Hopp til hovedinnholdet

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.

2019

To document

Abstract

Abstract: GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). Following a previous Long Database Report (Dengler et al. 2018, Phyto-coenologia 48, 331–347), we provide here the first update on content and functionality of GrassPlot. The current version (GrassPlot v. 2.00) contains a total of 190,673 plots of different grain sizes across 28,171 independent plots, with 4,654 nested-plot series including at least four grain sizes. The database has improved its content as well as its functionality, including addition and harmonization of header data (land use, information on nestedness, structure and ecology) and preparation of species composition data. Currently, GrassPlot data are intensively used for broad-scale analyses of different aspects of alpha and beta diversity in grassland ecosystems.

To document

Abstract

We report an observation of a flightless fledgling Lapland longspur (Calcarius lapponicus (Linnaeus, 1758)) at a long-term study site near Kangerlussuaq, Greenland, in late July 2018. Based on our observations of longspur nests at the site dating back to 1993, we estimate that the fledgling observed in 2018 may have originated from a nest initiated 12–37 d later than nesting in previous years. Onset of spring in 2018 was late, but comparable with other years in which longspur nests were observed a full calendar month earlier than in 2018. An analysis including multiple candidate predictor variables revealed a strong negative association between estimated longspur nest initiation dates and mean May temperature, as well as a weaker association with the length of the annual period of vegetation green up at the site. Given the limitations of our data, however, we are unable to assign causality to the 2018 observation, and cannot rule out other possibilities, such as that it may have resulted from a second clutch.

To document

Abstract

No abstract has been registered

Abstract

The extent of land lease is increasing in many countries, including Norway. This paper develops a von Thünen type model of optimal land plots to lease from a farm’s center. For a single farm setting, the optimality principle is that land is leased as long as the expected marginal value of leasing a tract of land is greater than or equal to the expected marginal costs of leasing the land. The single farm model setting captures land lease at the extensive margin, i.e., under absence of competition for leasing land. Land lease at the intensive margin, i.e., when there is competition for leasing farm fields, is more interesting. We distinguish between two cases. In the first case, continued farm operations do not depend on being able to lease more land. Then we show that optimal land lease results when the expected profits for each farm of leasing its least profitable field is equal among farms competing for the same farm field. This also corresponds to an economically efficient allocation of leased land. Our second case at the intensive margin is more complicated. Here, farm survival depends on attracting acreage of leased land to allow for investment in cost saving technology. We show that the resulting allocation of leased land corresponds to the solution of a game involving bidding for land in order to prevent other farmers from getting land, which in turn leads to farmer exit and therefore increases the future supply of land available at the land lease market. In the first round of the game, winners of the land lease auction pay more for the leased land than they would have done in the absence of preventive bidding. The model framework is applicable for other settings where locking out competitors are parts of agents’ strategy space.