Meetnet functievervulling bos: eerste resultaten beschikbaar

De statistieken van vroeger zijn de meetnetten van nu. Meetnetten meten en moeten liefst de gegevens aanleveren om beleidsprestaties en ¿effecten te monitoren. Met de resultaten kan nieuw beleid worden ontwikkeld en bestaand beleid geëvalueerd. Vorig jaar is een nieuw meetnet gestart, het Meetnet Functievervulling Bos (MFV-bos). De eerste resultaten zijn onlangs beschikbaar gekomen. Deze bijdrage bevat een korte uitleg over de achtergrond van het MFV-bos en enkele in het oog springende resultate

Forest Focus in Nederland; een blauwdruk voor een nationaal programma bosmonitoring

De Europese Commissie heeft een nieuwe Verordening inzake de bewaking van bossen en milieu-interacties in de Gemeenschap, `Forest Focus` opgesteld. Forest Focus is een voortzetting en belangrijke uitbreiding van de verordening tegen schade aan bossen door luchtverontreiniging, waaraan Nederland een bijdrage levert door het monitoren van zogenaamde level 1 en level 2 plots. Op 11 level 1 plots wordt de bosvitaliteit gemeten en op 13 Level 2 plots wordt zowel de stress op - als de reactie van het bosecosysteem bepaald. Forest Focus verplicht de lidstaten een Nationaal Programma Bosmonitoring op te stellen. Het programma moet voorzien in de monitoring in bossen van biodiversiteit, koolstofvastlegging en de invloed van klimaatverandering. Deze `Blauwdruk` bevat hiervoor een voorstel voor Nederland

Bayesian classification of vegetation types with Gaussian mixture density fitting to indicator values.

Question: Is it possible to mathematically classify relevés into vegetation types on the basis of their average indicator values, including the uncertainty of the classification? Location: The Netherlands. Method: A large relevé database was used to develop a method for predicting vegetation types based on indicator values. First, each relevé was classified into a phytosociological association on the basis of its species composition. Additionally, mean indicator values for moisture, nutrients and acidity were computed for each relevé. Thus, the position of each classified relevé was obtained in a three-dimensional space of indicator values. Fitting the data to so called Gaussian Mixture Models yielded densities of associations as a function of indicator values. Finally, these density functions were used to predict the Bayesian occurrence probabilities of associations for known indicator values. Validation of predictions was performed by using a randomly chosen half of the database for the calibration of densities and the other half for the validation of predicted associations. Results and Conclusions: With indicator values, most relevés were classified correctly into vegetation types at the association level. This was shown using confusion matrices that relate (1) the number of relevés classified into associations based on species composition to (2) those based on indicator values. Misclassified relevés belonged to ecologically similar associations. The method seems very suitable for predictive vegetation models

The need of data harmonization to derive robust empirical relationships between soil conditions and vegetation.

Question: Is it possible to improve the general applicability and significance of empirical relationships between abiotic conditions and vegetation by harmonization of temporal data? Location: The Netherlands. Methods: Three datasets of vegetation, recorded after periods with different meteorological conditions, were used to analyze relationships between soil moisture regime (expressed by the mean spring groundwater level - MSLt calculated for different periods) and vegetation (expressed by the mean indicator value for moisture regime Fm). For each releve, measured groundwater levels were interpolated and extrapolated to daily values for the period 1970-2000 by means of an impulse-response model. Sigmoid regression lines between MSLt and Fm were determined for each of the three datasets and for the combined dataset. Results: A measurement period of three years resulted in significantly different relationships between Fm and MSLt for the three datasets (F-test,/? <0.05>. The three regression lines only coincided for the mean spring groundwater level computed over the period 1970-2000 (AfSLclimate) and thus provided a general applicable relationship. Precipitation surplus prior to vegetation recordings strongly affected the relationships. Conclusions: Harmonization of time series data (1) eliminates biased measurements, (2) results in generally applicable relationships between abiotic and vegetation characteristics and (3) increases the goodness of fit of these relationships. The presented harmonization procedure can be used to optimize many relationships between soil and vegetation characteristics. © IAVS; Opulus Press Uppsala

Micromilling analysis

The original publication is available at http://www.isem.org.za/index.php/isem/isem2011.Conference of the ISEM 2011 Proceedings, Stellenbosch, South Africa, 21 - 23 September 2011.Conference theme - Innovative Systems Thinking: Unravelling Complexity for Successful Solutions.This paper reports on a Techno-economic model of micromilling, incorporating major contributors to products’ manufacturing cost. Micromilling is a comparatively new machining technology and is developing rapidly. Many new products are significantly smaller than their legacy counterparts, due to drivers such as increased micro processing, portability advantages and resource scarcity. This allows micro manufacturing in general and micromilling specifically to seize market share at the expense of earlier manufacturing technologies. The most advantageous areas to consider micromilling were identified as medical implants, micro-moulds, developing and prototyping, small and medium batches of complex 3D shapes and dental accessories.The Industrial, Systems and Engineering Management (ISEM) conference is a joint initiative between the Southern African Institute for Industrial Engineering (SAIIE), INCOSE (South Africa) and the Graduate School for Technology Management at the University of PretoriaPublishers' Versio