• Energy Research

The annual income of small-scale farmers in the Jordan Valley, West Bank, Palestine remains persistently low compared to other sectors. The objective of this study was therefore to explore some of the main barriers to reducing poverty and increasing farm income in the region. A “Rural Household Multi-Indicator Survey” (RHoMIS) was conducted with 248 farmers in the three governorates of the Jordan Valley. The results of the survey were verified in a series of stakeholder interviews and participatory workshops where farmers and stakeholders provided detailed insight with regard to the relationships between land tenure status, farm management, and poverty. The analyses of the data revealed that differences in cropping system were significantly associated with land tenure status, such that rented land displayed a greater proportion of open field cropping, while owned land and sharecropping tenure status displayed greater proportions of production systems that require greater initial investment (i.e., perennial and greenhouse). Moreover, as confirmed by a structural equation model and the interviews and workshops these associations led to significant differences in farm income and progress out of poverty index scores. However, while sharecropping farms enjoyed the benefits of being able to invest in longer-term, more profitable farming strategies, questions were raised regarding the sustainability of these farms as well as the vulnerability of the farming households that manage the land. We concluded that small-scale agricultural development in the Jordan Valley relies on farming households achieving more secure land tenure and that rural development agencies should prioritise farming households that rent land and practice open field cropping systems within their projects and programmes.

Earthworm distribution in global soils Earthworms are key components of soil ecological communities, performing vital functions in decomposition and nutrient cycling through ecosystems. Using data from more than 7000 sites, Phillips et al. developed global maps of the distribution of earthworm diversity, abundance, and biomass (see the Perspective by Fierer). The patterns differ from those typically found in aboveground taxa; there are peaks of diversity and abundance in the mid-latitude regions and peaks of biomass in the tropics. Climate variables strongly influence these patterns, and changes are likely to have cascading effects on other soil organisms and wider ecosystem functions. Science , this issue p. 480 ; see also p. 425

Abstract While livestock play a vital role in supporting livelihoods of many people in Africa, they are also a major source of greenhouse gas emissions (GHG). An increasing population coupled with growing demand for livestock products means that there is an urgent need to implement cost-effective Climate Smart Agriculture (CSA) practices that can reduce emissions from livestock systems in Africa. The objective of this research was therefore to assess the effect of implementing CSA practices on milk yields and GHG emission intensities (EI) from three dairy production system types (no-graze, semi-intensive, and extensive) in Kenya. The research developed marginal abatement cost curves (MACC) to assess of the economic costs and trade-offs for the use of CSA practices in each of the dairy production systems. The research was conducted on 666 dairy farms in four counties in Kenya. Data from a farm survey and participatory workshops were used to categorise farms into production systems, estimate carbon emissions using the Agrecalc (Agricultural Resource Efficiency Calculator) tool, assess the effects of the use of CSA practices on milk yields and GHG EI, gain information on the costs of implementing CSA practices, and develop the MACCs. Our results showed that common CSA practices enhance milk yields and reduce GHG EI in dairy production systems. However, these benefits were not equally experienced by all production systems, with only clear statistical effects observed in extensive production systems. In these systems, farms using five or more CSA practices saw a 44% increase in milk production and a 25% reduction in GHG EI compared to farms not using any CSA practices. The MACCs revealed that the costs associated with the implementation of the CSA practices were higher for extensive production systems, but increased milk production meant that the net increases in value production were higher for extensive production systems. This indicates that upfront investment costs are important barriers to the use of CSA practices. Our results provide strong evidence that rural development projects are likely to be more successful when targeting farm types and using a “toolbox” approach. Moreover, the results demonstrate the importance for the establishment of policy and financing mechanisms to facilitate financing and decreasing the perceived risks involved in investing in CSA practices.

Data collated from data provided by original data collectors or from data provided within published articles. The MetaData.csv provides information on each of the original data sources, including bibliographic information about the original article and information on how many sites were sampled. The SiteData.csv gives site-level variables, such as geographic coordinates, the environmental parameters as well as site-level community metrics (species richness, total abundance and total biomass). The SppOccData.csv provides the observation level data - the occurrence, abundance and/or biomass of individual species/morpho-species/life-stage at a particular site. Not every data source contained such observation level data. Metadata information about the variables in each file are provided in the files MetaData_info.csv, SiteData_info.csv and SppOccData_info.csv, respectively. All files provided use the character encoding UTF-8, and missing values are represented by "NA". This dataset contains key characteristics about the data described in the Data Descriptor Global data on earthworm abundance, biomass, diversity and corresponding environmental properties. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format ---------------------------------------------------------------- Please remove before publishing. manuscript number:SDATA-20-00920 edit url: https://scientificdata.metadata-creator.com/?id=ag5maWdtZXRhLTIzMDExMXIXCxIKU3VibWlzc2lvbhiAgICgzKucCgw Related publications: https://doi.org/10.1126/science.aax4851 Please remove before publishing. ----------------------------------------------------------------