Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID â–Č Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-1811 Peer reviewed articles 2022 Prentice, I.C., Villegas-Diaz, R., Harrison, S.P. Accounting for atmospheric carbon dioxide variations in pollen-based reconstructions of past hydroclimates Global and Planetary Changes 10.1016/j.gloplacha.2022.103790 Uncategorized Uncategorized No abstract available 787203
publications-1812 Peer reviewed articles 2021 Sandy P Harrison, Iain Colin Prentice, Keith J Bloomfield, Ning Dong, Matthias Forkel, Matthew Forrest, Ramesh K. Ningthoujam, Adam Pellegrini, Yicheng Shen, Mara Baudena, Annabelle W Cardoso, Jessica C. Huss, Jaideep Joshi, Imma Oliveras, Juli G. Pausas, Kimberley J Simpson Understanding and modelling wildfire regimes: an ecological perspective Environmental Research Letters 10.1088/1748-9326/ac39be Hydrological modeling Irrigation Systems Abstract Recent extreme wildfire seasons in several regions have been associated with exceptionally hot, dry conditions, made more probable by climate change. Much research has focused on extreme fire weather and its drivers, but natural wildfire regimes—and their interactions with human activities—are far from being comprehensively understood. There is a lack of clarity about the ‘causes’ of wildfire, and about how ecosystems could be managed for the co-existence of wildfire and people. We present evidence supporting an ecosystem-centred framework for improved understanding and modelling of wildfire. Wildfire has a long geological history and is a pervasive natural process in contemporary plant communities. In some biomes, wildfire would be more frequent without human settlement; in others they would be unchanged or less frequent. A world without fire would have greater forest cover, especially in present-day savannas. Many species would be missing, because fire regimes have co-evolved with plant traits that resist, adapt to or promote wildfire. Certain plant traits are favoured by different fire frequencies, and may be missing in ecosystems that are normally fire-free. For example, post-fire resprouting is more common among woody plants in high-frequency fire regimes than where fire is infrequent. The impact of habitat fragmentation on wildfire crucially depends on whether the ecosystem is fire-adapted. In normally fire-free ecosystems, fragmentation facilitates wildfire starts and is detrimental to biodiversity. In fire-adapted ecosystems, fragmentation inhibits fires from spreading and fire suppression is detrimental to biodiversity. This interpretation explains observed, counterintuitive patterns of spatial correlation between wildfire and potential ignition sources. Lightning correlates positively with burnt area only in open ecosystems with frequent fire. Human population correlates positively with burnt area only in densely forested regions. Models for vegetation-fire interactions must be informed by insights from fire ecology to make credible future projections in a changing climate. 787203
publications-1813 Peer reviewed articles 2022 Dong, N, Wright, I. J., Chen, J.M., Luo, X., Wang, H., Keenan, T.F., Smith, N.G. & Prentice, I.C. Rising CO2 and warming reduce global canopy deman for nitrogen. New Phytologist 10.1111/nph.18076 Hydrological modeling Irrigation Systems SummaryNitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO2 and climate change. By extension, it has been suggested that declining carboxylation capacity (Vcmax) and leaf N content in enhanced‐CO2 experiments and satellite records signify increasing N limitation of primary production. We predicted Vcmax using the coordination hypothesis and estimated changes in leaf‐level photosynthetic N for 1982–2016 assuming proportionality with leaf‐level Vcmax at 25°C. The whole‐canopy photosynthetic N was derived using satellite‐based leaf area index (LAI) data and an empirical extinction coefficient for Vcmax, and converted to annual N demand using estimated leaf turnover times. The predicted spatial pattern of Vcmax shares key features with an independent reconstruction from remotely sensed leaf chlorophyll content. Predicted leaf photosynthetic N declined by 0.27% yr−1, while observed leaf (total) N declined by 0.2–0.25% yr−1. Predicted global canopy N (and N demand) declined from 1996 onwards, despite increasing LAI. Leaf‐level responses to rising CO2, and to a lesser extent temperature, may have reduced the canopy requirement for N by more than rising LAI has increased it. This finding provides an alternative explanation for declining leaf N that does not depend on increasing N limitation. 787203
publications-1814 Peer reviewed articles 2020 Mengmeng Liu, Iain Colin Prentice, Cajo J. F. ter Braak, Sandy P. Harrison An improved statistical approach for reconstructing past climates from biotic assemblages Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 10.1098/rspa.2020.0346 Hydrological modeling Irrigation Systems 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. 787203
publications-1815 Peer reviewed articles 2020 Ning Dong, Iain Colin Prentice, Ian J. Wright, Bradley J. Evans, Henrique F. Togashi, Stefan Caddy‐Retalic, Francesca A. McInerney, Ben Sparrow, Emrys Leitch, Andrew J. Lowe Components of leaf‐trait variation along environmental gradients New Phytologist 10.1111/nph.16558 Uncategorized River Basins Summary 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. 787203
publications-1816 Peer reviewed articles 2020 Fortunat Joos, Renato Spahni, Benjamin D. Stocker, Sebastian Lienert, Jurek MĂŒller, Hubertus Fischer, Jochen Schmitt, I. Colin Prentice, Bette Otto-Bliesner, Zhengyu Liu N<sub>2</sub>O changes from the Last Glacial Maximum to the preindustrial – Part 2: terrestrial N<sub>2</sub>O emissions and carbon–nitrogen cycle interactions Biogeosciences 10.5194/bg-17-3511-2020 Data Management & Analytics Natural Water Bodies Abstract. 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. 787203
publications-1817 Peer reviewed articles 2023 Dong, N., Dechant, B., Wang, H., Wright, I.J. & Prentice, I.C Global leaf-trait mapping based on optimality theory Global Ecology and Biogeography 10.1111/geb.13680 IoT & Sensors Natural Water Bodies AbstractAimLeaf traits are central to plant function, and key variables in ecosystem models. However recently published global trait maps, made by applying statistical or machine‐learning techniques to large compilations of trait and environmental data, differ substantially from one another. This paper aims to demonstrate the potential of an alternative approach, based on eco‐evolutionary optimality theory, to yield predictions of spatio‐temporal patterns in leaf traits that can be independently evaluated.InnovationGlobal patterns of community‐mean specific leaf area (SLA) and photosynthetic capacity (Vcmax) are predicted from climate via existing optimality models. Then leaf nitrogen per unit area (Narea) and mass (Nmass) are inferred using their (previously derived) empirical relationships to SLA and Vcmax. Trait data are thus reserved for testing model predictions across sites. Temporal trends can also be predicted, as consequences of environmental change, and compared to those inferred from leaf‐level measurements and/or remote‐sensing methods, which are an increasingly important source of information on spatio‐temporal variation in plant traits.Main conclusionsModel predictions evaluated against site‐mean trait data from > 2,000 sites in the Plant Trait database yielded R2 = 73% for SLA, 38% for Nmass and 28% for Narea. Declining species‐level Nmass, and increasing community‐level SLA, have both been recently reported and were both correctly predicted. Leaf‐trait mapping via optimality theory holds promise for macroecological applications, including an improved understanding of community leaf‐trait responses to environmental change. 787203
publications-1818 Peer reviewed articles 2020 Sean F. Cleator, Sandy P. Harrison, Nancy K. Nichols, I. Colin Prentice, Ian Roulstone A new multivariable benchmark for Last Glacial Maximum climate simulations Climate of the Past 10.5194/cp-16-699-2020 Data Management & Analytics Natural Water Bodies Abstract. 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). 787203
publications-1819 Peer reviewed articles 2020 AliĂ©nor Lavergne, David Sandoval, Vincent J. Hare, Heather Graven, Iain Colin Prentice Impacts of soil water stress on the acclimated stomatal limitation of photosynthesis: Insights from stable carbon isotope data Global Change Biology 10.1111/gcb.15364 Data Management & Analytics Natural Water Bodies AbstractAtmospheric 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 (ÎČ) expected from the theory to explain the variance in the data, and investigate the responses of ÎČ (and thus χ) to soil water content and suction across seed plant groups, leaf phenological types and regions. Overall, ÎČ 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 ÎČ 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 stress. 787203
publications-1820 Peer reviewed articles 2021 Catherine Morfopoulos, Jean‐François MĂŒller, Trissevgeni Stavrakou, Maite Bauwens, Isabelle De Smedt, Pierre Friedlingstein, Iain Colin Prentice, Pierre Regnier Vegetation responses to climate extremes recorded by remotely sensed atmospheric formaldehyde Global Change Biology 10.1111/gcb.15880 IoT & Sensors Natural Water Bodies AbstractAccurate 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. 787203