Local diversity of native arbuscular mycorrhizal symbionts differentially affects growth and nutrition of three crop plant species

Intact whole native AMF communities occurring across a 100-m-long field were used for the evaluation of plant performance, as determined by the actual fungal species colonizing host roots. The soil from distinct plots within a “hot spot” field was collected to set up 54 experimental units where three different plant species were grown, in order to test whether the whole native AMF communities were able to differentially affect plant growth, to assess the genetic identity of the AMF actually colonizing the tested plants and to analyse their community composition in the different hosts. Molecular analyses revealed that plant growth and nutrition of the crop plants were differentially affected by the diverse native arbuscular mycorrhizal communities colonizing the roots of the three plants, whose performance varied depending on the identity of plant hosts and fungal symbionts, more than on a rich and diversified AMF community. Such results, improving our understanding of AMF distribution at the local scale, represent a starting point allowing the selection, isolation and characterization of the most efficient AMF assemblages to be used as inoculants in sustainable food production systems.     

Quantifying the effects of soil and climate on aboveground biomass production of <Emphasis Type="Italic">Salix miyabeana</Emphasis> SX67 in Quebec

Soil and climatic conditions for optimizing aboveground biomass yields of bioenergy short rotation coppices (SRCs) of Salix are not well elucidated. The objective of this study was to identify and quantify the limitations induced by soil and climate, and compare the magnitude of their effects, on annual aboveground yields across ten SRCs of Salix miyabeana SX67 in Quebec, Canada. The effects of weather variation between years on yields were also tested within locations. In five plots per SRC, soil bulk density, particle size, exchangeable cations and bulk composition were analysed, and moisture deficits were estimated using leaf δ¹³C. For each location, numerous weather variables were simulated for spring, summer and the whole growing season. Climate was calculated by averaging weather variables for growing seasons for which annual yields were available. Annual aboveground biomass yields were modelled using linear regression, partitioning of the variance and mixed models with soil, weather and climate variables as predictors. Across SRCs, silt content, soil organic matter, pH, exchangeable Ca and Mg, and total N and Zn were significantly and positively related to aboveground yields (adj. R ² ranging from 0.38 to 0.79). Generally, annual yields were negatively related to summer temperature within SRCs (adj. R ² = 0.92) and drought across SRCs (adj. R ² = 0.54). Partitioning of the variance revealed that soil variables (~80%) had a greater effect on productivity than did climate variables (~10%). In fact, soil properties buffered or exacerbated water shortages and, thus, had a preponderant effect on yield.     

Additions of landscape metrics improve predictions of occurrence of species distribution models

Species distribution models are used to aid our understanding of the processes driving the spatial patterns of species’ habitats. This approach has received criticism, however, largely because it neglects landscape metrics. We examined the relative impacts of landscape predictors on the accuracy of habitat models by constructing distribution models at regional scales incorporating environmental variables (climate, topography, vegetation, and soil types) and secondary species occurrence data, and using them to predict the occurrence of 36 species in 15 forest fragments where we conducted rapid surveys. We then selected six landscape predictors at the landscape scale and ran general linear models of species presence/absence with either a single scale predictor (the probabilities of occurrence of the distribution models or landscape variables) or multiple scale predictors (distribution models + one landscape variable). Our results indicated that distribution models alone had poor predictive abilities but were improved when landscape predictors were added; the species responses were not, however, similar to the multiple scale predictors. Our study thus highlights the importance of considering landscape metrics to generate more accurate habitat suitability models.     

The effect of resident vegetation cover on abundance and diversity of green lacewings (Neuroptera: Chrysopidae) on olive trees

Understorey habitats are optimal ecological structures for natural enemy enhancement in fruit orchards. A large-scale experiment was carried out to establish the effect of resident vegetation cover (VC) on green lacewings as compared to bare soil, the dominant soil management strategy used in Spanish olive orchards. Lacewings were sampled using baited McPhail traps for adults, and suction was used to collect adults and larvae from olive canopies. Additionally, we monitored the presence of the lacewing’s main target pest, olive moth eggs, as well as VC composition and density. McPhail trapping showed higher Chrysopidae abundances in VC plots during two consecutive years even though flowering plants represented 29.7 % of the total. Multivariate analysis identified Chrysoperla carnea s.l. and Pseudomallada prasinus as contributing to differences in abundance. VC slightly increased capture diversity; however, no specific link between any Chrysopidae species and VC was detected. No differences were observed in individuals collected through suction in 2009, which could be attributed to low sampling efficiency. In 2010, when sampling was increased considerably, higher adult and larval abundances were recorded in VC only with respect to C. carnea s.l. A delay was detected between McPhail captures and suction collection peaks. The fact that VC promoted higher abundance detected earlier through trapping, and later on olive canopies through suction, coinciding with P. oleae presence, suggests that resident VC may contribute to a build-up of green lacewing populations moving onto the crop at the time of the pest attack.     

Genetic diversity patterns in ex situ collections of <Emphasis Type="Italic">Oryza officinalis</Emphasis> Wall. ex G. Watt revealed by morphological and microsatellite markers

This study was conducted to understand variation patterns and establish the population structure in the wild rice species, Oryza officinalis, using accessions collected across the 11 regions/areas of endemism in Asia and Oceania and conserved ex situ in the International Rice Genebank at the International Rice Research Institute. Morphological and microsatellite data detected a tendency for latitudinal divergence in O. officinalis and divided the accessions into (1) Malesian and (2) South and East Asian populations. Cluster and ordination analyses of morphological characters revealed that accessions from Malesia (Regions 1–6), Vietnam (Region 7), and Central Thailand (Region 8) showed short (16.19 ± 3.70 cm) and slender (1.53 ± 2.06 cm) flag leaves that are erect to almost horizontal, short panicles (25.19 ± 3.02 cm) and mainly purple internodes; and (3) accessions from Northern Thailand and Myanmar (Region 9), India (Region 10) and China (Region 11) characterized by long (29.57 ± 4.94 cm) and broad (2.18 ± 3.33 cm) flag leaves that are horizontal to drooping, long panicles (35.26 ± 2.63 cm) and green internodes. With 79.3 % of the SSR markers being polymorphic, molecular analyses detected an average of 5.31 alleles per marker with a total of 154 alleles. Differentiation was evident among the regions with FST = 0.2173, although there is an apparent loss of heterozygosity across regions indicated by an over-all positive FIS. Based on the results, issues related to the management of O. officinalis, specifically filling gaps in the collection and the formulation of seed multiplication practices are addressed.