Impact of climate change on phenological shifts in the Bavarian deciduous forests

Spring in Bavaria's deciduous forests now arrives roughly 16 days earlier than it did four decades ago—a shift large enough to alter forest carbon uptake, disrupt pollinator synchrony, and change the seasonal rhythms that local communities have observed for centuries. This research analysed phenological records from 42 monitoring stations across the Bavarian deciduous forest belt to quantify long-term trends in leaf-out date, leaf-fall date, and growing season length over the period 1980–2022. Records were obtained from the German Meteorological Service (DWD) phenological observation network and paired with daily temperature and precipitation data from the same stations. Results showed that mean leaf-out date advanced by 3.8 days per decade (p < 0.001), while leaf-fall was delayed by 2.7 days per decade (p < 0.01), extending the growing season by an average of 6.5 days per decade. Spring temperatures (March–April mean) increased by 1.6°C over the 43-year record and explained 72.4% of the variance in leaf-out timing. Elevation modulated the response: low-elevation stations (300–500 m) gained 18 growing-season days, while high-elevation stations (1100–1400 m) gained only 13 days. These phenological shifts carry consequences for forest productivity, water balance, and frost-damage risk, as earlier leaf-out exposes developing foliage to late-spring freezing events whose frequency has not declined proportionally. The research provides a quantitative phenological baseline for Bavarian forests that can inform adaptive forest management under continued warming.

Illustrations explain the paper; charts are replotted from the paper's own table values.

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The Frost-Risk WindowClose ×

AI-generated conceptual illustration (European beech trees in a deciduous forest). It explains the idea and does not show study data.

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Replotted from source data

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Leaf-Out Trend (d/dec) and Leaf-Fall Trend (d/dec) and more: 300–500 m vs 500–700 m vs 700–900 m vs 900–1100 m vs 1100–1400 mClose ×

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

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Replotted from source data

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ΔT Spring (°C) and Projected Leaf-Out Shift (d) and more: Current (2022) vs Moderate (+1.5°C) vs Intermediate (+2.5°C) vs High (+4.0°C)Close ×

Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

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Introduction

Here is a fact that would have surprised a forester working in Bavaria in the 1970s: the European beech trees (Fagus sylvatica) that dominate the region's deciduous forests now begin unfolding their leaves in early April, when four decades ago they reliably waited until late April [1] . That two-to-three-week shift is not a quirk of a single warm year-it is a persistent, statistically robust trend driven by rising spring temperatures that have warmed the Bavarian lowlands by roughly 1.5-2.0°C since 1980 [2] . And beech is not alone: oak, maple, ash, and linden have all advanced their spring phenology by similar margins, reshaping the seasonal calendar of one of central Europe's most extensively monitored forest landscapes. Phenology-the timing of recurring biological events-is among the most sensitive biological indicators of climate change [3] . In temperate deciduous forests, the two cardinal phenological events are leaf-out (budburst and leaf expansion in spring) and leaf-fall (senescence and abscission in autumn). Together they define the growing season, the period during which the forest actively photosynthesises, transpires water, and sequesters carbon. Extending the growing season by even a few days per decade can measurably increase annual net primary productivity, but it also increases water demand and may expose early foliage to damaging late-frost events if cold spells haven't retreated at the same pace as leafout has advanced [4] . Bavaria offers an ideal setting for phenological research because the DWD has maintained a volunteer observer network since the 1950s, producing one of the longest and most spatially dense phenological datasets in Europe [5] . The region's deciduous forests span an elevation gradient from roughly 300 m in the Danube lowlands to 1,400 m in the Bavarian Alps foothills, providing a natural experiment in how altitude modulates the phenological response to warming. This research analysed 43 years of phenological records from 42 DWD stations across the Bavarian deciduous forest belt, quantified trends in leaf-out, leaf-fall, and growing season length, tested the sensitivity of these events to spring and autumn temperatures, and examined how elevation influences the magnitude of phenological change. The work was coordinated through the Pondicherry Institute of Climate and Environment using data accessed through the DWD open data portal during 2022.

Seasonal Variations and Temporal Patterns

Phenological observations at each station followed the DWD standard protocol, in which trained volunteer observers record the calendar date of first leaf-out (BBCH stage 11: first leaves fully unfolded) and general leaf-fall (BBCH stage 95: 50% of leaves fallen) for selected indicator species-primarily European beech (Fagus sylvatica), pedunculate oak (Quercus robur), and Norway maple (Acer platanoides) [6] . Growing season length was computed as the number of days between leaf-out and leaffall. To capture intra-annual variability, monthly mean temperatures and precipitation totals were extracted from the DWD climate data archive for each station and aggregated into seasonal windows: spring (March-April), early summer (May-June), late summer (July-August), and autumn (September-October). The spring temperature window was selected as the main candidate driver of leafout timing based on the known temperature sensitivity of budburst in European beech, which responds primarily to heat accumulation above a base temperature of approximately 5 °C during March and April [7] .

Materials and Methods

Materials and Methods

Materials

Materials

Methods

Temporal trends in leaf-out date, leaf-fall date, and growing season length were estimated for each station using ordinary least-squares linear regression against year, and the regional mean trend was computed as the average of station-level slopes. Trends were tested for significance using the Mann-Kendall non-parametric test at p < 0.05. The sensitivity of leaf-out to spring temperature was quantified by regressing station-level leaf-out date against March-April mean temperature, yielding a sensitivity coefficient (days/°C) for each station [8] . Elevation effects were assessed by grouping stations into five elevation bands (300-500, 500-700, 700-900, 900-1100, and 1100-1400 m) and comparing trend magnitudes among bands using one-way ANOVA. Latefrost risk was evaluated by computing the frequency of days with minimum temperature below 0°C after the mean leafout date for each decade. All analyses used R 4.2.3.

Scenario Development

To project future phenological conditions, three warming scenarios were applied to the observed temperaturephenology relationships. The scenarios were based on IPCC AR6 global warming levels adapted to the Bavarian regional context using Euro-CORDEX downscaled projections [9] : (1) a moderate scenario with +1.5°C additional warming above the 2022 baseline by 2060, (2) an intermediate scenario with +2.5°C by 2060, and (3) a high scenario with +4.0°C by 2060. Projected leaf-out dates were calculated by multiplying the observed sensitivity coefficient (days/°C) by each scenario's temperature increment and subtracting the result from the current mean leaf-out date. Growing season extension was estimated similarly. These projections assume a linear and stationary temperature-phenology relationship-an assumption that may break down at very high warming levels where photoperiod constraints or chilling requirements begin to limit further advancement [10] . Table 2 reports the temperature sensitivity coefficients and scenario projections. The mean leaf-out sensitivity was -4.7 days/°C of spring warming. Under the three scenarios, leafout would advance by an additional 7, 12, and 19 days respectively by 2060, pushing the mean leaf-out date into mid-to-late March under the high scenario. Late-frost frequency after leaf-out increased from 1.4 events per spring in the 1980s to 2.1 events per spring in the 2010s, indicating that the frost-risk window has not closed as fast as leaf-out has advanced.

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Table 2Close ×

Temperature sensitivity and scenario-based projections for leaf-out date advancement

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Original paper figureSource PDF · page 3 ↗

Results

Results

Discussion

The leaf-out advancement of 3.8 days per decade documented here for Bavarian forests falls within the range of 2.5-5.0 days per decade reported by the European Phenology Network for temperate deciduous forests across central Europe [11] . What distinguishes the Bavarian dataset is its elevation gradient, which reveals a clear attenuation of the phenological response with altitude. Low-elevation stations showed the strongest trends-consistent with the greater absolute warming observed in valley bottoms compared with higher terrain, where free-atmosphere temperature lapse rates buffer surface warming somewhat [12] . The growing frost-risk paradox is perhaps the most practically relevant finding. Although late-spring frosts have become slightly less frequent overall, leaf-out has advanced faster than the last frost date has retreated, meaning that the overlap window-the period during which new foliage is exposed to freezing temperatures-has actually widened [13] .

In the 1980s, an average of 1.4 frost events occurred after mean leaf-out; by the 2010s that figure rose to 2.1. For forest managers, this means that the carbon-gain benefit of a longer growing season comes with an increased risk of frost damage to early foliage, which can reduce annual increment in beech by 10-20% in a severe frost year. The scenario projections suggest that under continued warming, leaf-out could shift into mid-March by 2060 under the high scenario. At that point, photoperiod constraints and chilling requirements may begin to limit further advancement, because many temperate tree species need a minimum duration of winter cold to break dormancy [14] . The linear sensitivity model used here does not capture this saturation effect, so the projected shifts for the high scenario should be treated as upper bounds. Incorporating processbased phenological models that explicitly account for chilling and photoperiod interactions would improve the realism of future projections.

Conclusion

Conclusion

Acknowledgement

Acknowledgements Funding SourcesThis research was supported by general institutional research funds from the Pondicherry Institute of Climate and Environment. No external competitive grants were applied. Institutional SupportThe authors thank the Pondicherry Institute of Climate and Environment for computing and data analysis resources. Phenological and climate data were accessed through the German Meteorological Service (DWD) open data portal. Contributions Not Qualifying for AuthorshipThe authors acknowledge the DWD volunteer phenological observers whose decades of record-keeping made this long-term analysis possible.

Figures and tables from the paper

Elevation Band	Stations (n)	Leaf-Out Trend (d/dec)	Leaf-Fall Trend (d/dec)	GS Change (d/dec)	Total GS Gain (d)	p-value
300–500 m	10	−4.2	+2.9	+7.1	18	< 0.001
500–700 m	11	−4.0	+2.8	+6.8	17	< 0.001
700–900 m	9	−3.7	+2.7	+6.4	16	< 0.001
900–1100 m	7	−3.4	+2.4	+5.8	14	0.002
1100–1400 m	5	−3.1	+2.2	+5.3	13	0.008
All Stations	42	−3.8	+2.7	+6.5	16 (mean)	< 0.001

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Table 1Close ×

Phenological trends by elevation band across the Bavarian deciduous forest belt (1980–2022)

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Original paper tableSource PDF · page 2 ↗

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Figure 1Close ×

Temporal trends in leaf-out date and leaf-fall date for

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Figure 2Close ×

Growing season length by elevation band for the 1985

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Original paper figureSource PDF · page 3 ↗

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