Biology subjects

Francois, C.

Publications and source records attributed to Francois, C..

4 recordsLinked to original sources

bioRxiv2022

Contribution of deep soil layers to the transpiration of a temperate deciduous forest: quantification and implications for the modelling of productivity

Climate change is imposing drier atmospheric and edaphic conditions on temperate forests. Here, we investigated how deep soil (down to 300 cm) water extraction contributed to the provision of water in the Fontainebleau-Barbeau temperate oak forest over two years, including the 2018 record drought. Deep water provision was key to sustain canopy transpiration during drought, with layers below 150 cm contributing up to 60% of the transpired water in August 2018, despite their very low density of fine roots. We further showed that soil databases used to parameterize ecosystem models largely underestimated the amount of water extractable from the soil by trees, due to a considerable underestimation of the tree rooting depth. The consensus database established for France gave an estimate of 207 mm for the soil water holding capacity (SWHC) at Fontainebleau-Barbeau, when our estimate based on the analysis of soil water content measurements was 1.9 times as high, reaching 390{+/-}17 mm. Running the CASTANEA forest model with the database-derived SWHC yielded a 350 gC m-2 y-1 average underestimation of annual gross primary productivity under current climate, reaching up to 700 gC m-2 y-1 under climate change scenario RCP8.5. It is likely that the strong underestimation of SWHC that we show at our site is not a special case, and concerns a large number of forest sites. Thus, we argue for a generalisation of deep soil water content measurements in forests, in order to improve the estimation of SWHC and the simulation of the forest carbon cycle in the current context of climate change. HighlightsO_LIForest-atmosphere carbon exchanges remained insensitive to record drought. C_LIO_LIDeep soil (150-300 cm) provisioned up to 60% of the water transpired by the forest during drought. C_LIO_LISoil databases were underestimating soil water holding capacity by a factor of two. C_LIO_LISimulated forest productivity is strongly sensitive to soil water holding capacity parameter. C_LIO_LIDeep soil water content measurements are urgently needed to correctly estimate the soil water holding capacity. C_LI

ecology↗

bioRxiv2021

Leaf area index estimation of even-aged oak (Quercus petraea) forests using in situ stand dendrometric parameters

The leaf area index (LAI) is a key characteristic of forest stand aboveground net productivity (ANP), and many methods have been developed to estimate the LAI. However, every method has flaws, e.g., methods may be destructive, require means or time and/or show intrinsic bias and estimation errors. A relationship using basal area (G) and stand age to estimate LAI was proposed by Sonohat et al. (2004). We used literature data in addition to data form measurements campaign made in the northern half of France to build a data set with large ranges of pedoclimatic conditions, stand age and measured LAI. We validated the Sonohat et al. (2004) relationship and attempted to improve or modify it using other stand/dendrometric characteristics that could be predictors of the LAI. The result is a series of three models using the G, age and/or quadratic mean diameter (Dg), and the models were able to estimate the LAI of an oak only even-aged forest stand with good confidence (root mean square error, RMSE < 0.75) While G is the main predictor here, age and Dg could be used conjointly or exclusively given the available data, with variable precision in the estimations. Although these models could not, by construction, relate to the interannual variability of the LAI, they may provide the theoretical LAI of an untouched forest (no meteorological, biotic or anthropogenic perturbation) in recent years. additionally, the use of this model may be more interesting than an LAI measurement campaign, depending on the means to be invested in such a campaign.

ecology↗

bioRxiv2021

" Idol with feet of clay ": reliable predictions of forest ecosystem functioning require flawless climate forcings.

Climate change affects various aspects of the functioning of ecosystem, especially photosynthesis, respiration and carbon storage. We need accurate modelling approaches (impact models) to simulate the functioning, vitality and provision of ecosystem services of forests in a warmer world. These impact models require climate data as forcings, which are often produced by climate models comparing more or less well with observational climate data. The bias percentage of the climate forcings propagates throughout the modeling chain from the climate model to the impact model. In this study, we aimed to quantify these bias percentage, addressing three questions: (1) Do the impact model predictions vary when forcing it with different climate models, and how do the predictions under climate model vs. observational climate forcing differ? (2) Does the variability in the impact climate simulations caused by climate forcings fade out at large spatial scale? (3) How the fact of using simulated climatic data affects the process-based model predictions in the case of stressful events? To answer these questions, we present results obtained over the historical period (e.g. 1970-2010) with the CASTANEA ecophysiological forest model and use the data from three climate models. Our analysis focuses on French forests, studying European beech (Fagus sylvatica), temperate deciduous oaks (Quercus robur and Q. petraea), Scots pine (Pinus sylvestris) and spruce (Picea abies) monospecific stands. We show that prediction of photosynthesis, respiration and wood growth highly depends on the climate model used, whether debiased or not, and also on species and region considered. Overall, we observed an improvement of prediction after a monthly mean bias or monthly quantile mapping correction for three model considered, but not with the same success. Then we highlighted a large variability in the processes simulated by the impact model under different climate forcings when considering the plot (i.e. scale of a few hectares) scale. This variability fades out at larger scale (e.g. the scale of an ecological region, i.e. 100 km2), owing to an aggregation effect. Moreover, process predictions obtained under different climate forcings are more variable during driest years. These results highlight the necessity to quantify bias and uncertainties in climate forcings before predicting fluxes dynamics with process-based model.

ecology↗

bioRxiv2020

Characterization and validation of 15 α-synuclein conformation-specific antibodies using well-characterized preparations of α-synuclein monomers, fibrils and oligomers with distinct structures and morphology: How specific are the conformation-specific α-synuclein antibodies?

Increasing evidence suggests that alpha-synuclein (-syn) oligomers are obligate intermediates in the pathway involved in -syn fibrillization and Lewy body (LB) formation, and may also accumulate within LBs in Parkinsons disease (PD) and other synucleinopathies. Therefore, the development of tools and methods to detect and quantify -syn oligomers has become increasingly crucial for mechanistic studies to understand the role of these oligomers in PD, and to develop new diagnostic methods and therapies for PD and other synucleinopathies. The majority of these tools and methods rely primarily on the use of aggregation state-specific or conformation-specific antibodies. Given the impact of the data and knowledge generated using these antibodies on shaping the foundation and directions of -syn and PD research, it is crucial that these antibodies are thoroughly characterized, and their specificity or ability to capture diverse -syn species is tested and validated. Herein, we describe an antibody characterization and validation pipeline that allows a systematic investigation of the specificity of -syn antibodies using well-defined and well-characterized preparations of various -syn species, including monomers, fibrils, and different oligomer preparations that are characterized by distinct morphological, chemical and secondary structure properties. This pipeline was used to characterize 18 -syn antibodies, 16 of which have been reported as conformation- or oligomer-specific antibodies, using an array of techniques, including immunoblot analysis (slot blot and Western blot), a digital ELISA assay using single molecule array technology and surface plasmon resonance. Our results show that i) none of the antibodies tested are specific for one particular type of -syn species, including monomers, oligomers or fibrils; ii) all antibodies that were reported to be oligomer-specific also recognized fibrillar -syn; and iii) a few antibodies showed high specificity for oligomers and fibrils but did not bind to monomers. These findings suggest that the great majority of -syn aggregate-specific antibodies do not differentiate between oligomers and fibrils, thus highlighting the importance of exercising caution when interpreting results obtained using these antibodies. Our results also underscore the critical importance of the characterization and validation of antibodies before their use in mechanistic studies and as diagnostic and therapeutic agents. This will not only improve the quality and reproducibility of research and reduce costs but will also reduce the number of therapeutic antibody failures in the clinic.

neuroscience↗