Publications
434 results found
Togashi HF, Prentice IC, Atkin OK, et al., 2018, Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis, Biogeosciences, Vol: 15, Pages: 3461-3474, ISSN: 1726-4170
Ecosystem models commonly assume that key photosynthetic traits, such as carboxylation capacity measured at a standard temperature, are constant in time. The temperature responses of modelled photosynthetic or respiratory rates then depend entirely on enzyme kinetics. Optimality considerations, however, suggest this assumption may be incorrect. The "coordination hypothesis" (that Rubisco- and electron-transport-limited rates of photosynthesis are co-limiting under typical daytime conditions) predicts, instead, that carboxylation (Vcmax) capacity should acclimate so that it increases somewhat with growth temperature but less steeply than its instantaneous response, implying that Vcmax when normalized to a standard temperature (e.g. 25 °C) should decline with growth temperature. With additional assumptions, similar predictions can be made for electron-transport capacity (Jmax) and mitochondrial respiration in the dark (Rdark). To explore these hypotheses, photosynthetic measurements were carried out on woody species during the warm and the cool seasons in the semi-arid Great Western Woodlands, Australia, under broadly similar light environments. A consistent proportionality between Vcmax and Jmax was found across species. Vcmax, Jmax and Rdark increased with temperature in most species, but their values standardized to 25 °C declined. The ci : ca ratio increased slightly with temperature. The leaf N : P ratio was lower in the warm season. The slopes of the relationships between log-transformed Vcmax and Jmax and temperature were close to values predicted by the coordination hypothesis but shallower than those predicted by enzyme kinetics.
Harrison SP, Bartlein PJ, Brovkin V, et al., 2018, The biomass burning contribution to climate-carbon-cycle feedback, Earth System Dynamics, Vol: 9, Pages: 663-677, ISSN: 2190-4979
Temperature exerts strong controls on the incidence and severity of fire. All else equal, warming is expected to increase fire-related carbon emissions, and thereby atmospheric CO2. But the magnitude of this feedback is very poorly known. We use a single-box model of the land biosphere to quantify this positive feedback from satellite-based estimates of biomass burning emissions for 2000–2014 CE and from sedimentary charcoal records for the millennium before the industrial period. We derive an estimate of the centennial-scale feedback strength of 6.5 ± 3.4 ppm CO2 per degree of land temperature increase, based on the satellite data. However, this estimate is poorly constrained, and is largely driven by the well-documented dependence of tropical deforestation and peat fires (primarily anthropogenic) on climate variability patterns linked to the El Niño–Southern Oscillation. Palaeo-data from pre-industrial times provide the opportunity to assess the fire-related climate–carbon-cycle feedback over a longer period, with less pervasive human impacts. Past biomass burning can be quantified based on variations in either the concentration and isotopic composition of methane in ice cores (with assumptions about the isotopic signatures of different methane sources) or the abundances of charcoal preserved in sediments, which reflect landscape-scale changes in burnt biomass. These two data sources are shown here to be coherent with one another. The more numerous data from sedimentary charcoal, expressed as normalized anomalies (fractional deviations from the long-term mean), are then used – together with an estimate of mean biomass burning derived from methane isotope data – to infer a feedback strength of 5.6 ± 3.2 ppm CO2 per degree of land temperature and (for a climate sensitivity of 2.8 K) a gain of 0.09 ± 0.05. This finding indicates that the positive carbon cycle feedback from increased fire provides a substantial
Bloomfield KJ, Cernusak LA, Eamus D, et al., 2018, A continental-scale assessment of variability in leaf traits: within species, across sites and between seasons., Functional Ecology, Vol: 2018, Pages: 1-15, ISSN: 0269-8463
Plant species show considerable leaf trait variability that should be accounted for in dynamic global vegetation models (DGVMs). In particular, differences in the acclimation of leaf traits during periods more and less favourable to growth have rarely been examined.We conducted a field study of leaf trait variation at seven sites spanning a range of climates and latitudes across the Australian continent; 80 native plant species were included. We measured key traits associated with leaf structure, chemistry and metabolism during the favourable and unfavourable growing seasons.Leaf traits differed widely in the degree of seasonal variation displayed. Leaf mass per unit area (Ma) showed none. At the other extreme, seasonal variation accounted for nearly a third of total variability in dark respiration (Rdark).At the non‐tropical sites, carboxylation capacity (Vcmax) at the prevailing growth temperature was typically higher in summer than in winter. When Vcmax was normalized to a common reference temperature (25°C), however, the opposite pattern was observed for about 30% of the species. This suggests that metabolic acclimation is possible, but far from universal.Intraspecific variation—combining measurements of individual plants repeated at contrasting seasons, different leaves from the same individual, and multiple conspecific plants at a given site—dominated total variation for leaf metabolic traits Vcmax and Rdark. By contrast, site location was the major source of variation (53%) for Ma. Interspecific trait variation ranged from only 13% of total variation for Vcmax up to 43% for nitrogen content per unit leaf area.These findings do not support a common practice in DGVMs of assigning fixed leaf trait values to plant functional types. Trait‐based models should allow for interspecific differences, together with spatial and temporal plasticity in leaf structural, chemical and metabolic traits.
Stocker BD, Zscheischler J, Keenan TF, et al., 2018, Quantifying soil moisture impacts on light use efficiency across biomes., New Phytologist, Vol: 218, Pages: 1430-1449, ISSN: 0028-646X
Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.
Wang H, Harrison SP, Prentice IC, et al., 2017, The China Plant Trait Database: toward a comprehensive regional compilation of functional traits for land plants., Ecology, Vol: 99, Pages: 500-500, ISSN: 0012-9658
Plant functional traits provide information about adaptations to climate and environmental conditions, and can be used to explore the existence of alternative plant strategies within ecosystems. Trait data are also increasingly being used to provide parameter estimates for vegetation models. Here we present a new database of plant functional traits from China. Most global climate and vegetation types can be found in China, and thus the database is relevant for global modeling. The China Plant Trait Database contains information on morphometric, physical, chemical, and photosynthetic traits from 122 sites spanning the range from boreal to tropical, and from deserts and steppes through woodlands and forests, including montane vegetation. Data collection at each site was based either on sampling the dominant species or on a stratified sampling of each ecosystem layer. The database contains information on 1,215 unique species, though many species have been sampled at multiple sites. The original field identifications have been taxonomically standardized to the Flora of China. Similarly, derived photosynthetic traits, such as electron-transport and carboxylation capacities, were calculated using a standardized method. To facilitate trait-environment analyses, the database also contains detailed climate and vegetation information for each site. The data set is released under a Creative Commons BY license. When using the data set, we kindly request that you cite this article, recognizing the hard work that went into collecting the data and the authors' willingness to make it publicly available.
Terrer C, Vicca S, Stocker BD, et al., 2017, Ecosystem responses to elevated CO2 governed by plant-soil interactions and the cost of nitrogen acquisition., New Phytologist, Vol: 217, Pages: 507-522, ISSN: 0028-646X
Contents Summary I. II. III. IV. References SUMMARY: Land ecosystems sequester on average about a quarter of anthropogenic CO2 emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants' ability to store additional carbon (C) under rising CO2 , but these mechanisms are not well understood. Here, we review findings from elevated CO2 experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO2 may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N-fixing microbes. We found that N-acquisition efficiency is positively correlated with leaf-level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N-fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.
Wang H, Prentice IC, Keenan TF, et al., 2017, Towards a universal model for carbon dioxide uptake by plants, NATURE PLANTS, Vol: 3, Pages: 734-741, ISSN: 2055-026X
Wright IJ, Dong N, Maire V, et al., 2017, Global climatic drivers of leaf size, Science, Vol: 357, Pages: 917-921, ISSN: 0036-8075
Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves, the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot, sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich "next-generation" vegetation models in which leaf temperature and water use during photosynthesis play key roles.
Wright IJ, Dong N, Maire V, et al., 2017, Global climatic drivers of leaf size, SCIENCE, Vol: 357, Pages: 917-921, ISSN: 0036-8075
Leaf size varies by over a 100,000-fold among species worldwide. Although 19th-century plant geographers noted that the wet tropics harbor plants with exceptionally large leaves, the latitudinal gradient of leaf size has not been well quantified nor the key climatic drivers convincingly identified. Here, we characterize worldwide patterns in leaf size. Large-leaved species predominate in wet, hot, sunny environments; small-leaved species typify hot, sunny environments only in arid conditions; small leaves are also found in high latitudes and elevations. By modeling the balance of leaf energy inputs and outputs, we show that daytime and nighttime leaf-to-air temperature differences are key to geographic gradients in leaf size. This knowledge can enrich “next-generation” vegetation models in which leaf temperature and water use during photosynthesis play key roles.
Dong N, Prentice IC, Harrison SP, et al., 2017, Biophysical homoeostasis of leaf temperature: A neglected process for vegetation and land-surface modelling, Global Ecology and Biogeography, Vol: 26, Pages: 998-1007, ISSN: 1466-822X
AimLeaf and air temperatures are seldom equal, but many vegetation models assume that they are. Land-surface models calculate canopy temperatures, but how well they do so is unknown. We encourage consideration of the leaf- and canopy-to-air temperature difference (ΔΤ) as a benchmark for land-surface modelling and an important feature of plant and ecosystem function.LocationTropical SW China.Time period2013.Major Taxa studiesTropical trees.MethodsWe illustrate diurnal cycles of leaf- and canopy-to-air temperature difference (ΔΤ) with field measurements in a tropical dry woodland and with continuous monitoring data in a tropical seasonal forest. The Priestley–Taylor (PT) and Penman–Monteith (PM) approaches to evapotranspiration are used to provide insights into the interpretation and prediction of ΔT. Field measurements are also compared with land-surface model results obtained with the Joint U.K. Land Environment Simulator (JULES) set up for the conditions of the site.ResultsThe ΔT followed a consistent diurnal cycle, with negative values at night (attributable to negative net radiation) becoming positive in the morning, reaching a plateau and becoming negative again when air temperature exceeded a ‘crossover’ in the 24–29 °C range. Daily time courses of ΔT could be approximated by either the PT or the PM model, but JULES tended to underestimate the magnitude of negative ΔT.Main conclusionsLeaves with adequate water supply are partly buffered against air-temperature variations, through a passive biophysical mechanism. This is likely to be important for optimal leaf function, and land-surface and vegetation models should aim to reproduce it.
Keenan TF, Prentice IC, Canadell JG, et al., 2017, Corrigendum: Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake, Nature Communications, Vol: 8, ISSN: 2041-1723
Colloff MJ, Lavorel S, van Kerkhoff LE, et al., 2017, Transforming conservation science and practice for a postnormal world., Conservation Biology, Vol: 31, Pages: 1008-1017, ISSN: 0888-8892
We examine issues to consider when reframing conservation science and practice in the context of global change. New framings of the links between ecosystems and society are emerging that are changing peoples' values and expectations of nature, resulting in plural perspectives on conservation. Reframing conservation for global change can thus be regarded as a stage in the evolving relationship between people and nature rather than some recent trend. New models of how conservation links with transformative adaptation include how decision contexts for conservation can be reframed and integrated with an adaptation pathways approach to create new options for global-change-ready conservation. New relationships for conservation science and governance include coproduction of knowledge that supports social learning. New processes for implementing adaptation for conservation outcomes include deliberate practices used to develop new strategies, shift world views, work with conflict, address power and intergenerational equity in decisions, and build consciousness and creativity that empower agents to act. We argue that reframing conservation for global change requires scientists and practitioners to implement approaches unconstrained by discipline and sectoral boundaries, geopolitical polarities, or technical problematization. We consider a stronger focus on inclusive creation of knowledge and the interaction of this knowledge with societal values and rules is likely to result in conservation science and practice that meets the challenges of a postnormal world.
Goll DS, Winkler AJ, Raddatz T, et al., 2017, Carbon-nitrogen interactions in idealized simulations with JSBACH (version 3.10), Geoscientific Model Development, Vol: 10, Pages: 2009-2030, ISSN: 1991-959X
Recent advances in the representation of soil carbon decomposition and carbon–nitrogen interactions implemented previously into separate versions of the land surface scheme JSBACH are here combined in a single version, which is set to be used in the upcoming 6th phase of coupled model intercomparison project (CMIP6).Here we demonstrate that the new version of JSBACH is able to reproduce the spatial variability in the reactive nitrogen-loss pathways as derived from a compilation of δ15N data (R = 0. 76, root mean square error (RMSE) = 0. 2, Taylor score = 0. 83). The inclusion of carbon–nitrogen interactions leads to a moderate reduction (−10 %) of the carbon-concentration feedback (βL) and has a negligible effect on the sensitivity of the land carbon cycle to warming (γL) compared to the same version of the model without carbon–nitrogen interactions in idealized simulations (1 % increase in atmospheric carbon dioxide per year). In line with evidence from elevated carbon dioxide manipulation experiments, pronounced nitrogen scarcity is alleviated by (1) the accumulation of nitrogen due to enhanced nitrogen inputs by biological nitrogen fixation and reduced losses by leaching and volatilization. Warming stimulated turnover of organic nitrogen further counteracts scarcity.The strengths of the land carbon feedbacks of the recent version of JSBACH, with βL = 0. 61 Pg ppm−1 and γL = −27. 5 Pg °C−1, are 34 and 53 % less than the averages of CMIP5 models, although the CMIP5 version of JSBACH simulated βL and γL, which are 59 and 42 % higher than multi-model average. These changes are primarily due to the new decomposition model, indicating the importance of soil organic matter decomposition for land carbon feedbacks.
Xu-Ri, Prentice IC, 2017, Modelling the demand for new nitrogen fixation by terrestrial ecosystems, Biogeosciences, Vol: 14, Pages: 2003-2017, ISSN: 1726-4170
Continual input of reactive nitrogen (N) is requiredto support the natural turnover of N in terrestrial ecosystems.This “N demand” can be satisfied in various ways, includingbiological N fixation (BNF) (the dominant pathway undernatural conditions), lightning-induced abiotic N fixation, Nuptake from sedimentary substrates, and N deposition fromnatural and anthropogenic sources. We estimated the globalnew N fixation demand (NNF), i.e. the total new N inputrequired to sustain net primary production (NPP) in nonagriculturalterrestrial ecosystems regardless of its origin,using a N-enabled global dynamic vegetation model (DyNLPJ).DyN-LPJ does not explicitly simulate BNF; rather, itestimates total NNF using a mass balance criterion and assumesthat this demand is met from one source or another.The model was run in steady state and then in transient modedriven by recent changes in CO2 concentration and climate.A range of values for key stoichiometric parameters was considered,based on recently published analyses. Modelled NPPand C : N ratios of litter and soil organic matter were consistentwith independent estimates. Modelled geographic patternsof ecosystem NNF were similar to other analyses, butactual estimated values exceeded recent estimates of globalBNF. The results were sensitive to a few key parameters: thefraction of litter carbon respired to CO2 during decompositionand plant-type-specific C : N ratios of litter and soil. Themodelled annual NNF increased by about 15 % during thecourse of the transient run, mainly due to increasing CO2concentration. The model did not overestimate recent terrestrialcarbon uptake, suggesting that the increase in NNF demandhas so far been met. Rising CO2 is further increasingthe NNF demand, while the future capacity of N sources tosupport this is unknown.
Rabin SS, Melton JR, Lasslop G, et al., 2017, The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 10, Pages: 1175-1197, ISSN: 1991-959X
The important role of fire in regulating vegetation community composition and contributions to emissions of greenhouse gases and aerosols make it a critical component of dynamic global vegetation models and Earth system models. Over 2 decades of development, a wide variety of model structures and mechanisms have been designed and incorporated into global fire models, which have been linked to different vegetation models. However, there has not yet been a systematic examination of how these different strategies contribute to model performance. Here we describe the structure of the first phase of the Fire Model Intercomparison Project (FireMIP), which for the first time seeks to systematically compare a number of models. By combining a standardized set of input data and model experiments with a rigorous comparison of model outputs to each other and to observations, we will improve the understanding of what drives vegetation fire, how it can best be simulated, and what new or improved observational data could allow better constraints on model behavior. In this paper, we introduce the fire models used in the first phase of FireMIP, the simulation protocols applied, and the benchmarking system used to evaluate the models. We have also created supplementary tables that describe, in thorough mathematical detail, the structure of each model.
Li G, Gerhart LM, Harrison SP, et al., 2017, Changes in biomass allocation buffer low CO2 effects on tree growth during the last glaciation, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
Isotopic measurements on junipers growing in southern California during the last glacial, when the ambient atmospheric [CO2] (ca) was ~180 ppm, show the leaf-internal [CO2] (ci) was approaching the modern CO2 compensation point for C3 plants. Despite this, stem growth rates were similar to today. Using a coupled light-use efficiency and tree growth model, we show that it is possible to maintain a stable ci/ca ratio because both vapour pressure deficit and temperature were decreased under glacial conditions at La Brea, and these have compensating effects on the ci/ca ratio. Reduced photorespiration at lower temperatures would partly mitigate the effect of low ci on gross primary production, but maintenance of present-day radial growth also requires a ~27% reduction in the ratio of fine root mass to leaf area. Such a shift was possible due to reduced drought stress under glacial conditions at La Brea. The necessity for changes in allocation in response to changes in [CO2] is consistent with increased below-ground allocation, and the apparent homoeostasis of radial growth, as ca increases today.
Davis T, Prentice IC, Stocker BD, et al., 2017, Simple process-led algorithms for simulating habitats (SPLASH v.1.0): robust indices of radiation, evapotranspiration and plant-available moisture, Geoscientific Model Development, Vol: 10, Pages: 689-708, ISSN: 1991-9603
Bioclimatic indices for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios depend on estimates of surface fluxes and other quantities, such as radiation, evapotranspiration and soil moisture, for which direct observations are sparse. These quantities can be derived indirectly from meteorological variables, such as near-surface air temperature, precipitation and cloudiness. Here we present a consolidated set of simple process-led algorithms for simulating habitats (SPLASH) allowing robust approximations of key quantities at ecologically relevant timescales. We specify equations, derivations, simplifications, and assumptions for the estimation of daily and monthly quantities of top-of-the-atmosphere solar radiation, net surface radiation, photosynthetic photon flux density, evapotranspiration (potential, equilibrium, and actual), condensation, soil moisture, and runoff, based on analysis of their relationship to fundamental climatic drivers. The climatic drivers include a minimum of three meteorological inputs: precipitation, air temperature, and fraction of bright sunshine hours. Indices, such as the moisture index, the climatic water deficit, and the Priestley–Taylor coefficient, are also defined. The SPLASH code is transcribed in C++, FORTRAN, Python, and R. A total of 1 year of results are presented at the local and global scales to exemplify the spatiotemporal patterns of daily and monthly model outputs along with comparisons to other model results.
Davis TW, Prentice IC, Stocker BD, et al., 2017, Simple Process-Led Algorithms for Simulating Habitats (SPLASH v.1.0): Robust Indices of Radiation, Evapotranspiration and Plant-Available Moisture, Geoscientific Model Development, Vol: 10, Pages: 689-708, ISSN: 1991-959X
Bioclimatic indices for use in studies of ecosystemfunction, species distribution, and vegetation dynamics underchanging climate scenarios depend on estimates of surfacefluxes and other quantities, such as radiation, evapotranspi-ration and soil moisture, for which direct observations aresparse. These quantities can be derived indirectly from me-teorological variables, such as near-surface air temperature,precipitation and cloudiness. Here we present a consolidatedset of simple process-led algorithms for simulating habitats(SPLASH) allowing robust approximations of key quantitiesat ecologically relevant timescales. We specify equations,derivations, simplifications, and assumptions for the estima-tion of daily and monthly quantities of top-of-the-atmospheresolar radiation, net surface radiation, photosynthetic photonflux density, evapotranspiration (potential, equilibrium, andactual), condensation, soil moisture, and runoff, based onanalysis of their relationship to fundamental climatic drivers.The climatic drivers include a minimum of three meteoro-logical inputs: precipitation, air temperature, and fraction ofbright sunshine hours. Indices, such as the moisture index,the climatic water deficit, and the Priestley–Taylor coeffi-cient, are also defined. The SPLASH code is transcribed inC++, FORTRAN, Python, and R. A total of 1 year of resultsare presented at the local and global scales to exemplify thespatiotemporal patterns of daily and monthly model outputsalong with comparisons to other model results.
Dong N, Prentice IC, Evans BJ, et al., 2017, Leaf nitrogen from first principles: field evidence for adaptive variation with climate, Biogeosciences, Vol: 14, Pages: 481-495, ISSN: 1726-4189
Nitrogen content per unit leaf area (Narea) is a key variable in plant functional ecology and biogeochemistry. Narea comprises a structural component, which scales with leaf mass per area (LMA), and a metabolic component, which scales with Rubisco capacity. The co-ordination hypothesis, as implemented in LPJ and related global vegetation models, predicts that Rubisco capacity should be directly proportional to irradiance but should decrease with increases in ci : ca and temperature because the amount of Rubisco required to achieve a given assimilation rate declines with increases in both. We tested these predictions using LMA, leaf δ13C, and leaf N measurements on complete species assemblages sampled at sites on a north–south transect from tropical to temperate Australia. Partial effects of mean canopy irradiance, mean annual temperature, and ci : ca (from δ13C) on Narea were all significant and their directions and magnitudes were in line with predictions. Over 80 % of the variance in community-mean (ln) Narea was accounted for by these predictors plus LMA. Moreover, Narea could be decomposed into two components, one proportional to LMA (slightly steeper in N-fixers), and the other to Rubisco capacity as predicted by the co-ordination hypothesis. Trait gradient analysis revealed ci : ca to be perfectly plastic, while species turnover contributed about half the variation in LMA and Narea.
Terrer C, Vicca S, Hungate BA, et al., 2017, Response to Comment on "Mycorrhizal association as a primary control of the CO2 fertilization effect", Science, Vol: 355, ISSN: 0036-8075
Norby et al. center their critique on the design of the data set and the response variable used. We address these criticisms and reinforce the conclusion that plants that associate with ectomycorrhizal fungi exhibit larger biomass and growth responses to elevated CO2 compared with plants that associate with arbuscular mycorrhizae.
Prentice IC, Cleator SF, Huang YH, et al., 2017, Reconstructing ice-age palaeoclimates: Quantifying low-CO2 effects on plants, Global and Planetary Change, Vol: 149, Pages: 166-176, ISSN: 0921-8181
We present a novel method to quantify the ecophysiological effects of changes in CO2 concentration during the reconstruction of climate changes from fossil pollen assemblages. The method does not depend on any particular vegetation model. Instead, it makes use of general equations from ecophysiology and hydrology that link moisture index (MI) to transpiration and the ratio of leaf-internal to ambient CO2 (χ). Statistically reconstructed MI values are corrected post facto for effects of CO2 concentration. The correction is based on the principle that e, the rate of water loss per unit carbon gain, should be inversely related to effective moisture availability as sensed by plants. The method involves solving a non-linear equation that relates e to MI, temperature and CO2 concentration via the Fu-Zhang relation between evapotranspiration and MI, Monteith's empirical relationship between vapour pressure deficit and evapotranspiration, and recently developed theory that predicts the response of χ to vapour pressure deficit and temperature. The solution to this equation provides a correction term for MI. The numerical value of the correction depends on the reconstructed MI. It is slightly sensitive to temperature, but primarily sensitive to CO2 concentration. Under low LGM CO2 concentration the correction is always positive, implying that LGM climate was wetter than it would seem from vegetation composition. A statistical reconstruction of last glacial maximum (LGM, 21±1 kyr BP) palaeoclimates, based on a new compilation of modern and LGM pollen assemblage data from Australia, is used to illustrate the method in practice. Applying the correction brings pollen-reconstructed LGM moisture availability in southeastern Australia better into line with palaeohydrological estimates of LGM climate.
Prentice IC, Rogers A, Medlyn BE, et al., 2016, A roadmap for improving the representation of photosynthesis in Earth system models, New Phytologist, Vol: 213, Pages: 22-42, ISSN: 1469-8137
Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. ● Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of A to key environmental variables: light, temperature,carbon dioxide concentration, vapor pressure deficit and soil water content. ● We identified research areas where limited process knowledge prevents inclusion ofphysiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation.● We provide a roadmap for new science needed to improve the representation ofphotosynthesis in the next generation of terrestrial biosphere and Earth System Models.
Wang H, Prentice IC, Davis TW, et al., 2016, Photosynthetic responses to altitude: an explanation based on optimality principles, New Phytologist, Vol: 213, Pages: 976-982, ISSN: 1469-8137
Keenan TF, Prentice IC, Canadell JG, et al., 2016, Recent pause in the growth rate of atmospheric CO2 due to enhanced terrestrial carbon uptake, Nature Communications, Vol: 7, Pages: 1-10, ISSN: 2041-1723
Terrestrial ecosystems play a significant role in the global carbon cycle and offset a large fraction of anthropogenic CO2 emissions. The terrestrial carbon sink is increasing, yet the mechanisms responsible for its enhancement, and implications for the growth rate of atmospheric CO2, remain unclear. Here using global carbon budget estimates, ground, atmospheric and satellite observations, and multiple global vegetation models, we report a recent pause in the growth rate of atmospheric CO2, and a decline in the fraction of anthropogenic emissions that remain in the atmosphere, despite increasing anthropogenic emissions. We attribute the observed decline to increases in the terrestrial sink during the past decade, associated with the effects of rising atmospheric CO2 on vegetation and the slowdown in the rate of warming on global respiration. The pause in the atmospheric CO2 growth rate provides further evidence of the roles of CO2 fertilization and warming-induced respiration, and highlights the need to protect both existing carbon stocks and regions, where the sink is growing rapidly.
Thomas RT, Prentice IC, Graven H, et al., 2016, Increased light-use efficiency in northern terrestrial ecosystems indicated by CO2 and greening observations, Geophysical Research Letters, Vol: 43, Pages: 11339-11349, ISSN: 1944-8007
Observations show an increasing amplitude in the seasonal cycle of CO2 (ASC) north of 45°N of 56 ± 9.8% over the last 50 years and an increase in vegetation greenness of 7.5–15% in high northern latitudes since the 1980s. However, the causes of these changes remain uncertain. Historical simulations from terrestrial biosphere models in the Multiscale Synthesis and Terrestrial Model Intercomparison Project are compared to the ASC and greenness observations, using the TM3 atmospheric transport model to translate surface fluxes into CO2 concentrations. We find that the modeled change in ASC is too small but the mean greening trend is generally captured. Modeled increases in greenness are primarily driven by warming, whereas ASC changes are primarily driven by increasing CO2. We suggest that increases in ecosystem-scale light use efficiency (LUE) have contributed to the observed ASC increase but are underestimated by current models. We highlight potential mechanisms that could increase modeled LUE.
De Kauwe MG, Lin Y-S, Wright IJ, et al., 2016, A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis (vol 210, pg 1130, 2016), NEW PHYTOLOGIST, Vol: 212, Pages: 792-792, ISSN: 0028-646X
Li G, Harrison SP, Prentice IC, 2016, A model analysis of climate and CO<inf>2</inf> controls on tree growth and carbon allocation in a semi-arid woodland, Ecological Modelling, Vol: 342, Pages: 175-185, ISSN: 1872-7026
Many studies have failed to show an increase in the radial growth of trees in response to increasing atmospheric CO2 concentration [CO2] despite the expected enhancement of photosynthetic rates and water-use efficiency at high [CO2]. A global light use efficiency model of photosynthesis, coupled with a generic carbon allocation and tree-growth model based on mass balance and tree geometry principles, was used to simulate annual ring-width variations for the gymnosperm Callitris columellaris in the semi-arid Great Western Woodlands, Western Australia, over the past 100 years. Parameter values for the tree-growth model were derived from independent observations except for sapwood specific respiration rate, fine-root turnover time, fine-root specific respiration rate and the ratio of fine-root mass to foliage area (ζ), which were calibrated to the ring-width measurements by approximate Bayesian optimization. This procedure imposed a strong constraint on ζ. Modelled and observed ring-widths showed quantitatively similar, positive responses to total annual photosynthetically active radiation and soil moisture, and similar negative responses to vapour pressure deficit. The model also produced enhanced radial growth in response to increasing [CO2] during recent decades, but the data do not show this. Recalibration in moving 30-year time windows produced temporal shifts in the estimated values of ζ, including an increase by ca 12% since the 1960s, and eliminated the [CO2]-induced increase in radial growth. The potential effect of CO2 on ring-width was thus shown to be small compared to effects of climate variability even in this semi-arid climate. It could be counteracted in the model by a modest allocation shift, as has been observed in field experiments with raised [CO2].
De Kauwe MG, Keenan TF, Medlyn BE, et al., 2016, CORRESPONDENCE: Satellite based estimates underestimate the effect of CO<sub>2</sub> fertilization on net primary productivity, NATURE CLIMATE CHANGE, Vol: 6, Pages: 892-893, ISSN: 1758-678X
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- Citations: 64
De Kauwe MG, Keenan TF, Medlyn BE, et al., 2016, Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity, Nature Climate Change, Vol: 6, Pages: 892-893, ISSN: 1758-678X
Ukkola AM, Keenan TF, Kelley DI, et al., 2016, Vegetation plays an important role in mediating future water resources, Environmental Research Letters, Vol: 11, ISSN: 1748-9326
Future environmental change is expected to modify the global hydrological cycle, with consequences for the regional distribution of freshwater supplies. Regional precipitation projections, however, differ largely between models, making future water resource projections highly uncertain. Using two representative concentration pathways and nine climate models, we estimate 21st century water resources across Australia, employing both a process-based dynamic vegetation model and a simple hydrological framework commonly used in water resource studies to separate the effects of climate and vegetation on water resources. We show surprisingly robust, pathway-independent regional patterns of change in water resources despite large uncertainties in precipitation projections. Increasing plant water use efficiency (due to the changing atmospheric CO2) and reduced green vegetation cover (due to the changing climate) relieve pressure on water resources for the highly populated, humid coastal regions of eastern Australia. By contrast, in semi-arid regions across Australia, runoff declines are amplified by CO2-induced greening, which leads to increased vegetation water use. These findings highlight the importance of including vegetation dynamics in future water resource projections.
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