Application of body size spectra to nematode trait-index analyses

Current trait-based indices of soil fauna for assessing soil quality rely on extensive knowledge of life history traits for hyper-diverse groups. We look at the effects of clear-cut forest harvesting and subsequent wood ash application on the free-living nematode community using trait-based indices and body size spectra. We test the hypothesis that body size is a unifying trait and that the body size spectra can be used to demonstrate changes in soil quality while overcoming taxonomic impediments. Undisturbed boreal forest floor soils were compared with clear-cut sites amended with zero, one-half calcium equivalent wood ash, equivalent calcium reintroduction, and twice calcium reintroduction. Total abundance, trait-based metrics for the Maturity Index, and two metrics of body size spectra were calculated. Nematode abundance was not a good indicator of soil disturbance, while traditional trait-based approaches (the summed Maturity Index) demonstrated predicted changes in community structure. Analysis of two types of body size spectra elucidated how the community had changed under disturbance, and revealed that smaller bodied organisms were lost under ash amended treatments compared to both clear-cut and undisturbed forest. Using the body size spectra for nematodes is a simple addition to current trait-based approaches that can supplement soil assessments for disturbance and quality without requiring taxonomic expertise.     

Transgressive variants for red pericarp grain with high yield potential derived from Oryza rufipogon × Oryza sativa: Field evaluation, screening for blast disease, QTL validation and background marker analysis for agronomic traits

Five transgressive variants (advanced breeding lines from BC₂F₅ and BC₂F₆ generation) were derived from a cross between the wild relative, O. rufipogon Griff. and O. sativa L. subsp. indica cv. MR219, a popular high yielding Malaysian rice cultivar. The aim of the study was to evaluate the pericarp colour of the grains along with yield potential and to validate quantitative trait loci (QTLs) for agronomic traits. The variants were screened against blast disease. Background marker analysis was also done for the promising variants. The field trials were carried out at a single location (due to containment purposes) over two seasons using randomized complete block design (RCBD) with three replications. A trait-based marker analysis was used to identify QTLs for validation in BC₂F₅ generation. Analysis of variance (ANOVA) showed that the seasonal factors influenced different agronomic traits. Variant G33 produced significantly (p < 0.05) higher yield (5.20 t/ha) than the control, MR219 (4.53 t/ha). Eighteen QTLs for different agronomic traits were identified in BC₂F₂ population in a previous study. Among them 14 QTLs were found in BC₂F₅ population of the present study. The yield of variant G33 was influenced by several QTLs viz. qGPL-1, qSPL-1-2, qSPL-8 and qYLD-4, which were introgressed from the donor parent revealed by background marker analysis using BC₂F₇ generation. Percentage (99%) of red pericarp grain of G33 and G34 in BC₂F₅ and BC₂F₆ generations indicated the stability of pericarp colour which was transferred from the wild relative. Variant G33 showed resistance against two pathotype of blast disease (Magnaporthe oryzae). Among the evaluated variants, G33 could be considered for inclusion in the cultivar development program for red rice with high yield potential and resistance to blast disease. This study demonstrated that the alleles from wild relative could improve the yield and yield related traits through allelic interaction, even though the phenotypic traits were inferior to the recurrent parent.     

A trait-based typification of urban forests as nature-based solutions

Urban forests as nature-based solutions (UF-NBS) are important tools for climate change adaptation and sustainable development. However, achieving both effective and sustainable UF-NBS solutions requires diverse knowledge. This includes knowledge on UF-NBS implementation, on the assessment of their environmental impacts in diverse spatial contexts, and on their management for the long-term safeguarding of delivered benefits. A successful integration of such bodies of knowledge demands a systematic understanding of UF-NBS. To achieve such an understanding, this paper presents a conceptual UF-NBS model obtained through a semantic, trait-based modelling approach. This conceptual model is subsequently implemented as an extendible, re-usable and interoperable ontology. In so doing, a formal, trait-based vocabulary on UF-NBS is created, that allows expressing spatial, morphological, physical, functional, and institutional UF-NBS properties for their typification and a subsequent integration of further knowledge and data. Thereby, ways forward are opened for a more systematic UF-NBS impact assessment, management, and decision-making.     

Agronomic performance of rice breeding lines selected based on plant traits or grain yield

Selection for yield per se has greatly contributed to yield improvement in many crops. It is expected that selection based on plant traits is more effective in increasing crop yield potential. This study was conducted to compare the effectiveness of trait-based and yield-based selection in increasing rice yield and to determine whether lines with ideotype traits have the potential to express higher yield under optimal crop management conditions. Lines were selected based on plant traits or on grain yield measured in a breeder's replicated yield trial. The main target traits for selection were plant height, leaf and panicle morphology, grain size, total dry weight, and grain-filling percentage. Yield performance of trait-based selection was compared with that of yield-based selection in an agronomic trial with optimum crop management for three seasons. Trait-based selection increased leaf area index and total dry weight but reduced spikelet number per m² and harvest index compared with yield-based selection. Consequently, selection based on plant traits did not increase grain yield compared with selection based on yield per se. In one of the three seasons, yield of trait-based selection was significantly lower than that of yield-based selection. Among all tested breeding lines, maximum yield was produced by yield-based selection and minimum yield came from trait-based selection. These results suggest that lines with ideotype traits did not express higher grain yield than lines selected based on yield per se under optimal crop management conditions, and yield-based selection was as effective in increasing rice grain yield as trait-based selection in the late generations of the breeding cycle.     

Understanding mechanisms of soil biota involvement in soil aggregation: A way forward with saprobic fungi?

Soil aggregation is a key ecosystem process that strongly affects soil structure. Soil structure is the three dimensional arrangement of primary particles, organic matter, soil aggregates and associated pores. As such, soil aggregation influences the organization of soil biodiversity and soil-borne biogeochemical processes. Saprobic fungi (SF) have promising but largely untapped potential to offer new perspectives and insights into mechanisms of soil aggregation. The study of SF permits identification of traits that may predict soil aggregation component processes: formation, stabilization and disintegration. The measurement of fungal key traits in experiments aimed at soil aggregation effects will generate data necessary for mechanistic understanding. When such efforts are combined with collecting such information across a range of systems in curated databases this can, by channeling efforts, lead to a step change in our understanding and modeling of organism-mediated soil aggregation mechanisms and changes in functional diversity due to global change.