@phdthesis{Cord2012,
  author    = {Cord, Anna},
  title     = {Potential of multi-temporal remote sensing data for modeling tree species distributions and species richness in Mexico},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-71021},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Current changes of biodiversity result almost exclusively from human activities. This anthropogenic conversion of natural ecosystems during the last decades has led to the so-called 'biodiversity crisis', which comprises the loss of species as well as changes in the global distribution patterns of organisms. Species richness is unevenly distributed worldwide. Altogether, 17 so-called 'megadiverse' nations cover less than 10\% of the earth's land surface but support nearly 70\% of global species richness. Mexico, the study area of this thesis, is one of those countries. However, due to Mexico's large extent and geographical complexity, it is impossible to conduct reliable and spatially explicit assessments of species distribution ranges based on these collection data and field work alone. In the last two decades, Species distribution models (SDMs) have been established as important tools for extrapolating such in situ observations. SDMs analyze empirical correlations between geo-referenced species occurrence data and environmental variables to obtain spatially explicit surfaces indicating the probability of species occurrence. Remote sensing can provide such variables which describe biophysical land surface characteristics with high effective spatial resolutions. Especially during the last three to five years, the number of studies making use of remote sensing data for modeling species distributions has therefore multiplied. Due to the novelty of this field of research, the published literature consists mostly of selective case studies. A systematic framework for modeling species distributions by means of remote sensing is still missing. This research gap was taken up by this thesis and specific studies were designed which addressed the combination of climate and remote sensing data in SDMs, the suitability of continuous remote sensing variables in comparison with categorical land cover classification data, the criteria for selecting appropriate remote sensing data depending on species characteristics, and the effects of inter-annual variability in remotely sensed time series on the performance of species distribution models. The corresponding novel analyses were conducted with the Maximum Entropy algorithm developed by Phillips et al. (2004). In this thesis, a more comprehensive set of remote sensing predictors than in the existing literature was utilized for species distribution modeling. The products were selected based on their ecological relevance for characterizing species distributions. Two 1 km Terra-MODIS Land 16-day composite standard products including the Enhanced Vegetation Index (EVI), Reflectance Data, and Land Surface Temperature (LST) were assembled into enhanced time series for the time period of 2001 to 2009. These high-dimensional time series data were then transformed into 18 phenological and 35 statistical metrics that were selected based on an extensive literature review. Spatial distributions of twelve tree species were modeled in a hierarchical framework which integrated climate (WorldClim) and MODIS remote sensing data. The species are representative of the major Mexican forest types and cover a variety of ecological traits, such as range size and biotope specificity. Trees were selected because they have a high probability of detection in the field and since mapping vegetation has a long tradition in remote sensing. The result of this thesis showed that the integration of remote sensing data into species distribution models has a significant potential for improving and both spatial detail and accuracy of the model predictions.},
  subject      = {Fernerkundung},
  language  = {en}
}
@phdthesis{Hancock2012,
  author    = {Hancock, Christine [geb. Herbst]},
  title     = {Influence of land use on Plantago lanceolata L. and its higher trophic levels at different spatial scales and in three geographic regions},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-73877},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2012},
  abstract  = {Heutzutage pr{\"a}gen landwirtschaftlich genutzte Fl{\"a}chen einen großen Teil der deutschen Landschaft. Die Umwandlung von nat{\"u}rlichen Lebensr{\"a}umen zu bewirtschaftetem Gr{\"u}nland beeinflusst grundlegend die Vielfalt von Pflanzen und Tieren. Zwar erh{\"o}ht die intensive Nutzung dieser Fl{\"a}chen die Produktivit{\"a}t der Pflanzen oder die Biomasse als Viehfutter auf den Wiesen. Wie diese Einfl{\"u}sse auf die Artenvielfalt, {\"O}kosysteme und trophische Interaktionen, im Laufe der Jahre wirken ist jedoch immer noch nicht vollst{\"a}ndig verstanden. Um die Funktionen der Biodiversit{\"a}t in einer landwirtschaftlich genutzten Fl{\"a}che zu verstehen konzentrierte sich meine Arbeit auf den Einfluss der Landnutzung (D{\"u}ngung, Beweidung und Mahd) auf ein Herbivor-Parasitoid-System von Plantago lanceolata. Der Spitzwegerich ist ein generalistisches Kraut mit kosmopolitischem Vorkommen. Er kann in einem sehr breiten Spektrum von Bodenverh{\"a}ltnissen (sowohl in nassen und auch in trockenen Lebensr{\"a}umen) vorkommen und ist daher ein ideales Modellsystem zur Untersuchung tritrophischer Systeme in einem Landnutzungs-intensit{\"a}tsgradienten. Die R{\"u}sselk{\"a}fer Mecinus labilis und M. pascuorum ern{\"a}hren sich von P. lanceolata und legen dort ihre Eier ab. Mesopolobus incultus ist ein generalistisch lebender Parasitoid, der verschiedenen Insektenordnungen parasitiert. Die einzigen Wirte auf P. lanceolata sind jedoch die beiden erw{\"a}hnten R{\"u}sselk{\"a}ferarten. Das Ziel meiner Studie war es, den Einfluss der Landnutzung auf ein tritrophisches System und seiner umgebenden Vegetation (Struktur, Dichte und Artenreichtum) auf unterschiedlichen r{\"a}umlichen Skalen wie Subplot, Plot und Landschaftebene in drei verschiedenen Regionen (Nord-, Mittel- und S{\"u}ddeutschland) zu untersuchen. Ich untersuchte den Einfluss der Nutzungsintensit{\"a}t nicht nur korrelativ, sondern auch experimentell. Zus{\"a}tzlich zielte ich darauf ab, aufzuzeigen wie die Vegetationszusammensetzung die Metabolite der Wirtspflanze ver{\"a}ndert und ob diese Ver{\"a}nderungen Auswirkungen auf h{\"o}here trophische Ebenen im Feld haben.},
  subject      = {Landnutzung},
  language  = {en}
}
@phdthesis{Fricke2022,
  author    = {Fricke, Ute},
  title     = {Herbivory, predation and pest control in the context of climate and land use},
  doi       = {10.25972/OPUS-28732},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-287328},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {Chapter 1 - General introduction Anthropogenic land-use and climate change are the major drivers of the global biodiversity loss. Yet, biodiversity is essential for human well-being, as we depend on the availability of potable water, sufficient food and further benefits obtained from nature. Each species makes a somewhat unique contribution to these ecosystem services. Furthermore, species tolerate environmental stressors, such as climate change, differently. Thus, biodiversity is both the "engine" and the "insurance" for human well-being in a changing climate. Here, I investigate the effects of temperature and land use on herbivory (Chapter 2), predation (Chapter 3) and pest control (Chapter 4), and at the same time identify features of habitats (e.g. plant richness, proximity to different habitat types) and landscapes (e.g. landscape diversity, proportion of oilseed rape area) as potential management targets in an adaptation strategy to climate change. Finally, I discuss the similarities and differences between factors influencing herbivory, predation and pest control, while placing the observations in the context of climate change as a multifaceted phenomenon, and highlighting starting points for sustainable insect pest management (Chapter 5). Chapter 2 - Plant richness, land use and temperature differently shape invertebrate leaf-chewing herbivory on major plant functional groups Invertebrate herbivores are temperature-sensitive. Rising temperatures increase their metabolic rates and thus their demand for carbon-rich relative to protein-rich resources, which can lead to changes in the diets of generalist herbivores. Here, we quantified leaf-area loss to chewing invertebrates among three plant functional groups (legumes, non-leguminous forbs and grasses), which largely differ in C:N (carbon:nitrogen) ratio. This reseach was conducted along spatial temperature and land-use gradients in open herbaceous vegetation adjacent to different habitat types (forest, grassland, arable field, settlement). Herbivory largely differed among plant functional groups and was higher on legumes than forbs and grasses, except in open areas in forests. There, herbivory was similar among plant functional groups and on legumes lower than in grasslands. Also the presence of many plant families lowered herbivory on legumes. This suggests that open areas in forests and diverse vegetation provide certain protection against leaf damage to some plant families (e.g. legumes). This could be used as part of a conservation strategy for protected species. Overall, the effects of the dominant habitat type in the vicinity and diverse vegetation outweighed those of temperature and large-scale land use (e.g. grassland proportion, landscape diversity) on herbivory of legumes, forbs and grasses at the present time. Chapter 3 - Landscape diversity and local temperature, but not climate, affect arthropod predation among habitat types Herbivorous insects underlie top-down regulation by arthropod predators. Thereby, predation rates depend on predator community composition and behaviour, which is shaped by temperature, plant richness and land use. How the interaction of these factors affects the regulatory performance of predators was unknown. Therefore, we assessed arthropod predation rates on artificial caterpillars along temperature, and land-use gradients. On plots with low local mean temperature (≤ 7°C) often not a single caterpillar was attacked, which may be due to the temperature-dependent inactivity of arthropods. However, multi-annual mean temperature, plant richness and the dominant habitat type in the vicinity did not substantially affect arthropod predation rates. Highest arthropod predation rates were observed in diverse landscapes (2-km scale) independently of the locally dominanting habitat type. As landscape diversity, but not multi-annual mean temperature, affected arthropod predation rates, the diversification of landscapes may also support top-down regulation of herbivores independent of moderate increases of multi-annual mean temperature in the near future. Chapter 4 - Pest control and yield of winter oilseed rape depend on spatiotemporal crop-cover dynamics and flowering onset: implications for global warming Winter oilseed rape is an important oilseed crop in Europe, yet its seed yield is diminished through pests such as the pollen beetle and stem weevils. Damage from pollen beetles depends on pest abundances, but also on the timing of infestation relative to crop development as the bud stage is particularly vulnerable. The development of both oilseed rape and pollen beetles is temperature-dependent, while temperature effects on pest abundances are yet unknown, which brings opportunities and dangers to oilseed rape cropping under increased temperatures. We obtained measures of winter oilseed rape (flowering time, seed yield) and two of its major pests (pollen beetle, stem weevils) for the first time along both land-use and temperature gradients. Infestation with stem weevils was not influenced by any temperature or land-use aspect considered, and natural pest regulation of pollen beetles in terms of parasitism rates of pollen beetle larvae was low (< 30\%), except on three out of 29 plots. Nonetheless, we could identify conditions favouring low pollen beetle abundances per plant and high seed yields. Low pollen beetle densities were favoured by a constant oilseed rape area relative to the preceding year (5-km scale), whereas a strong reduction in area (> 40\%) caused high pest densities (concentration effect). This occurred more frequently in warmer regions, due to drought around sowing, which contributed to increased pollen beetle numbers in those regions. Yet, in warmer regions, oilseed rape flowered early, which possibly led to partial escape from pollen beetle infestation in the most vulnerable bud stage. This is also suggested by higher seed yields of early flowering oilseed rape fields, but not per se at higher temperatures. Thus, early flowering (e.g. cultivar selection) and the interannual coordination of oilseed rape area offer opportunities for environmental-friendly pollen beetle management. Chapter 5 - General discussion Anthropogenic land-use and climate change are major threats to biodiversity, and consequently to ecosystem functions, although I could show that ecosystem functions such as herbivory and predation barely responded to temperature along a spatial gradient at present time. Yet, it is important to keep several points in mind: (i) The high rate of climate warming likely reduces the time that species will have to adapt to temperature in the future; (ii) Beyond mean temperatures, many aspects of climate will change; (iii) The compensation of biodiversity loss through functional redundancy in arthropod communities may be depleted at some point; (iv) Measures of ecosystem functions are limited by methodological filters, so that changes may be captured incompletely. Although much uncertainty of the effects of climate and land-use change on ecosystem functions remains, actions to halt biodiversity loss and to interfere with natural processes in an environmentally friendly way, e.g. reduction of herbivory on crops, are urgently needed. With this thesis, I contribute options to the environment-friendly regulation of herbivory, which are at least to some extent climate resilient, and at the same time make a contribution to halt biodiversity loss. Yet, more research and a transformation process is needed to make human action more sustainable. In terms of crop protection, this means that the most common method of treating pests with fast-acting pesticides is not necessarily the most sustainable. To realize sustainable strategies, collective efforts will be needed targeted at crop damage prevention through reducing pest populations and densities in the medium to long term. The sooner we transform human action from environmentally damaging to biodiversity promoting, the higher is our insurance asset that secures human well-being under a changing climate.},
  subject      = {{\"O}kologie},
  language  = {en}
}
@phdthesis{Koenig2018,
  author    = {K{\"o}nig, Julia Maria},
  title     = {Fungal grass endophytes and their dependence on land-use intensity},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-163890},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {Plant-associated fungi can affect the plants' interaction with herbivores and other microorganisms. For example, many common forage grasses are infected with Epichlo{\"e} endophytes. The endophytes systemically colonize the aerial parts of the plants. They produce bioprotective alkaloids that can negatively affect insects and livestock feeding on the grasses, and interact with other fungal species which living from the plants' nutrients. Environmental conditions strongly influence Epichlo{\"e} endophytes. Endophyte-mediated effects on herbivores are more pronounced under increased temperatures and the endophytes may benefit from land use in managed grasslands. Under the framework of the large-scale German project "Biodiversity Exploratories", I investigated whether infection rates and alkaloid concentrations of Epichlo{\"e} festucae var. lolii in Lolium perenne (Chapter I) and Epichlo{\"e} endophytes (E. uncinata, E. siegelii) in Festuca pratensis (Chapter II) depend on land use and season. Further I analysed, whether foliar fungal assemblages of L. perenne are affected by the presence of Epichlo{\"e} endophytes (Chapter IV).},
  subject      = {Endophytische Pilze},
  language  = {en}
}
@phdthesis{Mayr2021,
  author    = {Mayr, Antonia Veronika},
  title     = {Following Bees and Wasps up Mt. Kilimanjaro: From Diversity and Traits to hidden Interactions of Species},
  doi       = {10.25972/OPUS-18292},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-182922},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2021},
  abstract  = {Chapter 1 - General Introduction One of the greatest challenges of ecological research is to predict the response of ecosystems to global change; that is to changes in climate and land use. A complex question in this context is how changing environmental conditions affect ecosystem processes at different levels of communities. To shed light on this issue, I investigate drivers of biodiversity on the level of species richness, functional traits and species interactions in cavity-nesting Hymenoptera. For this purpose, I take advantage of the steep elevational gradient of Mt. Kilimanjaro that shows strong environmental changes on a relatively small spatial scale and thus, provides a good environmental scenario for investigating drivers of diversity. In this thesis, I focus on 1) drivers of species richness at different trophic levels (Chapter 2); 2) seasonal patterns in nest-building activity, life-history traits and ecological rates in three different functional groups and at different elevations (Chapter 3) and 3) changes in cuticular hydrocarbons, pollen composition and microbiomes in Lasioglossum bees caused by climatic variables (Chapter 4). Chapter 2 - Climate and food resources shape species richness and trophic interactions of cavity-nesting Hymenoptera Drivers of species richness have been subject to research for centuries. Temperature, resource availability and top-down regulation as well as the impact of land use are considered to be important factors in determining insect diversity. Yet, the relative importance of each of these factors is unknown. Using trap nests along the elevational gradient of Mt. Kilimanjaro, we tried to disentangle drivers of species richness at different trophic levels. Temperature was the major driver of species richness across trophic levels, with increasing importance of food resources at higher trophic levels in natural antagonists. Parasitism rate was both related to temperature and trophic level, indicating that the relative importance of bottom-up and top-down forces might shift with climate change. Chapter 3 - Seasonal variation in the ecology of tropical cavity-nesting Hymenoptera Natural populations fluctuate with the availability of resources, presence of natural enemies and climatic variations. But tropical mountain seasonality is not yet well investigated. We investigated seasonal patterns in nest-building activity, functional traits and ecological rates in three different insect groups at lower and higher elevations separately. Insects were caught with trap nests which were checked monthly during a 17 months period that included three dry and three rainy seasons. Insects were grouped according to their functional guilds. All groups showed strong seasonality in nest-building activity which was higher and more synchronised among groups at lower elevations. Seasonality in nest building activity of caterpillar-hunting and spider-hunting wasps was linked to climate seasonality while in bees it was strongly linked to the availability of flowers, as well as for the survival rate and sex ratio of bees. Finding adaptations to environmental seasonality might imply that further changes in climatic seasonality by climate change could have an influence on life-history traits of tropical mountain species. Chapter 4 - Cryptic species and hidden ecological interactions of halictine bees along an elevational Gradient Strong environmental gradients such as those occurring along mountain slopes are challenging for species. In this context, hidden adaptations or interactions have rarely been considered. We used bees of the genus Lasioglossum as model organisms because Lasioglossum is the only bee genus occurring with a distribution across the entire elevational gradient at Mt. Kilimanjaro. We asked if and how (a) cuticular hydrocarbons (CHC), which act as a desiccation barrier, change in composition and chain length along with changes in temperature and humidity (b), Lasioglossum bees change their pollen diet with changing resource availability, (c) gut microbiota change with pollen diet and climatic conditions, and surface microbiota change with CHC and climatic conditions, respectively, and if changes are rather influenced by turnover in Lasioglossum species along the elevational gradient. We found physiological adaptations with climate in CHC as well as changes in communities with regard to pollen diet and microbiota, which also correlated with each other. These results suggest that complex interactions and feedbacks among abiotic and biotic conditions determine the species composition in a community. Chapter 5 - General Discussion Abiotic and biotic factors drove species diversity, traits and interactions and they worked differently depending on the functional group that has been studied, and whether spatial or temporal units were considered. It is therefore likely, that in the light of global change, different species, traits and interactions will be affected differently. Furthermore, increasing land use intensity could have additional or interacting effects with climate change on biodiversity, even though the potential land-use effects at Mt. Kilimanjaro are still low and not impairing cavity-nesting Hymenoptera so far. Further studies should address species networks which might reveal more sensitive changes. For that purpose, trap nests provide a good model system to investigate effects of global change on multiple trophic levels and may also reveal direct effects of climate change on entire life-history traits when established under different microclimatic conditions. The non-uniform effects of abiotic and biotic conditions on multiple aspects of biodiversity revealed with this study also highlight that evaluating different aspects of biodiversity can give a more comprehensive picture than single observations.},
  subject      = {land use},
  language  = {en}
}
@phdthesis{Steckel2013,
  author    = {Steckel, Juliane},
  title     = {Effects of landscape heterogeneity and land use on interacting groups of solitary bees, wasps and their flying and ground-dwelling antagonists},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-87900},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Die Heterogenit{\"a}t unserer heutigen Landschaften und Habitate ist gepr{\"a}gt und von jahrzehntelanger Landnutzungsintensivierung. Die daraus hervorgegangene Verarmung von weitr{\"a}umigen Arealen f{\"u}hrte zu einer zeitlich und r{\"a}umlich stark eingeschr{\"a}nkten Verf{\"u}gbarkeit von Nistm{\"o}glichkeiten und Nahrungsressourcen f{\"u}r Wildbienen und Wespen. Die Folgen sich ver{\"a}ndernder Ressourcenverf{\"u}gbarkeit f{\"u}r Wildbienen und Wespen war und ist eine Gef{\"a}hrdung der Artenvielfalt und der {\"O}kosystemprozesse, die diese Arten in Gang halten. Konsequenzen f{\"u}r diese wichtigen Best{\"a}uber und Pr{\"a}datoren sind kaum erforscht, genauso wenig wie f{\"u}r ihre Gegenspieler als nat{\"u}rliche Top-Down-Regulatoren. Nisthilfen f{\"u}r Wildbienen, Wespen und ihre nat{\"u}rlichen Gegenspieler eignen sich hervorragend um diese Wissensl{\"u}cken zu f{\"u}llen, da sie wertvolle Einblicke gew{\"a}hren in ansonsten verborgene trophische Interaktionen, wie Parasitierung und Pr{\"a}dation, aber auch in {\"O}kosystemprozesse wie Best{\"a}ubung und Reproduktion. Somit stellten wir uns in Kapitel II zun{\"a}chst die Frage, wie die Abundanz von st{\"a}ngelnistenden Bienen und Wespen im Gr{\"u}nland von dessen Bewirtschaftung abh{\"a}ngt. Außerdem untersuchten wir, wie Landnutzung die Effektivit{\"a}t der Top-Down-Regulation von Wildbienen und Wespen durch zwei verschiedene Gruppen von Gegenspielern beeinflusst. Dazu haben wir einer der beiden Gruppen, den bodenlebenden Gegenspielern, den Zugang zu den Nisthilfen vorenthalten. In einer großangelegten Feldstudie, die sich {\"u}ber drei verschiedene Regionen Deutschlands erstreckte, installierten wir 760 Nisthilfen auf 95 Gr{\"u}nlandfl{\"a}chen. Der Versuchsplan beinhaltete gem{\"a}hte und nicht gem{\"a}hte Versuchsplots, sowie Plots mit und ohne Ausschluss von Bodenpr{\"a}datoren. Wildbienen und Wespen besiedelten die Nisthilfen unabh{\"a}ngig davon, ob Bodenpr{\"a}datoren nun Zugang zu den Nisthilfen hatten oder nicht. Allerdings erh{\"o}hte sich die Rate der von fliegenden Gegenspielern gefressenen und parasitierten Brutzellen (Fressrate) sobald bodenlebende Gegenspieler ausgeschlossen wurden. Diese Fressrate war vom experimentellen M{\"a}hen unabh{\"a}ngig. Jedoch wiesen ungem{\"a}hte Versuchsplots marginal signifikant mehr Brutzellen von Wespen auf. Beide Manipulationen, das M{\"a}hen und der Pr{\"a}datorausschluss, interagierten signifikant. So wurden auf gem{\"a}hten Plots, auf denen Bodenpr{\"a}datoren ausgeschlossen waren, h{\"o}here Fressraten der fliegenden Gegenspieler beobachtet, w{\"a}hrend dieser Effekt auf der ungem{\"a}hten Plots ausblieb. Das Thema in Kapitel III ist der relative Einfluss lokaler Gr{\"u}nlandnutzung, Landschaftsdiversit{\"a}t und Landschaftsstruktur auf Artenvielfalt und -abundanz von Wildbienen, Wespen und ihrer fliegenden Gegenspieler. Dazu kartierten wir Landnutzungstypen innerhalb konzentrischer Kreise um die Versuchsplots. Mithilfe der digitalisierten Landschaftsdaten berechneten wir Indices als Maße f{\"u}r Landschaftsdiversit{\"a}t und -struktur f{\"u}r acht Radien bis 2000 m. Der negative Effekt lokaler Landnutzung auf die Wirtsabundanz war nur marginal signifikant. Jedoch stellten wir einen positiven Effekt der Landschaftsdiversit{\"a}t innerhalb kleiner Radien auf die Artenvielfalt und -abundanz der Wirte fest. Die fliegenden Gegenspieler allerdings profitierten von einer komplexen Landschaftsstruktur innerhalb großer Radien. Die letzte Studie, vorgestellt in Kapitel IV, behandelt die Bedeutung von Ressourcenverf{\"u}gbarkeit f{\"u}r die Dauer von Fouragierfl{\"u}gen und die sich daraus ergebenen Konsequenzen f{\"u}r den Reproduktionserfolg der Roten Mauerbiene. Dazu beobachteten wir nistenden Bienen auf 18 Gr{\"u}nlandfl{\"a}chen in zwei der Untersuchungsregionen in Deuschland. Wir ermittelten die lokale Landnutzungsintensit{\"a}t, lokale Bl{\"u}tendeckung sowie Landschaftsdiversit{\"a}t und -struktur als wichtige potentielle Einflussfaktoren. Jede Gr{\"u}nlandfl{\"a}che wurde mit acht Nisthilfen und 50 weiblichen Bienen ausgestattet. Verschiedene Nestbau-Aktivit{\"a}ten, wie Fouragierfl{\"u}ge f{\"u}r Pollen und Nektar, wurden aufgenommen. Wir stellten fest, dass Fouragierfl{\"u}ge f{\"u}r Pollen und Nektar in komplexen, strukturreichen Landschaften signifikant k{\"u}rzer waren, dass jedoch weder lokale Faktoren, noch Landschaftsdiversit{\"a}t eine Rolle spielten. Wir konnten keinen Zusammenhang zwischen der Dauer von Fouragierfl{\"u}gen und Reproduktionserfolg feststellen. Um eine r{\"a}umlich und zeitlich konstante Versorgung von Nahrungs- und Nistressourcen zu gew{\"a}hrleisten und damit biotische Interaktionen, Diversit{\"a}t und Besiedlungserfolg von Wildbienen, Wespen und ihrer Gegenspieler zu unterst{\"u}tzen, empfehlen wir Maßnahmen, die sowohl die lokale Landnutzung als auch unterschiedliche Landschaftsfaktoren ber{\"u}cksichtigen.},
  subject      = {Wildbienen},
  language  = {en}
}
@phdthesis{Loew2013,
  author    = {L{\"o}w, Fabian},
  title     = {Agricultural crop mapping from multi-scale remote sensing data - Concepts and applications in heterogeneous Middle Asian agricultural landscapes},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-102093},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2013},
  abstract  = {Agriculture is mankind's primary source of food production and plays the key role for cereal supply to humanity. One of the future challenges will be to feed a constantly growing population, which is expected to reach more than nine billion by 2050. The potential to expand cropland is limited, and enhancing agricultural production efficiency is one important means to meet the future food demand. Hence, there is an increasing demand for dependable, accurate and comprehensive agricultural intelligence on crop production. The value of satellite earth observation (EO) data for agricultural monitoring is well recognized. One fundamental requirement for agricultural monitoring is routinely updated information on crop acreage and the spatial distribution of crops. With the technical advancement of satellite sensor systems, imagery with higher temporal and finer spatial resolution became available. The classification of such multi-temporal data sets is an effective and accurate means to produce crop maps, but methods must be developed that can handle such large and complex data sets. Furthermore, to properly use satellite EO for agricultural production monitoring a high temporal revisit frequency over vast geographic areas is often necessary. However, this often limits the spatial resolution that can be used. The challenge of discriminating pixels that correspond to a particular crop type, a prerequisite for crop specific agricultural monitoring, remains daunting when the signal encoded in pixels stems from several land uses (mixed pixels), e.g. over heterogeneous landscapes where individual fields are often smaller than individual pixels. The main purposes of the presented study were (i) to assess the influence of input dimensionality and feature selection on classification accuracy and uncertainty in object-based crop classification, (ii) to evaluate if combining classifier algorithms can improve the quality of crop maps (e.g. classification accuracy), (iii) to assess the spatial resolution requirements for crop identification via image classification. Reporting on the map quality is traditionally done with measures that stem from the confusion matrix based on the hard classification result. Yet, these measures do not consider the spatial variation of errors in maps. Measures of classification uncertainty can be used for this purpose, but they have attained only little attention in remote sensing studies. Classifier algorithms like the support vector machine (SVM) can estimate class memberships (the so called soft output) for each classified pixel or object. Based on these estimations, measures of classification uncertainty can be calculated, but it has not been analysed in detail, yet, if these are reliable in predicting the spatial distribution of errors in maps. In this study, SVM was applied for the classification of agricultural crops in irrigated landscapes in Middle Asia at the object-level. Five different categories of features were calculated from RapidEye time series data as classification input. The reliability of classification uncertainty measures like entropy, derived from the soft output of SVM, with regard to predicting the spatial distribution of error was evaluated. Further, the impact of the type and dimensionality of the input data on classification uncertainty was analysed. The results revealed that SMVs applied to the five feature categories separately performed different in classifying different types of crops. Incorporating all five categories of features by concatenating them into one stacked vector did not lead to an increase in accuracy, and partly reduced the model performance most obviously because of the Hughes phenomena. Yet, applying the random forest (RF) algorithm to select a subset of features led to an increase of classification accuracy of the SVM. The feature group with red edge-based indices was the most important for general crop classification, and the red edge NDVI had an outstanding importance for classifying crops. Two measures of uncertainty were calculated based on the soft output from SVM: maximum a-posteriori probability and alpha quadratic entropy. Irrespective of the measure used, the results indicate a decline in classification uncertainty when a dimensionality reduction was performed. The two uncertainty measures were found to be reliable indicators to predict errors in maps. Correctly classified test cases were associated with low uncertainty, whilst incorrectly test cases tended to be associated with higher uncertainty. The issue of combining the results of different classifier algorithms in order to increase classification accuracy was addressed. First, the SVM was compared with two other non-parametric classifier algorithms: multilayer perceptron neural network (MLP) and RF. Despite their comparatively high classification performance, each of the tested classifier algorithms tended to make errors in different parts of the input space, e.g. performed different in classifying crops. Hence, a combination of the complementary outputs was envisaged. To this end, a classifier combination scheme was proposed, which is based on existing algebraic operators. It combines the outputs of different classifier algorithms at the per-case (e.g. pixel or object) basis. The per-case class membership estimations of each classifier algorithm were compared, and the reliability of each classifier algorithm with respect to classifying a specific crop class was assessed based on the confusion matrix. In doing so, less reliable classifier algorithms were excluded at the per-class basis before the final combination. Emphasis was put on evaluating the selected classification algorithms under limiting conditions by applying them to small input datasets and to reduced training sample sets, respectively. Further, the applicability to datasets from another year was demonstrated to assess temporal transferability. Although the single classifier algorithms performed well in all test sites, the classifier combination scheme provided consistently higher classification accuracies over all test sites and in different years, respectively. This makes this approach distinct from the single classifier algorithms, which performed different and showed a higher variability in class-wise accuracies. Further, the proposed classifier combination scheme performed better when using small training set sizes or when applied to small input datasets, respectively. A framework was proposed to quantitatively define pixel size requirements for crop identification via image classification. That framework is based on simulating how agricultural landscapes, and more specifically the fields covered by one crop of interest, are seen by instruments with increasingly coarser resolving power. The concept of crop specific pixel purity, defined as the degree of homogeneity of the signal encoded in a pixel with respect to the target crop type, is used to analyse how mixed the pixels can be (as they become coarser) without undermining their capacity to describe the desired surface properties (e.g. to distinguish crop classes via supervised or unsupervised image classification). This tool can be modulated using different parameterizations to explore trade-offs between pixel size and pixel purity when addressing the question of crop identification. Inputs to the experiments were eight multi-temporal images from the RapidEye sensor. Simulated pixel sizes ranged from 13 m to 747.5 m, in increments of 6.5 m. Constraining parameters for crop identification were defined by setting thresholds for classification accuracy and uncertainty. Results over irrigated agricultural landscapes in Middle Asia demonstrate that the task of finding the optimum pixel size did not have a "one-size-fits-all" solution. The resulting values for pixel size and purity that were suitable for crop identification proved to be specific to a given landscape, and for each crop they differed across different landscapes. Over the same time series, different crops were not identifiable simultaneously in the season and these requirements further changed over the years, reflecting the different agro-ecological conditions the investigated crops were growing in. Results further indicate that map quality (e.g. classification accuracy) was not homogeneously distributed in a landscape, but that it depended on the spatial structures and the pixel size, respectively. The proposed framework is generic and can be applied to any agricultural landscape, thereby potentially serving to guide recommendations for designing dedicated EO missions that can satisfy the requirements in terms of pixel size to identify and discriminate crop types. Regarding the operationalization of EO-based techniques for agricultural monitoring and its application to a broader range of agricultural landscapes, it can be noted that, despite the high performance of existing methods (e.g. classifier algorithms), transferability and stability of such methods remain one important research issue. This means that methods developed and tested in one place might not necessarily be portable to another place or over several years, respectively. Specifically in Middle Asia, which was selected as study region in this thesis, classifier combination makes sense due to its easy implementation and because it enhanced classification accuracy for classes with insufficient training samples. This observation makes it interesting for operational contexts and when field reference data availability is limited. Similar to the transferability of methods, the application of only one certain kind of EO data (e.g. with one specific pixel size) over different landscapes needs to be revisited and the synergistic use of multi-scale data, e.g. combining remote sensing imagery of both fine and coarse spatial resolution, should be fostered. The necessity to predict and control the effects of spatial and temporal scale on crop classification is recognized here as a major goal to achieve in EO-based agricultural monitoring.},
  subject      = {Fernerkundung},
  language  = {en}
}