Spatio-temporal analysis of tree height in a young cork oak plantation

被引:6
|
作者
Sedda, L. [1 ]
Atkinson, P. M. [2 ]
Filigheddu, M. R. [3 ]
Cotzia, G. [3 ]
Dettori, S. [3 ]
机构
[1] Univ Oxford, Dept Zool, Oxford OX1 3PS, England
[2] Univ Southampton, Sch Geog, Southampton, Hants, England
[3] Univ Sassari, Dipartimento Econ & Sistemi Arborei, I-07100 Sassari, Italy
关键词
Bayesian maximum entropy; spatio-temporal geostatistics; space-time trends; cork oak; Sardinia; SPATIAL-PATTERNS; MANAGEMENT; WIND; PREDICTION; VARIABLES; FORESTS; WEIGHT; GROWTH; L;
D O I
10.1080/13658816.2010.517534
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cork oak is one of the most valuable natural forest genera in the Mediterranean basin. Modelling cork oak growth has been a challenge for foresters in recent years because of strong site and genetic influences, below-ground competition, management regimes and age effects. Because cork productivity is related to forest height, which is, in turn, related directly with site characteristics, an increase in the accuracy of height prediction implies improved productivity estimation. A Bayesian maximum entropy (BME) geostatistical model was applied to characterize the space-time pattern of height of young cork oak in a forest stand from central Sardinia in the years 2000, 2002, 2003, 2006 and 2008. Cork oak height maps were produced for each of the 5 years. The main goals were to analyse and interpret through time (i) the changes in spatial correlation and (ii) the changes in spatial distribution of cork oak height. The plantation was characterized by an increasing spatial dependence through time, whereas the temporal range was 2 years. Cork oak height was significantly correlated with wind speed (reduced by a neighbouring forest) in all the years implying a single trend. The correlations were larger for 2006 and 2008 than for previous years. Three other environmental variables (shade, elevation and slope) were less significant and their influence restricted to 2 years only. This research has several implications for the management of cork oak in the young phase.
引用
收藏
页码:1083 / 1096
页数:14
相关论文
共 50 条
  • [31] Spatio-temporal Structure of Diurnal and Semidiurnal Tides in Geopotential Height Field
    Cho, Hyeong-Oh
    Son, Seok-Woo
    Lee, Yong-Hee
    JOURNAL OF THE KOREAN EARTH SCIENCE SOCIETY, 2016, 37 (07): : 465 - 475
  • [32] The continuous spatio-temporal model (CSTM) as an exhaustive framework for multi-scale spatio-temporal analysis
    Van de Weghe, N.
    de Roo, B.
    Qiang, Y.
    Versichele, M.
    Neutens, T.
    de Maeyer, P.
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2014, 28 (05) : 1047 - 1060
  • [33] Three-Valued Spatio-Temporal Logic: A Further Analysis on Spatio-Temporal Properties of Stochastic Systems
    Vissat, Ludovica Luisa
    Loreti, Michele
    Nenzi, Laura
    Hillston, Jane
    Marion, Glenn
    QUANTITATIVE EVALUATION OF SYSTEMS (QEST 2017), 2017, 10503 : 317 - 332
  • [34] Spatio-temporal Analysis of Human Mortality in Canada
    Cupido, Kyran
    McClure, Olivia
    CANADIAN STUDIES IN POPULATION, 2022, 49 (3-4) : 183 - 198
  • [35] A changepoint analysis of spatio-temporal point processes
    Altieri, Linda
    Scott, E. Marian
    Cocchi, Daniela
    Illian, Janine B.
    SPATIAL STATISTICS, 2015, 14 : 197 - 207
  • [36] Data analysis and processing for spatio-temporal forecasting
    Lee, Hyoungwoo
    Choo, Jaegul
    20TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2020), 2020, : 737 - 739
  • [37] A general method of spatio-temporal clustering analysis
    DENG Min
    LIU QiLiang
    WANG JiaQiu
    SHI Yan
    ScienceChina(InformationSciences), 2013, 56 (10) : 158 - 171
  • [38] A spatio-temporal analysis of fires in South Africa
    Strydom, Sheldon
    Savage, Michael J.
    SOUTH AFRICAN JOURNAL OF SCIENCE, 2016, 112 (11-12)
  • [39] Multiscale recurrence analysis of spatio-temporal data
    Riedl, M.
    Marwan, N.
    Kurths, J.
    CHAOS, 2015, 25 (12)
  • [40] A general method of spatio-temporal clustering analysis
    Min Deng
    QiLiang Liu
    JiaQiu Wang
    Yan Shi
    Science China Information Sciences, 2013, 56 : 1 - 14