Integrated Assessment of Crop–Livestock Production Systems Beyond Biophysical Methods

Masikati, Patricia; Kee-Tui, Sabine Homann; Descheemaeker, Katrien; Sisito, Gevious; Senda, Trinity S.; Crespo, Olivier; Nhamo, Nhamo

doi:10.1016/b978-0-12-810521-4.00013-x

Cited by 8 publications

(6 citation statements)

References 33 publications

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“…For instance, if biotic stress in the analysis is linked to certain weather patterns and stochastic probabilities of occurrence, the crop growth model output needs to be combined with disease progress curves and damage functions to adequately account for biotic stress. While many of these bio-economic models focus on crop production, a number also take into account crop-livestock interactions [195,197,294,355].…”

Section: Bio-economic Modellingmentioning

confidence: 99%

Role of Modelling in International Crop Research: Overview and Some Case Studies

et al. 2018

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Crop modelling has the potential to contribute to global food and nutrition security. This paper briefly examines the history of crop modelling by international crop research centres of the CGIAR (formerly Consultative Group on International Agricultural Research but now known simply as CGIAR), whose primary focus is on less developed countries. Basic principles of crop modelling building up to a Genotype × Environment × Management × Socioeconomic (G × E × M × S) paradigm, are explained. Modelling has contributed to better understanding of crop performance and yield gaps, better prediction of pest and insect outbreaks, and improving the efficiency of crop management including irrigation systems and optimization of planting dates. New developments include, for example, use of remote sensed data and mobile phone technology linked to crop management decision support models, data sharing in the new era of big data, and the use of genomic selection and crop simulation models linked to environmental data to help make crop breeding decisions. Socio-economic applications include foresight analysis of agricultural systems under global change scenarios, and the consequences of potential food system shocks are also described. These approaches are discussed in this paper which also calls for closer collaboration among disciplines in order to better serve the crop research and development communities by providing model based recommendations ranging from policy development at the level of governmental agencies to direct crop management support for resource poor farmers.

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Section: Bio-economic Modellingmentioning

confidence: 99%

Role of Modelling in International Crop Research: Overview and Some Case Studies

et al. 2018

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“…This includes evidence of improved outcomes, based on which policy and decision makers can design technology and institutional development. Testing the options in real time is neither possible nor ethical, resulting in the need for appropriate ex ante impact assessments, simulation methods, and tools (e.g., Masikati et al, 2017;.…”

Section: Introduction: Regional Agriculture and Climate Change Challe...mentioning

confidence: 99%

Handbook of Climate Change and Agroecosystems

Rosenzweig

Mutter

Contreras

2021

Handbook of Climate Change and Agroecosystems

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The challenges and opportunities that nations and regions of the world face with regard to food security today and in the future can benefit greatly from scientific and technological innovations that continue to be the hallmark of human ingenuity in this era of increasing global competition for limited resources on planet Earth. Securing food, fibre, feed, and energy for the current inhabitants and future generations is one of the grand challenges facing humans in this century, and perhaps the next one, especially in light of rapid changes in the Earth's planetary system. This handbook is dedicated to the research findings by a team of several hundred distinguished scientists, policy experts, and decision makers from around the world who worked together, through the AgMIP and by way of their national programs and contributions, to assess the current state of scientific understanding and knowledge of the food systems in order to address this global grand challenge.There are several unique features in this handbook and it is the content that sets it apart from other science-based assessments and reports. First, it is solution-oriented in that the findings and recommendations are intended to be actionable by stakeholders and decision makers who were an integral part of the assessment process. This participatory approach enabled the findings and outcomes to be accessible and useful for adaptive measures towards a more sustainable food system for present and future generations. Second, the regional and sectoral focus of the assessment, based on newly developed Representative Agricultural Pathways (RAPs), potential pathways for development that account for specific and unique soil-crop-climate conditions regionally and globally. Third, the multidisciplinary team of scientists and decision makers that AgMIP recruited and engaged in the assessment process facilitated sharing of the best available information and knowledge to accomplish the stated goals of this project.Fourth, these efforts helped in advancing the state of scientific understanding, knowledge, and sharing of and access to attendant capabilities, such as observations, models, and analysis tools, by all those involved in the project without any restriction. This was further enhanced through sharing of the results openly at scientific and technical stakeholder workshops and events, and by including them in vii viii Foreword major international science-based assessments, such as the Global Environmental Outlook-6 (GEO6) and the Intergovernmental Panel on Climate Change (IPCC) assessment reports.The first chapter in this handbook sets the stage by identifying and describing the goals and objectives of this major and seminal scientific effort, and the outcomes of the entire process. It identifies the key ingredients for the success of such efforts (e.g., participatory and stakeholder engagement) and the lessons learned. The subsequent chapters describe in greater depth and detail the soil-crop-climate-specific analyses conducted for specific regions across the g...

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“…Significant research has been conducted in terms of assessing the vulnerability and adaptation of the smallholder farmers to climate change [15,16]. There is however still much work to be done to improve the understanding of the implications that climate change may have in rangelands and how livestock farmers need to position themselves to hedge against the risks and shocks.…”

Section: Introductionmentioning

confidence: 99%

Modeling Climate Change Impacts on Rangeland Productivity and Livestock Population Dynamics in Nkayi District, Zimbabwe

et al. 2020

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Smallholder farmers in semi-arid areas depend on both cropping and livestock as the main sources of livelihoods. Rangeland productivity varies on both spatial and temporal scales and provides the major source of feed for livestock. Rangeland productivity is expected to decline with climate change thereby reducing livestock feed availability and consequently livelihoods that depend on livestock. This study was carried out to assess the impacts of climate change on rangeland productivity and consequently livestock population dynamics using a 30-year simulation modeling approach. The climate scenarios used in the simulations are built from the localized predictions by General Circulation Models (GCMs). The primary climate variables under consideration are rainfall (+/−7% change), carbon dioxide (CO2 up to 650 ppm) and temperature (+4 °C change). This was done by applying the SAVANNA ecosystem model which simulates rangeland processes and demographic responses of herbivores on a temporal and spatial scale using a weekly internal time step and monthly spatial and temporal outputs. The results show that rainfall levels of less than 600 mm/year have the largest negative effect on herbaceous biomass production. The amount of biomass from the woody layer does not change much during the year. The carbon dioxide (CO2) effects are more influential on the tree and shrub layers (C3 plants) than the herbaceous layer (C4 grasses). The CO2 effect was more dominant than the effects of rainfall and temperature. In the baseline simulations, the shrub plant layer increased significantly over 30 years while there is a three-fold increase in the woody plant layer (trees and shrubs) where biomass increased from a 1980 production to that of 2010. The biomass of the herbaceous layer was stable over the historical period (1980 to 2010) with values fluctuating between 200 and 400 g/m2. Grass green biomass has a variable distribution where most production occurred in the fields and cleared areas while lower levels of production were found in the forested areas. The spatial distribution of shrub green biomass was less directly linked to yearly rainfall. Shrub biomass was mostly found in forested areas, and it showed a steady increase in production. Cattle, donkey, and goat populations rose slowly from 1980 but the rise was disrupted by a dry period during the late 1980s to the early 1990s causing a decline in all populations primarily due to grass unavailability. The populations of cattle goats and donkeys started to rise again from 1995 onwards due to improvements in rainfall. Cattle and donkey populations were rising faster than that of goats while sheep population was not changing much for most of the simulation period, otherwise they declined significantly during the drought of 2002. Similar changes in simulated grass biomass (g/m2) were observed in almost all climate scenarios, except for the peak and low years. The livestock population simulation showed few variations in livestock population under all scenarios. The main conclusion from the study is that CO2 effects on rangeland productivity are much more dominant than the localized effects of rainfall and temperature. This has implications of favoring the growth of the tree and shrub layers over herbaceous layer, which meant that in the long run, the species that are able to use tree and shrub layers may be kept as a livelihood source as they will have a feed source.

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Integrated Assessment of Crop–Livestock Production Systems Beyond Biophysical Methods

Cited by 8 publications

References 33 publications

Role of Modelling in International Crop Research: Overview and Some Case Studies

Role of Modelling in International Crop Research: Overview and Some Case Studies

Handbook of Climate Change and Agroecosystems

Modeling Climate Change Impacts on Rangeland Productivity and Livestock Population Dynamics in Nkayi District, Zimbabwe

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