Institut für Landwirtschaftliche Betriebslehre

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/16

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Numerische Modellierung und Simulation der räumlichen und zeitlichen Variabilität von Lachgasemissionen aus Agrarökosystemen
(2005) Huber, Stefan; Doluschitz, Reiner
The aim of this dissertation is to characterize the spatial and temporal variability of nitrous oxide emissions from agroecosystems by means of linking mathematical simulation models to Geographical Information-Systems (GIS). Specifically, this study tries to accomplish a methodological goal and a thematic goal. A general software framework for the linkage of agroecosystem-modells and GIS by employing object-oriented and component-based concepts is developed. As an example for the implementation of this framework, the agroecosystem-modell DNDC, the two-dimensional soil water model SWMS2d, and GIS are integrated to the new model Spatial DNDC. This new model is applied to the study of the spatial and temporal variability of nitrous oxide emissions from agroecosystems at different scales. The simulation of the emissions at 281 independent soil profiles from a 40 ha field in Michigan/USA for nine years shows a large temporal and spatial variability ranging from 0.35 to 4.21 kg N2O-N/ha/a. Except for three years the yearly emissions are always lognormal distributed. While comparing simulated and measured daily emissions cannot be regarded as satisfactorily, it can be shown that the median of the daily N2O-emission rates can be employed as a characteristic measure for the given site. The influence of lateral soil water movement on the emission of N2O is studied by employing SpatialDNDC on a dataset from Scheyern/Bavaria, which comprises measurement data for five sites along hill-slope transect for the year 1997. The simulated daily emission rates are very similar for the five sites and are in good agreement with the measurements. The temporal variability of the daily emission rates is largely shaped by the occurrence of nitrogen fertilization-events and following precipitation events. By looking at the yearly emissions a distinct, downslope-directed gradient can be seen with the highest emission of 6.87 kg N2O-N/ha/a at the highest hill position, and the lowest emission of 6.37 kg N2O-N/ha/a at the lowest hill position. This gradient can be explained by the soil water household which is largely influenced by a dry period in spring. Due to lateral water movement plants growing at lower positions have more water available for early-spring growth leading to higher water extraction during the dry period. Therefore the average soil water content, which is a major impact factor for N2O-emissions in SpatialDNDC, lower at the downslope positions as compared to the upslope positions. The modelling of N2O from agroecosystems in the North-China-Plain can merely be regarded as a test case for application of SpatialDNDC to larger regions and whole nations, respectively, since detailed input and validation data are missing. The three simulation studies show distinctively the two main problems of the regional usage of agroecosystem models: On the one hand detailed input data are missing leaving for the modeller only the option to make simplifying assumptions and thereby introducing great uncertainty into simulation results. On the other hand regional calibration and validation data are missing, which are crucial to the realistic depiction of variability within large study regions.
Theoretical analysis and preference modelling for the valuation of ecosystem services from native pollinators in selected Thai rural communities
(2018) Narjes, Manuel; Lippert, Christian
Until now, the existing microeconomic models concerned with pollination markets have not accommodated the global diversity of beekeeper-farmer interactions. The most prominent of such theoretical models is dedicated to describing the determinants of colony stocking densities and of equilibrium wages that farmers have paid to commercial beekeepers for decades in the highly bee-pollination reliant almond monocultures of California. This cumulative dissertation generalizes this basic model by taking into account the marginal productivity of a given agro-ecosystem’s wild bees and the opportunity costs that farmers incur when assigning labor time to beekeeping. In that regard, we assessed the economic potential of on-farm beekeeping, which can involve several bee species, by juxtaposing this activity’s net benefits against those from hiring commercial pollination services. In addition to serving as a classification tool for a plurality of farmer-beekeeper-nature interactions and related optimization problems, the resulting analytical framework helps identifying the institutional settings that are most likely to lead to a specific bioeconomic equilibrium supply of pollination. What is more, it illustrates the interplay of the pertinent economic and agro-ecological factors, thus assisting the postulation of empirically testable hypotheses. We also conducted two separate discrete choice experiments (DCEs) with orchardists from the Thai provinces of Chiang Mai (N = 198 respondents) and Chanthaburi (N = 127), in order to elicit their preferences for changes in the population of local wild bees that would hypothetically result from a conservation policy consisting (along with a per-household implementation fee) of at least one of the following three measures: (i) offering farmers bee-friendly alternatives to conventional agro-chemicals, (ii) enabling the protection and/or rehabilitation of natural bee habitats near cropland, and (iii) fostering the husbandry of native bee species by transferring technical knowledge on the practice of on-farm beekeeping. In this context, we fitted random parameter logit models on the Chiang Mai dataset. They yielded a significant willingness to pay (WTP) for the presented conservation measures and suggested that the disutility the respondents perceived for a 50% decline in the local population of native bees was greater than the utility they would derive from experiencing a bee population increase of the same magnitude. Moreover, comparing our aggregated WTP estimates to the expected production losses, showed that orchard farmers underestimated the true use value of pollination. On the other hand, the average WTP for all conservation measures combined by far exceeded the costs that, according to our calculations, each household would incur for such a project to be implemented. Our models also indicated a significant preference heterogeneity in the sampled population, which we could partly explain with idiosyncratic variables such as the respondents’ attitudes towards native bees and beekeeping. Finally, we examined further sources of randomness in the observed choice behavior, by modelling the unknown choice decision-relevant influences that could not be captured during the DCEs. To that end, we fitted generalized mixed logit (GMXL) models on the pooled datasets, which allowed comparing, on a common utility scale, the part-worth (value) estimates from Chiang Mai and Chanthaburi, where different experimental designs were applied. Our results reveal that farmers in Chanthaburi, who reported having experienced crop declines that they attributed to insufficient pollination, introduced less subjective factors into their choices than their Chiang Mai counterparts, who may have been less familiar with the importance of conserving bees. Moreover, the GMXL results also suggest that Chanthaburi farmers placed a significantly higher value on the above-mentioned measures (i) and (ii), while caring comparatively less about a 50% decline in local wild bee colonies. One can thus hypothesize that an actual local pollinator decline may have made Chanthaburi farmers more aware of the importance of conserving native bees, while paradoxically making them more independent from the provision of wild pollination services, as they started managing crop pollination with stingless bees.

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