368 results found
Harrison S, Cramer W, Franklin O, et al., 2021, Eco-evolutionary optimality as a means to improve vegetation and land-surface models, New Phytologist, Vol: 231, Pages: 2125-2141, ISSN: 0028-646X
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 change.
Luo X, Keenan T, Chen JM, et al., 2021, Global variation in the fraction of leaf nitrogen allocated to photosynthesis, Nature Communications, Vol: 12, ISSN: 2041-1723
Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5- bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in-situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.
Daniel F, Prentice IC, Gallagher R, et al., 2021, AusTraits, a curated plant trait database for the Australian flora., Scientific Data, ISSN: 2052-4463
We introduce the AusTraits database - a compilation of values of plant traits for taxa in theAustralian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across28640 taxa from field campaigns, published literature, taxonomic monographs, andindividual taxon descriptions. Traits vary in scope from physiological measures ofperformance (e.g. photosynthetic gas exchange, water-use efficiency) to morphologicalattributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecologicalvariation. AusTraits contains curated and harmonised individual- and species-levelmeasurements coupled to, where available, contextual information on site properties andexperimental conditions. This article provides information on version 3.0.2 of AusTraitswhich contains data for 997808 trait-by-taxon combinations. We envision AusTraits as anongoing collaborative initiative for easily archiving and sharing trait data and also providesa template for other national or regional initiatives globally to fill persistent gaps in traitknowledge.
Sato H, Kelly D, Mayor S, et al., 2021, Dry corridors opened by fire and low CO2 in Amazonian rainforest during last glacial maximum, Nature Geoscience, Vol: 14, Pages: 578-585, ISSN: 1752-0894
The dynamics of Amazonian rainforest over long timescales connects closely to its rich biodiversity. While palaeoecological studies have suggested its stability through the Pleistocene, palaeontological evidence indicates the past existence of major expansions of savanna and grassland. Here we present integrated modeling evidence for a grassier Neotropics during the Last Glacial Maximum (LGM), congruent with palaeoecological and biological studies. Vegetation re-constructions were generated using the Land Processes and eXchanges (LPX) model, driven by model reconstructions of LGM climate, and compared against palynological data. A factorial experiment was performed to quantify the impacts of fire and low CO2 on vegetation and model-data agreement. Fire and low CO2 both individually and interactively induced widespread expansion of savanna and grassland biomes while improving model-data agreement. The interactive effects of fire and low CO2 induced the greatest ‘savannafication’ of the Neotropics, providing integrated evidence for a number of biogeographically relevant open vegetation formations including two dry corridors; paths of savanna and grassland through and around Amazonia that facilitated major dispersal and evolutionary diversification events. Our results show a bimodality in tree cover that was driven by fire and further enhanced by ‘CO2 deprivation’, which suggests biome instability in this region of climate space.
Xu H, Wang H, Prentice IC, et al., 2021, Coordination of plant hydraulic and photosynthetic traits: confronting optimality theory with field measurements, New Phytologist, ISSN: 0028-646X
Close coupling between water loss and carbon dioxide uptake requires coordination of plant hydraulics and photosynthesis. However, there is still limited information on the quantitative relationships between hydraulic and photosynthetic traits.We propose a basis for these relationships based on optimality theory, and test its predictions by analysis of measurements on 107 species from 11 sites, distributed along a nearly 3000-m elevation gradient.Hydraulic and leaf-economic traits were less plastic, and more closely associated with phylogeny, than photosynthetic traits. The two sets of traits are linked by the sapwood-to-leaf area ratio (Huber value, vH). The observed coordination between vH and sapwood hydraulic conductivity (KS) and photosynthetic capacity (Vcmax) conformed to the proposed quantitative theory. Substantial hydraulic diversity was related to the trade-off between KS and vH. Leaf drought tolerance (inferred from turgor loss point, –Ψtlp) increased with wood density, but the trade-off between hydraulic efficiency (KS) and –Ψtlp was weak. Plant trait effects on vH were dominated by variation in KS, while effects of environment were dominated by variation in temperature.This research unifies hydraulics, photosynthesis and the leaf economics spectrum in a common theoretical framework, and suggests a route towards the integration of photosynthesis and hydraulics in land-surface models.
Morfopoulos C, Muller J-F, Stavrakou T, et al., 2021, Vegetation responses to climate extremes recorded by remotely sensed atmospheric formaldehyde, Global Change Biology, ISSN: 1354-1013
Accurate monitoring of vegetation stress is required for better modelling and forecasting of primary production, in a world where heatwaves and droughts are expected to become increasingly prevalent. Variability in formaldehyde (HCHO) concentrations in the troposphere is dominated by local emissions of short-lived biogenic (BVOC) and pyrogenic volatile organic compounds. BVOCs are emitted by plants in a rapid protective response to abiotic stress, mediated by the energetic status of leaves (the excess of reducing power when photosynthetic light and dark reactions are decoupled, as occurs when stomata close in response to water stress). Emissions also increase exponentially with leaf temperature. New analytical methods for the detection of spatiotemporally contiguous extremes in remote-sensing data are applied here to satellite-derived atmospheric HCHO columns. BVOC emissions are shown to play a central role in the formation of the largest positive HCHO anomalies. Although vegetation stress can be captured by various remotely sensed quantities, spaceborne HCHO emerges as the most consistent recorder of vegetation responses to the largest climate extremes, especially in forested regions.
Kuhn- Regnier A, Voulgarakis A, Nowack P, et al., 2021, The importance of antecedent vegetation and drought conditions as global drivers of burnt areas, Biogeosciences, Vol: 18, Pages: 3861-3879, ISSN: 1726-4170
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.
Kuhn-Régnier A, Voulgarakis A, Nowack P, et al., 2021, Supplementary material to "Quantifying the Importance of Antecedent Fuel-Related VegetationProperties for Burnt Area using Random Forests", Biogeosciences, ISSN: 1726-4170
Mengoli G, Agustí-Panareda A, Boussetta S, et al., 2021, Ecosystem photosynthesis in land-surface models: a first-principles approach, Publisher: Cold Spring Harbor Laboratory
Vegetation regulates land-atmosphere water and energy exchanges and is an essential component of land-surface models (LSMs). However, LSMs have been handicapped by assumptions that equate acclimated photosynthetic responses to environment with fast responses observable in the laboratory. These time scales can be distinguished by including specific representations of acclimation, but at the cost of further increasing parameter requirements. Here we develop an alternative approach based on optimality principles that predict the acclimation of carboxylation and electron-transport capacities, and a variable controlling the response of leaf-level carbon dioxide drawdown to vapour pressure deficit (VPD), to variations in growth conditions on a weekly to monthly time scale. In the “P model”, an optimality-based light-use efficiency model for gross primary production (GPP) on this time scale, these acclimated responses are implicit. Here they are made explicit, allowing fast and slow response time-scales to be separated and GPP to be simulated at sub-daily timesteps. The resulting model mimics diurnal cycles of GPP recorded by eddy-covariance flux towers in a temperate grassland and boreal, temperate and tropical forests, with no parameter changes between biomes. Best performance is achieved when biochemical capacities are adjusted to match recent midday conditions. This model suggests a simple and parameter-sparse method to include both instantaneous and acclimated responses within an LSM framework, with many potential applications in weather, climate and carbon - cycle modelling.
Wei D, Gonzalez-Samperiz P, Gil-Romera G, et al., 2021, Seasonal temperature and moisture changes in interior semi-arid Spain from the last interglacial to the late Holocene, Quaternary Research, Vol: 101, Pages: 143-155, ISSN: 0033-5894
The El Cañizar de Villarquemado pollen record covers the last part of MIS 6 to the late Holocene. We use Tolerance-Weighted Averaging Partial Least-Squares (TWA-PLS) to reconstruct mean temperature of the coldest month (MTCO) and growing degree days above 0° C (GDD0) and the ratio of annual precipitation to annual potential evapotranspiration (MI), accounting for the ecophysiological effect of changing CO2 on water-use efficiency. Rapid summer warming occurred during the Zeifen-Kattegat Oscillation at the transition to MIS 5. Summers were cold during MIS 4 and MIS 2, but some intervals of MIS 3 had summers as warm as the warmest phases of MIS 5 or the Holocene. Winter temperatures declined from MIS 4 to MIS 2. Changes in temperature seasonality within MIS 5 and MIS 1 are consistent with insolation seasonality changes. Conditions became progressively more humid during MIS 5, and MIS 4 was also humid although MIS 3 was more arid. Changes in MI and GDD0 are anti-correlated, with increased MI during summer warming intervals. Comparison with other records shows glacial-interglacial changes were not unform across the circum-Mediterranean region but available quantitative reconstructions are insufficient to determine if east-west differences reflect the circulation-driven precipitation dipole seen in recent decades.
Peng Y, Bloomfield K, Cernusak L, et al., 2021, Global climate and nutrient controls of photosynthetic capacity, Communications Biology, Vol: 4, ISSN: 2399-3642
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.
Xu H, Wang H, Prentice IC, et al., 2021, Predictability of leaf traits with climate and elevation: a case study in Gongga Mountain, China, Tree Physiology: an international botanical journal, ISSN: 0829-318X
Leaf mass per area (Ma), nitrogen content per unit leaf area (Narea), maximum carboxylation capacity (Vcmax) and the ratio of leaf-internal to ambient CO2 partial pressure (χ) are important traits related to photosynthetic function, and show systematic variation along climatic and elevational gradients. Separating the effects of air pressure and climate along elevational gradients is challenging due to the covariation of elevation, pressure and climate. However, recently developed models based on optimality theory offer an independent way to predict leaf traits, and thus to separate the contributions of different controls. We apply optimality theory to predict variation in leaf traits across 18 sites in the Gongga Mountain region. We show that the models explain 59% of trait variability on average, without site- or region-specific calibration. Temperature, photosynthetically active radiation, vapor pressure deficit, soil moisture and growing-season length are all necessary to explain the observed patterns. The direct effect of air pressure is shown to have a relatively minor impact. These findings contribute to a growing body of research indicating that leaf-level traits vary with the physical environment in predictable ways, suggesting a promising direction for the improvement for terrestrial ecosystem models.
Turner M, Wei D, Prentice IC, et al., 2021, The impact of methodological decisions in climate reconstructions using WA- PLS, Quaternary Research, Vol: 99, Pages: 341-356, ISSN: 0033-5894
Most techniques for pollen-based quantitative climate reconstruction use modern assemblages as a reference data set. We examine the implication of methodological choices in the selection and treatment of the reference data set for climate reconstructions using Weighted Averaging Partial Least Squares (WA-PLS) regression, using records of the last glacial period from Europe. We show that the training data set used is important, because it determines the climate space sampled. The range and continuity of sampling along the climate gradient is more important than sampling density. Reconstruction uncertainties are generally reduced when more taxa are included, but combining related taxa that are poorly sampled in the data set to a higher taxonomic level provides more stable reconstructions. Excluding taxa that are climatically insensitive, or systematically over-represented in fossil pollen assemblages because of known biases in pollen production or transport, makes no significant difference to the reconstructions. However, the exclusion of taxa over-represented because of preservation issues does produce an improvement. These findings are relevant not only for WA-PLS reconstructions but also for similar approaches using modern assemblage reference data. There is no universal solution to these issues, but we propose a number of checks to evaluate the robustness of pollen-based reconstructions.
Joshi J, Stocker B, Hofhansl F, et al., 2020, Towards a unified theory of plant photosynthesis and hydraulics, Publisher: Cold Spring Harbor Laboratory
The global carbon and water cycles are strongly governed by the simultaneous diffusion of CO2 and water vapour through the leaves of terrestrial plants. These diffusive fluxes are controlled by plants’ adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to changing environments. Tested with experimental data from eighteen species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance, and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature, and CO2. Consistent with widely observed patterns, inferred trait values for the analysed species display a spectrum of stomatal strategies, a safety-efficiency trade-off, and a convergence towards low hydraulic safety margins. Our unifying theory opens new avenues for reliably modelling the interactive effects of drying soil and air and rising atmospheric CO2 on global photosynthesis and transpiration.
Prentice IC, Cai W, 2020, Recent trends in gross primary production and their drivers: analysis and modelling at flux-site and global scales, Environmental Research Letters, Vol: 15, ISSN: 1748-9326
Gross primary production (GPP) by terrestrial ecosystems is the largest flux in the global carbon cycle, and its continuing increase in response to environmental changes is key to land ecosystems' capacity to offset anthropogenic CO2 emissions. However, the CO2- and climate-sensitivities of GPP vary among models. We applied the 'P model'—a parameter-sparse and extensively tested light use efficiency (LUE) model, driven by CO2, climate and remotely sensed greenness data—at 29 sites with multi-year eddy-covariance flux measurements. Observed (both positive and negative) GPP trends at these sites were predicted, albeit with some bias. Increasing LUE (due to rising atmospheric CO2 concentration) and green vegetation cover were the primary controls of modelled GPP trends across sites. Global GPP simulated by the same model increased by 0.46 ± 0.09 Pg C yr–2 during 1982–2016. This increase falls in the mid-range rate of simulated increase by the TRENDY v8 ensemble of state-of-the-art ecosystem models. The modelled LUE increase during 1900–2013 was 15%, similar to a published estimate based on deuterium isotopomers. Rising CO2 was the largest contributor to the modelled GPP increase. Greening, which may in part be caused by rising CO2, ranked second but dominated the modelled GPP change over large areas, including semi-arid vegetation on all continents. Warming caused a small net reduction in modelled global GPP, but dominated the modelled GPP increase in high northern latitudes. These findings strengthen the evidence that rising LUE due to rising CO2 level and increased green vegetation cover (fAPAR) are the main causes of increasing GPP, and thereby, the terrestrial carbon sink.
Prentice IC, Liu M, ter Braak CJF, et al., 2020, An improved statistical approach for reconstructing past climates from biotic assemblages, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 476, Pages: 1-21, ISSN: 1364-5021
Quantitative reconstructions of past climates are an important resource for evaluating how well climate models reproduce climate changes. One widely used statistical approach for making such reconstructions from fossil biotic assemblages is weighted averaging partial least-squares regression (WA-PLS). There is however a known tendency for WA-PLS to yield reconstructions compressed towards the centre of the climate range used for calibration, potentially biasing the reconstructed past climates. We present an improvement of WA-PLS by assuming that: (i) the theoretical abundance of each taxon is unimodal with respect to the climate variable considered; (ii) observed taxon abundances follow a multinomial distribution in which the total abundance of a sample is climatically uninformative; and (iii) the estimate of the climate value at a given site and time makes the observation most probable, i.e. it maximizes the log-likelihood function. This climate estimate is approximated by weighting taxon abundances in WA-PLS by the inverse square of their climate tolerances. We further improve the approach by considering the frequency ( fx) of the climate variable in the training dataset. Tolerance-weighted WA-PLS with fx correction greatly reduces the compression bias, compared with WA-PLS, and improves model performance in reconstructions based on an extensive modern pollen dataset.
Collalti A, Ibrom A, Stockmarr A, et al., 2020, Forest production efficiency increases with growth temperature, Nature Communications, Vol: 11, ISSN: 2041-1723
Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or—more generally—for the production of organic matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings—FPE declining with age—are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate.
Paillassa J, Wright I, Prentice IC, et al., 2020, When and where soil is important to modify the carbon and water economy of leaves., New Phytologist, Vol: 228, Pages: 121-135, ISSN: 0028-646X
Photosynthetic “least‐cost” theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate‐related costs for both resources increase.Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci/Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets.The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit‐costs are presumably higher. Higher values of soil silt and depth increased Ci/Ca, likely by providing greater H2O supply, alleviating biophysical photosynthetic limitation when soil water is scarce.Climate is important in controlling the optimal balance of H2O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate‐demand driven predictions of Ci/Ca by up to 30% at a global scale.
Lavergne A, Sandoval D, Hare VJ, et al., 2020, Impacts of soil water stress on the acclimated stomatal limitation of photosynthesis: insights from stable carbon isotope data., Global Change Biology, Vol: 26, Pages: 7158-7172, ISSN: 1354-1013
Atmospheric aridity and drought both influence physiological function in plant leaves, but their relative contributions to changes in the ratio of leaf-internal to ambient partial pressure of CO2 (χ) - an index of adjustments in both stomatal conductance and photosynthetic rate to environmental conditions - are difficult to disentangle. Many stomatal models predicting χ include the influence of only one of these drivers. In particular, the least-cost optimality hypothesis considers the effect of atmospheric demand for water on χ but does not predict how soils with reduced water further influence χ, potentially leading to an overestimation of χ under dry conditions. Here we use a large network of stable carbon isotope measurements in C3 woody plants to examine the acclimated response of χ to soil water stress. We estimate the ratio of cost factors for carboxylation and transpiration (β) expected from the theory to explain the variance in the data, and investigate the responses of β (and thus χ) to soil water content and suction across seed plant groups, leaf phenological types and regions. Overall, β decreases linearly with soil drying, implying that the cost of water transport along the soil-plant-atmosphere continuum increases as water available in the soil decreases. However, despite contrasting hydraulic strategies, the stomatal responses of angiosperms and gymnosperms to soil water tend to converge, consistent with the optimality theory. The prediction of β as a simple, empirical function of soil water significantly improves χ predictions by up to 6.3 ± 2.3% (mean ± sd of adjusted-R2 ) over 1980-2018 and results in a reduction of around 2% of mean χ values across the globe. Our results highlight the importance of soil water status on stomatal functions and plant water-use efficiency, and suggest the implementation of trait-based hydraulic functions into the model to account for soil water stre
Hantson S, Kelley DI, Arneth A, et al., 2020, Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project, Geoscientific Model Development, Vol: 13, Pages: 3299-3318, ISSN: 1991-959X
Global fire-vegetation models are widely used to assess impacts of environmental change on fire regimes and the carbon cycle and to infer relationships between climate, land use and fire. However, differences in model structure and parameterizations, in both the vegetation and fire components of these models, could influence overall model performance, and to date there has been limited evaluation of how well different models represent various aspects of fire regimes. The Fire Model Intercomparison Project (FireMIP) is coordinating the evaluation of state-of-the-art global fire models, in order to improve projections of fire characteristics and fire impacts on ecosystems and human societies in the context of global environmental change. Here we perform a systematic evaluation of historical simulations made by nine FireMIP models to quantify their ability to reproduce a range of fire and vegetation benchmarks. The FireMIP models simulate a wide range in global annual total burnt area (39–536 Mha) and global annual fire carbon emission (0.91–4.75 Pg C yr−1) for modern conditions (2002–2012), but most of the range in burnt area is within observational uncertainty (345–468 Mha). Benchmarking scores indicate that seven out of nine FireMIP models are able to represent the spatial pattern in burnt area. The models also reproduce the seasonality in burnt area reasonably well but struggle to simulate fire season length and are largely unable to represent interannual variations in burnt area. However, models that represent cropland fires see improved simulation of fire seasonality in the Northern Hemisphere. The three FireMIP models which explicitly simulate individual fires are able to reproduce the spatial pattern in number of fires, but fire sizes are too small in key regions, and this results in an underestimation of burnt area. The correct representation of spatial and seasonal patterns in vegetation appears
Joos F, Spahni R, Stocker BD, et al., 2020, N2O changes from the Last Glacial Maximum to the preindustrial - Part 2: terrestrial N2O emissions and carbon-nitrogen cycle interactions, Biogeosciences, Vol: 17, Pages: 3511-3543, ISSN: 1726-4170
Carbon–nitrogen (C–N) interactions regulate N availability for plant growth and for emissions of nitrous oxide (N2O) and the uptake of carbon dioxide. Future projections of these terrestrial greenhouse gas fluxes are strikingly divergent, leading to major uncertainties in projected global warming. Here we analyse the large increase in terrestrial N2O emissions over the past 21 000 years as reconstructed from ice-core isotopic data and presented in part 1 of this study. Remarkably, the increase occurred in two steps, each realized over decades and within a maximum of 2 centuries, at the onsets of the major deglacial Northern Hemisphere warming events. The data suggest a highly dynamic and responsive global N cycle. The increase may be explained by an increase in the flux of reactive N entering and leaving ecosystems or by an increase in N2O yield per unit N converted. We applied the LPX-Bern dynamic global vegetation model in deglacial simulations forced with Earth system model climate data to investigate N2O emission patterns, mechanisms, and C–N coupling. The N2O emission changes are mainly attributed to changes in temperature and precipitation and the loss of land due to sea-level rise. LPX-Bern simulates a deglacial increase in N2O emissions but underestimates the reconstructed increase by 47 %. Assuming time-independent N sources in the model to mimic progressive N limitation of plant growth results in a decrease in N2O emissions in contrast to the reconstruction. Our results appear consistent with suggestions of (a) biological controls on ecosystem N acquisition and (b) flexibility in the coupling of the C and N cycles during periods of rapid environmental change. A dominant uncertainty in the explanation of the reconstructed N2O emissions is the poorly known N2O yield per N lost through gaseous pathways and its sensitivity to soil conditions. The deglacial N2O record provides a constraint for future studies.
Waring B, Neumann M, Prentice IC, et al., 2020, What role can forests play in tackling climate change?, What role can forests play in tackling climate change?, www.imperial.ac.uk/grantham, Publisher: Grantham Institute, Discussion paper 6
This discussion paper consolidates knowledge on the potential environmental, economic and societal benefits of using trees to reduce the concentration of carbon dioxide in the atmosphere. It highlights areas for further research and defines the limits of trees’ ability to halt the progress of climate change.
Qiao S, Wang H, Harrison SP, et al., 2020, Extending a first-principles primary production model to predict wheat yields, Agricultural and Forest Meteorology, Vol: 287, Pages: 1-16, ISSN: 0168-1923
Climate exerts a major influence on crop development and yield. Despite extensive modelling efforts, there is still considerable uncertainty about the consequences of a changing climate for the yields of major crops. Existing crop models are complex and rely on many assumptions and parameters, motivating a quest for more parsimonious models with stronger theoretical and empirical foundations. This paper presents a prototype of such a model for wheat, informed by measurements of gross primary production (GPP), biomass and yield at research sites across the wheat-growing regions of China. First, GPP was predicted using a recently developed first-principles model driven only by climate, carbon dioxide (CO2) concentration, and light absorbed by leaves. Modelled GPP was shown to agree well with eddy-covariance measurements. Second, the data were used to show that above-ground biomass (AB) is proportional to time-integrated GPP, and that grain yield shows a saturating relationship with AB. Simple empirical equations based on these findings were combined with modelled GPP to predict yield, including propagated errors due to parameter uncertainty in both the GPP model and the empirical equations. The resulting 'hybrid' model, applied in a variety of climates, successfully predicted measured interannual variations in AB and yield. Third, the model was extended to include a phenology scheme, a mass-balance equation relating mean leaf area index to accumulated GPP over the growth phase, and an independently observed response of leaf mass-per-area to CO2. Sensitivity analyses and scenario runs with this extended model showed a positive but saturating (at ∼600 ppm) response of yield to rising CO2, consistent with experimental evidence. This positive effect was partially counteracted by a net negative response of yield to increasing temperature, caused by increasing photorespiration and an accelerated growth cycle.
Peng Y, Bloomfield K, Prentice IC, 2020, A theory of plant function helps to explain leaf-trait and productivity responses to elevation, New Phytologist, Vol: 226, Pages: 1274-1284, ISSN: 0028-646X
Several publications have examined leaf‐trait and carbon‐cycling shifts along an Amazon‐Andes transect spanning 3.5 km elevation and 16℃ mean annual temperature. Photosynthetic capacity was previously shown to increase as temperature declines with increasing elevation, counteracting enzyme‐kinetic effects. Primary production declines, nonetheless, due to decreasing light availability. We aimed to predict leaf‐trait and production gradients from first principles, using published data to test an emerging theory whereby photosynthetic traits and primary production depend on optimal acclimation and/or adaptation to environment.We re‐analysed published data for 210 species at 25 sites, fitting linear relationships to elevation for both predicted and observed photosynthetic traits and primary production.Declining leaf‐internal/ambient CO2 ratio (χ) and increasing carboxylation (Vcmax) and electron‐transport (Jmax) capacities with increasing elevation were predicted. Increases in leaf nitrogen content with elevation were explained by increasing Vcmax and leaf mass‐per‐area. Leaf and soil phosphorus covaried, but after controlling for elevation, no nutrient metric accounted for any additional variance in photosynthetic traits. Primary production was predicted to decline with elevation.This analysis unifies leaf and ecosystem observations in a common theoretical framework. The insensitivity of primary production to temperature is shown to emerge as a consequence of the optimization of photosynthetic traits.
Terrer C, Jackson RB, Prentice IC, et al., 2020, Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass (vol 21, pg 561, 2020), NATURE CLIMATE CHANGE, Vol: 10, Pages: 696-697, ISSN: 1758-678X
Plants and vegetation play a critical—but largely unpredictable—role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change.
Waring B, Neumann M, Prentice IC, et al., 2020, Forests and decarbonization: roles of natural and planted forests, Frontiers in Forests and Global Change, Vol: 3, ISSN: 2624-893X
The severe consequences of human disruptions to the global carbon cycle have prompted intense interest in strategies to reduce atmospheric CO2 concentrations. Because growing forests capture CO2 in their biomass and soils, large-scale tree planting efforts have been advertised as a viable way to counteract anthropogenic emissions as part of net-zero emission strategies. Here, we assess the potential impact of reforestation and afforestation on the global climate system, and identify ecological, economic, and societal implications of such efforts.
Wei D, Prentice IC, Harrison SP, 2020, The climatic space of European pollen taxa, ECOLOGY, Vol: 101, ISSN: 0012-9658
Dong N, Prentice IC, Wright IJ, et al., 2020, Components of leaf-trait variation along environmental gradients, New Phytologist, Vol: 228, Pages: 82-94, ISSN: 0028-646X
Leaf area (LA), mass per area (LMA), nitrogen per unit area (Narea) and the leaf-internal to ambient CO2 ratio (χ) are fundamental traits for plant functional ecology and vegetation modelling. Here we aimed to assess how their variation, within and between species, tracks environmental gradients.Measurements were made on 705 species from 116 sites within a broad north–south transect from tropical to temperate Australia. Trait responses to environment were quantified using multiple regression; within- and between-species responses were compared using analysis of covariance and trait-gradient analysis.Leaf area, the leaf economics spectrum (indexed by LMA and Narea) and χ (from stable carbon isotope ratios) varied almost independently among species. Across sites, however, χ and LA increased with mean growing-season temperature (mGDD0) and decreased with vapour pressure deficit (mVPD0) and soil pH. LMA and Narea showed the reverse pattern. Climate responses agreed with expectations based on optimality principles. Within-species variability contributed < 10% to geographical variation in LA but > 90% for χ, with LMA and Narea intermediate.These findings support the hypothesis that acclimation within individuals, adaptation within species and selection among species combine to create predictable relationships between traits and environment. However, the contribution of acclimation/adaptation vs species selection differs among traits.
Cleator SF, Harrison SP, Nichols NK, et al., 2020, A new multivariable benchmark for Last Glacial Maximum climate simulations, Climate of the Past, Vol: 16, Pages: 699-712, ISSN: 1814-9324
We present a new global reconstruction of seasonal climates at the Last Glacial Maximum (LGM, 21 000 years BP) made using 3-D variational data assimilation with pollen-based site reconstructions of six climate variables and the ensemble average of the PMIP3—CMIP5 simulations as a prior (initial estimate of LGM climate). We assume that the correlation matrix of the uncertainties in the prior is both spatially and temporally Gaussian, in order to produce a climate reconstruction that is smoothed both from month to month and from grid cell to grid cell. The pollen-based reconstructions include mean annual temperature (MAT), mean temperature of the coldest month (MTCO), mean temperature of the warmest month (MTWA), growing season warmth as measured by growing degree days above a baseline of 5 ∘C (GDD5), mean annual precipitation (MAP), and a moisture index (MI), which is the ratio of MAP to mean annual potential evapotranspiration. Different variables are reconstructed at different sites, but our approach both preserves seasonal relationships and allows a more complete set of seasonal climate variables to be derived at each location. We further account for the ecophysiological effects of low atmospheric carbon dioxide concentration on vegetation in making reconstructions of MAP and MI. This adjustment results in the reconstruction of wetter climates than might otherwise be inferred from the vegetation composition. Finally, by comparing the uncertainty contribution to the final reconstruction, we provide confidence intervals on these reconstructions and delimit geographical regions for which the palaeodata provide no information to constrain the climate reconstructions. The new reconstructions will provide a benchmark created using clear and defined mathematical procedures that can be used for evaluation of the PMIP4–CMIP6 entry-card LGM simulations and are available at https://doi.org/10.17864/1947.244 (Cleator et al., 2020b).
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