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The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Evergreen conifer forests are the most prevalent land cover type in North America. Seasonal changes in the color of evergreen forest canopies have been documented with near-surface remote sensing, but the physiological mechanisms underlying these changes, and the implications for photosynthetic uptake, have not been fully elucidated. Here, we integrate on-the-ground phenological observations, leaf-level physiological measurements, near surface hyperspectral remote sensing and digital camera imagery, tower-based CO2 flux measurements, and a predictive model to simulate seasonal canopy color dynamics. We show that seasonal changes in canopy color occur independently of new leaf production, but track changes in chlorophyll fluorescence, the photochemical reflectance index, and leaf pigmentation. We demonstrate that at winter-dormant sites, seasonal changes in canopy color can be used to predict the onset of canopy-level photosynthesis in spring, and its cessation in autumn. Finally, we parameterize a simple temperature-based model to predict the seasonal cycle of canopy greenness, and we show that the model successfully simulates interannual variation in the timing of changes in canopy color. These results provide mechanistic insight into the factors driving seasonal changes in evergreen canopy color and provide opportunities to monitor and model seasonal variation in photosynthetic activity using color-based vegetation indices.

Climate extremes such as heat waves and droughts are projected to occur more frequently with increasing temperature and an intensified hydrological cycle. It is important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to heat and drought stress as indicated by air temperature (Ta ) and evaporative fraction (EF). Using normalized daily carbon fluxes from the FLUXNET Network for 34 forest sites in North America, the seasonal pattern of sensitivities of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (RE) in response to Ta and EF anomalies were compared for different forest types. The results showed that warm temperatures in spring had a positive effect on NEP in conifer forests but a negative impact in deciduous forests. GEP in conifer forests increased with higher temperature anomalies in spring but decreased in summer. The drought-induced decrease in NEP, which mostly occurred in the deciduous forests, was mostly driven by the reduction in GEP. In conifer forests, drought had a similar dampening effect on both GEP and RE, therefore leading to a neutral NEP response. The NEP sensitivity to Ta anomalies increased with increasing mean annual temperature. Drier sites were less sensitive to drought stress in summer. Natural forests with older stand age tended to be more resilient to the climate stresses compared to managed younger forests. The results of the Classification and Regression Tree analysis showed that seasons and ecosystem productivity were the most powerful variables in explaining the variation of forest sensitivity to heat and drought stress. Our results implied that the magnitude and direction of carbon flux changes in response to climate extremes are highly dependent on the seasonal dynamics of forests and the timing of the climate extremes.

Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance momentum-flux data. At 69 forest sites, annual ha robustly predicted site-to-site and year-to-year differences in canopy heights (R2 = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly ha successfully captured the dynamics of vegetation canopies over growing seasons (R2 > 0.70 in 74 site-years). Our results demonstrate the potential of flux-derived ha determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying ha derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.

Evapotranspiration (ET) is commonly estimated using the Penman-Monteith equation, which assumes that the plant canopy is a big leaf (BL) and the water flux from vegetation is regulated by canopy stomatal conductance (Gs). However, BL has been found to be unsuitable for terrestrial biosphere models built on the carbon-water coupling principle because it fails to capture daily variations of gross primary productivity (GPP). A two-big-leaf scheme (TBL) and a two-leaf scheme (TL) that stratify a canopy into sunlit and shaded leaves have been developed to address this issue. However, there is a lack of comparison of these upscaling schemes for ET estimation, especially on the difference between TBL and TL. We find that TL shows strong performance (r2 = 0.71, root-mean-square error = 0.05 mm/h) in estimating ET at nine eddy covariance towers in Canada. BL simulates lower annual ET and GPP than TL and TBL. The biases of estimated ET and GPP increase with leaf area index (LAI) in BL and TBL, and the biases of TL show no trends with LAI. BL miscalculates the portions of light-saturated and light-unsaturated leaves in the canopy, incurring negative biases in its flux estimation. TBL and TL showed improved yet different GPP and ET estimations. This difference is attributed to the lower Gs and intercellular CO2 concentration simulated in TBL compared to their counterparts in TL. We suggest to use TL for ET modeling to avoid the uncertainty propagated from the artificial upscaling of leaf-level processes to the canopy scale in BL and TBL.

We studied the recovery of tree- and stand-level carbon (C) storage in a lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) forest in northern British Columbia that experienced substantial (~83%) mortality in 2006-2007 (total loss by 2013 = 86%) during a severe mountain pine beetle (MPB; Dendroctonus ponderosae Hopkins, 1902) infestation. Earlier work suggested that this forest recovered positive annual C storage 3 years after attack based on eddy covariance measurements. We sought to confirm these results by examining C storage in surviving pine trees using tree core analysis. Average growth release of surviving lodgepole pine trees was 392% (range of -53% to 2326%) compared with mean decadal growth prior to MPB attack. Nearly 97% of trees underwent a growth release, considerably higher than the 15%-75% reported for lodgepole pine in previous studies. Mean annual stem C storage of the surviving trees in this study was highly correlated (r = 0.88) with 10 years of annual net ecosystem productivity estimates made using the eddy covariance technique, indicating that surviving lodgepole pine remain an important part of C recovery after MPB attack. Mean annual stem C storage was also highly correlated (r = 0.92) with the cumulative percentage of downed stems per hectare at the site, suggesting that increased availability of resources is likely assisting the growth release. Key words: forest disturbance, growth release, dendrochronology, lodgepole pine, carbon storage, mountain pine beetle. Nous avons etudie la recuperation des arbres et le stockage du carbone (C) a l'echelle du peuplement dans une foret de pin tordu latifolie (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) du nord de la Colombie-Britannique, qui a connu une mortalite importante (~83%) en 2006-2007 (perte totale accumulee en 2013 = 86%) lors d'une infestation severe du dendroctone du pin ponderosa (DPP; Dendroctonus ponderosae Hopkins, 1902). Des travaux anterieurs indiquent que cette foret a retrouve un stockage annuel de C positif trois ans apres une attaque sur la base de mesures de covariance des turbulences. Nous avons cherche a confirmer ces resultats en examinant le stockage de C dans les tiges de pin qui ont survecu a l'aide de l'analyse de carottes de bois. La reprise de croissance moyenne des pins tordus qui ont survecu atteignait 392% (etendue de -53 a 2326%) comparativement a la croissance decennale moyenne anterieurement a l'attaque du DPP. Presque 97% des tiges ont connu une reprise de croissance considerablement plus elevee que 15-75%, l'eventail des pourcentages qui ont ete rapportes lors d'etudes anterieures dans le cas du pin tordu. Dans cette etude, le stockage annuel moyen de C dans le tronc des arbres qui ont survecu etait etroitement correle (r = 0,88) avec les estimations de productivite annuelle nette de l'ecosysteme pendant 10 ans obtenues a l'aide de la methode de covariance des turbulences, indiquant que les pins tordus qui ont survecu demeurent un element important de la recuperation de C apres une attaque du DPP. Le stockage annuel moyen de C dans le tronc etait aussi etroitement correle (r = 0,92) avec le pourcentage cumulatif de tiges au sol a l'hectare sur le site, indiquant qu'une augmentation de la disponibilite des ressources contribue probablement a la reprise de croissance. [Traduit par la Redaction] Mots-cles: perturbation forestiere, reprise de croissance, dendrochronologie, pin tordu, stockage du carbone, dendroctone du pin ponderosa., Introduction The mountain pine beetle (MPB) (Dendroctonus ponderosae Hopkins, 1902) is a bark beetle native to western North America that ranges from Mexico to central British Columbia (BC), Canada. Lodgepole [...]

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models.

Although evapotranspiration (ET) from the land is a key variable in Earth system models, the accurate estimation of ET based on physical principles remains challenging. Parameters used in current ET models are largely empirically based, which could be problematic under rapidly changing climatic conditions. Here, we propose a physically based ET model that estimates ET based on the surface flux equilibrium (SFE) theory and the maximum entropy production (MEP) principle. We derive an expression for aerodynamic resistance based on the MEP principle, then propose a novel ET model that integrates the SFE model and the MEP principle. The proposed model, which is referred to as the SFE‐MEP model, becomes equivalent to the MEP state in non‐equilibrium conditions when turbulent mixing is weak and the land surface is dry. Under conditions meeting land‐atmosphere equilibrium, the SFE‐MEP model is similar to ET estimation based on the SFE model. This blended nature of the SFE‐MEP ET model allows accurate ET estimation for most inland regions by overcoming the ET overestimation issue of the SFE model in dry conditions. As a result, the SFE‐MEP model significantly improves the performance of SFE ET estimation, particularly for arid regions. The proposed model and its high accuracy of ET estimation enable novel insight into various Earth system models as it does not require any empirical parameters and only uses readily obtainable meteorological variables including reference height air temperature, relative humidity, available energy, and radiometric surface temperature. Plain Language Summary: Terrestrial evaporation, also known as evapotranspiration (ET), is a central variable controlling the water, energy, and carbon cycles. However, it is difficult to estimate ET from physical principles due to complex interactions between the land and the atmosphere. An emerging theory of surface flux equilibrium (SFE) suggests that atmospheric observations reflect land surface conditions owing to a land‐atmosphere coupling, making it possible to estimate ET only using meteorological information. Nevertheless, we demonstrate that if the equilibrium is not quickly achieved, particularly in dry regions, the emerging SFE theory cannot properly estimate ET. We resolve this problem by introducing the maximum entropy production principle, a thermodynamic principle that can be applicable to non‐equilibrium conditions. By combining two theories with complementary relationships, we significantly improve ET estimation performance. In our approach, empirical and adjustable parameters are not required and ET can be easily estimated based on a land‐atmosphere coupling by using meteorological information and land surface temperature. Key Points: Identify non‐equilibrium conditions where the surface flux equilibrium theory does not perform wellPropose a model to improve the performance of evapotranspiration estimation compared to the surface flux equilibrium approachThe proposed model only uses readily obtainable meteorological variables and radiometric surface temperature [ABSTRACT FROM AUTHOR]