Predicting ecosystem productivity based on plant community traits

The integration of plant functional traits to improve predictions of ecosystem productivity holds many opportunities, especially considering that intrinsic links are expected between plant traits and ecosystem function.We present a novel framework for ‘trait-based productivity’ (TBP) enabling the prediction of productivity-related ecosystem functions from plant community traits and environmental conditions.The TBP framework takes an emergent perspective considering the ecosystem as a whole, in which individual plant traits scale up to community-scale ‘traits’ that in combination influence ecosystem functions.The TBP framework has potential to drive a new generation of ecological models at a wide range of spatial scales, informed by species’ traits derived from open access trait databases and high-resolution remote sensing imagery data. With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change. With the rapid accumulation of plant trait data, major opportunities have arisen for the integration of these data into predicting ecosystem primary productivity across a range of spatial extents. Traditionally, traits have been used to explain physiological productivity at cell, organ, or plant scales, but scaling up to the ecosystem scale has remained challenging. Here, we show the need to combine measures of community-level traits and environmental factors to predict ecosystem productivity at landscape or biogeographic scales. We show how theory can extend the production ecology equation to enormous potential for integrating traits into ecological models that estimate productivity-related ecosystem functions across ecological scales and to anticipate the response of terrestrial ecosystems to global change. For decades, plant functional traits have been used for mechanistic analysis and prediction of processes at a wide range of ecological scales, from organs to species to ecosystems [1.Violle C. et al.Let the concept of trait be functional.Oikos. 2007; 116: 882-892Crossref Scopus (3034) Google Scholar, 2.McGill B.J. et al.Rebuilding community ecology from functional traits.Trends Ecol. Evol. 2006; 21: 178-185Abstract Full Text Full Text PDF PubMed Scopus (3128) Google Scholar, 3.Levine J.M. A trail map for trait-based studies.Nature. 2016; 529: 163-164Crossref PubMed Scopus (37) Google Scholar, 4.Mittelbach G.G. McGill B.J. Community Ecology. Oxford University Press, 2019Crossref Google Scholar, 5.Sack L. et al.How do leaf veins influence the worldwide leaf economic spectrum? Review and synthesis.J. Exp. Bot. 2013; 64: 4053-4080Crossref PubMed Scopus (165) Google Scholar]. 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The enigma of terrestrial primary productivity: measurements, models, scales and the diversity–productivity relationship.Ecography. 2017; 40: 239-252Crossref Scopus (50) Google Scholar, 24.Zhang Y. et al.Advances in hyperspectral remote sensing of vegetation traits and functions.Remote Sens. Environ. 2021; 252112121Crossref PubMed Scopus (38) Google Scholar, 25.He L. et al.Diverse photosynthetic capacity of global ecosystems mapped by satellite chlorophyll fluorescence measurements.Remote Sens. Environ. 2019; 232111344Crossref PubMed Scopus (50) Google Scholar]. Yet, currently, differences in annual GPP among ecosystems are determined primarily by the quantity of photosynthetic tissue and the intensity and seasonality of its activity, not taking into account a wide range of other available traits. While efforts have been made to directly scale up from individual plant traits and community-scale traits to ecosystem productivity, and traits have been used as inputs into dynamic vegetation models to determine photosynthesis and thereby ecosystem productivity, new approaches are needed to incorporate the wide range of all available effect traits. This more comprehensive approach, along with taking into account environmental factors, should allow for determining the variation in productivity within and among natural ecosystems. Substantial gaps have existed in the ability to link plant traits with productivity in a meaningful way. Although a number of hypotheses exist for relating functional traits to ecosystem productivity (Box 1), challenges arise when trying to generalize these ideas. First, there is no consensus on how the productivity of naturally assembled or experimental systems (such as plantations and crop fields) depends on traits that would contribute to growth [26.Genung M.A. et al.Species loss drives ecosystem function in experiments, but in nature the importance of species loss depends on dominance.Glob. Ecol. Biogeogr. 2020; 29: 1531-1541Crossref Scopus (24) Google Scholar]. For example, the growth rate hypothesis of stoichiometric ecology postulates that higher productivity would arise from a lower N:P ratio (i.e., a higher concentration of phosphorus) in agricultural fields or controlled experiments due to the increased demand for rRNA production needed to sustain rapid growth, yet no evidence has supported this hypothesis in naturally assembled communities [27.Elser J. et al.Growth rate–stoichiometry couplings in diverse biota.Ecol. Lett. 2003; 6: 936-943Crossref Scopus (746) Google Scholar,28.Elser J.J. et al.Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems.Ecol. Lett. 2007; 10: 1135-1142Crossref PubMed Scopus (3221) Google Scholar]. Indeed, tropical forests generally have both higher GPP and N:P ratio than cool temperate forests [28.Elser J.J. et al.Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems.Ecol. Lett. 2007; 10: 1135-1142Crossref PubMed Scopus (3221) Google Scholar], and grasslands, typically less productive than forests, also have higher leaf N:P [29.Tian D. et al.Global leaf nitrogen and phosphorus stoichiometry and their scaling exponent.Natl. Sci. Rev. 2018; 5: 728-739Crossref Scopus (114) Google Scholar]. Evidently, in natural communities, dominant species, which contribute strongly to GPP, may have moderate or high N:P ratios but prevail due to stress tolerance, in contrast with agricultural fields and experimental plantations, in which the fastest growing species, with low N:P, would dominate, as these systems are under continuous management and/or protection from drought, competition, pests, and other stresses. Therefore, it remains unclear if there is a general application of stoichiometric principles to derive trait–productivity relationships. Second, the scaling of traits from organ and even species to ecosystem scales often runs into challenging and complex transmutation problems. It is self-evident that a combination of a large number of traits will influence productivity, and, as highlighted by the Jensen’s inequality, the average of a function is not the function of the average due to the perturbation of nonlinearity and variation [30.McGill B.J. The what, how and why of doing macroecology.Glob. Ecol. Biogeogr. 2019; 28: 6-17Crossref Scopus (60) Google Scholar]. Yet, as many studies found that the net assimilation rate of leaves is highly correlated across species with traits such as specific leaf area (SLA) and mass-based leaf nitrogen concentration (N, mg g−1) [31.Reich P.B. The world-wide ‘fast–slow’ plant economics spectrum: a traits manifesto.J. Ecol. 2014; 102: 275-301Crossref Scopus (2062) Google Scholar, 32.Reich P.B. et al.Generality of leaf trait relationships: a test across six biomes.Ecology. 1999; 80: 1955-1969Crossref Scopus (1096) Google Scholar, 33.Field C. Mooney H. Photosynthesis – nitrogen relationship in wild plants.in: On the Economy of Plant Form and Function: Proceedings of the Sixth Maria Moors Cabot Symposium, Evolutionary Constraints on Primary Productivity, Adaptive Patterns of Energy Capture in Plants, Harvard Forest, August 1983. Cambridge University Press, 1986Google Scholar], such univariate relationships have inspired many studies to treat complex plant communities as a simple big-leaf model (averaging the properties of all leaves) or a multilayer model (treating sunlit and shaded leaves in each layer separately) to scale linearly from organ and leaf levels to processes occurring at the level of groups of leaves or canopies and thereby simulate primary productivity at the ecosystem level [34.Kull O. Jarvis P.G. The role of nitrogen in a simple scheme to scale up photosynthesis from leaf to canopy.Plant Cell Environ. 1995; 18: 1174-1182Crossref Scopus (114) Google Scholar, 35.Farquhar G.D. Models of integrated photosynthesis of cells and leaves.Philos. Trans. R. Soc. Lond. B Biol. Sci. 1989; 323: 357-367Crossref Google Scholar, 36.Luo X. et al.Comparison of big-leaf, two-big-leaf, and two-leaf upscaling schemes for evapotranspiration estimation using coupled carbon-water modeling.J. Geophys. Res. Biogeosci. 2018; 123: 207-225Crossref Scopus (54) Google Scholar]. This direct upscaling of leaf biochemical traits has not generally been validated, and the associated uncertainty increases with the spatial scale considered (Figure 1) [30.McGill B.J. The what, how and why of doing macroecology.Glob. Ecol. Biogeogr. 2019; 28: 6-17Crossref Scopus (60) Google Scholar]. For example, the optimal temperature for the parameters of leaf photosynthetic physiology, such as electron transport rate and maximum rate of carboxylation by Rubisco, does not predict those considered at the ecosystem level [37.Huang M. et al.Air temperature optima of vegetation productivity across global biomes.Nat. Ecol. Evol. 2019; 3: 772-779Crossref PubMed Scopus (234) Google Scholar]. Indeed, for ecosystems across elevation gradients, leaf-level photosynthetic parameters, such as the maximum rates of carboxylation of Rubisco (Vcmax) and electron transport (Jmax), do not decline with elevation and may even increase, whereas ecosystem-level productivity (such as GPP and NPP) declines with elevation [38.Malhi Y. et al.The variation of productivity and its allocation along a tropical elevation gradient: a whole carbon budget perspective.New Phytol. 2017; 214: 1019-1032Crossref PubMed Scopus (104) Google Scholar]. These challenges point to the necessity for clear matching of processes and scales when estimating ecosystem processes from traits [39.McGill B.J. Matters of scale.Science. 2010; 328: 575Crossref PubMed Scopus (271) Google Scholar], though such matching has not been applied in many recent studies that found weak relationships between ecosystem processes and single traits or finding relationships but of unclear causality [40.Harfoot M.B. et al.Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.PLoS Biol. 2014; 12e1001841Crossref PubMed Scopus (130) Google Scholar,41.Li Y. et al.Leaf size of woody dicots predicts ecosystem primary productivity.Ecol. Lett. 2020; 23: 1003-1013Crossref PubMed Scopus (31) Google Scholar]. Overall, optimism in using this reductionist approach must be tempered.Box 1The basic concepts of the major hypotheses for trait-based ecosystem functionVegetation, as the primary producer, plays a dominant role in shaping ecosystem function. There are five major hypotheses in trait-based ecology for the role of plants in driving ecosystem functions.(i)The mass ratio hypothesis, also known as the dominance hypothesis [83.Grime J.P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects.J. Ecol. 1998; 86: 902-910Crossref Scopus (1939) Google Scholar], holds that the traits of the dominant species are more important than species richness per se, in determining ecosystem processes, and thus predictions should be made on the basis of scaling the species’ trait values by their contribution to vegetation biomass, often by calculating a CWM [6.Garnier E. et al.Plant functional markers capture ecosystem properties during secondary succession.Ecology. 2004; 85: 2630-2637Crossref Scopus (1548) Google Scholar].(ii)The functional complementarity hypothesis holds that the difference in trait values among the organisms in a community influences ecosystem processes through mechanisms such as complementary resource use. Thus, positive relationships are expected between ecosystem functions and indices capturing the community functional diversity [84.Wang R. et al.Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity.Sci. Rep. 2015; 5: 14454Crossref PubMed Scopus (80) Google Scholar], including single-trait indicators (1D indices), such as FDvar (functional logarithmic variance) and multiple-trait indicators (multidimensional indices), such as FDQ (Rao’s quadratic entropy) [85.Mouchet M.A. et al.Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules.Funct. Ecol. 2010; 24: 867-876Crossref Scopus (1047) Google Scholar].(iii)The growth rate hypothesis predicts that organisms with higher growth rate (the rate of change in biomass per unit biomass) also have higher P concentration and lower C∶P and N∶P ratios [27.Elser J. et al.Growth rate–stoichiometry couplings in diverse biota.Ecol. Lett. 2003; 6: 936-943Crossref Scopus (746) Google Scholar,28.Elser J.J. et al.Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems.Ecol. Lett. 2007; 10: 1135-1142Crossref PubMed Scopus (3221) Google Scholar].(iv)The vegetation quantity hypothesis (also known as the green soup hypothesis) holds that productivity is mainly driven by vegetation biomass, regardless of traits; that is, vegetation ‘quantity’ is more important than ‘quality’ [45.Lohbeck M. et al.Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.Ecology. 2015; 96: 1242-1252Crossref PubMed Scopus (183) Google Scholar]. This idea has also been referred to as a trait-based approach, if biomass is considered a performance trait [86.Enquist B.J. et al.Scaling from traits to ecosystems: developing a general trait driver theory via integrating trait-based and metabolic scaling theories.Adv. Ecol. Res. 2015; 52: 249-318Crossref Scopus (248) Google Scholar].(v)The ecosystem allometry approach also does not consider plant traits and only biomass, placing an emphasis on the size distribution of individual plants within communities [7.Garnier E. et al.Plant Functional Diversity: Organism Traits, Community Structure, and Ecosystem Properties. Oxford University Press, 2016Google Scholar,87.Kerkhoff A.J. et al.Plant allometry, stoichiometry and the temperature-dependence of primary productivity.Glob. Ecol. Biogeogr. 2005; 14: 585-598Crossref Scopus (272) Google Scholar], and predicting NPP = ∑k=0K nk × βg × MT(k)3/4, where nk is the number of individuals present per m2 in the size class k, and βg is an allometric coefficient (as a constant regardless of species) linking the absolute growth rate of the whole plant with its total biomass (MT), and the 3/4 scaling exponent is attributed to constraints imposed by resource distribution within cells and plants [88.Brown J.H. et al.Toward a metabolic theory of ecology.Ecology. 2004; 85: 1771-1789Crossref Scopus (5110) Google Scholar]. Vegetation, as the primary producer, plays a dominant role in shaping ecosystem function. There are five major hypotheses in trait-based ecology for the role of plants in driving ecosystem functions.(i)The mass ratio hypothesis, also known as the dominance hypothesis [83.Grime J.P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects.J. Ecol. 1998; 86: 902-910Crossref Scopus (1939) Google Scholar], holds that the traits of the dominant species are more important than species richness per se, in determining ecosystem processes, and thus predictions should be made on the basis of scaling the species’ trait values by their contribution to vegetation biomass, often by calculating a CWM [6.Garnier E. et al.Plant functional markers capture ecosystem properties during secondary succession.Ecology. 2004; 85: 2630-2637Crossref Scopus (1548) Google Scholar].(ii)The functional complementarity hypothesis holds that the difference in trait values among the organisms in a community influences ecosystem processes through mechanisms such as complementary resource use. Thus, positive relationships are expected between ecosystem functions and indices capturing the community functional diversity [84.Wang R. et al.Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity.Sci. Rep. 2015; 5: 14454Crossref PubMed Scopus (80) Google Scholar], including single-trait indicators (1D indices), such as FDvar (functional logarithmic variance) and multiple-trait indicators (multidimensional indices), such as FDQ (Rao’s quadratic entropy) [85.Mouchet M.A. et al.Functional diversity measures: an overview of their redundancy and their ability to discriminate community assembly rules.Funct. Ecol. 2010; 24: 867-876Crossref Scopus (1047) Google Scholar].(iii)The growth rate hypothesis predicts that organisms with higher growth rate (the rate of change in biomass per unit biomass) also have higher P concentration and lower C∶P and N∶P ratios [27.Elser J. et al.Growth rate–stoichiometry couplings in diverse biota.Ecol. Lett. 2003; 6: 936-943Crossref Scopus (746) Google Scholar,28.Elser J.J. et al.Global analysis of nitrogen and phosphorus limitation of primary producers in freshwater, marine and terrestrial ecosystems.Ecol. Lett. 2007; 10: 1135-1142Crossref PubMed Scopus (3221) Google Scholar].(iv)The vegetation quantity hypothesis (also known as the green soup hypothesis) holds that productivity is mainly driven by vegetation biomass, regardless of traits; that is, vegetation ‘quantity’ is more important than ‘quality’ [45.Lohbeck M. et al.Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.Ecology. 2015; 96: 1242-1252Crossref PubMed Scopus (183) Google Scholar]. This idea has also been referred to as a trait-based approach, if biomass is considered a performance trait [86.Enquist B.J. et al.Scaling from traits to ecosystems: developing a general trait driver theory via integrating trait-based and metabolic scaling theories.Adv. Ecol. Res. 2015; 52: 249-318Crossref Scopus (248) Google Scholar].(v)The ecosystem allometry approach also does not consider plant traits and only biomass, placing an emphasis on the size distribution of individual plants within communities [7.Garnier E. et al.Plant Functional Diversity: Organism Traits, Community Structure, and Ecosystem Properties. Oxford University Press, 2016Google Scholar,87.Kerkhoff A.J. et al.Plant allometry, stoichiometry and the temperature-dependence of primary productivity.Glob. Ecol. Biogeogr. 2005; 14: 585-598Crossref Scopus (272) Google Scholar], and predicting NPP = ∑k=0K nk × βg × MT(k)3/4, where nk is the number of individuals present per m2 in the size class k, and βg is an allometric coefficient (as a constant regardless of species) linking the absolute growth rate of the whole plant with its total biomass (MT), and the 3/4 scaling exponent is attributed to constraints imposed by resource distribution within cells and plants [88.Brown J.H. et al.Toward a metabolic theory of ecology.Ecology. 2004; 85: 1771-1789Crossref Scopus (5110) Google Scholar]. In particular, scaling up from traits to ecosystem functions requires adequate consideration of matching size and units. For a long time, the weighted average of individual traits within a community based on the mass ratio hypothesis has been tacitly adopted to represent community-level traits. Indeed, the community-weighted mean (CWM) trait value reflects the central behavior of species; for example, higher CWM leaf nutrient concentrations, in particular nitrogen, typically indicate a community dominated by individuals of fast-growing acquisitive species with higher light-saturated photosynthetic rates [7.Garnier E. et al.Plant Functional Diversity: Organism Traits, Community Structure, and Ecosystem Properties. Oxford University Press, 2016Google Scholar,42.Wright S.J. et al.Functional traits and the growth–mortality trade-off in tropical trees.Ecology. 2010; 91: 3664-3674Crossref PubMed Scopus (708) Google Scholar], and with a relatively high ecosystem (production) efficiency [6.Garnier E. et al.Plant functional markers capture ecosystem properties during secondary succession.Ecology. 2004; 85: 2630-2637Crossref Scopus (1548) Google Scholar,10.Reich P.B. et al.From tropics to tundra: global convergence in plant functioning.Proc. Natl. Acad. Sci. U. S. A. 1997; 94: 13730-13734Crossref PubMed Scopus (1845) Google Scholar]. Nonetheless, high light-saturated photosynthetic rates per unit leaf area or mass provide limited information about the carbon uptake of the entire plant under typical conditions [43.Yang J. et al.Why functional traits do not predict tree demographic rates.Trends Ecol. Evol. 2018; 33: 326-336Abstract Full Text Full Text PDF PubMed Scopus (128) Google Scholar,44.Rubio V.E. et al.Improving predictions of tropical tree survival and growth by incorporating measurements of whole leaf allocation.J. Ecol. 2021; 109: 1331-1343Crossref Scopus (5) Google Scholar], let alone the carbon capture capacity of the ecosystem considered per land area. Meanwhile, both the vegetation quantity hypothesis and the metabolic scaling theory based on allomorphic growth consider biomass as a proxy for community size, an approach supported by a large body of empirical evidence for predicting productivity-related ecosystem functions [45.Lohbeck M. et al.Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.Ecology. 2015; 96: 1242-1252Crossref PubMed Scopus (183) Google Scholar, 46.Prado-Junior J.A. et al.Conservative species drive biomass productivity in tropical dry forests.J. Ecol. 2016; 104: 817-827Crossref Scopus (171) Google Scholar, 47.Heckman R.W. et al.Plant biomass, not plant economics traits, determines responses of soil CO2 efflux to precipitation in the C4 grass Panicum virgatum.J. Ecol. 2020; 108: 2095-2106Crossref Scopus (7) Google Scholar, 48.Enquist B.J. et al.A general integrative model for scaling plant growth, carbon flux, and functional trait spectra.Nature. 2007; 449: 218-222Crossref PubMed Scopus (183) Google Scholar]. Nevertheless, the complexity of trait variation and of the ecosystems themselves render them not immediately amenable to the simple reductionist approach of scaling up directly from biomass (Box 1). Furthermore, it is unclear how to scale up from biomass for the prediction of ecosystem function while integrating multiple leaf traits and environmental variables, which a rich body of evidence indicates would influence ecosystem properties. New ways to integrate plant traits and community or ecosystem contextual information are necessary. As a new approach to predict ecosystem function from underlying processes (Box 1), the calculation of ‘ecosystem traits’ (‘community traits’) was recently proposed [9.He N.P. et al.Ecosystem traits linking functional traits to macroecology.Trends Ecol. Evol. 2019; 34: 200-210Abstract Full Text Full Text PDF PubMed Scopus (128) Google Scholar] (Table 1 and Box 2). Calculation of plant community traits involves scaling-up and scale-matching traits measured at the organ level to derive a trait value per land area; these plant community traits can then be tested for correlation with ecosystem functioning across natural ecosystems [9.He N.P. et al.Ecosystem traits linking functional traits to macroecology.Trends Ecol. Evol. 2019; 34: 200-210Abstract Full Text Full Text PDF PubMed Scopus (128) Google Scholar,49.He N.P. et al.Variation in leaf anatomical traits from tropical to cold-temperate forests and linkage to ecosystem functions.Funct. Ecol. 2018; 32: 10-19Crossref Scopus (79) Google Scholar]. Such scaled-up versions of ‘effect traits’ [50.Suding K.N. et al.Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants.Glob. Chang. Biol. 2008; 14: 1125-1140Crossref Scopus (880) Google Scholar] have strong promise