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-1711 Peer reviewed articles 2022 Shen, Y; Sweeney, L; Liu, M; Lopez-Saez, J.A; Perez-Diaz, S; Luelmo-Lautenschlaegerer, R; Gil-Romera, E; Hoefer, D; Jimenez-Moreno, G; Schnedier, H; Prentice, I.C; Harrison, S.P. Reconstructing burnt area during the Holocene: an Iberian case study Climate of the Past 10.5194/cp-18-1189-2022 Simulation & Modeling Glacier Abstract. Charcoal accumulated in lake, bog or other anoxic sediments through time has been used to document the geographical patterns in changes in fire regimes. Such reconstructions are useful to explore the impact of climate and vegetation changes on fire during periods when human influence was less prevalent than today. However, charcoal records only provide semi-quantitative estimates of change in biomass burning. Here we derive quantitative estimates of burnt area from vegetation data in two stages. First, we relate the modern charcoal abundance to burnt area using a conversion factor derived from a generalised linear model of burnt area probability based on eight environmental predictors. Then, we establish the relationship between fossil pollen assemblages and burnt area using tolerance-weighted weighted averaging partial least-squares regression with a sampling frequency correction (fxTWA-PLS). We test this approach using the Iberian Peninsula as a case study because it is a fire-prone region with abundant pollen and charcoal records covering the Holocene. We derive the vegetation–burnt area relationship using the 31 records that have both modern and fossil charcoal and pollen data and then reconstruct palaeoburnt area for the 113 records with Holocene pollen records. The pollen data predict charcoal-derived burnt area relatively well (R2 = 0.44), and the changes in reconstructed burnt area are synchronous with known climate changes through the Holocene. This new method opens up the possibility of reconstructing changes in fire regimes quantitatively from pollen records, after regional calibration of the vegetation–burnt area relationship, in regions where pollen records are more abundant than charcoal records. 787203
publications-1712 Peer reviewed articles 2020 Jennifer Paillassa, Ian J. Wright, I. Colin Prentice, Steeve Pepin, Nicholas G. Smith, Gilbert Ethier, Andrea C. Westerband, Laurent J. Lamarque, Wang Han, Will K. Cornwell, Vincent Maire When and where soil is important to modify the carbon and water economy of leaves New Phytologist 10.1111/nph.16702 Data Management & Analytics Hydropower Dams & reservoirs Summary 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. 787203
publications-1713 Peer reviewed articles 2022 Wang, H., Harrison, S.P., Li, M., Prentice, I.C., Qiao, S., Wang, R., Xu, H., Mengoli, G., Peng, Y. and Yang, Y. CPTDv2: The China Plant Trait Database Version 2 Scientific Data 10.1038/s41597-022-01884-4 Simulation & Modeling Glacier AbstractPlant functional traits represent adaptive strategies to the environment, linked to biophysical and biogeochemical processes and ecosystem functioning. Compilations of trait data facilitate research in multiple fields from plant ecology through to land-surface modelling. Here we present version 2 of the China Plant Trait Database, which contains information on morphometric, physical, chemical, photosynthetic and hydraulic traits from 1529 unique species in 140 sites spanning a diversity of vegetation types. Version 2 has five improvements compared to the previous version: (1) new data from a 4-km elevation transect on the edge of Tibetan Plateau, including alpine vegetation types not sampled previously; (2) inclusion of traits related to hydraulic processes, including specific sapwood conductance, the area ratio of sapwood to leaf, wood density and turgor loss point; (3) inclusion of information on soil properties to complement the existing data on climate and vegetation (4) assessments and flagging the reliability of individual trait measurements; and (5) inclusion of standardized templates for systematical field sampling and measurements. 787203
publications-1714 Peer reviewed articles 2022 Haas, O. Prentice, I. C & Harrison, S.P. Global environmental controls on wildfire burnt area, size and intensity. Environmental Research Letters 10.1088/1748-9326/ac6a69 Simulation & Modeling Glacier AbstractFire is an important influence on the global patterns of vegetation structure and composition. Wildfire is included as a distinct process in many dynamic global vegetation models but limited current understanding of fire regimes restricts these models’ ability to reproduce more than the broadest geographic patterns. Here we present a statistical analysis of the global controls of remotely sensed burnt area (BA), fire size (FS), and a derived metric related to fire intensity (FI). Separate generalized linear models were fitted to observed monthly fractional BA from the Global Fire Emissions Database (GFEDv4), median FS from the Global Fire Atlas, and median fire radiative power from the MCD14ML dataset normalized by the square root of median FS. The three models were initially constructed from a common set of 16 predictors; only the strongest predictors for each model were retained in the final models. It is shown that BA is primarily driven by fuel availability and dryness; FS by conditions promoting fire spread; and FI by fractional tree cover and road density. Both BA and FS are constrained by landscape fragmentation, whereas FI is constrained by fuel moisture. Ignition sources (lightning and human population) were positively related to BA (after accounting for road density), but negatively to FI. These findings imply that the different controls on BA, FS and FI need to be considered in process-based models. They highlight the need to include measures of landscape fragmentation as well as fuel load and dryness, and to pay close attention to the controls of fire spread. 787203
publications-1715 Peer reviewed articles 2024 Victor Flo, Jaideep Joshi, Manon Sabot, David Sandoval, Iain Colin Prentice Incorporating photosynthetic acclimation improves stomatal optimisation models Plant, Cell & Environment 10.1111/pce.14891 Simulation & Modeling Glacier AbstractStomatal opening in plant leaves is regulated through a balance of carbon and water exchange under different environmental conditions. Accurate estimation of stomatal regulation is crucial for understanding how plants respond to changing environmental conditions, particularly under climate change. A new generation of optimality‐based modelling schemes determines instantaneous stomatal responses from a balance of trade‐offs between carbon gains and hydraulic costs, but most such schemes do not account for biochemical acclimation in response to drought. Here, we compare the performance of six instantaneous stomatal optimisation models with and without accounting for photosynthetic acclimation. Using experimental data from 37 plant species, we found that accounting for photosynthetic acclimation improves the prediction of carbon assimilation in a majority of the tested models. Photosynthetic acclimation contributed significantly to the reduction of photosynthesis under drought conditions in all tested models. Drought effects on photosynthesis could not accurately be explained by the hydraulic impairment functions embedded in the stomatal models alone, indicating that photosynthetic acclimation must be considered to improve estimates of carbon assimilation during drought. 787203
publications-1716 Peer reviewed articles 2022 Fu, Z., Ciais, P., Prentice, I.C., Gentine, P., Makowski, D., Bastos, A., Luo, X., Green, J., Stoy, P., Yang, H. and Hajima, T. Atmospheric dryness reduces photosynthesis along a large range of soil water deficits Nature Communications 10.1038/s41467-022-28652-7 AI & Machine Learning Glacier AbstractBoth low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates. 787203
publications-1717 Peer reviewed articles 2022 Chen, J.M., Wang, R., Liu, Y., He, L., Croft, H., Luo, X., Wang, H., Smith, N.G., Keenan, T.F., Prentice, I.C., Zhang, Y., Ju, W., Dong, N. Global datasets of leaf photosynthetic capacity for ecological and earth system research. Earth System Science Data 10.5194/essd-14-4077-2022 Simulation & Modeling Glacier Abstract. The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r2=0.79,RMSE=15.46”mol m−2 s−1, P<0.001) and compare well with 3672 ground-based measurements (r2=0.69,RMSE=13.8”mol m−2 s−1 and P<0.001 for SIF; r2=0.55,RMSE=18.28”mol m−2 s−1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC, and SIF+LCC are available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R and https://doi.org/10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022). 787203
publications-1718 Peer reviewed articles 2022 Cruz-Silva, E; Harrison, S.P.; Marinova-Wolff, E; Prentice, I.C. A new method based on surface-sample pollen data for reconstructing palaeovegetation patterns Journal of Biogeography 10.1111/jbi.14448 Data Management & Analytics Glacier AbstractAimBiomisation has been the most widely used technique to reconstruct past regional vegetation patterns because it does not require an extensive modern pollen dataset. However, it has well‐known limitations including its dependence on expert judgement for the assignment of pollen taxa to plant functional types (PFTs) and PFTs to biomes. Here we present a new method that combines the strengths of biomisation with those of the alternative dissimilarity‐based techniques.LocationThe Eastern Mediterranean‐Black Sea Caspian Corridor (EMBSeCBIO).TaxonPlantsMethodsModern pollen samples, assigned to biomes based on potential natural vegetation data, are used to characterize the within‐biome means and standard deviations of the abundances of each taxon. These values are used to calculate a dissimilarity index between any pollen sample and every biome, and thus assign the sample to the most likely biome. We calculate a threshold value for each modern biome; fossil samples with scores below the threshold for all modern biomes are thus identified as non‐analogue vegetation. We applied the new method to the EMBSeCBIO region to compare its performance with existing reconstructions.ResultsThe method captured changes in the importance of individual taxa along environmental gradients. The balanced accuracy obtained for the EMBSeCBIO region using the new method was better than obtained using biomisation (77% vs. 65%). When the method was applied to high‐resolution fossil records, 70% of the entities showed more temporally stable biome assignments than obtained using biomisation. The technique also identified likely non‐analogue assemblages in a synthetic modern dataset and in fossil records.Main conclusionsThe new method yields more accurate and stable reconstructions of vegetation than biomisation. It requires an extensive modern pollen dataset, but is conceptually simple, and avoids subjective choices about taxon allocations to PFTs and PFTs to biomes. 787203
publications-1719 Peer reviewed articles 2020 Shengchao Qiao, Han Wang, I. Colin Prentice, Sandy P. Harrison Extending a first-principles primary production model to predict wheat yields Agricultural and Forest Meteorology 10.1016/j.agrformet.2020.107932 AI & Machine Learning Uncategorized No abstract available 787203
publications-1720 Peer reviewed articles 2023 Keith J. Bloomfield; Benjamin D. Stocker; Trevor F. Keenan; I. Colin Prentice Environmental controls on the light use efficiency of terrestrial gross primary production Global Change Biology 10.1111/gcb.16511 AI & Machine Learning Hydropower Dams & reservoirs AbstractGross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies. 787203