This session is organized by a consortium representing the International Society of Biometeorology (Phenology Commission), the Pan-European Phenology Network - PEP725, the Swiss Academy of Science SCNAT, the TEMPO French Phenology Network and the USA National Phenology Network.
Phenotypic plasticity is defined as the variation of a trait of a given genotype caused by variation in the environmental conditions. Phenotypic plasticity is present both in animals and plants, but it is generally more pronounced in the traits of plants than in those of animals. The size of the organism is probably the best-known example of phenotypic plasticity in plants: under limited availability of growth resources plants remain small, whereas the body size of animals under limited availability of resources is generally less plastic. The timing of phenological events, such as spring leaf-out, is another good example of a plant trait with a high degree of phenotypic plasticity. Rather than taking place on a given constant calendar day every year, as a result of year-to-year variation of environmental factors the timing of leaf-out may vary by one or two months between years. We put forward a hierarchical concept stating that in addition to the phenological timing as such (classical plasticity of phenology), also the environmental responses regulating phenological timing can be plastic (ecophysiological plasticity of phenology). For instance, the depth of dormancy in trees varies according to the environmental factors prevailing during dormancy induction. This indicates that the responses to chilling and forcing temperatures during dormancy are plastic. Similarly, it has been shown with several crop cultivars that rather than being always the same, the optimal model predicting the timing of phenological stages in the development of the cultivar varies among geographical locations. This shows that the modelled phenological responses of the cultivar are plastic. In this paper we review the studies supporting this hierarchical two-level concept of plasticity in plant phenology and discuss its implications to process-based plant phenology modelling.
How to cite: Hänninen, H., Zhang, R., and Wu, J.: Phenotypic plasticity in plant phenology: a hierarchy of two levels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12216, https://doi.org/10.5194/egusphere-egu26-12216, 2026.
Many key phenological stages of temperate fruit trees are strongly controlled by environmental conditions. This includes the timing of dormancy release and flowering which are regulated by exposure to winter chilling and subsequent mild temperatures (forcing), processes that are essential to ensure high fruit yield and quality. Warmer winters due to global warming are associated with advanced flowering phenology and higher risks of frosts in the early spring, as well as delays and reductions in chill accumulation, which in turn can cause poor flowering and fruit set, with dramatic consequences for fruit production. In this context, a major challenge is to understand and predict the impacts of climate change on flowering, and ultimately, to breed fruit trees adapted to future climatic conditions.
In this study, we used flowering observations from a wide range of sweet cherry (Prunus avium L.) cultivars grown at the INRAE experimental station located in southwestern France, spanning the period from 1981 to 2024. Since cultivars were observed over different periods, resulting in a heterogeneous dataset, flowering dates were corrected for year effect using an ANOVA model to perform pairwise comparisons among cultivars and construct similarity clusters based on flowering precocity. We defined six classes from very early to very late flowering. Partial Least Squares Regression analyses were then used to identify the sensitivity periods when flowering dates are mostly regulated by chilling and forcing for the different flowering precocity classes through time (~4 decades). We aimed (i) to evaluate how the periods of sensitivity to forcing and chilling have shifted over the last decades, and (ii) to test whether distinguishable patterns could be observed between flowering precocity classes.
Our results suggest that, during the earliest years of observation (from 1981 to 2000), the periods of sensitivity to chilling and forcing did not overlap. However, over the last two decades, the period of sensitivity to chilling has been delayed, while the sensitivity period to forcing has advanced, resulting in an overlapping and more complex response to low and warm temperatures. This evolution could be attributed to longer periods of chill accumulation due to milder fall and winter temperatures whereas warmer winter and spring temperatures may lead to earlier response to forcing, with a more pronounced shift for early flowering cultivars. These results reveal that phenology models based on strictly sequential chilling and forcing phases may no longer be sufficient to predict flowering of cherry cultivars under warming conditions and models that account for overlapping sensitivity period should be preferred.
How to cite: Wenden, B., Mariadassou, M., and Vitasse, Y.: Increasing overlap of chilling and forcing sensitivity periods in sweet cherry flowering under warming conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12635, https://doi.org/10.5194/egusphere-egu26-12635, 2026.
In extratropical trees plant phenology is fundamentally constrained by the seasonal dormancy cycle. During autumn, buds are progressively induced into deep endodormancy until a peak dormancy depth is reached. While the dormancy phenomena of temperate and boreal tree species have been extensively studied, despite the high biodiversity and large carbon stocks of subtropical forests and their high sensitivity to climate warming, the timing and physiological regulation of dormancy in subtropical trees remain poorly characterized. To compare latitudinal differences in the timing of peak dormancy, we sampled multiple tree species across seven sites spanning the latitudinal gradient from 22° to 45° N in China and quantified dormancy depth by transferring plants collected at successive autumn and winter dates from natural conditions into a 25 °C growth chamber and measuring their time to budburst. We found a strong latitudinal gradient in the timing of peak dormancy, with trees at lower latitudes reaching their maximum dormancy significantly later than those at higher latitudes. Across species and sites, the day of year corresponding to peak dormancy advanced by approximately 2.2 days per degree of latitude, indicating a systematic delay of dormancy induction toward warmer regions. These results demonstrate that the timing of dormancy induction is not fixed across regions but varies systematically with latitude, providing a physiological basis for redefining the time when winter chilling accumulation should begin in different climate zones.
How to cite: Li, Z. and Hänninen, H.: Latitudinal differences in induction of endodormancy in extratropical trees, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8824, https://doi.org/10.5194/egusphere-egu26-8824, 2026.
In temperate and boreal environments, temperatures drop below the threshold for growth. Woody perennial plants then become dormant to ensure survival, while structures develop cold hardiness. Chilling requirements for dormancy must be met, and then cold hardiness must be lost, before growth can resume in spring. Rates of cold hardiness loss (deacclimation rates) have been shown to increase with chilling accumulation. To demonstrate effects of chilling and cold hardiness on plant phenology, here we combine data from three experiments: a natural temperature gradient on a mountain (“Mountain”, Mt. Washington, NH, USA), a natural temperature gradient across the continental USA (“Continental”, many locations between 32.8°N and 47.5°N), and an experimental temperature gradient (the Spruce and Peatland Responses Under Changing Environments, “SPRUCE”, MN, USA). For all three, buds were collected from woody perennial plants from late summer to early spring to measure field cold hardiness. Additionally, cuttings were collected and placed under forcing conditions (22 °C, 16h-day/8h-night) to measure deacclimation rates and time to budbreak. At “mountain”, buds were collected from several altitudes from base (490m) to treeline (1,615). At “SPRUCE”, warming ranges from ambient (+0°C) to constant +9°C above ambient. For “mountain” and “continental”, genotypic effects are expected due to local adaptation.
“Mountain”. Field cold hardiness showed a negative relationship with elevation: higher elevations plants showed had greater cold hardiness than lower elevations. However, the effect of elevation decreased in mid-winter. Until late fall, deacclimation rates were negligible, regardless of altitude, indicating chilling accumulation had not reached a threshold that would allow for growth resumption. In early December, plants from higher altitudes had accumulated enough chilling to start deacclimating at higher rates. From late December to February, all altitudes seemed to have reached a maximized deacclimation rate. Therefore, chilling is not a limiting factor in these environments. Higher elevations showed higher deacclimation rates, demonstrating the adaptive response to the shorter growing season in higher altitudes: once warm temperatures resume, cold hardiness is quickly lost for growth resumption.
“SPRUCE”. Cold hardiness is lesser in warming treatments during fall and spring. In mid-winter, no differences in cold hardiness are observed, regardless of degree of warming. However, the safety margin (distance from air temperature to cold hardiness) is only smaller in warmer treatments during spring, and for some species. At “SPRUCE” dormancy appears to progress faster in warmer treatments based on budbreak, but not based on deacclimation rates.
“Continental”. Colder locations advanced faster through dormancy than warmer locations. Additional artificial chilling was provided to samples from all locations. Additional chilling for warmer locations led to faster budbreak due to increased rates of deacclimation – a dormancy effect. For colder locations, however, additional chilling only resulted in faster budbreak due to cold hardiness loss during artificial chilling, thus not necessarily a dormancy effect.
In all experiments, loss of cold hardiness in field conditions precedes budbreak, and therefore provides progress information towards spring phenological events. The inclusion of cold hardiness dynamics in phenology models can provide better insight into causes of shifts in phenological timing.
How to cite: Kovaleski, A., Campos-Arguedas, F., Kirchhof, E., North, M., and Didevarasl, A.: Cold hardiness dynamics contain adaptive traits that provide phenology information during the dormant season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15822, https://doi.org/10.5194/egusphere-egu26-15822, 2026.
Zhejiang A&F University, State Key Laboratory for Development and Utilization of Forest Food Resources, Hangzhou, China
Cold damage is a significant natural factor affecting plant growth and distribution. It is particularly important at spring budburst stage, when plants undergo marked changes in cold hardiness. Global climate change has led to frequent extreme low-temperature events, exacerbating the risk of cold damage. Earlier research has predominantly focused on single tree species or single phenological stages, lacking systematic comparisons of cold hardiness among tree species across latitudes during key phenological stages. China encompasses tropical, subtropical, warm temperate, mid-temperate, and cold temperate climatic zones. Significant climatic differences exist across this latitudinal range, resulting in varying degrees of cold damage and substantial morphological and physiological variation among plant traits across regions. We analysed systematically differences in cold hardiness across three developmental stages (dormant bud, bud swelling, fully expanded leaves) between 25 typical tree species from five climatic zones, ranging from latitude 43°20' in the north to latitude 23°15' in the south. The cold hardiness (LT50) was determined using the electrolyte leakage method and observations of mortality. The dependence of cold hardiness on latitude and phenological stage was examined by logistic regression. Furthermore, we explored the physiological and ecological mechanisms underlying cold hardiness by examining changes in dormancy depth, concentrations of osmotic substances (soluble sugars, soluble proteins), antioxidant enzyme activities (SOD, POD), concentrations of endogenous hormones (gibberellin, abscisic acid), and morphological structural indicators (leaf thickness, specific leaf area, etc.) The existing results indicate that northern tree species exhibit greater tolerance to cold hardness before and at the stage of bud burst compared to southern species, along with higher soluble sugar and protein contents as well as enhanced antioxidant enzyme activity. The results provide a theoretical basis for forest tree breeding for cold hardiness, cultivation zoning, and cold damage early warning, thus enhancing forest production under changing climatic conditions.
How to cite: Wang, Z. and Huang, Y.: Divergent strategies of northern versus southern tree species in coping with cold stress during dormancy and budburst, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6213, https://doi.org/10.5194/egusphere-egu26-6213, 2026.
Temperature is considered the primary driver of spring leaf phenology in temperate trees, playing a dual role by regulating dormancy release through winter chilling exposure and promoting budburst via the accumulation of forcing temperatures in late winter and spring. Accurately capturing the temperature experienced by buds during dormancy is therefore essential for predicting budburst dates. As air temperatures increase with climate change, spring phenological events are occurring earlier in the Northern Hemisphere, yet this advancement is not well captured by land surface models for reasons that remain poorly understood. One likely source of error is the use of air temperature instead of bud temperature, as bud meristems can differ from ambient air temperatures by several degrees, depending on time of day, climate conditions (e.g. bright sky) and also species-specific bud traits. Sunlight, and especially photoperiod, is often proposed as a secondary driver of spring leaf phenology, but its exact role is still debated. In particular, photoperiod alone cannot account for the energetic effects of solar radiation on bud temperature or for light-dependent biochemical processes in bud tissues. In this study, we tested the hypothesis that bud traits partly explain species-specific differences between bud and air temperature and their responses to sunlight. We further examined whether accounting for bud temperature and traits improves predictions of individual bud temperature sums across bud development stages.
To address this, we designed a common-garden experiment combining direct bud temperature measurements using fine-wire thermocouples inserted inside buds, with measurements of key morphological, radiometric and physiological bud traits across 12 temperate tree species. Using statistical models, we were able to weigh the influence of bud traits on the temperature difference between buds and the surrounding air (∆Tbud-air) and its sensitivity to sunlight. Our study revealed a strong, yet species-specific, relationship between incident shortwave radiation (SWin) and ∆Tbud-air. We then developed a single model showing how interspecific variation in ∆Tbud-air responds to SWin. For instance, during morning hours, 46% of the sensitivity of ∆Tbud-air to SWin was explained by differences in bud diameter, density, the presence of internal bristles, and reflectance in the visible spectrum. During night, variation in the amplitude of ∆Tbud-air was explained for 33% by bud diameter, gravimetric water content and reflectance in the middle infrared.
By linking simple bud trait metrics to bud–air temperature differences, this study provides new insights into the interspecific sensitivity of bud temperature to microclimate, thanks to simple bud traits, and into the combined roles of air temperature and sunlight in regulating spring phenology of temperate trees.
How to cite: de Felix, L., Ogée, J., Caignard, T., Ladet, A., Vitasse, Y., Wenden, B., Bonnet, H., and Peaucelle, M.: Bud traits capture inter-species differences in bud temperature dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12004, https://doi.org/10.5194/egusphere-egu26-12004, 2026.
In the temperate deciduous forests of the northern hemisphere, spring-active wildflowers are vulnerable to climate change based on their strategy for seasonal light acquisition. This diverse group of plants is characterized by their temporal niche, emerging after snowmelt but before canopy leaf-out to assimilate a significant portion of their yearly carbon budget. This shade-avoidance strategy is particularly important for the spring ephemerals, which rely entirely on the spring light window for their yearly growth. As canopy trees leaf out earlier with warmer spring temperatures, is wildflower phenology keeping pace? Recent studies conducted at a broad spatial scale have demonstrated that the answer to this question varies across continents and regions. The purpose of this study is to track spring wildflower phenological sensitivity to climate at a local scale. In the spring of 2025, we established 32 plots across two mountains in northeastern North America, determining plot location by stratifying across gradients of topography and elevation. Specifically, we 1) identified warm and cool aspect slopes, 2) separated each slope into increments spanning 60 m elevation gain, and 3) identified convex and concave landforms within each slope aspect and elevation band combination. We resampled all plots nine times between early spring and fall, following National Phenology Network (NPN) protocols to generate more than 3000 phenological observations of 60 wildflower taxa. For a subset of these species, we measured physiological parameters using a LI-COR LI-600. At each plot, we stationed a TOMST TMS-4 datalogger to generate measurements of air temperature, soil temperature, and soil moisture at sub-daily temporal scales. We used a Bayesian framework to construct generalized additive models of microclimatic variation over time and generalized linear models of the timing of key phenological events. Our results demonstrate the effect of slope aspect, elevation, and landform on microclimatic variation. Air temperature was lower at higher elevations and on the cool aspect slopes, and soil moisture was higher in the concave landforms. Wildflower phenological traits displayed variation along these microclimatic gradients, with the timing of peak vegetative abundance and peak flowering slightly later at higher elevations and on the cool aspect slopes. Proxies for photosynthetic rate were highest for the spring ephemerals, indicating an aggressive growth strategy to compensate for their short growing season. These initial findings encourage further study to assess the potential for localized habitats to function as microrefugia for spring wildflower biodiversity – microclimates where the extremes of macroclimatic warming are buffered, providing vulnerable taxa with more time for adaptation and migration.
How to cite: Southgate, M. and Tourville, J.: Tracking spring wildflower phenological sensitivity to microclimate in North American temperate deciduous forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15582, https://doi.org/10.5194/egusphere-egu26-15582, 2026.
Leaf senescence timing impacts carbon, water and nutrient cycles as well as biotic interactions and microclimatic conditions. Consequently, it is crucial to elucidate drivers and to anticipate future shifts of leaf senescence. One major driver of leaf senescence is widely believed to be temperature. Numerous studies investigated the effect of temperature on leaf senescence, yet most delineate periods of interest based on calendar times (e.g. weeks or months). However, across years or locations the same calendar time does not equal the same point in the seasonal cycle of a plant, i.e. in “phenological time”. Thus, expressing temperature-dependencies in calendar time might mask effects that are more obvious in phenological time.
To elucidate the influence of temperature on leaf senescence synchronized in phenological time we performed three investigations. First, using data on Malus domestica for Germany we examined whether phases of temperature-dependency of leaf senescence manifest, and whether these phases occur consistently across cultivars. Second, we examined whether theses phases occur consistently in Malus domestica over Europe, covering a broad range of climates, altitudes and latitudes. Third, we examined if the same phases occur in another pome fruit (Pyrus communis), stone fruit (Prunus avium) and other deciduous tree species (Fagus sylvatica, Quercus robur) in Europe.
In Malus domestica, we consistently, i.e. independent of cultivar, latitude, climate and for altitudes up to 1,400 m, found a spring phase, occurring around 300 to 100 days before 50 % of leaves fell (DBLF50), and a fall phase, occurring around 80 DBLF50 until the day of 50 % leaf fall (DOLF50). In a multiple linear regression, the mean temperatures of the spring and fall phases combined are a great predictor of DOLF50 in Malus domestica (R² = 0.841 for Germany and 0.718 for Europe). Likewise, these phases were observed in all other species investigated, and the same multiple linear regression performed again well (R² between 0.777 and 0.887). Higher temperatures during the spring or fall phases respectively led to a delay or advancement of DOLF50. This contrasts with the majority of studies which delineated temperature effects on leaf senescence using calendar periods.
Consequently, the novel approach to synchronize observations in phenological time allowed to uncover new insights on the temperature-dependency of leaf senescence timing. Namely, the consistent presence of a spring and a fall phase with inverse temperature effects on leaf senescence, across cultivars, latitudes, altitudes, climates and for a range of species. This finding, crucially, could enable the development of a “unifying” modelling framework for leaf senescence prediction across cultivars and species.
How to cite: Ohnemus, T., Paasch, S., and Mollenhauer, H.: Synchronization in Phenological Time uncovers two-Phase Temperature Control of Leaf Fall Timing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3881, https://doi.org/10.5194/egusphere-egu26-3881, 2026.
Perennial plants reproduce through a high interannual variability in seed production, with irregular years of high reproductive output—a phenomenon known as mast seeding or masting. While mast seeding is linked to fluctuations in weather and resource availability, the molecular mechanisms that trigger or suppress flower production remain poorly understood. Here, we explored molecular basis of tree flowering, and relationships between gene expression and environment. We collected a unique nine-year dataset of seasonal gene expression from leaf samples of Japanese beech (Fagus crenata) at Mt. Naeba in central Japan. From a total of 40,000 genes, we identified 20 genes whose expression levels were associated with heavy flowering, including key floral regulators and additional genes related to sulfur deficiency. Nitrogen has previously been shown to be a key trigger of flowering in F. crenata. We found that increased nitrogen availability elevates sulfur demand, and when sulfur supply fails to keep pace, plants experience sulfur limitation and activate a low-sulfur response that suppresses flowering. These findings provide new insights into how seasonal molecular regulation of tree flowering shapes reproductive phenology and its relationship with resource availability.
How to cite: Journe, V., Ikezaki, Y., Hirakawa, H., Kashima, M., Nagano, A., Torimaru, T., Tomaru, N., Miyazawa, S.-I., Yamaguchi, N., Han, Q., and Satake, A.: Seasonal gene expression revealed new molecular pathways to explain forest tree flowering, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8963, https://doi.org/10.5194/egusphere-egu26-8963, 2026.
Seed production in many forest tree species is characterized by mast seeding, a reproductive strategy involving large interannual fluctuations in seed production that are highly synchronized among individuals. These fluctuations underpin forest regeneration processes and have cascading effects on forest dynamics. Over the past few decades, a decline in the synchronization of seed production has been observed in many masting species across several regions, raising concerns about the future of forest regeneration and ecosystem dynamics.
Pollen limitation plays a central role in masting processes, driving both the magnitude of interannual variation in seed production and the synchronization of fruiting among trees. This limitation is primarily governed by two key processes: floral phenology and interannual resource investment in flowering. In the context of climate change, a central question is whether the observed changes in the synchronization of fruit production result from shifts in resource allocation to flowering between trees or from changes in flowering phenology. This distinction is critical, as each mechanism implies different trajectories for forest ecosystems under ongoing climate change.
Flowering phenology, which is strongly controlled by meteorological conditions, is a key determinant of pollen limitation because it influences the weather conditions experienced during pollen maturation and dispersal. Early flowering is often associated with unfavorable weather conditions, leading to increased flower abortion and reduced pollen dispersal. The degree of synchronization in flowering phenology among individuals is also a critical component of pollen limitation, as strong synchrony enhances pollen exchange and increases fruit production. Resource investment in flowering, by contrast, is largely driven by summer weather conditions, with higher temperatures generally promoting greater allocation to flowering. Climate change induces multiple environmental changes and can notably affect the homogeneity of microlocal conditions experienced by individual trees. For instance, warm spring conditions have been associated with more homogeneous microlocal environments, resulting in increased synchronization of floral phenology among trees. In this context, it is urgent to determine how the influence of microclimatic conditions on tree reproduction and flowering phenology is evolving under climate change.
This work combines more than 30 years of annual monitoring of individual fruit production across over 200 trees spanning the entire distribution range of Q. lobata, together with pollen surveys and tree-level meteorological measurements. It aims to disentangle the respective roles of floral phenology and resource investment in shaping masting dynamics, and to assess how masting in Q. lobata responds to the constraints imposed by climate change across its distribution range.
How to cite: Fleurot, E., Koenig, W., and Pesendorfer, M.: Is flowering phenology driving rapid changes in forest trees reproductive synchrony?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20740, https://doi.org/10.5194/egusphere-egu26-20740, 2026.
Climate change is rapidly altering alpine ecosystems, creating an urgent need for indicators capable of detecting biological responses of animal communities. While impacts of climate change on animal biodiversity are often assessed using few or single-species approaches, responses of entire animal communities remain poorly explored.
Here, we propose and test a new bioacoustic indicator to quantify community-level phenological responses of birds to climatic variability using passive acoustic monitoring. The indicator integrates three complementary components: (i) community composition, (ii) seasonal patterns of occurrence for non-resident species, and (iii) vocal activity phenology, quantified through the timing, duration, and intensity of diel and daily vocal activity. The main aim is to assess if this approach can be used as a tool for long-term monitoring of climate-driven changes in bird communities, including both community composition and phenological responses.
Within the Agile Arvier project (Next Generation EU), passive acoustic monitoring was conducted in the Aosta Valley region (north-western Italian Alps) at three sites between 1800 and 2100 m a.s.l.: an abandoned pasture, a larch and a spruce dominated forests. Three autonomous recorders (Song Meter 4, Wildlife Acoustics), one per site, were deployed to record continuously. To validate the proposed indicator, we used the first year of acoustic data and performed species identification using a deep learning classifier (BirdNET), followed by expert manual validation. Verified detections were used subsequently to quantify the intensity of vocal activity for phenological analyses. Climatic variables (air temperature, solar radiation, wind speed, and precipitation) were included in the analyses. Generalized Additive Models were used to quantify the effects of climatic variables on vocal activity, while Linear Mixed Models were applied to analyse shifts in the daily start and end times of vocalizations at the community level.
Across the three sites, 72 bird species were detected, representing all species expected to occur at the monitored sites. The arrival and departure dates of non-resident species were clearly detected, and vocal activity consistently described the phenology of the analysed periods. Solar radiation and air temperature emerged as the primary drivers of vocal activity, while increased wind speed significantly reduced it. Community-level phenological patterns differed among habitats: birds in the abandoned pasture began vocal activity later and ended earlier than in forested sites, resulting in a narrower daily vocal window. In contrast, larch and spruce forests exhibited highly similar phenological patterns despite differences in elevation, suggesting a potential buffering effect of forest structure.
As vocal activity metrics were tightly linked to environmental variables across fine and multiple temporal scales, the proposed bioacoustic indicator can be considered a robust and scalable approach for monitoring long-term variation in both the composition and phenology of mountain bird communities in response to climate change.
How to cite: Koliopoulos, S., Guarnieri, C., Pogliotti, P., Tibone, C., Crea, D., Tagliaferro, F., Ferraris, D., and Galvagno, M.: Who Is Heard? A New Bioacoustic Indicator to Assess Climate Change Impacts on Alpine Bird Communities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17557, https://doi.org/10.5194/egusphere-egu26-17557, 2026.
Phenological monitoring—tracking the timing of biological events such as leaf emergence and senescence—is essential for understanding how ecosystems respond to environmental change. Over the past two decades, phenocameras (automated digital cameras that capture repeated images of vegetation) have transformed phenology research, providing nearly daily, high-resolution data across various ecosystems. Despite major progress worldwide, there is an imbalance in phenocamera coverage between temperate and tropical ecosystems. This gap limits our understanding of tropical vegetation dynamics and affects the accuracy of global vegetation models that inform climate projections. In this review, we synthesize the global use of phenocameras, highlighting their methodological advances, ecological insights, and key applications. We focus on tropical ecosystems, identifying critical gaps, challenges, and opportunities to expand phenocam networks in these biodiverse regions. We conducted a systematic literature review on Web of Science, analyzing studies that used digital cameras for phenological monitoring in natural vegetation. Metadata from the selected articles was compiled, resulting in a total of 196 papers included in the review. Phenocamera applications primarily tracked phenological patterns and developed new methods. Camera-based time series validated orbital sensors, explored leaf phenological drivers, and related to terrestrial productivity proxies. Long-term studies on interannual phenological variation and climate change impacts were limited in both temperate and tropical regions. The global distribution of sites confirmed a concentration of study locations in the northern hemisphere, with most sites in the USA and Western Europe—mainly within temperate biomes such as Boreal forests, Temperate Seasonal Forests, Temperate Woodlands and Shrublands, and temperate grasslands and deserts. Tropical studies mainly focused on seasonally dry ecosystems like seasonally dry tropical forests, scrublands (Caatinga), and savanna woodlands and grasslands. They also included wet forests like the Amazon Rainforest, Atlantic Forest, and tropical mountain grasslands. By addressing these challenges and biases, our review shows a growing monitoring presence in the tropics, promoting a more equitable distribution of phenological research and improving our understanding of climate change effects on biodiversity and ecosystem dynamics worldwide. The insights from our analytical framework can guide future work, helping to develop inclusive phenological monitoring methods and supporting the increasing emphasis on phenology's role in conservation and climate resilience. Addressing these needs is crucial for establishing a more comprehensive, globally balanced phenological monitoring network, which is vital for better ecosystem models and for guiding conservation and climate policies in tropical regions.
Acknowledgements: FAPESP research grants #2021/10639-5, #2022/07735-5, and FAPESP fellowship grants #2024/09117-2 (BA) and #2024/06113-6 (MMPS). CNPQ (428055/2018-4; 306563/2022-3)
How to cite: Alberton, B., Maniçoba da Rosa Ferraz Jardim, A., Pereira dos Santos, M. M., Carita Vaz, M., Mainardi, A., Fu, Y. H., and Morellato, P.: Two Decades of Phenocam Studies: Progress and Challenges in Tropical Phenology Ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-564, https://doi.org/10.5194/egusphere-egu26-564, 2026.
Plant phenology is among the most sensitive biological indicators of climate change, reflecting how shifts in temperature and precipitation regimes alter the timing of key plant life-cycle events such as leaf emergence and flowering. Because these plant phenology developmental stages are tightly coupled to environmental cues, even subtle climatic changes can produce advances or delays in phenological phases, making them powerful measurable integrators of ecosystem responses to ongoing global warming. To investigate future changes in spring phenology, with particular emphasis on elevation-dependent responses, a climate-driven phenological model based on the Spring Indices methodology was developed. The study included both historical and projected flowering onset shifts for common hazel (Corylus avellana), dandelion (Taraxacum officinale), and common lilac (Syringa vulgaris). Phenological observations from 46 stations of the Slovenian National Phenological were be combined with high-resolution climate data, and future phenological responses were simulated using 21st-century climate projections under two emission scenarios. Specifically, the study examined whether the agreement between model predictions and observed records varied with elevation during the reference period and whether this relationship changes in the future climate. The results indicated a systematic advancement of spring phenophases throughout Slovenia, driven by rising air temperatures. Moreover, the magnitude of this advancement increases with elevation, suggesting an enhanced sensitivity of high-altitude ecosystems to climate warming. These findings highlighted the growing role of topography in shaping future plant phenological patterns and have important implications for ecosystem functioning and climate-impact assessments in mountainous ecosystems.
How to cite: Oblišar, G. and Vilhar, U.: Potential shifts in the phenological development of representative spring plant species in Slovenia until the end of the 21st century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22968, https://doi.org/10.5194/egusphere-egu26-22968, 2026.
In recent decades, increasing attention has been devoted to studying the ecological and social impacts of our changing climate. In this study, we analyze temporal cluster changes in European phenology as captured by the so-called Extended spring indices. These indices consistently translate temperature records into a suite of biologically meaningful climate change indicators. More precisely, we use the European database of high spatial resolution Extended Spring Indices that we published in the 4TU.ResearchData repository (Izquierdo-Verdiguier et al. 2024) to analyze cluster transition. This database has a spatial resolution of 1 km² and covers the period from 1950 to 2020 at an annual temporal frequency. Four phenological indicators, namely the First Bloom, First Leaf, Last Freeze, and Damage Index were used in this study. The First Bloom, First Leaf, and Last Freeze indices are expressed as the day of year (DOY) on which the respective event occurred, while the Damage Index is computed as the difference between the dates of First Leaf and Last Freeze. To investigate long-term changes in these indices, two 30-year median composites (1960–1989 and 1990–2019) were generated, reflecting the commonly applied climatological assumption of climate variability occurring in 30-year cycles. The MiniBatch K-means clustering algorithm was subsequently applied to both composites, as it has proven effective for clustering large-scale datasets. After deriving cluster centroids for each period, the Hungarian algorithm was employed to align clusters between consecutive periods by matching centroids, ensuring consistent cluster labeling across time. Based on the aligned clusters, transition matrices were computed to quantify pixel-level transitions and changes in cluster characteristics (Atif et al. 2022). The resulting transition maps and cluster statistics enable a detailed visualization of spatial shifts between phenological regimes as well as changes in the internal properties of individual clusters. Our results indicate pronounced phenological changes across Europe between the two 30-years periods, most notably characterized by an earlier onset of First Leaf and First Bloom. By quantifying temporal transitions among phenoregions, this study provides a comprehensive and high-resolution baseline for understanding the rapid reorganization currently reshaping European ecosystems.
Izquierdo-Verdiguier, E., & Zurita-Milla, R. (2024). A multi-decadal 1 km gridded database of continental-scale spring onset products. Scientific Data, 11(1), 905.
Atif, M. & Leisch F. (2022). clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets. PLOS one, 12 (17).
How to cite: Scharl, T., Kovarnik, R., Zurita-Milla, R., and Izquierdo-Verdiguier, E.: Spatiotemporal Cluster Transitions in High-Resolution European Phenological Spring Indices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6940, https://doi.org/10.5194/egusphere-egu26-6940, 2026.
Biosphere atmosphere coupling is an uncertain but important process for the terrestrial carbon sink and therefore for climate projections. The coupling depends on the phenological state, in particular for deciduous plants which only lead to a strong coupling during the growing season. However, plant phenology dynamically itself adapts to the changing climate. Therefore understanding how and why phenology shifts is an important task.
The main challenge in modeling phenology is that it mixes vastly different time scales from daily meteorology that determines the timing of phenological events to the century long lifespan of trees that influence phenology through the different behavior of different species. Mechanistic models (e.g. GDD, GSI) cannot capture this and instead only use the recent past to estimate the phenological state. A promising alternative is data driven models but existing models also use either only the recent past (Liu et al., 2024) or only very long time scales (Reimers et al., 2023) and fail to represent the full complexity.
In this work we propose a novel neural network architecture that in two steps calculates, first, the daily phenological potentials for each day and, second, combines these into a phenological time series using transformer models. We train this model on the PhenoCam V2 and Daymet datasets
for seven different plant functional types across North America.
We demonstrate that our model is a plausible mechanistic representation of plant phenology. It has strong prediction performance on a hold out test set, it emits the same latent relationships as the observations and the sensitivities of the model agree with sensitivities reported in the
literature.
We find that under warming the start of the season moves forward (3.27d ◦C−1 for deciduous broadleaf forests (DBF)) and the end of the season moves backward (2.30d ◦C−1 for DBF) but the level of the growing season does not increase. Further we find that current meteorology is less important than long term memory effects through, for example, species. In fact current meteorology is only during the start and end of the season more important than the memory effect.
Additionally we investigate the effect of frost at the beginning of the growing season. We find that such a frost event delays the development of the plant such that it stays delayed until the end of the season. Under warming the vulnerability as well as the timing of the strongest vulnerability changes, but these changes vary between plant functional types. Such data-driven insights in phenological behavior in response to environmental change are key to inform the next generation of Earth system models.
Liu et al., 2024 Liu, Guohua, et al. “DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology.”
GeoscientificModel Development 17.17 (2024): 6683-6701.
Reimers et al., 2024 Reimers, Christian, et al. “Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests.” arXiv preprint arXiv:2401.03960 (2024).
How to cite: Reimers, C., Liu, G., Reichstein, M., and Winkler, A.: A novel data-driven phenology model reveals how and why seasonal timing shifts under climate change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16670, https://doi.org/10.5194/egusphere-egu26-16670, 2026.
Phenology affects tree growth, as well as ecosystem dynamics such as the carbon, water and nutrient cycles. As phenology represents a plastic response of trees to environmental changes, leaf phenology of temperate trees has been intensively investigated in the last three decades in the context of global change. Accordingly, most research has been focused on the relationship between phenology and its environmental and climatic drivers such as air temperate, light, elevated CO2, etc. Little attention has been given to the impact on phenology of non-climatic factors, in particularly the impact of soil nutrient availability. Here, we present a new analysis showing that soil fertility has a small but significant effect in advancing spring phenology of temperate deciduous forest trees. The analysis was based on data from monitoring programs (i.e. ICP forests and RENECOFOR) combining long-term phenological observations to soil physical and chemical properties for 121 European sites. First, we built meteorological models explaining a large portion (80-90%) of the inter-site budburst variability. Second, we related the residuals of the meteorological models to site fertility derived from a validated fertility index based on soil organic carbon, C:N ratio and pH. Third, we studied the effect of site fertility on chilling and forcing. Spring phenology was investigated using budburst date (50% of buds at budburst) but also the ancillary variables of budburst start (5% budburst) and budburst end (95% budburst). We found that more fertile sites showed an advanced spring phenology up to 3-4 days. This was most clear when sites were aggregated but it was also significant at species level (for the model species Fagus sylvatica, Quercus petraea, and Quercus robur) when considering budburst start and budburst end. Furthermore, we observed a significant interaction between fertility and chilling requirements indicating that trees at lower fertility sites show heightened avoidance of a premature budburst and require increased forcing. Our results suggest differences in the adaption of spring phenology to varying nutrient availability. Whilst small, the effect of fertility on budburst can be crucial in determining late frost risk. Furthermore, the effect of soil fertility on the interplay between chilling and forcing temperatures to initiate budburst suggests that its impact on spatial variability might increase under climate change. This warrants implementation in dynamic global vegetation models, and further encourages the community to study the impact of non-climatic drivers of forest phenology.
How to cite: Campioli, M. and Heinecke, T.: Soil fertility advances spring phenology of deciduous trees across temperate European forests , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1696, https://doi.org/10.5194/egusphere-egu26-1696, 2026.
Climate warming alters the start (SOS) and end (EOS) of growing seasons, impacting biotic interactions and biogeochemical cycles. However, the global constraints between these two stages – how SOS influences EOS (SOS-EOS effect) and vice-versa (EOS-SOS effect) – remain poorly understood, hindering future growing-season projections. Using MODIS satellite-derived phenology data for deciduous vegetation and European ground observations for deciduous tree species, we show that earlier SOS typically advances EOS (on average by 0.19 ± 0.001 days per day [MODIS] and 0.12 ± 0.002 days per day [ground]), while EOS exerts a weaker influence on subsequent SOS (-0.05 days per day). The SOS-EOS effect often outweighed abiotic factors, with SOS being the top predictor of EOS in 34% of pixels (β = 0.27), while preseason temperature was the primary predictor of SOS in 58% (β = -0.33). More importantly, we identified a dampening interaction, where an increase in one carry-over effect reduced the other, with distinct and opposing geographic patterns: the SOS-EOS effect was twice as strong as the EOS-SOS effect in temperate deciduous forests, while the EOS-SOS effect was up to three times stronger in boreal taiga and tundra. Mechanistically, these patterns are likely to reflect developmental (cell and tissue growth) and stress-related constraints (SOS-EOS effect) and chilling requirements during dormancy (EOS-SOS effect at high latitudes). These findings highlight how plant-internal physiological feedbacks constrain phenological responses to climate change, emphasizing the need to integrate carry-over effects into future ecosystem models.
How to cite: Wu, Z., Fu, Y., Crowther, T., Renner, S., Vitasse, Y., Mo, L., Zou, Y., Mirzagholi, L., Li, M., Rebindaine, D., Gong, Y., Guo, Z., Wang, N., and Zohner, C.: Global carry-over effects between the timing of spring leaf-out and autumn senescence within and across years, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3769, https://doi.org/10.5194/egusphere-egu26-3769, 2026.
In response to solar forcing, hydrometeorological variability, and ecosystem properties, a global seasonal oscillation of vegetation greenness can be observed from space. This “green wave” plays a central role in regulating carbon uptake, energy exchange, and biosphere–atmosphere interactions. Yet, the dynamics of this large-scale macrophenological signal have so far been described mainly through summary statistics of local or pixel-based indicators. A concise global descriptor of the green wave is still lacking. Here, we introduce a metric that characterizes global vegetation seasonality by computing the spatio-temporal center of mass of terrestrial greenness from satellite observations.
The resulting global three-dimensional trajectory provides an intuitive and integrative representation of seasonal and interannual macrophenological variability. Based on earlier evidence of widespread greening in the northern hemisphere, we expected a strong poleward displacement during boreal summer and a weaker compensating shift during austral summer. Instead, we find a consistent northward displacement during both seasonal phases. Across independent datasets, the austral summer shift exceeds the boreal one. This asymmetry leads to a contraction of the annual latitudinal amplitude of the green wave, a tendency that further strengthens in future projections using CMIP6 models. The proposed trajectory framework offers a new way to quantify and communicate large-scale biosphere change in physically interpretable units, and provides a basis for linking vegetation dynamics to climate forcing and human land use.
How to cite: Mahecha, M., Kraemer, G., Renhardt, M., Montero, D., Gans, F., Bastos, A., Feilhauer, H., Flik, I., Ji, C., Kattenborn, T., Migliavacca, M., Mönks, M., Quaas, J., Sippel, S., Walther, S., Wieneke, S., Wirth, C., and Camps-Valls, G.: Global shifts in Earth’s seasonal green wave, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17483, https://doi.org/10.5194/egusphere-egu26-17483, 2026.
Drought is regarded as one of the most significant consequences of climate change for ecosystem dynamics. In tropical dry ecosystems, where seasonal drought is a key climatic feature, intensified dry conditions can significantly disrupt vegetation responses, particularly leaf phenology, which directly regulates carbon uptake, water exchange, and ecosystem productivity. Despite this, the extent to which climate variability and drought events drive long-term phenological responses remains insufficiently understood, especially in seasonally dry tropical forests (SDTFs). In this study, we investigated how climate variability and drought severity influence leaf phenology in two major SDTFs: the Caatinga and the Cerrado. Drought severity was assessed using the Standardized Precipitation Evapotranspiration Index (SPEI) across three long-term monitoring sites: Caatinga (CAAT) and Cerrado (CORE and PEG). To capture ecosystem-scale phenological dynamics, we analyzed long-term (2000–2023) satellite-derived phenological time series based on the Enhanced Vegetation Index (EVI), and assessed drought impacts through phenocamera observations focused on individual tree crowns at each site. Our results show that all study sites experienced moderate to exceptional droughts during the study period, with prolonged dry conditions frequently coinciding with marked vegetation anomalies detected by EVI, particularly in the Caatinga, reflecting prolonged periods of reduced canopy cover during the dry season. Interannual variability in the start of the growing season (SOS) was influenced by climatic drivers, with rainfall generally promoting earlier leaf flushing in the Caatinga, while drier years were associated with delayed SOS. In the Cerrado, higher temperatures appeared to interact with delayed SOS patterns. These findings highlight contrasting climatic controls on leaf phenology across ecosystems and reinforce the role of climate variability in shaping phenological dynamics in tropical dry biomes under extreme events.
Keywords: Caatinga, extreme events, Leaf phenology, climate variability
Acknowlegments: The authors gratefully acknowledge the financial support from the São Paulo Research Foundation (FAPESP) Grants (#2021/10639-5, #2022/02323-0, #2022/07735-5) and felowships #2024/06113-6, #2023/05323-4 and 2025/19074-1, the Pernambuco State Research Support Foundation (FACEPE) (Grant # BFP-0103-5.01/23), the National Council for Scientific and Technological Development (CNPq) Grants #403692/2024-5 and #306562/2022-3 (Productivity fellowship to PM), the Coordination for the Improvement of Higher Education Personnel-CAPES (Finance code 001), and the Brazilian Agricultural Research Corporation (EMBRAPA) (Grants #10.23.00.111.00.00 and 10.25.00.144.00.00).
How to cite: Morellato, P., Santos, M. M., Jardim, A., Alberton, B., Domingues, T., and Moura, M.: Influence of climate variability on leaf phenology in seasonally dry tropical ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22051, https://doi.org/10.5194/egusphere-egu26-22051, 2026.
Dry tropical ecosystems contribute nearly 40% of the interannual variability in global terrestrial carbon exchange, yet the driver of leaf emergence timing, a key determinant of ecosystem productivity, remains uncertain. Competing hypotheses emphasize rainfall cues or avoidance of herbivory, but their relative roles are unresolved at a pan-tropical scale. Here, using global data on satellite-based phenology, climate, plant traits, and ground-based insect occurrence, we show that leaf emergence across the dry tropics is closely synchronized with insect outbreak timing, contradicting the herbivory-avoidance hypothesis. Instead, in ~90% of the region, leaves emerge before the rainy-season begins: forests lead rainfall by 40.3±24.3 days, compared with shrublands (22.1±21.4 days) and grasslands (20.0±21.3 days). The stronger advances in forests likely reflect integrated trait-mediated adaptations, with deeper rooting, greater stem water reserves, and tighter stomatal regulation enabling them to mobilize pre-season moisture. These traits, together with wetter climate, extend the growing period and reduce phenological sensitivity to decadal rainfall variability by ~50% relative to non-forest systems, conferring greater stability under decadal climate shifts. These findings falsify the herbivory-avoidance hypothesis and identify trait‑climate mediation as key drivers of dry tropical phenology, offering a mechanistic basis to improve carbon-cycle models, assess climate impacts, and inform adaptation strategies.
How to cite: Zeng, X., Wang, J., Hughes, A. C., Zohner, C. M., Wigneron, J.-P., Ciais, P., Detto, M., Song, G., Guo, Z., Feng, Y., Peaucelle, M., Zhao, Y., Huang, H., Lu, X., Saleska, S. R., Wright, S. J., Penuelas, J., Malhi, Y., Liu, L., and Wu, J.: Trait–climate mediation, not herbivory avoidance, shapes leaf emergence strategies in global dry tropics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11811, https://doi.org/10.5194/egusphere-egu26-11811, 2026.
Urbanization-induced warming advanced the timing of spring budburst, impacting on urban ecosystems. However, how urban artificial light affects the spring budburst and its spatial variation within species distribution are less studied, especially lacking experimental evidences. Here, we conducted a climate-controlled experiment using twigs collected from artificial light (AL) and no-artificial light (NoAL) conditions at three latitudinal gradients (Lhigh, Lmiddle and Llow) in China. We found that the temperature responsiveness of spring budburst (Tres, defined as the number of days to budburst after the twigs are placed into the chambers, with a smaller value indicating stronger responsiveness) was significantly stronger for NoAL individuals (54.3 days) than AL individuals (60.7 days). Additionally, AL twigs exhibited a greater photoperiod limitation (12.7 days vs. 7.6 days) and a higher heat requirement (732.15 K vs. 679.15 K) than NoAL twigs, suggesting that individuals exposed to artificial light may have adapted to longer photoperiod and increased the heat requirement for budburst. More importantly, Tres difference between AL and NoAL individuals was more pronounced in northern sites (5.8 days at Lhigh, 12.2 days at Lmiddle) than in southern sites (0.7 days at Llow), possibly due to higher inter-annual temperature variability at higher latitudes. Our findings provide experimental evidence of the effect of artificial light on tree budburst and highlight the need to consider the adaptability of urban trees when studying phenological responses to climate change in urban environments.
How to cite: Gong, Y., Wu, Z., Chen, S., and Fu, Y.: Artificial light reduced the temperature responsiveness of Ginkgo budburst, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2871, https://doi.org/10.5194/egusphere-egu26-2871, 2026.
This study provides an agroclimatic characterization of viticulture in the main wine-producing regions of Spain, with the aim of analysing the climatic controls on grapevine development and assessing recent climate-driven trends. Ten representative Protected Designations of Origin (PDOs), covering most of the national vineyard area and encompassing a wide range of geographical and climatic conditions, were selected. Daily meteorological data (maximum, minimum and mean temperatures, and accumulated precipitation) from official sources were analysed for the period 1981–2022.
Key bioclimatic indices commonly used in viticulture were computed, including the Huglin Index (HI), Dryness Index (DI), and Cool Night Index (CI). Statistical analyses were conducted to identify significant differences among regions, evaluate temporal trends, and classify the study areas using the Multicriteria Climatic Classification (MMC) system.
The results reveal a generalized increase in the HI across all PODs, indicating a consistent warming trend and a progressive shift in grapevine phenology. The DI emerged as the main limiting factor in several regions, particularly in Ribera del Guadiana and La Mancha, where irrigation is becoming increasingly necessary to sustain productivity. Analysis of the CI shows that cooler regions, such as Ribera del Duero and Rueda, still offer favourable conditions for preserving wine acidity and aromatic complexity, whereas warmer areas, including Valencia, exhibit reduced nocturnal cooling and a potential loss of freshness. The observed warming trends imply significant shifts in grapevine phenology, potentially affecting harvest timing, grape composition and wine quality.
Overall, the study highlights how climate variability and ongoing climate change are reshaping viticultural suitability in Spain, emphasizing the need for adaptive management strategies to ensure the long-term sustainability and quality of wine production under future climate conditions.
How to cite: Paniagua Simón, L. L., García Martín, A., Barrena Gil, S., García García, D., Rebollo Castillo, F. J., and Moral García, F. J.: Agroclimatic characterization and climate change trends in Spanish wine-growing regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3758, https://doi.org/10.5194/egusphere-egu26-3758, 2026.
Spain is one of the leading plum-producing countries in Europe, contributing approximately 30% of total continental production. Spanish plum production is characterized by a wide range of high-quality cultivars, including Claudia, Golden Japan and Reina Claudia Verde. Other major plum-producing countries in Europe include France, Italy, Poland and Romania.
The main objectives of this study are to: (i) characterize the thermal requirements of the vegetative cycles of early-, mid- and late-season Japanese plum (Prunus salicina) varieties cultivated in the main producing regions of Spain; (ii) compare the principal growing areas from an agroclimatic perspective; and (iii) assess temporal trends in key bioclimatic indices across these regions.
The analysis was based on the period 1981–2024 and included the following variables: frost-free period, start and end dates of the vegetative cycle, number of days with optimal temperatures for growth and ripening, thermal integral of the crop cycle and ripening phase, as well as their associated trends.
The results reveal pronounced agroclimatic differences among producing regions, particularly between Seville and Valencia. These areas exhibit the longest frost-free periods, earlier flowering dates across all varietal groups, and shorter ripening phases for early varieties. Valencia records the highest number of days with optimal temperatures for plum cultivation, whereas Seville presents the highest mean temperatures throughout the crop cycle for all varietal groups. Marked differences in accumulated growing degree days were observed, strongly conditioning varietal suitability to regional agroclimatic conditions. In this context, Seville (4204 °C·day) and Murcia (4025 °C·day) show the highest thermal integrals, favouring earlier ripening compared to other regions and indicating a higher suitability for extra-early varieties. All studied regions exhibit highly significant increasing trends, reflecting a general warming of plum-growing areas, with the strongest increase detected in Murcia, reaching 22.9 °C·day·yr⁻¹ for late-cycle varieties.
How to cite: García Martín, A., Paniagua Simón, L. L., Pineda Sánchez, M., García García, D., Moral García, F. J., and Rebollo Castillo, F. J.: Thermal requirements and climate trends of Japanese plum (Prunus salicina Lindl.) in the main producing regions of Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3795, https://doi.org/10.5194/egusphere-egu26-3795, 2026.
Increasing drought stress threatens subtropical forests, which are renowned for their complex vertical canopy stratification. However, the differential responses of leaf phenology to drought across vertical strata (i.e., overstory and understory) remain unclear. In this study, we established a near-surface remote sensing system integrating unmanned aerial vehicles and ground-fixed cameras. Through a 70% throughfall exclusion experiment, we amassed over 430,000 images to investigate drought responses in overstory and understory leaf phenology. Our results reveal significantly greater sensitivity of understory leaf phenology to extreme drought compared to the overstory. Drought exerted no statistically significant effect on overstory leaf phenology during either leaf development or senescence phases. In contrast, understory leaf senescence phenology advanced markedly under drought conditions, with 11.75 and 15.76 days for the start and end of the leaf-falling event, respectively. For the understory layer, our analysis detected that pre-season temperature primarily regulated leaf development phenology, while soil moisture dominated variability in leaf senescence phenology. Furthermore, we demonstrated that divergent water-use efficiency modulates stratum-specific phenological responses to drought. High water-use efficiency in overstory tree and seedling conferred greater drought resistance, whereas low water-use efficiency in understory shrubs increased susceptibility. These findings highlight the necessity for coordinated multi-stratum monitoring of forest responses to climate change and underscore the pivotal role of water availability in shaping understory phenological patterns in subtropical forests.
How to cite: Sun, H., Yan, L., Li, Z., Cheng, W., Zhou, X., and Xia, J.: Understory leaf phenology exhibits greater sensitivity than overstory to extreme drought in a subtropical forest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8634, https://doi.org/10.5194/egusphere-egu26-8634, 2026.
Partitioning biomass and functions such as effective separation between leaf (green part) from floral part of plant communities allows a more accurate estimation of photosynthetic vs. reproductive investment. Particularly facing the rise in global temperatures due to climate change, plant communities alter their metabolism, growth, and gas exchange, ultimately affecting functional traits. Local-scale predictions of ecosystem risks require high-resolution monitoring of these responses. However, field sampling of plant functional traits detecting early signals of climate impact remains labor-intensive, hence necessitating scalable methods that automate the detection of reproductive vs. vegetative structures. Proximal sensing, particularly terrestrial laser scanning (TLS), offers a promising solution by enabling non-destructive, high-resolution 3D scans of vegetation capturing plant intensities and complex architecture.
A key TLS output, intensity—the strength of the backscattered laser signal—reflects surface properties and may serve as a functional and phenological trait. We tested this hypothesis by measuring TLS intensity in four plant species (Lotus corniculatus, Plantago lanceolata, Plantago media, and Trifolium pratense) under controlled greenhouse conditions (TraitComic Experiment). Each species exhibited a distinct intensity fingerprint, with further differentiation between floral and vegetative structures. Floral intensity patterns correlated with geometric shape and volume, suggesting a link to phenological traits.
Our findings demonstrate that TLS-derived intensity data at 1550nm alone can discriminate species-specific and phenological features, providing a basis for upscaling to natural grasslands. By linking these signatures to ecosystem functional traits (e.g., water use efficiency, carbon dynamics), TLS intensity could enhance climate resilience assessments. This approach bridges high-resolution remote sensing with ecological trait analysis, offering a scalable tool for biodiversity monitoring under climate change.
How to cite: Guimaraes-Steinicke, C., Wende, K., Saxena, S., Weigelt, A., and Mora, K.: Floral vs. vegetative structure fingerprints identified by terrestrial laser scanning intensity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11392, https://doi.org/10.5194/egusphere-egu26-11392, 2026.
Phenology at the Deutscher Wetterdienst (DWD) involves the observation and analysis of recurring, seasonally driven development stages of plants, such as flowering, leaf unfolding, fruit ripening, and leaf fall. These phenological phases are closely linked to weather and climate conditions and therefore serve as biologically based indicators of climate variability and long-term change. The DWD phenological observations are used in multiple contexts, including climate monitoring and diagnostics, agrometeorological services, and scientific studies that analyse shifts in phase timing in relation to temperature trends. Phenological information also supports operational applications, for example in agricultural modelling and other environment-related services.
A key element of DWD’s phenological activities is its long-running observation network, which is based on standardized and quality-controlled field observations. In recent years, DWD has started to complement this classical network with additional digital data sources in order to improve spatial coverage and temporal resolution. One important development is the crowdsourcing feature “Pflanzenmeldungen” in the DWD WarnWetter app, which allows citizens to submit geo-referenced reports of plant development stages via smartphone. These reports can help capture regional differences, extreme-year signals, and near-real-time vegetation responses, particularly in areas with fewer traditional observations. By integrating these app-based reports with established phenological datasets and expert workflows, DWD aims to extend and enrich its national phenology record while maintaining scientific usability.
Further expansion of digital data sources is planned through a collaboration with Flora Incognita, a machine-learning-based plant identification platform. This cooperation aims to link phenological monitoring with scalable species recognition and user-driven reporting. The combination of supported plant identification and structured phenological input is expected to improve data consistency, encourage participation, and increase the volume and resolution of phenological information.
Overall, DWD’s phenology programme is developing toward a hybrid monitoring system that integrates long-term standardized observations with crowdsourced app data and AI-supported plant identification. This approach enhances spatial and temporal coverage and strengthens the basis for monitoring climate impacts on vegetation and for providing robust phenology-based climate services.
How to cite: Posada Navia-Osorio, R. and Lifka, S.: Expanding DWD phenology monitoring through crowdsourced plant reports and AI-enabled data partnership, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12746, https://doi.org/10.5194/egusphere-egu26-12746, 2026.
Ongoing climate change, together with land-use transformation, biological invasions, and increasing human pressure, is intensifying alterations in ecosystem dynamics and phenological patterns. Plant phenology has gained a central role as a key biological indicator of ecosystem responses to climate variability, since long-term shifts in phenological timing influence ecosystem functioning, productivity, and trophic interactions. Historically, phenological monitoring has relied on labor-intensive field observations, often constrained by limited spatial coverage and temporal continuity. In recent years, advances in near-surface sensing technologies—including unmanned aerial vehicles, phenocams, and spectral reflectance sensors—together with satellite remote sensing have substantially transformed phenological studies. These new applications are particularly important for monitoring vulnerable hotspots, such ecosystems in Mediterranean regions, whose complex functioning result from the interaction of climatic gradients, geomorphological processes, disturbance regimes, and species-specific functional traits. Moreover, recently, new AI-based approaches have gained importance as powerful framework for continuous, multi-scale phenological monitoring.
This contribution is aimed to provide an overview of major methods and techniques adopted for phenological research supported by artificial intelligence (AI). Among the most widespread applications, developments in machine learning (ML) and deep learning (DL) enable the automated analysis of large and complex image datasets, facilitating the extraction of robust phenological signals and supporting the development of standardized monitoring frameworks for assessing ecosystem responses to climate change. Also, Computer Vision techniques applied to phenocam imagery exemplify these advances: deep learning models, particularly convolutional neural networks, can automatically classify phenological stages from high-frequency image data. Extracted visual features can be further analyzed using temporal modelling approaches, such as neural networks, temporal convolutional networks, or Transformer-based architectures, to characterize seasonal dynamics. In addition, chromatic indices derived from vegetation pixels can be combined with AI-based correction methods to reduce the effects of illumination variability, weather conditions, and sensor-specific biases, improving the reliability of phenological metrics. Despite these advances, challenges remain, including limited training data availability, spectral similarity among plant species, and strong local environmental heterogeneity, which require context-specific calibration.
Overall, the integration of satellite observations, phenocam networks, and AI-driven tools offers a powerful framework for continuous, multi-scale phenological monitoring. As climate change accelerates shifts in plant development and ecosystem seasonality, such integrated approaches will be essential for improving ecological forecasting and supporting resilient biodiversity monitoring strategies.
How to cite: Cesaraccio, C., Piga, A., and Spano, D.: From field observations to AI-based phenology: an overview of advances in monitoring ecosystem responses to climate change , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12782, https://doi.org/10.5194/egusphere-egu26-12782, 2026.
Aeroallergens such as pollen and fungal spores can trigger allergic reactions and therefore are of medical and clinical relevance. Allergic diseases are widespread worldwide and affect a large percentage of the population, placing a substantial burden on public health systems. Their prevalence and impact highlight the importance of understanding spatial and temporal variability in aeroallergen exposure. Thus, this study aims to assess spatial and temporal variability in airborne pollen exposure at two sites in and around Ingolstadt, Germany, based on three years of volumetric pollen monitoring.
To enable a direct urban–rural comparison, airborne pollen were monitored over three years (2019–2021) at two nearby study sites in Ingolstadt, Germany: an urban site in the city center (WFI) and a more rural site in the surrounding area (RSK) at a distance of approximately 8 km. Samplers (7-day volumetric traps) were mounted on rooftops to capture daily and bihourly pollen concentrations. We analyzed daily data to identify the most abundant pollen types, and quantified the duration of the pollen seasons, peak days and peak values, and the Seasonal Pollen Integral (SPIn).
Across all years and both sites, the dominant pollen types were Betula, Pinus, Taxus, Urticaceae, and Poaceae. Betula contributed up to one-third of airborne pollen to the pollen load. Among herbaceous taxa, Urticaceae was consistently most abundant, accounting for up to 37% of the annual total. Peak daily mean Betula concentrations at both sites occurred in 2020, reaching 2,378 pollen grains/m³ (WFI) and 2,788 pollen grains/m³ (RSK). We observed substantial differences in Poaceae pollen concentrations between the urban and more rural site across all study years. For example, in 2019 the peak concentration at the more rural site was eight times higher than at the urban site (371 vs. 46 pollen grains/m³). The longest pollen seasons were observed for Picea and Brassicaceae: at WFI, 251 (2021) and 185 (2019) days, respectively; at RSK, 173 (2021) and 178 (2019) days, respectively.
Despite the short distance between the two sites, clear urban-rural differences in pollen exposure were observed, pointing to the importance of land use and other local environmental conditions. Extending the monitoring period in future studies will be essential to assess the robustness of these patterns and their variability over time.
How to cite: Jetschni, J. and Jochner-Oette, S.: Airborne pollen concentrations in and around Ingolstadt, Germany: a three-year observational study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17035, https://doi.org/10.5194/egusphere-egu26-17035, 2026.
The Mediterranean region is widely recognized as a climate change hotspot. Extreme heat events are becoming more frequent and present increasing risks to vineyards and other cultivated crops. Satellite remote sensing allow us to monitor over large areas and long time periods vegetation responses to such events. However, it is important to understand spatial scaling effects (i.e., due to vegetation crown architecture and satellite pixel resolution) and lagged temporal dynamics (i.e., legacy effects in vegetation functioning). Here, we focus on three selected viticultural regions in the Peloponnese and Western Greece and we synthesized remote sensing data and environmental variables to address the above-mentioned issues. The regional climatic conditions at each vineyard, were identified sing ERA5-Land reanalysis dataset, accessed via the Copernicus Climate Data Store. With respect to spatial scale, we analysed NDVI time series derived from Landsat (30 m), Sentinel-2 (10 m), and PlanetScope (3 m) imagery. These data are used to assess spatiotemporal heterogeneities in vineyard canopy responses to extreme heat events. Moreover, we analysed NDVI responses during recent heatwave events, characterized by their duration, timing within the growing season, and maximum temperature, and quantified vegetation recovery following each event. The results showed consistent NDVI reductions associated with heatwaves, with differences in the intensity and duration of the response across regions, vineyard varieties, irrigation practices, and events. Landsat data provide a stable long-term reference, while Sentinel-2 and PlanetScope improve the detection of short-term changes and spatial variability. Despite differences in spatial resolution, all three datasets capture similar temporal NDVI patterns. These results demonstrate that multi-sensor NDVI time series can be used to detect and compare vineyard vegetation responses to extreme heat events. The proposed approach provides a simple and widely applicable framework for monitoring agricultural impacts of climate extremes using operational openly-available satellite data.
How to cite: Pantazis, C., Bakali, I., Sotiriou, V., Pappas, C., Argiriou, A., and Nastos, P.: Assessing Heatwave Impacts on Western Greece and Peloponnese Vineyards Through Remote Sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21647, https://doi.org/10.5194/egusphere-egu26-21647, 2026.
Phenology is a science with strong media interest. It attracts public attention from several perspectives:
- The empirical verification of advances or delays in the occurrence of different plant or animal phenophases.
- The possibility of quantifying phenophase shifts and their correlation with climatic variables to establish the relationship with climate change.
- The concrete economic impact on crop management and the resulting production.
- The aesthetic beauty associated with phenophase events, such as leaf senescence (for example, the annual chromatic variations of deciduous forests) or spring flowering (as seen in extensive fruit tree crops).
Several cases are presented in which the media have requested collaboration from the Phenological Network of Catalonia, as well as the impact on different social media platforms of posts related to phenology. It is also shown how the evolution of informational interest in phenology can be measured through parameters such as the number of views of television videos, news published online, link sharing, retweets, likes, etc. From these parameters, a growing interest in phenology among the population is inferred.
How to cite: Busto, M., de Yzaguirre, X., and Cunillera, J.: Interest and Impact of Phenology in the Media, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22720, https://doi.org/10.5194/egusphere-egu26-22720, 2026.
Forecasting autumn phenology remains challenging partly because many models rely on daily mean or daily minimum temperature (Tmin) as the primary thermal cue. However, a growing body of evidence suggests that daytime cooling, i.e. low values of daily maximum temperature (Tmax), can exert disproportionate control on end-of-season transitions, implying that models based on Tmin or daily means may miss key mechanisms. Here we ask: Does late-season nighttime cooling ever induce bud set and leaf senescence when daytime temperatures remain relatively warm? Using 330 European beech (Fagus sylvatica) saplings, we ran a controlled-environment manipulation experiment targeting autumn phenology. Across two treatment windows (Jul 3 – Aug 15 and Aug 15 – Sep 25), we imposed a nighttime cooling gradient (night temperatures of −1, 8, or 14 °C [control]) while holding daytime conditions constant. Additionally, we included an all-day cooling treatment (8 °C for 24 h) to contrast “night-only” versus “full-day” cooling. To test whether developmental state modulates responsiveness, plants were stratified into early- vs. late-leafing groups reflecting faster versus slower spring development. In the first window, no level of nighttime cooling alone induced earlier bud set or leaf senescence; in contrast, full-day cooling (and, by inference, reduced daytime temperatures) had a consistent advancing effect. Evidence from the second window indicates that nighttime cooling can contribute only at the very end of the growing season, when photoperiod is shortest and trees are most responsive. These results support the idea that daytime cooling (low Tmax) can be the decisive thermal signal for autumn transitions, and they motivate phenology models that explicitly separate day vs. night temperature effects rather than relying on Tmin or daily means alone.
How to cite: Rebindaine, D., Gessler, A., Crowther, T. W., Nüesch, M., and Zohner, C. M.: Summer daytime cooling, not nighttime cooling, induces earlier bud set and leaf senescence in European beech, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7713, https://doi.org/10.5194/egusphere-egu26-7713, 2026.
In high-latitude regions, snow dynamics influence plant phenology and ecological processes, ultimately feeding back to the climate system. However, it remains unclear how the timing of snow melt regulates the start of the growing season (SOS) across northern forest and non-forest ecosystems, and how these effects depend on moisture and temperature regimes. Here, we combine satellite-derived plant phenology with reanalysis snow and environmental datasets spanning 2001–2024 across the Northern Hemisphere north of 50°N to better understand these mechanisms. We partitioned the pre-growing season into three cascading phases: (P1) pre-melt snow accumulation, (P2) snowmelt, and (P3) post-melt vegetation activation. Linear mixed-effects models show that air temperature during P3 explains the largest share of SOS variation (β≈ -0.61, p < 0.001), while the end of snowmelt represents a key physical threshold for SOS, particularly in non-forest ecosystems (β ≈ 0.1, p < 0.001). Overall, environmental conditions during P3 exert the strongest control on spring green-up, being more than twice as important than that of earlier stages (P1 and P2). Using piecewise structural equation modeling, we identify different ecological strategies between ecosystems: Non-forest ecosystems exhibit greater sensitivity to snow melt timing, with an effect size about three times greater than in forests. These findings indicate that forests are comparatively less sensitive to snowmelt timing, whereas non-forest ecosystems remain highly vulnerable to shifts in snowmelt timing and the associated changes in temperature and moisture conditions.
How to cite: Mu, Y., Luo, Y., Che, T., M. Zohner, C., and Gessler, A.: Snowmelt timing has a stronger effect on northern spring green-up in non-forest than forest ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14519, https://doi.org/10.5194/egusphere-egu26-14519, 2026.
Vegetation phenology, the timing of periodic events in vegetation development, is an essential indicator for detecting climate-vegetation dynamics. Although the importance of vegetation growth carryover (VGC) on phenology has been recognized in the Northern Hemisphere (NH), it is unclear how VGC and climatic factors contribute to phenology and how these contributions evolve at a global scale. Utilizing two sets of satellite NDVI data (1982-2022) and PEP725 ground observations (1963-2015), we explored the impacts of climate change and VGC on start-of-season (SOS) and end-of-season (EOS) across the Northern and Southern Hemispheres during the past five decades. Here we show that, globally, advanced SOS was driven primarily by increasing temperature and radiation, while delayed EOS was attributed to rising temperature and the carryover effect of spring vegetation growth (VGCSOS). VGCSOS was the dominant driver of EOS in the SH, whereas temperature played a larger role in the NH. Over the past four decades, the contribution of VGCSOS on EOS has increased significantly on a global scale. However, the SH experienced pronounced "warming and drying" trends, which weakened the relative contribution of VGCSOS on EOS compared to climate-driven delays. These findings improve our understanding of vegetation dynamics and offer valuable insights for predicting vegetation growth and carbon sequestration under future global warming scenarios.
How to cite: Tang, D., Xie, S., Peng, J., Sun, Y., Degen, A. A., Sun, Y., Luo, J., Li, Z., Kuang, Y., Wei, L., Hu, W., Dong, L., Hou, Q., Dong, X., Zhang, L., Ran, J., Fu, Y. H., and Deng, J.: The Increased Effect of Spring Leaf Unfolding on Autumn Senescence in the Northern and Southern Hemispheres , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16727, https://doi.org/10.5194/egusphere-egu26-16727, 2026.
Plant phenology controls many ecological processes, and its observation can provide valuable insights about the status of vegetation (e.g., water stress). In recent years there has been a growing interest in capturing seasonal variations using time-lapse digital cameras (phenocams), an inexpensive alternative to field surveys. In fact, pheno-cam images have become a popular reference for phenology studies based on Earth Observation. However, the analysis of long archives acquired under difficult conditions may pose some challenges such as degraded (blur, corruption), misaligned or mis-colored images (e.g. inconsistencies due white balance).
In this study we analyzed the images acquired from the tower of the Zöbelboden LTER site, describing the process we followed to ensure the archive was consistent. Once it was homogenized, we compared the chromatic coordinates with Sentinel-1 backscatter to understand how it is linked with leaf phenology of different tree species.
Archive preparation relied on machine vision techniques. Blur estimation was used to detect degraded images. Registration relied on a group of well aligned images that were used to create a robust synthetic reference based on Sobel edge detector and principal component analysis. The rest of the images were compared with this reference, completing the alignment using Keypoint matching and enhanced cross-correlation. The impact of white balancing was reduced using vicarious calibration, matching the data distributions of stable areas (tree trunks) to the reference from well calibrated images.
When we examined the correlation between the chromatic coordinates and Sentinel-1 terrain-flattened backscatter (gamma) the absolute coefficient often exceeded 0.4 when comparing green and blue with the cross-polarized backscatter or the cross-ratio. Green is tied to photosynthetic activity, whereas the proportion of blue remains lower where leaves are still present (green, active; yellow, senescing; red/brown, dry leaves). These hints Sentinel-1 can be used to track leaf phenology, which would be a powerful asset thanks to its cloud-penetrating capabilities.
How to cite: Borlaf-Mena, I., Dirnböck, T., Reuß, F. D., and Vreugdenhil, M.: Homogenizing pheno-cam data to understand Sentinel-1 backscatter dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18459, https://doi.org/10.5194/egusphere-egu26-18459, 2026.
Tree phenology is both a crucial proxy for ecosystem services such as biomass production and an important indicator for the impact of climate change on forests due to its dependence on local climatic conditions. Both traditional monitoring and phenological cameras (pheno cams) offer only few observation points, limiting the study of large-scale spatial patterns. Optical satellite time-series can provide the necessary spatio-temporal extent needed. However, their agreement with in situ data is often unknown and uncertainties are high.
This study is part of the AI-Klima project and aims to fill these gaps for the Bohemian Forest, where traditional and pheno cam observations are available, but no large-scale spatio-temporal analysis of tree phenology has been conducted to date. The studied period stretches over two decades, from 2000 to 2024. The study area, the Bohemian Forest, is a cross-border region including the German Bavarian Forest National Park (BFNP) and the Czech Šumava National Park. It contains a diverse forest composition and with both managed and unmanaged areas.
Forest phenology in satellite data is analyzed via an innovative method combination and validated with pheno cam data. EVI time series data from harmonized Landsat 4-9 and Sentinel 2 data is used to calculate six phenological timings per pixel and year: (1) start of the green up in spring, (2) point of fastest growth (spring inflection point (SIP)), (3) end of spring growth, (4) start of senescence in autumn, (5) point of fastest decline (autumn inflection point), (6) end of the autumn decline. This is achieved through a novel dynamic combination of filtering and fitting methods for time series smoothing. This approach accounts for the high variability of available data. Phenological timings are then obtained trough geometric analysis of the smoothed time series curve.
To validate the results, time series of 15 pheno cams are analyzed in a similar way, obtaining reference phenological timings. Here, the Green Chromatic Coordinate (GCC) is used as a spectral index instead of the EVI. To insure accuracy, the pheno cam images are pre-processed to exclude bad-quality images using both traditional and AI-driven methods.
The resulting phenological timings for every year over the whole study area are analyzed for temporal trends and spatial patterns in forest phenology. For spring phenology, first results show spatially heterogeneous patterns of change in the inflection point timing. Lower elevation areas display comparatively little change, while many higher elevation areas show an unexpected strong trend of later spring inflection points. This goes against the expected trend of earlier springs due to climate change, but might be explained by the effect of mass bark beetle outbreaks and consequent shift in vegetation composition. However, the influence of data availability, alongside data quality, will need to be discussed critically as well, since for some years, only a small number of cloud free satellite scenes is available.
Combined with other work package outputs in AI-Klima, the phenology trends will be utilized to identify the forest stands most impacted by climate change in the Bohemian Forest Ecosystem.
How to cite: Schierghofer, C. J., Heurich, M., Hechtl, C., Hais, M., Grill, S., Vrieling, A., and Lehnert, L.: Spatial Trends in Tree Phenology in the Bohemian Forest Ecosystem over the Last Two Decades, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18555, https://doi.org/10.5194/egusphere-egu26-18555, 2026.
Crop models such as IVINE (Italian Vineyard Integrated Numerical model for Estimating physiological values), developed at the University of Turin Physics Department since 2015, represent a sophisticated tool for simulating the complex interactions between vineyards and the atmosphere. These models are designed to accurately reproduce the phenology and key physiological processes that dictate crop growth and yield quality, including photosynthesis, respiration, nutrient uptake, and water use efficiency. Given that the precise identification of the main phenological stages is crucial for guiding the timing and intensity of various biological processes, the model must meticulously account for a wide array of fluctuating environmental factors. These include primary meteorological variables — temperature, humidity, wind speed, atmospheric pressure, and precipitation — as well as variables related to the surface layer and the root zone, such as soil water availability and energy content. Furthermore, the model incorporates detailed site-specific parameters, including soil texture, physical characteristics, and the specific morphological properties of the vegetation. A fundamental phase of this research involves the rigorous validation of the model for specific cultivars; this is achieved through experimental runs in distinct geographical regions, where simulation outputs are compared against high-resolution field measurements. Once validated, these models serve as reliable "numerical laboratories" for conducting predictive simulations under varying environmental scenarios. In this work, we present the results of simulations focused on the Timorasso grape variety, a traditional Piedmontese cultivar. The study compares model outputs with detailed field observations provided by a leading winery in the region, bridging the gap between theoretical modeling and practical viticulture. The meteorological input data were meticulously compiled into a dedicated database, integrating records from the regional agrometeorological network (RAM) and the ARPA hydro-meteorological network, with missing values filled through site-specific interpolation techniques. Soil-related variables were generated using the UTOPIA (University of TOrino land surface Process Interaction model in Atmosphere) model, while soil texture and organic matter content were retrieved from the international SoilGrids database to ensure a comprehensive characterization of the vineyard environment.
How to cite: Cassardo, C., Andreoli, V., Isnardi, F., and Zilli, S.: Simulating grapevine phenology with IVINE and UTOPIA models: a case study on the Timorasso cultivar, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19649, https://doi.org/10.5194/egusphere-egu26-19649, 2026.
Understanding vegetation phenology at landscape to continental scales is essential for tracking ecosystem responses to climate change, improving biodiversity assessments, and strengthening land-surface models. While satellite remote sensing provides broad spatial coverage, it often lacks the temporal and structural detail required to resolve fine-scale phenological dynamics. In particular, satellite phenology products struggle to capture species-specific phenological responses to climatic variability. Over the past decade, PhenoCam networks have been developed to address some of these limitations. Here, we build on these efforts and introduce a novel Switzerland-scale phenocam dataset capturing both individual- and canopy-level phenological signals. We curate a large collection of high-frequency, high-resolution webcam imagery and use it to monitor expert-annotated regions of interest (ROIs) corresponding to individual trees with known species, as well as tree canopies.
The first iteration of the dataset is based on imagery acquired at 32 sites across Switzerland, spanning the full elevational range of the country. For some sites, observations begin as early as 2010 and extend to the present day. On average, each site has a temporal coverage of six years, amounting to a total of 175 site-years. The dataset currently includes over 5,000 tree-years of observations for individual trees, enabling species-level analyses of phenological variability. For all individual-tree and canopy-level ROIs, we apply automated greenness-based methods to extract green-up and green-down dates, allowing the investigation of species-specific phenological patterns across Switzerland’s climatic gradients, which are strongly structured by elevation. For approximately 1,000 tree-years, expert-annotated phenophase dates are available, providing a unique benchmark for calibration and validation. We are thus able to report robust phenological transition dates for more than ten tree species in Switzerland over the past decade. The large number of individuals included in our monitoring efforts also allows for cross-sectional comparisons of season length and its variability across species, elevation, and years.
By making high-frequency phenological observations available at the country scale, the SwissPhenoCam dataset provides a valuable resource for phenology monitoring and supports the development and evaluation of methods for phenological modeling and forecasting. We invite the community to use this dataset to advance understanding of vegetation dynamics in a rapidly changing world.
How to cite: Sainte Fare Garnot, V., Lever, J., Vitasse, Y., Wegner, J. D., and Gessler, A.: The SwissPhenoCam dataset: Country-scale phenology monitoring at the individual tree level , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13207, https://doi.org/10.5194/egusphere-egu26-13207, 2026.
Global warming alters spring phenology in temperate forests, with significant implications for tree vitality, growth, and ecological interactions. However, temperature requirements for dormancy release and budburst differ among populations adapted to different climatic condition, complicating predictions of spring phenology across broad geographic regions.
Here, we quantified chilling and forcing requirements of three deciduous tree species (Fagus sylvatica, Quercus robur, and Tilia cordata) using four provenances per species spanning a latitudinal gradient from Spain to Poland. Saplings were exposed to either ambient or warmed (+5 °C) open-top chambers and subsequently transferred at monthly intervals from November to February to a 20°C forcing chamber.
We found that reduced chilling (due to earlier transfer into warming conditions) substantially delayed budburst, with T. cordata showing the highest chilling requirement, followed by F. sylvatica, whereas Q. robur exhibited the lowest. Interestingly, we detected both co- and counter-gradient patterns of genetic variation in budburst timing. In Q. robur and, to a lower extent, in T. cordata, Polish provenances budburst later than Spanish ones, while German and Swiss populations were intermediate. In contrast, F. sylvatica showed the reverse pattern with the Spanish provenance tending to budburst latest and the Polish one earliest. These differences likely reflect provenance-specific frost risks and resulting genetic differentiation in chilling and forcing requirements. Remarkably, insufficient chilling significantly reduced budburst success by 25–85 % across species. The effect was most pronounced in T. cordata, where success dropped below 10 % in saplings transferred in November or December, regardless of provenance. These findings underscore the critical role of winter chilling in regulating budburst and maintaining tree vitality, as well as provenance-specific adaptation, suggesting that species adapted to low winter chilling might be candidates for assisted migration under rapid climate change.
How to cite: Vitasse, Y., Walde, M. G., Beil, I., Klisz, M., and Wu, Z.: Provenance-specific chilling and forcing requirements regulate spring phenology of three European temperate tree species , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9015, https://doi.org/10.5194/egusphere-egu26-9015, 2026.
