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[bullet] BACKGROUND: and Aims In a leaf canopy, there is a turnover of leaves; i.e. they are produced, senesce and fall. These processes determine the amount of leaf area in the canopy, which in turn determines canopy photosynthesis. The turnover rate of leaves is affected by environmental factors and is different among species. This mini-review discusses factors responsible for leaf dynamics in plant canopies, focusing on the role of nitrogen. [bullet] Scope Leaf production is supported by canopy photosynthesis that is determined by distribution of light and leaf nitrogen. Leaf nitrogen determines photosynthetic capacity. Nitrogen taken up from roots is allocated to new leaves. When leaves age or their light availability is lowered, part of the leaf nitrogen is resorbed. Resorbed nitrogen is re-utilized in new organs and the rest is lost with dead leaves. The sink-source balance is important in the regulation of leaf senescence. Several models have been proposed to predict response to environmental changes. A mathematical model that incorporated nitrogen use for photosynthesis explained well the variations in leaf lifespan within and between species. [bullet] CONCLUSION: When leaf turnover is at a steady state, the ratio of biomass production to nitrogen uptake is equal to the ratio of litter fall to nitrogen loss, which is an inverse of the nitrogen concentration in dead leaves. Thus nitrogen concentration in dead leaves (nitrogen resorption proficiency) and nitrogen availability in the soil determine the rate of photosynthesis in the canopy. Dynamics of leaves are regulated so as to maximize carbon gain and resource-use efficiency of the plant.

This paper introduces the Global Multilayer Canopy OPTimization (GMC‐OPT) model, designed to scale sub‐daily leaf‐level carbon fluxes to the canopy level. The model integrates three core components: canopy radiative transfer, optimization‐based physiology, and energy balance. This study highlights the model's simulation of gross primary productivity (GPP), with a novel focus on vertically resolved radiation fields, photosynthetic capacity, and associated physiological processes. Specifically, the model accounts for: (a) sub‐daily stomatal conductance optimization; (b) sub‐daily timing of photosynthetic capacity optimization, and (c) vertical positioning of seasonal leaf turnover. After benchmarking against flux tower GPP data, GMC‐OPT achieves high agreement with the tower GPP at annual, monthly, and hourly scales. Model calibration suggests a lower‐than‐expected efficiency in converting absorbed photosynthetically active radiation (APAR), primarily because not all APAR reaches chlorophyll. In addition, the model predicts a decrease in photosynthetic capacity from the top to the bottom of the canopy, with vertical acclimation becoming less responsive under high light intensities at the upper canopy. The model further reveals distinct plant functional type strategies on seasonal acclimation due to vertical leaf turnover. Tree‐dominated biomes such as needleleaf and mixed forests tend to prioritize light harvesting, while non‐tree biomes do not. Deciduous broadleaf forests maintain a relatively constant leaf and canopy photosynthetic capacity through leaf turnover, whereas biomes such as evergreen broadleaf forests and woody savannas often reallocate nutrients within existing leaves through acclimation. GMC‐OPT promises a powerful diagnostic tool for exploring interactions among carbon, water, nutrients, and energy in a changing environment. Plain Language Summary A novel framework called Global Multilayer Canopy OPTimization (GMC‐OPT) is developed for scaling hourly leaf photosynthesis to the canopy level. The model consists of three interconnected components: radiative transfer, physiology, and energy balance. GMC‐OPT explicitly incorporates the canopy's radiation field and accounts for the effects of vertical structure on photosynthetic acclimation across sub‐daily and seasonal timescales. Specifically, it determines the sub‐daily timing of photosynthetic capacity acclimation and how seasonal vertical acclimation is shaped by the position of leaf turnover. The model provides valuable insights into the impact of structural changes on plant photosynthesis and highlights how different plant functional types respond to and utilize these changes. GMC‐OPT GPP shows high agreement with FLUXNET2015 eddy covariance‐derived GPP at hourly, monthly, and annual scales. It can also serve as a valuable tool for depicting various within‐canopy photosynthetic characteristics. Key Points The multilayer Global Multilayer Canopy OPTimization (GMC‐OPT) model estimates leaf‐level carbon flux to the canopy level at sub‐daily scales GMC‐OPT highlights distinct plant functional type strategies in shaping seasonal canopy photosynthetic capacity through vertical leaf turnover GMC‐OPT agrees well with flux tower gross primary productivity, making it a promising diagnostic tool for understanding the canopy carbon, water, nutrient nexus

An excess of ozone (O3) is currently stressing plant ecosystems and may negatively affect the nutrient use of plants. Plants may modify leaf turnover rates and nutrient allocation at the organ level to counteract O3 damage. We investigated leaf turnover rate and allocation of primary (C, N, P, K) and secondary macronutrients (Ca, S, Mg) under various O3 treatments (ambient concentration, AA, with a daily hourly average of 35 ppb; 1.5 × AA; 2.0 × AA) and fertilization levels (N: 0 and 80 kg N ha−1 y−1; P: 0 and 80 kg N ha−1 y−1) in an O3-sensitive poplar clone (Oxford: Populus maximowiczii Henry × P. berolinensis Dippel) in a Free-Air Controlled Exposure (FACE) experiment. The results indicated that both fertilization and O3 had a significant impact on the nutrient content. Specifically, fertilization and O3 increased foliar C and N contents (+5.8% and +34.2%, respectively) and root Ca and Mg contents (+46.3% and +70.2%, respectively). Plants are known to increase the content of certain elements to mitigate the damage caused by high levels of O3. The leaf turnover rate was accelerated as a result of increased O3 exposure, indicating that O3 plays a main role in influencing this physiological parameter. A PCA result showed that O3 fumigation affected the overall allocation of primary and secondary elements depending on the organ (leaves, stems, roots). As a conclusion, such different patterns of element allocation in plant leaves in response to elevated O3 levels can have significant ecological implications.

Tropical forest phenology directly affects regional carbon cycles, but the relation between species‐specific and whole‐canopy phenology remains largely uncharacterized. We present a unique analysis of historical tropical tree phenology collected in the central Congo Basin, before large‐scale impacts of human‐induced climate change. Ground‐based long‐term (1937–1956) phenological observations of 140 tropical tree species are recovered, species‐specific phenological patterns analyzed and related to historical meteorological records, and scaled to characterize stand‐level canopy dynamics. High phenological variability within and across species and in climate–phenology relationships is observed. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species‐specific decoupling in time along a bi‐modal seasonality. The majority of the species remain evergreen, although central African forests experience relatively low rainfall. Annually a maximum of 1.5% of the canopy is in leaf senescence or leaf turnover, with overall phenological variability dominated by a few deciduous species, while substantial variability is attributed to asynchronous events of large and/or abundant trees. Our results underscore the importance of accounting for constituent signals in canopy‐wide scaling and the interpretation of remotely sensed phenology signals. Ground‐based long‐term (1937–1956) phenological observations of tropical tree species in the central Congo Basin are recovered and allow for the analysis of species‐specific phenological patterns. The onset of leaf phenophases in deciduous species was triggered by drought and light availability for a subset of species and showed a species‐specific decoupling in time along the bi‐modal seasonality. Few deciduous species dominate stand‐level canopy dynamics while substantial variability is attributed to asynchronous events of large and/or abundant trees.

A key issue in plant/herbivore interaction research is to understand which plant traits drive differences in herbivore damage. Variation in chemical, physical or phenological traits of plants may all modulate the degree of herbivore damage among species and individuals, yet the relative importance of these factors is still subject to debate, particularly in species‐rich systems such as tropical rain forests. To address this issue, we quantified leaf herbivore damage in 28 common tree species of the Yasuní forest dynamic plot (YFDP) in the Ecuadorian Amazon over 11 months. Census data from the YFDP allowed us to quantify several aspects of tree ecology potentially affecting herbivory including leaf turnover and spatial distribution patterns. We measured six chemical, eight physical and four ecological traits of the focal species. Using a combination of multivariate analyses and phylogenetic generalized linear regression model (PGLS), we assessed trade‐offs between physical and chemical traits and the relative effect of all these traits on leaf herbivore damage. Herbivore damage was highly variable among species and individuals, with leaves on average displaying damage over 13.4% (2.5–29.5%) of their area. We found no significant trade‐off between physical and chemical defences for the 28 studied tree species. Overall, leaf size, shearing resistance, cellulose, ash content and leaf size × ash were the best predictors of herbivore damage. Surprisingly, condensed tannins and latex did not significantly correlate with herbivore damage. In addition, we found no relationships between herbivory and local tree density. However, we did find a weak effect of tree clustering and strong effect of tree leaf turnover rates on herbivore damage. Synthesis. In the western Amazon, leaves are defended against herbivores through a combination of physical (toughness), chemical (toughness‐related elements), and phenological (rapid leaf replacement) characteristics that do not appear to be subject to obvious trade‐offs. Conventional strategies, such as condensed tannins or latex, do not seem to be strongly involved as a defence against herbivores in this community.

Spatial and temporal patterns of tropical leaf renewal are poorly understood and poorly parameterized in modern Earth System Models due to lack of data. Remote sensing has great potential for sampling leaf phenology across tropical landscapes but until now has been impeded by lack of ground-truthing, cloudiness, poor spatial resolution, and the cryptic nature of incremental leaf turnover in many tropical plants. To our knowledge, satellite data have never been used to monitor individual crown leaf phenology in the tropics, an innovation that would be a major breakthrough for individual and species-level ecology and improve climate change predictions for the tropics. In this paper, we assessed whether satellite data can detect leaf turnover for individual trees using ground observations of a candidate tropical tree species, Moabi (Baillonella toxisperma), which has a mega-crown visible from space. We identified and delineated Moabi crowns at Lopé NP, Gabon from satellite imagery using ground coordinates and extracted high spatial and temporal resolution, optical, and synthetic-aperture radar (SAR) timeseries data for each tree. We normalized these data relative to the surrounding forest canopy and combined them with concurrent monthly crown observations of new, mature, and senescent leaves recorded from the ground. We analyzed the relationship between satellite and ground observations using generalized linear mixed models (GLMMs). Ground observations of leaf turnover were significantly correlated with optical indices derived from Sentinel-2 optical data (the normalized difference vegetation index and the green leaf index), but not with SAR data derived from Sentinel-1. We demonstrate, perhaps for the first time, how the leaf phenology of individual large-canopied tropical trees can directly influence the spectral signature of satellite pixels through time. Additionally, while the level of uncertainty in our model predictions is still very high, we believe this study shows that we are near the threshold for orbital monitoring of individual crowns within tropical forests, even in challenging locations, such as cloudy Gabon. Further technical advances in remote sensing instruments into the spatial and temporal scales relevant to organismal biological processes will unlock great potential to improve our understanding of the Earth system.

Parental distance and plant density dependence of seedling leaf turnover and survival was examined to investigate predictions of the Janzen–Connell hypothesis. The focal study species, Shorea macroptera is a canopy tree species in a lowland rain forest in peninsular Malaysia. We found that the peak of the distribution of plants shifted from 3–6 m to 6–9 m during the course of the change from seedling to sapling stage. The leaf demography of the seedlings was influenced by their distance from the adult tree and also by the seedling density. Although significant density-and distance dependence in leaf production was not detected, seedling leaf loss decreased with distance from the parent tree and with seedling density. Similarly, leaf damage was not found to be distance-or density-dependent, but net leaf gain of seedlings increased with distance from the parent tree. Although no significant distance-or densitydependence was evident in terms of leaf damage, significant distance dependence of the net leaf gain was found. Thus, we concluded that positive distance dependence in the leaf turnover of seedlings may gradually contribute to a shift in the distribution pattern of the progeny through reductions in growth and survivorship.

1. Canopy photosynthesis models combined with optimization theory have been an important tool to understand environmental responses and interspecific variations in vegetation structure and functioning, but their predictions are often quantitatively incorrect. Although evolutionary game theory and the dynamic modelling of leaf turnover have been suggested useful to solve this problem, there is no model that combines these features. 2. Here, we present such a model of leaf area dynamics that incorporates game theory. 3. Leaf area index (LAI; leaf area per unit ground area) was predicted to increase with an increasing degree of interaction between genetically distinct neighbour plants in light interception. This implies that stands of clonal plants that consist of genetically identical daughter ramets have different LAI from other plants. LAI was also sensitive to the assumed vertical pattern of leaf shedding: LAI was predicted to increase with the degree to which leaves were assumed to be shed from higher positions in the canopy. Our model provides more realistic predictions of LAI than previous static optimization, dynamic optimization or static game theoretical models. 4. We suggest that both leaf dynamics and game theoretical considerations of plant competition are indispensable to scale from individual leaf traits to the structure and functioning of vegetation stands, especially in herbaceous species.

Question: Although the restinga vegetation lies adjacent to the species-rich Atlantic Rainforest, fewer species thrive due to low available resources of the sandy substrate. We asked whether there is a specific set of functional traits related to the ability to attain high dominance in a restinga dominated by a CAM photosynthesis tree.Location: Restinga of Jurubatiba National Park, north of the state of Rio de Janeiro, Brazil. Methods: We chose traits that are commonly used in large screenings, leaf mass per area (LMA), leaf longevity (LL) and leaf nitrogen concentration (LNC). We also measured the functional traits, midday leaf water potential (Ψmin), pressure-volume curves, nitrogen isotope discrimination (δ15N) and chlorophyll fluorescence. We compared species using ANOVA and ordination analysis. Results: The two most dominant species differed from subordinate species in terms of leaf succulence (SUC) and Ψmin. However, they were also significantly different from each other in LMA, SUC, leaf thickness and LNC. Ψmin and δ15N had the strongest loadings on the third ordination axis, which, despite explaining only 18.2% of total variance, was the only axis reflecting variation in species dominance. Conclusions: Despite high interspecific variation, the most common traits of the leaf economic spectrum were not directly associated with variation in species dominance. In contrast, the bulk modulus of elasticity, Ψmin and δ15N were important not only to track the connection between plant traits and environmental factors, but also between plant traits and community structure.

A model of dynamics of leaves and nitrogen is developed to predict the effect of environmental and ecophysiological factors on the structure and photosynthesis of a plant canopy. In the model, leaf area in the canopy increases by the production of new leaves, which is proportional to the canopy photosynthetic rate, with canopy nitrogen increasing with uptake of nitrogen from soil. Then the optimal leaf area index (LAI; leaf area per ground area) that maximizes canopy photosynthesis is calculated. If leaf area is produced in excess, old leaves are eliminated with their nitrogen as dead leaves. Consequently, a new canopy having an optimal LAI and an optimal amount of nitrogen is obtained. Repeating these processes gives canopy growth. The model provides predictions of optimal LAI, canopy photosynthetic rates, leaf life span, nitrogen use efficiency, and also the responses of these factors to changes in nitrogen and light availability. Canopies are predicted to have a larger LAI and a higher canopy photosynthetic rate at a steady state under higher nutrient and/or light availabilities. Effects of species characteristics, such as photosynthetic nitrogen use efficiency and leaf mass per area, are also evaluated. The model predicts many empirically observed patterns for ecophysiological traits across species.