Convergence in phosphorus constraints to photosynthesis in forests around the world.

Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements.

Direct evidence for phosphorus limitation on Amazon forest productivity.

The productivity of rainforests growing on highly weathered tropical soils is expected to be limited by phosphorus availability1. Yet, controlled fertilization experiments have been unable to demonstrate a dominant role for phosphorus in controlling tropical forest net primary productivity. Recent syntheses have demonstrated that responses to nitrogen addition are as large as to phosphorus2, and adaptations to low phosphorus availability appear to enable net primary productivity to be maintained across major soil phosphorus gradients3. Thus, the extent to which phosphorus availability limits tropical forest productivity is highly uncertain. The majority of the Amazonia, however, is characterized by soils that are more depleted in phosphorus than those in which most tropical fertilization experiments have taken place2. Thus, we established a phosphorus, nitrogen and base cation addition experiment in an old growth Amazon rainforest, with a low soil phosphorus content that is representative of approximately 60% of the Amazon basin. Here we show that net primary productivity increased exclusively with phosphorus addition. After 2 years, strong responses were observed in fine root (+29%) and canopy productivity (+19%), but not stem growth. The direct evidence of phosphorus limitation of net primary productivity suggests that phosphorus availability may restrict Amazon forest responses to CO2 fertilization4, with major implications for future carbon sequestration and forest resilience to climate change.

Leaf nitrogen from the perspective of optimal plant function.

Leaf dry mass per unit area (LMA), carboxylation capacity (V cmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and V cmax at 25°C (V cmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to V cmax25 and LMA. Relationships of observed V cmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and V cmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean V cmax25, 43% in LMA and 31% in Narea. Predicted V cmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils. Synthesis. Global patterns of variation in observed site-mean Narea can be explained by climate-induced variations in optimal V cmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of V cmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole-plant carbon allocation, rather than via leaf-level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.

Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees?

Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from -0.003 to -0.065 µmol CO2 m-2 s-1 day-1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees.

Local hydrological gradients structure high intraspecific variability in plant hydraulic traits in two dominant central Amazonian tree species.

Addressing the intraspecific variability of functional traits helps understand how climate change might influence the distribution of organismal traits across environments, but this is notably understudied in the Amazon, especially for plant hydraulic traits commonly used to project drought responses. We quantified the intraspecific trait variability of leaf mass per area, wood density, and xylem embolism resistance for two dominant central Amazonian tree species, along gradients of water and light availability, while accounting for tree age and height. Intraspecific variability in hydraulic traits was high, with within-species variability comparable to the whole-community variation. Hydraulic trait variation was modulated mostly by the hydrological environment, with higher embolism resistance of trees growing on deep-water-table plateaus compared with shallow-water-table valleys. Intraspecific variability of leaf mass per area and wood density was mostly modulated by intrinsic factors and light. The different environmental and intrinsic drivers of variation among and within individuals lead to an uncoupled coordination among carbon acquisition/conservation and water-use traits. Our findings suggest multivariate ecological strategies driving tropical tree distributions even within species, and reflect differential within-population sensitivities along environmental gradients. Therefore, intraspecific trait variability must be considered for accurate predictions of the responses of tropical forests to climate change.

Global climate and nutrient controls of photosynthetic capacity.

There is huge uncertainty about how global exchanges of carbon between the atmosphere and land will respond to continuing environmental change. A better representation of photosynthetic capacity is required for Earth System models to simulate carbon assimilation reliably. Here we use a global leaf-trait dataset to test whether photosynthetic capacity is quantitatively predictable from climate, based on optimality principles; and to explore how this prediction is modified by soil properties, including indices of nitrogen and phosphorus availability, measured in situ. The maximum rate of carboxylation standardized to 25 °C (Vcmax25) was found to be proportional to growing-season irradiance, and to increase-as predicted-towards both colder and drier climates. Individual species' departures from predicted Vcmax25 covaried with area-based leaf nitrogen (Narea) but community-mean Vcmax25 was unrelated to Narea, which in turn was unrelated to the soil C:N ratio. In contrast, leaves with low area-based phosphorus (Parea) had low Vcmax25 (both between and within communities), and Parea increased with total soil P. These findings do not support the assumption, adopted in some ecosystem and Earth System models, that leaf-level photosynthetic capacity depends on soil N supply. They do, however, support a previously-noted relationship between photosynthesis and soil P supply.

Small tropical forest trees have a greater capacity to adjust carbon metabolism to long-term drought than large canopy trees.

The response of small understory trees to long-term drought is vital in determining the future composition, carbon stocks and dynamics of tropical forests. Long-term drought is, however, also likely to expose understory trees to increased light availability driven by drought-induced mortality. Relatively little is known about the potential for understory trees to adjust their physiology to both decreasing water and increasing light availability. We analysed data on maximum photosynthetic capacity (Jmax , Vcmax ), leaf respiration (Rleaf ), leaf mass per area (LMA), leaf thickness and leaf nitrogen and phosphorus concentrations from 66 small trees across 12 common genera at the world's longest running tropical rainfall exclusion experiment and compared responses to those from 61 surviving canopy trees. Small trees increased Jmax , Vcmax , Rleaf and LMA (71, 29, 32, 15% respectively) in response to the drought treatment, but leaf thickness and leaf nutrient concentrations did not change. Small trees were significantly more responsive than large canopy trees to the drought treatment, suggesting greater phenotypic plasticity and resilience to prolonged drought, although differences among taxa were observed. Our results highlight that small tropical trees have greater capacity to respond to ecosystem level changes and have the potential to regenerate resilient forests following future droughts.

Global photosynthetic capacity is optimized to the environment.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax ), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Mapping local and global variability in plant trait distributions.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Leaf-level photosynthetic capacity in lowland Amazonian and high-elevation Andean tropical moist forests of Peru.

We examined whether variations in photosynthetic capacity are linked to variations in the environment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/western Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax ), and the maximum rate of electron transport (Jmax )), leaf mass, nitrogen (N) and phosphorus (P) per unit leaf area (Ma , Na and Pa , respectively), and chlorophyll from 210 species at 18 field sites along a 3300-m elevation gradient. Western blots were used to quantify the abundance of the CO2 -fixing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than lowland TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efficiency. At any given Na and Pa , the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a small subset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in defining the photosynthetic capacity of TMFs, with variations in N allocation and Rubisco activation state further influencing photosynthetic rates and N-use efficiency of these critically important forests.

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis.

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax ). Estimating this parameter using A-Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci ) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat ) measurements, from which Vcmax can be extracted using a 'one-point method'. We used a global dataset of A-Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'. If leaf respiration during the day (Rday ) is known exactly, Vcmax can be estimated with an r(2) value of 0.98 and a root-mean-squared error (RMSE) of 8.19 µmol m(-2) s(-1) . However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r(2) of 0.95 and an RMSE of 17.1 µmol m(-2) s(-1) . The one-point method provides a robust means to expand current databases of field-measured Vcmax , giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation.

Model-data synthesis for the next generation of forest free-air CO2 enrichment (FACE) experiments.

The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits.

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits.

Leaf dark respiration (Rdark ) is an important yet poorly quantified component of the global carbon cycle. Given this, we analyzed a new global database of Rdark and associated leaf traits. Data for 899 species were compiled from 100 sites (from the Arctic to the tropics). Several woody and nonwoody plant functional types (PFTs) were represented. Mixed-effects models were used to disentangle sources of variation in Rdark . Area-based Rdark at the prevailing average daily growth temperature (T) of each site increased only twofold from the Arctic to the tropics, despite a 20°C increase in growing T (8-28°C). By contrast, Rdark at a standard T (25°C, Rdark (25) ) was threefold higher in the Arctic than in the tropics, and twofold higher at arid than at mesic sites. Species and PFTs at cold sites exhibited higher Rdark (25) at a given photosynthetic capacity (Vcmax (25) ) or leaf nitrogen concentration ([N]) than species at warmer sites. Rdark (25) values at any given Vcmax (25) or [N] were higher in herbs than in woody plants. The results highlight variation in Rdark among species and across global gradients in T and aridity. In addition to their ecological significance, the results provide a framework for improving representation of Rdark in terrestrial biosphere models (TBMs) and associated land-surface components of Earth system models (ESMs).

The relationship of leaf photosynthetic traits - V cmax and J max - to leaf nitrogen, leaf phosphorus, and specific leaf area: a meta-analysis and modeling study.

Great uncertainty exists in the global exchange of carbon between the atmosphere and the terrestrial biosphere. An important source of this uncertainty lies in the dependency of photosynthesis on the maximum rate of carboxylation (V cmax) and the maximum rate of electron transport (J max). Understanding and making accurate prediction of C fluxes thus requires accurate characterization of these rates and their relationship with plant nutrient status over large geographic scales. Plant nutrient status is indicated by the traits: leaf nitrogen (N), leaf phosphorus (P), and specific leaf area (SLA). Correlations between V cmax and J max and leaf nitrogen (N) are typically derived from local to global scales, while correlations with leaf phosphorus (P) and specific leaf area (SLA) have typically been derived at a local scale. Thus, there is no global-scale relationship between V cmax and J max and P or SLA limiting the ability of global-scale carbon flux models do not account for P or SLA. We gathered published data from 24 studies to reveal global relationships of V cmax and J max with leaf N, P, and SLA. V cmax was strongly related to leaf N, and increasing leaf P substantially increased the sensitivity of V cmax to leaf N. J max was strongly related to V cmax, and neither leaf N, P, or SLA had a substantial impact on the relationship. Although more data are needed to expand the applicability of the relationship, we show leaf P is a globally important determinant of photosynthetic rates. In a model of photosynthesis, we showed that at high leaf N (3 gm(-2)), increasing leaf P from 0.05 to 0.22 gm(-2) nearly doubled assimilation rates. Finally, we show that plants may employ a conservative strategy of J max to V cmax coordination that restricts photoinhibition when carboxylation is limiting at the expense of maximizing photosynthetic rates when light is limiting.

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites.

AIM: The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. LOCATION: Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1. METHODS: Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. RESULTS: The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. MAIN CONCLUSIONS: Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Foliar trait contrasts between African forest and savanna trees: genetic versus environmental effects.

Variations in leaf mass per unit area (Ma) and foliar concentrations of N, P, C, K, Mg and Ca were determined for 365 trees growing in 23 plots along a West African precipitation gradient ranging from 0.29 to 1.62m a-1. Contrary to previous studies, no marked increase in Ma with declining precipitation was observed, but savanna tree foliar [N] tended to be higher at the drier sites (mass basis). Generally, Ma was slightly higher and [N] slightly lower for forest vs savanna trees with most of this difference attributable to differences in soil chemistry. No systematic variations in [P], [Mg] and [Ca] with precipitation or between trees of forest vs savanna stands were observed. We did, however, find a marked increase in foliar [K] of savanna trees as precipitation declined, with savanna trees also having a significantly lower [K] than those of nearby forest. These differences were not related to differences in soil nutrient status and were accompanied by systematic changes in [C] of opposite sign. We suggest an important but as yet unidentified role for K in the adaption of savanna species to periods of limited water availability; with foliar [K] being also an important factor differentiating tree species adapted to forest vs savanna soils within the 'zone of transition' of Western Africa.

Variations in Amazon forest productivity correlated with foliar nutrients and modelled rates of photosynthetic carbon supply.

The rate of above-ground woody biomass production, W(P), in some western Amazon forests exceeds those in the east by a factor of 2 or more. Underlying causes may include climate, soil nutrient limitations and species composition. In this modelling paper, we explore the implications of allowing key nutrients such as N and P to constrain the photosynthesis of Amazon forests, and also we examine the relationship between modelled rates of photosynthesis and the observed gradients in W(P). We use a model with current understanding of the underpinning biochemical processes as affected by nutrient availability to assess: (i) the degree to which observed spatial variations in foliar [N] and [P] across Amazonia affect stand-level photosynthesis; and (ii) how these variations in forest photosynthetic carbon acquisition relate to the observed geographical patterns of stem growth across the Amazon Basin. We find nutrient availability to exert a strong effect on photosynthetic carbon gain across the Basin and to be a likely important contributor to the observed gradient in W(P). Phosphorus emerges as more important than nitrogen in accounting for the observed variations in productivity. Implications of these findings are discussed in the context of future tropical forests under a changing climate.

Life form-specific variations in leaf water oxygen-18 enrichment in Amazonian vegetation.

Leaf water (18)O enrichment (Delta(o)) influences the isotopic composition of both gas exchange and organic matter, with Delta(o) values responding to changes in atmospheric parameters. In order to examine possible influences of plant parameters on Delta(o) dynamics, we measured oxygen isotope ratios (delta(18)O) of leaf and stem water on plant species representing different life forms in Amazonia forest and pasture ecosystems. We conducted two field experiments: one in March (wet season) and another in September (dry season) 2004. In each experiment, leaf and stem samples were collected at 2-h intervals at night and hourly during the day for 50 h from eight species including upper-canopy forest trees, upper-canopy forest lianas, and lower-canopy forest trees, a C(4) pasture grass and a C(3) pasture shrub. Significant life form-related differences were detected in (18)O leaf water values. Initial modeling efforts to explain these observations over-predicted nighttime Delta(o) values by as much as 10 per thousand. Across all species, errors associated with measured values of the delta(18)O of atmospheric water vapor (delta(v)) appeared to be largely responsible for the over-predictions of nighttime Delta(o) observations. We could not eliminate collection or storage of water vapor samples as a possible error and therefore developed an alternative, plant-based method for estimating the daily average delta(v) value in the absence of direct (reliable) measurements. This approach differs from the common assumption that isotopic equilibrium exists between water vapor and precipitation water, by including transpiration-based contributions from local vegetation through (18)O measurements of bulk leaf water. Inclusion of both modified delta(v) and non-steady state features resulted in model predictions that more reliably predicted both the magnitude and temporal patterns observed in the data. The influence of life form-specific patterns of Delta(o) was incorporated through changes in the effective path length, an important but little known parameter associated with the Péclet effect.