Remote sensing of vegetation fires and its contribution to a fire management information system

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the type of information remote sensing can provide to the fire community. It considers first fire management information needs in the context of fire management information system. An introduction to remote sensing then precedes the description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate how the information can be used in practice

Distribution and diversity of the vectors of Rift Valley fever along the livestock movement routes in the northeastern and coastal regions of Kenya

BACKGROUND : Knowledge of vector ecology is important in understanding the transmission dynamics of vector borne disease. In this study, we determined the distribution and diversity of mosquitoes along the major nomadic livestock movement routes (LMR) in the traditional pastoral ecozone of northeastern Kenya. We focused on the vectors of Rift Valley fever virus (RVFv) with the aim of understanding their ecology and how they can potentially influence the circulation of RVFv. METHODS : Mosquito surveys were conducted during the short and long rainy seasons from November 2012 to August 2014 using CO2-baited CDC light traps at seven sites selected for their proximity to stopover points that provide pasture, water and night bomas (where animals spend nights). We compared mosquito abundance and diversity across the sites, which were located in three ecological zones (IV, V and VI), based on the classification system of agro-ecological zones in Kenya. RESULTS : Over 31,000 mosquitoes were trapped comprising 21 species belonging to 6 genera. Overall mosquito abundance varied significantly by ecological zones and sites. Mansonia species (Ma. uniformis and Ma. africana) were predominant (n = 12,181, 38.3 %). This was followed by the primary RVF vectors, Ae. ochraceus and Ae. mcintoshi comprising 17.9 and 14.98 %, respectively, of the total captures and represented across all sites and ecological zones. The Shannon diversity index ranged from 0.8 to 2.4 with significant zone, site and seasonal variations. There was also significant species richness of RVF vector across ecological zones. CONCLUSION : Our findings highlight differential occurrence of RVFv vectors across ecological zones and sampling sites, which may be important in determining areas at risk of emergence and circulation of RVFv. Moreover, the vector distribution map along LMR generated in this study will guide potential interventions for control of the disease, including strategic vaccination for livestock.International Development Research Centre’s (IDRC) funding to icipe under the Eco-health program.http://www.parasitesandvectors.comhb201

8. Remote Sensing Of Vegetation Fires And Its Contribution To A Fire Management Information System

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information. As indicated in previous chapters, fire management usually comprises activities designed to control the frequency, area, intensity or impact of fire. These activities are undertaken in different institutional, economic, social, environmental and geographical contexts, as well as at different scales, from local to national. The range of fire management activities also varies considerably according to the management issues at stake, as well as the available means and capacity to act. Whatever the level, effective fire management requires reliable information upon which to base appropriate decisions and actions. Information will be required at many different stages of this fire management system. To illustrate this, we consider a typical and generic description of a fire management loop , as provided in Figure 8.1. Fire management objectives result from fire related knowledge . For example, they may relate to sound ecological reasons for prescribed burning in a particular land management context, or to frequent, uncontrolled fires threatening valuable natural or human resources. Whatever the issues, appropriate objectives require scientific knowledge (such as fire impact on ecosystems components, such as soil and vegetation), as well as up-to date monitoring information (such as vegetation status, fire locations, land use, socioeconomic context, etc.). Policies, generally at a national and governmental level, provide the official or legal long term framework (e.g. five to ten years) to undertake actions. A proper documentation of different fire issues, and their evolution, will allow their integration into appropriate policies, whether specific to fire management, or complementary to other policies in areas such as forestry, rangeland, biodiversity, land tenure, etc. Strategies are found at all levels of fire management. They provide a shorter-term framework (e.g. one to five years) to prioritise fire management activities. They involve the development of a clear set of objectives and a clear set of activities to achieve these objectives. They may also include research and training inputs required, in order to build capacity and to answer specific questions needed to improve fire management. The chosen strategy will result from a trade-off between priority fire management objectives and the available capacity to act (e.g. institutional framework, budget, staff, etc.), and will lead towards a better allocation of resources for fire management operations to achieve specific objectives. One example in achieving an objective of conserving biotic diversity may be the implementation of a patch-mosaic burning system (Brockett et al., 200 1 ) instead of a prescribed block burning system, based on an assumption that the former should better promote biodiversity in the long-term than the latter (Parr & Brockett, 1999). This strategy requires the implementation of early season fires to reduce the size of later season fires. The knowledge of population movements, new settlements or a coming El Nino season, should help focus the resources usage, as these factors might influence the proportion as well as the locations of area burned. Another strategy may be to prioritise the grading of fire lines earlier than usual based on information on high biomass accumulation. However, whatever the strategies, they need to be based on reliable information

8. Remote Sensing Of Vegetation Fires And Its Contribution To A Fire Management Information System

In the last decade, research has proven that remote sensing can provide very useful support to fire managers. This chapter provides an overview of the types of information remote sensing can provide to the fire community. First, it considers fire management information needs in the context of a fire management information system. An introduction to remote sensing then precedes a description of fire information obtainable from remote sensing data (such as vegetation status, active fire detection and burned areas assessment). Finally, operational examples in five African countries illustrate the practical use of remotely sensed fire information. As indicated in previous chapters, fire management usually comprises activities designed to control the frequency, area, intensity or impact of fire. These activities are undertaken in different institutional, economic, social, environmental and geographical contexts, as well as at different scales, from local to national. The range of fire management activities also varies considerably according to the management issues at stake, as well as the available means and capacity to act. Whatever the level, effective fire management requires reliable information upon which to base appropriate decisions and actions. Information will be required at many different stages of this fire management system. To illustrate this, we consider a typical and generic description of a fire management loop , as provided in Figure 8.1. Fire management objectives result from fire related knowledge . For example, they may relate to sound ecological reasons for prescribed burning in a particular land management context, or to frequent, uncontrolled fires threatening valuable natural or human resources. Whatever the issues, appropriate objectives require scientific knowledge (such as fire impact on ecosystems components, such as soil and vegetation), as well as up-to date monitoring information (such as vegetation status, fire locations, land use, socioeconomic context, etc.). Policies, generally at a national and governmental level, provide the official or legal long term framework (e.g. five to ten years) to undertake actions. A proper documentation of different fire issues, and their evolution, will allow their integration into appropriate policies, whether specific to fire management, or complementary to other policies in areas such as forestry, rangeland, biodiversity, land tenure, etc. Strategies are found at all levels of fire management. They provide a shorter-term framework (e.g. one to five years) to prioritise fire management activities. They involve the development of a clear set of objectives and a clear set of activities to achieve these objectives. They may also include research and training inputs required, in order to build capacity and to answer specific questions needed to improve fire management. The chosen strategy will result from a trade-off between priority fire management objectives and the available capacity to act (e.g. institutional framework, budget, staff, etc.), and will lead towards a better allocation of resources for fire management operations to achieve specific objectives. One example in achieving an objective of conserving biotic diversity may be the implementation of a patch-mosaic burning system (Brockett et al., 200 1 ) instead of a prescribed block burning system, based on an assumption that the former should better promote biodiversity in the long-term than the latter (Parr & Brockett, 1999). This strategy requires the implementation of early season fires to reduce the size of later season fires. The knowledge of population movements, new settlements or a coming El Nino season, should help focus the resources usage, as these factors might influence the proportion as well as the locations of area burned. Another strategy may be to prioritise the grading of fire lines earlier than usual based on information on high biomass accumulation. However, whatever the strategies, they need to be based on reliable information

The Utility of AISA Eagle Hyperspectral Data and Random Forest Classifier for Flower Mapping

Peer reviewe

Factors influencing the efficiency of generating genetically engineered pigs by nuclear transfer: multi-factorial analysis of a large data set

Background: Somatic cell nuclear transfer (SCNT) using genetically engineered donor cells is currently the most widely used strategy to generate tailored pig models for biomedical research. Although this approach facilitates a similar spectrum of genetic modifications as in rodent models, the outcome in terms of live cloned piglets is quite variable. In this study, we aimed at a comprehensive analysis of environmental and experimental factors that are substantially influencing the efficiency of generating genetically engineered pigs. Based on a considerably large data set from 274 SCNT experiments (in total 18,649 reconstructed embryos transferred into 193 recipients), performed over a period of three years, we assessed the relative contribution of season, type of genetic modification, donor cell source, number of cloning rounds, and pre-selection of cloned embryos for early development to the cloning efficiency. Results: 109 (56%) recipients became pregnant and 85 (78%) of them gave birth to offspring. Out of 318 cloned piglets, 243 (76%) were alive, but only 97 (40%) were clinically healthy and showed normal development. The proportion of stillborn piglets was 24% (75/318), and another 31% (100/318) of the cloned piglets died soon after birth. The overall cloning efficiency, defined as the number of offspring born per SCNT embryos transferred, including only recipients that delivered, was 3.95%. SCNT experiments performed during winter using fetal fibroblasts or kidney cells after additive gene transfer resulted in the highest number of live and healthy offspring, while two or more rounds of cloning and nuclear transfer experiments performed during summer decreased the number of healthy offspring. Conclusion: Although the effects of individual factors may be different between various laboratories, our results and analysis strategy will help to identify and optimize the factors, which are most critical to cloning success in programs aiming at the generation of genetically engineered pig models

Advances in crop insect modelling methods—Towards a whole system approach

A wide range of insects affect crop production and cause considerable yield losses. Difficulties reside on the development and adaptation of adequate strategies to predict insect pests for their timely management to ensure enhanced agricultural production. Several conceptual modelling frameworks have been proposed, and the choice of an approach depends largely on the objective of the model and the availability of data. This paper presents a summary of decades of advances in insect population dynamics, phenology models, distribution and risk mapping. Existing challenges on the modelling of insects are listed; followed by innovations in the field. New approaches include artificial neural networks, cellular automata (CA) coupled with fuzzy logic (FL), fractal, multi-fractal, percolation, synchronization and individual/agent based approaches. A concept for assessing climate change impacts and providing adaptation options for agricultural pest management independently of the United Nations Intergovernmental Panel on Climate Change (IPCC) emission scenarios is suggested. A framework for estimating losses and optimizing yields within crop production system is proposed and a summary on modelling the economic impact of pests control is presented. The assessment shows that the majority of known insect modelling approaches are not holistic; they only concentrate on a single component of the system, i.e. the pest, rather than the whole crop production system. We suggest system thinking as a possible approach for linking crop, pest, and environmental conditions to provide a more comprehensive assessment of agricultural crop production.Peer reviewe

MHC class II–restricted antigen presentation by plasmacytoid dendritic cells inhibits T cell–mediated autoimmunity

Although plasmacytoid dendritic cells (pDCs) express major histocompatibility complex class II (MHCII) molecules, and can capture, process, and present antigens (Ags), direct demonstrations that they function as professional Ag-presenting cells (APCs) in vivo during ongoing immune responses remain lacking. We demonstrate that mice exhibiting a selective abrogation of MHCII expression by pDCs develop exacerbated experimental autoimmune encephalomyelitis (EAE) as a consequence of enhanced priming of encephalitogenic CD4+ T cell responses in secondary lymphoid tissues. After EAE induction, pDCs are recruited to lymph nodes and establish MHCII-dependent myelin-Ag–specific contacts with CD4+ T cells. These interactions promote the selective expansion of myelin-Ag–specific natural regulatory T cells that dampen the autoimmune T cell response. pDCs thus function as APCs during the course of EAE and confer a natural protection against autoimmune disease development that is mediated directly by their ability to present of Ags to CD4+ T cells in vivo

Maturation of Dendritic Cells Is Accompanied by Rapid Transcriptional Silencing of Class II Transactivator (Ciita) Expression

Cell surface expression of major histocompatibility complex class II (MHCII) molecules is increased during the maturation of dendritic cells (DCs). This enhances their ability to present antigen and activate naive CD4+ T cells. In contrast to increased cell surface MHCII expression, de novo biosynthesis of MHCII mRNA is turned off during DC maturation. We show here that this is due to a remarkably rapid reduction in the synthesis of class II transactivator (CIITA) mRNA and protein. This reduction in CIITA expression occurs in human monocyte-derived DCs and mouse bone marrow–derived DCs, and is triggered by a variety of different maturation stimuli, including lipopolysaccharide, tumor necrosis factor α, CD40 ligand, interferon α, and infection with Salmonella typhimurium or Sendai virus. It is also observed in vivo in splenic DCs in acute myelin oligodendrocyte glycoprotein induced experimental autoimmune encephalitis. The arrest in CIITA expression is the result of a transcriptional inactivation of the MHC2TA gene. This is mediated by a global repression mechanism implicating histone deacetylation over a large domain spanning the entire MHC2TA regulatory region

Dectin-1 diversifies Aspergillus fumigatus–specific T cell responses by inhibiting T helper type 1 CD4 T cell differentiation

By modifying dendritic cell cytokine production, Dectin-1 suppresses Th1 differentiation in mice infected with the fungal pathogen Aspergillus fumigatus