Seasonal Variation in the Capacity for Plant Trait Measures to Predict Grassland Carbon and Water Fluxes

There is a need for accurate predictions of ecosystem carbon (C) and water fluxes in field conditions. Previous research has shown that ecosystem properties can be predicted from community abundance-weighted means (CWM) of plant functional traits and measures of trait variability within a community (FDvar). The capacity for traits to predict carbon (C) and water fluxes, and the seasonal dependency of these trait-function relationships has not been fully explored. Here we measured daytime C and water fluxes over four seasons in grasslands of a range of successional ages in southern England. In a model selection procedure, we related these fluxes to environmental covariates and plant biomass measures before adding CWM and FDvar plant trait measures that were scaled up from measures of individual plants grown in greenhouse conditions. Models describing fluxes in periods of low biological activity contained few predictors, which were usually abiotic factors. In more biologically active periods, models contained more predictors, including plant trait measures. Field-based plant biomass measures were generally better predictors of fluxes than CWM and FDvar traits. However, when these measures were used in combination traits accounted for additional variation. Where traits were significant predictors their identity often reflected seasonal vegetation dynamics. These results suggest that database derived trait measures can improve the prediction of ecosystem C and water fluxes. Controlled studies and those involving more detailed flux measurements are required to validate and explore these findings, a worthwhile effort given the potential for using simple vegetation measures to help predict landscape-scale fluxes.

The two modes of an athlete: Dual-process theories in the field of sport

The goal of the present article is to introduce dual-process theories – in particular the default-interventionist model – as an overarching framework for attention-related research in sports. Dual-process theories propose that two different types of processing guide human behavior. Type 1 processing is independent of available working memory capacity (WMC), whereas Type 2 processing depends on available working memory capacity. We review the latest theoretical developments on dual-process theories and present evidence for the validity of dual-process theories from various domains. We demonstrate how existing sport psychology findings can be integrated within the dual-process framework. We illustrate how future sport psychology research might benefit from adopting the dual-process framework as a meta-theoretical framework by arguing that the complex interplay between Type 1 and Type 2 processing has to be taken into account in order to gain a more complete understanding of the dynamic nature of attentional processing during sport performance at varying levels of expertise. Finally, we demonstrate that sport psychology applications might benefit from the dual-process perspective as well: dual-process theories are able to predict which behaviors can be more successfully executed when relying on Type 1 processing and which behaviors benefit from Type 2 processing.