Availability and evaluation of European forest soil monitoring data in the study on the effects of air pollution on forests

Abstract

In the study of air pollution effects on forest ecosystems, solid soil data such as cation exchange capacity, base saturation and other exchangeable cation fractions, soil texture, soil moisture, soil weathering rates, C/N ratio and other variables form an important information base for many air pollution impact models. This paper shows some of the possibilities and the limitations of the soil data that European countries collected on the systematic Level I and on the intensive and permanent Level II monitoring plots within the ICP Forests programme. The soil data date from a first inventory in the 1990s and from a second inventory more than 10 years later. Both surveys were conducted following a common manual on sampling and analysis of soil. An example of the changes in pH(CaCl2) and base saturation in the forest floor and mineral soil on more than 2000 plots till a depth of 80 cm between the two surveys is presented. In this period the pH(CaCl2) significantly increased in the very acid forest soils [with pH(CaCl2) below 4.0] but further decreased in forest soils with pH(CaCl2) above 4.0. Following the trend in pH, the base saturation increased in soils with a very low buffering capacity (soils with a base saturation below 20% in the first inventory) and decreased in forest soils with reference base saturation values above 20%. There is both a decrease of soil pH and base saturation in the forest floor of the Arenosols and Podzols. In the Podzols this decreasing trend could not be established in the mineral soil, though this decreasing trend persisted in a number of mineral soil layers of the Arenosols. The only consistent increasing trend of pH and base saturation when stratifying according to the WRB reference soil groups was seen in the forest floor of the Luvisols and Cambisols

Soil chemical and physical status in semideciduous Atlantic Forest fragments affected by atmospheric deposition in central-eastern São Paulo State, Brazil

“…However, the forest soils near the industrial complex (Paulínia and Americana) were more acidic (pH = 3.6-3.9) than those located farther apart from industries near rural or urban sources (pH = 4.0-4.5), indicating that acidic deposition increases near the industrial area. The pH and base saturation are important indicators of chemical processes in the soil and thus are key descriptors for monitoring forest changes (Cools & Des Vos 2011 ), which had a direct influence on soil acidity and increase of m% (Jobbágy & Jackson 2001, Boruvka et al 2005, Ok et al 2007, Kimetu et al 2008, Ke-Hui et al 2010, SanClements et al 2010, as well as on the availability of heavy metals (Wei et al 2006, Wilson et al 2008, Stevens et al 2009). Furthermore, basic cations and organic matter buffer the soil acidity (Ross et al 2008, Ke-Hui et al 2010.…”

“…Soil sampling procedures were based on protocols for monitoring European forests (Cools & Des Vos 2011, Ferretti et al 2010, Filizola et al 2006, modified according to the forest physiognomy and environmental conditions found in the tropics. Two plots of 140 × 50 m were established at each sampling site (forest remnant) 100 m apart from the forest edge, totalling 14 000 m 2 at each site.…”

Variables related to nitrogen deposition improve defoliation models for European forests

“…biotic factors such as pests, or abiotic factors such as storms) (hereafter referred as BADoAP), annual total N thr deposition and a set of variables known to be directly or indirectly related to N deposition, namely foliar N ratios (N/Ca, N/P, N/K, N/Mg) and soil pH, exchangeable base cations (BCE) and C/N ratio in the mineral top soil (Ferretti et al 2014b;Cools and De Vos 2011;Cools et al 2014) (Table 1). For both predictors and response variables, assessment and measurement methods were those reported by Ferretti and Fischer (2013).…”

Bioindication and modelling of atmospheric deposition in forests enable exposure and effect monitoring at high spatial density across scales

“…For estimating atmospheric deposition we have to quantify the ratio between deposition values inside and outside of forests. Data to calculate these ratios should be collected in compliance with MSS and geostatistical criteria such as spatial auto-correlation which in general should be implemented in environmental monitoring schemes (Clarke et al 2010;Cools and de Vos 2011;Ferretti 2010Ferretti , 2011Ferretti et al 2014.…”

“…Currently, it comprises approximately 760 permanent plots in 30 participating countries, including 500 plots with atmospheric deposition and forest ecosystem impact monitoring . Comparability and meaningful interpretation of data derived from long-term monitoring across time require representative measurements based on harmonized methods and a statistically sound design (Clarke et al 2010;Cools and de Vos 2011;Ferretti 2010Ferretti , 2011Ferretti et al 2014. Within this context, the spatial representativity and comparability of atmospheric deposition measurements are crucial issues -for exposure and effect assessments Erisman et al 2003;Lorenz and Granke 2009;Žlindra et al 2011).…”