Retrospective Predictions of Rice and Other Crop Production in Madagascar Using Soil Moisture and an NDVI-Based Calendar from 2010–2017

Predicting rice productivity for ground data-sparse regions: A transferable framework and its application to North Korea

The use of observation-dependent methods for crop productivity and food security assessment is challenging in data-sparse regions. This study presents a transferable framework and applies it to North Korea (NK) to assess rice productivity based on climate similarity, transferable machine-learning techniques, and extendable multi-source data. We initially divided the primary phenological stages of rice in the study region and extracted dynamic rice distributions based on Moderate Resolution Imaging Spectroradiometer products and phenological observations. We compared the performances of four representative environmentally driven models (Linear Regression, back-propagation Neural Network, Support Vector Machine, and Random Forest) in simulating rice productivity using an extensive dataset that included multi-angle vegetation monitoring, climate variables, and planting distribution information. The framework integrated an optimal environmentally driven model with agricultural management practices for transferability to predict rice productivity in NK over multiple years. Additionally, two crop growth scenarios (whole growth period (WGP) and seeding-heading period (SHP)) were compared to assess pre-harvest forecasting capabilities and identify dominant factors. Finally, independent datasets from the Food and Agriculture Organization, World Food Program, and Global Gridded Crop Models were used to validate the magnitude and spatial distribution of the predicted results. The results showed that phenological identification based on remote sensing can accurately capture rice growth characteristics and map rice distribution. Random Forest outperformed other models in simulating rice productivity variation, with r-squares of 0.87 and 0.83 in the WGP and SHP, respectively. The solar-induced chlorophyll fluorescence, maximum temperature, and evapotranspiration collectively determined approximately 40 % of the variation in yield simulated using Random Forest. Conversely, planting areas contributed over 42 % of the variation in rice production. Compared to Food and Agriculture Organization statistics, the environmentally driven framework explained 78.72 % and 76.89 % of the production variation and 69.42 % and 71.15 % of the yield variation in NK under the WGP and SHP, respectively. Moreover, the environmental management-driven framework captured over 90 % of the yield variation. The predicted spatial pattern of rice productivity exhibited significant concordance with the World Food Program and Global Gridded Crop Model reports. In summary, the proposed transferable framework for crop productivity assessment contributes to early warnings of production reduction and has the potential for scalability across various crops and data-sparse regions.

Prevalence of micronutrient deficiencies across diverse environments in rural Madagascar

It is estimated that billions of people around the world are affected by micronutrient deficiencies. Madagascar is considered to be particularly nutritionally vulnerable, with nearly half of the population stunted, and parts of the country facing emergency, near famine-like conditions (IPC4). Although Madagascar is generally considered among the most undernourished of countries, empirical data in the form of biological samples to validate these claims are extremely limited. Our research drew data from three studies conducted between 2013-2020 and provided comprehensive biomarker profile information for 4,710 individuals from 30 communities in five different ecological regions during at least one time-point. Estimated prevalences of nutrient deficiencies and inflammation across various regions of rural Madagascar were of concern for both sexes and across all ages, with 66.5% of the population estimated to be deficient in zinc, 15.6% depleted in vitamin B12 (3.6% deficient), 11.6% deficient in retinol, and lower levels of iron deficiency (as indicated by 11.7% deficient in ferritin and 2.3% deficient assessed by soluble transferrin receptors). Beyond nutrient status biomarkers, nearly one quarter of the population (24.0%) exhibited chronic inflammation based on high values of α-1-acid glycoprotein, and 12.3% exhibited acute inflammation based on high values of C-reactive protein. There is an 8-fold difference between the lowest and highest regional observed prevalence of vitamin B12 deficiency, a 10-fold difference in vitamin A deficiency (based on retinol), and a 2-fold difference in acute inflammation (CRP) and deficiencies of zinc and iron (based on ferritin), highlighting strong geographical variations in micronutrient deficiencies across Madagascar.

Reproductive ecology of the black rat (Rattus rattus) in Madagascar: the influence of density-dependent and -independent effects

The black rat (Rattus rattus) poses a severe threat to food security and public health in Madagascar, where it is a major cause of pre- and post-harvest crop losses and an important reservoir for many zoonotic diseases, including plague. Elsewhere, ecologically based rodent management (EBRM) strategies have been developed using ecological information to inform decisions on where and when to target control. EBRM could deliver improved health and well-being outcomes in Madagascar if adapted to the local ecological context. Using data collected from removal studies, we explored spatio-temporal patterns in the breeding activity of the black rat (R. rattus) in domestic and agricultural habitats across Madagascar and investigated to what extent these trends are influenced by rainfall and rat density. We identified clear spatio-temporal variation in the seasonality of R. rattus reproduction. Reproduction was highly seasonal both inside and outside of houses, but seasonal trends varied between these two habitats. Seasonal trends were explained, in part, by variation in rainfall; however, the effect of rainfall on reproductive rates did itself vary by season and habitat type. A decline in breeding intensity with increasing rat density was recorded outside of houses. This has important implications for control, as populations may compensate for removal through increased reproduction. We recommend that sustained control initiated before the main breeding season, combined with improved hygiene and adequate rodent-proofing in homes and grain stores, could curtail population growth and reduce pre- and post-harvest losses provided that these measures overcome the compensatory response of rodent populations.