856 resultados para Socio-ecological models


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Das Mahafaly Plateau im südwestlichen Madagaskar ist gekennzeichnet durch raue klimatische Bedingungen, vor allem regelmäßige Dürren und Trockenperioden, geringe Infrastruktur, steigende Unsicherheit, hohe Analphabetenrate und regelmäßige Zerstörung der Ernte durch Heuschreckenplagen. Da 97% der Bevölkerung von der Landwirtschaft abhängen, ist eine Steigerung der Produktivität von Anbausystemen die Grundlage für eine Verbesserung der Lebensbedingungen und Ernährungssicherheit in der Mahafaly Region. Da wenig über die Produktivität von traditionellen extensiven und neu eingeführten Anbaumethoden in diesem Gebiet bekannt ist, waren die Zielsetzungen der vorliegenden Arbeit, die limitierenden Faktoren und vielversprechende alternative Anbaumethoden zu identifizieren und diese unter Feldbedingungen zu testen. Wir untersuchten die Auswirkungen von lokalem Viehmist und Holzkohle auf die Erträge von Maniok, der Hauptanbaufrucht der Region, sowie die Beiträge von weiteren Faktoren, die im Untersuchungsgebiet ertragslimitierend sind. Darüber hinaus wurde in der Küstenregion das Potenzial für bewässerten Gemüseanbau mit Mist und Holzkohle untersucht, um zu einer Diversifizierung von Einkommen und Ernährung beizutragen. Ein weiterer Schwerpunkt dieser Arbeit war die Schätzung von Taubildung und deren Beitrag in der Jahreswasserbilanz durch Testen eines neu entworfenen Taumessgerätes. Maniok wurde über drei Jahre und in drei Versuchsfeldern in zwei Dörfern auf dem Plateau angebaut, mit applizierten Zeburindermistraten von 5 und 10 t ha-1, Holzkohleraten von 0,5 und 2 t ha-1 und Maniokpflanzdichten von 4500 Pflanzen ha-1. Maniokknollenerträge auf Kontrollflächen erreichten 1 bis 1,8 t Trockenmasse (TM) ha-1. Mist führte zu einer Knollenertragssteigerung um 30 - 40% nach drei Jahren in einem kontinuierlich bewirtschafteten Feld mit geringer Bodenfruchtbarkeit, hatte aber keinen Effekt auf den anderen Versuchsfeldern. Holzkohle hatte keinen Einfluss auf Erträge über den gesamten Testzeitraum, während die Infektion mit Cassava-Mosaikvirus zu Ertragseinbußen um bis zu 30% führte. Pflanzenbestände wurden felder-und jahresübergreifend um 4-54% des vollen Bestandes reduziert, was vermutlich auf das Auftreten von Trockenperioden und geringe Vitalität von Pflanzmaterial zurückzuführen ist. Karotten (Daucus carota L. var. Nantaise) und Zwiebeln (Allium cepa L. var. Red Créole) wurden über zwei Trockenzeiten mit lokal erhältlichem Saatgut angebaut. Wir testeten die Auswirkungen von lokalem Rindermist mit einer Rate von 40 t ha-1, Holzkohle mit einer Rate von 10 t ha-1, sowie Beschattung auf die Gemüseernteerträge. Lokale Bewässerungswasser hatte einen Salzgehalt von 7,65 mS cm-1. Karotten- und Zwiebelerträge über Behandlungen und Jahre erreichten 0,24 bis 2,56 t TM ha-1 beziehungsweise 0,30 bis 4,07 DM t ha-1. Mist und Holzkohle hatten keinen Einfluss auf die Erträge beider Kulturen. Beschattung verringerte Karottenerträge um 33% im ersten Jahr, während sich die Erträge im zweiten Jahr um 65% erhöhten. Zwiebelerträge wurden unter Beschattung um 148% und 208% im ersten und zweiten Jahr erhöht. Salines Bewässerungswasser sowie Qualität des lokal verfügbaren Saatgutes reduzierten die Keimungsraten deutlich. Taubildung im Küstendorf Efoetsy betrug 58,4 mm und repräsentierte damit 19% der Niederschlagsmenge innerhalb des gesamten Beobachtungszeitraum von 18 Monaten. Dies weist darauf hin, dass Tau in der Tat einen wichtigen Beitrag zur jährlichen Wasserbilanz darstellt. Tageshöchstwerte erreichten 0,48 mm. Die getestete Tauwaage-Vorrichtung war in der Lage, die nächtliche Taubildung auf der metallischen Kondensationsplatte zuverlässig zu bestimmen. Im abschließenden Kapitel werden die limitierenden Faktoren für eine nachhaltige Intensivierung der Landwirtschaft in der Untersuchungsregion diskutiert.

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La formiga argentina (Linepithema humile) es troba entre les espècies més invasores: originària d'Amèrica del Sud, actualment ha envaït nombroses àrees arreu del món. Aquesta tesi doctoral intenta fer una primera anàlisi integrada i multiescalar de la distribució de la formiga argentina mitjançant l'ús de models de nínxol ecològic. D'acord amb els resultats obtinguts, es preveu que la formiga argentina assoleixi una distribució més àmplia que l'actual. Les prediccions obtingudes a partir dels models concorden amb la distribució actualment coneguda i, a més, indiquen àrees a prop de la costa i dels rius principals com a altament favorables per a l'espècie. Aquests resultats corroboren la idea que la formiga argentina no es troba actualment en equilibri amb el medi. D'altra banda, amb el canvi climàtic, s'espera que la distribució de la formiga argentina s'estengui cap a latituds més elevades en ambdós hemisferis, i sofreixi una retracció en els tròpics a escales globals.

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Environmental change research often relies on simplistic, static models of human behaviour in social-ecological systems. This limits understanding of how social-ecological change occurs. Integrative, process-based behavioural models, which include feedbacks between action, and social and ecological system structures and dynamics, can inform dynamic policy assessment in which decision making is internalised in the model. These models focus on dynamics rather than states. They stimulate new questions and foster interdisciplinarity between and within the natural and social sciences.

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In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.

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This study aimed to analyze the spatial distribution of dengue risk and its association with socio-environmental conditions. This was an ecological study of the counts of autochthonous dengue cases in the municipality of Campinas, São Paulo State, Brazil, in the year 2007, aggregated according to 47 coverage areas of municipal health centers. Spatial models for mapping diseases were constructed with Bayesian hierarchical models, based on Integrated Nested Laplace Approximation (INLA). The analyses were stratified according to two age groups, 0 to 14 years and above 14 years. The results indicate that the spatial distribution of dengue risk is not associated with socio-environmental conditions in the 0 to 14 year age group. In the age group older than 14 years, the relative risk of dengue increases significantly as the level of socio-environmental deprivation increases. Mapping of socio-environmental deprivation and dengue cases proved to be a useful tool for data analysis in dengue surveillance systems.

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In Eritrea findet eine rasche Verbreitung von Prosopis (juliflora) statt, die sich negativ auf die Naturresourcen als auch die sozio-ökonomische Lage der ländlichen Bevölkerung auswirkt. Die Landbevölkerung Eritrea's ist davon überzeugt, dass die Pflanze vor allem die Ernährungssicherung beeinträchtigt und will deshalb, dass sie ausgerottet wird. Die vorliegende Dissertation beschreibt die Auswirkung von Posopis auf lokale Öko- und Wirtschaftssysteme und zieht Vergleiche mit der diesbezüglichen Situation in anderen Ländern. Im Weiteren stellt sie einen Prosopis Management-Plan vor, dessen Ziel es ist, die zunehmende Verbreitung zu verhindern. Auch liefert sie eine Gegenüberstellung der Ansichten von wissenschaftlichen Experten einerseits und Bauern und Nomaden andrerseits. Sie zeigt auf, dass die weit verbreitete Annahme der Experten das Problem Prosopis durch ökonomische Nutzung ("eradication by utilisation") in Schach halten zu können, fraglich ist.

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Organic farming means a holistic application of agricultural land-use, hence, this study aimed to assess ecological and socio-economic aspects that show benefits of the strategy and achievements of organic farming in comparison to conventional farming in Darjeeling District, State of West Bengal, India and Kanagawa Prefecture/Kanto in Central Japan. The objective of this study has been empirically analysed on aspects of crop diversity, yield, income and sales prices in the two study regions, where 50 households each, i.e. in total 100 households were interviewed at farm-level. Therefore, the small sample size does not necessarily reflect the broad-scale of the use and benefit of organic farming in both regions. The problems faced in mountainous regions in terms of agriculture and livelihoods for small-scale farmers, which are most affected and dependant on their immediate environment, such as low yields, income and illegal felling leading to soil erosion and landslides, are analyzed. Furthermore, factors such as climate, soils, vegetation and relief equally play an important role for these farmers, in terms of land-use. To supplement and improve the income of farmers, local NGOs have introduced organic farming and high value organic cash crops such as ginger, tea, orange and cardamom and small income generating means (floriculture, apiary etc.). For non-certified and certified organic products the volume is given for India, while for Japan only certified organic production figures are given, as there are several definitions for organic in Japan. Hence, prior to the implementation of organic laws and standards, even reduced chemical input was sold as non-certified organic. Furthermore, the distribution and certification system of both countries are explained in detail, including interviews with distribution companies and cooperatives. Supportive observations from Kanagawa Prefecture and the Kanto region are helpful and practical suggestions for organic farmers in Darjeeling District. Most of these are simple and applicable soil management measures, natural insect repelling applications and describe the direct marketing system practiced in Japan. The former two include compost, intercropping, Effective Microorganisms (EM), clover, rice husk charcoal and wood vinegar. More supportive observations have been made at organic and biodynamic tea estates in Darjeeling District, which use citronella, neem, marigold, leguminous and soil binding plants for soil management and natural insect control. Due to the close ties between farmers and consumers in Japan, certification is often neither necessary nor wanted by the producers. They have built a confidence relationship with their customers; thus, such measures are simply not required. Another option is group certification, instead of the expensive individual certification. The former aims at lower costs for farmers who have formed a cooperative or a farmers' group. Consumer awareness for organic goods is another crucial aspect to help improve the situation of organic farmers. Awareness is slightly more advanced in Kanto than in Darjeeling District, as it is improved due to the close (sales) ties between farmers and consumers in Kanto. Interviews conducted with several such cooperatives and companies underline the positive system of TEIKEI. The introduction of organic farming in the study regions has shown positive effects for those involved, even though it still in its beginning stages in Darjeeling District. This study was only partly able to assess the benefits of organic agriculture at its present level for Darjeeling District, while more positively for the organic farmers of Kanto. The organic farming practice needs further improvement, encouragement and monitoring for the Darjeeling District farmers by locals, consumers, NGOs and politicians. The supportive observations from Kanagawa Prefecture and the Kanto region are a small step in this direction, showing how, simple soil improvements and thus, yield and income increases, as well as direct sales options can enhance the livelihood of organic farmers without destroying their environment and natural resources.

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Latent class regression models are useful tools for assessing associations between covariates and latent variables. However, evaluation of key model assumptions cannot be performed using methods from standard regression models due to the unobserved nature of latent outcome variables. This paper presents graphical diagnostic tools to evaluate whether or not latent class regression models adhere to standard assumptions of the model: conditional independence and non-differential measurement. An integral part of these methods is the use of a Markov Chain Monte Carlo estimation procedure. Unlike standard maximum likelihood implementations for latent class regression model estimation, the MCMC approach allows us to calculate posterior distributions and point estimates of any functions of parameters. It is this convenience that allows us to provide the diagnostic methods that we introduce. As a motivating example we present an analysis focusing on the association between depression and socioeconomic status, using data from the Epidemiologic Catchment Area study. We consider a latent class regression analysis investigating the association between depression and socioeconomic status measures, where the latent variable depression is regressed on education and income indicators, in addition to age, gender, and marital status variables. While the fitted latent class regression model yields interesting results, the model parameters are found to be invalid due to the violation of model assumptions. The violation of these assumptions is clearly identified by the presented diagnostic plots. These methods can be applied to standard latent class and latent class regression models, and the general principle can be extended to evaluate model assumptions in other types of models.

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Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

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Comparison of mitochondrial and morphological divergence in eight populations of a widespread leaf-litter skink is used to determine the relative importance of geographic isolation and natural selection in generating phenotypic diversity in the Wet Tropics Rainforest region of Australia. The populations occur in two geographically isolated regions, and within each region, in two different habitats (closed rainforest and tall open forest) that span a well characterized ecological gradient. Morphological differences among ancient geographic isolates (separated for several million years, judging by their mitochondrial DNA sequence divergence) were slight, but morphological and life history differences among habitats were large and occurred despite moderate to high levels of mitochondrial gene flow. A field experiment identified avian predation as one potential agent of natural selection. These results indicate that natural selection operating across ecological gradients can be more important than geographic isolation in similar habitats in generating phenotypic diversity. In addition, our results indicate that selection is sufficiently strong to overcome the homogenizing effects of gene flow, a necessary first step toward speciation in continuously distributed populations. Because ecological gradients may be a source of evolutionary novelty, and perhaps new species, their conservation warrants greater attention. This is particularly true in tropical regions, where most reserves do not include ecological gradients and transitional habitats.

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In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.