The three major axes of terrestrial ecosystem function.

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.

Theory and tests for coordination among hydraulic and photosynthetic traits in co-occurring woody species.

Co-occurring plants show wide variation in their hydraulic and photosynthetic traits. Here, we extended 'least-cost' optimality theory to derive predictions for how variation in key hydraulic traits potentially affects the cost of acquiring and using water in photosynthesis and how this, in turn, should drive variation in photosynthetic traits. We tested these ideas across 18 woody species at a temperate woodland in eastern Australia, focusing on hydraulic traits representing different aspects of plant water balance, that is storage (sapwood capacitance, CS), demand vs supply (branch leaf : sapwood area ratio, AL : AS and leaf : sapwood mass ratio and ML : MS), access to soil water (proxied by predawn leaf water potential, ΨPD) and physical strength (sapwood density, WD). Species with higher AL : AS had higher ratio of leaf-internal to ambient CO2 concentration during photosynthesis (ci : ca), a trait central to the least-cost theory framework. CS and the daily operating range of tissue water potential (∆Ψ) had an interactive effect on ci : ca. CS, WD and ΨPD were significantly correlated with each other. These results, along with those from multivariate analyses, underscored the pivotal role leaf : sapwood allocation (AL : AS), and water storage (CS) play in coordination between plant hydraulic and photosynthetic systems. This study uniquely explored the role of hydraulic traits in predicting species-specific photosynthetic variation based on optimality theory and highlights important mechanistic links within the plant carbon-water balance.

Nitrogen concentration and physical properties are key drivers of woody tissue respiration.

BACKGROUND AND AIMS: Despite the critical role of woody tissues in determining net carbon exchange of terrestrial ecosystems, relatively little is known regarding the drivers of sapwood and bark respiration. METHODS: Using one of the most comprehensive wood respiration datasets to date (82 species from Australian rainforest, savanna and temperate forest), we quantified relationships between tissue respiration rates (Rd) measured in vitro (i.e. 'respiration potential') and physical properties of bark and sapwood, and nitrogen concentration (Nmass) of leaves, sapwood and bark. KEY RESULTS: Across all sites, tissue density and thickness explained similar, and in some cases more, variation in bark and sapwood Rd than did Nmass. Higher density bark and sapwood tissues had lower Rd for a given Nmass than lower density tissues. Rd-Nmass slopes were less steep in thicker compared with thinner-barked species and less steep in sapwood than in bark. Including the interactive effects of Nmass, density and thickness significantly increased the explanatory power for bark and sapwood respiration in branches. Among these models, Nmass contributed more to explanatory power in trunks than in branches, and in sapwood than in bark. Our findings were largely consistent across sites, which varied in their climate, soils and dominant vegetation type, suggesting generality in the observed trait relationships. Compared with a global compilation of leaf, stem and root data, Australian species showed generally lower Rd and Nmass, and less steep Rd-Nmass relationships. CONCLUSIONS: To the best of our knowledge, this is the first study to report control of respiration-nitrogen relationships by physical properties of tissues, and one of few to report respiration-nitrogen relationships in bark and sapwood. Together, our findings indicate a potential path towards improving current estimates of autotrophic respiration by integrating variation across distinct plant tissues.

Nutrients and water availability constrain the seasonality of vegetation activity in a Mediterranean ecosystem.

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPPmax ). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree-grass ecosystem, we established three landscape-level (24 ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green-up and dry-down), slopes during green-up and dry-down period, and seasonal amplitude, were extracted from time series of GPPmax and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPPmax was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green-up period. Yet, both fertilized sites senesced earlier during the dry-down period (17-19 days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPPmax during the green-up period and a sharper decline in GPPmax during the dry-down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient-water interaction in such water-limited ecosystems. With the projected warming-drying trend, the positive effects of N fertilization induced by N deposition on GPPmax may be counteracted by an earlier and faster dry-down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water-limited ecosystems.

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC-based T estimates show higher correlation to sap flow-based T than EC-based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high-quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data-based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use for global water and carbon cycling in a changing climate.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF - especially from space - is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

Plant functional traits and canopy structure control the relationship between photosynthetic CO2 uptake and far-red sun-induced fluorescence in a Mediterranean grassland under different nutrient availability.

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.

Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests.

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy.

Terrestrial gross primary production inferred from satellite fluorescence and vegetation models.

Determining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth's carbon budget. Dynamical global vegetation models (DGVMs) provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar-induced chlorophyll fluorescence (SIF) opens up a new possibility to provide direct global observational constraints for GPP. Here, we apply an optimal estimation approach to infer the global distribution of GPP from an ensemble of eight DGVMs constrained by global measurements of SIF from the Greenhouse Gases Observing SATellite (GOSAT). These estimates are compared to flux tower data in N. America, Europe, and tropical S. America, with careful consideration of scale differences between models, GOSAT, and flux towers. Assimilation of GOSAT SIF with DGVMs causes a redistribution of global productivity from northern latitudes to the tropics of 7-8 Pg C yr(-1) from 2010 to 2012, with reduced GPP in northern forests (~3.6 Pg C yr(-1) ) and enhanced GPP in tropical forests (~3.7 Pg C yr(-1) ). This leads to improvements in the structure of the seasonal cycle, including earlier dry season GPP loss and enhanced peak-to-trough GPP in tropical forests within the Amazon Basin and reduced growing season length in northern croplands and deciduous forests. Uncertainty in predicted GPP (estimated from the spread of DGVMs) is reduced by 40-70% during peak productivity suggesting the assimilation of GOSAT SIF with models is well-suited for benchmarking. We conclude that satellite fluorescence augurs a new opportunity to quantify the GPP response to climate drivers and the potential to constrain predictions of carbon cycle evolution.

Ecological functioning in grass-shrub Mediterranean ecosystems measured by eddy covariance.

Climate change may alter ecosystem functioning, as assessed via the net carbon (C) exchange (NEE) with the atmosphere, composed of the biological processes photosynthesis (GPP) and respiration (R(eco)). In addition, in semi-arid Mediterranean ecosystems, a significant fraction of respired CO2 is stored in the vadose zone and emitted afterwards by subsoil ventilation (VE), contributing also to NEE. Such conditions complicate the prediction of NEE for future change scenarios. To evaluate the possible effects of climate change on annual NEE and its underlying processes (GPP, R(eco) and VE) we present, over a climate/altitude range, the annual and interannual variability of NEE, GPP, R(eco) and VE in three Mediterranean sites. We found that annual NEE varied from a net source of around 130 gC m(-2) in hot and arid lowlands to a net sink of similar magnitude for alpine meadows (above 2,000 m a.s.l) that are less water stressed. Annual net C fixation increased because of increased GPP during intermittent and several growth periods occurring even during winter, as well as due to decreased VE. In terms of interannual variability, the studied subalpine site behaved as a neutral C sink (from emission of 49 to fixation of 30 gC m(-2) year(-1)), with precipitation as the main factor controlling annual GPP and R(eco). Finally, the importance of VE as 0-23% of annual NEE is highlighted, indicating that this process could shift some Mediterranean ecosystems from annual C sinks to sources.

Leaf-level coordination principles propagate to the ecosystem scale.

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.