Background And Aims: Tropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three-times greater for the tropics than other ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink.
View Article and Find Full Text PDFThe advent of new spaceborne imaging spectrometers offers new opportunities for ecologists to map vegetation traits at global scales. However, to date most imaging spectroscopy studies exploiting satellite spectrometers have been constrained to the landscape scale. In this paper we present a new method to map vegetation traits at the landscape scale and upscale trait maps to the continental level, using historical spaceborne imaging spectroscopy (Hyperion) to derive estimates of leaf mass per area, nitrogen, and carbon concentrations of forests in Québec, Canada.
View Article and Find Full Text PDFVegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems.
View Article and Find Full Text PDFTerrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy-scale CO and water fluxes.
View Article and Find Full Text PDFWildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.
View Article and Find Full Text PDFWithin vascular plants, the partitioning of hydraulic resistance along the soil-to-leaf continuum affects transpiration and its response to environmental conditions. In trees, the fractional contribution of leaf hydraulic resistance (R ) to total soil-to-leaf hydraulic resistance (R ), or fR (=R /R ), is thought to be large, but this has not been tested comprehensively. We compiled a multibiome data set of fR using new and previously published measurements of pressure differences within trees in situ.
View Article and Find Full Text PDFThe representation of stomatal regulation of transpiration and CO assimilation is key to forecasting terrestrial ecosystem responses to global change. Given its importance in determining the relationship between forest productivity and climate, accurate and mechanistic model representation of the relationship between stomatal conductance (g ) and assimilation is crucial. We assess possible physiological and mechanistic controls on the estimation of the g (stomatal slope, inversely proportional to water use efficiency) and g (stomatal intercept) parameters, using diurnal gas exchange surveys and leaf-level response curves of six tropical broadleaf evergreen tree species.
View Article and Find Full Text PDFPhotosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.].
View Article and Find Full Text PDFMany terrestrial biosphere models depend on an understanding of the relationship between stomatal conductance and photosynthesis. However, unlike the measurement of photosynthetic parameters, such as the maximum carboxylation capacity, where standard methods (e.g.
View Article and Find Full Text PDFStomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO between the leaf and the atmosphere. Representation of stomatal conductance (g ) is therefore an essential component of models that seek to simulate water and CO exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g and photosynthetic CO assimilation (A).
View Article and Find Full Text PDFAs the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework.
View Article and Find Full Text PDFThe Arctic-Boreal Region (ABR) has a large impact on global vegetation-atmosphere interactions and is experiencing markedly greater warming than the rest of the planet, a trend that is projected to continue with anticipated future emissions of CO . The ABR is a significant source of uncertainty in estimates of carbon uptake in terrestrial biosphere models such that reducing this uncertainty is critical for more accurately estimating global carbon cycling and understanding the response of the region to global change. Process representation and parameterization associated with gross primary productivity (GPP) drives a large amount of this model uncertainty, particularly within the next 50 years, where the response of existing vegetation to climate change will dominate estimates of GPP for the region.
View Article and Find Full Text PDFTropical forests are one of the main carbon sinks on Earth, but the magnitude of CO2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO2 fluxes are critical, but traditional approaches are time-consuming.
View Article and Find Full Text PDFDrought is the most important limitation on crop yield. Understanding and detecting drought stress in crops is vital for improving water use efficiency through effective breeding and management. Leaf reflectance spectroscopy offers a rapid, non-destructive alternative to traditional techniques for measuring plant traits involved in a drought response.
View Article and Find Full Text PDFLeaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (V ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-V relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China.
View Article and Find Full Text PDFPartial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring.
View Article and Find Full Text PDFThe finely tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. We measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions.
View Article and Find Full Text PDFUnderstanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.
View Article and Find Full Text PDFIn an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery.
View Article and Find Full Text PDFMechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation (A). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB).
View Article and Find Full Text PDFPlant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top of canopy leaves only.
View Article and Find Full Text PDFGlob Chang Biol
February 2020
Stomata regulate CO uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (g ) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.
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