Social Learning Processes in Swiss Soil Protection? The 'From Farmer - To Farmer' Project

Social learning approaches have become a prominent focus in studies related to sustainable agriculture. In order to better understand the potential of social learning for more sustainable development, the present study assessed the processes, effects and facilitating elements of interaction related to social learning in the context of Swiss soil protection and the innovative ‘From Farmer - To Farmer’ project. The study reveals that social learning contributes to fundamental transformations of patterns of interactions. However, the study also demonstrates that a learning-oriented understanding of sustainable development implies including analysis of the institutional environments in which the organizations of the individual representatives of face-to-face-based social learning processes are operating. This has shown to be a decisive element when face-to-face-based learning processes of the organisations’ representatives are translated into organisational learning. Moreover, the study revealed that this was achieved not directly through formalisation of new lines of institutionalised cooperation but by establishing links in a ‘boundary space’ trying out new forms of collaboration, aiming at social learning and co-production of knowledge. It is argued that further research on social learning processes should give greater emphasis to this intermediary level of ‘boundary spaces’.

Organic vs. Conventional Grassland Management: Do N-15 and C-13 Isotopic Signatures of Hay and Soil Samples Differ?

Distinguishing organic and conventional products is a major issue of food security and authenticity. Previous studies successfully used stable isotopes to separate organic and conventional products, but up to now, this approach was not tested for organic grassland hay and soil. Moreover, isotopic abundances could be a powerful tool to elucidate differences in ecosystem functioning and driving mechanisms of element cycling in organic and conventional management systems. Here, we studied the delta N-15 and delta C-13 isotopic composition of soil and hay samples of 21 organic and 34 conventional grasslands in two German regions. We also used Delta delta N-15 (delta N-15 plant - delta N-15 soil) to characterize nitrogen dynamics. In order to detect temporal trends, isotopic abundances in organic grasslands were related to the time since certification. Furthermore, discriminant analysis was used to test whether the respective management type can be deduced from observed isotopic abundances. Isotopic analyses revealed no significant differences in delta C-13 in hay and delta C-13 in both soil and hay between management types, but showed that delta C-13 abundances were significantly lower in soil of organic compared to conventional grasslands. delta C-15 values implied that management types did not substantially differ in nitrogen cycling. Only delta C-13 in soil and hay showed significant negative relationships with the time since certification. Thus, our result suggest that organic grasslands suffered less from drought stress compared to conventional grasslands most likely due to a benefit of higher plant species richness, as previously shown by manipulative biodiversity experiments. Finally, it was possible to correctly classify about two third of the samples according to their management using isotopic abundances in soil and hay. However, as more than half of the organic samples were incorrectly classified, we infer that more research is needed to improve this approach before it can be efficiently used in practice.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

Mapping material distribution in a heterogeneous sand tank by image analysis

Water flow and solute transport through soils are strongly influenced by the spatial arrangement of soil materials with different hydraulic and chemical properties. Knowing the specific or statistical arrangement of these materials is considered as a key toward improved predictions of solute transport. Our aim was to obtain two-dimensional material maps from photographs of exposed profiles. We developed a segmentation and classification procedure and applied it to the images of a very heterogeneous sand tank, which was used for a series of flow and transport experiments. The segmentation was based on thresholds of soil color, estimated from local median gray values, and of soil texture, estimated from local coefficients of variation of gray values. Important steps were the correction of inhomogeneous illumination and reflection, and the incorporation of prior knowledge in filters used to extract the image features and to smooth the results morphologically. We could check and confirm the success of our mapping by comparing the estimated with the designed sand distribution in the tank. The resulting material map was used later as input to model flow and transport through the sand tank. Similar segmentation procedures may be applied to any high-density raster data, including photographs or spectral scans of field profiles.

The Aeolian Flux of Calcium, Chloride and Nitrate to the McMurdo Dry Valleys Landscape: Evidence from Snow Pit Analysis

We have determined the flux of calcium, chloride and nitrate to the McMurdo Dry Valleys region by analysing snow pits for their chemical composition and their snow accumulation using multiple records spanning up to 48 years. The fluxes demonstrate patterns related to elevation and proximity to the ocean. In general, there is a strong relationship between the nitrate flux and snow accumulation, indicating that precipitation rates may have a great influence over the nitrogen concentrations in the soils of the valleys. Aeolian dust transport plays an important role in the deposition of some elements (e.g. C(2+)) into the McMurdo Dry Valleys' soils. Because of the antiquity of some of the soil surfaces in the McMurdo Dry Valleys regions, the accumulated atmospheric flux of salts to the soils has important ecological consequences. Although precipitation may be an important mechanism of salt deposition to the McMurdo Dry Valley surfaces, it is poorly understood because of difficulties in measurement and high losses from sublimation.

Biotic and Abiotic Properties Mediating Plant Diversity Effects on Soil Microbial Communities in an Experimental Grassland

Plant diversity drives changes in the soil microbial community which may result in alterations in ecosystem functions. However, the governing factors between the composition of soil microbial communities and plant diversity are not well understood. We investigated the impact of plant diversity (plant species richness and functional group richness) and plant functional group identity on soil microbial biomass and soil microbial community structure in experimental grassland ecosystems. Total microbial biomass and community structure were determined by phospholipid fatty acid (PLFA) analysis. The diversity gradient covered 1, 2, 4, 8, 16 and 60 plant species and 1, 2, 3 and 4 plant functional groups (grasses, legumes, small herbs and tall herbs). In May 2007, soil samples were taken from experimental plots and from nearby fields and meadows. Beside soil texture, plant species richness was the main driver of soil microbial biomass. Structural equation modeling revealed that the positive plant diversity effect was mainly mediated by higher leaf area index resulting in higher soil moisture in the top soil layer. The fungal-to-bacterial biomass ratio was positively affected by plant functional group richness and negatively by the presence of legumes. Bacteria were more closely related to abiotic differences caused by plant diversity, while fungi were more affected by plant-derived organic matter inputs. We found diverse plant communities promoted faster transition of soil microbial communities typical for arable land towards grassland communities. Although some mechanisms underlying the plant diversity effect on soil microorganisms could be identified, future studies have to determine plant traits shaping soil microbial community structure. We suspect differences in root traits among different plant communities, such as root turnover rates and chemical composition of root exudates, to structure soil microbial communities.

Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

Outbreak investigation identifies a single Listeria monocytogenes strain in sheep with different clinical manifestations, soil and water.

Listeria (L.) monocytogenes causes orally acquired infections and is of major importance in ruminants. Little is known about L. monocytogenes transmission between farm environment and ruminants. In order to determine potential sources of infection, we investigated the distribution of L. monocytogenes genetic subtypes in a sheep farm during a listeriosis outbreak by applying four subtyping methods (MALDI-TOF-MS, MLST, MLVA and PFGE). L. monocytogenes was isolated from a lamb with septicemia and from the brainstem of three sheep with encephalitis. Samples from the farm environment were screened for the presence of L. monocytogenes during the listeriosis outbreak, four weeks and eight months after. L. monocytogenes was found only in soil and water tank swabs during the outbreak. Four weeks later, following thorough cleaning of the barn, as well as eight months later, L. monocytogenes was absent in environmental samples. All environmental and clinical L. monocytogenes isolates were found to be the same strain. Our results show that the outbreak involving two different clinical syndromes was caused by a single L. monocytogenes strain and that soil and water tanks were potential infection sources during this outbreak. However, silage cannot be completely ruled out as the bales fed prior to the outbreak were not available for analysis. Faeces samples were negative, suggesting that sheep did not act as amplification hosts contributing to environmental contamination. In conclusion, farm management appears to be a crucial factor for the limitation of a listeriosis outbreak.

Afdeyu Research Substation: Hydrometeorological Data Analysis 1984-2007

This report presents a basic analyis of the data collected on agroclimatology, erosion, and soil and water conservation at Afdeyu Station in the central highlands of Eritrea between 1984 and 2007. Datasets and graphs include rainfall, air and soil surface temperatures, soil loss, surface runoff, river discharge, and land use including cropping patterns of the measured catchment.

Plant diversity drives soil microbial biomass carbon in grasslands irrespective of global environmental change factors

Soil microbial biomass is a key determinant of carbon dynamics in the soil. Several studies have shown that soil microbial biomass significantly increases with plant species diversity, but it remains unclear whether plant species diversity can also stabilize soil microbial biomass in a changing environment. This question is particularly relevant as many global environmental change (GEC) factors, such as drought and nutrient enrichment, have been shown to reduce soil microbial biomass. Experiments with orthogonal manipulations of plant diversity and GEC factors can provide insights whether plant diversity can attenuate such detrimental effects on soil microbial biomass. Here, we present the analysis of 12 different studies with 14 unique orthogonal plant diversity × GEC manipulations in grasslands, where plant diversity and at least one GEC factor (elevated CO2, nutrient enrichment, drought, earthworm presence, or warming) were manipulated. Our results show that higher plant diversity significantly enhances soil microbial biomass with the strongest effects in long-term field experiments. In contrast, GEC factors had inconsistent effects with only drought having a significant negative effect. Importantly, we report consistent non-significant effects for all 14 interactions between plant diversity and GEC factors, which indicates a limited potential of plant diversity to attenuate the effects of GEC factors on soil microbial biomass. We highlight that plant diversity is a major determinant of soil microbial biomass in experimental grasslands that can influence soil carbon dynamics irrespective of GEC.

Evaluation of soil salinity amelioration technologies in Timpaki, Crete

Salinization is a soil threat that adversely affects ecosystem services and diminishes soil functions in many arid and semi-arid regions. Soil salinity management depends on a range of factors, and can be complex expensive and time demanding. Besides taking no action, possible management strategies include amelioration and adaptation measures. The WOCAT Technologies Questionnaire is a standardized methodology for monitoring, evaluating and documenting sustainable land management practices through interaction with the stakeholders. Here we use WOCAT for the systematic analysis and evaluation of soil salinization amelioration measures, for the RECARE project Case Study in Greece, the Timpaki basin, a semi-arid region in south-central Crete where the main land use is horticulture in greenhouses irrigated by groundwater. Excessive groundwater abstractions have resulted in a drop of the groundwater level in the coastal part of the aquifer, thus leading to seawater intrusion and in turn to soil salinization due to irrigation with brackish water. Amelioration technologies that have already been applied in the case study by the stakeholders are examined and classified depending on the function they promote and/or improve. The documented technologies are evaluated for their impacts on ecosystem services, cost and input requirements. Preliminary results show that technologies which promote maintaining existing crop types while enhancing productivity and decreasing soil salinity such as composting, mulching, rain water harvesting and seed biopriming are preferred by the stakeholders. Further work will include result validation using qualitative approaches.

Evaluation of promising technologies for soil salinity amelioration in Timpaki (Crete): A participatory approach

Soil salinity management can be complex, expensive, and time demanding, especially in arid and semi-arid regions. Besides taking no action, possible management strategies include amelioration and adaptation measures. Here we apply the World Overview of Conservation Approaches and Technologies (WOCAT) framework for the systematic analysis and evaluation and selection of soil salinisation amelioration technologies in close collaboration with stakeholders. The participatory approach is applied in the RECARE (Preventing and Remediating degradation of soils in Europe through Land Care) project case study of Timpaki, a semiarid region in south-central Crete (Greece) where the main land use is horticulture in greenhouses irrigated by groundwater. Excessive groundwater abstractions have resulted in a drop of the groundwater level in the coastal part of the aquifer, thus leading to seawater intrusion and in turn to soil salinisation. The documented technologies are evaluated for their impacts on ecosystem services, cost, and input requirements using a participatory approach and field evaluations. Results show that technologies which promote maintaining existing crop types while enhancing productivity and decreasing soil salinity are preferred by the stakeholders. The evaluation concludes that rainwater harvesting is the optimal solution for direct soil salinity mitigation, as it addresses a wider range of ecosystem and human well-being benefits. Nevertheless, this merit is offset by poor financial motivation making agronomic measures more attractive to users.

Actions of the International Union of Soil Science towards a global agenda for the sustainable use of soils

In a multi-level stakeholder approach the international level is of primordial importance not only in terms of legal frameworks, but also in terms of scientific analysis of the needs, options and constraints, as well as related to monitoring and evaluation systems. The Working Group on 'International Actions for the Sustainable Use of Soils' (IASUS) of the International Union of Soil Science (IUSS) identified a number of issues and measures in preparation of the 17thWorld Congress of Soil Science held in Bangkok, Thailand, in August 2002, and prepared a resolution in support of a 'global agenda for the sustainable use of soils', which was adopted on 21st August 2002 on the closing day of the congress.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.