Humans affect ecosystems by changing species compositions, landscape and climate. This thesis aims to increase our understanding of anthropogenic effects on mesopredator abundance due to changes in apex predator status, landscape and climate. I show that in Eurasia the abundance of a mesopredator, the red fox (Vulpes vulpes), is limited top-down by the Eurasian lynx (Lynx lynx) and bottom-up by winter severity. However, where lynx has been eradicated, fox abundance is instead related to bottom-factors such as cropland (paper I, II). Fox abundance was highest when croplands constituted 25% of the landscape (paper II). I also project red fox abundance in Sweden over the past 200 years and in future scenarios in relation to lynx density, land use and climate change. The projected fox abundance was highest in 1920, when lynx was eradicated and the proportion of cropland was 22%. In 2010, when lynx had recolonised, the projected fox abundance was lower than in 1920, but higher than in 1830. Future scenarios indicated that lynx abundance must increase in respond to climate change to keep fox at the same density as today. The results suggest a mesopredator release when lynx was eradicated, boosted by land use and climate change, and that changes in bottom-up factors can modify the relative strength of top-down factors (paper IV). From 1846-1922, lynx, wolverine (Gulo gulo) and grey wolf (Canis lupus) declined in Scandinavia due to persecution; however I show that the change in wolverine abundance was positively related to the changes in lynx and wolf abundance. This indicates that wolverine is subsidized by carrions from lynx and wolf kills rather than limited top-down by them (paper III). This thesis illustrates how mesopredator abundance is determined by a combination of top-down and bottom-up processes, and how anthropogenic impacts not only can change the structures of predator guilds, but also may modify top-down processes through changes in bottom-up factors. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 3: Submitted. Paper 4: Manuscript.</p><p> </p>

Landwirtschaftliche Expansion und Intensivierung treiben die Umwandlung natürlicher Ökosysteme weltweit. Bis heute ist unklar, inwieweit politische Maßnahmen negative Folgen für die Umwelt minimieren können. Die Kombination mit Szenarien-Analysen kann ein Rahmen zur Unterstützung von Planungsprozessen schaffen, um potentielle Auswirkungen von politischen Maßnahmen zu erforschen. Das Ziel dieser Dissertation war es, die Triebkräfte der Veränderung von Argentiniens Agrarlandschaften zu verstehen, potentielle zukünftige Landnutzungsveränderungen zu analysieren und den Einfluss ökonomischer und naturschutzbezogener politischer Maßnahmen auf diese zu erfassen. Im ersten Teil der Dissertation wurden die Triebkräfte landwirtschaftlichen Landnutzungswandels mittels eines Nettoertrags-Modells ermittelt. Danach wurde der Einfluss von ökonomischen und naturschutzbezogenen Maßnahmen auf zukünftige Landnutzungsveränderungen sowie auf die Konnektivität von Waldgebieten mit Hilfe von Landnutzungs-Szenarien analysiert. Die Ergebnisse zeigen, dass landwirtschaftliche Intensivierung von ökonomischen Maßnahmen getrieben ist, während landwirtschaftliche Expansion durch naturräumliche Eigenschaften und Zonierungsprogramme jenseits der Profitmaximierung determiniert wird. Politische Maßnahmen mögen einen geringeren Einfluss auf Landnutzungswandel haben als bisher erwartet. Die Entwicklung von Agrarland konzentriert sich auf Gebiete mit hoher Priorität für den Umweltschutz. Zonierungsprogramme wie das Argentinische Waldgesetz stellen wirkungsvolle Maßnahmen dar, um umweltschädigenden Entwicklungen vorzubeugen. Die Erkenntnisse zeigen, dass Naturschutz nicht zwingend im Konflikt mit ökonomischer Entwicklung steht, denn mittels Landschaftsplanung kann die Konnektivität von Waldgebieten auch unter gleichbleibenden Abholzungsraten bewahrt werden. Die Dissertation zeigt den Mehrwert von a-priori Evaluierungen der potentiellen Einflüsse von Maßnahmen auf Landnutzungswandel. / Agricultural expansion and intensification drive the conversion of natural areas worldwide. Yet, it is not clear where and how much production would need to expand and intensify to meet future demands and how policies may help minimizing environmental trade-offs. Particularly the latter requires an understanding of the underlying forces that drive agricultural land-use changes. This offers a framework for planners and decision makers to explore potential impacts from policies, especially in very dynamic regions. Argentina, where agricultural expansion and intensification result in dramatic conversions of natural areas, is a good example of a dynamic human-environment system. The goal of this thesis was to understand the drivers of agricultural land-use change and to explore future trajectories of land-use change, and how economic and conservation policies may impact them. This thesis examines drivers of agricultural land-use changes using a net returns model of agricultural production. Then, it evaluates the effects of economic and conservation policies on future land-use changes and on the connectivity of forests by developing scenarios of future land-use change. Results highlight that agricultural intensification in Argentina is driven by economic interventions, whereas agricultural expansion primarily responds to environmental characteristics and zonation programs. Economic policies may have less power in governing land use changes than previously thought, as results suggest that there are other factors, than profit maximization, influencing land conversions. Future agricultural development would occur in priority areas for conservation in Argentina, but zonation policies, such as the Forest Law, appear to be powerful in limiting potential environmental trade-offs. Conservation planning does not necessarily need to conflict with economic development, since under similar deforestation rates; landscape planning can preserve forest connectivity in the Chaco.

This dissertation combines large scale datasets to evaluate crop prediction, land values, and consumption of a crop being considered to advance a sustainable bioeconomy. In chapter 2, we propose a novel application of the multinomial logit (MNL) model to estimate the conditional transition probabilities of crop choice for the state of Kentucky. Utilizing the recovered transition probabilities the forecast distributions of total acreages for alfalfa, corn, soybeans, tobacco, and wheat produced in the state from 2010 to 2015 can be recovered. The Cropland Data Layer is merged with the Common Land Unit dataset to allow for the identification of crop choice at the field level. Our findings show there are higher probabilities of planting soybeans or wheat after corn relative to corn after corn, tobacco, or alfalfa. In addition, the transition probability of the crop rotation demonstrates that corn will be planted after soybean, and vice versa and that alfalfa has a lower probability of being rotated with other crops from year to year. These findings are expected with traditional crop rotation in the U.S., and a characteristic of a perennial crop, especially for alfalfa. Finally, forecasting results indicate that there are significantly wider distributions in corn and soybean, whereas there is a little variation in the tobacco, wheat and alfalfa acres in the simulation. In chapter 3, we identify critical consumer-demographic characteristics that are associated with the consumption of products containing hemp and investigate their effect on total expenditure in the U.S. To estimate the likelihood of market participation and consumption level, the Heckman selection model, is employed using the maximum likelihood estimation procedure utilizing Nielsen consumer panel data from 2008 to 2015. Results indicate marketing strategies targeting consumers with higher education and income levels can attract new customers and increase sales from current consumers for this burgeoning market. Head-of-household age in different regions shows mixed effects on decisions to purchase hemp products and consumption levels. Findings will provide a basic understanding of a consumer profile and overall hemp market that has had double-digit growth over the last six years. As the industry continues to move forward, policymakers are going to need a deeper understanding of the factors driving the industry if they are going to create regulations that support the development of the industry. In chapter 4, we investigate the factors that affect agricultural land values by proposing a new rich dataset, Zillow Transaction and Assessment Data (ZTRAX) provided by Zillow from 2009 to 2014. we also examine whether National Commodity Crop Productivity Index (NCCPI) could be a good indicator of land values or not by comparing two different regression models between county-level cash rent and parcel-level NCCPI. Finally, this study incorporates flexible functional forms of the parcel size to test the parcel size and land values relations. Findings show that factors influencing agricultural land values in states with heterogeneous agricultural lands such as Kentucky are not different from other states with relatively homogeneous agricultural lands. This study also provides suggestive evidence that there is a non-linear relationship between parcel size and land values. Furthermore, we find that a disaggregated NCCPI at parcel-level could be considered an acceptable indicator to estimate agricultural values compared to an aggregated cash rent at county-level.

The aim of this thesis is to compare the National Footprint Accounts of the Czech Republic in the section of cropland and grazing land for the year 2007 based on globally available data and data available in the Czech Republic, and also to compare these National Footprint Accounts of the Czech Republic based on nationally available data from the years 2007 and 2013. This thesis used the method of calculation of the National Footprint Accounts developed by Global Footprint Network. The ecological footprint of cropland of the Czech Republic is lower according to national data compared to global data while the ecological footprint of grazing land is higher. According to national data, the ecological footprint of both cropland and grazing land of the Czech Republic was lower in 2013 compared to 2007. This work gives an opportunity to compare the calculation of the ecological footprint and biocapacity of cropland and grazing land based on different data sources and to compare the results based on data from 2007 and 2013. Powered by TCPDF (www.tcpdf.org)

Die Nachfrage nach Agrarprodukten hat rapide zugenommen, besonders in schnell wachsenden Volkswirtschaften. Agrarimporte nach China gestiegen, trotz der vielfach gestiegenen Inlandsproduktion seit der Reform und Öffnung 1978. Jedoch ging die Steigerung der Agrarproduktion einher mit hohen Umweltkosten, zum einen durch eine massive Erhöhung der Inputintensität und zum anderen durch die Veränderung der Anbaumuster. In dieser Arbeit habe ich umwelt- und sozioökonomische Daten auf Kreis-Ebene analysiert, um ein grundliegendes quantitatives Verständnis der Muster, Determinanten und Ursachen der landwirtschaftlichen Landnutzungsveränderung in China von 1980 bis 2011 zu entwickeln. In Kapitel II und III habe ich die Veränderung der Anbaumuster der Hauptkultur auf Kreisebene zusammengefasst. Ich habe diese Daten mittels explorativer Geodatenanalyse und räumlich expliziter Panel-Regression untersucht, um raum-zeitliche Determinanten der Änderung in Anbaufläche und Ertrag der Hauptkultur zu identifizieren. In Kapitel IV nutzte ich diese Daten, um die Veränderung der Technischen Effizienz in der Pflanzenproduktion mit Hilfe eines stochastischen Grenzansatzes zu ermitteln, wiederum durch den Einsatz einer räumlich-ökonometrischen Panel-Analyse. Insgesamt hat sich die räumliche Konzentration von Hauptkulturen erhöht. Haupteinflussfaktor für diese Entwicklung war die Bevölkerung. Diese Analyse beleuchtet die Muster und Treiber des agrarwirtschaftlichen Landnutzungswandel für gesamt China und gibt Einblicke in die Brennpunkte des Wandels in Landnutzungsumfang und –intensität. Außerdem zeigten die Elastizitäten der Input-Veränderungen einen Trend in der Pflanzenproduktionsintensität von traditionell zu wissenschaftlich-technologischen Eingriffen. Die Ergebnisse können zur Einwicklung räumlich ausgerichteter Landnutzungspolitiken in China beitragen. Sie stellen außerdem wichtige Fallbeweise für den globalen Landnutzungswandel zur Verfügung. / Abstract Demand for agricultural products has been increasing at an unprecedented pace, particularly in rapidly growing economies such as China. Agricultural imports to China have soared despite domestic production increasing manifold since reforming and opening in 1978. However, the increase in agricultural production in China involved high environmental costs, brought about by massively increasing input intensity and by the transition in cropping patterns. In this thesis, I analysed environmental and socioeconomic data at county level to develop a solid quantitative understanding of patterns, determinants, and causes of agricultural land-use changes across all of China from 1980 to 2011. In Chapter II and Chapter III, I summarized the changes in patterns of the main crops at county level. I then examined these data with exploratory spatial data analysis and spatially explicit panel regressions in order to identify the spatial and temporal determinants of changes in area and yield of major crops. In chapter IV, I used the same dataset, but focussed on changes in technical efficiency in crop production using a stochastic frontier approach, again by employing spatial econometric panel analysis. Overall, the spatial concentration of the major crops increased, with population the main determinant for this trend. Furthermore, modern inputs, including machinery and fertilizer, were increasingly important in crop production, and land use efficiency increased slightly and varied temporally and spatially. This analysis shed light on the patterns and drivers of agricultural land-system change for all of China, including insights on hotspots of changes in land use extent and intensity. Besides, the elasticity of input changes showed the growth of crop production was shift from traditional farming practices to modern. This study is valuable to inform and spatially target land-use policies in China and provide important case evidence for global land-use change.

The research uses cameras mounted to a vehicle to capture geotagged images while conducting a transect survey. The images from two capture dates were manually classified into different classes of previous crop, tillage systems, residue cover, and cover crop utilization. The raw data was compared against the Indiana Cropland Transect Survey and the USDA-NASS Cropland Data Layer. The symmetric Kullback-Liebler divergence method was used to compared the distributions looking for similarities. <div><br></div><div>The manually classified data was then used to build satellite segmentation models using artificial neural networks , decision trees, k nearest neighbors, random forests, and support vector machine methods. The models were compared using overall accuracy, kappa coefficient, specificity, sensitivity, positive prediction value, and negative prediction value. The best model for each category of previous crop, tillage system, residue cover, and cover crop was used to segment a Sentenial-2 imagery downloaded from Copernicus Open Access hub. The results of the segment were compared by looking at the agreement at individual pixel locations from the segmented raster to the manually classified data and the Indiana Cropland Transect Survey. </div><div><br></div><div>Finally, all the images captured were used to being the development of a automated image classifier using nested convolutional neural networks (CNN). A small set of images was used to build the CNN. That model when then make prediction on new unclassified images. The predictions were manually checked. The check images were used to the to build the training and validation pools for the models. The first network divided the images into field or not field.</div><div>The second branch was field images divided in to images containing green growing plants of brown dead plants or residues. The final branch was determining the amount of surface cover left on a field. The results from each run of the training process were saved and used to assess model performance looking at accuracy and loss.</div>

<p dir="ltr">The Temperate Plains ecoregion of Indiana has experienced significant agricultural development since the 19th century, which has left streams vulnerable to impacts such as sedimentation and nutrient accumulation. This thesis describes first the accuracy of the USDA Cropland Data Layer (CDL) in land cover change, and second, the relationships between agricultural and forested land covers and stream biological integrity. I first employed the CDL to review land cover change, particularly relating to agriculture and forest, for the area of interest between 2010 and 2020. I determined that the CDL improved in accuracy for the area of interest in the chosen timeframe for non-agricultural and non-forest land cover. I concluded that the CDL was best used as a supplement to primary-source land cover measures. Next, I calculated the fish Index of Biotic Integrity (IBI) scores for 20 sampled agricultural and forested streams in North-Central Indiana. I also assessed the stream habitats at all sites using the Qualitative Habitat Evaluation Index (QHEI) and percent cultivated crops in drainage basin areas for all streams. Forested streams had significantly higher QHEI scores than agricultural streams (median = 62 and 40.4, respectively). No other relationships were statistically different, including IBI and land cover category, which may have been due to the small sample size (n = 20). I concluded that future studies may build on these findings by controlling for agricultural drainage types or using precise measures of forested land cover.</p>

Die Landwirtschaft liefert einen Großteil der Nahrungsmittel und Rohstoffe für den menschlichen Verbrauch und wird aufgrund globaler Dynamiken des Bevölkerungswachstums, Änderungen der Ernährungszusammensetzung und Auswirkungen des Klimawandels herausgefordert. Gleichzeitig hat die intensive landwirtschaftliche Produktion oft erhebliche Auswirkungen auf die Leistungen und Funktionen von Ökosystemen. Agrarökosystemmodelle können verwendet werden, um Auswirkungen der Landwirtschaft über verschiedene zeitliche und räumliche Skalen zu quantifizieren. Globale Bewertungen werden jedoch durch die begrenzte Verfügbarkeit von Daten einzelner agronomischer Maßnahmen und dem Wissen über die damit verbundenen biophysikalischen und biogeochemischen Prozesse erschwert. Ziel dieser Doktorarbeit ist es, das Verständnis über Anforderungen an Daten von landwirtschaftlichen Produktionssystemen und deren Anwendungsmethoden in globalen Modellierungsstudien zu erweitern. Darüber hinaus zielt diese Doktorarbeit darauf ab die Arten, räumliche Ausdehnung, Umweltwirkung und Potenziale von unterschiedlichen Bewirtschaftungsmethoden auf globalem Ackerland abzuschätzen. Die Ergebnisse der ersten Studie zeigen, inwiefern die Aggregation von rasterzellenbasiert simulierten Ernteerträgen zu national und globalen Durchschnittserträgen mit vier unterschiedlichen Datenprodukten zu Unsicherheiten von ~10 % führen kann. Der zweite Forschungsartikel präsentiert eine Klassifikation von sechs Bodenbearbeitungssystemen, deren Kartierung und ermittelten Merkmale zur Parametrisierung in globalen Agrarökosystemmodell verwendet werden können. Zuletzt werden mit Hilfe des globalem Modells LPJml5.0- tillage-cc die biophysikalischen Auswirkungen von Zwischenfruchtanbau im Vergleich zu Schwarzbrache auf die Kohlenstoff-, Stickstoff- und Wasserdynamiken abgeschätzt. Die Ergebnisse der Thesis zeigen Potenziale von und Trade-offs zwischen ackerbaulichen Bewirtschaftungsmethoden und deren globaler Modellierung auf. / Agricultural production provides a major share of food, feed, fiber, and fuel for anthropogenic usage, and is challenged by projected increasing demand due to dynamics of population growth, changes in dietary compositions, and climate change impacts. At the same time, intensive agricultural production practices have environmental externalities, which negatively affect ecosystems’ services and functions. Agroecosystem models can be used to quantify impacts of cropland use across various temporal and spatial scales, but global assessments are hampered by the limited availability of land management data and of knowledge regarding associated biophysical and biogeochemical processes and functions. The objective of the thesis is to increase the understanding of agricultural management data requirements and implications for their usages in global modeling studies. Further, the thesis aims to identify types, spatial distribution, as well as to estimate impacts, and potentials of cropland management practices to support sustainable development. In the first study, it was assessed in which way the application of different harvested crop area datasets for the national and global aggregation of modeled crop yield outputs from the grid cell to country and global scale, induces average uncertainty of ~10 % to the results. The second study presents a global classification of six soil management systems whereas the derived mapping and characteristics can be used for parameterization across a range of intensity levels in global land use modeling studies. In the third study different cropland management practices were assessed using LPJml5.0-tillage-cc, with a modified code for the representation of cover crops growing as grass on cropland between two consecutive main crop growing seasons. The thesis’ findings reveal potential and trade-offs of land management practices and their impact assessment using global agroecosystem models.

No description available.

Energie und Rohstoffe auf Basis von Biomasse gelten als wichtiger Beitrag, um den anthropogen begründeten Klimawandel zu mindern. Diese publikationsbasierte Arbeit analysiert, inwiefern Aussagen über Vorzüglichkeit von Biomassenutzung im direkten Vergleich oder auch in komplexeren wirtschaftlichen Nutzungssystemen durch Unsicherheiten in den Treibhausgasemissionen (THG) oder durch die Anwendung der Bewertungsmethodik beeinflusst werden. Eine Fallstudie zur stationären Biostromerzeugung aus der Vergasung von Pappelhackschnitzeln zeigte mittels Monte-Carlo-Analyse, dass dieser Biostrom trotz Unsicherheiten weniger THG emittiert bzw. sogar Kohlendioxid sequestrieren könnte. Die zweite Fallstudie analysierte Biomassenutzung im Systemzusammenhang. Sie bezog neben THG-Emissionen als Bewertungskriterien sowohl den Bedarf an Agrarfläche als auch an fossilen Ressourcen mit ein. Für das Beispiel der Häuserdämmung mittels Hanffasern oder Styropor konnte aus den drei Kriterien auch unter Berücksichtigung mehrerer Szenarien keine eindeutige Vorzugslösung der Biomassenutzung abgeleitet werden. Basierend auf dem Produktivitätskonzept stellt der dritte Beitrag mit CUDe (Carbon Utilization Degree) einen Ansatz vor, wie die Nutzungseffizienz des in der Biomasse bereitgestellten Kohlenstoffs bewertet werden könnte. THG-Minderungsrechnungen erfordern eine fundierte Kenntnis der Methode als auch des Produktionssystems in seinem regionalen Kontext. Als Landnutzungseffekte sollten neben Änderungen im Bodenkohlenstoffgehalt auch Unterschiede in Lachgas-Hintergrundemissionen von annuellen gegenüber mehrjährigen Kulturen berücksichtigt werden. Trade-Offs sprechen dafür, Biomassenutzungssysteme nicht nur hinsichtlich Klimawirksamkeit zu optimieren. Ergänzend könnte Kohlenstoff auch als Ressource betrachtet und mit Effizienzkriterien bewertet werden. Biomassenutzung ließe sich so optimieren, dass gemeinsam mit Klimaschutz weitere aktuelle Handlungsfelder adressiert werden. / Biomass-based energy and materials are considered important for the mitigation of human-induced climate change and as relevant bioeconomic feedstock. This publication-based dissertation aims to contribute to the discussion about the reliability of mitigation assessment of biomass applications in an increasingly bio-based, low-carbon economy that also fulfils sustainability constraints of resource conservation. It analysed how preference of biomass use in direct comparison as well as in larger economic context is affected by single uncertainties as well as by mitigation calculation methods. A case study on stationary bioelectricity generation from poplar wood chip gasification with a Monte Carlo approach showed that such bioelectricity could emit less greenhouse gases (GHG) or even sequester carbon despite existing uncertainties. The second case study analysed biomass use in a systemic context. Besides GHG emissions also resource demand of cropland and fossil fuels were used to assess two strategies to isolate buildings. From the three criteria, none of the strategies would clearly be preferred. The third case study presented an approach to assess the efficiency of biomass carbon use (CUDe; Carbon Utilization Degree) and applied it exemplarily to a biogas and a hemp insulation system. GHG mitigation analyses of biomass use must be performed with profound knowledge of the methodology and the biomass system in its regional context. In land use change assessment, emissions resulting from deviating nitrous oxide baselines from annual and perennial crops should be considered in addition to carbon stock changes. Optimization of biomass applications only with respect to GHG emissions (or other single criteria) might overlook trade-offs. However, multi-criteria analyses might yield ambiguous results. A resource-efficient viewpoint on biogenic carbon use instead of its sole GHG implications might help to foster a transformation to bio-based, low-carbon economies.