Global decadal variability of plant carbon isotope discrimination and its link to gross primary production

Carbon isotope discrimination (Δ13C) in C3 woody plants is a key variable for the study of photosynthesis. Yet how Δ13C varies at decadal scales, and across regions, and how it is related to gross primary production (GPP), are still incompletely understood. Here we address these questions by implementing a new Δ13C modelling capability in the land-surface model JULES incorporating both photorespiratory and mesophyll-conductance fractionations. We test the ability of four leaf-internal CO2 concentration models embedded in JULES to reproduce leaf and tree-ring (TR) carbon isotopic data. We show that all the tested models tend to overestimate average Δ13C values, and to underestimate interannual variability in Δ13C. This is likely because they ignore the effects of soil water stress on stomatal behavior. Variations in post-photosynthetic isotopic fractionations across species, sites and years, may also partly explain the discrepancies between predicted and TR-derived Δ13C values. Nonetheless, the “least-cost” (Prentice) model shows the lowest biases with the isotopic measurements, and lead to improved predictions of canopy-level carbon and water fluxes. Overall, modelled Δ13C trends vary strongly between regions during the recent (1979–2016) historical period but stay nearly constant when averaged over the globe. Photorespiratory and mesophyll effects modulate the simulated global Δ13C trend by 0.0015 ± 0.005‰ and –0.0006 ± 0.001‰ ppm−1, respectively. These predictions contrast with previous findings based on atmospheric carbon isotope measurements. Predicted Δ13C and GPP tend to be negatively correlated in wet-humid and cold regions, and in tropical African forests, but positively related elsewhere. The negative correlation between Δ13C and GPP is partly due to the strong dominant influences of temperature on GPP and vapor pressure deficit on Δ13C in those forests. Our results demonstrate that the combined analysis of Δ13C and GPP can help understand the drivers of photosynthesis changes in different climatic regions

Spatio‐Temporal Variations in Carbon Isotope Discrimination Predicted by the JULES Land Surface Model

Stable carbon isotopes in plants can help evaluate and improve the representation of carbon and water cycles in land-surface models, increasing confidence in projections of vegetation response to climate change. Here, we evaluated the predictive skills of the Joint UK Land Environmental Simulator (JULES) to capture spatio-temporal variations in carbon isotope discrimination (Δ13C) reconstructed by tree rings at 12 sites in the United Kingdom over the period 1979–2016. Modeled and measured Δ13C time series were compared at each site and their relationships with local climate investigated. Modeled Δ13C time series were significantly correlated (p < 0.05) with tree-ring Δ13C at eight sites, but JULES underestimated mean Δ13C values at all sites, by up to 2.6‰. Differences in mean Δ13C may result from post-photosynthetic isotopic fractionations that were not considered in JULES. Inter-annual variability in Δ13C was also underestimated by JULES at all sites. While modeled Δ13C typically increased over time across the UK, tree-ring Δ13C values increased only at five sites located in the northern regions but decreased at the southern-most sites. Considering all sites together, JULES captured the overall influence of environmental drivers on Δ13C but failed to capture the direction of change in Δ13C caused by air temperature, atmospheric CO2 and vapor pressure deficit at some sites. Results indicate that the representation of carbon-water coupling in JULES could be improved to reproduce both the trend and magnitude of interannual variability in isotopic records, the influence of local climate on Δ13C, and to reduce uncertainties in predicting vegetation-environment interactions

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generate parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration, and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental chang

The College News, 1923-01-24, Vol. 09, No. 13

Bryn Mawr College student newspaper. Merged with The Haverford News in 1968 to form the Bi-college News (with various titles from 1968 on). Published weekly (except holidays) during the academic year

Improvement of isotope-based climate reconstructions in Patagonia through a better understanding of climate influences on isotopic fractionation in tree rings

International audienc

Rapid decrease of the Labrador Sea’s influence on black spruce ecosystems with distance inland

Abstract In eastern Canada, Black spruce (Picea mariana Mill. B.S.P.) grows in a wide variety of climates, from maritime-oceanic conditions near the Labrador Sea, to more continental climates, inland. Along this gradient, timing and provenance of heat and moisture that support growth are uncertain, weakening our capacity to predict the response of boreal ecosystems to climate variability. Here, we measured the stable oxygen isotopic composition of black spruce tree-ring cellulose at three sites in eastern Canada and provide evidence of a rapid decrease of Labrador Sea’s influence on adjacent ecosystems. Our results report a landwards decrease in the oxygen isotope composition of both tree-ring cellulose (δ 18O T R C ) and precipitation water (δ 18O p ). We also reveal a rapid landwards decoupling between δ 18O T R C variability (1950-2013), maximum temperature and Sea Surface Temperature variations over the Northwest Atlantic. Thus, despite their apparent ecological homogeneity, eastern Canada’s black spruce ecosystems rely on heterogeneous sources of heat and moisture

Eco-evolutionary optimality as a means to improve vegetation and land-surface models.

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change