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.
2020
Abstract
Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves
Abstract
No abstract has been registered
Editors
Ragnar Våga PedersenAbstract
Brochure in English about NIBIO. NIBIO contributes to food security and safety, sustainable resource management, innovation and value creation through research and knowledge production. Multi-disciplinary and integrated activities Science-policy-stakeholder interactions
Authors
Lorène Julia Marchand Inge Dox Jožica Gričar Peter Prislan Sebastien Leys Jan Van den Bulcke Patrick Fonti Holger Lange Erik Matthysen Josep Peñuelas Paolo Zuccarini Matteo CampioliAbstract
No abstract has been registered
Authors
Habtamu AlemAbstract
The study aimed to extend the static concepts of multiproduct technical efficiency and determinants into a dynamic setting within the input distance function framework. The existing literature in performance analysis of the dairy farms in Norway based on static modelling and thus ignores the inter-temporal nature of production decisions. The empirical application focused on the farm-level analysis of the Norwegian dairy sector for 2000- 2018. The dynamic efficiency allows analysing the performance of dairy farms in regards of inter-temporal optimization of the investment behaviour. The analysis shows that the static model efficiency study in the previous studies underestimate the performance of the dairy farms. The marginal effects experience positively correlated with dairy farm technical efficiency whereas copped subsidy and asset debt ratio negatively correlated to the performance of the dairy farm.
Authors
Steen Magnussen Ronald E. McRoberts Johannes Breidenbach Thomas Nord-Larsen Göran Ståhl Lutz Fehrmann Sebastian SchnellAbstract
No abstract has been registered
Authors
Barbara Łaska-Zieja Damian Marcinkowski Wojciech Golimowski Gniewko Niedbała Ewelina WojciechowskaAbstract
No abstract has been registered
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No abstract has been registered
Abstract
Agricultural practices to improve yields in small‐scale farms in Africa usually focus on improving growing conditions for the crops by applying fertilizers, irrigation, and/or pesticides. This may, however, have limited effect on yield if the availability of effective pollinators is too low. In this study, we established an experiment to test whether soil fertility, soil moisture, and/or pollination was limiting watermelon (Citrullus lanatus) yields in Northern Tanzania. We subjected the experimental field to common farming practices while we treated selected plants with extrafertilizer applications, increased irrigation and/or extra pollination in a three‐way factorial experiment. One week before harvest, we assessed yield from each plant, quantified as the number of mature fruits and their weights. We also assessed fruit shape since this may affect the market price. For the first fruit ripening on each plant, we also assessed sugar content (brix) and flesh color as measures of fruit quality for human consumption. Extra pollination significantly increased the probability of a plant producing a second fruit of a size the farmer could sell at the market, and also the fruit sugar content, whereas additional fertilizer applications or increased irrigation did not improve yields. In addition, we did not find significant effects of increased fertilizer or watering on fruit sugar, weight, or color. We concluded that, insufficient pollination is limiting watermelon yields in our experiment and we suggest that this may be a common situation in sub‐Saharan Africa. It is therefore critically important that small‐scale farmers understand the role of pollinators and understand their importance for agricultural production. Agricultural policies to improve yields in developing countries should therefore also include measures to improve pollination services by giving education and advisory services to farmers on how to develop pollinator‐friendly habitats in agricultural landscapes.
Authors
Cecilia E. Müller Astrid JohansenAbstract
No abstract has been registered