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.
2023
Abstract
Wetlands are simply areas that are fully or partially saturated with water. Not much attention has been given to wetlands in the past, due to the unawareness of their value to the general public. However, wetlands have numerous hydrological, ecological, and social values. They play an important role in interactions among soil, water, plants, and animals. The rich biodiversity in the vicinity of wetlands makes them invaluable. Therefore, the conservation of wetlands is highly important in today’s world. Many anthropogenic activities damage wetlands. Climate change has adversely impacted wetlands and their biodiversity. The shrinking of wetland areas and reducing wetland water levels can therefore be frequently seen. However, the opposite can be seen during stormy seasons. Since wetlands have permissible water levels, the prediction of wetland water levels is important. Flooding and many other severe environmental damage can happen when these water levels are exceeded. Therefore, the prediction of wetland water level is an important task to identify potential environmental damage. However, the monitoring of water levels in wetlands all over the world has been limited due to many difficulties. A Scopus-based search and a bibliometric analysis showcased the limited research work that has been carried out in the prediction of wetland water level using machine-learning techniques. Therefore, there is a clear need to assess what is available in the literature and then present it in a comprehensive review. Therefore, this review paper focuses on the state of the art of water-level prediction techniques of wetlands using machine-learning techniques. Nonlinear climatic parameters such as precipitation, evaporation, and inflows are some of the main factors deciding water levels; therefore, identifying the relationships between these parameters is complex. Therefore, machine-learning techniques are widely used to present nonlinear relationships and to predict water levels. The state-of-the-art literature summarizes that artificial neural networks (ANNs) are some of the most effective tools in wetland water-level prediction. This review can be effectively used in any future research work on wetland water-level prediction.
Authors
Anita SønstebyAbstract
No abstract has been registered
Authors
Astor Toraño-Caicoya Marta Vergarechea Clemens Blattert Julian Klein Kyle Eyvindson Daniel Burgas Riera Tord Snäll Mikko Mönkkönen Rasmus Astrup Fulvio Di Fulvio Niklas Forsell Markus Hartikainen Enno Uhl Werner Poschenrieder Clara Antón FernándezAbstract
Forests provide a range of vital services to society and are critical habitats for biodiversity, holding inherent multifunctionality. While traditionally viewed as a byproduct of production-focused forestry, today's forest ecosystem services and biodiversity (FESB) play an essential role in several sectoral policies’ needs. Achieving policy objectives requires careful management considering the interplay of services, influenced by regional aspects and climate. Here, we examined the multifunctionality gap caused by these factors through simulation of forest management and multi-objective optimization methods across different regions - Finland, Norway, Sweden and Germany (Bavaria). To accomplish this, we tested diverse management regimes (productivity-oriented silviculture, several continuous cover forestry regimes and set asides), two climate scenarios (current and RCP 4.5) and three policy strategies (National Forest, Biodiversity and Bioeconomy Strategies). For each combination we calculated a multifunctionality metric at the landscape scale based on 5 FESB classes (biodiversity conservation, bioenergy, climate regulation, wood, water and recreation). In Germany and Norway, maximum multifunctionality was achieved by increasing the proportion of set-asides and proportionally decreasing the rest of management regimes. In Finland, maximum MF would instead require that policies address greater diversity in management, while in Sweden, the pattern was slightly different but similar to Finland. Regarding the climate scenarios, we observed that only for Sweden the difference in the provision of FESB was significant. Finally, the highest overall potential multifunctionality was observed for Sweden (National Forest scenario, with a value of 0.94 for the normalized multifunctionality metric), followed by Germany (National Forest scenario, 0.83), Finland (Bioeconomy scenario, 0.81) and Norway (National Forest scenario, 0.71). The results highlight the challenges of maximizing multifunctionality and underscore the significant influence of country-specific policies and climate change on forest management. To achieve the highest multifunctionality, strategies must be tailored to specific national landscapes, acknowledging both synergistic and conflicting FESB.
Authors
Astor Toraño Caicoya Marta Vergarechea Clemens Blattert Julian Klein Kyle Eyvindson Daniel Burgas Riera Tord Snäll Mikko Mönkkönen Rasmus Astrup Fulvio Di Fulvio Niklas Forsell Markus Hartikainen Enno Uhl Werner Poschenrieder Clara Antón FernándezAbstract
Forests provide a range of vital services to society and are critical habitats for biodiversity, holding inherent multifunctionality. While traditionally viewed as a byproduct of production-focused forestry, today's forest ecosystem services and biodiversity (FESB) play an essential role in several sectoral policies’ needs. Achieving policy objectives requires careful management considering the interplay of services, influenced by regional aspects and climate. Here, we examined the multifunctionality gap caused by these factors through simulation of forest management and multi-objective optimization methods across different regions - Finland, Norway, Sweden and Germany (Bavaria). To accomplish this, we tested diverse management regimes (productivity-oriented silviculture, several continuous cover forestry regimes and set asides), two climate scenarios (current and RCP 4.5) and three policy strategies (National Forest, Biodiversity and Bioeconomy Strategies). For each combination we calculated a multifunctionality metric at the landscape scale based on 5 FESB classes (biodiversity conservation, bioenergy, climate regulation, wood, water and recreation). In Germany and Norway, maximum multifunctionality was achieved by increasing the proportion of set-asides and proportionally decreasing the rest of management regimes. In Finland, maximum MF would instead require that policies address greater diversity in management, while in Sweden, the pattern was slightly different but similar to Finland. Regarding the climate scenarios, we observed that only for Sweden the difference in the provision of FESB was significant. Finally, the highest overall potential multifunctionality was observed for Sweden (National Forest scenario, with a value of 0.94 for the normalized multifunctionality metric), followed by Germany (National Forest scenario, 0.83), Finland (Bioeconomy scenario, 0.81) and Norway (National Forest scenario, 0.71). The results highlight the challenges of maximizing multifunctionality and underscore the significant influence of country-specific policies and climate change on forest management. To achieve the highest multifunctionality, strategies must be tailored to specific national landscapes, acknowledging both synergistic and conflicting FESB.
Authors
Adam Eindride Naas Rune Halvorsen Peter Horvath Anders Kvalvåg Wollan Harald Bratli Katrine Marie Brynildsrud Eirik Aasmo Finne Lasse Torben Keetz Eva Lieungh Christine Olson Trond Simensen Olav Skarpaas Hilde Tandstad Michal Torma Espen Sommer Værland Anders BrynAbstract
Questions Field-based ecosystem mapping is prone to observer bias, typically resulting in a mismatch between maps made by different mappers, that is, inconsistency. Experimental studies testing the influence of site, mapping scale, and differences in experience level on inconsistency in field-based ecosystem mapping are lacking. Here, we study how inconsistencies in field-based ecosystem maps depend on these factors. Location Iškoras and Guollemuorsuolu, northeastern Norway, and Landsvik and Lygra, western Norway. Methods In a balanced experiment, four sites were field-mapped wall-to-wall to scales 1:5000 and 1:20,000 by 12 mappers, representing three experience levels. Thematic inconsistency was calculated by overlay analysis of map pairs from the same site, mapped to the same scale. We tested for significant differences between sites, scales, and experience-level groups. Principal components analysis was used in an analysis of additional map inconsistencies and their relationships with site, scale and differences in experience level and time consumption were analysed with redundancy analysis. Results On average, thematic inconsistency was 51%. The most important predictor for thematic inconsistency, and for all map inconsistencies, was site. Scale and its interaction with site predicted map inconsistencies, but only the latter were important for thematic inconsistency. The only experience-level group that differed significantly from the mean thematic inconsistency was that of the most experienced mappers, with nine percentage points. Experience had no significant effect on map inconsistency as a whole. Conclusion Thematic inconsistency was high for all but the dominant thematic units, with potentially adverse consequences for mapping ecosystems that are fragmented or have low coverage. Interactions between site and mapping system properties are considered the main reasons why no relationships between scale and thematic inconsistency were observed. More controlled experiments are needed to quantify the effect of other factors on inconsistency in field-based mapping.
Abstract
No abstract has been registered
Authors
Karin Juul Hesselsøe Anne friederike Borchert Karin Normann Trygve S. Aamlid Pia Heltoft ThomsenAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Svenja B. KroegerAbstract
No abstract has been registered
Abstract
No abstract has been registered