Über dieOrientierungsmechanismen der Borkenkäfer auf ihr Fortpflanzungsmaterial

Ohne Zusammenfassung     

Mixing methods – assessment of potential benefits for natural resources planning

Multi-objective forest planning is a multi-methodological endeavor whose success largely depends on how well the combined use of different methods contributes to the goals of the planning. This review assessed the benefits of mixing methods in natural resources planning. A sample of 30 peer-reviewed research articles was analyzed using an evaluation framework, designed based on democracy and planning theories, and participatory planning literature, including four dimensions: transparency, flexibility, consensus building, and operability. According to analyses, mixing different types (i.e. qualitative and quantitative) of methods generally yields greater benefits than the combination of similar methods. The subsample of 12 planning cases that utilized simulation-optimization software (SOS) appeared operable and moderately transparent, whereas flexibility and consensus building were often lacking. In comparison to the wide scholarly discussion on multi-methodology and mixing methods, it was observed that successful mixing examples in natural resource planning are still scarce and there are weaknesses in bridging the methods together. There is an evident need to pursue and to better communicate the benefits of mixing. Some good mixing examples utilizing SOS provided evidence that forest planning processes would make an excellent venue for studying the benefits and caveats of using mixed methods.     

Integrated incentives for fertility control

Incentive proposals for fertility control have stimulated considerable debate and only narrowly conceived trials. As a result, there exists a tendency to dismiss almost offhandedly the entire concept of using material incentives to further contraceptive practice before any have been adequately tried. Moreover, a majority of proposals thus far have been characterized by a search to uncover the "one best way" to circumvent the myriad frustrations encountered in attempting to reduce birthrates in traditional societies.     

The influence of the hemoglobin concentration in growing mink kits on certain skin characteristics

The relationship between some skin characteristics and hemoglobin values during the growth period were statistically examined in standard male minks. Significant correlations) (P < 0.05–0.001) were found between the hemoglobin concentrations determined at 3 points during the growth period (in July, August and November) and the density and colour of underfur, and skin length, respectively. According to the study even the early hemoglobin values in July and August have a significant influence on the size and quality of the pelt. Mink kits with low hemoglobin values are liable to develop a winter fur coat with defective pigmentation and hair structure of the underfur. Anemic minks develop the most extreme stage of the pigmentation defect and these so-called cotton fur skins have little value in the fur garment industry. When these abnormal hemoglobin values are recognized at an early stage, cotton fur skins may be avoided, and larger skins of better quality may be produced.     

Remote sensing and forest inventories in Nordic countries – roadmap for the future

The Nordic countries have long traditions in forest inventory and remote sensing (RS). In sample-based national forest inventories (NFIs), utilization of aerial photographs started during the 1960s, satellite images during the 1980s, laser scanning during the 2000s, and photogrammetric point clouds during the 2010s. In forest management inventories (FMI), utilization of aerial photos started during the 1940s and laser scanning during the 2000s. However, so far, RS has mostly been used for map production and research rather than for estimation of regional parameters or inference on their accuracy. In recent years, the RS technology has been developing very fast. At the same time, the needs for information are constantly increasing. New technologies have created possibilities for cost-efficient production of accurate, large area forest data sets, which also will change the way forest inventories are done in the future. In this study, we analyse the state-of-the-art both in the NFIs and FMIs in the Nordic countries. We identify the benefits and drawbacks of different RS materials and data acquisition approaches with different user perspectives. Based on the analysis, we identify the needs for further development and emerging research questions. We also discuss alternatives for ownership of the data and cost-sharing between different actors in the field.     

Effects of auxiliary data source and inventory unit size on the efficiency of sample-based coarse woody debris inventory

The efficiency of a sample-based inventory can be greatly improved if lower cost information on the study area is utilized. It has been observed that the use of airborne laser scanning (ALS) data in the design phase may improve the efficiency of dead wood (coarse woody debris, CWD) volume inventory notably, i.e. a smaller standard error of the mean is observed with the same inventory costs. In the present case, several auxiliary data sources were employed in the design phase by using ‘probability proportional to size’ sampling to select the sample units to be inventoried in the field. It was observed that a combination of ALS data with either aerial photographs or stand-register data can improve the sampling efficiency even more than the use of ALS as a single data source. Since these additional data sources are often gathered for the inventory of living trees, their use does not incur extra expenses for CWD assessment. Thus, the use of these data separately or together with ALS data can greatly improve the cost-efficiency of a CWD volume inventory. It was also observed that the size of the sample units has a slight effect on the sampling efficiency. Even though the improvement in the sampling efficiency was usually greater with larger sample unit sizes, the CWD volume inventory was most efficient with moderate grid cell sizes.     

Effect of tree-level airborne laser-scanning measurement accuracy on the timing and expected value of harvest decisions

The objective was to compare tree-level airborne laser-scanning (ALS) data accuracy with standwise estimation data accuracy as input data for forest planning, using tree- and stand-level simulators. The influence of the input data accuracy was studied with respect to (1) timing of the next thinning or clear-cutting and (2) the relative variation in the predicted income of the next logging expressed as the net present value (NPV). The timing and predicted NPV of thinning and clear-cutting operations were considered separately. The research was based on Monte Carlo simulations carried out with the tree- and stand-level simulators using a simulation and optimisation (SIMO) framework. The simulations used treewise measurements taken on 270 circular plots measured at the Evo Field Station, Finland, as input data. Deviations in the tree data measured were generated according to the mean standard errors found in standwise field estimation and tree-level ALS. The accuracy factors of ALS individual tree detection were based on the EUROSDR/ISPRS Tree Extraction Project. The results show that input data accuracy significantly affects both the timing and relative NPV of loggings. Tree-level ALS produces more accurate simulation results than standwise estimation with the error levels assumed. Diameter-based characteristics are the most important input data in all simulations. Accurate tree height estimates cannot be fully utilised in current simulators.     

Propagating the errors of initial forest variables through stand- and tree-level growth simulators

Developments in the field of remote sensing have led to various cost-efficient forest inventory methods at different levels of detail. Remote-sensing techniques such as airborne laser scanning (ALS) and digital photogrammetry are becoming feasible alternatives for providing data for forest planning. Forest-planning systems are used to determine the future harvests and silvicultural operations. Input data errors affect the forest growth projections and these effects are dependent on the magnitude of the error. Our objective in this study was to determine how the errors typical to different inventory methods affect forest growth projections at individual stand level during a planning period of 30 years. Another objective was to examine how the errors in input data behave when different types of growth simulators are used. The inventory methods we compared in this study were stand-wise field inventory and single-tree ALS. To study the differences between growth models, we compared two forest simulators consisting of either distance-independent tree-level models or stand-level models. The data in this study covered a 2,000-ha forest area in southern Finland, including 240 sample plots with individually measured trees. The analysis was conducted with Monte Carlo simulations. The results show that the tree-level simulator is less sensitive to errors in the input data and that by using single-tree ALS data, more precise growth projections can be obtained than using stand-wise field inventory data.     

Comparison of field sampling methods for assessing coarse woody debris and use of airborne laser scanning as auxiliary information

Coarse woody debris (CWD) has been recognized as one of the strongest indicators of forest biodiversity and its assessment has been emphasized in the development of new inventory methods. In this study, the most commonly referenced probability sampling methods were tested in a field area of 305.8 ha to gain comparative information on their performance and efficiency. Simple random sampling (SRS), systematic sampling and cluster sampling with fixed sized circular sample plots were tested, as well as strip sampling, transect relascope sampling and adaptive cluster sampling (ACS). Point relascope sampling and line intersect sampling were also tested for inventories of downed dead wood volumes. In addition, the amount of standing dead wood was assessed by means of traditional small angle relascope sampling. In general, the use of additional information in the inventory process has shown promising results. A new method for using data derived from airborne laser scanning (ALS) as a source of auxiliary information in the assessment of CWD volumes is presented, using probability proportional to size (PPS) sampling for the selection of the first-stage sample units in ACS (ACS_PPS) and for the placement of fixed sized plots (PLOT_PPS). The sampling methods were compared in terms of the cost-effectiveness. Point relascope sampling proved the most efficient sampling method for inventorying CWD volumes. PLOT_PPS and ACS_PPS were more efficient than the inventory of fixed sized plots (PLOT_SRS) and ACS (ACS_SRS) where sample units were selected with SRS. However, these methods could not achieve the same efficiency as relascope samplings. Nevertheless, the use of probability layers derived from ALS data gave promising results and offers new possibilities for inventorying CWD volumes more efficiently.