982 resultados para tropical forests


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ZusammenfassungDie Spurengase NOx (Stickstoffoxid (NO) und Stickstoffdioxid (NO2)) haben massgeblichen Einfluss auf die Produktion von OH (Hydroxylradikal) und Ozon (O3) in der Troposphäre. Die Bodenemissionen dieser Gase sind weitgehend unbekannt. Das Ziel dieser Arbeit war, die für die NO Bodenemissionen relevanten Prozesse durch Labor und Feldmessungen zu untersuchen und diese durch Modellsimulationen für zwei Regionen, ein tropisches Regenwaldgebiet in Rondônia (Brasilien) und subtropische Savannen in Zimbabwe abzuschätzen. Unter Verwendung der gemessenen NO Werte ergaben die Simulationen mit einem modifizierten prozessorientierten Modell, dass Abholzung in den Tropen nach einer kurzzeitigen Erhöhung zu einer langfristigen Abnahme der Bodenemissionen führt. Ein 'up scaling' der Modellresultate ergab ausgehend von der ursprünglichen Bewaldung der Region eine Verdopplung der NO Bodenemission bis 1999. Sowohl für nährstoffarme Böden der Tropen als auch für die nährstoffreichen Savannenböden waren Landnutzung und Bodenfeuchte die wichtigsten Einflussgrössen für die Regulierung der Emissionen. Über den Zeitraum eines Jahres waren die Emissionsraten der Tropen (0.49 kgNhayr-1) ungefähr halb so gross wie die der subtropischen Savannen (0.86 kgNhayr-1). Solange die Abholzung der Regenwälder voranschreitet werden die Tropen starken Einfluss auf die troposphärische Chemie haben.

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Volatile organic compounds play a critical role in ozone formation and drive the chemistry of the atmosphere, together with OH radicals. The simplest volatile organic compound methane is a climatologically important greenhouse gas, and plays a key role in regulating water vapour in the stratosphere and hydroxyl radicals in the troposphere. The OH radical is the most important atmospheric oxidant and knowledge of the atmospheric OH sink, together with the OH source and ambient OH concentrations is essential for understanding the oxidative capacity of the atmosphere. Oceanic emission and / or uptake of methanol, acetone, acetaldehyde, isoprene and dimethyl sulphide (DMS) was characterized as a function of photosynthetically active radiation (PAR) and a suite of biological parameters, in a mesocosm experiment conducted in the Norwegian fjord. High frequency (ca. 1 minute-1) methane measurements were performed using a gas chromatograph - flame ionization detector (GC-FID) in the boreal forests of Finland and the tropical forests of Suriname. A new on-line method (Comparative Reactivity Method - CRM) was developed to directly measure the total OH reactivity (sink) of ambient air. It was observed that under conditions of high biological activity and a PAR of ~ 450 μmol photons m-2 s-1, the ocean acted as a net source of acetone. However, if either of these criteria was not fulfilled then the ocean acted as a net sink of acetone. This new insight into the biogeochemical cycling of acetone at the ocean-air interface has helped to resolve discrepancies from earlier works such as Jacob et al. (2002) who reported the ocean to be a net acetone source (27 Tg yr-1) and Marandino et al. (2005) who reported the ocean to be a net sink of acetone (- 48 Tg yr-1). The ocean acted as net source of isoprene, DMS and acetaldehyde but net sink of methanol. Based on these findings, it is recommended that compound specific PAR and biological dependency be used for estimating the influence of the global ocean on atmospheric VOC budgets. Methane was observed to accumulate within the nocturnal boundary layer, clearly indicating emissions from the forest ecosystems. There was a remarkable similarity in the time series of the boreal and tropical forest ecosystem. The average of the median mixing ratios during a typical diel cycle were 1.83 μmol mol-1 and 1.74 μmol mol-1 for the boreal forest ecosystem and tropical forest ecosystem respectively. A flux value of (3.62 ± 0.87) x 1011 molecules cm-2 s-1 (or 45.5 ± 11 Tg CH4 yr-1 for global boreal forest area) was derived, which highlights the importance of the boreal forest ecosystem for the global budget of methane (~ 600 Tg yr-1). The newly developed CRM technique has a dynamic range of ~ 4 s-1 to 300 s-1 and accuracy of ± 25 %. The system has been tested and calibrated with several single and mixed hydrocarbon standards showing excellent linearity and accountability with the reactivity of the standards. Field tests at an urban and forest site illustrate the promise of the new method. The results from this study have improved current understanding about VOC emissions and uptake from ocean and forest ecosystems. Moreover, a new technique for directly measuring the total OH reactivity of ambient air has been developed and validated, which will be a valuable addition to the existing suite of atmospheric measurement techniques.

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Within this doctoral thesis, biogenic emissions of several globally relevant halocarbons (methyl chloride, methyl bromide, methyl iodide, dibromomethane, chloroform and bromoform) have been investigated in different environments. An airborne study was focused on the tropical rainforest ecosystem, while shipborne measurements investigated naturally occurring oceanic plankton blooms. Laboratory experiments using dried plant material were made to elucidate abiotic production mechanisms occurring in organic matter. Airborne measurements over the tropical rainforest of Suriname and French Guyana (3 - 6 °N, 51 - 59 °W) revealed net fluxes of 9.5 (± 3.8 2σ) µg m-2 h-1 methyl chloride and 0.35 (± 0.15 2σ) µg m-2 h-1 chloroform emitted in the long dry season (October) 2005. An extrapolation of these numbers to all tropical forests helped to narrow down the range of the recently discovered and poorly quantified methyl chloride source from tropical ecosystems. The value for methyl chloride obtained (1.5 (± 0.6 2σ) Tg yr-1) affirms that the contribution of the tropical forest ecosystem is the major source in the global budget of methyl chloride. The extrapolated global net chloroform flux from tropical forests (56 (± 23 2σ) Gg yr-1) is of minor importance (5 - 10 %) compared to the global sources. A source of methyl bromide from this region could not be verified. The abiotic formation of methyl chloride and methyl bromide from dead plant material was tested in a laboratory study. The release from plant tissue representative of grassland, deciduous forest, agricultural areas and coastal salt marshes (hay, ash, tomato and saltwort) has been monitored. Incubations at different temperatures (25 - 50 °C) revealed significant emissions even at ambient temperature, and that the emissions increased exponentially with temperature. The strength of the emission was found to be additionally dependent on the availability of halide and the methoxyl group within the plant tissue. However, high water content in the plant material was found to inhibit methyl halide emissions. The abiotic nature of the reaction yielding methyl halides was confirmed by its high activation energy calculated via Arrhenius plots. Shipborne measurements of the atmospheric mixing ratios of methyl chloride, methyl bromide, methyl iodide, dibromomethane and bromoform have been conducted along a South Atlantic transect from the 27.01. - 05.02.2007 to characterize halocarbon emissions from a large-scale natural algae bloom encountered off the coast of Argentina. Mixing ratios of methyl chloride and methyl bromide were not significantly affected by the occurrence of the phytoplankton bloom. Emissions of methyl iodide, dibromomethane and bromoform showed pronounced mixing ratio variations, triggered by phytoplankton abundance. Methyl iodide was strongly correlated with dimethyl sulfide throughout the sampled region. A new technique combining satellite derived biomass marker (chlorophyll a) data with back trajectory analysis was successfully used to attribute variations in mixing ratios to air masses, which recently passed over areas of enhanced biological production.

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Where one or a few tree species reach local high abundance, different ecological factors may variously facilitate or hinder their regeneration. Plant pathogens are thought to be one of those possible agents which drive intraspecific density-dependent mortality of tree seedlings in tropical forests. Experimental evidence for this is scarce, however. In an African rain forest at Korup, we manipulated the density of recently established seedlings (~5–8 wk old; low vs. high-density) of two dominant species of contrasting recruitment potential, and altered their exposure to pathogens using a broad-spectrum fungicide. Seedling mortality of the abundantly recruiting subcanopy tree Oubanguia alata was strongly density-dependent after 7 mo, yet fungicide-treated seedlings had slightly higher mortality than controls. By contrast, seedling mortality of the poorly recruiting large canopy-emergent tree Microberlinia bisulcata was unaffected by density or fungicide. Ectomycorrhizal colonization of M. bisulcata was not affected by density or fungicide either. For O. alata, adverse effects of fungicide on its vesicular arbuscular mycorrhizas may have offset any possible benefit of pathogen removal. We tentatively conclude that fungal pathogens are not a likely major cause of density dependence in O. alata, or of early post-establishment mortality in M. bisulcata. They do not explain the latter's currently very low recruitment rate at Korup.

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Tropical trees have been shown to be more susceptible to warming compared to temperate species, and have shown growth and photosynthetic declines at elevated temperatures as little as 3oC above ambient. However, regional and global vegetation models lack the data needed to accurately represent physiological response to increased temperatures in tropical forests. We compared the instantaneous photosynthetic responses to elevated temperatures of four mature tropical rainforest tree species in Puerto Rico and the temperate broadleaf species sugar maple (Acer saccharum) in Michigan. Contrary to expectations, leaves in the upper canopy of both temperate and tropical forests had temperature optima that are already exceeded by mean daily leaf temperatures. This indicates that tropical and temperate forests are already seeing photosynthesis decline at mid-day temperature. This decline may worsen as air temperatures rise with climate change if trees are unable to acclimate, increasing the likelihood that forests may shift from carbon sinks to sources. A secondary study was conducted on experimentally warmed sugar maple seedlings to determine if photosynthesis had been able to acclimate to +5oC air temperature over four years. Species abundance models had predicted a decline of sugar maple within the Upper Peninsula of Michigan over the next 100 years, due to elevated temperature and altered precipitation. Instantaneous photosynthetic temperature response curves on both control and heated seedlings showed that the differences between treatments were not statistically significant, though there was a 16% increase in temperature optima and a 3% increase in maximum rates of photosynthesis in warmed plots. Though evidence of acclimation was not significant, the seedlings did not fare poorly as the models suggest.

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Incident rainfall is a major source of nutrient input to a forest ecosystem and the consequent throughfall and stemflow contribute to nutrient cycling. These rain-based fluxes were measured over 12 mo in two forest types in Korup National Park, Cameroon, one with low (LEM) and one with high (HEM) ectomycorrhizal abundances of trees. Throughfall was 96.6 and 92.4% of the incident annual rainfall (5370 mm) in LEM and HEM forests respectively; stemflow was correspondingly 1.5 and 2.2%. Architectural analysis showed that ln(funneling ratio) declined linearly with increasing ln(basal area) of trees. Mean annual inputs of N, P, K, Mg and Ca in incident rainfall were 1.50, 1.07, 7.77, 5.25 and 9.27 kg ha(-1), and total rain-based inputs to the forest floor were 5.0, 3.2, 123.4, 14.4 and 37.7 kg ha-1 respectively. The value for K is high for tropical forests and that for N is low. Nitrogen showed a significantly lower loading of throughfall and stemflow in HEM than in LEM forest, this being associated in the HEM forest with a greater abundance of epiphytic bryophytes which may absorb more N. Incident rainfall provided c. 35% of the gross input of P to the forest floor (i. e., rain-based plus small litter inputs), a surprisingly high contribution given the sandy P-poor soils. At the start of the wet season leaching of K from the canopy was particularly high. Calcium in the rain was also highest at this time, most likely due to washing off of dry-deposited Harmattan dusts. It is proposed that throughfall has an important `priming' function in the rapid decomposition of litter and mineralization of P at the start of the wet season. The contribution of P inputted from the atmosphere appears to be significant when compared to the rates of P mineralization from leaf litter.

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The growth rate of atmospheric carbondioxide(CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO 2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

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The Janzen–Connell hypothesis proposes that specialized herbivores maintain high numbers of tree species in tropical forests by restricting adult recruitment so that host populations remain at low densities. We tested this prediction for the large timber tree species, Swietenia macrophylla, whose seeds and seedlings are preyed upon by small mammals and a host-specific moth caterpillar Steniscadia poliophaea, respectively. At a primary forest site, experimental seed additions to gaps – canopy-disturbed areas that enhance seedling growth into saplings – over three years revealed lower survival and seedling recruitment closer to conspecific trees and in higher basal area neighborhoods, as well as reduced subsequent seedling survival and height growth. When we included these Janzen–Connell effects in a spatially explicit individual-based population model, the caterpillar's impact was critical to limiting Swietenia's adult tree density, with a > 10-fold reduction estimated at 300 years. Our research demonstrates the crucial but oft-ignored linkage between Janzen–Connell effects on offspring and population-level consequences for a long-lived, potentially dominant tree species.

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Conspecific effects of neighbours on small-tree survival may have a role in tree population dynamics and community composition of tropical forests. This notion was tested with data from two 4-ha plots in lowland forest at Danum, Sabah (Borneo), for a 21-year interval (censuses at 1986, 1996, 2001, 2007). Species with ≥45 focal trees 10 to <100 cm stem girth per plot in 1986 were selected. Logistic regressions fitted mean focal tree size and mean inverse-distance-weighted basal area abundance of neighbours (within 20 m), for the periods over which each focus tree was alive. Coefficients of variation of neighbourhood basal area abundance, both spatially and temporally, quantified the changing environment of each focus tree. Fits were critically and individually evaluated, with corrections for spatial autocorrelation. Conspecific effects at Danum was generally very weak or non-existent: species’ mortality rates varied also across plots. The main reasons appear to be that (1) species were not dense enough to interact despite frequent although weak spatial aggregation, and their neighbourhoods were highly differing in species composition; and (2) these neighbourhoods were highly variable temporally, meaning that focus trees experienced stochastically fluctuating neighbourhood environments. Only one species, Dimorphocalyx muricatus, showed strong conspecific effects (varying between plots) which can be explained by its distinct ecology. This understorey species is highly aggregated on ridges and is drought-tolerant. That this functionally and habitat-specialized species, has implied intraspecific density-dependent feedback in its dynamics is a remarkable indication of the overall processes maintaining stability of the Danum forest.

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Seven sediment cores from the cruises of the "Meteor" and "Valdivia" were examined palynologically. The cores were retrieved from the lower continental slope in the area of between 33.5° N and 8° N, off the West African coast. Most of the cores contain sediments from the last Glacial and Interglacial period. In some cases, the Holocene sediments are missing. Some individual cores contain sediments also from earlier Glacial and Interglacial periods. The main reason for making this palynological study was to find out the differences between the vegetation of Glacial and Interglacial periods in those parts of West Africa which at present belong to the Mediterranean zone, the Sahara and the zones of the savannas and tropical forests. In today's Mediterranean vegetation zone at core 33.5° N, forests and deciduous forests in particular, are missing during Glacial conditions. Semi-deserts are found instead of these. In the early isotope stage 1, there is a very significant development of forests which contain evergreen oaks; this is the Mediterranean type of vegestation development. The Sahara type of vegetation development is shown in four cores from between 27° N and 19° N. The differences between Glacial and Interglacial periods are very small. It must be assumed therefore that in this latitudes, both Glacial and Interglacial conditions gave rise to desert generally. The results are in favour of a slightly more arid climate during Glacial and more humid one during Interglacial periods. The southern boundary of the Sahara and the adjacent savannas with grassland and tropical woods were situated more to the south during the Glacial periods than they were during the Interglacial ones. In front of today's savanna belt, it can be seen from the palynological results that there are considerable differences between the vegetation of Glacial and Interglacial periods. The woods are more important in Interglacial periods. During the Glacial periods these are replaced from north to south decreasingly by grassland (savanna and rainforest type of vegetation development). The southern limit of the Sahara during stage 2 was somewhat between 12° N and 8° N which is between 1.5 and 5 degrees in latitude further south than it i s today. Not only do these differences in climate and vegetation apply to the maximum of the last Glacial and for the Holocene, but they apparently apply also to the older Glacial and Interglacial periods, where they have been found in the profiles. The North African deset belt can be said to have expanded during Glacial times both towards the north and towards the south. All the available evidence of this study indicates that the grass land or the semi-desert of the Southern Europe cam einto connection with those of the N Africa; there could not have been any forest zone between them. The present study was also a good opportunity for investigating some of the basic marine palynological problems. The very well known overrepresentation of pollen grains of the genus Pinus in marine sediments can be traced as fa as 21° N. The present southern limit for the genus Pinus is on the Canaries and on the African continent as approximately 31° N. Highest values of Ephedra pollen grains even occur south of the main area of the present distribution of that genus. These does not seem to be any satisfactory explanation for this. In general, it would appear that the transport of pollen grains from the north is more important than transport from the south. The results so far, indicate strongly that further palynological studies are necessary. These should concentrate particularly on cores from between 33° N and 27° N as well as between 17° N and 10° N. It would also be useful to have a more detailed examination of sediments from the last Intergalcial period (substage 5 e). Absolute pollen counts and more general examination of surface samples would be desirable. Surface samples should be taken from the shelf down to the bottom of the continental slope in different latitudes.

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Species?habitat associations may contribute to the maintenance of species richness in tropical forests, but previous research has been conducted almost exclusively in lowland forests and has emphasized the importance of topography and edaphic conditions. Is the distribution of woody plant species in a Peruvian cloud forest determined by microhabitat conditions? What is the role of environmental characteristics and forest structure in habitat partitioning in a tropical cloud forest? We examined species?habitat associations in three 1-ha plots using the torus-translation method. We used three different criteria to define habitats for habitat partitioning analyses, based on microtopography, forest structure and both sets of factors. The number of species associated either positively or negatively with each habitat was assessed. Habitats defined on the basis of environmental conditions and forest structure discriminated a greater number of positive and negative associations at the scale of our analyses in a tropical cloud forest. Both topographic conditions and forest structure contribute to small-scale microhabitat partitioning of woody plant species in a Peruvian tropical cloud forest. Nevertheless, canopy species were most correlated with the distribution of environmental variables, while understorey species displayed associations with forest structure.

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Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- andWeibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (?40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8Mgha?1 (range 6.6 to 112.4) to 8.0Mgha?1 (?2.5 to 23.0). For all plots, aboveground live biomass was ?52.2 Mgha?1 (?82.0 to ?20.3 bootstrapped 95%CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in eastcentral Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 PgC (31?39 bootstrapped 95%CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

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La pérdida de bosques en la Tierra, principalmente en ecosistemas amazónicos, es un factor clave en el proceso del cambio climático. Para revertir esta situación, los mecanismos REDD (Reducing Emission from Deforestation and forest Degradation) están permitiendo la implementación de actividades de protección del clima a través de la reducción de emisiones por deforestación evitada, según los esquemas previstos en el Protocolo de Kioto. El factor técnico más crítico en un proyecto REDD es la determinación de la línea de referencia de emisiones, que define la expectativa futura sobre las emisiones de CO2 de origen forestal en ausencia de esfuerzos adicionales obtenidos como consecuencia de la implementación del programa REDD para frenar este tipo de emisiones. La zona del estudio se ubica en la región de San Martín (Perú), provincia cubierta fundamentalmente por bosques tropicales cuyas tasas de deforestación son de las más altas de la cuenca amazónica. En las últimas décadas del siglo XX, la región empezó un acelerado proceso de deforestación consecuencia de la integración vial con el resto del país y la rápida inmigración desde zonas rurales en busca de nuevas tierras agrícolas. Desde el punto de vista de la investigación llevada a cabo en la tesis doctoral, se pueden destacar dos líneas: 1. El estudio multitemporal mediante imágenes de satélite Landsat 5/TM con el propósito de calcular las pérdidas de bosque entre períodos. El estudio multitemporal se llevó a cabo en el período 1998-2011 utilizando imágenes Landsat 5/TM, aplicando la metodología de Análisis de Mezclas Espectrales (Spectral Mixtures Analysis), que permite descomponer la reflectancia de cada píxel de la imagen en diferentes fracciones de mezcla espectral. En este proceso, las etapas más críticas son el establecimiento de los espectros puros o endemembers y la recopilación de librerías espectrales adecuadas, en este caso de bosques tropicales, que permitan reducir la incertidumbre de los procesos. Como resultado de la investigación se ha conseguido elaborar la línea de referencia de emisiones histórica, para el período de estudio, teniendo en cuenta tanto los procesos de deforestación como de degradación forestal. 2. Relacionar los resultados de pérdida de bosque con factores de causalidad directos e indirectos. La determinación de los procesos de cambio de cobertura forestal utilizando técnicas geoespaciales permite relacionar, de manera significativa, información de los indicadores causales de dichos procesos. De igual manera, se pueden estimar escenarios futuros de deforestación y degradación de acuerdo al análisis de la evolución de dichos vectores, teniendo en cuenta otros factores indirectos o subyacentes, como pueden ser los económicos, sociales, demográficos y medioambientales. La identificación de los agentes subyacentes o indirectos es una tarea más compleja que la de los factores endógenos o directos. Por un lado, las relaciones causa – efecto son mucho más difusas; y, por otro, los efectos pueden estar determinados por fenómenos más amplios, consecuencia de superposición o acumulación de diferentes causas. A partir de los resultados de pérdida de bosque obtenidos mediante la utilización de imágenes Landsat 5/TM, se investigaron los criterios de condicionamiento directos e indirectos que podrían haber influido en la deforestación y degradación forestal en ese período. Para ello, se estudiaron las series temporales, para las mismas fechas, de 9 factores directos (infraestructuras, hidrografía, temperatura, etc.) y 196 factores indirectos (económicos, sociales, demográficos y ambientales, etc.) con, en principio, un alto potencial de causalidad. Finalmente se ha analizado la predisposición de cada factor con la ocurrencia de deforestación y degradación forestal por correlación estadística de las series temporales obtenidas. ABSTRACT Forests loss on Earth, mainly in Amazonian ecosystems, is a key factor in the process of climate change. To reverse this situation, the REDD (Reducing Emission from Deforestation and forest Degradation) are allowing the implementation of climate protection activities through reducing emissions from avoided deforestation, according to the schemes under the Kyoto Protocol. Also, the baseline emissions in a REDD project defines a future expectation on CO2 emissions from deforestation and forest degradation in the absence of additional efforts as a result of REDD in order to stop these emissions. The study area is located in the region of San Martín (Peru), province mainly covered by tropical forests whose deforestation rates are the highest in the Amazon basin. In the last decades of the twentieth century, the region began an accelerated process of deforestation due to road integration with the rest of the country and the rapid migration from rural areas for searching of new farmland. From the point of view of research in the thesis, we can highlight two lines: 1. The multitemporal study using Landsat 5/TM satellite images in order to calculate the forest loss between periods. The multitemporal study was developed in the period 1998-2011 using Landsat 5/TM, applying the methodology of Spectral Mixture Analysis, which allows decomposing the reflectance of each pixel of the image in different fractions of mixture spectral. In this process, the most critical step is the establishment of pure spectra or endemembers spectra, and the collecting of appropriate spectral libraries, in this case of tropical forests, to reduce the uncertainty of the process. As a result of research has succeeded in developing the baseline emissions for the period of study, taking into account both deforestation and forest degradation. 2. Relate the results of forest loss with direct and indirect causation factors. Determining the processes of change in forest cover using geospatial technologies allows relating, significantly, information of the causal indicators in these processes. Similarly, future deforestation and forest degradation scenarios can be estimated according to the analysis of the evolution of these drivers, taking into account other indirect or underlying factors, such as economic, social, demographic and environmental. Identifying the underlying or indirect agents is more complex than endogenous or direct factors. On the one hand, cause - effect relationships are much more diffuse; and, second, the effects may be determined by broader phenomena, due to superposition or accumulation of different causes. From the results of forest loss obtained using Landsat 5/TM, the criteria of direct and indirect conditioning that might have contributed to deforestation and forest degradation in that period were investigated. For this purpose, temporal series, for the same dates, 9 direct factors (infrastructure, hydrography, temperature, etc.) and 196 underlying factors (economic, social, demographic and environmental) with, in principle, a high potential of causality. Finally it was analyzed the predisposition of each factor to the occurrence of deforestation and forest degradation by statistical correlation of the obtained temporal series.

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Mapping aboveground carbon density in tropical forests can support CO2 emissionmonitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador?s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg?C? ha?1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.

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Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.