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ABSTRACT AimTo quantify the intra‐community variability of leaf‐out (ICVLo) among dominant trees in temperate deciduous forests, assess its links with specific and phylogenetic diversity, identify its environmental drivers and deduce its ecological consequences with regard to radiation received and exposure to late frost. LocationEastern North America (ENA) and Europe (EUR). Time Period2009–2022. Major Taxa StudiedTemperate deciduous forest trees. MethodsWe developed an approach to quantify ICVLo through the analysis of RGB images taken from phenological cameras. We related ICVLo to species richness, phylogenetic diversity and environmental conditions. We quantified the intra‐community variability of the amount of radiation received and of exposure to late frost. ResultsLeaf‐out occurred over a longer time interval in ENA than in EUR. The sensitivity of leaf‐out to temperature was identical in both regions (−3.4 days per °C). The distributions of ICVLo were similar in EUR and ENA forests, despite the latter being more species‐rich and phylogenetically diverse. In both regions, cooler conditions and an earlier occurrence of leaf‐out resulted in higher ICVLo. ICVLo resulted in ca. 8% difference of radiation received from leaf‐out to September among individual trees. Forest communities in ENA had shorter safety margins as regards the exposure to late frosts, and were actually more frequently exposed to late frosts. Main ConclusionsWe conducted the first intercontinental analysis of the variability of leaf‐out at the scale of tree communities. North American and European forests showed similar ICVLo, in spite of their differences in terms of species richness and phylogenetic diversity, highlighting the relevance of environmental controls on ICVLo. We quantified two ecological implications of ICVLo (difference in terms of radiation received and exposure to late frost), which should be explored in the context of ongoing climate change, which affects trees differently according to their phenological niche. 

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under- sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups. 

Abstract The influence of aquaporin (AQP) activity on plant water movement remains unclear, especially in plants subject to unfavorable conditions. We applied a multitiered approach at a range of plant scales to (i) characterize the resistances controlling water transport under drought, flooding, and flooding plus salinity conditions; (ii) quantify the respective effects of AQP activity and xylem structure on root (Kroot), stem (Kstem), and leaf (Kleaf) conductances; and (iii) evaluate the impact of AQP-regulated transport capacity on gas exchange. We found that drought, flooding, and flooding plus salinity reduced Kroot and root AQP activity in Pinus taeda, whereas Kroot of the flood-tolerant Taxodium distichum did not decline under flooding. The extent of the AQP control of transport efficiency varied among organs and species, ranging from 35–55% in Kroot to 10–30% in Kstem and Kleaf. In response to treatments, AQP-mediated inhibition of Kroot rather than changes in xylem acclimation controlled the fluctuations in Kroot. The reduction in stomatal conductance and its sensitivity to vapor pressure deficit were direct responses to decreased whole-plant conductance triggered by lower Kroot and larger resistance belowground. Our results provide new mechanistic and functional insights on plant hydraulics that are essential to quantifying the influences of future stress on ecosystem function. 

Solar-Induced Chlorophyll Fluorescence (SIF) can provide key information about the state of photosynthesis and offers the prospect of defining remote sensing-based estimation of Gross Primary Production (GPP). There is strong theoretical support for the link between SIF and GPP and this relationship has been empirically demonstrated using ground-based, airborne, and satellite-based SIF observations, as well as modeling. However, most evaluations have been based on monthly and annual scales, yet the GPP:SIF relations can be strongly influenced by both vegetation structure and physiology. At the monthly timescales, the structural response often dominates but short-term physiological variations can strongly impact the GPP:SIF relations. Here, we test how well SIF can predict the inter-daily variation of GPP during the growing season and under stress conditions, while taking into account the local effect of sites and abiotic conditions. We compare the accuracy of GPP predictions from SIF at different timescales (half-hourly, daily, and weekly), while evaluating effect of adding environmental variables to the relationship. We utilize observations for years 2018–2019 at 31 mid-latitudes, forested, eddy covariance (EC) flux sites in North America and Europe and use TROPOMI satellite data for SIF. Our results show that SIF is a good predictor of GPP, when accounting for inter-site variation, probably due to differences in canopy structure. Seasonally averaged leaf area index, fraction of absorbed photosynthetically active radiation (fPAR) and canopy conductance provide a predictor to the site-level effect. We show that fPAR is the main factor driving errors in the linear model at high temporal resolution. Adding water stress indicators, namely canopy conductance, to a multi-linear SIF-based GPP model provides the best improvement in the model precision at the three considered timescales, showing the importance of accounting for water stress in GPP predictions, independent of the SIF signal. SIF is a promising predictor for GPP among other remote sensing variables, but more focus should be placed on including canopy structure, and water stress effects in the relationship, especially when considering intra-seasonal, and inter- and intra-daily resolutions. 

Abstract Wetlands are responsible for 20%–31% of global methane (CH₄) emissions and account for a large source of uncertainty in the global CH₄budget. Data‐driven upscaling of CH₄fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH₄emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH₄flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH₄fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH₄emissions of 146 ± 43 TgCH₄ y⁻¹for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH₄ y⁻¹) and overlaps with top‐down atmospheric inversion models (155–200 TgCH₄ y⁻¹). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH₄fluxes has the potential to produce realistic extra‐tropical wetland CH₄emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).