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Remotely sensed spectral indicators of bird taxonomic, functional and phylogenetic diversity across Afrotropical urban and non-urban habitats
No full textUrban areas are quickly expanding around the world, promoting deep changes in biodiversity. However, certain biogeographic realms, like the Afrotropics, are clearly understudied despite urbanization overlapping with their biodiversity hotspots. A commonly highlighted reason for the lack of information from the Afrotropics has been the logistical problem associated with data collection in the field. Recent advances in satellite remote sensing imagery offer an excellent opportunity to revert this situation, enhancing the understanding of urban impacts on biodiversity. The Normalized Difference Vegetation Index (NDVI) is the most commonly used remotely sensed spectral index (hereafter: indicator) despite several studies showing its limitations and advocating for the use of alternative indicators. Thus, this study identifies the best indicators of bird taxonomic, functional, and phylogenetic diversity in Afrotropical urban and non-urban areas. To do so, we sampled birds at 400 points equally distributed across eight Nigerian areas, two vegetation zones (rainforest vs savannah), and two habitats (urban vs non-urban), and extracted 29 indicators (mean and SD) at 50-m radius of each point (exact area of bird censuses). Random Forest Regressions and Generalized Linear Mixed Effect Models were used to identify the topmost ranked indicator of each avian diversity component, and its variation between urban and non-urban areas. The Modified Chlorophyll Absorption Ratio Index (MCARI) was the best indicator of taxonomic and phylogenetic diversity, while the Normalized Difference Water Index II (NDWI2) and Soil Adjusted Total Vegetation Index (SATVI) got the most support for functional diversity and phylogenetic divergence, respectively. In most cases, NDVI ranks very low (occupying the 25th percentile), not supporting its use for monitoring avian diversity in the Afrotropics. MCARI and NDWI2 showed different associations with taxonomic and functional diversity depending on the habitat, highlighting the need for considering urban areas differently while using these indicators. Our study provides useful tools to remotely monitor Afrotropical avian diversity, particularly in expansive, inaccessible or insecure areas, which could also be more cost-effective
Falling transport costs and agricultural development: implications of von Thuenen's model of the dual economy
No full textRainfall forecasts, learning subsidies and conservation agriculture adoption: Experimental evidence from Zambia
No full textAdapting smallholder rainfed farming systems to climate change requires adoption of technologies that build resilience to climate shocks. One such technology is conservation agriculture, yet its adoption by smallholders in Southern Africa is not widespread. We use incentivized economic field experiments in Zambia to test, ex-ante, whether providing rainfall forecasts and a time-bound learning subsidy can help increase the adoption of conservation agriculture. We found that providing rainfall forecasts predicting low rainfall significantly increased the probability of adopting conservation agriculture by 8 percentage points, while offering a subsidy increased the chances of adoption by 11 percentage points. Bundling rainfall forecasts and subsidies did not significantly influence adoption, perhaps because these were not complementary. Having experienced normal rainfall in the previous experiment round (cropping season) was associated with 6 percentage points higher odds of adopting conservation agriculture, while past exposure to low rainfall significantly reduced the probability of adoption by 6 percentage points. These results suggest that farmers do not expect two subsequent seasons to be the same given the increase in rainfall variability in the region. Other important drivers of adoption are hosting demonstration plots and education level of the participant. These findings provide evidence that providing rainfall forecasts and time-bound learning subsidies may be effective ways to enhance the adoption of conservation agriculture in Zambia and imply a need to reframe conservation agriculture as means to address low and erratic rainfall. Future research can evaluate the persistence of such effects using randomized controlled trials
Stability of grain zinc concentrations across lowland rice environments favors zinc biofortification breeding
No full textIntroduction One-third of the human population consumes insufficient zinc (Zn) to sustain a healthy life. Zn deficiency can be relieved by increasing the Zn concentration ([Zn]) in staple food crops through biofortification breeding. Rice is a poor source of Zn, and in countries predominantly relying on rice without sufficient dietary diversification, such as Madagascar, Zn biofortification is a priority. Methods Multi-environmental trials were performed in Madagascar over two years, 2019 and 2020, to screen a total of 28 genotypes including local and imported germplasm. The trials were conducted in the highlands of Ankazomiriotra, Anjiro, and Behenji and in Morovoay, a location representative of the coastal ecosystem. Contributions of genotype (G), environment (E), and G by E interactions (GEIs) were investigated. Result The grain [Zn] of local Malagasy rice varieties was similar to the internationally established grain [Zn] baseline of 18–20 μg/g for brown rice. While several imported breeding lines reached 50% of our breeding target set at +12 μg/g, only few met farmers’ appreciation criteria. Levels of grain [Zn] were stable across E. The G effects accounted for a main fraction of the variation, 76% to 83% of the variation for year 1 and year 2 trials, respectively, while GEI effects were comparatively small, contributing 23% to 9%. This contrasted with dominant E and GEI effects for grain yield. Our results indicate that local varieties tested contained insufficient Zn to alleviate Zn malnutrition, and developing new Zn-biofortified varieties should therefore be a priority. GGE analysis did not distinguish mega-environments for grain [Zn], whereas at least three mega-environments existed for grain yield, differentiated by the presence of limiting environmental conditions and responsiveness to improved soil fertility. Discussion Our main conclusion reveals that grain [Zn] seems to be under strong genetic control in the agro-climatic conditions of Madagascar. We could identify several interesting genotypes as potential donors for the breeding program, among those BF156, with a relatively stable grain [Zn] (AMMI stability value (ASV) = 0.89) reaching our target (>26 μg/g). While selection for grain yield, general adaptation, and farmers’ appreciation would have to rely on multi-environment testing, selection for grain [Zn] could be centralized in earlier generations
RIICE development in Cote d’Ivoire : AfricaRice report of 2024. Transforming Agrifood Systems in West and Central Africa Initiative (TAFS-WCA)
No full textCôte d'Ivoire has significant potential for rice production, yet the country
remains heavily reliant on imports due to low yields and limited adoption of
improved technologies. Climate change further exacerbates these challenges,
affecting rice productivity and food security. The Remote Sensing-based
Information and Insurance for Crops in Emerging Economies (RIICE) decision
support system was introduced to provide reliable, real-time data on rice
cultivation, yield forecasts, and climate-related risks. This report details activities
conducted by AfricaRice in 2024 related to the adaptation and implementation of
the RIICE tool in Côte d'Ivoire through field experiments, georeferencing of rice
fields, and the collection of leaf area index (LAI) data as well as feedback from
stakeholders to ensure the tool is co-designed, responds to the local needs and that
challenges related to infrastructure requirements and capacity building are
addressed in the road for institutionalization. The findings highlight the potential of
RIICE to enhance rice sector planning, improve resilience among smallholder
farmers, and support policy decisions for achieving rice self-sufficiency