Intensive monitoring of forest ecosystems in Europe

Forest Ecology and Management 174 (2003) 77±95

Intensive monitoring of forest ecosystems in Europe 1. Objectives, set-up and evaluation strategy W. de Vriesa,*, E. Velb, G.J. Reindsa, H. Deelstrab, J.M. Klapa, E.E.J.M. Leetersa, C.M.A. Hendriksa, M. Kerkvoordenb, G. Landmannc, J. Herkendelld, T. Haussmanne, J.W. Erismanf a

AlterraÐGreen World Research, PO Box 47, NL-6700 AA Wageningen, The Netherlands b Oranjewoud International, PO Box 24, NL-8440 AA Heerenveen, The Netherlands c Min. Agri PeÃche DERF/DSF, 19 av du Maine, F-75732 Paris Cedex 15, France d European Commission, DG VI.FII.2, Rue de la Loi 130 10/177, B-1040 Brussels, Belgium e ICP Forests/BML 35, PO Box 14 02 70, D-53107 Bonn, Germany f ECN, PO Box 1, NL-1755 ZG Petten, The Netherlands Received 28 March 2001; received in revised form 25 October 2001; accepted 18 December 2001

Abstract In order to contribute to a better understanding of the impact of air pollution and other environmental factors on forest ecosystems, a Pan-European Programme for Intensive and Continuous Monitoring of Forest Ecosystems has been implemented in 1994. Results of the Programme must contribute to a European wide overview of impacts of air pollution and the further development of its control strategies, being described in air pollution protocols. Objectives of the Intensive Monitoring Programme related to air pollution are the assessment of: (i) responses of forest ecosystems to changes in air pollution; (ii) differences between present loads and critical loads (long-term sustainable inputs) of atmospheric deposition; and (iii) impacts of future scenarios of atmospheric deposition on the ecosystem condition. Furthermore, the Intensive Monitoring Programme contributes to the assessment of `criteria and indicators for sustainable forest management', such as the maintenance of forests as a net carbon sink to reduce the build up of atmospheric greenhouse gasses and the maintenance of species diversity of ground vegetation. The Intensive Monitoring Programme, which is carried out on approximately 860 selected plots, comprises monitoring of crown condition, forest growth and the chemical status of soil and foliage at all plots and monitoring of deposition, meteorology, soil solution and ground vegetation in a subset of the plots. In order to meet the major objectives of the Intensive Monitoring Programme, studies have been or are presently carried out with respect to the assessment of: (i) correlations between site and stress factors and the ``forest ecosystem condition''; (ii) trends in stress factors and/or ecosystem conditions; (iii) critical loads, by evaluating the fate of atmospheric pollutants in the ecosystem with input±output budgets; and (iv) large-scale and long-term impacts of climate and deposition on forests and vice versa. Examples of those studies are given and the potential of the Programme to ful®l the objectives is evaluated. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Monitoring; Forest vitality; Air pollution; Carbon sequestration; Critical loads; Sustainable forest management

* Corresponding author. Tel.: ‡31-317-474353; fax: ‡31-317-419000. E-mail address: [email protected] (W. de Vries).

0378-1127/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 1 1 2 7 ( 0 2 ) 0 0 0 2 9 - 4

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1. Introduction The health and vitality of forest ecosystems has become a subject of wide public and political concern since the beginning of the 1980s, due to the extensive forest damage observed in rural areas in central Europe (e.g. SchuÈtt et al., 1983; Lammel, 1984). Since 1986, forest vitality characteristics, i.e. defoliation and discoloration are monitored at a systematic grid throughout the whole of Europe (e.g. EC and UN/ ECE, 2000). In broader terms, the concern was related to the (long-term) sustainability of forest ecosystems in view of adverse environmental impacts, such as air pollution and climate changes, and the possibility to counteract these effects by forest management practices. The monitoring of forest (crown) condition (the so-called Level 1 Monitoring Programme) started in the middle of the 1980s at a systematic 16 km  16 km grid. Its major aim is to gain insight in the geographic and temporal variations in forest condition and its relationship with stress factors, including air pollution. The Level 1 Monitoring Programme is based on both the European Scheme on the Protection of Forests against Atmospheric Pollution (Council Regulation EEC No. 3528/ 86) and the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests). The latter Programme is part of the Convention of Long-range Transboundary Air Pollution of the UN/ECE (CLRTAP). In that same period, the Convention also set-up a Task Force on Mapping, with the aim to map critical loads of air pollutants on terrestrial (especially forest) and aquatic ecosystems. Within the same political context a ``Pan-European Programme for Intensive and Continuous Monitoring of Forest Ecosystems'' (the so-called Level 2 Programme) started in 1994. The major aim of the Intensive Monitoring Programme is to contribute to a better understanding of the impact of air pollution and other environmental factors on forest ecosystems. This Monitoring Programme focuses on air pollution impacts, since the results should be useful for the validation and further development of protocols on air pollution control strategies used within the convention, but over time, natural stress factors gained increasing attention. The implementation of the Intensive Monitoring Programme partly ful®ls the ®rst

Resolution of the ®rst ``Ministerial Conference on the Protection of Forests (MCPFE) in Europe'' held in Strasbourg (MCPFE, 1990). The second Conference in Helsinki (MCPFE, 1993), especially emphasised `criteria and indicators for sustainable forest management', conservation of biological diversity and adaptation to climate change. The same topics were stressed at the `third MCPFE in Europe' in Lisbon (MCPFE, 1998). Considering those policy issues, the scope of the Programme has recently been widened to these topics (ICP Forests, 2000). At this moment 863 permanent observation plots for intensive monitoring of forest ecosystems have been selected in 30 participating countries (512 in the European Union and 351 in non-EU countries). The Intensive Monitoring Programme aims to follow trends in stresses and responses for these selected ecosystems over a period of at least 15±20 years. The ``core'' activities are the assessment of crown condition, increment and the chemical composition of foliage and soil on all plots. Additional measurements on a sub-sample of the plots include atmospheric deposition, meteorological variables, soil solution chemistry and ground vegetation. In all these surveys, a number of mandatory and optional variables have been de®ned. Data are submitted by National Focal Centres (NFCs), including both EU-member states and non-member states, to a Forest Intensive Monitoring Co-ordinating Institute (FIMCI), being a contractor of the European Commission (EC). FIMCI has been set-up to validate, store, distribute and evaluate the data at European level. Within FIMCI, Alterra Green World Research and Oranjewoud International work together. The major aim of this paper is to introduce the Intensive Monitoring Programme by presenting and discussing:  Objectives in view of hypotheses for environmental effects on forest ecosystems (see Section 2) and the policy questions and scientific questions related to forest condition in Europe (Section 3).  The design and protocols, specifically in terms of plot selection, data assessment and quality assurance/quality control (Section 4).  Examples with respect to data evaluation, including correlative studies, trend studies and critical load assessments (Section 5).

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 The adequacy of the Programme and the possibilities to integrate the data evaluation with results from other research and monitoring programmes (Section 6). In a subsequent paper (de Vries et al., this volume), results will be presented of surveys on atmospheric deposition and soil solution chemistry, focusing on the interrelationship. 2. Hypotheses for environmental effects on forest ecosystems To evaluate the adequacy of the programme with respect to its major aim (gain better insight into the impacts of air pollution), it is helpful to consider the major hypotheses with respect to air pollution stress. Fig. 1 presents a conceptual overview of various hypotheses of forest ecosystem response to stress, focusing on air pollution. Note that nearly all forms of air pollution are mentioned, including S and N compounds, causing acidi®cation and eutrophication,

79

ozone, the greenhouse gases CO2, N2O and CH4, which cause global warming, and heavy metals, except persistent organic pollutants. Apart from impacts by natural stress and forest management, cause±effect relationships for forest ecosystems, speci®cally on forest condition and forest growth, in view of air pollution, can be divided into (see de Vries et al., 2000a for a detailed literature review; compare Fig. 1):  Aboveground impacts of elevated concentrations of SO2, NOx and O3 on: (i) the leaf stomata causing disturbances to water regulation and physiological drought; (ii) carbon allocation shifts leading to a weakened root system; and (iii) accelerated foliar leaching affecting the nutrient status.  Soil acidification by S and N deposition, including: (i) the loss of base cations (BC) from the soil causing deficiency of these nutrients (notably Mg); (ii) the release of toxic aluminium affecting fine root growth and inhibiting the uptake of BC; and (iii) a decrease in pH that may increase the mobility of heavy metals.

Fig. 1. Conceptual overview of the principal pathways and hypothesised mechanisms of forest ecosystem response to pollutant stress (modi®ed after NAPAP, 1990).

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information on the potential impact of stress factors on the different compartments is given in de Vries (1999).

 Soil eutrophication by elevated N inputs, causing: (i) a deficiency of base cation nutrients due to elevated demands, induced by an initial growth increase; (ii) enhanced drought stress since an elevated N input favours growth of canopy biomass, whereas root growth is relatively unaffected; and (iii) an increased sensitivity to natural stresses, such as frost and fungal diseases.

3. Objectives of the Intensive Monitoring Programme 3.1. Objectives in view of air pollution effects The original major aim of the `Pan-European Programme for the Intensive Monitoring of Forest Ecosystems' was to `to gain a better insight in the impacts of air pollution (speci®cally the elevated deposition levels of SOx, NOx and NHx) and other stress factors on forest ecosystems'. Scienti®c evaluations should thus be focused on the investigation of relationships between the variables describing the forest condition (such as defoliation, growth and nutrition) and the in¯uencing variables (such as site and stand characteristics, meteorology and deposition). As stated before, the results from the Intensive Monitoring Programme should be useful for the validation (and possibly the further development) of protocols on air pollution control strategies used within the convention. In 1994, a second protocol for SOx has been signed by the countries under the convention based on the concept of critical loads. Recently, a

It seems most appropriate to assume that forest condition (and to a lesser extent forest growth) does respond to all these stress factors, but that the contribution may differ depending on the geographic region. For example, direct impacts of sulphur dioxide and soil acidi®cation may dominate in parts of central Europe, eutrophication by nitrogen in parts of western Europe, ozone in parts of southern Europe, whereas natural stress is occurring all over Europe. For other parts of the ecosystem, however, the situation is different. For example, elevated N inputs are likely to be the most important cause of changes in the species composition of the ground vegetation, whereas acidi®cation, together with heavy metals are likely to be most important in relation to the species diversity of soil organisms. Those differences are further illustrated in Table 1 (compare also with Fig. 3). More

Table 1 Tentative overview of key stress factors for different effects in various ecosystem compartments Compartment

Effect

Key stress factorsa Global change

Air pollution

CO2

Climate change

N

Acidity

Ozone

‡ ‡

‡ ‡ ‡

‡ ‡ ‡

‡ ‡ ‡

‡ ‡ ‡/

‡ ‡

‡ ‡

‡ ‡

‡ ‡/

‡/

‡ ‡

‡

‡

‡

‡/

‡

Tree

Condition Growth Nutrition

Soil

Quality Carbon storage

Groundwater

Quality

‡

‡

‡

Flora

Species composition

‡

‡

‡

Soil fauna

Species composition

‡

‡/

‡

a

Ecological conditions and forest managementb

‡

‡

Metals

‡

Climate anomalies

Biotic factors

Site and stand characteristics

‡ ‡ ‡

‡ ‡/

‡ ‡ ‡

‡/

‡ ‡

A `‡' signi®es that an impact is expected, whereas a ` ' implies the reverse. A `‡/ ' signi®es that the impact is likely to be small. One should distinguish: (i) ``permanent'' factors, such as site characteristics (possibly modi®ed by forest history) and stand characteristics (as in¯uenced by silviculture), which may predispose forests to impact of air pollution, natural stress factors, and global change; and (ii) ``short-term'' stress factors, such as climate anomalies or biotic factors. b

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multi-pollutant multi-effect protocol, including SOx, NOx, NH3 and O3 has been signed in 1999 based on the same concept. In this context, a critical load is de®ned as `a quantitative estimate of an exposure (deposition level) to one or more pollutants (e.g. sulphur, nitrogen, heavy metals) below which signi®cant harmful effects on speci®ed sensitive elements of the environment (e.g. forest soils or forest ecosystems) do not occur according to present knowledge' (Nilsson and Grennfelt, 1988). At present, the concept of critical loads is strongly based on the use of soil chemical criteria, such as an Al=…Ca ‡ Mg ‡ K† ratio in the soil solution for critical acid loads. Furthermore, criteria for the foliar chemistry, such as N contents in foliage, are used in relation to critical N loads (e.g. de Vries, 1994; Posch et al., 1997). Validation of those critical loads on real ®eld data is, however, still needed. Concerning the importance of: (i) contributing to the further development of air pollution protocols; and (ii) deriving insight in the effects of present emission control measures, more speci®c objectives of the Intensive Monitoring Programme are the assessment of:  Responses of forest ecosystems to changes in air pollution by deriving trends in stress factors, including climate change and air pollution (acidification, eutrophication, ozone and toxic elements) and ecosystem condition.  Critical loads of atmospheric deposition, related to the chemical ecosystem condition, in relation to present loads by evaluating the fate of atmospheric pollutants in the ecosystem in terms of accumulation, release and leaching.  Impacts of future scenarios of atmospheric deposition on the (chemical) ecosystem condition.  Relevance of the results on a European scale, to contribute to a European wide overview of impacts of air pollution and its control strategies. The two latter objectives require the combination of results of the Intensive Monitoring Programme with other data available from extensive research or monitoring programmes. 3.2. Objectives in view of other prominent environmental issues The further development and monitoring of `criteria and indicators for sustainable forest management', is

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now also part of the objectives of the Intensive Monitoring Programme. Examples are the maintenance of: (i) forest ecosystem health/vitality and forest production; (ii) biological diversity of ground vegetation; and (iii) protective functions of soil and water resources; and (iv) forest potential as a net carbon sink to reduce the build up of atmospheric greenhouse gasses. Within the Intensive Monitoring Programme, changes (trends) in those indicators are assessed, such as forest health in terms of crown condition, forest production (tree growth) and the related carbon storage, species diversity of the ground vegetation and the chemical composition of soil and soil water in relation to changes (trends) in stress factors. The assessment of long-term sustainability is further related to the derivation of critical loads, a concept related to long-term nutrient availability and the occurrence of toxic elements. This concept is in line with the overall trend to debate environmental management issues, including climate change, biodiversity and air pollution, in terms of sustainability or sustainable developments (WCED, 1987; UN, 1992). In a review paper, Van Breemen et al. (1998) noted that the critical load approach is an adequate quantitative approach to derive criteria and indicators for the conservation and sustainable management of forests. In view of the rati®cation of the, so-called, Kyoto protocol, the programme can also contribute to the assessment of changes in carbon storage in forests (net carbon sequestration). This aim is primarily related to the impact of climate change. This topic has gained increased importance since 174 nations have rati®ed the United Nations Framework Convention on Climate Change (UNFCCC) in December 1997. According to this protocol, countries can reduce their emissions by both limiting fossil fuel consumption and by increasing net carbon sequestration in terrestrial ecosystems. In the protocol carbon sequestration is limited to strictly de®ned cases of afforestation, reforestation and deforestation (the so-called Kyoto forests). A full carbon budget, re¯ecting changes in carbon storage over suf®cient time scales (at least 5±10 years) is, however, needed to make a proper balance of carbon release and sequestration (Steffen et al., 1998). In this context, information on changes in carbon pools, both aboveground in standing biomass and belowground in soils, over a large number of forest stands does give relevant information when combined with other supportive

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measurements. Furthermore, information on the immobilisation on nitrogen in forest ecosystems, based on input±output budgets, can be used to assess carbon sequestration (see Section 5.4).

in Fig. 2. This map is based on information submitted until February 2000. The map indicates that the (relative) number of plots at which the continuous surveys on deposition, meteorology and soil solution are carried out varies strongly between countries.

4. Set-up of the Pan-European Intensive Monitoring of Forest Ecosystems

4.2. Available data

4.1. Conducted survey and plot selection The Intensive Monitoring Programme aims at the assessment of key variables describing the condition of the forest ecosystem and the stress on the ecosystem over a period of at least 15±20 years. The different surveys that are carried out and their temporal resolution is as follows:  crown condition (mandatory, at least once a year);  chemical composition of needles and leaves (mandatory, at least every 2 years);  soil chemistry (mandatory, every 10 years);  increment/forest growth (mandatory, every 5 years);  atmospheric deposition (mandatory on part of the plots, continuous);  soil solution chemistry (mandatory on part of the plots, continuous);  meteorology (mandatory on part of the plots, continuous);  ground vegetation (optional, at least every 5 years);  remote sensing/aerial photography (optional, at least once). Table 2 shows the number of plots selected and installed and the number of plots on which the different surveys are (planned to be) executed. Within each of these surveys, a number of mandatory and optional variables have been de®ned. An overview of the surveys carried out at the different plots is given

For a large number of monitoring plots in Europe (approximately 200±860 depending on the data considered), the intensive monitoring database contains data on:  Site factors: stand and site characteristics, stand history/management.  Stress factors: meteorological data and air pollution/atmospheric deposition data, pests and diseases.  `Biological' ecosystem condition: crown condition, forest growth, species composition of the ground vegetation.  `Chemical' ecosystem condition: foliar chemistry, soil chemistry, soil solution chemistry. A hypothetical ¯ow diagram of possible relationships between site and stress factors and effects (chemical and ecological ecosystem condition), related to the available data in the intensive monitoring database, is given in Fig. 3. It shows that the chemical condition of the ecosystem is mainly in¯uenced by the site and stress factors, whereas both site and stress factors and the chemical ecosystem condition in¯uence the `ecological' condition. The various relationships, indicated in Fig. 3, can be derived with the aid of empirical models, using, e.g. statistical techniques, or by process-based models, as further illustrated in the paper (Section 5). A selection of key variables, that give an adequate description of: (i) the ecological and chemical condition of the ecosystem; and (ii) the stresses on that

Table 2 Overview of the number of selected plots for the different surveys in the Intensive Monitoring Programme Countries

Total

Crown

Soil

Foliar

Growth

Atmospheric deposition

Meteorology

Soil solution

Ground vegetation

Remote sensing

Total EU Total non-EU

513 352

513 352

513 352

513 345

511 350

263 233

153 36

201 41

375 246

223 11

Total

865

865

865

858

861

496

189

242

621

234

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Fig. 2. Geographical distribution of surveys conducted at the Intensive Monitoring Plots (based on information received until February 1999; core relates to surveys conducted with respect to crown condition, soil chemistry, foliar chemistry and forest growth).

ecosystem in the various surveys/studies, is given in Table 3 (MuÈller Edzards et al., 1997). The relevance of the key variables follows directly from the objectives of the Intensive Monitoring Programme in view of hypotheses on air pollution effects (see also Klap et al., 1997, 2000). Note that the total number of variables that are assessed within the surveys is larger. Data on metals in soil (solution) and deposition are optional. Studies on the impact of heavy metals and related critical loads, however, require information on heavy metals in both deposition and soil solution (e.g. for model validation). If the Intensive Monitoring Programme is to contribute to this issue in the near future, one may thus include those data as key variables as well. It should be noted that the Intensive Monitoring Programme does not include in-depth scienti®c research on cause±effect relationships. Instead, the potentially available data set should be

used to test present hypotheses on the impact of natural and anthropogenic stress factors, including air pollution, on a European wide scale. 4.3. Quality assurance and quality control An important issue in all data evaluations is the comparability of data obtained by the application of different methods. In this context, the following harmonisation/evaluations take place:  Literature reviews on the comparability of data assessment methods. An example is a review of different methods for the sampling of soil solution chemistry (Derome et al., 2001).  Sample exchanges to evaluate the comparability of analyses performed by laboratories in the different participating countries, such as tests on deposition samples (LoÈvblad, 1997) and soil samples.

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W. de Vries et al. / Forest Ecology and Management 174 (2003) 77±95

Fig. 3. Flow diagram illustrating the relationships between site and stress factors and the forest ecosystem condition.

 Joint field campaigns to assess the comparability of data in the field. This is specifically relevant for the visual assessment of crown condition since there may be a systematic `observer variation' between countries (e.g. Innes et al., 1993) and/or differences in absolute or relative (locally defined) reference trees (see, e.g. MuÈller Edzards et al., 1997). In order to avoid such a disadvantage, investigations to correct for systematic country effects are relevant (see also MuÈller Edzards et al., 1997). This is crucial to perform statistical studies on a European scale (Klap et al., 2000). A joint field campaign has also been carried out with respect to deposition monitoring, comparing impacts of different sampler spacing and sampler numbers in the Speulder forest in the Netherlands (Draaijers et al., 2001).  Improvement of data quality, data comparability and evaluation possibilities of the stored data by: (i) using quality assurance programmes; (ii) increasing the data comparability by streamlining the monitoring methods used; and (iii) linking

monitoring data and information on data assessment methods (e.g. de Vries et al., 1999, 2000b). 5. Examples of relevant data evaluations in view of the objectives To reach the major objectives of the Intensive Monitoring Programme, it is considered necessary to:  Relate site and stress factors to the forest ecosystem condition (major aim of the Programme) by correlative studies.  Establish trends in forest (ecosystem) condition, and provide insight in (statistically significant) possible relationships with trends in stress factors.  Establish input±output budgets, describing the fate of atmospheric pollutants.  Provide information on the long-term sustainability of forest ecosystem with respect to atmospheric impacts, by determining critical loads.

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Table 3 Key variables describing the `ecological and chemical' forest condition and stress Type of parameter

Key parameter

Ecological condition Crown condition Increment Ground vegetation

Defoliation, discoloration, LAIa Diameter, tree height, volume (mortality) Species occurrence and abundance, ground vegetation indices

Chemical condition Foliar composition Major nutrients Minor nutrients Toxic elements

N, P, S, Ca, Mg, K, N/P, N/Mg, N/K Fe, Mn, Cu, Zn Al, Pb, Cd

Soil composition Carbon Nutrients Acidity Toxic elements

C N, P, Cab, Mgb, Kb, C/N, N/P pH, base saturationb Pb, Cd, Cu, Zn

Soil solution chemistry

SO4, NO3, NH4, Ca, Mg, K, Al, Fe, Mn, pH, DOC

Site factors Stand characteristics Site characteristics

Tree species, tree age, stand density index, site structure index Climatic region, altitude, soil type

Stress factors (short term) Biotic stress Air pollution Meteorology

Damage types caused by known factors (insects, fungi) O3, SO2, NOx and NH3 concentrations in air SO4, NO3, NH4, Ca, Mg, K, pH in bulk deposition and throughfalla Precipitation, temperature (radiation, wind speed), evapotranspirationc

a

These variables are yet hardly or not available. Nutrients are most relevant for the organic layer and acidity variables for the mineral layer. c Evapotranspiration can be calculated from the mandatory meteorological variables. b

 Validate and initialise models predicting future impacts.  Generalise the results gained by combining data from the Intensive Monitoring Programme with other databases (upscaling studies). Examples of several studies (being) carried out are given below to illustrate the use of such studies in reaching the mentioned objectives. 5.1. Correlative studies 5.1.1. General approach Considering the lack of process-based information in the Intensive Monitoring Programme and the present knowledge of the multiple stress factors affecting forest condition, a study of the relationship between forest condition variables and the most relevant stress factors, can best be investigated in a correlative

empirical study. Relevant correlative studies are investigations of the relationship between ground vegetation, forest growth and crown condition versus stand and site characteristics, atmospheric deposition, foliar composition, soil and soil solution chemistry (see also Fig. 3). At present correlative studies have been carried focusing on the relation of crown condition, foliar chemistry, soil chemistry and soil solution chemistry versus atmospheric deposition (de Vries et al., 1998, 1999, 2000b). Those statistical relationships have been derived, using knowledge on the various in¯uencing factors. The various studies were carried out with different statistical approaches including ordination techniques and multiple regression models. Ordination was used as an exploratory technique, being particularly suitable when analysing multiple responses (y-variables) to multiple causes (x-variables). Multiple regression models were used for more in-depth

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times the reverse was true. This conclusion is in line with results from other correlative studies on the impact of acid deposition (Klap et al., 1997, 2000; Hendriks et al., 1997, 2000). There are possible explanations for this, such as:

assessments of relationships between effect variables and stress factors. Within the regression model the effect of each stress factor was tested by a thorough search procedure called Rselect (Oude Voshaar, 1994). Relationships between the chemical composition of the soil solution in forest soils on one hand and the atmospheric deposition, precipitation and stand and site characteristics on the other hand are presented in the subsequent paper (de Vries et al., this volume).

 A negative effect of precipitation due to excessive wetness and a positive effect by a decrease in drought stress.  A negative effect of N deposition in N saturated systems and a positive effect of an increased N availability in nutrient poor forests.

5.1.2. Study related to crown condition Here, we report on an example of a correlative crown condition study carried out at approximately 262 plots where throughfall data were available. The study was conducted to analyse the impact of different environmental factors on the defoliation of pine, spruce, oak and beech. Results showed that 30±50% of the variation in defoliation could be explained by the variation in stand age, soil type, precipitation, N and S deposition and foliar chemistry (Table 4). As with previous studies (e.g. Klap et al., 1997, 2000; MuÈller Edzards et al., 1997) highly signi®cant adverse relations were found between defoliation and stand age for all tree species except pine. The defoliation of spruce and oak appeared to be larger in poorly buffered sandy soils compared to well-buffered clayey soils. An increase in precipitation and in N deposition sometimes caused an increased defoliation and some-

Most likely this effect is due to bias. Impacts of foliar contents on defoliation were generally small. An in-depth interpretation was still hampered by a lack of information on stand history, pests and diseases and air quality at most of the plots and by the relatively small data set used for the so-called regression analysis. More information on the study is given in de Vries et al. (2000b). The results are only considered as a ®rst step. When more data become available, the relationship may be improved by including (see, e.g. Klap et al., 2000):  The temporal correlations between the repeated observations on the same site (longitudinal data) and the spatial correlation between neighbouring sites.  Prolonged or delayed effect of certain stress factors on the forest condition (so-called prolonged or

Table 4 Overview of the predictor variables explaining defoliation of the four most represented tree species of the Intensive Monitoring Plots with the number of plots (n) and the percentage accounted for …R2adj † Variable Soil type Age (year) Precipitation (mm per year) Temperature (8C) N deposition (molc ha 1 per year) S deposition (molc ha 1 per year) Foliar N content (g kg 1) Foliar Ca content (g kg 1) n R2adj

Scots pine

‡

‡‡c

d

Common beech

‡

‡‡

e

‡‡

‡‡

‡

‡‡ 95 35

For soil type implies that this variable was signi®cantly related to defoliation. Signi®cant and positive correlated with response variable. c Highly signi®cant and positive correlated with response variable. d Highly signi®cant and negative correlated with response variable. e Signi®cant and negative correlated with response variable. b

Pedunculate oak

a

‡b ‡

59 21 a

Norway spruce

33 44

35 48

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delayed effects). This holds specifically for climatic stress factors (such as an extreme drought or frost period), but it may also hold for a severe acute event of atmospheric pollution.  The occurrence of interactions between predictor variables in the regression model. For instance, it might be necessary to include interaction terms between meteorological stress variables and soil variables and bio-geographic region.  The use of threshold values with respect to the stress factors, such as critical concentration levels for ozone in the atmosphere or critical values for the nutrient contents in foliage. When values of stress factors are known (based on process-oriented research on causal dose±effect relationships), it may be put to zero below an assumed critical limit. One may, however, also try to derive a critical level from available data. 5.1.3. Study related to foliar condition The chemical composition of the foliage of forest trees is an important indicator for the functioning of trees, especially with respect to their nutrition. The content of elements (nutrients) in the foliage provides information on de®ciency or excess, either in absolute values or relative to the content of other elements. Criteria for de®ciency (low) or excess (high) in nutrient contents and nutrient ratios are based on expert judgements from a Forest Foliage Expert Panel as presented in Stefan et al. (1997). An evaluation of the foliar composition of pine, spruce, oak and beech 674 plots showed that in approximately 30% of the stands, the nutrient status of the foliage can be judged as insuf®cient and/or unbalanced, taking for all nutrients into account (see Table 5). Beech had the highest percentage of stands with an insuf®cient and unbalanced status with respect to K, Ca and Mg. Taking all nutrients into account an insuf®cient and unbalanced status for one or more of them occurred at 22±55% of the plots, the higher value relating to beech. This illustrates that in most cases, only one nutrient was insuf®cient or unbalanced compared to nitrogen. An assessment of relationships of the foliar nutrient contents with environmental factors took place at some 200 plots where throughfall data were available using multiple regression analyses. There was a statistically signi®cant in¯uence of stand age, soil type,

87

Table 5 Percentage of Intensive Monitoring Plots with insuf®cient nutrient availability and/or an unbalanced nutrient status compared to nitrogen Tree

P

K

Ca

Mg

All nutrients

Pine …n ˆ 245† Spruce …n ˆ 200† Oak …n ˆ 126† Beech …n ˆ 103† All trees …n ˆ 645†

10 7 26 23 14

13 10 5 14 11

5 2 7 11 5

4 4 8 32 9

27 22 38 55 32

altitude, precipitation temperature, soil chemistry and atmospheric deposition on foliar nutrient contents. The in¯uence of these environmental factors differed, however, considerably per nutrient and tree species. There was a relatively high in¯uence on the foliar contents of N (44±63% of its variation could be explained) and Mg (33±71%). Low percentages variation accounted for were found for P (20±29%) and K (26±38%). The impact of site and stand characteristics (soil type, altitude and stand age) differed for tree species. The N and S deposition was signi®cantly related to the foliar N and S content for the coniferous species. The impact of N deposition was larger on pine than on spruce as illustrated in Fig. 4. This result shows that a possible imbalance of nutrients compared to nitrogen is certainly in¯uenced by atmospheric N input, at least for these tree species. For both pine and spruce, a large variation in N contents was, however, observed even at low N inputs. This variation is most probably caused by local differences in N availability from the soil, which among other factors, strongly depends on the historical use of the soils. 5.2. Trend studies related to soil chemistry assessment The occurrence of trends and the possible relationship between trends (e.g. in crown condition and air pollution) is one of the central aims of the Intensive Monitoring Programme. When data from repeated surveys become available, such trend studies may be carried out. It is important to realise that they can usually only be detected after a relatively long time period, especially for variables that change slowly, such as soil variables and forest biomass.

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Fig. 4. Relationships between N contents in pine (A) and spruce (B) and N input by throughfall.

In case of the soil survey, a repetition is intended once every 10 years. Special emphasis should in this case also be given to the reliability of the derived data since the differences may not only be caused by temporal changes but also by spatial variability. Information on the number of samples taken and, where available, the sample mean and standard deviation is crucial in this context. An analysis of changes that are required to detect signi®cant trends in element pools was recently carried out using present data on those pools (de Vries et al., 2000b). Required changes in pools of carbon, nitrogen and BC were calculated as a function of the measured pool size, its standard deviation (assuming a deviation of 20% of the mean value) and the number of samples that were taken to derive those data. Smallest changes were required in the organic layer, followed by the mineral topsoil, as illustrated for nitrogen in Table 6. An assessment of time periods needed to get signi®cant trends and of relationships with environmental factors was conducted at approximately 200 plots for which deposition data were available. The evaluation focused on nitrogen in the organic layer, since this pool is most liable to change by nitrogen deposition. A direct comparison of required changes in the N pool in the organic layer and the accumulated N input in a 10year period, assuming that deposition remains constant for the next 10 years, suggested that a signi®cant change can be expected at more than 50% of plots. In reality, however, not all N will be retained in the

organic layer since part is accumulating in the mineral soil and part is leached to groundwater. Using a simple model, allowing for these aspects, resulted in an estimated 25% of the plots where a signi®cant change can be expected (Fig. 5). The required time periods that are needed to assess signi®cant trends in pools, become proportional greater with the pool size itself and generally decrease with an increase in atmospheric deposition. More information on the study is given in de Vries et al. (2000b). 5.3. Input±output budget studies, and the assessment of critical loads Input±output budget studies inform about possible accumulation or release of sulphur, nitrogen, BC and aluminium in the ecosystem. More speci®cally, results Table 6 The ranges in nitrogen pools and the required changes in those pools to assess signi®cant differences for the organic layer and the mineral topsoil of Intensive Monitoring Plots Range (%)

5 50 95

N pool (kg ha 1)

Required changes (kg ha 1)

Organic layer

Topsoil

Organic layer

Topsoil

66 396 2731

447 1537 3860

14 81 793

68 318 1700

W. de Vries et al. / Forest Ecology and Management 174 (2003) 77±95

89

Fig. 5. Relationships between calculated required time periods to assess signi®cant trends in N pools and the original N pool for different N deposition ¯uxes (A) and C/N ratios (B).

about the input and output of SO4, NO3 and NH4 give insight in: (i) the actual rate of acidi®cation due to anthropogenic sources; and (ii) the potential rate of acidi®cation by immobilisation of S and N. Results about the input and output of Al and BC give information about the mechanisms buffering the acid input. The ratio of Al to BC release is believed to be a key aspect with respect to soil mediated effects of acid inputs (Sverdrup and Warfvinge, 1993). These features can be used to derive critical deposition levels for forest soils (ecosystems), and the comparison of these loads with present loads will help assessing air pollution stress on the chemical ecosystem condition. Recently, input±output budget studies have been carried out at approximately 120 intensive monitoring plots where atmospheric deposition and soil solution chemistry data are available (de Vries et al., 2001). Present deposition thresholds (PDTs) for the selected intensive monitoring plots will be based on the estimation and interpretation of various buffer processes from an input±output budget for N, S and BC according to Nretention ˆ Ndeposition Nleaching ˆ Nnet ‡ Ndenitrification ‡ Nnet uptake Sretention ˆ Sdeposition Sleaching ˆ Snet ‡ Snet uptake

immobilisation

(1)

immobilisation

(2)

BCrelease ˆ BCdeposition

BCleaching

ˆ BCweathering ‡ BCexchange BCnet uptake BCnet immobilisation PDTnitrogen ˆ Nretention ‡ Nleaching …crit†

(3) (4)

PDTacidity ˆ BCrelease ‡ Sretention ‡ Nretention ‡ ACleaching …crit†

(5)

The different terms are derived as follows:  Input fluxes from fortnightly or monthly measurements of the chemical composition of bulk deposition and throughfall water, multiplied by the water fluxes while correcting for canopy uptake. In this context, use is made of a canopy budget model, as summarised in Draaijers et al. (1998).  Output fluxes by multiplying fortnightly or monthly measurements of the soil solution composition at various depths with simulated unsaturated soil water fluxes (e.g. Van Grinsven et al., 1987).  The term Nleaching(crit) will either be related to a critical N content in the foliage in view of negligible growth response or increased risks for frost, drought, pests and diseases or to the occurrence of ground vegetation changes.  The term ACleaching(crit) will be related to a critical Al/BC ratio in terms of root growth or root uptake.

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Results of the study are foreseen in a one year period. Apart from deriving PDTs, long-term steady-state critical loads will be derived, in which dynamic processes such as net mineralisation/immobilisation of N, S and BC and adsorption/exchange of BC are not considered. The equations to calculate critical loads (CLO) are (de Vries, 1993; Sverdrup and Warfvinge, 1993): CLOnitrogen ˆ Ndenitrification ‡ Nnet ‡ Nleaching …crit†

uptake

CLOacidity ˆ BCdeposition ‡ BCweathering BCnet ‡ Ndenitrification ‡ Nnet uptake ‡ ACleaching …crit†

(6)

Table 7 Estimated net carbon sink for European forests due to net tree growth and net immobilisation in the soil Region

Carbon sequestration in forest (Gt per year) Actual tree wood

Long-term Forest soil tree wood

EU countries Other European countries

0.184 0.095

0.073 0.038

0.0076 0.0016

Total

0.279

0.115

0.0093

uptake

(7)

5.4. Generalisation studies: predicting carbon sequestration at the European scale as an example Generalisation or upscaling is speci®cally useful to:  Increase the availability of data at the intensive monitoring sites when data are collected only at part of the plots.  Scale up results from Level 2 to the plots that are monitored at a systematic grid (Level 1 plots), which are representative for the whole of Europe. Upscaling can be done by:  interpolation of available data (e.g. meteorological data);  extrapolation by validated process-oriented models (e.g. atmospheric deposition data);  extrapolation by statistical relationships between the data to be derived (e.g. the chemical ecosystem condition) and readily available data (e.g. stand and site characteristics and atmospheric deposition data); An upscaling approach was applied to assess N and C sequestration in European forests. The calculation of N sequestration was based on available relationships between the N input in deposition and the magnitude of N leaching from forests (and, inversely, the N sequestration in forests), as a function of the forest ¯oor C/N ratio (e.g. Matzner and Grosholz, 1997; Gundersen et al., 1998; Dise et al., 1998). An

improvement of those estimates is foreseen, based on the input±output budget study at Level 2 plots presented in the previous section. Net C sequestration was based calculated by multiplying the nitrogen retention by the C/N ratio of the forest soil considered. Assumptions and limitations of this approach are discussed by Nadelhoffer et al. (1999) and de Vries et al. (2000c). The estimated actual and long-term carbon sequestration in tree wood and forest soil is given in Table 7. Results for the actual carbon sequestration in tree wood appeared to be comparable to those based on CO2 exchange ¯uxes (NEE) derived by Martin et al. (1998) based on the Euro¯ux sites. Long-term carbon sequestration data for tree wood are comparable to those derived from repeated forest inventories (Kauppi et al., 1992; Nabuurs et al., 1998). Results for the forest soil were, however, much lower than those derived from by Schulze et al. (2000) based on the C retention in 11 sites (0.21 Gt C per year). The latter estimate is likely to be an overestimate, as it would imply that the C/N ratio of European forest soils is strongly increasing. There are no indications that this is the case. To the reverse, it is more likely that C/N ratios are decreasing, especially in areas with an elevated N deposition. This result thus illustrates that it is dangerous to make estimates on a European scale based on a limited number of plots using a simple upscaling procedure. The major result of the calculation was that C sequestration by forest is mainly due to a net increase in forest growth, since the long-term sequestration in the soil is very limited. More information on the procedure and results is given in de Vries et al. (2000c).

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6. Discussion 6.1. Adequacy/limitations of the intensive monitoring database Comparison of Figs. 1 and 3 illustrates that most stress and overall response factors are included, at least at part of the intensive monitoring plots. This includes atmospheric deposition of S and N compounds, meteorological conditions, changes in the chemical conditions in foliage, soil and soil solution and the overall response of the ecosystem in terms of crown condition, growth and species composition of the ground vegetation. However, several limitations can be identi®ed:  There is no information with respect to effects on roots, such as variables describing fine root growth, mycorrhizae frequency, and soil micro-organisms/ fauna (missing `boxes' in Fig. 3), the programme being strongly focused on aboveground effects.  Information on the exposure to gaseous pollutants is almost lacking. Especially the lack of ozone data is felt as a serious limitation that needs further attention.  Information on the leaf area index (LAI) is missing, which is a crucial parameter in estimating (modelling) net carbon exchange fluxes.  Information on biotic stresses (pests/diseases) is limited, the programme being strongly focuses on the impacts of climate and chemicals (nutrients, acidity).  Information on forest history and stand dynamics is also insufficient, having in mind that reactions of forest stands to current stresses may depend on past forest management. Actions have been initiated to try to ®ll in some of these gaps, but standardised, robust sampling and measurement protocols, which can be repeated over time, are often lacking (root system) or are very timeconsuming (e.g. several surveys every year for a proper assessment of biotic factors). Possibly one of the easiest gap to ®ll in is the assessment of ozone concentrations using passive samplers (in addition to interpolated data from existing stations). Comparison of the boxes in bold in Fig. 1, which are measured at part or all intensive monitoring plots, and the other boxes, which are not measured, illustrates

91

that the underlying mechanisms or processes are not measured. This limits information on the causality between causes and effects. For example, information on plant physiological processes, nutrient cycling processes (foliar uptake, litterfall, mineralisation, root uptake), nitrogen transformation and geochemical processes (e.g. nitri®cation, weathering) is missing. As an example, elevated ozone concentrations may cause changes in carbon allocation patterns that will affect root growth, competitive patterns and the ability to respond to stress (see also Fig. 2) and this information is not available. It has to be stressed, however, that the Monitoring Programme is not meant to be an in-depth research programme that deciphers all the complexities involved. Using the above given example, one can study the overall impact on growth and crown condition (see Table 1), while interpreting the results in view of the available knowledge. One may also think about including a few ``process-based'' variables (e.g. litterfall, mineralisation) in the measurement programme on a part of the Level 2 plots. In any case, the data are very useful for model initialisation and/or model validation (especially in the course of time) using model parameters that are derived from other process-oriented laboratory and ®eld studies (use of so-called generic parameter data). The data set can also be used for calibrating those data on measured responses. The strength of the Intensive Monitoring Programme is the large number of sites and the length of data in time. The data should include key variables or indicators for both overall stress and decline. This requirement is largely ful®lled and as such, the Programme can meet its initial objectives and contribute strongly to the implementation of the indicators for the conservation and sustainable management of forests (see Section 3.2), as illustrated in Table 8. From Table 8, it is clear that nearly all surveys do contribute to several of the quantitative indicators mentioned. A repetition of the increment survey and soil survey, for example, gives information on the change in carbon storage in the forest and forest soil. Input±output balances, based on the surveys for deposition, meteorology and soil solution, gives insight in nutrient balances in the soil, etc. The present surveys do, however, not contribute to indicators related to species diversity of the (soil) fauna or the

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Table 8 Possible contribution of the Intensive Monitoring Programme to the implementation of criteria and indicators for the conservation and sustainable management of forests Compartment

Criteriaa

Indicatorsb

Survey

Whole ecosystem

Contribution to global carbon cycles

Mean and total volume of growing stock Total carbon storage

Incrementc

Forest health and vitality

Deposition of air pollutants Serious defoliation Serious damage by natural stress factorsd Balance between growth and removals Number and percentage of threatened species Soil chemical propertiese Nutrient balance

Tree layer

Productive functions Ground vegetation/fauna

Biological diversity

Soil

Protective functions

Soil, increment Deposition Crown condition Crown condition/meteorology Incrementc Ground vegetation Soil Deposition, meteorology and soil solution

a

Each criterion starts with `Maintenance and conservation or enhancement of . . .'. Each indicator starts with `Changes in . . . during the last 5 or 10 years'. c Even though the Intensive Monitoring Programme does contribute to this item by means of an increment survey, the number of sites is very limited. d Natural stress factors include pests, diseases, forest ®res, storms, game and grazing. e In the Resolution L2, changes in soil chemical properties are placed under `forest health and vitality', whereas it is placed under ``Protective functions of forests'' in the Montreal Process. In our view, this is a more proper place. b

social function of forests such as recreation. In this context, it is also relevant to state that there are several indicators, which are not mentioned in Resolution L2, which can be derived from, e.g. the foliar survey (tree nutrition) and the meteorological survey (extreme temperatures, drought and frost stress; see Table 8). 6.2. Integration and interaction with other monitoring and research programmes It is the integration of data sets that will lead to the most advantageous use of the data gathered at the Intensive Monitoring Programme. There are various possibilities of integration and interaction with other programmes, including:  Using data from other programmes in data evaluations and model predictions.  Applying data gathered at the Intensive Monitoring Programme in other programmes.  Combining the overall aims, data management and data evaluation procedures of the Intensive

Monitoring Programme with other monitoring programmes. Those aspects are discussed in more detail below. 6.2.1. Using data from other programmes in data evaluations and model predictions It is clear that not all the relevant data are gathered at all the intensive monitoring plots. A striking example is the lack of air concentration data at nearly all the plots and of atmospheric deposition data at part of the plots. An estimate of air quality data could also be made by atmospheric emission/transport models, while making use of data available at EMEP. Similarly, meteorological data may be interpolated from data that are available at nearby meteorological stations. In this context, it is useful to conduct studies in which interpolated data from nearby weather stations are compared with available measured data at part of the intensive monitoring plots. Another example is the use of model parameters, such as rate constants for processes as a function of environmental conditions, from previous research programmes (e.g. BIATEX, NITREX and

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EXMAN) and ongoing research within the Fifth Framework Programme of DG Research of the EC. 6.2.2. Applying data gathered at the Intensive Monitoring Programme in other programmes Inversely, other research programmes could use data from the Intensive Monitoring Programme. An example is the request for data by the Carbo-Europe group, a cluster of seven projects dealing with largescale carbon sequestration. Within this cluster, very intensive measurements on the exchange of water, heat and CO2 are carried out at more than 30 plots, part of them being previous Euro¯ux plots. Combination of those data with those from the Intensive Monitoring Programme, while using an adequate modelling and upscaling approach, can be most bene®cial to gain insight in the interactive effects of changes in climate, atmospheric deposition and land use on pools and ¯uxes of carbon, nutrients and water on a large regional scale. 6.2.3. Combination of aims, data management and data evaluation procedures of the Intensive Monitoring Programme with other monitoring programmes This aspect of integration has been discussed extensively at a Workshop in March 1999 entitled NoLIMITS (Networking of Long-term Integrated Monitoring in Terrestrial Systems), that was funded by the European Network for Research in Global Change (ENRICH). In general, it would be most advantageous to improve: (i) the comparability between monitoring projects by developing a basic measurement protocol; and (ii) the possibilities for integrating research projects by using common sites. Examples where such combinations would be useful are the ICP on Integrated Monitoring, where similar intensive measurements are taking place in forested catchments (e.g. Kleemola and Forsius, 1999), and the Carbo-Europe programme mentioned before. Actually, only three of the 32 Carbo-Europe plots coincide with those from the Intensive Monitoring Programme. Considering that the integration of data gathered in different programmes will lead to the most advantageous use of it has lead us to the initiation of information exchange at various programme meetings, including the comparison of measurement protocols and data evaluation methodologies.

93

Acknowledgements We gratefully acknowledge the European Commission for their ®nancial support. Thanks to the submission of data and information by the National Focal Centres to FIMCI without which the preparation of this paper was not possible. We also thank the Scienti®c Advisory Group of the Intensive Monitoring Programme for its active participation in discussing the results. References de Vries, W., 1993. Average critical loads for nitrogen and sulphur and its use in acidi®cation abatement policy in The Netherlands. Water Air Soil Pollut. 68, 399±434. de Vries, W., 1994. Soil response to acid deposition at different regional scales. Field and laboratory data, critical loads and model predictions. Ph.D. Thesis. Agricultural University, Wageningen, The Netherlands, 487 pp. de Vries, W., 1999. Intensive Monitoring of Forest Ecosystems in Europe. Evaluation of the programme in view of its objectives, studies to reach the objectives and priorities for the scienti®c evaluation of the data. A Strategy Document. Forest Intensive Monitoring Coordinating Institute, Heerenveen, The Netherlands, 40 pp. de Vries, W., Reinds, G.J., Deelstra, H.D., Klap, J.M., Vel, E., 1998. Intensive Monitoring of Forest Ecosystems in Europe. Technical Report 1998. UN/ECE, EC, Forest Intensive Monitoring Coordinating Institute, Heerenveen, The Netherlands, 193 pp. de Vries, W., Reinds, G.J., Deelstra, H.D., Klap, J.M., Vel, E., 1999. Intensive Monitoring of Forest Ecosystems in Europe. Technical Report 1999. UN/ECE, EC, Forest Intensive Monitoring Coordinating Institute, Heerenveen, The Netherlands, 173 pp. de Vries, W., Klap, J.M., Erisman, J.W., 2000a. Effects of environmental stress and crown condition in Europe. I. Hypothesis and approach to the study. Water Air Soil Pollut. 119, 317±333. de Vries, W., Reinds, G.J., Kerkvoorde, M., Hendriks, C.M.A., Leeters, E.E.J.M., Gros, C.P., Voogd, J.C.H., Vel, E., 2000b. Intensive Monitoring of Forest Ecosystems in Europe. Technical Report 2000. UN/ECE, EC, Forest Intensive Monitoring Coordinating Institute, Heerenveen, The Netherlands, 188 pp. de Vries, W., Reinds, G.J., Gundersen, P., Klap, J.M., 2000c. Assessment of the current carbon sequestration in European forest soils. In: Fischer, R., de Vries, W., Seidling, W., Kennedy, P., Lorenz, M. (Eds.), Forest Condition in Europe. Executive Report 2000. UN/ECE and EC, Geneva, Brussels, pp. 32±34. de Vries, W., Reinds, G.J., van der Salm, C., Draaijers, G.P.J., Bleeker, A., Erisman, J.W., Auee, J., Gundersen, P., Kristensen, H.L., van Dobben, de Zwart, D., Derome, J., Voogd, J.C.H.,

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