Report - ICP Forests

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54 3. Intensive Monitoring 3.3 Soil solution chemistry and its trends 3.3.1 Introduction Effects of atmospheric deposition need to be regarded with respect to the receptor. Most important effects on soil solution (and as such on solid soil phase) are a change of buffer range as a result of acid deposition and mobilisation of potentially toxic elements as well as nutrient imbalances and resulting nutrient deficiencies. These soil and soil solution mediated processes affect vegetation in terms of reduced growth resulting from impaired nutrient uptake, fine root dieback and general stress reactions of the vegetation like excessive flowering (Koch and Matzner, 1993; Løkke et al., 1996; Sverdrup and Warfvinge, 1993). An important tool to describe risks of atmospheric pollution is the calculation of critical loads and their exceedances, aiming at the protection of forest ecosystems from harmful effects on forest structure or function (Augustin et al., 2005). The critical load concept is accepted as the basis for air pollution abatement strategies, in order to reduce or prevent damage to the functioning and vitality of forest ecosystems caused by transboundary acidic deposition (Løkke et al., 1996). Critical loads are defined as “a quantitative estimate of an exposure to one or more pollutants below which significant harmful effects on specified sensitive elements of the environment do not occur according to present knowledge” (Spranger et al., 2004). Critical load calculations balance the depositions to which the ecosystem is exposed with its capacity to buffer the input, take up or remove it from the system without harmful effects within or outside the system (Spranger et al., 2004). Critical loads can be derived empirically or can be calculated by means of a simple mass balance or dynamic models. The so-called Simple Mass Balance (SMB) model can be considered a standard model for calculating critical loads for terrestrial ecosystems under CLRTAP (Spranger et al., 2004). Critical loads can be calculated for acidifying substances, eutrophying N compounds and heavy metals. Model-based approaches for calculating critical loads aim at linking deposition of air pollution with its biological effects to the ecosystem. As the biological effects often are of complex nature, chemical criteria are mostly used to simplify the modelling. This calls for appropriate (soil) chemical criteria with proven (empirical) relationships to biological effects. For theses chemical criteria values have to be defined that mark the threshold below which harmful effects on the specified biological indicator are not expected (Spranger et al., 2004). Exceedances of critical limits do not necessarily result in instant dieback of trees or ecosystems but do illustrate an enhanced risk for trees to be more susceptible to additional stressors. Exceedances may result in a loss of assimilation area, growth reductions and nutrient imbalances (Augustin et al., 2005). Consequently critical loads are a function of the chosen chemical threshold values (critical limits) applied within the model (Hall et al., 2010). This chapter presents pH and basic cation to aluminium ratio in the soil solution of a broad share of Level II plots and evaluates these parameters against well documented critical limits. The results presented in the following sub-chapters are a first analysis. The temporal analysis of BC/Al ratio and pH values is not sufficient to describe the changes in soil solution chemistry. Concentrations of BC, Al and main anions (NO 3 , SO 4 ) need to be investigated in follow-up studies.
3. Intensive Monitoring 55 3.3.2. Methods 3.3.2.1 Number of plots In the 1990s, soil solution chemistry assessment started at a restricted number of Level II plots. Until the year 1998 the number of Level II plots with data availability in the transnational data base increased to over 200 plots and remained rather unchanged until 2006. From 1990 to 2006 soil solution chemistry data are available from 298 different plots in 24 countries. In 2006, soil solution data were collected at 226 plots in 21 countries. Due to a number of administrational and technical changes in data base administration in the past decade, the quality of soil solution data in the transnational data base was not satisfactory. After intensive data quality assessment and consultation of the submitting countries in 2009 data quality for the monitoring years up to 2006 could be remarkably improved. Table 3.3.2.1-1: Number of plots with available soil solution data for all monitoring years and submitting countries. Striped green marks “no data submitted”, striped orange marks “data quality assessment still ongoing”. COUNTR 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 FR 15 15 15 15 15 13 14 14 14 14 14 14 BE 8 8 8 8 8 6 7 7 7 7 NL 11 11 11 14 11 14 14 14 14 7 3 3 3 3 3 DE 1 1 1 49 67 78 78 68 79 79 76 76 76 76 IT 2 2 2 2 2 4 8 UK 6 7 7 7 7 7 9 9 9 IE 1 4 4 4 3 3 3 3 3 3 3 3 3 3 DK 16 15 10 10 7 9 6 8 8 8 8 GR 2 2 2 1 1 1 1 ES 2 2 2 3 3 3 SE 41 39 41 41 44 45 46 47 45 43 43 AT 1 2 2 2 2 2 2 2 2 2 FI 6 16 15 16 16 16 15 15 15 17 CH 8 8 7 7 7 7 7 7 HU 1 RO 4 PL 1 1 NO 17 16 18 17 15 14 14 13 8 8 8 SK 3 3 LT 1 1 1 1 1 1 2 2 CZ 1 1 3 3 3 2 9 11 EE 2 2 2 3 4 4 4 5 SI 2 2 2 BG 3 1 LV 1 1 1 CY 2 2 3.3.2.2 Methodology of soil solution sampling Soil solution sampling on the monitoring plots is harmonized with regard to sampled horizon and sampling technique. 91.5 % of all soil solution samplers are located in mineral horizons, 7.9 and 0.7 % in organic and hygromorphic horizons, respectively. Since 2002, only lysimeters are used for soil solution collection. In 2006, 72% of all samplers were tension lysimeters and 28% were zero-tension lysimeters. In the years before,
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W O R K R E P O R T Institute for W
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