Publications by authors named "Prentice I"

Plants acclimate to temperature by adjusting their photosynthetic capacity over weeks to months. However, most evidence for photosynthetic acclimation derives from leaf-scale experiments. Here we address the scarcity of evidence for canopy-scale photosynthetic acclimation by examining the correlation between maximum photosynthetic rates (A) and growth temperature ( ) across a range of concurrent temperatures and canopy foliage quantity, using data from >200 eddy covariance sites.

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Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we show possible reasons for this data-model mismatch.

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Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO and N input, alongside theoretical and ecological principles for modelling.

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  • * An extensive dataset for 16 different FTs is analyzed using advanced statistical methods to explore trait relationships among non-woody, woody deciduous, and woody evergreen plants.
  • * Key findings reveal that plant size traits generally increase in warmer climates, while leaf characteristics are influenced by moisture levels, providing a foundation for global trait-based ecosystem modeling.
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  • During dry periods, decreasing soil moisture leads to plant water stress, highlighting the need for better quantification of a critical soil moisture threshold (θ) to improve climate and resource projections.* -
  • By combining satellite data and ground observations, researchers created a global map of θ, finding it averages at 0.19 m/m, with variations based on ecosystem types.* -
  • The study identified key factors influencing θ, such as aridity, leaf area, and soil texture, and noted an increase in the number of stressful days for plants over the last 40 years, which has implications for understanding water stress in ecosystems.*
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  • - Tropical forests in equatorial Africa are crucial for the global carbon cycle, but there has been insufficient biometric data on their productivity levels (GPP and NPP).
  • - A study conducted on 14 one-hectare plots in West Africa revealed that these forests generally exhibit higher productivity and lower carbon use efficiency compared to a similar aridity gradient in the Amazon.
  • - The research highlighted that the highest reported NPP and GPP for intact forests occur at a medium-aridity site in Ghana, with findings indicating that existing data models underestimate forest productivity in both regions.
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  • Stomatal opening in leaves helps regulate carbon and water exchange, crucial for understanding plant responses to climate change.
  • New optimality-based models analyze stomatal behavior but often overlook how plants adjust biochemically to drought stress.
  • A study on 37 plant species shows that including photosynthetic acclimation in these models significantly improves predictions of carbon assimilation during drought conditions.
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Leaf dark respiration (R ) 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 R and Rubisco carboxylation capacity (V ) at 25°C (R , V ) are coordinated so that R variations support V at a level allowing full light use, with V reflecting daytime conditions (for photosynthesis), and R /V reflecting night-time conditions (for starch degradation and sucrose export).

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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.

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  • Leaf dry mass per unit area (LMA), carboxylation capacity, and leaf nitrogen are crucial traits for understanding plant ecology and ecosystem models, but there’s no clear agreement on how to regulate or model them.* -
  • This study confirmed that leaf nitrogen can be accurately predicted from LMA and carboxylation capacity at 25°C, with global variations in these traits linked to climate factors, as proposed by leaf-level optimality theory.* -
  • The research found that LMA is the strongest predictor of leaf nitrogen, explaining significant portions of global variation, while soil type affected predictions, suggesting that leaf nitrogen should be viewed as a result of environmental optimization rather than a cause.*
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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.

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  • The 'Global Spectrum of Plant Form and Function Dataset' includes mean values for six key vascular plant traits, essential for understanding plant variation.
  • This dataset aggregates around 1 million trait records from the TRY database and other sources, encompassing 92,159 species mean values across 46,047 species.
  • Comprehensive data quality management and validation ensure this is the largest and most reliable collection of empirical data on vascular plant traits available.
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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 C species; however, additional assumptions are required to "scale up" from leaf to canopy.

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Plant water stress occurs at the point when soil moisture (SM) limits transpiration, defining a critical SM threshold (θ). Knowledge of the spatial distribution of θ is crucial for future projections of climate and water resources. Here, we use global eddy covariance observations to quantify θ and evaporative fraction (EF) regimes.

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  • The global carbon and water cycles are influenced by gas exchanges through plant leaves, which are regulated by plants’ adaptations to optimize carbon gain while managing water risks.
  • A new trait-based optimality theory has been developed that connects plant responses and biochemical adjustments to rapidly changing environmental conditions.
  • This model, tested on 18 plant species, accurately predicts declines in carbon absorption and stomatal conductance during drought, while aligning with empirical data on how gas exchange is affected by factors like atmospheric pressure and temperature.
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"Least-cost theory" posits that C 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 CO drawdown (lower ratio of leaf internal to ambient CO , C :C ) during light-saturated photosynthesis, and at higher leaf N per area (N ) and higher carboxylation capacity (V ) for a given rate of stomatal conductance to water vapour, g .

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  • - Recent observations show mixed vegetation responses on the Tibetan Plateau, with drier areas experiencing greening and wetter regions facing browning, despite similar climatic trends from 1982 to 2016.
  • - A new model based on eco-evolutionary optimality (EEO) effectively explains these divergent trends by examining the limitations of water and energy, achieving a strong correlation with satellite data.
  • - The study suggests that while increased CO2 promotes plant growth, its effects on photosynthesis are diminishing, indicating a shift in vegetation sensitivity from water to energy limitations due to climate change.
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Aim: Biomisation 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.

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  • Leaf morphology shows distinct patterns related to climate, with key traits differing between wetter and drier environments, as well as between seasonal and non-seasonal climates.
  • A study analyzed 22 leaf traits from 662 woody species across China, uncovering significant trait variation driven by moisture, temperature, and plant family.
  • The research identified specific trait syndromes linked to climate types, highlighting contrasts such as microphyll leaves in moist regions versus smaller, glaucous leaves in arid areas.
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  • Nitrogen (N) limitation may restrict carbon uptake in plants, particularly with rising CO2 and climate change, highlighting concerns over declining carboxylation capacity and leaf N content.
  • Researchers predicted changes in leaf-level photosynthetic nitrogen (N) using satellite data from 1982-2016, finding that leaf N content declined at a similar rate to observed data, despite increasing leaf area index (LAI).
  • The study suggests that rising CO2 and temperature may actually reduce the overall N demand of canopies more than LAI increases it, offering a different perspective on declining leaf N that isn't solely based on increased N limitation.
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SignificanceThe magnitude of the CO fertilization effect on terrestrial photosynthesis is uncertain because it is not directly observed and is subject to confounding effects of climatic variability. We apply three well-established eco-evolutionary optimality theories of gas exchange and photosynthesis, constraining the main processes of CO fertilization using measurable variables. Using this framework, we provide robust observationally inferred evidence that a strong CO fertilization effect is detectable in globally distributed eddy covariance networks.

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Both 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.

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The global terrestrial carbon sink is increasing, offsetting roughly a third of anthropogenic CO released into the atmosphere each decade, and thus serving to slow the growth of atmospheric CO. It has been suggested that a CO-induced long-term increase in global photosynthesis, a process known as CO fertilization, is responsible for a large proportion of the current terrestrial carbon sink. The estimated magnitude of the historic increase in photosynthesis as result of increasing atmospheric CO concentrations, however, differs by an order of magnitude between long-term proxies and terrestrial biosphere models.

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  • - Understanding carbon isotope discrimination (Δ C) in woody plants is essential for studying photosynthesis, but its variation over decades and relationships with gross primary production (GPP) are not fully understood.
  • - A new modeling capability in the land-surface model JULES was implemented to analyze Δ C, revealing that most models overestimate average Δ C and underestimate variability due to neglecting the impact of soil water stress.
  • - The study found that Δ C trends vary significantly by region from 1979 to 2016 but remain constant globally, and correlations between Δ C and GPP differ across environments, with negative correlations in wet-humid regions due to temperature effects.
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