Tritrophic interactions follow phylogenetic escalation and climatic adaptation

One major goal in plant evolutionary ecology is to address how and why tritrophic interactions mediated by phytochemical plant defences vary across species, space, and time. In this study, we tested three classical hypotheses about plant defences: (i) the resource-availability hypothesis, (ii) the altitudinal/elevational gradient hypothesis and (iii) the defence escalation hypothesis. For this purpose, predatory soil nematodes were challenged to hunt for root herbivores based on volatile cues from damaged or intact roots of 18 Alpine Festuca grass species adapted to distinct climatic niches spanning 2000 meters of elevation. We found that adaptation into harsh, nutrient-limited alpine environments coincided with the production of specific blends of volatiles, highly attractive for nematodes. We also found that recently-diverged taxa exposed to herbivores released higher amounts of volatiles than ancestrally-diverged species. Therefore, our model provides evidence that belowground indirect plant defences associated with tritrophic interactions have evolved under two classical hypotheses in plant ecology. While phylogenetic drivers of volatile emissions point to the defence-escalation hypothesis, plant local adaptation of indirect defences is in line with the resource availability hypothesis

Characterizing volatiles and attractiveness of five brassicaceous plants with potential for a 'push-pull' strategy toward the cabbage root fly, delia radicum

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Selecting volatiles to protect brassicaceous crops against the cabbage root fly, Delia radicum

Publication Inra prise en compte dans l'analyse bibliométrique des publications scientifiques mondiales sur les Fruits, les Légumes et la Pomme de terre. Période 2000-2012. http://prodinra.inra.fr/record/256699International audienceVolatiles resulting from plantherbivore interactions play an important role in the behavioral decisions of phytophagous, predatory, and parasitoid insects and could be used for managing pest insects. However, to date and after about 40 years of research, documented studies on applications in the field remain extremely scarce. Delia radicum L. (Diptera: Anthomyiidae), the cabbage root fly, is a major pest of brassicaceous crops for which classical control strategies are currently lacking. Our previous studies showed that dimethyl disulfide (DMDS), a compound emitted by roots heavily infested by D. radicum larvae, was attractive for the flys main natural enemies and could lead to a reduction of 60% in number of eggs laid on treated plants in the field. As a follow-up of this work, we conducted another field study to select additional volatiles that could be used in a pushpull approach. Several synthetic herbivore-induced plant volatiles, selected on the basis of their potential action on the behavior of both the fly and its natural enemies, were placed in odor dispensers in experimental broccoli plots and their influence on oviposition by D. radicum and egg predation by ground-dwelling predators was assessed. Our results confirmed the role of DMDS in reducing D. radicum egg numbers on broccoli plants and revealed that (Z)-3-hexenyl acetate, a green leaf volatile released by recently damaged plants, strongly stimulated fly oviposition. Also, two of the compounds tested slightly modified predation activity of ground-dwelling predators: acetophenone decreased the proportion of predated patches, whereas methyl salicylate increased it. This study is a first step in designing a pushpull strategy to control the cabbage root fly

A global database of soil nematode abundance and functional group composition

As the most abundant animals on earth, nematodes are a dominant component of the soil community. They play critical roles in regulating biogeochemical cycles and vegetation dynamics within and across landscapes and are an indicator of soil biological activity. Here, we present a comprehensive global dataset of soil nematode abundance and functional group composition. This dataset includes 6,825 georeferenced soil samples from all continents and biomes. For geospatial mapping purposes these samples are aggregated into 1,933 unique 1-km pixels, each of which is linked to 73 global environmental covariate data layers. Altogether, this dataset can help to gain insight into the spatial distribution patterns of soil nematode abundance and community composition, and the environmental drivers shaping these patterns.Peer reviewe

A global database of soil nematode abundance and functional group composition [Data paper]

Measurement(s)Abundance center dot Nematoda center dot environmental factorTechnology Type(s)Elutriative Centrifugation center dot computational modeling techniqueFactor Type(s)geographic locationSample Characteristic - OrganismNematodaSample Characteristic - Environmentsoil environment center dot climateSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11925843 As the most abundant animals on earth, nematodes are a dominant component of the soil community. They play critical roles in regulating biogeochemical cycles and vegetation dynamics within and across landscapes and are an indicator of soil biological activity. Here, we present a comprehensive global dataset of soil nematode abundance and functional group composition. This dataset includes 6,825 georeferenced soil samples from all continents and biomes. For geospatial mapping purposes these samples are aggregated into 1,933 unique 1-km pixels, each of which is linked to 73 global environmental covariate data layers. Altogether, this dataset can help to gain insight into the spatial distribution patterns of soil nematode abundance and community composition, and the environmental drivers shaping these patterns

A global database of soil nematode abundance and functional group composition

This study uses direct measurements of soil nematode abundance from 6,825 georeferenced locations around the world, covering all continents and all terrestrial biomes. We describe the data sources, methodology and data processing steps to transform the data into a version that can be used for, for example, geospatial modeling. To do so, the samples were aggregated to the 1-km2 pixel level, each pixel is linked to 73 global covariate layers. These include on soil physiochemical properties, and vegetation, climate, and topographic, anthropogenic, and spectral reflectance information