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Publisher: Elsevier   (Total: 3157 journals)

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Showing 1 - 200 of 3161 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: 35, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 24, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 96, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 27, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 37, 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: 416, 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: 10, 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: 261, 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: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, 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: 7)
Acute Pain     Full-text available via subscription   (Followers: 14, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 17, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 10, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 23)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 159, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, 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: 15, 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: 24, 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: 33, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, 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: 4)
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: 9, SJR: 1.316, CiteScore: 2)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 26, 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: 12)
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: 25)
Advances in Ecological Research     Full-text available via subscription   (Followers: 44, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 28, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 8)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 46, 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: 59, 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: 23, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 12, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
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: 8)
Advances in Marine Biology     Full-text available via subscription   (Followers: 18, 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: 7, 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: 23)
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: 2)
Advances in Organ Biology     Full-text available via subscription   (Followers: 1)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 17, 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: 12)
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: 10)
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: 19)
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: 64)
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: 6)
Advances in Space Research     Full-text available via subscription   (Followers: 404, 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: 11, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 34, 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: 14)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 47, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 349, 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: 458, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (Followers: 1, SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 17, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 31, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 42, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 4)
Agriculture and Natural Resources     Open Access   (Followers: 3)
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: 12, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 11)
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: 10, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 51, 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: 53, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 56, 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: 29, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 35, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 47)
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: 222, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 66, 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: 28, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 29, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 38, 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: 7)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 63, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 18, 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: 42, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 185, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 12, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 12)
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: 203, 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: 17  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0168-1923
Published by Elsevier Homepage  [3157 journals]
  • Dynamical effects of plastic mulch on evapotranspiration partitioning in a
           mulched agriculture ecosystem: Measurement with numerical modeling
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Pei Wang, Yujing Deng, Xiao-Yan Li, Zhongwang Wei, Xia Hu, Fei Tian, Xiuchen Wu, Yongmei Huang, Yu-Jun Ma, Cicheng Zhang, Yang Wang, Engui Li, Jiaqi Wang Mulching is a common and effective practice to artificially reduce evaporation for the purposes of water conservation in arid/semiarid ecosystems. Few studies have quantified the effects of plastic mulch on evapotranspiration (ET) partitioning impacted by different biophysical processes between bare and mulch-covered soil within a soil-mulch–plant-atmosphere continuum. Here, we partitioned ET flux into bare soil evaporation (Ebs), mulch-covered soil evaporation (Ems) and transpiration (T) in an oasis cropland ecosystem that was partially covered by plastic film, using an improved multisource energy balance model. The modeled water/energy fluxes agreed well with those measured by the eddy covariance. The modeled surface temperatures of both bare soil and mulch-covered soil were also consistent with measured fluxes, with a high R2 (0.81). During the growing season, the mean fractional contribution to total ET was 21 ± 12%, 6 ± 4%, and 73 ± 14% for Ebs, Ems and T, respectively. Comparisons of modeled output with and without considering mulching effects indicate that mulching increases the T/ET by decreasing E (0.02 ± 0.02 mm h−1), with a mean value of 7.2% and a range of 0–16% during the growing season. Mulching also increases soil temperature, while decreasing available energy at the land surface. These results show that the effects of mulching on ET partitioning varied with leaf development and were more sensitive during periods characterized by a lower leaf area index (e.g., the initial growing period and the period after clear cutting). Without considering mulch effects, the ET (E/ET) flux would be an overestimate, mainly because soil resistance and the availability of soil water would be underestimated. This study highlights the potential of plastic film mulch as a viable management option for soil water conservation and improving soil temperature, which is crucial for plant growth in arid and semiarid ecosystems.Graphical abstractThe mean fraction of ET for bare soil evaporation (Ebs/ET), mulch covered soil evaporation (Ems/ET) and plant transpiration (T/ET), was (a) 12 ± 6%, 5 ± 4%, and 83 ± 8% for peak growing stage, (b) 35 ± 8%, 9 ± 2%, and 55 ± 9% for early/late growing stage, respectively, (c) relationship between leaf area index (LAI) and the differences in modeling with and without consideration of plastic mulch on ET partition into transpiration and evaporation fraction (T/ET and E/ET) during the growing season.Graphical abstract for this article
       
  • A new multi-sensor integrated index for drought monitoring
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Wenzhe Jiao, Chao Tian, Qing Chang, Kimberly A. Novick, Lixin Wang Drought is one of the most expensive but least understood natural disasters. Remote sensing based integrated drought indices have the potential to describe drought conditions comprehensively, and multi-criteria combination analysis is increasingly used to support drought assessment. However, conventional multi-criteria combination methods and most existing integrated drought indices fail to adequately represent spatial variability. An index that can be widely used for drought monitoring across all climate regions would be of great value for ecosystem management. To this end, we proposed a framework for generating a new integrated drought index applicable across diverse climate regions. In this new framework, a local ordered weighted averaging (OWA) model was used to combine the Temperature Condition Index (TCI) from the Moderate-resolution Imaging Spectroradiometer (MODIS), the Vegetation Condition Index (VCI) developed using the Vegetation Index based on Universal Pattern Decomposition method (VIUPD), the Soil Moisture Condition Index (SMCI) derived from the Advanced Microwave Scanning Radiometer–Earth Observation System (AMSR-E), and the Precipitation Condition Index (PCI) derived from the Tropical Rainfall Measuring Mission (TRMM). This new index, which we call the “Geographically Independent Integrated Drought Index (GIIDI),” was validated in diverse climate divisions across the continental United States. Results showed that GIIDI was better correlated with in-situ PDSI, Z-index, SPI-1, SPI-3 and SPEI-6 (overall r-value = 0.701, 0.794, 0.811, 0.733, 0.628; RMSE = 1.979, 0.810, 0.729, 1.049 and 1.071, respectively) when compared to the Microwave Integrated Drought Index (MIDI), Optimized Meteorological Drought Index (OMDI), Scaled Drought Condition Index (SDCI), PCI, TCI, SMCI, and VCI. GIIDI also performed well in most climate divisions for both short-term and long-term drought monitoring. Because of the superior performance of GIIDI across diverse temporal and spatial scales, GIIDI has considerable potential for improving our ability to monitor drought across a range of biomes and climates.
       
  • Growth stage-dependant variability in water vapor and CO2 exchanges over a
           humid alpine shrubland on the northeastern Qinghai-Tibetan Plateau
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Hongqin Li, Jingbin Zhu, Fawei Zhang, Huidan He, Yongsheng Yang, Yingnian Li, Guangmin Cao, Huakun Zhou Large uncertainties exist in carbon-water-climate feedbacks in cold regions, partly due to an insufficient understanding of the simultaneous effects of climatic and biotic controls on water and carbon dynamics. The 10-year growing season flux data were analyzed to evaluate the relative contributions of climatic and biotic effects on the variability of water vapor (ET) and net ecosystem CO2 (NEE) exchanges over a humid alpine deciduous shrubland on the northeastern Qinghai-Tibetan Plateau. The results showed that the alpine shrubland ecosystem acted as a water source and a carbon sink during the growing season, and its potential ET and NEE ranged from 161.4 mm and –41.0 g C·m−2 to 408.0 mm and –278.4 g C·m−2 at a 95% confidence interval, respectively. The average 8-day ET and NEE during the early growing season (June to July) were both significantly (P < 0.05) more than those of the late growing season (August to September). And the slopes of ET and NEE against the Julian day during the two growth stages also changed significantly (P < 0.01). Such asymmetric manners of ET and NEE during the two growth stages were probably related to the seasonal variations of net radiation (Rn) and vegetation growth (satellite-derived enhanced vegetation index: EVI), respectively. The structural equation models showed that the seasonal variations of 8-day ET were jointly determined by Rn and vapor pressure deficit (VPD), as partly indicated by a modest decoupling coefficient (0.54 ± 0.03). The seasonal variability in 8-day NEE was controlled by the combinations of EVI and growing season degree days (GDD). The standardized coefficient of the direct effect of EVI on ET was 0.16, much less than the corresponding value (0.51) on NEE, suggesting that a weak coupling between ET and NEE arose likely because water vapor loss were about half controlled by surface evaporation, whereas CO2 flux were largely regulated by vascular plant activity. Our results highlighted the asymmetric sensitivities of ET and NEE during the early and the late growing season, and the weak coupling of water loss and carbon fixation during the whole growing season. These findings would provide a new sight to understand the growth stage-dependent responses of water budget and carbon sequestration to grazing management and climate change in humid alpine shrublands.
       
  • Climate at ecologically relevant scales: A new temperature and soil
           moisture logger for long-term microclimate measurement
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Jan Wild, Martin Kopecký, Martin Macek, Martin Šanda, Jakub Jankovec, Tomáš Haase Climate measurements are needed at a scale at which organisms live and die. Currently available climate sensors, however, are not well suited for long-term field measurements at such a scale. We have therefore developed a new temperature and moisture logger, the Temperature-Moisture-Sensor (TMS), which we designed for a wide range of ecological applications. The device mimics a small herbaceous plant. Its belowground part houses a patented, proprietary soil moisture sensor working on the time-domain transmission principle. Air, surface and soil temperatures are measured simultaneously by three independent sensors. The TMS data logger has a large memory and long battery life, so it is suitable for taking long-term microclimate measurements in the field. With a data acquisition interval of 15 min, it has sufficient memory to last for almost 15 years.We have thoroughly tested the TMS logger both in the laboratory and in demanding field conditions ranging from tropical rain forests of Africa to high-elevation cold deserts of the Himalayas. The device has provided microclimate measurements in a wide range of environmental conditions and has also performed well in controlled laboratory settings.The key added value of the TMS logger is that it concurrently measures soil moisture as well as soil, surface and air temperature at a biologically relevant scale. It is also able to continuously measure the microclimate for several years even in the most extreme conditions. The device can therefore be used to build extensive tailored field measurement networks providing crucial data about microclimate conditions shaping biological processes in the face of climate change.
       
  • Improving empirical storm damage models by coupling with high-resolution
           gust speed data
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Axel T. Albrecht, Christopher Jung, Dirk Schindler Empirical forest storm damage models can assist in identifying the key factors of the occurrence of storm damage in order to develop locally adapted measures to minimize damage in forests. Yet, there is a significant lack of knowledge in these models concerning the correlation between storm damage and high-impact near-surface airflow. To improve our understanding in this field, we built Random Forests (RF) and Generalized Linear Models (GLM) for evaluating the association between high resolution gust speed data and long-term, multi-event forest storm damage data from long-term permanent forest growth and yield plots. The tested gust speed data were derived from two different gust speed models: a numerical non-hydrostatic mesoscale model and a statistical model.In all RF and GLM models gust speed was a statistically significant predictor. The performance of the evaluated empirical models was very high (area under the receiver operating characteristic curve values AUC = 0.86–0.99). Depending on the type of model, the relative importance of gust speed was moderate to very high (up to 35%). However, starting from models using all significant predictors and excluding gust speed, the performance loss was almost negligible in all models. Furthermore, modeling long-term storm damage for each storm event individually performed better compared to modeling average long-term, event-unspecific storm damage.Our results demonstrate that empirical storm damage models using only gust speed as a predictor can reach moderate (GLM) to very high (RF) performance, even without any other information on terrain and forest attributes. However, if detailed terrain and forest data are available, empirical storm damage models may have such a high performance that adding gust speed data improves them very little. The correlation between gust speed and storm damage in the coupled modeling system is a fundamental first step in being able to evaluate potential changes of forest storm damage in a changing climate with potentially changing wind regimes. Additionally, further improvements could be achieved by improved representation of airflow in complex forest.
       
  • Remotely sensed agricultural grassland productivity responses to land use
           and hydro-climatic drivers under extreme drought and rainfall
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Jarrod Kath, Andrew F. Le Brocque, Kathryn Reardon-Smith, Armando Apan Climate change is expected to increase the frequency and intensity of drought globally with potentially significant consequences for grasslands. We examined grassland responses to a long-term drought on the Darling Downs, eastern Australia, using the Enhanced Vegetation Index (EVI), a remotely sensed measure of primary productivity. This extreme drought period had rainfall deficits comparable to the hottest and driest projected climate change scenarios for 2030 and was followed by extreme rainfall. This juxtaposition allowed investigation of grassland dynamics (decline and recovery) under extreme climatic variability. Our aim was to determine whether factors associated with grassland decline during extreme drought are the same as those that drive recovery post drought. There is limited knowledge about whether the determinants of grassland decline and recovery are consistent, but this information is important for understanding how best to reduce grassland decline, without inhibiting recovery. We calculated EVI (Enhanced Vegetation Index) trends at 2549 grassland sites situated in an agricultural landscape and used boosted regression trees to model these against multiple hydro-climatic and land use factors. As anticipated, hydro-climatic variables were key drivers of EVI trends in both the drought and wet phases, with higher soil moisture corresponding to less decline in the drought phase and enhanced recovery in the wet phase; however, land use and plant trait variables were also important predictors of EVI trends. Higher proportions of dryland agriculture in the local landscape, high C3:C4 ratios and lower proportions of woody vegetation in the local landscape were associated with negative EVI trends (i.e. greater decline) during drought, but had inverse or negligible effects during the post drought recovery phase. Our results suggest that mitigating decline and fostering grassland recovery following drought requires considering multiple hydro-climatic, land use and plant trait drivers and how their importance changes under drought and wet phases.
       
  • Microclimate and matter dynamics in transition zones of forest to arable
           land
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Martin Schmidt, Gunnar Lischeid, Claas Nendel Human-driven fragmentation of landscapes leads to the formation of transition zones between ecosystems that are characterised by fluxes of matter, energy and information. These transition zones may offer rather inhospitable habitats that could jeopardise biodiversity. On the other hand, transition zones are also reported to be hotspots for biodiversity and even evolutionary processes.The general mechanisms and influence of processes in transition zones are poorly understood. Although heterogeneity and diversity of land use of fragments and the transition zones between them play an important role, most studies only refer to forested transition zones. Often, only an extrapolation of measurements in the different fragments themselves is reported to determine gradients in transition zones.In this article, we analyse environmental gradients and their effects on biota and matter dynamics along transects between managed continental temperate forests and agricultural land for one year. Accordingly, we found S-shaped microclimatic gradients in transition zones of 50–80 m between arable lands and forests. Aboveground biomass was lower within 65 m of the transition zone, 30 m in the arable land and 35 m in the forest. Soil carbon and nitrogen contents were elevated close to the transition zone’s zero line.This paper contributes to a quantitative understanding of agricultural landscapes beyond individual ecotopes, and towards connected ecosystem mosaics that may be beneficial for the provision of ecosystem services.Graphical abstractGraphical abstract for this article
       
  • Nitrogen depositions increase soil respiration and decrease temperature
           sensitivity in a Moso bamboo forest
    • Abstract: Publication date: 15 April 2019Source: Agricultural and Forest Meteorology, Volume 268Author(s): Quan Li, Xinzhang Song, Scott X. Chang, Changhui Peng, Wenfa Xiao, Junbo Zhang, Wenhua Xiang, Yan Li, Weifeng Wang Nitrogen (N) deposition plays an important role in regulating forest productivity and microbial biomass and activities, ultimately influencing soil respiration (Rs). However, the effects of increasing atmospheric N depositions on Rs in subtropical Moso bamboo forests remain poorly understood. Here, we conducted a 4-year field experiment in a subtropical Moso bamboo forest to quantify the effect of simulated N depositions at four rates (0, 30, 60 and 90 kg N ha−1 yr-1) on Rs. The mean Rs rate of the control was 353.17 ± 53.23 mg CO2 m-2 h-1 or 30.75 ± 2.38 t CO2 ha-1 yr-1. Soil respiration showed significantly higher sensitivity (Q10) to soil temperature than to air temperature, and the Rs rate was significantly positively related to soil microbial biomass carbon, soil temperature, and NO3-. In response to N addition treatments of 30, 60, and 90 kg N ha-1 yr-1, the mean annual Rs increased by approximately 45.7%, 37.7%, and 13.0%, respectively, compared with the control. Nitrogen depositions decreased the temperature sensitivity of Rs, leading to predictions that they may be able to mitigate the priming effects of future climate warmings on Rs in Moso bamboo forests in the coming decades. Combined models based on the significant relationships between Rs rates, daily mean air temperatures, and hourly soil temperatures at a depth of 5 cm may reliably and feasibly estimate annual soil CO2 efflux. On average, soil emitted 470 kg CO2  ha-1 yr-1 per 1 kg N ha-1 yr-1 added, which declined when N addition surpassed the N saturation threshold of 60 kg N ha-1 yr-1. Our findings provide a method for estimating annual soil CO2 efflux and new insights into the effects of N deposition rates on soil CO2 efflux in Moso bamboo forests.
       
  • Effects of afforestation on soil nitrous oxide emissions in a subtropical
           montane agricultural landscape: A 3-year field experiment
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Minghua Zhou, Xiaoguo Wang, Yun Ke, Bo Zhu Afforestation, through the conversion of upland cropland to forest, is of great significance to land use change in montane (hilly) agricultural landscapes worldwide. Such afforestation is implemented to improve soil and water conservation and facilitate terrestrial carbon sequestration. However, particularly for subtropical and tropical regions, the effects of afforestation on soil N2O emissions have not been well investigated. Therefore, a three-year field experiment was conducted to simultaneously monitor N2O emissions from three paired sites of afforestation with cypress (Cypressus funebris) and adjacent cropland under a wheat-maize rotation system. The experiment was carried out in a subtropical montane agricultural landscape in southwest China. In both forest and cropland ecosystems, the N2O emissions exhibited a pronounced spatial and temporal variability. These variations in N2O emissions can be well explained by the spatiotemporal dynamics of environmental variables, such as soil temperature, WFPS, soil NH4+ or NO3− availability, because these environmental variables correlated significantly with the N2O emissions across different experimental sites and years. The average annual N2O fluxes were 2.69 kg N ha-1 for cropland and 0.13 kg N ha-1 for afforestation. It is noteworthy that the annual N2O fluxes for afforestation found in the present study constitute one of the lowest recorded N2O fluxes for unfertilized forest ecosystems globally. Overall, across all experimental sites and years, afforestation with cypress (Cypressus funebris) stands significantly decreased N2O fluxes by over twenty times relative to the adjacent cropland. This outcome suggests that afforestation could be an effective mitigation strategy for soil N2O emissions in a subtropical montane agricultural landscape.
       
  • Comparing the effects of growing conditions on simulated Ethiopian tef and
           wheat yields
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Kirsten Paff, Senthold Asseng Tef and wheat are staple grains in Ethiopia and are an important part of Ethiopian food security. The DSSAT NWheat and DSSAT Tef models were used to examine the effects of nitrogen fertilizer, planting date, and atmospheric CO2 on tef and wheat grain yields across four locations in Ethiopia and a 30-year time period.Observed wheat yields were consistently higher than observed tef yields, but the models showed that tef could outproduce wheat in some low yielding scenarios. Wheat yields were more responsive to N fertilizer than tef, due to a higher harvest index causing more of the additional biomass to be allocated to grain yields. Frequently, high rainfall increased N leaching, exacerbated N stress, and reduced yields for both crops. Early planting was often detrimental to yields, except for regions and years with terminal drought and heat stress. With continuously increasing atmospheric CO2 concentrations, wheat, as a C3 crop, will further outperform tef, a C4 crop, in the future, as long as N is not limiting. Breeding for lodging resistance and a higher harvest index could significantly improve future tef yields, while higher N applications and the use of split fertilizer applications to avoid leaching would improve both tef and wheat yields. As wheat has a higher N response than tef, is more responsive to future elevated atmospheric CO2 levels, and is generally higher yielding, wheat could add more to food security in Ethiopia. However, under low input, low yielding conditions, growing tef will likely remain the preferred cereal in Ethiopia due to its higher cultural, nutritional and economic value.
       
  • Simulating International Drought Experiment field observations using the
           Community Land Model
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Timothy W. Hilton, Michael E. Loik, J. Elliott Campbell Anthropogenic climate change will alter regional hydrologic cycles around the world, in part by increasing the frequency or duration of droughts in some areas. The International Drought Experiment (IDE) is investigating the impact of severe drought on terrestrial vegetation by experimentally reducing precipitation at dozens of sites. Here we implement the IDE precipitation reduction protocol using the Community Land Model (CLM). Though many model results suggest that carbon fertilization will outpace drought-caused reduction of terrestrial carbon uptake, uncertainty is large. We therefore configure CLM to consider carbon cycling impacts of reduced moisture availability without intertwining the effects of carbon fertilization or phenological changes. California hosts a number of IDE sites and a wide range of topography, climate, and biomes. CMIP5 predictions suggest 21st century California will experience droughts in excess of the 1000-year climatological record for both frequency and magnitude. CLM suggests that some regions, including much of Northern California, may experience a steeper decline in gross primary productivity (GPP) during 21st century severe droughts than during 20th century severe droughts. Vegetation in Northern California experiences virtually all of this GPP reduction during the dry season, with little wet season GPP reduction even during severe drought. Southern California vegetation experiences soil moisture GPP limitation at virtually all times, increasing substantially with drought severity. Southern California should experience a more pronounced shift in GPP seasonality and decline in magnitude relative to Northern California during droughts. Some parts of every vegetated continent see changes to drought response and seasonality similar to Southern California. Our CLM results provide drought impacts that forthcoming IDE field observations may test, can help to spatially upscale site-based IDE observations of drought impact, and provide CLM's prediction of reduced precipitation impacts per unit leaf area index.
       
  • Optimized sowing time windows mitigate climate risks for oats production
           under cool semi-arid growing conditions
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Yue Zhang, Lizhen Zhang, Ning Yang, Neil Huth, Enli Wang, Wopke van der Werf, Jochem B. Evers, Qi Wang, Dongsheng Zhang, Ruonan Wang, Hui Gao, Niels P.R. Anten Year to year variability in weather poses serious risks to crop production in the environmentally fragile agro-ecosystems of cool semi-arid areas, and future climate changes might further aggravate those risks. This study aims to quantify the contribution of altered sowing time windows to reduce climate risk for the production of oats (Avena sativa), a crop that is well adapted to short growing seasons and low rainfall. The APSIM-Oats model was calibrated and validated for phenology, above-ground dry matter and yield using data from field experiments with five sowing dates, conducted from 2009 to 2013 in Inner Mongolia, China. The model was used to determine yield trends and yield-limiting factors under rain-fed conditions using historical weather data. Changes in temperature had greater impact on crop production than changes in rainfall and the simulations indicated the importance of changed sowing windows to lengthen the growth duration and optimize water use. Delayed sowing of oats, 10 days later than current practice, ensured more secure temperature and rainfall conditions from emergence to flowering and substantially increased yields and decreased climate risk. Delayed sowing also reduced climate risk under two future climate scenarios, RCP4.5 (stabilize growth) and RCP8.5 (high greenhouse gas emission). We conclude that adaptation of sowing time of oats provides a practical strategy for enhancing yield and mitigating climate risk under climate change.
       
  • Hybrid artificial intelligence models based on a neuro-fuzzy system and
           metaheuristic optimization algorithms for spatial prediction of wildfire
           probability
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Abolfazl Jaafari, Eric K. Zenner, Mahdi Panahi, Himan Shahabi This study provides a new comparative analysis of four hybrid artificial intelligence models for the spatially explicit prediction of wildfire probabilities. Each model consists of an adaptive neuro-fuzzy inference system (ANFIS) combined with a metaheuristic optimization algorithm, i.e., genetic algorithm (GA), particle swarm optimization (PSO), shuffled frog leaping algorithm (SFLA), and imperialist competitive algorithm (ICA). A spatial database was constructed based on 159 fire events from the Hyrcanian ecoregion (Iran) for which a suite of predictor variables was derived. Each predictor variable was discretized into classes. The step-wise weight assessment ratio analysis (SWARA) procedure was used to assign weights to each class of each predictor variable. Weights indicate the strength of the spatial relationship between each class and fire occurrence and were used for training the hybrid models. The hybrid models were validated using several performance metrics and compared to the single ANFIS model. Although the single ANFIS model outperformed the hybrid models in the training phase, its accuracy decreased considerably in the validation phase. All hybrid models performed well for both training and validation datasets, but the ANFIS-ICA hybrid showed superior predictive performance of spatially explicit wildfire prediction and mapping for the dataset. The results clearly demonstrate the ability of the optimization algorithms to overcome the over-fitting problem of the single ANFIS model at the learning stage of the fire pattern. This study contributes to the suite of research that seeks to obtain reliable estimates of relative likelihoods of natural hazards.Graphical abstractGraphical abstract for this article
       
  • Causal, temporal and spatial statistics of wildfires in areas of planted
           forests in Brazil
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Fernando Coelho Eugenio, Alexandre Rosa dos Santos, Beatriz Duguy Pedra, José Eduardo Macedo Pezzopane, Reginaldo Gonçalves Mafia, Edmilson Bitti Loureiro, Lima Deleon Martins, Nathália Suemi Saito Wildfires are the result of a complex interaction between climate, vegetation, topography and socioeconomic factors (BEDIA et al., 2012). The present study aims at analyzing how the relations between the meteorological and physical variables of the terrain correlate with the parameters of occurrence of wildfires in areas of planted forests in Brazil. The analysis of the wildfire regime in the study area was divided into three important aspects: temporal, spatial and causal. There are two periods of wildfire occurrence in the studied area, and for the first season, subzone 1 is from December to March; for the subzone 2 is from January to March; and, for subzone 3, is in the months of January and February. The second season, for all subzones, is between the months of August and October. Most climatic variables, isolated, do not present a direct relation with the occurrence of wildfires for both subzones, excepting some variables in some subzones. Considering both subzones, approximately 80% of the fires analyzed correspond to areas smaller than 4 ha.Graphical abstractGraphical abstract for this article
       
  • Point source emission estimation using eddy covariance: Validation using
           an artificial source experiment
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Dumortier Pierre, Aubinet Marc, Lebeau Frédéric, Naiken Alwin, Bernard Heinesch Eddy covariance is increasingly used to monitor cattle emissions. However, the turbulent flux calculation method and the footprint models upon which calculations are based are insufficiently validated. In addition, available footprint models presume the source to be placed at soil height, which is obviously not the case for cattle. The present study uses a single known artificial point source placed at cow’s muzzle height in order to assess the impact of the flux calculation method (averaging method, averaging period, quality filters) and of the footprint model on the emission estimates. The optimal calculation method and footprint model combination (running mean, 15 min averaging periods, no application of the Foken and Wichura (1996) stationarity filter, and the use of the Kormann and Meixner (2001) footprint function) led to estimated emissions between 90 and 113% of the true emission, leading to the conclusion that the use of eddy-covariance for point-source emission estimation is feasible provided an adequate calculation method is selected.
       
  • Ridge-furrow full film mulching: An adaptive management strategy to reduce
           irrigation of dryland winter rapeseed (Brassica napus L.) in northwest
           China
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Xiaobo Gu, Huanjie Cai, Zhitao Zhang, Heng Fang, Pengpeng Chen, Peng Huang, Yupeng Li, Yuannong Li, Li Zhang, Jiaming Zhou, Yadan Du Ridge-furrow full film mulching (RFFM) has been widely adopted as a water-saving and yield-improving planting pattern in arid and semi-arid regions. Whether or not RFFM can replace the conventional flat planting pattern (FP) with supplemental irrigation in dryland farming has not been tested. Moreover, the effects of reducing irrigation frequency and amount on crops in dryland farms under different rainfall years (dry, normal or wet years) remain unknown. Present study selected winter rapeseed (Brassica napus L.) as a test crop for a three-year field experiment to investigate the irrigation water-saving potential of RFFM. Six treatments: 1) FP without irrigation (FP0); 2) FP with 30-mm irrigation at the overwintering stage (FP1); 3) FP with 30- and 60-mm irrigation at the overwintering and stem-elongation stages, respectively (FP2); 4) FP with 30-, 60- and 60-mm irrigation at the overwintering, stem-elongation and flowering stages, respectively (FP3); 5) RFFM without irrigation (RFFM0); and 6) RFFM with 45-mm irrigation at the flowering stage (RFFM1) were conducted to explore their effects on root and shoot biomass, nutrient uptake, yield, oil production, evapotranspiration (ET) and water use efficiency (WUE). The results indicated that RFFM0 significantly promoted root and shoot biomass accumulation and nutrient uptake. Thus it significantly improved yield by 23.7–39.0%, oil production by 26.8–43.3% and WUE by 71.3–86.5%, and simultaneously decreased ET by 21.2–29.7% in comparison to FP0 and FP1 in dry, normal and wet years. Furthermore, the yield-increasing effect in RFFM0 was nearly equal to FP3 in the normal rainfall and wet years, and was equivalent to FP2 in the dry year. Yield and oil production in RFFM1 were significantly higher than in RFFM0, and were commensurate with those in FP3 in the dry year. Therefore, RFFM reduced a two-time application with total 90 mm irrigation water in a dry year, as well as a three-time application with total 150 mm irrigation water in normal rainfall and wet years for dryland winter rapeseed. Overall, RFFM is a promising adaptive agronomic strategy to apply in dryland regions to sustain food security, and cope with water scarcity, a potential threat to dryland farming due to climate change.
       
  • Determinants of tree sway frequency in temperate deciduous forests of the
           Northeast United States
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Amanda Bunce, John C. Volin, David R. Miller, Jason Parent, Mark Rudnicki Trees are the most common cause of utility damage and power outages during storms in the northeastern United States. Previous studies on tree sway and risk of wind-throw have largely been conducted in heavily managed coniferous stands, while relatively little is known for northeastern mixed temperate deciduous forests. The objective of this study was to identify factors determining tree sway frequency in northeastern forests. To this end, we monitored the fundamental vibrational frequency (FVF) of 39 trees representing nine different tree species on 3 sites in southern New England over one year, and regressed those measurements against 25 potential predictor variables.Results showed that four predictors were significant across all sites and species. The height to the base of the live crown, as well as tree slenderness, defined as diameter-at-breast height divided by tree height squared (DBH  ∙ H−2), were significant. Previous studies on coniferous trees support the significance of slenderness. The other two predictors accounted for the presence or absence of foliage and whether temperatures were above or below freezing. These findings highlight the relationship of tree shape and FVF, and indicate the relationship is similar between excurrent (e.g., coniferous) and decurrent (e.g., northeastern broadleaves) species when they are grown in closed canopy situations, regardless of species mix or location. Given this relationship, and our understanding of the relationship of FVF to wind-firmness, forest management practices designed to effect slenderness and tree shape have the potential to increase wind-firmness and reduce tree-related storm damage to utility infrastructure.Graphical abstractGraphical abstract for this article
       
  • Representing explicit budburst and senescence processes for evergreen
           conifers in global models
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Marc Peaucelle, Philippe Ciais, Fabienne Maignan, Manuel Nicolas, Sébastien Cecchini, Nicolas Viovy Global ecosystem models lack an explicit representation of budburst and senescence for evergreen conifers despite their primordial role in the carbon cycle. In this study we evaluated eight different budburst models, combining forcing, chilling and photoperiod, for their ability to describe spring budburst, and one model of needle senescence for temperate evergreen coniferous forests. The models’ parameters were optimized against field observations from a national forest monitoring network in France. The best fitting budburst model was determined according to a new metrics which accounts for both temporal and spatial variabilities of budburst events across sites. The best model could reproduce observed budburst dates both at the site scale (±5 days) and at regional scale (±12 days). We also showed that the budburst models parameterized at site scale lose some predictive capability when applied at coarser spatial resolution, e.g., in grid-based simulations. The selected budburst model was then coupled to a senescence function defined from needle survivorship observations in order to describe the full phenology cycle of coniferous forests. Implemented in the process-driven ecosystem model ORCHIDEE, this new conifer phenology module represented accurately the intra and inter-annual dynamics of leaf area index at both the local and regional scales when compared against MODIS remote sensing observations. A sensitivity analysis showed only a small impact of the new budburst model on the timing of the seasonal cycle of photosynthesis (GPP). Yet, due to the faster renewal of needles compared to the standard version of ORCHIDEE, we simulated an increase in the GPP by on average 15% over France, while the simulated needle turnover was doubled. Compared to 1970–2000, projections indicated an advancement of the budburst date of 10.3 ± 2.8 and 12.3 ± 4.1 days in average over the period 2060–2100 with the best forcing and chilling-forcing models respectively. Our study suggests that including an explicit simulation of needle budburst and senescence for evergreen conifers in global terrestrial ecosystem models may significantly impact future projections of carbon budgets.Graphical abstractWe calibrated and implemented a new phenology module for evergreen conifers in the global model ORCHIDEE with an explicit representation of both needle budburst and senescence. The new phenology module now allows to represent the seasonality of observed leaf area for evergreen conifers at the regional scale. Sensitivity tests in ORCHIDEE show a strong impact on the simulated carbon cycle for which we highlighted a 15% increase of the growth primary productivity and a doubling of the needle turnover compared to default simulations. We argue that global ecosystem models have to simulate explicit phenological processes for evergreen species if we want to improve future projections of the carbon budget.Graphical abstract for this article
       
  • Estimation of evapotranspiration of a salt marsh in southern South America
           with coupled Penman-Monteith and surface resistance models
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): María I. Gassmann, Natalia E. Tonti, Antonella Burek, Claudio F. Pérez One of the most recommended method to estimate evapotranspiration (ET) of vegetated surfaces with different soil moisture conditions is the Penman-Monteith equation (PM). Canopy and soil conditions are parameterized through the surface resistance or conductance, while the contribution of the canopy to ET is measured by the canopy resistance. The study of natural ecosystems has gained interest because of its importance in water and carbon cycles. However, unlike monocultures, natural environments are composed of a mixture of species that make the estimation of ET with PM troublesome. This feature makes them suitable for ET estimation considering the contribution of both, the canopy and the soil represented by the surface resistance (rs), or the contribution of the canopy, represented by the canopy resistance (rc). This work aims to model the surface and canopy resistances using conventional meteorological, biological and pedological variables observed at a salt marsh used for livestock production in Buenos Aires province, Argentina. Twelve models (M1 to M12) based on the net solar radiation (Rn), air temperature (Ta), air relative humidity (RH), surface wind velocity (U), dew point departure (Dp), aerodynamic resistance (ra), leaf area index (LAI) and volumetric soil water content (ϑs) were obtained using two different regression methodologies. Surface resistances during daytime were calculated inverting the PM equation with ET fluxes measured with the eddy covariance method. PM-derived rs varied between 20 and 1000 s m−1, with a median of 137 s m−1. From 1620 observations, 468 were used for model calibration while 1152 for model validation. M5 and M11 with Rn, RH, ra, LAI predictor variables were the best models with 80.8 s m−1 root mean square error, 0.51 determination coefficient, 0.69 and 0.65 index of agreement, respectively. The modelled resistances allowed the estimation of latent heat fluxes with a root mean quadratic error varying from 60.7 to 69.5 W m-2. These results show the possibility to achieve rs from a minimum set of variables easily measured in the field which in turn, allows to estimate the ET of salt marsh ecosystems with scarce meteorological information.
       
  • A spatially explicit modeling analysis of adaptive variation in temperate
           tree phenology
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Liang Liang The geographic applicability of most phenological models is limited because of a lack in accounting for plant genotypic variation over space. This limitation may be partly addressed by quantifying plant adaptation patterns as revealed by common garden/provenance trial research. This study delineated adaptive patterns of a widely distributed tree species in North America—white ash (Fraxinus americana) using multi-year common garden observations of leaf out and leaf senescence phenology. Geographically varied phenology-climate (i.e., phenoclimatic) relationships of tree provenances were investigated both with the aid of interannual temperature variations and using process-based models. Interannual weather fluctuations likely led to varied gradients of spring phenological timing by tree origin latitude as influenced by interactions of chilling and forcing, while the latitudinal gradient of autumn phenology consistently followed a photoperiod-driven pattern. Fitted models revealed latitudinal gradients of chilling requirement (for dormancy release), forcing requirement (for bud break), and critical day length requirement (for leaf senescence) for the tree provenances. When these genotype-specific phenoclimatic relationships were accounted for in spring models, predictions closely matched the latitudinal gradient of USA-National Phenology Network (NPN) observations. On the other hand, average (non-spatial) model predictions of bud break tended to be biased in the species’ northern and southern ranges. This finding shows that introducing genotypic differences to phenological models is necessary for accurate prediction of temperate tree phenology over broad geographic regions.
       
  • Modelling and measurement of water productivity and total evaporation in a
           dryland soybean crop
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): N.C. Mbangiwa, M.J. Savage, T. Mabhaudhi Simpler crop models simulating evaporation are needed to provide information to farmers, policy makers and decision makers on how to maximise crop yield responses to water. This is becoming important as the frequency and severity of droughts in South Africa is increasing. In this regard, prediction of yield, determination of water productivity and total evaporation (ET) are increasingly becoming essential in water resource management. The overall objective of the study was to compare the FAO AquaCrop daily model output of ET to the residual ET for non-stressed dryland soybean in a sub-humid climate. Energy balance residual ET estimates using an eddy covariance (EC) system and modelled ET using AquaCrop obtained from Glycine max (L.) Merrill grown in the midlands of KwaZulu-Natal, South Africa during the 2012/13 growing season are compared. The modelled and observed yield showed good agreement, while the residual ET was 21.6% less than the modelled. The energy balance closure computed using the daily sums of sensible heat and latent energy fluxes against daily available energy flux for unstable atmospheric conditions was 0.77. A closure of 0.99 was achieved when the EC latent energy flux was replaced with residual latent energy flux. A good fit between the modelled and observed percentage green canopy cover was observed (slope = 0.86, intercept = 15.46%, root mean square error = 10.50% and R2 = 0.83). Season-long daily residual ET values were consistently low for most of the growth stages compared to the modelled, except for the maturity stage. However, the residual ET comparisons with the AquaCrop model improved after gap-filling was applied to discarded data and for when the EC system failed.
       
  • Wavelength selection of the multispectral lidar system for estimating leaf
           chlorophyll and water contents through the PROSPECT model
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Jia Sun, Shuo Shi, Jian Yang, Wei Gong, Feng Qiu, Lunche Wang, Lin Du, Biwu Chen The estimation of leaf biochemical constituents is of high interest for the physiological and ecological applications of remote sensing. The multispectral lidar (MSL) system emerges as a promising active remote sensing technology with the ability to acquire both three-dimensional and spectral characteristics of targets. The detection wavelengths of the MSL system can be geared toward the specific application purposes. Therefore, it’s important to conduct the wavelength selection work to maximize the potential of the MSL system in vegetation monitoring. Traditional strategies of wavelength selection attempt to establish an empirical relationship between large quantities of observed reflectance and foliar biochemical constituents. By contrast, this study proposed to select wavelengths through the radiative transfer model PROSPECT. A five-wavelength combination was established to estimate leaf chlorophyll and water contents: 680, 716, 1104, 1882 and 1920 nm. The consistency of the wavelengths selected were tested by running different versions of PROSPECT model. Model inversion using simulated and experimental datasets showed that the selected wavelengths have the ability to retrieve leaf chlorophyll and water contents accurately. Overall, this study demonstrated the potential of the MSL system in vegetation monitoring and can serve as a guide in the design of new MSL systems for the application community.
       
  • Transition model for airflow fields from single plants to multiple plants
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Hong Cheng, Weiwei He, Chenchen Liu, Xueyong Zou, Liqiang Kang, Tianle Chen, Kaidi Zhang The biocontrol measurement is the most effective method for land desertification control in arid and semi-arid areas where is limited by water and poor soil, and thus. Optimizations are needed for the existing biocontrol methods for anti-desertification and soil-erosion control so that the scope and scale of the biocontrol can be reduced. The premise for the optimization work is to reveal the distribution law of airflow fields around vegetation. Current studies are lack of the spatial express of airflow speed on a 2-D surface and there is no report on the transition of airflow fields from single plant to multiple plants. Based on detail experiments in a wind tunnel for the airflow fields around a single plant, a single-row forest belt with different plant spacing, a multi-row forest belt with different numbers of rows but the same plant spacing, and a double-row forest belt with various arrangements, this paper developed the horizontal model (Eq. (9)) for the airflow fields around single plant comprehensively analyzing the effect of plants characteristic parameters (such as crown width (W), height (H), porosity (β) etc.) on the horizontal and vertical air flow field partition around single plants and proposed a transition model (Eqs. (13) or 14) for airflow fields from single plant to multiple plants. These researches lay the theoretical foundations for optimum biocontrol plant configurations to address anti-desertification and soil erosion control.
       
  • Fine dead fuel moisture shows complex lagged responses to environmental
           conditions in a saw palmetto (Serenoa repens) flatwoods
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): J. Kevin Hiers, Christina L. Stauhammer, Joseph J. O’Brien, Henry L. Gholz, Timothy A. Martin, John Hom, Gregory Starr Fine dead fuel moisture has a major influence on wildland fire behavior yet the dynamics driving water exchange of fuel particles in forested environments remain poorly understood. Most fire behavior models rely on simple, stand-level fuel moisture estimates, ignoring potentially important variation occurring within fuelbeds that could influence fire behavior. This is especially true in surface fire regimes where variation in fine-scale fuel properties drive fire behavior and subsequent fire effects. Saw palmetto [Serenoa repens (Bartr.) Small] dominated fuelbeds in the pine forests of the southeastern United States have high within stand variation in one of the most fire prone habitats in the world. Pine needles and palmetto fronds dominate the biomass of fine dead fuel types that produce extreme fire behavior. To assess predictors of fine dead fuel moisture, we analyzed fuel moisture dynamics of these two fine dead fuel types over a two-year period in conjunction with under- and overstory forest meteorological data. Using multiple models and time lag analysis of within-stand moisture dynamics, the results indicate that saw palmetto and pine dramatically differ in drying regimes, primarily resulting from different responses to cumulative rainfall, net radiation, and antecedent atmospheric moisture content. Despite being responsive to changes in relative humidity, saw palmetto was significantly dryer than pine under nearly all meteorological conditions, and it was capable of maintaining extremely low fuel moisture despite high relative humidity or rainfall. Our results point to the need to capture additional drivers of microclimatic variation to aid fire managers in accurately predicting within-stand fuel moisture and subsequent fire behavior. Improving the scientific community’s understanding of variation in complex fuel beds is critical for effectively managing risk in fire prone ecosystems.
       
  • Cork rings suggest how to manage Quercus suber to mitigate the
           effects of climate changes
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Carla Leite, Vanda Oliveira, Alexandra Lauw, Helena Pereira Climate scenarios in the Mediterranean region predicts raising temperatures and more frequent and extreme drought conditions. Cork oak is a Mediterranean species with a large distribution in Portugal from which cork is extracted in a sustainable way and mainly used as the raw material for cork stoppers and insulating materials. To study the response of cork oak to drought and the effect of phellogen age on that response we examined cork growth from a 30-year chronology of trees from 12 sites in the main Portuguese cork oak production area. For the first time in cork, a components resilience study was performed. The research confirmed that drought reduces cork growth and provided extra knowledge on the responses of cork oak to drought: more severe droughts correspond to higher decrease of cork growth and more trees affected but to greater recovery performance. Moreover, cork oak is very tolerant and resilient to extreme droughts. Nevertheless, there are other factors that affect cork growth during and after drought, namely site, tree and the age of the phellogen. In fact, in the first 2 years and in the last 2 years of the production cycle the effects of drought on growth are more pronounced than in the middle of the cycle. The age of the phellogen is significant in the recovery, resistance and resilience but not in the relative resilience. The most noticeable differences occurred in the recovery for phellogen under 3 years (17% lower than that for phellogen with 3 to 6 years of age). Moreover, under drought conditions, there is a strong evidence that forest managers should enlarge debarking rotations, namely if drought occurs in the first 2 years of the production cycle and/or establish new cork oak stands in more humid areas, namely, in higher latitudes than the actual species distribution area.
       
  • In-situ monitoring of soil water isotopic composition for partitioning of
           evapotranspiration during one growing season of sugar beet (Beta vulgaris)
           
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Maria Quade, Anne Klosterhalfen, Alexander Graf, Nicolas Brüggemann, Normen Hermes, Harry Vereecken, Youri Rothfuss Field-based quantitative observations of hydrological feedbacks of terrestrial vegetation to the atmosphere are crucial for improving land-surface model parametrizations. This is especially true in the specific context of partitioning of evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T): land surface models are able to compute E and T separately while observed transpiration fractions (T/ET) are still sparse.In this study, we present the application of an on-line non-destructive method based on gas-permeable tubing for the in-situ collection of soil water vapor. This allowed for monitoring of the hydrogen and oxygen isotopic compositions (δ2H and δ18O) of soil water during a field campaign where ET of sugar beet (Beta vulgaris) was partitioned. T/ET estimates obtained with the non-destructive method were compared with the commonly used destructive sampling of soil and subsequent cryogenic extraction of soil water under vacuum. Finally, isotope-based T/ET estimates were compared to those obtained from a combination of micro-lysimeter and eddy covariance (EC) measurements. Significant discrepancies between the values of isotopic composition of evaporation derived destructively and non-destructively from those of soil water using a well-known transfer resistance model led in turn to significant differences in T/ET. This is in line with recent findings on the systematic offsets of soil water isotopic composition values in relation to the water sampling and extraction measurement techniques and calls for further investigation of these isotopic offsets for accurate separation of E from T in the field. These discrepancies were, however, smaller than those observed between δ2H- or δ18O-based T/ET estimates, and more than three times smaller than those between isotope-based and lysimeter-based estimates.
       
  • Soil water repellency decreases summer maize growth
    • Abstract: Publication date: 15 March 2019Source: Agricultural and Forest Meteorology, Volumes 266–267Author(s): Yi Li, Ning Yao, Dexiu Tang, Henry Wai Chau, Hao Feng A two-year summer maize irrigation experiment was conducted in soil lysimeters under a rain-shelter to analyze the effects of water repellency on soil moisture, evapotranspiration, crop growth, and yields. Soil water droplet penetration time (WDPT) was initially 1, 7, 9, 12 and 16 s, showing wettable or slight water repellency, denoted as the treatments CK, WR1, WR2, WR3, and WR4, respectively. Soil water storage dynamics were observed using the lysimeters. The WDPT and volumetric soil water content (θv) on surface soil was measured daily. The results revealed that WDPT values of all the five treatments increased significantly as the sowing days increased and reached peaks before the subsequent irrigation. However, the peak decreased as irrigation events increased. The maximum WDPT values of CK, WR1, WR2, WR3, and WR4 were 31, 2000, 2200, 2300 and 2355s during the entire crop growth period, and indicated more persistent water repellency than the initial conditions. During the two irrigations, θv decreased with the increase of WDPT. The daily and cumulative evapotranspiration at the early growth stage differed slightly but decreased from CK to WR4 at the later crop growth stages. Likewise, soil water storage increased. The higher water consumption of summer maize in CK resulted in lower soil water storage and good plant growth, thus in soils with higher WDPTs, the lower values of LAI, the mass of roots and leaves, and root lengths were noted. The crop growth decreased regularly with the increase in initial WDPT. The main reason was due to a decrease in soil water availability for the crop and impeded root water uptake as the initial WDPT increased. The variation in initial WDPTs had a significant impact on WUE. In conclusion, more persistent water repellent soils result in a decrease in summer maize growth.
       
  • Scaling and balancing methane fluxes in a heterogeneous tundra ecosystem
           of the Lena River Delta
    • Abstract: Publication date: Available online 15 November 2018Source: Agricultural and Forest MeteorologyAuthor(s): Norman Rößger, Christian Wille, Georg Veh, Julia Boike, Lars Kutzbach Methane fluxes on an active flood plain situated in the Siberian Lena River Delta were studied applying the eddy covariance method. During the growing season, the observed fluxes exhibited a great deal of temporal variability, which was largely the result of the pronounced spatial variability of soil and vegetation characteristics within the footprint. Explaining this variability was based on three data-driven modelling approaches: the automatically operating algorithms stepwise regression as well as neural network, and a mechanistic model, which utilised exponential relationships between the methane flux and both flux drivers soil temperature and friction velocity. A substantial improvement in model performance was achieved by applying footprint information in the form of relative contributions of three vegetation classes to the flux signal. This aspect indicates that the vegetation served as an integrated proxy for flux drivers, whose characteristics permanently varied according to the shifting source area. The neural network performed best in explaining the variability of the observed methane fluxes. However, validating the models’ generalisability revealed that the mechanistic model provided the most predictive power suggesting that this model best captured the causality between the methane flux and its drivers. After integrating the gap-filled time series, all models yielded footprint budgets that were similar in magnitude. These budgets, however, lacked representativity due to the sensor location bias, i.e. their strong dependence on tower location, measurement height and wind field conditions. Thus, an unbiased budget of the total area of the flood plain was estimated utilising the mechanistic model. Initially, a downscaling procedure partitioned the observed flux with a seasonal mean of 0.012 μmol m-2 s-1 into three individual vegetation class fluxes accounting for shrubs (0.0004 μmol m-2 s-1), sedges (0.052 μmol m-2 s-1) and intermediate vegetation (0.018 μmol m-2 s-1). These decomposed fluxes in turn formed the basis – in conjunction with a classified high-resolution orthomosaic of the flood plain – for the vegetation class area-weighted upscaling. Alternatively, the straightforward upscaling of the footprint budgets (without the preceding downscaling) yielded budgets that underestimated the methane source strength of the flood plain by roughly 42 %. Hence, the application of fine-scale information on surface characteristics is crucial for both modelling methane flux dynamics and adequately estimating budgets of heterogeneous ecosystems being abundant in the tundra biome.
       
 
 
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