Uncertainty in detecting the disturbance history of forest ecosystems using dendrochronology |
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| Institution: | 1. Department of Forest Ecology, The Silva Tarouca Research Institute for Landscape and Ornamental Gardening, Lidická 25/27, 602 00 Brno, Czech Republic;2. Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Sokolovská 83, 186 75 Praha 8, Czech Republic;3. Department of Forest Botany, Dendrology and Geobiocenology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemedelska 1, 613 00 Brno, Czech Republic;1. INIA-CIFOR, Forest Research Centre, Ctra A Coruña km 7.5, 28040 Madrid, Spain;2. Forest Sciences Centre of Catalonia (CTFC), Ctra Sant Llorenc, km 2, 25280, Solsona, Spain;3. Dpt. Agroforestry Science, University of Huelva. Ctra Palos–La Rábida s/n, 21819, Palos de la Frontera, Spain;4. Forest Service, Junta de Castilla y León, C/ Duque de la Victoria, 8, 47001, Valladolid, Spain;5. iuFOR, Sustainable Forest Management Research Institute UVa-INIA, Spain;1. University of Huelva, Faculty of Humanities, Dept. History I, Av. de las Fuerzas Armadas s/n, 21007 Huelva, Spain;2. University of Santiago de Compostela, Department of Botany, EPS, Campus de Lugo, 27002 Lugo, Spain;3. University of Huelva, Agroforestry Sciences Department, Campus La Rábida, 21819 Palos de la Frontera, Huelva, Spain;4. Van Daalen Dendrochronologie, H.G. Gooszenstraat 1, Unit 15, 7415 CL, Deventer, The Netherlands;5. Centro de Investigación Forestal, Instituto Nacional de Investigaciones Agrarias, Crta. La Coruña km. 7.5, 28040 Madrid, Spain;6. Arkeolan Foundation, Laboratorio de Dendrocronología, c/ Francisco de Gainza,4. 20302 Irun, Gipuzkoa, Spain;7. University of Arizona, Laboratory of Tree-Ring Research, Tucson, AZ 85721, USA;8. Nicolaus Copernicus University, Institute for the Study, Conservation and Restoration of Cultural Heritage, 87-100 Torun, Poland;9. Cultural Heritage Agency of the Netherlands, P.O. Box 1600, 3800 BP Amersfoort, The Netherlands;10. Utrecht University, Faculty of Geosciences, Department of Physical Geography, P.O. Box 80.115, 3508 TC Utrecht, The Netherlands;11. The Netherlands Centre for Dendrochronology/RING Foundation, P.O. Box 1600, 3800 BP Amersfoort, The Netherlands;1. Department of Geography, Johannes Gutenberg University, 55099 Mainz, Germany;2. Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY 10964, USA;3. Institute of Geosciences, University of Mainz, 55128 Mainz, Germany;4. Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland;5. Oeschger Centre for Climate Change Research, Bern, Switzerland;6. Global Change Research Centre AS CR, Brno, Czech Republic |
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| Abstract: | QuestionsUncertainty in detecting disturbance histories has long been ignored in dendrochronological studies in forest ecosystems. Our goal was to characterize this uncertainty in relation to the key parameters of forest ecosystems and sample size. In addition, we aimed to provide a method to define uncertainty bounds in specific forest ecosystems with known parameters, and to provide a required (conservative) minimal sample size to achieve a pre-defined level of uncertainty if no actual key forest parameters are known.LocationTraining data were collected from ?ofínský Prales (48°40′N, 14°42′E, 735–830 m a.s.l., granite, Czech Republic).MethodsWe used probability theory and expressed uncertainty as the length (the difference between the upper and lower bounds) of the 95% confidence interval. We studied the uncertainty of (i) the initial growth of trees – if they originated under canopy or in a gap; and (ii) the responses to disturbance events during subsequent growth – on the basis of release detection in the radial growth of trees. These two variables provide different information, which together give a picture of the disturbance history. While initial growth date the existence of a gap in a given decade (recent as well as older gaps are included), release demonstrates the moment of a disturbance event.ResultsWith the help of general mathematical deduction, we have obtained results valid across vegetation types. The length of a confidence interval depends on the sample size, proportion of released trees in a population, as well as on the variability of tree layer features (e.g., crown area of suppressed and released trees).ConclusionsMost studies to date have evaluated the initial growth of trees with higher uncertainty than for canopy disturbed area. The length of the 95% confidence interval for detecting initial growth has been rarely shorter than 0.1 (error ± 5%) and has mostly been much longer. To reach 95% confidence interval length of 0.1 (error ± 5%) when detecting the canopy disturbed area, at least 485 tree cores should be evaluated in studied time period, while to reach a 0.05 interval length (error ± 2.5%) at least 1925 tree cores are required. Our approach can be used to find the required sample size in each specific forest ecosystem to achieve pre-defined levels of uncertainty while detecting disturbance history. |
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| Keywords: | Dendroecology Growth release Disturbance regime Sample size Probability theory Forest dynamics |
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