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.
2022
Abstract
Using periodic measurements from permanent plots in non-thinned and thinned Norway spruce (Picea abies (L.) H. Karst.) stands in Norway, individual-tree growth models were developed to predict annual diameter increment, height increment, and height to crown base increment. Based on long-term data across a range of thinning regimes and stand conditions, alternative approaches for modeling response to treatment were assessed. Dynamic thinning response functions in the form of multiplicative modifiers that predict no effect at the time of thinning, a rapid increase followed by an early maximum before the effect gradually declines to zero could not be fitted to initially derived baseline models without thinning related predictors. However, alternative approaches were used and found to perform well. Specifically, indicator variables representing varying time periods after thinning were statistically significant and behaved in a robust manner as well as consistent with general expectations. In addition, they improved overall prediction accuracy when incorporated as fixed effects into the baseline models for diameter and height to crown base increment. Further, more simply, including exponentially decreasing multiplicative thinning response functions improved prediction accuracy for height increment and height to crown base increment. Irrespective of studied attribute and modelling approach, improvement in performance of these extended models was relatively limited when compared to the corresponding baseline models and more pronounced in trees from thinned stands. We conclude that the largely varying and often multi-year measurement intervals of the periodic data used in this study likely prevented the development of more sophisticated thinning response functions. However, based on the evaluation of the final models’ overall performance such complex response functions may not to be necessary to reliably predict individual tree growth after thinning for certain conditions or species, which should be further considered in future analyses of similar nature.
Authors
Marta Vergarechea Rasmus Astrup Carolin Fischer Knut Øistad Clemens Blattert Markus Hartikainen Kyle Eyvindson Fulvio Di Fulvio Nicklas Forsell Daniel Burgas Astor Toraño-Caicoya Mikko Mönkkönen Clara Antón FernándezAbstract
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving mitigation targets and at the same time meet nationally determined targets for other FES. Using data from the Norwegian national forest inventory (NFI) we simulated the development of Norwegian forests under different management regimes and defined different forest policy scenarios, according to the most relevant forest policies in Norway: national forest policy (NFS), biodiversity policy (BIOS), and bioeconomy policy (BIES). Finally, through multi-objective optimization, we identified the combination of management regimes matching best with each policy scenario. The results for all scenarios indicated that Norway will be able to satisfy wood demands of up to 17 million m3 in 2093. However, the policy objectives for FES under each scenario caused substantial differences in terms of the management regimes selected. We observed that BIES and NFS resulted in very similar forest management programs in Norway, with a dominance of extensive management regimes. In BIOS there was an increase of set aside areas and continuous cover forestry, which made it more compatible with biodiversity indicators. We also found multiple synergies and trade-offs between the FES, likely influenced by the definition of the policy targets at the national scale.
Abstract
No abstract has been registered
Abstract
1. Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. We describe ecochange as an R-package that integrates spatial analyses with a monitoring workflow for computing routines necessary for biodiversity monitoring. 2. The ecochange comprises three modules for data integration, statistical analysis and graphics. The first module currently downloads and integrates diverse remote sensing products belonging to the essential biodiversity class of structure. The module for statistical analysis calculates RasterStack ecosystem-change representations across areas of interest; this module also allows focusing on species habitats while deriving changes in a variety of indicators, including ecosystem areas, conditional entropy and fractal dimension indices. The graphics module produces level and bar plots that ease the development of indicator reports. 3. Its functionality is described with an example workflow to calculate ecosystem-class areas and conditional entropy across an area of interest contained in the package documentation. 4. We conclude that ecochange features procedures necessary to derive ecosystem structure indicators integrating the retrieval of spatially explicit data with the use of workflows to calculate/visualize biodiversity indicators at the national/regional scales.
Abstract
To meet international and national commitments to decrease emissions of fossil fuels, cities around the world must obtain information on their historical levels of emissions, identifying hotspots that require special attention. Direct atmospheric measurements of pollution sources are almost impossible to obtain retrospectively. However, tree rings serve as an archive of environmental information for reconstructing the temporal and spatial distribution of fossil-fuel emissions in urban areas. Here, we present a novel methodology to reconstruct the spatial and temporal contribution of fossil-fuel CO2 concentration ([CO2F]) in the urban area of Medellin, Colombia. We used a combination of dendrochronological analyses, radiocarbon measurements, and statistical modeling. We obtained annual maps of [CO2F] from 1977 to 2018 that describe changes in its spatial distribution over time. Our method was successful at identifying hotspots of emissions around industrial areas, and areas with high traffic density. It also identified temporal trends that may be related to socioeconomic and technological factors. We observed an important increase in [CO2F] during the last decade, which suggests that efforts of city officials to reduce traffic and emissions did not have a significant impact on the contribution of fossil fuels to local air. The method presented here could be of significant value for city planners and environmental officials from other urban areas around the world. It allows identifying hotspots of fossil fuels emissions, evaluating the impact of previous environmental policies, and planning new interventions to reduce emissions.
Abstract
No abstract has been registered
Abstract
There is debate on which tree species can sustain forest ecosystem services in a drier and warmer future. In Europe, the use of non-native timber species, such as Douglas fir (Pseudotsuga menziesii [Mirb.] Franco), is suggested as a solution to mitigate climate change impacts because of their high growth resilience to drought. However, the biogeographical, climatic and ecological limits for widely planted timber species still need to be defined. Here, we study the growth response to climate variables and drought of four Douglas fir plantations in northern Spain subjected to contrasting climate conditions. Further, we measure wood density in one of the sites to obtain a better understanding of growth responses to climate. Correlative analyses and simulations based on the Vaganov–Shaskin process-based model confirm that growth of Douglas fir is constrained by warm and dry conditions during summer and early autumn, particularly in the driest study site. Minimum wood density increased in response to dry spring conditions. Therefore, planting Douglas fir in sites with a marked summer drought will result in reduced growth but a dense earlywood. Stands inhabiting dry sites are vulnerable to late-summer drought stress and can act as “sentinel plantations”, delineating the tolerance climate limits of timber species.
Abstract
The British forestry sector lacks reliable dynamic growth models for stands of improved Sitka spruce, the most important commercial forest type in Great Britain. The aim of this study is to fill this gap by trialling a new modelling framework and to lay the foundations of a future dynamic growth simulator for that forest type. First, we present single tree diameter and height increment models that are climate sensitive and include explicit competition effects. The predictions from the increment models are pooled to project diameter and height at a given age. These projections are then used as inputs to an integrated taper model from which stochastic tree volume predictions are obtained. Retrospective data from over 1400 trees collected in two extensive genetic trials in Scotland and Wales were used for the purposes of this study. Diameter increment and height increment predictions were highly accurate and diameter and height projections proved consistent. The predicted volume at the time of harvesting also exhibited a high degree of accuracy, which shows the robustness of our approach. Further data will be needed in the future to recalibrate the present models and extend their range of validity to the whole of Great Britain.
Abstract
Lack of national soil property maps limits the studies of soil moisture (SM) dynamics in Norway. One alternative is to apply the global soil data as input for macro-scale hydrological modelling, but the quality of these data is still unknown. The objectives of this study are 1) to evaluate two recent global soil databases (Wise30sec and SoilGrids) in comparison with data from local soil profiles; 2) to evaluate which database supports better model performance in terms of river discharge and SM for three macro-scale catchments in Norway and 3) to suggest criteria for the selection of soil data for models with different complexity. The global soil databases were evaluated in three steps: 1) the global soil data are compared directly with the Norwegian forest soil profiles; 2) the simulated discharge based on the two global soil databases is compared with observations and 3) the simulated SM is compared with three global SM products. Two hydrological models were applied to simulate discharge and SM: the Soil and Water Integrated Model (SWIM) and the Variable Infiltration Capacity (VIC) model. The comparison with data from local soil profiles shows that SoilGrids has smaller mean errors than Wise30sec, especially for upper soil layers, but both soil databases have large root mean squared errors and poor correlations. SWIM generally performs better in terms of discharge using SoilGrids than using Wise30sec and the simulated SM has higher correlations with the SM products. In contrast, the VIC model is less sensitive to soil input data and the simulated SM using Wise30sec is higher correlated with the SM products than using SoilGrids. Based on the results, we conclude that the global soil databases can provide reasonable soil property information at coarse resolutions and large areas. The selection of soil input data should depend on the characteristics of both models and study areas.
Abstract
No abstract has been registered