43 research outputs found
Species-specific, pan-European diameter increment models based on data of 2.3 million trees
ResearchBackground: Over the last decades, many forest simulators have been developed for the forests of individual
European countries. The underlying growth models are usually based on national datasets of varying size, obtained
from National Forest Inventories or from long-term research plots. Many of these models include country- and
location-specific predictors, such as site quality indices that may aggregate climate, soil properties and topography
effects. Consequently, it is not sensible to compare such models among countries, and it is often impossible to
apply models outside the region or country they were developed for. However, there is a clear need for more
generically applicable but still locally accurate and climate sensitive simulators at the European scale, which requires
the development of models that are applicable across the European continent. The purpose of this study is to
develop tree diameter increment models that are applicable at the European scale, but still locally accurate. We
compiled and used a dataset of diameter increment observations of over 2.3 million trees from 10 National Forest
Inventories in Europe and a set of 99 potential explanatory variables covering forest structure, weather, climate, soil
and nutrient deposition.
Results: Diameter increment models are presented for 20 species/species groups. Selection of explanatory variables
was done using a combination of forward and backward selection methods. The explained variance ranged from
10% to 53% depending on the species. Variables related to forest structure (basal area of the stand and relative size
of the tree) contributed most to the explained variance, but environmental variables were important to account for
spatial patterns. The type of environmental variables included differed greatly among species.
Conclusions: The presented diameter increment models are the first of their kind that are applicable at the
European scale. This is an important step towards the development of a new generation of forest development
simulators that can be applied at the European scale, but that are sensitive to variations in growing conditions and
applicable to a wider range of management systems than before. This allows European scale but detailed analyses
concerning topics like CO2 sequestration, wood mobilisation, long term impact of management, etcinfo:eu-repo/semantics/publishedVersio
Forest carbon sequestration:the impact of forest management
In this chapter, we describe alternative ways in which forests and forestry can help to mĂtigate climate change, along with the potential impact of these activities. The three carbon storage compartments should be considered inall impact estimates. Carbon content in living biomass is easily estimated via species-specific equations or by applying factors to oven-dry biomass weights (e.g.,lbañez et al.,2002, Herrero et al.,2011,Castaño and Bravo, 2012).Litter carbon content has been analysed in many studies on primary forest productivity, though
information regarding the influence of forest management on litter carbon content is less abundant (Blanco et al., 2006). In the last decade,efforts have been made to assess soil carbon in forests, but studies on the effect of forest management on soils show discrepancies (Lindner and Karjalainen,2007).Hoover (2011), for example,found no difference in forest floor carbon stocks among stands subjected to partial or complete harvest treatments in the United States.Instituto Universitario de GestiĂłn Forestal Sostenibl
A method for validating the accuracy of NMR protein structures
We present a method that measures the accuracy of NMR protein structures. It compares random coil index [RCI] against local rigidity predicted by mathematical rigidity theory, calculated from NMR structures [FIRST], using a correlation score (which assesses secondary structure), and an RMSD score (which measures overall rigidity). We test its performance using: structures refined in explicit solvent, which are much better than unrefined structures; decoy structures generated for 89 NMR structures; and conventional predictors of accuracy such as number of restraints per residue, restraint violations, energy of structure, ensemble RMSD, Ramachandran distribution, and clashscore. Restraint violations and RMSD are poor measures of accuracy. Comparisons of NMR to crystal structures show that secondary structure is equally accurate, but crystal structures are typically too rigid in loops, whereas NMR structures are typically too floppy overall. We show that the method is a useful addition to existing measures of accuracy