Crop yields fail to rise in smallholder farming systems in sub-Saharan Africa.

Drawing on a harmonized longitudinal dataset covering more than 55,000 smallholder farms in six African countries, we analyze changes in crop productivity from 2008 to 2019. Because smallholder farmers represent a significant fraction of the world's poorest people, agricultural productivity in this context matters for poverty reduction and for the broader achievement of the UN Sustainable Development Goals. Our analysis measures productivity trends for nationally representative samples of smallholder crop farmers, using detailed data on agricultural inputs and outputs which we integrate with detailed data on local weather and environmental conditions. In spite of government commitments and international efforts to strengthen African agriculture, we find no evidence that smallholder crop productivity improved over this 12-y period. Our preferred statistical specification of total factor productivity (TFP) suggests an overall decline in productivity of -3.5% per year. Various other models we test also find declining productivity in the overall sample, and none of them finds productivity growth. However, the different countries in our sample experienced varying trends, with some instances of growth in some regions. The results suggest that major challenges remain for agricultural development in sub-Saharan Africa. They complement previous analyses that relied primarily on aggregate national statistics to measure agricultural productivity, rather than detailed microdata.

Fertilizer management for global ammonia emission reduction.

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1-5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr-1, lower than previous estimates that did not fully consider fertilizer management practices6-9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr-1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases.

Evaluating the impacts of land use change on ecosystem service values under multiple scenarios in the Hunshandake region of China.

Changes in land use in an agro-pastoral region affect the delivery of ecosystem services. The trajectory of future land use change and its impacts on human society are not yet well understood, which poses a challenge to efforts to balance the socioeconomic development with the supply of ecosystem services. Taking the Hunshandake region for a case study, we developed four land use scenarios, and projected the future land use patterns under those scenarios using the GeoSOS-FLUS model. We then assessed the ecosystem service values (ESV) using a modification of the equivalent-coefficient method that accounts for differences in net primary production, and explored the impacts of land use change on ESV from 2018 to 2030. We found important land use conversions among the forest, grassland, and cropland uses, mainly in the southern part of our study area. The presence of ESV change hotspots and cold spots suggested that the changes were clustered in the southeastern part. The ESV gain and loss matrix showed that the land use changes under a scenario that prioritized ecosystem services and the comprehensive development scenario increased ESV from 2018 to 2030 with the conversion of cropland to forest. Our results provide important knowledge to inform land use decisions and facilitate sustainable development in the Hunshandake region.

Land Cover Change and Its Impact in Crop Yield: A Case Study from Western Nepal.

This study was conducted in Tanahun district of Gandaki Province, Nepal, to analyze the land cover change over two decades, the migration effect in land cover, and the impact caused in crop production by Rhesus macaque. Landsat TM/ETM+ for land use of 2000 and 2010 extracted by ICIMOD and Landsat 8 OLI/TIRS satellite images for land cover 2019 were downloaded from the USGS website. A purposive sample for household survey was carried out based on crops damaged by the monkey. Two hundred and fifty households were taken as samples. The Landsat images were analyzed by ArcGIS, and the social data were analyzed using SPSS and MS Excel. Land cover change data revealed increment of forest cover from 36.57% to 40.91% and drastic decrease in agriculture crops from 57.52% to 43.78% in the period of 20 years. The accuracy of the data showed overall classification accuracy of 86.11%, 81.08%, and 75% with overall kappa statistics 0.83, 0.77, and 0.74, respectively. The migration effect in the land cover was related to remittance and migrated members and found a significant positive relationship. Analyzing the trend of production with an increase in the forest cover, 21% decrease in paddy, 5% decrease in maize, and 26% decrease in millet were found as compared to the production in 2000. The econometric model concluded that the quantity of crop damage was negatively significant in relation to distance from forest and distance from water body while positively significant to distance from settlements and distance from owner's home. The quantity of crop damage was estimated 113.89 kg per household, and the cost was 78.82 USD. This study recommends active forest management; regular thinning, and weeding. Remittance generated should be invested in the agriculture field by the households. Damage relief should be made available for the damage cost by Rhesus macaque.

Drought Analysis Using Standardized Evapotranspiration and Aridity Index at Bilate Watershed: Sub-Basins of Ethiopian Rift Valley.

In Ethiopia, more prevalent drought happenings have been documented in the past century. The problem has gradually expanded from the north to the rest parts with deepened intensity. The study aimed to examine the magnitudes of spatiotemporal patterns of drought at the Bilate watershed from 1981 to 2016. Monthly rainfall and temperature data were used for the analysis. The Standardized Evapotranspiration Indexes (SPEI) at SPEI-03 and SPEI-12 timescales were applied to evaluate the drought patterns. Among different drought indices, the SPEI is the most valuable and preferred Index for drought studies. The SPEI method considers the role of temperature than other indices to compare drought in time and space. The Mann-Kendall test was used for trend analysis. Accordingly, the result revealed that 1988-2016 were years of continuous drought events in both timescales with (SPEI = -2.5 to -1.2) drought value. Drought severity and frequency were highly detected at Wulberag areas (SPEI: -2.5). Durame, Angacha, and Alaba experienced increasing drought trends (Z = -1.96-1.6) and Welayita Sodo is Z = -0.07-0.03. Bilate-Tena and Hossana area of the watershed were less affected by drought than other areas. Spatially, the drought occurrences were observed in all areas of the watershed with varying magnitude. In the SPEI-12 timescale, more frequent drought occurrences were observed than SPEI-03. It was found that severe drought was observed in 1987, 1993/94, 2000-2005, and 2010. Moreover, the watershed experienced an Aridity Index (AI) of 0.43 (43%) and was subjected to potential high evapotranspiration (PET). The highest PET was observed at Bilate-Tena, Angacha, Hosanna, Wulberag, Alaba, Welayita Sodo, and Durame (151.6, 119.6, 119.3, 140.8, 142, 127.5, and 125.7 mm/year, respectively. Hence, the finding of this study could initiate a further inquiry on drought risk management, early warning responses, and local scale planning.

Effect of Shade on Agro-Morphological Parameters and Weed Flora of Saffron (Crocus sativus L.) Cultivation in the Semiarid Zone of Eastern Morocco.

Saffron (Crocus sativus) has been an important medicinal plant since ancient times. This study aimed to seek the optimal light intensity for saffron growth by quantifying the effects of different shade levels on yield, vegetative growth, and weed development in the eastern region of Morocco. The plants were grown for 24 months in full sun (control) and 30%, 50%, and 70% shade. Overall, the results showed that shade positively affected the yield and vegetative growth parameters of saffron plants, with the highest yield (0.61 g/m2) and number of leaves (105 leaves/tuft) recorded when the plants were exposed to light shade (30%). The color of the leaves under the 70% shade levels was dark green. The results from the underground part showed that shade is positively correlated with the weight and diameter of daughter corms where the 70% shade recorded the highest values of weight (65 g) and percentage of large diameter corms (39%). As for weed density, this parameter was significantly affected by shade. The lowest weed density was recorded for the 70% shade treatment. In conclusion, 30% shade is suggested as optimal light irradiation for saffron cultivation.

Mapping spatial distribution and geographic shifts of East African highland banana (Musa spp.) in Uganda.

East African highland banana (Musa acuminata genome group AAA-EA; hereafter referred to as banana) is critical for Uganda's food supply, hence our aim to map current distribution and to understand changes in banana production areas over the past five decades. We collected banana presence/absence data through an online survey based on high-resolution satellite images and coupled this data with independent covariates as inputs for ensemble machine learning prediction of current banana distribution. We assessed geographic shifts of production areas using spatially explicit differences between the 1958 and 2016 banana distribution maps. The biophysical factors associated with banana spatial distribution and geographic shift were determined using a logistic regression model and classification and regression tree, respectively. Ensemble models were superior (AUC = 0.895; 0.907) compared to their constituent algorithms trained with 12 and 17 covariates, respectively: random forests (AUC = 0.883; 0.901), gradient boosting machines (AUC = 0.878; 0.903), and neural networks (AUC = 0.870; 0.890). The logistic regression model (AUC = 0.879) performance was similar to that for the ensemble model and its constituent algorithms. In 2016, banana cultivation was concentrated in the western (44%) and central (36%) regions, while only a small proportion was in the eastern (18%) and northern (2%) regions. About 60% of increased cultivation since 1958 was in the western region; 50% of decreased cultivation in the eastern region; and 44% of continued cultivation in the central region. Soil organic carbon, soil pH, annual precipitation, slope gradient, bulk density and blue reflectance were associated with increased banana cultivation while precipitation seasonality and mean annual temperature were associated with decreased banana cultivation over the past 50 years. The maps of spatial distribution and geographic shift of banana can support targeting of context-specific intensification options and policy advocacy to avert agriculture driven environmental degradation.

Short-term effects of cadmium on leaf growth and nutrient transport in rice plants.

Consumption of rice grains contaminated with high concentrations of cadmium (Cd) can cause serious long-term health problems. Moreover, even low Cd concentrations present in the soil can result in the abatement of plant performance, leading to lower grain yield. Studies examining the molecular basis of plant defense against Cd-induced oxidative stress could pave the way in creating superior rice varieties that display an optimal antioxidative defense system to cope with Cd toxicity. In this study, we showed that after one day of Cd exposure, hydroponically grown rice plants exhibited adverse shoot biomass and leaf growth effects. Cadmium accumulates especially in the roots and the leaf meristematic region, leading to a disturbance of manganese homeostasis in both the roots and leaves. The leaf growth zone showed an increased amount of lipid peroxidation indicating that Cd exposure disturbed the oxidative balance. We propose that an increased expression of genes related to the glutathione metabolism such as glutathione synthetase 2, glutathione reductase and phytochelatin synthase 2, rather than genes encoding for antioxidant enzymes, is important in combating early Cd toxicity within the leaves of rice plants. Furthermore, the upregulation of two RESPIRATORY BURST OXIDASE HOMOLOG genes together with a Cd concentration-dependent increase of abscisic acid might cause stomatal closure or cell wall modification, potentially leading to the observed leaf growth reduction. Whereas abscisic acid was also elevated at long term exposure, a decrease of the growth hormone auxin might further contribute to growth inhibition and concomitantly, an increase in salicylic acid might stimulate the activity of antioxidative enzymes after a longer period of Cd exposure. In conclusion, a clear interplay between phytohormones and the oxidative challenge affect plant growth and acclimation during exposure to Cd stress.

Steady agronomic and genetic interventions are essential for sustaining productivity in intensive rice cropping.

Intensive systems with two or three rice (Oryza sativa L.) crops per year account for about 50% of the harvested area for irrigated rice in Asia. Any reduction in productivity or sustainability of these systems has serious implications for global food security. Rice yield trends in the world's longest-running long-term continuous cropping experiment (LTCCE) were evaluated to investigate consequences of intensive cropping and to draw lessons for sustaining production in Asia. Annual production was sustained at a steady level over the 50-y period in the LTCCE through continuous adjustment of management practices and regular cultivar replacement. Within each of the three annual cropping seasons (dry, early wet, and late wet), yield decline was observed during the first phase, from 1968 to 1990. Agronomic improvements in 1991 to 1995 helped to reverse this yield decline, but yield increases did not continue thereafter from 1996 to 2017. Regular genetic and agronomic improvements were sufficient to maintain yields at steady levels in dry and early wet seasons despite a reduction in the yield potential due to changing climate. Yield declines resumed in the late wet season. Slower growth in genetic gain after the first 20 y was associated with slower breeding cycle advancement as indicated by pedigree depth. Our findings demonstrate that through adjustment of management practices and regular cultivar replacement, it is possible to sustain a high level of annual production in irrigated systems under a changing climate. However, the system was unable to achieve further increases in yield required to keep pace with the growing global rice demand.

Personalized digital extension services and agricultural performance: Evidence from smallholder farmers in India.

Productivity growth in smallholder agriculture is an important driver of rural economic development and poverty reduction. However, smallholder farmers often have limited access to information, which can be a serious constraint for increasing productivity. One potential mechanism to reduce information constraints is the public agricultural extension service, but its effectiveness has often been low in the past. Digital technologies could enhance the effectiveness of extension by reducing outreach costs and helping to better tailor the information to farmers' individual needs and conditions. Using primary data from India, this study analyses the association between digital extension services and smallholder agricultural performance. The digital extension services that some of the farmers use provide personalized information on the types of crops to grow, the types and quantities of inputs to use, and other methods of cultivation. Problems of selection bias in the impact evaluation are reduced through propensity score matching (PSM) combined with estimates of farmers' willingness to pay for digital extension. Results show that use of personalized digital extension services is positively and significantly associated with input intensity, production diversity, crop productivity, and crop income.

Conservation outreach that acknowledges human contributions to climate change does not inhibit action by U.S. farmers: Evidence from a large randomized controlled trial embedded in a federal program on soil health.

Technologies and practices that reduce the environmental impacts of US agriculture are well documented. Less is known about how best to encourage their adoption. We report on the results of a large randomized controlled trial conducted with nearly 10,000 agricultural producers in the United States. The experiment was embedded in US Department of Agriculture outreach efforts to improve soil conservation practices. USDA varied the content of mailings to test two sets of competing theories about outreach to agricultural producers. Contrary to conventional wisdom, we find no evidence that acknowledging the link between climate change and agricultural production discourages conservation action. Furthermore, we find that producers who were invited to a webinar were less likely to take any action to learn more about conservation practices than producers who were not told about the webinar, a result that runs counter to the popular wisdom that offering more options leads to more action.

Modelling smallholder farmers' preferences for soil fertility management technologies in Benin: A stated preference approach.

The decline of soil fertility is a major constraint which results in lower levels of crop productivity, agricultural development and food security in Sub-Saharan Africa. This study is the first to perform a focalized investigation on the most interesting technological profiles to offer to each category of producers in Benin agricultural development hubs (ADHs) using the stated preference method, more precisely, the improved choice experiment method. The investigation focused on 1047 sampled plots from 962 randomly selected producers in villages of the Smallholder Agricultural Productivity Enhancement Program in Sub-Saharan Africa of the ADHs. An analysis of the experimental choice data with the endogenous attribute attendance and the latent class models was carried out to account for the attribute non-attendance phenomenon and the heterogeneity of the producers' preferences. However, three classes of producer with different socio-economic, demographic, and soil physicochemical characteristics were identified. Thus, the heterogeneity of preferences was correlated with the attributes linked to the cost, sustainability, and frequency of plot maintenance. All producers, regardless of the ADHs, had a strong attachment to accessibility of technologies with short time restoration of soil fertility, and the ability to obtain additional benefits. These latest attributes, added to that relating to cost, tended to have a low probability of rejection in the decision-making process. These results have implications for local decision-makers facing the complex problem of resolving land degradation and local economic development challenges. The generalizability of these findings provides useful insight and direction for future studies in Sub-Saharan Africa.

Influence of rice varieties, organic manure and water management on greenhouse gas emissions from paddy rice soils.

The study is focused on impact of manure application, rice varieties and water management on greenhouse gas (GHG) emissions from paddy rice soil in pot experiment. The objectives of this study were a) to assess the effect of different types of manure amendments and rice varieties on greenhouse gas emissions and b) to determine the optimum manure application rate to increase rice yield while mitigating GHG emissions under alternate wetting and drying irrigation in paddy rice production. The first pot experiment was conducted at the Department of Agronomy, Yezin Agricultural University, Myanmar, in the wet season from June to October 2016. Two different organic manures (compost and cow dung) and control (no manure), and two rice varieties; Manawthukha (135 days) and IR-50 (115 days), were tested. The results showed that cumulative CH4 emission from Manawthukha (1.084 g CH4 kg-1 soil) was significantly higher than that from IR-50 (0.683 g CH4 kg-1 soil) (P<0.0046) with yield increase (P<0.0164) because of the longer growth duration of the former. In contrast, higher cumulative nitrous oxide emissions were found for IR-50 (2.644 mg N2O kg-1 soil) than for Manawthukha (2.585 mg N2O kg-1 soil). However, IR-50 showed less global warming potential (GWP) than Manawthukha (P<0.0050). Although not significant, the numerically lowest CH4 and N2O emissions were observed in the cow dung manure treatment (0.808 g CH4 kg-1 soil, 2.135 mg N2O kg-1 soil) compared to those of the control and compost. To determine the effect of water management and organic manures on greenhouse gas emissions, second pot experiments were conducted in Madaya township during the dry and wet seasons from February to October 2017. Two water management practices {continuous flooding (CF) and alternate wetting and drying (AWD)} and four cow dung manure rates {(1) 0 (2) 2.5 t ha-1 (3) 5 t ha-1 (4) 7.5 t ha-1} were tested. The different cow dung manure rates did not significantly affect grain yield or greenhouse gas emissions in this experiment. Across the manure treatments, AWD irrigation significantly reduced CH4 emissions by 70% during the dry season and 66% during the wet season. Although a relative increase in N2O emissions under AWD was observed in both rice seasons, the global warming potential was significantly reduced in AWD compared to CF in both seasons (P<0.0002, P<0.0000) according to reduced emission in CH4. Therefore, AWD is the effective mitigation practice for reducing GWP without compromising rice yield while manure amendment had no significant effect on GHG emission from paddy rice field. Besides, AWD saved water about 10% in dry season and 19% in wet season.

Diversity increases yield but reduces harvest index in crop mixtures.

Resource allocation to reproduction is a critical trait for plant fitness1,2. This trait, called harvest index in the agricultural context3-5, determines how plant biomass is converted to seed yield and consequently financial revenue from numerous major staple crops. While plant diversity has been demonstrated to increase plant biomass6-8, plant diversity effects on seed yield of crops are ambiguous9 and dependent on the production syndrome10. This discrepancy might be explained through changes in the proportion of resources invested in reproduction in response to changes in plant diversity, namely through changes in species interactions and microenvironmental conditions11-14. Here, we show that increasing crop plant diversity from monocultures over two- to four-species mixtures increased annual primary productivity, resulting in overall higher plant biomass and, to a lesser extent, higher seed yield in mixtures compared with monocultures. The difference between the two responses to diversity was due to a reduced harvest index of the eight tested crop species in mixtures, possibly because their common cultivars have been bred for maximum performance in monoculture. While crop diversification provides a sustainable measure of agricultural intensification15, the use of currently available cultivars may compromise larger gains in seed yield. We therefore advocate regional breeding programmes for crop varieties to be used in mixtures that should exploit complementarity16 among crop species.

Temporal and spatial variations of soil C, N contents and C:N stoichiometry in the major grain-producing region of the North China Plain.

Soil C, N contents and C:N stoichiometry are important indicators of soil quality, the variation characteristics of which have great significance for soil carbon-nitrogen cycle and sustainable utilization. Based on 597 observations along with soil profiles of 0-20cm depth in the 1980s and the 2010s, the temporal and spatial variations of soil C, N contents and C:N stoichiometry in the major grain-producing region of the North China Plain were illustrated. Results showed that there were significant changes in soil C, N contents over time, with increasing rates of 60.47% and 50%, respectively. The changes of C, N contents resulting in a general improvement of C:N stoichiometry. There was a significant decline in nugget effects of soil C, N contents from the 1980s to 2010s, the spatial autocorrelation of soil nutrients showed an increasing trend, and the effect of random variation was reduced. C:N stoichiometry was higher in Huixian City and Weihui City, and lower in Yanjin County, an apparent decline was observed in the spatial difference of soil C:N stoichiometry from the 1980s to 2010s. Soil C, N contents and C:N stoichiometry differed among soil types, agricultural land-use types, and topography in space. The temperature, precipitation, and fertilization structure were considered as the main factors that induce the temporal variations. These findings indicated that the soil nutrient elements in the farmland ecosystems changed in varying degrees in both time and space scales, and the variation was influenced by soil types, land-use types, topography, meteorological factors, and fertilization structure.

Vulnerability of maize, millet, and rice yields to growing season precipitation and socio-economic proxies in Cameroon.

In sub-Saharan Africa growing season precipitation is affected by climate change. Due to this, in Cameroon, it is uncertain how some crops are vulnerable to growing season precipitation. Here, an assessment of the vulnerability of maize, millet, and rice to growing season precipitation is carried out at a national scale and validated at four sub-national scales/sites. The data collected were historical yield, precipitation, and adaptive capacity data for the period 1961-2019 for the national scale analysis and 1991-2016 for the sub-national scale analysis. The crop yield data were collected for maize, millet, and rice from FAOSTAT and the global yield gap atlas to assess the sensitivity both nationally and sub-nationally. Historical data on mean crop growing season and mean annul precipitation were collected from a collaborative database of UNDP/Oxford University and the climate portal of the World Bank to assess the exposure both nationally and sub-nationally. To assess adaptive capacity, literacy, and poverty rate proxies for both the national and regional scales were collected from KNOEMA and the African Development Bank. These data were analyzed using a vulnerability index that is based on sensitivity, exposure, and adaptive capacity. The national scale results show that millet has the lowest vulnerability index while rice has the highest. An inverse relationship between vulnerability and adaptive capacity is observed. Rice has the lowest adaptive capacity and the highest vulnerability index. Sub-nationally, this work has shown that northern maize is the most vulnerable crop followed by western highland rice. This work underscores the fact that at different scales, crops are differentially vulnerable due to variations in precipitation, temperature, soils, access to farm inputs, exposure to crop pest and variations in literacy and poverty rates. Therefore, caution should be taken when transitioning from one scale to another to avoid generalization. Despite these differences, in the sub-national scale, western highland rice is observed as the second most vulnerable crop, an observation similar to the national scale observation.

Welfare impacts of smallholder farmers' participation in multiple output markets: Empirical evidence from Tanzania.

A relatively large body of literature has documented the welfare effects of smallholder farmers' participation in single-commodity output markets. However, limited empirical evidence is available when smallholder farmers participate in multiple-commodities output markets. We tried to fill this gap in the literature by estimating the impacts of smallholder farmers' contemporaneous participation in both maize and legume markets vis-à-vis in only maize or legume markets using household-level data from Tanzania. Applying a multinomial endogenous switching regression model that allows controlling for observed and unobserved heterogeneity associated with market participation in single-commodity and multiple-commodity markets, results showed that smallholder farmers' participation in both single-and multiple-commodity markets was positively and significantly associated with household income and food security. Moreover, the greatest benefits were obtained when farmers participated in multiple-commodity markets, suggesting the importance of policies promoting diversification in crop income sources to increase welfare and food security. Our findings also signal the complementary-rather than substitute-nature of accessing multiple-commodity markets for enhancing household livelihoods under a specialization strategy. Finally, important policy implications are suggested, from promoting and supporting public infrastructure investments to expanding road networks to reduce transportation costs, especially in remote communities, to enhance smallholder farmer access to profitable maize and legume markets in Tanzania.

Regional differences in farmers' preferences for a native bee conservation policy: The case of farming communities in Northern and Eastern Thailand.

Evidence points to past bee-mediated crop pollination deficits in Chanthaburi province, Eastern Thailand. Conversely, no such evidence has yet been reported for Chiang Mai province (Northern Thailand), suggesting that wild pollination is delivered there above the requirements of local orchards. Discrete choice experiments (DCE) were conducted to elicit the preferences of pollinator-dependent orchard farmers with regard to three pollinator conservation measures and their possible effects on of native bee populations in each region. We fitted random parameter logit (RPL) models on the resulting data to capture preference heterogeneity and to obtain willingness to pay (WTP) point estimates. To test our results' robustness, we also inspected for scale heterogeneity by fitting generalized mixed logit (GMXL) models on the pooled and individual datasets. This yielded WTP space estimates (i.e., directly from WTP distributions) and made possible the comparison of farmers' preferences for a native bee conservation policy in both regions. The results hint at significant WTP differences for some of the conservation policy attributes between both provinces. Furthermore, unobserved contributions to choice seem to have been more random in Chiang Mai. Our analyses also suggest that farmers who engage in bee-related activities are WTP more for a conservation policy that includes bee husbandry.

Crop origins explain variation in global agricultural relevance.

Human food production is dominated globally by a small number of crops. Why certain crops have attained high agricultural relevance while others have remained minor might partially stem from their different origins. Here, we analyse a dataset of 866 crops to show that seed crops and species originating from seasonally dry environments tend to have the greatest agricultural relevance, while phylogenetic affinities play a minor role. These patterns are nuanced by root and leaf crops and herbaceous fruit crops having older origins in the aseasonal tropics. Interestingly, after accounting for these effects, we find that older crops are more likely to be globally important and are cultivated over larger geographical areas than crops of recent origin. Historical processes have therefore left a pervasive global legacy on the food we eat today.