This page has only limited features, please log in for full access.
Timber harvesting operations using heavy forest machinery frequently results in severe soil compaction and displacement, threatening sustainable forest management. An accurate prediction of trafficability, considering actual operating conditions, minimizes these impacts and can be facilitated by various predictive tools. Within this study, we validated the accuracy of four terramechanical parameters, including Cone Index (MPa, Penetrologger), penetration depth (cm, Penetrologger), cone penetration (cm blow−1, dual-mass dynamic cone penetrometer) and shear strength (kPa, vane meter), and additionally two cartographic indices (topographic wetness index and depth-to-water). Measurements applying the four terramechanical approaches were performed at 47 transects along newly assigned machine operating trails in two broadleaved dominated mixed stands. After the CTL thinning operation was completed, measurement results and cartographic indices were correlated against rut depth. Under the rather dry soil conditions (29 ± 9 vol%), total rut depth ranged between 2.2 and 11.6 cm, and was clearly predicted by rut depth after a single pass of the harvester, which was used for further validations. The results indicated the easy-to-measure penetration depth as the most accurate approach to predict rut depth, considering coefficients of correlation (rP = 0.44). Moreover, cone penetration (rP = 0.34) provided reliable results. Surprisingly, no response between rut depth and Cone Index was observed, although it is commonly used to assess trafficability. The relatively low moisture conditions probably inhibited a correlation between rutting and moisture content. Consistently, cartographic indices could not be used to predict rutting. Rut depth after the harvester pass was a reliable predictor for total rut depth after 2–5 passes (rP = 0.50). Rarely used parameters, such as cone penetration or shear strength, outcompeted the highly reputed Cone Index, emphasizing further investigations of applied tools.
Marian Schönauer; Stephan Hoffmann; Joachim Maack; Martin Jansen; Dirk Jaeger. Comparison of Selected Terramechanical Test Procedures and Cartographic Indices to Predict Rutting Caused by Machine Traffic during a Cut-to-Length Thinning-Operation. Forests 2021, 12, 113 .
AMA StyleMarian Schönauer, Stephan Hoffmann, Joachim Maack, Martin Jansen, Dirk Jaeger. Comparison of Selected Terramechanical Test Procedures and Cartographic Indices to Predict Rutting Caused by Machine Traffic during a Cut-to-Length Thinning-Operation. Forests. 2021; 12 (2):113.
Chicago/Turabian StyleMarian Schönauer; Stephan Hoffmann; Joachim Maack; Martin Jansen; Dirk Jaeger. 2021. "Comparison of Selected Terramechanical Test Procedures and Cartographic Indices to Predict Rutting Caused by Machine Traffic during a Cut-to-Length Thinning-Operation." Forests 12, no. 2: 113.
Prerequisite for a sustainable fulfilment of timber and non-timber functions of forests is the knowledge of criteria and indicators describing the state and dynamics of forest ecosystems at the landscape level. Without this knowledge, a conversion of Agenda 21 and the Helsinki-process into practical management is impossible. However, besides the important basic scientific duty of determining suitable criteria for the different functions of the forests, much emphasis has to be put into the transfer of data from sample plot investigations and field studies to other areas (regionalization).
Martin Jansen; Michael Judas; Joachim Saborowski. Abstract. Spatial Modelling in Forest Ecology and Management 2002, 1 -1.
AMA StyleMartin Jansen, Michael Judas, Joachim Saborowski. Abstract. Spatial Modelling in Forest Ecology and Management. 2002; ():1-1.
Chicago/Turabian StyleMartin Jansen; Michael Judas; Joachim Saborowski. 2002. "Abstract." Spatial Modelling in Forest Ecology and Management , no. : 1-1.
Spatial classification of landscape and the description of local site characteristics are the two fundamental principles of forest planning. They both form the foundation for any kind of natural and sustainable forest management.
Martin Jansen; V. Stüber; H. Wachter; W. Schmidt; Joachim Saborowski; V. Mues; C. Eberl; B. Sloboda; R. Schulz. Spatial models for site evaluation and forest planning. Spatial Modelling in Forest Ecology and Management 2002, 143 -161.
AMA StyleMartin Jansen, V. Stüber, H. Wachter, W. Schmidt, Joachim Saborowski, V. Mues, C. Eberl, B. Sloboda, R. Schulz. Spatial models for site evaluation and forest planning. Spatial Modelling in Forest Ecology and Management. 2002; ():143-161.
Chicago/Turabian StyleMartin Jansen; V. Stüber; H. Wachter; W. Schmidt; Joachim Saborowski; V. Mues; C. Eberl; B. Sloboda; R. Schulz. 2002. "Spatial models for site evaluation and forest planning." Spatial Modelling in Forest Ecology and Management , no. : 143-161.
The Lower Saxony working group for forest site evaluation compiled a site map based on soil morphology, vegetation ecology, and relief analyses (fig. 5.16, path 1 ). For this, sample plot investigations were extrapolated to the mapping area, i.e. regionalized. A site map delineates sites types that are identified by four different numbers which encode the ecological information (see chap. 3.2.2). The water budget of the area as well as the geological parent material with its different characteristics are nominally scaled variables. The nutrient index is ordinal.
Martin Jansen; C. Eberl; F. Reese. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management 2002, 68 -86.
AMA StyleMartin Jansen, C. Eberl, F. Reese. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management. 2002; ():68-86.
Chicago/Turabian StyleMartin Jansen; C. Eberl; F. Reese. 2002. "Spatial prediction of climate, soil, and macrofauna." Spatial Modelling in Forest Ecology and Management , no. : 68-86.
The objective of this section is to investigate the possibilities of country-wide regionalization of climatic elements for forest management purposes in Lower Saxony. We analyse the influence of geomorphological variables, derived from a digital elevation model (DEM) and landuse (see chapter 5.1), on the spatial distribution of air temperature and precipitation.
V. Mues; Martin Jansen; B. Sloboda; K. Radier&; Joachim Saborowski. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management 2002, 41 -67.
AMA StyleV. Mues, Martin Jansen, B. Sloboda, K. Radier&, Joachim Saborowski. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management. 2002; ():41-67.
Chicago/Turabian StyleV. Mues; Martin Jansen; B. Sloboda; K. Radier&; Joachim Saborowski. 2002. "Spatial prediction of climate, soil, and macrofauna." Spatial Modelling in Forest Ecology and Management , no. : 41-67.
Many projects in ecological research are concerned with spatially arranged measurements. A common situation can mathematically be described by a finite set of points (locations)
Dr. J. Saborowski; M. Jansen. Statistical methods for regionalization of ecological state variables. Spatial Modelling in Forest Ecology and Management 2002, 19 -26.
AMA StyleDr. J. Saborowski, M. Jansen. Statistical methods for regionalization of ecological state variables. Spatial Modelling in Forest Ecology and Management. 2002; ():19-26.
Chicago/Turabian StyleDr. J. Saborowski; M. Jansen. 2002. "Statistical methods for regionalization of ecological state variables." Spatial Modelling in Forest Ecology and Management , no. : 19-26.
Spatial modelling has been restricted to Lower Saxony, a federal state in the north of Germany (fig. 3.1) with an area of 47 600 km2, reaching from the North Sea in the northwest to the Harz mountains in the southeast.
R. Schulz; Martin Jansen. Study areas and basic data. Spatial Modelling in Forest Ecology and Management 2002, 11 -18.
AMA StyleR. Schulz, Martin Jansen. Study areas and basic data. Spatial Modelling in Forest Ecology and Management. 2002; ():11-18.
Chicago/Turabian StyleR. Schulz; Martin Jansen. 2002. "Study areas and basic data." Spatial Modelling in Forest Ecology and Management , no. : 11-18.
Geomorphometric variables have been used for decades for several objectives, e.g. the prediction of soil loss determined by slope, or colluvial erosion and accumulation caused by type and degree of curvature particularly in agriculture (Seiler 1982). Another field of application is geotechnique, e.g. the estimation of landslide susceptibility, depending on so-called form elements of certain plan and profile curvature and slope gradients (Dikau 1990). Gardner et al. 1990 describe the rapid increase in the possibilities of DEM analysis; today, e.g. even complex hydrological features such as stream orders can be calculated very fast.
R. Schulz; V. Mues; Martin Jansen; Michael Judas; Joachim Saborowski. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management 2002, 27 -40.
AMA StyleR. Schulz, V. Mues, Martin Jansen, Michael Judas, Joachim Saborowski. Spatial prediction of climate, soil, and macrofauna. Spatial Modelling in Forest Ecology and Management. 2002; ():27-40.
Chicago/Turabian StyleR. Schulz; V. Mues; Martin Jansen; Michael Judas; Joachim Saborowski. 2002. "Spatial prediction of climate, soil, and macrofauna." Spatial Modelling in Forest Ecology and Management , no. : 27-40.
The treatment of forests was and still is characterized by spatial relationships. In contrast to the production of hand crafted and industrial goods, the production of agricultural and forest products always depends on areal units. Already in the past, the conscious treatment of forest resources oriented at sustainability was connected with the existence and quality of spatial information. This is obvious in the quotation from J.G. Krunitz in volume 14 of the Oeconomische Encyclopaedic of 1778 (p. 714, as quoted by Steinsiek 1999): “Sind die Förste nicht gründlich und auf eine geometrische Art vermessen, so wird die ganze Forstwirthschaft nur auf eine Gerathewohl getrieben, und alle andere Eintheilung der Förste, welche man vornimmt, wird allemahl einen unsicheren und ungewissen Grund haben, weil sie nur auf ein Ungefähr gemacht ist.”1
Martin Jansen; Michael Judas; Joachim Saborowski. Introduction. Spatial Modelling in Forest Ecology and Management 2002, 3 -9.
AMA StyleMartin Jansen, Michael Judas, Joachim Saborowski. Introduction. Spatial Modelling in Forest Ecology and Management. 2002; ():3-9.
Chicago/Turabian StyleMartin Jansen; Michael Judas; Joachim Saborowski. 2002. "Introduction." Spatial Modelling in Forest Ecology and Management , no. : 3-9.
The question of the natural state of the vegetation in forests plays a vital role in the discussion of the importance of forests as habitats. To take into account conservation aspects as a management objective, most German state forest departments catalogue forests resembling natural woodlands (see Otto 1989, 1992, 1995; Beese 1996).
M. Jansen; Dr. W. Schmidt; V. Stüber; H. Wächter; C. Naeder; M. Weckesser; Dr. F.J. Knauft. Spatial models for site evaluation and forest planning. Spatial Modelling in Forest Ecology and Management 2002, 162 -175.
AMA StyleM. Jansen, Dr. W. Schmidt, V. Stüber, H. Wächter, C. Naeder, M. Weckesser, Dr. F.J. Knauft. Spatial models for site evaluation and forest planning. Spatial Modelling in Forest Ecology and Management. 2002; ():162-175.
Chicago/Turabian StyleM. Jansen; Dr. W. Schmidt; V. Stüber; H. Wächter; C. Naeder; M. Weckesser; Dr. F.J. Knauft. 2002. "Spatial models for site evaluation and forest planning." Spatial Modelling in Forest Ecology and Management , no. : 162-175.