Spatial neighborhood matrix computation: Inverse distance weighted versus binary contiguity

Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

Modelling the impact of land use change on water quality in agricultural catchments

Export coefficient modelling was used to model the impact of agriculture on nitrogen and phosphorus loading on the surface waters of two contrasting agricultural catchments. The model was originally developed for the Windrush catchment where the highly reactive Jurassic limestone aquifer underlying the catchment is well connected to the surface drainage network, allowing the system to be modelled using uniform export coefficients for each nutrient source in the catchment, regardless of proximity to the surface drainage network. In the Slapton catchment, the hydrological path-ways are dominated by surface and lateral shallow subsurface flow, requiring modification of the export coefficient model to incorporate a distance-decay component in the export coefficients. The modified model was calibrated against observed total nitrogen and total phosphorus loads delivered to Slapton Ley from inflowing streams in its catchment. Sensitivity analysis was conducted to isolate the key controls on nutrient export in the modified model. The model was validated against long-term records of water quality, and was found to be accurate in its predictions and sensitive to both temporal and spatial changes in agricultural practice in the catchment. The model was then used to forecast the potential reduction in nutrient loading on Slapton Ley associated with a range of catchment management strategies. The best practicable environmental option (BPEO) was found to be spatial redistribution of high nutrient export risk sources to areas of the catchment with the greatest intrinsic nutrient retention capacity.

An empirical test of the gravity p-median model

A customer is presumed to gravitate to a facility by the distance to it and the attractiveness of it. However regarding the location of the facility, the presumption is that the customer opts for the shortest route to the nearest facility.This paradox was recently solved by the introduction of the gravity p-median model. The model is yet to be implemented and tested empirically. We implemented the model in an empirical problem of locating locksmiths, vehicle inspections, and retail stores ofv ehicle spare-parts, and we compared the solutions with those of the p-median model. We found the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Testing the gravity p-median model empirically

Regarding the location of a facility, the presumption in the widely used p-median model is that the customer opts for the shortest route to the nearest facility. However, this assumption is problematic on free markets since the customer is presumed to gravitate to a facility by the distance to and the attractiveness of it. The recently introduced gravity p-median model offers an extension to the p-median model that account for this. The model is therefore potentially interesting, although it has not yet been implemented and tested empirically. In this paper, we have implemented the model in an empirical problem of locating vehicle inspections, locksmiths, and retail stores of vehicle spare-parts for the purpose of investigating its superiority to the p-median model. We found, however, the gravity p-median model to be of limited use for the problem of locating facilities as it either gives solutions similar to the p-median model, or it gives unstable solutions due to a non-concave objective function.

Geographical variation in mutualistic networks: similarity, turnover and partner fidelity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Helmintofauna associada a leptodactylus fuscus (Anura: Leptodactylidae) em regiões de Cerrado, Pantanal e Caatinga no Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Dispersal dynamics in food webs

Studies of food webs suggest that limited nonrandom dispersal can play an important role in structuring food webs. It is not clear, however, whether density-dependent dispersal fits empirical patterns of food webs better than density-independent dispersal. Here, we study a spatially distributed food web, using a series of population-dispersal models that contrast density-independent and density-dependent dispersal in landscapes where sampled sites are either homogeneously or heterogeneously distributed. These models are fitted to empirical data, allowing us to infer mechanisms that are consistent with the data. Our results show that models with density-dependent dispersal fit the α, β, and γ tritrophic richness observed in empirical data best. Our results also show that density-dependent dispersal leads to a critical distance threshold beyond which site similarity (i.e., β tritrophic richness) starts to decrease much faster. Such a threshold can also be detected in the empirical data. In contrast, models with density-independent dispersal do not predict such a threshold. Moreover, preferential dispersal from more centrally located sites to peripheral sites does not provide a better fit to empirical data when compared with symmetric dispersal between sites. Our results suggest that nonrandom dispersal in heterogeneous landscapes is an important driver that shapes local and regional richness (i.e., α and γ tritrophic richness, respectively) as well as the distance-decay relationship (i.e., β tritrophic richness) in food webs.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

Modelos de demanda potencial de viajeros en redes de transporte público : aplicaciones en el Metro de Madrid

Este trabajo propone una metodología basada en Sistemas de Información Geográfica para estimar la demanda de viajes en estaciones de redes de transporte público, tomando como ejemplo la red de metro de Madrid. Primero se emplea una serie de datos descriptivos para caracterizar la red, clasificar las estaciones y obtener una tipología de las mismas. Luego, con el objetivo de explicar y predecir los viajes (entradas a la red) se generan dos modelos: uno sencillo a partir de las tasas de penetración de uso del metro en función de la distancia (distance decay), y otro más complejo basado en un modelo de regresión lineal múltiple (MRLM) que incorpora variables relativas a la estación y su entorno (densidad, mezcla de usos, diseño urbano, presencia de modos competidores). Su aplicación muestra resultados alentadores, y se plantea como una alternativa a los clásicos modelos de cuatro etapas, más complejos y con un mayor coste económico.

R&D, Spillovers, Innovation Systems and the Genesis of Regional Growth in Europe. Bruges European Economic Research (BEER) Papers 5/October 2006

Research on the impact of innovation on regional economic performance in Europe has fundamentally followed three approaches: a) the analysis of the link between investment in R&D, patents, and economic growth; b) the study of the existence and efficiency of regional innovation systems; and c) the examination of geographical diffusion of regional knowledge spillovers. These complementary approaches have, however, rarely been combined. Important operational and methodological barriers have thwarted any potential cross-fertilization. In this paper, we try to fill this gap in the literature by combining in one model R&D, spillovers, and innovation systems approaches. A multiple regression analysis is conducted for all regions of the EU-25, including measures of R&D investment, proxies for regional innovation systems, and knowledge and socio-economic spillovers. This approach allows us to discriminate between the influence of internal factors and external knowledge and institutional flows on regional economic growth. The empirical results highlight how the interaction between local and external research with local and external socioeconomic and institutional conditions determines the potential of every region in order to maximise its innovation capacity. They also indicate the importance of proximity for the transmission of economically productive knowledge, as spillovers show strong distance decay effects. In the EU-25 context, only the innovative efforts pursued within a 180 minute travel radius have a positive and significant impact on regional growth performance.

Anthropogenic and climatic controls on surface water across the contiguous United States

Anthropogenic activities and climatic processes heavily influence surface water resources by causing their progressive depletion, which in turn affects both societies and the environment. Therefore, there is an urgent need to understand the contribution of human and climatic dynamics on the variation of surface water availability. Here, this investigation is performed on the contiguous United States (CONUS) using remotely-sensed data. Three anthropogenic (i.e., urban area, population, and irrigation) and two climatic factors (i.e., precipitation and temperature) were selected as potential drivers of changes in surface water extent and the overlap between the increase or decrease in these drivers and the variation of surface water was examined. Most of the river basins experienced a surface water gain due to precipitation increase (eastern CONUS), and a reduction of irrigated land (western CONUS). River basins of the arid southwestern region and some river basins of the northeastern area encountered a surface water loss, essentially induced by population growth, along with a precipitation deficit and a general expansion of irrigated land. To further inspect the role of population growth and urbanization on surface water loss, the spatial interaction between human settlements and surface water depletion was examined by evaluating the frequency of surface water loss as a function of distance from urban areas. The decline of the observed frequency was successfully reproduced with an exponential distance-decay model, proving that surface water losses are more concentrated in the proximity of cities. Climatic conditions influenced this pattern, with more widely distributed losses in arid regions compared to temperate and continental areas. The results presented in this Thesis provide an improved understanding of the effects of anthropogenic and climatic dynamics on surface water availability, which could be integrated in the definition of sustainable strategies for urbanization, water management, and surface water restoration.

Radioactivity levels of 238U and 232Th decay series and related dose rates in the surroundings of a coal power plant using high resolution g-spectrometry

Gamma radiations measurements were carried out in the vicinity of a coal-fired power plant located in the southwest coastline of Portugal. Two different gamma detectors were used to assess the environmental radiation within a circular area of 20 km centred in the coal plant: a scintillometer (SPP2 NF, Saphymo) and a high purity germanium detector (HPGe, Canberra). Fifty urban and suburban measurements locations were established within the defined area and two measurements campaigns were carried out. The results of the total gamma radiation ranged from 20.83 to 98.33 counts per second (c.p.s.) for both measurement campaigns and outdoor doses rates ranged from 77.65 to 366.51 Gy/h. Natural emitting nuclides from the U-238 and Th-232 decay series were identified as well as the natural emitting nuclide K-40. The radionuclide concentration from the uranium and thorium series determined by gamma spectrometry ranged from 0.93 to 73.68 Bq/kg, while for K-40 the concentration ranged from 84.14 to 904.38 Bq/kg. The obtained results were used primarily to define the variability in measured environmental radiation and to determine the coal plant’s influence in the measured radiation levels. The highest values were measured at two locations near the power plant and at locations between the distance of 6 and 20 km away from the stacks, mainly in the prevailing wind direction. The results showed an increase or at least an influence from the coal-fired plant operations, both qualitatively and quantitatively.

Decay of linkage disequilibrium within genes across HGDP-CEPH human samples: most population isolates do not show increased LD

Background: It is well known that the pattern of linkage disequilibrium varies between human populations, with remarkable geographical stratification. Indirect association studies routinely exploit linkage disequilibrium around genes, particularly in isolated populations where it is assumed to be higher. Here, we explore both the amount and the decay of linkage disequilibrium with physical distance along 211 gene regions, most of them related to complex diseases, across 39 HGDP-CEPH population samples, focusing particularly on the populations defined as isolates. Within each gene region and population we use r2 between all possible single nucleotide polymorphism (SNP) pairs as a measure of linkage disequilibrium and focus on the proportion of SNP pairs with r2 greater than 0.8.Results: Although the average r2 was found to be significantly different both between and within continental regions, a much higher proportion of r2 variance could be attributed to differences between continental regions (2.8% vs. 0.5%, respectively). Similarly, while the proportion of SNP pairs with r2 > 0.8 was significantly different across continents for all distance classes, it was generally much more homogenous within continents, except in the case of Africa and the Americas. The only isolated populations with consistently higher LD in all distance classes with respect to their continent are the Kalash (Central South Asia) and the Surui (America). Moreover, isolated populations showed only slightly higher proportions of SNP pairs with r2 > 0.8 per gene region than non-isolated populations in the same continent. Thus, the number of SNPs in isolated populations that need to be genotyped may be only slightly less than in non-isolates. Conclusion: The "isolated population" label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.

Decay of linkage disequilibrium within genes across HGDP-CEPH human samples: most population isolates do not show increased LD

Background It is well known that the pattern of linkage disequilibrium varies between human populations, with remarkable geographical stratification. Indirect association studies routinely exploit linkage disequilibrium around genes, particularly in isolated populations where it is assumed to be higher. Here, we explore both the amount and the decay of linkage disequilibrium with physical distance along 211 gene regions, most of them related to complex diseases, across 39 HGDP-CEPH population samples, focusing particularly on the populations defined as isolates. Within each gene region and population we use r2 between all possible single nucleotide polymorphism (SNP) pairs as a measure of linkage disequilibrium and focus on the proportion of SNP pairs with r2 greater than 0.8. Results Although the average r2 was found to be significantly different both between and within continental regions, a much higher proportion of r2 variance could be attributed to differences between continental regions (2.8% vs. 0.5%, respectively). Similarly, while the proportion of SNP pairs with r2 > 0.8 was significantly different across continents for all distance classes, it was generally much more homogenous within continents, except in the case of Africa and the Americas. The only isolated populations with consistently higher LD in all distance classes with respect to their continent are the Kalash (Central South Asia) and the Surui (America). Moreover, isolated populations showed only slightly higher proportions of SNP pairs with r2 > 0.8 per gene region than non-isolated populations in the same continent. Thus, the number of SNPs in isolated populations that need to be genotyped may be only slightly less than in non-isolates. Conclusion The 'isolated population' label by itself does not guarantee a greater genotyping efficiency in association studies, and properties other than increased linkage disequilibrium may make these populations interesting in genetic epidemiology.

Evaluating Design Decay during Software Evolution

Les logiciels sont en constante évolution, nécessitant une maintenance et un développement continus. Ils subissent des changements tout au long de leur vie, que ce soit pendant l'ajout de nouvelles fonctionnalités ou la correction de bogues dans le code. Lorsque ces logiciels évoluent, leurs architectures ont tendance à se dégrader avec le temps et deviennent moins adaptables aux nouvelles spécifications des utilisateurs. Elles deviennent plus complexes et plus difficiles à maintenir. Dans certains cas, les développeurs préfèrent refaire la conception de ces architectures à partir du zéro plutôt que de prolonger la durée de leurs vies, ce qui engendre une augmentation importante des coûts de développement et de maintenance. Par conséquent, les développeurs doivent comprendre les facteurs qui conduisent à la dégradation des architectures, pour prendre des mesures proactives qui facilitent les futurs changements et ralentissent leur dégradation. La dégradation des architectures se produit lorsque des développeurs qui ne comprennent pas la conception originale du logiciel apportent des changements au logiciel. D'une part, faire des changements sans comprendre leurs impacts peut conduire à l'introduction de bogues et à la retraite prématurée du logiciel. D'autre part, les développeurs qui manquent de connaissances et–ou d'expérience dans la résolution d'un problème de conception peuvent introduire des défauts de conception. Ces défauts ont pour conséquence de rendre les logiciels plus difficiles à maintenir et évoluer. Par conséquent, les développeurs ont besoin de mécanismes pour comprendre l'impact d'un changement sur le reste du logiciel et d'outils pour détecter les défauts de conception afin de les corriger. Dans le cadre de cette thèse, nous proposons trois principales contributions. La première contribution concerne l'évaluation de la dégradation des architectures logicielles. Cette évaluation consiste à utiliser une technique d’appariement de diagrammes, tels que les diagrammes de classes, pour identifier les changements structurels entre plusieurs versions d'une architecture logicielle. Cette étape nécessite l'identification des renommages de classes. Par conséquent, la première étape de notre approche consiste à identifier les renommages de classes durant l'évolution de l'architecture logicielle. Ensuite, la deuxième étape consiste à faire l'appariement de plusieurs versions d'une architecture pour identifier ses parties stables et celles qui sont en dégradation. Nous proposons des algorithmes de bit-vecteur et de clustering pour analyser la correspondance entre plusieurs versions d'une architecture. La troisième étape consiste à mesurer la dégradation de l'architecture durant l'évolution du logiciel. Nous proposons un ensemble de m´etriques sur les parties stables du logiciel, pour évaluer cette dégradation. La deuxième contribution est liée à l'analyse de l'impact des changements dans un logiciel. Dans ce contexte, nous présentons une nouvelle métaphore inspirée de la séismologie pour identifier l'impact des changements. Notre approche considère un changement à une classe comme un tremblement de terre qui se propage dans le logiciel à travers une longue chaîne de classes intermédiaires. Notre approche combine l'analyse de dépendances structurelles des classes et l'analyse de leur historique (les relations de co-changement) afin de mesurer l'ampleur de la propagation du changement dans le logiciel, i.e., comment un changement se propage à partir de la classe modifiée è d'autres classes du logiciel. La troisième contribution concerne la détection des défauts de conception. Nous proposons une métaphore inspirée du système immunitaire naturel. Comme toute créature vivante, la conception de systèmes est exposée aux maladies, qui sont des défauts de conception. Les approches de détection sont des mécanismes de défense pour les conception des systèmes. Un système immunitaire naturel peut détecter des pathogènes similaires avec une bonne précision. Cette bonne précision a inspiré une famille d'algorithmes de classification, appelés systèmes immunitaires artificiels (AIS), que nous utilisions pour détecter les défauts de conception. Les différentes contributions ont été évaluées sur des logiciels libres orientés objets et les résultats obtenus nous permettent de formuler les conclusions suivantes: • Les métriques Tunnel Triplets Metric (TTM) et Common Triplets Metric (CTM), fournissent aux développeurs de bons indices sur la dégradation de l'architecture. La d´ecroissance de TTM indique que la conception originale de l'architecture s’est dégradée. La stabilité de TTM indique la stabilité de la conception originale, ce qui signifie que le système est adapté aux nouvelles spécifications des utilisateurs. • La séismologie est une métaphore intéressante pour l'analyse de l'impact des changements. En effet, les changements se propagent dans les systèmes comme les tremblements de terre. L'impact d'un changement est plus important autour de la classe qui change et diminue progressivement avec la distance à cette classe. Notre approche aide les développeurs à identifier l'impact d'un changement. • Le système immunitaire est une métaphore intéressante pour la détection des défauts de conception. Les résultats des expériences ont montré que la précision et le rappel de notre approche sont comparables ou supérieurs à ceux des approches existantes.