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Abstract
Physiological processes cause movements of tree stems and branches that occur in a circadian rhythm and over longer time periods, but there is a lack of quantitative understanding of the cause-and-effect relationships. We investigated the movement of tree branches in a long-term drought experiment and at a circadian time scale using time-series of terrestrial laser scanning measurements coupled with measurements of environmental drivers and tree water status. Our results showed that movement of branches was largely explained by leaf water status measured as leaf water potential in a controlled environment for both measured trees (R2 = 0.86 and R2 = 0.75). Our hypothesis is that changes in leaf and branch water status would cause branch movements was further supported by strong relationship between vapor pressure deficit and overnight branch movement (R2 = [0.57–0.74]). Due to lower atmospheric water demand during the nighttime, tree branches settle down as the amount of water in leaves increases. The results indicate that the quantified movement of tree branches could help us to further monitor and understand the water relations of tree communities.
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Jin S, Su Y, Zhang Y, Song S, Li Q, Liu Z, Ma Q, Ge Y, Liu L, Ding Y, Baret F, Guo Q. Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series. PLANT PHENOMICS (WASHINGTON, D.C.) 2021; 2021:9895241. [PMID: 34557676 PMCID: PMC8441379 DOI: 10.34133/2021/9895241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 07/27/2021] [Indexed: 06/02/2023]
Abstract
Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of trees, but no consistent patterns have been drawn. Meanwhile, whether TLS can capture structural rhythm in crops is unclear. Here, we aim to explore the seasonal and circadian rhythms in maize structural traits at both the plant and leaf levels from time-series TLS. The seasonal rhythm was studied using TLS data collected at four key growth periods, including jointing, bell-mouthed, heading, and maturity periods. Circadian rhythms were explored by using TLS data acquired around every 2 hours in a whole day under standard and cold stress conditions. Results showed that TLS can quantify the seasonal and circadian rhythm in structural traits at both plant and leaf levels. (1) Leaf inclination angle decreased significantly between the jointing stage and bell-mouthed stage. Leaf azimuth was stable after the jointing stage. (2) Some individual-level structural rhythms (e.g., azimuth and projected leaf area/PLA) were consistent with leaf-level structural rhythms. (3) The circadian rhythms of some traits (e.g., PLA) were not consistent under standard and cold stress conditions. (4) Environmental factors showed better correlations with leaf traits under cold stress than standard conditions. Temperature was the most important factor that significantly correlated with all leaf traits except leaf azimuth. This study highlights the potential of time-series TLS in studying outdoor agricultural chronobiology.
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Affiliation(s)
- Shichao Jin
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production Co-Sponsored by Province and Ministry, Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanjun Su
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yongguang Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Sciences, Nanjing University, Nanjing, Jiangsu 210023, China
| | - Shilin Song
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qing Li
- National Technique Innovation Center for Regional Wheat Production/Key Laboratory of Crop Ecophysiology, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, 210095 Jiangsu, China
| | - Zhonghua Liu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qin Ma
- Department of Forestry, Mississippi State University, Mississippi State 39759, USA
| | - Yan Ge
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production Co-Sponsored by Province and Ministry, Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - LingLi Liu
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanfeng Ding
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production Co-Sponsored by Province and Ministry, Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
| | - Frédéric Baret
- Plant Phenomics Research Centre, Academy for Advanced Interdisciplinary Studies, Collaborative Innovation Centre for Modern Crop Production Co-Sponsored by Province and Ministry, Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, Nanjing 210095, China
- Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Institut National de la Recherche Agronomique, Unité Mixte de Recherche 1114 Domaine Saint-Paul, Avignon Cedex 84914, France
| | - Qinghua Guo
- Department of Ecology, College of Environmental Sciences, and Key Laboratory of Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China
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Bakay L, Moravčík Ľ. Quantification of Circadian Movement of Small-Leaved Lime ( Tilia cordata Mill.) Saplings With Short Interval Terrestrial Laser Scanning. FRONTIERS IN PLANT SCIENCE 2020; 11:984. [PMID: 32695135 PMCID: PMC7339927 DOI: 10.3389/fpls.2020.00984] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 06/16/2020] [Indexed: 06/02/2023]
Abstract
The goal of the study was to quantify and identify patterns in circadian movements of small-leaved lime (Tillia cordata) saplings with the help of terrestrial laser scanning (TLS). The movements were monitored every 60 min 24 h a day and every 30 min in the hour of sunrise and sunset. In order to exclude wind effects the monitored saplings were indoors. The resulting point clouds were used in creating a time series of branch and foliage movements with high precision. The circadian vertical movement of saplings was evaluated through target points, which has a potential of capturing the point-wise movement more accurately. Our results clearly show that small saplings move their branches and leaves during 24 h in complex ways and that is difficult to identify general patterns. Since we worked with small saplings and our movement threshold was 5 mm, we detected random fluctuation-oscillation as the most common movement in monitored saplings. The results highlight the potential of TLS measurements in support of chronobiology and the possibilities to analyze circadian movements of saplings in controlled environment.
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Affiliation(s)
- Ladislav Bakay
- Department of Planting Design and Maintenance, Slovak University of Agriculture, Nitra, Slovakia
| | - Ľuboš Moravčík
- Department of Garden and Landscape Architecture, Slovak University of Agriculture, Nitra, Slovakia
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A Method for Tree Detection Based on Similarity with Geometric Shapes of 3D Geospatial Data. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2020. [DOI: 10.3390/ijgi9050298] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This paper presents an approach to detecting patterns in a three-dimensional context, emphasizing the role played by the local geometry of the surface model. The core of the associated algorithm is represented by the cosine similarity computed to sub-matrices of regularly gridded digital surface/canopy models. We developed an accompanying software instrument compatible with a GIS environment which allows, as inputs, locations in the surface/canopy model based on field data, pre-defined geometric shapes, or their combination. We exemplified the approach for a study case dealing with the locations of scattered trees and shrubs previously identified in the field in two study sites. We found that the variation in the pairwise similarities between the trees is better explained by the computation of slopes. Furthermore, we considered a pre-defined shape, the Mexican Hat wavelet. Its geometry is controlled by a single number, for which we found ranges of best fit between the shapes and the actual trees. Finally, a suitable combination of parameters made it possible to determine the potential locations of scattered trees. The accuracy of detection was equal to 77.9% and 89.5% in the two study sites considered. Moreover, a visual check based on orthophotomaps confirmed the reliability of the outcomes.
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Puttonen E, Bucksch A, Zlinszky A, Pfeifer N. Editorial: Optical Approaches to Capture Plant Dynamics in Time, Space, and Across Scales. FRONTIERS IN PLANT SCIENCE 2018; 9:791. [PMID: 29942323 PMCID: PMC6004393 DOI: 10.3389/fpls.2018.00791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 05/24/2018] [Indexed: 06/08/2023]
Affiliation(s)
- Eetu Puttonen
- Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, Kirkkonummi, Finland
- Center of Excellence in Laser Scanning Research, Masala, Finland
| | - Alexander Bucksch
- Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, United States
- Institute of Bioinformatics, University of Georgia, Athens, GA, United States
- Department of Plant Biology, University of Georgia, Athens, GA, United States
| | - András Zlinszky
- Balaton Limnological Institute, Centre for Ecological Research, Hungarian Academy of Sciences, Tihany, Hungary
| | - Norbert Pfeifer
- Department of Geodesy and Geoinformation, Technische Universität Wien, Vienna, Austria
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