skip to main content


Title: Uncertainties in estimating global potential yields and their impacts for long-term modeling
Abstract

Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.

 
more » « less
Award ID(s):
1739823
NSF-PAR ID:
10372990
Author(s) / Creator(s):
; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Food Security
Volume:
14
Issue:
5
ISSN:
1876-4517
Page Range / eLocation ID:
p. 1177-1190
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The direct impacts of climate change on crop yields and human health are individually well-studied, but the interaction between the two have received little attention. Here we analyze the consequences of global warming for agricultural workers and the crops they cultivate using a global economic model (GTAP) with explicit treatment of the physiological impacts of heat stress on humans’ ability to work. Based on two metrics of heat stress and two labor functions, combined with a meta-analysis of crop yields, we provide an analysis of climate, impacts both on agricultural labor force, as well as on staple crop yields, thereby accounting for the interacting effect of climate change on both land and labor. Here we analyze the two sets of impacts on staple crops, while also expanding the labor impacts to highlight the potential importance on non-staple crops. We find, worldwide, labor and yield impacts within staple grains are equally important at +3C warming, relative to the 1986–2005 baseline. Furthermore, the widely overlooked labor impacts are dominant in two of the most vulnerable regions: sub-Saharan Africa and Southeast Asia. In those regions, heat stress with 3C global warming could reduce labor capacity in agriculture by 30%–50%, increasing food prices and requiring much higher levels of employment in the farm sector. The global welfare loss at this level of warming could reach $136 billion, with crop prices rising by 5%, relative to baseline.

     
    more » « less
  2. Abstract

    Meeting ambitious climate targets will require deploying the full suite of mitigation options, including those that indirectly reduce greenhouse-gas (GHG) emissions. Healthy diets have sustainability co-benefits by directly reducing livestock emissions as well as indirectly reducing land use emissions. Increased crop productivity could indirectly avoid emissions by reducing cropland area. However, there is disagreement on the sustainability of proposed healthy U.S. diets and a lack of clarity on how long-term sustainability benefits may change in response to shifts in the livestock sector. Here, we explore the GHG emissions impacts of seven scenarios that vary U.S. crop yields and healthier diets in the U.S. and overseas. We also examine how impacts vary across assumptions of future ruminant livestock productivity and ruminant stocking density in the U.S. We employ two complementary land use models—the US FABLE Calculator, an agricultural and forestry sector accounting model with high agricultural commodity representation, and GLOBIOM, a spatially explicit partial equilibrium optimization model for global land use systems. Results suggest that healthier U.S. diets that follow the Dietary Guidelines for Americans reduce agricultural and land use greenhouse gas emissions by 25–57% (approx 120–310 MtCO2e/y) and pastureland area by 28–38%. The potential emissions and land sparing benefits of U.S. agricultural productivity growth are modest within the U.S. due to the increasing comparative advantage of U.S. crops. Our findings suggest that healthy U.S. diets can significantly contribute toward meeting U.S. long-term climate goals for the land use sectors.

     
    more » « less
  3. Abstract

    The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present‐day agricultural sustainability across environmental, economic, and social dimensions with a process‐based integrated assessment model, in order to allow forward‐looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present‐day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant‐based (“flexitarian”) diets, and economy‐wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter‐regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post‐processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios.

     
    more » « less
  4. Abstract

    Food security and the agricultural economy are both dependent on the temporal stability of crop yields. To this end, increasing crop diversity has been suggested as a means to stabilize agricultural yields amidst an ongoing decrease in cropping system diversity across the world. Although diversity confers stability in many natural ecosystems, in agricultural systems the relationship between crop diversity and yield stability is not yet well resolved across spatial scales. Here, we leveraged crop area, production, and price data from 1981 to 2020 to assess the relationship between crop diversity and the stability of both economic and caloric yields at the state level within the USA. We found that, after controlling for climatic instability and differences in irrigated area, crop diversity was positively associated with economic yield stability but negatively associated with caloric yield stability. Further, we found that crops with a propensity for increasing economic yield stability but reducing caloric yield stability were often found in the most diverse states. We propose that price responses to changes in production for high-value crops underly the positive relationship between diversity and economic yield stability. In contrast, spatial concentration of calorie-dense crops in low-diversity states contributes to the negative relationship between diversity and caloric yield stability. Our results suggest that the relationship between crop diversity and yield stability is not universal, but instead dependent on the spatial scale in question and the stability metric of interest.

     
    more » « less
  5. Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980–2012, including the Millennium Drought in Australia (2001–2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25–45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops. 
    more » « less