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.
2017
Abstract
The goal of this study was to assess the long-term effects of partial harvesting and supplementary soil scarification on the frequency of root and butt rot in managed uneven-sized Norway spruce stands. Frequency of rot and the population structure of the rot fungi were assessed on 1353 stumps after clear-cutting 21 years after a selection harvesting experiment. The initial experiment was comprised of three harvest strength (low, intermediate and high) of single-tree selection, removing approximately 25, 45 and 65% of the stand basal area. Uncut control plots were established at the same time. Supplementary soil scarification was applied in subplots within the single-tree selection plots, using a medium-sized excavator. After clear-cutting the stumps were analyzed with respect to rot caused by Heterobasidion parviporum, Armillaria spp., Stereum sanguinolentum as well as other rot fungi. Rot caused by Armillaria spp. was most common (8.6% of the stumps), while infection by H. parviporum (2.9%) or S. sanguinolentum (3.0%) was less frequent. The group “other rot” (5.4%) comprised 21 identified taxa, each occurring in 1–15 stumps. Significantly lower rot frequencies were found for the uncut control (16.3%) and intermediate harvest strength (15.7%), compared with low harvest strength (23.6%). A rot frequency of 21.0% was found in the high harvest strength. In two of three harvest strengths, the rot frequency was higher than for the uncut control. As the observed rot frequencies did not increase consistently with increasing harvest strength, the results do not completely support the initial expectations of increased rot after single-tree selection compared with the uncut control. However, since the probability of rot in individual stumps on plots treated with single-tree selection was significantly affected by the distance to the nearest strip road (H. parviporum) as well as dependent on the size of and distance to the nearest stump of trees cut during the experimental harvest (H. parviporum, S. sanguinolentum and total rot), it is evident that the single-tree selection harvesting was partially responsible for some of the observed rot. One of the selection criteria in the initial harvest was a sanitary removal of trees of poor vitality. Varying degrees of sanitation felling may therefore have offset the effects of new infections in wounds or spread of rot fungi through adjacent stumps. Supplementary soil scarification in small gaps of the residual stand had no significant effect on the frequency of rot, suggesting that such treatment may be used to facilitate regeneration in uneven-sized spruce stands on similar sites.
Abstract
National parks are established to reduce human influence on nature and contribute to species conservation, biodiversity and ecological services. Other states of protection like the UNESCO world heritage sites, for example, are created for maintaining culturally important places or lifestyles. In the Matobo Hills (Zimbabwe) both states of protection are present, a national park and a world heritage site. In addition, the land outside the National Park belongs to two different systems of ownership, namely “common” (i.e. community-owned) and “not-common” (privately or governmentally owned) land. In this paper, we investigated how the state of protection and the ownership affected the land use and land cover. We derived maps using Landsat images from 1989, 1998 and 2014 by supervised classification with Random Forests. To compensate for the lack of ground data we inferred past land use and land cover from recent observations combining photographs, Google Earth images and change detection. We could identify four classes, namely shrub land, forest, patchy vegetation and agricultural area. The Matobo National Park showed a stable composition of land cover during the study period and the main changes were observable in the surroundings. Outside the national park, forest increased by about 7%. The common lands have changed substantially and their agricultural area decreased. We attribute this development to the Fast Track Land Reform, which took place in the early 2000s. Our approach shows that combining information on recent land cover with change detection allows to study the temporal development of protected areas.
Authors
Sebastian Sippel Jakob Zscheischler Martin Heimann Holger Lange Miguel D. Mahecha Geert Jan van Oldenborgh Friederike E.L. Otto Markus ReichsteinAbstract
Daily precipitation extremes and annual totals have increased in large parts of the global land area over the past decades. These observations are consistent with theoretical considerations of a warming climate. However, until recently these trends have not been shown to consistently affect dry regions over land. A recent study, published by Donat et al. (2016), now identified significant increases in annual-maximum daily extreme precipitation (Rx1d) and annual precipitation totals (PRCPTOT) in dry regions. Here, we revisit the applied methods and explore the sensitivity of changes in precipitation extremes and annual totals to alternative choices of defining a dry region (i.e. in terms of aridity as opposed to precipitation characteristics alone). We find that (a) statistical artifacts introduced by data pre-processing based on a time-invariant reference period lead to an overestimation of the reported trends by up to 40 %, and that (b) the reported trends of globally aggregated extremes and annual totals are highly sensitive to the definition of a "dry region of the globe". For example, using the same observational dataset, accounting for the statistical artifacts, and based on different aridity-based dryness definitions, we find a reduction in the positive trend of Rx1d from the originally reported +1.6 % decade−1 to +0.2 to +0.9 % decade−1 (period changes for 1981–2010 averages relative to 1951–1980 are reduced to −1.32 to +0.97 % as opposed to +4.85 % in the original study). If we include additional but less homogenized data to cover larger regions, the global trend increases slightly (Rx1d: +0.4 to +1.1 % decade−1), and in this case we can indeed confirm (partly) significant increases in Rx1d. However, these globally aggregated estimates remain uncertain as considerable gaps in long-term observations in the Earth's arid and semi-arid regions remain. In summary, adequate data pre-processing and accounting for uncertainties regarding the definition of dryness are crucial to the quantification of spatially aggregated trends in precipitation extremes in the world's dry regions. In view of the high relevance of the question to many potentially affected stakeholders, we call for a well-reflected choice of specific data processing methods and the inclusion of alternative dryness definitions to guarantee that communicated results related to climate change be robust.
Abstract
We investigate a set of long-term river runoff time series at daily resolution from Brazil, monitored by the Agencia Nacional de Aguas. A total of 150 time series was obtained, with an average length of 65 years. Both long-term trends and human influence (water management, e.g. for power production) on the dynamical behaviour are analyzed. We use Horizontal Visibility Graphs (HVGs) to determine the individual temporal networks for the time series, and extract their degree and their distance (shortest path length) distributions. Statistical and information-theoretic properties of these distributions are calculated: robust estimators of skewness and kurtosis, the maximum degree occurring in the time series, the Shannon entropy, permutation complexity and Fisher Information. For the latter, we also compare the information measures obtained from the degree distributions to those using the original time series directly, to investigate the impact of graph construction on the dynamical properties as reflected in these measures. Focus is on one hand on universal properties of the HVG, common to all runoff series, and on site-specific aspects on the other. Results demonstrate that the assumption of power law behaviour for the degree distribtion does not generally hold, and that management has a significant impact on this distribution. We also show that a specific pretreatment of the time series conventional in hydrology, the elimination of seasonality by a separate z-transformation for each calendar day, is highly detrimental to the nonlinear behaviour. It changes long-term correlations and the overall dynamics towards more random behaviour. Analysis based on the transformed data easily leads to spurious results, and bear a high risk of misinterpretation.
Authors
Holger LangeAbstract
Long time series of environmental variables are reflecting the dynamics of ecosystems. Data on climate, water, carbon, nutrients and other observables provide the key to understand terrestrial systems and to detect trends, systemic changes and responses, e.g. to changing climate, disturbances, or management. We present a number of diagnostic measures, based on symbolic dynamics or order statistics, which quantify the information content and the complexity of environmental time series. Three examples for the application of complexity measures in environmental sciences will be provided: Earth System Models and their ability to reproduce observations of Gross Primary Productivity, the dynamics of river runoff, and long-term behavior of ion concentrations in stream water from a monitoring site in Germany. Diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.
Abstract
No abstract has been registered
Abstract
In the present study we applied X-band interferometric SAR (InSAR) data from the TanDEM-X mission, and investigated the relationship between InSAR height above ground and above-ground biomass (AGB) in a forest with very high biomass. We carried out this study in the East Usambara Mountains in Tanzania, with AGB ranging up to N1000 t/ha. Field inventory provided AGB data for 153 plots of 900 m2 in size. An airborne laser scanning (ALS) provided a DTM as well as AGB predictions for larger 8100 m2 cells over the entire study area. Three TanDEM-X acquisitions provided single-pass InSAR data, from which we generated a Digital Surface Models (DSM) and InSAR height by subtracting the ALS DTM. The results showed that proportionality may represent the relationship where AGB increased with 18.4 t/ha per m increase in InSAR height. The accuracy was low with RMSE = 203 t/ha (44%), which was partly attributable to small field plots and partly to a limited sensitivity of InSAR height to variations in basal area and stand density. An identical proportionality model, with less residual noise, was achieved by replacing the small field plots with the 8100 m2 cells having AGB predictions from ALS data.
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
No abstract has been registered