Identifying drivers of non-stationary climate-growth relationships of European beech.

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude. Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

Evaluating tramway infrastructure on biodiversity and ecosystem services.

Tramways in urban areas for mass transit has been suggested to have a lower environmental footprint than roads. However, studies on the impact of tramways and the surrounding infrastructure on biodiversity is extremely rare despite the potential ecological effects associated with this anthropogenic feature. Surprisingly, we found fewer than 10 papers published on tramway-wildlife interactions, which is significantly lower (vs dozens of thousands) than that of other transportation methods. As tramways and stations may be managed sustainably by planting short vegetation on the track and roofs of tramway stations, they may be good examples of land-sharing policies in green urban planning, improving both biodiversity and people's well-being. The potential environmental benefits of green practices for commercially available tramways should be strictly tested and applied, especially in the context of the growing popularity of tramway systems worldwide.

Revealing legacy effects of extreme droughts on tree growth of oaks across the Northern Hemisphere.

Forests are undergoing increasing risks of drought-induced tree mortality. Species replacement patterns following mortality may have a significant impact on the global carbon cycle. Among major hardwoods, deciduous oaks (Quercus spp.) are increasingly reported as replacing dying conifers across the Northern Hemisphere. Yet, our knowledge on the growth responses of these oaks to drought is incomplete, especially regarding post-drought legacy effects. The objectives of this study were to determine the occurrence, duration, and magnitude of legacy effects of extreme droughts and how that vary across species, sites, and drought characteristics. The legacy effects were quantified by the deviation of observed from expected radial growth indices in the period 1940-2016. We used stand-level chronologies from 458 sites and 21 oak species primarily from Europe, north-eastern America, and eastern Asia. We found that legacy effects of droughts could last from 1 to 5 years after the drought and were more prolonged in dry sites. Negative legacy effects (i.e., lower growth than expected) were more prevalent after repetitive droughts in dry sites. The effect of repetitive drought was stronger in Mediterranean oaks especially in Quercus faginea. Species-specific analyses revealed that Q. petraea and Q. macrocarpa from dry sites were more negatively affected by the droughts while growth of several oak species from mesic sites increased during post-drought years. Sites showing positive correlations to winter temperature showed little to no growth depression after drought, whereas sites with a positive correlation to previous summer water balance showed decreased growth. This may indicate that although winter warming favors tree growth during droughts, previous-year summer precipitation may predispose oak trees to current-year extreme droughts. Our results revealed a massive role of repetitive droughts in determining legacy effects and highlighted how growth sensitivity to climate, drought seasonality and species-specific traits drive the legacy effects in deciduous oak species.

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues.

Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000-2020 based on four different derivation methods using a unique long-term data set of in-situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter-annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter-annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre-solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.

Climate change is associated with asynchrony in arrival between two sympatric cuckoos and both host arrival and prey emergence.

Matching the timing of spring arrival to the breeding grounds with hosts and prey is crucial for migratory brood parasites such as cuckoos. Previous studies have focused mostly on phenological mismatch between a single cuckoo species and its hosts but information regarding climate-driven mismatch between multiple sympatric cuckoo species and their hosts and invertebrate prey is still lacking. Here, we analysed long-term data (1988-2023) on the first arrival date of two declining migratory cuckoo species and their 14 migratory host species breeding in sympatry and prey emergence date in Tatarstan (southeast Russia). We found that the common cuckoo (Cuculus canorus; wintering in Africa) generally arrived on breeding grounds earlier than the oriental cuckoo (Cuculus optatus; wintering in southeast Asia and Australia). Both cuckoos have advanced their arrival dates over 36 years but less than their hosts, potentially resulting in an increasing arrival mismatch between cuckoos and their hosts. Moreover, cuckoo arrival advanced less than the emergence date of their prey over time. These observations indicate that climate change may disrupt co-fluctuation in the phenology of important life stages between multiple sympatric brood parasites, their hosts and prey with potential cascading consequences for population dynamics of involved species.

Weather explains the decline and rise of insect biomass over 34 years.

Insects have a pivotal role in ecosystem function, thus the decline of more than 75% in insect biomass in protected areas over recent decades in Central Europe1 and elsewhere2,3 has alarmed the public, pushed decision-makers4 and stimulated research on insect population trends. However, the drivers of this decline are still not well understood. Here, we reanalysed 27 years of insect biomass data from Hallmann et al.1, using sample-specific information on weather conditions during sampling and weather anomalies during the insect life cycle. This model explained variation in temporal decline in insect biomass, including an observed increase in biomass in recent years, solely on the basis of these weather variables. Our finding that terrestrial insect biomass is largely driven by complex weather conditions challenges previous assumptions that climate change is more critical in the tropics5,6 or that negative consequences in the temperate zone might only occur in the future7. Despite the recent observed increase in biomass, new combinations of unfavourable multi-annual weather conditions might be expected to further threaten insect populations under continuing climate change. Our findings also highlight the need for more climate change research on physiological mechanisms affected by annual weather conditions and anomalies.

Weather, weekday, and vacation effects on webcam recorded daily visitor numbers in the alpine winter season.

Winter tourism is an important economic factor in the European Alps, which could be exposed to severely changing meteorological conditions due to climate change in the future. The extent to which meteorology influences winter tourism figures has so far been analyzed mainly based on monthly or seasonal data and in relation to skier numbers. Therefore, we record for the first time daily visitor numbers at five Bavarian winter tourism destinations based on 1518 webcam images using object detection and link them to meteorological and time-related variables. Our results show that parameters such as temperature, cloud cover or sunshine duration, precipitation, snow depth, wind speed, and relative humidity play a role especially at locations that include other forms of winter tourism in addition to skiing. In the ski resorts studied, on the other hand, skiing is mostly independent of current weather conditions, which can be attributed mainly to artificial snowmaking. Moreover, at the webcam sites studied, weekends and vacation periods had an equal or even stronger influence on daily visitor numbers than the current weather conditions. The extent to which weather impacts the (future) visitor numbers of a winter tourism destination must therefore be investigated individually and with the inclusion of non-meteorological variables influencing human behavior.

Earlier and more uniform spring green-up linked to lower insect richness and biomass in temperate forests.

Urbanization and agricultural intensification are considered the main causes of recent insect decline in temperate Europe, while direct climate warming effects are still ambiguous. Nonetheless, higher temperatures advance spring leaf emergence, which in turn may directly or indirectly affect insects. We therefore investigated how Sentinel-2-derived start of season (SOS) and its spatial variability (SV-SOS) are affected by spring temperature and whether these green-up variables can explain insect biomass and richness across a climate and land-use gradient in southern Germany. We found that the effects of both spring green-up variables on insect biomass and richness differed between land-use types, but were strongest in forests. Here, insect richness and biomass were higher with later green-up (SOS) and higher SV-SOS. In turn, higher spring temperatures advanced SOS, while SV-SOS was lower at warmer sites. We conclude that with a warming climate, insect biomass and richness in forests may be affected negatively due to earlier and more uniform green-up. Promising adaptation strategies should therefore focus on spatial variability in green-up in forests, thus plant species and structural diversity.

Spatial scaling in bed-site selection by roe deer fawns: Implications for mitigating neonatal mortality during mowing.

When habitat use by field-dwelling animals coincides in space and time with agricultural practices such as spring mowing of meadows, human-wildlife conflicts can have deadly consequences for wildlife. Roe deer (Capreolus capreolus L.) fawns are particularly vulnerable because they hide in meadows during the rearing phase. Thus, a better understanding of the habitat drivers of bed-site selection is critical to mitigating fawn mortality during mowing. Here, we tease apart the among-field (presumably driven by maternal behaviour) and within-field (driven by fawn behaviour) components of bed-site selection of roe deer during the spring mowing season. We collected over 600 fawn bed sites across an environmentally diverse study region. At the among-field scale, we implemented a used versus available design and employed a two-part statistical model (GAMLSS) to identify habitat characteristics that were linked to either fawn presence (vs. absence) or abundance on a given field. At the within-field scale, we compared habitat characteristics at fawn bed-sites with paired random sites using a conditional logistic regression model. At the among-field scale, fawns were more likely to be present, and were more abundant, in fields within more diverse, rural landscapes, with nearby woodland. Surprisingly, fawns were more often present in fields that were near roads and had lower vegetation productivity. At the within-field scale, however, fawns preferred bed-sites which were further from both roads and woodland, but that provided the best visual cover to minimise predation risk. Our findings revealed substantial and novel scale-dependent differences in the drivers of habitat selection of mothers and fawns, which, together, determine the precise locations of bed-sites between and within meadows. These results may aid wildlife managers in identifying areas where there is a high probability of encountering a roe deer fawn so as to initiate targeted searches prior to mowing and, ultimately, mitigate fawn mowing mortality.

Association between short-term exposure to air pollution and COVID-19 mortality in all German districts: the importance of confounders.

Background: The focus of many studies is to estimate the effect of risk factors on outcomes, yet results may be dependent on the choice of other risk factors or potential confounders to include in a statistical model. For complex and unexplored systems, such as the COVID-19 spreading process, where a priori knowledge of potential confounders is lacking, data-driven empirical variable selection methods may be primarily utilized. Published studies often lack a sensitivity analysis as to how results depend on the choice of confounders in the model. This study showed variability in associations of short-term air pollution with COVID-19 mortality in Germany under multiple approaches accounting for confounders in statistical models. Methods: Associations between air pollution variables PM2.5, PM10, CO, NO, NO2, and O3 and cumulative COVID-19 deaths in 400 German districts were assessed via negative binomial models for two time periods, March 2020-February 2021 and March 2021-February 2022. Prevalent methods for adjustment of confounders were identified after a literature search, including change-in-estimate and information criteria approaches. The methods were compared to assess the impact on the association estimates of air pollution and COVID-19 mortality considering 37 potential confounders. Results: Univariate analyses showed significant negative associations with COVID-19 mortality for CO, NO, and NO2, and positive associations, at least for the first time period, for O3 and PM2.5. However, these associations became non-significant when other risk factors were accounted for in the model, in particular after adjustment for mobility, political orientation, and age. Model estimates from most selection methods were similar to models including all risk factors. Conclusion: Results highlight the importance of adequately accounting for high-impact confounders when analyzing associations of air pollution with COVID-19 and show that it can be of help to compare multiple selection approaches. This study showed how model selection processes can be performed using different methods in the context of high-dimensional and correlated covariates, when important confounders are not known a priori. Apparent associations between air pollution and COVID-19 mortality failed to reach significance when leading selection methods were used. Supplementary Information: The online version contains supplementary material available at 10.1186/s12302-022-00657-5.

Jet stream position explains regional anomalies in European beech forest productivity and tree growth.

The mechanistic pathways connecting ocean-atmosphere variability and terrestrial productivity are well-established theoretically, but remain challenging to quantify empirically. Such quantification will greatly improve the assessment and prediction of changes in terrestrial carbon sequestration in response to dynamically induced climatic extremes. The jet stream latitude (JSL) over the North Atlantic-European domain provides a synthetic and robust physical framework that integrates climate variability not accounted for by atmospheric circulation patterns alone. Surface climate impacts of north-south summer JSL displacements are not uniform across Europe, but rather create a northwestern-southeastern dipole in forest productivity and radial-growth anomalies. Summer JSL variability over the eastern North Atlantic-European domain (5-40E) exerts the strongest impact on European beech, inducing anomalies of up to 30% in modelled gross primary productivity and 50% in radial tree growth. The net effects of JSL movements on terrestrial carbon fluxes depend on forest density, carbon stocks, and productivity imbalances across biogeographic regions.

Climate-change-driven growth decline of European beech forests.

The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from -20% to more than -50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

Indoor Pollen Concentrations of Mountain Cedar (Juniperus ashei) during Rainy Episodes in Austin, Texas.

Standard pollen monitoring programs evaluate outdoor pollen concentrations; however, information on indoor pollen is crucial for human wellbeing as people spend most of the day in indoor environments. In this study, we investigated the differences in indoor mountain cedar pollen loads between rooms of different uses and with different ventilation at The University of Texas in Austin and focused on the effect of rainy episodes on indoor/outdoor ratios of pollen concentrations. Pollen were sampled outdoors and indoors, specifically in seven rooms and in two thermal labs with controlled ventilation, during the daytime on 6 days in 2015. We calculated daily pollen concentrations, campaign pollen integrals (CPIn, the sum of all daily pollen concentrations) and ratios between indoor and outdoor concentrations (I/O ratio). Pollen concentrations differed substantially based on features related to room use and ventilation: Whereas the highest CPIn was observed in a room characterized by a frequently opened window and door, the smallest CPIn was related to a storeroom without any windows and no forced ventilation. Our results showed that rainy episodes were linked to a higher mean I/O ratio (0.98; non-rainy episodes: 0.05). This suggests that pollen accumulated indoors and reached higher levels than outdoors. Low ratios seem to signal a low level of risk for allergic people when staying inside. However, under very high outdoor pollen concentrations, small ratios can still be associated with high indoor pollen levels. In turn, high I/O ratios are not necessarily related to a (very) high indoor exposure. Therefore, I/O ratios should be considered along with pollen concentration values for a proper risk assessment. Exposure may be higher in indoor environments during prevailing precipitation events and at the end of the pollen season of a specific species. Standardized indoor environments (e.g., thermal labs) should be included in pollen monitoring programs.

Modelling the Relative Abundance of Roe Deer (Capreolus capreolus L.) along a Climate and Land-Use Gradient.

European roe deer (Capreolus capreolus L.) are important given their economic, recreational and ecological value. However, uncontrolled roe deer numbers can result in negative impacts on forest regeneration and agricultural crops, disease transmission and occurrences of deer-vehicle collisions. Information on the abundance and distribution is needed for effective management. We combined distance sampling (DS) of roe deer dung pellet groups with multiple variables to develop a density surface model (DSM) in the federal state of Bavaria in south-eastern Germany. We used the estimates of pellet group density as a proxy for roe deer relative abundance. We extrapolated our best DSM, conducted a quantitative evaluation and contrasted relative abundance along climate and land-use gradients. Relative abundance of roe deer was influenced by a combination of habitat type, climate and wildlife management variables, which differed between seasons and which reflected changes in food and shelter availability. At the landscape scale, the highest abundance was observed in agriculture-dominated areas and the lowest in urban areas. Higher abundance was also observed in areas with intermediate temperatures compared to the warmest areas. Our results provide information on possible future changes in the distribution of relative abundance due to changes in climate and land-use.

Correction: Impact of elevated air temperature and drought on pollen characteristics of major agricultural grass species.

[This corrects the article DOI: 10.1371/journal.pone.0248759.].

Universal thermal climate index associations with mortality, hospital admissions, and road accidents in Bavaria.

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.

Weather conditions during hunting season affect the number of harvested roe deer (Capreolus capreolus).

Due to human-induced climate and landscape changes, distribution and abundance of many ungulate species have increased worldwide. Especially in areas where natural predators are absent, hunting is the essential management tool for regulating ungulate populations. Therefore, understanding the factors associated with harvest rates is the first step toward an adaptive management approach. Weather influences hunter and ungulate behavior and thus presumably harvest, but how and which meteorological parameters are linked to harvest numbers have rarely been evaluated. We used nearly 65,000 "sit and wait" and driven hunt harvests of roe deer (Capreolus capreolus) in Bavaria, Germany, and weather data from 2008 to 2017 to test for factors affecting roe deer harvests (i.e., temperature, rain hours, wind speed, sunshine duration, snow depth, workdays vs. weekends, month) using zero-inflated negative binomial mixed-effect models. Our results reveal that, besides workdays, high temperatures and prolonged rain resulted in fewer harvested animals, whereas sunshine duration in summer and snow height in snow-rich areas partially favored harvests during sitting hunts in summer and winter, respectively. The influence of wind speed varied over the course of the year. In summer and autumn, wind speed commonly had a negative effect, positively affecting harvests in winter in some regions. Daily harvest numbers decreased during the summer and autumn hunting periods (May till mid-October), while they increased during the winter period (mid-October till mid-January). Interestingly, harvest success during driven hunts, which are planned well in advance and therefore take place largely independent of weather conditions, was similarly affected by the weather. This result suggests that the inferred weather influence is not only due to the hunters' decisions but also due to deer behavior. Since many ungulate populations may further benefit from climate change, building an understanding of the relationship between hunting success and weather will aid adaptive ungulate management.

Effects of future climate change on birch abundance and their pollen load.

Climate change impacts on the structure and function of ecosystems will worsen public health issues like allergic diseases. Birch trees (Betula spp.) are important sources of aeroallergens in Central and Northern Europe. Birches are vulnerable to climate change as these trees are sensitive to increased temperatures and summer droughts. This study aims to examine the effect of climate change on airborne birch pollen concentrations in Central Europe using Bavaria in Southern Germany as a case study. Pollen data from 28 monitoring stations in Bavaria were used in this study, with time series of up 30 years long. An integrative approach was used to model airborne birch pollen concentrations taking into account drivers influencing birch tree abundance and birch pollen production and projections made according to different climate change and socioeconomic scenarios. Birch tree abundance is projected to decrease in parts of Bavaria at different rates, depending on the climate scenario, particularly in current centres of the species distribution. Climate change is expected to result in initial increases in pollen load but, due to the reduction in birch trees, the amount of airborne birch pollen will decrease at lower altitudes. Conversely, higher altitude areas will experience expansions in birch tree distribution and subsequent increases in airborne birch pollen in the future. Even considering restrictions for migration rates, increases in pollen load are likely in Southwestern areas, where positive trends have already been detected during the last three decades. Integrating models for the distribution and abundance of pollen sources and the drivers that control birch pollen production allowed us to model airborne birch pollen concentrations in the future. The magnitude of changes depends on location and climate change scenario.

Climate sensitivity and drought seasonality determine post-drought growth recovery of Quercus petraea and Quercus robur in Europe.

Recent studies have identified strong relationships between delayed recovery of tree growth after drought and tree mortality caused by subsequent droughts. These observations raise concerns about forest ecosystem services and post-drought growth recovery given the projected increase in drought frequency and extremes. For quantifying the impact of extreme droughts on tree radial growth, we used a network of tree-ring width data of 1689 trees from 100 sites representing most of the distribution of two drought tolerant, deciduous oak species (Quercus petraea and Quercus robur). We first examined which climatic factors and seasons control growth of the two species and if there is any latitudinal, longitudinal or elevational trend. We then quantified the relative departure from pre-drought growth during droughts, and how fast trees were able to recover the pre-drought growth level. Our results showed that growth was more related to precipitation and climatic water balance (precipitation minus potential evapotranspiration) than to temperature. However, we did not detect any clear latitudinal, longitudinal or elevational trends except a decreasing influence of summer water balance on growth of Q. petraea with latitude. Neither species was able to maintain the pre-drought growth level during droughts. However, both species showed rapid recovery or even growth compensation after summer droughts but displayed slow recovery in response to spring droughts where none of the two species was able to fully recover the pre-drought growth-level over the three post-drought years. Collectively, our results indicate that oaks which are considered resilient to extreme droughts have also shown vulnerability when droughts occurred in spring especially at sites where long-term growth is not significantly correlated with climatic factors. This improved understanding of the role of drought seasonality and climate sensitivity of sites is key to better predict trajectories of post-drought growth recovery in response to the drier climate projected for Europe.

Establishing the twig method for investigations on pollen characteristics of allergenic tree species.

The twig method in climate chambers has been shown to successfully work as a proxy for outdoor manipulations in various experimental setups. This study was conducted to further establish this method for the investigation of allergenic pollen from tree species (hazel, alder, and birch). Direct comparison under outdoor conditions revealed that the cut twigs compared to donor trees were similar in the timing of flowering and the amount of pollen produced. Cut twigs were able to flower in climate chambers and produced a sufficient amount of pollen for subsequent laboratory analysis. The addition of different plant or tissue fertilizers in the irrigation of the twigs did not have any influence; rather, the regular exchange of water and the usage of fungicide were sufficient for reaching the stage of flowering. In the experimental setup, the twigs were cut in different intervals before the actual flowering and were put under warming conditions in the climate chamber. An impact of warming on the timing of flowering/pollen characteristics could be seen for the investigated species. Therefore, the twig method is well applicable for experimental settings in pollen research simulating, e.g., accelerated warming under climate change.