Visible injury, crown condition, and growth responses of selected Italian forests in relation to ozone exposure

Environmental Pollution 157 (2009) 1427–1437

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Visible injury, crown condition, and growth responses of selected Italian forests in relation to ozone exposure Filippo Bussotti a, *, Marco Ferretti b a b

` degli Studi di Firenze, Dipartimento di Biologia Vegetale, Piazzale delle Cascine 28, 50144 Firenze, Italy Universita ` di Siena, Italy TerraData environmetrics, Dipartimento di Scienze Ambientali, Universita

Despite considerable exceedance of internationally agreed exposure limits, evidence of ozone effects on selected Italian forest sites is limited.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 September 2008 Accepted 18 September 2008

The impact of ozone on forest ecosystems in Italy is monitored within the CONECOFOR programme. Ozone levels are measured in 30 plots using passive samplers. Response parameters used are: crown condition (transparency), BAI (basal area increment), and visible symptoms on spontaneous vegetation. Levels of AOT40 are above the concentration-based critical level of 5 ppmh in all sites, but the evidence of impact on forest vegetation remains limited. Ozone is a predictor of crown transparency residuals in beech sites over two consecutive years, but the variance explained amounts to less than 10%. The relation between BAI reduction and ozone is even less certain. Transparency and BAI are more readily explainable in terms of ecological conditions of the site and climate fluctuations. The interpretation of visible symptoms is doubtful, and is conditioned by the prevailing ecological factors in the areas. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Basal area increment Crown transparency Critical levels Forest monitoring Visible leaf injuries

1. Introduction Ozone [O3] has been acknowledged as being the air pollutant of major concern for forests in Southern Europe (Bussotti and Ferretti, 1998). High exposure levels were reported for the permanent monitoring plots of the Italian national forest monitoring programme CONECOFOR (CONtrollo ECOsistemi FORestali) (Gerosa et al., 2003, 2007). Exposure levels in terms of AOT40 exceed by far the 5 ppmh concentration-based critical level (CLec) set by the UN/ ECE to protect ‘‘sensitive vegetation under sensitive conditions’’ (UN/ECE, 2004; Ferretti et al., 2007b). When high levels of ozone are documented, the question is: is there any evidence of effect on vegetation and mature trees under field conditions? However, the problem of moving from a potential risk estimate to the actual effects is not easy to solve, since it is difficult to work on mature forests. Most of our knowledge on the mechanistic cause–effect relationship comes from studies of young trees growing in controlled or semi-controlled conditions whose physiology and responses are very different from those of adult trees (Kolb et al., 1997; Kolb and Matyssek, 2001; Matyssek et al., 2007). Adult trees have a marked ability to buffer the effects of ozone, thanks to their reserve organs which enable them to enact greater detoxification and defence mechanisms than young trees (Nunn et al., 2005). Within a pluri-annual free air ozone enrichment experiment on a mature forest (Kranzberg, Germany), a 2 O3 regime did not * Corresponding author. Tel.: þ39 055 3288369; fax: þ39 055 360137. E-mail address: filippo.bussotti@unifi.it (F. Bussotti). 0269-7491/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.envpol.2008.09.034

significantly affect adult beech trees over the short-term (annual) scale (Wipfler et al., 2005; Matyssek et al., 2007; Gielen et al., 2007). However, long-term growth reduction, as a consequence of acclimation processes in a worsened environment, cannot be ruled out. European forests are showing a long-term trend of increased productivity, because of a combination of factors including increased CO2, nitrogen depositions and climate changes (Nabuurs et al., 2003). These factors ameliorates the resilience of trees against ozone, but, on the other hands, ozone itself is considered a factor potentially capable of reducing the ‘‘benefits’’ of CO2 and N fertilization (King et al., 2005; Magnani et al., 2007). Traditionally, association and consistency between cause (ozone) and effects (various tree response indicators) on adult trees have been investigated through correlative studies at different spatial and temporal scales (Table 1). These studies have had a number of applications, mostly because they represent the only option for large-scale field monitoring in conditions where it is not possible to set up experiments (Ferretti et al., 2007a). Correlative studies can be divided into different categories in relation to the nature of the predictor data and the response indicators used. These distinctions are relevant and useful in understanding the pros and cons of the activity carried out in Italy. As far as the predictor is concerned, two main categories can be identified: studies based on modelled ozone exposure (predictor) and measured effects (different metrics) (e.g. Mu¨ller-Edzards et al., 1997; Zierl, 2002) and studies based on measured ozone exposure and measured effects (e.g. Ferretti et al., 2003, 2007a; McLaughlin and Downing, 2002). It is worth noting that the first category of

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Table 1 Summary of the investigation about ozone effects on different indicators in the field (crown transparency, basal area increment, branches and leaf morphology). See text for details. Reference

Kind of survey and response parameter

Main results

Peterson et al. (1991)

Dendroecological studies on 56 Pinus ponderosa stands in Sierra Nevada, California. Correlative studies. Statistical analysis of crown conditions along to an ozone pollution gradient in UK Dendroecological studies on Pinus strobus trees growing in the Acadia National Park, Maine, USA Differences in radial growth were tested in Liriodendron tulipifera and Prunus serotina in relation to the foliar symptoms history Stem increment of mature Fagus sylvatica trees from 57 plots in Switzerland was analysed with respect to environmental factors using multilinear regression Epidemiological surveys in Pinus halepensis stands in Spain.

Radial increments were reduced since 1950 in areas with the highest levels of ozone and foliar injuries. Crown conditions worsened at high ozone-level sites

Innes and Boswell (1991), Innes and Whittaker (1993) Bartholomay et al. (1997) Somers et al. (1998)

Braun et al. (1999)

Sanz et al. (2000) Mu¨ller-Edzards et al. (1997), Klap et al. (2000), De Vries et al. (2003) Zierl (2002)

Stribley and Ashmore (2002) McLaughlin and Downing (2002) Dittmar et al. (2003)

Correlative studies. Statistical analysis of crown conditions according to ozone gradients within the permanent monitoring European network Stomatal ozone uptake was modelled at the permanent monitoring plots in Switzerland, and results were related to defoliation Quantitative twig analysis was performed on old beech trees in Southern Britain Stem increment of mature Pinus taeda Dendroecological studies in mature beech trees growing in Central Europe

Ferretti et al. (2003)

Crown transparency (CT) and basal area increments (BAI) in permanent monitoring plots in Italy (Fagus sylvatica, Picea abies, deciduous oaks) over the period 1996–2000

Vollenweider et al. (2003b)

Stem diameter reduction was evaluated on 120 Prunus serotina trees, growing in Massachusetts, over a 31-year period, in relation to foliar symptoms 17 long-term monitoring plots in the Carpathian mountains

Muzika et al. (2004) Bussotti et al. (2005b) Ewald (2005)

Karlsson et al. (2006) Ferretti et al. (2007a)

Braun et al. (2007)

Augustaitis and Bytnerowicz (2008)

Leaf morphology of Fagus sylvatica in Italy, from 7 plots according to a latitudinal gradient Multivariate analysis on Picea abies in permanent plots in the Bavarian Alps. Radial growth, during 9 years, of mature Picea abies trees in Southern Sweden Crown conditions in Fagus sylvatica plots across SW Europe

Annual shoot growth of mature Fagus sylvatica in 83 Swiss plots and Picea abies in 61 plots was evaluated for 11 and 8 consecutive years Correlative study of crown conditions and growth on Pinus sylvestris plots in Lithuania.

studies is subjected to an additional source of uncertainty caused by the inherent uncertainty of the predictor, whose true value remains unknown, adding a further potential error to the regression analysis (Nicolich, 2005). The response indicators are also different: crown condition (e.g. Zierl, 2002; Innes and Boswell, 1991; Innes and Whittaker, 1993; Mu¨ller-Edzards et al., 1997; Klap et al., 2000; Ferretti et al., 2003, 2007a), basal area increment (BAI) (Braun et al., 1999; McLaughlin and Downing, 2002; Ferretti et al., 2003; Muzika et al., 2004; Karlsson et al., 2006), tree-ring increments (Peterson et al., 1991; Bartholomay et al., 1997; Dittmar et al., 2003), leaf morphology (Bussotti et al., 2005b) and ramification structure (Stribley and Ashmore, 2002; Braun et al., 2007). Starting in 2001, visible leaf injuries were introduced as a response parameter within the panEuropean forest monitoring programme, based on similar programmes in North America (Flagler, 1998; Smith et al., 2003; Coulston et al., 2003), and on European studies confirming the

Radial growth inversely correlates with ozone exposure. Significant growth reduction (30%) over 10 years was found for Liriodendron tulipifera. In Prunus serotina the growth reduction (8%) was not significant. There was a negative relationship between ozone dose and diameter increment. That reduction exceeded the reduction found in experiments with beech seedlings. Foliar injuries (chlorotic mottles) were related to ozone levels and crown defoliation. Correlation between ozone concentration and mean defoliation was found for beech, but not for holm oak. Correlations between ozone uptake and increased defoliation were found. Drought reduced the response to high ozone concentrations. Reduction of growth in mature woodland trees was associated with ozone exposure, and drought stress. Ozone reduced stem growth rate, interacting with soil moisture and high air temperature. Increased growth trend is obvious from 1950 at lower altitude sites, but from the late 1970 there is a reduction of growth at the higher altitude sites. Interactions between ozone and drought were hypothesized. Results varied according to the response parameter and the species. The CT residuals correlate negatively with AOT40 in Fagus sylvatica; BAI residual correlated negatively with ozone concentrations in Picea abies and oaks. Symptomatic trees had 28% lower stem growth than asymptomatic trees. The maximum O3 value reported at the sites was negatively correlated with overall growth. Leaf thickness and related sclerophylly parameters were enhanced from site factors and ozone. Transparency increased in shallow calcareous soils, by elevated stand age and, to a smaller degree, by an interaction between ozone exposure and drought. Ozone was a significant (negative) factor to predict the tree growth, after stand basal area, temperature sum and soil moisture index. Ozone exposure (AOT40) was a significant predictor for crown transparency, but the role of ozone was lower than other environmental factors. In beech (but not in spruce) a significant association between growth and ozone was found which corresponded to a 7.4% growth reduction. No interaction was found between ozone and drought. Peak concentrations of ambient O3 can have a negative impact on pine tree crown defoliation and stem growth reduction under field conditions

presence of this phenomenon (Skelly et al., 1999; Innes et al., 2001; VanderHeyden et al., 2001). The Italian national forest monitoring programme (CONECOFOR) was set up in 1995. Although the programme was not designed to specifically address the ozone issue, the importance of ozone as a stressor of concern was acknowledged from its early stages, and ozone concentration has been measured by passive sampling since 1996. Assessment of crown condition (since 1996), visible foliar injury (since 2001) and measurement of basal area (in 1996; 1999; 2005) were carried out in the same plots and this provides the basis for evaluating whether recorded high exposure levels led to consistent responses by the trees. This paper will summarize the results obtained by four response studies carried out on the CONECOFOR plots over the period 1996– 2005 and reported in detail elsewhere (Ferretti et al., 2003, 2007a; Bussotti et al., 2006a). In particular, we will (i) report the main findings relating to ozone effects on vegetation at selected plots;

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Table 2 The original (installed in 1996) twenty sites of the CONECOFOR programme: main tree species, management, structure, age and tree density, at the moment of their establishment. Plot code

Main tree species (MTS)

Management system

Structural type

Stand age (years)

Tree density (n, ha1)

FRI2 LOM1 TRE1 VAL1 ABR1 CAL1 CAM1 PUG1 VEN1 EMI2 PIE1 BAS1 SIC1 UMB1 LAZ1 MAR1 EMI1 FRI1 SAR1 TOS1

Picea abies Picea abies Picea abies Picea abies Fagus sylvatica Fagus sylvatica Fagus sylvatica Fagus sylvatica Fagus sylvatica Fagus sylvatica Fagus sylvatica Quercus cerris Quercus cerris Quercus cerris Quercus cerris Quercus cerris Quercus spp. Mixed broadleaves Quercus ilex Quercus ilex

high forest high forest high forest high forest high forest high forest high forest high forest high forest stored coppice trans. crop trans. crop trans. crop trans. crop stored coppice stored coppice stored coppice trans. crop stored coppice stored coppice

one-storied stratified one-storied irregular one-storied one-storied one-storied one-storied one-storied two-storied one-storied two-storied one-storied one-storied one-storied one-storied one-storied one-storied one-storied two-storied

90–110 80 180–200 140 110 100–120 100 75 115–130 45 55–70 60 50 75 35 35 45 45 50 50

532 1043 393 745 899 333 228 940 345 4540 1213 917 855 739 1629 4233 2057 1126 1710 2404

(ii) identify uncertainties and weaknesses; and (iii) suggest possible improvements. 2. Effect-related activity within CONECOFOR The CONECOFOR programme was established in 1995 under the auspices of the UN/ECE CLRTAP and following EU regulations (3528/86; 2158/92 until 2152/2003 – Forest Focus). The programme now includes 31 permanent monitoring plots (PMPs), which have evolved out of the original 20 installed in 1995. Several investigations are carried out at the PMPs and internationally agreed Standard Operating Procedures and Quality Assurance are observed (www.icp-forest.org). Table 2 gives an overview of the 20 sites initially installed. These sites, where we have the most complete data set, were considered for analysis.

consistent and comparable since 1996 (Bussotti et al., 2005–2006). ‘‘Transparency’’ is assumed as proxy for defoliation and is assessed with reference to photographs (namely: Mu¨ller and Stierlin, 1990 for mountain species; Ferretti, 1994 for Mediterranean species) where reference standards are given for each species. Photographic reference allows a better temporal analysis than the so-called ‘‘reference tree’’ method (see Redfern and Boswell, 2004). Transparency is evaluated according to a proportional scale with 5% intervals (0 ¼ not transparent tree; 5; 10; 15.100 ¼ dead tree). Transparency, or defoliation, is also the most used index to compare tree conditions across countries and time (Mu¨ller-Edzards et al., 1997), but differences in the methods applied by different countries may represent a source of bias. Quality Assurance (QA) procedures

2.1. Ozone monitoring Since 1996 all plots are equipped with passive samplers (Buffoni and Tita, 2003; Mangoni and Buffoni, 2005–2006), providing weekly measurements from June to September (1996–2000) and from April to September (starting in 2001). Details are provided by Buffoni and Tita (2000, 2003) and Mangoni and Buffoni (2005– 2006). On the basis of passive sampling, AOT40 (ozone accumulated over threshold 40 ppb) for the period April–September was estimated for each plot and year (Gerosa et al., 2003, 2007). As an example, Fig. 1 shows the mean AOT40 over the period 2000–2003 recorded at 41 background automatic stations of the national air quality network and at 26 CONECOFOR plots. AOT40 for forests reached 50 ppmh at individual sites (3) and 30 ppmh at 47% of the sites. The critical level (CLec) of 5 ppmh for forests set by UN/ECE (2004) was exceeded almost everywhere. 2.2. Response indicators 2.2.1. Tree crown condition Tree conditions are visually assessed annually by trained surveyors who have gone through intensive training and field checks. Surveyors follow Standard Operating Procedures (SOPs) (Bussotti et al., 2002). Assessment started in 1996 on 19 plots and now covers all the 31 plots of the programme. For each plot, a total of 30 trees are considered and a number of tree condition indicators are assessed. However, only crown transparency data have been

Fig. 1. Mean April–September AOT40 at Italian sites over the period 2000–2004. The PMPs of the CONECOFOR programme are the dots; triangles indicate automatic monitoring stations. Data are in ppbh (after Ferretti et al., 2007b, modified).

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include annual training courses and field checks (Ferretti et al., 1999). Measurement Quality Objectives (MQOs) are usually reached in most plots (Bussotti et al., 2005–2006). 2.2.2. Basal area increment The diameter at breast height (dbh) of all trees alive (threshold 3–5 cm in coppice and high forests, respectively) was measured at the CONECOFOR plots in the winters of 1996–1997, 1999–2000 and 2004–2005 (Fabbio and Amorini, 2002; Fabbio et al., 2006, 2005– 2006). These data were used to calculate mean annual basal area increment. Tree species were determined and social rank was estimated for each tree according to three classes: dominant, intermediate, and dominated layers (in even-aged forests) or upper, intermediate, and lower layers (in uneven-aged forests). 2.2.3. Visible injuries Visible injuries have been monitored since 2001 on a selection of Level II plots (Table 3), according to ICP-Forests’ protocols (Working Group on Air Quality, 2004) and several pictorial atlases (Innes et al., 2001; Sanz et al., 2001; Schaub et al., 2002). Since ICPForests’ protocols were modified in 2003, we will concentrate on the more complete set of data relating to the years from 2003 to 2007. The protocol currently in use calls for sampling vegetation (herbs, shrubs and trees) of a forest edge: the overall area being sampled is subdivided into miniplots, 2  1 m each and distributed randomly along the edge. Within each miniplot, a record is made of all species present and all symptomatic species: thus, findings can be presented either as a percentage of symptomatic miniplots or as a percentage of symptomatic species within the overall number of species (see Bussotti et al., 2003a, 2006a). In all, 9 PMPs were monitored, although at differing frequencies (LOM3 was monitored every year, while some other plots were monitored only once). Priority was given to those plots where beech (Fagus sylvatica) was the main tree species (MTS), since beechwoods are considered sites containing many sensitive species and also because beechwoods are distributed from Northern to Southern Italy. The same surveyor, trained within the annual ICP-Forests Training Courses (Bussotti et al., 2003b, 2006b), assessed all the plots. Symptoms were always assessed in the last week of August. QA procedures include the confirmation of species (in case of doubtful identification) and a comparison of symptoms with those available on the various pictorial atlases and on the web (e.g. http://www.gva.es/ceam/ICPforests/). Visible injuries may be associated with specific anatomical markers (cf. Vollenweider et al., 2003a; Vollenweider and Gu¨nthard-Goerg, 2006; Gu¨nthard-Goerg and Vollenweider, 2007). The most reliable markers are HR – Hypersensitive Response – with collapsed palisade tissue cells and thickening of cellular walls. In order to verify the presence of these markers, microscopy investigations were carried out on trees from the LOM3 plot (Vollenweider et al., 2004; Bussotti et al., 2005a; Bussotti, 2006). These

included both woody species (Acer pseudoplatanus, Fraxinus excelsior, Laburnum alpinum, F. sylvatica, Viburnum lantana) and herbs (Centaurea nigrescens, Astrantia major, Mycelis muralis) (Bussotti et al., 2005a; Bussotti, 2006). 2.3. Assumptions and limitations As explained in previous papers (e.g. Ferretti et al., 2003, 2007a), several attributes concerning crown condition and growth are averaged at plot level and used as predictor and/or response indicators. This approach requires a number of assumptions (Ferretti and Chiarucci, 2003). A first assumption concerns the ability of the available data to provide reliable, unbiased estimates of population parameters (e.g. mean values and totals) at plot level. Another important assumption concerns the consistency of data through time. Although a huge effort has been made to ensure maximum consistency within the investigations carried out in the CONECOFOR programme, those surveys involving visual assessment (crown condition, ground vegetation assessment, visible injury) are always subjected to bias. To carry out the various analyses, we assumed that data were comparable through space and time, but we invite readers to be careful when considering this aspect. Another important aspect that can influence the analysis is the number of plots and the number of years per plot that can be used for the analysis. Up to now, the length of the data series prevented multivariate analysis by plot; the only approach possible was to use data across different plots. 3. Is there evidence of effects? From 2003 to 2007 four ozone response studies were carried out within the CONECOFOR programme in Italy (see Ferretti et al., 2003, 2007a; Bussotti et al., 2003a). The studies differ as to response indicator used (crown transparency, BAI, visible injury), time frame (1996–2000; 2000–2002; 2003–2004) and geographical coverage (beech and spruce plots scattered throughout Italy; beech plots along an ozone gradient; a small number of plots selected according to ozone exposure). 3.1. Response study 1: tree crown transparency of beech and Norway spruce In a first study Ferretti et al. (2003) used plot median annual crown transparency (CT) recorded in 1996, 1997, 1998, 1999 and 2000 as response indicators for ozone effects on beech and Norway spruce. The null hypothesis tested was that deviations from expected CT were not related to O3 exposure. Three steps were undertaken. First, expected CT was modelled by multiple regression after Principal Component Analysis. For beech, a model with elevation, stem density, topsoil C/N ratio, foliar concentration of Ca and summer precipitation was used to predict expected CT

Table 3 Features of the CONECOFOR plots where the survey on visible ozone symptoms was conducted, and main results.

Coordinates X Coordinates Y Altitude (m asl) Ozone (April–September 2000–2002), AOT40 ppbh Main tree species Nr surveys (2003–2007) Symptomatic plots (%) Nr species (total) Nr symptomatic species (total) Symptomatic species (%)

ABR1

CAM1

EMI2

LIG1

LOM2

LOM3

PIE1

TOS1

VEN1

þ41500 5100 þ13 350 2300 1500 48,628

þ40 250 5200 þ15 260 1000 1175 43,830

þ44 060 3100 þ11070 0000 975 13,476

þ44 2401000 þ09 270 3000 1250 18,213

þ45 570 2600 þ10 070 5300 1150 26,698

þ45 540 4100 þ09 300 1700 1400 53,252

þ45 400 5500 þ08 040 0200 1150 23,068

þ43 300 3400 þ10 260 1900 150 17,248

þ46 030 2600 þ12 0105600 1100 9021

Beech 1 33.3 21 5

Beech 1 44.4 14 2

Beech 1 2.0 14 1

Beech 2 5.5 11 1

Spruce 3 53.3 28 12

Beech 5 81.0 44 24

Beech 3 6.5 15 5

Holm oak 2 17.2 19 6

Beech 2 3.0 24 2

23.8

14.2

7.1

4.1

25.0

25.5

5.5

19.2

4.1

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(R2 ¼ 0.57; P ¼ 0.0007). For spruce, the model included stand density, topsoil C/N ratio, foliar concentration of Ca and P (R2 ¼ 0.66; P ¼ 0.002) (Tables 4 and 5). As was to be expected, results confirm that stand, soil and nutrition explain a large portion of CT variability in beech and spruce. Residuals (measured  predicted) were calculated for each plot where the selected predictors were available. To avoid misinterpretation, all plots for which damage to tree crowns due to recognized biotic/abiotic factors (insects, fungi, hail, drought) was reported, as well as potential surveyor bias (Bussotti et al., 2002), were excluded from the analysis. Residuals were regressed against AOT40 up to the date of crown assessment. A significant relationship was detected for beech (R2 ¼ 0.54; P < 0.039), but not for Norway spruce (R2 ¼ 0.016; P > 0.05).

related factors, including meteorology and air pollutants) (Ferretti, 2004). Thus CT residuals (predicted  measured) can be used to test relationships with the above listed actors. In our case, CT residuals showed a consistent – although not significant – trend, with decreasing residual values at increasing AOT40 (Fig. 2). However, transparency residuals were always within 5%, which is the detection limit of the transparency/defoliation assessment (Percy and Ferretti, 2004), and a marked effect was obvious only for very high O3 exposures (AOT40 > 35,000 ppbh). If data in Fig. 2 are analysed by individual years, then AOT40 becomes a significant predictor of CT in 2001 (n ¼ 8; R2 ¼ 0.84, P ¼ 0.012), but not in 2000 and 2002. It is worth noting that 2001 was the year with the highest AOT40 over the period examined (Gerosa et al., 2007) and that 2002 was the year with a particularly cool summer throughout Italy.

3.2. Response study 2: tree crown transparency (CT) of beech along an ozone gradient

3.3. Response study 3: plot basal area increment (BAI) of beech, spruce and oaks

A second study (Ferretti et al., 2007a) considered only plots with beech as main tree species, located along a gradient that also included some Swiss and one Spanish site, in 2000, 2001, and 2002. These years were characterized by fairly different ozone levels in Europe and Italy (see Gerosa et al., 2007). For this study, two different approaches were adopted. First, different multiple regression techniques were used to test the dependence of plot CT on different independent variables, including ozone. Secondly, we used a conceptual model based on the temporal autocorrelation of defoliation data to evaluate the possible role of O3 in determining deviations from expected CT. Four regression models (R2 ¼ 0.71– 0.86; P < 0.001) (Tables 4 and 5) identified a number of significant predictors of defoliation. They include: site characteristics (aspect, stand density), soil chemical properties (content of C, N and pH of the organic soil), foliar nutrients (P, K and Mg) and ozone exposure (AOT40). Foliar content of P and AOT40 were significant predictors and at similar significance levels according to all the models (Ferretti et al., 2007a) As far as the autocorrelative model is concerned (Tables 4 and 5), we re-calculated the data only for Italian plots. CT at a given year t was predicted on the basis of the CT at the previous year t  1 and compared to the CT actually measured on year t. The assumption is that – in the short-term – changes in CT are determined by factors that may fluctuate considerably in the short-term (e.g. pests and diseases, fire, hail, wind, management operations, atmosphere-

The possible role of ozone in explaining deviation from expected BAI in beech, spruce and oaks was investigated by Ferretti et al. (2003). Stand density, mean summer precipitation, median CT, foliar N/Ca and N/K were able to predict standardized BAI and explained a large portion of the variance (R2 ¼ 0.74; P ¼ 0.017) (Tables 4 and 5). Residuals (measured  predicted) were calculated for each plot where the selected predictors were available and plotted against mean AOT40 values over the period 1997–1999. Overall, residuals were not related to AOT40. Within the different species, significant relationships were found only for the oak plots (n ¼ 4; R2 ¼ 0.99, P < 0.05), but not for spruce and beech. 3.4. Response study 4: visible injury Over the period 2003–2007, a total of 45 plant taxa (species or genuses) were found to be symptomatic; of these, 23 (about 50%) are not listed as ozone-sensitive either in current literature or in the lists of sensitive species (Working Group on Air Quality, 2004). Among the ozone-sensitive species, most displayed aspecific symptoms (reddening, discoloration). Many of the species monitored were herbs and, at the time of symptom assessment (late summer), had already produced fruits and were thus in an advanced state of senescence. The first element highlighted by Tables 3 and 6 is that most plots and symptomatic species were found in alpine and pre-alpine sites in Northern Italy (LOM2 and

Table 4 Summary of the investigation about ozone effects on crown transparency and basal area increment at selected CONECOFOR plots. A: modelling of the response indicator. The table reports the statistical method used to model the response indicator, the predictors used in the model, the proportion of variance explained by the model in relation to measured data, and the significance of the model. See text for details. Study

Species

Response

Modelling of response n plots

Statistical method to model response

Predictors in the model

Variance explained

elevation, stand density, topsoil C/N, foliar Ca, summer precipitation stand density, topsoil C/N ratio, foliar Ca and P

57.0

0.0007

66.0

0.0020

71.2 86.8

<0.0001 <0.0001

86.5

<0.001

85.3

<0.0001

55.0

<0.001

74.0

0.017

1

Beech

crown transparency

30

Multiple regression after PCA

1

Spruce

crown transparency

20

Multiple regression after PCA

2

Beech

crown transparency

24

Stepwise ordinary least square regression FW Stepwise ordinary least square regression BW Partial least square regression

3

Beech, spruce, deciduous oaks

standardized basal area increment

40

Genetic algorithm ordinary least square regression Linear first order regression

20

Multiple regression after PCA

Foliar P, AOT40 Foliar P, AOT40, organic soil C and pH, aspect Foliar P, K, Mg, AOT40, organic soil C and N, stand density, aspect Foliar P, K, AOT40, organic soil N, aspect Previous year crown transparency (autocorrelative model) Stand density, summer precipitation, crown transparency, foliar N/Ca and N/K

Significance of model

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Table 5 Summary of the investigation about ozone effects on crown transparency and basal area increment at selected CONECOFOR plots. Assessment of the role of ozone. The table reports the AOT40 range of exposure, the statistical method used to assess the effect of ozone and the significance of AOT40 in predicting the response indicators. Study

Species

Response

n plots

1 1

Beech Spruce

crown transparency crown transparency

8 14

2

Beech

crown transparency

24 24 24 24 21 7 3 4

3

Beech Spruce Deciduous oaks a b c

standardized basal area increment

AOT40 range (ppbh)

Statistical method to assess ozone effects

Significance of AOT40

Regression of model Residuals vs. AOT40 Regression of model residuals vs. AOT40

0.039 ns

3703–52,031

response already in model response already in model response already in model response already in model Regression of model residuals vs. AOT40

0.008 0.008 7.2b 0.008 0.075

4009–22,681c 5290–12,682c 17,072–29,256c

Regression of model Residuals vs. AOT40 Regression of model Residuals vs. AOT40 Regression of model residuals vs. AOT40

ns ns 0.05

405–4453a 861–10,794a

June-assessment date. Variance explained. Mean 1996–1999 June–September.

LOM3). In the other plots the presence of ozone-like symptoms appears to be determined by the behaviour of a small number – or even just one – species. In LOM3 (and, to a lesser extent, in LOM2) there is a higher percentage of miniplots and symptomatic species; the difference with other plots appears even greater if symptomatic species are considered in absolute numbers. However, it is worth noting that number and – to a lesser extent – percentage of symptomatic species appear significantly related to the species richness of the sites: the more species present, the greater the frequency of symptomatic ones (Fig. 3). Since percentage of symptomatic species was less influenced by inherent site species richness, we use these data as a possible response indicator of ozone impact for those plots for which AOT40 estimates exist (Fig. 4). Ozone exposure was not a significant predictor of frequency of species with visible injury (P ¼ 0.15). Even when considering inter-annual changes (2003–2004) it is difficult to observe any common pattern: while a marked decrease in AOT40 resulted in a decrease of the frequency in symptomatic species at PIE1 and VEN1, slighter changes in AOT40 at LOM3 and TOS1 resulted in negligible changes in the symptoms’ frequency. Fairly high percentages of symptomatic plots and species were also found in ABR1, CAM1 and TOS1. But in these sites the result appears to be influenced by a lower number of symptomatic

CT residuals (Exp-Meas), %

5 4

2000

n=21 y = -6E-05x + 0.8815

3

2001

R2 = 0.16; P=0.075

2002

2 1 0 -1 -2 -3 -4 -5

0

10000

20000

30000

40000

50000

60000

AOT40, ppbh Fig. 2. Residuals (expected  measured) crown transparency (CT) regressed against AOT40 from 1st April to the date of assessment of CT assessment. Data from beech PMPs over the period 2000–2002. See text for details.

species, in conditions of reduced biodiversity. Further, these are for the most part species displaying aspecific symptoms (reddening) and/or not previously reported as being ozonesensitive. But TOS1, the only holm oakwood considered, yielded different results. Here no symptoms were observed on the typical Mediterranean species, which are well-known to be non-sensitive (Bussotti and Gerosa, 2002; Paoletti, 2006); symptoms were found prevalently in exotic species, which become invasive in disturbed sites. 4. Discussion In many of the correlative studies on mature forests, the variability in the response indicators considered (crown condition and growth) was effectively explained by ecological and cultivation conditions, soil condition, and by water shortage (De Vries et al., 2003; Zierl, 2002, 2004; Seidling, 2007; Ewald, 2005). Similarly, Karlsson et al. (2006) found that the strongest explanatory variable for stem basal area increment (BAI) was the stand basal area, which was specific for each plot and each year, followed by the temperature sum and the soil moisture index. The role of ozone expressed as AOT40, even though significant, came after these four variables. Cleaning up the data by excluding the noise of site features, Augustaitis and Bytnerowicz (2008) found inverse relations between ozone and response indicators (increased concentrations and/or ozone peaks leading to reductions of BAI and transparency/ defoliation) in Pinus sylvestris in Lithuania. Correlations between predictive variables (site features, environmental parameters) and crown condition (defoliation and discoloration) were investigated at European level by multivariate statistical analysis and multiple correlations; and the possible influence of ozone on European forests as a whole was reported by Klap et al. (2000). The main findings concern Quercus ilex and F. sylvatica (significant correlation between AOT60 and defoliation). In Q. ilex the correlation was only slightly significant, while in F. sylvatica it was more marked. Nevertheless, analyses which involve data coming from the all over Europe may be biased by the different methods used to assess defoliation/transparency in different countries, as well as by surveyor errors that may affect the results (Ferretti et al., 2003; Dobbertin, 2005; Bussotti et al., 2005–2006). Often, the lack of environmental data (weather, soil condition, ozone concentrations in atmosphere) actually measured in sites and over study periods may seriously jeopardize the reliability of findings. Muzika et al. (2004), for example, base their interpretation of BAI evolution of a multi-year historical series on ozone concentration data relating only to the previous two years.

F. Bussotti, M. Ferretti / Environmental Pollution 157 (2009) 1427–1437

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Table 6 Symptomatic species recorded within the field surveys carried out in the period 2003–2007 in Italy, in the 11 assessed areas (indicated with ). The column EU indicates if the species is present in the European list of sensitive species (Working Group on Air Quality, 2004). The visible manifestation is described under the column ‘‘Symptom’’. Species

Permanent monitoring plot ABR1

Acer pseudoplatanus Ailanthus altissima Alchemilla sp. Astrantia major Centaurea Clematis vitalba Corylus avellana Euphorbia dulcis Euphrasia kerneri Fagus sylvatica Fragaria vesca Fraxinus excelsior Gentiana asclepiadea Geranium spp. Globularia nudicaulis Helleborus niger Hieracium sp. Horminum pyrenaicum Knautia spp. Laburnum alpinum Lactuca serriola Lotus corniculatus Pastinaca sativa Pimpinella major Plantago spp. Polygala chamaebuxus Polygonatum sp. Polygonum sp. pl. Potentilla erecta Primula vulgaris Ranunculus spp. Robinia pseudoacacia Rosa canina Rubia peregrina Rubus sp. Salvia pratense Sanguisorba minor Stachys spp. Taraxacum officinalis Trifolium pratense Vaccinium myrtyllus Veronica spp. Viburnum lantana Vitis vinifera

CAM1

EMI2

LIG1

LOM2

LOM3

PIE1

TOS1

VEN1

 



  

 

 

       

 





   



 



  



   



 

   





  



     

 

 

 

   

  

 



 

   

Symptom

References

Interveinal reddish stippling Interveinal whitish-brown stipples Brown-reddish patches Brown-reddish stippling Interveinal reddening Interveinal reddening Bronzing on the upper leaf surface Reddening Brown-reddish stippling Bronzing of the upper surface Interveinal reddening Interveinal brown stippling Bronzing of the upper surface Brown-reddish stippling Brown-reddish stippling Bronzing of the upper surface Brown-reddish patches Interveinal reddening and bronzing Brown-reddish stippling Brown stippling Reddening Brown-reddish stippling Reddening Reddening Brown-reddish stippling Brown-reddish stippling Brown-reddish stippling Brown-reddish patches Brown-reddish stippling Brown patches Brown-reddish stippling Interveinal brown stippling Interveinal reddening and bronzing Interveinal reddening Reddening on the upper surface Interveinal reddening and yellowing Interveinal reddening Yellowing Interveinal reddening Brown-reddish stippling Interveinal reddening and bronzing Brown-reddish stippling Interveinal red stippling Reddening

VAN, INN, SKE, SAN, BUS INN, SKE, SAN, GRA, BUS SKE, MAN1 MAN1, MAN2 MAN1, MAN2, BAS SAN INN, SKE, SAN

EU

 

INN, SKE, SAN, VAN, BUS INN, SKE, SAN, VAN, NOV, BUS INN, SAN, MAN1

SAN, BUS2

INN

INN, SKE INN, SKE, SAN

INN, SKE, MAN1, MAN2

INN, VAN, NOV, BUS INN, SAN

The column ‘‘Reference’’ indicates the authors that have described the specific ozone symptom: BUS ¼ Bussotti et al. (2005a); BUS2 ¼ Bussotti (2006); GRA ¼ Gravano et al. (2003); INN ¼ Innes et al. (2001); MAN1 ¼ Manning et al. (2002); MAN2 ¼ Manning and Godzik (2004); NOV ¼ Novak et al. (2003); SAN ¼ Sanz et al. (2001); SKE ¼ Skelly et al. (1999); VAN ¼ VanderHeyden et al. (2001); VOL ¼ Vollenweider et al. (2003a); WG ¼ Working Group on Air Quality (2004).

The availability and reliability of meteorological and soil condition data, alongside atmospheric ozone concentrations, is in any case essential in order to shift from an exposure-based approach to a flux-based approach, albeit through modelling (Schaub et al., 2007). The differences between exposure to ozone and its actual uptake by trees may alter the results. Zierl (2002), for example, applied to Swiss forests a hydrological model that simulates stomatal conductance – and therefore ozone absorption – suggesting that ozone uptake, rather than exposure, is a better predictor of defoliation. In our studies the role of ozone exposure on crown transparency was uncertain, and – when significant – its contribution to the variance was limited (<10%). Only in one case (response study 1, CT of beech 1996–2000), the variance explained was relatively high (55%), but the number of datapoints was limited and some caution is needed in interpreting these results. Within the examined data, O3 seemed to play a ‘‘triggering’’ role, forcing deviations from expected transparency only at very high exposure levels. Another source of noise, beside those already mentioned (errors by observers, use of non-specific response indicators, inadequate

availability of environmental data), was the difference of age, plant genotype and management (see Table 2) among the plots. This noise was unavoidable since we do not yet have sufficient data to carry out analyses of individual plots. A new study is currently being developed at the individual plot scale and using the complete 1996–2005 data series. As far as the basal area increment is concerned, although a significant decrease of BAI was obvious at increasing AOT40 on deciduous oaks, this evidence should be evaluated taking into account the low number of cases (n ¼ 4). Similarly to CT, several factors may have had an influence, primarily the difference between ozone exposure and uptake, as well as the role of other potential factors that may have influenced the growth of beech in the various PMPs, but were not fully considered in the BAI model (e.g. hail episodes, leaf defoliators and leaf miners – Bussotti et al., 2002). Visible ozone symptoms are a very attractive response indicator, since they would appear to give reliable indications on cause–effect relationships. Further, the spread of ozone symptoms in crowns can be directly related to defoliation (Sanz et al., 2000, in Pinus

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60

14

Symptomatic species, %

Symptomatic species, n

16

12 10 8 6 4

y = 0.2548x - 1.8924

2 0

R2 = 0.5714; P<0.0001 0

20

40

60

50 40 30 20 10 0

y = 0.4216x + 4.5878 R2 = 0.19; P=0.029 0

Total species, n

20

40

60

Total species, n

Fig. 3. Frequency of symptomatic species regressed against species richness. Left: number of symptomatic species; right: percentage. Regression data are reported in each diagram.

halepensis in Spain) and to diameter increment reductions (Somers et al., 1998; Vollenweider et al., 2003b). In an open-top chamber experiment in Switzerland, Novak et al. (2007) related growth reduction in an ozone-sensitive poplar clone to reduction of the photosynthesis apparatus, which was a consequence of widespread foliar symptoms. Nevertheless, symptoms are not necessarily related to growth reduction (Novak et al., 2007), because of the onset of processes of compensation within the crown (Temple and Miller, 1994). In many cases, the observed symptoms in field surveys were aspecific and difficult to interpret (Lorenz et al., 2005; Bussotti et al., 2006b). In particular, this was the case of colour changes: reddening (due to anthocyanin accumulation in mesophyll cells as antioxidant substances, or in the upper epidermis as filters against excess sunlight, cf. Neill and Gould, 2003); browning (often caused by degeneration of plasmatic content in palisade mesophyll cells); yellowing (depigmentation attributable to early aging processes). In other cases (especially in the woody species in LOM3), the visible injury that was assumed to be specific (stipples) was confirmed in its specificity by microscopy tests (Bussotti et al., 2005b; Bussotti, 2006). But findings from herbaceous species were contradictory. Only in some cases (C. nigrescens, A. major, M. muralis) were reddening or discoloration accompanied by HR manifestations in the palisade mesophyll. Overall, once all uncertain findings are excluded, definite foliar symptoms are reduced to a few 50 2003

Symptomatic species, %

45

2004

n=7; y = 0.0002x + 1.7385 R2 = 0.307; P=0.154

40 35 30 25

5. Conclusions Despite the high ozone levels in Italian forests, there is only limited evidence of the impact of this pollutant on the mature forest trees at the CONECOFOR plots. Among the response parameters normally used, worsening of crown condition and BAI reduction are markedly aspecific and were demonstrated as being affected by concurrent stress factors, as well as by the intrinsic structural or genetic features of the species in the plot. It is the opinion of the authors that evidence of ozone effects can best be highlighted where no other, predominant, oxidative stress factors are present (Bussotti, 2008), since the latter can reduce, mask or, sometimes, increase the action of ozone, as is the case with the interaction with drought (McLaughlin and Downing, 2002; Lo¨w et al., 2006). From a mechanistic (i.e. cause–effect relation) point of view, increment reduction is logically linked to impaired carbon-reduction efficiency, or to the re-allocation of metabolites from growth functions to defence strategies. The biological significance of crown transparency as a response to ozone stress is, however, less clear. If we correlate transparency (or a delta of transparency, i.e. the difference between current transparency and that of the previous year) with current ozone levels, we might assume that there will be Table 7 In column A are listed the species with their symptomatic manifestation clearly attributable to ozone. In column B are listed some common species sensitive to ozone, but with aspecific symptoms that can be confused with other causes.

20 15 10 5 0

observations in LOM3 (the plot with the highest exposure levels) and a few ruderal species in TOS1. Table 7 shows some of the most common species that can lead to misunderstandings or mistaken assessments. The injuries that can be considered certain are instances of necrotic stipples meeting the requirements described by Innes et al. (2001), i.e. interveinal injuries on the abaxial surface of leaves, prevalently in older leaves, since these symptoms have been reproduced under experimental conditions in these same species (Table 6).

0

40000

80000

120000

AOT40, ppbh Fig. 4. Frequency of symptomatic species (%) regressed against April–September AOT40 (ppbh) at four sites and two years. Arrows indicate changes of the same plot between the two years. Regression data reported within the diagram.

A. Ozone symptoms easy to recognise

B. Ozone symptoms doubtful

Acer pseudoplatanus Fraxinus excelsior Sambucus sp. pl. Laburnum alpinum Populus nigra Ailanthus altissima Fagus sylvatica (only stippling) Robinia pseudoacacia Viburnum lantana (when red stipples come from the bottom)

Rubus sp. pl. (reddening) Cornus sp. pl. (reddening) Corylus avellana (bronzing) Viburnum opulus (reddening) Prunus avium (reddening) Fagus sylvatica (bronzing) Centaurea sp. pl. (reddening) Fraxinus ornus (bronzing)

F. Bussotti, M. Ferretti / Environmental Pollution 157 (2009) 1427–1437

a progressive crown density reduction (a loss of leaves) over the course of the season, as a consequence of exposure to and/or cumulative dose of ozone, since ozone action at the time of spring leaf-formation is to be considered nil. On the other hand, it may be that the effect of persistent exposure (over several years) leads to the progressive loss of crown vitality as a consequence of reduced photosynthesis efficiency and/or a greater consumption of reserves. In this case we would expect the transparency to be the result of shorter sprouts (Braun et al., 1999) and smaller sized leaves from the beginning of leaf sprouting. Ideally, visible ozone injuries should be a highly specific indicator, but a variety of elements make them problematic for practical applications. These elements include: ecological differences between different sites, genetic differences between individuals of the same species (Paludan-Mu¨ller et al., 1999; Bassin et al., 2004) and differences in the sensitivity of individual trees (Farage, 1996; Cascio et al., 2007). We could increase our ability to isolate the effect of ozone if we selected, within the same ozone concentration gradient, plots that displayed similar ecological conditions. The presence, within these plots, of species displaying ascertained and unequivocable symptoms may provide us with reasonably certain information on the direct action of ozone. And even the presence of a high number of species displaying symptoms of a doubtful and controversial nature may always be considered an indication of oxidative pressure. Although our results may question the suitability of the current monitoring programme to detect the effect of ozone on forests, three questions deserve consideration. First, effects are obviously far fewer than expected, given the current ozone levels in Italy. Secondly, the CONECOFOR programme was not specifically designed to detect ozone effects, and differences between plots cause considerable noise in the analysis. Thirdly, our data series is now long enough that an analysis based on individual plots should be possible. Ten years of concurrent ozone, meteo, nutrition and effects monitoring on the same site will provide a great deal of conclusive information. In particular, this latter point highlights the importance of long-term observations, that are essential to understand the response of forests to environmental changes. Acknowledgement This paper was prepared within the contract between the Ministry for Agriculture and Forestry Policy – National Forest Service (co-ordinator of the CONECOFOR Programme, National Focal Centre – Italy) and the Department of Plant Biology, University of Florence, Italy. References Augustaitis, A., Bytnerowicz, A., 2008. Contribution to ambient zone to Scots pine defoliation and reduced growth in the Central European forests: a Lithuanian case study. Environmental Pollution 155, 436–445. Bartholomay, G.Y., Eckert, R.T., Smith, K.T., 1997. Reduction in tree-ring widths of white pine following ozone exposure at Acadia National Park, Maine, USA. Canadian Journal of Forest Research 27, 361–368. Bassin, S., Ko¨lliker, R., Cretton, C., Bertossa, M., Widmer, F., Bungener, P., Fuhrer, J., 2004. Intra-specific variability of ozone sensitivity in Centaurea jacea L., a potential bioindicator for elevated ozone concentrations. Environmental Pollution 131, 1–12. Braun, S., Rihm, B., Schindler, C., Flu¨ckiger, W., 1999. Growth of mature beech in relation to ozone and nitrogen deposition: an epidemiological approach. Water, Air and Soil Pollution 116, 357–364. Braun, S., Schindler, C., Rihm, B., Flu¨ckiger, W., 2007. Shoot growth of mature Fagus sylvatica and Picea abies in relation to ozone. Environmental Pollution 146, 624– 628. Buffoni, A., Tita, M., 2000. Ozone measurements by passive samplers at Italian forest sites. Annali dell’Istituto Sperimentale per la Selvicoltura 30 (Suppl. 1), 121–127. Buffoni, A., Tita, M., 2003. Ozone measurements by passive sampling at the permanent plots of the CONECOFOR programme. Annali dell’Istituto Sperimentale per la Selvicoltura 30 (Suppl. 1), 29–40.

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