Submitted by William Justo Figueiro (williamjf) on 2015-08-28T17:15:44Z No. of bitstreams: 1 32e.pdf: 2782096 bytes, checksum: 5928fd17fc9df8b5902bae55c6c45acf (MD5) / Made available in DSpace on 2015-08-28T17:15:44Z (GMT). No. of bitstreams: 1 32e.pdf: 2782096 bytes, checksum: 5928fd17fc9df8b5902bae55c6c45acf (MD5) Previous issue date: 2013-08-27 / CMPC - Celulose Riograndense / A vegetação do sul do Brasil é composta pelos biomas Pampa e Mata Atlântica. Nossas áreas de estudo situam-se próximo aos limites destes dois biomas, formando um mosaico campo-floresta. A pecuária e a silvicultura de eucalipto são atividades largamente difundidas ao longo destas formações. A mudança de manejo da matriz, da pecuária para a silvicultura de eucalipto, pode levar a alterações nas características autoecológicas de espécies arbóreas florestais. O estudo das características autoecológicas em ambientes com diferentes históricos de uso da terra pode ajudar a compreender como as espécies arbóreas respondem às alterações de habitat ou das condições ambientais. Este estudo objetiva analisar como atributos autoecológicos entre espécies arbóreas florestais variam segundo uma mudança de manejo da matriz no extremo sul da Mata Atlântica, de campos nativos com pecuária extensiva para plantações de eucaliptos sobre essas pastagens. De forma específica, pretende-se (i) determinar o efeito da mudança de manejo sobre atributos autoecológicos entre espécies, e havendo este efeito, (ii) que padrões de alteração autoecológica podem ser identificados entre espécies. De acordo com nossos resultados, a mudança de manejo da matriz da paisagem causou alterações nos padrões autoecológicos das espécies arbóreas. A amplitude destas variações foi diferente para cada espécie e dependeu de sua plasticidade fenotípica e das condições ambientais locais. A longo prazo, os padrões de alterações autoecológicas encontrados podem refletir uma mudança na composição de espécies em decorrência da mudança de manejo. / The vegetation of southern Brazil is composed of Pampa and Atlantic Rain Forest biomes. Our study areas are located near the boundaries of these two biomes, forming a 24 grassland-forest mosaic. The livestock and eucalyptus plantations are widely diffused throughout these formations. The change of matrix management, of livestock for eucalyptus plantations, can lead to changes in the autoecological attributes of forest tree species. The study of the autoecological attributes in environments with different historical of land use can help to understand how tree species respond to changes in habitat or environmental conditions. This study aims to analyze how autoecological attributes between forest tree species varies as a consequence of change in management matrix at the southern Atlantic Rain Forest, of grasslands with extensive livestock for eucalyptus plantations on these pastures. Specifically, we intend to (i) determine the effect of changing management on autoecological attributes among species, and having this effect, (ii) what patterns of autoecological change can be identified between species. According to our results, the change in management of landscape matrix caused changes in autoecological patterns of tree species. The extent of these variations was different for each species and depended on their phenotypic plasticity and local environmental conditions. Long-term, patterns of autoecological change found may reflect a change in species composition due to the change in management of landscape matrix.

Bezüglich des Waldes hat sich in den letzten Jahren seitens der Politik und Wirtschaft ein steigender Informationsbedarf entwickelt. Zur Bereitstellung dieses Bedarfes stellt die Fernerkundung ein wichtiges Hilfsmittel dar, mit dem sich flächendeckende Datengrundlagen erstellen lassen. Die k-nächsten-Nachbarn-Methode (kNN-Methode), die terrestrische Aufnahmen mit Fernerkundungsdaten kombiniert, stellt eine Möglichkeit dar, diese Datengrundlage mit Hilfe der Fernerkundung zu verwirklichen. Deshalb beschäftigt sich die vorliegende Dissertation eingehend mit der kNN-Methode. An Hand der zwei Merkmale Grundfläche (metrische Daten) und Totholz (kategoriale Daten) wurden umfangreiche Berechnungen durchgeführt, wobei verschiedenste Variationen der kNN-Methode berücksichtigt wurden. Diese Variationen umfassen verschiedenste Einstellungen der Distanzfunktion, der Wichtungsfunktion und der Anzahl k-nächsten Nachbarn. Als Fernerkundungsdatenquellen kamen Landsat- und Hyperspektraldaten zum Einsatz, die sich sowohl von ihrer spektralen wie auch ihrer räumlichen Auflösung unterscheiden. Mit Hilfe von Landsat-Szenen eines Gebietes von verschiedenen Zeitpunkten wurde außerdem der multitemporale Ansatz berücksichtigt. Die terrestrische Datengrundlage setzt sich aus Feldaufnahmen mit verschiedenen Aufnahmedesigns zusammen, wobei ein wichtiges Kriterium die gleichmäßige Verteilung von Merkmalswerten (z.B. Grundflächenwerten) über den Merkmalsraum darstellt. Für die Durchführung der Berechnungen wurde ein Programm mit Visual Basic programmiert, welches mit der Integrierung aller Funktionen auf der Programmoberfläche eine benutzerfreundliche Bedienung ermöglicht. Die pixelweise Ausgabe der Ergebnisse mündete in detaillierte Karten und die Verifizierung der Ergebnisse wurde mit Hilfe des prozentualen Root Mean Square Error und der Bootstrap-Methode durchgeführt. Die erzielten Genauigkeiten für das Merkmal Grundfläche liegen zwischen 35 % und 67 % (Landsat) bzw. zwischen 65 % und 67 % (HyMapTM). Für das Merkmal Totholz liegen die Übereinstimmungen zwischen den kNN-Schätzern und den Referenzwerten zwischen 60,0 % und 73,3 % (Landsat) und zwischen 60,0 % und 63,3 % (HyMapTM). Mit den erreichten Genauigkeiten bietet sich die kNN-Methode für die Klassifizierung von Beständen bzw. für die Integrierung in Klassifizierungsverfahren an. / Mapping forest variables and associated characteristics is fundamental for forest planning and management. The following work describes the k-nearest neighbors (kNN) method for improving estimations and to produce maps for the attributes basal area (metric data) and deadwood (categorical data). Several variations within the kNN-method were tested, including: distance metric, weighting function and number of neighbors. As sources of remote sensing Landsat TM satellite images and hyper spectral data were used, which differ both from their spectral as well as their spatial resolutions. Two Landsat scenes from the same area acquired September 1999 and 2000 regard multiple approaches. The field data for the kNN- method comprise tree field measurements which were collected from the test site Tharandter Wald (Germany). The three field data collections are characterized by three different designs. For the kNN calculation a program with integration all kNN functions were developed. The relative root mean square errors (RMSE) and the Bootstrap method were evaluated in order to find optimal parameters. The estimation accuracy for the attribute basal area is between 35 % and 67 % (Landsat) and 65 % and 67 % (HyMapTM). For the attribute deadwood is the accuracy between 60 % and 73 % (Landsat) and 60 % and 63 % (HyMapTM). Recommendations for applying the kNN method for mapping and regional estimation are provided.

No description available.

Le maintien ou l'amélioration de la biodiversité est un des objectifs importants de la gestion forestière durable. La flore du sous-bois, qui représente la partie la plus diversifiée de la flore dans les forêts tempérées, joue des rôles écologiques importants. Pourtant, elle pourrait être impactée par l'augmentation de la mécanisation de la gestion forestière. A l'échelle de la parcelle, nous avons étudié en forêt de Montargis les effets simples et combinés de caractéristiques du peuplement et de la surface en cloisonnement sur la diversité floristique du sous-bois (richesse et abondance). Les caractéristiques du peuplement (type de peuplement ou surface terrière des essences à étaient les meilleurs indicateurs de la diversité du sous-bois. La surface des cloisonnements avait un effet négligeable. A plus petite échelle – à l’intérieur du cloisonnement – nous avons étudié la réponse statistique de la diversité du sous-bois à la position dans ou hors du cloisonnement, à des facteurs micro-environnementaux (humidité du sol, compaction du sol, lumière) et aux caractéristiques du peuplement. A cette échelle, les meilleurs modèles incluaient pour les groupes écologiques la position par rapport au cloisonnement, l’humidité du sol et/ou la compaction du sol, selon le groupe écologique considéré. Au niveau espèce, la position par rapport au cloisonnement était le facteur dominant. Globalement, les cloisonnements avaient soit pas d’effet soit un impact positif sur la diversité floristique de sous-bois. Ces résultats ont dépendants du contexte écologique et historique de la forêt de Montargis. L’utilisation d’engins plus lourds ou des passages répétés sur une plus longue période pourraient changer ces conclusions. / Maintaining or improving biodiversity is an important goal of sustainable forest management.Ground flora, which is responsible for most floristic diversity in temperate forests, plays multiple important roles in biodiversity but may be impacted by the increasing mechanisation of forest practices. At stand scale, we investigated in Montargis forest the individual and combined effects of tree stand attributes and skid trail area on ground flora diversity. Tree stand attributes (stand type or basal area) were the best indicators of ground flora diversity, depending on the successional traits or light preference of the species group. The effects of skid trail area were negligible. At finer scale, we studied plant response to skid trail disturbance (represented by subplot on and off skid trails), micro-environmental factors (soil moisture, soil compaction, light) and stand attribute (stand type, basal area). The best models for ecological groups included subplot location, soil moisture or soil compaction, depending on which ecological groups (classified by life form, seed bank persistence, light and moisture requirements) the species belonged to. Stand type as a covariate played a significantly important role in fine-scale diversity pattern. Subplot location was the dominant factor at species level. In conclusion, skid trails had either no impact or a positive impact on ground flora diversity. These results are dependent on the context of Montargis forest (ecological and historical), especially that mechanized harvesting is relatively recent. The employment of heavier machines and increased number of passages is likely to happen. This might induce greater soil compaction and negative effects on plant.

Bezüglich des Waldes hat sich in den letzten Jahren seitens der Politik und Wirtschaft ein steigender Informationsbedarf entwickelt. Zur Bereitstellung dieses Bedarfes stellt die Fernerkundung ein wichtiges Hilfsmittel dar, mit dem sich flächendeckende Datengrundlagen erstellen lassen. Die k-nächsten-Nachbarn-Methode (kNN-Methode), die terrestrische Aufnahmen mit Fernerkundungsdaten kombiniert, stellt eine Möglichkeit dar, diese Datengrundlage mit Hilfe der Fernerkundung zu verwirklichen. Deshalb beschäftigt sich die vorliegende Dissertation eingehend mit der kNN-Methode. An Hand der zwei Merkmale Grundfläche (metrische Daten) und Totholz (kategoriale Daten) wurden umfangreiche Berechnungen durchgeführt, wobei verschiedenste Variationen der kNN-Methode berücksichtigt wurden. Diese Variationen umfassen verschiedenste Einstellungen der Distanzfunktion, der Wichtungsfunktion und der Anzahl k-nächsten Nachbarn. Als Fernerkundungsdatenquellen kamen Landsat- und Hyperspektraldaten zum Einsatz, die sich sowohl von ihrer spektralen wie auch ihrer räumlichen Auflösung unterscheiden. Mit Hilfe von Landsat-Szenen eines Gebietes von verschiedenen Zeitpunkten wurde außerdem der multitemporale Ansatz berücksichtigt. Die terrestrische Datengrundlage setzt sich aus Feldaufnahmen mit verschiedenen Aufnahmedesigns zusammen, wobei ein wichtiges Kriterium die gleichmäßige Verteilung von Merkmalswerten (z.B. Grundflächenwerten) über den Merkmalsraum darstellt. Für die Durchführung der Berechnungen wurde ein Programm mit Visual Basic programmiert, welches mit der Integrierung aller Funktionen auf der Programmoberfläche eine benutzerfreundliche Bedienung ermöglicht. Die pixelweise Ausgabe der Ergebnisse mündete in detaillierte Karten und die Verifizierung der Ergebnisse wurde mit Hilfe des prozentualen Root Mean Square Error und der Bootstrap-Methode durchgeführt. Die erzielten Genauigkeiten für das Merkmal Grundfläche liegen zwischen 35 % und 67 % (Landsat) bzw. zwischen 65 % und 67 % (HyMapTM). Für das Merkmal Totholz liegen die Übereinstimmungen zwischen den kNN-Schätzern und den Referenzwerten zwischen 60,0 % und 73,3 % (Landsat) und zwischen 60,0 % und 63,3 % (HyMapTM). Mit den erreichten Genauigkeiten bietet sich die kNN-Methode für die Klassifizierung von Beständen bzw. für die Integrierung in Klassifizierungsverfahren an. / Mapping forest variables and associated characteristics is fundamental for forest planning and management. The following work describes the k-nearest neighbors (kNN) method for improving estimations and to produce maps for the attributes basal area (metric data) and deadwood (categorical data). Several variations within the kNN-method were tested, including: distance metric, weighting function and number of neighbors. As sources of remote sensing Landsat TM satellite images and hyper spectral data were used, which differ both from their spectral as well as their spatial resolutions. Two Landsat scenes from the same area acquired September 1999 and 2000 regard multiple approaches. The field data for the kNN- method comprise tree field measurements which were collected from the test site Tharandter Wald (Germany). The three field data collections are characterized by three different designs. For the kNN calculation a program with integration all kNN functions were developed. The relative root mean square errors (RMSE) and the Bootstrap method were evaluated in order to find optimal parameters. The estimation accuracy for the attribute basal area is between 35 % and 67 % (Landsat) and 65 % and 67 % (HyMapTM). For the attribute deadwood is the accuracy between 60 % and 73 % (Landsat) and 60 % and 63 % (HyMapTM). Recommendations for applying the kNN method for mapping and regional estimation are provided.

Mid-rotation fertilization and vegetation control are some of the most common silvicultural treatments in loblolly pine (Pinus taeda L.) plantations in the southeastern United States. Competing vegetation is commonly thought to sequester fertilizer nitrogen (N) and reduce the potential growth response to a mid-rotation fertilization treatment. This experiment aims to identify what proportion of applied N fertilizer is retained in the crop tree pine foliage, and the degree to which understory vegetation is competing for this resource. Our mid-rotation loblolly pine plantation received an application of 15N fertilization (urea 365 kg/ha, at 46% N by weight, i.e. 168 kg/ha of N) and a portion of plots received an understory vegetation control (basal spray application of triclopyr; 13.6% active ingredient) treatment either before fertilization or not at all. One-year post-fertilization, 15N contents within pine foliage, leaf fall/leaf litter, forest floor, and soil were measured, as was competing vegetation presence. There was significant variation in applied nitrogen acquisition among the different ecosystem components measured, with 0-15 cm soils retaining a majority at 32-37% added 15N. Differences in fertilizer N acquisition in pine foliage between plots with and without understory vegetation control was marginally significant (p = 0.06) with pine foliage in plots without understory vegetation capturing greater 15N (4.3% greater). Red maple (Acer rubrum) and oak species (Quercus spp.) were the most common competitors but neither had a uniquely pronounced effect on pine nitrogen sequestration. My data indicate that increasing competition reduces fertilizer N foliar concentrations in crop pine trees but at a modest rate and equally across species groups. An unrefined threshold determining when fertilizer N capture in crop pine trees was affected was found at 3.1 m2/ha of competing vegetation basal area. This site will continue to be monitored over time to assess fertilizer N retention in loblolly pine each year after fertilization and evaluate the fertilizer N capture within competing vegetation. / Master of Science / Some of the most prevalent management practices for mid-rotation (age 15, i.e., roughly halfway through a crop cycle) loblolly pine (Pinus taeda L.) plantations in the southeastern United States are fertilization and vegetation control. Nitrogen (N) is consistently one of the most limiting factors to productivity. The addition of N via fertilization is therefore a common forestry practice. However, when a stand is fertilized, the added resource is partitioned and cycled throughout the ecosystem. It is presumed that the amount of fertilizer N obtained by crop trees in a plantation is dependent on the level of competing vegetation (i.e., weed-trees and shrubs) present on site. Controlling competing vegetation prior to fertilization may therefore be warranted under certain conditions. To date, the amount of competing vegetation where it begins to impact fertilizer uptake by the crop tree is unknown. This study aims to elucidate this competing vegetation threshold to better inform mid-rotation management of loblolly pine plantations. This study examined applied fertilizer N capture in ecosystem components with varying levels of understory vegetation, and found more fertilizer N in pine foliage when understory vegetation was completely removed prior to fertilization. No single understory hardwood weed species had a uniquely strong influence on crop tree productivity uptake. Plots that ranked in the upper third in competing vegetation presence did have significantly less foliar fertilizer N in the pine crop trees. Additional replication of this study would be necessary to determine a universal threshold of competing vegetation which would trigger the removal of competing vegetation prior to fertilization.

No description available.

Contexte. Après des siècles de diminution, la surface forestière de la plupart des pays développés augmente, un phénomène appelé « transition forestière ». Le stock de bois sur pied présente une augmentation plus rapide mais son évolution, associée à des problématiques actuelles majeures, reste négligée. Il est indispensable de caractériser et comprendre ces évolutions, d’en connaître les causes sous-jacentes, et de les reconstituer sur le long terme afin de pouvoir situer les ressources forestières dans une trajectoire d’ensemble et anticiper leur dynamique future. Cette thèse est consacrée aux forêts françaises métropolitaines et repose principalement sur les données de l’IFN. Objectifs. (1) Analyser les changements de surfaces, de stock et de densité de stock et leurs hétérogénéités spatiales et temporelles, sur 40 ans (1975 – 2015) en fonction de facteurs présumés structurer ces évolutions (géographie, propriété et composition). L’existence de changements de vitesse d’expansion a été recherchée. Le lien entre les changements de stock et des propriétés de la forêt (stock et densité de stock initiaux, augmentation récente de surface) ont été analysés. (2) Analyser les mécanismes des changements de stock et décomposer l’expansion selon des ensembles forestiers homogènes du point de vue de leur dynamique. L’analyse se fonde sur une estimation des flux de stock : croissance, recrutement, mortalité et prélèvement. (3) Situer l’expansion actuelle du stock dans une dynamique séculaire. Les stocks de 1892, 1908 et 1929 (associés aux surfaces de statistiques anciennes) ont été estimés par une approche d’imputation conditionnelle de la densité. Un modèle synthétique de densification du stock des forêts a été testé afin d’étudier à quelles conditions sur cette densification il est possible de retracer la chronologie présumée du stock. Résultats. (1) Sur 40 ans, l’expansion en stock a été trois fois plus rapide que celle des surfaces, soulignant l’intensité de la densification des forêts, et ne présente aucun signe de saturation. Les forêts privées, et principalement les forêts feuillues, présentent les expansions de stock et de densité de stock les plus marquées, suggérant le rôle important de l’expansion naturelle et de l’abandon de terres agricoles. Les modèles statistiques révèlent l’effet positif du stock initial et des variations passées de surface sur l’expansion. (2) L’analyse des mécanismes d’expansion a mis en évidence le moindre niveau des prélèvements relativement à la croissance des forêts, et la contribution des forêts jeunes au développement des ressources. Quatre ensembles forestiers synthétiques de dynamiques distinctes et principalement composés de stocks en forêt privée expliquant l’expansion du stock sont identifiés. (3) La reconstitution du stock depuis 1850 suggère une faible densité de stock au début de la période (25 m3/ha) et une augmentation de stock de presque +300% entre 1892 et 2010, soulignant l’importance de cette expansion. Un modèle convexe a été nécessaire pour représenter la densification des forêts, attestant d’une inertie importante à la reconstitution des ressources, interprétée relativement à la baisse progressive des prélèvements ou à une reconstitution progressive de fertilité. Les analyses suggèrent enfin une évolution différenciée dans le temps du modèle de densification pour les forêts provenant de plantations. Conclusion. Ces travaux ont permis de montrer l’importance de l’expansion en stock et la nécessité de contextualiser cette expansion. Cette expansion ancienne ne montre pour l’instant aucune saturation et constitue un stock de carbone croissant qui ne devrait pas diminuer dans les prochaines décennies à conditions contextuelles identiques. L’analyse causale révèle qu’une part importante de l’expansion du stock ne constitue pas une ressource immédiatement disponible. Les futures politiques d’intensification des prélèvements doivent donc être circonstanciées et échelonnées dans le temps / Context. After centuries of decrease, the forest area of most developed countries increase, a phenomenon termed “forest transition”. While current increase in growing stock (GS) is greater than that in area, it remains far less studied. These changes are linked to major current issues. It is essential to assess these changes, to decipher their underlying causes, and to quantify them over the longer term in order to locate current forest resources on a broad trajectory and to anticipate their future dynamics. This thesis is dedicated to French metropolitan forests, which exhibit the most intensive changes in the growing stock in Europe, and relies on data from the French NFI program. Objectives. (1) Analyse forest areal, GS and GS density (GSD) changes and their spatio-temporal variations over 40 years (1975-2015). They were related to factors hypothesized to feature forest changes (geographical contexts, ownership and species composition). We screened for changes in the rate of expansion. The relationships between GS changes and some forest attributes (initial GS and GSD, recent forest area increase) were investigated. (2) Uncover the processes of GS changes and to split the GS expansion magnitude across dynamically-homogeneous forest ensembles. The study was based on GS flux estimation (growth, ingrowth, mortality and harvest). (3) Locate the actual GS expansion in a secular perspective. This analysis consisted in reconstructing the GS chronology since 1850. Levels of GS in 1892, 1908 and 1929 (associated to area of ancient statistics) were estimated using a conditional imputation approach for GSD estimation. Then, a holistic growing stock densification model was implemented to inquire the conditions required on densification patterns and magnitude to simulate the reconstituted GS chronology. Results. (1) Over 40 years, GS increases were three times faster than the areal ones, underlining the intensity of forest densification. No sign of saturation was found. Private forests, and mainly broadleaved ones, presented the greatest GS and GSD increases, suggesting the essential role of natural expansion and agricultural land abandonment. Regression models revealed the positive effect of initial GS and of recent areal increases on GS expansion. (2) The analysis of GS expansion processes evidenced the low level of harvests in comparison to forest growth, and the contribution of recent forests to wood resource development. It led to identify 4 synthetic forest ensembles contributing to the expansion and of distinct dynamics, mainly composed of private forests. (3) GS suggested a very low mean GSD at the beginning of the period (25 m3/ha) and a GS increase by almost +300% between 1892 and 2010, underlying the importance of this expansion. A convex growth model was required to simulate historical forest densification, attesting of a significant inertia in wood resource reconstitution after the forest transition, interpreted based on a gradual decrease in harvest rates for which indices were collected, or to a gradual recovery of site fertility. The analysis also suggested a distinct kinetics for GS densification in plantation forests. Conclusions. These researches reveal the magnitude of GS expansion and the importance of its analysis across forest contexts. This ancient expansion does not present any current sign of saturation and constitute a persistent carbon sink which should not decrease in the next decades assuming similar contextual conditions. According to the process analysis of GS expansion, a significant fraction of the GS increases does not constitute readily available additional wood resources. Thus, future harvest intensification policies must be contextualized and evolving in time