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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2003

Abstract

Bumblebees are important pollinators of crops and wild flowers, and their foraging range has considerable management interest. It is commonly assumed that bumblebees prefer to forage as close to their nest as possible. However, a review of the literature shows that there is little empirical evidence to support this assumption. An experiment aimed at investigating whether bumblebee workers forage close to their nests, and distances between three commercially produced bumblebee nests and an introduced forage patch were manipulated. The results presented here show that bumblebee workers significantly increased their use of a flower resource after their nests had been moved from within the resource to more than 100 m away.

Abstract

The three organic cropping systems Landvik (in Grimstad), Voll (at Ås) and Kvithamar (in Stjørdal) were established in 1993 on previously conventionally farmed soils of marine origin. The six-year crop rotation at Landvik was designed for an organic stockless farm producing cash crops. These crops were fertilized with composted organic household waste from the nearby community (maximum 100 kg N ha-1) and composted waste from the system itself. The rotation at Voll was designed for an arable farm withbeef production from suckling cows (0.9 animal units ha-1), and the rotation at Kvithamar was designed for a dairy cattle farm (1.0 animal unit ha-1). During the first six years of organic farming, the soil reserves of K were slightly depleted. The nutrient balance was –250 kg K ha-1 at Voll and –420 kg K ha-1 at Landvik, and the content of easily soluble K in the plough layer decreased at these sites. At Kvithamar, however, where the K balance for six years was –380 kg ha-1, no changes in soil content of K were recorded. For P, the six-year balance was positive at Landvik, where altogether 120 kg P ha-1 was supplied from composted household waste. The P balance was negative (-40 kg ha-1) at Voll and Kvithamar, and at Voll the content of easily soluble P in the plough layer was lower in 1999 than in 1993. In the study period, the yields were variable both within and between the systems. We have not identified any trends or variations in yields that might have been directly caused by changesin soil nutrient status or other soil quality components. At Voll and Kvithamar, however, the number of earthworm and the soil macroporosity increased from 1993 to 1999, with a concurrent slight increase in the yields of leys (Voll) and grain crops and swedes (Kvithamar). In the system at Landvik the yields of potatos and carrots were higher the first two than the last four years. At this site the soil structure was good, and the porosity and earthworm activity high, during the whole study period.

Abstract

At present there are nearly 20 000 milk producers in Norway, and approximately 10 per cent of them are members of the Norwegian Dairy Financial Recording (NDFR). The NDFR is an important basis for production and financial advice given by the dairies. There is a great interest among milk producers and advisors in comparing results from different farms to find out why some are doing well and some are doing not so well, and to learn from those doing well. Gross margin (GM) per litre of milk produced is the traditional indicator for efficiency. This data, as other data on milk production, indicate that there is a wide variation in gross margin per litre of milk between farms with seemingly similar conditions for producing milk. This is interpreted as a potential for improving the efficiency of many producers. However, for many reasons gross margin per litre of milk is not an ideal indicator. A new version of the NDFR contains more information, for instance information on fixed costs of roughages produced on the farm. It is hoped that the new version of the NDFR makes it a better tool for improving the profitability of milk production. In an ongoing project we try to use the NDFR to analyse who are doing well and why. We use a combination of Data Envelopment Analysis (DEA) and statistical analysis. For each farm we produce an efficiency index, and then we apply statistical methods to find factors that can explain the index. So far we have only very preliminary results. Management factors are important, but the NDFR data-base have very little information on management factors. It is planned to collect such data for a sample of farmers and include that in the study at a later stage.

Abstract

Areas near the Norwegian-Russian border are being strongly contaminated by heavy metal emissions from copper-nickel smelters in the Kola peninsula. The present report presents data for the four elements arsenic, chromium, cobalt, and selenium in vegetation sampled in eastern Finmark, obtained by neutron activation analysis. It is no doubt that the smelters in Nikel and Zapolyarny, constitute the main source of these elements in this area. Some chromium comes from local domestic sources. Still, however, the concentration of these elements in soil and vegetation are probably too low as such to represent any harm to the ecosystem.

Abstract

As more data have been amassed and interest in working with the ensuing data sets have grown, methods for organizing and examining the data have evolved. The need to work with these larger amounts of data has led to the development of ‘data mining’ methods and software. Data mining has a somewhat skewed reputation, and has often been characterised as ‘data dredging’ or ‘fishing expeditions’ . However, most of us must admit that such ‘expeditions’ or what one also could call hypothesis-generating approaches where we look for both likely and less likely associations, has occurred within our own research. In principal, generating promising associations is what data mining is all about. In this paper we have applied one of many commercial software available (Enterprise Miner, SAS) on a small dataset merged from a questionnaire data set and the national dairy cattle health and production records. We investigated for patterns separating organic dairy farmers from the conventional ones. The main framework of the data mining approach, some of the core modelling methods and the data mining results are briefly described and assessed.