Distribución espacial, dinámica espacio-temporal, regeneración y diversidad en las comunidades de Quercus faginea del Pirineo Central Aragonés

En muchos bosques Mediterráneos, Quercus faginea se considera como un componente estructural importante de las comunidades nativas porque ofrece hábitat para una amplia diversidad de comunidades de plantas y animales, y por lo tanto, es de gran interés para la conservación de los ecosistemas. A pesar de su importancia, esta especie es poco estudiada en comparación con otras especies tal como Q. ilex y Fagus syvatica. Esta tesis doctoral analiza el efecto de los factores abióticos y el uso antrópico en la distribución de Q. faginea en el Pirineo Central, examina la dinámica espaciotemporal de los bosques de Q. faginea del Prepirineo Central durante el periodo entre 1957 y 2006, evalúa el papel del cambio del uso del suelo y el cambio climático en el establecimiento y la dinámica re-generacional de los bosques de Q. faginea, analiza la relación entre la expansión de Q. faginea observada en algunos campos abandonados y los cambios socioeconómicos en siete municipios del Prepirineo Central durante la segunda mitad del siglo XX, estudia la organización de la diversidad florística a múltiples escalas espaciales e identifica los factores ambientales que han influenciado en la distribución espacial de la diversidad florística en los bosque de Q. faginea, e investiga el efecto del uso histórico del suelo en las comunidades vegetales (diversidad y composición florística) de los bosques de Q. faginea del Prepirineo Central

Plant β-diversity i in human-altered forest ecosystems: the importance of the structural, spatial, and topographical characteristics of stands in patterning plant species assemblages

An understanding of spatial patterns of plant species diversity and the factors that drive those patterns is critical for the development of appropriate biodiversity management in forest ecosystems. We studied the spatial organization of plants species in human- modified and managed oak forests (primarily, Quercus faginea) in the Central Pre- Pyrenees, Spain. To test whether plant community assemblages varied non-randomly across the spatial scales, we used multiplicative diversity partitioning based on a nested hierarchical design of three increasingly coarser spatial scales (transect, stand, region). To quantify the importance of the structural, spatial, and topographical characteristics of stands in patterning plant species assemblages and identify the determinants of plant diversity patterns, we used canonical ordination. We observed a high contribution of ˟-diversity to total -diversity and found ˟-diversity to be higher and ˞-diversity to be lower than expected by random distributions of individuals at different spatial scales. Results, however, partly depended on the weighting of rare and abundant species. Variables expressing the historical management intensities of the stand such as mean stand age, the abundance of the dominant tree species (Q. faginea), age structure of the stand, and stand size were the main factors that explained the compositional variation in plant communities. The results indicate that (1) the structural, spatial, and topographical characteristics of the forest stands have the greatest effect on diversity patterns, (2) forests in landscapes that have different land use histories are environmentally heterogeneous and, therefore, can experience high levels of compositional differentiation, even at local scales (e.g., within the same stand). Maintaining habitat heterogeneity at multiple spatial scales should be considered in the development of management plans for enhancing plant diversity and related functions in human-altered forest

Effects of Previous Land-Use on Plant Species Composition and Diversity in Mediterranean Forests

At some point in their history, most forests in the Mediterranean Basin have been subjected to intensive management or converted to agriculture land. Knowing how forest plant communities recovered after the abandonment of forest-management or agricultural practices (including livestock grazing) provides a basis for investigating how previous land management have affected plant species diversity and composition in forest ecosystems. Our study investigated the consequences of historical “land management” practices on present-day Mediterranean forests by comparing species assemblages and the diversity of (i) all plant species and (ii) each ecological group defined by species’ habitat preferences and successional status (i.e., early-, mid-, and late-successional species). We compared forest stands that differed both in land-use history and in successional stage. In addition, we evaluated the value of those stands for biodiversity conservation. The study revealed significant compositional differentiation among stands that was due to among-stand variations in the diversity (namely, species richness and evenness) of early-, intermediate-, and late-successional species. Historical land management has led to an increase in compositional divergences among forest stands and the loss of late-successional forest species

Modeling of the current and future potential distribution of Atlas cedar (Cedrus atlantica) forests revealed shifts in the latitudinal, longitudinal and altitudinal range towards more humid conditions

Environmental forcing affects biodiversity in some parts of the biosphere where many sensitive species, including endemic and rare species, respond through changes in their geographical distribution. Modelling of spatial dynamics of species is crucial to advance our understanding of species’ adaptive behaviour and sensitivity to environmental changes and forcings. The present study aimed at assessing suitable habitats of the Atlas cedar (Cedrus atlantica) in North Algeria for the current period (1990–2000) and predicting its future range in 2050 and 2070, following climate warming scenarios. The Maximum Entropy (MaxEnt) model was used to model the present and future potential distribution of Atlas cedar forests. A total of 1,328 occurrence records obtained from field surveys and 50 environmental variables were used. These variables included 19 climatic variables (WorldClim database), 21 edaphic proprieties (SoilGrids database), and 10 topographic traits (retrieved from a 30 m digital elevation model). MaxEnt showed high predictive power with a significant value of Area Under Curve (AUC=0.988). Potential distribution of Cedrus atlantica forests for the present period was confined to mountain areas (predicted potential range size = 2089 km²). Environmental factors with the highest percentage of contribution included: soil total nitrogen (22.2%), elevation (20.5%), mean temperature of the most humid quarter ‘Bio8’ (18.8%), slope (12.9%), soil total carbon (10.3%), and precipitation of the driest month ‘Bio14’ (3.4%). The species range is expected to reduce significantly under future climate change scenarios (decline of about 70.4–80.6% of its current potential distribution), with a shift towards more humid conditions, in this case to the north and east towards more humid climates and mesic habitats. The predicted shifts in the altitude gradient follow in the direction of higher elevations, with the disappearance of cedar forests at low altitudes. This indicates that the identified Atlas cedar refugia resulting from climate change are determined by humidity. Our findings provide information on the magnitude of environmental forcings that seriously threaten Cedrus atlantica forests in drought-prone areas in North Africa. It is therefore necessary to implement effective strategies to preserve and protect more sensitive forests

Spatio-temporal dynamics of Quercus faginea forests in the Spanish Central Pre-Pyrenees

11 páginas, 2 figuras, 4 tablas.-- Fecha de publicación online.-- El PDF del artículo es la versión manuscrita de autor.Anthropomorphic changes in land use have extensively modified natural forests in the European countries over the twentieth century. This yielded a decline in the number of plant species and fragmentation of their populations. Understanding of the impact of land use changes on the spatio-temporal dynamics of forest species is essential to the ecological sustainability of the natural forests in the region. In this study, we examined the spatio-temporal dynamics of Q. faginea forests in the Central Pre-Pyrenees (Spain) over period from 1957 to 2006. Gains and losses in Q. faginea forests were quantified by means of construction of matrix of changes. Patch fragmentation, isolation, and irregularity were assessed using a set of standard landscape metrics. Also, the probable factors influencing these changes were identified employing three statistical models. The univariate generalized additive model (GAM) was used to explore the nature of the relationship between the response and predictor variables. The Bayesian model averaging (BMA) and the adaptative regression mixed with model screening (ARMS) were employed to identify the most important factors affecting changes in Quercus faginea forests. The results of this research revealed substantial changes in the spatial patterns of Q. faginea forests in the Central Pre-Pyrenees over the last 50 years. These changes have been clearly reflected in noteworthy increase of fragmentation, isolation degrees, and patch irregularity. Changes in the spatial patterns of Q. faginea forests were particularly driven by the vast introduction of pine plantations and the former deforestation, associated with increasing the amount of croplands and pastures. In addition, roads acted as attractors for changes in land use and deforestation, which influenced strongly the spatial variability in Q. faginea forests. Therefore, the long-term sustainability of these forests largely depends on the landscape conservation, where this species occurs. Moreover, an improvement in the integrity and connectivity of the remaining patches of native Q. faginea forests is still demanded.This research was funded by the Spanish Ministry of Science and Innovation (CICYT CGL2008-00655/BOS) and YK was a recipient of a pre-doctoral fellowship from the Spanish Agency for International Cooperation and Development (MAECAECID).Peer reviewe

Cours de système d'information géographique

I. Généralités........................................................................................................................ 1I.1. Définitions des Systèmes d’Information Géographique (SIG)................ 1I.2. Historique de SIG.........................................................................................................2I.3. L’information géographique (IG)..........................................................................2I.4. Les principales composantes d’un SIG ............................................................3I.5. Les fonctionnalités d’un SIG (les 5 A) ..............................................................4I.6. Domaines d’application des SIG ......................................................................... 5I.7. Le SIG idéal ................................................................................................................... 5I.8. Quelques logiciels SIG............................................................................................. 6I.8.1. Logiciels libres......................................................................................................... 6I.8.2. Logiciels Gratuits .................................................................................................. 7I.8.3. Logiciels Commerciaux....................................................................................... 7II. Les données dans les SIG......................................................................................... 8II.1. Types de données dans les SIG ......................................................................... 8II.1.1. Données spatiales ................................................................................................ 8II.1.2. Données associées ............................................................................................. 11II.2. Mode d’acquisition des données .....................................................................12II.2.1. Import de fichiers ................................................................................................12II.2.2. Levés topographiques (par l’utilisation d’un Théodolite) .............. 13II.2.3. Photos aériennes ............................................................................................... 13II.2.4. Images satellites ................................................................................................ 15II.2.5. Global Positioning System (GPS) ................................................................ 16II.2.6. Digitalisation ....................................................................................................... 16II.2.7. Scannage de plans ............................................................................................ 17II.3. Base de données géographique ..................................................................... 17III. Notions spatiales fondamentales ................................................................... 19III.1. Systèmes de référence géographique ........................................................ 19III.1.1. Coordonnées géographiques ....................................................................... 19III.1.2. Géoïde, Ellipsoïde et Datum.......................................................................... 19III.1.3. Exemples de systèmes de référence géographique ..........................21III.2. Systèmes Projections cartographiques .....................................................21IV. Analyse spatiale........................................................................................................26IV.1. Quelques définitions de l’analyse spatiale ..............................................26IV.2. Analyse spatiale en mode vecteur .............................................................26IV.2.1. Opérateurs danalyse spatiale en mode vecteur ...............................26IV.3. Analyse spatiale en mode raster..................................................................34IV.3.1. Opérateurs raster...............................................................................................34V. Interpolation des données spatiales ............................................................. 42V.1. Définition.................................................................................................................. 42V.2. L’interpolation déterministe globale ......................................................... 44V.3. L’interpolation déterministe locale ............................................................ 44V.3.1. Polygones de Thiessen ...................................................................................45V.3.2. Méthodes d’interpolation à partie d’une triangulation...................47V.3.3. Méthodes d’interpolation barycentriques.............................................48V.3.4. Les splines ...........................................................................................................50V.4. L’interpolation stochastique...........................................................................52V.4.1. Le krigeage ..........................................................................................................52VI. Modèle numérique de terrain/d’altitude ...................................................54VI.1. Définitions ............................................................................................................54VI.2. Représentation....................................................................................................54V.2.2. Semis irrégulier de points ou TIN (Triangular Irregular Network) ..............................................................................................................................................55VI.2.3. Représentation maillée (grille, matrice, raster)...............................56VI.3. Formats et résolution .....................................................................................56VI.4. Modes d’acquisition de l’altitude ............................................................. 57VI.4.1. Acquisition directe par des méthodes de topométrie : Levés sur le terrain de topométrie ............................................................................................... 57VI.4.2. Numérisation (vectorisation) de courbes de niveau provenant de cartes .................................................................................................................................58VI.4.3. Restitution photogrammétrique de photographies aériennes.58VI.4.4. Radargrammétrie ..........................................................................................60VI.4.5. Laser grammétrie ou altimétrie par «laser à balayage»............ 61VI.5. Les erreurs du MNT .........................................................................................64VI.6. Comparatif de validité.....................................................................................65VI.7. Quelques sources de MNT/MNA.................................................................65VI.8. Variables du relief dérivées.........................................................................66VI.8.1.Pente, orientation...........................................................................................66VI.8.2. Concavité, convexité ..................................................................................66VI.9. Variables thématiques dérivées ...............................................................66VI.9.1. Visibilité............................................................................................................ 67VI.9.2. Ombre portée et ombre projetée........................................................... 67VI.9.3. Taux d’ensoleillement ................................................................................68VI.9.4. Ligne de drainage..........................................................................................69VI.9.5. Limites de bassin versant hydrologique ......................................... 70VI.10. Domaines d’application ............................................................................ 70VI.10.1. Usages du MNA ......................................................................................... 70VI.11. Usages du MNA ..............................................................................................72VII. Création des cartes d’aptitudes ................................................................ 75VII.1. Etape 1 : définition du problème .......................................................... 75VII.2. Etape 2 : décomposition du problème ............................................. 76VII.2.1. Où sont les emplacements dont le terrain est relativement plat ? ........................................................................................................................................ 76VII.2.2. L’utilisation du sol est-elle appropriée dans ces emplacements ? ....................................................................................................................................... 76VII.2.3. Ces emplacements sont-ils assez proches d’installations récréatives ?............................................................................................................ 77VII.2.4. Sont-ils assez éloignés des écoles existantes ?..................... .77VII.3. Etape 3 : exploration des jeux de données en entrée ......... ..78VII.4. Etape 4 : exécution de .l'analyse..................................................... 79VII.4.1. Classement des zones à proximité d’installations récréatives avec l’outil reclassification ........................................................................... 81VII.4.2. Classement des zones éloignées des écoles existantes....83VII.4.3. Classement des pentes du terrain ..............................................84VII.4.4. Classement des occupations du sol ...........................................86VII.4.5. Regroupement des cartes d’aptitude......................................... 87VII.4.6. Superposition pondérée ...................................................................90MasterDepuis plus de trente ans, le développement de l'informatique a entraîné des modifications importantes pour la géographie et la cartographie. La production de données s'est accélérée, grâce à de nouvelles méthodes de collecte et d'acquisition. Le traitement des données localisées s'est largement développé, avec la saisie numérique des données graphiques, cartes et plans, avec les systèmes de gestion de bases de données et les capacités de stockage des systèmes informatiques.Enfin, de nombreux aspects de la cartographie ont été automatisés et les techniques de production complètement modifiées, avec en corollaire uneaccélération de la diffusion et de l'utilisation de données géographiques. Les systèmes d’information géographique ont la particularité de faire appel à de nombreux domaines scientifiques et techniques tel que la géodésie, les systèmes de gestion de bases de données, le traitement d’images, l’algorithmique géométrique, la modélisation et l’interpolation géométrique, la statistique, la cartographie automatique, l’analyse spatiale, etc. Les systèmes d’information géographique ont aussi la particularité de regrouper différentes méthodes et techniques informatiques qui leurs permettent de modéliser, de saisir sous forme numérique, de stocker, de gérer, de consulter, d'analyser, de représenter des objets ou des collections d'objets géographiques, avec la spécificité de prendre en compte les caractéristiques spatiales de ces objets au même titre que les attributsdescriptifs qui y sont attachés.Ce polycopié est consacré à l’étude des différents concepts autour des systèmes d’information géographique. Il prend en compte le fait que les étudiants seront confrontés lors de leurs futures activités à des problématiques de gestion d’information géographique. Le polycopié présente les différentes clés qui leur permettront de remplir soit des fonctions techniques autour du SIG soit de gérer des projets traitant de données géographiques (gestion de prestataires, maîtrise d’ouvrage, management d’équipe SIG, composante SIG d’un projet plus général, etc.)Ainsi à l’issue de ce cours, les étudiants seront capables de :- Comprendre la notion de l’information géographique numérique.- Comprendre les concepts de bases des SIG.- Découvrir les fonctionnalités des SIG.- Utiliser efficacement les outils SIG de traitements de données urbaines mis à leur disposition dans le cadre de leur vie professionnelle.- Découvrir la variété de domaines d’application.- Pratiquer sur le logiciel SIG Arc GIS

Spatial distribution, spatio-temporal dynamic, regeneration, and diversity in the Quercus faginea communities of the Aragón' s Central Pyrenees

199 páginas.- Memoria presentada por Yacine Kouba para optar al grado de Doctor en Geografía por la Universidad de Zaragoza (2014)En muchos bosques Mediterráneos, Quercus faginea se considera como un componente estructural importante de las comunidades nativas porque ofrece hábitat para una amplia diversidad de comunidades de plantas y animales, y por lo tanto, es de gran interés para la conservación de los ecosistemas. A pesar de su importancia, esta especies es poco estudiada en comparación con otras especies tal como Q. ilex y Fagus syvatica. Esta tesis doctoral (i) analiza el efecto de los factores abióticos y el uso antrópico en la distribución de Q. faginea en el Pirineo Central, (ii) examina la dinámica espaciotemporal de los bosques de Q. faginea del Prepirineo Central durante el periodo entre 1957 y 2006, (iii) evalúa el papel del cambio del uso del suelo y el cambio climático en el establecimiento y la dinámica re-generacional de los bosques de Q. faginea, (iv) analiza la relación entre la expansión de Q. faginea observada en algunos campos abandonados y los cambios socioeconómicos en siete municipios del Prepirineo Central durante la segunda mitad del siglo XX, (v) estudia la organización de la diversidad florística a múltiples escalas espaciales e identifica los factores ambientales que han influenciado en la distribución espacial de la diversidad florística en los bosque de Q. faginea, e (vi) investiga el efecto del uso histórico del suelo en las comunidades vegetales (diversidad y composición florística) de los bosques de Q. faginea del Prepirineo Central.Peer reviewe

Effects of abiotic and anthropogenic factors on the spatial distribution of Quercus faginea in the Spanish Central Pyrenees

9 páginas, 1 tabla, 1 figura.-- El PDF del artículo es su versión post-print.Abiotic factors often are the most important factors influencing a species’ distribution. Nevertheless, when investigating the underlying causes of a species’ distribution, it is important to assess both the abiotic and the anthropogenic factors (land-use variables) that might have influenced the species’ distribution. That is especially true in the Mediterranean Basin, where natural ecosystems have undergone significant changes in response to anthropogenic pressures in the region. In this study, we examined the effects of abiotic and anthropogenic factors on the distribution of Quercus faginea in the Spanish Central Pyrenees. Information on the presence–absence of Q. faginea, and abiotic and anthropogenic variables, were derived using GIS based on digital maps and aerial photographs. To identify and quantify the factors that have affected significantly the spatial distribution of Q. faginea, we used Bayesian Model Averaging and hierarchical partitioning. In the Spanish Central Pyrenees, on a broad scale, abiotic variables; i.e. climate and lithology, were the factors that had the greatest effect on the spatial distribution of Q. faginea; however, recently introduced pine plantations and previous livestock pressure have had a negative effect on the distribution of Q. faginea in the region.The Spanish CICYT CGL2008-00655/ BOS Project supported this research financially. The first author was supported through MAEC-AECID grant from the Spanish Agency for International Cooperation and Development.Peer reviewe

Vegetation transects Sierra de Guara (Huesca, Spain)

This data set include 30 vegetation transects of 500 m length each, sampled by point intercept method every 40 cm. Transects Geographical location withprojection system: ETRS89. Vegetation community: Quercus faginea forest. Species code included Methodology and area description can be found in : Kouba, Y, Alados, C. L: Bueno, G. (2011) Effects of abiotic and anthropogenic factors on the spatial distribution of Quercus faginea in the Spain Central Pyrenees. Plant Ecology. 212(6): 999-1007 Kouba, Y, Alados, C. L. (2012) Spatio-temporal dynamics of Quercus faginea forests in the Spanish Central Pre-Pyrenees. European Journal of Forest Research 131, 369-379 DOI 10.1007/s10342-011-0509-1. Kouba, Y., Camarero J.J. & Alados, C.L. 2012. Roles of land-use and climate change on the establishment and regeneration dynamics of Mediterranean semi-deciduous oak forests. Forest Ecology and Management 274: 143-150. Kouba, Y., Martínez-García, F., De Frutos, A., Alados, C. L. (2014). Plant β-diversity in human-altered forest ecosystems: The importance of the structural, spatial, and topographical characteristics of stands in patterning plant species assemblages. European Journal of Forest Research. DOI 10.1007/s10342-014-0822-6. Kouba, Y., Martínez_García, F., De Frutos, A., Alados, C.L., 2015. Effects of previous land-use on plant species composition and diversity in Mediterranean forests. PlosOne 10(9): e0139031.This work was supported by the following research projects: Spanish Ministry of Science and Innovation (CICYT: CGL2008-00655/BOS and CGL2008-04847-C02-01/BOS)Peer reviewe

The Influence of Tourism Development Strategies on the Attractiveness of Mountainous Destinations: A Case Study of the Aures Mountains in Algeria

Tourism development strategies play a crucial role in tourism development. However, the reaction of the former to the needs of visitors and its effect on attractiveness is essential, especially in mountainous destinations. This study evaluates the impact of tourism development strategies on the attractiveness of mountain destinations. The study relied on appropriate elements derived from the literature. The study was conducted in three tourist sites in the Aures Mountains, and the sample included 468 visitors. The results showed that the destination’s attractiveness depends mainly on local factors such as nature, monuments, traditional food, and apple purchase, in addition to the quality of the price, which received the satisfaction of the majority of visitors. In turn, visitors were dissatisfied with the services assigned to tourism development strategies, such as accommodation, entertainment, communications, and transportation. The results also showed that the return to the destination is affected by nature and determined by several factors such as age, gender, use of a specific vehicle, and proximity. Therefore, the destination’s attractiveness is not based on the elements assigned to tourism strategies; this indicates the gap in local potential and tourism development