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Large-scale commercial cropping of soybeans expanded in the tropical Amazon and Cerrado biomes of Brazil after 1990. More recently, cropping intensified from single-cropping of soybeans to double-cropping of soybeans with corn or cotton. Cropland expansion and intensification, and the accompanying use of mineral fertilizers, raise concerns about whether nutrient runoff and impacts to surface waters will be similar to those experienced in commercial cropland regions at temperate latitudes. We quantified water infiltration through soils, water yield, and streamwater chemistry in watersheds draining native tropical forest and single-and double-cropped areas on the level, deep, highly weathered soils where cropland expansion and intensification typically occurs. Although water yield increased four-fold from croplands, streamwater chemistry remained largely unchanged. Soil characteristics exerted important control over the movement of nitrogen (N) and phosphorus (P) into streams. High soil infiltration rates prevented surface erosion and movement of particulate P, while P fixation in surface soils restricted P movement to deeper soil layers. Nitrogen retention in deep soils, likely by anion exchange, also appeared to limit N leaching and export in streamwater from both single-and double-cropped watersheds that received nitrogen fertilizer. These mechanisms led to lower streamwater P and N concentrations and lower watershed N and P export than would be expected, based on studies from temperate croplands with similar cropping and fertilizer application practices.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.
The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b(899). The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.
The public promotion of renewable energies is expected to increase the number of biogas plants and stimulate energy crops cultivation (e. g. maize) in Germany. In order to assess the indirect effects of the resulting land-use changes on biodiversity, we developed six land-use scenarios and simulated the responses of six farmland wildlife species with the spatially explicit agent-based model system ALMaSS. The scenarios differed in composition and spatial configuration of arable crops. We implemented scenarios where maize for energy production replaced 15% and 30% of the area covered by other cash crops. Biogas maize farms were either randomly distributed or located within small or large aggregation clusters. The animal species investigated were skylark (Alauda arvensis), grey partridge (Perdix perdix), European brown hare (Lepus europaeus), field vole (Microtus agrestis), a linyphiid spider (Erigone atra) and a carabid beetle (Bembidion lampros). The changes in crop composition had a negative effect on the population sizes of skylark, partridge and hare and a positive effect on the population sizes of spider and beetle and no effect on the population size of vole. An aggregated cultivation of maize amplified these effects for skylark. Species responses to changes in the crop composition were consistent across three differently structured landscapes. Our work suggests that with the compliance to some recommendations, negative effects of biogas-related land-use change on the populations of the six representative farmland species can largely be avoided.
Agriculture is one of the most important human activities providing food and more agricultural goods for seven billion people around the world and is of special importance in sub-Saharan Africa. The majority of people depends on the agricultural sector for their livelihoods and will suffer from negative climate change impacts on agriculture until the middle and end of the 21st century, even more if weak governments, economic crises or violent conflicts endanger the countries’ food security. The impact of temperature increases and changing precipitation patterns on agricultural vegetation motivated this thesis in the first place. Analyzing the potentials of reducing negative climate change impacts by adapting crop management to changing climate is a second objective of the thesis. As a precondition for simulating climate change impacts on agricultural crops with a global crop model first the timing of sowing in the tropics was improved and validated as this is an important factor determining the length and timing of the crops´ development phases, the occurrence of water stress and final crop yield. Crop yields are projected to decline in most regions which is evident from the results of this thesis, but the uncertainties that exist in climate projections and in the efficiency of adaptation options because of political, economical or institutional obstacles have to be considered. The effect of temperature increases and changing precipitation patterns on crop yields can be analyzed separately and varies in space across the continent. Southern Africa is clearly the region most susceptible to climate change, especially to precipitation changes. The Sahel north of 13° N and parts of Eastern Africa with short growing seasons below 120 days and limited wet season precipitation of less than 500 mm are also vulnerable to precipitation changes while in most other part of East and Central Africa, in contrast, the effect of temperature increase on crops overbalances the precipitation effect and is most pronounced in a band stretching from Angola to Ethiopia in the 2060s. The results of this thesis confirm the findings from previous studies on the magnitude of climate change impact on crops in sub-Saharan Africa but beyond that helps to understand the drivers of these changes and the potential of certain management strategies for adaptation in more detail. Crop yield changes depend on the initial growing conditions, on the magnitude of climate change, and on the crop, cropping system and adaptive capacity of African farmers which is only now evident from this comprehensive study for sub-Saharan Africa. Furthermore this study improves the representation of tropical cropping systems in a global crop model and considers the major food crops cultivated in sub-Saharan Africa and climate change impacts throughout the continent.