Biome-specific effects of nitrogen and phosphorus on the photosynthetic characteristics of trees at a forest-savanna boundary in Cameroon

Journal ArticleThe final publication is available at Springer via http://dx.doi.org/10.1007/s00442-015-3250-5Photosynthesis/nutrient relationships of proximally growing forest and savanna trees were determined in an ecotonal region of Cameroon (Africa). Although area-based foliar N concentrations were typically lower for savanna trees, there was no difference in photosynthetic rates between the two vegetation formation types. Opposite to N, area-based P concentrations were—on average—slightly lower for forest trees; a dependency of photosynthetic characteristics on foliar P was only evident for savanna trees. Thus savanna trees use N more efficiently than their forest counterparts, but only in the presence of relatively high foliar P. Along with some other recent studies, these results suggest that both N and P are important modulators of woody tropical plant photosynthetic capacities, influencing photosynthetic metabolism in different ways that are also biome specific. Attempts to find simple unifying equations to describe woody tropical vegetation photosynthesis-nutrient relationships are likely to meet with failure, with ecophysiological distinctions between forest and savanna requiring acknowledgement.Natural Environment Research Council (NERC) TROBIT consortiumRoyal Society - University Research Fellowshi

The response of carbon assimilation and storage to long‐term drought in tropical trees is dependent on light availability

Whether tropical trees acclimate to long‐term drought stress remains unclear. This uncertainty is amplified if drought stress is accompanied by changes in other drivers such as the increases in canopy light exposure that might be induced by tree mortality or other disturbances. Photosynthetic capacity, leaf respiration, non‐structural carbohydrate (NSC) storage and stomatal conductance were measured on 162 trees at the world's longest running (15 years) tropical forest drought experiment. We test whether surviving trees have altered strategies for carbon storage and carbon use in the drier and elevated light conditions present following drought‐related tree mortality. Relative to control trees, the surviving trees experiencing the drought treatment showed functional responses including: (a) moderately reduced photosynthetic capacity; (b) increased total leaf NSC; and (c) a switch from starch to soluble sugars as the main store of branch NSC. This contrasts with earlier findings at this experiment of no change in photosynthetic capacity or NSC storage. The changes detected here only occurred in the subset of drought‐stressed trees with canopies exposed to high radiation and were absent in trees with less‐exposed canopies and also in the community average. In contrast to previous results acquired through less intensive species sampling from this experiment, we also observe no species‐average drought‐induced change in leaf respiration. Our results suggest that long‐term responses to drought stress are strongly influenced by a tree's full‐canopy light environment and therefore that disturbance‐induced changes in stand density and dynamics are likely to substantially impact tropical forest responses to climate change. We also demonstrate that, while challenging, intensive sampling is essential in tropical forests to avoid sampling biases caused by limited taxonomic coverage.Publicado online em 29 set. 2020

Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees?

Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from −0.003 to −0.065 μmol CO2 m−2 s−1 day−1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax). Estimating this parameter using A–Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat) measurements, from which Vcmax can be extracted using a 'one-point method'.\ud \ud We used a global dataset of A–Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'.\ud \ud If leaf respiration during the day (Rday) is known exactly, Vcmax can be estimated with an r2 value of 0.98 and a root-mean-squared error (RMSE) of 8.19 μmol m−2 s−1. However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r2 of 0.95 and an RMSE of 17.1 μmol m−2 s−1.\ud \ud The one-point method provides a robust means to expand current databases of field-measured Vcmax, giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation

Multiscale phenology of seasonally dry tropical forests in an aridity gradient

The leaf phenology of seasonally dry tropical forests (SDTFs) is highly seasonal, marked by synchronized flushing of new leaves triggered by the first rains of the wet season. Such phenological transitions may not be accurately detected by remote sensing vegetation indices and derived transition dates (TDs) due to the coarse spatial and temporal resolutions of satellite data. The aim of this study was to compared TDs from PhenoCams and satellite remote sensing (RS) and used the TDs calculated from PhenoCams to select the best thresholds for RS time series and calculate TDs. For this purpose, we assembled cameras in seven sites along an aridity gradient in the Brazilian Caatinga, a region dominated by SDTFs. The leafing patterns were registered during one to three growing seasons from 2017 to 2020. We drew a region of interest (ROI) in the images to calculate the normalized green chromatic coordinate index. We compared the camera data with the NDVI time series (2000–2019) derived from near-infrared (NIR) and red bands from MODIS product data. Using calibrated PhenoCam thresholds reduced the mean absolute error by 5 days for SOS and 34 days for EOS, compared to common thresholds in land surface phenology studies. On average, growing season length (LOS) did not differ significantly among vegetation types, but the driest sites showed the highest interannual variation. This pattern was applied to leaf flushing (SOS) and leaf fall (EOS) as well. We found a positive relationship between the accumulated precipitation and the LOS and between the accumulated precipitation and maximum and minimum temperatures and the vegetation productivity (peak and accumulated NDVI). Our results demonstrated that (A) the fine temporal resolution of phenocamera phenology time series improved the definitions of TDs and thresholds for RS landscape phenology; (b) long-term RS greening responded to the variability in rainfall, adjusting their timing of green-up and green-down, and (C) the amount of rainfall, although not determinant for the length of the growing season, is related to the estimates of vegetation productivity

Direct evidence for phosphorus limitation on Amazon forest productivity

The productivity of rainforests growing on highly weathered tropical soils is expected to be limited by phosphorus availability1. Yet, controlled fertilization experiments have been unable to demonstrate a dominant role for phosphorus in controlling tropical forest net primary productivity. Recent syntheses have demonstrated that responses to nitrogen addition are as large as to phosphorus2, and adaptations to low phosphorus availability appear to enable net primary productivity to be maintained across major soil phosphorus gradients3. Thus, the extent to which phosphorus availability limits tropical forest productivity is highly uncertain. The majority of the Amazonia, however, is characterized by soils that are more depleted in phosphorus than those in which most tropical fertilization experiments have taken place2. Thus, we established a phosphorus, nitrogen and base cation addition experiment in an old growth Amazon rainforest, with a low soil phosphorus content that is representative of approximately 60% of the Amazon basin. Here we show that net primary productivity increased exclusively with phosphorus addition. After 2 years, strong responses were observed in fine root (+29%) and canopy productivity (+19%), but not stem growth. The direct evidence of phosphorus limitation of net primary productivity suggests that phosphorus availability may restrict Amazon forest responses to CO2 fertilization4, with major implications for future carbon sequestration and forest resilience to climate change.The authors acknowledge funding from the UK Natural Environment Research Council (NERC), grant number NE/L007223/1. This is publication 850 in the technical series of the BDFFP. C.A.Q. acknowledges the grants from Brazilian National Council for Scientific and Technological Development (CNPq) CNPq/LBA 68/2013, CNPq/MCTI/FNDCT no. 18/2021 and his productivity grant. C.A.Q., H.F.V.C., F.D.S., I.A., L.F.L., E.O.M. and S.G. acknowledge the AmazonFACE programme for financial support in cooperation with Coordination for the Improvement of Higher Education Personnel (CAPES) and the National Institute of Amazonian Research as part of the grants CAPES-INPA/88887.154643/2017-00 and 88881.154644/2017-01. T.F.D. acknowledges funds from FundacAo de Amparo a Pesquisa do Estado de SAo Paulo (FAPESP), grant 2015/50488-5, and the Partnership for Enhanced Engagement in Research (PEER) programme grant AID-OAA-A-11-00012. L.E.O.C.A. thanks CNPq (314416/2020-0)

Mapping local and global variability in plant trait distributions

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration - specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways - without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R-2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra-and interspecific trait variation on ecosystem functioning.Peer reviewe