Storm disturbances in a Swedish forest—A case study comparing monitoring and modelling

The Effect of Nitrogen Fertilization on Tree Growth, Soil Organic Carbon and Nitrogen Leaching—A Modeling Study in a Steep Nitrogen Deposition Gradient in Sweden

Nitrogen (N) fertilization in forests has the potential to increase tree growth and carbon (C) sequestration, but it also means a risk of N leaching. Dynamic models can, if the important processes are well described, play an important role in assessing benefits and risks of nitrogen fertilization. The aim of this study was to test if the ForSAFE model is able to simulate correctly the effects of N fertilization when considering different levels of N availability in the forest. The model was applied for three sites in Sweden, representing low, medium and high nitrogen deposition. Simulations were performed for scenarios with and without fertilization. The effect of N fertilization on tree growth was largest at the low deposition site, whereas the effect on N leaching was more pronounced at the high deposition site. For soil organic carbon (SOC) the effects were generally small, but in the second forest rotation SOC was slightly higher after fertilization, especially at the low deposition site. The ForSAFE simulations largely confirm the N saturation theory which state that N will not be retained in the forest when the ecosystem is N saturated, and we conclude that the model can be a useful tool in assessing effects of N fertilization.

Responses of forest ecosystems in Europe to decreasing nitrogen deposition

Average nitrogen (N) deposition across Europe has declined since the 1990s. This resulted in decreased N inputs to forest ecosystems especially in Central and Western Europe where deposition levels are highest. While the impact of atmospheric N deposition on forests has been receiving much attention for decades, ecosystem responses to the decline in N inputs received less attention. Here, we review observational studies reporting on trends in a number of indicators: soil acidification and eutrophication, understory vegetation, tree nutrition (foliar element concentrations) as well as tree vitality and growth in response to decreasing N deposition across Europe. Ecosystem responses varied with limited decrease in soil solution nitrate concentrations and potentially also foliar N concentrations. There was no large-scale response in understory vegetation, tree growth, or vitality. Experimental studies support the observation of a more distinct reaction of soil solution and foliar element concentrations to changes in N supply compared to the three other parameters. According to the most likely scenarios, further decrease of N deposition will be limited. We hypothesize that this expected decline will not cause major responses of the parameters analysed in this study. Instead, future changes might be more strongly controlled by the development of N pools accumulated within forest soils, affected by climate change and forest management.

Spatial landscape model to characterize biological diversity using R statistical computing environment

Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output.