced in 2014. Earlier phenology was linked to higher growth in 2013, but interestingly later phenology had positive effects on wood and needle biomass when subjected to drought. Lastly, stable carbon isotope ratios indicated a clear drought response of carbon assimilation. Drought-induced reduction of the photosystem II efficiency was only observed under warmer conditions but showed compensation under ambient temperatures. Besides these direct drought impacts, also interactive effects of previous drought events were shown, either reinforcing or sometimes attenuating the actual impact. Thus, depending on amount and timing of events, Scots pine seedlings, particularly from southern origins, might be well adapted and resilient to drought stress and should be considered when discussing assisted migration under changing climatic conditions.

The phenology of spring leaf unfolding plays a key role in the structure and functioning of ecosystems. The classical concept of heat requirement (growing degree days) for leaf unfolding was developed hundreds of years ago, but this model does not include the recently reported greater importance of daytime than night-time temperature. A manipulative experiment on daytime vs night-time warming with saplings of three species of temperate deciduous trees was conducted and a Bayesian method was applied to explore the different effects of daytime and night-time temperatures on spring phenology. We found that both daytime and night-time warming significantly advanced leaf unfolding, but the sensitivities to increased daytime and night-time temperatures differed significantly. Trees were most sensitive to daytime warming (7.4 ± 0.9, 4.8 ± 0.3 and 4.8 ± 0.2 d advancement per degree Celsius warming (d °C−1) for birch, oak and beech, respectively) and least sensitive to night-time warming (5.5 ± 0.9, 3.3 ± 0.3 and 2.1 ± 0.9 d °C−1). Interestingly, a Bayesian analysis found that the impact of daytime temperature on leaf unfolding was approximately three times higher than that of night-time temperatures. Night-time global temperature is increasing faster than daytime temperature, so model projections of future spring phenology should incorporate the effects of these different temperatures.

Several methods exist for extracting plant phenological information from time series of satellite data. However, there have been only a few successful attempts to temporarily match satellite observations (Land Surface Phenology or LSP) with ground based phenological observations (Ground Phenology or GP). The classical pixel to point matching problem along with the temporal and spatial resolution of remote sensing data are some of the many issues encountered. In this study, MODIS-sensor’s Normalised Differenced Vegetation Index (NDVI) time series data were smoothed using two filtering techniques for comparison. Several start of season (SOS) methods established in the literature, namely thresholds of amplitude, derivatives and delayed moving average, were tested for determination of LSP-SOS for broadleaf forests at a site in southwestern Germany using 2001–2013 time series of NDVI data. The different LSP-SOS estimates when compared with species-rich GP dataset revealed that different LSP-SOS extraction methods agree better with specific phases of GP, and the choice of data processing or smoothing strongly affects the LSP-SOS extracted. LSP methods mirroring late SOS dates, i.e., 75% amplitude and 1st derivative, indicated a better match in means and trends, and high, significant correlations of up to 0.7 with leaf unfolding and greening of late understory and broadleaf tree species. GP-SOS of early understory leaf unfolding partly were significantly correlated with earlier detecting LSP-SOS, i.e., 20% amplitude and 3rd derivative. Early understory SOS were, however, more difficult to detect from NDVI due to the lack of a high resolution land cover information.

Grass pollen allergens are known to be one of the major triggers of hay fever with an increasing number of humans affected by pollen associated health impacts. Climate change characterized by increasing air temperature and more frequent drought periods might affect plant development and pollen characteristics. In this study a one-year (2017) field experiment was conducted in Bavaria, Germany, simulating drought by excluding rain and elevated air temperature by installing a heating system to investigate their effects primarily on the allergenic potential of eight selected cultivars of the two grass species timothy and perennial ryegrass. It could be shown for timothy that especially under drought and heat conditions the allergen content is significantly lower accompanied by a decrease in pollen weight and protein content. In perennial ryegrass the response to drought and heat conditions in terms of allergen content, pollen weight, and protein content was more dependent on the respective cultivar probably due to varying requirements for their growth conditions and tolerance to drought and heat. Results support recommendations which cultivars should be grown preferentially. The optimal choice of grass species and respective cultivars under changing climate conditions should be a major key aspect for the public health sector in the future.