5.3.! Distribution pattern of epiphytic Iichens on tree stems and in responses to sulphur and nitrogen deposition
5.3.2 Understorey vegetation in response to sulphur and nitrogen deposition
Unlike the epiphytic lichens on homogeneous tree stems, the vegetation types at the IM sites were rather diverse due to environmental variation such as soil type and nutrient status. They can be roughly divided into eight groups based on TWINSPÄN classification (Table 5.7), namely Fagus forest, subalpine birch forest, alpine meadow, spruce forest, spruce-pine mixed forest, poor fen, intermediate fen and rich fen. Ät the Italian area 3 (1T03) at 1870 m a.s.1., the understorey vegetation was similar to that of the spruce forests in Sweden and Finland due to the presence of some common species such as Vaccinium myrtillus, V vitis-idea and Deschampsiafiexousa. The major vegetation types are spruce forest and mixed coniferous (spruce-pine) forest. PCÄ (principal component analysis) ordination, using only forest sites, gave detailed information about the similarity among the sites within the TWINSPÄN groups 4 and5,i.e. the spruce and spruce-pine mixed forests (Figure 5.5). The sites were well separated based on ffieir species assemblages. For example SEO8 (Sandnäset), with relatively rich soil and nifrogen demanding plants, stands alone at the upper-right corner (Figure 5.5b). The species poor spruce (SF06, SF07 at Vindien) and mixed coniferous forests (SF10 at Tandövala, SEllat Tresticklan), form their own clusters and correspond well to the species ordination (Figure 5.5a). In short, bothTWINSPAN classification and PCÄ ordination demonsfrate high heterogeneity of species composition among the IM sites.
Characteristics of plant commanities in response to their chemical environment were presented by the indices based on Ellenberg’s indicator scores.
These indices showed quite sfrong relation to the soil water pH and the total nifrogen content (Table 5.8). Data included in the analysis were from Sweden and Finland only. Data from the Estonian site on calcareous soil were excluded due to the extreme soil character. Indicator indices based on Ellenberg’s R score showed stronger response to soil pH and nitrogen concentration than those based on N (Table 5.8). Mean scores showed stronger relafions to soil pH and nifrogen concentration than the weighted ones. The response of mean acid-intolerance score was stronger (r=0.$2 for pH, r=0.96 for nitrogen) than all of the others. But with regard to deposition, the relation was reverse. Weighted nifrogen-demand score showed slightly closer relation to 5 and N deposition than did other scores (Table 5.9).
The Finnish Envronment 27
0
Table5.1ClassificationofvegetationmonitoringsitesusingTWINSPAN.Cuttingleveisweresetat0.5,3.0,7.5,7.5,37.5,and75.0.Groupswerederivedafterthreedivisions.
Piotno.AreacodeSitecodePiotno.AreacodeSitecodePiotno.AreacodeSitecodePiotno.AreacodeSitecode
1.Fagus4.Spruce5.Sprucepinemixed
118SF13S161SF8S12EE1512119SF13Si62SF8SI3FilS3 120SF13$163SF8$17F135158SF8S18H3$159SF8$126LT251002.Subalpinebirch60SF85128SF1$164$E85181SF105130SF5$165SF8S182SF10SI
31SF5$14Fil8383SF1051 32SE5sj5FIlS884SF10sf 33SF5S1 6FilS8855ElO81
24ff3S186SF10$134SE5$125LT1510091SE115127RU1651192SF1151 43SF65198SF11S23.MpinemeadowSF6si99SF11S2 45SE6S1100SF11$235SE5S246516101SF11S237SF5S247SF6$1102SF11S2 36SF5S248SF6S1 103SF11S2 38SF5$249SF6$1 104SF11S2 39SF5S250SE7SI 93SF11$1 40SF5S2 51SF7$1 94SF11SI
52SE7$1 95SF11SI41SF5S296SF11S153SE7S142SF5$297SF11S154SF7SI55SF751 105SF12S1106SF128156SF7SI107SF125157SE7$1108SF12$19F1354109SF12S110F13S4110SF125113F14S2111SF12SI14F14S2112SF12S115F145518F15S216F14$519F155272SF9S120F15S373SF9$121F15S374SF9S122F15S475SF9SI23F15S476SF9SI 6.Poorfen
87SF10
88SF10
89SF1090SF1077SF978SF979SF9
80SE9
11R3
12F13
17F14
7.Intermediatefen
113SE12114SF12115SE12116SF12
117SF12
29SF1
8.Richfen
71SF8
67SF8
68SF870SF8
66SF8
69SF8 cEc0>cLu-ccc$2GJS2H
S2S2
S2
52
52
52
S7
S7
S6
S252
S2
S2
S2
52
S2
S2
S252
52S2
6
Table 5.8 Correlation matrx (Person) of soil water (0-25 cm in depth) p11, total nitrogen concentration and vegetation indices of mean acid-intoierance score (MM), weighted acid-intolerance score (WAS), mean nitrogen-demand score (MNS) and weighted nitrogen-demand score (WNS).
Variable pH N total WAS MAS WNS MNS
pH 1.00
Ntotal 074 100
WAS 0.4$ 0.78 1.00
MAS 0.82 0.96 0.81 1.00
WNS 0.21 0.33 0.78 0.45 1.00
MNS 0.71 0.56 0.65 0.71 0.76 1.00
Soil water pH was significantly and negatively correlated to SO4S and nitrogen concentration in deposition (Figure 5.6) but not to that in soil water (Figure 5.7). The correlation between sulphur and total nitrogen concentration in deposition was almost a straight line (Figure 5.8 a). However, this pattern was changed in the soil water (Figure 5.8 b). At the finnish (fbi, f103, F104 and F105) and Swedish sites (SF01, SF02 and SF03), the linear relation between sulphur and total nitrogen concentration was absent, but it was remained at the German, Italian and Fstonian sites, as well as at F10155. The 504S concentration in soil water was rather high at the Fstonia site, however, the soil water pH was also high at that site (FF1S8 in Table 5.3) indicating the great buffering capacity of calcareous soil to acid deposition. In contrast, the German site DEO1 (wet vegetation) showed low pH in soil water while the SO4S was also quite low (DF1533, DF1S43 in Table 5.3) indicating organic acidifying processes.
Tahle 5.9Correlation matrx (Person) of sulphur and total nitrogen deposition and four communbity indices weighted and mean acid-intolerance scores (WAS,MAS), weighted and mean nitrogen-demand scores (WNS, MNS).
Variable SO4S N total WAS MAS WNS MNS
$045 1
N total 0.99 1
WAS -0.04 -0.09 1
MAS 0.10 0.01 0.76 1
WNS 0.34 0.30 0.47 0.73
MNS 0.29 0.25 0.30 0.64 0.91
The FnnFsh Enronment 27
0
—
SEII LTI
SEII
su Fil
SEE6
5511 SSl FIlSF 556
LT2 SF11 SF11 SE8lO FIl
SSl SEIS
SjI FFi3 1lf3
Figure 5.5 PCA ordination of IM sites with vegetation monitoring (VG) based on their species composition.
The
FinnIsh Envronment 27 0.5
<0 0
-0.5
—1
0
cl-3
0 PCA 1
(b)
SF8 SF8 SE8 SESg
558
FilTS
1—
0
SEi22 SF12SF12
SEili5
SF11
5U16
iV
Fil
—I
657
—1
PCA 1
2
6.0 5.8 5.5 5.2 5.0
1::
“ 4.2 4.0 3.8 3.5 6.0 5.8 5.5 5.2 5.0 4.8 6 45 4.2 4.0 3.8 3.5TotatNiitsoi!water
Figure5.6RegressiondiagramsofS045,totalnitrogenconcentrationandpHinsoilwateragainstsulphurandtotalnitrogenindeposition.Thesignificanceofthe relationsisdenotedbythestars. S04$insoi!waterpHinsoi!water 4.5 4.0 3.5 3.0 2.5 2.0 ‘.5 1.0 0.5
0 1- 0 (3 0
u Y=.06$+.103*X 0 =.214 p=0.03‘ TotalNdeposition,kg.ha1.yr’
H m :3 :3 m :3 < 0
1 0
3.5 3.0 2.5 0 2.0 0 (3 o1.5
0 (3 Z1.0 0 H 0 3.5 bi)3.0 2.5 2.0 1.5 1.0 E—0.5 0
oY=I.426+.088*X oR2—128 p=0.110 00 Oo 0 0246810121416 TotalNdeposition,kg.ha1.yr1 Y=.98+.217*X0 R2=.271 p=0.0I** 0 0 0
0 4.5 4.0 b3.5 3.0 0 2.5 0
1
‘i1.0 0 “ 0.5 00246810121416 TotalNdeposition,kg.ha1.yH 0 Y=.07+.115*X 0 R2=.095 p=0.17 01I2 SO4Sdeposition,kg.ha1.yr1
0246810120246 SO4Sdeposition,kg.ha1.yr’
1012 SO4Sdeposition,kg.ha1.yr’
I)
c 0
figure 5J Regression diagram of soi! water pH against concentration of 5045 and tota! nitrogen in soi water.
0
The Rnnsh Envwenment 27Y=4.955- .011 *X R2 =5$14E4
p=o.9 0
00 0
0
0 0
0 0
@ 0
0 0
0
0 0
0 6.5
6.0
5.5
5.0
4.5
4.0
3.5
6.5
6.0
5.5
5.0
4.5
4.0
3,5
1 2 3 4
SO4S concentrafioniiisoi! water, mgIl
5
Y=4.887+,073*X R2— 031
p=0.4 0
0 0
-1 0 1 2 3 4
Total-N concentration in soil water, mg/1
5 6
14
12
6
0 -ø
2
0
6,0
5.0
- 4,0
0 0
3.0 0 0
2.0
0(.)
1.0
0
-1 0 1 2 3 4 5 6
Total N concentration in soil water, mg/1
Figure 5.8 Regression diagram of S04S against total nitrogen, indeposition and in soil water.
The Fnneh Envronment 27
0
0 2 4 6 $ 10 12 14 16
Total N deposition, kg.ha1,y(1
Y=L58+.351*X
(b) R2-. .153
p=0.05
0
EErnS8
0
DEOIS33
) 0
00555
0
DE05S43
0
5.4 Discussion
Obviously; for various reasons the IM member countries have different priorities in the selection of subprogrammes, and they cannot be forced to conduct certain subprogrammes. However, it is strongiy recommended that they should run specific packages or combinations of subprogrammes. For instance if a country starts the vegetation subprogramme it should at least start deposition and soil water chemistry as well. The Epiphytic Lichen subprogramme should always he combined with Deposition Chemistry subprogramme. It is waste of money to run one subprogramme and not that other one which generates its necessary input data.
The distribution pattern of epiphytic lichens on tree stems was quite clear at the IM sites as shown by both the TWINSPÄN and RDA analysis. The species assemblages showed great differences between the Northwest and Southeast part of the IM region, with the division line at 55°N. It appears wrong to use a phyto sociological approach in assessment of deposition effect over large regions because of the natural variation of species distribution. Besides, since not ali countries have inciuded ali species, there couid be a discrepancy in the comparison between countries.
Community indices based on eco-physiological characteristics and sensitivity to pollutants of the individual species could be used as bioindicators since they are neufral to species assemblage and their distributions. However, a lot of work stiil has to be done to obtain good indicator scores for epiphytic lichens. For instance it could include experiments with fransplantation and open-top chambers or climatic chambers with addition of S and N. Aigal thickness and colonisation rate in response to climate variabies and deposition should also be tested in such chambers.
Mean sensitivity tMS) showed a closer relation to deposition than weighted sensitivity This means that the proportion based on the presence of sensitive species among the total species pool may give better indication of the air quality than the proportion based on dominance measurements. The implication for field observation is that it may well be enough tonote mere presence ratherthan any sort of dominance, e. g. cover. This makes both the field work and the data treatment quicker and simpier compared with the procedure prescribed in the manual. The sensitivity values were mainly based on the responses to °2(cf.
Huitengren 1991), This may explain why the MS response to 5045 deposition was stronger than to nitrogen deposition.
In the atmosphere-vegetation-soil system, the vegetation acts as a modifier between deposition and soil water. The effect of nitrogen deposition on soil water depends on vegetation dynamics and soil properties. Nitrogen from deposition is normally taken up directiy by the piants. On the other hand, acid deposition is usually not modified by plants and thus it directly effects soil pH. One hypothesis may he drawn from the resuit: in the atmosphere- vegetation-soil water system, the relation between deposition and soil water chemistry is affected by vegetation activity For the processes in which the vegetation is actively involved the relationship between deposifion and soii water is skewed, otherwise this relationship is direct. At the Swedish and Finnish sites the strong linear relation between sulphur and total nitrogen in deposition did not remain in the soil water.
At German and Italian sites, however, this relation applied. The explanation could be that in boreal forests nitrogen is normally in short supply. The nitrogen in the rain water was taken up immediately by the vegetation whiie the SO4S jtist went through. Therefore, the relation between S045 and total nitrogen in soil water was skewed compared to that in deposition.
0
The Fnneh nvironment 27The mechanism of acidification seems more complicated than eufrofication.
The results suggest that plants respond to N deposition more directly than to SO4S deposition with respect to vegetation indices.
Even though some data are missing concerning the system of deposition soil water-vegetation, we can stili extract some interesting signals. This is quite promising for vegetation monitoring in the future.
Ä general experience from the evaluation of vegetation and relevant environmental data is that a more frequent establishment of vegetation monitoring, combined with deposition chemistry and throughfall monitoring in parUcular, among the participating countries would greatly increase the possibility to assess the impact of air pollutants on the large international scale.