Absence of Gigasporales and rarity of spores in a hot desert revealed by a multimethod approach.

Hot deserts impose extreme conditions on plants growing in arid soils. Deserts are expanding due to climate change, thereby increasing the vulnerability of ecosystems and the need to preserve them. Arbuscular mycorrhizal fungi (AMF) improve plant fitness by enhancing plant water/nutrient uptake and stress tolerance. However, few studies have focused on AMF diversity and community composition in deserts, and the soil and land use parameters affecting them. This study aimed to comprehensively describe AMF ecological features in a 5,000 km2 arid hyperalkaline region in AlUla, Saudi Arabia. We used a multimethod approach to analyse over 1,000 soil and 300 plant root samples of various species encompassing agricultural, old agricultural, urban and natural ecosystems. Our method involved metabarcoding using 18S and ITS2 markers, histological techniques for direct AMF colonization observation and soil spore extraction and observation. Our findings revealed a predominance of AMF taxa assigned to Glomeraceae, regardless of the local conditions, and an almost complete absence of Gigasporales taxa. Land use had little effect on the AMF richness, diversity and community composition, while soil texture, pH and substantial unexplained stochastic variance drove these compositions in AlUla soils. Mycorrhization was frequently observed in the studied plant species, even in usually non-mycorrhizal plant taxa (e.g. Amaranthaceae, Urticaceae). Date palms and Citrus trees, representing two major crops in the region, however, displayed a very low mycorrhizal frequency and intensity. AlUla soils had a very low concentration of spores, which were mostly small. This study generated new insight on AMF and specific behavioral features of these fungi in arid environments.

Testing Differences Between Pathogen Compositions with Small Samples and Sparse Data.

The structure of pathogen populations is an important driver of epidemics affecting crops and natural plant communities. Comparing the composition of two pathogen populations consisting of assemblages of genotypes or phenotypes is a crucial, recurrent question encountered in many studies in plant disease epidemiology. Determining whether there is a significant difference between two sets of proportions is also a generic question for numerous biological fields. When samples are small and data are sparse, it is not straightforward to provide an accurate answer to this simple question because routine statistical tests may not be exactly calibrated. To tackle this issue, we built a computationally intensive testing procedure, the generalized Monte Carlo plug-in test with calibration test, which is implemented in an R package available at https://doi.org/10.5281/zenodo.635791 . A simulation study was carried out to assess the performance of the proposed methodology and to make a comparison with standard statistical tests. This study allows us to give advice on how to apply the proposed method, depending on the sample sizes. The proposed methodology was then applied to real datasets and the results of the analyses were discussed from an epidemiological perspective. The applications to real data sets deal with three topics in plant pathology: the reproduction of Magnaporthe oryzae, the spatial structure of Pseudomonas syringae, and the temporal recurrence of Puccinia triticina.