The objectives of this study were to determine the loading of dead and down forest fuels in 6 forest cover types on the upper Coastal Plain of Virginia, specifically in the Richmond National Battlefield Park, and to determine the relationships between the fuels and the vegetation. The forest fuels and vegetation were sampled in stands of the following cover types: pine, oak-pine, mixed hardwood-pine, oak, mixed hardwood, and oak-mixed hardwood. The planar intersect method was utilized to quantify the woody fuels. and the forest floor was sampled in fixed area plots. The weight. volume, depth. and species of fuel particles was determined for each stand sampled in the Park, and this information was combined for an estimate of fuel loading by cover type. The overstory trees were sampled within prism plots, and the understory was sampled in fixed area plots. Standard forestry information was collected for each sampled stand, and estimates of species dominance, density, frequency and importance were determined. In general, the fuel loading was not different between the six cover types as determined with ANOVA procedures. due to the large variation of loads within each. The loading of certain sizes of fuel particles were different between a few cover types, due to both the influence of the overstory species and the site they had occupied. For example, the 1-hr. time-lag branch fuel loading was significantly greater in the oak cover type than in the pine or mixed hardwood cover types. Another significant difference was in the forest floor loads: the mixed hardwood cover type had a lighter forest floor than the pine or oak-pine cover types. This was most likely due to the higher quality of sites upon which the mixed hardwood stand were found, and the higher palatability of litter produced by these species, which would favor the decomposition of litter more than conditions found in the pine or oak-pine cover types. To quantify relationships between the fuel loads and forest vegetation and site characteristics, Spearman's rank correlation coefficients were calculated between all the variables. Many significant relationships were found, though all but one correlation coefficient was under 0.51: total forest floor load and forest floor depth had a correlation coefficient of 0.75. Forest and site variables significantly related to fuel loadings were tested for their predictive value with multiple regression statistics. The resulting set of regressions had low coefficients of determination and varying levels of precision; their usefulness would depend on the level of sampling intensity and precision one would want to expend to get an estimate of fuel loading in a stand. If a rough estimate requiring little time in the field is desirable, then these regressions would be useful. / Master of Science

The link between aboveground net primary productivity (ANPP) and resource gradients generated by complex terrain (solar radiation, nutrients, and moisture) has been established in the literature. Belowground ecosystem stocks and functions, such as soil organic carbon (SOC), dissolved organic carbon (DOC), and belowground productivity have also been related to the same topography and resource distributions, and therefore it is expected that they share spatial and temporal patterns with ANPP. However, stand structure on complex terrain is a function of multiple trajectories of forest development that interact with existing resource gradients, creating feedbacks that complicate the relationships between resource availability and ANPP. On a 96 ha forested watershed in the H.J. Andrews Experimental Forest in the Western Cascades range of Oregon, spatiotemporal heterogeneity in the secondary succession of a replanted Pseudotsuga menziesii stand following harvest results from the interaction of stand composition and abiotic drivers and may create unique "hot spots" and "hot moments" that complicate gradient relationships. In this dissertation, I tested the hypotheses that (chapter 3) multiple successional trajectories exist and can be predicted from a general linear model using specific topographic, historical, and biological parameters and that an estimated "maximum ANPP" may better represent stand characteristics than ANPP measured at a particular moment in time. I also test that (chapter 4) the distribution of light fraction carbon (LFC; C with a density of less than 1.85 g/cm��) is spatially variable, elevated on hardwood-initiated sites (hardwood biomass > 50% of biomass), and positively correlated with litter fall and ANPP. Chapter 4 also tests that heavy fraction carbon (HFC; C with a density of greater than 1.85 g/cm��) is a function of both soil mineralogy, stand composition, and ANPP, such that edges observed spatially in site mineralogy (changes in soil type) are reflected in sharp changes in the composition of the forest community and the magnitude of HFC stores. Finally, I hypothesized (chapter 5) that in complex terrain, dissolved organic carbon (DOC) export can be predicted from landform characteristics, relates to ANPP, and may be measured by several methods which are well-correlated with one another. In chapter 6, I discuss how litter fall measurements can be extrapolated to a watershed extent, and use litter fall as an example of the error that can occur in scaling up measurements taken at a small scale, within a heterogeneous stand on complex terrain, to a landscape scale extent. / Graduation date: 2013

En dépit de ses ressources naturelles, le Katanga connaît une déforestation inquiétante durant ces dernières années. Avec 157.525 km², la forêt au Katanga ne recouvre plus que moins de 4% environ du territoire. Les forêts sont considérablement en régression, soit un taux de déforestation annuelle d’environ -0,20%. Ce processus s’est récemment accéléré, tout particulièrement dans les zones minières et dans les hinterlands de tous les grands centres urbains, suite à une forte pression démographique et aux activités minières qui en résultent. Le paysage forestier est donc dynamique et change, en composition et en configuration spatiale au cours du temps. L’objectif principal de cette étude était d’évaluer l’état de la fragmentation de la forêt au Katanga, en utilisant les techniques et méthodes de l‘écologie du paysage. Un accent particulier a été mis sur l’impact des activités minières sur les paysages forestiers et sur l’exploitation artisanale de bois énergie. Cette quantification de l’état de la fragmentation peut être utile d’une part aux services publics de l'État congolais pour évaluer de manière différenciée les processus de déforestation et la vulnérabilité du paysage, et d’en tirer les conséquences opérationnelles. D’autre part elle est utile aux services de recherche et de conservation pour prendre en considération les facteurs de risque de la déforestation au côté des autres (vent, pluie, érosion, crues, ruissellement, etc.). Dans la présente étude, nous nous sommes basés sur l’hypothèse selon laquelle les actions anthropiques sont les principales causes de la fragmentation de l’habitat. <p><p>Les résultats ont montré que l’exploitation minière et la croissance démographique sont deux facteurs de la déforestation, considérés comme les paramètres principaux du processus de changement du paysage au Katanga. L’analyse spatiale, faite grâce à la cartographie et aux systèmes d’information géographique, a permis de faire le calcul d’indices de composition et de configuration du paysage afin d’analyser la structure spatiale des forêts. La structure a été ensuite modélisée pour évaluer les impacts de concessions, des routes et des sites miniers sur la forêt. En fonction de résultats obtenus, on constate que les forêts du Katanga subissent une pression anthropique assez forte et la tendance générale de la fragmentation des forêts est inquiétante. Les habitats forestiers sont entrain d’être transformés en formations savanicoles. Les activités minières ont un impact défavorable sur les forêts de la province. La présence des plusieurs compagnies minières a favorisé l'augmentation des sites miniers et la densification du réseau routier. <p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Indiana University-Purdue University Indianapolis (IUPUI) / Urban forestry is a very important element of urban structures that can improve the environment and life quality within the urban areas. Having an accurate classification of urban forests and grass areas would help improve focused urban tree planting and urban heat wave mitigation efforts. This research project will compare the use of high – resolution aerial imagery and LiDAR data when used to classify canopy and grass areas. The high – resolution image, with 1 – meter resolution, was captured by The National Agriculture Imagery Program (NAIP) on 6/6/2012. Its coordinate system is the North American Datum of 1983 (NAD83). The LiDAR data, with 1.0 – meter average post spacing, was captured by Indiana Statewide Imagery and LiDAR Program from 03/13/2011 to 04/30/2012.The study area is called the Near East Side Community Organization (NESCO) neighborhood. It is located on the east side of downtown Indianapolis, Indiana. Its boundaries are: 65 interstate, East Massachusetts Avenue, East 21st Street, North Emerson Avenue, and the rail road tracks on the south of the East Washington Street. This research will also perform the accuracy assessment based on the results of classifications using high – resolution aerial imagery and LiDAR data in order to determine and explain which method is more accurate to classify urban canopy and grass areas.