Läplanteringars betydelse för jordbruket och biologisk mångfald

Ever since the Stone Age, nature and man have collaborated in the change in the cultural landscape with all its components. The basis for the function of this circulation is partly about how and to what extent man uses nature's resources, and partly how nature itself responds to the changes. Through a more intensive rationalization of agriculture, the result has been a more open landscape in Skåne, Sweden. Despite its strong character, this has resulted in a problematic landslide that affects arable land. Valuable topsoil is transported away, some crop reduction occurs, and various animal species find it more difficult to find protection in this type of environment. In order to gain a better understanding of the connection and the problem, the structural properties of shelterbelts and the qualities of plant material have been studied. Shelterbelts in Skåne and Sweden as a whole, is not a particularly established tradition but is well used in Denmark. The historical use of shelterbelts has mainly revolved around reducing erosion and topsoil erosion by establishing them along arable land. The results from above-named plantings have had a positive effect on those problems. The agricultural landscape plays an important role in the protection of biodiversity, where this type of structural planting could be a good way to achieve interaction between animals and help preserve biodiversity. Thus, this study intends to link a vegetative windbreak in the form of a shelterbelt and examine ways to support biodiversity. As a result of this literature study, two plant lists have been compiled. The first one with plant choices that are suitable for shelterbelts and the other second one brings up choices that interface with the biodiversity. Furthermore, a blueprint has been made as suggestion for how a shelterbelt could be structured and composed

North American Land Data Assimilation System: A Framework for Merging Model and Satellite Data for Improved Drought Monitoring

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological–ecological–human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources. This chapter provides an overview of drought-related activities associated with the North American Land Data Assimilation System (NLDAS), which purports to provide an incremental step toward improved drought monitoring and forecasting. The NLDAS was originally conceived to improve short-term weather forecasting by providing better land surface initial conditions for operational weather forecast models. This reflects increased recognition of the role of land surface water and energy states, such as surface temperature, soil moisture, and snowpack, to atmospheric processes via feedbacks through the coupling of the water and energy cycles. Phase I of the NLDAS (NLDAS-1; Mitchell et al., 2004) made tremendous progress toward developing an operational system that gave high-resolution land hydrologic products in near real time. The system consists of multiple land surface models (LSMs) that are driven by an observation-based meteorological data set both in real time and retrospectively. This work resulted in a series of scientific papers that evaluated the retrospective data (meteorology and model output) in terms of their ability to reflect observations of the water and energy cycles and the uncertainties in the simulations as measured by the spread among individual models (Pan et al., 2003; Robock et al., 2003; Sheffield et al., 2003; Lohmann et al., 2004; Mitchell et al., 2004; Schaake et al., 2004). These evaluations led to the implementation of significant improvements to the LSMs in the form of new model physics and adjustments to parameter values and to the methods and input meteorological data (Xia et al., 2012). The system has since expanded in scope to include model intercomparison studies, real-time monitoring, and hydrologic prediction and has inspired other activities such as high-resolution land surface modeling and global land data assimilation systems (e.g., the Global Land Data Assimilation System [GLDAS], Rodell et al., 2004; the Land Information System [LIS], Kumar et al., 2006)

North American Land Data Assimilation System: A Framework for Merging Model and Satellite Data for Improved Drought Monitoring

Drought is a pervasive natural climate hazard that has widespread impacts on human activity and the environment. In the United States, droughts are billion-dollar disasters, comparable to hurricanes and tropical storms and with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined (NCDC, 2009). Reduction of the impacts and increased preparedness for drought requires the use and improvement of monitoring and prediction tools. These tools are reliant on the availability of spatially extensive and accurate data for representing the occurrence and characteristics (such as duration and severity) of drought and their related forcing mechanisms. It is increasingly recognized that the utility of drought data is highly dependent on the application (e.g., agricultural monitoring versus water resource management) and time (e.g., short- versus long-term dryness) and space (e.g., local versus national) scales involved. A comprehensive set of drought indices that considers all components of the hydrological–ecological–human system is necessary. Because of the dearth of near-real-time in situ hydrologic data collected over large regions, modeled data are often useful surrogates, especially when combined with observations from remote sensing and in situ sources. This chapter provides an overview of drought-related activities associated with the North American Land Data Assimilation System (NLDAS), which purports to provide an incremental step toward improved drought monitoring and forecasting. The NLDAS was originally conceived to improve short-term weather forecasting by providing better land surface initial conditions for operational weather forecast models. This reflects increased recognition of the role of land surface water and energy states, such as surface temperature, soil moisture, and snowpack, to atmospheric processes via feedbacks through the coupling of the water and energy cycles. Phase I of the NLDAS (NLDAS-1; Mitchell et al., 2004) made tremendous progress toward developing an operational system that gave high-resolution land hydrologic products in near real time. The system consists of multiple land surface models (LSMs) that are driven by an observation-based meteorological data set both in real time and retrospectively. This work resulted in a series of scientific papers that evaluated the retrospective data (meteorology and model output) in terms of their ability to reflect observations of the water and energy cycles and the uncertainties in the simulations as measured by the spread among individual models (Pan et al., 2003; Robock et al., 2003; Sheffield et al., 2003; Lohmann et al., 2004; Mitchell et al., 2004; Schaake et al., 2004). These evaluations led to the implementation of significant improvements to the LSMs in the form of new model physics and adjustments to parameter values and to the methods and input meteorological data (Xia et al., 2012). The system has since expanded in scope to include model intercomparison studies, real-time monitoring, and hydrologic prediction and has inspired other activities such as high-resolution land surface modeling and global land data assimilation systems (e.g., the Global Land Data Assimilation System [GLDAS], Rodell et al., 2004; the Land Information System [LIS], Kumar et al., 2006)

The iconographic brain: a critical philosophical inquiry into (the resistance of) the image

The brain image plays a central role in contemporary image culture and, in turn, (co)constructs contemporary forms of subjectivity. The central aim of this paper is to probe the unmistakably potent interpellative power of brain images by delving into the power of imaging and the power of the image itself. This is not without relevance for the neurosciences, inasmuch as these do not take place in a vacuum; hence the importance of inquiring into the status of the image within scientific culture and science itself. I will mount a critical philosophical investigation of the brain qua image, focusing on the issue of mapping the mental onto the brain and how, in turn, the brain image plays a pivotal role in processes of subjectivation. Hereto, I draw upon Science & Technology Studies, juxtaposed with culture and ideology critique and theories of image culture. The first section sets out from Althusser's concept of interpellation, linking ideology to subjectivity. Doing so allows to spell out the central question of the paper: what could serve as the basis for a critical approach, or, where can a locus of resistance be found? In the second section, drawing predominantly on Baudrillard, I delve into the dimension of virtuality as this is opened up by brain image culture. This leads to the question of whether the digital brain must be opposed to old analog psychology: is it the psyche which resists? This issue is taken up in the third section which, ultimately, concludes that the psychological is not the requisite locus of resistance. The fourth section proceeds to delineate how the brain image is constructed from what I call the data-gaze (the claim that brain data are always already visual). In the final section, I discuss how an engagement with theories of iconology affords a critical understanding of the interpellative force of the brain image, which culminates in the somewhat unexpected claim that the sought after resistance lies in the very status of the image itself

Midwifery tutors' capacity and willingness to teach contraception, post-abortion care, and legal pregnancy termination in Ghana

<p>Abstract</p> <p>Background</p> <p>Ghana has a high maternal mortality rate of 540 per 100 000. Although abortion complications usually are treatable, the risks of morbidity and death increase when treatment is delayed. Delay in care may occur when women have difficulty accessing treatment because health care providers are not trained, equipped, or willing to treat the complications of abortion. Gaps in the midwifery tutors' knowledge on comprehensive abortion care (CAC) have resulted in most midwives in Ghana not knowing the legal indications under which safe abortion care can be provided, and lacking the skills and competencies for CAC services. The aim of this study is to assess the capacity and willingness of midwifery tutors to teach contraception, post abortion care and legal termination in Ghana.</p> <p>Methods</p> <p>This study focused on all 14 midwifery schools in the country. A total of 74 midwifery tutors were interviewed for this study. Structured self-administered questionnaires were used for data collection. The data were entered and checked for consistencies using Epiinfo 6.04 and analyzed using Stata 8. Descriptive analysis was used and frequencies reported with percentages.</p> <p>Results</p> <p>In total, 74 midwifery tutors were interviewed. Of these, 66 (89.2%) were females. The tutors had mainly been trained as midwives (51.4%) and graduate nurses (33.8%). Respondents were predominantly Christians (97.3%).</p> <p>The study discovered that only 18.9% of the tutors knew all the legal indications under which safe abortion care could be provided. The content of pre-service training of tutors did not include uterine evacuation with manual vacuum aspirator (MVA).</p> <p>The study also highlighted some factors that influence midwifery tutors' willingness to teach comprehensive abortion care. It was also revealed that personal and religious beliefs greatly influence teaching of Comprehensive Abortion Care.</p> <p>Conclusion</p> <p>The findings of this survey suggest that the majority of tutors did not know the abortion law in Ghana as well as the Ghana Health Service Reproductive Health Standards and Protocol. Thus, there is a need to enhance their capacities to teach the present pre-service students the necessary skills to offer CAC after school and to understand related issues such as related legal matters.</p

A Growth Model for North Queensland Rainforests

A model to predict the growth of commercial timber in north Queensland's rainforests is described. More than 100 commercial species and several hundred other tree species are aggregated into about 20 species groups based on growth habit, volume relationships and commercial criteria. Trees are grouped according to species group and tree size into cohorts, which form the basis for simulation. Equations for predicting increment, mortality and recruitment are presented. The implications of the model on rainforest management for timber production are examined. The model has been used in setting the timber harvest from these rainforests, and should provide an objective basis for investigating the impact of rainforest management strategies. The approach should be applicable to other indigenous forests

An Ultra-High Discrimination Y Chromosome Short Tandem Repeat Multiplex DNA Typing System

In forensic casework, Y chromosome short tandem repeat markers (Y-STRs) are often used to identify a male donor DNA profile in the presence of excess quantities of female DNA, such as is found in many sexual assault investigations. Commercially available Y-STR multiplexes incorporating 12–17 loci are currently used in forensic casework (Promega's PowerPlex® Y and Applied Biosystems' AmpFlSTR® Yfiler®). Despite the robustness of these commercial multiplex Y-STR systems and the ability to discriminate two male individuals in most cases, the coincidence match probabilities between unrelated males are modest compared with the standard set of autosomal STR markers. Hence there is still a need to develop new multiplex systems to supplement these for those cases where additional discriminatory power is desired or where there is a coincidental Y-STR match between potential male participants. Over 400 Y-STR loci have been identified on the Y chromosome. While these have the potential to increase the discrimination potential afforded by the commercially available kits, many have not been well characterized. In the present work, 91 loci were tested for their relative ability to increase the discrimination potential of the commonly used ‘core’ Y-STR loci. The result of this extensive evaluation was the development of an ultra high discrimination (UHD) multiplex DNA typing system that allows for the robust co-amplification of 14 non-core Y-STR loci. Population studies with a mixed African American and American Caucasian sample set (n = 572) indicated that the overall discriminatory potential of the UHD multiplex was superior to all commercial kits tested. The combined use of the UHD multiplex and the Applied Biosystems' AmpFlSTR® Yfiler® kit resulted in 100% discrimination of all individuals within the sample set, which presages its potential to maximally augment currently available forensic casework markers. It could also find applications in human evolutionary genetics and genetic genealogy

Direct Evidence for Dominant Bond-directional Interactions in a Honeycomb Lattice Iridate Na2IrO3

Heisenberg interactions are ubiquitous in magnetic materials and have been prevailing in modeling and designing quantum magnets. Bond-directional interactions offer a novel alternative to Heisenberg exchange and provide the building blocks of the Kitaev model, which has a quantum spin liquid (QSL) as its exact ground state. Honeycomb iridates, A2IrO3 (A=Na,Li), offer potential realizations of the Kitaev model, and their reported magnetic behaviors may be interpreted within the Kitaev framework. However, the extent of their relevance to the Kitaev model remains unclear, as evidence for bond-directional interactions remains indirect or conjectural. Here, we present direct evidence for dominant bond-directional interactions in antiferromagnetic Na2IrO3 and show that they lead to strong magnetic frustration. Diffuse magnetic x-ray scattering reveals broken spin-rotational symmetry even above Neel temperature, with the three spin components exhibiting nano-scale correlations along distinct crystallographic directions. This spin-space and real-space entanglement directly manifests the bond-directional interactions, provides the missing link to Kitaev physics in honeycomb iridates, and establishes a new design strategy toward frustrated magnetism.Comment: Nature Physics, accepted (2015