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NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.

2024

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Soil erosion is a significant environmental issue in most mountainous areas and is further exacerbated due to ongoing climatic changes and anthropogenic activities. Soil erosion not only triggers natural disasters like landslides but also degrades the fertile topsoil layers. Therefore, modeling and evaluation of soil erosion in mountainous areas and river basins are highly important. The Uma Oya River Basin (UORB), Sri Lanka is an area with rich biodiversity and is also important for agricultural production. Moreover, this area is frequently discussed due to the ongoing developments of the Uma Oya Project. This paper presents a comprehensive evaluation of soil erosion in the UORB and results are compared for two decades from 2000 to 2020. The Revised Universal Soil Loss Equation (RUSLE) was used to determine the annual soil erosion rates. In addition, the spatial-temporal variation of land use and land cover was assessed in the UORB. Results revealed that extreme soil erosion scenarios occur when forests and other vegetation lands are converted to agricultural lands and farmlands. We found that soil loss in the area largely happened due to steep slopes, reduction of vegetation and forest covers, and growth of cultivation lands. Erosion-prone areas in the river basin are identified and conservation strategies are discussed. In addition, the impact of the ongoing climate change on the UORB is highlighted.

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This study evaluates the rainfall erosivity (RE) and erosivity density (ED) over the Kelani River basin, Sri Lanka for a period of 31 years (1990–2020). The river basin is well known for its annual floods during the southwestern monsoon season and severe erosion including landslides can be observed. The catchment was analyzed for its RE using the Wischmeier and Smith algorithm and for its ED using Kinnel's algorithm. The monthly rainfall data spreading over the river basin were used to analyze the monthly, seasonal, and annual RE and ED. Interestingly, the annual RE showed a linear increasing trend line over 31 years, and a maximum value of 2,831.41 MJ mm ha−1 h−1 yr−1 was able to be observed in the year 2016. The RE peaks in May which is in the southwestern monsoon season. This reveals that the risk of soil erosion in the basin is high in the southwestern monsoon season. In addition, land use and land cover changes over the years have adversely impacted the erosion rates. Therefore, it is highly recommended to investigate soil erosion in-depth and then implement relevant regulations to conserve the soil layers upstream of the river basin.

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This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km2), Kandy (2.74 km2), and Badulla (10.41 km2), as having a “very low risk" of forest fire potential. Conversely, districts like Hambanthota (0.1 km2), Kaluthara (0.04 km2), and Kurunegala (0.2 km2) exhibit a “very high risk" of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a “medium risk" of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country.

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Soils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-based carbon markets and suggest potential strategies for climate change mitigation. Enhancing our understanding of SOC dynamics and adopting precise environmental predictors will contribute to the formulation of targeted soil management strategies and accelerate progress toward achieving climate goals.

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Aim of study: An adjuvant is a material that is added to a spray carrier to improve the application technology's efficiency but lacks phytosanitary qualities. Our objective was to determine the best option of combining fungicides and adjuvants to control soybean (Glycine max) leaf diseases in three cropping seasons. Area of study: The experiment was developed in the Campos Gerais region (PR - Brazil). Material and methods: The five treatments consisted of 1) control (without applying fungicides on soybean plants); 2) fungicide application on soybean plants without adjuvant; 3) fungicide with adjuvant based on mineral oil; 4) fungicide with adjuvant based on lecithin and 5) propionic acid and fungicide with 50% of the dose of adjuvant based on mineral oil + 50% of the dose of surfactant adjuvant based on lecithin and propionic acid. The analyzed variables were the physicochemical characteristics of the spray carrier, the incidence and severity of diseases, and the yield components. A completely randomized design was used to study the physicochemical characteristics of the carrier and in randomized blocks for the field experiment. We used five replicates per treatment. Main results: No foaming and mixing incompatibility of the spray carrier was observed in any treatment. The adjuvant based on lecithin and propionic acid further acidified the spray carrier and presented the same surface tension as mineral oil. The soybean plants that did not receive chemical treatment had a higher occurrence of diseases, which reduced the productive potential. Research highlights: Adding adjuvants to the spray carrier did not increase the performance of fungicides in controlling diseases and did not affect the yield components.

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The No-till system and organic fertilization combined can be a potential strategy to avoid nutrient leaching, as the soil structure plays a crucial role in retaining them. In this study, we evaluated the influence of different rates of a bio-fertilizer made of industrial organic waste (IOW) from a poultry slaughterhouse on the percolation and stocks of nitrate in disturbed and undisturbed soil samples collected from a subtropical no-till field in southern Brazil. In an incubation experiment, we performed a percolation experiment using lysimeters and simulated rainfall for 180 days and evaluated the remaining soil nitrate stock after the incubation period. We set up a completely randomized experiment with three replicates using four IOW rates (equivalent to 0, 2, 4, and 8 Mg ha−1) and two sample types: disturbed and undisturbed soils. Using the bio-fertilizer increased nitrate mineralization from 0.77 to 1.55 kg ha−1 day−1. Overall, the IOW application increased the amount of percolated nitrate, significantly influenced by the simulated rainfall (p < 0.01). The amount of water flushed through the lysimeters was significantly higher for the disturbed soils (p < 0.05, LSD test), suggesting that the loosened structure promoted a higher water flux. No differences were observed between undisturbed and disturbed samples for nitrate percolation, implying that the amount of nitrate in the liquid soil phase may be a more critical factor in determining nitrate leaching than the water flux. The disturbed samples presented significantly higher nitrate percolation with increasing IOW rates, regardless of precipitation. Stocks in the 0–5 cm depth were 6.6 kg ha−1 higher for undisturbed samples (p < 0.05, LSD test). This result suggests preserving the soil structure can significantly increase the nitrate stocks upon IOW application.

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Land-use change has driven soil carbon stock losses in ecosystems worldwide. Implementing agricultural crops and exploiting forest resources trigger the breakdown of soil aggregates, thus exposing organic matter to microbial decomposition and enhancing carbon dioxide emissions, especially in biomes more susceptible to climate extremes as in the tropical semiarid regions. This study was based on the hypothesis that the undisturbed soil from the dry forest (Caatinga biome under natural revegetation in Brazilian semiarid) would have an improvement in the mass of macroaggregates and recover more than 50% of the soil C stock within 10 years. Thus, a field experiment was conducted to investigate soils from the Caatinga biome under native vegetation, “cowpea cropping” for over 30 years, and soil under natural revegetation for over 10 years, after conventional soil cultivation of maize and cowpea, to determine soil and soil-aggregates carbon stocks and to estimate the recovery rate of these stocks. The proportional mass of aggregates of different sizes and the total stock of particulate organic carbon (POC) were also quantified. The results showed that soil under preserved native vegetation of dry forest Caatinga biome had higher total soil C stock (50.9 Mg ha−1) than that under cowpea cropping (23.2 Mg ha−1) and natural revegetation (45.1 Mg ha−1). The proportional mass of large macroaggregates was higher in soil under native vegetation for all depths. However, soil under cowpea cropping had lower C stocks in macroaggregates, and recovered roughly 63% of the original C stocks, while revegetation recovered 78% of the stock in 10 years. Although the conventional management system for cowpea monoculture aggravated losses in soil carbon stock by more than 50% of the original C stocks, dry forest under natural revegetation recovered 79% of this stock and almost 100% of POC stock in 10 years (~12 Mg ha−1). Furthermore, soil under undisturbed Caatinga dry forest achieved C stock levels equivalent to that of the global average range for semiarid tropical environments. The high recovery rate of C stock in forest soil under natural revegetation indicates the resilience potential of organisms responsible for structural protection of aggregates and the encapsulated soil organic matter content.