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Jucker T, Bongalov B, Burslem DFRP, Nilus R, Dalponte M, Lewis SL, Phillips OL, Qie L, Coomes DA. Topography shapes the structure, composition and function of tropical forest landscapes. Ecol Lett 2018; 21:989-1000. [PMID: 29659115 PMCID: PMC6849614 DOI: 10.1111/ele.12964] [Citation(s) in RCA: 81] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 12/17/2017] [Accepted: 03/18/2018] [Indexed: 12/20/2022]
Abstract
Topography is a key driver of tropical forest structure and composition, as it constrains local nutrient and hydraulic conditions within which trees grow. Yet, we do not fully understand how changes in forest physiognomy driven by topography impact other emergent properties of forests, such as their aboveground carbon density (ACD). Working in Borneo – at a site where 70‐m‐tall forests in alluvial valleys rapidly transition to stunted heath forests on nutrient‐depleted dip slopes – we combined field data with airborne laser scanning and hyperspectral imaging to characterise how topography shapes the vertical structure, wood density, diversity and ACD of nearly 15 km2 of old‐growth forest. We found that subtle differences in elevation – which control soil chemistry and hydrology – profoundly influenced the structure, composition and diversity of the canopy. Capturing these processes was critical to explaining landscape‐scale heterogeneity in ACD, highlighting how emerging remote sensing technologies can provide new insights into long‐standing ecological questions.
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Affiliation(s)
- Tommaso Jucker
- Department of Plant Sciences, Forest Ecology and Conservation group, University of Cambridge, Cambridge, UK.,CSIRO Land and Water, 147 Underwood Avenue, Floreat, 6014, WA, Australia
| | - Boris Bongalov
- Department of Plant Sciences, Forest Ecology and Conservation group, University of Cambridge, Cambridge, UK
| | - David F R P Burslem
- School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen, UK
| | - Reuben Nilus
- Sabah Forestry Department, Forest Research Centre, P.O. Box 1407, 90715, Sandakan, Sabah, Malaysia
| | - Michele Dalponte
- Department of Sustainable Agro-ecosystems and Bioresources, Research and Innovation Centre, Fondazione E. Mach, Via E. Mach 1, 38010, San Michele all'Adige, Italy
| | - Simon L Lewis
- School of Geography, University of Leeds, Leeds, LS2 9JT, UK
| | | | - Lan Qie
- School of Geography, University of Leeds, Leeds, LS2 9JT, UK.,Imperial College London, Silwood Park Campus, Buckhusrt Road, Ascot, SL5 7PY, UK
| | - David A Coomes
- Department of Plant Sciences, Forest Ecology and Conservation group, University of Cambridge, Cambridge, UK
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Castillo-Ruiz FJ, Castro-Garcia S, Blanco-Roldan GL, Sola-Guirado RR, Gil-Ribes JA. Olive Crown Porosity Measurement Based on Radiation Transmittance: An Assessment of Pruning Effect. Sensors (Basel) 2016; 16:E723. [PMID: 27213391 DOI: 10.3390/s16050723] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2016] [Revised: 05/05/2016] [Accepted: 05/13/2016] [Indexed: 11/16/2022]
Abstract
Crown porosity influences radiation interception, air movement through the fruit orchard, spray penetration, and harvesting operation in fruit crops. The aim of the present study was to develop an accurate and reliable methodology based on transmitted radiation measurements to assess the porosity of traditional olive trees under different pruning treatments. Transmitted radiation was employed as an indirect method to measure crown porosity in two olive orchards of the Picual and Hojiblanca cultivars. Additionally, three different pruning treatments were considered to determine if the pruning system influences crown porosity. This study evaluated the accuracy and repeatability of four algorithms in measuring crown porosity under different solar zenith angles. From a 14° to 30° solar zenith angle, the selected algorithm produced an absolute error of less than 5% and a repeatability higher than 0.9. The described method and selected algorithm proved satisfactory in field results, making it possible to measure crown porosity at different solar zenith angles. However, pruning fresh weight did not show any relationship with crown porosity due to the great differences between removed branches. A robust and accurate algorithm was selected for crown porosity measurements in traditional olive trees, making it possible to discern between different pruning treatments.
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Poblete-Echeverría C, Fuentes S, Ortega-Farias S, Gonzalez-Talice J, Yuri JA. Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient. Sensors (Basel) 2015; 15:2860-72. [PMID: 25635411 PMCID: PMC4367337 DOI: 10.3390/s150202860] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Accepted: 12/10/2014] [Indexed: 11/23/2022]
Abstract
Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAI(D)), which was compared with LAI estimated by the proposed digital photography method (LAI(M)). Results showed that the LAI(M) was able to estimate LAI(D) with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (f(f)) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.
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Affiliation(s)
- Carlos Poblete-Echeverría
- Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Talca 3460000, Chile.
| | - Sigfredo Fuentes
- Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Melbourne, VIC 3010, Australia.
| | - Samuel Ortega-Farias
- Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca, Talca 3460000, Chile.
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Zheng G, Moskal LM. Retrieving Leaf Area Index (LAI) Using Remote Sensing: Theories, Methods and Sensors. Sensors (Basel) 2009; 9:2719-45. [PMID: 22574042 PMCID: PMC3348792 DOI: 10.3390/s90402719] [Citation(s) in RCA: 108] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2008] [Revised: 04/03/2009] [Accepted: 04/17/2009] [Indexed: 12/04/2022]
Abstract
The ability to accurately and rapidly acquire leaf area index (LAI) is an indispensable component of process-based ecological research facilitating the understanding of gas-vegetation exchange phenomenon at an array of spatial scales from the leaf to the landscape. However, LAI is difficult to directly acquire for large spatial extents due to its time consuming and work intensive nature. Such efforts have been significantly improved by the emergence of optical and active remote sensing techniques. This paper reviews the definitions and theories of LAI measurement with respect to direct and indirect methods. Then, the methodologies for LAI retrieval with regard to the characteristics of a range of remotely sensed datasets are discussed. Remote sensing indirect methods are subdivided into two categories of passive and active remote sensing, which are further categorized as terrestrial, aerial and satellite-born platforms. Due to a wide variety in spatial resolution of remotely sensed data and the requirements of ecological modeling, the scaling issue of LAI is discussed and special consideration is given to extrapolation of measurement to landscape and regional levels.
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Affiliation(s)
- Guang Zheng
- Remote Sensing and Geospatial Analysis Laboratory and Precision Forestry Cooperative, College of Forest Resources, University of Washington, Box 352100, Seattle, Washington, USA 98195-2100; E-Mail: (G.Z.)
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