Changing Food Consumption Patterns and Land Requirements for Food in the Six Geopolitical Zones in Nigeria

Research on food consumption in Nigeria has mainly focused on food intake, household diversity, and purchasing power. We investigated a knowledge gap for food consumed by households and the land requirements for food resulting from household consumption patterns. The food consumed and the household size determine the land requirement for food. Therefore, a quantity-based analysis and a land demand methodology were applied to derive household food quantity and land requirements for food respectively. The results show that a greater percentage of household income is spent on cereals and starchy roots as the main source of calories and that cowpea is a secondary food option for households. In addition, households are changing their dietary intake from rice to maize and rice to cassava and yams as a cheaper alternative and experts’ measurements of food security at the household level indicates that households in our study are moderately food insecure. Other findings showthat the country’s specific and per capita land requirements for food have gradually increased between 2000 and 2018. Across the six geopolitical zones, Northern regions with higher populations have high land requirements for food, especially for rice and maize (cereals), while Southern regions have high land requirements for cassava and yams (starchy roots) due to their respective consumption and household sizes. In addition, from our study, the land requirements for food show the actual cropland area of South South fed 5000 households. Consequently, a scenario analysis shows that the land requirements for food in our study exceeds the entire geographical area of Nigeria. Therefore, continued population growth without improved living standards and adequate food production output per hectare will further exacerbate food insecurity and land shortage in Nigeria.

Research and technology development needs for scaling up conservation agriculture systems, practices and innovations in Africa.

Although the net agricultural production across all regions of Africa has experienced a significant increase, African agriculture has performed below its potential over recent decades. Many aspects have been fronted to curb this situation, including sustainable intensification of farming systems and value-chain transformation through Conservation Agriculture (CA) across Africa. Based on the latest update, Africa has about 2.7 million ha under CA, an increase of 458% over the past 10 years with 2008/09 as baseline. However, this constitutes a mere 1.5% of the global area under CA, and less than 1.4% of the total cropland area in Africa. A combination of modern techniques and the optimization of agroecological processes in CA systems and practices requires that agricultural research plays a bigger role in its evolution and focus in the different regions of Africa. This targeted research should crucially contribute towards making agriculture in Africa more productive, competitive, sustainable and inclusive in terms of its functionality towards the farmer, society and nature. Scientific solutions for agricultural transformation need to be pursued without losing sight of the potentials and fragility of Africa's agricultural environments, the complexity of its agricultural production systems and the continent's rich biodiversity. The agricultural research and development agenda in Africa must build on the rich traditional farming culture, knowledge and practices, supported by coherent longer-vision for investments in science for agricultural development. Most of these investments are expected to come from national public and private sources, with governments also expected to invest in generation of 'public goods' such as the national or global environmental benefits typical of CA, and to also catalyse innovation and support market growth. The absolute imperative is that farmers must shift from outdated conventional tillage-based methods to modern, well-tested and knowledge-based methods of land use. Making this transition will be difficult without the creation of an enabling environment. This chapter discusses the various roles and advances required in CA-based research that will support the adoption of CA systems by millions of smallholder farmers in Africa with a view to enhancing sustainable and effective agricultural development and economic growth.

An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East

The primary driver of the land carbon sink is gross primary productivity (GPP), the gross absorption of carbon dioxide (CO2) by plant photosynthesis, which currently accounts for about one-quarter of anthropogenic CO2 emissions per year. This study aimed to detect the variability of carbon productivity using the Standardized Evapotranspiration Deficit Index (SEDI). Sixteen countries in the Middle East (ME) were selected to investigate drought. To this end, the yearly GPP dataset for the study area, spanning the 35 years (1982–2017) was used. Additionally, the Global Land Evaporation Amsterdam Model (GLEAM, version 3.3a), which estimates the various components of terrestrial evapotranspiration (annual actual and potential evaporation), was used for the same period. The main findings indicated that productivity in croplands and grasslands was more sensitive to the SEDI in Syria, Iraq, and Turkey by 34, 30.5, and 29.6% of cropland area respectively, and 25 31.5 and 30.5% of grass land area. A significant positive correlation against the long-term data of the SEDI was recorded. Notably, the GPP recorded a decline of >60% during the 2008 extreme drought in the north of Iraq and the northeast of Syria, which concentrated within the agrarian ecosystem and reached a total vegetation deficit with 100% negative anomalies. The reductions of the annual GPP and anomalies from 2009 to 2012 might have resulted from the decrease in the annual SEDI at the peak 2008 extreme drought event. Ultimately, this led to a long delay in restoring the ecosystem in terms of its vegetation cover. Thus, the proposed study reported that the SEDI is more capable of capturing the GPP variability and closely linked to drought than commonly used indices. Therefore, understanding the response of ecosystem productivity to drought can facilitate the simulation of ecosystem changes under climate change projections.

Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century

Spatiotemporally consistent data on global cropland extent is essential for tracking progress towards sustainable food production. In the present study, we present an analysis of global cropland area change for the first two decades of the twenty-first century derived from satellite data time-series. We estimate that, in 2019, the cropland area was 1,244 Mha with a corresponding total annual net primary production (NPP) of 5.5 Pg C year−1. From 2003 to 2019, cropland area increased by 9% and cropland NPP by 25%, primarily due to agricultural expansion in Africa and South America. Global cropland expansion accelerated over the past two decades, with a near doubling of the annual expansion rate, most notably in Africa. Half of the new cropland area (49%) replaced natural vegetation and tree cover, indicating a conflict with the sustainability goal of protecting terrestrial ecosystems. From 2003 to 2019, global per-capita cropland area decreased by 10% due to population growth. However, the per-capita annual cropland NPP increased by 3.5% as a result of intensified agricultural land use. The presented global, high-resolution, cropland map time-series supports monitoring of natural land appropriation at the local, national and international levels.

A Quantitative Review of Irrigation Development in the Yazoo–Mississippi Delta from 1991 to 2020

The Yazoo–Mississippi Delta is one of the regions within the Lower Mississippi River Basin where substantial irrigation development and consequent groundwater depletion have occurred over the past three decades. To describe this irrigation development, a study was conducted to analyze existing geospatial datasets and to synthesize the results with those of past government surveys. The effort produced a quantitative review characterizing three aspects of irrigation development from 1991 to 2020. First, the expansion of irrigated area was tracked in terms of absolute area and in terms of fraction relative to total land or cropland area. Second, trends in irrigated land cover were traced in terms of irrigated crop mix, irrigated fractions of main crops, and comparisons with non-irrigated land. Third, changes in irrigation systems were examined in terms of water sources, energy sources, and application methods. Original findings of this study for the end of 2020 included moderate positive spatial autocorrelation in the density of irrigated areas; a higher irrigated crop preference for soybean and rice over cotton and corn in highly hydric soils; and 91% and 3% of permitted areas studied being respectively under groundwater withdrawal permits exclusively and under surface water diversion permits exclusively. By compiling such information, this paper can serve as a convenient reference on the recent history and status of irrigation development in the Yazoo–Mississippi Delta.

Statistical Analysis of Cropland Area in Canada using the Autoregressive Hidden Markov Time Series Model

Crop production and other agricultural activities are as old as human existence and becoming increasingly intensive, spatially concentrated and specialized. However, diversification in economic activities and recent development in technology in many developed countries have led to significant increase in land use. Thereby, resulting to huge reduction in the total land area available for agricultural activities especially crop production. This study examines the distribution of cropland area in Canada in relation to three contributing factors using the Autoregressive Hidden Markov time series Model (AR-HMM) due to the limitations of the ordinary Autoregressive model in the accuracy of its parameter estimation. Expectation-Maximization (E-M) algorithm method was used to estimate the model parameters so as to investigate the effects of the factors on cropland distribution using secondary data from Food and Agriculture Organisation (FAO). Jarque-Bera and D'Agostino normality tests were carried out to examine the normality of the series. Augmented Dickey Fuller (ADF) and the KPSS tests established the stationarity of the series. The ideal stationary probability distribution for transition was at AR (3)-HMM with the minimum Bayesian Information Criterion (BIC) of 16270.62. The prior transition states for the HMM are 0.462, 0.260 and 0.278 respectively. In conclusion, this study suggests that deforestation and other land use activities as a result of commercial and technological advancements should be minimized to ensure more available cropland area.

A 1 km global cropland dataset from 10 000 BCE to 2100 CE

Cropland greatly impacts food security, energy supply, biodiversity, biogeochemical cycling, and climate change. Accurately and systematically understanding the effects of agricultural activities requires cropland spatial information with high resolution and a long time span. In this study, the first 1 km resolution global cropland proportion dataset for 10 000 BCE–2100 CE was produced. With the cropland map initialized in 2010 CE, we first harmonized the cropland demands extracted from the History Database of the Global Environment 3.2 (HYDE 3.2) and the Land-Use Harmonization 2 (LUH2) datasets and then spatially allocated the demands based on the combination of cropland suitability, kernel density, and other constraints. According to our maps, cropland originated from several independent centers and gradually spread to other regions, influenced by some important historical events. The spatial patterns of future cropland change differ in various scenarios due to the different socioeconomic pathways and mitigation levels. The global cropland area generally shows an increasing trend over the past years, from 0×106 km2 in 10 000 BCE to 2.8×106 km2 in 1500 CE, 6.2×106 km2 in 1850 CE, and 16.4×106 km2 in 2010 CE. It then follows diverse trajectories under future scenarios, with the growth rate ranging from 16.4 % to 82.4 % between 2010 CE and 2100 CE. There are large area disparities among different geographical regions. The mapping result coincides well with widely used datasets at present in both distribution pattern and total amount. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The spatiotemporally continuous and conceptually consistent global cropland dataset serves as a more comprehensive alternative for long-term earth system simulations and other precise analyses. The flexible and efficient harmonization and downscaling framework can be applied to specific regions or extended to other land use and cover types through the adjustable parameters and open model structure. The 1 km global cropland maps are available at https://doi.org/10.5281/zenodo.5105689 (Cao et al., 2021a).

Dynamic Amazonia: The EU–Mercosur Trade Agreement and Deforestation

The trade agreement between the European Union and the Mercosur countries will increase deforestation in the Mercosur countries and Brazil, in particular, if ratified by member countries. We use a computable general equilibrium model to analyze how trade, land use, and agricultural production will change as a result of the agreement. We then use a statistical model to spatially allocate the predicted deforestation within the Brazilian Amazon. The models estimate that the agreement will cause additional deforestation in Brazil ranging from 56 to 173 thousand ha to accommodate increases in cropland area, depending on the level of governance, use of double-cropping techniques, and trade elasticity parameters. Most additional deforestation in Amazonia would be clustered near current deforestation hotspot areas. Some hotspots threaten the integrity of Indigenous lands and conservation units. Although a low deforestation scenario with gains in welfare is theoretically possible when high governance and multiple-cropping systems are in place, political challenges remain and cast doubt on Brazil’s ability to rein on illegal deforestation.