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Publisher: Elsevier   (Total: 3042 journals)

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Showing 1 - 200 of 3042 Journals sorted alphabetically
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 19, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 16, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 81, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 23, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 27, SJR: 2.515, h-index: 90)
Achievements in the Life Sciences     Open Access   (Followers: 4)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 5, SJR: 0.338, h-index: 19)
Acta Astronautica     Hybrid Journal   (Followers: 326, SJR: 0.726, h-index: 43)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Biomaterialia     Hybrid Journal   (Followers: 25, SJR: 2.02, h-index: 104)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription  
Acta de Investigación Psicológica     Open Access   (Followers: 2)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.172, h-index: 29)
Acta Haematologica Polonica     Free   (SJR: 0.123, h-index: 8)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.604, h-index: 38)
Acta Materialia     Hybrid Journal   (Followers: 203, SJR: 3.683, h-index: 202)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.615, h-index: 21)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.442, h-index: 21)
Acta Oecologica     Hybrid Journal   (Followers: 9, SJR: 0.915, h-index: 53)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription   (Followers: 1)
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.311, h-index: 16)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 2)
Acta Poética     Open Access   (Followers: 4)
Acta Psychologica     Hybrid Journal   (Followers: 22, SJR: 1.365, h-index: 73)
Acta Sociológica     Open Access  
Acta Tropica     Hybrid Journal   (Followers: 5, SJR: 1.059, h-index: 77)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 4)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 3)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 4, SJR: 0.383, h-index: 19)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 2)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 5, SJR: 0.141, h-index: 3)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 4, SJR: 0.112, h-index: 2)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 3)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.967, h-index: 57)
Addictive Behaviors     Hybrid Journal   (Followers: 15, SJR: 1.514, h-index: 92)
Addictive Behaviors Reports     Open Access   (Followers: 5)
Additive Manufacturing     Hybrid Journal   (Followers: 7, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 20)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 124, SJR: 5.2, h-index: 222)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.265, h-index: 53)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, SJR: 0.739, h-index: 33)
Advances in Accounting     Hybrid Journal   (Followers: 9, SJR: 0.299, h-index: 15)
Advances in Agronomy     Full-text available via subscription   (Followers: 15, SJR: 2.071, h-index: 82)
Advances in Anesthesia     Full-text available via subscription   (Followers: 24, SJR: 0.169, h-index: 4)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 3)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 6, SJR: 1.054, h-index: 35)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 10, SJR: 0.801, h-index: 26)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 21, SJR: 1.286, h-index: 49)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 16, SJR: 3.31, h-index: 42)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.277, h-index: 43)
Advances in Botanical Research     Full-text available via subscription   (Followers: 3, SJR: 0.619, h-index: 48)
Advances in Cancer Research     Full-text available via subscription   (Followers: 25, SJR: 2.215, h-index: 78)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 0.9, h-index: 30)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 2.139, h-index: 42)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 24, SJR: 0.183, h-index: 23)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.665, h-index: 29)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 8, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, SJR: 0.938, h-index: 33)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 18, SJR: 2.314, h-index: 130)
Advances in Computers     Full-text available via subscription   (Followers: 16, SJR: 0.223, h-index: 22)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 4)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 22)
Advances in Ecological Research     Full-text available via subscription   (Followers: 39, SJR: 3.25, h-index: 43)
Advances in Engineering Software     Hybrid Journal   (Followers: 25, SJR: 0.486, h-index: 10)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 40, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 3)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 8)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 44, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 14)
Advances in Genetics     Full-text available via subscription   (Followers: 15, SJR: 2.558, h-index: 54)
Advances in Genome Biology     Full-text available via subscription   (Followers: 12)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 2.325, h-index: 20)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 20, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.497, h-index: 31)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 24)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.396, h-index: 27)
Advances in Immunology     Full-text available via subscription   (Followers: 34, SJR: 4.152, h-index: 85)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 1.132, h-index: 42)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 3, SJR: 1.274, h-index: 27)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 4)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 4)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.764, h-index: 15)
Advances in Lipobiology     Full-text available via subscription   (Followers: 2)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 16, SJR: 1.645, h-index: 45)
Advances in Mathematics     Full-text available via subscription   (Followers: 10, SJR: 3.261, h-index: 65)
Advances in Medical Sciences     Hybrid Journal   (Followers: 5, SJR: 0.489, h-index: 25)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.44, h-index: 51)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 22)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 10)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.324, h-index: 8)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 4)
Advances in Oncobiology     Full-text available via subscription   (Followers: 3)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 15, SJR: 2.885, h-index: 45)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.148, h-index: 11)
Advances in Parasitology     Full-text available via subscription   (Followers: 7, SJR: 2.37, h-index: 73)
Advances in Pediatrics     Full-text available via subscription   (Followers: 21, SJR: 0.4, h-index: 28)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 13)
Advances in Pharmacology     Full-text available via subscription   (Followers: 15, SJR: 1.718, h-index: 58)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 7, SJR: 0.384, h-index: 26)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.248, h-index: 11)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 8)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 19, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 58)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 5, SJR: 0.478, h-index: 32)
Advances in Radiation Oncology     Open Access  
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 2, SJR: 0.1, h-index: 2)
Advances in Space Research     Full-text available via subscription   (Followers: 339, SJR: 0.606, h-index: 65)
Advances in Structural Biology     Full-text available via subscription   (Followers: 8)
Advances in Surgery     Full-text available via subscription   (Followers: 6, SJR: 0.823, h-index: 27)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 29, SJR: 1.321, h-index: 56)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 15)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 1.878, h-index: 68)
Advances in Water Resources     Hybrid Journal   (Followers: 43, SJR: 2.408, h-index: 94)
Aeolian Research     Hybrid Journal   (Followers: 5, SJR: 0.973, h-index: 22)
Aerospace Science and Technology     Hybrid Journal   (Followers: 311, SJR: 0.816, h-index: 49)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.318, h-index: 36)
African J. of Emergency Medicine     Open Access   (Followers: 4, SJR: 0.344, h-index: 6)
Ageing Research Reviews     Hybrid Journal   (Followers: 7, SJR: 3.289, h-index: 78)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 398, SJR: 1.385, h-index: 72)
Agri Gene     Hybrid Journal  
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 15, SJR: 2.18, h-index: 116)
Agricultural Systems     Hybrid Journal   (Followers: 30, SJR: 1.275, h-index: 74)
Agricultural Water Management     Hybrid Journal   (Followers: 38, SJR: 1.546, h-index: 79)
Agriculture and Agricultural Science Procedia     Open Access  
Agriculture and Natural Resources     Open Access   (Followers: 1)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 50, SJR: 1.879, h-index: 120)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.434, h-index: 14)
Air Medical J.     Hybrid Journal   (Followers: 5, SJR: 0.234, h-index: 18)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.285, h-index: 3)
Alcohol     Hybrid Journal   (Followers: 9, SJR: 0.922, h-index: 66)
Alcoholism and Drug Addiction     Open Access   (Followers: 5)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.436, h-index: 12)
Alexandria J. of Medicine     Open Access  
Algal Research     Partially Free   (Followers: 8, SJR: 2.05, h-index: 20)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 3)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.46, h-index: 29)
Allergology Intl.     Open Access   (Followers: 5, SJR: 0.776, h-index: 35)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 6, SJR: 0.158, h-index: 9)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 46, SJR: 4.289, h-index: 64)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 5)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 3)
American Heart J.     Hybrid Journal   (Followers: 46, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 45, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 34, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 6, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 15, SJR: 1.653, h-index: 93)
American J. of Human Genetics     Hybrid Journal   (Followers: 30, SJR: 8.769, h-index: 256)
American J. of Infection Control     Hybrid Journal   (Followers: 24, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 32, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 44, SJR: 2.023, h-index: 189)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 182, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 54, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 2)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.249, h-index: 88)
American J. of Otolaryngology     Hybrid Journal   (Followers: 23, SJR: 0.59, h-index: 45)
American J. of Pathology     Hybrid Journal   (Followers: 23, SJR: 2.653, h-index: 228)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 21, SJR: 2.764, h-index: 154)
American J. of Surgery     Hybrid Journal   (Followers: 33, SJR: 1.286, h-index: 125)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.653, h-index: 70)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 5)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.066, h-index: 51)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 52, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 4)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 2, SJR: 0.209, h-index: 27)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription   (SJR: 0.104, h-index: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 2, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 38, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 161, SJR: 0.725, h-index: 154)
Analytical Chemistry Research     Open Access   (Followers: 8, SJR: 0.18, h-index: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 10)
Anesthésie & Réanimation     Full-text available via subscription  
Anesthesiology Clinics     Full-text available via subscription   (Followers: 21, SJR: 0.421, h-index: 40)
Angiología     Full-text available via subscription   (SJR: 0.124, h-index: 9)
Angiologia e Cirurgia Vascular     Open Access  
Animal Behaviour     Hybrid Journal   (Followers: 153, SJR: 1.907, h-index: 126)
Animal Feed Science and Technology     Hybrid Journal   (Followers: 5, SJR: 1.151, h-index: 83)
Animal Reproduction Science     Hybrid Journal   (Followers: 5, SJR: 0.711, h-index: 78)
Annales d'Endocrinologie     Full-text available via subscription   (SJR: 0.394, h-index: 30)
Annales d'Urologie     Full-text available via subscription  
Annales de Cardiologie et d'Angéiologie     Full-text available via subscription   (SJR: 0.177, h-index: 13)
Annales de Chirurgie de la Main et du Membre Supérieur     Full-text available via subscription  
Annales de Chirurgie Plastique Esthétique     Full-text available via subscription   (Followers: 2, SJR: 0.354, h-index: 22)
Annales de Chirurgie Vasculaire     Full-text available via subscription   (Followers: 1)

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Journal Cover Agricultural Systems
  [SJR: 1.275]   [H-I: 74]   [30 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0308-521X
   Published by Elsevier Homepage  [3042 journals]
  • Integrating economic and environmental impact analysis: The case of
           rice-based farming in northern Thailand
    • Authors: S.J. Ramsden; P. Wilson; B. Phrommarat
      Pages: 1 - 10
      Abstract: Publication date: October 2017
      Source:Agricultural Systems, Volume 157
      Author(s): S.J. Ramsden, P. Wilson, B. Phrommarat
      Crop production is associated with a range of potential environmental impacts, including field emissions of greenhouse gases, loss of nitrogen and phosphorous nutrients to water and toxicity effects on humans and natural ecosystems. Farmers can mitigate these environmental impacts by changing their farming systems; however these changes have implications for production and profitability. To address these trade-offs, a farm-level model was constructed to capture the elements of a rice-based production system in northern Thailand. Life Cycle Assessment (LCA) was used to generate environmental impacts, across a range of indicators, for all crops and associated production processes in the model. A baseline, profit maximising combination of crops and resource use was generated and compared with a greenhouse gas minimising scenario and an alternative inputs (fertilisers and insecticides) scenario. Greenhouse gas minimisation showed a reduction in global warming potential of 13%; other impact indicators also decreased. Associated profit foregone was 10% as measured by total gross margin. With the alternative farm inputs (ammonium sulphate, organic fertiliser and fipronil insecticide), results indicated that acidification, eutrophication, freshwater and terrestrial ecotoxicity impacts were reduced by 43, 37, 47 and 91% respectively with relatively small effects on profit.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.006
      Issue No: Vol. 157 (2017)
  • Environmental impact assessment of double- and relay-cropping with winter
           camelina in the northern Great Plains, USA
    • Authors: Marisol Berti; Burton Johnson; David Ripplinger; Russ Gesch; Alfredo Aponte
      Pages: 1 - 12
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Marisol Berti, Burton Johnson, David Ripplinger, Russ Gesch, Alfredo Aponte
      Recent findings indicate that double- or relay-cropping winter camelina (Camelina sativa L. Crantz.) with, forage, or food crops can increase yield per area, improve energy balance, and provide several ecosystem services. Double-cropping can help balance food and energy production. The objective of this study was to determine the environmental impact of double- and relay-cropping systems as compared with monocultured maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] in the Midwest, USA. Ten crop sequences composed of double- and relay-cropped forage sorghum [Sorghum bicolor (L.) Moench.] and soybean with winter camelina were evaluated and compared with their monoculture counterparts. The environmental aspects evaluated included global warming potential (GWP), abiotic depletion, acidification, eutrophication, ecotoxicity, and human toxicity. Additionally, provisioning and regulating ecosystem services were estimated, including: primary aboveground productivity, soil erosion, and biodiversity in each crop sequence. The analysis was conducted from ‘cradle-to-gate’, including only the agricultural phase. Global warming potential estimated by three different methods indicated that winter camelina as a monocrop had a GWP of 579 to 922kgCO2e ha−1. Maize in monoculture had higher GWP than all other double- and relay-cropping systems studied. The higher emissions of double- and relay-cropping systems and maize can be explained by higher N fertilizer application, which led to greater field N2O emissions. Also, the additional sowing and harvesting of the double- or relay-crop increased CO2 emissions due to increased diesel use. Winter camelina as a monocrop had the lowest values in all impact categories, indicating camelina agricultural production phase has low environmental impact compared with maize and soybean in monoculture. Double- and relay- cropping systems increased primary productivity per unit area and biodiversity and reduced soil erosion potential. Increasing productivity with the additional environmental benefits of these systems may encourage more farmers to adopt sustainable agricultural practices.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.05.012
      Issue No: Vol. 156 (2017)
  • A quantitative value chain analysis of policy options for the beef sector
           in Botswana
    • Authors: Kanar Dizyee; Derek Baker; Karl M. Rich
      Pages: 13 - 24
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Kanar Dizyee, Derek Baker, Karl M. Rich
      The liberalization of beef exports in Botswana is hotly debated among policy makers and relevant value chain actors. While some policy makers argue that such a move might increase prices for producers and make beef unaffordable for consumers, others suggest an open market would reduce the profitability of the beef sector in Botswana. At the same time, these impacts will be mediated by the presence of animal disease and the availability of sufficient feed and water. In this paper, we constructed an integrated system dynamics (SD) model that captures the feedbacks between the biological dynamics of cattle production, the economics of animal and meat marketing and trade, and the impacts that environmental pressures such as rainfall and animal disease have on the system. We used this model to run a series of scenarios associated with market liberalization and animal health shocks to quantify their impacts throughout the value chain, taking into account the feedbacks between biology, markets, and environment on the value chain itself. This approach allows for a holistic evaluation of policy options on different chain actors and whole chain performance, and provides a knowledge base for prioritizing interventions. Model results suggested that although disease control policies benefit all value chain actors, gains from market liberalization come at the expense of substantial losses to Botswana Meat Commission (BMC) and its contracted feedlots. They also suggest that combining market liberalization policy reforms with better animal disease controls greatly improved the financial performance of all value chain actors.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.05.007
      Issue No: Vol. 156 (2017)
  • Benchmarking nutrient use efficiency of dairy farms: The effect of
           epistemic uncertainty
    • Authors: W. Mu; E.A. Groen; C.E. van Middelaar; E.A.M. Bokkers; S. Hennart; D. Stilmant; I.J.M. de Boer
      Pages: 25 - 33
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): W. Mu, E.A. Groen, C.E. van Middelaar, E.A.M. Bokkers, S. Hennart, D. Stilmant, I.J.M. de Boer
      The nutrient use efficiency (NUE) of a system, generally computed as the amount of nutrients in valuable outputs over the amount of nutrients in all inputs, is commonly used to benchmark the environmental performance of dairy farms. Benchmarking the NUE of farms, however, may lead to biased conclusions because of differences in major decisive characteristics between farms, such as soil type and production intensity, and because of epistemic uncertainty of input parameters caused by errors in measurement devices or observations. This study aimed to benchmark the nitrogen use efficiency (NUEN; calculated as N output per unit of N input) of farm clusters with similar characteristics while including epistemic uncertainty, using Monte Carlo simulation. Subsequently, the uncertainty of the parameters explaining most of the output variance was reduced to examine if this would improve benchmarking results. Farms in cluster 1 (n=15) were located on sandy soils and farms in cluster 2 (n=17) on loamy soils. Cluster 1 farms were more intensive in terms of milk production per hectare and per cow, had less grazing hours, and fed more concentrates compared to farms in cluster 2. The mean NUEN of farm in cluster 1 was 43%, while in cluster 2 it was 26%. Input parameters that explained most of the output variance differed between clusters. For cluster 1, input of feed and output of roughage were most important, whereas for cluster 2, the input of mineral fertilizer (or fixation) was most important. For both clusters, the output of milk was relatively important. Including the epistemic uncertainty of input parameters showed that only 37% of the farms in cluster 1 (out of 105 mutual comparisons) differed significantly in terms of their NUEN, whereas in cluster 2 this was 82% (out of 120 comparisons). Therefore, benchmarking NUEN of farms in cluster 1 was no longer possible, whereas farms in cluster 2 could still be ranked when uncertainty was included. After reducing the uncertainties of the most important parameters, 72% of the farms in cluster 1 differed significantly in terms of their NUEN, and in cluster 2 this was 87%. Results indicate that reducing epistemic uncertainty of input parameters can significantly improve benchmarking results. The method presented in this study, therefore, can be used to draw more reliable conclusions regarding benchmarking the NUE of farms, and to identify the parameters that require more precision to do so.

      PubDate: 2017-06-02T15:54:20Z
      DOI: 10.1016/j.agsy.2017.04.001
      Issue No: Vol. 156 (2017)
  • Low-input dairy farming in Europe: Exploring a context-specific notion
    • Authors: J. Bijttebier; J. Hamerlinck; S. Moakes; N. Scollan; J. Van Meensel; L. Lauwers
      Pages: 43 - 51
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): J. Bijttebier, J. Hamerlinck, S. Moakes, N. Scollan, J. Van Meensel, L. Lauwers
      Frequently acknowledged as coming forward to environmental issues by reducing external input use, low input (LI) dairy farming is gaining attention. The absence of a clearly delineated description of LI dairying, however, hampers identification and analysis of these farming systems. This paper aims at empirically examining, EU wide, the farm structure, production intensity and productivity of LI with respect to their high input (HI) conventional counterpart and to organic dairying (ORG). A pragmatic quartiles-based categorization of farms from the Farm Accountancy Data Network of 20 important EU dairy countries, with the value of external input costs per grazing livestock unit (GLU) is used as prior discriminating indicator between LI and HI. LI dairy farms are smaller than HI dairy farms, in particular when farm size is expressed as total farm capital. Other variables that differentiate between LI and HI in most countries are number of dairy cows per GLU and area of forage and grassland on total agricultural area. Partial productivities in HI farms exceed those in LI farms, most apparent is milk production per cow. Differentiation of forage production between LI and HI is less uniform throughout Europe. A pairwise matching of differentiation profiles between countries indicates that differentiation between LI and HI is country specific. A similar diversity in country-specific differentiation between ORG and LI farming is found.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.016
      Issue No: Vol. 156 (2017)
  • Climate change impacts on EU agriculture: A regionalized perspective
           taking into account market-driven adjustments
    • Authors: María Blanco; Fabien Ramos; Benjamin Van Doorslaer; Pilar Martínez; Davide Fumagalli; Andrej Ceglar; Francisco J. Fernández
      Pages: 52 - 66
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): María Blanco, Fabien Ramos, Benjamin Van Doorslaer, Pilar Martínez, Davide Fumagalli, Andrej Ceglar, Francisco J. Fernández
      The biophysical and economic consequences of climate change for agriculture are surrounded by uncertainties. The evaluation of climate change impacts on global and regional agriculture has been studied at length. In most cases, however, global and regional impacts are examined separately. Here we present a regionalized assessment – for the 2030 time horizon – covering the whole European Union while accounting for market feedback through international markets. To account for uncertainty on climate effects, we defined several simulation scenarios that differ as to climate projections and assumptions on the degree of carbon fertilization. Biophysical simulations show that crop productivity effects are largely determined by the degree of carbon fertilization, leading to decreased productivity in the absence of carbon fertilization and increased productivity otherwise. The magnitude of those effects differs across regions and crops, with maize being one of the most negatively affected in the EU. Economic simulations show that, while, on the whole, crop price effects attenuate the global impacts of climate change, aggregate results conceal significant regional disparities and their related trade adjustment. These results suggest that a multi-scale perspective is helpful for assessing climate change impacts on agriculture, as it will improve understanding of how regional and global agrifood markets respond to climate change and how these responses interact with each other.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.013
      Issue No: Vol. 156 (2017)
  • The role of soils in the analysis of potential agricultural production: A
           case study in Lebanon
    • Authors: A. Bonfante; M.H. Sellami; M.T. Abi Saab; R. Albrizio; A. Basile; S. Fahed; P. Giorio; G. Langella; E. Monaco; J. Bouma
      Pages: 67 - 75
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): A. Bonfante, M.H. Sellami, M.T. Abi Saab, R. Albrizio, A. Basile, S. Fahed, P. Giorio, G. Langella, E. Monaco, J. Bouma
      Maintaining cereal production in the Bekaa valley in Lebanon presents a serious challenge. Lack of water is the driving force of agricultural research which is mainly focused on introduction of drought resistant cultivars, application of conservation tillage and supplemental irrigation. In this context forty-eight experimental plots were laid out for three years in a statistical split plot design. The statistical analyses showed that aboveground biomass and yield were significantly affected by irrigation for barley but not for the yield of durum wheat. Effects of soil tillage practices and introduction of new cultivares were not significant. A soil survey indicated that the implicit assumption of soil homogeneity of the agronomic design was correct for surface soil but that two different soil types (Cambisols and Fluvisols) had to be distinguished considering subsoil conditions and corresponding rooting patterns. Therefore, the main objective of this paper was to determine the effects of different soil types on crop response and, in addition, to assess how physically-based modeling can predict future effects of climate change on crops and soils. Simulation model SWAP was validated for local conditions using measurements of soil water contents, aboveground biomass and yield of wheat. Considering two rather than one soil type for the experimental area resulted in different conclusions for both crops as to the effectivity of both conservation tillage and irrigation, demonstrating that a distinction of only one soil type results in misleading results. The validated model was applied to estimate yields considering climate change, focusing on the application of supplemental irrigation. Yields for “Mikii3” a durum wheat cultivar are expected to increase by appr. 14% in both soils due to climate change. More importantly, only 3 supplemental irrigations would be needed for the deep soil requiring 5% more water as compared with current climate trend, while the shallow soil needs 13 irrigations, corresponding with a need for 35% more water. This is highly significant from an economic point of view and supports the relevance of distinguishing two soil types. It was demonstrated the synergy of joint research by the agronomic and soil science community and the need for executing a soil survey in future when planning agronomic experiments, including a hydrological soil characterisation.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.018
      Issue No: Vol. 156 (2017)
  • Mapping regional risks from climate change for rainfed rice cultivation in
    • Authors: Kuntal Singh; Colin J. McClean; Patrick Büker; Sue E. Hartley; Jane K. Hill
      Pages: 76 - 84
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Kuntal Singh, Colin J. McClean, Patrick Büker, Sue E. Hartley, Jane K. Hill
      Global warming is predicted to increase in the future, with detrimental consequences for rainfed crops that are dependent on natural rainfall (i.e. non-irrigated). Given that many crops grown under rainfed conditions support the livelihoods of low-income farmers, it is important to highlight the vulnerability of rainfed areas to climate change in order to anticipate potential risks to food security. In this paper, we focus on India, where ~50% of rice is grown under rainfed conditions, and we employ statistical models (climate envelope models (CEMs) and boosted regression trees (BRTs)) to map changes in climate suitability for rainfed rice cultivation at a regional level (~18×18km cell resolution) under projected future (2050) climate change (IPCC RCPs 2.6 and 8.5, using three GCMs: BCC-CSM1.1, MIROC-ESM-CHEM, and HadGEM2-ES). We quantify the occurrence of rice (whether or not rainfed rice is commonly grown, using CEMs) and rice extent (area under cultivation, using BRTs) during the summer monsoon in relation to four climate variables that affect rice growth and yield namely ratio of precipitation to evapotranspiration (PER), maximum and minimum temperatures (T max and T min ), and total rainfall during harvesting. Our models described the occurrence and extent of rice very well (CEMs for occurrence, ensemble AUC=0.92; BRTs for extent, Pearson's r=0.87). PER was the most important predictor of rainfed rice occurrence, and it was positively related to rainfed rice area, but all four climate variables were important for determining the extent of rice cultivation. Our models project that 15%–40% of current rainfed rice growing areas will be at risk (i.e. decline in climate suitability or become completely unsuitable). However, our models project considerable variation across India in the impact of future climate change: eastern and northern India are the locations most at risk, but parts of central and western India may benefit from increased precipitation. Hence our CEM and BRT models agree on the locations most at risk, but there is less consensus about the degree of risk at these locations. Our results help to identify locations where livelihoods of low-income farmers and regional food security may be threatened in the next few decades by climate changes. The use of more drought-resilient rice varieties and better irrigation infrastructure in these regions may help to reduce these impacts and reduce the vulnerability of farmers dependent on rainfed cropping.

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.009
      Issue No: Vol. 156 (2017)
  • Carbon and nitrogen environmental trade-offs of winter rye cellulosic
           biomass in the Chesapeake Watershed
    • Authors: Amanda M. Ramcharan; Tom L. Richard
      Pages: 85 - 94
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Amanda M. Ramcharan, Tom L. Richard
      Cellulosic biomass from winter crops can complement maize stover harvested from maize (Zea mays L.) – soybean (Glycine max L.) rotations. In this study, we assessed on-field environmental impacts related to carbon (C) and nitrogen (N) by modeling representative agro-ecological conditions prevalent in the mid-Atlantic region of the United States. We used the biophysical model Cycles to simulate management scenarios for maize-soybean cropping systems that included winter rye (Secale cereale L.). The model was used to quantify changes in N losses via nitrate leaching (NO3), emissions of nitrous oxide (N2O) and ammonia (NH3), changes in soil organic carbon, and carbon dioxide equivalent emissions per megajoule (CO2eq MJ−1). Including winter rye in the rotation reduced NO3 leaching over a winter fallow control (77% on average), even when the winter rye was fertilized and regardless of whether stover, winter rye, or both cellulosic feedstocks were harvested. Applying fertilizer to winter rye did however increase NO3 leaching as well as NH3 and N2O emissions. Model results consistently showed fertilizing the winter rye improved both biomass yield and soil C levels compared to unfertilized winter rye, regardless of location, soil, fertilizer type or stover harvest. While it is difficult to simultaneously reduce agricultural nitrogen losses, produce renewable energy and increase soil carbon, results can guide management of these trade-offs while tapping into an abundant energy resource and reducing greenhouse gas emissions.
      Graphical abstract image

      PubDate: 2017-06-12T08:09:49Z
      DOI: 10.1016/j.agsy.2017.05.017
      Issue No: Vol. 156 (2017)
  • Lessons learned from the long-term analysis of cacao yield and stand
           structure in central Cameroonian agroforestry systems
    • Authors: Stéphane Saj; Patrick Jagoret; Louis Essola Etoa; Eltson Eteckji Fonkeng; Justin Ngala Tarla; Jean-Daniel Essobo Nieboukaho; Kenneth Mvondo Sakouma
      Pages: 95 - 104
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Stéphane Saj, Patrick Jagoret, Louis Essola Etoa, Eltson Eteckji Fonkeng, Justin Ngala Tarla, Jean-Daniel Essobo Nieboukaho, Kenneth Mvondo Sakouma
      In Sub-Saharan Africa, cacao cultivation is a major driver of deforestation and cacao-producing countries are among the poorest in the world. Two different production schemes compete today: a “land-sharing” strategy supports cacao based agroforestry systems (cAFS) while a “land-sparing” approach advocates for the intensification of these systems. Yet, we believe that a path exists between these two options which could be fruitful, sustainable and ecologically sound for the regions in which cacao is grown. To prove our point we investigated the competition balance, stand structure and accessible yields of 144 cacao-producing plots in cAFS of Central Cameroon. A 100-year chronosequence and a large array of situations, ranging from very simple systems to very complex cAFS were used. We used basal area (BA) ratios of different components of the systems to gauge interspecific competition. We found that yields were highly dependent on the age of the plot, the BA of associated tree community and the structure of the cacao stand. We found that very long-term sustainability could be achieved if the BA share of the cacao stand does not exceed 40% of the total BA of the cAFS. While interspecific competition prevailed, some associated functional groups of woody species were consistently related to higher cacao yields. This may underline putative synergistic - or less damageable - effects on yields for a given range of plantation age and interspecific competition level. The BA of the cacao stand steadily increased with age yet yields did not similarly rise. Hence, our results show that while rejuvenation and densification practices permitted the maintenance of a “baseline” production, these practices needed to be better studied and improved in order to get higher yields - especially for cAFS which are over 40years old. Finally, the high accessible yields found underlined the good production potential of cAFS that is to be reached if a better knowledge of how cAFS function is acquired and if intensification in terms of inputs and/or manpower is undertaken. Such intensification would not compulsorily include cAFS simplification and therefore would, at least partly, facilitate the preservation of the ecosystem services that cAFS support.

      PubDate: 2017-06-16T08:22:47Z
      DOI: 10.1016/j.agsy.2017.06.002
      Issue No: Vol. 156 (2017)
  • Combining environmentally and economically sustainable dairy and beef
           production in Sweden
    • Authors: Anna Hessle; Jan Bertilsson; Bo Stenberg; Karl-Ivar Kumm; Ulf Sonesson
      Pages: 105 - 114
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Anna Hessle, Jan Bertilsson, Bo Stenberg, Karl-Ivar Kumm, Ulf Sonesson
      To achieve a more sustainable food sector, a supply chain approach is needed. In this study, experts in different areas along supply chains co-operated in an interactive process to define future environmentally sustainable supply chains of milk and beef. The basis was to use existing techniques, to have production performance corresponding to the best quartile of today and to consider other sustainability aspects, such as economics. The work resulted in concrete descriptions of alternative product chains for delivered milk and beef. To also permit concrete descriptions of the latter part of the product chains, two consumer-packed end products were selected for monitoring, namely fresh milk and sirloin steak. The production systems investigated comprised cropping, livestock production, industrial processing and production, logistics, packaging and wastage and distribution, but not retailers or consumers. The study area was a Swedish county and the reference level was its production of milk and beef in 2012. The future product chains were assumed to deliver the same amounts of commodities as in 2012, but with reduced environmental impact. Primary production was required to be at least as profitable as today. Beside description of the current situation, three alternative scenarios were created, focusing on delivery of ecosystem services, plant nutrient circulation and minimising climate impact, respectively. Life cycle assessments were performed for these four scenarios (reference plus three alternative scenarios) for single-product chains and county-wide. Furthermore, production costs in primary production were calculated for the four scenarios. The results revealed great potential to reduce the negative environmental impact of Swedish dairy and beef production at current volumes, irrespective of whether ecosystem services, plant nutrient circulation or climate impact is in focus. The single most important factor for decreased environmental impact for livestock production was increased production efficiency. Measures in agriculture, especially concerning feeds, were critical, but actions in processing and distribution also contributed. All alternative scenarios resulted in lower production costs than at present. It was obvious that as dairy and beef systems are connected, the potential for their environmental improvement must be analysed together. In conclusion, increased efficiency can decrease the negative environmental impact of Swedish cattle production and also reduce costs to the farmer.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.004
      Issue No: Vol. 156 (2017)
  • Predicting farmer uptake of new agricultural practices: A tool for
           research, extension and policy
    • Authors: Geoff Kuehne; Rick Llewellyn; David J. Pannell; Roger Wilkinson; Perry Dolling; Jackie Ouzman; Mike Ewing
      Pages: 115 - 125
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Geoff Kuehne, Rick Llewellyn, David J. Pannell, Roger Wilkinson, Perry Dolling, Jackie Ouzman, Mike Ewing
      There is much existing knowledge about the factors that influence adoption of new practices in agriculture but few attempts have been made to construct predictive quantitative models of adoption for use by those planning agricultural research, development, extension and policy. ADOPT (Adoption and Diffusion Outcome Prediction Tool) is the result of such an attempt, providing predictions of a practice's likely rate and peak level of adoption as well as estimating the importance of various factors influencing adoption. It employs a conceptual framework that incorporates a range of variables, including variables related to economics, risk, environmental outcomes, farmer networks, characteristics of the farm and the farmer, and the ease and convenience of the new practice. The ability to learn about the relative advantage of the practice, as influenced by characteristics of both the practice and the potential adopters, plays a central role. Users of ADOPT respond to 22 questions related to: a) characteristics of the practice that influence its relative advantage, b) characteristics of the population influencing their perceptions of the relative advantage of the practice, c) characteristics of the practice influencing the ease and speed of learning about it, and d) characteristics of the potential adopters that influence their ability to learn about the practice. ADOPT provides a prediction of the diffusion curve of the practice and sensitivity analyses of the factors influencing the speed and peak level of adoption. In this paper the model is described and its ability to predict the diffusion of agricultural practices is demonstrated using examples of new crop types, new cropping technology and grazing options. As well as providing predictions, ADOPT is designed to increase the conceptual understanding and consideration of the adoption process by those involved in agricultural research, development, extension and policy.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.06.007
      Issue No: Vol. 156 (2017)
  • Creating an enabling environment for industry-driven pest suppression: The
           case of suppressing Queensland fruit fly through area-wide management
    • Authors: Heleen Kruger
      Pages: 139 - 148
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): Heleen Kruger
      Increasing concerns about pests call for the development and uptake of innovative pest management approaches. This coincides with many governments pushing for greater industry self-reliance. This paper investigates how to create a more enabling environment for local industries to suppress Queensland fruit fly (QFly) through industry-driven, area-wide management (AWM). This key recommended approach requires high technical capability and is reliant on cooperation between horticulture growers and other risk contributors, such as town residents, with QFly hosts on their properties. Agriculture Innovation Systems thinking and a functional-structural analysis are applied to the current QFly management innovation system to understand how it constrains or facilitates local industries pursuing AWM. This assists with identifying governance interventions that will support local industries to undertake AWM. Data is derived from semi-structured interviews with key informants from stakeholder groups and a grower survey in three regions where AWM has been achieved or is being attempted. Key blocking mechanisms hindering local industries to pursue AWM have been identified as a lack of local capacity; weak connections between local industries and the broader innovation system; lack of AWM investment; and reliance on voluntary cooperation. Suggestions for policy interventions include supporting intermediation; strengthening local capacity and enabling co-regulation.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.05.008
      Issue No: Vol. 156 (2017)
  • Freshwater use in livestock production—To be used for food crops or
           livestock feed?
    • Authors: Ylva Ran; Corina E. van Middelaar; Mats Lannerstad; Mario Herrero; Imke J.M. de Boer
      Pages: 1 - 8
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Ylva Ran, Corina E. van Middelaar, Mats Lannerstad, Mario Herrero, Imke J.M. de Boer
      Current approaches to estimate freshwater use in livestock production systems generally fail to consider the competition for water resources with alternative uses, such as production of food crops food or other ecosystem services. This article presents a new method to account for the competition for freshwater use between food crops and animal feed, while assessing freshwater use in livestock production systems. The developed water use ratio (WUR) is defined as the maximum amount of human digestible protein (HDP) derived from food crops from the consumptive water use (CWU) appropriated to produce 1kg of animal-source food (ASF) over the amount of HDP in that 1kg of ASF. The CWU for livestock production is first categorized according to the land over which it is consumed, based on the suitability of that land to produce food crops. Then, the method assesses food-feed competition by determining the amount of HDP that could have been produced from food crops, using the same CWU currently used to produce ASF. The method enables identification of livestock production systems that contribute to global food supply without competing significantly over water resources with food production, based on their CWU. Three beef production systems in Uruguay are used to illustrate the method. During the backgrounding and the finishing stages, which are analyzed in this study, cattle can be kept on natural pasture (NP), seeded pasture (SP) or in feedlots (FL). The following three systems were analysed: i) NP-NP, ii) SP-SP and iii) SP-FL. Results show that the NP-NP system uses the largest amount of water per kg of beef output. However, results also show that the SP-SP and SP-FL systems can potentially produce more HDP by growing food crops than by producing beef. Based on the traditional measure for water productivity, i.e. the quantity of CWU per kilo of beef produced, we would conclude that the NP-NP system is least efficient, whereas based on the WUR the NP-NP system is the only system producing HDP more efficiently than food crops. Sustainable intensification not only implies improving agriculture and livestock productivity per unit of resource used, but also improving the number of human beings nourished. Results from this study illustrate the importance of considering competition and trade-offs with other uses when evaluating water use efficiency of livestock systems to promote sustainable intensification.

      PubDate: 2017-04-11T18:44:05Z
      DOI: 10.1016/j.agsy.2017.03.008
      Issue No: Vol. 155 (2017)
  • Management options for dairy farms under climate change: Effects of
           intensification, adaptation and simplification on pastures, milk
           production and profitability
    • Authors: Matthew T. Harrison; Brendan R. Cullen; Dan Armstrong
      Pages: 19 - 32
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Matthew T. Harrison, Brendan R. Cullen, Dan Armstrong
      There are few holistic analyses of agricultural systems that inclusively consider how the combination of gradual climate change and increased frequencies of extreme climatic events influence biophysical variables as well as economic returns. Here we examine how climate change to 2040 influences pasture growth rates, grazed pasture harvested (PH) and profitability of three case study (baseline) farms in southern Australia. We applied ‘development options’ (or adaptations) to baseline farms in each region that either intensified, simplified or modified the seasonal distribution of feed supply (Intensify, Simplify or Adapt, respectively) by manipulating several components of the farm system simultaneously, including herd size, liveweight and farm assets. In general, climate change reduced annual pasture produced. On dryland farms, hotter, drier conditions reduced growing durations through later autumn breaks and earlier finishes to spring growth, although winter growth rates were enhanced. On irrigated farms, the magnitude and inter-annual variability of PH was less influenced by climate change. Overall, climate change reduced milk production and income, and increased costs due to additional fodder conservation and more purchased feed. Current climate variability caused far greater inter-annual variation in PH and profit compared with the long-term impacts of climate change. This suggests that farm outcomes may be improved by tactically managing for short-term climatic variability, rather than by making long-term strategic changes in preparation for climate change. Future work on adapting dairy businesses to climate change should examine development options that help maintain or extend growing season length and/or harness the additional winter growth. Our study indicates that climate change impacts on dairy systems will be regionally-specific; no individual development option was universally effective in reducing pasture losses to climate change across regions and development options, and no option consistently increased or decreased PH across sites. Future adaptation strategies should thus take into account not only local climate variability as well as climate change, but also the existing farming systems already operating at each site.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.003
      Issue No: Vol. 155 (2017)
  • Environmental footprint of the integrated France–Italy beef production
           system assessed through a multi-indicator approach
    • Authors: Marco Berton; Jacques Agabriel; Luigi Gallo; Michel Lherm; Maurizio Ramanzin; Enrico Sturaro
      Pages: 33 - 42
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Marco Berton, Jacques Agabriel, Luigi Gallo, Michel Lherm, Maurizio Ramanzin, Enrico Sturaro
      This study aims to evaluate the environmental footprint of the integrated France–Italy beef production system (extensive grassland-based suckler cow-calf farms in France with intensive cereal-based fattening farms in northeastern Italy) using a multi-indicator approach, which combines environmental impact categories computed with a cradle-to-farm gate Life Cycle Assessment, and food-related indicators based on the conversion of gross energy and protein of feedstuffs into raw boneless beef. The system boundaries were set from the calves' birth to their sale to the slaughterhouse, including the herd management, on- and off-farm feed production and materials used on the farms. One kilogram of body weight (BW) sold was used as the functional unit. The study involved 73 Charolais batches (i.e., a group of animals homogenous for age, finishing period and fattening farm), kept at 14 Italian farms. Data from 40 farms originating from the Charolais Network database (INRA) were used to characterize the French farm types, which were matched to the fattening batches according to the results of a cluster analysis. The impact categories assessed were as follows (mean±SD per kg BW): global warming potential (GWP, 13.0±0.7kg CO2-eq, reduced to 9.9±0.7kg CO2-eq when considering the carbon sequestration due to French suckler cow-calf system permanent grassland), acidification potential (AP, 193±13g SO2-eq), eutrophication potential (EP, 57±4g PO4-eq), cumulative energy demand (CED, 36±5MJ), and land occupation (LO, 18.7±0.8m2/year). The on-farm impacts outweighed those of the off-farm activities, except in the case of CED. On average, 41MJ and 16.7kg of dietary feed gross energy and protein were required to provide 1MJ or 1kg of protein of raw boneless beef, respectively, but nearly 85% and 80%, respectively, were derived from feedstuffs not suitable for human consumption. Emission-related (GWP, AP, EP) and resource utilization categories (CED, LO) were positively correlated. Food-related indicators showed positive correlations with emission-related indicators when the overall feedstuffs of the diet were considered but negative correlations when only the potentially human-edible portions of the beef diets were considered. In conclusion, the integration of the pasture-based France suckler cow-calf system with the cereal-based Italian fattening farms allows for the exploitation of the resources available, increasing the share of non-human-edible feedstuffs while maintaining good livestock productive efficiency. Combining indicators of impact categories with indicators of feed net supply may improve the assessment of the environmental footprint of livestock systems.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.005
      Issue No: Vol. 155 (2017)
  • Yield gap analyses to estimate attainable bovine milk yields and evaluate
           options to increase production in Ethiopia and India
    • Authors: Dianne Mayberry; Andrew Ash; Di Prestwidge; Cécile M. Godde; Ben Henderson; Alan Duncan; Michael Blummel; Y. Ramana Reddy; Mario Herrero
      Pages: 43 - 51
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Dianne Mayberry, Andrew Ash, Di Prestwidge, Cécile M. Godde, Ben Henderson, Alan Duncan, Michael Blummel, Y. Ramana Reddy, Mario Herrero
      Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields.

      PubDate: 2017-04-26T00:01:49Z
      DOI: 10.1016/j.agsy.2017.04.007
      Issue No: Vol. 155 (2017)
  • Adoption of agroforestry and the impact on household food security among
           farmers in Malawi
    • Authors: Jeanne Y. Coulibaly; Brian Chiputwa; Tebila Nakelse; Godfrey Kundhlande
      Pages: 52 - 69
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Jeanne Y. Coulibaly, Brian Chiputwa, Tebila Nakelse, Godfrey Kundhlande
      Agroforestry is increasingly regarded as an important adaptation and mitigation strategy against climate change. In particular, the use of fertilizer trees has been promoted as a practice that contributes to improved soil fertility through nitrogen fixation, by increasing supply of nutrients for crop production. While a lot of the evidence on the impact of fertilizer trees relies on on-farm experiments and correlational analysis, there is a paucity of rigorous evidence under actual smallholder farming conditions. This paper analyzes the impacts of adopting fertilizer trees such as Gliricidia sepium and Faidherbia albida on household food security. We draw on survey data of 338 farmers in Malawi and use an endogenous switching regression to rigorously analyze adoption impacts. Econometric results show that use of fertilizer tree adoption increases the value of food crops by 35%. Disaggregation of the impacts through stratification by land ownership further reveal that farmers with smaller farms of up to 2 acres realize the highest gains. Furthermore, fertilizer tree use in conjunction with improved maize seed also significantly increased value of food crops. This study offers preliminary insights that contribute to an emerging field of research on quantitative assessment of agricultural interventions such as agroforestry practices using novel analytical approaches. We provide some policy insights and recommend the need for future research to be designed around development initiatives that consider fine-scale variation in social, economic and ecological context of farmers to improve uptake and adaptation to realize the full potential of agroforestry in improving soil fertility and household food security.

      PubDate: 2017-05-03T00:18:45Z
      DOI: 10.1016/j.agsy.2017.03.017
      Issue No: Vol. 155 (2017)
  • Accurate crop yield predictions from modelling tree-crop interactions in
           gliricidia-maize agroforestry
    • Authors: Philip J. Smethurst; Neil I. Huth; Patricia Masikati; Gudeta W. Sileshi; Festus K. Akinnifesi; Julia Wilson; Fergus Sinclair
      Pages: 70 - 77
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Philip J. Smethurst, Neil I. Huth, Patricia Masikati, Gudeta W. Sileshi, Festus K. Akinnifesi, Julia Wilson, Fergus Sinclair
      Agroforestry systems, containing mixtures of trees and crops, are often promoted because the net effect of interactions between woody and herbaceous components is thought to be positive if evaluated over the long term. From a modelling perspective, agroforestry has received much less attention than monocultures. However, for the potential of agroforestry to impact food security in Africa to be fully evaluated, models are required that accurately predict crop yields in the presence of trees. The positive effects of the fertiliser tree gliricidia (Gliricidia sepium) on maize (Zea mays) are well documented and use of this tree-crop combination to increase crop production is expanding in several African countries. Simulation of gliricidia-maize interactions can complement field trials by predicting crop response across a broader range of contexts than can be achieved by experimentation alone. We tested a model developed within the APSIM framework. APSIM models are widely used for one dimensional (1D), process-based simulation of crops such as maize and wheat in monoculture. The Next Generation version of APSIM was used here to test a 2D agroforestry model where maize growth and yield varied spatially in response to interactions with gliricidia. The simulations were done using data for gliricidia-maize interactions over two years (short-term) in Kenya and 11years (long-term) in Malawi, with differing proportions of trees and crops and contrasting management. Predictions were compared with observations for maize grain yield, and soil water content. Simulations in Kenya were in agreement with observed yields reflecting lower observed maize germination in rows close to gliricidia. Soil water content was also adequately simulated, except for a tendency for slower simulated drying of the soil profile each season. Simulated maize yields in Malawi were also in agreement with observations. Trends in soil carbon over a decade were similar to those measured, but could not be statistically evaluated. These results show that the agroforestry model in APSIM Next Generation adequately represented tree-crop interactions in these two contrasting agro-ecological conditions and agroforestry practices. Further testing of the model is warranted to explore tree-crop interactions under a wider range of environmental conditions.

      PubDate: 2017-05-08T00:24:36Z
      DOI: 10.1016/j.agsy.2017.04.008
      Issue No: Vol. 155 (2017)
  • Contribution of dung beetles to cattle productivity in the tropics: A
           stochastic-dynamic modeling approach
    • Authors: Jose Lopez-Collado; Magdalena Cruz-Rosales; Julio Vilaboa-Arroniz; Imelda Martínez-Morales; Hector Gonzalez-Hernandez
      Pages: 78 - 87
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Jose Lopez-Collado, Magdalena Cruz-Rosales, Julio Vilaboa-Arroniz, Imelda Martínez-Morales, Hector Gonzalez-Hernandez
      Dung beetles provide different services to agroecosystems. Previous economic assessment of this insect group highlights their importance in temperate zones using linear models or ecosystem services frameworks. This paper proposes a stochastic-dynamic model to simulate dung production and degradation in order to estimate the contribution of dung beetles to dual-purpose cattle production in the tropical grasslands of Veracruz, Mexico. The model allowed for estimation of sampling distributions of dung occurrence in the field, the coverage area, nitrogen burial, and maintenance of clean grasslands and their economic benefits. Contributions of dung beetles are expressed as 95% confidence intervals. Dung beetles removed from 56.2 to 116.9depositionsha−1 d−1 and the efficiency in dung removal was between 65 to 69%. At the grassland scale, dung beetles cleaned an area from 8.5 to 26.9m2 ha−1 d−1. Nitrogen burial ranged from 32.2 to 136.2kgha−1 y−1. The clean area maintained annually varied between 31 to 98% of the pastures. The annual benefit per animal unit ranged between US$149.1 to US$ 423.6 and at state level the benefit (US$×10E6) was between 140.6 and 455.8. The most important economic contribution was maintaining clean areas (71.4%), then by incorporating nitrogen as fertilizer (28.3%), and last in milk and meat benefits (<1%). The model allowed for the representation of the natural variability of some key factors involved in dung processing by beetles related to dual-purpose cattle production.
      Graphical abstract image

      PubDate: 2017-05-08T00:24:36Z
      DOI: 10.1016/j.agsy.2017.05.001
      Issue No: Vol. 155 (2017)
  • Towards a complexity-aware theory of change for participatory research
           programs working within agricultural innovation systems
    • Authors: Boru Douthwaite; Elizabeth Hoffecker
      Pages: 88 - 102
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Boru Douthwaite, Elizabeth Hoffecker
      Agricultural innovation systems (AIS) are increasingly recognized as complex adaptive systems in which interventions cannot be expected to create predictable, linear impacts. Nevertheless, the logic models and theory of change (ToC) used by standard-setting international agricultural research agencies and donors assume that agricultural research will create impact through a predictable linear adoption pathway which largely ignores the complexity dynamics of AIS, and which misses important alternate pathways through which agricultural research can improve system performance and generate sustainable development impact. Despite a growing body of literature calling for more dynamic, flexible and “complexity-aware” approaches to monitoring and evaluation, few concrete examples exist of ToC that takes complexity dynamics within AIS into account, or provide guidance on how such theories could be developed. This paper addresses this gap by presenting an example of how an empirically-grounded, complexity-aware ToC can be developed and what such a model might look like in the context of a particular type of program intervention. Two detailed case studies are presented from an agricultural research program which was explicitly seeking to work in a “complexity-aware” way within aquatic agricultural systems in Zambia and the Philippines. Through an analysis of the outcomes of these interventions, the pathways through which they began to produce impacts, and the causal factors at play, we derive a “complexity-aware” ToC to model how the cases worked. This middle-range model, as well as an overarching model that we derive from it, offer an alternate narrative of how development change can be produced in agricultural systems, one which aligns with insights from complexity science and which, we argue, more closely represents the ways in which many research for development interventions work in practice. The nested ToC offers a starting point for asking a different set of evaluation and research questions which may be more relevant to participatory research efforts working from within a complexity-aware, agricultural innovation systems perspective.

      PubDate: 2017-05-13T08:12:18Z
      DOI: 10.1016/j.agsy.2017.04.002
      Issue No: Vol. 155 (2017)
  • Bio-economic evaluation of cropping systems for saline coastal Bangladesh:
           II. Economic viability in historical and future environments
    • Authors: Jahangir Kabir; Rob Cramb; Donald S. Gaydon; Christian H. Roth
      Pages: 103 - 115
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Jahangir Kabir, Rob Cramb, Donald S. Gaydon, Christian H. Roth
      The objective of this study was to assess the impacts of climate change and salinity on the economic viability of rice-based cropping systems under farmers' current management across current and future climate and salinity scenarios in south-west coastal Bangladesh. Detailed case studies were conducted in two contrasting coastal villages in Dacope Sub-district, Khulna District. Enterprise budgets were developed using APSIM-simulated and extrapolated yields together with crop management, cost, and price data obtained from the villages and estimated from various sources. The projected impact of climate change and salinization on the economic viability (profitability and riskiness) of most cropping systems was not pronounced. Thus rice-based cropping systems are likely to remain viable in both optimistic and pessimistic climate scenarios in coming decades, even allowing for salinization, because some of the positive effects of climate change were projected to offset the sizeable losses due to salinity. Moreover, where small yield declines were projected these were often offset by higher future prices. Sustainably-managed rice/shrimp cropping systems are likely to remain the most profitable option in locations with access to tidal saline water. In other sites, given adequate freshwater for irrigation in the dry season, rice/non-rice cropping systems were projected to be the most viable options, especially incorporating newer crops such as sunflower and maize. Dry-season rice and wheat were not projected to be viable options.

      PubDate: 2017-05-13T08:12:18Z
      DOI: 10.1016/j.agsy.2017.05.002
      Issue No: Vol. 155 (2017)
  • Irrigated agricultural development in northern Australia: Value-chain
           challenges and opportunities
    • Authors: Andrew Ash; Trish Gleeson; Murray Hall; Andrew Higgins; Garry Hopwood; Neil MacLeod; Dean Paini; Perry Poulton; Di Prestwidge; Tony Webster; Peter Wilson
      Pages: 116 - 125
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Andrew Ash, Trish Gleeson, Murray Hall, Andrew Higgins, Garry Hopwood, Neil MacLeod, Dean Paini, Perry Poulton, Di Prestwidge, Tony Webster, Peter Wilson
      There is renewed interest in expanded agricultural development in northern Australia supported by increasing global demand for food, the region's proximity to Asian markets, and the current government policy initiatives to support economically sustainable and vibrant rural and regional communities. The production potential, financial returns, and the supply chain implications for irrigated agriculture were assessed in four different regions across northern Australia to provide a systems analysis of development opportunities and challenges. Gross margins for high volume, low value broadacre crops were mostly either negative or weakly positive, principally due to high transport costs to established markets in southern and eastern Australia. The returns were largely positive for higher value horticultural and specialist niche crops or industrial crops with local processing facilities. Scenarios incorporating alternative transport routes to Asia provided modest cost savings, but required assumptions for suitable shipping routes and cost-effective availability of containers, but did not significantly boost gross margins. When scaled to whole irrigation areas, the regional gross value of production could be significant but improving returns at farm scale requires more cost-effective supply chains. The ability to generate sufficient returns on capital investment was strongly influenced by the sequence of years associated with climatic variability and/or other unexpected shocks experienced in the years immediately following investment. The analysis highlighted that each component of the system – climate, soils, water, agronomic practice, pests and diseases, farm operations, management, planning, supply chains, infrastructure, labour, services, markets – needs to be understood but ultimate success will depend on managing the complexity of the whole farming system and value-chain. Further, scaling up development at a considered pace and being prepared for considerable lags before positive returns on investment are achieved will be critical for successful long-term irrigated agricultural ventures in northern Australia.

      PubDate: 2017-05-13T08:12:18Z
      DOI: 10.1016/j.agsy.2017.04.010
      Issue No: Vol. 155 (2017)
  • Impact of roughage-concentrate ratio on the water footprints of beef
    • Authors: Julio Cesar Pascale Palhares; Marcela Morelli; Ciniro Costa Junior
      Pages: 126 - 135
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Julio Cesar Pascale Palhares, Marcela Morelli, Ciniro Costa Junior
      The aim of this study was to determine the water footprint of beef feedlots up to the farm gate and evaluate the impact of roughage-concentrate ratio on the green water footprint. The study purpose was to provide strategic insights about nutritional management and water used that have a positive impact reducing water demand and increasing water efficiency. A regional bottom-up approach of the beef feedlot production was applied and water footprint methodology was used as the primary method. We included green and blue volumetric water footprint. Sensitivity assessment was done to explore differences in agricultural performance. Total water footprint ranged from 1935 to 9673m3 kg−1 of meat. The results are demonstrating the variability in water footprint that can exist from farm to farm. Green water represented on average 84.5% and blue water 15.4% of the footprint value. The farms with larger amounts of concentrate in the diet had high footprint values and the differences in feed composition have a significant effect on the water footprint. The average water footprint of the current crop yield was 5814Lkg−1 of meat. With a reduction of 25% in the current crop yields, it was 7.416Lkg−1 of meat and with an increase of 25% in the current crop yields, 4677Lkg−1 of meat. These results show that increasing agricultural productivity has positive impacts on reducing the water footprint. The results show that the water footprint values of feedlots are determined largely by the type of animal diet and by performance indicators of the animals. The roughage-concentrate ratio and type of roughage are the nutritional aspects that most significantly influence the footprint values. This study supports the recommendation that beef feedlots should place emphasis on maximizing the use of roughage, because this could decrease the pressure on fresh water resources.

      PubDate: 2017-05-13T08:12:18Z
      DOI: 10.1016/j.agsy.2017.04.009
      Issue No: Vol. 155 (2017)
  • Social and ecological analysis of commercial integrated crop livestock
           systems: Current knowledge and remaining uncertainty
    • Authors: R.D. Garrett; M.T. Niles; J.D.B. Gil; A. Gaudin; R. Chaplin-Kramer; A. Assmann; T.S. Assmann; K. Brewer; P.C. de Faccio Carvalho; O. Cortner; R. Dynes; K. Garbach; E. Kebreab; N. Mueller; C. Peterson; J.C. Reis; V. Snow; J. Valentim
      Pages: 136 - 146
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): R.D. Garrett, M.T. Niles, J.D.B. Gil, A. Gaudin, R. Chaplin-Kramer, A. Assmann, T.S. Assmann, K. Brewer, P.C. de Faccio Carvalho, O. Cortner, R. Dynes, K. Garbach, E. Kebreab, N. Mueller, C. Peterson, J.C. Reis, V. Snow, J. Valentim
      Crops and livestock play a synergistic role in global food production and farmer livelihoods. Increasingly, however, crops and livestock are produced in isolation, particularly in farms operating at the commercial scale. It has been suggested that re-integrating crop and livestock systems at the field and farm level could help reduce the pollution associated with modern agricultural production and increase yields. Despite this potential, there has been no systematic review to assess remaining knowledge gaps in both the social and ecological dimensions of integrated crop and livestock systems (ICLS), particularly within commercial agricultural systems. Based on a multi-disciplinary workshop of international experts and additional literature review, we assess the current knowledge and remaining uncertainties about large-scale, commercial ICLS and identify the source of remaining knowledge gaps to establish priorities for future research. We find that much is understood about nutrient flows, soil quality, crop performance, and animal weight gain in commercial ICLS, but there is little knowledge about its spatial extent, animal behavior or welfare in ICLS, or the tradeoffs between biodiversity, pest and disease control, greenhouse gas (GHG) mitigation, and drought and heat tolerance in ICLS. There is some evidence regarding the economic outcomes in commercial ICLS and supply chain and policy barriers to adoption, but little understanding of broader social outcomes or cultural factors influencing adoption. Many of these knowledge gaps arise from a basic lack of data at both the field and system scales, which undermines both statistical analysis and modeling efforts. Future priorities for the international community of researchers investigating the tradeoffs and scalability of ICLS include: methods standardization to better facilitate international collaborations and comparisons, continued social organization for better data utilization and collaboration, meta-analyses to answer key questions from existing data, the establishment of long term experiments and surveys in key regions, a portal for citizen science, and more engagement with ICLS farmers.

      PubDate: 2017-05-23T08:31:59Z
      DOI: 10.1016/j.agsy.2017.05.003
      Issue No: Vol. 155 (2017)
  • Greenhouse gas abatement on southern Australian grains farms: Biophysical
           potential and financial impacts
    • Authors: Elizabeth A. Meier; Peter J. Thorburn; Marit E. Kragt; Nikki P. Dumbrell; Jody S. Biggs; Frances C. Hoyle; Harm van Rees
      Pages: 147 - 157
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Elizabeth A. Meier, Peter J. Thorburn, Marit E. Kragt, Nikki P. Dumbrell, Jody S. Biggs, Frances C. Hoyle, Harm van Rees
      The agricultural sector generates a substantial proportion of global greenhouse gas (GHG) emissions through emissions of carbon dioxide (CO2) and nitrous oxide (N2O). Changes to agricultural practices can provide GHG abatement by maintaining or increasing soil organic carbon (SOC) stored in soils or vegetation, or by decreasing N2O emissions. However, it can be difficult to identify practices that achieve net abatement because practices that increase SOC stocks may also increase N2O emissions from the soil. This study simulated the net on-farm GHG abatement and gross margins for a range of management scenarios on two grain farms from the western and southern grain growing regions of Australia using the Agricultural Production Systems sIMulator (APSIM) model. The soils and practices selected for the study were typical of these regions. Increased cropping intensity consistently provided emissions reductions for all site-soil combinations. The practice of replacing uncropped or unmanaged pasture fallows with a winter legume crop was the only one of nine scenarios to decrease GHG emissions and increase gross margins relative to baseline practice at both locations over the 100-year simulation period. The greatest abatement was obtained by combining this practice with an additional summer legume crop grown for a short period as green manure. However, adding the summer legume decreased farm gross margins because the summer crop used soil moisture otherwise available to the following cash crop, thus reducing yield and revenue. Annual N2O emissions from the soil were an order of magnitude lower from sandy-well-drained soils at the Western Australian location (Dalwallinu) than at the other location (Wimmera) with clay soil, highlighting the importance of interactions between climate and soil properties in determining appropriate GHG abatement practices. Thus, greatest abatement at Dalwallinu was obtained from maintaining or increasing SOC, but managing both N2O emissions and SOC storage were important for providing abatement at Wimmera.

      PubDate: 2017-05-23T08:31:59Z
      DOI: 10.1016/j.agsy.2017.04.012
      Issue No: Vol. 155 (2017)
  • Assessing the potential economic benefits to farmers from various GM crops
           becoming available in the European Union by 2025: Results from an expert
    • Authors: P.J. Jones; I.D. McFarlane; J.R. Park; R.B. Tranter
      Pages: 158 - 167
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): P.J. Jones, I.D. McFarlane, J.R. Park, R.B. Tranter
      This paper reports on a study that identified a range of crop-trait combinations that are: agronomically suited to the EU; provide advantages to arable farmers and consumers; and are either already available in international markets, or advancing along the development pipeline and likely to become available by 2025. An expert stakeholder panel was recruited and asked for their views, using the Delphi approach, on the impact of these crop-traits on enterprise competitiveness, through changes to yields, production costs and product prices. In terms of input traits, there was consensus that traits such as herbicide tolerant/insect resistant (HT/IR) maize, HT sugar beet and HT soya bean would provide positive benefits for farmers. Output-side traits such as winter-sown rape with reduced saturated fats, were seen as offering benefits to consumers, but were either likely to be restricted to niche markets, or offer relatively modest price premia to farmers growing them. Our analysis of the financial impact of the adoption of GM crops more widely in the EU, showed that the competitiveness of the agricultural sector could well be improved by this. However, such improvements would be relatively small-scale in that large-scale national natural advantages from either economic or environmental conditions is unlikely to be overturned.

      PubDate: 2017-05-23T08:31:59Z
      DOI: 10.1016/j.agsy.2017.05.005
      Issue No: Vol. 155 (2017)
  • Impacts of farmers' management styles on income and labour under
           alternative extensive land use scenarios
    • Authors: Claire Morgan-Davies; Ron Wilson; Tony Waterhouse
      Pages: 168 - 178
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Claire Morgan-Davies, Ron Wilson, Tony Waterhouse
      High Nature Value farming systems cover a large proportion of the agricultural land in marginal and mountain areas of Europe. These large areas face environmental, economic and social challenges and formulating policies that support all these aspects is difficult. Although farmers play an important role in maintaining the ecological diversity of these areas, their differing management styles are often not recognised when land use policies are formulated. This paper examines these issues using an optimisation model based on an extensive livestock farm in Western Scotland, where four farmers' management styles are combined with a series of six alternative future land use scenarios, to provide a more realistic and robust insight of policy impacts on land use and habitat, labour and farm income. The management styles derived from a typology that was based on a composite of both available resources and attitudinal components. The six alternative scenarios encompassed competitive land use diversification options (woodland and wild deer shooting), abandonment of native pasture for agriculture, no support, high market prices for livestock products, and increased animal efficiency. Although diversification via forestry was found to be potentially central to increasing farming incomes, farmers' reticence to adopt forestry or any diversification was a major constraint. This case study also reinforced that managing livestock on these HNV farming systems was not economical unless support subsidies were in place. The only scenario which could enhance the HNV biodiversity value on farms was one with high market prices, resulting in the most varied land use (sheep, cattle and forestry). All others scenarios meant an increase in afforestation (which displaced livestock), an increase in livestock grazing or abandonment of the land, none of which would maintain biodiversity in these areas. Very few scenarios were able to increase on-farm labour demand and although greater flexibility in farm labour was found to be essential, labour scarcity in these marginal mountain areas remained a problem. In conclusion, this case study reinforced that farmers' management style and motivation do play a major role on how they respond to policies, and unless this role is acknowledged by policy-makers, these European HNV areas may not be targeted properly for the most desired outcomes and sustainability.

      PubDate: 2017-05-28T08:44:57Z
      DOI: 10.1016/j.agsy.2017.04.011
      Issue No: Vol. 155 (2017)
  • Next generation agricultural system data, models and knowledge products:
    • Authors: John M. Antle; James W. Jones; Cynthia E. Rosenzweig
      Pages: 186 - 190
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): John M. Antle, James W. Jones, Cynthia E. Rosenzweig
      Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30–40years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a “NextGen” study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.003
  • Next generation data systems and knowledge products to support
           agricultural producers and science-based policy decision making
    • Authors: Susan M. Capalbo; John M. Antle; Clark Seavert
      Pages: 191 - 199
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Susan M. Capalbo, John M. Antle, Clark Seavert
      Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. We describe two analytical tools - AgBiz Logic and TOA-MD - that demonstrate the current capability of farmlevel and landscape-scale models. The use of these tools is explored with a case study of an oilseed crop, Camelina sativa, which could be used to produce jet aviation fuel. We conclude with a discussion of innovations needed to facilitate the use of farm and policy-level models to generate data and analysis for improved knowledge products.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.10.009
  • Towards a new generation of agricultural system data, models and knowledge
           products: Information and communication technology
    • Authors: Sander J.C. Janssen; Cheryl H. Porter; Andrew D. Moore; Ioannis N. Athanasiadis; Ian Foster; James W. Jones; John M. Antle
      Pages: 200 - 212
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): Sander J.C. Janssen, Cheryl H. Porter, Andrew D. Moore, Ioannis N. Athanasiadis, Ian Foster, James W. Jones, John M. Antle
      Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.017
  • Modelling the impacts of pests and diseases on agricultural systems
    • Authors: M. Donatelli; R.D. Magarey; S. Bregaglio; L. Willocquet; J.P.M. Whish; S. Savary
      Pages: 213 - 224
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): M. Donatelli, R.D. Magarey, S. Bregaglio, L. Willocquet, J.P.M. Whish, S. Savary
      The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Key research questions not only involve the assessment of the potential effects of climate change on known pathosystems, but also on new pathogens which could alter the (still incompletely documented) impacts of pests and diseases on agricultural systems. Yield loss data collected in various current environments may no longer represent a adequate reference to develop tactical, decision-oriented, models for plant diseases and pests and their impacts, because of the ongoing changes in climate patterns. Process-based agricultural simulation modelling, on the other hand, appears to represent a viable methodology to estimate the impacts of these potential effects. A new generation of tools based on state-of-the-art knowledge and technologies is needed to allow systems analysis including key processes and their dynamics over appropriate suitable range of environmental variables. This paper offers a brief overview of the current state of development in coupling pest and disease models to crop models, and discusses technical and scientific challenges. We propose a five-stage roadmap to improve the simulation of the impacts caused by plant diseases and pests; i) improve the quality and availability of data for model inputs; ii) improve the quality and availability of data for model evaluation; iii) improve the integration with crop models; iv) improve the processes for model evaluation; and v) develop a community of plant pest and disease modelers.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2017.01.019
  • Next generation crop models: A modular approach to model early vegetative
           and reproductive development of the common bean (Phaseolus vulgaris L)
    • Authors: C. Hwang; M.J. Correll; S.A. Gezan; L. Zhang; M.S. Bhakta; C.E. Vallejos; K.J. Boote; J.A. Clavijo-Michelangeli; J.W. Jones
      Pages: 225 - 239
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): C. Hwang, M.J. Correll, S.A. Gezan, L. Zhang, M.S. Bhakta, C.E. Vallejos, K.J. Boote, J.A. Clavijo-Michelangeli, J.W. Jones
      The next generation of gene-based crop models offers the potential of predicting crop vegetative and reproductive development based on genotype and weather data as inputs. Here, we illustrate an approach for developing a dynamic modular gene-based model to simulate changes in main stem node numbers, time to first anthesis, and final node number on the main stem of common bean (Phaseolus vulgaris L.). In the modules, these crop characteristics are functions of relevant genes (quantitative trait loci (QTL)), the environment (E), and QTL×E interactions. The model was based on data from 187 recombinant inbred (RI) genotypes and the two parents grown at five sites (Citra, FL; Palmira, Colombia; Popayan, Colombia; Isabela Puerto Rico; and Prosper, North Dakota). The model consists of three dynamic QTL effect models for node addition rate (NAR, No. d−1), daily rate of progress from emergence toward flowering (RF), and daily maximum main stem node number (MSNODmax), that were integrated to simulate main stem node number vs. time, and date of first flower using daily time steps. Model evaluation with genotypes not used in model development showed reliable predictions across all sites for time to first anthesis (R2 =0.75) and main stem node numbers during the linear phase of node addition (R2 =0.93), while prediction of the final main stem node number was less reliable (R2 =0.27). The use of mixed-effects models to analyze multi-environment data from a wide range of genotypes holds considerable promise for assisting development of dynamic QTL effect models capable of simulating vegetative and reproductive development.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.10.010
  • Brief history of agricultural systems modeling
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 240 - 254
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): James W. Jones, John M. Antle, Bruno Basso, Kenneth J. Boote, Richard T. Conant, Ian Foster, H. Charles J. Godfray, Mario Herrero, Richard E. Howitt, Sander Janssen, Brian A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler
      Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the “next generation” models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.05.014
  • Towards a new generation of agricultural system data, models and knowledge
           products: Design and improvement
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 269 - 288
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): John M Antle, Bruno Basso, Richard T Conant, H Charles J Godfray, James W Jones, Mario Herrero, Richard E Howitt, Brian A Keating, Rafael Munoz-Carpena, Cynthia Rosenzweig, Pablo Tittonell, Tim R Wheeler
      This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a “pre-competitive” space for model development to a “competitive space” for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.021
  • Toward a new generation of agricultural system data, models, and knowledge
           products: State of agricultural systems science
    • Authors: James W. Jones; John M. Antle; Bruno Basso; Kenneth J. Boote; Richard T. Conant; Ian Foster; H. Charles J. Godfray; Mario Herrero; Richard E. Howitt; Sander Janssen; Brian A. Keating; Rafael Munoz-Carpena; Cheryl H. Porter; Cynthia Rosenzweig; Tim R. Wheeler
      Pages: 269 - 288
      Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155
      Author(s): James W. Jones, John M. Antle, Bruno Basso, Kenneth J. Boote, Richard T. Conant, Ian Foster, H. Charles J. Godfray, Mario Herrero, Richard E. Howitt, Sander Janssen, Brian A. Keating, Rafael Munoz-Carpena, Cheryl H. Porter, Cynthia Rosenzweig, Tim R. Wheeler
      We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

      PubDate: 2017-06-22T08:35:16Z
      DOI: 10.1016/j.agsy.2016.09.021
  • Farm types and farmer motivations to adapt: Implications for design of
           sustainable agricultural interventions in the rubber plantations of South
           West China
    • Authors: James Hammond; Mark T. van Wijk; Alex Smajgl; John Ward; Tim Pagella; Jianchu Xu; Yufang Su; Zhuangfang Yi; Rhett D. Harrison
      Pages: 1 - 12
      Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154
      Author(s): James Hammond, Mark T. van Wijk, Alex Smajgl, John Ward, Tim Pagella, Jianchu Xu, Yufang Su, Zhuangfang Yi, Rhett D. Harrison
      Tropical land use is one of the leading causes of global environmental change. Sustainable agricultural development aims to reduce the negative environmental impacts of tropical land use whilst enhancing the well-being of the smallholder farmers residing in those areas. Interventions with this goal are typically designed by scientists educated in the Western tradition, and often achieve lower than desired uptake by smallholder farmers. We build on work done in farm type classification and studies of factors that influence adaptation, trialling a suite of household survey questions to elucidate the motivational factors that influence a farmer's willingness to adapt to external change. Based on a sample of 1015 households in the rubber growing region of Xishuangbanna, South-west China, we found that farm types based on structural characteristics (e.g. crops, livelihoods) could not be used to accurately predict farmers' motivations to adapt. Amongst all six farm types identified, the full range of motivational typologies was found. We found six motivational types, from most to least likely to adapt, named: Aspirational Innovators, Conscientious, Copy Cats, Incentive-centric, Well Settled, and Change Resistant. These groups roughly corresponded with those identified in literature regarding diffusion of innovations, but such classifications are rarely used in development literature. We predict that only one third of the population would be potentially willing to trial a new intervention, and recommend that those sectors of the population should be identified and preferentially targeted by development programs. Such an approach requires validation that these motivational typologies accurately predict real behaviour – perhaps through a panel survey approach. Dedicated data gathering is required, beyond what is usually carried out for ex-ante farm typologies, but with some refinements of the methodology presented here the process need not be onerous. An improved suite of questions to appraise farmers' motivations might include value orientations, life satisfaction, and responses to various scenarios, all phrased to be locally appropriate, with a scoring system that uses the full range of potential scores and a minimum of follow up and peripheral questions.

      PubDate: 2017-03-04T05:50:03Z
      DOI: 10.1016/j.agsy.2017.02.009
  • Prioritizing investments for climate-smart agriculture: Lessons learned
           from Mali
    • Authors: N. Andrieu; B. Sogoba; R. Zougmore; F. Howland; O. Samake; O. Bonilla-Findji; M. Lizarazo; A. Nowak; C. Dembele; C. Corner-Dolloff
      Pages: 13 - 24
      Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154
      Author(s): N. Andrieu, B. Sogoba, R. Zougmore, F. Howland, O. Samake, O. Bonilla-Findji, M. Lizarazo, A. Nowak, C. Dembele, C. Corner-Dolloff
      Agricultural productivity and growth in Mali are under threat from erratic rainfall, resulting in more frequent dry years. The national economy is vulnerable to climate change due to 50% of the gross domestic product coming from the agricultural sector and 75% of the population living in rural areas. The Climate-Smart Agriculture (CSA) concept arises from a need to provide innovative solutions towards the complex and integrated goals of increasing yields, improving resilience, and promoting a low emissions agricultural sector. A major challenge for policymakers to operationalize CSA is the identification, valuation (cost-benefit), and subsequent prioritization of climate-smart options and portfolios (groups of CSA options) for investment. This paper presents the process, results, and lessons learned from a yearlong pilot of the Climate-Smart Agriculture Prioritization Framework (CSA-PF) in Mali. Key national and international stakeholders participated in the co-development and prioritization of two CSA portfolios and related action plans for the Malian Sudanese zone. Initial steps towards outcomes of the process include inclusion of prioritized CSA practices in ongoing development projects and prompting discussion of modifications of future calls for agricultural development proposals by regional donors.

      PubDate: 2017-03-09T13:17:04Z
      DOI: 10.1016/j.agsy.2017.02.008
  • Diversity of high-latitude agricultural landscapes and crop rotations:
           Increased, decreased or back and forth?
    • Authors: Pirjo Peltonen-Sainio; Lauri Jauhiainen; Jaana Sorvali
      Pages: 25 - 33
      Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154
      Author(s): Pirjo Peltonen-Sainio, Lauri Jauhiainen, Jaana Sorvali
      Land use change is a continuously on-going process that has many impacts on the environmental footprint of agriculture and especially on the biodiversity of agricultural landscapes. This study used field scale data from 1995 to 2011 (165,760 field parcels) on a study region that represents the prime crop production area of Finland, to assess how agricultural land use has changed since the launching of the EU Common Agricultural Policy. Six five-year crop rotation types were identified: cereal species monoculture, cereal monoculture, rotation with a break-crop, diverse crop rotation, perennial, non-permanent grassland rotation and environmental fallow rotation. Shifts in the frequencies of different crop rotation types and composition of their crop species were monitored. Furthermore, the contribution of different field characteristics, on a farmer's land allocation to different rotation types, was assessed. The ultimate goal was to understand whether land use changes, in general, have contributed to any increase in heterogeneity of landscapes and whether they have impacted diversity of crop rotation types. We found that different crop rotation types were applied on a farm, but that farmers have quite consistent drivers for land allocation to different rotation types; although, economic incentives influence the introduction, expansion and/or withdrawal of crops from rotations. The farmers' readiness to implement land use changes was dependent on farm size. There has been a shift towards lower shares of cereal species monocultures, grassland rotations and diverse crop rotations, while environmental fallow rotations have increased. According to the five-year rotation plans shared by 16 interviewed farmers, there was a noted desire for more diverse rotation types originating from adverse experiences with cereal monocultures and soil degradation; however, they were keen on reducing the number of environmental fallows and concentrating on food production. It is important to carry out follow-up studies to understand the impacts of the demonstrated and anticipated land use changes on biodiversity. Future policy development should benefit from a gained understanding of the drivers of farmers' decisions for facilitating unimpeded implementation.

      PubDate: 2017-03-09T13:17:04Z
      DOI: 10.1016/j.agsy.2017.02.011
  • On-farm compliance costs and N surplus reduction of mixed dairy farms
           under grassland-based feeding systems
    • Authors: Gabriele Mack; Robert Huber
      Pages: 34 - 44
      Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154
      Author(s): Gabriele Mack, Robert Huber
      Grassland-based feeding systems have the potential to reduce N input in agriculture through lower use of concentrates. Switzerland has recently introduced a new voluntary grassland-based milk and meat programme that restricts the concentrate and maize use in milk production systems. We analysed the on-farm compliance costs and the N surplus reduction potential for a sample of 2004 mixed dairy farms using farm-optimisation models implemented in the agent-based agricultural sector model SWISSland. Based on the simulation results, we used regression analysis to identify driving forces for the level of compliance costs and the reduction in N surplus of farms which allowed to investigate the effectiveness and the efficiency of the programme for the whole farm population. Our results imply that a payment for reducing the on-farm consumption of concentrate and maize feed does not substantially reduce N surpluses in Swiss agriculture. The heterogeneity of farms results in a distribution of compliance costs with a large group of farms having no or minimal costs. With the current payment of 200 CHF per hectare, reductions of 10.7 and 26.3tonnes of N can be achieved at high costs of 57 and 161 CHF per kg N in the lowland and mountain region respectively. Results also imply that specialisation represented by a high proportion of milk production, high levels of milk yields per cow as well as high milk prices increases the on-farm compliance costs of the programme. In contrast, diversification strategies that focus on intensive milk production in combination with additional low N fed livestock to optimise the use of grass at farm level reduces the compliance costs.

      PubDate: 2017-03-28T13:42:08Z
      DOI: 10.1016/j.agsy.2017.03.003
  • Ecosystem-based interventions and farm household welfare in degraded
           areas: Comparative evidence from Ethiopia
    • Authors: Kindie Getnet; Wolde Mekuria; Simon Langan; Mike Rivington; Paula Novo; Helaina Black
      Pages: 53 - 62
      Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154
      Author(s): Kindie Getnet, Wolde Mekuria, Simon Langan, Mike Rivington, Paula Novo, Helaina Black
      Agricultural productivity and farm household welfare in areas of severe land degradation can be improved through ecosystem-based interventions. Decisions on the possible types of practices and investments can be informed using evidence of potential benefits. Using farm household data together with a farm level stochastic simulation model provides an initial quantification of farm income and nutrition outcomes that can be generated over a five year period from manure and compost based organic amendment of crop lands. Simulated results show positive income and nutrition impacts. Mean farm income increases by 13% over the planning period, from US$32,833 under the business as usual situation (application of 50kg DAP and 25kgureaha−1 yr−1) to US$37,172 under application of 10tha−1 yr−1 farm yard manure during the first three years and 5tha−1 yr−1 during the last two years. As a result of organic soil amendment, there is an associated increase in the available calorie, protein, fat, calcium, and iron per adult equivalent, giving the improvement in farm household nutrition. The evidence is substantive enough to suggest the promotion and adoption at scale, in degraded ecosystems, of low cost organic soil amendment practices to improve agricultural productivity and subsequent changes in farm household welfare.

      PubDate: 2017-03-28T13:42:08Z
      DOI: 10.1016/j.agsy.2017.03.001
  • Mitigating nitrous oxide and manure-derived methane emissions by removing
           cows in response to wet soil conditions
    • Authors: T.J. van; der Weerden Laurenson Vogeler P.C. Beukes S.M. Thomas
      Abstract: Publication date: September 2017
      Source:Agricultural Systems, Volume 156
      Author(s): T.J. van der Weerden, S. Laurenson, I. Vogeler, P.C. Beukes, S.M. Thomas, R.M. Rees, C.F.E. Topp, G. Lanigan, C.A.M. de Klein
      In pasture-based grazing systems, urine deposition is the major source of the greenhouse gas nitrous oxide (N2O). Livestock treading damage and high soil water contents increase the risk of N2O emissions. Duration controlled grazing (DCG) practices that are implemented in response to soil water conditions above a threshold may therefore provide an effective means of reducing greenhouse gas (GHG) emissions from dairy farms. The objective of this study was to evaluate the potential decrease in GHG emissions from dairy farms when implementing DCG when soil water content is above a specific threshold (akin to ‘wet’ days). We used the DairyNZ Whole Farm Model and APSIM model to assess the cost-benefit of implementing DCG to reduce total N2O and manure-derived CH4 emissions from dairy farms. We modelled scenarios on poorly drained or imperfectly drained soils in four regions of New Zealand including Waikato, Manawatu, Canterbury and Southland, where the grazing time on wet days was 0, 13, 17 or 21h per day. Emissions were estimated using a refined version of New Zealand's current national greenhouse gas inventory methodology. Our analysis suggested that reducing the grazing time from 21h to 0, 13 or 17h per day when soils were wet could reduce annual N2O and manure-derived CH4 emissions by up to, respectively, 12, 9 or 5% on farms with poorly drained soils. The 13h per day grazing duration was the least costly, particularly if there were >150 ‘wet’ days per year. In contrast, for dairy farms on imperfectly-drained soils, DCG increased emissions, suggesting this management approach for reducing GHG emissions is not suitable for these soils.

      PubDate: 2017-06-22T08:35:16Z
  • Inside Front Cover - Editorial Board Page/Cover image legend if applicable
    • Abstract: Publication date: July 2017
      Source:Agricultural Systems, Volume 155

      PubDate: 2017-06-22T08:35:16Z
  • Market-level effects of firm-level adaptation and intermediation in
           networked markets of fresh foods: A case study in Colombia
    • Authors: Gonzalo
      Abstract: Publication date: Available online 21 June 2017
      Source:Agricultural Systems
      Author(s): Gonzalo Mejía, César García-Díaz
      This paper presents a multi-agent simulation that studies market competition in a multi-stage negotiation with both direct sales and intermediation, in the presence of cost heterogeneity at the agent (i.e., producer) level. Producers sell their products according to an adaptive reinforcement strategy. Product is sold to clients (small shops and consumers) according to two types of marketplaces, which are characterized by whether they obtain the product from intermediaries or directly from producers. The model is applied to the case of a networked market of potato (Solanum tuberosum) producers in Bogotá, Colombia, and calibrated to real data. The results reveal that, contingent upon the number of producers, number of intermediaries, unit transportation cost and producers' culture, intermediation might lead to greater traded quantities than sales through farmers' (local) markets. Also, we found that increasing the intensity of competition among intermediaries is at odds with the increase of producers' long run profit. Thus, we conclude that intermediation still plays an important role to maintain the supply ecosystem, especially when transportation costs are important in a network of isolated and fragmented network of producers.

      PubDate: 2017-06-22T08:35:16Z
  • Next generation agricultural system models and knowledge products:
           Synthesis and strategy
    • Authors: John M. Antle; James W. Jones; Cynthia Rosenzweig
      Abstract: Publication date: Available online 2 June 2017
      Source:Agricultural Systems
      Author(s): John M. Antle, James W. Jones, Cynthia Rosenzweig
      The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. This strategy is designed to facilitate a transition from the current, primarily supply-driven approach toward a more demand-driven approach that would address key Use Cases where better data, models and knowledge products are seen by end-users as essential to meet their needs.

      PubDate: 2017-06-07T07:54:56Z
      DOI: 10.1016/j.agsy.2017.05.006
  • Inside Front Cover - Editorial Board Page/Cover image legend if applicable
    • Abstract: Publication date: June 2017
      Source:Agricultural Systems, Volume 154

      PubDate: 2017-05-13T08:12:18Z
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