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 (SDBBi and SDLSi, 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 SDBBi (resp. SDLSi) with a precision of 3 (resp. 7) days. The within-population of leaf senescence (average SDLSi = 8.5 days) was on average two times larger than for budburst (average SDBBi = 4.0 days). We evidenced that warmer temperature during the budburst period and a late average budburst date were associated with a lower SDBBi, 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 SDLSi, 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 SDLSi.

"Green pointillism": detecting the within-population variability of budburst in temperate deciduous trees with phenological cameras.

Phenological cameras have been used over a decade for identifying plant phenological markers (budburst, leaf senescence) and more generally the greenness dynamics of forest canopies. The analysis is usually carried out over the full camera field of view, with no particular analysis of the variability of phenological markers among trees. Here we show that images produced by phenological cameras can be used to quantify the within-population variability of budburst (WPVbb) in temperate deciduous forests. Using seven site-years of image analyses, we report a strong correlation (r2 = 0.97) between the WPVbb determined with a phenological camera and its quantification through ground observation. We show that WPVbb varies strongly (by a factor of 4) from year to year in a given population and that those variations are linked with temperature conditions during the budburst period, with colder springs associated to a higher differentiation of budburst (higher WPVbb) among trees. Deploying our approach at the continental scale, i.e., throughout phenological cameras networks, would improve the understanding of the spatial (across populations) and temporal (across years) variations of WPVbb, which have strong implications on forest functioning, tree fitness and phenological modelling.

Linking phytoplankton pigment composition and optical properties: A framework for developing remote-sensing metrics for monitoring cyanobacteria.

This study has been performed in the framework of a research program aiming to develop a low-cost aerial sensor for the monitoring of cyanobacteria in freshwater ecosystems that could be used for early detection. Several empirical and mechanistic remote-sensing tools have been already developed and tested at large scales and have proven useful in monitoring cyanobacterial blooms. However, the effectiveness of these tools for early detection is hard to assess because such work requires the detection of low concentrations of characteristic pigments amid complex ecosystems exhibiting several confounding factors (turbidity, blooms of other species, etc.). We developed a framework for performing high-throughput measurements of the absorbance and reflectance of small volumes (∼ = 20 mL) of controlled mixtures of phytoplankton species and studied the potential of this framework to validate remote-sensing proxies of cyanobacteria concentration. The absorption and reflectance spectra of single and multiple cultures carried a specific signal that allowed for the quantitative analysis of culture mixes. This specific signal was shown to be related to known pigment absorbance spectra. The concentrations of chlorophyll-a and -b, phycocyanin and phycoerythrin could be obtained from direct absorbance measurements and were correlated with the concentration obtained after pigment extraction (R2 ≥ 0.96 for all pigments). A systematic test of every possible two-band and three-band normalized difference between optical indices was then performed, and the coincidental correlation with chlorophyll-b (absent in cyanobacteria) was used as an indicator of non-specificity. Two-band indices were shown to suffer from non-specificity issues and could not yield strong and specific relationships with phycocyanin or phycoerythrin (maximum R2 < 0.5). On the other hand, the three-band modified normalized difference indices yielded strong specific relationships (R2 > 0.8).

Management Zone Delineation for Winegrape Selective Harvesting Based on Fluorescence-Sensor Mapping of Grape Skin Anthocyanins.

We analyzed the potential of non-destructive optical sensing of grape skin anthocyanins for selective harvesting in precision viticulture. We measured anthocyanins by a hand-held fluorescence optical sensor on a 7 ha Sangiovese vineyard plot in central Italy. Optical indices obtained by the sensor were calibrated for the transformation in units of anthocyanins per berry mass, i.e., milligrams per gram of berry fresh weight. A full protocol for optimal data filtration, interpolation, and homogeneous zone delineation based on a very large number of optical measurements is proposed. Both the single signal-based fluorescence index (ANTHR) and the two signal ratio-based index (ANTHRG) can be used for Sangiovese grapes. Significant separations of grape-quality batches were obtained by several methods of data classification and zone delineations. Basic statistical criteria were as efficient as the K-means clustering. The best separations were obtained for three classes of grape skin anthocyanin.

Potential use of the PRI and active fluorescence for the diagnosis of the physiological state of plants under ozone exposure and high atmospheric vapor pressure deficit.

Assessing photosynthesis rates with remote sensing is important for tracking the physiological state of plants. The photochemical reflectance index (PRI) is a good estimator of short-term light-use efficiency (LUE) at the leaf scale but its responses to environmental factors are poorly understood. In this study, we assessed changes in the responses of the PRI to ozone exposure and to an increase in atmospheric drought (separately and combined) in oak (Quercus robur) and holm oak (Quercus ilex) that were planted in climatic cells under controlled conditions. The aim was to evaluate the ability of the PRI as a relevant indicator to assess the impact of abiotic factors on photosynthesis. Leaf-scale measurements of biochemical, physiological and spectral properties, including the PRI in dim light on dark-adapted leaves (PRI0), kinetics of PRI responses to PAR variations (photosynthetically active radiation), and leaf chlorophyll fluorescence parameters were performed. The results show that PRI0 is a good proxy of the leaf chlorophyll content, and is correlated to chlorophyll fluorescence parameters on dark adapted leaves (Fo, Fm). The correction of the PRI from the leaf chlorophyll content variations (PRIc) significantly improves correlations between the PRI and NPQ (non-photochemical quenching). The variability of PARsat (estimated PAR value at PRI saturation using PRI vs. PAR relationships) depends on ozone exposure and on the increase in atmospheric vapor pressure deficit. For Quercus robur, results highlight that PARsat is linked to abiotic stress indicating that the PRI may be used as a relevant indicator of abiotic factors limiting the photosynthesis. Quercus ilex did not show significant variability in PRI0 and PARsat, which suggest that it is a more drought resistant species than Q. robur.

Environmental control of carbon allocation matters for modelling forest growth.

We aimed to evaluate the importance of modulations of within-tree carbon (C) allocation by water and low-temperature stress for the prediction of annual forest growth with a process-based model. A new C allocation scheme was implemented in the CASTANEA model that accounts for lagged and direct environmental controls of C allocation. Different approaches (static vs dynamic) to modelling C allocation were then compared in a model-data fusion procedure, using satellite-derived leaf production estimates and biometric measurements at c. 104 sites. The modelling of the environmental control of C allocation significantly improved the ability of CASTANEA to predict the spatial and year-to-year variability of aboveground forest growth along regional gradients. A significant effect of the previous year's water stress on the C allocation to leaves and wood was reported. Our results also are consistent with a prominent role of the environmental modulation of sink demand in the wood growth of the studied species. Data available at large scales can inform forest models about the processes driving annual and seasonal C allocation. Our results call for a greater consideration of C allocation drivers, especially sink-demand fluctuations, for the simulations of current and future forest productivity with process-based models.

Explaining the variability of the photochemical reflectance index (PRI) at the canopy-scale: Disentangling the effects of phenological and physiological changes.

Assessing photosynthesis rates at the ecosystem scale and over large regions is important for tracking the global carbon cycle and remote sensing has provided new and useful approaches for performing this assessment. The photochemical reflectance index (PRI) is a good estimator of short-term light-use efficiency (LUE) at the leaf scale; however, confounding factors appear at larger temporal and spatial scales. In this study, canopy-scale PRI variability was investigated for three species (Fagus sylvatica L., Quercus robur L. and Pinus sylvestris L.) growing under contrasting soil moisture conditions. Throughout the growing season, no significant differences in chlorophyll content and in violaxanthin, antheraxanthin and zeaxanthin were found between species or treatments. The daily PRI vs PAR (photosynthetically active radiation) relationships were determined using continuous measurements obtained at high frequency throughout the entire growing season, from early spring budburst to later autumn senescence, and were used to deconvolute the physiological PRI variability related to LUE variations due to phenological variability and related to temporal changes in the biochemical and structural canopy attributes. The PRI vs PAR relationship is used to show that the canopy-scale PRI measured at low radiation depends on the chlorophyll content of the canopy. The range of PRI variations at an intra-daily scale and the dynamics of the xanthophyll pool do not vary between days, which suggests that the PRI responds to a xanthophyll ratio. The PAR values at PRI saturation are mainly related to the canopy chlorophyll content during budburst and senescence and to the soil moisture content when the chlorophyll content is no longer a limiting factor. This parameter is significantly lower in the oak species that experience less stress from variations in soil moisture and is species dependant. These results provide new insights regarding the analysis and the meaning of PRI variability as a proxy for LUE at the canopy scale.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

BACKGROUND AND AIMS: The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. METHODS: The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. KEY RESULTS: The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. CONCLUSIONS: This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.

Tree age-related effects on sun acclimated leaves in a chronosequence of beech (Fagus sylvatica) stands.

The assessment of the effect of tree age on leaves is usually limited by the difficulty of sampling sun leaves from tall ageing trees. In this study, we investigated tree age-related effects on sun leaves in a chronosequence of beech (Fagus sylvatica L.) stands. The effects of stand age on leaf mass to area ratio (LMA), chlorophyll (Chl), epidermal polyphenols (EPhen), nitrogen and carbon contents in sun leaves were investigated in 17 even-aged stands distributed into six age classes (14-175 years old). Chl and EPhen were assessed in vivo with SPAD and Dualex portable leaf-clips respectively. Leaves were sampled by shooting and sun leaves were identified based on criteria obtained from a vertical profile of the ratio abaxial vs adaxial EPhen across the canopy. Sun leaves were characterised by a high and similar adaxial and abaxial EPhen contents, high LMA value and low mass-based Chl content. These sun leaf characteristics, together with leaf nitrogen and carbon contents, were not significantly affected by stand age. Along the chronosequence, beech trees invested a stable fraction of leaf mass into nitrogen, carbon, Chl and EPhen with decreasing leaf size, i.e. dry mass and area.

Modeling annual production and carbon fluxes of a large managed temperate forest using forest inventories, satellite data and field measurements.

We evaluated annual productivity and carbon fluxes over the Fontainebleau forest, a large heterogeneous forest region of 17,000 ha, in terms of species composition, canopy structure, stand age, soil type and water and mineral resources. The model is a physiological process-based forest ecosystem model coupled with an allocation model and a soil model. The simulations were done stand by stand, i.e., 2992 forest management units of simulation. Some input parameters that are spatially variable and to which the model is sensitive were calculated for each stand from forest inventory attributes, a network of 8800 soil pits, satellite data and field measurements. These parameters are: (1) vegetation attributes: species, age, height, maximal leaf area index of the year, aboveground biomass and foliar nitrogen content; and (2) soil attributes: available soil water capacity, soil depth and soil carbon content. Main outputs of the simulations are wood production and carbon fluxes on a daily to yearly basis. Results showed that the forest is a carbon sink, with a net ecosystem exchange of 371 g C m(-2) year(-1). Net primary productivity is estimated at 630 g C m(-2) year(-1) over the entire forest. Reasonably good agreement was found between simulated trunk relative growth rate (2.74%) and regional production estimated from the National Forest Inventory (IFN) (2.52%), as well as between simulated and measured annual wood production at the forest scale (about 71,000 and 68,000 m(3) year(-1), respectively). Results are discussed species by species.