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Information on the onset of leaf senescence in temperate deciduous trees and comparisons on its assessment methods are limited, hampering our understanding of autumn dynamics. We compare five field proxies, five remote sensing proxies and two data analysis approaches to assess leaf senescence onset at one main beech stand, two stands of oak and birch, and three ancillary stands of the same species in Belgium during 2017 and 2018. Across species and sites, onset of leaf senescence was not significantly different for the field proxies based on Chl leaf content and canopy coloration, except for an advanced canopy coloration during the extremely dry and warm 2018. Two remote sensing indices providedresults fully consistent with the field data. A significant lag emerged between leaf senescence onset and leaf fall, and when a threshold of 50% change in the seasonal variable under study (e.g. Chl content) was used to derive the leaf senescence onset. Our results provide unprecedented information on the quality and applicability of different proxies to assess leaf senescence onset in temperate deciduous trees. In addition, a sound base is offered to select the most suited methods for the different disciplines that need thistype of data.

Wild rice species are a source of genetic material for improving cultivated rice (Oryza sativa) and a means to understand its evolutionary history. Renewed interest in non‐steady‐state photosynthesis in crops has taken place due its potential in improving sustainable productivity. Variation was characterized for photosynthetic induction and relaxation at two leaf canopy levels in three rice species. The wild rice accessions had 16%–40% higher rates of leaf CO2 uptake (A) during photosynthetic induction relative to the O. sativa accession. However, O. sativa had an overall higher photosynthetic capacity when compared to accessions of its wild progenitors. Additionally, O. sativa had a faster stomatal closing response, resulting in higher intrinsic water‐use efficiency during high‐to‐low light transitions. Leaf position in the canopy had a significant effect on non‐steady‐state photosynthesis, but not steady‐state photosynthesis. The results show potential to utilize wild material to refine plant models and improve non‐steady‐state photosynthesis in cultivated rice for increased productivity. We characterized non‐steady state photosynthesis in an elite rice cultivar and single accessions of its two closest wild relatives and ancestors. The two wild accessions can adjust more rapidly and assimilate more CO2 during transitions from shade to full sunlight. This suggests considerable breeding potential in using this and broader biodiversity in improving rice productivity.

While the influences of droughts on Amazon rainforest have been extensively examined, little attention was paid to the extremely wet years characterized by low radiation which may limit the rainforest growth. Here, based on a series of satellite-observed vegetation and hydro-meteorological products, we found a two-stage canopy growth anomaly in the record-breaking wet year 2009, i.e. negative anomalies during April–July followed by positive ones during August–November. Our analysis suggests that, in April–July, low radiation associated with above-average rainfall and cloud cover was the most likely cause for negative anomalies in the canopy growth. In August–November, the rainfall and cloud cover were close to the average, but the solar radiation reaching the land surface was considerably above the average. This was because the atmospheric aerosols were extremely low, resulting from reduced biomass burning activities under the wet conditions. Large-scale positive anomalies in the canopy growth were observed during this 4 month period, mainly driven by the above-average radiation. During the severe drought year 2005, the forest canopy growth also experienced a two-stage process, but in the opposite order from the one in 2009. In April–July, enhanced canopy growth was observed in response to the above-average radiation. With the drought progress and soil water depletion, the canopy senescence was observed during the drought peak in August–November. Interestingly, if we examined the regional canopy growth anomaly during the typical dry season (i.e. July–September), both years showed similarly negative anomalies, but resulting from opposite eco-hydrological processes. This study identifies the explanation for the negative anomalies in the dry-season canopy growth over southern Amazon rainforest in both flood and drought years, and also underscores the necessity to separate different hydro-meteorological stages to better understand vegetation responses to extreme events.

Fine-scale height-growth response of boreal trees to canopy openings is difficult to measure from the ground, and there are important limitations in using stereo-photogrammetry in defining gaps and determining individual crowns and height. However, precise knowledge on height growth response to different openings is critical for refining partial harvesting techniques. In this study, we question whether conifers and hardwoods respond equally in terms of sapling growth or lateral growth to openings. We also ask to what distance gaps affect tree growth into the forest. We use multi-temporal lidar to characterize tree/sapling height and lateral growth responses over five years to canopy openings and high resolution images to identify conifers and hardwoods. Species-class-wise height-growth patterns of trees/saplings in various neighborhood contexts were determined across a 6-km 2 matrix of Canadian boreal mixed deciduous coniferous forests. We then use statistical techniques to probe how these growth responses vary by spatial location with respect to the gap edge. Results confirm that both mechanisms of gap closure contribute to the closing of canopies at a rate of 1.2%% per annum. Evidence also shows that both hardwood and conifer gap edge trees have a similar lateral growth (average of 22 cm/yr) and similar rates of height growth irrespective of their location and initial height. Height growth of all saplings, however, was strongly dependent on their position within the gap and the size of the gap. Results suggest that hardwood and softwood saplings in gaps have greatest growth rates at distances of 0.5-–2 m and 1.5-–4 m from the gap edge and in openings smaller than 800 m 2 and 250 m 2 , respectively. Gap effects on the height growth of trees in the intact forest were evident up to 30 m and 20 m from gap edges for hardwood and softwood overstory trees, respectively. Our results thus suggest that foresters should consider silvicultural techniques that create many small openings in mixed coniferous deciduous boreal forests to maximize the growth response of both residual and regenerating trees.

Accurate estimation of green canopy cover (GCC) in rubber plantations is crucial for monitoring vegetation health and assessing stress impacts. This study validates satellite-derived GCC estimates using unmanned aerial vehicle (UAV)-based remote sensing, ground observations, spaceborne remote sensing (satellite imagery), and supervised machine learning regression approaches. Sentinel-2 and Landsat imagery were utilized to derive spectral vegetation indices (SVIs) under varying stress conditions, while UAV-based GCC assessments provided high-resolution reference data for validation. The findings revealed that while certain SVIs exhibited strong correlations with canopy density under stable conditions, their predictive accuracy declined significantly during extreme stress events, such as Pestalotiopsis outbreaks and seasonal leaf fall periods. To improve estimation accuracy, supervised machine learning regression models were developed, with Random Forest (RF) outperforming Support Vector Machines (SVMs), Classification and Regression Trees (CARTs), and Linear Regression (LR). RF achieved the highest predictive accuracy (R2 = 0.82, RMSE = 6.48, MAE = 4.97), demonstrating its reliability in capturing non-linear interactions between canopy heterogeneity and environmental stressors. These results highlight the limitations of traditional vegetation indices and emphasize the importance of multi-sensor integration and advanced modeling techniques for more precise GCC monitoring.

We examine the physical and biological responses of forest canopies to step changes in light caused by passing low cumulus clouds that intermittently block the direct solar beam. Using data obtained at a tropical rainforest and at a midlatitude deciduous forest, we estimate the course of sensible heat flux, net ecosystem exchange, evapotranspiration, and water-use efficiency in response to the rapid changes in the incident radiative flux. To describe these fluxes during the interval over which the effects of stomatal time delays can be most influential, eddy fluxes are estimated over minute or shorter intervals by invoking a conditional-sampling procedure based on forming a Reynolds-average ensemble. The most important differences between the two forests’ physical responses are in the thermal balances and heat-flux time response constants. During the initial period after the light transition the only mean variables that show appreciable changes are the blackbody and air temperatures, the other scalars being little affected. We find that a distinct transient thermal internal boundary layer appears ≈ 20 m thick above the temperate deciduous forest and ≈ 45 m thick above the tropical rainforest. At each forest, the effective thickness of the inferred thermal outer-canopy ‘big leaf’ is about 1 mm. Twenty minutes after the abrupt change in incident light, ensemble eddy-flux estimates approach those found using conventional time averaging, confirming the validity of the ensemble approach. Previously unrecognized transient maxima in net ecosystem exchange and evapotranspiration are evident 5–10 min following the shadow-to-light transition, longer than the average light interval between shadows observed on partly-cloudy days in each case. Short-term variations in sensible heat flux, net ecosystem exchange, and evapotranspiration approximate an exponential adjustment, implying that first-order time-dependent single-leaf models are adequate to describe whole-canopy processes in these cases, providing an experimental method for determining whole-canopy bulk stomatal time constants. During the sunlit interval (direct and diffuse radiative fluxes combined) net ecosystem exchange is enhanced, while under cloud shadow (only diffuse radiative flux) water-use efficiency increases. This light and shadow alternation provides a mechanism describing the observed enhanced net ecosystem exchange and water-use efficiency under certain types of partly-cloudy sky. We apply empirical flux-response curves to an idealized case of radiative flux varying in a regular on–off light and shadow pattern. For this case, an analytical solution for mean net ecosystem exchange flux as a function of diffuse-radiation fraction yields results that strongly resemble previous findings based on conventional time-averaged fluxes. Our analysis and modelling indicates that a well-known correlation between diffuse radiative flux and enhanced net ecosystem exchange and water-use efficiency on cloudy days is in many cases not causal, but rather to be a consequence of time averaging over light-and-shadow intervals. By linking processes associated with photosynthesis in fluctuating light at the leaf scale to the canopy scale, our efforts facilitate the scaling-up of leaf responses to the ecosystem scale.

Climate change and water scarcity are major threats to the sustainability of wheat production in Mediterranean regions. Thus, timely and reliable water demand assessments are crucial to drive decisions on crop management strategies that are useful for agricultural adaptation to climate change challenges. Although the AquaCrop model is widely used to infer crop yields, it requires continuous field-based observations (mainly soil water content and crop coverage). Often, these areas suffer from a scarcity of in situ data, suggesting the need for remote sensing and model-based decision support. In this framework, this research intends to compare the performance of the AquaCrop model using four different input combinations, with one employing ERA5-Land and crop cover retrieved by satellite images exclusively. A field experiment was conducted on durum wheat (highly sensitive to water stress and playing a strategic role in national food security) in northwest Tunisia during the growing season of 2024–2025, where meteorological variables, green Canopy Cover (gCC), Soil Water Content (SWC), and final yields (biological and grain) were monitored. The AquaCrop model was applied. Four model input combinations were evaluated. In situ meteorological data or ERA5-Land (E5L) reanalysis were combined with either measured-gCC (measured-gCC) or Sentinel-2 NDVI-derived gCC (NDVI-gCC). The results showed that E5L reproduced temperature with RMSE < 2.4 °C (NSE > 0.72) and ETo with RMSE equal to 0.57 mm d−1 (NSE = 0.79), while precipitation presented larger discrepancies (RMSE = 4.14 mm d−1, NSE = 0.58). Sentinel-2 effectively captured gCC dynamics (RMSE = 15.65%, NSE = 0.73) and improved AquaCrop perfomance (RMSE = 5.29%, NSE = 0.93). Across all combinations, AquaCrop reproduced yields within acceptable deviations. The simulated biological yield ranged from 9.7 to 11.0 t ha−1 compared to the observed 10.3 t ha−1, while grain yield ranged from 3.0 to 3.5 t ha−1 against the observed 3.3 t ha−1. As expected, the best agreement with measured yield data was obtained using in situ meteorological data and measured-gCC, even if the use of in situ meteorological data coupled with NDVI-gCC, or E5L-based meteorological data coupled with NDVI-gCC, produced realistic estimates. These results highlight that the application of AquaCrop employing E5L and Sentinel-2 inputs is a feasible alternative for crop monitoring in data-scarce environments.

High-wire tomato production requires labor-intensive tasks such as clipping, suckering, and leaf pruning. Leaf pruning is essential for managing a balance between vegetative and reproductive growth of plants. Commercial practices involve maintaining a certain number of leaves or no leaves below harvesting trusses. However, an optimum timing of leaf pruning for saving labor demand and improving crop performance is not well characterized. Here, we introduce a data-driven leaf pruning method, in which lower leaves were removed when weekly light integral (WLI) below canopy fell below a pre-determined WLI based on the lowest leaf's light compensation point (LCP). The number of leaves to prune at a time was three and a minimum pruning interval was one week. Additionally, we evaluated two ranges of photosynthetically active radiation (PAR): PAR (400 - 700 nm) and ePAR (400 - 750 nm) for monitoring WLI below the canopy. We compared the new leaf-pruning method based on WLI PAR (in Experiments 1 and 2) and WLI ePAR (only in Experiment 2) to the conventional leaf-pruning method, in which leaves below harvesting trusses were removed followed by harvesting (Control). For the evaluation, indeterminate tomato cultivar 'Maxxiany' was grown in a Venlo-style greenhouse (482 m and 7-m gutter height) at a density of 3 plants m . Regardless of PAR range, the WLI-based pruning methods resulted in 35 - 42% fewer pruning events. The fewer pruning events were associated with the supplemental lighting use, leaving significantly more leaves per plant in the WLI-based pruning method than in Control. No significant differences were observed in the weekly increase in stem length, the stem diameter, and the cumulative yields between WLI-based pruning method and Control. However, WLI-based pruning method increased the total soluble solid contents of the harvested fruit. These findings suggest that: 1) Leaf pruning strategies should be adjusted based on light availability within the crop canopy, which is influenced by solar radiation and supplemental lighting, and 2) Monitoring WLI below canopy to determine leaf pruning timing is an effective method in lowering labor cost without reducing yield and fruit quality.

Forest canopies play a crucial role in structuring communities of vascular epiphytes by providing substrate for colonization, by locally varying microclimate, and by causing epiphyte mortality due to branch or tree fall. However, as field studies in the three‐dimensional habitat of epiphytes are generally challenging, our understanding of how forest structure and dynamics influence the structure and dynamics of epiphyte communities is scarce. Mechanistic models can improve our understanding of epiphyte community dynamics. We present such a model that couples dispersal, growth, and mortality of individual epiphytes with substrate dynamics, obtained from a three‐dimensional functional–structural forest model, allowing the study of forest–epiphyte interactions. After validating the epiphyte model with independent field data, we performed several theoretical simulation experiments to assess how (a) differences in natural forest dynamics, (b) selective logging, and (c) forest fragmentation could influence the long‐term dynamics of epiphyte communities. The proportion of arboreal substrate occupied by epiphytes (i.e., saturation level) was tightly linked with forest dynamics and increased with decreasing forest turnover rates. While species richness was, in general, negatively correlated with forest turnover rates, low species numbers in forests with very‐low‐turnover rates were due to competitive exclusion when epiphyte communities became saturated. Logging had a negative impact on epiphyte communities, potentially leading to a near‐complete extirpation of epiphytes when the simulated target diameters fell below a threshold. Fragment size had no effect on epiphyte abundance and saturation level but correlated positively with species numbers. Synthesis: The presented model is a first step toward studying the dynamic forest–epiphyte interactions in an agent‐based modeling framework. Our study suggests forest dynamics as key factor in controlling epiphyte communities. Thus, both natural and human‐induced changes in forest dynamics, for example, increased mortality rates or the loss of large trees, pose challenges for epiphyte conservation. Field studies in the three‐dimensional habitat of epiphytes are generally challenging, and our understanding of how forests influence epiphyte communities is thus scarce. By developing and applying an agent‐based model, we were able to analyze forest–epiphyte interactions and demonstrate how forest dynamics can control epiphyte communities.

1 Regeneration in forest canopy gaps is thought to lead invariably to the rapid recruitment and growth of trees and the redevelopment of the canopy. Our observations, however, suggest that an alternate successional pathway is also likely, whereby gap-phase regeneration is dominated by lianas and stalled in a low-canopy state for many years. We investigated gap-phase regeneration in an old-growth tropical forest on Barro Colorado Island (BCI) in Panama to test the following two hypotheses: (i) many gaps follow a pathway in which they remain at a low canopy height and are dominated by lianas and (ii) the paucity of trees in this pathway is a function of liana density. 2 We surveyed a total of 428 gaps of varying ages (c. 5, c. 10, and 13+ years old) and identified those which followed the conventional pathway of regeneration and others that remained stalled in a low-canopy state for many years and were dominated by either lianas or palms. Each of these pathways will likely have different successional trajectories that will favour the growth of a distinct suite of mature species and ultimately result in contrasting species composition. 3 The successional pathway of liana-dominated, stalled gaps is common throughout the forest. We estimate conservatively that 7.5% of the gaps that form each year will follow this pathway, probably due to the suppression of tree regeneration by lianas, and that many of these stalled gaps will persist for much longer than 13 years. Consequently, a high proportion of gaps in the forest at any given time will be stalled. Furthermore, liana tangles, which persist in the tropical forest understorey for extended periods of time, almost certainly originate in these gaps. 4 Liana abundance was positively correlated with pioneer tree abundance and diversity while negatively correlated with non-pioneer tree abundance and diversity. Thus, lianas appear to inhibit non-pioneer tree survival while indirectly enhancing that of pioneer trees. 5 Lianas are abundant in many types of tropical and temperate forests and a successional pathway involving liana-dominated, stalled gaps may therefore be frequent and widespread.