Report - ICP Forests

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74 3. Intensive Monitoring The nominal variables (country, tree species and climate zone) were transformed to dummy variables (one for each class with value 1 if a record is in that class, otherwise 0). Table 3.4.2-1: Classification of plots according to main tree species Tree Tree species Number of plots Group Pinus sylvestris 230 Pins Picea abies (P. excelsa) 181 Pice Fagus sylvatica 114 Fags Quercus robur (Q. pedunculata) 57 Qurp Quercus petraea 41 Qurp Quercus ilex 17 QurM Pseudotsuga menziesii 14 conf Abies alba 14 conf Pinus pinaster 13 conf Picea sitchensis 11 conf Pinus nigra 10 Pins Quercus cerris 9 QurM Quercus pyrenaica (Q. toza) 5 QurM Quercus suber 5 QurM Betula pendula 4 deci Pinus halepensis 4 conf Larix decidua 4 conf Quercus frainetto (Q. conferta) 3 QurM Pinus brutia 3 conf Pinus pinea 3 conf Eucalyptus sp. 3 deci Pinus contorta 3 conf Carpinus betulus 2 deci Fraxinus excelsior 2 deci Quercus faginea 2 QurM Castanea sativa (C. vesca) 2 deci Populus canescens 1 deci Fagus moesiaca 1 deci Populus hybrides 1 deci Quercus rotundifolia 1 QurM Alnus glutinosa 1 deci Other broadleaves 1 deci Other conifers 1 conf Abies borisii-regis 1 conf Juniperus oxycedrus 1 conf Juniperus thurifera 1 conf Pinus canariensis 1 conf Pinus cembra 1 conf Pinus mugo (P. montana) 1 conf Pinus radiata (P.insignis) 1 conf Pinus uncinata 1 conf Erica arborea 1 deci
3. Intensive Monitoring 75 Missing values and correspondence between vegetation and abiotic data After the exclusion of records with deficient soil data, there are three records without coordinates (and hence, without climate zone and EMEP deposition estimates). These were also excluded from the analysis. After these exclusions and the replacement of missing soil data by estimates, 616 usable records remain with soil, 'other', and EMEP deposition data, and 265 with soil, 'other', bulk and throughfall deposition data. Annex 3.4.3 gives the correlation matrix of all variables used in the CCA analysis of last relevé per plot using EMEP deposition estimates. Other analyses have been carried out on different subsets of the data and therefore have slightly different correlation matrices; for the correlation between the EMEP estimates and measured bulk and throughfall deposition see Annex 3.4.2. On the vegetation side, species with less than three occurrences and relevés with less than three species were excluded from the multivariate analysis of the last relevé per plot, to avoid a very heterogeneous data set. This resulted in 598 usable records, of which 477 had usable abiotic data (excl. bulk and throughfall deposition). These 477 relevés had 170 species (after the exclusion of very rare ones). A separate analysis was done with the bulk and throughfall deposition data instead of the EMEP estimates; for this analysis there were 181 usable records containing 114 species. For the analysis of the vegetation change the first and the last relevé of each plot were used if the interval between them was seven years or more; this yielded 161 plots, of which 138 had usable abiotic data, and 60 bulk deposition and throughfall data. In this operation rare species or species-poor relevés were not excluded because the linear statistical methods used here are less sensitive to heterogeneity. 3.4.3 Statistical methods The statistical methods used are similar to those used in 2002 (De Vries et al. 2002). The effect of the environmental variables on the vegetation of the last relevé of each plot was assessed by canonical correspondence analysis (CCA). The exclusion of very rare species (< 3 occurrences) and downweighting of rare species resulted in a gradient length GL 1 = 7.5 and explained variance λ 1 / Σλ = 4.6% for the first axis at 477 samples and 170 species which was judged acceptable. The change in the vegetation was determined as (%cover in last relevé) minus (%cover in first relevé) per species. The significance of this change was determined by ordinary linear statistics. The relation between the change in the vegetation and the environmental variables was analysed for all species together using RDA (= the linear form of CCA = the canonical form of PCA). Ellenberg values were determined as the unweighted mean over all species (incl. the rare species but excl. relevés with < 3 species with a known Ellenberg value). The relation between the change in Ellenberg values and environmental variables was assessed using multiple regression. All multivariate operations were carried out by the program CANOCO v 4.53, all univariate operation by the program GENSTAT v 12.1. 3.4.4 Results CCA analysis of last relevé per plot Possible observer effects were assessed by determining the unique contributions ('TMVs') of the countries and the 'real' environmental variables (Table 3.4.4-1). Out of a total of 25% variance that can be explained anyway, 5% is uniquely due to the countries. As both the geographical coordinates and climate zones are among the environmental variables this 'county effect' is most probably caused by methodological differences. Estonia, France, the Netherlands, Ireland and Italy are the most deviant countries (in that order) and their effect is significant even after accounting for the effect of all environmental variables. Therefore the countries were used as covariables in the subsequent analysis. Table 3.4.4-2 gives the result of the forward selection. Like in De Vries at el. (2002), the variables were included in the model stepwise, at each step
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W O R K R E P O R T Institute for W
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United Nations Economic Commission
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4.18 REPUBLIC OF MOLDOVA ..........
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8 Preface
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10 Summary Ground vegetation was an
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12 1. Introduction
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14 2. Large Scale Crown Condition S
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Page 94 and 95: 94 Annex soil organic layer soil mi
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124 Annex Observed trees Observed p
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126 Annex Annex I-3 Percentage of t
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128 Annex Annex I-5 Changes in mean
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130 Annex Period 1998 - 2009 Year M
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132 Annex Annex II National Surveys
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134 Annex Annex II-2 Percent of tre
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136 Annex Annex II-4 Percent of bro
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138 Annex Annex II-6 Percent of dam
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140 Annex Annex II-8 Changes in def
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142 Annex 100 Croatia all species c
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144 Annex 100 France * all species
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146 Annex 100 Latvia all species co
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148 Annex 100 The Netherlands all s
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150 Annex 100 Serbia all species co
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152 Annex 100 Turkey all species co
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154 Annex Annex IV Testing statisti
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156 Annex 2. Expert Panels, WG and
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158 Annex Expert Panel on Crown Con
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160 Annex FFCC FSCC Bundesforschung
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162 Annex BELGIUM Tel. +32 54 43 71
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164 Annex DENMARK Phone: +45 39 47
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166 Annex 1055 BUDAPEST HUNGARY Pho
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168 Annex Republic of Moldova (Min)
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170 Annex SERBIA Phone: +381 11 3 5
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172 Annex Ukraine (NFC) (Min) Unite
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174 Annex
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