Vorläufige Ergebnisse eines Pappel-Durchforstungs-Versuches in Südafrika
The present article deals with the response ofP. deltoides to thinning. In 1965 an experiment was laid out in an 8-year old poplar plantation, site class, 0.5 in the mist belt of Natal. The S% defined as the ratio mean distance between the trees mean height of the stand = 100 was used to express stand density and to characterize the degree of thinning. Three thinning degrees, designated as A, B and C, with an S% of 24,31 and 36 respectively, were tested in a completely randomized design wth four replications. The plot areas were 0.144 hectare and each plot was surrounded by a 5.4 m. wide buffer zone. In 1965, immediately after the thinning of the plots, the mean basal areas per hectare of the A, B and C plots were: A: 23.0 m2(= 100) B: 15.5 m2(= 66) C: 11.3 (= 49) The relationship between basal area at the beginning of the growing season and the basal area increment during the first growing season was expressed by the equation: basal area increment (m2/hect./annum) = -10.417+21.9258 (log basal area) - 8.3256 (log basal area)2 the multiple correlation coefficient being equal to 0.860. During the second growing season there was a weakly significant negative correlation between basal area and basal area increment. During the third year stand density and growth were not related. An analysis of the relationship between periodic current volume growth during the 3-year growth period and the mean stand density during this period, the latter defined as the average of the stand densities at the beginning and end of the period, revealed that basal area is more suitable to express stand density than S%. In the regression analysis, the residual variation with S% as explanatory variable was 8.3% of the total variation, as against 2.0% with mean basal area as explanatory variable. There was a linear relationship between basal area and periodic current volume increment. For a mean basal area during the growth period of 28.0 m2 per hectare, the annual volume increment was 49 m3, for a basal area of 14 m2, it was 35.5% below this maximum. During the third growing season the A-plots reached the “natural stocking density”, defined as the maximum basal area which the stand can carry on a certain site and at a given age. In the financial calculations, the indicating per cent was defined as: $$w = 100 \cdot \left[ {\sqrt[n]{{\frac{{2(A_{x + n} - A_x ) - n(O \cdot op)V}}{{Hk_x + Hk_{x + n} + 2B}} + 1 - 1}}} \right]$$ where: Ax, Ax+n = net-value of the stand at x, x+n years n = length of period in years V = capitalized annual general cost Hkx, Hkx+n = cost value of stand at x, x+n years B = market value of land p = rate of interest. The indicating per cent as calculated for each of the 12 plots and the following equation fitted: Ind.% = -2.25 + 1.967 (mean basal area) - 0.04498 (mean basal area)2 The optimum basal area therefore was 22 m2 per hectare, i.e. 71-73% of the natural stocking density.
Soziale Stellung, Nachbarschaft und Zuwachs
Wenn wit einen Bestand betrachten, sei es ein Fichtenreinbestand oder ein Reinoder Mischbestand anderer Baumarten, fiillt auch dem unbefangenen Beobachter auf, daf~ der Zuwachs der B~ume trotz scheinbar gleicher ~iuflerer Bedingungen verschieden groB ist. B~iume gleicher Holzart und gleichen Alters unterscheiden sich im Zuwachs je nach ihrer sozialen Stellung, Niume verschiedener Holzarten zeigen bei sonst gleichen Bedingungen unterschiedlichen Zuwachs, innerhalb derselben Baumart k6nncn Zuwachsunterschiede durch verschiedene Rassen oder Genotypen bedingt sein. Der Einflul~ yon Standort, Klima und Alter soll im folgenden unberiicksichtigt bleiben, da diese Einfluf~gr6gen in den untersuchten Best~inden als konstant angesehen werden diJrfen. Diese zuletzt genannten Faktoren bestimmen vor allem die m/Sgliche Gesamtleistung eines Bestandes. Fi.ir die Leistung und die Leistungsm/Sglichkeit des einzelnen Baumes dagegen ist vor allem seine Stellung im sozialen GefiJge mai~gebend. Das heigt, es muff zur Sch~itzung des Leistungsverm6gens auch das Verh~ilmis zu den Nachbarb~iumen mit beriicksichtigt werden. Eine Beurteilung der Leistungsf~ihigkeit einzelner Niume ist besonders bei Mischbestandsuntersuchungen wichtig. Aber auch bei der Frage nach der Wirkung verschiedener Durchforstungsoder Diingungsmafinahmen oder bei der Ansprache und Beurteilung verschiedener Rassen und Genotypen kann die richtige Einsch~itzung stellungsbedingter Zuwachsunterschiede yon einzelnen B~iumen sehr aufschluf~reich sein. Die ersten Versuche, die Niume nach ihrer sozialen Stellung einzustufen, wurden deshalb schon friJh unternommen, so etwa yon v. SEEBACrt, 1844 (S. ASSMANN, 1961, S. 82). Die bekannteste Baumklasseneinteilung stammt von KI~AFT aus dem Jahre 1884 (Kt~AFT, 1884, S. 22). KI~AFT spricht yon Stammklassen und unterscheidet vorherrschende, herrschende, gering mitherrschende, beherrschte und ganz unterst~indige St~imme, gliedert also ausschliet~lich nach sozialen Gesichtspunkten. Das KRAFTsche System hat sich fiir die Beschreibung gleichaltriger, geschlossener Reinbest~/nde ausgezeichnet bew~ihrt. Ein Nachteil ist allerdings, daf~ die Zuordnung zu den Baumklassen doch weitgehend subjektiv ist. Aui~erdem ist das KRAFTsche System bei der Beschreibung stark aufgelichteter Best~inde und bei MischbestSnden nur bedingt anwendbar. Bei Untersuchungen in Mischbesfiinden versuchte deshalb der Verfasser, objektiv ermittelte Mef~werte an die Stelle subjektiv ermittelter Baumklassen treten zu lassen (KENNEL, 1965). Uber die Leistung der verschiedenen Baumklassen in Fichtenbest~inden haben zuletzt VANSELOW (1951) und MAGm (1952) berichtet.
Ocean predictive skill assessments in the South Atlantic: Crowd-sourcing of student-based discovery
Autonomous Underwater Gliders have over a decade long history of successful regional deployments serving scientific, societal and security needs in application areas ranging from pole to pole and including the full range of water depths from shallow coastal seas to the deep ocean. Glider deployments covering the basin scale are much fewer, but are a growing capacity as demonstrated by the Woods Hole to Bermuda line that crosses the Gulf Stream, the Atlantic Crossing line that follows the Gulf Stream, and the basin circling flights now being conducted as part of the Challenger Glider Mission. The next step in the evolution of the global Challenger mission is to enable an ensemble of modelers from different institutions and agencies to participate in a meaningful way. This process with be formalized in 2014 by leveraging the data management tools of the U.S. Integrated Ocean Observing System (IOOS) and the education tools of the U.S. National Science Foundation's (NSF) Ocean Observing Initiative (OOI). The Education Visualization (EV) tools developed by the OOI's Education and Public Engagement (EPE) Implementing Organization (IO) are currently being configured through the cyber OOI net to display real time OOI glider data with intuitive interactive browser-based tools, reducing the barriers for student participation in sea exploration and discovery. Through U.S. IOOS, forecast ocean data will be harvested from the ephemeral ocean snapshots produced by an ensemble of ocean models along the same glider tracks as Challenger. The parallel observed and forecast datasets, both evolving in real time, will be accessible through the same OOI EV tools, enabling student participation in a crowd-sourced ocean predictive skill experiment. The result will satisfy one of the important goals of the Challenger mission by enabling students to assess of the quality of the ensemble of available global scale ocean models. Student research team projects that use the new model data comparison capabilities will be conducted during the summer of 2014. Students will compare an ensemble of the global ocean models along the high velocity transport pathways by gliders on basin-scale missions, such as one that traverses the northern side of the South Atlantic gyre along the Brazilian shelfbreak. The lasting impact of the Challenger mission will be a global fleet available to respond to events, an assessment of the ocean models along the fastest ocean transport pathways, and the establishment of a network of gliderports for global response.