The identity of the fungi responsible for fruitlet core rot (FCR) disease in pineapple has been the subject of investigation for some time. This study describes the diversity and toxigenic potential of fungal species causing FCR in La Reunion, an island in the Indian Ocean. One-hundred-and-fifty fungal isolates were obtained from infected and healthy fruitlets on Reunion Island and exclusively correspond to two genera of fungi: Fusarium and Talaromyces. The genus Fusarium made up 79% of the isolates, including 108 F. ananatum, 10 F. oxysporum, and one F. proliferatum. The genus Talaromyces accounted for 21% of the isolated fungi, which were all Talaromyces stollii. As the isolated fungal strains are potentially mycotoxigenic, identification and quantification of mycotoxins were carried out on naturally or artificially infected diseased fruits and under in vitro cultures of potential toxigenic isolates. Fumonisins B1 and B2 (FB1-FB2) and beauvericin (BEA) were found in infected fruitlets of pineapple and in the culture media of Fusarium species. Regarding the induction of mycotoxin in vitro, F. proliferatum produced 182 mg kg⁻1 of FB1 and F. oxysporum produced 192 mg kg⁻1 of BEA. These results provide a better understanding of the causal agents of FCR and their potential risk to pineapple consumers.
We present and analyze a model aiming at recovering as dynamical outcomes of tree-grass interactions the wide range of vegetation physiognomies observable in the savanna biome along rainfall gradients at regional/continental scales. The model is based on two ordinary differential equations (ODE), for woody and grass biomass. It is parameterized from literature and retains mathematical tractability, since we restricted it to the main processes, notably tree-grass asymmetric interactions (either facilitative or competitive) and the grass-fire feedback. We used a fully qualitative analysis to derive all possible long term dynamics and express them in a bifurcation diagram in relation to mean annual rainfall and fire frequency. We delineated domains of monostability (forest, grassland, savanna), of bistability (e.g. forest-grassland or forest-savanna) and even tristability. Notably, we highlighted regions in which two savanna equilibria may be jointly stable (possibly in addition to forest or grassland). We verified that common knowledge about decreasing woody biomass with increasing fire frequency is recovered for all levels of rainfall, contrary to previous attempts using analogous ODE frameworks. Thus, this framework appears able to render more realistic and diversified outcomes than often thought of. Our model can help figure out the ongoing dynamics of savanna vegetation in large territories for which local data are sparse or absent. To explore the bifurcation diagram with different combinations of the model parameters, we have developed a user-friendly R-Shiny application freely available at : https://gitlab.com/cirad-apps/tree-grass.
Molecular tip-dating of phylogenetic trees is a growing discipline that uses DNA sequences sampled at different points in time to co-estimate the timing of evolutionary events with rates of molecular evolution. Such inferences should only be performed when there is sufficient temporal signal within the analysed dataset. Hence, it is important for researchers to be able to test their dataset for the amount and consistency of temporal signal prior to any tip-dating inference. For this purpose, the most popular method considered to-date has been the root-to-tip regression which consist in fitting a linear regression of the number of substitutions accumulated from the root to the tips of a phylogenetic tree as a function of sampling times. The main limitation of the regression method, in its current implementation, relies in the fact that the temporal signal can only be tested at the whole-tree evolutionary scale. To fill this methodological gap, we introduce phylostems, a new graphical and user-friendly tool developed to investigate temporal signal at every evolutionary scale of a phylogenetic tree. Phylostems allows detecting without a priori whether any subset of a tree would contain sufficient temporal signal for tip-based inference to be performed. We provide a how to guide by running phylostems on empirical datasets and supply guidance for results interpretation. Phylostems is freely available at https://pvbmt-apps.cirad.fr/apps/phylostems.
Intensive chayote cultivation in Réunion almost disappeared in the 2000s due to significant yield losses from fruit fly attacks on this historically important crop (Dacus ciliatus, Zeugodacus cuurbitae and Dacus demmerezi). Since the late 2000s, the adoption of agroecological crop protection practices have led to the effective management of fruit fly populations, a significant reduction in pesticide use, an increase in chayote production and plantations, and the development of organic production. To assist in fruit fly management, a qualitative model which simulates fruit fly damage to chayote crops, known as IPSIM-chayote, was developed, providing satisfactory prediction results. It has a user-friendly interface and is now available free of charge online, in three languages (French, English and Spanish): https://pvbmt-apps.cirad.fr/apps/ipsim-chayote/?lang=en. The IPSIM-chayote modeling platform can be used by farmers as a diagnosis to simulate fruit fly damage to their crops and as a decision-making tool for their agricultural practices. The model can be used as a training resource in agroecological crop protection. Public authorities and local government can use it as a tool in planning and forecasting agricultural development. Finally, researchers can use it as a prediction tool and a resource for the exchange of information, allowing them to review scientific knowledge or identify new, relevant research areas suited to the context and challenges. IPSIM-chayote can be considered as a forum for exchange and can stimulate collaborative work between individuals. It is a flexible model, as it allows variables to be added. IPSIM-chayote is the first qualitative model developed for crop pests in a tropical environment. It could serve as a basis for the development of other similar models simulating crop pest incidence, thus contributing significantly to the development of agroecological crop protection.
As impacts of introduced species cascade through trophic levels, they can cause indirect and counter-intuitive effects. To investigate the impact of invasive species at the network scale, we use a generalized food web model, capable of propagating changes through networks with a series of ecologically realistic criteria. Using data from a small British offshore island, we quantify the impacts of four virtual invasive species (an insectivore, a herbivore, a carnivore and an omnivore whose diet is based on a rat) and explore which clusters of species react in similar ways. We find that the predictions for the impacts of invasive species are ecologically plausible, even in large networks. Species in the same taxonomic group are similarly impacted by a virtual invasive species. However, interesting differences within a given taxonomic group can occur. The results suggest that some native species may be at risk from a wider range of invasives than previously believed. The implications of these results for ecologists and land managers are discussed.
Motivation Molecular tip-dating of phylogenetic trees is a growing discipline that uses DNA sequences sampled at different points in time to co-estimate the timing of evolutionary events with rates of molecular evolution. Importantly, such inferences should only be performed on datasets displaying sufficient temporal signal, a feature important to test prior to any tip-dating inference. For this purpose, the most popular method considered to-date has been the “root-to-tip regression” which consist in fitting a linear regression of the number of substitutions accumulated from the root to the tips of a phylogenetic tree as a function of sampling times. The main limitation of the regression method, in its current implementation, relies in the fact that the temporal signal can only be tested at the whole-tree scale (i.e. its root). Results To overcome this limitation we introduce Phylostems, a new graphical user-friendly tool developed to investigate temporal signal within every clade of a phylogenetic tree. We provide a “how to” guide by running Phylostems on an empirical dataset and supply guidance for results interpretation. Availability Phylostems is freely available at https://pvbmt-apps.cirad.fr/apps/phylostems.
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