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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., Three key axes of variation of ecosystem functional changes and their underlying causes are identified from a dataset of surface gas exchange measurements across major terrestrial biomes and climate zones.

Understanding the coordination of ecosystem functions across biomes and climate is still a major challenge that hampers our ability to properly predict biosphere response to climate change. Theories such as the leaf economics spectrum and the least cost investment strategy postulate that plants optimize the rate of investment in transpiration, photosynthetic capacity, and nitrogen (N) allocation dependent on the ratio of their costs to gain given their resources and environment.In this contribution we test whether theories about functional traits coordination at leaf and organs level are emerging at ecosystem scale. We further investigate the existence of a global spectrum of ecosystem functional properties, and analyze how state of the art terrestrial biosphere models reproduce the spectrum.To do so we used data of CO2, water and energy exchange for 164 sites (1237 site years) from the FLUXNET LaThuile and FLUXNET 2015 datasets with at least 3 years of data. For 61 sites, we were able to compile site information on canopy-scale measurements of foliar N concentration, maximum leaf area index , and stand age, from the literature.We find evidence that a global spectrum of ecosystem functional properties exist, and that most of the variability (66.2%) is captured by three dimensions. The first dimension represents ecosystem productivity; the second the water availability gradient, and climate limitations to productivity; the third dimension reflects ecosystem respiration potential and carbon-use efficiency and is related to aridity and stand age and disturbance regimes. The first two dimensions of the spectrum are well captured by ecosystem models, while the third dimension is poorly reproduced. This might be related to the spin up of the models (steady-state condition) or to an incomplete representation of processes related to age that might limit the ability of models to accurately predict the dynamic carbon, water and nutrient cycling in ecosystems in disturbed areas.Finally, we show across ecosystems globally that leaf level theories can be in some cases translated to the ecosystem scale. As a main example we found an inverse relationship between photosynthetic N and water use efficiency as postulated by the least cost investment theory across FLUXNET sites. However, this is possible only when the contribution of vegetation is properly accounted for, and evaporation from soil and wet surfaces is removed from the analysis. This highlights that emerging biological patterns at ecosystem scale might be masked by other factors related to physical rather than biological responses.

Global change is affecting terrestrial carbon balances. The effect of climate on ecosystem carbon balance has been largely explored, but the roles of other concurrently changing factors, such as diversity and nutrient availability, remain elusive. We used eddy‐covariance carbon‐flux measurements from 62 ecosystems from which we compiled information on climate, ecosystem type, stand age, species abundance and foliar concentrations of N and P of the main species, to assess their importance in the ecosystem carbon balance. Climate and productivity were the main determinants of ecosystem C balance and its stability. In P‐rich sites, increasing N was related with increased gross primary production and respiration and vice versa, but reduced net C uptake. Our analyses did not provide evidence for a strong relation between ecosystem diversity and their productivity and stability. Nonetheless, these results suggest that nutrient imbalances and, potentially, diversity loss may alter future global carbon balance.

Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resources availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESA's Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. These field plots represent major European forest types, from boreal forests in Finland to Mediterranean mixed forests in Spain. Based on in-situ data collected in 2013 we computed functional dispersion (FDis), a measure of FD, using foliar and whole-plant traits of known ecological significance. These included five foliar traits: leaf nitrogen concentration (N%), leaf carbon concentration (%C), specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA). In addition they included three whole-plant traits: tree height (H), crown cross-sectional area (CCSA), and diameter-at-breast-height (DBH). We applied partial least squares regression using Sentinel-2 surface reflectance measured in 2015 as predictive variables to model in-situ FDis measurements. We predicted, in cross-validation, 55% of the variation in the observed FDis. We also showed that the red-edge, near infrared and shortwave infrared regions of Sentinel-2 are more important than the visible region for predicting FDis. An initial 30-m resolution mapping of FDis revealed large local FDis variation within each forest type. The novelty of this study is the effective integration of spaceborne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes., This work was primarily supported by an iDiv-Flexpool project “Observing effects of biodiversity on ecosystem functioning across time, space, and wavelength: oBEF-Across” and a European Union H2020 project “Detecting changes in essential ecosystem and biodiversity properties - towards a Biosphere Atmosphere Change Index: BACI” (grant agreement number: 640176). The data from FunDivEUROPE network was collected with the financial support from the European Union Seventh Framework Programme (FP7/2007-2013) (grant agreement number: 265171). Remeasurements across all FunDivEUROPE plots were financed by EU H2020 project Soil4Europe (Bioidversa 2017-2019). We thank Prof. Dr. Michael Scherer-Lorenzen and Prof. Dr. Kris Verheyen from FunDivEUROPE network for their generous help with field data during the paper revision. DEPM and MM and MDM also acknowledge the support of the Trustee European Commission project no H2020-MSCA-ITN-2016 – 721995. The free use of Sentinel-2 data is enabled by ESA's Copernicus Open Access Hub. The in-situ plant traits data collected over Finnish, Romanian, and Spanish sites were supported by a Marie-Curie Fellowship (DIVERFOR, FP7-PEOPLE-2011-IEF. No. 302445) to R. Benavides. The free access of plant trait data was supported by the TRY initiative (http://www.try-db.org)

Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary production (GPP). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F760) in a Mediterranean grassland manipulated with nutrient addition of nitrogen (N), phosphorous (P) or nitrogen¿phosphorous (NP). Using the soil¿canopy observation of photosynthesis and energy (SCOPE) model, we investigated how nutrient-induced changes in canopy structure (i.e. changes in plant forms abundance that influence leaf inclination distribution function, LIDF) and functional traits (e.g. N content in dry mass of leaves, N%, Chlorophyll a+b concentration (Cab) and maximum carboxylation capacity (Vcmax)) affected the observed linear relationship between F760 and GPP. We conclude that the addition of nutrients imposed a change in the abundance of different plant forms and biochemistry of the canopy that controls F760. Changes in canopy structure mainly control the GPP¿F760 relationship, with a secondary effect of Cab and Vcmax. In order to exploit F760 data to model GPP at the global/regional scale, canopy structural variability, biodiversity and functional traits are important factors that have to be considered., The authors acknowledge the Alexander von Humboldt Foundation for supporting this research with the Max-Planck Prize to Markus Reichstein, and the EUFAR TA project DEHESHyrE (EU FP7 Program). We acknowledge the Majadas de Tietar city council for its support. The authors acknowledge the Freiland Group and in particular Martin Hertel from MPI-Jena and Ramon Lopez-Jimenez (CEAM) for technical assistance. The authors thank the anonymous referee and the editor for their comments on the work, Alessandro Cescatti for discussions about the results and Silvana Schott for the graphics.

In the version of this Article originally published, the wrong Supplementary Information pdf was uploaded, in which the figures did not correspond with those mentioned in the main text and the R code was not presented properly. This has now been replaced.

Sun-induced fluorescence (SIF) in the far-red region provides a new noninvasive measurement approach that has the potential to quantify dynamic changes in light-use efficiency and gross primary production (GPP). However, the mechanistic link between GPP and SIF is not completely understood. We analyzed the structural and functional factors controlling the emission of SIF at 760 nm (F

The total uptake of carbon dioxide by ecosystems via photosynthesis (gross primary productivity, GPP) is the largest flux in the global carbon cycle. A key ecosystem functional property determining GPP is the photosynthetic capacity at light saturation (GPPsat), and its interannual variability (IAV) is propagated to the net land–atmosphere exchange of CO2. Given the importance of understanding the IAV in CO2 fluxes for improving the predictability of the global carbon cycle, we have tested a range of alternative hypotheses to identify potential drivers of the magnitude of IAV in GPPsat in forest ecosystems. Our results show that while the IAV in GPPsat within sites is closely related to air temperature and soil water availability fluctuations, the magnitude of IAV in GPPsat is related to stand age and biodiversity (R2 = 0.55, P < 0.0001). We find that the IAV of GPPsat is greatly reduced in older and more diverse forests, and is higher in younger forests with few dominant species. Older and more diverse forests seem to dampen the effect of climate variability on the carbon cycle irrespective of forest type. Preserving old forests and their diversity would therefore be beneficial in reducing the effect of climate variability on Earth's forest ecosystems. Interannual variability (IAV) of the net carbon dioxide exchange over land is globally the main determinant of the variability of atmospheric CO2 growth rate1,2. So understanding the factors controlling the IAV in CO2 fluxes is essential to improve the predictability of the global carbon cycle3. Ecosystem biotic properties — such as soil and canopy nutrient status, rates of change in physiological properties of the vegetation, or the sensitivity of these properties to environmental factors — influence ecosystem CO2 exchange. Recent studies have shown that the IAV of the carbon budget can be better explained by variation in biotic properties of ecosystems such as photosynthetic capacity (GPPsat) than directly by environmental and climatic drivers4,​5,​6. GPPsat is defined as the value of gross primary productivity (GPP) at saturating light under non-stressed conditions, minimizing the influence of anomalous hydrometeorological conditions (for example, droughts and heatwaves), which potentially affect photosynthesis. A robustly retrieved characterization of GPPsat can be regarded as an ecosystem functional property reflecting the physiological response of the ecosystem to the environment. Given that IAV of GPPsat must propagate to observed GPP, this quantity is thought to be a key variable in understanding IAV of carbon fluxes7. In fact, recent studies demonstrated that GPPsat correlates more strongly than any climatic variable with annual GPP8, but also correlates with net ecosystem CO2 exchange5. The magnitude of IAV in GPPsat has been shown to exhibit considerable variation across ecosystems9, yet no obvious explanation for this pattern has been reported in the literature. However, the consequences are important: a low IAV in GPPsat would suggest that ecosystem functioning is not very sensitive to climatic variability, and that it preserves its functionality under the influence of that variability — and, likewise, high IAV is a consequence of high sensitivity. The capability of an ecosystem to preserve its functioning and structure over time (after external disturbances or climate extremes), is often defined as ecosystem stability and is linked to ecosystem resilience10. Using this terminology, low values of IAV in GPPsat can be understood as a characterization of high ecosystem functional stability. The relation of ecosystem functionality, structure and stability has been a matter of debate for many decades in the field of ecology. In particular, the diversity of vascular plants has been investigated as a stabilizing factor with respect to variations in productivity, for example by buffering the ecosystem’s sensitivity to climate extremes11. However, it is also well known that plant diversity is co-limited by soil properties12, ecosystem management, and climate conditions. Another variable to consider is stand age (the mean age of the forest stand or the number of years after a major stand replacement after disturbance), which may affect ecosystem stability through adaptation, particularly of trees to their environment — hence increasing ecosystem resilience to climate variability13. Moreover, structural parameters such as canopy cover, rooting depth, canopy height or leaf area index (LAI), which also depend on tree species diversity and stand age14, have an important effect on the ecosystem response to variation in environmental drivers since they define the capacity of trees to access resources such as water and light15. For instance, a regional study in the Amazon basin has shown that GPP, derived from the remotely sensed enhanced vegetation index, is less sensitive to environmental influences in regions with high canopy cover16. Despite this growing body of ecological knowledge, it remains largely uncertain which factors stabilize ecosystem functional properties at the global scale. In particular, we do not understand the causes of variability of specific ecosystem functional properties, such as photosynthetic capacity across ecosystem types, which ultimately controls ecosystem productivity. Here we hypothesize that stand age and species diversity play an important role in stabilizing ecosystem photosynthetic capacity. We test this hypothesis while also considering other factors related to climate, water availability, forest structure and soil properties that might have direct or indirect effects on ecosystem photosynthetic capacity. In this study, we used measurements of ecosystem-level fluxes, and climate variables (temperature, precipitation, and water availability), species richness, stand age, forest structure (canopy cover, height, and LAI), and soil properties (nutrient availability17) derived from satellite data, in situ observations and the literature (see the Methods). We used half-hourly ecosystem-level GPP fluxes estimated by the means of the eddy-covariance technique at 50 FLUXNET sites18 with at least 4 years of measured fluxes, and with different vegetation types across different climatic regions. We included data from evergreen forest (EF) as well as deciduous broadleaved and mixed forest (DBMF) located in temperate, boreal, mediterranean, tropical and dry climate regions (Supplementary Fig. 1 and Table 1). All 50 sites have information on stand age (referred to simply as ‘age’ in Figs 1–3) and species richness in addition to the CO2 flux data. Species richness (‘sp. no.’ in Figs 1–3) is the number of dominant plant species (for example tree or herb) that account for a cumulative abundance of 90 percent at a given site. We collected additional information on (i) canopy cover, (ii) canopy height, (iii) LAI, (iv) temperature and precipitation, and (v) soil water availability index (WAI) for a subset of 44 sites; and (vi) an index of nutrient availability for 36 sites compiled from the literature17 (see Methods).

Terrestrial ecosystems strongly determine the exchange of carbon, water and energy between the biosphere and atmosphere. These exchanges are influenced by environmental conditions (e.g., local meteorology, soils), but generally mediated by organisms. Often, mathematical descriptions of these processes are implemented in terrestrial biosphere models. Model implementations of this kind should be evaluated by empirical analyses of relationships between observed patterns of ecosystem functioning, vegetation structure, plant traits, and environmental conditions. However, the question of how to describe the imprint of plants on ecosystem functioning based on observations has not yet been systematically investigated. One approach might be to identify and quantify functional attributes or responsiveness of ecosystems (often very short-term in nature) that contribute to the long-term (i.e., annual but also seasonal or daily) metrics commonly in use. Here we define these patterns as “ecosystem functional properties”, or EFPs. Such as the ecosystem capacity of carbon assimilation or the maximum light use efficiency of an ecosystem. While EFPs should be directly derivable from flux measurements at the ecosystem level, we posit that these inherently include the influence of specific plant traits and their local heterogeneity. We present different options of upscaling in situ measured plant traits to the ecosystem level (ecosystem vegetation properties – EVPs) and provide examples of empirical analyses on plants’ imprint on ecosystem functioning by combining in situ measured plant traits and ecosystem flux measurements. Finally, we discuss how recent advances in remote sensing contribute to this framework.