Visibilidad y percepción en la construcción de un paisaje Prehistórico. El caso de Calviá (Mallorca, Islas Baleares)

El presente trabajo se centra en el estudio del papel que juega el control visual del espacio en las prácticas sociales de las comunidades prehistóricas. Este trabajo se articula a partir de un estudio de caso, el término municipal de Calviá, situado en el sureste de la isla de Mallorca, para analizar las diferentes formas de monumentalidad arquitectónica y cómo estas se constituyen cómo un punto de referencia social dentro del paisaje. Partiendo de una amplia horquilla temporal, que abarcaría el Bronce Naviforme (1550-850 AC), el período Talayótico (850-550 AC) y el Postalayótico (550-123 AC), se propone analizar los cambios y pervivencias en la construcción del paisaje, a través de estrategias de visibilidad, percepción y movimiento alrededor de los monumentos arquitectónicos. A través de la perspectiva de la Arqueología del Paisaje y mediante el uso de Sistemas de Información Geográfica (SIG) se propone un análisis de tendencias a largo plazo en la configuración social de un paisaje.

Assessing trends in land use change in the Borana rangeland Ethiopia as one cause of greenhouse gas emissions and carbon sequestration variations

Landnutzungsänderungen sind eine wesentliche Ursache von Treibhausgasemissionen. Die Umwandlung von Ökosystemen mit permanenter natürlicher Vegetation hin zu Ackerbau mit zeitweise vegetationslosem Boden (z.B. nach der Bodenbearbeitung vor der Aussaat) führt häufig zu gesteigerten Treibhausgasemissionen und verminderter Kohlenstoffbindung. Weltweit dehnt sich Ackerbau sowohl in kleinbäuerlichen als auch in agro-industriellen Systemen aus, häufig in benachbarte semiaride bis subhumide Rangeland Ökosysteme. Die vorliegende Arbeit untersucht Trends der Landnutzungsänderung im Borana Rangeland Südäthiopiens. Bevölkerungswachstum, Landprivatisierung und damit einhergehende Einzäunung, veränderte Landnutzungspolitik und zunehmende Klimavariabilität führen zu raschen Veränderungen der traditionell auf Tierhaltung basierten, pastoralen Systeme. Mittels einer Literaturanalyse von Fallstudien in ostafrikanischen Rangelands wurde im Rahmen dieser Studie ein schematisches Modell der Zusammenhänge von Landnutzung, Treibhausgasemissionen und Kohlenstofffixierung entwickelt. Anhand von Satellitendaten und Daten aus Haushaltsbefragungen wurden Art und Umfang von Landnutzungsänderungen und Vegetationsveränderungen an fünf Untersuchungsstandorten (Darito/Yabelo Distrikt, Soda, Samaro, Haralo, Did Mega/alle Dire Distrikt) zwischen 1985 und 2011 analysiert. In Darito dehnte sich die Ackerbaufläche um 12% aus, überwiegend auf Kosten von Buschland. An den übrigen Standorten blieb die Ackerbaufläche relativ konstant, jedoch nahm Graslandvegetation um zwischen 16 und 28% zu, während Buschland um zwischen 23 und 31% abnahm. Lediglich am Standort Haralo nahm auch „bare land“, vegetationslose Flächen, um 13% zu. Faktoren, die zur Ausdehnung des Ackerbaus führen, wurden am Standort Darito detaillierter untersucht. GPS Daten und anbaugeschichtlichen Daten von 108 Feldern auf 54 Betrieben wurden in einem Geographischen Informationssystem (GIS) mit thematischen Boden-, Niederschlags-, und Hangneigungskarten sowie einem Digitales Höhenmodell überlagert. Multiple lineare Regression ermittelte Hangneigung und geographische Höhe als signifikante Erklärungsvariablen für die Ausdehnung von Ackerbau in niedrigere Lagen. Bodenart, Entfernung zum saisonalen Flusslauf und Niederschlag waren hingegen nicht signifikant. Das niedrige Bestimmtheitsmaß (R²=0,154) weist darauf hin, dass es weitere, hier nicht erfasste Erklärungsvariablen für die Richtung der räumlichen Ausweitung von Ackerland gibt. Streudiagramme zu Ackergröße und Anbaujahren in Relation zu geographischer Höhe zeigen seit dem Jahr 2000 eine Ausdehnung des Ackerbaus in Lagen unter 1620 müNN und eine Zunahme der Schlaggröße (>3ha). Die Analyse der phänologischen Entwicklung von Feldfrüchten im Jahresverlauf in Kombination mit Niederschlagsdaten und normalized difference vegetation index (NDVI) Zeitreihendaten dienten dazu, Zeitpunkte besonders hoher (Begrünung vor der Ernte) oder niedriger (nach der Bodenbearbeitung) Pflanzenbiomasse auf Ackerland zu identifizieren, um Ackerland und seine Ausdehnung von anderen Vegetationsformen fernerkundlich unterscheiden zu können. Anhand der NDVI Spektralprofile konnte Ackerland gut Wald, jedoch weniger gut von Gras- und Buschland unterschieden werden. Die geringe Auflösung (250m) der Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI Daten führte zu einem Mixed Pixel Effect, d.h. die Fläche eines Pixels beinhaltete häufig verschiedene Vegetationsformen in unterschiedlichen Anteilen, was deren Unterscheidung beeinträchtigte. Für die Entwicklung eines Echtzeit Monitoring Systems für die Ausdehnung des Ackerbaus wären höher auflösende NDVI Daten (z.B. Multispektralband, Hyperion EO-1 Sensor) notwendig, um kleinräumig eine bessere Differenzierung von Ackerland und natürlicher Rangeland-Vegetation zu erhalten. Die Entwicklung und der Einsatz solcher Methoden als Entscheidungshilfen für Land- und Ressourcennutzungsplanung könnte dazu beitragen, Produktions- und Entwicklungsziele der Borana Landnutzer mit nationalen Anstrengungen zur Eindämmung des Klimawandels durch Steigerung der Kohlenstofffixierung in Rangelands in Einklang zu bringen.

Representações Sociais da Cannabis no Concelho de Góis

A cannabis permanece como a substância ilícita mais consumida no mundo. Defendida por uns e “diabolizada” por outros, constitui uma das substâncias psicoactivas mais polémicas. Alguns autores destacaram já, a importância do estudo das representações sociais das substâncias psicoactivas. No entanto, desconhecem-se investigações que abordem a representação social desta substância num espaço rural. São objectivos deste estudo: 1) conhecer as representações sociais da cannabis no que diz respeito à substância, ao consumidor e ao contexto da utilização, 2) identificar as diferenças existentes entre utilizadores e não utilizadores desta substância da amostra em estudo. Para concretizar estes objectivos, foi realizado um estudo qualitativo que recorreu a uma dupla abordagem etno-metodológica e fenomenológica. Foram realizadas 30 entrevistas a indivíduos residentes nas duas maiores freguesias do concelho de Góis que, depois de transcritas, foram objecto de análise de conteúdo. No espaço rural considerado, a cannabis é maioritariamente representada como uma “droga”, indutora de uma sensação de mal-estar e causadora de dependência. Para os participantes o utilizador é percebido como detentor de características de personalidade negativas, que o induzem ao consumo. Relativamente ao eixo espacial, o espaço rural, e mais especificamente o concelho de Góis é representado como local de consumo e de produção da cannabis herbácea. Há uma distinção clara entre a representação social dos participantes que não utilizam a substância e os que utilizam. O último grupo representa-a como uma “droga leve”, e mostra-se esclarecido sobre as possíveis consequências da sua utilização. Neste grupo é ainda evidente a valorização da cannabis herbácea, em detrimento dos seus derivados. /

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

Spatial and Temporal Variations in Airborne Ambrosia Pollen in Europe

Aim: The European Commission Cooperation in Science and Technology (COST) Action FA1203 “SMARTER” aims to make recommendations for the sustainable management of Ambrosia across Europe and for monitoring its efficiency and cost effectiveness. The goal of the present study is to provide a baseline for spatial and temporal variations in airborne Ambrosia pollen in Europe that can be used for the management and evaluation of this noxious plant . Location: The full range of Ambrosia artemisiifolia L. distribution over Europe (39oN-60oN; 2oW-45oE). Methods: Airborne Ambrosia pollen data for the principal flowering period of Ambrosia (August-September) recorded during a 10-year period (2004-2013) were obtained from 242 monitoring sites. The mean sum of daily average airborne Ambrosia pollen and the number of days that Ambrosia pollen was recorded in the air were analysed. The mean and Standard Deviation (SD) were calculated regardless of the number of years included in the study period, while trends are based on those time series with 8 or more years of data. Trends were considered significant at p < 0.05. Results: There were few significant trends in the magnitude and frequency of atmospheric Ambrosia pollen (only 8% for the mean sum of daily average Ambrosia pollen concentrations and 14% for the mean number of days Ambrosia pollen was recorded in the air). Main conclusions: The direction of any trends varied locally and reflect changes in sources of the pollen, either in size or in distance from the monitoring station. Pollen monitoring is important for providing an early warning of the expansion of this invasive and noxious plant.

How can geographical information systems and spatial analysis inform a response to prescription opioid misuse? a discussion in the context of existing literature

REGIONAL CONVERGENCE AND R&D INVESTMENT: APPLIED INVESTIGATION IN PORTUGAL

R&D investments are seen has having an enormous potential impact on the competitive position of regions and perhaps on regional convergence (or divergence) too. The aim of the paper is to study both the localization of R&D investments and regional income distribution among the NUTs 3 regions of Portugal to conclude if these variables are related or not. To study the spatial convergence (approximation) of per capita income (GDPpc) and R&D investments in the regions of Portugal, we use a standard methodology of spatial econometrics. We conclude that regions with higher GDPpc are not the same with the highest concentration of R&D investments, with the exception of the northern coastline. The R&D investments are geographically linked to the network of higher education institutions, especially in the interior regions of the country. The northern regions reveal more dynamic in terms of R&D, which apparently is not felt in the population's standard of living measured by GDPpc.

Spatial multicriteria decision analysis to potential beekeeping assessment. Case study: Montesinho Natural Park (Portugal)

The Multicriteria decision analysis is a tool to support decision-making in the identification of areas with the utmost beekeeping potential. This paper design a GIS multicriteria approach to assess the beekeeping potential. The development of a conceptual model structure requires the participation of stakeholders and experts in that process. The spatial Multicriteria Decision Analysis (MCDA) allowed defining the potential beekeeping map. The resulting maps can be used by the beekeepers associations to easily select the more suitable areas for the apiaries location or relocation and avoid prohibited areas by legal requirements.

Application of GIS in potential beekeeping assessment: Case study of Montesinho Natural Park (Portugal)

Planners require solutions that address routine work needs and seems essential to improving efficiency and productivity. There are a great number of different factors related to beekeeper activity as well the quality and productivity of different bee products. The spatial analysis is a powerful tool for overlap and relates various levels of information on a map, and consequently a very useful for beekeeping activity planning. This work proposes and applies a methodology to potential beekeeping assessment in Montesinho Natural Park, a region in the northwest of Portugal. The beekeeping potential maps were developed with the following data sources: legal standards, vegetation, land use, topography, water resources, roads, electromagnetic fields, and some honey physico-chemical analysis. The design and implementation of spatial analysis model based on Geographic Information System (GIS) to beekeeping planning activities has already been described by Anjos et al (2014). Spatial analysis techniques allows to define the potential beekeeper map supporting the beekeeper management in this region. Anjos O, Silva G, Roque N, Fernandez P, 2014. GIS based analysis to support the beekeeping planning. Book of abstracts of the International Symposium on Bee Products 3rd edition – Annual meeting of the International Honey Commission (IHC), Faculty of medicine, University of Rijeka, p:61

Determination of biodiversity and spatial and temporal distribution pattern of demersal fishes in the Oman Sea

In this project, have been studied to determine the appropriate model to spatial, temporal and diversity of demersal fishes in the Sea of Oman, including Trichiuridae, Nemipteridae, Haemulidae, Arridae, Synodontidae, Batoidfishes, Carangidae, Scianidae, Carchariniformes and Serranidae. This research became operational from catch data during 2003 to 2013 (in 2007, due to the lack of ship failed). Processing and calculations was evaluated by using the software Excel, SPSS, Arc GIS and table curve 3D highest biomass and abundance was showed in strata A and C and 10-30 m depth layers was showed the best condition biomass. In other words, highest biomass was showed in the eastern region in the Oman Sea than the central and western regions. Batoidfishes and Trichiuridae had the highest biomass .Depth factors was showed a significant correlation with the biomass. Scianidae, Serranidae and Haemulidae were showed a large decline. Synodontidae was showed a very large increase. The largest of Shannon index belong to central and western region of the Oman Sea. The highest Shannon index was showed 10-20 and 50-100 m, respectively. The Distribution maps based on the biomass was analyzed by using Arc GIS software. So that were identified in the first time in a ten-year period and carefully catch stations any economic of aquatic group. In conclusion, the depth can be found in the pattern of distribution, abundance and diversity of fish from away the beach so that follow specific pattern.

Geography, History and Natural Sciences: an interdisciplinary teaching approach with GIS

Geographic Information System (GIS) is a technology that deals with location to support better representations and decision making. It has a long tradition in several planning areas, such as urbanism, environment, riskiness, transportation, archeology or tourism. In academics context higher education has followed that evolution. Despite of their potentialities in education, GIS technologies at the elementary and secondary have been underused. Empowering graduates to learn with GIS and to manipulate spatial data can effectively facilitate the teaching of critical thinking. Likewise it has been recognized that GIS tools can be incorporated as an interdisciplinary pedagogical tool. Nevertheless more practical examples on how GIS tools can enhance teaching and learning process, namely to promote interdisciplinary approaches. The proposed paper presents some results obtained from the project “Each thing in its place: the science in time and space”. This project results from the effort of three professors of Geography, History and Natural Sciences in the context of Didactics of World Knowledge curricular unit to enhance interdisciplinarity through Geographic Information Technologies (GIT). Implemented during the last three years this action-research project developed the research practice using GIS to create an interdisciplinary attitude in the future primary education teachers. More than teaching GIS the authors were focused on teaching with GIS to create an integrated vision where spatial data representation linked the space, the time and natural sciences. Accumulated experience reveals that those technologies can motivate students to learn and facilitating teacher’s interdisciplinary work.

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels (< 0.5-m depth) can pose a risk to plant health and machinery before harvesting. By simulating time-series models, the risk of exceeding critical thresholds during a continuous period of time (e.g. 10 days) is described by probability levels. These simulated probabilities were interpolated spatially using universal kriging, incorporating information related to the drainage basin from a digital elevation model. The resulting map reduced model uncertainty. Three areas were defined as presenting potential risk at the end of the rainy season. These areas deserve attention with respect to water-management and land-use planning.

Método de elaboração de mapas dos cenários climáticos futuros para o Brasil.

Human activities are altering greenhouse gas concentrations in the atmosphere and causing global climate change. The issue of impacts of human-induced climate change has become increasingly important in recent years. The objective of this work was to develop a database of climate information of the future scenarios using a Geographic Information System (GIS) tools. Future scenarios focused on the decades of the 2020?s, 2050?s, and 2080?s (scenarios A2 and B2) were obtained from the General Circulation Models (GCM) available on Data Distribution Centre from the Third Assessment Report (TAR) of Intergovernmental Panel on Climate Change (IPCC). The TAR is compounded by six GCM with different spatial resolutions (ECHAM4:2.8125×2.8125º, HadCM3: 3.75×2.5º, CGCM2: 3.75×3.75º, CSIROMk2b: 5.625×3.214º, and CCSR/NIES: 5.625×5.625º). The mean monthly of the climate variables was obtained by the average from the available models using the GIS spatial analysis tools (arithmetic operation). Maps of mean monthly variables of mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity, and solar radiation were elaborated adopting the spatial resolution of 0.5° X 0.5° latitude and longitude. The method of elaborating maps using GIS tools allowed to evaluate the spatial and distribution of future climate assessments. Nowadays, this database is being used in studies of impacts of climate change on plant disease of Embrapa projects.