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Publisher: Elsevier   (Total: 3159 journals)

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Showing 1 - 200 of 3159 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 9)
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 32, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 22, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 90, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 34, SJR: 1.771, CiteScore: 3)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 7)
Acta Astronautica     Hybrid Journal   (Followers: 407, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 2)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 8, SJR: 0.18, CiteScore: 1)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.128, CiteScore: 0)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 245, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 10, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 27, SJR: 1.331, CiteScore: 2)
Acta Sociológica     Open Access   (Followers: 1)
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.052, CiteScore: 2)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3, SJR: 0.374, CiteScore: 1)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.344, CiteScore: 1)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.19, CiteScore: 0)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 6)
Acute Pain     Full-text available via subscription   (Followers: 15, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 16, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 9, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 142, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, SJR: 0.694, CiteScore: 3)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 12, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 22, SJR: 2.089, CiteScore: 5)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 0.572, CiteScore: 2)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.61, CiteScore: 7)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.686, CiteScore: 2)
Advances in Cancer Research     Full-text available via subscription   (Followers: 30, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 7, SJR: 1.453, CiteScore: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 1.992, CiteScore: 5)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 3)
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: 27, SJR: 0.156, CiteScore: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.713, CiteScore: 1)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 10, SJR: 1.316, CiteScore: 2)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 1.977, CiteScore: 8)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.205, CiteScore: 1)
Advances in Dermatology     Full-text available via subscription   (Followers: 15)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
Advances in Digestive Medicine     Open Access   (Followers: 9)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 24)
Advances in Ecological Research     Full-text available via subscription   (Followers: 43, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 27, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 44, SJR: 5.39, CiteScore: 8)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 9)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 54, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 16, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 8, SJR: 12.74, CiteScore: 13)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 1.193, CiteScore: 3)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 11, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.193, CiteScore: 0)
Advances in Immunology     Full-text available via subscription   (Followers: 36, SJR: 4.433, CiteScore: 6)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 1.163, CiteScore: 2)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 2, SJR: 1.938, CiteScore: 3)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6, SJR: 0.176, CiteScore: 0)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 3)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.682, CiteScore: 2)
Advances in Lipobiology     Full-text available via subscription   (Followers: 1)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 14, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.027, CiteScore: 2)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.694, CiteScore: 2)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.158, CiteScore: 3)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 21)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 1)
Advances in Organ Biology     Full-text available via subscription   (Followers: 1)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 16, SJR: 1.875, CiteScore: 4)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.174, CiteScore: 0)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 1.579, CiteScore: 4)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 10)
Advances in Pharmacology     Full-text available via subscription   (Followers: 16, SJR: 1.536, CiteScore: 3)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.574, CiteScore: 1)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.109, CiteScore: 1)
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: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 0.791, CiteScore: 2)
Advances in Psychology     Full-text available via subscription   (Followers: 62)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (SJR: 0.263, CiteScore: 1)
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.101, CiteScore: 0)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 5)
Advances in Space Research     Full-text available via subscription   (Followers: 395, SJR: 0.569, CiteScore: 2)
Advances in Structural Biology     Full-text available via subscription   (Followers: 5)
Advances in Surgery     Full-text available via subscription   (Followers: 10, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 31, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 18)
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: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 46, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 337, SJR: 0.796, CiteScore: 3)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.42, CiteScore: 2)
African J. of Emergency Medicine     Open Access   (Followers: 6, SJR: 0.296, CiteScore: 0)
Ageing Research Reviews     Hybrid Journal   (Followers: 11, SJR: 3.671, CiteScore: 9)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 443, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 16, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 32, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 43, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 1)
Agriculture and Natural Resources     Open Access   (Followers: 2)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 57, SJR: 1.747, CiteScore: 4)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.589, CiteScore: 3)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.26, CiteScore: 0)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.19, CiteScore: 0)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 9)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 10, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 50, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 50, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 54, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 44, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 28, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 34, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 45)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3, SJR: 1.967, CiteScore: 2)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 202, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 63, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 27, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 28, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 37, SJR: 1.141, CiteScore: 2)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.767, CiteScore: 1)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 6)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 62, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 16, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.277, CiteScore: 0)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription  
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5, SJR: 4.849, CiteScore: 10)
Analytica Chimica Acta     Hybrid Journal   (Followers: 40, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 172, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 10, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 23, SJR: 0.683, CiteScore: 2)
Angiología     Full-text available via subscription   (SJR: 0.121, CiteScore: 0)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1, SJR: 0.111, CiteScore: 0)
Animal Behaviour     Hybrid Journal   (Followers: 191, SJR: 1.58, CiteScore: 3)

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Journal Cover
Agricultural and Forest Meteorology
Journal Prestige (SJR): 1.818
Citation Impact (citeScore): 5
Number of Followers: 16  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0168-1923
Published by Elsevier Homepage  [3159 journals]
  • Sensitivity of simulated crop yield and nitrate leaching of the
           wheat-maize cropping system in the North China Plain to model parameters
    • Abstract: Publication date: 15 December 2018Source: Agricultural and Forest Meteorology, Volume 263Author(s): Mohamed Jabloun, Xiaoxin Li, Xiying Zhang, Fulu Tao, Chunsheng Hu, Jørgen E. OlesenAbstractProcess-based crop simulation models are often over-parameterised and are therefore difficult to calibrate properly. Following this rationale, the Morris screening sensitivity method was carried out on the DAISY model to identify the most influential input parameters operating on selected model outputs, i.e. crop yield, grain nitrogen (N), evapotranspiration and N leaching. The results obtained refer to the winter wheat-summer maize cropping system in the North China Plain. In this study, four different N fertiliser treatments over six years were considered based on a randomised field experiment at Luancheng Experimental Station to elucidate the impact of weather and nitrogen inputs on model sensitivity. A total of 128 parameters were considered for the sensitivity analysis. The ratios [output changes/parameter increments] demonstrated high standard deviations for the most relevant parameters, indicating high parameter non-linearity/interactions. In general, about 34 parameters influenced the outputs of the DAISY model for both crops. The most influential parameters depended on the output considered with sensitivity patterns consistent with the expected dominant processes. Interestingly, some parameters related to the previous crop were found to affect output variables of the following crop, illustrating the importance of considering crop sequences for model calibration. The developed RDAISY toolbox used in this study can serve as a basis for following sensitivity analysis of the DAISY model, thus enabling the selection of the most influential parameters to be considered with model calibration.
       
  • Direct and carry-over effects of summer rainfall on ecosystem carbon
           uptake and water use efficiency in a semi-arid woodland
    • Abstract: Publication date: 15 December 2018Source: Agricultural and Forest Meteorology, Volume 263Author(s): Qiaoqi Sun, Wayne S. Meyer, Petra MarschnerAbstractBiological activity in semi-arid and arid ecosystems is strongly dependent on rainfall, particularly in summer. A period of favourable rainfall can alter ecosystem carbon balance and is likely influence inner-annual variability of the regional and global carbon cycle. The effect of rainfall variability on ecosystem carbon and water fluxes in semi-arid ecosystems, particularly in woody ecosystems has not been adequately investigated. In this study, we used eddy covariance data from four springs (September–November), four summers (December of that year–February of the following year) and three following autumns (March–May) between 2010 and 2013 in a semi-arid woodland of southern Australia to better understand the effect of pre-summer, summer and post-summer rainfall variability on diurnal pattern of carbon flux. In 2010/11 summer, La Niῆa conditions resulted in extensive rainfall, which marked an historic record over the last 100 years. The 2011/12 summer was also moist. In contrast, the two following summers (2012/13 and 2013/14) were dry. Cumulative net ecosystem productivity (NEP) was lower in dry summers than in moist summers, due to lower maximum carbon flux rate and total hours of net carbon uptake. Maximum NEP and gross primary productivity rates on a given day were reached earlier in dry summers, indicating that photosynthetic activity was not suppressed by high temperatures but by water availability. Ecosystem water use efficiency, calculated as the ratio of daily NEP to evapotranspiration, was higher in moist than dry summers. In addition, the effect of summer rain extended into the following autumn. Cumulative NEP and ecosystem water use efficiency in autumn following a dry summer were lower than when following a moist summer. We conclude that summer rainfall has a strong impact on the carbon cycle in semi-arid woodlands due to its direct and carry-over effect. Therefore seasonal rainfall variation is likely to determine inter-annual variability of annual net carbo uptake of this ecosystem.
       
  • Predicting water balance of wheat and crop rotations with a simple model:
           AqYield
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): H. Tribouillois, J. Constantin, M. Willaume, A. Brut, E. Ceschia, T. Tallec, N. Beaudoin, O. TherondAbstractDesigning cropping systems that are well-adapted to water-limited conditions is one challenge of adapting agriculture to climate change. It requires estimating impacts of current and future cropping practices on crop water use and water resource availability in agricultural areas. Crop models such as AqYield are useful tools for evaluating effects of climate, soil and crop practices on evapotranspiration (ET) and drainage that directly impact soil available water (AW). AqYield is a simple model with few input data that has already been satisfactory evaluated for spring crops in southwestern France. Our main objective was to evaluate the ability of AqYield to predict components of soil water balance at the field level for crop rotations. First, we calibrated and evaluated AqYield predictions for winter wheat in France under a wide range of contrasting climatic and soil conditions. Fifty experimental situations (site × year × management) were chosen for calibration. AqYield was evaluated (i) for winter wheat in nine experimental situations, using daily drainage and ET data, and (ii) for two crop rotations on two fields with 7-years of continuous measurements of daily ET flux. During calibration, AqYield predicted soil AW in the contrasting situations with a model efficiency of 0.83, in the same range of accuracy as those of other widely published models. AqYield also predicted ET accurately from calibration and validation datasets, with a model efficiency of 0.84 and 0.69, respectively, for monthly ET. AqYield predicted daily and monthly drainage less accurately, although the range of drainage during the cropping period was predicted well. At the crop-rotation scale, AqYield yielded acceptable predictions of ET for contrasting climate conditions and crops. Whereas AqYield is simple and requires only a few input data, it accurately predicted ET of cropping systems. It therefore could be useful as a module in more complex modeling approaches.
       
  • Characterization of spatial and temporal combinations of climatic factors
           affecting yields: An empirical model applied to the French barley belt
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Damien Beillouin, Marie-Hélène Jeuffroy, Arnaud GauffreteauAbstractThe adaptation of genotypes to environmental conditions is one of the main levers for maintaining an acceptable level of production, both in terms of quality and quantity. To breed suitable genotypes and for the farmers to choose the most adapted one to his farm conditions, the factors affecting production must be precisely characterized. Here, we analyzed the impacts of the climatic factors on winter barley yield in 35 départements (French geographic units) over 25 years, by partial least squares (PLS) regression analysis. Using ascendant hierarchical clustering based on PLS results, we defined the main combinations of climatic factors affecting yield in the French barley belt, hereafter referred as “climatic-stress patterns” (CPs).Four CPs captured 27% of total yield variability and widely differ in term of yield. Crops experienced low winter rainfall and few days with heat stress (31.8% of environments- mean yield of 7.2 t ha−1), high winter frost levels and high amounts of precipitation during stem elongation (34.7% of environments- mean yield of 6.5 t ha−1), high temperature during grain filling either with low vernalization temperatures (28.9% of environments- mean yield of 6.2 t ha−1), or high winter rainfall (4.6% of environments –mean yield of 5.5 t ha−1). Two-thirds of the French départements experienced all the four CPS over the years studied. Three clusters of regions with homogeneous frequencies of the CPs were identified.The regions with similar climatic-stress patterns could help breeders to design genotypes better adapted to the different local French growing conditions. It could also help farmers to choose the most appropriate cultivars to grow.
       
  • How well do meteorological drought indices predict live fuel moisture
           content (LFMC)' An assessment for wildfire research and operations in
           Mediterranean ecosystems
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Julien Ruffault, Nicolas Martin-StPaul, Francois Pimont, Jean-Luc DupuyAbstractLive Fuel Moisture Content (LFMC) is a critical variable affecting fire ignition, behavior and severity in many ecosystems. Although the use of meteorological drought indices as proxies for LFMC is a straightforward and widespread approach, it is largely unknown whether it can provide reliable estimates of LFMC, either for local or spatial applications. We address this issue by evaluating the capacity of drought indices to predict LFMC quantitative variations and critical values. LFMC observations used for reference were measured on six different Mediterranean shrub species for 15 years in 20 different sites in Southern France. Six drought indices were evaluated: the Duff Moisture Code (DMC) and Drought Code (DC) of the Canadian Forest Fire Weather Index System, the Keetch-Byram Drought Index (KBDI), the Nesterov Index (NI) and the Relative Water Content (RWC) of the soil derived from a forest water balance model for low (80 mm) and high (160 mm) field capacities. The species were classified in two groups according to their seasonal variability: high and low responding species. We found large differences in the capacity of drought indices to predict LFMC, with indices that simulate long-term drought dynamics (DC, RWC and KBDI) generally performing better than others (NI and DMC). Once calibrated at stand scale, drought indices showed a good potential for predicting LFMC of high responding species, although large variations between sites were observed. In contrast, spatial predictability was limited with a RMSE and R2 on the order of 20% and 0.3, respectively (for high responding species). Our results suggest that drought indices should therefore be used with caution for spatial applications in wildfire research and operational fire management. Because they can explicitly consider environmental (soil, climate) and biological (species traits related to dehydration) factors, mechanistic indices have a great potential to improve LFMC predictions.
       
  • A half-Gaussian fitting method for estimating fractional vegetation cover
           of corn crops using unmanned aerial vehicle images
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Linyuan Li, Xihan Mu, Craig Macfarlane, Wanjuan Song, Jun Chen, Kai Yan, Guangjian YanAbstractAccurate estimates of fractional vegetation cover (FVC) using remotely sensed images collected using unmanned aerial vehicles (UAVs) offer considerable potential for field measurement. However, most existing methods, which were originally designed to extract FVC from ground-based remotely sensed images (acquired at a few meters above the ground level), cannot be directly used to process aerial images because of the presence of large quantities of mixed pixels. To alleviate the negative effects of mixed pixels, we proposed a new method for decomposing the Gaussian mixture model and estimating FVC, namely, the half-Gaussian fitting method for FVC estimation (HAGFVC). In this method, the histograms of pure vegetation pixels and pure background pixels are firstly fit using two half-Gaussian distributions in the Commission Internationale d’Eclairage (CIE) L*a*b* color space. Then, a threshold is determined based on the parameters of Gaussian distribution to generate a more accurate FVC estimate. We acquired low-altitude remote-sensing (LARS) images in three vegetative growth stages at different flight altitudes over a cornfield. The HAGFVC method successfully fitted the half-Gaussian distributions and obtained stable thresholds for FVC estimation. The results indicate that the HAGFVC method can be used to effectively and accurately derive FVC images, with a small mean bias error (MBE) and with root mean square error (RMSE) of less than 0.04 in all cases. Comparatively, other methods we tested performed poorly (RMSE of up to 0.36) because of the abundance of mixed pixels in LARS images, especially at high altitudes above ground level (AGL) or in the case of moderate vegetation coverage. The results demonstrate the importance of developing image-processing methods that specially account for mixed pixels for LARS images. Simulations indicated that the theoretical accuracy (no errors in fitting the half-Gaussian distributions) of the HAGFVC method reflected an RMSE of less than 0.07. Additionally, this method provides a useful approach to efficiently estimating FVC by using LARS images over large areas.
       
  • Parametrization of aerodynamic and canopy resistances for modeling
           evapotranspiration of greenhouse cucumber
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Haofang Yan, Chuan Zhang, Miriam Coenders Gerrits, Samuel Joe Acquah, Hengnian Zhang, Haimei Wu, Baoshan Zhao, Song Huang, Hanwen FuAbstractEstimating the latent heat flux accurately is important to improve greenhouse crops irrigation schedules. Aerodynamic and canopy resistances, as two key parameters in the Bulk transfer equations, are already difficult to measure in the open field and even more in greenhouses. In this study, an experiment was conducted in a Venlo-type cucumber greenhouse where meteorological data and the latent heat flux were measured with lysimeters. Two methods: (1) Inversing Bulk Transfer equation (IBTE-method) and (2) Appling a convective heat transfer coefficient (CHTC-method), were used to evaluate the aerodynamic resistance. A fixed aerodynamic resistance ( = 35 s m−1) was decided by analyzing the sensitivity of heat fluxes to its changes. The reproduced sensible and latent heat flux were compared to the measured values and the good agreements between measured and estimated values were obtained. The variation of daily canopy resistance which was calculated by IBTE-method was simulated by days after transplanting of cucumber plants and net radiation inside the greenhouse. Quadratic polynomial equations between canopy resistance and days after transplant were obtained, and were integrated into the Bulk transfer equation to predict the latent heat flux. The comparing of the measured and estimated latent heat flux showed that the Bulk transfer equation integrating the fixed aerodynamic resistance and canopy resistance sub-model could be used to predict the latent heat flux of greenhouse cucumber with the index of agreement higher than 0.8.
       
  • Inter-annual variability of Net Ecosystem Productivity for a temperate
           mixed forest: A predominance of carry-over effects'
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Marc Aubinet, Quentin Hurdebise, Henri Chopin, Alain Debacq, Anne De Ligne, Bernard Heinesch, Tanguy Manise, Caroline VinckeAbstractThis study presents twenty years of Net Ecosystem Productivity estimations obtained using eddy covariance in a mixed forest, dominated by beech with sparse conifers, at the Vielsalm station, in the Belgian Ardennes.First the quality and reliability of the data set is discussed. An uncertainty analysis showed that if, on one hand, the site heterogeneity and set-up changes may strongly affect yearly NEP estimates, questioning thus the total carbon budget relevance, on the other hand, robust inter-annual anomalies may be obtained as long as a site dedicated data treatment is carefully applied. A validation of the anomalies by comparison with a growth index derived from tree ring measurements is given. The resulting anomalies (range: [−206; + 123] g C m−2 yr−1, standard deviation: 93 g C m−2 yr−1) being larger than their own uncertainty (∼30 g C m−2 yr−1), an inter-annual variability analysis is possible.This analysis shows that the sources of NEP inter-annual variability at the Vielsalm station are multiple but the most prominent causes are biotic processes driven by carry-over effects of preceding meteorological events. The lowest observed NEP, in 2000, resulted from a bark beetle attack probably prompted by an early frost event in 1998. Besides, the robust lagged correlation between NEP anomalies and mean vapor pressure deficit during the preceding vegetation season also suggests a carry-over effect of water limitation during the previous year on the beech NEP. Mechanisms driving this carry-over effect are supposedly linked to tree physiology, which is confirmed by a dependency of canopy photosynthetic capacity to previous year water limitation. Some hypotheses, involving biomass allocation and bud formation, are proposed to explain its lagged impact on canopy photosynthetic capacity.Other causes of NEP inter-annual variability are the radiation during the current vegetation season and the temperature at the end of the winter but the latter variable rather indicates an effect on the conifers interspersed in the plot. Overall, the photosynthetic capacity combined with these two factors explained about 75% of NEP inter-annual variability.
       
  • A model for leaf temperature decoupling from air temperature
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Benjamin Blonder, Sean T. MichaletzAbstractLeaf temperature (Tleaf) influences rates of respiration, photosynthesis, and transpiration. The local slope of the relationship between Tleaf and Tair, β, describes leaf thermal responses. A range of values have been observed, with β 1 indicating megathermy where Tleaf increasingly exceeds Tair. However, theory for variation in β has not been developed. Here we derive an equation for β that predicts how it varies with multiple trait and microenvironment variables. The approach also predicts how maintenance of Tleaf away from lethally high values may help explain regulation of stomatal conductance (gS). The work delineates contexts in which each class of leaf thermal response is expected and develops concepts for predicting leaf responses to thermally extreme environments.
       
  • Comment on “Upland grasslands in Northern England were atmospheric
           carbon sinks regardless of management regime” by Eze et al.
    • Abstract: Publication date: Available online 31 July 2018Source: Agricultural and Forest MeteorologyAuthor(s): Mathias Hoffmann, Vytas Huth, Jürgen Augustin
       
  • Coupling the land surface model Noah-MP with the generic crop growth model
           Gecros: Model description, calibration and validation
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): J. Ingwersen, P. Högy, H.D. Wizemann, K. Warrach-Sagi, T. StreckAbstractInteractions between vegetation and atmosphere have a large impact on weather and climate. During the last decade, enormous efforts have been made to improve the representation of vegetation dynamics in land surface models (LSM). The present study extends the LSM Noah-MP by the dynamic crop growth model Gecros that enables simulating the development of crop stands in a weather-driven manner. This extension is a pre-requisite to simulate two-way climate-crop interactions in climate projections. Based on a comprehensive five-year dataset on energy- and water fluxes, and soil water and crop data from two different climate regions of southwest Germany, we adapted the crop growth model Gecros, integrated it with Noah-MP, calibrated the coupled model for winter wheat and maize and tested its robustness in multiple-year validation runs against independent measurements. This sound data set yielded a robust parameterization that performed well both in calibration and in validation runs over in total 16 seasons. Due to pronounced differences in phenology among maize cultivars, wheat simulations were better than maize simulations. The simulated dynamics in leaf area index of wheat and maize differed largely from the one used in standard Noah-MP simulations. The new model yielded pronounced differences in the partitioning of evapotranspiration into transpiration and soil evaporation. The added value of the improved description of vegetation dynamics needs to be evaluated in high-resolution coupled crop-climate simulations in future.
       
  • Response of crop yield and nitrogen use efficiency for wheat-maize
           cropping system to future climate change in northern China
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Shuo Liang, Yuefen Li, Xubo Zhang, Zhigang Sun, Nan Sun, Yinghua Duan, Minggang Xu, Lianhai WuAbstractClimate change and excessive fertilization will threaten the crops yields and nitrogen utilization in coming decades. The aim of this study is to quantify the response of crop yields and nitrogen use efficiency (NUE) to different fertilization strategies and climate change scenarios in the northern China by 2100 using the process-based SPACSYS model. The model was calibrated and validated with the data from four long-term experiments with winter wheat (Triticum Aestivium L.) and summer maize (Zea mays L.) rotation in the northern China. Five fertilizer treatments based on the long-term experiments were chosen: non-fertilizer (CK), a combination of mineral nitrogen, phosphorus and potassium (NPK), NPK plus manure (NPKM), a high application rate of NPKM (hNPKM) and NPK plus maize straw (NPKS). The model simulations and projections were performed under four different climate change scenarios including baseline, RCP2.6, RCP4.5 and RCP8.5. Validation demonstrated that SPACSYS can adequately simulate crop yields, N uptake and annual NUE for the wheat–maize rotation. Without considering the impact of cultivar change, maize yield would increase by an average of 8.5% and wheat yield would decrease by 3.8%, and the annual NUE would decrease by an average of 15% for all fertilization treatments under RCP climate scenarios compared with the baseline. This might be the interactive effects among elevated CO2 concentration, more concentrated and intensive rainfall events, and warming temperature. For each climate scenario, manure amendment could alleviate the negative influences of future climate change on crop growth and nitrogen utilization, given that manure applied treatments had higher soil organic matter and persistent supply of nutrients, which resulted in a more stable crop yield and N removal by wheat and maize than other treatments. In addition, the highest and most stable annual NUE (38.70–52.78%), crop yields and N removal were found in hNPKM treatment until 2100. The results could provide a reference for nitrogen fertilization in study regions to improve crop yield and nitrogen use efficiency and minimize environmental risks in the future.
       
  • Trans-Pacific ENSO teleconnections pose a correlated risk to agriculture
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Weston Anderson, Richard Seager, Walter Baethgen, Mark CaneThe El Niño Southern Oscillation (ENSO) is a major source of interannual climate variability. ENSO life cycles and the associated teleconnections evolve over multiple years at a global scale. This analysis is the first attempt to characterize the structure of the risk posed by trans-Pacific ENSO teleconnections to crop production in the greater Pacific Basin region.In this analysis we identify the large-scale atmospheric dynamics of ENSO teleconnections that affect heat and moisture stress during the growing seasons of maize, wheat and soy. We propose a coherent framework for understanding how trans-Pacific ENSO teleconnections pose a correlated risk to crop yields in major agricultural belts of the Americas, Australia and China over the course of an ENSO life cycle by using observations and a multi-model ensemble of climate anomalies during crop flowering seasons.Trans-Pacific ENSO teleconnections are often (but not always) offsetting between major producing regions in the Americas and those in northern China or Australia. El Niños tend to create good maize and soybean growing conditions in the US and southeast South America, but poor growing conditions in northern China, southern Mexico and the Cerrado in Brazil. The opposite is true during La Niña. Wheat growing conditions in southeast South America generally have the opposite sign of those in Australia. Furthermore, multi-year La Niñas can force multi-year growing season anomalies in Argentina and Australia.Most ENSO teleconnections relevant for crop flowering seasons are the result of a single trans-Pacific circulation anomaly that develops in boreal summer and persists through the following spring. During the late summer and early fall of a developing ENSO event, the tropical Pacific forces an atmospheric anomaly in the northern midlatitudes that spans the Pacific from northern China to North America and in the southern midlatitudes from Australia to southeast South America. This anomaly directly links the soybean and maize growing seasons of the US, Mexico and China and the wheat growing seasons of Argentina, southern Brazil and Australia. The ENSO event peaks in boreal winter, when the atmospheric circulation anomalies intensify and affect maize and soybeans in southeast South America. As the event decays, the ENSO-induced circulation anomalies persist through the wheat flowering seasons in China and the US.Graphical abstractSchematic of life-cycles of ENSO teleconnections for the La Niña life cycle, in which a La Niña is preceded by an El Niño and followed by a second year of weaker La Niña conditions. Black arrows indicate robust teleconnections to crop flowering seasons. Grey arrows indicate weak teleconnections. Dotted arrows indicate no teleconnection. Ocean colors indicate the intensity of either cold SST anomalies (blue) or warm SST anomalies (red). Tropical Pacific SST anomalies develop in JASO, peak in NDJF, and decay in MAMJ. While atmospheric teleconnections are strongest in NDJF, there are fewer crop flowering seasons in these months compared to JASO or MAMJGraphical abstract for this article
       
  • Drivers of spatio-temporal variability of carbon dioxide and energy fluxes
           in a Mediterranean savanna ecosystem
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Tarek S. El-Madany, Markus Reichstein, Oscar Perez-Priego, Arnaud Carrara, Gerardo Moreno, M. Pilar Martín, Javier Pacheco-Labrador, Georg Wohlfahrt, Hector Nieto, Ulrich Weber, Olaf Kolle, Yun-Peng Luo, Nuno Carvalhais, Mirco MigliavaccaAbstractTo understand what is driving spatial flux variability within a savanna type ecosystem in central Spain, data of three co-located eddy covariance (EC) towers in combination with hyperspectral airborne measurements and footprint analysis were used. The three EC systems show consistent, and unbiased mass and energy fluxes. Nevertheless, instantaneous between-tower flux differences i.e. paired half hourly fluxes, showed large variability. A period of 13 days around an airborne hyperspectral campaign was analyzed and proved that between-tower differences can be associated to biophysical properties of the sampled footprint areas. At high photosynthetically active radiation (PAR) net ecosystem exchange (NEE) was mainly controlled by chlorophyll content of the vegetation (estimated through MERIS Terrestrial Chlorophyll Index (MTCI)), while sensible heat flux (H) was driven by surface temperature. The spatial variability of biophysical properties translates into flux variability depending on the location and size of footprints. For H, negative correlations were found with surface temperature for between-tower differences, and for individual towers in time, meaning that higher H was observed at lower surface temperatures. High aerodynamic conductance of tree canopies reduces the canopy surface temperature and the excess energy is relieved as H. Therefore, higher tree canopy fractions yielded to lower surface temperatures and at the same time to higher H. For NEE, flux differences between towers were correlated to differences in MTCI of the respective footprints, showing that higher chlorophyll content of the vegetation translates into more photosynthetic CO2 uptake, which controls NEE variability. Between-tower differences of latent heat fluxes (LE) showed no consistent correlation to any vegetation index (VI), or structural parameter e.g. tree-grass-fraction. This missing correlation is most likely caused by the large contribution of soil evaporation to ecosystem LE, which is not captured by any of the biophysical and structural properties.To analyze if spatial heterogeneity influences the uncertainty of measured fluxes three different measures of uncertainty were compared: the standard deviation of the marginal distribution sampling (MDS), the two-tower-approach (TTA), and the variance of the covariance (RE). All three uncertainty estimates had similar means and distributions at the individual towers while the methods were significantly different to each other. The uncertainty estimates increased from RE over TTA to MDS, indicating that different components like space, time, meteorology, and phenology are factors, which affect the uncertainty estimates. Differences between uncertainty estimates from the RE and TTA indicate that spatial heterogeneity contributes significantly to the ecosystem-flux uncertainty.
       
  • Seasonal change of leaf and woody area profiles in a midlatitude deciduous
           forest canopy from classified dual-wavelength terrestrial lidar point
           clouds
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Zhan Li, Alan Strahler, Crystal Schaaf, David Jupp, Michael Schaefer, Pontus OlofssonAbstractThis study demonstrates the retrieval of separate vertical height profiles of leaf and woody areas in both leaf-off and leaf-on seasons at a largely broadleaf deciduous forest site in the Harvard Forest of central Massachusetts, USA, using point clouds acquired by a terrestrial laser scanner (TLS), the Dual-Wavelength Echidna® Lidar (DWEL). Drawing on dual-wavelength information from the DWEL, we classified points as leafy or woody hits using their near-infrared (1064 nm) and shortwave infrared (1548 nm) apparent reflectance coupled with the 3-D spatial distribution patterns of points. We developed a new indirect assessment approach that quantified the accuracies (user’s, producer’s and overall) and variance of accuracies of the 3-D point classifications. The overall classification accuracy estimated by this indirect approach was 0.60 ± 0.01 – 0.77 ± 0.01 for leaf-off points and 0.71 ± 0.02 – 0.78 ± 0.01 for leaf-on points. These estimated accuracies were then utilized to adjust the proportions of separate gap probabilities to reduce the biases in the separate leaf and woody area profiles due to classification errors. Separate retrievals of leaf and woody area profiles revealed the change in their spatial heterogeneity over the 1-ha plot with season. These retrievals also allowed height-explicit estimation of the woody-to-total ratio, which is an empirical parameter often used to remove woody contributions to leaf area index retrievals made by optical methods. The estimates suggested the woody-to-total ratios generally stayed stable along height in the middle and upper canopy for this site but varied in the lower canopy. More accurate estimates of leaf area and its vertical profile are important for better measurement and modeling of the radiation regime of forest canopies, and thus their photosynthetic capacity. By separating leafy and woody materials in three dimensions, dual-wavelength TLS offers the prospect of better understanding of forest cycling of matter and energy within local and global ecosystems.
       
  • Modelling the crop water-satisfied degree on the grid scale: A CropWRA
           model and the case study of Hanjiang River Basin, China
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Qiwu Yu, Zhenfa Tu, Guangming Yu, Lili Xu, Daman Yang, Yi YangAn assessment model for the satisfied degree of crop water requirements (CWR) on the grid scale, the CropWRA model, is developed to support precise management of agricultural water resources. On the grid scale, we urge that the CWR satisfied degree is not only rested with the abundance of water resources in a region, but also related to crop types, growing periods, water accessibility, etc. The CropWRA model also consists of corresponding indexes such as the CWR characteristics, crop planting combination and proportion, available water of agricultural production, water accessibility, etc. In this case study, the CWR satisfied degree of main food crops is evaluated with DEM data, hydrological data, meteorological and climate data, crop experiment and observation data, and statistical data in Hanjiang River Basin, China. In general, the results show that agricultural water resources can satisfy the CWR but the spatial differences are profoundly remarkable. The CropWRA index varies from -20% to 200%, and this difference is the comprehensive effects caused by the topography, river system, crop planting combination, land use, and water resources composition, etc. CropWRA model reveals the spatial differences in the relationships of CWR supply and demand and can provide the data support for precise water resource allocation.Graphical abstractGraphical abstract for this article
       
  • Thermal history parameters drive changes in physiology and cold hardiness
           of young grapevine plants during winter
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Francisco Gonzalez Antivilo, Rosalía Cristina Paz, Mariela Echeverria, Markus Keller, Jorge Tognetti, Roberto Borgo, Fidel Roig JuñentAbstractVitis vinifera is mainly cultivated in temperate areas, where seasons are well defined and winter conditions might be severe. To survive under these conditions during the dormant season, grapevines sense environmental parameters to trigger different protective mechanisms that lead to cold hardiness (CH). Crop yield and sustainability will be determined according to the level of CH reached in each organ. Moreover, different cultivars of V. vinifera exhibit different behavior throughout the dormant season, attaining a different status of CH. However, there is scarce information concerning how the same cultivar behaves under contrasting thermal environments. The aim of our research was to unveil how CH varies in trunks of the same cultivar under two contrasting environments and define which are the main thermal and biochemical parameters involved in this process. We submitted 2-year old plants of the same clone of cv. Malbec to two different thermal conditions: natural winter (control) and artificially warm winter (treatment). CH status, thermal and biochemical parameters in trunks were measured periodically over the dormant season, and this experiment was repeated for three years. Our results suggest that grapevine trunks subjected to a different environment reach dissimilar CH status, except at the end of winter. In addition, we determined that daily minimum temperature is the main thermal parameter that drives changes in CH. Also, we found that the total soluble sugars have the greatest relative weight in determining the CH compared with the other compounds evaluated. These results have practical implications in the establishment of vineyards for new growing regions. Moreover, with rising minimum temperature predicted by climate change scenarios, grapevines may be more vulnerable to cold events during the dormant season.
       
  • Azodyn-Barley, a winter-barley crop model for predicting and ranking
           genotypic yield, grain protein and grain size in contrasting pedoclimatic
           conditions
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Damien Beillouin, Margot Leclère, Corentin M. Barbu, Maud Bénézit, Ronan Trépos, Arnaud Gauffreteau, Marie-Hélène JeuffroyAbstractIncreasing societal demand for a more ecological agriculture stimulates demand for farm management systems adapted to non-standard situations such as low-nitrogen systems. However, trade-offs between traits of interest could make difficult to reach high agronomic and environment performances. For malting barley, premium prices depend on grain protein content and grain size with strong trade-offs with yield, such traits being highly dependent on practices and genotypes. Here we assume that such trade-offs can be implicitly embedded in models taking into account varietal traits. Starting with an existing wheat-crop model, we developed a parsimonious barley-crop model on how genotypic traits, crop management practices and pedo-climatic environment determine yield, grain protein content and grain size. Grain size predictions required the development of a new module. We parameterized the model with published and new experimental data using 200 genotype-by-environment combinations of high- and low-input management situations. The model was then assessed on 280 other situations, including high and low level of nitrogen input. The relative root mean square error of prediction of the model on hold-out data was below 15% for grain yield, grain protein content and grain retention fraction in high and low-input situations. In addition, the model correctly ranked 72% of the genotype pairs for grain yield, 55% for grain protein content and 85% for grain retention fraction. Our model can be used to predict grain protein content and retention fraction, and rank yield and calibrated yield performance of existing combinations of genotype by management by environment combinations. It also could help to explore new combinations, to support breeding.
       
  • The combined effect of elevation and meteorology on potato crop dynamics:
           A 10-year study in the Gamo Highlands, Ethiopia
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Thomas T. Minda, M.K. van der Molen, Paul C. Struik, Marie Combe, Pedro A. Jiménez, Muhammad S. Khan, Jordi Vilà-Guerau de ArellanoAbstractPotato (Solanum tuberosum L.) is an important crop in the Gamo Highlands in Ethiopia. The region is characterised by a complex topography with large inter-annual weather variations, where potatoes grow in a range of altitudes between 1,600 and 3,200 m above sea level (a.s.l.). Traditional large-scale crop modelling studies only crudely represent the effect of complex topography, misrepresenting spatial variability in meteorology and potato growth in the region. Here, we investigate how weather influenced by topography affects crop growth.We used the Weather Research and Forecasting (WRF) model to simulate weather in relation to topography in coarse (54 km × 54 km) and fine (2 km × 2 km) resolution domains. The first has a resolution similar to those used by large-scale crop modelling studies that only crudely resolve the horizontal and vertical spatial effects of topography. The second realistically represents the most important topographical variations. The weather variables modelled in both the coarse and fine resolution domains are given as input to the GECROS model (Genotype-by-Environment interaction on CROp growth Simulator) to simulate the potato growth. We modelled potato growth from 2001 to 2010 and studied its inter-annual variability. This enabled us to determine for the first time in Ethiopia how variations in weather are linked to crop dynamics as a function of elevation at a fine resolution.We found that due to its finer representation of topography, weather and crop growth spatio-temporal variations were better represented in the fine than in the coarse resolution domain. The magnitude of crop growth variables such as Leaf Area Index (LAI) and Length of the Growing Season (LGS) obtained with weather from the coarse resolution domain were unrealistically low, hence unacceptable. Nevertheless, the resulting potato yields in the coarse resolution domain were comparable with the yields from the fine resolution domain. We explain this paradoxical finding in terms of a compensating effect, as the opposite effects of temperature and precipitation on yield compensated for each other along the major potato growing transect in the Gamo Highlands. These offsetting effects were also dependent on the correct estimations of the LGS, LAI. We conclude that a well-resolved representation of complex topography is crucial to realistically model meteorology and crop physiology in tropical mountainous areas.
       
  • Grazing modulates soil temperature and moisture in a Eurasian steppe
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Yuchun Yan, Ruirui Yan, Jiquan Chen, Xiaoping Xin, David J. Eldridge, Changliang Shao, Xu Wang, Shijie Lv, Dongyan Jin, Jinqaing Chen, Zhenjie Guo, Baorui Chen, Lijun XuAbstractFew studies have addressed the potential grazing effects on microclimate, such as surface temperature and moisture, and their feedback effects on grassland function. A continuous, approximately three-year long study was conducted in experimental plots of various grazing intensities, and in situ soil temperature and moisture were measured. The results indicated that grazing significantly altered soil temperature and moisture. Soil temperature increased exponentially with increasing grazing intensity in the warm season due to the removal of aboveground biomass (AGB) and decreased linearly with increasing grazing intensity in the cold season due to decreases in both AGB and wind-blown snow accumulation. Heavy grazing increased soil temperature (10 cm depth) by an average of 2.6 °C from April to October (the largest hourly temperature increase was 8.8 °C), representing a soil warming effect 3.7 times that of global warming. Our findings showed that, compared with ungrazed plots, grazed plots had decreased soil water storage due to less winter snow accumulation, especially in the early growing season (EGS) because of the smaller amount of winter snow accumulation than in ungrazed plots. In the EGS, the average water storage in the 0–100 cm layer of the ungrazed plots was 23.3%, which was 1.3–1.8 times that of the grazed plots. Our results showed that grazing also produced warming and drying effects on grassland soil. The long-term feedback effects of grazing-induced soil warming and drying on the ecosystem might be an important mechanism accelerating the degradation and desertification of these grasslands.
       
  • Comparing empirical and survey-based yield forecasts in a dryland
           agro-ecosystem
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Yi Zhao, Noemi Vergopolan, Kathy Baylis, Jordan Blekking, Kelly Caylor, Tom Evans, Stacey Giroux, Justin Sheffield, Lyndon EstesAbstractAccurate crop yield forecasts before harvest are crucial for providing early warning of agricultural losses, so that policy-makers can take steps to minimize hunger risk. Within-season surveys of farmers’ end-of-season harvest expectations are one important method governments use to develop yield forecasts. Survey-based methods have two potential limitations whose effects are poorly understood. First, survey-based forecasts may be subject to errors and biases in the response data. For example, the weather variables that most impact yields may not be the same as those that farmers consider when shaping their yield expectations, thereby undermining forecast accuracy. Secondly, surveys are typically conducted late in the growing season, giving the government less advance notices of potential crop failures or low yields, and are costly to implement. Here we investigate these limitations within the context of Zambia’s annual Crop Forecast Survey (CFS). Concerning the first limitation, we analyzed the differences between CFS-predicted yields and reported yields collected by Post Harvest Surveys, and found that excess rainfall during the planting stage was more important to the actual yield than to farmers’ yield forecasts. For the second limitation, we evaluated whether a simple empirical yield forecast model could produce earlier and more accurate yield forecasts than the CFS. A random forest model using weather variables, soil texture, and soil pH as predictors were able to produce yield forecasts at the same or higher accuracy since the planting season.
       
  • Decomposing sources of uncertainty in climate change projections of boreal
           forest primary production
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Tuomo Kalliokoski, Annikki Mäkelä, Stefan Fronzek, Francesco Minunno, Mikko PeltoniemiAbstractWe are bound to large uncertainties when considering impacts of climate change on forest productivity. Studies formally acknowledging and determining the relative importance of different sources of this uncertainty are still scarce, although the choice of the climate scenario, and e.g. the assumption of the CO2 effects on tree water use can easily result in contradicting conclusions of future forest productivity. In a large scale, forest productivity is primarily driven by two large fluxes, gross primary production (GPP), which is the source for all carbon in forest ecosystems, and heterotrophic respiration. Here we show how uncertainty of GPP projections of Finnish boreal forests divides between input, mechanistic and parametric uncertainty. We used the simple semi-empirical stand GPP and water balance model PRELES with an ensemble of downscaled global circulation model (GCM) projections for the 21st century under different emissions and forcing scenarios (both RCP and SRES). We also evaluated the sensitivity of assumptions of the relationships between atmospheric CO2 concentration (Ca), photosynthesis and water use of trees. Even mean changes in climate projections of different meteorological variables for Finland were so high that it is likely that the primary productivity of forests will increase by the end of the century. The scale of productivity change largely depends on the long-term Ca fertilization effect on GPP and transpiration. However, GCM variability was the major source of uncertainty until 2060, after which emission scenario/pathway became the dominant factor. Large uncertainties with a wide range of projections can make it more difficult to draw ecologically meaningful conclusions especially on the local to regional scales, yet a thorough assessment of uncertainties is important for drawing robust conclusions.
       
  • How stand tree motion impacts wind dynamics during windstorms
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Sylvain Dupont, Pauline Défossez, Jean-Marc Bonnefond, Mark R. Irvine, Didier GarrigouAbstractUnderstanding how wind and trees interact during wind storms is crucial for better predicting forest wind damage. The complexity of this interaction is enhanced by the fragmented environment of forests. Here, we present an unprecedented field experiment (TWIST) where both the wind dynamics and the tree motion in the edge region of a maritime pine forest have been recorded simultaneously during four non-destructive wind storms. For three of them, the instrumented trees were under stand flow while for one of them they were under an edge flow. Our measurements demonstrate that the well-known characteristics of stand-flow dynamics remain valid under high wind conditions. Only the sub-canopy flow appeared more intermittent as canopy-top turbulent structures penetrate easier within the canopy due to the tree foliage reconfiguration. Under similar storm intensity, the tree motions were lower under edge flow than under stand flow due to the lower turbulence of the former flow while the mean wind speed was higher. This result demonstrates the importance of considering both the turbulence and the mean wind speed in wind risk models. No impact of tree motion other than tree reconfiguration were observed on the stand flow dynamics. On the other hand, for the edge flow, our measurements reveal a peak in frequency on the wind velocity fluctuations related to the fundamental tree vibration mode. This peak was especially visible at canopy top and in the upper trunk space under high wind conditions. Compared to the stand flow, we suspect that the velocity fluctuations induced by the tree motion emerge in the edge flow due to the lower background turbulence. Our edge storm was nonetheless not strong enough for tree motion to enhance flow turbulence and for trees to enter into resonance. These findings may suggest a higher susceptibility of near-edge trees to reach resonance than stand trees due to the motion of upwind trees in a lower background turbulence.
       
  • Comparisons of fire weather indices using Canadian raw and homogenized
           weather data
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Y. Tsinko, A. Bakhshaii, E.A. Johnson, Y.E. MartinAbstractModifications to the environment around a weather station or changes in instrument result in discontinuities or shift in weather data. This paper asks the often ignored questions such as, “what are the impacts of inhomogenized data'” and “does using homogenized weather data affect the conclusions of environmental research'” To answer these questions, we used the Canadian Forest Fire Weather Index (CFFWI) System for our studies. Weather station data are used to calculate wildfire danger indices. The homogenized data and raw (inhomogenized) observations for sixteen weather stations spread across Canada were used to calculate the CFFWI indices. The sixteen weather stations were further divided into three subset of stations based on the length of the accessible data during the fire season (April to end of September). The first set included stations that covered just 27 years of data and the second data sets had 49 years of data, while the third set included only five stations with the longest time period of 66 years. The majority of the stations, as measured by the Wilcoxon signed-rank test, rejected the null hypothesis (difference between the pairs follows a symmetric distribution around zero). The rejection rate increases to 100% as the length of data record increases from 27 to 66 years. Homogenization of 66 years data reduced the indices values approximately 0.7–8.4% and also reversed the long-term trend in some stations such as Kapuskasing.
       
  • Microbial properties regulate spatial variation in the differences in
           heterotrophic respiration and its temperature sensitivity between primary
           and secondary forests from tropical to cold-temperate zones
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Qing Wang, Nianpeng He, Li Xu, Xuhui ZhouAbstractLarge quantities of forest products globally have been lumbered, resulting in widespread conversion from primary forests [PFs] to secondary forests [SFs]. This transformation has exerted important impacts on the global carbon [C] cycle. Therefore, it is essential to clarify how soil C, which is a vital component of the global C pool, responds to the converting of forests from PFs to SFs, in parallel to identifying the underlying mechanisms. Here, nine paired (PFs and SFs) soil samples (0–10 cm) were obtained from tropical to cold-temperate zones along the north-south transect of eastern China (NSTEC). The heterotrophic respiration rate [RH] as per soil organic C at a reference temperature of 20 °C [R20-C] and its temperature sensitivity [Q10] were measured and calculated through 14 d incubation experiments. Our results showed that most of R20-C and Q10 in SFs were greater than those in PFs. Strong spatial variation in the differences in R20-C and Q10 between PFs and SFs [△R20-C, △Q10] was observed along the NSTEC, with the greatest △R20-C, △Q10 being detected in the soils of mid-latitude forests. Overall, 83.2% of the spatial variation in △R20-C was explained by physical-chemical and microbial properties, which contributed 68.5% and 52.4% variation solely, respectively. Similarly, 79% of the variation in △Q10 between PFs and SFs was explained by microbial properties, physical-chemical properties, and dissolved organic C, which contributed 81.6%, 10.5%, and 9% variation solely, respectively. Overall, our findings demonstrate high spatial variation in △RH and △Q10 between PFs and SFs, which was mainly explained by microbial properties of soils.
       
  • Quantification of forest canopy changes caused by spruce budworm
           defoliation using digital hemispherical imagery
    • Abstract: Publication date: 15 November 2018Source: Agricultural and Forest Meteorology, Volume 262Author(s): Shawn D. Donovan, David A. MacLean, John A. Kershaw, Michael B. LavigneAbstractDetection of spruce budworm (Choristoneura fumiferana Clem.) defoliation is critical for forest protection strategies aimed at minimizing losses in growth and mortality. However current aerial and ground survey methods of detecting defoliation are imprecise and subjective, limiting their usefulness. We evaluated the use of hemispherical crown canopy images to quantify annual spruce budworm defoliation, comparing images taken before and after defoliation in each of two years in 75 sample plots in Québec, Canada. Gradient Boosting Machine analysis identified gap fraction change from May-October, gap fraction after defoliation, insecticide spraying, and % balsam fir (Abies balsamea (L.) Mill.) basal area as important explanatory variables of defoliation. Logistic Generalized Linear Model (GLM) and Random Forests (RF) models were trained on a random two-thirds of sample plots combining both years, and defoliation predictions were validated on the remaining one-third of plots. RF predictions consistently resulted in slightly higher correlations and lower root mean squared errors (RMSEs) than GLM predictions. Defoliation models including insecticide spraying, gap fraction change May-October, and % balsam fir basal area had RMSEs of 14–22%, whereas models excluding insecticide spraying had higher RMSEs of 18–24%. Model goodness-of-fit using two-sample Kolmogorov-Smirnov tests indicated that predicted and measured annual defoliation had similar distributions, with the exception of GLM and RF models excluding spray compared to ocular defoliation. Use of hemispherical images to quantify gap fraction change is a feasible, non-destructive, and objective method to assess canopy foliage changes caused by spruce budworm defoliation.
       
  • Corrigendum to “Diel ecosystem conductance response to vapor pressure
           deficit is suboptimal and independent of soil moisture” [Agric. For.
           Meteorol. 250–251 (2018) 24–34]
    • Abstract: Publication date: Available online 11 June 2018Source: Agricultural and Forest MeteorologyAuthor(s): Changjie Lin, Pierre Gentine, Yuefei Huang, Kaiyu Guan, Hyungsuk Kimm, Sha Zhou
       
  • An automated approach for wood-leaf separation from terrestrial LIDAR
           point clouds using the density based clustering algorithm DBSCAN
    • Abstract: Publication date: Available online 24 May 2018Source: Agricultural and Forest MeteorologyAuthor(s): Roberto Ferrara, Salvatore G.P. Virdis, Andrea Ventura, Tiziano Ghisu, Pierpaolo Duce, Grazia PellizzaroAbstractThe terrestrial light detection and ranging (LiDAR) technique has been recently used to provide 3D structural information of forest canopy at the individual tree level. However, the operational use of Terrestrial Laser Scanner (TLS) for canopy characterization of broadleaf non-deciduous forests needs further investigations. The estimation of wood volume, above-ground woody biomass, tree canopy characteristics and leaf area index often requires separation of photosynthetically active material and non-photosynthetically active material. This article describes an automated wood-leaves separation method, based on spatial geometric information of TLS point clouds, for broad leaved non-deciduous trees. Scans of seven individuals of Quercus suber L. trees were acquired by using the TLS phase-based Leica HDS6100. Point clouds were partitioned in cubic volumes (voxels) that were used as input to generate clusters through the point density algorithm DBSCAN. The clustering process led to the identification of wood and non-wood voxels. A specific automatic routine was written to process data from the point clouds to the visualization of clustering results. The analysis of results showed good performance for this approach, with the overall accuracy in classifying wood components of trees ranging from 95% to 97%. The largest accuracies were observed for branches larger than 5 cm in diameter whereas the accuracy of classification dropped, as expected, for branches with diameter lower than 3 cm.The results suggest that the proposed method can be conveniently used to extract woody components from point clouds of broad leaved non-deciduous trees.
       
 
 
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