Biology subjects

Prentice, C.

Publications and source records attributed to Prentice, C..

7 recordsLinked to original sources

bioRxiv2026

Energy quality shapes biodiversity across coastal oceans

Earth's biodiversity is distributed unevenly, typically peaking in warm, vegetated, and stable environments. This has frequently been linked to energy availability, which boosts productivity, bolsters populations, and facilitates coexistence. Here, we examine the relationship between energy and biodiversity across coastal oceans using particulate organic matter biogeochemistry and environmental DNA. We reveal that energy quantity (concentrations of carbon, nitrogen, and hydrolyzable amino acids) and salinity, two variables that co-vary with freshwater inflow, jointly predict species richness at regional and global scales. Biodiversity was lowest at sites and locations with high energy inflow and low salinity, suggesting that environmental filtering associated with the osmotic stress induced by freshwater inflow outweighs raw resource availability in governing species richness. Independent of this gradient, however, energy quality (defined via C:N ratios, {delta}C values, and amino acid profiles) was associated with higher biodiversity. Labile, protein-rich, marine-derived resources supported higher biodiversity across all taxa at the regional scale, and a larger number of planktonic consumer taxa at both regional and global scales. High energy quality sites were also enriched in key planktonic groups such as calanoid and cyclopoid copepods, suggesting that these sites act as hotspots of planktonic biodiversity across coastal seascapes. Our findings suggest that few species can directly harness the plentiful resources provided by terrestrial subsidies in coastal oceans because they arrive in low salinity waters. In turn, high-quality food attracts a diverse range of consumers, which may seed the patchy foraging hotspots that characterize open-water food webs. Altered coastal hydrodynamics and biogeochemistry may therefore affect nearshore biodiversity, food webs, and fisheries.

ecology↗

bioRxiv2024

A general model for the seasonal to decadal dynamics of leaf area

Leaf phenology, represented at ecosystem scale by the seasonal dynamics of leaf area index (LAI), is a key control on the exchanges of CO2, energy and water between the land and atmosphere. Robust simulation of leaf phenology is thus important for both dynamic global vegetation models (DGVMs) and land-surface representations in climate and Earth System models. There is no general agreement on how leaf phenology should be modelled. However, a recent theoretical advance posits a universal relationship between the time course of "steady-state" gross primary production (GPP) and LAI - that is, the mutually consistent LAI and GPP that would pertain if weather conditions were held constant. This theory embodies the concept that leaves should be displayed when their presence is most beneficial to plants, combined with the reciprocal relationship of LAI and GPP via (a) the Beers law dependence of GPP on LAI, and (b) the requirement for GPP to support the allocation of carbon to leaves. Here we develop a global prognostic leaf phenology model, combining this theoretical approach with a parameter-sparse terrestrial GPP model (the P model) that achieves good fit to GPP derived from flux towers in all biomes, and a scheme based on the P model that predicts seasonal maximum LAI as the lesser of an energy-limited rate (maximizing GPP) and a water-limited rate (maximizing the use of available precipitation). The exponential moving average method is used to represent the time lag between leaf allocation and modelled steady-state LAI. The model captures satellite-derived LAI dynamics across biomes at both site and global levels. Since this model outperforms the 15 DGVMs used in the TRENDY project, it could provide a basis for improved representation of leaf-area dynamics in vegetation and climate models.

plant biology↗

bioRxiv2024

Thermal acclimation of stem respiration reduces global carbon burden

Stem respiration is a key driver of carbon flux from ecosystems to the atmosphere, yet its response to global warming remains poorly constrained. In particular it has been proposed that stem respiration acclimates to changing temperatures, which could have large implications for carbon cycling under climate change, but no theory exists to predict acclimated respiration rates. Here, we hypothesized that stem respiration is physiologically linked to transpiration in order to maintain hydraulic continuity. We then use that linkage, combined with Eco-evolutionary optimality theory, to develop a theoretical prediction of the temperature sensitivity of both acclimated and instantaneous stem respiration. Leveraging an extensive global dataset, we observe temperature sensitivities of stem respiration across geographical and seasonal variations that are consistent with this prediction. Our findings reveal that stem respiration contributes approximately a quarter of the global above-ground auto-trophic respiration, with an estimated annual emission of around 11.20 {+/-} 5.88 Pg C--comparable to total anthropogenic emissions. Importantly, incorporating thermal acclimation of stem respiration into projections significantly reduces predicted land ecosystem carbon emissions by 4.41 and 9.56 Pg C under the SSP126 and SSP585 scenarios, respectively, for the 21st century.

ecology↗

bioRxiv2023

Photosynthetic and water transport strategies of plants along a tropical forest aridity gradient: a test of optimality theory

(1) The research conducted, including the rationaleThe direct effect of aridity on photosynthetic and water-transport strategies is not easy to discern in global analyses because of large-scale correlations between precipitation and temperature. We analyze tree traits collected along an aridity gradient in Ghana, West Africa that shows little temperature variation, in an attempt to disentangle thermal and hydraulic influences on plant traits. (2) MethodsPredictions derived from optimality theory on the variation of key plant traits along the aridity gradient are tested with field measurements. (3) resultsMost photosynthetic traits show trends consistent with optimality-theory predictions, including higher photosynthetic capacity in the drier sites, and an association of higher photosynthetic capacity with greater respiration rates and greater water transport. Hydraulic traits show less consistency with theory or global-scale pattern, especially predictions based on xylem efficiency-safety tradeoff. Nonetheless, the link between photosynthesis and water transport still holds: species (predominantly deciduous species found in drier sites) with both higher sapwood-to-leaf area ratio (AS/AL) and potential hydraulic conductivity (Kp), implying higher transpiration, tend to have both higher photosynthetic capacity and lower leaf-internal CO2. (4) ConclusionsThese results indicate that aridity is an independent driver of spatial patterns of photosynthetic traits, while plants show a diversity of water-transport strategies along the aridity gradient. Plain language summaryAlong an aridity gradient in Ghana, West-Africa, we used optimality theory to explain that aridity is an important driver of photosynthetic traits, independent of temperature. Toward drier sites, plants have higher photosynthetic capacities per leaf area but have fewer leaves. We also explain how plants arrange water transportation to support quicker photosynthesis at drier sites. However, plants at the drier sites seem to have diverse combinations of hydraulic traits to satisfy the need for photosynthesis. We reported surprising data-theory inconsistency for some hydraulic traits along the aridity gradient where further research is needed.

ecology↗

bioRxiv2021

Land-surface evapotranspiration derived from a first-principles primary production model

We propose an application of eco-evolutionary optimality theory in the context of monitoring and modelling physical land-surface processes. Evapotranspiration (ET) links the water and carbon cycles in the atmosphere, hydrosphere, and biosphere. We develop an ET modelling framework based on the hypothesis that canopy conductance acclimates to plant growth conditions so that the total costs of maintaining carboxylation and transpiration capacities are minimized. This is combined with the principle of co-ordination between the light- and Rubisco-limited rates of photosynthesis to predict gross primary production (GPP). Transpiration (T) is predicted from GPP via canopy conductance. No plant type- or biome-specific parameters are required. ET is estimated from T by calibrating a site-specific (but time-invariant) ratio of modelled average T to observed average ET. Predicted seasonal cycles of GPP were well supported by (weekly) GPP data at 20 widely distributed eddy-covariance flux sites (228 site-years), with correlation coefficients (r) = 0.81 and root-mean-square error (RMSE) = 18.7 gC/week and Nash-Sutcliffe efficiency coefficient (NSE) = 0.61. Seasonal cycles of ET were also well supported, with r = 0.85, RMSE = 5.5 mm week-1 and NSE = 0.66. Estimated T/ET ratios (0.52-0.92) showed significant positive relationships to radiation, precipitation and green vegetation cover and negative relationships to temperature and modelled T (r = 0.84). Although there are still uncertainties to be improved in the current framework, particularly in estimating T/ET, we see the application of eco-evolutionary principles as a promising direction for water resources research. HighlightsO_LIBuilding an evapotranspiration estimation framework based on a priori primary productivity model (the P model). C_LIO_LIAssessing the contribution of environmental indicators to the ratio of transpiration to evapotranspiration. C_LIO_LIProving the reliability of this approach to estimate evapotranspiration. C_LI

ecology↗

bioRxiv2019

Th22 cells are a major contributor to the mycobacterial CD4+ T cell response and are depleted during HIV infection

HIV-1 infection substantially increases the risk of developing tuberculosis (TB). Some mechanisms, such as defects in the Th1 response to Mycobacterium tuberculosis (M.tb) in HIV-infected individuals have been widely reported. However, Th1-independent mechanisms also contribute to protection against TB. To identify a broader spectrum of defects in TB immunity during HIV infection, we examined IL-17 and IL-22 production in response to mycobacterial antigens in individuals with latent TB infection (LTBI) and HIV co-infection. Upon stimulating with mycobacterial antigens, we observed a distinct CD4+ T helper lineage producing IL-22 in the absence of IL-17 and IFN-{gamma}. Th22 cells were present at high frequencies in response to mycobacterial antigens in blood and contributed up to 50% to the CD4+ T cell response to mycobacteria, comparable in magnitude to the IFN-{gamma} Th1 response (median 0.91% and 0.55%, respectively). Phenotypic characterization of Th22 cells revealed that their memory differentiation was similar to M.tb-specific Th1 cells (i.e. predominantly early-differentiated CD45RO+CD27+ phenotype). Moreover, CCR6 and CXCR3 expression profiles of Th22 cells were similar to Th17 cells, while their CCR4 and CCR10 expression patterns displayed an intermediate phenotype between Th1 and Th17 cells. Strikingly, mycobacterial IL-22 responses were three-fold lower in HIV-infected individuals compared to uninfected individuals, and the magnitude of responses correlated inversely with HIV viral load. These data provide important insights into mycobacteria-specific T helper subsets and suggest a potential role for IL-22 in protection against TB during HIV infection. Further studies are needed to fully elucidate the role of IL-22 in protective TB immunity.

immunology↗

bioRxiv2018

Thermal acclimation of leaf respiration consistent with optimal plant function

Main Main References Introduction Terrestrial plant respiration is a major component of the global carbon cycle, releasing ca. 60 Pg C yr-1 to the atmosphere: six times more than anthropogenic CO2 emissions from all sources combined (Ciais et al. 2014). About half this flux is leaf maintenance respiration in darkness (Rd) (Atkin et al. 2007). Rd is highly temperature-dependent, following a near-exponential relationship over short time-scales (Heskel et al. 2016). It has been predicted that global warming will increase Rd and accelerate future climate change via a carbon-climate feedback (Cox et al. 2000; Huntingford et al. 2013). However, large uncertainties in future ...

ecology↗