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.
2021
Abstract
No abstract has been registered
Authors
Cerena J. Brewen John-Pascal Berrill Martin W. Ritchie Kevin Boston Christa M. Dagley Bobette Jones Michelle Coppoletta Coye L. BurnettAbstract
Quaking aspen (Populus tremuloides) is a valued, minor component on northeastern California landscapes. It provides a wide range of ecosystem services and has been in decline throughout the region for the last century. This decline may be explained partially by the lack of fire on the landscape due to heavier fire suppression, as aspen benefit from fire that eliminates conifer competition and stimulates reproduction through root suckering. However, there is little known about how aspen stand area changes in response to overlapping fire. Our study area in northeastern California on the Lassen, Modoc and Plumas National Forests has experienced recent large mixed-severity wildfires where aspen was present, providing an opportunity to study the re-introduction of fire. We observed two time periods; a 52-year absence of fire from 1941 to 1993 preceding a 24-year period of wildfire activity from 1993 to 2017. We utilized aerial photos and satellite imagery to delineate aspen stands and assess conifer cover percent. We chose aspen stands in areas where wildfires overlapped (twice-burned), where only a single wildfire burned, and areas that did not burn within the recent 24-year period. We observed these same stands within the first period of fire exclusion for comparison (i.e., 1941–1993). In the absence of fire, all aspen stand areas declined and all stands experienced increases in conifer composition. After wildfire, stands that burned experienced a release from conifer competition and increased in stand area. Stands that burned twice or at high severity experienced a larger removal of conifer competition than stands that burned once at low severity, promoting expansion of aspen stand area. Stands with less edge:area ratio also expanded in area more with fire present. Across both time periods, stand movement, where aspen stand footprints were mostly in new areas compared to footprints of previous years, was highest in smaller stands. In the fire exclusion period, smaller stands exhibited greater loss of area and changes in location (movement) than in the return of fire period, highlighting their vulnerability to loss via succession to conifers in the absence of disturbances that provide adequate growing space for aspen over time.
Authors
Puchun Niu Angela Dagmar Schwarm Helge Bonesmo Alemayehu Kidane Bente Aspeholen Åby Tonje Marie Storlien Michael Kreuzer Maria Clementina Alvarez Flores Jon Kristian Sommerseth Egil PrestløkkenAbstract
Simple Summary: Many techniques exist to quantify enteric methane (CH4) emissions from dairy cows. Since measurement on the entire national cow populations is not possible, it is necessary to use estimates for national inventory reporting. This study aimed to develop (1) a basic equation of enteric CH4 emissions from individual animals based on feed intake and nutrient contents of the diet, and (2) to update the operational way of calculation used in the Norwegian National Inventory Report based on milk yield and concentrate share of the diet. An international database containing recently published data was used for this updating process. By this the accuracy of the CH4 production estimates included in the national inventory was improved. Abstract: The aim of this study was to develop a basic model to predict enteric methane emission from dairy cows and to update operational calculations for the national inventory in Norway. Development of basic models utilized information that is available only from feeding experiments. Basic models were developed using a database with 63 treatment means from 19 studies and were evaluated against an external database (n = 36, from 10 studies) along with other extant models. In total, the basic model database included 99 treatment means from 29 studies with records for enteric CH4 production (MJ/day), dry matter intake (DMI) and dietary nutrient composition. When evaluated by low root mean square prediction errors and high concordance correlation coefficients, the developed basic models that included DMI, dietary concentrations of fatty acids and neutral detergent fiber performed slightly better in predicting CH4 emissions than extant models. In order to propose country-specific values for the CH4 conversion factor Ym (% of gross energy intake partitioned into CH4 ) and thus to be able to carry out the national inventory for Norway, the existing operational model was updated for the prediction of Ym over a wide range of feeding situations. A simulated operational database containing CH4 production (predicted by the basic model), feed intake and composition, Ym and gross energy intake (GEI), in addition to the predictor variables energy corrected milk yield and dietary concentrate share were used to develop an operational model. Input values of Ym were updated based on the results from the basic models. The predicted Ym ranged from 6.22 to 6.72%. In conclusion, the prediction accuracy of CH4 production from dairy cows was improved with the help of newly published data, which enabled an update of the operational model for calculating the national inventory of CH4 in Norway.
Authors
Sophie Mentzel Merete Grung Knut-Erik Tollefsen Marianne Stenrød Roger Holten S. Jannicke MoeAbstract
Future weather patterns are expected to result in increased precipitation and temperature, in Northern Europe. These changes can potentially cause an increase in plant disease and insect pests which will alter agricultural practice amongst other things the used crop types and application patterns of pesticides. We use a Bayesian network to explore a probabilistic risk assessment approach to better account for variabilities and magnitudes of pesticide exposure to the aquatic ecosystem. As Bayesian networks link selected input and output variables from various models and other information sources, they can serve as meta-models. In this study, we are using a pesticide fate and transport models (e.g. WISPE) with specific environmental factors such as soil and site parameters together with chemical properties and climate scenarios that are linked to a representative Norwegian study area. The derived exposure of pesticide of the study area is integrated in the Bayesian network model to estimate the risk to the aquatic ecosystem also integrating an effect distribution derived from toxicity test. This Bayesian network model will allow to incorporate climate predictions into ecological risk assessment.
Abstract
No abstract has been registered
Authors
Chen Wu Cecilia Deng Elena Hilario Nick W. Albert Declan Lafferty Ella R. P. Grierson Blue J. Plunkett Caitlin Elborough Ali Saei Catrin S. Günther Hilary Ireland Alan Yocca Patrick P. Edger Laura Jaakola Katja Karppinen Adrian Grande Ritva Kylli Veli-Pekka Lehtola Andrew C. Allan Richard V. Espley David ChagnéAbstract
No abstract has been registered
Authors
Dag Fjeld Kari Väätäinen Henrik von Hofsten Daniel Noreland Ingeborg Callesen Andis LazdinsAbstract
Transport cost calculations are fundamental for most types of transport research. Applications can range from estimating the cost benefits of developing transport technologies (e.g. increased truck GVWs) to comparing profitability between alternative infrastructure investments (e.g. rail or sea terminals). Most stakeholders rely on a favourite spreadsheet, however these vary considerably with respect to functionality, resolution and transparency. During 2019 and 2020 the NB Nord Road and Transport group has worked towards a common Nordic-Baltic costing framework for road, rail and sea transport. The goal has been to propose a general model per transport method which is user-friendly, while retaining the necessary resolution and functionality to model actual costs for specific transport orders or contracts. The handbook provides: a) complete explanation of its formulas, b) calculation examples and c) a corresponding Excel spreadsheet...
Abstract
Distribution modeling methods are used to provide occurrence probability surfaces for modeled targets. While most often used for modeling species, distribution modeling methods can also be applied to vegetation types. However, surfaces provided by distribution modeling need to be transformed into classified wall-to-wall maps of vegetation types to be useful for practical purposes, such as nature management and environmental planning. The paper compares the performance of three methods for assembling predictions for multiple vegetation types, modeled individually, into a wall-to-wall map. The authors used grid-cell based probability surfaces from distribution models of 31 vegetation types to test the three assembly methods. The first, a probability-based method, selected for each grid cell the vegetation type with the highest predicted probability of occurrence in that cell. The second, a performance-based method, assigned the vegetation types, ordered from high to low model performance, to a fraction of the grid cells given by the vegetation type’s prevalence in the study area. The third, a prevalence-based method, differed from the performance-based method by assigning vegetation types in the order from low to high prevalence. Thus the assembly methods worked in two principally different ways: the probability-based method assigned vegetation types to grid cells in a cell-by-cell manner, and both the performance-based method and prevalence-based method assigned them in a type-by-type manner. All methods were evaluated by use of reference data collected in the field, more or less independently of the data used to parameterize the vegetation-type models. Quantity, allocation, and total disagreement, as well as proportional dissimilarity metrics, were used for evaluation of assembly methods. Overlay analysis showed 38.1% agreement between all three assembly methods. The probability-based method had the lowest total disagreement with, and proportional dissimilarity from, the reference datasets, but the differences between the three methods were small. The three assembly methods differed strongly with respect to the distribution of the total disagreement on its quantity and allocation components: the cell-by-cell assignment method strongly favored allocation disagreement and the type-by-type methods strongly favored quantity disagreement. The probability-based method best reproduced the general pattern of variation across the study area, but at the cost of many rare vegetation types, which were left out of the assembled map. By contrast, the prevalence-based and performance-based methods represented vegetation types in accordance with nationwide area statistics. The results show that maps of vegetation types with wall-to-wall coverage can be assembled from individual distribution models with a quality acceptable for indicative purposes, but all the three tested methods currently also have shortcomings. The results also indicate specific points in the methodology for map assembly that may be improved. area frame survey, assembly strategies, distribution modeling, spatial probabilities, vegetation mapping, vegetation types
Authors
Michal Hájek Borja Jiménez-Alfaro Ondřej Hájek Lisa Brancaleoni Marco Cantonati Michele Carbognani Anita Dedić Daniel Dítě Renato Gerdol Petra Hájková Veronika Horsáková Florian Jansen Jasmina Kamberović Jutta Kapfer Tiina Hilkka Maria Kolari Mariusz Lamentowicz Predrag Lazarević Ermin Mašić Jesper Erenskjold Moeslund Aaron Pérez-Haase Tomáš Peterka Alessandro Petraglia Eulàlia Pladevall-Izard Zuzana Plesková Stefano Segadelli Yuliya Semeniuk Patrícia Singh Anna Šímová Eva Šmerdová Teemu Tahvanainen Marcello Tomaselli Yuliya Vystavna Claudia Biţă-Nicolae Michal HorsákAbstract
Water resources and associated ecosystems are becoming highly endangered due to ongoing global environmental changes. Spatial ecological modelling is a promising toolbox for understanding the past, present and future distribution and diversity patterns in groundwater-dependent ecosystems, such as fens, springs, streams, reed beds or wet grasslands. Still, the lack of detailed water chemistry maps prevents the use of reasonable models to be applied on continental and global scales. Being major determinants of biological composition and diversity of groundwater-dependent ecosystems, groundwater pH and calcium are of utmost importance. Here we developed an up-to-date European map of groundwater pH and Ca, based on 7577 measurements of near-surface groundwater pH and calcium distributed across Europe. In comparison to the existing European groundwater maps, we included several times more sites, especially in the regions rich in spring and fen habitats, and filled the apparent gaps in eastern and southeastern Europe. We used random forest models and regression kriging to create continuous maps of water pH and calcium at the continental scale, which is freely available also as a raster map (Hájek et al., 2020b; https://doi.org/10.5281/zenodo.4139912). Lithology had a higher importance than climate for both pH and calcium. The previously recognised latitudinal and altitudinal gradients were rediscovered with much refined regional patterns, as associated with bedrock variation. For ecological models of distribution and diversity of many terrestrial ecosystems, our new map based on field groundwater measurements is more suitable than maps of soil pH, which mirror not only bedrock chemistry but also vegetation-dependent soil processes.
Authors
Barry Antonio Costa-Pierce Abagail Bockus Bela H. Buck Sander van den Burg Thierry Chopin João Gomes Ferreira Nils Goseberg Kevin Heasman Johan Johansen Sandra Shumway Neil A. Sims Albert G. J. TaconAbstract
recent publication by Belton et al. raises points for policy-makers and scientists to consider with respect to the future of aquaculture making recommendations on policies and investments in systems and areas of the world where aquaculture can contribute most. Belton et al. take an ‘us versus them’ approach separating aquaculture by economics, livelihood choices, and water salinity. They conclude “that marine finfish aquaculture in offshore environments will confront economic, biophysical, and technological limitations that hinder its growth and prevent it from contributing significantly to global food and nutrition security.” They argue that land-based freshwater aquaculture is a more favorable production strategy than ocean/marine aquaculture; they disagree with government and non-governmental organizations spatial planning efforts that add new aquaculture to existing ocean uses; they advocate for an open commons for wild fisheries as opposed to aquaculture; and they oppose ‘open ocean’ aquaculture and other types of industrial, capital-intensive, ‘carnivorous’ fish aquaculture. They discredit marine aquaculture rather than explain how all aquaculture sectors are significantly more efficient and sustainable for the future of food than nearly all land-based animal protein alternatives. As an interdisciplinary group of scientists who work in marine aquaculture, we disagree with both the biased analyses and the advocacy presented by Belton et al. Marine aquaculture is growing and is already making a significant contribution to economies and peoples worldwide. None of the concerns Belton et al. raise are new, but their stark statement that farming fish in the sea cannot ‘nourish the world’ misses the mark, and policy-makers would be wrong to follow their misinformed recommendations.