900 resultados para Land use change
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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).
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The soil carbon (C) stock of the Republic of Ireland is estimated to have been 2048 Mt in 1990 and 2021 Mt in 2000. Peat holds around 53% of the soil C stock, but on 17% of the land area. The C density of soils (t C ha-1) is mapped at 2 km*2 km resolution. The greatest soil C densities occur where deep raised bogs are the dominant soil; in these grid squares C density can reach 3000 t C ha-1. Most of the loss of soil C between 1990 and 2000-up to 23 Mt C (1% of 1990 soil C stock)-was through industrial peat extraction. The average annual change in soil C stocks from 1990 to 2000 due to land use change was estimated at around 0.02% of the 1990 stock. Considering uncertainties in the data used to calculate soil C stocks and changes, the small average annual 'loss' could be regarded as 'no change'.
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A large hydrochemical data-set for the East Yorkshire Chalk has been assessed. Controls on the distribution of water qualities within this aquifer reflect: water-rock interactions (affecting especially the carbonate system and associated geochemistry); effects of land-use change (especially where the aquifer is unconfined); saline intrusion and aquifer refreshening (including ion exchange effects); and aquifer overexploitation (in the semi-confined and confined zones of the aquifer). Both Sr and I prove useful indicators of groundwater ages, with I/Cl ratios characterising two sources of saline waters. The hydrochemical evidence clearly reveals the importance of both recent management decisions and palaeohydrogeology in determining the evolution and distribution of groundwater salinity within the artesian and confined zones of the aquifer. Waters currently encountered in the aquifer are identified as complex (and potentially dynamic) mixtures between modern recharge waters, modern seawater, and old seawaters which entered the aquifer many millennia ago.
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Studies of animal movement are rapidly increasing as tracking technologies make it possible to collect more data of a larger variety of species. Comparisons of animal movement across sites, times, or species are key to asking questions about animal adaptation, responses to climate and land-use change. Thus, great gains can be made by sharing and exchanging animal tracking data. Here we present an animal movement data model that we use within the Movebank web application to describe tracked animals. The model facilitates data comparisons across a broad range of taxa, study designs, and technologies, and is based on the scientific questions that could be addressed with the data.
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Biofuels have had bad press in recent years. There are primarily two distinct issues. The biofuel crops with the best yields (such as sugarcane or oil palm) grow in tropical countries where habitat destruction has occurred in association with the biofuel system. First generation indigenous energy crops commonly used for transport fuel in Europe (such as rapeseed and wheat) have low yields and/or the energy balance of the associated biofuel system is poor. This paper shows that grass is a crop with significant yields and grass biomethane (a gaseous renewable transport biofuel) has a very good energy balance and does not involve habitat destruction, land use change, new farming practices or annual tilling. The gross and net energy production per hectare are almost identical to palm oil biodiesel; the net energy of the grass system is at least 50% better than the next best indigenous European biofuel system investigated. Ten percent of Irish grasslands could fuel over 55% of the Irish private car fleet. © 2009 Elsevier Ltd. All rights reserved.
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Natural ecosystems are increasingly exposed to multiple anthropogenic stressors, including land-use change, deforestation, agricultural intensification, and urbanisation, all of which have led to widespread habitat fragmentation, which is also likely to be amplified further by predicted climate change. The potential interactive effects of these different stressors cannot be determined by studying each in isolation, although such synergies have been largely ignored in ecological field studies to date. Here, we use a model system of naturally fragmented islands in a braided river network, which is exposed to periodic inundation, to investigate the interactive effects of habitat isolation and flood disturbance. Food web structure was similar across the islands during periods of hydrological stability, but several key properties were altered in the aftermath of flood disturbance, based on distance of the islands from the regional source pool of species: taxon richness and mean food chain length declined with habitat isolation after flooding, while the proportion of basal species increased. Greater species turnover through time reflected the slower process of re-colonisation on the more distant islands following disturbance. Increased variability of several food web properties over a 1-year period highlighted the reduced temporal stability of isolated habitat fragments. Many of these effects reflected the differential successes of predator and prey species at re-colonising the islands: even though larger, more mobile consumers may reach the more distant islands first, they cannot establish populations until the lower trophic levels have successfully reassembled. These results highlight the susceptibility of fragmented ecosystems to environmental perturbations. © 2013 Elsevier Ltd.
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Arcellacea (testate lobose amoebae) are important lacustrine environmental indicators that have been used in paleoclimatic reconstructions, assessing the effectiveness of mine tailings pond reclamation projects and for studying the effects of land use change in rural, industrial and urban settings. Recognition of ecophenotypically significant infra-specific ‘strains’ within arcellacean assemblages has the potential to enhance the utility of the group in characterizing contemporary and paleoenvironments. We present a novel approach which employs statistical tools to investigate the environmental and taxonomic significance of proposed strains. We test this approach on two identified strains: Difflugia protaeiformis Lamarck strain ‘acuminata’ (DPA), characterized by fine grained agglutination, and Difflugia protaeiformis Lamarck strain ‘claviformis’ (DPC), characterized by coarse grained agglutination. Redundancy analysis indicated that both organisms are associated with similar environmental variables. No relationship was observed between substrate particle size and abundance of DPC, indicating that DPC has a size preference for xenosomes during test construction. Thus DPC should not be designated as a distinct strain but rather form a species complex with DPA. This study elucidates the need to justify the designation of strains based on their autecology in addition to morphological stability.
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There is a need for coordinated research for the sustainable management of tropical peatland. Malaysia has 6% of global tropical peat by area and peatlands there are subject to land use change at an unprecedented rate. This paper describes a stakeholder engagement exercise that identified 95 priority research questions for peatland in Malaysia, organized into nine themes. Analysis revealed the need for fundamental scientific research, with strong representation across the themes of environmental change, ecosystem services, and conversion, disturbance and degradation. Considerable uncertainty remains about Malaysia's baseline conditions for peatland, including questions over total remaining area of peatland, water table depths, soil characteristics, hydrological function, biogeochemical processes and ecology. More applied and multidisciplinary studies involving researchers from the social sciences are required. The future sustainability of Malaysian peatland relies on coordinating research agendas via a ‘knowledge hub’ of researchers, strengthening the role of peatlands in land-use planning and development processes, stricter policy enforcement, and bridging the divide between national and provincial governance. Integration of the economic value of peatlands into existing planning regimes is also a stakeholder priority. Finally, current research needs to be better communicated for the benefit of the research community, for improved societal understanding and to inform policy processes.
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This study of the Mahavavy-Kinkony Wetland Complex (MKWC) assesses the impacts of habitat change on the resident globally threatened fauna. Located in Boeny Region, northwest Madagascar, the Complex encompasses a range of habitats including freshwater lakes, rivers, marshes, mangrove forests, and deciduous forest. Spatial modelling and analysis tools were used to (i) identify the important habitats for selected, threatened fauna, (ii) assess their change from 1950 to 2005, (iii) detect the causes of change, (iv) simulate changes to 2050 and (v) evaluate the impacts of change. The approach for prioritising potential habitats for threatened species used ecological science techniques assisted by the decision support software Marxan. Nineteen species were analysed: nine birds, three primates, three fish, three bats and one reptile. Based on knowledge of local land use, supervised classification of Landsat images from 2005 was used to classify the land use of the Complex. Simulations of land use change to 2050 were carried out based on the Land Change Modeler module in Idrisi Andes with the neural network algorithm. Changes in land use at site level have occurred over time but they are not significant. However, reductions in the extent of reed marshes at Lake Kinkony and forests at Tsiombikibo and Marofandroboka directly threaten the species that depend on these habitats. Long term change monitoring is recommended for the Mahavavy Delta, in order to evaluate the predictions through time. The future change of Andohaomby forest is of great concern and conservation actions are recommended as a high priority. Abnormal physicochemical properties were detected in lake Kinkony due to erosion of the four watersheds to the south, therefore an anti-erosion management plan is required for these watersheds. Among the species of global conservation concern, Sakalava rail (Amaurornis olivieri), Crowned sifaka (Propithecus coronatus) and dambabe (Paretroplus dambabe) are estimated the most affected, but at the site level Decken’s sifaka (Propithecus deckeni), kotsovato (Paretroplus kieneri) and Madagascan big-headed turtle (Erymnochelys madagascariensis) are also threatened. Local enforcement of national legislation on hunting means that MKWC is among the sites where the flying fox (Pteropus rufus) and Madagascan rousette (Rousettus madagascariensis) are well protected. Ecological restoration, ecological research and actions to reduce anthropogenic pressures are recommended.
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Beta diversity quantifies spatial and/or temporal variation in species composition. It is comprised of two distinct components, species replacement and nestedness, which derive from opposing ecological processes. Using Scotland as a case study and a β-diversity partitioning framework, we investigate temporal replacement and nestedness patterns of coastal grassland species over a 34-yr time period. We aim to 1) understand the influence of two potentially pivotal processes (climate and land-use changes) on landscape-scale (5 × 5 km) temporal replacement and nestedness patterns, and 2) investigate whether patterns from one β-diversity component can mask observable patterns in the other.
We summarised key aspects of climate driven macro-ecological variation as measures of variance, long-term trends, between-year similarity and extremes, for three important climatic predictors (minimum temperature, water-balance and growing degree-days). Shifts in landscape-scale heterogeneity, a proxy of land-use change, was summarised as a spatial multiple-site dissimilarity measure. Together, these climatic and spatial predictors were used in a multi-model inference framework to gauge the relative contribution of each on temporal replacement and nestedness patterns.
Temporal β-diversity patterns were reasonably well explained by climate change but weakly explained by changes in landscape-scale heterogeneity. Climate was shown to have a greater influence on temporal nestedness than replacement patterns over our study period, linking nestedness patterns, as a result of imbalanced gains and losses, to climatic warming and extremes respectively. Important climatic predictors (i.e. growing degree-days) of temporal β-diversity were also identified, and contrasting patterns between the two β-diversity components revealed.
Results suggest climate influences plant species recruitment and establishment processes of Scotland's coastal grasslands, and while species extinctions take time, they are likely to be facilitated by climatic perturbations. Our findings also highlight the importance of distinguishing between different components of β-diversity, disentangling contrasting patterns than can mask one another.
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Dissertação de mestrado em Agricultura Sustentável, apresentada na Escola Superior Agrária de Santarém, Instituto Politécnico de Santarém.
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The resurgence of malaria in highland regions of Africa, Oceania and recently in South America underlines the importance of the study of the ecology of highland mosquito vectors of malaria. Since the incidence of malaria is limited by the distribution of its vectors, the purpose of this PhD thesis was to examine aspects of the ecology of Anopheles mosquitoes in the Andes of Ecuador, South America. A historical literature and archival data review (Chapter 2) indicated that Anopheles pseudopunctipennis transmitted malaria in highland valleys of Ecuador prior to 1950, although it was eliminated through habitat removal and the use of chemical insecticides. Other anopheline species were previously limited to low-altitude regions, except in a few unconfirmed cases. A thorough larval collection effort (n=438 attempted collection sites) in all road-accessible parts of Ecuador except for the lowland Amazon basin was undertaken between 2008 - 2010 (Chapter 3). Larvae were identified morphologically and using molecular techniques (mitochondrial COl gene), and distribution maps indicated that all five species collected (Anopheles albimanus, An. pseudopunctipennis, Anopheles punctimacula, Anopheles oswaldoi s.l. and Anopheles eiseni) were more widespread throughout highland regions than previously recorded during the 1940s, with higher maximum altitudes for all except An. pseudopunctipennis (1541 m, 1930 m, 1906 m, 1233 m and 1873 m, respectively). During larval collections, to characterize species-specific larval habitat, a variety of abiotic and biotic habitat parameters were measured and compared between species-present and species-absent sites using chi-square tests and stepwise binary logistic regression analyses (Chapter 4). An. albimanus was significantly associated with permanent pools with sand substrates and An. pseudopunctipennis with gravel and boulder substrates. Both species were significantly associated with floating cyanobacterial mats and warmer temperatures, which may limit their presence in cooler highland regions. Anopheles punctimacula was collected more often than expected from algae-free, shaded pools with higher-than-average calculated dissolved oxygen. Anopheles oswaldoi s.l., the species occurring on the Amazonian side of the Andes, was associated with permanent, anthropogenic habitats such as roadside ditches and ponds. To address the hypothesis that human land use change is responsible for the emergence of multiple highland Anopheles species by creating larval habitat, common land uses in the western Andes were surveyed for standing water and potential larval habitat suitability (Chapter 5). Rivers and road edges provided large amounts of potentially suitable anopheline habitat in the western Andes, while cattle pasture also created potentially suitable habitat in irrigation canals and watering ponds. Other common land uses surveyed (banana farms, sugarcane plantations, mixed tree plantations, and empty lots) were usually established on steep slopes and had very little standing water present. Using distribution and larval habitat data, a GIS-based larval habitat distribution model for the common western species was constructed in ArcGIS v.l 0 (ESRI 2010) using derived data layers from field measurements and other sources (Chapter 6). The additive model predicted 76.4 - 97.9% of the field-observed collection localities of An. albimanus, An. pseudopunctipennis and An. punctimacula, although it could not accurately distinguish between species-absent and speciespresent sites due to its coarse scale. The model predicted distributional expansion and/or shift of one or more anopheline species into the following highland valleys with climate warming: Mira/Chota, Imbabura province, Tumbaco, Pichincha province, Pallatanga and Sibambe, Chimborazo province, and Yungilla, Azuay province. These valleys may serve as targeted sites of future monitoring to prevent highland epidemics of malaria. The human perceptions of malaria and mosquitoes in relation to land management practices were assessed through an interview-based survey (n=262) in both highlands and lowlands, of male and female land owners and managers of five property types (Chapter 7). Although respondents had a strong understanding of where the disease occurs in their own country and of the basic relationship among standing water, mosquitoes and malaria, about half of respondents in potential risk areas denied the current possibility of malaria infection on their own property. As well, about half of respondents with potential anopheline larval habitat did not report its presence, likely due to a highly specific definition of suitable mosquito habitat. Most respondents who are considered at risk of malaria currently use at least one type of mosquito bite prevention, most commonly bed nets. In conclusion, this interdisciplinary thesis examines the occurrence of Anopheles species in the lowland transition area and highlands in Ecuador, from a historic, geographic, ecological and sociological perspective.
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Die gegenwärtige Entwicklung der internationalen Klimapolitik verlangt von Deutschland eine Reduktion seiner Treibhausgasemissionen. Wichtigstes Treibhausgas ist Kohlendioxid, das durch die Verbrennung fossiler Energieträger in die Atmosphäre freigesetzt wird. Die Reduktionsziele können prinzipiell durch eine Verminderung der Emissionen sowie durch die Schaffung von Kohlenstoffsenken erreicht werden. Senken beschreiben dabei die biologische Speicherung von Kohlenstoff in Böden und Wäldern. Eine wichtige Einflussgröße auf diese Prozesse stellt die räumliche Dynamik der Landnutzung einer Region dar. In dieser Arbeit wird das Modellsystem HILLS entwickelt und zur Simulation dieser komplexen Wirkbeziehungen im Bundesland Hessen genutzt. Ziel ist es, mit HILLS über eine Analyse des aktuellen Zustands hinaus auch Szenarien über Wege der zukünftigen regionalen Entwicklung von Landnutzung und ihrer Wirkung auf den Kohlenstoffhaushalt bis 2020 zu untersuchen. Für die Abbildung der räumlichen und zeitlichen Dynamik von Landnutzung in Hessen wird das Modell LUCHesse entwickelt. Seine Aufgabe ist die Simulation der relevanten Prozesse auf einem 1 km2 Raster, wobei die Raten der Änderung exogen als Flächentrends auf Ebene der hessischen Landkreise vorgegeben werden. LUCHesse besteht aus Teilmodellen für die Prozesse: (A) Ausbreitung von Siedlungs- und Gewerbefläche, (B) Strukturwandel im Agrarsektor sowie (C) Neuanlage von Waldflächen (Aufforstung). Jedes Teilmodell umfasst Methoden zur Bewertung der Standorteignung der Rasterzellen für unterschiedliche Landnutzungsklassen und zur Zuordnung der Trendvorgaben zu solchen Rasterzellen, die jeweils am besten für eine Landnutzungsklasse geeignet sind. Eine Validierung der Teilmodelle erfolgt anhand von statistischen Daten für den Zeitraum von 1990 bis 2000. Als Ergebnis eines Simulationslaufs werden für diskrete Zeitschritte digitale Karten der Landnutzugsverteilung in Hessen erzeugt. Zur Simulation der Kohlenstoffspeicherung wird eine modifizierte Version des Ökosystemmodells Century entwickelt (GIS-Century). Sie erlaubt einen gesteuerten Simulationslauf in Jahresschritten und unterstützt die Integration des Modells als Komponente in das HILLS Modellsystem. Es werden verschiedene Anwendungsschemata für GIS-Century entwickelt, mit denen die Wirkung der Stilllegung von Ackerflächen, der Aufforstung sowie der Bewirtschaftung bereits bestehender Wälder auf die Kohlenstoffspeicherung untersucht werden kann. Eine Validierung des Modells und der Anwendungsschemata erfolgt anhand von Feld- und Literaturdaten. HILLS implementiert eine sequentielle Kopplung von LUCHesse mit GIS-Century. Die räumliche Kopplung geschieht dabei auf dem 1 km2 Raster, die zeitliche Kopplung über die Einführung eines Landnutzungsvektors, der die Beschreibung der Landnutzungsänderung einer Rasterzelle während des Simulationszeitraums enthält. Außerdem integriert HILLS beide Modelle über ein dienste- und datenbankorientiertes Konzept in ein Geografisches Informationssystem (GIS). Auf diesem Wege können die GIS-Funktionen zur räumlichen Datenhaltung und Datenverarbeitung genutzt werden. Als Anwendung des Modellsystems wird ein Referenzszenario für Hessen mit dem Zeithorizont 2020 berechnet. Das Szenario setzt im Agrarsektor eine Umsetzung der AGENDA 2000 Politik voraus, die in großem Maße zu Stilllegung von Ackerflächen führt, während für den Bereich Siedlung und Gewerbe sowie Aufforstung die aktuellen Trends der Flächenausdehnung fortgeschrieben werden. Mit HILLS ist es nun möglich, die Wirkung dieser Landnutzungsänderungen auf die biologische Kohlenstoffspeicherung zu quantifizieren. Während die Ausdehnung von Siedlungsflächen als Kohlenstoffquelle identifiziert werden kann (37 kt C/a), findet sich die wichtigste Senke in der Bewirtschaftung bestehender Waldflächen (794 kt C/a). Weiterhin führen die Stilllegung von Ackerfläche (26 kt C/a) sowie Aufforstung (29 kt C/a) zu einer zusätzlichen Speicherung von Kohlenstoff. Für die Kohlenstoffspeicherung in Böden zeigen die Simulationsexperimente sehr klar, dass diese Senke nur von beschränkter Dauer ist.
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Landwirtschaft spielt eine zentrale Rolle im Erdsystem. Sie trägt durch die Emission von CO2, CH4 und N2O zum Treibhauseffekt bei, kann Bodendegradation und Eutrophierung verursachen, regionale Wasserkreisläufe verändern und wird außerdem stark vom Klimawandel betroffen sein. Da all diese Prozesse durch die zugrunde liegenden Nährstoff- und Wasserflüsse eng miteinander verknüpft sind, sollten sie in einem konsistenten Modellansatz betrachtet werden. Dennoch haben Datenmangel und ungenügendes Prozessverständnis dies bis vor kurzem auf der globalen Skala verhindert. In dieser Arbeit wird die erste Version eines solchen konsistenten globalen Modellansatzes präsentiert, wobei der Schwerpunkt auf der Simulation landwirtschaftlicher Erträge und den resultierenden N2O-Emissionen liegt. Der Grund für diese Schwerpunktsetzung liegt darin, dass die korrekte Abbildung des Pflanzenwachstums eine essentielle Voraussetzung für die Simulation aller anderen Prozesse ist. Des weiteren sind aktuelle und potentielle landwirtschaftliche Erträge wichtige treibende Kräfte für Landnutzungsänderungen und werden stark vom Klimawandel betroffen sein. Den zweiten Schwerpunkt bildet die Abschätzung landwirtschaftlicher N2O-Emissionen, da bislang kein prozessbasiertes N2O-Modell auf der globalen Skala eingesetzt wurde. Als Grundlage für die globale Modellierung wurde das bestehende Agrarökosystemmodell Daycent gewählt. Neben der Schaffung der Simulationsumgebung wurden zunächst die benötigten globalen Datensätze für Bodenparameter, Klima und landwirtschaftliche Bewirtschaftung zusammengestellt. Da für Pflanzzeitpunkte bislang keine globale Datenbasis zur Verfügung steht, und diese sich mit dem Klimawandel ändern werden, wurde eine Routine zur Berechnung von Pflanzzeitpunkten entwickelt. Die Ergebnisse zeigen eine gute Übereinstimmung mit Anbaukalendern der FAO, die für einige Feldfrüchte und Länder verfügbar sind. Danach wurde das Daycent-Modell für die Ertragsberechnung von Weizen, Reis, Mais, Soja, Hirse, Hülsenfrüchten, Kartoffel, Cassava und Baumwolle parametrisiert und kalibriert. Die Simulationsergebnisse zeigen, dass Daycent die wichtigsten Klima-, Boden- und Bewirtschaftungseffekte auf die Ertragsbildung korrekt abbildet. Berechnete Länderdurchschnitte stimmen gut mit Daten der FAO überein (R2 = 0.66 für Weizen, Reis und Mais; R2 = 0.32 für Soja), und räumliche Ertragsmuster entsprechen weitgehend der beobachteten Verteilung von Feldfrüchten und subnationalen Statistiken. Vor der Modellierung landwirtschaftlicher N2O-Emissionen mit dem Daycent-Modell stand eine statistische Analyse von N2O-und NO-Emissionsmessungen aus natürlichen und landwirtschaftlichen Ökosystemen. Die als signifikant identifizierten Parameter für N2O (Düngemenge, Bodenkohlenstoffgehalt, Boden-pH, Textur, Feldfrucht, Düngersorte) und NO (Düngemenge, Bodenstickstoffgehalt, Klima) entsprechen weitgehend den Ergebnissen einer früheren Analyse. Für Emissionen aus Böden unter natürlicher Vegetation, für die es bislang keine solche statistische Untersuchung gab, haben Bodenkohlenstoffgehalt, Boden-pH, Lagerungsdichte, Drainierung und Vegetationstyp einen signifikanten Einfluss auf die N2O-Emissionen, während NO-Emissionen signifikant von Bodenkohlenstoffgehalt und Vegetationstyp abhängen. Basierend auf den daraus entwickelten statistischen Modellen betragen die globalen Emissionen aus Ackerböden 3.3 Tg N/y für N2O, und 1.4 Tg N/y für NO. Solche statistischen Modelle sind nützlich, um Abschätzungen und Unsicherheitsbereiche von N2O- und NO-Emissionen basierend auf einer Vielzahl von Messungen zu berechnen. Die Dynamik des Bodenstickstoffs, insbesondere beeinflusst durch Pflanzenwachstum, Klimawandel und Landnutzungsänderung, kann allerdings nur durch die Anwendung von prozessorientierten Modellen berücksichtigt werden. Zur Modellierung von N2O-Emissionen mit dem Daycent-Modell wurde zunächst dessen Spurengasmodul durch eine detailliertere Berechnung von Nitrifikation und Denitrifikation und die Berücksichtigung von Frost-Auftau-Emissionen weiterentwickelt. Diese überarbeitete Modellversion wurde dann an N2O-Emissionsmessungen unter verschiedenen Klimaten und Feldfrüchten getestet. Sowohl die Dynamik als auch die Gesamtsummen der N2O-Emissionen werden befriedigend abgebildet, wobei die Modelleffizienz für monatliche Mittelwerte zwischen 0.1 und 0.66 für die meisten Standorte liegt. Basierend auf der überarbeiteten Modellversion wurden die N2O-Emissionen für die zuvor parametrisierten Feldfrüchte berechnet. Emissionsraten und feldfruchtspezifische Unterschiede stimmen weitgehend mit Literaturangaben überein. Düngemittelinduzierte Emissionen, die momentan vom IPCC mit 1.25 +/- 1% der eingesetzten Düngemenge abgeschätzt werden, reichen von 0.77% (Reis) bis 2.76% (Mais). Die Summe der berechneten Emissionen aus landwirtschaftlichen Böden beträgt für die Mitte der 1990er Jahre 2.1 Tg N2O-N/y, was mit den Abschätzungen aus anderen Studien übereinstimmt.