Farm woodlots in rural Rwanda: purposes and determinants

The development of farm woodlots as an alternative source of livelihood for smallholder farmers in diverse biophysical and socio-economic conditions is a challenging issue in developing countries, such as Rwanda, where the majority of the population relies on subsistence farming. There is a need to understand why and when farmers decide to grow trees and woodlots on their farms. The objective of this study was to analyse the determinants and the purposes that enhance the propensity to grow woodlots in low, medium and high altitude regions of Rwanda. Necessary information for this study came from a survey of 480 households across these regions. The results showed regional variations in the determinants of woodlot farming, demonstrating the importance of not extrapolating the results between regions. Pooled data across regions indicated that age of the householder, number of salaried household members, farm size, travel distance to fuelwood sources and household location in medium forest cover region had positive significant effects on the propensity to grow farm woodlots. In contrast, household location in low forest cover region, ownership of livestock and monthly frequency of purchasing fuelwood were inversely related to the presence of farm woodlots. Many households planted eucalyptus woodlots for economic reasons, not for environmental purposes. Livestock and crop production were more attractive to rural households than woodlot farming. The findings of the study can be used by policymakers and extension services in order to promote sustainable land use practices by focusing on the challenges of competing land uses, farm size, unemployment, dependence on forests for fuelwood supply and subsistence farming.     

Multiple species-specific controls of root-feeding nematodes in natural soils

One of the major limitations to enhance sustainability of crop production systems is the inability to control root-feeding nematodes without using chemical biocides. In soils under wild vegetation, however, root-feeding nematodes affect plant performance and plant community composition varying from substantially to insignificantly. Previous studies in natural ecosystems have already shown that mutualistic symbionts, such as arbuscular mycorrhizal fungi and endophytes, may influence plant exposure to root-feeding nematodes. In order to learn more from natural systems, we examined nematode control in the root zone of a wild coastal foredune grass by microorganisms, other nematodes and microarthropods. We cultured all eight root-feeding nematode species that occur in the root zone of marram grass (Ammophila arenaria) in coastal foredunes of the Netherlands. Then, in an indoor growth experiment we exposed each nematode species to the potential natural antagonists collected from the same dune soil. Most of the eight dominant root-feeding nematode species could be controlled to some extent by more than one group of soil organisms added. The effectiveness of control varied among nematode species, which seemed to be controlled in a species-specific way. We conclude that in a natural soil the effectiveness of control by microorganisms, other nematodes or microarthropods varies among root-feeding nematode species. Most are controlled, at least to some extent, by soil microbes. However, some root-feeding nematode species are controlled only by microarthropods. Our results strongly suggest that sustainable agriculture will benefit from using a range of biological control mechanisms when controlling root-feeding nematodes, rather than relying on single control agents. Our suggestion also implies that conserving soil biodiversity is crucial in order to enhance the reliability of biological crop protection against soil-borne pests and diseases.     

Predicting land cover changes and their impact on the sediment influx in the Lake Balaton catchment

The land cover pattern in the Lake Balaton catchment (Hungary) has been changing since decollectivization in the 1990s. These land cover changes significantly impact the landscape connectivity, controlling the influx of sediments into the lake. A comparison of high resolution land cover maps from 1981, 2000 and 2005 showed a significant extensification of the agriculture with land cover conversions from arable land and vineyards to grassland and forest. For each land unit transition probabilities were assessed using logistic regression techniques to evaluate to which extent land cover changes are controlled by physical or socio-economic parameters. A stochastic land cover allocation algorithm was applied to generate future land cover patterns. The landscape connectivity for each of the simulated land cover patterns was assessed by means of a distributed routing algorithm. The simulations suggest that further land abandonment in the upslope parts of the catchment will cause a non-linear reduction of average soil erosion rates. The changes, however, have a relatively low impact on the sediment volume entering the lake because of the land unit’s poor connectivity with permanent river channels. The major contributors to the lakes sediment load are the vineyards near the lakeshore. They are likely to be maintained because of their touristic value. A significant reduction of the total sediment input in the lake can be expected only if soil conservation measures in the vineyards near the shorelines are undertaken.     

Histological characteristics and stereological volume assessment of the ovine tonsils

Tonsils form a first line of defence against foreign antigens and therefore play a key role in immunity. Since documented information about ovine tonsils is limited, a study was performed in which the morphological characteristics and the volume of lymphoid tissue present in each ovine tonsil were determined. The tonsils of five adult healthy sheep were examined histologically and the volumes were estimated using the Cavalieri method. The pharyngeal tonsil had a mean volume of 1296.1 ± 205.9 mm³ and was by far the largest ovine tonsil, followed by the paired palatine tonsil with a mean volume of 715.0 ± 110.5 mm³. The tonsil of the soft palate, the paired tubal and paraepiglottic tonsils and the lingual tonsil were much smaller with a mean volume of, respectively, 90.3 ± 24.9 mm³, 80.1 ± 24.3 mm³, 29.7 ± 11.8 mm³ and 10.1 ± 2.8 mm³. The folds and crypts of the pharyngeal and palatine tonsils were covered by a reticular and a non-reticular epithelium. Both tonsils were mainly composed of primary and secondary lymph follicles. The palatine tonsils contained 1–3 crypts with a few secondary infoldings. Lymphoid tissue in the tonsil of the soft palate was located at the nasopharyngeal (dorsal) side of the soft palate. The tubal tonsil was lined with a pseudostratified columnar ciliated epithelium and consisted of scattered lymphoid cells and lymph follicles. The paraepiglottic tonsil consisted of lymph follicles and aggregated lymphoid cells. Its overlying keratinized stratified squamous epithelium was folded and often heavily infiltrated by lymphocytes. The ovine lingual tonsil was not macroscopically visible and did not contain clearly distinguishable lymph follicles. It consisted of aggregations of lymphoid cells that were mainly located within the vallate lingual papillae.     

A global benchmark map of water productivity for rainfed and irrigated wheat

The growing pressure on fresh water resources demands that agriculture becomes more productive with its current water use. Increasing water productivity is an often cited solution, though the current levels of water productivity are not systematically mapped. A global map of water productivity helps to identify where water resources are productively used, and identifies places where improvements are possible. The WATPRO water productivity model for wheat, using remote sensing data products as input, was applied at a global scale with global data sets of the NDVI and surface albedo to benchmark water productivity of wheat for the beginning of this millennium. Time profiles of the NDVI were used to determine the time frame from crop establishment to harvest on a pixel basis, which was considered the modelling period. It was found that water productivity varies from approximately 0.2 to 1.8 kg of harvestable wheat per cubic metre of water consumed. From the 10 largest producers of wheat, France and Germany score the highest country average water productivity of 1.42 and 1.35 kg m⁻³, respectively. The results were compared with modelling information by Liu et al. (2007) who applied the GEPIC model at a global scale to map water productivity, and by Chapagain and Hoekstra (2004) who used FAO statistics to determine water productivity per country. A comparison with Liu et al. showed a good correlation for most countries, but the correlation with the results by Chapagain and Hoekstra was less obvious. The global patterns of the water productivity map were compared with global data sets of precipitation and reference evapotranspiration to determine the impact of climate and of water availability reflected by precipitation. It appears that the highest levels of water productivity are to be expected in temperate climates with high precipitation. Due to its non-linear relationship with precipitation, it is expected that large gains in water productivity can be made with in situ rain water harvesting or supplemental irrigation in dry areas with low seasonal precipitation. A full understanding of the spatial patterns by country or river basin will support decisions on where to invest and what measures to take to make agriculture more water productive.     

Can differences in soil community composition after peat meadow restoration lead to different decomposition and mineralization rates?

Reducing decomposition and mineralization of organic matter by increasing groundwater levels is a common approach to reduce plant nutrient availability in many peat meadow restoration projects. The soil community is the main driver of these processes, but how community composition is affected by peat meadow restoration is largely unknown. Furthermore, it is unclear whether restoration induced changes could lead to altered decomposition and mineralization rates. We determined soil community composition in restored peat meadows with different groundwater levels and soil pH. This composition was subsequently used in food web model calculations of C and N mineralization rates to assess whether differences in soil community composition may have contributed to differences in decomposition and mineralization rates observed between these meadows.Community composition of micro-organisms, Collembola and Enchytraeidae differed considerably between meadows and were correlated with differences in groundwater levels and soil pH. Collembolan and enchytraeid species from wet and neutral environments were more abundant at meadows with higher groundwater levels. Lower fungal to bacterial PLFA ratios and higher numbers of protozoa indicated an increased importance of the bacterial part of the food web at meadows with higher groundwater levels. Food web model calculations suggested that the observed changes in community composition would lead to higher rates of C and N mineralization at meadows with high groundwater levels. Results from modeling were consistent with field measurements of C mineralization, but not with measurements of N mineralization.We conclude that understanding changes in soil community composition in response to specific restoration measures may help us to better understand ecosystem responses to wetland restoration schemes, especially regarding soil biogeochemical processes.     

Reliability of an expert-based runoff and erosion model: Application of STREAM to different environments

During the last decades, the European loess belt has been confronted with a significant increase in environmental problems due to erosion on agricultural land. Spatially distributed runoff and erosion models operating at the catchment scale are therefore needed to evaluate the impact of potential mitigation measures. Expert-based models offer an alternative solution to process-based and empirical models, but their decision rules are only valid for the local conditions for which they have been derived. The STREAM model, which was developed in Normandy (France), has been applied in two Belgian catchments having a similar soil texture, as well as in a catchment of southern France differing by soil, land use and climate characteristics. The performance of hydrological models can be assessed for instance by calculating the Nash–Sutcliffe efficiency criterion (E_NS). When applied to Belgium, the model results are satisfactory to good after an adaptation of the decision rules (0.90 < E_NS < 0.93 for runoff predictions and 0.85 < E_NS < 0.89 for erosion predictions). Given the important environmental differences between Normandy and southern France, the model rules were also adapted for application in the latter environment. Unfortunately, the quality of runoff predictions was insufficient to simulate erosion in southern France. In conclusion, STREAM is a reliable model providing satisfactory runoff and erosion predictions in the regions where hortonian overland flow dominates. Nevertheless, an adaptation of decision rules based on local multi-scale (plot, field, catchment) data is needed, before running the model. STREAM can then serve as a decision support tool to design for instance flood control measures.