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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.

2023

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Soil health assessments that integrate physical, chemical and biological indicators help the evaluation of soil functioning, provide a framework for monitoring soil degradation, guide land management activities and secure the delivery of soil ecosystem services. In this study, we assessed soil health by soil texture class on arable land in Southeast Norway and mid-Norway and between grassland and arable land in mid-Norway. We used descriptive statistics and the Welch t-test with unequal variance and Bonferroni corrections to compare a physical soil indicator (bulk density) and chemical indicators (organic matter, P-AL, K-AL, Ca-AL, Mg-AL, Na-AL and pH). We developed scoring curves from cumulative normal distribution functions on regional soil data for various soil indicators where climate, soil texture class and land use were considered. Our results show that for certain soil texture classes, average soil indicator values differed between pedo-climatic zones on arable land, but for others the difference was not significant. The variability between the pedo-climatic zones for these can be neglected, but for the ones that differ, the variability is important to consider when assessing soil health. Similarly, this was the case when comparing land use (grassland and arable land) for most soil indicators in mid-Norway. This finding illustrates the importance of addressing unique local conditions in soil health assessments. We propose aggregating similar soil texture classes where no differences are apparent when developing scoring curves. The sub-optimal levels of plant available nutrients (P-AL and K-AL) found in the soil in both pedo-climatic zones highlights the importance of suitable threshold values for targeted soil ecosystem services to ensure soil health and sustainable agricultural production. We also recommend prioritizing the most relevant soil ecosystem services to limit the number of soil indicators that need monitoring.

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Greenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.

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Agroforestry practices improve soil health which in turn improves crop nutrient concentrations and quality. This study examined how the agroforestry tree Gliricidia sepium intercropped with soybean, groundnuts, or maize affects crop nutrient compositions. The study was conducted in five Zambian chiefdoms for three crop-growing seasons (2019–2022) on 13 farmer-led demonstration trial sites. Seven treatments were tested that included maize, soybean, and groundnut plots with and without Gliricidia interventions. Grain samples were analyzed for crop nutrient contents using standard laboratory methods. Results showed that the treatments significantly (P < 0.05) improved maize nutritional properties except for crude fiber, total carbohydrate, and metabolizable energy. G. sepium intercropping with maize and soybean decreased the antinutritional contents and displayed better functional qualities. All elemental mineral components (except potassium, calcium, and sodium) were higher in the Gliricidia + maize intercrop than in the control treatment. The Gliricidia+soybean intercrop had lower mean mineral concentrations than the control (soybean only) except for Mg, Cu, and Zn. The Giliricidia+groundnut intercrop significantly increased groundnut mineral components except for Nitrogen, Phosphorus, Potassium, and Iron. It can be concluded that G. sepium intercropped with maize, soybean, and groundnuts significantly improved the crops’ nutritional quality.

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Introduction: Conventional rice production techniques are less economical and more vulnerable to sustainable utilization of farm resources as well as significantly contributed GHGs to atmosphere. Methods: In order to assess the best rice production system for coastal areas, six rice production techniques were evaluated, including SRI-AWD (system of rice intensification with alternate wetting and drying (AWD)), DSR-CF (direct seeded rice with continuous flooding (CF)), DSR-AWD (direct seeded rice with AWD), TPR-CF (transplanted rice with CF), TPR-AWD (transplanted rice with AWD), and FPR-CF (farmer practice with CF). The performance of these technologies was assessed using indicators such as rice productivity, energy balance, GWP (global warming potential), soil health indicators, and profitability. Finally, using these indicators, a climate smartness index (CSI) was calculated. Results and discussion: Rice grown with SRI-AWD method had 54.8 % higher CSI over FPR-CF, and also give 24.5 to 28.3% higher CSI for DSR and TPR as well. There evaluations based on the climate smartness index can provide cleaner and more sustainable rice production and can be used as guiding principle for policy makers.

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På oppdrag fra vannområdet Bunnefjorden med Årungen- og Gjersjøvassdraget (PURA) er den empiriske modellen Agricat 2 brukt til å beregne potensialet for erosjon og fosforavrenning fra jordbruksarealer i 16 tiltaksområder, ved faktisk drift i 2022. Arealfordelingen av faktisk drift (vekst, jordarbeiding og miljøtiltak) i 2022 har framkommet av registerdata fra Landbruksdirektoratet og føringer/informasjon fra Follo Landbrukskontor, og er fordelt på de dyrka arealene etter bestemte rutiner i modellen. Arealfordelingsrutinen i modellen ga følgende utbredelse av kombinasjon vekst/jordarbeiding i vannområdet for 2022: 47 % stubb (jordarbeiding vår eller direktesåing), 10 % gras, 11 % vårkorn med høstpløying, 14 % høstkorn med høstpløying, 15 % høstharving til vår- og høstkorn samt frukt og bær, og 3 % poteter og grønnsaker. Arealfordelingen varierte mellom tiltaksområder. Eksisterende grasdekte kantsoner og fangdammer inngikk også i beregningene. Jord- og fosfortap i vannområdet PURA i 2022 ble beregnet til henholdsvis 3,5 kilotonn SS og 6,0 tonn TP. For individuelle tiltaksområder varierte jordtapet fra nær 0 til 1,6 kilotonn, og fosfortap fra nær 0 til 2,8 tonn. Forskjeller i drift bidro til å forklare forskjellene mellom tiltaksområder.