Aggregate Traits Research Articles

Leaf palatability and decomposability increase during a 200-year-old post-cultural woody succession in New Zealand

Question: How do aggregate trait values and functional diversity of leaf traits linked to palatability and decomposability change during a woody post-cultural succession spanning 200 years? Location: Coastal Marlborough, South Island, New Zealand. Methods: The biomass of all woody species was determined in 32 20-m × 20-m plots ranging from 10 to 200 years in time since last disturbance. Species abundances were combined with data on leaf nutrient, secondary metabolite and structural carbohydrate content to calculate biomass-weighted trait means (i.e. aggregate trait values) and functional diversity index values for each plot. Aggregate trait values and functional diversity were regressed on successional age and total live above-ground carbon content to examine functional shifts with succession and one consequence of succession – increasing above-ground carbon. Results: Almost all significant regressions between aggregate trait values and both successional age and above-ground carbon indicated a shift toward increased leaf palatability and decomposability during succession. The relationships were all non-linear, with aggregate trait value shifts occurring relatively early in the successional sequence. There was weak evidence for an increase in functional richness with succession, but this was a secondary effect relative to the shifts in aggregate trait values. Conclusions: These results are in direct contrast with studies of the early stages of herbaceous post-cultural successions from grasslands to shrublands, which have found a shift towards communities of decreasing palatability and decomposability, suggesting that functional shifts in woody succession may be fundamentally different.

Selection ratios on community aggregated traits estimate ecological filters imposed on species by sites

Variation in community structure is mediated by interactions between species traits and a site's environmental characteristics. Previously, data on community composition at sites has been employed to correlate trait and environmental variables (e.g., RLQ analysis) and to predict community-level expression of quantitative traits (i.e., community aggregated traits). Here, we demonstrate that the selection ratio, a method originating in animal resource selection studies, can estimate the ecological filters that site conditions impose on species traits by combining observed community aggregated traits with null models of species availability. This flexible, nonparametric approach expresses the filter at each site as a probability density function for the selection of individuals possessing a given trait value. By doing so, it generalizes the community aggregated trait concept to include categorical as well as continuous traits and allows for both intraspecific variation in trait expression and differences in species availability among sites. The resulting site-level filter functions can be related to environmental covariates by standard statistical approaches (e.g., regression). The method complements existing techniques for analyzing trait-environment interactions in community ecology.

Differential effects of functional traits on aboveground biomass in semi‐natural grasslands

Despite increasing evidence on the importance of species functional characteristics for ecosystem processes, two major hypotheses suggest different mechanisms: the ‘mass ratio hypothesis’ assumes that functional traits of the dominant species determine ecosystem processes, while the ‘complementarity hypothesis’ predicts that resource niches may be used more completely when a community is functionally more diverse. Here, we present a method which uses two different groups of biotic predictor variables being (1) abundance‐weighted mean (=aggregated) trait values and (2) functional trait diversity based on Rao's quadratic diversity (FDQ) to test the competing hypotheses on biodiversity–ecosystem functioning relationships after accounting for co‐varying abiotic factors. We applied this method to data recorded on biodiversity–biomass relationships and environmental variables in 35 semi‐natural temperate grasslands and used a literature‐based matrix of fourteen plant functional traits to assess the explanatory power of models including different sets of predictor variables. Aboveground community biomass did not correlate with species richness. Abiotic factors, in particular soil nitrogen concentration, explained about 50% of variability in aboveground biomass. The best model incorporating functional trait diversity explained only about 30%, while the best model based on aggregated trait values explained about 54% of variability in aboveground biomass. The inclusion of all predictor variable groups in a combined model increased the predictive power to about 75%. This model comprised soil nitrogen concentration as abiotic factor, aggregated traits being indicative for species competitive dominance (rooting depth, leaf distribution, specific leaf area, perennial life cycle) and functional trait diversity in vegetative plant height, leaf area and life cycle. Our study strongly suggests that abiotic factors, trait values of the dominant species and functional trait diversity in combination may best explain differences in aboveground community biomass in natural ecosystems and that their isolated consideration may be misleading.

New method for rapid assessment of the functional composition of herbaceous plant communities

Abstract We propose a rapid sampling method to assess the functional composition of herbaceous plant communities without prior knowledge of the floristic composition. To determine the community‐level value of traits (‘aggregated trait values’) for a plant community, a standardized population‐centred method exists, but requires substantial manpower and reliable botanical knowledge. We tested an alternative method, the trait transect, using four subalpine pastures in the Beaufortain region (Northern French Alps) selected along a fertility gradient. We applied both methods to measure five commonly used ‘soft traits’ known to be responsive to soil nutrient availability: plant vegetative and reproductive height, specific leaf area, leaf dry matter and nitrogen contents. We tested whether the variation of these traits along the gradient detected with the population‐centred method was also detected with the trait transect. Both methods detected expected trends in the traits in response to the fertility gradient. The trait transect method was as efficient as the population‐centred method and is recommended as an appropriate tool for monitoring ecosystem changes in response to environmental conditions and management, especially in species‐rich communities.

Options for genetic improvement of milk composition

Genetic improvement is constrained by the long-term and cumulate nature of genetic improvement, by the economic rewards for making genetic change and by the variances and covariances among traits of interest. Genetic change is cumulate, so that small annual changes make substantial differences over time. This cumulate nature of genetic improvement dictates the importance of identifying long-term goals driven by robust economic signals and then adhering to them. The economic rewards for genetic improvement will ultimately determine the uptake and therefore the success of any breeding program. In developed countries the value of milk can be divided between the weight of water, fat and protein produced. Water generally has a negative value due the cost of handling, removal and disposal. Fat and protein have varying values depending on the market, but both will always have underlying positive values. Genetic variances and covariances among the aggregate composition traits, water, fat and protein, are such that simultaneous increase in the yield of all three is considerably easier than improvement of just one, or improvement of one while decreasing others. Selection for simultaneous increase of fat and protein percentage will also be successful, but at the price of not increasing fat and protein yield nearly as rapidly as when selecting directly on yield traits. In virtually all developed countries, the optimum selection goal will be for some combination of increased fat and protein yield that may lead to a gradual increase in the protein to fat ratio. Genetic polymorphisms in several protein genes have been associated with yield and with milk processing properties, but are unlikely to play more than a minor role in overall selection. There is some evidence of genetic variation in milk fat composition, but the level of variation and economic incentives for change mean that selection for milk fat composition is not worthwhile. Thus, with the exception of very slow changes in the water to fat to protein yield ratio, genetic improvement does not seem a particularly suitable route for altering milk composition.

Quantitative genetic studies on wool yellowing in Corriedale sheep. 1. Wool yellowing susceptibility and wool production traits—genetic parameter estimates

The potential for the reduction of wool yellowing susceptibility (YPC) in Corriedale sheep via selection was examined. The heritabilities of YPC and greasy fleece weight (GFW) and clean fleece weight (CFW), yield percentage (Yield), mean fibre diameter (MFD), and subjective greasy wool colour assessment (Visual), and phenotypic and genetic correlations among these traits were estimated from records on 1492 progeny of 53 sires of a Corriedale flock by using restricted maximum likelihood procedures using an average information algorithm. The heritability of YPC was 0·27 ± 0·06. Genetic correlations between YPC and GFW, CFW, Yield, MFD, and Visual were 0·20 ± 0·14, 0·11 ± 0·14, –0·15 ± 0·13, 0·24 ± 0·14, and 0·95 ± 0·06, respectively. Phenotypic correlations were low between these traits and YPC. Visual had a heritability of 0·30 ± 0·06 and medium-high genetic correlations with all traits, except CFW. Heritability estimates of GFW, CFW, Yield, and MFD were 0·55 ± 0·07, 0·52 ± 0·07, 0·51 ± 0·07, and 0·52 ± 0·07, respectively. The expected correlated responses to selection against YPC are likely to cause reductions in CFW and MFD. Correlated responses from the reduction of Visual are predicted to be greater for all production traits than those from the reduction of YPC. Responses in YPC are predicted to be slightly higher when selection is on Visual (–0·21 score/year) than when selection is on YPC itself (–0·19 score/year). A selection index, including CFW, MFD, and YPC as aggregate breeding and breeding objective traits, calculated at I = +3·26CFW – 0·14MFD + 0·03YPC, predicted a YPC increase, worsening the problem.

Correlated Changes in Agronomic Traits from S1‐line Recurrent Selection for Cold Tolerance in Two Maize Populations1

Cold tolerance is an aggregate trait important to dependable stand establishment in many environments. Selection for improved cold tolerant maize (Zea mays L.) germplasm, however, must not deter improvement of traits that are important later in the growing season. Correlated changes in agronomic traits due to five cycles of S1‐line recurrent selection for cold tolerance were evaluated in two maize populations. Correlated changes in means were expressed in terms of changes in allelic frequency due to pleiotropy or linkage and drift. Selection was associated with correlated genetic changes (2Δpα) grain yield [0.22 Mg ha‐1 cycle‐1 when averaged over both BS13(SCT) and BSSS2(SCT)], grain moisture (‐0.3% cycle‐1), early stand count (0.7 plants plot‐1 cycle‐1), and final stand (387.4 plants ha‐1 cycle‐1). Root lodging resistance was increased 2.5% cycle‐1 in BS13(SCT) and decreased 2.0% cycle‐1 in BSSS2(SCT). Stalk lodging resistance decreased 0.40% cycle‐1 in BS13(SCT). The increased frequencies of pleiotropic or linked genes controlling grain yield and grain moisture were expressed at both early and normal planting dates. The correlated genetic changes in early stand count, final stand, and root and stalk lodging resistance were influenced by date of planting. Genetic drift (2Δp2d) was significant for grain yield (‐0.23 Mg ha‐1 cycle‐1). Genetic drift overwhelmed the increase in allelic frequency due to selection for grain yield; hence, the populations per se were unchanged. The data suggesthat selection for cold tolerance with larger effective population sizes may result in correlated improvements in yield of the populations per se.

A genetic study of biomass in Tribolium. I. Path coefficient analysis of base populations.

Biomass, an aggregate trait combining the metric trait 13-day larval weight with the reproductive fitness trait number of larvae per mating, was investigated in two unrelated base populations of Tribolium castaneum, black and pearl.The black population was characterized by smaller 13-day larvae, more larvae per mating due to a higher rate of fecundity, and a smaller biomass than was observed for the pearl population. Both genetic and phenotypic variances were higher in black than in pearl. Heritability estimates for larval weight approached 0.20 in both populations while those for the fitness traits were smaller and seldom exceeded 10%. Non-additive genetic effects as well as maternal influences were observed in both populations. Positive estimates for the genetic correlations between larval weight and number of larvae per mating were observed for both populations (0.47 for black and 0.17 for pearl).Path coefficient analyses revealed that larval number in both populations had greater genetic and phenotypic influences on biomass than did larval weight. In turn, egg number had a greater influence on number of larvae than did larval viability.