Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2007
Authors
Miguel D. Mahecha Markus Reichstein Holger Lange Nuño Carvalhais T. Grünwald Dario Papale G. SeufertAbstract
Characterizing ecosystem-atmosphere interactions in terms of carbon and water exchange on different time scales is considered a major challenge in terrestrial biogeochemical cycle research. The respective time series currently comprise an observation period of up to one decade. In this study, we explored whether the observation period is already sufficient to detect cross-relationships between the variables beyond the annual cycle, as they are expected from comparable studies in climatology. We investigated the potential of Singular System Analysis (SSA) to extract arbitrary kinds of oscillatory patterns. The method is completely data adaptive and performs an effective signal to noise separation. We found that most observations (Net Ecosystem Exchange, NEE, Gross Primary Productivity, GPP, Ecosystem Respiration, Reco, Vapor Pressure Deficit, VPD, Latent Heat, LE, Sensible Heat, H, Wind Speed, u, and Precipitation, P) were influenced significantly by low-frequency components (interannual variability). Furthermore, we extracted a set of nontrivial relationships and found clear seasonal hysteresis effects except for the interrelation of NEE with Global Radiation (Rg). SSA provides a new tool for the investigation of these phenomena explicitly on different time scales. Furthermore, we showed that SSA has great potential for eddy covariance data processing, since it can be applied as a novel gap filling approach relying on the temporal correlation structure of the time series structure only.
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No abstract has been registered
Abstract
Ecological studies are often confronted with short and fragmented or unevenly sampled time series. Examples are, e.g., time series of biogeochemical fluxes measured on a variety of scales. Characterizing the observed time series patterns, particularly the correlation structure is crucial for an integrated ecosystem assessment or possibly for improved processes understanding.
Authors
Holger LangeAbstract
The net ecosystem productivity (NEP) of a sequence of threemonoaged Norway spruce stands located in southeast Norway is modelled using the biogeochemical model Biome-BGC. For calibration, we use estimated biomass stocks at the plot level and Leaf Area Index measurements. The model is run for 30 years of historical temperature measurements as well as for a regional climate scenario. It is shown that under current conditions, NEP develops from negative values for a young stand (30 years) to clearly positive for a middleaged (60 years) to slightly negative again for a very old and decaying stand (120 years). However, the old stand benefits substantially from the predicted increased temperatures in the climate scenario, rendering NEP positive again. For the 30 and 60 years stands, almost no change is predicted from Biome-BGC.
Authors
Wim de Vries G.W.W. Wamelink Gert Jan Reinds H.J.J. Wieggers J.P. Mol-Dijkstra J. Kros Gert-Jan Nabuurs A. Pussinen Svein Solberg Matthias Dobbertin Daniel Laubhann Hubert Sterba M. van OijenAbstract
No abstract has been registered
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Abstract
Forest health monitoring may be done with remote sensing. Satellite based SAR is one promising technology as it works day and night and with cloud cover, and because it is sensitive to 3D properties. We here apply an interferometry based XDEM approach, where we assumed that an increasing defoliation would cause an increasing X band penetration downwards into the canopy layer, and that the penetration depth is a function of the amount of leaf area index (LAI) penetrated. We had at hand data for a 4 km2 forest area, having an SRTM X and C band SAR data set from 2000; a discrete-return laser scanning data set from 2003; and ground based measurements of some hundred trees and a forest stand map from 2003. We initially adjusted the XDEM and CDEM using elevation data from some agricultural fields nearby the forest using an official, Norwegian DTM data base having a 25mx25m spatial resolution. All further analyses were carried out on a 10mx10m grid. With the laser data we obtained a DTM and a canopy surface model (CSM), where the latter was set to the 75 percentile of the DZ data in each grid cell. The X band penetrated about six m downwards into the canopy layer, which means that for all grid cells having a forest canopy lower than six m, the XDEM was around zero. With an increasing DSM from six m upwards, the DSM could be approximated by the linear function DSM = 6 + 0.91*XDEM, having a RMSE of 4.0 m. The laser data provided the possibility to estimate LAI in every grid cell and at any height in that cell. For every grid cell, an LAI value was estimated for the forest canopy being above the XDEM height, using the method of Solberg et al (2006), where LAI = C * ln(N/Nb), where LAI is effective LAI above a given height; C is a constant calibrated from ground based measurements with the value 2.0, N is the total number of laser pulses; and Nb is the number of laser pulses below the given height. The median LAIaboveX value was 1.42, and 25-75 percentile values being 0.86-2.15. Also, in order to have a more homogeneous data set we redid the analyses using only spruce dominated stands, and excluding all grid cells at stand borders. The latter was set as grid cells that had neighbour grid cells in a neighbour stand. This had however, only a minor influence on the results.
Abstract
No abstract has been registered
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Abstract
No abstract has been registered