Modelling leaf coloration dates over temperate China by considering effects of leafy season climate

Process-oriented models of leaf senescence are biased towards the mean: Impacts on model performance and future projections

The timing of leaf senescence in deciduous trees influences carbon uptake and the resources available for tree growth, defense, and reproduction. Therefore, simulated biosphere-atmosphere interactions and, eventually, estimates of the biospheric climate change mitigation potential are affected by the accuracy of process-oriented leaf senescence models. However, current leaf senescence models are likely to suffer from a bias towards the mean (BTM). This may lead to overly flat trends, whereby errors would increase with increasing difference from the average timing of leaf senescence, ultimately distorting model performance and projected future shifts. However, such effects of the BTM on model performance and future shifts have rarely been investigated. We analyzed >17 × 106 past dates and >49 × 106 future shifts of leaf senescence simulated by 21 process-oriented models that had been calibrated with >45,000 observations from Central Europe for three major European tree species. The surmised effects on model performance and future shifts occurred in all 21 models, revealing strong model-specific BTM. In general, the models performed only slightly better than a null model that just simulates the average timing of leaf senescence. While standard comparisons of model performance favored models with stronger BTM, future shifts of leaf senescence were smaller when projected by models with weaker BTM. Overall, the future shifts for 2090-2099 relative to 1990-1999 increased by an average of 13-14 days after correcting for the BTM. In conclusion, the BTM substantially affects simulations by state-of-the-art leaf senescence models, which compromises model comparisons and distorts projections of future shifts. Smaller shifts result from flatter trends associated with stronger BTM. Therefore, smaller shifts according to models with weaker BTM illustrate the considerable uncertainty in current leaf senescence projections. It is likely that state-of-the-art projections of future biosphere behavior under global change are distorted by erroneous leaf senescence models.

Spatiotemporal variation of cold requirements for leaf coloration and its environmental cues over the northern deciduous broadleaved forests

Evaluating the interactions between cold requirements for leaf coloration and environmental cues is crucial for understanding the mechanisms of leaf senescence and accurately predicting autumn phenology. Based on remote sensing-derived and ground-observed leaf coloration dates for deciduous broadleaf forests during 1981-2014, we determined location-specific cold requirements for autumn leaf coloration and assessed their spatiotemporal changes. Then, we revealed the major environmental cues of cold requirements and their spatial differentiation. Results show that cold requirements have nonsignificant trends during the past decades at 57.9% of pixels. The interannual variation of cold requirements was mainly influenced by growing-season accumulated temperature (GDDgs) at 35.8% of pixels and accumulated growing season index (AGSI) at 23.2% of pixels, but less affected by leaf unfolding and low precipitation index (LPI). The increase in GDDgs or AGSI may decrease cold requirements, and vice versa. The spatial differentiations of the effects of GDDgs and AGSI depend highly on local summer temperature among climatic classifications with similar humidity conditions. Specifically, the effects of GDDgs on cold requirements concentrated in humid regions with warmer summers, while that of AGSI mainly occurred in humid and winter dry regions with cooler summers. Higher summer temperatures would strengthen the effects of GDDgs and reduce the effects of AGSI on cold requirements. These findings deepen the understanding of the influences of environmental factors on leaf senescence progress and suggest that the shifts of factors affecting cold requirements under global warming may enlarge the uncertainty in predicting autumn leaf coloration dates.

Effect of climate warming on the timing of autumn leaf senescence reverses after the summer solstice

Climate change is shifting the growing seasons of plants, affecting species performance and biogeochemical cycles. Yet how the timing of autumn leaf senescence in Northern Hemisphere forests will change remains uncertain. Using satellite, ground, carbon flux, and experimental data, we show that early-season and late-season warming have opposite effects on leaf senescence, with a reversal occurring after the year's longest day (the summer solstice). Across 84% of the northern forest area, increased temperature and vegetation activity before the solstice led to an earlier senescence onset of, on average, 1.9 ± 0.1 days per °C, whereas warmer post-solstice temperatures extended senescence duration by 2.6 ± 0.1 days per °C. The current trajectories toward an earlier onset and slowed progression of senescence affect Northern Hemisphere-wide trends in growing-season length and forest productivity.

Acclimation of phenology relieves leaf longevity constraints in deciduous forests

Leaf phenology is key for regulating total growing-season mass and energy fluxes. Long-term temporal trends towards earlier leaf unfolding are observed across Northern Hemisphere forests. Phenological dates also vary between years, whereby end-of-season (EOS) dates correlate positively with start-of-season (SOS) dates and negatively with growing-season total net CO2 assimilation (Anet). These associations have been interpreted as the effect of a constrained leaf longevity or of premature carbon (C) sink saturation-with far-reaching consequences for long-term phenology projections under climate change and rising CO2. Here, we use multidecadal ground and remote-sensing observations to show that the relationships between Anet and EOS are opposite at the interannual and the decadal time scales. A decadal trend towards later EOS persists in parallel with a trend towards increasing Anet-in spite of the negative Anet-EOS relationship at the interannual scale. This finding is robust against the use of diverse observations and models. Results indicate that acclimation of phenology has enabled plants to transcend a constrained leaf longevity or premature C sink saturation over the course of several decades, leading to a more effective use of available light and a sustained extension of the vegetation CO2 uptake season over time.

Impact of microclimatic conditions and resource availability on spring and autumn phenology of temperate tree seedlings

Microclimatic effects (light, temperature) are often neglected in phenological studies and little information is known about the impact of resource availability (nutrient and water) on tree's phenological cycles. Here we experimentally studied spring and autumn phenology in four temperate trees in response to changes in bud albedo (white-painted vs black-painted buds), light conditions (nonshaded vs c. 70% shaded), water availability (irrigated, control and reduced precipitation) and nutrients (low vs high availability). We found that higher bud albedo or shade delayed budburst (up to +12 d), indicating that temperature is sensed locally within each bud. Leaf senescence was delayed by high nutrient availability (up to +7 d) and shade conditions (up to +39 d) in all species, except oak. Autumn phenological responses to summer droughts depended on species, with a delay for cherry (+7 d) and an advance for beech (-7 d). The strong phenological effects of bud albedo and light exposure reveal an important role of microclimatic variation on phenology. In addition to the temperature and photoperiod effects, our results suggest a tight interplay between source and sink processes in regulating the end of the seasonal vegetation cycle, which can be largely influenced by resource availability (light, water and nutrients).

The within-population variability of leaf spring and autumn phenology is influenced by temperature in temperate deciduous trees

Leaf phenology is a major driver of ecosystem functioning in temperate forests and a robust indicator of climate change. Both the inter-annual and inter-population variability of leaf phenology have received much attention in the literature; in contrast, the within-population variability of leaf phenology has been far less studied. Beyond its impact on individual tree physiological processes, the within-population variability of leaf phenology can affect the estimation of the average budburst or leaf senescence dates at the population scale. Here, we monitored the progress of spring and autumn leaf phenology over 14 tree populations (9 tree species) in six European forests over the period of 2011 to 2018 (yielding 16 site-years of data for spring, 14 for autumn). We monitored 27 to 512 (with a median of 62) individuals per population. We quantified the within-population variability of leaf phenology as the standard deviation of the distribution of individual dates of budburst or leaf senescence (SD_BBi and SD_LSi, respectively). Given the natural variability of phenological dates occurring in our tree populations, we estimated from the data that a minimum sample size of 28 (resp. 23) individuals, are required to estimate SD_BBi (resp. SD_LSi) with a precision of 3 (resp. 7) days. The within-population of leaf senescence (average SD_LSi = 8.5 days) was on average two times larger than for budburst (average SD_BBi = 4.0 days). We evidenced that warmer temperature during the budburst period and a late average budburst date were associated with a lower SD_BBi, as a result of a quicker spread of budburst in tree populations, with a strong species effect. Regarding autumn phenology, we observed that later senescence and warm temperatures during the senescence period were linked with a high SD_LSi, with a strong species effect. The shares of variance explained by our models were modest suggesting that other factors likely influence the within-population variation in leaf phenology. For instance, a detailed analysis revealed that summer temperatures were negatively correlated with a lower SD_LSi.

Increased growing-season productivity drives earlier autumn leaf senescence in temperate trees

Changes in the growing-season lengths of temperate trees greatly affect biotic interactions and global carbon balance. Yet future growing-season trajectories remain highly uncertain because the environmental drivers of autumn leaf senescence are poorly understood. Using experiments and long-term observations, we show that increases in spring and summer productivity due to elevated carbon dioxide, temperature, or light levels drive earlier senescence. Accounting for this effect improved the accuracy of senescence predictions by 27 to 42% and reversed future predictions from a previously expected 2- to 3-week delay over the rest of the century to an advance of 3 to 6 days. These findings demonstrate the critical role of sink limitation in governing the end of seasonal activity and reveal important constraints on future growing-season lengths and carbon uptake of trees.

Why don't phenophase dates in the current year affect the same phenophase dates in the following year?

Examining whether a phenophase occurrence date in the current year affects the same phenophase occurrence date in the following year is crucial for developing cross-year phenological prediction models. Here, we carried out correlation analyses between leaf unfolding start (LUS)/leaf fall end (LFE) dates in the current and following years for four dominant tree species in temperate northern China from 1981 to 2012. Then, we calculated the recurrence intervals of LUS and LFE between two adjacent years for each species. Moreover, we investigated temperature effects on LUS/LFE dates, growing season and non-growing season lengths. Results show that correlation coefficients between LUS/LFE dates in the current and following years are nonsignificant at most stations. The recurrence interval of a phenophase has slight interannual variation and correlates significantly (and negatively) with the phenophase occurrence date of the current year. Further analyses indicate that LUS dates correlate significantly (and negatively) with spring mean temperatures, while LFE dates correlate significantly (and positively) with autumn mean temperatures, but negatively with growing season mean temperatures. In addition, spring mean temperatures can influence growing season length by controlling LUS date but cannot influence the following non-growing season length. Similarly, autumn mean temperatures and growing season mean temperatures can influence the subsequent non-growing season length but cannot influence the growing season length of the following year. Our study highlights that recurrence interval and time restrictions in the effects of seasonal temperatures on phenophase dates are the main environmental causes of nonsignificant correlations between phenophase occurrence dates in the current and following years.

Modeling leaf senescence of deciduous tree species in Europe

Autumnal leaf senescence signals the end of photosynthetic activities in temperate deciduous trees and consequently exerts a strong control on various ecological processes. Predicting leaf senescence dates (LSD) with high accuracy is thus a prerequisite for better understanding the climate-ecosystem interactions. However, modeling LSD at large spatial and temporal scales is challenging. In this study, first, we used 19972 site-year records (848 sites and four deciduous tree species) from the PAN European Phenology network to calibrate and evaluate six leaf senescence models during the period 1980-2013. Second, we extended the spatial analysis by repeating the procedure across Europe using satellite-derived end of growing season and a forest map. Overall, we found that models that considered photoperiod and temperature interactions outperformed models using simple temperature or photoperiod thresholds for Betula pendula, Fagus sylvatica and Quercus robur. On the contrary, no model displayed reasonable predictions for Aesculus hippocastanum. This inter-model comparison indicates that, contrary to expectation, photoperiod does not significantly modulate the accumulation of cooling degree days (CDD). On the other hand, considering the carryover effect of leaf unfolding date could promote the models' predictability. The CDD models generally matched the observed LSD at species level and its interannual variation, but were limited in explaining the inter-site variations, indicating that other environmental cues need to be considered in future model development. The discrepancies remaining between model simulations and observations highlight the need of manipulation studies to elucidate the mechanisms behind the leaf senescence process and to make current models more realistic.