Spring phenology of temperate forest trees has advanced substantially over the last decades due to climate warming, but this advancement is slowing down despite continuous temperature rise. The ...decline in spring advancement is often attributed to winter warming, which could reduce chilling and thus delay dormancy release. However, mechanistic evidence of a phenological response to warmer winter temperatures is missing. We aimed to understand the contrasting effects of warming on plants leaf phenology and to disentangle temperature effects during different seasons. With a series of monthly experimental warming by ca. 2.4°C from late summer until spring, we quantified phenological responses of forest tree to warming for each month separately, using seedlings of four common European tree species. To reveal the underlying mechanism, we tracked the development of dormancy depth under ambient conditions as well as directly after each experimental warming. In addition, we quantified the temperature response of leaf senescence. As expected, warmer spring temperatures led to earlier leaf‐out. The advancing effect of warming started already in January and increased towards the time of flushing, reaching 2.5 days/°C. Most interestingly, however, warming in October had the opposite effect and delayed spring phenology by 2.4 days/°C on average; despite six months between the warming and the flushing. The switch between the delaying and advancing effect occurred already in December. We conclude that not warmer winters but rather the shortening of winter, i.e., warming in autumn, is a major reason for the decline in spring phenology.
Warm temperatures during spring accelerate leaf flushing in temperate trees. But why is this advancing effect declining? We experimentally investigated how leaf‐out dates are impacted by temperatures during the entire preceding non‐growing season, separately for every month. We found that in autumn, before the onset of leaf coloration, temperature has a surprisingly strong impact. Warming during this time delays leaf senescence and the induction of bud dormancy, resulting in a delay of next year's spring leaf phenology.
•Phenology of wood shows high variability across locations, species and years.•The coupling between leaf- and wood growth phenology has few generic trends.•Temperature and climate are key drivers of ...wood growth phenology variability.•Summer droughts shortens the wood-growing season.
Wood growth phenology of temperate deciduous trees is less studied than leaf phenology, hindering the understanding of their interaction. In order to describe the variability of wood growth and leaf phenology across locations, species and years, we performed phenological observations of both xylem formation and leaf development in three typical temperate forest areas in Western Europe (Northern Spain, Belgium and Southern Norway) for four common deciduous tree species (Fagus sylvatica L., Betula pendula Roth., Populus tremula L. and Quercus robur L.) in 2018, 2019 and 2020, with only beech and birch being studied in the final year.
The earliest cambial reactivation in spring occurred at the Belgian stands while the end of cambial activity and wood growth cessation generally occurred first in Norway. Results did not show much consistency across species, sites or years and lacked general patterns, except for the end of cambial activity, which occurred generally first in birch. For all species, the site variation in phenophases (up to three months) was substantially larger than the inter-annual variability (up to six weeks). The timeline of bud-burst and cambium reactivation, as well as of foliar senescence and cessation of wood growth, were variable across species even with the same type of wood porosity. Our results suggest that wood growth and leaf phenology are less well connected than previously thought. Linear models showed that temperature is the dominant driver of wood growth phenology, but with climate zone also having an effect, especially at the start of the growing season. Drought conditions, on the other hand, have a larger effect on the timing of wood growth cessation. Our comprehensive analysis represents the first large regional assessment of wood growth phenology in common European deciduous tree species, providing not only new fundamental insights but also a unique dataset for future modelling applications.
Functional biogeography of angiosperms Zanne, Amy E.; Pearse, William D.; Cornwell, William K. ...
The New phytologist,
06/2018, Letnik:
218, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Nonlinear relationships between species and their environments are believed common in ecology and evolution, including during angiosperms’ rise to dominance. Early angiosperms are thought of as woody ...evergreens restricted to warm, wet habitats. They have since expanded into numerous cold and dry places. This expansion may have included transitions across important environmental thresholds.
To understand linear and nonlinear relationships between angiosperm structure and biogeographic distributions, we integrated large datasets of growth habits, conduit sizes, leaf phenologies, evolutionary histories, and environmental limits. We consider current-day patterns and develop a new evolutionary model to investigate processes that created them.
The macroecological pattern was clear: herbs had lower minimum temperature and precipitation limits. In woody species, conduit sizes were smaller in evergreens and related to species’ minimum temperatures. Across evolutionary timescales, our new modeling approach found conduit sizes in deciduous species decreased linearly with minimum temperature limits. By contrast, evergreen species had a sigmoidal relationship with minimum temperature limits and an inflection overlapping freezing.
These results suggest freezing represented an important threshold for evergreen but not deciduous woody angiosperms. Global success of angiosperms appears tied to a small set of alternative solutions when faced with a novel environmental threshold.
•Vegetation season is up to 2 weeks longer in lower than upper tree crown.•Leaf unfolding rather than bud break timing differs vertically within tree crowns.•Faster leaf unfolding represents ...light-use optimization in lower crown parts.•Earlier senescence in upper vs lower crowns is driven by microclimatic gradients.
Tree crowns experience strong vertical microclimatic gradients, particularly in light availability. Surprisingly, little is known about whether these gradients cause within-crown variation in leaf phenology and whether such variations represent different light-use strategies of sun- and shade leaves.
In a temperate mixed forest at the Swiss Canopy Crane II site in Switzerland, we measured over three years the annual leaf phenology in the upper and lower crowns of mature trees from six broadleaved and three conifer species. We further recorded the microclimate (temperature, humidity, light) continuously in various positions within the canopy.
We found microclimatic canopy gradients to be strongest during summer, but negligible in winter and spring, indicating that any phenological gradients in autumn, but not in spring, might be driven by microclimatic differences. Budbreak timing did not differ within the crowns of any of the broadleaved trees. However, in the three species with deeper crowns, leaf unfolding was up to 10 days faster in the lower crown but showed no difference in the more shallow-crowned species. Surprisingly, only the evergreen conifers Abies alba and Picea abies showed earlier bud break in the lower crowns. In autumn, senescence in all broadleaved species progressed from the upper crown downwards, resulting in up to two weeks longer vegetation seasons in the lower crown.
With this first broad assessment of within-tree phenology, we show how microclimatic gradients and different light-use strategies lead to a considerable variability of within-crown phenological gradients. We interpret the faster leaf unfolding in the lower crown of three broadleaved species as a shade avoidance strategy, allowing shade branches to improve their C balance early in the season. In contrast, longer retention of lower leaves in autumn is unlikely to significantly improve the C balance, and more likely caused by higher summer temperature and irradiance in the upper leaves.
In temperate forests, autumn leaf phenology signals the end of leaf growing season and shows large variability across tree-crowns, which importantly mediates photosynthetic seasonality, hydrological ...regulation, and nutrient cycling of forest ecosystems. However, critical challenges remain with the monitoring of autumn leaf phenology at the tree-crown scale due to the lack of spatially explicit information for individual tree-crowns and high (spatial and temporal) resolution observations with nadir view. Recent availability of the PlanetScope constellation with a 3 m spatial resolution and near-daily nadir view coverage might help address these observational challenges, but remains underexplored. Here we developed an integration of PlanetScope with drone observations for improved monitoring of crown-scale autumn leaf phenology in a temperate forest in Northeast China. This integration includes: 1) visual identification of individual tree-crowns (and species) from drone observations; 2) extraction of time series of PlanetScope vegetation indices (VIs) for each identified tree-crown; 3) derivation of three metrics of autumn leaf phenology from the extracted VI time series, including the start of fall (SOF), middle of fall (MOF), and end of fall (EOF); and 4) accuracy assessments of the PlanetScope-derived phenology metrics with reference from local phenocams. Our results show that (1) the PlanetScope-drone integration captures large inter-crown phenological variations, with a range of 28 days, 25 days, and 30 days for SOF, MOF, and EOF, respectively, (2) the extracted crown-level phenology metrics strongly agree with those derived from local phenocams, with a root-mean-square-error (RMSE) of 4.1 days, 3.0 days and 5.4 days for SOF, MOF, and EOF, respectively, and (3) PlanetScope maps large variations in autumn leaf phenology over the entire forest landscape with spatially explicit information. These results demonstrate the ability of our proposed method in monitoring the large spatial heterogeneity of crown-scale autumn leaf phenology in the temperate forest, suggesting the potential of using high-resolution satellites to advance crown-scale phenology studies over large geographical areas.
In tropical forests, leaf phenology—particularly the pronounced dry-season green-up—strongly regulates biogeochemical cycles of carbon and water fluxes. However, uncertainties remain in the ...understanding of tropical forest leaf phenology at different spatial scales. Phenocams accurately characterize leaf phenology at the crown and ecosystem scales but are limited to a few sites and time spans of a few years. Time-series satellite observations might fill this gap, but the commonly used satellites (e.g. MODIS, Landsat and Sentinel-2) have resolutions too coarse to characterize single crowns. To resolve this observational challenge, we used the PlanetScope constellation with a 3 m resolution and near daily nadir-view coverage. We first developed a rigorous method to cross-calibrate PlanetScope surface reflectance using daily BRDF-adjusted MODIS as the reference. We then used linear spectral unmixing of calibrated PlanetScope to obtain dry-season change in the fractional cover of green vegetation (GV) and non-photosynthetic vegetation (NPV) at the PlanetScope pixel level. We used the Central Amazon Tapajos National Forest k67 site, as all necessary data (from field to phenocam and satellite observations) was available. For this proof of concept, we chose a set of 22 dates of PlanetScope measurements in 2018 and 16 in 2019, all from the six drier months of the year to provide the highest possible cloud-free temporal resolution. Our results show that MODIS-calibrated dry-season PlanetScope data (1) accurately assessed seasonal changes in ecosystem-scale and crown-scale spectral reflectance; (2) detected an increase in ecosystem-scale GV fraction (and a decrease in NPV fraction) from June to November of both years, consistent with local phenocam observations with R2 around 0.8; and (3) monitored large seasonal trend variability in crown-scale NPV fraction. Our results highlight the potential of integrating multi-scale satellite observations to extend fine-scale leaf phenology monitoring beyond the spatial limits of phenocams.
•A robust method cross-calibrated PlanetScope using BRDF-adjusted MODIS.•Calibrated data accurately assessed ecosystem-scale and crown-scale reflectance.•A dry-season decrease in non-photosynthetic vegetation (NPV) fraction was detected.•Large seasonal trend variability in crown-scale NPV fraction was quantified.
This study investigates the usefulness of MODIS (Moderate Resolution Imaging Spectroradiometer) satellite imagery for determining the start, end, and length of the growing season of selected ...deciduous tree species. Vegetation indices derived from satellite imagery provide consistent observations in a similar temporal sequence and are useful for determining phenological phases. Using time series of NDVI (Normalised Difference Vegetation Index) vegetation index from MODIS imagery, phenological patterns were detected at several points in Slovenia and different approaches to determine seasonal phases were compared. In addition, the derived seasonal phases with field phenological and meteorological data were also compared. It has been found that the success of determining phenological phases from satellite imagery depends on many factors: the spatial resolution of the satellite data, the smoothing method for the time series data, the method for determining phenological parameters, and the field data used for comparison. The results of the study show that phenological phases determined by using MODIS data with a resolution of 250 m best match the phenological data maintained by the Slovenian Forestry Institute using the mean seasonal values method.
Remote sensing of forests has become increasingly accessible with the use of unoccupied aerial vehicles (UAV), along with deep learning, allowing for repeated high-resolution imagery and the ...capturing of phenological changes at larger spatial and temporal scales. In temperate forests during autumn, leaf senescence occurs when leaves change colour and drop. However, the influence of leaf senescence in temperate forests on tree species segmentation using a Convolutional Neural Network (CNN) has not yet been evaluated. Here, we acquired high-resolution UAV imagery over a temperate forest in Quebec, Canada on seven occasions between May and October 2021. We segmented and labelled 23,000 tree crowns from 14 different classes to train and validate a CNN for each imagery acquisition. The CNN-based segmentation showed the highest F1-score (0.72) at the start of leaf colouring in early September and the lowest F1-score (0.61) at peak fall colouring in early October. The timing of the events occurring during senescence, such as leaf colouring and leaf fall, varied substantially between and within species and according to environmental conditions, leading to higher variability in the remotely sensed signal. Deciduous and evergreen tree species that presented distinctive and less temporally-variable traits between individuals were better classified. While tree segmentation in a heterogenous forest remains challenging, UAV imagery and deep learning show high potential in mapping tree species. Our results from a temperate forest with strong leaf colour changes during autumn senescence show that the best performance for tree species segmentation occurs at the onset of this colour change.
•Effect of leaf phenology on tree segmentation from drone imagery is not well known.•U-Net semantic segmentation yieled good tree-cover segmentation for most species.•The best performance was found at the onset of autumn colours.•Species with less heterogenous crowns between individuals were better segmented.•A dataset of 23,000 tree crown annotations over a growing season was generated.
•Drought advances cessation of wood growth in Betula pendula.•Drought can delay autumn leaf phenology.•A potential drought lag-effect was found on autumn leaf phenology in the next year.•Wood growth ...is more sensitive to site fertility than autumn leaf phenology.
Historically, the autumn dynamics of deciduous forest trees have not been investigated in detail. However, autumn phenological events, like onset of loss of canopy greenness (OLCG), onset of foliar senescence (OFS) and cessation of wood growth (CWG), have an important impact on tree radial growth and the entire ecosystem's seasonal dynamics. Here, we monitored the leaf and wood phenological events of silver birch (Betula pendula) at four different sites in Ås, southeastern Norway: (a) a natural mature stand, (b) a plantation on former agricultural ground, (c) young natural trees, and (d) young trees in pots under different fertilization levels. The study took place over four consecutive years (from 2017 to 2020), with a particular focus on 2018, a year in which there was a severe summer drought, and the next year, 2019, which featured more normal conditions. First, we provided a description of birch phenology within its mid-north distributional. Second, we showed that drought advanced CWG by about 5 to 6 weeks and it delayed OLCG and OFS up to 30 days. Third, we observed an unexpected advance in OLCG in 2019 compared to 2018 (30 days) and 2020 (14 days). OFS presented similar dynamics as OLCG, whereas CWG was advanced only in 2018. These findings might indicate lag-effects of severe drought on the next year autumn leaf phenology but not on wood growth. On the other hand, the comparison between the natural stand and the plantation showed that, under drought conditions, wood growth is more sensitive to site fertility than autumn leaf phenology. In summary, our study elucidated the autumn dynamics of an important deciduous forest species in the northern temperate zone and showed unexpected impacts of a severely dry and warm summer on the current and next year leaf phenology.
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