Chapter 11
Assessment of Visible Foliar Injury Induced by Ozone Marcus Schaub*,1 and Vicent Calatayud{ *
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland { Fundacio´n Centro de Estudios Ambientales del Mediterra´neo (CEAM), Parque Tecnolo´gico, Paterna, Spain 1 Corresponding author: e-mail:
[email protected]
Chapter Outline 11.1. Introduction 205 11.2. Objectives 207 11.3. Methods 207 11.3.1. Location of Measurements and Sampling 207 11.3.2. Equipment 209 11.3.3. Time of Observations and Sampling 209 11.3.4. Variables and Symptom Identification 209
11.3.5. Evaluation and Scoring 11.3.6. Symptom Documentation 11.4. Quality Assurance and Quality Control 11.5. Data Processing 11.6. Results Acknowledgments References
214 215 215 216 216 220 220
11.1 INTRODUCTION First observations of negative impacts of ground-level ozone (O3) on trees were made in North America, mainly around the metropolitan area of Los Angeles, California, on the coniferous species Pinus ponderosa Dougl. by Miller et al. (1963). Over the past several decades since these initial observations, O3 effects on forests have been the focus of numerous studies across North America and Europe (Krupa and Manning, 1988). As a result, the effects of tropospheric O3 have been well characterized for a variety of forest Developments in Environmental Science, Vol. 12. http://dx.doi.org/10.1016/B978-0-08-098222-9.00011-X © 2013 Elsevier Ltd. All rights reserved.
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species grown under a wide range of experimental and natural conditions (Matyssek and Sandermann, 2003). Sensitivity to O3 is species specific and depends upon several physiological, morphological, and biochemical plant characteristics as well as upon the environmental factors surrounding the plant. For the physiological aspect, differences in O3 sensitivity among species have been related to inherent differences in stomatal conductance, which is a key factor in determining O3 uptake into the leaf (Reich, 1987). In addition to O3 uptake, detoxification and defense capacities are believed to play an important role in determining the sensitivity of different species to O3 stress (Matyssek et al., 2007). The above indicated plant-specific characteristics are interrelated, vary over the course of the growing season, and are ultimately driven by environmental factors, such as soil water content, air temperature, vapor pressure deficit, wind speed, and light conditions (Emberson et al., 2000). However, although many of the underlying mechanisms of O3 sensitivity are fairly well understood, there is still considerable discussion as to how to apply the concept of O3 sensitivity to natural communities to develop representative regional and large-scale risk assessments across Europe (Karlsson et al., 2007; Matyssek et al., 2007). Many experiments have concentrated on explaining the mechanisms leading to O3 injury rather than to identify and characterize the symptoms observed in the field on a regional scale. The evidence we have today strongly suggests that O3 occurs at concentrations that cause visible foliar injury to a wide range of sensitive plants (Innes et al., 2001). Field surveys conducted from 1995 through 1998 in areas of southern Switzerland and Spain resulted in a list of approximately 80 herbaceous and woody species native to Switzerland and of 42 species native to southern Spain showing typical O3-induced foliar symptoms (Skelly et al., 1999). Between two experimental studies from VanderHeyden et al. (2001) and Novak et al. (2003), 22 different woody plant species have been confirmed as being sensitive to O3 and visible injury could be reproduced. The extent of visible O3 injury to susceptible species was also investigated on a total of 95 species across 13 nurseries, over four European countries during the 2006 season and O3 injury was observed in all countries demonstrating that the impacts of O3 are not restricted to countries with higher O3 concentrations (Benham et al., 2010). Several studies have also described relationships between the onset and development of O3-induced visible foliar injury and changes in leaf gas exchange (Zhang et al., 2001), chlorophyll fluorescence, and ultrastructural characteristics (Gravano et al., 2004), tree ring and stem growth (Novak et al., 2008), and root biomass (Dı´az-de-Quijano et al., 2012) in order to characterize species-specific differences in terms of O3-induced visible injury. Even though O3 visible injury does not include all the possible forms of injury to trees and natural vegetation, observation of typical symptoms on above ground plant parts in the field—also referred to as passive bio-indication—has turned out to be a valuable tool for the assessment of the impact of ambient O3 exposures on sensitive species in Europe (Bussotti et al., 2003).
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In combination with the monitoring of O3 concentrations (Chapter 19; see also Schaub et al., 2010a), the assessment of O3 visible injury serves to estimate the potential risk for ecosystems that are exposed to elevated ambient O3 concentrations. For example, within the International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests (ICP Forests), assessment of O3 injury to plants helps documenting the presence of environmental drivers that may affect forest condition across Europe (Schaub et al., 2010b). However, due to the complex nature of the diagnosis and the given restrictions of the investment, results from tree and vegetation assessments should be considered as semiquantitative. When monitoring is conceived for the long-term and the large-scale, harmonization of procedures is essential to ensure spatial and temporal data comparability. In the present chapter, methods to collect statistically sound, high quality, harmonized, and comparable data on O3-induced visible injury on forest vegetation at the ICP Forests intensive monitoring plots in Europe are presented.
11.2 OBJECTIVES The main objectives of assessing O3 visible injury on forest monitoring plots are to evaluate the potential for tropospheric O3 effects under real-field conditions, to couple the effects of assessment with O3 concentration monitoring (see Chapter 19), and to contribute to an O3 risk assessment for European forest ecosystems. In particular, the aims are (a) to quantify the occurrence of O3-induced injury at forest monitoring plots and (b) to detect significant temporal changes and trends.
11.3 METHODS 11.3.1 Location of Measurements and Sampling The assessment of O3 visible injury is best conducted within (in-plot) and in the vicinity (off-plot) of the plots where O3 monitoring is carried out (see Chapters 2 and 6). The in-plot assessment is conducted within the monitoring plot and considers leaves of the upper, fully sun-exposed crown of the present main tree species. Within the ICP Forests, such an assessment is customary carried out every second year in parallel with foliar sampling for chemical analysis (see Chapter 12). However, this frequency may be increased depending on the question to be investigated and the monitoring needs. For deciduous species (including broadleaf species and Larix spp.), current year leaves (C) and for evergreen species (including conifers and evergreen broadleaves such as Quercus ilex L.), current year (C) and previous year (C þ 1) leaves are assessed for O3 visible injury. Since most of the plots are situated in closed and therefore shaded forests and visible O3 injury is usually restricted to sunlight-exposed parts of the most
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upper crown, an off-plot assessment at a Light-Exposed Sampling Site (LESS) is also considered. The aim of the assessment within the LESS is to provide estimates for the occurrence of O3 visible injury on native forest vegetation that is growing under the most favorable environmental conditions for O3 effects. The LESS is installed in the vicinity of a meteorological monitoring station in the open field where, among others, also O3 concentrations are recorded (see Chapters 6 and 19). After the most appropriate forest edge is identified, the procedure as described in Figure 11.1 is to be applied. A fully randomized procedure is adopted to select vegetation quadrates within the selected forest edge. The number of quadrates to be randomly B
A
M
M 500 m
500 m
A
A N
C
N
D End End
Start 0
2
4
6
8
n
In gray, randomly selected rectangles to be sampled
Start FIGURE 11.1 Procedure for the establishment of the LESS nearby ICP Forests Level II plots: (1) Identify an area (A) (500 m radius) centered around the off-plot, open-field monitoring station (meteorological tower and/or deposition devices) where passive O3 samplers are installed (M) (A); (2) Identify all the light-exposed forest edges within A (yellow lines in A). (3) From those, choose the forest edge closest to M (red line, B). (4) Determine the start point and measure the length of the selected forest edge and virtually identify a 1-m width area along the forest edge. You now have an x m long and 1 m width transect (C). (5) Calculate how many possible 2 1 m nonoverlapping quadrates fit into the selected forest edge area by dividing the x-m long transect by 2. The 2-m long edge of the rectangular quadrate lies along (parallel) the forest edge. The total number of nonoverlapping quadrates is our target population (C). (6) Select your sampling quadrates randomly (D). (7) At the end, you will obtain a list of n codes. Each code is a 2 1-m quadrate within the LESS; the codes will give you the distance of the beginning of each quadrate from the beginning of the previously determined start of the forest edge (D). Now you are ready to start with the symptom assessment. Source: Schaub et al. (2010b).
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selected within the LESS depends on the length of the total LESS, the expected variance of observations among the quadrates, and the desired precision level of the estimate in terms of confidence interval (e.g., Elzinga et al., 2001). Table 11.1 provides the number of quadrates necessary to achieve an estimate of the mean number of symptomatic species along forest edges of different lengths, allowing a 10% error at a 95% probability level. The table is based on the variability among observations as emerged from intercalibration and training exercises carried out at the early stage of the O3 injury program in Europe. Within the ICP Forests, the LESS survey is carried out on an annual basis, but higher frequency can also be adopted for specific purposes.
11.3.2 Equipment Equipment to assessing O3 visible injury in the field is minimal: a 10 hand lens for closer examination of plant leaves serves for magnification and proper diagnosis of the symptoms. The respective plot maps, compass, and GPS help to determine the exact location (coordinates), exposition, and elevation of the LESS for repeated surveys and site description. Reference pictures are crucial to assist in symptom identification of known sensitive species. More detailed information can be found on the ICP Forests web page of the Expert Panel on Ambient Air Quality at http://icp-forests.net/page/expertpanel-on-ambient-air. A plant press and/or plastic bags, as well as a digital camera are useful to collect samples and to record symptoms for further analyses in the laboratory. Examples of respective field data sheets can be found in Schaub et al. (2010b).
11.3.3 Time of Observations and Sampling In-plot identification and quantification of O3 visible injury for conifers and broadleaves shall be carried out based on the regional phenology of the species represented at the monitoring plots, that is, October until February for evergreen main tree species and July to beginning of September for deciduous main tree species. The identification of O3 visible injury on trees, shrubs, and vines within the LESS (off-plot) are carried out at least once during late summer, preferably between the end of July and the beginning of September, before natural leaf discoloration sets in.
11.3.4 Variables and Symptom Identification For the in-plot assessment, the measured variables consist of symptomatic leaves or needles reported as frequency classes. For the LESS (off-plot), a list of symptomatic and nonsymptomatic species per quadrate is recorded. “Empty” quadrates, such as a gap, skidder trail, rock, etc. where no woody species are growing are also recorded. Table 11.2 provides an overview of
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TABLE 11.1 Sample Sizes (Possible Nonoverlapping Quadrates) at Specified Precision Levels, for Different Lengths of the Selected Forest Edge Length of light-exposed forest edge (m)
Possible 2 1 m nonoverlapping quadrates (n)
Adjusted sample size (FPC adjusted), 10% error (n)
30
15
13
35
18
15
40
20
17
45
23
18
50
25
20
60
30
23
70
35
26
80
40
28
90
45
31
100
50
33
150
75
33
200
100
33
250
125
33
300
150
33
350
175
33
400
200
33
450
225
33
500
250
33
600
300
33
700
350
33
800
400
33
900
450
33
1000
500
33
2000
1000
33
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TABLE 11.2 Reference List of Variables to be Measured/Reported for the Assessment of O3 Visible Injury at Intensive Monitoring Plots Variable
Reporting unit
In-plot survey Soil moisture
Soil moisture classes
Percentage of symptomatic, current year’s leaves, and needles on main tree species
Score per branch
Percentage of symptomatic, last year’s needles (Cþ1) on main tree species
Score per branch
Off-plot survey Number of symptomatic species per selected quadrate (LESS)
Species name and code
Number of nonsymptomatic species per selected quadrate (LESS)
Species name and code
List of symptomatic species outside of selected quadrates (LESS-plus)
Species name and code
In-plot survey: within the plot. Off-plot survey: light-exposed sampling site (at forest edge).
all variables that are measured for the O3 visible injury assessment in the field. Ozone visible injury can be identified and distinguished from symptoms caused by other biotic/abiotic factors by the following criteria (see also Figure 11.2): 1. Visible symptoms are typically expressed as either tiny, purple-red, yellow, or black spots (described as stipple) or as general, even distributed discoloration, reddening, or bronzing. 2. Look for O3 visible injury on fully developed and light-exposed leaves. 3. Symptoms are more severe on mid-aged and older leaves than on younger leaves. Older leaves are the first ones that develop symptoms followed by an accelerated natural senescence (age effect). 4. Shaded portions of two overlapping leaves do not show any visible injury (shade effect; Figure 11.2). 5. Ozone visible injury normally does not go through the leaf-tissue (exception, see point 6). Both, stippling and even discoloration occurs between the veins (interveinal) only and do not affect the veins.
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FIGURE 11.2 Typical ozone visible injury, expressed as even discoloration or bronzing between the veins on a Fagus sylvatica leaf. A shading effect is visible toward the stem of the lower leaf. Photo by M. Schaub.
6. Toward the end of the growing season, foliar symptoms may progress to leaf yellowing or premature senescence, followed by earlier leaf loss. Severely injured leaves may develop necrosis that can also be seen on the lower leaf surface toward the end of the growing season. 7. Plants grown on more humid sites are more likely to develop O3 visible injury compared with plants grown on drier sites (higher O3 uptake). The observed visible injury can be examined as described below, using a hand lens and the flow chart in Figure 11.3: 1. Is there any stippling? 2. Is there any reddening and/or even discoloration? 3. Do the symptoms, as described above, occur on the upper leaf surface only (except during late season when visible injury becomes more severe and necrotic)? 4. Are the symptoms expressed between the veins only and are they absent on the veins and veinlets (use a hand lens and hold leaf against the light)? 5. Are the symptoms evenly distributed? 6. Are the symptoms more developed on the older leaves (including leaflets, “age effect”)? If the above questions are answered affirmatively, the symptom can be considered as visible injury that is induced by O3. Additional and more detailed information on species-specific symptom expression is provided on the ICP Forests web page of the Expert Panel on Ambient Air Quality. Ozone visible injury on conifer species is expressed as chlorotic mottling and develops at the upper side of needles and branches within the upper parts
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Symptom
Interveinal
On veins
Lower leaf surface
Upper leaf surface
Stipple <1 mm
General discolor.
Old L. > young L.
Young L. > old L.
No insects
Old L. > young L.
O3 visible injury
Not O3 induced
O3 visible injury
Insects
Not O3 induced
Stipple <1 mm
General discolor
Old L. > young L.
Young L. > old L.
Not O3 induced
Early season
Late season
O3 visible injury
Young L. > old L.
Not O3 induced
No insects
Old L. > young L.
Young L. > old L.
O3 visible injury
Not O3 induced
Insects
Not O3 induced
Not O3 induced
Not O3 induced
FIGURE 11.3 Flowchart for the diagnosis of ozone visible injury on broad-leaf species. Source: Innes et al. (2001).
of the crown. As a result of chronic exposure to O3, chlorotic mottling is the most common O3-induced symptom described for conifer needles. For identification, the following criteria should be considered: 1. Chlorotic mottling can be described as yellow or light green areas of similar size without sharp borders between green and yellow zones. However, not all needles in a fascicle may be uniformly affected. 2. Chlorotic mottling frequently appears only in needles older than 1 year (second-year needles and older). The observed symptom seems to increase with increasing needle age (age effect). 3. Chlorotic mottling is more distinct on light-exposed needle areas in comparison with shaded ones (shade effect). 4. It is easier to observe the mottling if several needles are held close to each other, forming a “plane” of needles. The observed visible injury on conifers can be examined as described below, using a hand lens: 1. Is chlorotic mottling present in the C þ 1 and more intensively in the C þ n year needles?
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2. Is the color of the mottling yellow or light green? 3. Is the shape of the mottling areas regular with diffuse borders? 4. Is the mottling evenly distributed along the entire needle, and more intense in the abaxial surface or most light-exposed needle side? If the above questions are answered affirmatively, the symptom can be considered as visible injury that is induced by O3. Special attention has to be paid to confounding symptoms such as symptoms caused by spider mites and sucking insects. Using a hand lens helps to easily detect their remnants.
11.3.5 Evaluation and Scoring 11.3.5.1 In-Plot Assessment of Leaf and Needles from Mature Trees In-plot assessment on mature trees should include a minimum of three branches per tree and five trees per plot. The evaluation procedure shall be different for broadleaves and conifers. Once the branches are collected, all leaves per branch are examined under best light conditions and scored for the presence/absence of O3 visible injury. According to the following scoring system, the percentage of symptomatic leaves per branch is estimated: Score Score Score Score
0 ¼ None of the leaves are injured; 1 ¼ 1–5% of the leaves per branch show O3 symptoms; 2 ¼ 6–50% of the leaves per branch show O3 symptoms; 3 ¼ 51–100% of the leaves per branch show O3 symptoms.
For conifer species, the different needle age classes are identified separately. Only C and C þ 1 needles are assessed. Needles should be placed close to each other, forming a “plane” and examined in full sunlight. Chlorotic mottling will be scored for each needle age class in percentage of total surface affected. The resulting percentages per branch and needle age are then transformed to the corresponding score (classes), according to the following scoring system: Score Score Score Score
0 ¼ No injury present; 1 ¼ 1–5% of the surface is affected; 2 ¼ 6–50% of the surface is affected; 3 ¼ 51–100% of the surface is affected.
11.3.5.2 Off-Plot Assessment at the LESS For the off-plot symptom assessment of small trees, shrubs, and vines within the LESS, the procedure as described below should be applied. For each selected quadrate, the scientific name of the species and the indication whether they show symptoms or not should be reported. The assessment is conducted on trees, shrubs, and vines that are present within the LESS.
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The plant nomenclature must refer to internationally established species codes as found in, for example, Flora Europaea. Pictures of each injured species/ leaf should be collected in accordance with Section 11.3.6 (see below). For additional analyses and interpretation of the data, information on soil moisture conditions (wet, fresh, dry) within the LESS may be very useful. To achieve a more complete list of symptomatic species around the O3 monitoring device and in addition to the survey within the LESS, the forest edges within a radius of 500 m of the passive sampler’s location may be qualitatively assessed and symptomatic species recorded.
11.3.6 Symptom Documentation Symptoms should be documented with digital pictures. The pictorial collection is required for the validation of O3 visible injury observed in the field. This collection serves as documentation of the monitoring program. During each annual evaluation period, pictorial samples should be collected of two symptomatic and two nonsymptomatic leaves (preferably small branches) per symptomatic species showing O3 visible injury, visible O3-like symptoms respectively if not confirmed yet. For each symptomatic leaf, pictures of the entire plant, and the upper and the lower leaf surface should be taken. Each picture file may be labeled with the following specific code for proper longterm data management and storage: AA_YYMMDD_BBBB_REF_No.jpg, where AA ¼ country code, YY ¼ year, MM ¼ month, DD ¼ day, BBBB ¼ plot number, REF ¼ reference number, and No ¼ sequence number.
11.4 QUALITY ASSURANCE AND QUALITY CONTROL Several actions and tools are adopted to ensure data quality and are discussed in detail in Chapters 20 and 21. In brief, the basic QA/QC component are training and intercalibration exercises. Field exercises are essential and they can be organized at different levels, for example, local, national, and international (e.g., Bussotti et al., 2003). In addition, on-line tools include pictorial atlases provided by, for example, the ICP Forests Expert Panel on Ambient Air Quality (see http://icp-forests.net/page/expert-panel-on-ambient-air). The pictures contain species-specific symptom expressions on conifer and broadleaf species, including individual diagnostic descriptions for various species developing O3-like symptoms, confounding symptoms, and phenologically related information. For additional validation, microscopic analyses may be recommended. Data completeness requirements for the assessment of O3 visible injury is evaluated in terms of number of assessed branches (in-plot assessment) and quadrates (off-plot, LESS assessment) that are reported. For both, the in-plot and off-plot assessment, a minimum of 80% data completeness is expected.
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11.5 DATA PROCESSING Data are checked for plausibility and completeness, based on the results from the intercalibration exercises. For the in-plot assessment, the percentage of branches in the different frequency classes is assessed. For the LESS assessment, the following main data processing is suggested: 1. The frequency of quadrates including symptomatic plants allows conclusions on the percentage of affected vegetation area along the investigated forest edge. 2. The frequency of symptomatic species describes the percentage of symptomatic species over the total number of species of the forest edge. Mean number of symptomatic species and total number of symptomatic species are further indicators for temporal (from year to year) O3 risk assessment. Estimates should be calculated with confidence intervals at a 95% probability level (see Lorenz et al., 2008, p. 69). The results attributed to the respective countries may eventually be documented in a map covering Europe, characterizing areas of increased O3 risk for European forest ecosystems.
11.6 RESULTS Previous results related to visible injury as carried out according to the above referred methodology were presented by Ferretti et al. (2007) for south-west Europe and by Lorenz et al. (2008) for several countries across Europe. In 2009, a total of 15 European countries submitted their data on O3 injury assessment to the central ICP Forests database. The data from two countries did not comply with the Data Quality Limits (DQLs). Across the remaining 13 countries, a total number of 852 quadrates from 97 LESS and containing 598 different species were reported as assessed in August 2009. In respect to species diversity, a forest edge contained six different species on average. Across the 13 countries, 17 different species showed O3 symptoms (Table 11.3). For the 2009 dataset, no spatial trend could be detected which may be linked to geographical latitude and/or O3 concentrations. However, current investigations are undertaken to analyze the entire dataset from the past 10 years, starting in 2001. Furthermore, the environmental factors affecting O3 sensitivity are being considered with an O3 flux approach, estimating the amount of O3 that was taken up by the plant. This approach, combined with the monitoring of air pollution (Chapter 19) and O3 symptoms, may allow gaining a better understanding of the O3 risk for forests. The results demonstrate that O3 does have a negative effect on numerous plant species grown in different forests across Europe. The O3 injury assessment in the field provides a basis for further investigations of O3–plant interactions, possibly contributing to forest decline as found, for example, in the Catalan Pyrenees (Dı´az-de-Quijano et al., 2012). Intensive, long-term studies
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TABLE 11.3 Name of Symptomatic Species and Country Where it Occurred, Either Symptomatic or Nonsymptomatic for the 2009 O3 Symptom Survey Across Europe
Country
No. of LESS where species was present
No. of LESS where species was symptomatic
Austria
2
2
Italy
1
0
Lithuania
1
1
Slovak Republic
1
0
Spain
1
0
Switzerland
4
0
Austria
3
1
Italy
2
0
Lithuania
6
1
Romania
1
0
Slovak Republic
2
0
Spain
1
0
Switzerland
3
0
Czech Republic
1
1
Germany
2
0
Fagus moesiaca
Greece
1
1
Serbia
1
0
Fagus sylvatica
Austria
1
0
Germany
15
10
Italy
6
0
Romania
3
0
Slovak Republic
3
2
Spain
1
0
Switzerland
6
0
Czech Republic
1
1
Greece
1
0
Symptomatic species Cornus sanguinea
Corylus avellana
Crataegus sp.
Fragaria vesca
Continued
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TABLE 11.3 Name of Symptomatic Species and Country Where it Occurred, Either Symptomatic or Nonsymptomatic for the 2009 O3 Symptom Survey Across Europe—Cont’d
Country
No. of LESS where species was present
No. of LESS where species was symptomatic
Italy
5
0
Romania
1
0
Slovak Republic
5
0
Switzerland
3
0
Germany
2
0
Lithuania
7
1
Spain
2
0
Pinus radiata
Spain
1
1
Prunus avium
Austria
1
1
Germany
6
0
Italy
1
0
Slovak Republic
2
0
Switzerland
3
0
Austria
1
0
Czech Republic
1
1
Germany
8
0
Italy
2
0
Slovak Republic
4
0
Spain
3
0
Switzerland
1
0
Czech Republic
1
1
Italy
2
0
Romania
1
0
Symptomatic species
Frangula alnus
Prunus spinosa
Pyrus pyraster
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TABLE 11.3 Name of Symptomatic Species and Country Where it Occurred, Either Symptomatic or Nonsymptomatic for the 2009 O3 Symptom Survey Across Europe—Cont’d
Country
No. of LESS where species was present
No. of LESS where species was symptomatic
Ribes rubrum
Lithuania
3
1
Rubus idaeus
Austria
1
0
Belgium
2
0
Czech Republic
3
2
Germany
12
0
Italy
6
0
Lithuania
8
5
Slovak Republic
5
0
Austria
2
0
Czech Republic
2
1
Germany
1
0
Lithuania
7
1
Romania
1
0
Slovak Republic
4
1
Spain
2
0
Senecio hercynicus
Czech Republic
2
1
Sorbus torminalis
Greece
1
1
Italy
1
0
Vaccinium myrtillus
Czech Republic
1
1
Germany
2
0
Italy
5
0
Slovak Republic
3
0
Switzerland
1
0
Symptomatic species
Salix caprea
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of additional physiological measurements such as sap-flow are urgently needed to answer open questions of possible interactions between elevated exposures to O3 and frost hardiness, the actual uptake of O3 into plants, and the possible interactions with climate change on the water balance of mature trees. The presented monitoring survey for O3 visible symptoms may serve as a valuable measure to validate current modeling outputs for O3 risk assessment as it is the only O3 specific plant response that is monitored across European forests (in combination with O3 concentration, see Chapter 19) in a systematic and statistically sound way.
ACKNOWLEDGMENTS Marcus Schaub acknowledges the financial support by the Swiss Federal Agency for the Environment FOEN. Data from Europe 2009 and from Spain 2010 were gathered under Lifeþ project LIFE07 ENV/D/000218 FUTMON “Further development and implementation of an EU-level forest monitoring system.” Vicent Calatayud thanks the Spanish Ministry of Agriculture, Food and Environment and the COST Action FP0903 for contributing to this chapter. The projects CONSOLIDER-INGENIO 2010 (GRACCIE) and FEEDBACKS (Prometeo Program, Generalitat Valenciana) contribute to the support of CEAM.
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