Potential für ein starkes Netzwerk zwischen GFBio und FDM-Beratenden an Universitäten und Forschungsinstituten

GFBio (German Federation for Biological Data) hat sich in den letzten sechs Jahren als die zentrale Anlaufstelle für WissenschaftlerInnen und Datenverantwortliche rund um alle Fragen des Forschungsdatenmanagements in der Biodiversitätsforschung etabliert. Zentrales Ziel von GFBio ist die Sensibilisierung der Fachcommunity für die Themen Forschungsdatenmanagement, Langzeitarchivierung und Publikation von Forschungsdaten. Eine bisher nur unzureichend gelöste Herausforderung ist jedoch die Adressierung der Forschenden vor Ort. Die direkte Interaktion mit den Forschenden am jeweiligen Campus wird dabei durch die FDM-Beratenden geleistet. Die Erfahrung hat gezeigt, dass hier bereits hervorragende Arbeit geleistet wird, jedoch für eine in die Tiefe gehende fachspezifische Beratung oft die Ressourcen fehlen. Das von GFBio propagierte “front-office/back-office” Modell mit einer engen Verknüpfung der Aktivitäten von GFBio und der lokalen FDM-Beratenden ist durch seine Arbeitsteiligkeit zu beiderseitigem Vorteil. Im Folgenden wird GFBio mit seinen Kernservices vorgestellt sowie Anknüpfungspunkte für die Zusammenarbeit mit lokalen FDM-Beratenden aufgezeigt

Sampling procedures for throughfall monitoring: a simulation study

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events

Regionalisierung von Variablen forstlicher Stichprobeninventuren auf Betriebsebene

Eine periodische Bewertung des Waldzustandes auf der räumlichen Ebene der Maßnahmenumsetzung ist Voraussetzung für eine nachhaltige Bewirtschaftung. In der klassischen Forsteinrichtung erfolgt die Bewertung auf dieser Ebene, dem Bestand. Die Einführung einer Ökologischen Waldbauplanung und methodische Vorteile führen zu einer Abkehr von der klassischen Forsteinrichtung hin zu Betriebsinventuren auf Stichprobenbasis. Ökonomische Restriktionen erlauben dabei keine ausreichende Stichprobendichte zur Bewertung von Einzelbeständen. Auf der Grundlage der stichprobenweise erhobenen Information werden quantitative computergestützte Modelle entwickelt, die eine Vorhersage dieser Information für Flächen ermöglichen, die von keiner oder zu wenigen Stichproben getroffen wurden. Die Übertragung der Merkmale in die Fläche wird Regionalisierung genannt und erfolgt mit raumbezogenen Informationssystemen hauptsächlich über Hilfsvariable. Die Erhebung der Hilfsvariablen erfolgte mit Methoden der analogen und digitalen Fernerkundung sowohl an den Stichprobenpunkten als auch an den Vorhersagepunkten, aber auch terrestrisch. Techniken der Merkmalsschätzung sind die Stichprobentheorie, die Geostatistik und multivariate statistische Verfahren wie die kanonische Korrelationsanalyse.Sustainable forest management stipulates a periodical assessment of the state of forests at the spatial scale of management activities. Classical forest management planning surveys take place at such a spatial scale, that is, the forest stand. The introduction of continuous cover forestry systems as well as methodological advantages have lad to a replacement of classical forest management planning surveys by sample based inventories at the district level. However, economical constraints do not allow sample densities that enable a statistically sound assessment at the forest stand level. In the present study, based on the pointwise information of the sample based inventory, computer based models are developed that enable a prediction of the said information at the stand level. The resulting spatial generalization is commonly called regionalization. It is accomplished by means of geographical information systems and relies on auxiliary information. The latter is derived by analog and digital softcopy photogrammetry techniques at the sample locations as well as at all prediction locations. Terrestrial surveys are another source of auxiliary information. Geostatistics, sampling theory, and multivariate statistical procedures like the canonical correlation analysis are investigated methods for the feature prediction

A flexible statistics web processing service - Added value for information systems for experiment data

Data management in the life sciences has evolved from simple storage of data to complex information systems providing additional functionalities like analysis and visualization capabilities, demanding the integration of statistical tools

Identification of forest management types from ground-based and remotely sensed variables and the effects of forest management on forest structure and composition

Eleven types of forest management were investigated (coniferous and deciduous age-class forest at pole-, young- and old timber stage, continuous cover forest management, selectively cut forest management, farmers’ forest, coppice, coppicewith- standards and unmanaged forest) with respect to ground-based measurements (diameter at breast height, stand density, tree height, wood volume, tree species composition, coarse woody debris, regeneration, deer browsing) and remotely sensed variables by LiDAR (e. g. canopy height, canopy surface area, canopy depth). Wood volume ranged between 320 m3 ha-1 in continuous cover forest and 730 m3 ha-1 in farmers’ forest. Basal area was between 25 m2 ha-1 in deciduous age-class forest and 49 m2 ha-1 in farmers’ forest. Coarse woody debris ranged between 11 m3 ha-1 in selectively cut forest and 39 m3 ha-1 in unmanaged forest. Number of tree species was lowest in the selectively cut forest (1 to 2 tree species per ha) and highest in coppice forest (up to 8 tree species per ha). Density of regeneration was independent of management, but damage due to deer browsing was highest in unmanaged forest reserves and in selectively cut forest, leading to a decline of admixed species. We found that a classification according to management types as based on management plans is not appropriate for scientific studies of relations between forest structure, biodiversity, and management at plot scale. In reality, some management types, such as continuous cover forest, were not sufficiently distinct. The most consistent separation was between longrotation, short-rotation and uneven-aged forests. The remotely sensed variables distinguished forest structures more clearly than ground-based measurements. Nevertheless, structural variables might be rather similar between unrelated management systems and rather dissimilar even within the same management type at plot scales between 500 m2 and 0,64 ha. This study compares forest inventory between management types and documents the importance of including forest-management and forest structure in the evaluation of the climate mitigation potential of forests and of strategies for preservation of biodiversity

Moving in three dimensions: effects of structural complexity on occurrence and activity of insectivorous bats in managed forest stands

1. Forest management determines to a large degree the three-dimensional arrangement of the vegetation in production forest systems and hence has an essential influence on habitat quality for wildlife. We investigated the effects of forest structure on occurrence, activity and species composition of European bats, an ecologically important group of vertebrates known to be affected by the physical clutter of vegetation. 2. Species composition and activity of bats were assessed with acoustic monitoring on 50 one-hectare experimental plots in a biosphere reserve in Germany. Three-dimensional forest structure was assessed by Light Detection and Ranging (LiDAR), and a set of 20 mathematically derived and fine-grained structural parameters with a minimum of collinearity was used for a quantitative description of the vegetation structure. 3. Occurrence and activity of bats were positively associated with the structural parameters canopy height, standard deviation of the canopy surface roughness and edge fraction, indicating older forest stands with patches of different vegetation heights. In addition, species composition in differently managed forest stands was significantly influenced by the relative proportion of structural parameters. Species of one functional group, sharing similar adaptations in wing morphology and foraging strategy, showed similar associations with three-dimensional structural parameters. In addition, we found species-specific structural parameter associations explaining the occurrence and activity levels of individual species in differently managed production forest types. 4. Synthesis and applications. High-resolution LiDAR data are an important tool to assess structural habitat suitability for bat species. Our data revealed that bat occurrence and activity increases with structural heterogeneity in managed forest stands. Given, that bats provide an essential ecosystem service through top-down control of herbivorous insects, increasing stand structural heterogeneity through management practices (e. g. selective harvesting) is a very effective strategy to assure vital ecosystem functioning in production forest systems

Potential für ein starkes Netzwerk zwischen GFBio und FDM-Beratenden an Universitäten und Forschungsinstituten

GFBio (German Federation for Biological Data) hat sich in den letzten sechs Jahren als die zentrale Anlaufstelle für WissenschaftlerInnen und Datenverantwortliche rund um alle Fragen des Forschungsdatenmanagements in der Biodiversitätsforschung etabliert. Zentrales Ziel von GFBio ist die Sensibilisierung der Fachcommunity für die Themen Forschungsdatenmanagement, Langzeitarchivierung und Publikation von Forschungsdaten. Eine bisher nur unzureichend gelöste Herausforderung ist jedoch die Adressierung der Forschenden vor Ort. Die direkte Interaktion mit den Forschenden am jeweiligen Campus wird dabei durch die FDM-Beratenden geleistet. Die Erfahrung hat gezeigt, dass hier bereits hervorragende Arbeit geleistet wird, jedoch für eine in die Tiefe gehende fachspezifische Beratung oft die Ressourcen fehlen. Das von GFBio propagierte “front-office/back-office” Modell mit einer engen Verknüpfung der Aktivitäten von GFBio und der lokalen FDM-Beratenden ist durch seine Arbeitsteiligkeit zu beiderseitigem Vorteil. Im Folgenden wird GFBio mit seinen Kernservices vorgestellt sowie Anknüpfungspunkte für die Zusammenarbeit mit lokalen FDM-Beratenden aufgezeigt