Publikasjoner
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.
2020
Forfattere
O. Janne KjønaasSammendrag
Det er ikke registrert sammendrag
Forfattere
Liz Veerman Karsten Kalbitz Per Gundersen O. Janne Kjønaas Filip Moldan Patrick Schleppi Emiel E. van Loon Jorien Schoorl Wim Wessel Albert TietemaSammendrag
Increased anthropogenic nitrogen (N) inputs can alter the N cycle and affect forest ecosystem functions. The impact of increased N deposition depends among others on the ultimate fate of N in plant and soil N pools. Short-term studies (3-18 months) have shown that the organic soil layer was the dominant sink for N. However, longer time scales are needed to investigate the long-term fate of N. Therefore, the soils of four experimental forest sites across Europe were re-sampled similar to 2 decades after labelling with(15)N. The sites covered a wide range of ambient N deposition varying from 13 to 58 kg N ha(-1)year(-1). To investigate the effects of different N loads on(15)N recovery, ambient N levels were experimentally increased or decreased. We hypothesized that: (1) the mineral soil would become the dominant(15)N sink after 2 decades, (2) long-term increased N deposition would lead to lower(15)N recovery levels in the soil and (3) variables related to C dynamics would have the largest impact on(15)N recovery in the soil. The results show that large amounts of the added(15)N remain in the soil after 2 decades and at 2 out of 4 sites the(15)N recovery levels are higher in the mineral soil than in the organic soil. The results show no clear responses of the isotopic signature to the changes in N deposition. Several environmental drivers are identified as controlling factors for long-term(15)N recovery. Most drivers that significantly contribute to(15)N recovery are strongly related to the soil organic matter (SOM) content. These findings are consistent with the idea that much of the added(15)N is immobilized in the SOM. In the organic soil layer, we identify C stock, thickness of the organic layer, N-status and mean annual temperature of the forest sites as most important controlling factors. In the mineral soil we identify C stock, C content, pH, moisture content, bulk density, temperature, precipitation and forest stand age as most important controlling factors. Overall, our results show that these temperate forests are capable of retaining long-term increased N inputs preferably when SOM availability is high and SOM turnover and N availability are low.
Sammendrag
Protected Areas (PAs) in Tanzania had been established originally for the goal of habitat, landscape and biodiversity conservation. However, human activities such as agricultural expansion and wood harvesting pose challenges to the conservation objectives. We monitored a decade of deforestation within 708 PAs and their unprotected buffer areas, analyzed deforestation by PA management regimes, and assessed connectivity among PAs. Data came from a Landsat based wall-to-wall forest to non-forest change map for the period 2002–2013, developed for the definition of Tanzania’s National Forest Reference Emissions Level (FREL). Deforestation data were extracted in a series of concentric bands that allow pairwise comparison and correlation analysis between the inside of PAs and the external buffer areas. Half of the PAs exhibit either no deforestation or significantly less deforestation than the unprotected buffer areas. A small proportion (10%; n = 71) are responsible for more than 90% of the total deforestation; but these few PAs represent more than 75% of the total area under protection. While about half of the PAs are connected to one or more other PAs, the remaining half, most of which are Forest Reserves, are isolated. Furthermore, deforestation inside isolated PAs is significantly correlated with deforestation in the unprotected buffer areas, suggesting pressure from land use outside PAs. Management regimes varied in reducing deforestation inside PA territories, but differences in protection status within a management regime are also large. Deforestation as percentages of land area and forested areas of PAs was largest for Forest Reserves and Game Controlled areas, while most National Parks, Nature Reserves and Forest Plantations generally retained large proportions of their forest cover. Areas of immediate management concern include the few PAs with a disproportionately large contribution to the total deforestation, and the sizeable number of PAs being isolated. Future protection should account for landscapes outside protected areas, engage local communities and establish new PAs or corridors such as village-managed forest areas.
Forfattere
Fatima Heinicke Xiangfu Zhong Karola Manuela Zucknick Johannes Breidenbach Arvind Yegambaram Meenakshi Sundaram Siri Tennebø Flåm Magnus Leithaug Marianne Dalland Simon Rayner Benedicte Alexandra Lie Gregor GilfillanSammendrag
High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits.
Forfattere
Steen Magnussen Ronald E. McRoberts Johannes Breidenbach Thomas Nord-Larsen Göran Ståhl Lutz Fehrmann Sebastian SchnellSammendrag
Background: Large area forest inventories often use regular grids (with a single random start) of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations. A design-unbiased estimator of variance does not exist for this design. Oftentimes, a quasi-default estimator applicable to simple random sampling (SRS) is used, even if it carries with it the likely risk of overestimating the variance by a practically important margin. To better exploit the precision of systematic sampling we assess the performance of five estimators of variance, including the quasi default. In this study, simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear trends. We compared the results obtained with the SRS, Matérn’s, successive difference replication, Ripley’s, and D’Orazio’s variance estimators. Results: The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated, and in all study settings consistently closer to the target design variance than the estimator for SRS. The latter always produced the greatest overestimation. In populations with a near zero spatial autocorrelation, all estimators, performed equally, and delivered estimates close to the actual design variance. Conclusion: Without a linear trend, the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark; yet in terms of the least average absolute deviation, Matérn’s estimator held a narrow lead. With a strong or moderate linear trend, Matérn’s estimator is choice. In large populations, and a low sampling intensity, the performance of the investigated estimators becomes more similar. Keywords: Spatial autocorrelation, Linear trend, Model based, Design biased, Matérn variance, Successive difference replication variance, Geary contiguity coefficient, Random site effects
Forfattere
Johannes BreidenbachSammendrag
Det er ikke registrert sammendrag
Forfattere
Johannes BreidenbachSammendrag
Det er ikke registrert sammendrag
Sammendrag
Forest inventories provide predictions of stand means on a routine basis from models with auxiliary variables from remote sensing as predictors and response variables from field data. Many forest inventory sampling designs do not afford a direct estimation of the among-stand variance. As consequence, the confidence interval for a model-based prediction of a stand mean is typically too narrow. We propose a new method to compute (from empirical regression residuals) an among-stand variance under sample designs that stratify sample selections by an auxiliary variable, but otherwise do not allow a direct estimation of this variance. We test the method in simulated sampling from a complex artificial population with an age class structure. Two sampling designs are used (one-per-stratum, and quasi systematic), neither recognize stands. Among-stand estimates of variance obtained with the proposed method underestimated the actual variance by 30-50%, yet 95% confidence intervals for a stand mean achieved a coverage that was either slightly better or at par with the coverage achieved with empirical linear best unbiased estimates obtained under less efficient two-stage designs.
Forfattere
Arne SteffenremSammendrag
Det er ikke registrert sammendrag
Forfattere
Arne SteffenremSammendrag
Det er ikke registrert sammendrag