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SUMMARY STATEMENT The degree of inhibition of leaf respiration by light is often studied, but the methods used and the results obtained are variable. We suggest that in the future daytime leaf respiration is measured 3 min after dark acclimation to avoid under‐estimating the degree of light inhibition of leaf respiration. This will most likely speed up future surveys and perhaps also result in less inter‐study variation in the calculated degree of light inhibition of leaf respiration. 

Summary Nonstructural carbohydrate (NSC) concentrations might reflect the strategies described in the leaf economic spectrum (LES) due to their dependence on photosynthesis and respiration.We examined if NSC concentrations correlate with leaf structure, chemistry, and physiology traits for 114 species from 19 sites and 5 biomes around the globe.Total leaf NSC concentrations varied greatly from 16 to 199 mg g⁻¹dry mass and were mostly independent of leaf gas exchange and the LES traits. By contrast, leaf NSC residence time was shorter in species with higher rates of photosynthesis, following the fast‐slow strategies in the LES. An average leaf held an amount of NSCs that could sustain one night of leaf respiration and could be replenished in just a few hours of photosynthesis under saturating light, indicating that most daily carbon gain is exported.Our results suggest that NSC export is clearly linked to the economics of return on resource investment. 

Vegetation (species) abundances were measured from LTER heath tundra herbivore exclosures using the point frame method. This file contains the number of pin hits per species for each subplot. 

Ecosystem carbon dioxide (CO2) flux light response curves were measured from Arctic LTER heath tundra herbivore exclosures. Plot photographs were taken of each subplot using five consumer grade red, green and blue (RGB) wavelength camera. Structure from motion (SFM) photogrammetric method was then used to derive canopy structure. This file contains the CO2, normalized difference vegetation index (NDVI) data and photographs for each plot. 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the plant community of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1) Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer except for 2024 and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019 onward. At each site in each plot we collected relative abundance of plant species and ground cover in 8 1 square meter (m2) plots once each year (except in 2020). 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the belowground biogeochemistry of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1)Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer except for 2024 and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019 onward. At each site we collected temperature measurements using iButton data loggers from the soil surface, the soil organic layer, and the soil mineral layer every 4 hours from 2018 - 2024. iButton loggers were removed and replaced after soil thaw every summer. 

We conducted a manipulative experiment to quantify the impact of small mammal herbivores on the belowground biogeochemistry of the tundra at three sites near Toolik Lake, Alaska. At each site we set up grazing fences in July of 2018 to simulate different levels of small mammal herbivore (vole and lemming) activity. Each site had 3 treatment plots and a control plot: 1)Exclosure treatments (EX) were 8 meter (m) x 8m square mesh fences 2) control plots (CT) were 8m x 8m unfenced plots marked with pin flags at corners 3) press treatments (PR) were 20m x 20m square mesh fences stocked with 4 tundra voles (Microtus oeconomus) every summer and 4) pulse treatments (PU) where we stocked the fence with 4 voles in 2018 and then removed and excluded voles from 2019-2022. At each site we collected 10 thaw depth measurements along a transect from each treatment. 

The logarithmic law of the wall does not capture the mean flow when a boundary layer is subjected to a strong pressure gradient. In such a boundary layer, the mean flow is affected by the spatio-temporal history of the imposed pressure gradient; and accounting for history effects remains a challenge. This work aims to develop a universal mean flow scaling for boundary layers subjected to arbitrary adverse or/and favourable pressure gradients. We derive from the Navier–Stokes equation a velocity transformation that accounts for the history effects and maps the mean flow to the canonical law of the wall. The transformation is tested against channel flows with a suddenly imposed adverse or favourable pressure gradient, boundary layer flows subjected to an adverse pressure gradient, and Couette–Poiseuille flows with a streamwise pressure gradient. It is found that the transformed velocity profiles follow closely the equilibrium law of the wall. 

We develop a wall model for large-eddy simulation (LES) that takes into account various pressure-gradient effects using multi-agent reinforcement learning. The model is trained using low-Reynolds-number flow over periodic hills with agents distributed on the wall at various computational grid points. It utilizes a wall eddy-viscosity formulation as the boundary condition to apply the modeled wall shear stress. Each agent receives states based on local instantaneous flow quantities at an off-wall location, computes a reward based on the estimated wall-shear stress, and provides an action to update the wall eddy viscosity at each time step. The trained wall model is validated in wall-modeled LES of flow over periodic hills at higher Reynolds numbers, and the results show the effectiveness of the model on flow with pressure gradients. The analysis of the trained model indicates that the model is capable of distinguishing between the various pressure gradient regimes present in the flow. To further assess the robustness of the developed wall model, simulations of flow over the Boeing Gaussian bump are conducted at a Reynolds number of 2 million, based on the free-stream velocity and the bump width. The results of mean skin friction and pressure on the bump surface, as well as the velocity statistics of the flow field, are compared to those obtained from equilibrium wall model (EQWM) simulations and published experimental data sets. The developed wall model is found to successfully capture the acceleration and deceleration of the turbulent boundary layer on the bump surface, providing better predictions of skin friction near the bump peak and exhibiting comparable performance to the EQWM with respect to the wall pressure and velocity field. We also conclude that the subgrid-scale model is crucial to the accurate prediction of the flow field, in particular the prediction of separation. 

Abstract Climate change is increasing the intensity and frequency of extreme heat events. Ecological responses to extreme heat will depend on vegetation physiology and thermal tolerance. Here we report thatLarix sibirica, a foundation species across boreal Eurasia, is vulnerable to extreme heat at its southern range margin due to its low thermal tolerance (T_critof photosynthesis: ~ 37–48 °C). Projections from CMIP6 Earth System Models (ESMs) suggest that leaf temperatures might exceed the 25^thpercentile ofLarix sibirica’s T_critby two to three days per year within the next two to three decades (by 2050) under high emission scenarios (SSP3-7.0 and SSP5-8.5). This degree of warming will threaten the biome’s continued ability to assimilate and sequester carbon. This work highlights that under high emission trajectories we may approach an abrupt ecological tipping point in southern boreal Eurasian forests substantially sooner than ESM estimates that do not consider plant thermal tolerance traits.