Linking floral biodiversity with nitrogen and carbon translocations in semi-natural grasslands in Lithuania

© 2015 The Authors. Published by Walter de Gruyter/Sciendo. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1515/eko-2015-0014The aim of the present study is to evaluate the long-term effects of long-term piggery effluent application on semi-natural grassland ecotop-phytotop changes (above- and below-ground phytomass production, and carbon and nitrogen allocation in grassland communities) in relation to changes (or variability) in topsoil properties. Analysis of phytomass distribution in piggery effluent irrigated grassland communities showed that dry biomass yield varied from 1.7-5.3 t ha-1. Variability in soil and plant cover created a unique and highly unpredictable site specific system, where long-term anthropogenic influences established successor communities with specific characteristics of above- and below-ground biomass distribution. These characteristics depend more on grassland communities than on soil chemical properties. Families of grasses (Poaceae) dominated the surveyed communities and accumulated most carbon and least nitrogen, while legumes accumulated most nitrogen and lignin and least carbon. Carbon concentrations in above-ground biomass had minor variations, while accumulation of nitrogen was strongly influenced by species diversity (r = 0.94, n = 10, p <0.001) and production of above-ground biomass.Published versio

Interdisciplinary analysis of soil acidification hazard and its legacy effects in Lithuania

An analysis of factors influencing effective soil acidification management is reported. This analysis was conducted simultaneously at both national and local levels. These investigations were accomplished in three stages: (i) validation of acid soil spatial patterns using systems analysis and geoinformation methods; (ii) spatial statistical analysis of soil pH diversity using a statistical grid method; and (iii) development of the concept of soil acidity management. Results indicate the national spatial distribution of topsoil reaction is a natural and stable phenomenon related to Quaternary sub-surface deposits. However, secondary effects of topsoil liming are evident in both spatial and temporal soil reaction patterns

A multi-model comparison of soil carbon assessment of a coniferous forest stand

We simulated soil carbon stock dynamics of an Austrian coniferous forest stand with five soil-only models (Q, ROMUL, RothC, SoilCO2/RothC and Yasso07) and three plant soil models (CENTURY, Coup-Model and Forest-DNDC) for an 18-year period and the decomposition of a litter pulse over a 100-year period. The objectives of the study were to assess the consistency in soil carbon estimates applying a multi-model comparison and to present and discuss the sources of uncertainties that create the differences in model results. Additionally, we discuss the applicability of different modelling approaches from the view point of large-scale carbon assessments.Our simulation results showed a wide range in soil carbon stocks and stock change estimates reflecting substantial uncertainties in model estimates. The measured stock change estimate decreased much more than the model predictions. Model results varied not only due to the model structure and applied parameters, but also due to different input information and assumptions applied during the modelling processes. Initialization procedures applied with the models induced large differences among the modelled soil carbon stocks and stock change estimates. Decomposition estimates of the litter pulse driven by model structures and parameters also varied considerably.Our results support the use of relatively simple soil-only models with low data requirements in inventory type of large-scale carbon assessments. It is important that the modelling processes within the national inventories are transparently reported and special emphasis is put on how the models are used, which assumptions are applied and what is the quality of data used both as input and to calibrate the models. (C) 2012 Elsevier Ltd. All rights reserved