Imperial College London

Professor Iain Colin Prentice

Faculty of Natural SciencesDepartment of Life Sciences (Silwood Park)

Chair in Biosphere and Climate Impacts
 
 
 
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Contact

 

+44 (0)20 7594 2482c.prentice

 
 
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Location

 

2.3Centre for Population BiologySilwood Park

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Summary

 

Publications

Publication Type
Year
to

431 results found

Flo V, Joshi J, Sabot M, Sandoval D, Prentice ICet al., 2024, Incorporating photosynthetic acclimation improves stomatal optimisation models, Plant, Cell and Environment, ISSN: 0140-7791

Journal article

Blackford K, Kasoar M, Burton C, Burke E, Prentice IC, Voulgarakis Aet al., 2024, INFERNO-peat v1.0.0: a representation of northern high latitude peat fires in the JULES-INFERNO global fire model, Geoscientific Model Development, ISSN: 1991-959X

Journal article

Cruz-Silva E, Harrion SP, Prentice IC, Marinova Eet al., 2024, Holocene vegetation dynamics of the Eastern Mediterranean region: old controversies addressed by a new analysis, Journal of Biogeography, Vol: 51, Pages: 294-310, ISSN: 0305-0270

Aim:We reconstruct vegetation changes since 12 ky in the Eastern Mediterranean to examine four features of the regional vegetation history that are controversial: the extent of non-analogue vegetation assemblages in the transition from the Late Glacial to the early Holocene, the synchroneity of postglacial forest expansion, the geographical extent of temperate deciduous forest during the mid-Holocene and the timing and trigger for the re-establishment of drought-tolerant vegetation during the late Holocene.Location:The Eastern Mediterranean–Black Sea Caspian Corridor.Taxon:Vascular plants.Methods:We reconstruct vegetation changes for 122 fossil pollen records using a method that accounts for within-biome variability in pollen taxon abundance to determine the biome with which a sample has greatest affinity. Per-biome affinity threshold values were used to identify samples that do not belong to any modern biome. We apply time series analysis and mapping to examine space and time changes.Results:Sites with non-analogue vegetation were most common between 11.5 and 9.5 ky and mostly in the Carpathians. The transition from open vegetation to forest occurred at 10.64 ± 0.65 ky across the whole region. Temperate deciduous forest was not more extensive at 6 ky; maximum expansion occurred between 5.5 and 5 ky. Expansion of forest occurred between c. 4 and 2.8 k, followed by an abrupt decrease and a subsequent recovery. This pattern is not consistent with a systematic decline of forest towards more drought-tolerant vegetation in the late Holocene but is consistent with centennial-scale speleothem patterns linked to variations in moisture availability.Main Conclusions:We show the occurrence of non-analogue vegetation types peaked during early Holocene, forest expansion was synchronous across the region and there was an expansion of moisture-demanding temperate trees around 5.5 to 5 ky. There is no signal of a continuous late Holocene aridificat

Journal article

Keeping T, Harrison SP, Prentice IC, 2024, Modelling the daily probability of wildfire occurrence in the contiguous United States, Environmental Research Letters, Vol: 19, ISSN: 1748-9326

The development of a high-quality wildfire occurrence model is an essential component in mapping present wildfire risk, and in projecting future wildfire dynamics with climate and land-use change. Here, we develop a new model for predicting the daily probability of wildfire occurrence at 0.1° (∼10 km) spatial resolution by adapting a generalised linear modelling (GLM) approach to include improvements to the variable selection procedure, identification of the range over which specific predictors are influential, and the minimisation of compression, applied in an ensemble of model runs. We develop and test the model using data from the contiguous United States. The ensemble performed well in predicting the mean geospatial patterns of fire occurrence, the interannual variability in the number of fires, and the regional variation in the seasonal cycle of wildfire. Model runs gave an area under the receiver operating characteristic curve (AUC) of 0.85–0.88, indicating good predictive power. The ensemble of runs provides insight into the key predictors for wildfire occurrence in the contiguous United States. The methodology, though developed for the United States, is globally implementable.

Journal article

Ren Y, Wang H, Harrison SP, Prentice IC, Atkin OK, Smith NG, Mengoli G, Stefanski A, Reich PBet al., 2024, Reduced global plant respiration due to the acclimation of leaf dark respiration coupled to photosynthesis, New Phytologist, Vol: 241, Pages: 578-591, ISSN: 0028-646X

Leaf dark respiration (Rd) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that Rd and Rubisco carboxylation capacity (Vcmax) at 25°C (Rd,25, Vcmax,25) are coordinated so that Rd,25 variations support Vcmax,25 at a level allowing full light use, with Vcmax,25 reflecting daytime conditions (for photosynthesis), and Rd,25/Vcmax,25 reflecting night-time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5-yr warming experiment, and spatially using an extensive field-measurement data set. We compared the results to three published alternatives: Rd,25 declines linearly with daily average prior temperature; Rd at average prior night temperatures tends towards a constant value; and Rd,25/Vcmax,25 is constant. Our hypothesis accounted for more variation in observed Rd,25 over time (R2 = 0.74) and space (R2 = 0.68) than the alternatives. Night-time temperature dominated the seasonal time-course of Rd, with an apparent response time scale of c. 2 wk. Vcmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global Rd in response to rising CO2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Journal article

Ruehr S, Keenan TF, Williams C, Zhou Y, Lu X, Bastos A, Canadell JG, Prentice IC, Sitch S, Terrer Cet al., 2023, Publisher Correction: Evidence and attribution of the enhanced land carbon sink (Nature Reviews Earth & Environment, (2023), 4, 8, (518-534), 10.1038/s43017-023-00456-3), Nature Reviews Earth and Environment, Vol: 4

Correction to: Nature Reviews Earth & Environment, published online 25 July 2023. In the version of the article initially published, the y-axis labels in Fig. 7b, now reading “+” and “–”, read “234” and “254”, respectively. This has been corrected in the HTML and PDF versions of the article.

Journal article

Peng Y, Prentice IC, Bloomfield KJ, Campioli M, Guo Z, Sun Y, Tian D, Wang X, Vicca S, Stocker BDet al., 2023, Global terrestrial nitrogen uptake and nitrogen use efficiency, Journal of Ecology, Vol: 111, Pages: 2676-2693, ISSN: 0022-0477

1. Plant biomass production (BP), nitrogen uptake (Nup) and their ratio, nitrogen use efficiency (NUE), must be quantified to understand how nitrogen (N) cycling constrains terrestrial carbon (C) uptake. But the controls of key plant processes determining Nup and NUE, including BP, C and N allocation, tissue C:N ratios and N resorption efficiency (NRE), remain poorly known. 2. We compiled measurements from 804 forest and grassland sites and derived regression models for each of these processes with growth temperature, vapour pressure deficit, stand age, soil C:N ratio, fAPAR (remotely sensed fraction of photosynthetically active radiation absorbed by green vegetation) and growing-season average daily incident photosynthetic photon flux density (gPPFD) (effectively the seasonal concentration of light availability, which increases polewards) as predictors. An empirical model for leaf N was based on optimal photosynthetic capacity (a function of gPPFD and climate) and observed leaf mass-per-area. The models were used to produce global maps of Nup and NUE. 3. Global BP was estimated as 72 Pg C/yr; Nup as 950 Tg N/yr; and NUE as 76 gC/gN. Forest BP was found to increase with growth temperature and fAPAR and to decrease with stand age, soil C:N ratio and gPPFD. Forest NUE is controlled primarily by climate through its effect on C allocation – especially to leaves, being richer in N than other tissues. NUE is greater in colder climates, where N is less readily available, because belowground allocation is increased. NUE is also greater in drier climates because leaf allocation is reduced. NRE is enhanced (further promoting NUE) in both cold and dry climates. 4. These findings can provide observationally based benchmarks for model representations of C–N cycle coupling. State-of-the-art vegetation models in the TRENDY ensemble showed variable performance against these benchmarks, and models including coupled C–N cycling produced relatively poor simulations o

Journal article

Keenan TF, Luo X, Stocker BD, De Kauwe MG, Medlyn BE, Prentice IC, Smith NG, Terrer C, Wang H, Zhang Y, Zhou Set al., 2023, A constraint on historic growth in global photosynthesis due to rising CO2, Nature Climate Change, Vol: 13, Pages: 1376-1381, ISSN: 1758-678X

Theory predicts that rising CO2 increases global photosynthesis, a process known as CO2 fertilization, and that this is responsible for a large proportion of the current terrestrial carbon sink. The estimated magnitude of the historic CO2 fertilization, however, differs by an order ofmagnitude between long-term proxies, remote sensing-based estimates and terrestrial biosphere models. Here we constrain the likely historic effect of CO2 on global photosynthesis by combining terrestrial biosphere models, ecological optimality theory, remote sensing approaches and an emergent constraint based on global carbon budget estimates. Our analysis suggests that CO2 fertilization increased global annual terrestrial photosynthesis by 13.5 ± 3.5%, or 15.9 ± 2.9 Pg C u(mean ± standard deviation) between 1981 and 2020. Our results help resolve conflicting estimates of the historic sensitivity of global terrestrial photosynthesis to CO2 and highlight the large impact anthropogenic emissions have had on ecosystems worldwide.

Journal article

Xu H, Wang H, Prentice IC, Harrison SPet al., 2023, Leaf carbon and nitrogen stoichiometric variation alongenvironmental gradients, Biogeosciences, Vol: 20, Pages: 4511-4525, ISSN: 1726-4170

Leaf stoichiometric traits are central to ecosystem function and biogeochemical cycling, yet no accepted theory predicts their variation along environmental gradients. Using data in the China Plant Trait Database version 2, we aimed to characterize variation in leaf carbon and nitrogen per unit mass (Cmass, Nmass) and their ratio, and to test an eco-evolutionary optimality model for Nmass. Community-mean trait values were related to climate variables by multiple linear regression. Climatic optima and tolerances of major genera were estimated; Pagel’s λ was used to quantify phylogenetic controls, and Bayesian phylogenetic linear mixed models to assess the contributions of climate, species identity and phylogeny. Optimality-based predictions of community-mean Nmass were compared to observed values. All traits showed strong phylogenetic signals. Climate explained only 18 % of C : N ratio variation among species but 45 % among communities, highlighting the role of taxonomic replacement in mediating community-level responses. Geographic distributions of deciduous taxa separated primarily by moisture, evergreens by temperature. Cmass increased with irradiance, but decreased with moisture and temperature. Nmass declined with all three variables. C : N ratio variations were dominated by Nmass. The coefficients relating Nmass to the ratio of maximum carboxylation capacity at 25 °C (Vcmax25) and leaf mass per area (Ma) were influenced by leaf area index. The optimality model captured 68 % and 53 % of variation between communities for Vcmax25 and Ma respectively, and 30 % for Nmass. We conclude that stoichiometric variations along climate gradients are achieved largely by environmental selection among species and clades with different characteristic trait values. Variations in leaf C : N ratio are mainly determined by Nmass, and optimality-based modelling shows useful predictive ability for community-mean Nmass. These findings should help to improve the repres

Journal article

Cruz-Silva E, Harrison SP, Colin Prentice I, Marinova E, Bartlein PJ, Renssen H, Zhang Yet al., 2023, Pollen-based reconstructions of Holocene climate trends in the eastern Mediterranean region, Climate of the Past, Vol: 19, Pages: 2093-2108, ISSN: 1814-9324

There has been considerable debate about the degree to which climate has driven societal changes in the eastern Mediterranean region, partly through reliance on a limited number of qualitative records of climate changes and partly reflecting the need to disentangle the joint impact of changes in different aspects of climate. Here, we use tolerance-weighted, weighted-averaging partial least squares to derive reconstructions of the mean temperature of the coldest month (MTCO), mean temperature of the warmest month (MTWA), growing degree days above a threshold of 0 C (GDD0), and plant-available moisture, which is represented by the ratio of modelled actual to equilibrium evapotranspiration (α) and corrected for past CO2 changes. This is done for 71 individual pollen records from the eastern Mediterranean region covering part or all of the interval from 12.3 ka to the present. We use these reconstructions to create regional composites that illustrate the long-term trends in each variable. We compare these composites with transient climate model simulations to explore potential causes of the observed trends. We show that the glacial-Holocene transition and the early part of the Holocene was characterised by conditions colder than the present. Rapid increases in temperature occurred between ca. 10.3 and 9.3 ka, considerably after the end of the Younger Dryas. Although the time series are characterised by centennial to millennial oscillations, the MTCO showed a gradual increase from 9 ka to the present, consistent with the expectation that winter temperatures were forced by orbitally induced increases in insolation during the Holocene. The MTWA also showed an increasing trend from 9 ka and reached a maximum of ca. 1.5 C greater than the present at ca. 4.5 and 5 ka, followed by a gradual decline towards present-day conditions. A delayed response to summer insolation changes is likely a reflection of the persistence of the Laurentide and Fennoscandian ice sheets; subse

Journal article

Haas O, Prentice IC, Harrison SP, 2023, The response of wildfire regimes to Last Glacial Maximum carbon dioxide and climate, Biogeosciences, Vol: 20, Pages: 3981-3995, ISSN: 1726-4170

Climate and fuel availability jointly control the incidence of wildfires. The effects of atmospheric CO2 on plant growth influence fuel availability independently of climate, but the relative importance of each in driving largescale changes in wildfire regimes cannot easily be quantified from observations alone. Here, we use previously developed empirical models to simulate the global spatial pattern of burnt area, fire size, and fire intensity for modern and Last Glacial Maximum (LGM; ∼21 000 ka) conditions using both realistic changes in climate and CO2 and sensitivity experiments to separate their effects. Three different LGM scenarios are used to represent the range of modelled LGM climates.We show large, modelled reductions in burnt area at the LGM compared to the recent period, consistent with the sedimentary charcoal record. This reduction was predominantly driven by the effect of low CO2 on vegetation productivity. The amplitude of the reduction under low-CO2 conditions was similar regardless of the LGM climate scenario and was not observed in any LGM scenario when only climate effects were considered, with one LGM climate scenario showing increased burning under these conditions. Fire intensity showed a similar sensitivity to CO2 across different climates but was also sensitive to changes in vapour pressure deficit (VPD). Modelled fire size was reduced under LGM CO2 in many regions but increased under LGM climates because of changes in wind strength, dry days (DDs), and diurnal temperature range (DTR). This increase was offset under the coldest LGM climate in the northern latitudes because of a large reduction in VPD. These results emphasize the fact that the relative magnitudes of changes in different climate variables influence the wildfire regime and that different aspects of climate change can have opposing effects. The importance of CO2 effects imply that future projections of wildfire must take rising CO2 into account.

Journal article

Ruehr S, Keenan TF, Williams C, Zhou Y, Lu X, Bastos A, Canadell JG, Prentice IC, Sitch S, Terrer Cet al., 2023, Evidence and attribution of the enhanced land carbon sink, Nature Reviews Earth & Environment, Vol: 4, Pages: 518-534, ISSN: 2662-138X

Climate change has been partially mitigated by an increasing net land carbon sink in the terrestrial biosphere; understanding the processes that drive the land carbon sink is thus essential for protecting, managing, and projecting this important ecosystem service. In this Review, we examine evidence for an enhanced land carbon sink and attribute the observed response to drivers and processes. The land carbon sink has doubled from 1.2 ± 0.5 PgC yr-1 in the 1960s to 3.1 ± 0.6 PgC yr-1 in the 2010s. This trend results largely from carbon dioxide (CO2) fertilization increasing photosynthesis (driving an increase in the annual land carbon sink of >2PgC globally since 1900), mainly in tropical forest regions, and elevated temperatures reducing cold-limitation, mainly at higher latitudes. Continued long term land carbon sequestration is possible through the end of this century under multiple emissions scenarios, especially if nature-based climate solutions and appropriate ecosystem management are deployed. A new generation of globally distributed field experiments are needed to improve understanding of future carbon sink potential by measuring belowground carbon release, the response to CO2 enrichment, and long-term shifts in carbon allocation and turnover .

Journal article

Dong N, Dechant B, Wang H, Wright IJ, Prentice ICet al., 2023, Global leaf-trait mapping based on optimality theory, Global Ecology and Biogeography, Vol: 32, Pages: 1152-1162, ISSN: 1466-822X

AimLeaf 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.

Journal article

Tan S, Wang H, Prentice IC, Yang K, Nóbrega RLB, Liu X, Wang Y, Yang Yet al., 2023, Towards a universal evapotranspiration model based on optimality principles, Agricultural and Forest Meteorology, Vol: 336, Pages: 1-11, ISSN: 0168-1923

Natural resource management requires knowledge of terrestrial evapotranspiration (ET). Most existing numeric models for ET include multiple plant- or ecosystem-type specific parameters that require calibration. This is a significant source of uncertainty under changing environmental conditions. A novel ET model with no type−specific parameters was developed recently. Based on the coupling the diffusion (via stomata) of water and carbon dioxide (CO2), this model predicts canopy conductance based on environmental conditions using eco-evolutionary optimality principles that apply to all plant types. Transpiration (T) and ET are calculated from canopy conductance using the Penman-Monteith equation for T and a universal empirical function for the T:ET ratio. Here, the model is systematically evaluated at globally distributed eddy-covariance sites and river basins. Site-scale modelled ET agrees well with flux data (r = 0.81, root mean square error = 0.73 mm day–1 in 23,623 records) and modelled ET in 39 river basins agrees well with the ET estimated by monthly water budget using two runoff datasets (r = 0.62 and 0.66, respectively). Modelled global patterns of ET are consistent with existing global ET products. The model's universality, parsimony and accuracy combine to indicate a broad potential field of application in resource management and global change science.

Journal article

Shen Y, Cai W, Prentice IC, Harrison SPet al., 2023, Community abundance of resprouting in woody plants reflects fire return time, intensity, and type, Forests, Vol: 14, Pages: 1-13, ISSN: 1999-4907

Plants in fire-prone ecosystems have evolved a variety of mechanisms to resist or adapt to fire. Post-fire resprouting is a key adaptation that promotes rapid ecosystem recovery and hence has a major impact on the terrestrial carbon cycle. However, our understanding of how the incidence of resprouting varies in different fire regimes is largely qualitative. The increasing availability of plant trait data and plot-based species cover data provides an opportunity to quantify the relationships between fire-related traits and fire properties. We investigated the quantitative relationship between fire frequency (expressed as the fire return time) and the proportion of resprouters in woody plants using plot data on species cover from Australia and Europe. We also examined the relationship between the proportion of resprouters and gross primary production (GPP) and grass cover, where GPP was assumed to reflect fuel loads and hence fire intensity, while grass cover was considered to be an indicator of the likelihood of ground fire and the speed of fire spread, using generalised linear modelling. The proportion of resprouting species decreased significantly as the fire return time increased. When the fire return time was considered along with other aspects of the fire regime, the proportion of resprouters had significant negative relationships with the fire return time and grass cover and a significant positive relationship with GPP. These findings demonstrate that plants with the ability to resprout occur more often where fire regimes are characterised by high-frequency and high-intensity crown fires. Establishing quantitative relationships between the incidence of resprouting and the fire return time and fire type provides a basis for modelling resprouting as a consequence of the characteristics of the fire regime, which in turn makes it possible to model the consequences of changing fire regimes on ecosystem properties.

Journal article

Liu M, Shen Y, Gonzalez-Samperiz P, Gil-Romera G, ter Braak CJF, Prentice IC, Harrison SPet al., 2023, Holocene climates of the Iberian Penisula: pollen-based reconstructions of changes in the west-east gradient of temperature and moisture, Climate of the Past, Vol: 19, Pages: 803-834, ISSN: 1814-9324

The Iberian Peninsula is characterised by a steep west-east moisture gradient today, reflecting the dominance of maritime influences along the Atlantic coast and more Mediterranean-type climate further east. Holocene pollen records from the Peninsula suggest that this gradient was less steep during the mid-Holocene, possibly reflecting the impact of orbital changes on circulation and thus regional patterns in climate. Here we use 7214 pollen samples from 117 sites covering part or all of the last 12,000 years to reconstruct changes in seasonal temperature and in moisture across the Iberian Peninsula quantitatively. We show that there is an increasing trend in winter temperature at a regional scale, consistent with known changes in winter insolation. However, summer temperatures do not show the decreasing trend through the Holocene that would be expected if they were a direct response to insolation forcing. We show that summer temperature is strongly correlated with plant-available moisture (α), as measured by the ratio of actual evapotranspiration to equilibrium evapotranspiration, which declines through the Holocene. The reconstructions also confirm that the west-east gradient in moisture was considerably less steep than today during the mid-Holocene, indicating that atmospheric circulation changes (possibly driven by orbital changes) have been important determinants of the Holocene climate of the region.

Journal article

Bloomfield K, van Hoolst R, Balzarolo M, Janssens IA, Vicca S, Ghent D, Prentice ICet al., 2023, Towards a general monitoring system for terrestrial primary production: a test spanning the European drought of 2018, Remote Sensing, Vol: 15, Pages: 1-15, ISSN: 2072-4292

(1) Land surface models require inputs of temperature and moisture variables to generate predictions of gross primary production (GPP). Differences between leaf and air temperature vary temporally and spatially and may be especially pronounced under conditions of low soil moisture availability. The Sentinel-3 satellite mission offers estimates of the land surface temperature (LST), which for vegetated pixels can be adopted as the canopy temperature. Could remotely sensed estimates of LST offer a parsimonious input to models by combining information on leaf temperature and hydration? (2) Using a light use efficiency model that requires only a handful of input variables, we generated GPP simulations for comparison with eddy-covariance inferred estimates available from flux sites within the Integrated Carbon Observation System. Remotely sensed LST and greenness data were input from Sentinel-3. Gridded air temperature data were obtained from the European Centre for Medium-Range Weather Forecasts. We chose the years 2018–2019 to exploit the natural experiment of a pronounced European drought. (3) Simulated GPP showed good agreement with flux-derived estimates. During dry conditions, simulations forced with LST performed better than those with air temperature for shrubland, grassland and savanna sites. (4) This study advances the prospect for a global GPP monitoring system that will rely primarily on remotely sensed inputs.

Journal article

Qiao S, Harrison SP, Prentice IC, Wang Het al., 2023, Optimality-based modelling of wheat sowing dates globally, Agricultural Systems, Vol: 206, Pages: 1-11, ISSN: 0308-521X

CONTEXTSowing dates are currently an essential input for crop models. However, in the future, the optimal sowing time will be affected by climate changes and human adaptations to these changes. A better understanding of what determines the choice of wheat type and sowing dates is required to be able to predict future crop yields reliably.OBJECTIVEThis study was conducted to understand how climate conditions affect the choice of wheat types and sowing dates globally.METHODSWe develop a model integrating optimality concepts for simulating gross primary production (GPP) with climate constraints on wheat phenology to predict sowing dates. We assume that wheat could be sown at any time with suitable climate conditions and farmers would select a sowing date that maximises yields. The model is run starting on every possible climatically suitable day, determined by climate constraints associated with low temperature and intense precipitation. The optimal sowing date is the day which gives the highest yield in each location. We evaluate the simulated optimal sowing dates with data on observed sowing dates created by merging census-based datasets and local agronomic information, then predict their changes under future climate scenarios to gain insight into the impacts of climate change.RESULTS AND CONCLUSIONSCold-season temperatures are the major determinant of sowing dates in the extra-tropics, whereas the seasonal cycle of monsoon rainfall is important in the tropics. Our model captures the timing of reported sowing dates, with differences of less than one month over much of the world; maximum errors of up to two months occur in tropical regions with large altitudinal gradients. Discrepancies between predictions and observations are larger in tropical regions than temperate and cold regions. Slight warming is shown to promote earlier sowing in wet areas but later in dry areas; larger warming leads to delayed sowing in most regions. These predictions arise due to the interac

Journal article

Westerband AC, Wright IJ, Maire V, Paillassa J, Prentice IC, Atkin OK, Bloomfield KJ, Cernusak LA, Dong N, Gleason SM, Guilherme Pereira C, Lambers H, Leishman MR, Malhi Y, Nolan RHet al., 2023, Coordination of photosynthetic traits across soil and climate gradients, Global Change Biology, Vol: 29, Pages: 856-873, ISSN: 1354-1013

"Least-cost theory" posits that C3 plants should balance rates of photosynthetic water loss and carboxylation in relation to the relative acquisition and maintenance costs of resources required for these activities. Here we investigated the dependency of photosynthetic traits on climate and soil properties using a new Australia-wide trait dataset spanning 528 species from 67 sites. We tested the hypotheses that plants on relatively cold or dry sites, or on relatively more fertile sites, would typically operate at greater CO2 drawdown (lower ratio of leaf internal to ambient CO2 , Ci :Ca ) during light-saturated photosynthesis, and at higher leaf N per area (Narea ) and higher carboxylation capacity (Vcmax 25 ) for a given rate of stomatal conductance to water vapour, gsw . These results would be indicative of plants having relatively higher water costs than nutrient costs. In general, our hypotheses were supported. Soil total phosphorus (P) concentration and (more weakly) soil pH exerted positive effects on the Narea -gsw and Vcmax 25 -gsw slopes, and negative effects on Ci :Ca . The P effect strengthened when the effect of climate was removed via partial regression. We observed similar trends with increasing soil cation exchange capacity and clay content, which affect soil nutrient availability, and found that soil properties explained similar amounts of variation in the focal traits as climate did. Although climate typically explained more trait variation than soil did, together they explained up to 52% of variation in the slope relationships and soil properties explained up to 30% of the variation in individual traits. Soils influenced photosynthetic traits as well as their coordination. In particular, the influence of soil P likely reflects the Australia's geologically ancient low-relief landscapes with highly leached soils. Least-cost theory provides a valuable framework for understanding trade-offs between resource costs and use in plants, including

Journal article

Bloomfield KJ, Stocker BD, Keenan TF, Prentice ICet al., 2023, Environmental controls on the light use efficiency of terrestrial gross primary production, Global Change Biology, Vol: 29, Pages: 1037-1053, ISSN: 1354-1013

Gross 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.

Journal article

Wang H, Prentice IC, Wright IJ, warton DI, Qiao S, Xu X, Zhou J, Kikuzawa K, Stenseth NCet al., 2023, Leaf economics fundamentals explained by optimality principles, Science Advances, Vol: 9, ISSN: 2375-2548

The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics.

Journal article

Zhu Z, Wang H, Harrison SP, Prentice IC, Qiao S, Tan Set al., 2023, Optimality principles explaining divergent responses of alpine vegetation to environmental change, Global Change Biology, Vol: 29, Pages: 126-142, ISSN: 1354-1013

Recent increases in vegetation greenness over much of the world reflect increasing CO2 globally and warming in cold areas. However, the strength of the response to both CO2 and warming in those areas appears to be declining for unclear reasons, contributing to large uncertainties in predicting how vegetation will respond to future global changes. Here, we investigated the changes of satellite-observed peak season absorbed photosynthetically active radiation (Fmax) on the Tibetan Plateau between 1982 and 2016. Although climate trends are similar across the Plateau, we identified robust divergent responses (a greening of 0.31 ± 0.14% year−1 in drier regions and a browning of 0.12 ± 0.08% year−1 in wetter regions). Using an eco-evolutionary optimality (EEO) concept of plant acclimation/adaptation, we propose a parsimonious modelling framework that quantitatively explains these changes in terms of water and energy limitations. Our model captured the variations in Fmax with a correlation coefficient (r) of .76 and a root mean squared error of .12 and predicted the divergent trends of greening (0.32 ± 0.19% year−1) and browning (0.07 ± 0.06% year−1). We also predicted the observed reduced sensitivities of Fmax to precipitation and temperature. The model allows us to explain these changes: Enhanced growing season cumulative radiation has opposite effects on water use and energy uptake. Increased precipitation has an overwhelmingly positive effect in drier regions, whereas warming reduces Fmax in wetter regions by increasing the cost of building and maintaining leaf area. Rising CO2 stimulates vegetation growth by enhancing water-use efficiency, but its effect on photosynthesis saturates. The large decrease in the sensitivity of vegetation to climate reflects a shift from water to energy limitation. Our study demonstrates the potential of EEO approaches to reveal the

Journal article

Wang H, Harrison SP, Li M, Prentice IC, Qiao S, Wang R, Xu H, Mengoli G, Peng Y, Yang Yet al., 2022, The China plant trait database version 2, Scientific Data, Vol: 9, ISSN: 2052-4463

Plant 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.

Journal article

Díaz S, Kattge J, Cornelissen JHC, Wright IJ, Lavorel S, Dray S, Reu B, Kleyer M, Wirth C, Prentice IC, Garnier E, Bönisch G, Westoby M, Poorter H, Reich PB, Moles AT, Dickie J, Zanne AE, Chave J, Wright SJ, Sheremetiev SN, Jactel H, Baraloto C, Cerabolini BEL, Pierce S, Shipley B, Casanoves F, Joswig JS, Günther A, Falczuk V, Rüger N, Mahecha MD, Gorné LD, Amiaud B, Atkin OK, Bahn M, Baldocchi D, Beckmann M, Blonder B, Bond W, Bond-Lamberty B, Brown K, Burrascano S, Byun C, Campetella G, Cavender-Bares J, Chapin FS, Choat B, Coomes DA, Cornwell WK, Craine J, Craven D, Dainese M, de Araujo AC, de Vries FT, Domingues TF, Enquist BJ, Fagúndez J, Fang J, Fernández-Méndez F, Fernandez-Piedade MT, Ford H, Forey E, Freschet GT, Gachet S, Gallagher R, Green W, Guerin GR, Gutiérrez AG, Harrison SP, Hattingh WN, He T, Hickler T, Higgins SI, Higuchi P, Ilic J, Jackson RB, Jalili A, Jansen S, Koike F, König C, Kraft N, Kramer K, Kreft H, Kühn I, Kurokawa H, Lamb EG, Laughlin DC, Leishman M, Lewis S, Louault F, Malhado ACM, Manning P, Meir P, Mencuccini M, Messier J, Miller R, Minden V, Molofsky J, Montgomery R, Montserrat-Martí G, Moretti M, Müller S, Niinemets Ü, Ogaya R, Öllerer K, Onipchenko V, Onoda Y, Ozinga WA, Pausas JG, Peco B, Penuelas J, Pillar VD, Pladevall C, Römermann C, Sack L, Salinas N, Sandel B, Sardans J, Schamp B, Scherer-Lorenzen M, Schulze E-D, Schweingruber F, Shiodera S, Sosinski Ê, Soudzilovskaia N, Spasojevic MJ, Swaine E, Swenson N, Tautenhahn S, Thompson K, Totte A, Urrutia-Jalabert R, Valladares F, van Bodegom P, Vasseur F, Verheyen K, Vile D, Violle C, von Holle B, Weigelt P, Weiher E, Wiemann MC, Williams M, Wright J, Zotz Get al., 2022, The global spectrum of plant form and function: enhanced species-level trait dataset, Scientific Data, Vol: 9, Pages: 1-18, ISSN: 2052-4463

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

Journal article

Fu Z, Ciais P, Feldman A, Gentine P, Makowski D, Prentice IC, Stoy PC, Bastos A, Wigneron J-Pet al., 2022, Critical soil moisture thresholds of plant water stress in terrestrial cosystems, Science Advances, Vol: 8, Pages: 1-12, ISSN: 2375-2548

Plant water stress occurs at the point when soil moisture (SM) limits transpiration, defining a critical SM threshold (θcrit). Knowledge of the spatial distribution of θcrit is crucial for future projections of climate and water resources. Here, we use global eddy-covariance observations to quantify θcrit and evaporative fraction (EF) regimes. Three canonical variables describe how EF is controlled by SM: the maximum EF (EFmax), θcrit, and slope (S) between EF and SM. We find systematic differences of these three variables across biomes. Variation in θcrit, S, and EFmax is mostly explained by soil texture, vapor pressure deficit and precipitation, respectively, as well as vegetation structure. Dryland ecosystems tend to operate at low θcrit and show adaptation to water deficits. The negative relationship between θcrit and S indicates that dryland ecosystems minimize θcrit through mechanisms of sustained SM extraction and transport by xylem. Our results further suggest an optimal adaptation of local EF–SM response, that maximizes growing-season evapotranspiration and photosynthesis.

Journal article

Dong N, Prentice IC, Wright IJ, Wang H, Atkins OK, Bloomfield KJ, Domingues TF, Gleason SM, Maire V, Onoda Y, Poorter H, Smith NGet al., 2022, Leaf nitrogen from the perspective of optimal plant function, Journal of Ecology, Vol: 110, Pages: 2585-2602, ISSN: 0022-0477

1. Leaf dry mass per unit area (LMA), carboxylation capacity (Vcmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and Vcmax at 25˚C (Vcmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.2. A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to Vcmax25 and LMA. Relationships of observed Vcmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.3. LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and V¬cmax25. These traits in turn were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean Vcmax25, 43% in LMA, and 31% in Narea. Predicted Vcmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils.4. Synthesis. Global patterns of variation in observed site-mean Narea can be explained by climate-induced variations in optimal Vcmax25¬ and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of Vcmax25 and LMA, both being optim

Journal article

Joshi J, Stocker B, Hofhansl F, Zhou S, Dieckmann U, Prentice ICet al., 2022, Towards a unified theory of plant photosynthesis and hydraulics, Nature Plants, Vol: 8, Pages: 1304-1316, ISSN: 2055-026X

The global carbon and water cycles are governed by the coupling of CO2 and water vapour exchanges through the leaves of terrestrial plants, controlled by plant 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 environments changing on multiple timescales. Tested with experimental data from 18 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. Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO2 on global photosynthesis and transpiration.

Journal article

Nobrega R, Prentice IC, 2022, Holistic analysis of the carbon and water cycles to quantify the human footprint in basin-wide hydrological processes in the Amazon

<jats:p>&amp;lt;p&amp;gt;While land-cover clearing (LCC) immediately reduces evapotranspiration (ET), its effects on other water fluxes, such as river discharge and terrestrial water storage, exhibit contrasting responses depending on location and scale. One explanation for this is that LCC triggers a series of asynchronous disruptions in the equilibrium of hydrological processes that was established upon the long-term balance with regional climatological, edaphic, and geological characteristics. Water fluxes under these circumstances are not well represented by hydrological models that have Budyko-like approaches or rely on the stationarity of the hydrological responses. The complexity of such analysis is incremented once LCC is followed by the conversion to pastures and crops established over random spatial and temporal patterns throughout river basins. Here, we propose an analysis of river discharge and root zone storage capacity (RZSC) to unveil underlying relationships between stream dynamics and water consumption by plants. We use a time-series segmentation and residual trend analysis on streamflow and precipitation of high-order tributaries of the Tapaj&amp;amp;#243;s River in the Amazon whose catchments underwent an intense land-use change over the past decades. We estimate the RZSC using the mass-curve balance method by considering the annual land-cover changes over a &amp;gt;30-year period. Despite the common belief that increases in river discharge are primarily caused by reduced ET when precipitation trends are not significant, we show that this might not be the main trigger of streamflow change in these major Amazon catchments. Instead, the reduction in the RZSC caused by changes in the water consumption by plants over the dry season is tightly associated with the increased baseflow contribution to rivers. Finally, we analysed gross primary productivity (GPP) and ET estimates generated by a model based on eco-evolutionary optimalit

Journal article

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