985 resultados para Semi-deciduous forest


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Pollen analysis of Wisconsinan sediments from eleven localities in northern and central Illinois, combined with the results of older studies, allows a first general survey of the vegetational changes in Illinois during the last glaciation. In the late Altonian (after 40,000 B.P.), pine was already the most prevalent tree type in northern Illinois. Probably because of the influence of the last Altonian ice advance to northern Illinois, pine migrated to the south and reached south-central Illinois, which was at that time a region of prairie, with oak and hickory trees in favorable sites. Likewise in the late Altonian, spruce appeared in northern Illinois. Spruce also expanded its area to the south during the Wisconsinan, reaching south-central Illinois only after 21,000 B.P., in the early Woodfordian. Deciduous trees (predominantly oak) were present in south-central Illinois throughout the Wisconsinan. Their prevalence decreased to the north. The vegetation during the different subdivisions of the last glacial period in Illinois was approximately as follows: Late Altonian: Pine/spruce forest with some deciduous trees in northern and central Illinois; prairie and oak/hickory stands in south-central Illinois; immigration of pine. Farmdalian: Pine/spruce forest in central Illinois; deciduous trees and pine in south-central Illinois, with areas of open vegetation, perhaps similar to the present-day transition of prairie to forest in the northern Great Plains. Woodfordian: Northern and central Illinois ice covered; in south central Illinois, spruce and oak as dominant tree types, but also pine and grassland. During the Woodfordian, pine and spruce disappeared again from south-central Illinois, and oak/hickory forest and prairie again prevailed. The ice-free areas of northern Illinois become populated temporarily with spruce, but later there is proof of deciduous forest in this region. Pollen investigations in south-central Illinois have shown convincingly that deciduous trees could survive relatively close (less than 60 km) to the ice margin. Therefore the frequently presented view that arctic climatic conditions prevailed in North America during the last glaciation far south of the ice margin can be refuted for the Illinois area, confirming the opinion of other authors resulting from investigations of fossil mollusks and frost-soil features. The small number of localities investigated still permits no complete reconstruction of the vegetation zones and their possible movements in Illinois. During the Altonian and Farmdalian in Illinois, a vegetational zonation probably existed similar to that of today in North America. As the ice pushed southward as far as 39° 20' N. lat in the early Woodfordian, this zonation was apparently broken up under the influence of a relatively moderate climate. In any case, the Vandalia area, which was only about 60 km south of the ice, was at that time neither in a tundra zone nor in a zone of boreal coniferous forest.

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In this study, we investigated the relationship between vegetation and modern-pollen rain along the elevational gradient of Mount Paggeo. We apply multivariate data analysis to assess the relationship between vegetation and modern-pollen rain and quantify the representativeness of forest zones. This study represents the first statistical analysis of pollen-vegetation relationship along an elevational gradient in Greece. Hence, this paper improves confidence in interpretation of palynological records from north-eastern Greece and may refine past climate reconstructions for a more accurate comparison of data and modelling. Numerical classification and ordination were performed on pollen data to assess differences among plant communities that beech (Fagus sylvatica) dominates or co-dominates. The results show a strong relationship between altitude, arboreal cover, human impact and variations in pollen and nonpollen palynomorph taxa percentages.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Biológicas, Departamento de Ecologia, Programa de Pós-Graduação em Ecologia, 2015.

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Understanding factors that affect the distribution and abundance of species is critical to developing effective management plans for conservation. Our goal was to quantify the distribution and abundance of Canada Warbler (Cardellina canadensis), a threatened old-forest associate in Alberta, Canada. The Canada Warbler has declined across its range, including in Alberta where habitat loss and alteration from urban expansion, forestry, and energy development are changing the forest landscape. We used 110,427 point count survey visits from 32,287 unique survey stations to model local-level (150-m radius circular buffers) and stand-level (564-m radius circular buffers) habitat associations of the Canada Warbler. We found that habitat supporting higher densities of Canada Warblers was locally concentrated yet broadly distributed across Alberta’s boreal forest region. Canada Warblers were most commonly associated with older deciduous forest at the local scale, particularly near small, incised streams, and greater amounts of deciduous forest at the stand scale. Predicted density was lower in other forest types and younger age classes measured at the local scale. There was little evidence that local-scale fragmentation (i.e., edges created by linear features) influenced Canada Warbler abundance. However, current forestry practices in the province likely will reduce the availability of Canada Warbler habitat over time by cutting old deciduous forest stands. Our results suggest that conservation efforts aimed at Canada Warbler focus on retaining large stands of old deciduous forest, specifically stands adjacent to streams, by increasing the width of deciduous retention buffers along streams during harvest and increasing the size and number of old forest residual patches in harvested stands.

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Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.

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A Holocene palaeoecological sequence from Villaverde, south-central Spain, is presented. The pollen stratigraphy is used to infer past vegetation changes within a catchment area that represents the boundary between semi-arid, plateau and mountain vegetation. From c. 9700–7530 cal. yr BP, Pinus is dominant, probably as a result of a combination of a relatively dry climate and natural fire disturbance. From c. 7530–5900 cal. yr BP, moderate invasion by Quercus appears to be a migrational response following increased moisture and temperature, but in part shaped by competitive adjustments. From c. 5900–5000 cal. yr BP, the pine forests are replaced by deciduous-Quercus forests with an important contribution from Corylus, Betula, Fraxinus and Alnus. Mediterranean-type forests spread from c. 5000 to 1920 cal. yr BP coincident with expansions of Artemisia, Juniperus and other xerophytes. From c. 1920–1160 cal. yr BP, Pinus becomes dominant after a disturbance- mediated invasion of the oak forests. Human impact upon the regional landscape was negligible during the Neolithic, and limited in the Bronze and Iron Ages. Local deforestation and the expansion of agro-pastoral activities occur after c. 1600 cal. yr BP.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Für das Vermögen der Atmosphäre sich selbst zu reinigen spielen Stickstoffmonoxid (NO) und Stickstoffdioxid (NO2) eine bedeutende Rolle. Diese Spurengase bestimmen die photochemische Produktion von Ozon (O3) und beeinflussen das Vorkommen von Hydroxyl- (OH) und Nitrat-Radikalen (NO3). Wenn tagsüber ausreichend Solarstrahlung und Ozon vorherrschen, stehen NO und NO2 in einem schnellen photochemischen Gleichgewicht, dem „Photostationären Gleichgewichtszustand“ (engl.: photostationary state). Die Summe von NO und NO2 wird deshalb als NOx zusammengefasst. Vorhergehende Studien zum photostationären Gleichgewichtszustand von NOx umfassen Messungen an unterschiedlichsten Orten, angefangen bei Städten (geprägt von starken Luftverschmutzungen), bis hin zu abgeschiedenen Regionen (geprägt von geringeren Luftverschmutzungen). Während der photochemische Kreislauf von NO und NO2 unter Bedingungen erhöhter NOx-Konzentrationen grundlegend verstanden ist, gibt es in ländlicheren und entlegenen Regionen, welche geprägt sind von niedrigeren NOx-Konzetrationen, signifikante Lücken im Verständnis der zugrundeliegenden Zyklierungsprozesse. Diese Lücken könnten durch messtechnische NO2-Interferenzen bedingt sein - insbesondere bei indirekten Nachweismethoden, welche von Artefakten beeinflusst sein können. Bei sehr niedrigen NOx-Konzentrationen und wenn messtechnische NO2-Interferenzen ausgeschlossen werden können, wird häufig geschlussfolgert, dass diese Verständnislücken mit der Existenz eines „unbekannten Oxidationsmittels“ (engl.: unknown oxidant) verknüpft ist. Im Rahmen dieser Arbeit wird der photostationäre Gleichgewichtszustand von NOx analysiert, mit dem Ziel die potenzielle Existenz bislang unbekannter Prozesse zu untersuchen. Ein Gasanalysator für die direkte Messung von atmosphärischem NO¬2 mittels laserinduzierter Fluoreszenzmesstechnik (engl. LIF – laser induced fluorescence), GANDALF, wurde neu entwickelt und während der Messkampagne PARADE 2011 erstmals für Feldmessungen eingesetzt. Die Messungen im Rahmen von PARADE wurden im Sommer 2011 in einem ländlich geprägten Gebiet in Deutschland durchgeführt. Umfangreiche NO2-Messungen unter Verwendung unterschiedlicher Messtechniken (DOAS, CLD und CRD) ermöglichten einen ausführlichen und erfolgreichen Vergleich von GANDALF mit den übrigen NO2-Messtechniken. Weitere relevante Spurengase und meteorologische Parameter wurden gemessen, um den photostationären Zustand von NOx, basierend auf den NO2-Messungen mit GANDALF in dieser Umgebung zu untersuchen. Während PARADE wurden moderate NOx Mischungsverhältnisse an der Messstelle beobachtet (10^2 - 10^4 pptv). Mischungsverhältnisse biogener flüchtige Kohlenwasserstoffverbindungen (BVOC, engl.: biogenic volatile organic compounds) aus dem umgebenden Wald (hauptsächlich Nadelwald) lagen in der Größenordnung 10^2 pptv vor. Die Charakteristiken des photostationären Gleichgewichtszustandes von NOx bei niedrigen NOx-Mischungsverhältnissen (10 - 10^3 pptv) wurde für eine weitere Messstelle in einem borealen Waldgebiet während der Messkampagne HUMPPA-COPEC 2010 untersucht. HUMPPA–COPEC–2010 wurde im Sommer 2010 in der SMEARII-Station in Hyytiälä, Süd-Finnland, durchgeführt. Die charakteristischen Eigenschaften des photostationären Gleichgewichtszustandes von NOx in den beiden Waldgebieten werden in dieser Arbeit verglichen. Des Weiteren ermöglicht der umfangreiche Datensatz - dieser beinhaltet Messungen von relevanten Spurengasen für die Radikalchemie (OH, HO2), sowie der totalen OH-Reaktivität – das aktuelle Verständnis bezüglich der NOx-Photochemie unter Verwendung von einem Boxmodell, in welches die gemessenen Daten als Randbedingungen eingehen, zu überprüfen und zu verbessern. Während NOx-Konzentrationen in HUMPPA-COPEC 2010 niedriger sind, im Vergleich zu PARADE 2011 und BVOC-Konzentrationen höher, sind die Zyklierungsprozesse von NO und NO2 in beiden Fällen grundlegend verstanden. Die Analyse des photostationären Gleichgewichtszustandes von NOx für die beiden stark unterschiedlichen Messstandorte zeigt auf, dass potenziell unbekannte Prozesse in keinem der beiden Fälle vorhanden sind. Die aktuelle Darstellung der NOx-Chemie wurde für HUMPPA-COPEC 2010 unter Verwendung des chemischen Mechanismus MIM3* simuliert. Die Ergebnisse der Simulation sind konsistent mit den Berechnungen basierend auf dem photostationären Gleichgewichtszustand von NOx.

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Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

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Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

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Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation.