85 results found
Ma H, Mo L, Crowther TW, et al., 2021, The global distribution and environmental drivers of aboveground versus belowground plant biomass, NATURE ECOLOGY & EVOLUTION, Vol: 5, Pages: 1110-+, ISSN: 2397-334X
Harrison S, Cramer W, Franklin O, et al., 2021, Eco-evolutionary optimality as a means to improve vegetation and land-surface models, New Phytologist, 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.
Favero A, Mendelsohn R, Sohngen B, et al., 2021, Assessing the long-term interactions of climate change and timber markets on forest land and carbon storage, ENVIRONMENTAL RESEARCH LETTERS, Vol: 16, ISSN: 1748-9326
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.
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.
Harrison SP, Gaillard M-J, Stocker BD, et al., 2020, Development and testing scenarios for implementing land use and land cover changes during the Holocene in Earth system model experiments, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 13, Pages: 805-824, ISSN: 1991-959X
Peaucelle M, Janssens IA, Stocker BD, et al., 2019, Spatial variance of spring phenology in temperate deciduous forests is constrained by background climatic conditions, NATURE COMMUNICATIONS, Vol: 10, ISSN: 2041-1723
Fischer H, Schmitt J, Bock M, et al., 2019, N2O changes from the Last Glacial Maximum to the preindustrial - Part 1: Quantitative reconstruction of terrestrial and marine emissions using N2O stable isotopes in ice cores, BIOGEOSCIENCES, Vol: 16, Pages: 3997-4021, ISSN: 1726-4170
Guerrieri R, Belmecheri S, Ollinger SV, et al., 2019, Disentangling the role of photosynthesis and stomatal conductance on rising forest water-use efficiency, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 116, Pages: 16909-16914, ISSN: 0027-8424
Terrer C, Prentice I, Jackson R, et al., 2019, Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomas, Nature Climate Change, Vol: 9, Pages: 684-689, ISSN: 1758-678X
Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass, but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO2. Here, we present the first data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation, and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12±3% above current values, equivalent to 59±13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness9 and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections.
Fernandez-Martinez M, Yu R, Gamon J, et al., 2019, Monitoring Spatial and Temporal Variabilities of Gross Primary Production Using MAIAC MODIS Data, REMOTE SENSING, Vol: 11
Prentice I, Stocker B, Zscheischler J, et al., 2019, Drought impacts on terrestrial primary production underestimated by satellite monitoring, Nature Geoscience, Vol: 12, Pages: 264-270, ISSN: 1752-0894
Satellite retrievals of information about the Earth’s surface are widely used to monitor global terrestrial photosynthesis and primary production and to examine the ecological impacts of droughts. Methods for estimating photosynthesis from space commonly combine information on vegetation greenness, incoming radiation, temperature, and atmospheric demand for water (vapour-pressure deficit), but do not account for the direct effects of low soil moisture. They instead rely on vapour-pressure deficit as a proxy for dryness, despite widespread evidence that soil moisture deficits have a direct impact on vegetation, independent of vapour-pressure deficit. Here, we use a globally distributed measurement network to assess the effect of soil moisture on photosynthesis, and identify a common bias in an ensemble of satellite-based estimates of photosynthesis that is governed by the magnitude of soil moisture effects on photosynthetic light-use efficiency. We develop methods to account for the influence of soil moisture and estimate that soil moisture effects reduce global annual photosynthesis by ~15%, increase interannual variability by more than 100% across 25% of the global vegetated land surface, and amplify the impacts of extreme events on primary production. These results demonstrate the importance of soil moisture effects for monitoring carbon-cycle variability and drought impacts on vegetation productivity from space.
Vicca S, Stocker BD, Reed S, et al., 2018, Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling, ENVIRONMENTAL RESEARCH LETTERS, Vol: 13, ISSN: 1748-9326
Wang Y, Ciais P, Goll D, et al., 2018, GOLUM-CNP v1.0: a data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes, GEOSCIENTIFIC MODEL DEVELOPMENT, Vol: 11, Pages: 3903-3928, ISSN: 1991-959X
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.
Penuelas J, Sardans J, Filella I, et al., 2017, Impacts of Global Change on Mediterranean Forests and Their Services, FORESTS, Vol: 8, ISSN: 1999-4907
Li W, Ciais P, Peng S, et al., 2017, Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations, BIOGEOSCIENCES, Vol: 14, Pages: 5053-5067, ISSN: 1726-4170
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.
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.
Stocker BD, Yu Z, Massa C, et al., 2017, Holocene peatland and ice-core data constraints on the timing and magnitude of CO2 emissions from past land use, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 114, Pages: 1492-1497, ISSN: 0027-8424
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.
Arneth A, Sitch S, Pongratz J, et al., 2017, Historical carbon dioxide emissions caused by land-use changes are possibly larger than assumed, NATURE GEOSCIENCE, Vol: 10, Pages: 79-+, ISSN: 1752-0894
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.
Zhang Y, Xiao X, Guanter L, et al., 2016, Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production, SCIENTIFIC REPORTS, Vol: 6, ISSN: 2045-2322
Cervarich M, Shu S, Jain AK, et al., 2016, The terrestrial carbon budget of South and Southeast Asia, ENVIRONMENTAL RESEARCH LETTERS, Vol: 11, ISSN: 1748-9326
Zhao F, Zeng N, Asrar G, et al., 2016, Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis, BIOGEOSCIENCES, Vol: 13, Pages: 5121-5137, ISSN: 1726-4170
Calle L, Canadell JG, Patra P, et al., 2016, Regional carbon fluxes from land use and land cover change in Asia, 1980-2009, ENVIRONMENTAL RESEARCH LETTERS, Vol: 11, ISSN: 1748-9326
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