810 research outputs found
Influence of stress on secretory IgA: is it a possible stressmarker in animals?
No abstract availabl
Temporal and spatial dynamics of Fusarium spp. and mycotoxins in Swedish cereals during 16 years
We analysed the dynamics of Fusarium spp. and mycotoxin contamination in Swedish cereals during 2004-2018. More than 1400 cereal samples from field trials were included, collected in a monitoring programme run by the Swedish Board of Agriculture. Five Fusarium mycotoxins were quantified with LC-MS/MS and fungal DNA from four species was quantified using quantitative real-time PCR. Correlation analyses revealed that deoxynivalenol (DON) and zearalenone (ZEN) were mainly associated with Fusarium graminearum, but stronger correlations with F. culmorum was seen some years. Nivalenol (NIV) was associated with F. poae and the HT-2 and T-2 toxins with F. langsethiae. Clear differences in mycotoxin contamination between different cereal crops and geographical regions were identified. The highest levels of DON and ZEN were found in spring wheat in Western Sweden. For NIV, HT-2 and T-2 toxins, the levels were highest in spring oats and spring barley. Regional differences were not detected for NIV, while HT-2 and T-2 toxins were associated with the northernmost region. We found that delayed harvest was strongly associated with increased levels of DON and ZEN in several crops. However, harvest date did not influence the levels of NIV or HT-2 and T-2 toxins. Our results suggest similar distribution patterns of DON and ZEN, in contrast to NIV and HT-2 and T-2 toxins, probably mirroring the differences in the ecology of the toxin-producing Fusarium species. Timely harvest is important to reduce the risk of DON and ZEN contamination, especially for fields with other risk factors
Analyzing the environmental risk factors of European spruce bark beetle damage at the local scale
The frequent outbreaks of European spruce bark beetle Ips typographus (L.) have destroyed huge amounts of Norway spruce Picea abies (L.) forests in central and Northern Europe. Identifying the risk factors and estimating the damage level is important for strategic damage control. The risk factors of forest damage by spruce bark beetles have mostly been analyzed on the landscape scale, while the in-stand risk factors have been less investigated. This study aims at exploring the local-scale risk factors in a flat area with spruce-dominated forest in southern Sweden. The investigated factors include four abiotic factors, i.e., soil wetness, solar radiation, slope gradient, and aspect, and three biotic factors, i.e., the number of deciduous trees and trees that died from attacks in previous years that remained (TreesLeft) and removed (TreesRemoved) from the forest stand. We put up 24 pheromone bags in six stands attacked by bark beetle in the previous years, resulting in different numbers of infested trees in each plot. We explored in which microenvironment a pheromone bag resulted in more colonization, the impact radius of each factor, and the necessary factors for a risk model. The environmental factors were obtained from remote sensing-based products and images. A generalized linear model (GLM) was used with the environmental factors as the explanatory variables and the damage levels as the response variables, i.e., the number of attacked trees for the plot scale, and healthy/infested for the single-tree scale. Using 50 m and 15 m radius of the environmental factors resulted in the best fit for the model at plot and individual tree scales, respectively. At those radii, the damage risk increased both at plot and individual tree level when spruce were surrounded by more deciduous trees, surrounded by dead trees that had been removed from the forest, and spruces located at the north and east slopes (315 degrees-135 degrees of aspect, > 2 degrees slope). Soil wetness, solar radiation, and remaining standing dead trees in the surrounding did not significantly impact the damage level in the microenvironment of the study area. The GLM risk model yielded an overall accuracy of 0.69 in predicting individual trees being infested or healthy. Our efforts to investigate the risk factors provide a context for wall-to-wall mapping in-stand infestation risks, using remote sensing-based data
Normalized Projected Red & SWIR (NPRS): A New Vegetation Index for Forest Health Estimation and Its Application on Spruce Bark Beetle Attack Detection
Due to the ongoing global warming, European spruce bark beetles has become a serious threat to the spruce forests in Europe and caused serious environmental and economic issues. This study proposes a new vegetation index, Normalized Projected Red & SWIR (NPRS), for detection of spruce bark beetle attacks. 29 healthy and 24 bark beetle attacked plots in southern Sweden were used for evaluating the classification accuracy using NPRS at early-, intermediate- and late-stage attacks. The obtained kappa coefficients were 0.73, 0.80 and 0.88, respectively. It was concluded that the NPRS is a feasible method for continuous bark beetle mapping over large areas
Tree Species Classification with Multi-Temporal Sentinel-2 Data
The Sentinel-2 program provides the opportunity to monitor terrestrial ecosystems with a high temporal and spectral resolution. In this study, a multi-temporal Sentinel-2 data set was used to classify common tree species over a mature forest in central Sweden. The tree species to be classified were Norway spruce (Picea abies), Scots pine (Pinus silvestris), Hybrid larch (Larix x marschlinsii), Birch (Betula sp.) and Pedunculate oak (Quercus robur). Four Sentinel-2 images from spring (7 April and 27 May), summer (9 July) and fall (19 October) of 2017 were used along with the Random Forest (RF) classifier. A variable selection approach was implemented to find fewer and uncorrelated bands resulting in the best model for tree species identification. The final model resulting in the highest overall accuracy (88.2%) came from using all bands from the four image dates. The single image that gave the most accurate classification result (80.5%) was the late spring image (27 May); the 27 May image was always included in subsequent image combinations that gave the highest overall accuracy. The five tree species were classified with a user's accuracy ranging from 70.9% to 95.6%. Thirteen of the 40 bands were selected in a variable selection procedure and resulted in a model with only slightly lower accuracy (86.3%) than that using all bands. Among the highest ranked bands were the red edge bands 2 and 3 as well as the narrow NIR (near-infrared) band 8a, all from the 27 May image, and SWIR (short-wave infrared) bands from all four image dates. This study shows that the red-edge bands and SWIR bands from Sentinel-2 are of importance, and confirms that spring and/or fall images capturing phenological differences between the species are most useful to tree species classification
Early detection of forest stress from European spruce bark beetle attack, and a new vegetation index: Normalized distance red & SWIR (NDRS)
The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects of European spruce forests. A crucial measure in pest control is the removal of infested trees before the beetles leave the bark, which generally happens before the end of June. However, stressed tree crowns do not show any significant color changes in the visible spectrum at this early-stage of infestation, making early detection difficult. In order to detect the related forest stress at an early stage, we investigated the differences in radar and spectral signals of healthy and stressed trees. How the characteristics of stressed trees changed over time was analyzed for the whole vegetation season, which covered the period before attacks (April), early-stage infestation ('green-attacks', May to July), and middle to late-stage infestation (August to October). The results show that spectral differences already existed at the beginning of the vegetation season, before the attacks. The spectral separability between the healthy and infested samples did not change significantly during the 'green-attack' stage. The results indicate that the trees were stressed before the attacks and had spectral signatures that differed from healthy ones. These stress-induced spectral changes could be more efficient indicators of early infestations than the 'green-attack' symptoms.In this study we used Sentinel-1 and 2 images of a test site in southern Sweden from April to October in 2018 and 2019. The red and SWIR bands from Sentinel-2 showed the highest separability of healthy and stressed samples. The backscatter from Sentinel-1 and additional bands from Sentinel-2 contributed only slightly in the Random Forest classification models. We therefore propose the Normalized Distance Red & SWIR (NDRS) index as a new index based on our observations and the linear relationship between the red and SWIR bands. This index identified stressed forest with accuracies from 0.80 to 0.88 before the attacks, from 0.80 to 0.82 in the early-stage infestation, and from 0.81 to 0.91 in middle- and late-stage infestations. These accuracies are higher than those attained by established vegetation indices aimed at 'green-attack' detection, such as the Normalized Difference Water Index, Ratio Drought Index, and Disease Stress Water Index. By using the proposed method, we highlight the potential of using NDRS with Sentinel-2 images to estimate forest vulnerability to European spruce bark beetle attacks early in the vegetation season
Sediment transport and coastal evolution at Thuan An Inlet, Vietnam
The Tam Giang-Cau Hai lagoon is located outside of Hue in central Vietnam. Southeast of Thuan An inlet, one of the two inlets of the lagoon, a groin was constructed in 2008 as a measure to reduce the sediment transport to prevent the inlet from closing. This groin has caused erosion of the eastern sand spit of the inlet and accretion of sediment on the coastline south east of the groin. The objectives of this study was to make a model of the sediment transport on the southeast side of the groin to be able to analyse how different measures to reduce the erosion of the inlet would affect the sediment transport past the groin. The field measurements and parts of the data collection took place in Vietnam during nine weeks in the beginning of 2013. The position of the coastline at Thuan An inlet was measured and the rest of the data, such as e.g. wave data, bathymetry data, previously measured coastlines and sediment transport was obtained from Institute of Mechanics in Hanoi. Other data used in this thesis was also obtained from The University of Agriculture and Forestry in Hue and from The Oceanographic Institute in Nha Trang. The study area has a tropical monsoon climate with two monsoon season per year – the southeast monsoon and the northwest monsoon. The micro tidal climate in the area is fully semi-diurnal and gives that the main sediment transport is wave induced. The modelling software GENESIS was used to model the sediment transport past the groin. The model was calibrated and validated using measured data and then the sediment transport on the southeast side of the groin was modelled during the years 2013 to 2017. First, the case where no measures were taken was modelled, to see what will happen if no changes of the groin were made. After that, three different measures to decrease the accretion of sediment on the southeast side of the groin (i.e. increase the sediment transport past the groin in order to reduce the erosion of the Thuan An inlet) were modelled and analyzed. These three measures were making the groin shorter, increasing the permeability of the groin and dredging sand from southeast side of the groin. The result of the model and the different measures to reduce erosion were discussed. The conclusion was that interventions to reduce the erosion are needed to protect the lagoon and the people living around it and making their livelihood from it. Many people work with e.g. fishery, aquaculture and agriculture and these occupations could be severely affected of the results of continuous erosion, such as changed water environment in the lagoon and flooding
Analysis of midwifery students' written reflections to evaluate progression in learning during clinical practice at birthing units.
Written daily reflections during clinical practice on birthing units have been used during several years in midwifery education at Lund University, Sweden. However, the usefulness of these reflections for evaluation of progression in learning and professional development of students has to date not been evaluated. In order to analyse written reflections, two taxonomies developed by Bloom and Pettersen have been applied to the texts. Progression in the professional development of midwifery students can be seen through levels of complexity in cognitive and psycho-motor learning areas and also in the description of learning situations. Progression can be seen from a basic description of facts in simple situations at the beginning of the students' practice to a complex description of complicated situations towards the end of the practice. Written daily reflections appear to be a suitable method to help students to reflect in a structured way, thereby helping their professional development. Reflections can help clinical supervisors to understand the needs of the individual student and to support their knowledge accruement. Daily written reflections on clinical practice can be of use in other health education programs
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