Pixelating crop production: Consequences of methodological choices

Variable climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum) in Asia: results from a continental-scale modeling approach

Crop fungal diseases constitute a major cause of yield loss. The development of crop disease monitoring and forecasting tools is an important effort to aid farmers in adapting to climate variability and change. Recognizing weather as a main driver of fungal disease outbreaks, this work assesses the climate suitability for wheat blast (Magnaporthe oryzae pathotype Triticum, MoT) development in Asian wheat-producing countries. MOT was reported for the first time in Bangladesh in 2016 and could spread to other countries, provided that environmental conditions are suitable to spore development, distribution, and infection. With results from a generic infection model driven by air temperature and humidity, and motivated by the necessity to assess the potential distribution of MoT based on the response to weather drivers only, we quantify potential MOT infection events across Asia for the period 1980-2019. The results show a potential higher incidence of MOT in Bangladesh, Myanmar, and some areas of India, where the number of potential infection (NPI) events averaged up to 15 during wheat heading. Interannual trends show an increase in NPI over those three countries, which in turns show their higher interannual variability. Cold/dry conditions in countries such as Afghanistan and Pakistan appear to render them unlikely candidates for MOT establishment. The relationship between seasonal climate anomalies and NPI suggests a greater association with relative humidity than with temperature. These results could help to focus future efforts to develop management strategies where weather conditions are conducive for the establishment of MOT.

Improving Spatial Disaggregation of Crop Yield by Incorporating Machine Learning with Multisource Data: A Case Study of Chinese Maize Yield

Spatially explicit crop yield datasets with continuous long-term series are essential for understanding the spatiotemporal variation of crop yield and the impact of climate change on it. There are several spatial disaggregation methods to generate gridded yield maps, but these either use an oversimplified approach with only a couple of ancillary data or an overly complex approach with limited flexibility and scalability. This study developed a spatial disaggregation method using improved spatial weights generated from machine learning. When applied to Chinese maize yield, extreme gradient boosting (XGB) derived the best prediction results, with a cross-validation coefficient of determination (R2) of 0.81 at the municipal level. The disaggregated yield at 1 km grids could explain 54% of the variance of the county-level statistical yield, which is superior to the existing gridded maize yield dataset in China. At the site level, the disaggregated yields also showed much better agreement with observations than the existing gridded maize yield dataset. This lightweight method is promising for generating spatially explicit crop yield datasets with finer resolution and higher accuracy, and for providing necessary information for maize production risk assessment in China under climate change.

Village-level climate and weather variability, mediated by village-level crop yield, is associated with linear growth in children in Uganda

INTRODUCTION

To investigate total annual precipitation, precipitation anomaly and aridity index in relation to linear growth in children under 5 in Uganda and quantify the mediating role of crop yield.

METHODS

We analysed data of 5219 children under 5 years of age who participated in the 2016 Uganda Demographic and Health Survey. Annual crop yield in kilograms per hectare for 42 crops at a 0.1° (~10 km at the equator) spatial resolution square grid was obtained from the International Food Policy Research Institute. Normalised rainfall anomaly and total precipitation were derived from the African Rainfall Estimation Algorithm Version 2 product. Linear regression models were used to associate total annual precipitation and anomalies with height-for-age z-scores and to explore the mediating role of crop yield qualitatively. The intervening effects were quantitatively estimated by causal mediation models.

RESULTS

Twenty-nine per cent of children were stunted (95% CI 28% to 31%). After adjusting for major covariates, higher total annual precipitation was significantly associated with increasing height-for-age z-scores. At the mean, an increase of 1 standard deviation in local annual rainfall was associated with a 0.07-point higher z-score. Aridity index and precipitation anomaly were not associated with height-for-age z scores in altitude-adjusted models. Crop yields of nuts, seeds, cereals and pulses were significant mediating factors. For instance, 38% of the association between total annual precipitation with height-for-age z-scores can be attributed to the yield of sesame seeds.

CONCLUSIONS

Higher total annual precipitation at the village-level was significantly associated with higher height-for-age z-scores among children in Uganda. This association can be partially explained by higher crop yield, especially from seeds and nuts. This study suggests that more attention should be paid to villages with lower annual rainfall amounts to improve water availability for agriculture.

Farming by soil in Europe: status and outlook of cropping systems under different pedoclimatic conditions

Background

Despite of the importance of soils in agronomy, to date no comprehensive assessment of cropping in Europe has been performed from the viewpoint of the soil variability and its relationship to cropping patterns. In order to fill this knowledge gap, we studied the cropping patterns in different soils of European climate zones with regards to the shares of their crop types in a comparative manner. The study highlights the main features of farming by soil in Europe. Farming by soil in this context means the consideration of soil characteristics when selecting crop types and cropping patterns.

Methods

We first assessed the dissimilarity between the cropping compositions of different pedoclimatic zones in Europe. Next, we assessed the differences of crop distribution in the climate zones by soil types and main crop types by analyzing the degree of association of crops to soil types. A detailed country scale assessment was performed using crops-specific soil productivity maps and land use survey data from Hungary.

Results

Results suggest that, in general, farmers consciously take pedoclimatic condition of farming into account when selecting their cropping patterns. In other words, farming by soil is a common practice in the different climatic regions of Europe. However, we have strong reasons to believe that soil suitability-based cropping is not practiced to its full potential over the continent. For example, the findings of our European assessment suggest that production areas of legumes are not always optimized for the local pedoclimatic conditions in some zones. These findings also underline that economic drivers are decisive, when farmers adopt their cropping (eg. oil crops on Albeluvsiols in Europe). Win-win situations of economic considerations and soil suitability based management are observed in all pedoclimatic zones of Europe. The country analysis shows that cropping is progressively practiced on more suitable areas, depending also the crop tolerance to variable pedoclimatic conditions In conclusion, we can assume that pedoclimatic conditions of cropping are respected in most of Europe and farmers crops according to edaphic conditions whenever economic considerations do not override the ecological concerns of farming.

Assessment of acetochlor use areas in the sahel region of Western Africa using geospatial methods

The goal of this study was to determine the co-occurrence between acetochlor use on crops and potentially vulnerable soils in the Permanent Interstate Committee for Drought Control in the Sahel region of Western Africa. Acetochlor, a pre-emergence herbicide, is used primarily on row crops and has the potential to reach groundwater or surface water following a rain event shortly after application. Off-field transport is often determined by soil properties; therefore, soils within potential use areas were assessed and mapped to establish areas with soils vulnerable to leaching and/or runoff. Corn and cotton production areas were used as surrogate crops for high potential use areas of acetochlor within areas identified using GlobCover land use data and the Spatial Production Allocation Model agricultural statistics data. The geospatial analysis identified approximately 462 million ha of potentially vulnerable soils in the Sahel region of which 65.7 million ha are within agricultural areas. An adjustment for corn and cotton production areas showed that 2.2 million ha or 3.3% of agricultural fields could have potential restrictions for acetochlor use. Approximately 0.159 million ha of soils or 0.24% of agricultural fields are in the presence of shallow groundwater, defined by depth < 9 m. In addition, 0.0128 million ha or 0.02% were determined to be adjacent to surface water bodies. To understand the uncertainty associated with the use of specific land cover datasets, an overlay assessment was conducted using alternative data sources. Overlap between selected land cover datasets in the Sahel region varies and ranges from 24.7% to 75.5% based on a merged 2009 GlobCover and CCI LC datasets. In comparison with the merged 2005 and 2009 GlobCover dataset, the cropland overlaps range from 38.9% to 85.0%. This demonstrates that the choice of land cover dataset can have a significant impact on a spatial assessment. Results from this assessment demonstrate that only a small fraction of vulnerable agricultural soils across the region may be a risk for contamination by acetochlor of groundwater or surface resources, based on product label recommendations. Given the availability of spatial data in a region, the methods contained herein may additionally be used in other localities to provide similar information that can be helpful for water quality management.