Dataset Information

Links between plant litter chemistry, species diversity, and below-ground ecosystem function.

ABSTRACT: Decomposition is a critical source of plant nutrients, and drives the largest flux of terrestrial C to the atmosphere. Decomposing soil organic matter typically contains litter from multiple plant species, yet we lack a mechanistic understanding of how species diversity influences decomposition processes. Here, we show that soil C and N cycling during decomposition are controlled by the composition and diversity of chemical compounds within plant litter mixtures, rather than by simple metrics of plant species diversity. We amended native soils with litter mixtures containing up to 4 alpine plant species, and we used 9 litter chemical traits to evaluate the chemical composition (i.e., the identity and quantity of compounds) and chemical diversity of the litter mixtures. The chemical composition of the litter mixtures was the strongest predictor of soil respiration, net N mineralization, and microbial biomass N. Soil respiration and net N mineralization rates were also significantly correlated with the chemical diversity of the litter mixtures. In contrast, soil C and N cycling rates were poorly correlated with plant species richness, and there was no relationship between species richness and the chemical diversity of the litter mixtures. These results indicate that the composition and diversity of chemical compounds in litter are potentially important functional traits affecting decomposition, and simple metrics like plant species richness may fail to capture variation in these traits. Litter chemical traits therefore provide a mechanistic link between organisms, species diversity, and key components of below-ground ecosystem function.

SUBMITTER: Meier CL

PROVIDER: S-EPMC2604978 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Plant invasions have tremendous potential to alter food webs by changing basal resources. Recent studies document how plant invasions may contribute to increased arthropod abundances in detritus-based food webs. An obvious mechanism for this phenomenon-a bottom-up effect resulting from elevated levels of detritus from the invasive plant litter-has not been explicitly studied. We examined the effects of an annual grass invasion on ground arthropod assemblages in the coastal sage scrub (CSS) of southern California. Bottom-up food web theory predicts that the addition of detritus would increase generalist-feeding arthropods at all trophic levels; accordingly, we expected increases in fungi, Collembola, and common predators such as mites and spiders. For the common ant taxa, habitat alteration may also be important for predicting responses. Thus we expected that Forelius mccooki and Pheidole vistana, the most common ant species, would decline because of changes in soil temperature (F. mccooki) and habitat structure (P. vistana) associated with litter. We studied trends observationally and conducted a 3-year experiment in which we manipulated litter quantity. In contrast to other published studies, most detritus-based arthropod taxa declined in areas of high grass invasion, and, within trophic levels, responses often varied idiosyncratically. For the two most common taxa, a native ant (F. mccooki), and predatory mites in the Anystidae, we experimentally linked declines in abundance to increased levels of invasive grass litter. Such declines, especially those exhibited by the most common ant taxa, could have cascading effects on the CSS ecosystem, where ants are numerically dominant and thus may have broad influences on food web and ecosystem properties. Our results highlight that accurately predicting arthropod responses to invasive plant litter requires careful consideration of the structural and food resources provided by detritus to each particular food web.

Project description:Competitive interactions between plants can affect patterns of allocation to reproductive structures through modulation of resource availability. As floral traits involved in plant attractiveness to pollinators can be sensitive to these resources, competition with any neighbouring species may influence the attractiveness of insect-pollinated plants. While pollination research has primarily focused on above-ground interactions, this study aims at investigating if the presence of a competitor plant can modulate neighbouring insect-pollinated plant attractiveness to pollinators and resulting fecundity, especially through below-ground competitive interactions for soil resources. We set up a plot experiment in which we grew an insect-pollinated plant, Sinapis alba (Brassicaceae), in a mixture dominated by a wind-pollinated plant, Holcus lanatus (Poaceae). Individuals of S. alba were either subjected to or isolated from (with buried tubes in the soil) below-ground competition. Across the flowering season, floral traits involved in attractiveness of S. alba and pollinator visitation were followed at the plot and plant level to investigate different scales of attractiveness. At the end of the experiment, seeds were harvested to assess plant fecundity. Competition had a significant negative effect on plot and plant floral display size as well as flower size while nectar traits were not affected. When plants of S. alba were in competition, the time to first visit was altered: the proportion of plots that received a visit was smaller for a given time; in other words, it took more time for a given proportion of plots to be visited and some plots were even never visited. Moreover, pollinators made fewer visits per plots. The proportion of viable seeds produced by S. alba in competition was lower and probably linked to the competition itself rather than changes in pollinator visitation. This study suggests that competitive interactions between plants can modulate pollination interactions even when competing plant species are not insect-pollinated.

Dataset Information

Links between plant litter chemistry, species diversity, and below-ground ecosystem function.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets