Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including ...variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.
•We assess mechanisms regulating evapotranspiration (E) in Amazonia and cerrado.•Groundwater and deep root uptake can both sustain E during the dry season.•Canopy stomatal conductance regulates E ...even at sites with little water limitation.•Models capturing observed patterns in E may still poorly represent these mechanisms.•Model developments should focus on improved biological controls on E.
Evapotranspiration (E) in the Amazon connects forest function and regional climate via its role in precipitation recycling However, the mechanisms regulating water supply to vegetation and its demand for water remain poorly understood, especially during periods of seasonal water deficits In this study, we address two main questions: First, how do mechanisms of water supply (indicated by rooting depth and groundwater) and vegetation water demand (indicated by stomatal conductance and intrinsic water use efficiency) control evapotranspiration (E) along broad gradients of climate and vegetation from equatorial Amazonia to Cerrado, and second, how do these inferred mechanisms of supply and demand compare to those employed by a suite of ecosystem models? We used a network of eddy covariance towers in Brazil coupled with ancillary measurements to address these questions With respect to the magnitude and seasonality of E, models have much improved in equatorial tropical forests by eliminating most dry season water limitation, diverge in performance in transitional forests where seasonal water deficits are greater, and mostly capture the observed seasonal depressions in E at Cerrado However, many models depended universally on either deep roots or groundwater to mitigate dry season water deficits, the relative importance of which we found does not vary as a simple function of climate or vegetation In addition, canopy stomatal conductance (gs) regulates dry season vegetation demand for water at all except the wettest sites even as the seasonal cycle of E follows that of net radiation In contrast, some models simulated no seasonality in gs, even while matching the observed seasonal cycle of E. We suggest that canopy dynamics mediated by leaf phenology may play a significant role in such seasonality, a process poorly represented in models Model bias in gs and E, in turn, was related to biases arising from the simulated light response (gross primary productivity, GPP) or the intrinsic water use efficiency of photosynthesis (iWUE). We identified deficiencies in models which would not otherwise be apparent based on a simple comparison of simulated and observed rates of E. While some deficiencies can be remedied by parameter tuning, in most models they highlight the need for continued process development of belowground hydrology and in particular, the biological processes of root dynamics and leaf phenology, which via their controls on E, mediate vegetation-climate feedbacks in the tropics.
Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly ...impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches.
Determining climate change feedbacks from tropical rainforests requires an understanding of how carbon gain through photosynthesis and loss through respiration will be altered. One of the key changes ...that tropical rainforests may experience under future climate change scenarios is reduced soil moisture availability. In this study we examine if and how both leaf photosynthesis and leaf dark respiration acclimate following more than 12 years of experimental soil moisture deficit, via a through‐fall exclusion experiment (TFE) in an eastern Amazonian rainforest. We find that experimentally drought‐stressed trees and taxa maintain the same maximum leaf photosynthetic capacity as trees in corresponding control forest, independent of their susceptibility to drought‐induced mortality. We hypothesize that photosynthetic capacity is maintained across all treatments and taxa to take advantage of short‐lived periods of high moisture availability, when stomatal conductance (gₛ) and photosynthesis can increase rapidly, potentially compensating for reduced assimilate supply at other times. Average leaf dark respiration (Rd) was elevated in the TFE‐treated forest trees relative to the control by 28.2 ± 2.8% (mean ± one standard error). This mean Rd value was dominated by a 48.5 ± 3.6% increase in the Rd of drought‐sensitive taxa, and likely reflects the need for additional metabolic support required for stress‐related repair, and hydraulic or osmotic maintenance processes. Following soil moisture deficit that is maintained for several years, our data suggest that changes in respiration drive greater shifts in the canopy carbon balance, than changes in photosynthetic capacity.
•Three different understory leaf area index (LAIu) retrieval methods are compared.•The three methods show different strengths/weaknesses depending on LAI scale.•Variation in LAIu is significantly ...related to vegetation diversity.
Leaf area index (LAI) is a key ecological indicator for describing the structure of canopies and for modelling energy exchange between atmosphere and biosphere. While LAI of the forest overstory can be accurately assessed over large spatial scales via remote sensing, LAI of the forest understory (LAIu) is still largely ignored in ecological studies and ecosystem modelling due to the fact that it is often too complex to be destructively sampled or approximated by other site parameters. Additionally, so far only few attempts have been made to retrieve understory LAI via remote sensing, because dense canopies with high LAI are often hindering retrieval algorithms to produce meaningful estimates for understory LAI. Consequently, the forest understory still constitutes a poorly investigated research realm impeding ecological studies to properly account for its contribution to the energy absorption capacity of forest stands. This study aims to compare three conceptually different indirect retrieval methodologies for LAIu over a diverse panel of forest understory types distributed across Europe. For this we carried out near-to-surface measurements of understory reflectance spectra as well as digital surface photography over the extended network of Integrated Carbon Observation System (ICOS) forest ecosystem sites. LAIu was assessed by exploiting the empirical relationship between vegetation cover and light absorption (Beer-Lambert- Bouguer law) as well as by utilizing proposed relationships with two prominent vegetation indices: normalized difference vegetation index (NDVI) and simple ratio (SR). Retrievals from the three methods were significantly correlated with each other (r = 0.63–0.99, RMSE = 0.53–0.72), but exhibited also significant bias depending on the LAI scale. The NDVI based retrieval approach most likely overestimates LAI at productive sites when LAIu > 2, while the simple ratio algorithm overestimates LAIu at sites with sparse understory vegetation and presence of litter or bare soil. The purely empirical method based on the Beer-Lambert law of light absorption seems to offer a good compromise, since it provides reasonable LAIu values at both low and higher LAI ranges. Surprisingly, LAIu variation among sites seems to be largely decoupled from differences in climate and light permeability of the overstory, but significantly increased with vegetation diversity (expressed as species richness) and hence proposes new applications of LAIu in ecological modelling.
► We present the vertically explicit soil organic matter model SOMPROF. ► Test simulations show that the model produces realistic carbon stocks and profiles. ► Simulations show that the SOM profile ...strongly affects the respiration variability.
Most current soil organic matter (SOM) models represent the soil as a bulk without specification of the vertical distribution of SOM in the soil profile. However, the vertical SOM profile may be of great importance for soil carbon cycling, both on short (hours to years) time scale, due to interactions with the soil temperature and moisture profile, as well as on long (years to centuries) time scale because of depth-specific stabilization mechanisms of organic matter. It is likely that a representation of the SOM profile and surface organic layers in SOM models can improve predictions of the response of land surface fluxes to climate and environmental variability. Although models capable of simulating the vertical SOM profile exist, these were generally not developed for large scale predictive simulations and do not adequately represent surface organic horizons. We present SOMPROF, a vertically explicit SOM model, designed for implementation into large scale ecosystem and land surface models. The model dynamically simulates the vertical SOM profile and organic layer stocks based on mechanistic representations of bioturbation, liquid phase transport of organic matter, and vertical distribution of root litter input. We tested the model based on data from an old growth deciduous forest (Hainich) in Germany, and performed a sensitivity analysis of the transport parameters, and the effects of the vertical SOM distribution on temporal variation of heterotrophic respiration. Model results compare well with measured organic carbon profiles and stocks. SOMPROF is able to simulate a wide range of SOM profiles, using parameter values that are realistic compared to those found in previous studies. Results of the sensitivity analysis show that the vertical SOM distribution strongly affects temporal variation of heterotrophic respiration due to interactions with the soil temperature and moisture profile.
Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control ...respiratory variability. We measured leaf, live wood, and soil respiration, along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest. Scaling these fluxes to the ecosystem, and combining our data with results from other studies, we estimated an average total ecosystem respiration ($R_{eco}$) of$7.8 \mumol\cdot m^{-2}\cdot s^{-1}$. Average estimates (per unit ground area) for leaf, wood, soil, total heterotrophic, and total autotrophic respiration were$2.6, 1.1, 3.2, 5.6, and 2.2 \mumol\cdot m^{-2}\cdot s^{-1}$, respectively. Comparing autotrophic respiration with net primary production (NPP) estimates indicated that only ~30% of carbon assimilated in photosynthesis was used to construct new tissues, with the remaining 70% being respired back to the atmosphere as autotrophic respiration. This low ecosystem carbon use efficiency (CUE) differs considerably from the relatively constant CUE of ~0.5 found for temperate forests. Our$R_{eco}$estimate was comparable to the above-canopy flux ($F_{ac}$) from eddy covariance during defined sustained high turbulence conditions (when presumably$F_{ac} = R_{eco}$) of 8.4 (95% CI = 7.5-9.4). Multiple regression analysis demonstrated that ~50% of the nighttime variability in$F_{ac}$was accounted for by friction velocity (u*, a measure of turbulence) variables. After accounting for u* variability, mean$F_{ac}$varied significantly with seasonal and daily changes in precipitation. A seasonal increase in precipitation resulted in a decrease in$F_{ac}$, similar to our soil respiration response to moisture. The effect of daily changes in precipitation was complex: precipitation after a dry period resulted in a large increase in$F_{ac}$, whereas additional precipitation after a rainy period had little effect. This response was similar to that of surface litter (coarse and fine), where respiration is greatly reduced when moisture is limiting, but increases markedly and quickly saturates with an increase in moisture.
Information about the uncertainties associated with eddy covariance measurements of surface-atmosphere CO₂ exchange is needed for data assimilation and inverse analyses to estimate model parameters, ...validation of ecosystem models against flux data, as well as multi-site synthesis activities (e.g., regional to continental integration) and policy decision-making. While model residuals (mismatch between fitted model predictions and measured fluxes) can potentially be analyzed to infer data uncertainties, the resulting uncertainty estimates may be sensitive to the particular model chosen. Here we use 10 site-years of data from the CarboEurope program, and compare the statistical properties of the inferred random flux measurement error calculated first using residuals from five different models, and secondly using paired observations made under similar environmental conditions. Spectral analysis of the model predictions indicated greater persistence (i.e., autocorrelation or “memory”) compared to the measured values. Model residuals exhibited weaker temporal correlation, but were not uncorrelated white noise. Random flux measurement uncertainty, expressed as a standard deviation, was found to vary predictably in relation to the expected magnitude of the flux, in a manner that was nearly identical (for negative, but not positive, fluxes) to that reported previously for forested sites. Uncertainty estimates were generally comparable whether the uncertainty was inferred from model residuals or paired observations, although the latter approach resulted in somewhat smaller estimates. Higher order moments (e.g., skewness and kurtosis) suggested that for fluxes close to zero, the measurement error is commonly skewed and leptokurtic. Skewness could not be evaluated using the paired observation approach, because differencing of paired measurements resulted in a symmetric distribution of the inferred error. Patterns were robust and not especially sensitive to the model used, although more flexible models, which did not impose a particular functional form on relationships between environmental drivers and modeled fluxes, appeared to give the best results. We conclude that evaluation of flux measurement errors from model residuals is a viable alternative to the standard paired observation approach.
It is well recognized in the literature that topography can influence soil nutrient stocks and dynamics in temperate regions, but for tropical forests, this source of variation has sometimes been ...ignored. The nature of such variations may depend upon the soil type, which in turn, is closely linked to local or regional topography. This study characterizes the soil and describes the status of carbon and nitrogen in vegetation, litterfall, litter‐layer and soil upper layers along the main positions of a topographic gradient (plateau, slope and valley), 60 km north of Manaus, on Cuieiras Reserve watershed. Nitrogen concentrations in living leaves, fresh litterfall, litter‐layer and soil upper layers were lower in the valley than in both slope and plateau plots. Carbon concentrations in plant material were not significantly different among the three topographic positions, resulting in higher C : N ratios in valley plots. Local topography (plateau, slope and valley) clearly was an influential factor in the nutrient distribution along the study locations. Lower rates of N cycling processes in the valley are probably related to its sandy soil texture and seasonal flooding.
PDF
