The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Sensitivity of South American tropical forests to an extreme climate anomaly

The tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha −1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected

Study of microbial interaction networks among heterotrophic bacteria from river waters

Bien qu'elles ne représentent qu'un faible volume dans l'hydrosphère, les rivières représentent une composante vitale de la vie sur Terre, car elles sont un habitat pour la flore et la faune ainsi qu'une ressource cruciale pour la vie et les activités humaines. De tous les milieux aquatiques, ce sont sans doute les plus exposés à la dégradation par l'apport massif de matière organique et de polluants chimiques. Dans ce contexte, les communautés bactériennes sont largement reconnues comme jouant un rôle clé dans « l'auto-épuration » des rivières par la minéralisation de la matière organique et la libération de carbone dans l'atmosphère. Bien qu'il existe une littérature abondante décrivant la composition de ces communautés et corrélant leur structure aux paramètres environnementaux, peu d'études visent à décrypter le fonctionnement interne du microbiome, c'est-à-dire les interactions entre les membres de la communauté. La compréhension des réseaux d'interaction des communautés lotiques est importante pour aider à la préservation des écosystèmes fluviaux. Nous avons contribué à cette ligne de recherche en étudiant les interactions au sein une communauté microbienne modèle simplifiée composée de bactéries hétérotrophes isolées de la rivière belge Zenne. Des travaux antérieurs menés au laboratoire ESA sur cette communauté ont montré qu'elle était capable d'utiliser plus de sources de carbone, et plus efficacement, que ses souches individuelles. D'autres expériences ont montré que le taux de croissance moyen des souches en communauté était plus élevé que dans la plupart des monocultures, ce qui suggère l'existence d'interactions positives au sein de cette communauté. Suite à ces travaux, nous avons voulu étudier les interactions se produisant dans un sous-ensemble de cette communauté originelle (réduite à 15 souches). Dans un premier temps, nous avons essayé de quantifier les interactions par paire au sein de la communauté, en suivant par spectrophotométrie la croissance des monocultures et bi-cultures correspondantes et en comparant leurs taux de croissance et leurs capacités portantes respectifs, afin de construire des matrices d'interaction. Ces matrices avaient en commun une majorité d'interactions négatives ainsi qu'un petit nombre d'interactions positives et de cas d'absence d'interactions, mais elles présentaient des différences entre les phases exponentielle et stationnaire de croissance, un résultat qui a été constaté à 20 °C ainsi qu'à des températures plus élevées et non contrôlées. Comme ces expériences n'ont pas permis de mesurer avec précision l'effet de chaque souche sur chacune des autres souches, nous avons étudié les interactions par paire dans un sous-ensemble de la communauté, réduite à 4 souches. En combinant le séquençage du gène de l'ARNr 16S et la cytométrie en flux, nous avons réussi à construire des matrices d'interaction statistiquement robustes qui ont également montré des différences entre les deux phases de croissance. En outre, nous avons constaté qu'une souche peu abondante pouvait grandement influencer la dynamique d'une souche dominante.making up only a small volume in the hydrosphere, rivers represent a vital component for life on Earth by constituting a habitat for the flora and fauna, as well as a crucial resource for human life and activities. Of all aquatic environments, they are undoubtably the most exposed to degradation by massive input of organic matter and chemical pollutants. In that context, bacterial communities are widely recognized as playing a key role in the “self-purification” of rivers by mineralizing organic matter and releasing carbon into the atmosphere. Although there is substantial literature describing the composition of these communities and correlating their structure to environmental parameters, not many studies aim to decipher the internal functioning of the microbiome, that is, the interactions between community members. The comprehension of the interaction networks of riverine communities is important to help preserving riverine ecosystems. We contributed to this line of investigation by studying the interactions in a simplified model microbial community composed of heterotrophic bacteria isolated from the Belgian river Zenne. Previous work conducted at the ESA laboratory on this community showed that it was able to utilize more carbon sources, and more efficiently, than individual strains. Further experiments showed that the average growth rate of strains in the community was higher than in most monocultures, suggesting the existence of positive interactions within the community. Following this work, we aimed to study the interactions occurring in a subset of this original community (reduced to 15 strains). In a first instance, we tried to decipher the pairwise interactions within the community by following the growth of mono- and corresponding bi-cultures using spectrophotometry and compared their respective growth rates and carrying capacities to build interaction matrices. These matrices had in common a majority of negative interactions as well as a small number of positive interactions and cases of no interactions, but they displayed differences between the exponential and stationary phases of growth, a result that was found at 20 °C as well as at higher, uncontrolled temperature. As these experiments did not allow an accurate measurement of the effect of each strain on each other strain, we further investigated pair-wise interactions in a subset of the community (reduced to 4 strains). By combining 16S rRNA gene sequencing and flow cytometry, we managed to build statistically robust interaction matrices that also showed differences between the two growth phases. In addition, we detected that a strain with low abundance could greatly influence the dynamics of a dominant one.Doctorat en Sciences agronomiques et ingénierie biologiqueinfo:eu-repo/semantics/nonPublishe

The dynamic of a river model bacterial community in two different media reveals a divergent succession and an enhanced growth of most strains compared to monocultures

The dynamic of a community of 20 bacterial strains isolated from river water was followed in R2 broth and in autoclaved river water medium for 27 days in batch experiments. At an early stage of incubation, a fast-growing specialist strain, Acinetobater sp. dominated the community in both media. Later on, the community composition in both media diverged but was highly reproducible across replicates. In R2, several strains previously reported to degrade multiple simple carbon sources prevailed. In autoclaved river water, the community was more even and became dominated by several strains growing faster or exclusively in that medium. Those strains have been reported in the literature to degrade complex compounds. Their growth rate in the community was 1.5- to 7-fold greater than that observed in monoculture. Furthermore, those strains developed simultaneously in the community. Together, our results suggest the existence of cooperative interactions within the community incubated in autoclaved river water.info:eu-repo/semantics/publishe

First insight of microbial interactions between heterotrophic bacteria from river water

info:eu-repo/semantics/publishe

Deciphering Interactions Within a 4-Strain Riverine Bacterial Community.

The dynamics of a community of four planktonic bacterial strains isolated from river water was followed in R2 broth for 72 h in batch experiments. These strains were identified as Janthinobacterium sp. Brevundimonas sp. Flavobacterium sp. and Variovorax sp. 16S rRNA gene sequencing and flow cytometry analyses were combined to monitor the change in abundance of each individual strain in bi-cultures and quadri-culture. Two interaction networks were constructed that summarize the impact of the strains on each other's growth rate in exponential phase and carrying capacity in stationary phase. The networks agree on the absence of positive interactions but also show differences, implying that ecological interactions can be specific to particular growth phases. Janthinobacterium sp. was the fastest growing strain and dominated the co-cultures. However, its growth rate was negatively affected by the presence of other strains 10 to 100 times less abundant than Janthinobacterium sp. In general, we saw a positive correlation between growth rate and carrying capacity in this system. In addition, growth rate in monoculture was predictive of carrying capacity in co-culture. Taken together, our results highlight the necessity to take growth phases into account when measuring interactions within a microbial community. In addition, evidence that a minor strain can greatly influence the dynamics of a dominant one underlines the necessity to choose population models that do not assume a linear dependency of interaction strength to abundance of other species for accurate parameterization from such empirical data.info:eu-repo/semantics/publishe

CellScanner: supervised classification of microbial communities in flow cytometry data

info:eu-repo/semantics/nonPublishe

First insight of microbial interactions between heterotrophic bacteria from river water

info:eu-repo/semantics/publishe

Exploring the dynamics of a synthetic riverine bacterial community

info:eu-repo/semantics/nonPublishe