Soil scientists at AfrII host the CI President to Vital Signs data collection work in Nakasongola district
Soil Scientists at the Africa Innovations Institute (AfrII) are conducting countrywide data collection on soils and ecosystems under the Vital Signs Project (VS). Vital Signs generates near-real time data for better decisions in support of sustainable agriculture, environment conservation and climate change resilience. Vital Signs is a global project led by Conservation International (CI). The team recently hosted the CI President, Dr. Jennifer Morris on the Project work in Nakasongola district. She was accompanied by Dr. Alex, the Manager, Data Science-CI, and Dr. Alice Ruhweza, the Executive Director-Vital Signs Monitoring System. The team met with senior officials of the Nakasongola district Local Government during the data collection exercise for farmers and managers in the district.
The lead scientist of this work at AfrII, Dr. Julius Okwadi, the Vital Signs Uganda Country Director said the data collected is intended to guide better decision making by farmers and policy makers to design methods to improve the agricultural production system in Uganda.
“We have completed collection of biophysical data on 464 E-Plots from 6 landscapes, countrywide and also collected socio economic data to understand the health, nutrition status and income of the 180 households sampled” Okwadi said.
Okwadi added that Nakasongola has greatly faced climate change challenges, which is why it is one of the districts the project is focusing on to endeavor to address these.
Mr. Stephen Kwesiga (gesturing), a biophysical technician leads the AfrII team in taking soil samples in Nakasongola
Meanwhile, the AfrII Chairman, Professor George William Otim- Nape, said the work is going to be of great value to improve agriculture in Nakasongola but also Uganda at large. “Once we get the information required, we will use it to inform decision makers on best bet climate change adaptation practices to conserve nature and improve human wellbeing,” Otim added.
AfrII Chairman Prof Otim-Nape and CI President, Dr. Jennifer Morris observe a citrus plant in Nakasongola, affected by lack of some soil nutrients.
Dr. Jenifer Morris, the President of Conservation International says they want to understand the challenges of climate change and how other factors related to soil and health are impacting community livelihood around the country. “We are trying to get what data services are needed, identify the data gaps, and what kind of tools we can bring to help farmers in better decision making,” Moris said.
Dr. Gerald Kittaka, the production Officer Nakasongola District noted that drought has become a recurring hazard in Nakasongola coupled with pests and diseases which affect crops and animals leading to economic and material loss to the district.
An official at the district offices speaks to the visitors on the climate change challenges affecting Nakasongola district
Nakasongola is a district located in the cattle corridor of Uganda. It is highly vulnerable to Climate change hazards especially drought and rising temperatures. The district is affected by severe droughts that occur every 2 to 3 years compared to 5 to 10 years (20-40 years ago). In 2016, last year, 60-70% crop failure was registered (maize, groundnuts, cassava, citrus and coffee) causing heavy production losses resulting in famine and poverty.
In Feb 2017, this year, 115,433 people (59.8%) were food insecure and 28,384 (11.7%) in a crisis state and required emergency food aid.
Are benefits from agricultural intensification related to household income, level of education, and gender? – results from 758 households in Uganda, Rwanda, Tanzania and Ghana
By Robert Shaffer, Vital Signs Fellows &Scientists_DSSG 2017 ,Africa Innovations Institute,Tanzania Forest Conservation Group,Wildlife Conservation Society Rwanda,The Council for Scientific and Industrial Research Ghana
This analysis is a result of the collaboration between the eScience Insitute Data Science for Social Good Program and Vital Signs. Learn more about this program here.
In developing countries, agricultural intensification (defined as increased input per unit of land) is a key phenomenon of interest. These inputs may include land, fertilizers, pesticides and labor including use of agricultural machinery. Increasing agricultural intensification can contribute to aggregate-level increases in food availability and economic performance. However, these benefits may not be evenly distributed, largely based on unequal access to key inputs, either across landscapes or countries or according to some demographic feature of interest.
For the purposes of this study, we focus on investigating gender- and income-based equity outcomes as they relate to availability and usage of agricultural inputs. Previous studies examining the relationship between gender and input usage have returned mixed results; [1], for example, found organic fertilizer usage is substantially higher in male-headed households than female-headed households. By contrast, usage of improved fallows is largely unrelated to gender of household head. Here, we extend this investigation across an array of agricultural intensification indicators, and examine how usage of these inputs varies by gender and country in the Vital Signs dataset. We conclude by examining the relationship between input usage and landscape-level income and education equity outcomes.
High Resolution Soil Nutrient Maps Using Machine Learning
As part of its mission, Vital Signs collects soil samples from points scattered across the countries that it works in – filling critical gaps on soil nutrients, agricultural suitability, and land degradation. These soil samples are then analyzed in the World Agroforestry Center laboratory in Nairobi to yield data on soil properties including particle size, pH, nutrient availability and nutrient content. To date, Vital Signs has collected 5,969 soil samples and has had 3,714 analyzed by the lab. Here is the breakdown by country:
These soil samples fill critical data gaps for soils scientists and researchers worldwide. Recently, the lab-analyzed samples were used by the International Soil Reference and Information Center (ISRIC) in combination with soil samples from other initiatives like AfSIS and EthioSIS, and One Acre Fund to generate maps of soil nutrient content across the continent. These maps were created using ensemble machine learning techniques like random forests and gradient boosting using the soil samples from Vital Signs and other projects as training data. Geographic data on known soil nutrient co-variates like land cover, precipitation, lithology, and vegetation was used to predict nutrient availability at fine spatial scales across sub-Saharan Africa for organic Carbon, total (organic) Nitrogen, total Phosphorus, and extractable Phosphorous, Potassium, Calcium, Magnesium, Sulfur, Sodium, Iron, Manganese, Zinc, Copper, Aluminum and Boron. Cross validation found that all of the nutrients were predicted significantly except for Sulfur, Phosphorus and Boron.
Read full post on Vital Signs website: http://vitalsigns.org/soil-nutrient-maps
Are the effects of extension services on crop productivity moderated by farmer’s education attainment? Results from 25 Landscapes in Uganda, Rwanda, Tanzania and Ghana
This analysis is a result of the collaboration between the eScience Insitute Data Science for Social Good Program and Vital Signs. Learn more about this program here.
Existing studies of farmer field schools (FFS) have found that these programs exhibit a sizable positive effect on per-acre crop productivity value among households with lower educational attainment, with negligible effects on higher-education households[1] [2]. In these analyses, we examined whether a similar effect can be observed when examining a broader set of extension services.Agricultural households in Vital Signs landscapes were therefore asked whether they received extension services in the past 12 months. The categories of extension services used in this study were Agricultural Production, Agro-processing, Marketing, and Livestock Production.
In the analyses,we examined the effects of extension services on crop productivity and if these services were moderated by farmers’ educational attainment. To measure receipt of extension services, we counted the total number of instances in which a given household received advice on any of the topics measured in the Vital Signs dataset. For example, if a household received advice from two sources on Agricultural Production and one source on Agro-processing, we counted that household as having received three extension instances.
For education, previous studies [2] have measured education using educational attainment of the head of the household. However, based on our team’s experience providing and examining extension services in the region, we argue that the maximum individual-level educational attainment represents a better measure. Older household members often receive fewer opportunities to study than their younger counterparts, who may be able to “translate” advice.
Otherwise, to maintain consistency with existing work we attempted to maintain the same set of independent variables as those used in  [2]. In particular, we controlled for country, total area farmed, household size, age of household head, gender of household head, and median household-level field distance to road and market. We also included variables corresponding to field ownership and shared field usage, discretized into “All Owned”/“Some Owned”/“None Owned” and “All Shared”/“Some Shared”/“None Shared”, respectively.
Do female-headed households have less access to agricultural capital and services? results from vital signs data from 26 African landscapes
By Matthew Cooper, Felly Tusiime, Madeleine Nyiratuza, Kame Westerman, Tabby Njung’e, Alice Ruhweza, Peter Alele and Alex Zvoleff
In the struggle to produce more food sustainably, create economic growth, and improve health outcomes across the developing world, women play a pivotal role. Women often assume different agricultural roles than men: they grow more garden crops while men grow more commodity crops and field grains[1]. Women are also generally charged with childcare and eldercare, and pay more attention to household nutrition and child health. At the same time, women also face significant burdens in patriarchal societies where they have less access to land and income. Due to a range of legal and cultural constraints across Africa in land inheritance, ownership, access, control, and use, women make up only about 15 percent of agricultural land holders[2],[3]. However some countries are making more progress than others in the push for equality: in Rwanda, for example, women and men have equal rights to men with regard to land ownership, inheritance, access, control and use.
Vital Signs analyzed data it collected in Uganda, Rwanda, Tanzania and Ghana to identify the key differences between female headed households and male headed households. The data Vital Signs has collected supports these narratives. We used data from 820 households – 140 of which were headed by women – to analyze characteristics that were noticeably different between households headed by men and households headed by women. Some of the starkest differences are in women’s access to agricultural capital. Women own and farm smaller areas, and they use fewer pesticides, herbicides, or purchased seeds (see below). This jibes with global data, which shows that female farmers only receive about 5% of agricultural extension services, while only 15% of the world’s extension agents are women[4].
visit the Vital Signs website to read the full post.
For the live post on CI Connect: Click here to view.
Vital Signs Uganda team benefit from capacity building Science Course
AfrII Vital Signs members participating in a discussion about research in the Process of Science short course class. This short course is conducted by Professor Mark P. Simmons, a visiting Fulbright Scholar from Colorado State University.
The short course contributes to AfrII’s Capacity Building Programme in which our scientists and, or staff are to benefit in various areas including skills development in research among others.
The topics to be discussed in this class include;
1. Ten simple rules for aspiring scientists in a low-income country
2. How simple ideas lead to scientific discoveries
3. Limitations of statistical analyses and problems with reproducibility
4. A guide to academia: how people in science see each other
5. Building and maintaining a scientific reputation
6. Why knowledge for the pure sake of knowing is good enough to justify scientific research
7. Interception of politics and science
8.Ten simple rules for choosing between industry and academia
