for Journals by Title or ISSN
for Articles by Keywords

Publisher: Elsevier   (Total: 3177 journals)

 A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

        1 2 3 4 5 6 7 8 | Last   [Sort by number of followers]   [Restore default list]

Showing 1 - 200 of 3177 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 9)
AASRI Procedia     Open Access   (Followers: 14)
Academic Pediatrics     Hybrid Journal   (Followers: 30, SJR: 1.402, h-index: 51)
Academic Radiology     Hybrid Journal   (Followers: 22, SJR: 1.008, h-index: 75)
Accident Analysis & Prevention     Partially Free   (Followers: 87, SJR: 1.109, h-index: 94)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.612, h-index: 27)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 35, SJR: 2.515, h-index: 90)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 6, SJR: 0.338, h-index: 19)
Acta Astronautica     Hybrid Journal   (Followers: 387, SJR: 0.726, h-index: 43)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 2.02, h-index: 104)
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: 0.172, h-index: 29)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.123, h-index: 8)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.604, h-index: 38)
Acta Materialia     Hybrid Journal   (Followers: 243, SJR: 3.683, h-index: 202)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.615, h-index: 21)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.442, h-index: 21)
Acta Oecologica     Hybrid Journal   (Followers: 10, SJR: 0.915, h-index: 53)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, SJR: 0.311, h-index: 16)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1)
Acta Poética     Open Access   (Followers: 4)
Acta Psychologica     Hybrid Journal   (Followers: 25, SJR: 1.365, h-index: 73)
Acta Sociológica     Open Access  
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.059, h-index: 77)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.383, h-index: 19)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.141, h-index: 3)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3, SJR: 0.112, h-index: 2)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 6)
Acute Pain     Full-text available via subscription   (Followers: 14)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.967, h-index: 57)
Addictive Behaviors     Hybrid Journal   (Followers: 15, SJR: 1.514, h-index: 92)
Addictive Behaviors Reports     Open Access   (Followers: 7)
Additive Manufacturing     Hybrid Journal   (Followers: 9, SJR: 1.039, h-index: 5)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Cement Based Materials     Full-text available via subscription   (Followers: 3)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 135, SJR: 5.2, h-index: 222)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.265, h-index: 53)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, SJR: 0.739, h-index: 33)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.299, h-index: 15)
Advances in Agronomy     Full-text available via subscription   (Followers: 12, SJR: 2.071, h-index: 82)
Advances in Anesthesia     Full-text available via subscription   (Followers: 27, SJR: 0.169, h-index: 4)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 1.054, h-index: 35)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 10, SJR: 0.801, h-index: 26)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 22, SJR: 1.286, h-index: 49)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 3.31, h-index: 42)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.277, h-index: 43)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.619, h-index: 48)
Advances in Cancer Research     Full-text available via subscription   (Followers: 29, SJR: 2.215, h-index: 78)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 7, SJR: 0.9, h-index: 30)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 2.139, h-index: 42)
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: 0.183, h-index: 23)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.665, h-index: 29)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 10, SJR: 1.268, h-index: 45)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 28, SJR: 0.938, h-index: 33)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 2.314, h-index: 130)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.223, h-index: 22)
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: 8)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 21)
Advances in Ecological Research     Full-text available via subscription   (Followers: 42, SJR: 3.25, h-index: 43)
Advances in Engineering Software     Hybrid Journal   (Followers: 27, SJR: 0.486, h-index: 10)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 43, SJR: 5.465, h-index: 64)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 7)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 53, SJR: 0.674, h-index: 38)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 15)
Advances in Genetics     Full-text available via subscription   (Followers: 15, SJR: 2.558, h-index: 54)
Advances in Genome Biology     Full-text available via subscription   (Followers: 8)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 2.325, h-index: 20)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21, SJR: 0.906, h-index: 24)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 9, SJR: 0.497, h-index: 31)
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: 0.396, h-index: 27)
Advances in Immunology     Full-text available via subscription   (Followers: 36, SJR: 4.152, h-index: 85)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 1.132, h-index: 42)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 2, SJR: 1.274, h-index: 27)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 3)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.764, h-index: 15)
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: 15, SJR: 1.645, h-index: 45)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.261, h-index: 65)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.489, h-index: 25)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.44, h-index: 51)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 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: 0.324, h-index: 8)
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: 15, SJR: 2.885, h-index: 45)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 6, SJR: 0.148, h-index: 11)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 2.37, h-index: 73)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.4, h-index: 28)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 10)
Advances in Pharmacology     Full-text available via subscription   (Followers: 15, SJR: 1.718, h-index: 58)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.384, h-index: 26)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.248, h-index: 11)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 7)
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: 17)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 18, SJR: 1.5, h-index: 62)
Advances in Psychology     Full-text available via subscription   (Followers: 59)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.478, h-index: 32)
Advances in Radiation Oncology     Open Access  
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.1, h-index: 2)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 5)
Advances in Space Research     Full-text available via subscription   (Followers: 386, SJR: 0.606, h-index: 65)
Advances in Structural Biology     Full-text available via subscription   (Followers: 5)
Advances in Surgery     Full-text available via subscription   (Followers: 9, SJR: 0.823, h-index: 27)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 29, SJR: 1.321, h-index: 56)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 17)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 1.878, h-index: 68)
Advances in Water Resources     Hybrid Journal   (Followers: 46, SJR: 2.408, h-index: 94)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 0.973, h-index: 22)
Aerospace Science and Technology     Hybrid Journal   (Followers: 336, SJR: 0.816, h-index: 49)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.318, h-index: 36)
African J. of Emergency Medicine     Open Access   (Followers: 6, SJR: 0.344, h-index: 6)
Ageing Research Reviews     Hybrid Journal   (Followers: 10, SJR: 3.289, h-index: 78)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 437, SJR: 1.385, h-index: 72)
Agri Gene     Hybrid Journal  
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 15, SJR: 2.18, h-index: 116)
Agricultural Systems     Hybrid Journal   (Followers: 31, SJR: 1.275, h-index: 74)
Agricultural Water Management     Hybrid Journal   (Followers: 43, SJR: 1.546, h-index: 79)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 1)
Agriculture and Natural Resources     Open Access   (Followers: 2)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 56, SJR: 1.879, h-index: 120)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.434, h-index: 14)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.234, h-index: 18)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.285, h-index: 3)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 0.922, h-index: 66)
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: 0.436, h-index: 12)
Alexandria J. of Medicine     Open Access   (Followers: 1)
Algal Research     Partially Free   (Followers: 9, SJR: 2.05, h-index: 20)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.46, h-index: 29)
Allergology Intl.     Open Access   (Followers: 5, SJR: 0.776, h-index: 35)
Alpha Omegan     Full-text available via subscription   (SJR: 0.121, h-index: 9)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.158, h-index: 9)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 48, SJR: 4.289, h-index: 64)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 50, SJR: 3.157, h-index: 153)
American J. of Cardiology     Hybrid Journal   (Followers: 51, SJR: 2.063, h-index: 186)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 44, SJR: 0.574, h-index: 65)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10, SJR: 1.091, h-index: 45)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.653, h-index: 93)
American J. of Human Genetics     Hybrid Journal   (Followers: 31, SJR: 8.769, h-index: 256)
American J. of Infection Control     Hybrid Journal   (Followers: 26, SJR: 1.259, h-index: 81)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 34, SJR: 2.313, h-index: 172)
American J. of Medicine     Hybrid Journal   (Followers: 42, SJR: 2.023, h-index: 189)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 197, SJR: 2.255, h-index: 171)
American J. of Ophthalmology     Hybrid Journal   (Followers: 62, SJR: 2.803, h-index: 148)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 6)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.249, h-index: 88)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, h-index: 45)
American J. of Pathology     Hybrid Journal   (Followers: 27, SJR: 2.653, h-index: 228)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 27, SJR: 2.764, h-index: 154)
American J. of Surgery     Hybrid Journal   (Followers: 37, SJR: 1.286, h-index: 125)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.653, h-index: 70)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 6)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.066, h-index: 51)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 62, SJR: 0.124, h-index: 9)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 14)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.209, h-index: 27)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription   (SJR: 0.104, h-index: 3)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 4, SJR: 2.577, h-index: 7)
Analytica Chimica Acta     Hybrid Journal   (Followers: 39, SJR: 1.548, h-index: 152)
Analytical Biochemistry     Hybrid Journal   (Followers: 171, SJR: 0.725, h-index: 154)
Analytical Chemistry Research     Open Access   (Followers: 10, SJR: 0.18, h-index: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 1)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 22, SJR: 0.421, h-index: 40)
Angiología     Full-text available via subscription   (SJR: 0.124, h-index: 9)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 8 | Last   [Sort by number of followers]   [Restore default list]

Journal Cover Agricultural and Forest Meteorology
  [SJR: 2.18]   [H-I: 116]   [15 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0168-1923
   Published by Elsevier Homepage  [3177 journals]
  • Assessment of the effect of plastic mulching on soil respiration in the
           arid agricultural region of China under future climate scenarios
    • Authors: Yongxiang Yu; Hui Tao; Huaiying Yao; Chengyi Zhao
      Pages: 1 - 9
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Yongxiang Yu, Hui Tao, Huaiying Yao, Chengyi Zhao
      The application of plastic film to agricultural fields has been widely used in the arid and semi-arid regions of China to improve crop productivity and soil organic carbon storage. However, the impact of this practice on soil respiration under future climate scenarios remains poorly understood. Process-based model is a useful tool for simulating the effect of this practice on soil biochemical processes and for predicting future changes in soil respiration under different climate scenarios. In this study, the denitrification-decomposition (DNDC) model was evaluated against measured soil respiration. The DNDC model was used to simulate the temporal variation of soil respiration, and the application of plastic film increased the cumulative carbon dioxide (CO2) emissions compared with that of the fields without plastic film. Sensitivity tests indicated that plastic mulching decreased the sensitivity of DNDC-simulated soil respiration and plant biomass to changes in the temperature, precipitation and CO2 concentration. Across different climate scenarios, the DNDC model predicted that both soil respiration and plant biomass in the mulched treatment slightly changed from −0.2% to 2.1% and from −0.7% to 1.2%, respectively; and in the non-mulched treatment, soil respiration and biomass changed from −4.7% to 10.9% and from −8.7% to 7.8%, respectively. In the arid agricultural region of China, if the pollution of residual mulch film in the fields can be effectively controlled, the application of plastic film is an efficient method for increasing crop productivity and would likely mitigate changes in soil respiration under future climate scenarios.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.025
      Issue No: Vol. 256-257 (2018)
  • Water availability is more important than temperature in driving the
           carbon fluxes of an alpine meadow on the Tibetan Plateau
    • Authors: Tao Zhang; Yangjian Zhang; Mingjie Xu; Juntao Zhu; Ning Chen; Yanbin Jiang; Ke Huang; Jiaxing Zu; Yaojie Liu; Guirui Yu
      Pages: 22 - 31
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Tao Zhang, Yangjian Zhang, Mingjie Xu, Juntao Zhu, Ning Chen, Yanbin Jiang, Ke Huang, Jiaxing Zu, Yaojie Liu, Guirui Yu
      Temperature is conventionally considered as the dominant factor regulating carbon fluxes of the alpine meadow on the Tibetan Plateau, while contribution from water availability is composed of large uncertainty. In this study, eddy covariance (EC) data were used to assess the relative contribution of temperature and water availability to carbon fluxes of the alpine meadow ecosystem. The results showed that soil water content (SWC) was the most important factor controlling carbon fluxes – Net Ecosystem Productivity (NEP), Gross Primary Productivity (GPP) and Ecosystem Respiration (Re). The GPP and Re increased with strengthened SWC under any temperature conditions, indicating the dominant control of water availability on carbon fluxes. In addition, water availability regulated the response size of ecosystem to temperature, and could alleviate the stress caused by low temperature. The photosynthesis capacity of alpine plants at noon was depressed by water stress rather than by high temperature. The structural equation modeling (SEM) analysis further confirmed the dominance of SWC on the carbon fluxes. This study implies that effects of climatic change on this alpine ecosystem might be more induced by changes in water pattern than increased temperature, which provides new insights into the climate controls of carbon fluxes over alpine meadow, and adds to our understanding on climate change impacts on carbon cycling on the Tibetan Plateau.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.027
      Issue No: Vol. 256-257 (2018)
  • Evolution of rain and photoperiod limitations on the soybean growing
    • Authors: Gabriel M. Abrahão; Marcos H. Costa
      Pages: 32 - 45
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Gabriel M. Abrahão, Marcos H. Costa
      Over the course of a few decades, soybeans in Brazil evolved from being a localized crop, with planting suitable only in regions with long photoperiods, to being the most cultivated crop countrywide. This happened thanks to the development of varieties that allowed changes in the planting calendar, permitting both cultivation in lower latitudes and the adoption of modern double-cropping systems. Here we develop a spatial dataset of Brazilian soy planting-window estimates for rainfed single and double cropping as a function of time during the period 1974–2012 by combining estimates of two important historical limitations: photoperiod and duration and timing of the rainy season. We apply the same methods to future climate estimates to investigate a possible contraction in the area of double cropping due to changes in the rainy season with global change. The resulting dataset agrees with time-invariant official agricultural zoning and optimal yield experiments and provides unprecedented spatial and temporal information on the soy growing season in Brazil. Analysis of the evolution of planting limitations shows that the relaxation of photoperiod limitations gradually made double cropping possible in central–northern Brazil in the 1980s by lengthening the planting window and allowing farmers to make use of a larger portion of the rainy season. Due to these developments, there were 20 Mha potentially suitable for double cropping in 2012, and this potential has been increasingly exploited. Under the constraints of current widely used crop varieties, we predict that climate change poses a severe threat to this potential, causing area reductions of ∼17% in central Brazil and 61% in the MATOPIBA region, known as the world’s newest agricultural frontier.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.031
      Issue No: Vol. 256-257 (2018)
  • Can we use crop modelling for identifying climate change adaptation
    • Authors: Marc Corbeels; David Berre; Leonard Rusinamhodzi; Santiago Lopez-Ridaura
      Pages: 46 - 52
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Marc Corbeels, David Berre, Leonard Rusinamhodzi, Santiago Lopez-Ridaura
      Climate model projections coupled with process-based crop models are advocated for assessing impacts of climate change on crop yields and for informing crop-level adaptations. However, most reported studies are vague on the choice of the global circulation models (GCMs) for climate projections, and on the corresponding uncertainty with this type of model simulations. Here we investigated whether climate-crop modelling can be used for identifying crop management-level adaptation options. We focused our analyses on a case study for maize in southern Africa using the APSIM crop growth model and projections from 17 individual climate models for the period 2017–2060 for the contrasting representative concentration pathways 2.6 and 8.5. Intensification of nitrogen fertiliser use (from 30 to 90 kg N ha−1) was simulated as an example of a crop management-level adaptation to climate change. Uncertainties in crop yield predictions were about 30 to 60%, i.e. larger than expected crop responses to most management-level interventions or adaptations. Variation in simulated yields was caused by inter-seasonal rainfall variability and uncertainty with climate models. Some GCMs resulted in significantly different maize yield predictions, without any clear pattern across sites. Given these high uncertainties, we argue that crop modellers should be cautious when informing future crop management adaptation strategies based on climate-crop model ensembles. A better use of crop models is the simulation of crop responses to current weather variability aiming at the identification of crop management practices for coping with climate variability. Promising practices can then be evaluated with farmers on their feasibility over a range of plausible future biophysical and socio-economic farming conditions.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.026
      Issue No: Vol. 256-257 (2018)
  • The wind field in a cattle feedlot: measurements and simulations
    • Authors: J.D. Wilson; T.K. Flesch; S.M. McGinn
      Pages: 84 - 92
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): J.D. Wilson, T.K. Flesch, S.M. McGinn
      Cup and sonic anemometers were operated in and about an empty pen (60 m × 68 m) on the outer (south) edge of a large cattle feedlot in southern Alberta. Mean wind speed, measured at constant height above ground, varied by more than a factor of four across the pen, the spatial transects being distinct for different wind directions—implying (for instance) that efforts to quantify feedlot gas emissions by micrometeorological methods will be prone to error, unless the drastic lateral inhomogeneity of wind statistics is accounted for. A subset of the observations, selected for southerly winds and weak thermal stratification, were aggregated and compared with steady-state, three-dimensional numerical simulations using “ASL3D”, a Reynolds-averaged Navier–Stokes model with eddy viscosity closure that represents the influences both of feedlot windbreak fences and of topography (Wilson, 2018). Simulations confirm that wind drag on the tall (H ≈ 3 m), low porosity (25%) slatted wooden fences was by far the dominant aerodynamic disturbance at this site. Various options were tested for the placement of computational domain boundaries, and it was found that the influence of fences at the faraway edges of neighbouring pens is practically negligible in comparison with that of the fences lying immediately upwind—that is, the transect of relative mean wind speed within the instrumented pen was largely determined by the nearest upwind fence(s). It is also concluded that when the mean wind is obliquely incident on low porosity fences of this type, simulations are improved if the horizontal wind component tangential to the fence is forced to vanish (at the fence).

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.024
      Issue No: Vol. 256-257 (2018)
  • Seasonal and inter-annual variability of soil CO2 efflux in a Norway
           spruce forest over an eight-year study
    • Authors: Manuel Acosta; Eva Darenova; Lenka Krupková; Marian Pavelka
      Pages: 93 - 103
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Manuel Acosta, Eva Darenova, Lenka Krupková, Marian Pavelka
      Automated soil CO2 efflux chamber measurements were carried out over a period of eight years in a young Norway spruce forest in the northeast region of the Czech Republic to determine seasonal and inter-annual variables affecting this flux. The data obtained was summarized and analysed with the aims of estimating long-term carbon losses from the soil and comparing selected models to determine the model best describing soil CO2 efflux. Our results show that seasonal variation in soil CO2 efflux was driven mainly by soil temperature, while inter-annual variation showed the closest relationship with precipitation. The total amount of carbon released from the soil into the atmosphere per season varied from 6.4 to 11.2 tC ha−1 over the eight-year record. One of the variables used in the CO2 efflux models, beside environmental variables, was day of year (DOY). Incorporating this variable into models improved the estimation of soil CO2 efflux dynamics. Therefore, we assume that models incorporating DOY could be used effectively to gap-fill measured soil chamber data. These models could also be appropriate for filling longer gaps on a scale from days to weeks, because DOY, as a single parameter, covers up to 80% of variability in the data. This study also demonstrated the different levels of correlation between investigated climate variables and soil CO2 efflux at seasonal and inter-annual time scales. This highlights the importance of different environmental variables in interpreting long-term soil CO2 efflux data and also modelling the complexity of the processes connected with soil CO2 efflux in Norway spruce forest.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.005
      Issue No: Vol. 256-257 (2018)
  • Global patterns of vegetation carbon use efficiency and their climate
           drivers deduced from MODIS satellite data and process-based models
    • Authors: Yue He; Shilong Piao; Xiangyi Li; Anping Chen; Dahe Qin
      Pages: 150 - 158
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Yue He, Shilong Piao, Xiangyi Li, Anping Chen, Dahe Qin
      Carbon use efficiency (CUE), defined as the ratio of net primary production (NPP) to gross primary production (GPP), represents the capacity of plants in converting assimilated atmospheric carbon dioxide to ecosystem carbon storage. Process-based models are important tools for simulating NPP and GPP; yet the model performance in simulating vegetation CUE has not been fully explored. The goal of this paper is thus to investigate the spatial variations in CUE from different process-based carbon cycle models in comparison with that from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, and to analyze their linkage with climate factors. The global average CUE derived from the five process-based models is 0.45 ± 0.05 (range from 0.38 to 0.52), slightly lower than the value of 0.48 obtained from MODIS data. A strong latitudinal gradient of CUE, with greater CUE at high latitudes, is well agreed by these different datasets. However, there also exist considerable discrepancies in CUE estimations among those products, especially in temperate Northern Hemisphere. Furthermore, for both the satellite-based dataset and results from process-based models, vegetation CUE declines non-linearly with increase in temperature, but remains relatively stable with enhanced precipitation. Our results also indicate that the differences in global patterns of CUE estimated by different approaches could be primarily resulted from their systematic differences in autotrophic respiration (Ra) rather than in GPP. Understanding mechanisms behind spatio-temporal changes in Ra is therefore a critical step towards better quantifying global CUE.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.009
      Issue No: Vol. 256-257 (2018)
  • Analysis of evapotranspiration components of a rainfed olive orchard
           during three contrasting years in a semi-arid climate
    • Authors: W. Chebbi; G. Boulet; V. Le Dantec; Z. Lili Chabaane; P. Fanise; B. Mougenot; H. Ayari
      Pages: 159 - 178
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): W. Chebbi, G. Boulet, V. Le Dantec, Z. Lili Chabaane, P. Fanise, B. Mougenot, H. Ayari
      Evapotranspiration is one of the most important fluxes of the water budget in semi-arid areas. The estimation of actual crop transpiration is a major issue in those regions due to its remarkable impacts on the precision of irrigation scheduling, crop growth and yield. Rainfed olive trees are adapted to the southern part of the Mediterranean basin even though they are vulnerable to an increased number of drought spells that might occur under current climate change scenarios. This present paper studies both water and energy exchanges over a rainfed olive grove in semi-arid conditions. The hydrological functioning of sparse olive trees is difficult to characterize because of its low LAI. To better understand water exchanges within the Soil–Plant–Atmosphere continuum and better evaluate the evapotranspiration and its components, we combine data arising from eddy covariance, soil water content measurements and the sap flow method. First, we check the consistency of the evapotranspiration partitioning and water balance over three contrasted years: one wet and two dry. Total evapotranspiration (ET) from eddy covariance method compares well with the sum of the evaporation (E) generated from the surface soil moisture measurements and the transpiration derived from the sap flow method. The top meter soil water balance corresponds roughly to ET during the wet year but for the dry years there is an evidence of extraction by roots below the first meter of soil. Inter-annual variations of the transpiration and associated water stress levels are analyzed by the combined use of different types of eco-physiological (sap flow) as well as remotely sensed variables that can be monitored through proxi-detection (albedo, surface temperature, surface soil moisture). The amount and timing of vegetation stress are consistent throughout the various indicators. Consequently, this consistent set of data can be used to constrain a SVAT land-surface model capable of representing the various features of the water and energy budget for this specific land cover.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.020
      Issue No: Vol. 256-257 (2018)
  • Scaling up spring phenology derived from remote sensing images
    • Authors: Dailiang Peng; Chaoyang Wu; Xiaoyang Zhang; Le Yu; Alfredo R. Huete; Fumin Wang; Shezhou Luo; Xinjie Liu; Helin Zhang
      Pages: 207 - 219
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Dailiang Peng, Chaoyang Wu, Xiaoyang Zhang, Le Yu, Alfredo R. Huete, Fumin Wang, Shezhou Luo, Xinjie Liu, Helin Zhang
      Land surface phenology, especially spring phenology, has been reported as a powerful indicator of ecosystem responses to climate change. It also exerts strong control on the carbon, water and energy balances and, hence, climatic feedbacks. Researchers have produced numerous spring phenology products from various coarse-resolution remote sensing data at regional or global scales. Scaling up observations of spring phenology from plot-level (or finer resolution) to coarser resolution is important for the validation, synthesis, and evaluation of those products. The best method for scaling up is unclear although coarse resolution data can be obtained by averaging across fine-scale pixels, or selecting the start of spring phenology (SOS) date associated with the earliest 30% (or another percentile) of fine-scale pixels within a coarse-scale pixel. In this study, we tested different methods that were average and percentile approaches to aggregate SOS as measured at 250 m (SOS (250 m)) resolution to 8 km (SOS (8 km)) resolution pixels, and then to ecosystems and national scales for the continental United States. The results indicated that the average absolute difference (AAD) between SOS (250 m) and SOS (8 km) from the average approach was close to that achieved by the percentile approach. Relatively large AAD values occurred in the western and southern regions of the continental United States. The distribution of AAD was positively related to landscape heterogeneity. The percentile approach generally yielded smaller AADs than the average approach did, but these two approaches performed similarly. Across landscapes and ecosystems, the optimal percentile usually ranged from 30–45th instead of a single value. Our findings indicated that the percentile approach may be best for finer scale areas, but that the average approach is an adequate alternative for scaling up SOS in most circumstances. In addition, the detailed error distributions of scaling up spring phenology across scales are helpful to identify the appropriate method of scaling up for validating the coarse SOS products derived from remote sensing images.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.010
      Issue No: Vol. 256-257 (2018)
  • Rainfed maize yield response to management and climate covariability at
           large spatial scales
    • Authors: Elizabeth K. Carter; Jeff Melkonian; Scott Steinschneider; Susan J. Riha
      Pages: 242 - 252
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Elizabeth K. Carter, Jeff Melkonian, Scott Steinschneider, Susan J. Riha
      Statistical analyses of yield and climate data across large spatial scales are an important method for exploring crop sensitivity to a variable and changing climate. However, a variety of issues complicate the interpretation of climate impacts on yield, including spatial and temporal collinearity among climate variables and between climate and management variables, as well as complex responses of yield to interactions among climate variables across different growth development phases. All of these issues, if unaccounted for, can compromise yield projections under climate change. In this study, we present a series of nested models to analyze rainfed maize (Zea mays L.) yield response to climate (temperature, precipitation, solar radiation) at specific growth-development phases and under different crop management practices. The models, fit using elastic net regression to address collinearity, indicate that spatial gradients in management, which occur at the same scale as climate variability, explain the majority of location-based and total yield variance. Coefficient estimates of yield responses to high temperature/low precipitation conditions during key growth development phases are consistent with reported physiological responses of maize, but only when interaction terms are included between temperature and precipitation. Yield responses to temperature and solar radiation are also modified by prior temperature regime. Overall, failure to parameterize management practices and interactions between temperature and precipitation leads to systemic errors in models linking maize yields to climate impacts at large spatial scales, both under current and projected climate.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.029
      Issue No: Vol. 256-257 (2018)
  • BESS-Rice: A remote sensing derived and biophysical process-based rice
           productivity simulation model
    • Authors: Yan Huang; Youngryel Ryu; Chongya Jiang; Hyungsuk Kimm; Soyoun Kim; Minseok Kang; Kyomoon Shim
      Pages: 253 - 269
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Yan Huang, Youngryel Ryu, Chongya Jiang, Hyungsuk Kimm, Soyoun Kim, Minseok Kang, Kyomoon Shim
      Conventional process-based crop simulation models and agro-land surface models require numerous forcing variables and input parameters. The regional application of these crop simulation models is complicated by factors concerning input data requirements and parameter uncertainty. In addition, the empirical remotely sensed regional scale crop yield estimation method does not enable growth process modeling. In this study, we developed a process-based rice yield estimation model by integrating an assimilate allocation module into the satellite remote sensing-derived and biophysical process-based Breathing Earth System Simulator (BESS). Normalized accumulated gross primary productivity ( G P P n o r m - a c c u ) was used as a scaler for growth development, and the relationships between G P P n o r m - a c c u and dry matter partitioning coefficients were determined from the eddy covariance and biometric measurements at the Cheorwon Rice paddy KoFlux site. Over 95% of the variation in the dry matter allocation coefficients of rice grain could be explained by G P P n o r m - a c c u . The dynamics of dry matter distribution among different rice components were simulated, and the annual grain yields were estimated. BESS-Rice simulated GPP and dry matter partitioning dynamics, and rice yields were evaluated against in-situ measurements at three paddy rice sites registered in KoFlux. The results showed that BESS-Rice performed well in terms of rice productivity estimation, with average root mean square error (RMSE) value of 2.2 g C m−2 d−1 (29.5%) and bias of –0.5 g C m−2 d−1 (–7.1%) for daily GPP, and an average RMSE value of 534.8 kg ha−1 (7.7%) and bias of 242.1 kg ha−1 (3.5%) for the annual yield, respectively. BESS-Rice is much simpler than conventional crop models and this helps to reduce the uncertainty related to the forcing variables and input parameters and can result in improved regional yield estimation. The process-based mechanism of BESS-Rice also enables an agronomic diagnosis to be made and the potential impacts of climate change on rice productivity to be investigated.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.014
      Issue No: Vol. 256-257 (2018)
  • Identifying key meteorological factors to yield variation of potato and
           the optimal planting date in the agro-pastoral ecotone in North China
    • Authors: Jianzhao Tang; Jing Wang; Enli Wang; Qiang Yu; Hong Yin; Di He; Xuebiao Pan
      Pages: 283 - 291
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Jianzhao Tang, Jing Wang, Enli Wang, Qiang Yu, Hong Yin, Di He, Xuebiao Pan
      Precipitation is the key yield–determining factor for rainfed agricultural production such as the agro-pastoral ecotone in North China with high variation in precipitation. However, the yield–precipitation relationship depends on the distribution and amount of precipitation over the crop growth period. Understanding crop yield responses to precipitation can help develop appropriate measures to ensure stable crop production in the agro-pastoral ecotone. In this study, an experiment was conducted consisting of five planting dates each year across four years and three planting dates in one year, to investigate the potato yield response to precipitation at a representative site (Wuchuan) in the ecotone. The optimal planting date, with the highest potato yield, varied substantially in different years during the experimental period. It was found that potato yield had the highest correlation with the ratio of precipitation to potential evapotranspiration during the tuberization stage (PT/ETpT) (R2 = 0.51, P < 0.01), followed by the effective precipitation during the post-tuber bulking period (EPpoTB) (R2 = 0.43, P < 0.01) and during the entire growth period (EPgp) (R2 = 0.28, P < 0.05). The potato yield was positively related to total solar radiation during the growth period (Sgp) (R2 = 0.37, P < 0.01), especially during the pre-tuber bulking period (SprTB) (R2 = 0.44, P<0.01), while growth-period maximum temperature (Tmaxgp) had a negative effect on potato yield (R2 = 0.27, P < 0.05). The multiple linear regression equation of potato yield and meteorological factors during the potato growth period showed that the variation in PT/ETpT, EPpoTB and SprTB could explain 71% of the variation in potato yield. The optimal planting dates, based on the 80 t h percentile of the highest yield related to PT/ETpT, EPpoTB and SprTB within the potential planting window from 1961 to 2010, were found to be May 27–June 12 for a wet year, May 3–May 26 for a normal year, and April 4–May 2 for a dry year, if sufficient soil moisture could ensure emergence of potato.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.022
      Issue No: Vol. 256-257 (2018)
  • Spatiotemporal dynamics of leaf transpiration quantified with time-series
           thermal imaging
    • Authors: Gerald F.M. Page; Jean F. Liénard; Matthew J. Pruett; Kevan B. Moffett
      Pages: 304 - 314
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Gerald F.M. Page, Jean F. Liénard, Matthew J. Pruett, Kevan B. Moffett
      Accurately capturing the spatiotemporal dynamics of transpiration from sub-leaf to ecosystem scales remains a key challenge in eco-physiology and hydrology as typical methods face a trade-off between spatial coverage and temporal resolution. Here, we developed a new scalable, semi-automated method to produce highly precise estimates of water and energy fluxes and applied it to single leaves. High-resolution thermal infrared (TIR) images and paired colour photographs of excised soybean leaves were captured at 15 s intervals until wilting, automatically registered and segmented, and used as input for transient energy balance models to estimate latent heat flux (transpiration) at a temporal resolution of one second. Three approaches to estimating leaf boundary layer conductance to heat (g Ha ) and sensible heat flux were compared, two of which did not require the use of any dry or wet reference surface. The accuracy of water loss modeled using average leaf temperature was also compared to models retaining pixel-scale temperature heterogeneity at a spatial resolution of 0.326 mm2. Cumulative leaf water-losses modeled using average leaf temperature closely matched gravimetric measurements (r 2 = 0.95) and pixel-scale models identified striking spatiotemporal patterns of water loss at the sub-leaf scale. Different methods of estimating g Ha did not significantly alter model results. Use of leaf energy balance models with time series thermal images to quantify transient transpiration fluxes was able to accurately resolve 1-s time-varying leaf water loss in outdoor conditions, did not require any reference surfaces, and also produced data on the characteristic length scales of heterogeneous sub-leaf response. Given the ability to omit reference surfaces and retain accuracy, this approach also has the potential to be scaled-up to quantify energy fluxes in more complex plant canopies.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.02.023
      Issue No: Vol. 256-257 (2018)
  • Comparing crop growth and carbon budgets simulated across AmeriFlux
           agricultural sites using the Community Land Model (CLM)
    • Authors: Ming Chen; Tim J. Griffis; John M. Baker; Jeffrey D. Wood; Tilden Meyers; Andrew Suyker
      Pages: 315 - 333
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Ming Chen, Tim J. Griffis, John M. Baker, Jeffrey D. Wood, Tilden Meyers, Andrew Suyker
      Improvement of process-based crop models is needed to achieve high fidelity forecasts of regional energy, water, and carbon exchanges. However, most state-of-the-art Land Surface Models (LSMs) assessed in the fifth phase of the Coupled Model Inter-comparison project (CMIP5) simulated crops as unmanaged C3 or C4 grasses. This study evaluated the crop-enabled version of one of the most widely used LSMs, the Community Land Model (CLM4-Crop), for simulating corn and soybean agro-ecosystems at relatively long-time scales (up to 11 years) using 54 site-years of data. We found that CLM4-Crop had a biased phenology during the early growing season and that carbon emissions from corn and soybean were underestimated. The model adopts universal physiological parameters for all crop types neglecting the fact that different crops have different specific leaf area, leaf nitrogen content and vcmax25, etc. As a result, model performance varied considerably according to crop type. Overall, the energy and carbon exchange of corn systems were better simulated than soybean systems. Long-term simulations at multiple sites showed that gross primary production (GPP) was consistently over-estimated at soybean sites leading to very large short and long-term biases. A modified model, CLM4-CropM’, with optimized phenology and calibrated crop physiological parameters yielded significantly better simulations of gross primary production (GPP), ecosystem respiration (ER) and leaf area index (LAI) at both short (hourly) and long-term (annual to decadal) timescales for both soybean and corn.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.012
      Issue No: Vol. 256-257 (2018)
  • Evaluation of the drag coefficients of tree crowns by numerical modeling
           of their free fall
    • Authors: S.А. Borisevich; V.S. Vikhrenko
      Pages: 346 - 352
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): S.А. Borisevich, V.S. Vikhrenko
      The method for evaluation of wind loads and drag coefficients for the trees of different species, size and morphology in natural conditions that does not require special equipment is presented for the first time. Field experiments and numerical simulation were performed for five trees of the Scots pine trees (Pinus sylvestris L.) under free fall. The field experiments were carried out in the forest for symmetrical 23–27 m tall pine trees. The trees were cut by the chainsaw operator and the videos of a tree falling were obtained. Still images were captured from the video every second after the start of movement. Then the tree stem center lines from the images were obtained. After each run, the length and diameter of the stem and the geometrical characteristics of the tree crown were checked. Numerical experiments were carried out using the deformation model of the tree stem that is inspired by the Cosserat theory of elastic rods. Under the assumption that the drag force is distributed along the tree stem according to a triangular load and increases linearly with velocity, the dynamic global behavior of the real trees was reproduced and the tree stem center lines were obtained. By comparing the data of the two experiments, the drag coefficients of the whole pine trees were found.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.020
      Issue No: Vol. 256-257 (2018)
  • Intercropping of coffee with the palm tree, macauba, can mitigate climate
           change effects
    • Authors: Sandro L.S. Moreira; Cleverson V. Pires; Gustavo E. Marcatti; Ricardo H.S. Santos; Hewlley M.A. Imbuzeiro; Raphael B.A. Fernandes
      Pages: 379 - 390
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Sandro L.S. Moreira, Cleverson V. Pires, Gustavo E. Marcatti, Ricardo H.S. Santos, Hewlley M.A. Imbuzeiro, Raphael B.A. Fernandes
      Global climate changes can affect coffee production in Brazil, and in other coffee producing countries. We examined the potential for an agroforestry system with the native species, macauba (Acrocomia aculeata), to mitigate impacts on coffee production by reducing maximal air temperature and photosynthetic active radiation. The objective of this study was to investigate the influence of an agroforestry system with macauba on productivity, microclimatic characteristics and soil physical quality on a coffee plantation in the Atlantic Rainforest biome, in Southern Brazil. We measured soil attributes (moisture, temperature, and physical properties), microclimate conditions (air temperature, photosynthetic active radiation) and coffee production parameters (productivity and yield). Macauba palm trees were planted at different planting densities on the rows and distances from the coffee rows. Planting density of macauba and their distance from the coffee rows affected soil thermal-water regime. Compared with the traditional unshaded sole coffee planting, the intercropped cultivation provided more coffee yield on both macauba density planting and distance evaluated. On the other hand, coffee productivity was increased by agroforestry systems just for 4.2 m distance between palm trees and coffee rows. Planting density of macaubas did not affect coffee yield and productivity. Best coffee harvest in agroforestry systems with macauba was related to higher soil moisture at the depth of 20–40 cm, higher photosynthetic active radiation, and maximum air temperatures lower than 30 °C. Agroforestry with coffee and macauba trees can be an adaptation strategy under future climatic variability and change related to high temperatures and low rainfall.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.026
      Issue No: Vol. 256-257 (2018)
  • Drought sensitivity and stem growth variation of nine alien and native
           tree species on a productive forest site in Germany
    • Authors: Nils Hoffmann; Peter Schall; Christian Ammer; Bertram Leder; Torsten Vor
      Pages: 431 - 444
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Nils Hoffmann, Peter Schall, Christian Ammer, Bertram Leder, Torsten Vor
      Many non-native tree species have been introduced to Europe to improve forest productivity. It is assumed that some of these species are better able than native species to mitigate negative effects of climate change. A high growth-related tolerance to climatic extremes is essential to qualify a tree species’ suitability for cultivation and must be quantified before initiating adaptation measures. This study investigated basal area and volume increment (BAI and VI) data at various stem height positions to evaluate inter-annual growth variation (mean sensitivity) and drought tolerance of seven alien tree species (Acer rubrum L., Betula maximowicziana Regel, Castanea sativa Mill, Cryptomeria japonica D. Don, Metasequoia glyptostroboides Hu et Cheng, Thuja plicata Donn and Tsuga heterophylla Sarg.) which are considered stress tolerant, and two native species (Fagus sylvatica L., Picea abies H. Karst.) in the Arboretum Burgholz in West Germany. We found that mean sensitivity and response to drought (resistance, recovery, resilience) were related; i.e., sensitive species exhibited greater drought response than less sensitive species. In the drought years 2003, 2006 and 2010/2011, VI of the highly sensitive species C. japonica and P. abies and rather moderate sensitive A. rubrum decreased most strongly (36%), while less sensitive C. sativa and T. heterophylla were the most resistant tree species (25% decrease). B. maximowicziana, F. sylvatica, M. glyptostroboides and T. plicata were moderately sensitive to drought events (growth depression by 29%). Recovery after drought showed mainly a reverse response pattern; species with lower resistance recovered faster, but this trade-off was not uniform among species. Across drought events, we observed high variation in the response of individual trees and between different tree species. This finding indicates that species’ drought sensitivity depends strongly on the drought’s onset, duration and frequency. Along tree stems, mean sensitivity and response to drought in 2003 decreased species-specifically from lower to upper stem section height. Thus, quantifying drought sensitivity based solely on breast height measures may result in biased estimates of production declines.
      Graphical abstract image

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.008
      Issue No: Vol. 256-257 (2018)
  • Estimating bamboo forest aboveground biomass using EnKF-assimilated MODIS
           LAI spatiotemporal data and machine learning algorithms
    • Authors: Xuejian Li; Huaqiang Du; Fangjie Mao; Guomo Zhou; Liang Chen; Luqi Xing; Weiliang Fan; Xiaojun Xu; Yuli Liu; Lu Cui; Yangguang Li; Dien Zhu; Tengyan Liu
      Pages: 445 - 457
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Xuejian Li, Huaqiang Du, Fangjie Mao, Guomo Zhou, Liang Chen, Luqi Xing, Weiliang Fan, Xiaojun Xu, Yuli Liu, Lu Cui, Yangguang Li, Dien Zhu, Tengyan Liu
      High-precision LAI (leaf area index) spatiotemporal data obtained from MODIS satellite remote sensing products are important for studying vegetation growth status, biomass carbon reserves, and the spatiotemporal dynamics of carbon cycling. LAI significantly influences biomass accumulation during the growth of bamboo forest in subtropical zones. Therefore, we applied the ensemble Kalman filter (EnKF) data assimilation algorithm to assimilate MODIS LAI products, and used assimilated LAI and the normalized difference vegetation index, enhanced vegetation index, simple ratio index as variables in the random forest model to estimate bamboo forest above ground biomass (AGB) in Zhejiang Province. Assimilated LAI spatiotemporal data using EnKF greatly improve the accuracy of MODIS LAI products, the R2 between assimilated and observed LAI was 0.92, and the RMSE was 0.37. Variations in the assimilated LAI time series were consistent with the seasonal dynamics of bamboo forest growth and had a significant effect on AGB. Moreover, the random forest model had strong predictive capabilities. A comparison of training and testing results produced accuracy (R) values for the random forest model using the assimilated LAI time series of 0.71 and 0.73, respectively. Using the assimilated LAI achieved a more accurate AGB estimate than using MODIS LAI time series products, as the R values were 54.3% and 58.7% higher, and the RMSE values were 19.2% and 19.1% lower for training and testing results, respectively. The calculated spatial distribution of bamboo forest AGB in Zhejiang province was consistent with the observed values. By combining assimilation technology of the MODIS LAI time series with the random forest model to more accurately estimate bamboo forest AGB in Zhejiang province, this study provided a new method for estimating large scale forest AGB based on low-resolution time series data.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.04.002
      Issue No: Vol. 256-257 (2018)
  • Annual emissions of CO2, CH4 and N2O from a temperate peat bog: Comparison
           of an undrained and four drained sites under permanent grass and arable
           crop rotations with cereals and potato
    • Authors: Tanka P. Kandel; Poul Erik Lærke; Lars Elsgaard
      Pages: 470 - 481
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Tanka P. Kandel, Poul Erik Lærke, Lars Elsgaard
      Peatlands drained for agriculture are sources of atmospheric carbon dioxide (CO2) and nitrous oxide (N2O). Resulting emissions may depend on land-use, often as grassland or cropland, but few studies have directly compared the effects of land-uses. Here, we measured annual emissions of CO2, N2O and methane (CH4) from five sites in a temperate bog, representing an undrained natural bog (NB) site, and four drained sites used as permanent grassland (PG) and croplands with rotations of oat-potato, oat-spring barley and potato-spring barley (PO:SB) in the study year. Gas fluxes were measured at 1–2 week intervals using static chambers, and auxiliary data were obtained, such as temperature, depth of water table, ratio-vegetation index, pH and soil mineral N. Annual CO2 emissions were derived from empirical modelling, whereas CH4 and N2O emissions were linearly interpolated between measurement dates by bootstrapping. Soil respiration was lower at the NB site (1.8 Mg CO2-C ha−1 yr−1) than at the drained sites where emissions were in the range of 5.0–8.8 Mg CO2-C ha−1 yr−1. The N2O emission was negligible at NB (0.3 kg N2O ha−1 yr−1), low at three of the drained sites (1.5–3.7 kg N2O ha−1 yr–1), but high at PO:SB (37.7 kg N2O ha−1 yr−1). The CH4 emission was high at NB (172 kg CH4 ha−1 yr−1), but negligible at the drained sites (−1.5 to 1.5 kg CH4 ha−1 yr−1). The soil respiration at the drained sites indicated that peat losses were rather similar among the different cropping systems and depended mostly on drainage status, although soil respiration and peat mineralization may not scale directly. The pattern of N2O emissions suggested an increased risk of N2O emission from potato cultivation before and after the period of potato growth, likely due to microbial availability of NO3 – outside the growing season. For initiatives aiming at reduction of greenhouse gas emissions from agricultural peat soils, this means that, e.g., conversion from cropland to permanent grassland should preferably be accompanied by measures of rewetting, whereas for potato cropping, N availability outside the growing season should be minimized.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.03.021
      Issue No: Vol. 256-257 (2018)
  • Comparing methane emissions estimated using a backward-Lagrangian
           stochastic model and the eddy covariance technique in a beef cattle
    • Authors: Prajaya Prajapati; Eduardo A. Santos
      Pages: 482 - 491
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Prajaya Prajapati, Eduardo A. Santos
      Accurate methodologies to measure emissions of greenhouse gases (GHG) from livestock systems are necessary to improve the emission coefficients used in national GHG inventories and to evaluate mitigation strategies. The objective of this study was to compare methane (CH4) emissions estimated using the eddy covariance (EC) technique and a backward-Lagrangian stochastic (bLS) model. A closed-path EC system was used to measure CH4 fluxes in a commercial beef cattle feedlot. The EC fluxes were scaled from the feedlot to the animal scale using a footprint analysis. The EC measurements of CH4 concentration and wind data were used with the bLS model to infer CH4 emissions. The average CH4 emissions (±standard deviation) during the experiment were 87 (±30) g animal−1 d−1 and 85 (± 27) g animal−1 d−1 for EC and bLS techniques, respectively. These values are consistent with the results from previous studies with similar animal and feed characteristics. Both techniques were able to capture a pronounced daytime and nighttime variation in CH4 emissions, with higher CH4 emissions during the day and lower emissions at night. Our results indicate that the eddy covariance technique combined with footprint models can be successfully used to accurately measure enteric CH4 from cattle.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.04.003
      Issue No: Vol. 256-257 (2018)
  • The relationship between soil CO2 efflux and its carbon isotopic
           composition under non-steady-state conditions
    • Authors: Jian Zhou; Ziyao Yang; Genhong Wu; Yanzheng Yang; Guanghui Lin
      Pages: 492 - 500
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Jian Zhou, Ziyao Yang, Genhong Wu, Yanzheng Yang, Guanghui Lin
      Soil CO2 efflux and its carbon isotopic composition are undoubtedly important for estimating ecosystem carbon budgets and for partitioning respiration sources at various spatial and temporal scales. Under natural conditions, non-steady processes will strongly influence the diffusive fluxes of 13CO2 and 12CO2 between soil and the atmosphere, which results in variations of effluxed soil δ13CO2 and will lead to bias in respiration source partitioning. In this study, we present a set of quantitative relationships between soil CO2 efflux and its δ13C by solving the diffusion equation. The results showed that the effluxed δ13CO2 converged toward the respiratory δ13CO2 with an increasing efflux rate but that the values greatly differed at low efflux rates. Both our own experiments and data from the literature verified this convergence pattern of the effluxed δ13CO2, which implies that most of the variations in the δ13C of soil effluxed CO2 may derive from diffusive fractionation rather than from biological causes. Our results explain the isotopic flux patterns of CO2 under natural environmental variations and are vitally important for isotope-based modeling of ecosystem carbon exchange under changing climatic regimes.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.04.001
      Issue No: Vol. 256-257 (2018)
  • The role of heartwood water storage for sem-arid trees under drought
    • Authors: Guozheng Hu; Hongyan Liu; Huailiang Shangguan; Xiuchen Wu; Xiaotian Xu; Mathew Williams
      Pages: 534 - 541
      Abstract: Publication date: 15 June 2018
      Source:Agricultural and Forest Meteorology, Volumes 256–257
      Author(s): Guozheng Hu, Hongyan Liu, Huailiang Shangguan, Xiuchen Wu, Xiaotian Xu, Mathew Williams
      Stem water storage is an important water pool in forests. However, we know little about the heartwood water use processes and the water use strategies of trees in semi-arid temperate forests. We investigated Simon poplar (Populus simonii), a heartwood water storage tree species. A combination of methods (sap flow, the dendrometer and the soil–plant–atmosphere canopy model were used to trace the water use dynamics of Simon poplar trees. The aim was to understand how this heartwood water storage tree species survives under drought stress. Our field data showed that P. simonii had significantly higher heartwood water content (60%) than other tree species (30%) in the same region. The enhanced tree water deficit (TWD) and continuous stem shrinkage showed that the heartwood water supply was able to maintain sap flow (1.5–4.6 mm/d) during early growing season droughts. The strong water absorption ability of the roots resulted in the quick recovery of TWD, which caused the rain water could hardly reach 50 cm depth in the soil. The weakened link between transpiration and root water assimilation of heartwood water storage trees meant that sap flow was more sensitive to drivers such as air temperature (R  = −0.71, p < 0.01) and vapor pressure deficit (R = 0.69, p < 0.01). These results suggest that heartwood water storage may buffer drought events during the growing season and reduce the wide fluctuation in interannual precipitation. Therefore, heartwood water storage needs to be taken into account when calculating the soil–plant–atmosphere continuum and creating tree survival models.
      Graphical abstract image

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2018.04.007
      Issue No: Vol. 256-257 (2018)
  • Biometeorology – From agricultural origins to a last frontier in
    • Authors: Heping Liu; Gabriel G. Katul
      Pages: 1 - 2
      Abstract: Publication date: 28 May 2018
      Source:Agricultural and Forest Meteorology, Volume 255
      Author(s): Heping Liu, Gabriel G. Katul

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2017.12.247
      Issue No: Vol. 255 (2018)
  • Numerical study of the interplay between thermo-topographic slope flow and
           synoptic flow on canopy transport processes
    • Authors: Xiyan Xu; Chuixiang Yi; Leonardo Montagnani; Eric Kutter
      Pages: 3 - 16
      Abstract: Publication date: 28 May 2018
      Source:Agricultural and Forest Meteorology, Volume 255
      Author(s): Xiyan Xu, Chuixiang Yi, Leonardo Montagnani, Eric Kutter
      Canopy flow resulting from interaction between thermo-topographic slope flow and large-scale synoptic flow is very complicated and has been poorly understood. We apply a Reynolds-averaged Navier-Stokes (RANS) turbulence model to investigate how the interactions between local flow and synoptic winds affect CO2 movement in the canopy layer at the Renon site in the Italian Alps. Since the RANS simulations are compared to the data measured by multiple-tower experiments conducted during CarboEurope-IP advection campaigns (ADVEX) at Renon, our study can be viewed as a case study of a relatively common wooded slope. The thermal condition in the canopy is directly related to the canopy morphology: the dense canopy at our site causes stronger cooling but limits vertical exchange of heat flux, resulting in weak temperature inversion in the deep canopy. Under conditions with no synoptic wind, local flow leads to CO2 build-up mainly at downslope locations and no recirculation is formed. Recirculation that holds high CO2 mole fraction in the canopy is developed only under the condition that local slope wind is enhanced by northerly synoptic winds. No recirculation forms when southerly synoptic wind direction is opposite to the local wind direction, in which case CO2 is quite well mixed. This numerical study approach brings to light a better understanding of the CO2 closure problem: the measured net ecosystem exchange of CO2 is more likely to be underestimated in local non-synoptic slope flow and local synoptic-enhanced slope flow regimes at Renon. However, small-scale heterogeneity in canopy structure, variability in the CO2 source from soil and higher-resolution and larger-scale topography still challenge the application of this numerical approach in the FLUXNET community.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2017.03.004
      Issue No: Vol. 255 (2018)
  • Flow adjustment inside homogeneous canopies after a leading edge – An
           analytical approach backed by LES
    • Authors: Konstantin Kröniger; Tirtha Banerjee; Frederik De Roo; Matthias Mauder
      Pages: 17 - 30
      Abstract: Publication date: 28 May 2018
      Source:Agricultural and Forest Meteorology, Volume 255
      Author(s): Konstantin Kröniger, Tirtha Banerjee, Frederik De Roo, Matthias Mauder
      A two-dimensional analytical model for describing the mean flow behavior inside a vegetation canopy after a leading edge in neutral conditions was developed and tested by means of large eddy simulations (LES) employing the LES code PALM. The analytical model is developed for the region directly after the canopy edge, the adjustment region, where one-dimensional canopy models fail due to the sharp change in roughness. The derivation of this adjustment region model is based on an analytic solution of the two-dimensional Reynolds averaged Navier–Stokes equation in neutral conditions for a canopy with constant plant area density (PAD). The main assumptions for solving the governing equations are separability of the velocity components concerning the spatial variables and the neglection of the Reynolds stress gradients. These two assumptions are verified by means of LES. To determine the emerging model parameters, a simultaneous fitting scheme was applied to the velocity and pressure data of a reference LES simulation. Furthermore a sensitivity analysis of the adjustment region model, equipped with the previously calculated parameters, was performed varying the three relevant length, the canopy height (h), the canopy length and the adjustment length (L c ), in additional LES. Even if the model parameters are, in general, functions of h/L c , it was found out that the model is capable of predicting the flow quantities in various cases, when using constant parameters. Subsequently the adjustment region model is combined with the one-dimensional model of Massman [Bound. Layer Meteorol., 83(3):407–421, 1997], which is applicable for the interior of the canopy, to attain an analytical model capable of describing the mean flow for the full canopy domain. Finally the model is tested against an analytical model based on a linearization approach.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2017.09.019
      Issue No: Vol. 255 (2018)
  • Interactions between vegetation, atmospheric turbulence and clouds under a
           wide range of background wind conditions
    • Authors: M. Sikma; H.G. Ouwersloot; X. Pedruzo-Bagazgoitia; C.C. van Heerwaarden; J. Vilà-Guerau de Arellano
      Pages: 31 - 43
      Abstract: Publication date: 28 May 2018
      Source:Agricultural and Forest Meteorology, Volume 255
      Author(s): M. Sikma, H.G. Ouwersloot, X. Pedruzo-Bagazgoitia, C.C. van Heerwaarden, J. Vilà-Guerau de Arellano
      The effects of plant responses to cumulus (Cu) cloud shading are studied from free convective to shear-driven boundary-layer conditions. By using a large-eddy simulation (LES) coupled to a plant physiology embedded land-surface submodel, we study the vegetation–cloud feedbacks for a wide range (44) of atmospheric and plant stomatal conditions. The stomatal relaxation time is prescribed as an instantaneous, symmetrical (10, 15 and 20min) and asymmetrical (5min closing, 10min opening) response, and the background wind ranges from 0 to 20ms−1. We show that in free convective, non-shading (i.e. transparent) cloud conditions the near-surface updraft region is marked by an enhanced CO2 assimilation rate (A n; 7%) and increased latent (LE; 9%) and sensible heat (H; 19%) fluxes. When we introduce Cu shading, we find an enhancement in plant transpiration and CO2 assimilation rates under optically thin clouds due to an increase in diffuse radiation. However, these effects vanish when a background wind is present and the Cu are advected. Optically thick clouds reduce the assimilation rate and surface fluxes under all simulated wind conditions. With increasing background wind, the shaded surface area is enlarged due to Cu tilting. The consequent decrease in surface fluxes by a reduction in incoming radiation, is partly offset due to an enhancement in the surface exchange and turbulent mixing as a result of stronger wind speeds. Different and non-linear processes control the H and LE response to shading. H is mainly radiation driven, whereas plant responses dampen the shading effects on LE. As a result, the regional averaged (48km2) reduction in H and LE are found to be 18% and 5%, respectively, compared to non-shading cloud conditions. Surprisingly, a nearly uniform regional net radiation reduction of 11% is found, with only a deviation between all 35 Cu shading cases of 0.5% (i.e. 1.2Wm−2) at the moment of maximum cloud cover. By comparing four representative simulations that are equal in net available energy, but differ in interactive and prescribed surface energy fluxes, we find a relative reduction in cloud cover between 5 and 10% during the maximum cloud cover period when the dynamic surface heterogeneity is neglected. We conclude that the local and spatial dynamic surface heterogeneity influences Cu development, while the Cu–vegetation coupling becomes progressively weaker with increasing stomatal relaxation time and background wind.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2017.07.001
      Issue No: Vol. 255 (2018)
  • Large-eddy simulation of the impact of urban trees on momentum and heat
    • Authors: Qi Li; Zhi-Hua Wang
      Pages: 44 - 56
      Abstract: Publication date: 28 May 2018
      Source:Agricultural and Forest Meteorology, Volume 255
      Author(s): Qi Li, Zhi-Hua Wang
      Trees in urban environment have a profound impact on the microclimate and environmental sustainability. Realistically representing them in urban models is an ongoing area of research in urban environmental study. In this paper, we develop a novel large-eddy simulation (LES) model (LES-UrbanTree) that resolves the buildings and parameterizes urban trees by accounting for their aerodynamic impact. The shading effect of trees is explicitly taken into account in LES-UrbanTree by a subsurface conduction model coupled to LES. Two-dimensional street canyons with trees in the middle of the street are used as a prototype for case studies. It is found that under moderate canyon aspect ratio (i.e. height/width being 0.5 and 1), trees taller than the mean building height leads to the strongest modification of the flow and temperature fields. Tall trees strongly impact the downward transport of high momentum (i.e. sweeping events) and therefore alter the momentum and heat fluxes most significantly through direct interaction with the strong shear layer near the roof top. Simulations of street canyons of different aspect ratios also produce physically consistent results, thus demonstrating the application potential of LES-UrbanTree. The study overall highlights the importance of representing both the aerodynamic and thermodynamic changes due to trees in urban models.

      PubDate: 2018-04-24T14:49:44Z
      DOI: 10.1016/j.agrformet.2017.07.011
      Issue No: Vol. 255 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-