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MAPPING OF AMMONIA POLLUTION WITH EPIPHYTIC LICHENS IN THE NETHERLANDS
Lichenologist 31(1): 9–20 (1999) Article No. lich.1998.0138 Available online at http://www.idealibrary.com on
MAPPING OF AMMONIA POLLUTION WITH EPIPHYTIC LICHENS IN THE NETHERLANDS C. M. van HERK*
Abstract: In the Netherlands a monitoring programme is in operation to map the effects of ammonia pollution with epiphytic lichens. The method is presented here and the results are statistically correlated with abiotic data. The abundance of nitrophytes on Quercus robur appears to be a useful parameter. Detailed spatial patterns of ammonia pollution can be obtained with lichens. To avoid interference, it is important to consider other influences, for example dust, climate, exposure, age of the trees and other pollutants. 1999 The British Lichen Society
Introduction Since the 1950s lichens have often been used to map sulphur dioxide (SO2) air pollution in the Netherlands (Barkman 1958; de Wit 1976). During recent decades a progressive recovery of species sensitive to SO2 took place (van Dobben 1993), due presumably to the falling levels of SO2. Now there are several records of species that had not been seen for nearly a century (van Herk & Aptroot 1996). There are even species new to science that were absent before (Aptroot & van Herk 1998). Some changes, however, do not fit within the spatial patterns and temporal changes in SO2. In the course of ten years a spectacular increase in nitrophytic species has taken place in all parts of the country with a high cattle density (van der Knaap 1984; de Bakker 1987; van Dijk 1988). In these areas the trees have become covered with such species as Phaeophyscia orbicularis, Physcia adscendens and Xanthoria parietina. This phenomenon is especially apparent on trees with acid bark (Quercus, Fagus), on which nitrophytes were absent or scarce before. In the same period several acidophytes, for example Evernia prunastri, Hypogymnia physodes, Lecanora conizaeoides and Pseudevernia furfuracea rapidly decreased (van Dijk 1988; van Herk 1990). A large number of stations formerly covered with these species are now totally devoid of them. Outside the areas with intensive cattle breeding these changes are less significant. Air pollution with ammonia (NH3) is considered to be the most important cause of these changes. In the Netherlands the correlation between ammonia and lichens has been studied repeatedly. Correlations are reported by de Bakker & van Dobben (1988), van Dijk (1988), de Bakker (1989), Aptroot (1989), van Herk (e.g. 1990, 1991, 1993, 1995, 1996), van Dobben (e.g. 1991, 1993) and van Dobben & Wamelink (1992). In Belgium (Vlaanderen) *Lichenologisch Onderzoekbureau Nederland, Goudvink 47, NL–3766 WK Soest, The Netherlands. 0024–2829/99/010009+12 r30.00/0
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the effects of ammonia have been studied by Hoffmann (1993). In Great Britain effects of intensive cattle breeding have been reported from Devon (Benfield 1994). Field observations show a clear relationship between the distance from a livestock farm and the abundance of nitrophytes on trees (Fig. 1A–C). Some of the species are more dominant, whereas other species are present only in small quantities in the immediate surroundings of the farms, for example Phaeophyscia nigricans, Candelariella aurella and Caloplaca holocarpa (Fig. 2). Very polluted sites show a striking resemblance to epilithic vegetation of calcareous substrata such as concrete. Even Candelariella medians and Caloplaca decipiens have been found at such stations on trees. The transition zone surrounding a livestock farm is usually more or less compressed at the west side and a little elongated at the east side, indicating that westerly winds are more frequent. The effects are definitely not caused only by slurry. Even in woods small branches at the tops of trees are now covered with Physcia tenella and Xanthoria polycarpa. The atmospheric behaviour of ammonia supplies an explanation for the close transitions. At 100 m distance from a source, c. 10% of the ammonia is deposited and at 1000 m this is c. 20% (Asman & van Jaarsveld 1990a). However, the greater part of the ammonia disappears into the atmosphere close to the source so gradients of ammonia concentrations may be abrupt at ground level. Until 1980 epiphytic nitrophytes on acid bark were largely confined to farmyards, present in small quantities on trees surrounding dunghills. There was no indication that gaseous ammonia was important for their occurrence, only the direct influence of dung was apparent. At the end of the 1970s most of the farmers switched over from a heavy solid straw-mixed product to liquid manure. This switch might be an important cause of the observed changes, as already suggested by Benfield (1994). A few studies on bark chemistry demonstrate that the effects of ammonia on nitrophytes are not primarily caused by the increased availability of nitrogen (de Bakker & van Dobben 1988; van Herk 1990). More important is the rise in bark pH, caused by the adsorption of NH3. In areas with a high cattle density the pH of the Common Oak (Quercus robur), normally c. pH 4·5, can rise to c. 6·5. At pH 6·5 most acidophytes are replaced by nitrophytes. The term, ‘ nitrophytic ’ assumes that such species require some form of nitrogen. However, a high pH seems to be a more direct reason for their occurrence. A better name should be ‘ neutrophytic ’ but this name is already used for another ecological group. Real neutrophytic lichens (indifferent species), for example most Parmelia and Ramalina species seem not to be affected significantly by ammonia, although a slight positive reaction on ammonia might be possible. The Netherlands is one of the most polluted parts of Europe with respect to ammonia. Ammonia is especially a huge problem in regions with acid sandy soils. In large areas of the Netherlands the emission values exceed 10 000 kg NH3 km 2 year 1 (Asman & van Jaarsveld 1990a). Surprisingly ammonia contributes to about 45% of the total acidification in the Netherlands. Although ammonia is not acid in itself, nitrification transforms most of the
oak forest coniferous forest building
nursery road with oaks
greenhouse
maize field meadow hedge with oaks
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NIW 6–7 NIW 5–6
NIW 4–5 NIW 3–4 NIW 2–3 NIW 1–2 NIW 0–1
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F. 1. Spatial patterns in a hypothetical area with four livestock farms. A. Topography; B. Quantity of nitrophytes (NIW) on trees (all Quercus robur); C. Reconstruction of ammonia pollution isolines based on nitrophytes.
A
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Abundance
F. 2. Schematic reaction of several nitrophytic species to ammonia pollution in the Netherlands based on observations on Quercus robur. The degree of pollution at which a species appears is called the threshold. Most of the species become more common at a higher ammonia pollution.
Caloplaca holocarpa Candelariella aurella Phaeophyscia nigricans Rinodina gennarii
Candelariella reflexa Physcia caesia Physcia dubia
Candelariella vitellina Lecanora dispersa (incl. L. hageni) Phaeophyscia orbicularis
Physcia adscendens Xanthoria candelaria Xanthoria parietina
Xanthoria polycarpa
Physcia tenella
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ammonia into nitric acid (HNO3) after deposition. As far as is known, this process only takes place in the soil, not on the bark of trees (van Dobben 1993). Not all emitted ammonia appears to be deposited unchanged. Some ammonia reacts in the atmosphere with acids, leading to the deposition of, for example, ammonium sulphate [(NH4)2SO4], thus part of the emitted ammonia will be transformed into ammonium (NH4 + ). Regional ammonia and ammonium concentration and deposition calculations are available by means of mathematical models based on cattle density (Asman & Jaarsveld 1990b). Figure 3A, B shows the ammonia and ammonium concentrations based on these calculations. Real measurements of ammonia and ammonium are only acquired at a limited number of stations because the costs are very high. To fill a gap in our knowledge of ammonia pollution, most of the provincial authorities charged with reducing their pollution have taken the initiative to map parts of their territory using lichens. From 1989 onwards every year a part of Holland has been mapped using nitrophytes and acidophytes. This information is now used to take measures; for example, state-aided removal of livestock farms from the surroundings of nature reserves. Materials and Methods The important role of bark pH as an intermediate factor requires that the effects of ammonia are mapped with only one tree species, preferably one with acid bark. Therefore only Quercus robur is used. A limited area (province of Utrecht) has been mapped with several different tree species in order to investigate the effect of the tree species used. Some tree species have been compared by means of regression analyses (Table 1). At the moment about 5500 sampling sites, each consisting of ten trees, have been investigated, on average one site per 4 km2, covering about half of the Netherlands (Fig. 4). Sampling sites are at least at a 100 m distance from a livestock farm. Only straight and exposed trees, without low branches or shrubs in front, are used. Usually wayside trees are suitable. During subsequent years additional regions will be mapped. Although all epiphytic lichens have been examined, only selected results on nitrophytes and acidophytes are considered here. To achieve the mapping an integrated parameter was designed, the NIW (‘ Nitrofiele Indicatie Waarde ’). The NIW is defined as the mean number of nitrophytes found on the bark of one tree. Species covering more than 1 dm2 count as double. The following species are considered to be nitrophytes: Caloplaca citrina, C. holocarpa, Candelariella aurella, C. reflexa, C. vitellina, C. xanthostigma, Lecanora muralis, L dispersa s. lat. (inc. L. hageni), Phaeophyscia orbicularis, P. nigricans, Physcia adscendens, P. caesia, P. dubia, P. tenella, Rinodina gennarii, Xanthoria candelaria, X. calcicola, X. parietina and X. polycarpa. Note that common species present on all trees add much more to the NIW (2 points) than species present in small numbers on one out of ten trees only (0·1 point), thus quantity is an important element in the NIW. All common nitrophytes are used; only a few nitrophytes for which interference with sulphur dioxide is suspected (e.g. Candelaria concolor) have been omitted. The above calculation has also been carried out with acidophytes, mainly to investigate whether acidophytes reveal matching results. The species united into the AIW (‘ Acidofiele Indicatie Waarde ’) are Cetraria chlorophylla, Chaenotheca ferruginea, Cladonia (all species taken together), Evernia prunastri, Hypocenomyce scalaris, Hypogymnia physodes, H. tubulosa, Lecanora aitema, L. conizaeoides, L. pulicaris, Lepraria incana, Ochrolechia microstictoides, Parmelia saxatilis, Parmeliopsis ambigua, Placynthiella icmalea, Platismatia glauca, Pseudevernia furfuracea, Trapeliopsis flexuosa, T. granulosa and Usnea (all species taken together). At all sites the NIW and AIW have been calculated and both NIW and AIW have been used to produce detailed maps by means of linear interpolation. To investigate statistical significance, the NIW was related by means of multiple regression to several abiotic parameters, viz. ammonia air concentration, ammonium air concentration, sulphur
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F. 3. Ammonia (A) and ammonium (B) air concentration in the Netherlands in 1988 (ìg m 3) [source: National Institute of Public Health and Environmental Protection (RIVM)].
isolines
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F. 4. Ammonia pollution in the Netherlands derived from the abundance of nitrophytes on Quercus robur (NIW). dioxide air concentration, the structure of the landscape, distance from livestock farms, distance from maize fields, the girth of the trees, and the geographical position in the Netherlands.
Results Table 1 allows comparison of Quercus robur and Populuscanadensis for their abundance of nitrophytes. Both tree species yield no nitrophytes when the deposition values do not exceed, respectively, 1000 and 500 mol ha 1 year 1. Furthermore, with both tree species there is a good dose-response relationship and the explained variance is sufficient. There was insufficient data from Fraxinus excelsior, Salix, Tilia and Ulmus species. The dose-response relationship of Fraxinus and Salix is acceptable, but the explained variance is only small, which means that factors other than ammonia might dominate the results. Tilia and Ulmus do not show a dose-response relationship at all.
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T 1. Calculated linear regressions for the abundance of nitrophytes (NIW) on Quercus robur and Populus x canadensis against ammonia (NH3) deposition values (after van Herk 1996)* Linear model: Y=a+bX
Explained variance
Degrees of freedom
Probability level
17·9% 9·9%
173 144
P<0·0001 P=0·0001
NIWQu = 2·10·0020 NH3 NIWPo = 1·50·0028 NH3
*Dependent variables: Nitrofiele Indicatie Waarde with Quercus robur (NIWQu) and Nitrofiele Indicatie Waarde with Populuscanadensis (NIWPo). Independent variable: ammonia deposition values (mol ha 1year 1).
T 2. Multiple regression with the abundance of nitrophytes on Quercus robur (NIW) as dependent variable and nine other parameters as independent variables (after van Herk 1995)* In model Ammonia‡ Landscape Girth of trees Maize fields Livestock farms Y-co-ordinate
Regression coefficient +0·2373 0·0122 0·0603 0·0003 +0·0028 +0·0042
F-Remove 495·00 68·72 79·47 5·41 335·20 32·65
Not in model
Correlation
F-Enter
Ammonium Sulphur dioxide X-co-ordinate
0·015 0·032 0·004
0·53 2·46 0·05
*A total of 2349 sampling sites throughout the Netherlands were analysed. A variable enters the model when F-Enter is at least 4·00 (corresponds to P<0·05). The contribution of the variables on the left-hand side (‘ in model ’) is significant (P<0·05). No significant contribution to the model could be proved for the variables on the right-hand side (‘ not in model ’). Dependent variable=Nitrofiele Indicatie Waarde (NIW). Explained variance=47·1%, degrees of freedom=2342. ‡Explanation of variables: ammonia=mean ammonia (NH3) air concentration per 55 km2 (ìg . m3) [taken from the National Institute of Public Health and Environmental Protection (RIVM)]; ammonium=mean ammonium (NH4 + ) air concentration per 55 km2 (ìg . m3) (taken from RIVM); girth of trees=girth of the sampled trees (dm); landscape=‘ roughness ’ of the landscape, parameter to express to what rate the landscape causes turbulence and dilution (taken from RIVM); maize fields=presence of maize fields in the surroundings (—m distance); livestock farms=presence of livestock farms in the surroundings (—m distance); sulphur dioxide=mean SO2 air concentration per 55 km2 (ì . m3) (taken from RIVM); X-co-ordinate/Y-co-ordinate=West-East/North-South position in the Netherlands.
Other calculations (Table 2) make clear that Q. robur is very useful for mapping ammonia. Unfortunately, Q. robur is absent or sparse in the western part of the Netherlands. Investigations are being carried out to find whether Populus is an appropriate alternative in areas where Quercus does not occur. Figure 4 shows the abundance of nitrophytes in the area mapped so far. Detailed patterns of NIW are notable; areas with high and low values are situated close to each other. The overall similarity of the spatial patterns of NIW and the ammonia air concentration (Fig. 3A) is striking. There is not only a good correspondence concerning the polluted areas (e.g. Gelderse
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Vallei) and the cleaner areas (e.g. Drenthe). The size and position of the smaller polluted regions like Friese Wouden and Kempen is also clearly visible. It was not attempted to map individual livestock farms, although clusters of big farms are often visible in Fig. 4. The pattern derived from the lichen composition (Fig. 4) is obviously much more detailed than the pattern calculated using cattle density (Fig. 3A). Therefore, the lichen method is much more informative. The similarity between the NIW and the ammonium air concentration (Fig. 3B) is only slight. Multiple regression confirms this. The ammonia air concentration contributes considerably to the explained variance of the NIW, but the contribution of the ammonium air concentration is not significant (Table 2). The explanation is that ammonium has no effect on bark pH. Thus, only the effects of ammonia are visible with nitrophytes because ammonia gives rise to an increase in the pH. The increased nitrogen availability caused by ammonium apparently has no effect on the occurrence of nitrophytes, as already concluded in connection with bark chemistry. Neither has nitrogen oxide (NOx), emitted mainly by traffic, any effect on the occurrence of nitrophytes (statistical calculation not presented). The presence of livestock farms in the surroundings adds considerably to the variance (Table 2). Both parameters ‘ ammonia ’ and ‘ livestock farms ’ are good for 43% explained variance. The remaining four variables with a significant contribution in Table 2 add only 4%. Maize fields are usually spread heavily with slurry. The presence of maize fields, however, has only a slight effect on the presence of nitrophytes (Table 2). Perhaps only sources of ammonia with a continuous character have a clear effect, as maize fields are spread with slurry only once or twice a year. More important is the structure of the landscape. Very open ‘ windy ’ landscapes with only exposed trees yield more nitrophytes than landscapes with many hedges, bushes and ‘ hidden ’ rows of trees. In the last case the ammonia is probably spread over a lot of objects resulting in a dilution effect. An important cause of interference is the age of the trees. The NIW appears to be higher on young (slender) trees (see below). Nitrophytes (NIW) and acidophytes (AIW) appear to have oppositing behaviour (r= 0·64, P<0·0001). Thus, on trees with high NIW values, AIW values are usually low and vice versa. There are also other differences in behaviour between nitrophytes and acidophytes. Multiple regression shows that acidophytes are sensitive to both ammonia and ammonium (whereas nitrophytes react only to ammonia). This phenomenon is confirmed by field observations. At a lot of stations acidophytes (e.g. Hypogymnia physodes and Pseudevernia furfuracea) have disappeared on a large scale without any or only a small increase of nitrophytes. This is especially the case at some distance from the well-known areas with a high cattle density. (Fig. 3A) but within the areas for which a high ammonium deposition is calculated (Fig. 3B). This suggests that (at least some) acidophytes are not only sensitive to a rise of the pH, but also sensitive to an increase in the ammonium content of the bark. Competition with other lichens, for instance increasing nitrophytes, is in most cases not an important reason for their disappearance.
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Discussion The abundance of epiphytic nitrophytes can be used effectively to map spatial patterns of ammonia pollution. Lichens have the advantage that very detailed maps can be produced at relatively low costs. Only (expensive) direct measurement of the ammonia air concentration reveals comparable detailed information. At this moment permanent measurements are carried out at about 100 lichen monitoring stations by a Dutch institute for technical research (TNO). For this purpose special measuring tubes were developed, which can be suspended from a monitored tree. Once a month these tubes are collected and the mean ammonia concentration during the preceding month can be calculated. In the near future a comparison between lichen composition and these ammonia air concentrations will be carried out. These calculations are important for a further validation of the detailed patterns of ammonia pollution observed with nitrophytic lichens (Fig. 4). In other countries, on other substrata, or under other circumstances the occurrence of nitrophytes may be less obviously linked to nitrogenous emissions. The way in which nitrophytes react to the pH of the substratum means that the observations cannot be compared with the straight reaction of lichens to SO2. Interference from other factors, which might even be dominant must be considered. To avoid interference it is important to consider the influence of other factors such as climate, dust, the age of the trees, other pollutants, dogs, bark wounds, and salt spray. Each of these will be discussed. Climate is considered to be an important interfering factor. Within the Netherlands a slight shift in climatic conditions is evident, from dry in the South and East to slightly wetter near the coast and in the North. Some species are more drought resistant (Xanthoria parietina, Physcia adscendens), whereas other species are slightly more common in areas with higher precipitation (P. tenella, X. polycarpa). Within the area studied the effect of the climate as a whole is probably negligible on the NIW. However a slight shift along the Y-co-ordinate is apparent (Table 2), which might be due to climatic interference. Epiphytic nitrophytes also occur on the base of trees on calcareous soils, especially under dusty circumstances. As most of the soils in the Netherlands are non-calcareous and oligotrophic, dust is probably only a minor cause of interference in the area studied. In countries with a very dry climate, drought and dust might be dominant factors, preventing the use of nitrophytes as indicators of ammonia pollution. The age of the trees investigated appears to be important. Multiple regression shows that on old trees fewer nitrophytes occur than on young trees with the same NH3 pollution (Table 2). On young trees the NIW is about 0·7 NIW unit higher than on old trees. To avoid interference, trees with only slight differences in age should be compared. Nitrophytes are also common on trees polluted by dogs. In built-up areas it is sometimes difficult to find ‘ clean ’ trees. A practical solution might be not to use the base of trees since such pollution generally reaches no higher than 50 cm. Near bark wounds nitrophytes are also common, especially on Populus, Ulmus, Fraxinus, Acer and Fagus. Trees with bark wounds should be avoided.
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However, on Q. robur usually very few nitrophytes are to be found near bark wounds. Finally, salt spray causes some influence in coastal areas, but the effects seem to be restricted to a few kilometres along the coast. Table 2 shows that there appears to be no effect of SO2 on the NIW: in areas with a high SO2 concentration there is no ‘ deficit ’ of nitrophytes. If the (not significant) effect is calculated in a regression equation, the effect appears to be only 0·01 unit, thus negligible. It is surprising that SO2 levels have no effect on the spatial pattern of nitrophytes on oaks (NIWQu) in the Netherlands. At the moment the SO2 level is very low; even in the most polluted areas the concentration now rarely exceeds 30 ìg m 3. It is likely that SO2 is not limiting the occurrence of common nitrophytes any more. Furthermore no effect of SO2 on the pH of the bark of Q. robur could be traced (van Herk 1990). Even trees in the centre of cities with only Lecanora conizaeoides appeared to have the same pH as trees in large woods with lush Usnea (both pH 3·9). Only the effect of ammonia on the pH is apparent. However, the pH of tree species with neutral bark may be influenced by SO2 levels. A calculation carried out with Populus shows that this indeed seems to be the case. Multiple regression with SO2 and NH3 on NIWPo shows a just significant (but not dominant) effect of SO2 (van Herk 1997). A sensitivity scale based on separate species has not been used to estimate ammonia pollution, although clear differences in the species response exist (Fig. 2). It is obvious that in the area studied the total quantity of nitrophytes and acidophytes (NIW and AIW) at sampling sites are useful and sufficient indicators. The use of separate species as indicators of pollution zones has the disadvantage that a shift in response of a single species can disrupt the scale units. Such a shift could be caused by spatial differences of other pollutants, the climate or the ecology, as stated for X. parietina in connection with drought. I am grateful to Dr A. Aptroot and L. Spier for discussions on this subject and useful comments on the manuscript. Furthermore, I am grateful to the provincial administrations of Groningen, Friesland, Drenthe, Overijssel, Gelderland, Utrecht and Noord-Brabant for making this research possible and giving me the opportunity to publish this paper. R Aptroot, A. (1989) Veranderingen in de epifytenflora van de Provincie Utrecht over de periode 1984–1989. Utrecht: Provincie Utrecht. Aptroot, A. & van Herk, C. M. (1998) Lecanora barkmaneana, a new nitrophilous sorediate corticolous lichen from The Netherlands. Lichenologist 31: 3–8. Asman, W. A. H. & van Jaarsveld, J. A. (1990a) Gedrag van atmosferisch ammoniak. Proceedings Symposium Dierlijke Mest: Problemen en oplossingen. Den Haag: K. N. C. V. Asman, W. A. H. & van Jaarsveld, J. A. (1990b) A Variable-Resolution Statistical Transport Model Applied for Ammonia and Ammonium. RIVM report no. 228471007. Bilthoven. Barkman, J. J. (1958) Phytosociology and Ecology of Cryptogamic Epiphytes. Assen: Van Gorcum. Benfield, B. (1994) Impact of agriculture on epiphytic lichens at Plymtree, East Devon. Lichenologist 26: 91–96. de Bakker, A. J. (1987) Verslag van de herinventarisatie van Noord-Brabant en Limburg op epifytische lichenen in 1986. Buxbaumiella 20: 36–39. de Bakker, A. J. (1989) Monitoring van epifytische korstmossen in 1988. RIN-rapport 89/14: 1–53. Leersum: Rijksinstituut voor Natuurbeheer.
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de Bakker, A. J. & van Dobben, H. F. (1988) Effecten van ammoniakemissie op epifytische korstmossen, een correlatief onderzoek inde Peel. RIN-rapport 88/35: 1–48. Leersum: Rijksinstituut voor Natuurbeheer. de Wit, T. (1976) Epiphytic lichens and air pollution in The Netherlands. Bibliotheca Lichenologica 5: 1–115. Hoffmann, M. (1993) Verspreiding, Fytosociologie en Ecologie van Epifyten en Epifytengemeenschappen in Oost- en West-Vlaanderen. Proefschrift Universiteit Gent. van Dijk, H. W. J. (1988) Epifytische Kortstmossen, zure Regen en Ammoniak. Zwolle: Provincie Overijssel. van Dobben, H. F. (1991) Monitoring van epifytische korstmossen in 1989. RIN-rapport 91/8: 1–62. Leersum: Rijksinstituut voor Natuurbeheer. van Dobben, H. F. (1993) Vegetation as a monitor for deposition of nitrogen and acidity. Proefschrift RUU. Utrecht. van Dobben, H. F. & Wamelink, W. (1992) Effects of atmospheric chemistry and bark chemistry on epiphitic lichen vegetation in The Netherlands. RIN-rapport 92/23: 1–34. Wageningen: Instituut voor Bos- en Natuuronderzoek. van Herk, C. M. (1990) Epifytische Korstmossen in de Provincies Drenthe, Overijssel en Gelderland. Zwolle: Provincie Overijssel. van Herk, C. M. (1991) Korstmossen als Indicator voor zure Depositie, Basisrapport. Arnhem: Provincie Gelderland. van Herk, C. M. (1993) Korstmossen en zure Depositie in Drenthe en Friesland. Assen/Leeuwarden: Provincie Drenthe & Provincie Friesland. van Herk, C. M. (1995) Korstmossen en ammoniak. Buxbaumiella 36: 43–49. van Herk, C. M. (1996) Monitoring van Ammoniak en Zwaveldioxide met Korstmossen in de Provincie Utrecht. Soest: LON by order of Provincie Utrecht. van Herk, C. M. (1997) Monitoring van Ammoniak met Korstmossen in Zeeland. Soest: LON by order of Provincie Zeeland. van Herk, C. M. & Aptroot, A. (1996) Epifytische korstmossen komen weer terug. Natura 93: 130–132. van der Knaap, W. O. (1984) Epifyten in de provincie Utrecht 1979–1984. Buxbaumiella 16: 15–17. Accepted for publication 16 January 1998
MAPPING OF AMMONIA POLLUTION WITH EPIPHYTIC LICHENS IN THE NETHERLANDS C. M. van HERK*
Abstract: In the Netherlands a monitoring programme is in operation to map the effects of ammonia pollution with epiphytic lichens. The method is presented here and the results are statistically correlated with abiotic data. The abundance of nitrophytes on Quercus robur appears to be a useful parameter. Detailed spatial patterns of ammonia pollution can be obtained with lichens. To avoid interference, it is important to consider other influences, for example dust, climate, exposure, age of the trees and other pollutants. 1999 The British Lichen Society
Introduction Since the 1950s lichens have often been used to map sulphur dioxide (SO2) air pollution in the Netherlands (Barkman 1958; de Wit 1976). During recent decades a progressive recovery of species sensitive to SO2 took place (van Dobben 1993), due presumably to the falling levels of SO2. Now there are several records of species that had not been seen for nearly a century (van Herk & Aptroot 1996). There are even species new to science that were absent before (Aptroot & van Herk 1998). Some changes, however, do not fit within the spatial patterns and temporal changes in SO2. In the course of ten years a spectacular increase in nitrophytic species has taken place in all parts of the country with a high cattle density (van der Knaap 1984; de Bakker 1987; van Dijk 1988). In these areas the trees have become covered with such species as Phaeophyscia orbicularis, Physcia adscendens and Xanthoria parietina. This phenomenon is especially apparent on trees with acid bark (Quercus, Fagus), on which nitrophytes were absent or scarce before. In the same period several acidophytes, for example Evernia prunastri, Hypogymnia physodes, Lecanora conizaeoides and Pseudevernia furfuracea rapidly decreased (van Dijk 1988; van Herk 1990). A large number of stations formerly covered with these species are now totally devoid of them. Outside the areas with intensive cattle breeding these changes are less significant. Air pollution with ammonia (NH3) is considered to be the most important cause of these changes. In the Netherlands the correlation between ammonia and lichens has been studied repeatedly. Correlations are reported by de Bakker & van Dobben (1988), van Dijk (1988), de Bakker (1989), Aptroot (1989), van Herk (e.g. 1990, 1991, 1993, 1995, 1996), van Dobben (e.g. 1991, 1993) and van Dobben & Wamelink (1992). In Belgium (Vlaanderen) *Lichenologisch Onderzoekbureau Nederland, Goudvink 47, NL–3766 WK Soest, The Netherlands. 0024–2829/99/010009+12 r30.00/0
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the effects of ammonia have been studied by Hoffmann (1993). In Great Britain effects of intensive cattle breeding have been reported from Devon (Benfield 1994). Field observations show a clear relationship between the distance from a livestock farm and the abundance of nitrophytes on trees (Fig. 1A–C). Some of the species are more dominant, whereas other species are present only in small quantities in the immediate surroundings of the farms, for example Phaeophyscia nigricans, Candelariella aurella and Caloplaca holocarpa (Fig. 2). Very polluted sites show a striking resemblance to epilithic vegetation of calcareous substrata such as concrete. Even Candelariella medians and Caloplaca decipiens have been found at such stations on trees. The transition zone surrounding a livestock farm is usually more or less compressed at the west side and a little elongated at the east side, indicating that westerly winds are more frequent. The effects are definitely not caused only by slurry. Even in woods small branches at the tops of trees are now covered with Physcia tenella and Xanthoria polycarpa. The atmospheric behaviour of ammonia supplies an explanation for the close transitions. At 100 m distance from a source, c. 10% of the ammonia is deposited and at 1000 m this is c. 20% (Asman & van Jaarsveld 1990a). However, the greater part of the ammonia disappears into the atmosphere close to the source so gradients of ammonia concentrations may be abrupt at ground level. Until 1980 epiphytic nitrophytes on acid bark were largely confined to farmyards, present in small quantities on trees surrounding dunghills. There was no indication that gaseous ammonia was important for their occurrence, only the direct influence of dung was apparent. At the end of the 1970s most of the farmers switched over from a heavy solid straw-mixed product to liquid manure. This switch might be an important cause of the observed changes, as already suggested by Benfield (1994). A few studies on bark chemistry demonstrate that the effects of ammonia on nitrophytes are not primarily caused by the increased availability of nitrogen (de Bakker & van Dobben 1988; van Herk 1990). More important is the rise in bark pH, caused by the adsorption of NH3. In areas with a high cattle density the pH of the Common Oak (Quercus robur), normally c. pH 4·5, can rise to c. 6·5. At pH 6·5 most acidophytes are replaced by nitrophytes. The term, ‘ nitrophytic ’ assumes that such species require some form of nitrogen. However, a high pH seems to be a more direct reason for their occurrence. A better name should be ‘ neutrophytic ’ but this name is already used for another ecological group. Real neutrophytic lichens (indifferent species), for example most Parmelia and Ramalina species seem not to be affected significantly by ammonia, although a slight positive reaction on ammonia might be possible. The Netherlands is one of the most polluted parts of Europe with respect to ammonia. Ammonia is especially a huge problem in regions with acid sandy soils. In large areas of the Netherlands the emission values exceed 10 000 kg NH3 km 2 year 1 (Asman & van Jaarsveld 1990a). Surprisingly ammonia contributes to about 45% of the total acidification in the Netherlands. Although ammonia is not acid in itself, nitrification transforms most of the
oak forest coniferous forest building
nursery road with oaks
greenhouse
maize field meadow hedge with oaks
B
NIW 6–7 NIW 5–6
NIW 4–5 NIW 3–4 NIW 2–3 NIW 1–2 NIW 0–1
C
12 3
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6 6
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4 32 1
F. 1. Spatial patterns in a hypothetical area with four livestock farms. A. Topography; B. Quantity of nitrophytes (NIW) on trees (all Quercus robur); C. Reconstruction of ammonia pollution isolines based on nitrophytes.
A
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High threshold
Low threshold
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Abundance
F. 2. Schematic reaction of several nitrophytic species to ammonia pollution in the Netherlands based on observations on Quercus robur. The degree of pollution at which a species appears is called the threshold. Most of the species become more common at a higher ammonia pollution.
Caloplaca holocarpa Candelariella aurella Phaeophyscia nigricans Rinodina gennarii
Candelariella reflexa Physcia caesia Physcia dubia
Candelariella vitellina Lecanora dispersa (incl. L. hageni) Phaeophyscia orbicularis
Physcia adscendens Xanthoria candelaria Xanthoria parietina
Xanthoria polycarpa
Physcia tenella
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ammonia into nitric acid (HNO3) after deposition. As far as is known, this process only takes place in the soil, not on the bark of trees (van Dobben 1993). Not all emitted ammonia appears to be deposited unchanged. Some ammonia reacts in the atmosphere with acids, leading to the deposition of, for example, ammonium sulphate [(NH4)2SO4], thus part of the emitted ammonia will be transformed into ammonium (NH4 + ). Regional ammonia and ammonium concentration and deposition calculations are available by means of mathematical models based on cattle density (Asman & Jaarsveld 1990b). Figure 3A, B shows the ammonia and ammonium concentrations based on these calculations. Real measurements of ammonia and ammonium are only acquired at a limited number of stations because the costs are very high. To fill a gap in our knowledge of ammonia pollution, most of the provincial authorities charged with reducing their pollution have taken the initiative to map parts of their territory using lichens. From 1989 onwards every year a part of Holland has been mapped using nitrophytes and acidophytes. This information is now used to take measures; for example, state-aided removal of livestock farms from the surroundings of nature reserves. Materials and Methods The important role of bark pH as an intermediate factor requires that the effects of ammonia are mapped with only one tree species, preferably one with acid bark. Therefore only Quercus robur is used. A limited area (province of Utrecht) has been mapped with several different tree species in order to investigate the effect of the tree species used. Some tree species have been compared by means of regression analyses (Table 1). At the moment about 5500 sampling sites, each consisting of ten trees, have been investigated, on average one site per 4 km2, covering about half of the Netherlands (Fig. 4). Sampling sites are at least at a 100 m distance from a livestock farm. Only straight and exposed trees, without low branches or shrubs in front, are used. Usually wayside trees are suitable. During subsequent years additional regions will be mapped. Although all epiphytic lichens have been examined, only selected results on nitrophytes and acidophytes are considered here. To achieve the mapping an integrated parameter was designed, the NIW (‘ Nitrofiele Indicatie Waarde ’). The NIW is defined as the mean number of nitrophytes found on the bark of one tree. Species covering more than 1 dm2 count as double. The following species are considered to be nitrophytes: Caloplaca citrina, C. holocarpa, Candelariella aurella, C. reflexa, C. vitellina, C. xanthostigma, Lecanora muralis, L dispersa s. lat. (inc. L. hageni), Phaeophyscia orbicularis, P. nigricans, Physcia adscendens, P. caesia, P. dubia, P. tenella, Rinodina gennarii, Xanthoria candelaria, X. calcicola, X. parietina and X. polycarpa. Note that common species present on all trees add much more to the NIW (2 points) than species present in small numbers on one out of ten trees only (0·1 point), thus quantity is an important element in the NIW. All common nitrophytes are used; only a few nitrophytes for which interference with sulphur dioxide is suspected (e.g. Candelaria concolor) have been omitted. The above calculation has also been carried out with acidophytes, mainly to investigate whether acidophytes reveal matching results. The species united into the AIW (‘ Acidofiele Indicatie Waarde ’) are Cetraria chlorophylla, Chaenotheca ferruginea, Cladonia (all species taken together), Evernia prunastri, Hypocenomyce scalaris, Hypogymnia physodes, H. tubulosa, Lecanora aitema, L. conizaeoides, L. pulicaris, Lepraria incana, Ochrolechia microstictoides, Parmelia saxatilis, Parmeliopsis ambigua, Placynthiella icmalea, Platismatia glauca, Pseudevernia furfuracea, Trapeliopsis flexuosa, T. granulosa and Usnea (all species taken together). At all sites the NIW and AIW have been calculated and both NIW and AIW have been used to produce detailed maps by means of linear interpolation. To investigate statistical significance, the NIW was related by means of multiple regression to several abiotic parameters, viz. ammonia air concentration, ammonium air concentration, sulphur
2.0
6.0
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F. 3. Ammonia (A) and ammonium (B) air concentration in the Netherlands in 1988 (ìg m 3) [source: National Institute of Public Health and Environmental Protection (RIVM)].
isolines
A
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F. 4. Ammonia pollution in the Netherlands derived from the abundance of nitrophytes on Quercus robur (NIW). dioxide air concentration, the structure of the landscape, distance from livestock farms, distance from maize fields, the girth of the trees, and the geographical position in the Netherlands.
Results Table 1 allows comparison of Quercus robur and Populuscanadensis for their abundance of nitrophytes. Both tree species yield no nitrophytes when the deposition values do not exceed, respectively, 1000 and 500 mol ha 1 year 1. Furthermore, with both tree species there is a good dose-response relationship and the explained variance is sufficient. There was insufficient data from Fraxinus excelsior, Salix, Tilia and Ulmus species. The dose-response relationship of Fraxinus and Salix is acceptable, but the explained variance is only small, which means that factors other than ammonia might dominate the results. Tilia and Ulmus do not show a dose-response relationship at all.
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T 1. Calculated linear regressions for the abundance of nitrophytes (NIW) on Quercus robur and Populus x canadensis against ammonia (NH3) deposition values (after van Herk 1996)* Linear model: Y=a+bX
Explained variance
Degrees of freedom
Probability level
17·9% 9·9%
173 144
P<0·0001 P=0·0001
NIWQu = 2·10·0020 NH3 NIWPo = 1·50·0028 NH3
*Dependent variables: Nitrofiele Indicatie Waarde with Quercus robur (NIWQu) and Nitrofiele Indicatie Waarde with Populuscanadensis (NIWPo). Independent variable: ammonia deposition values (mol ha 1year 1).
T 2. Multiple regression with the abundance of nitrophytes on Quercus robur (NIW) as dependent variable and nine other parameters as independent variables (after van Herk 1995)* In model Ammonia‡ Landscape Girth of trees Maize fields Livestock farms Y-co-ordinate
Regression coefficient +0·2373 0·0122 0·0603 0·0003 +0·0028 +0·0042
F-Remove 495·00 68·72 79·47 5·41 335·20 32·65
Not in model
Correlation
F-Enter
Ammonium Sulphur dioxide X-co-ordinate
0·015 0·032 0·004
0·53 2·46 0·05
*A total of 2349 sampling sites throughout the Netherlands were analysed. A variable enters the model when F-Enter is at least 4·00 (corresponds to P<0·05). The contribution of the variables on the left-hand side (‘ in model ’) is significant (P<0·05). No significant contribution to the model could be proved for the variables on the right-hand side (‘ not in model ’). Dependent variable=Nitrofiele Indicatie Waarde (NIW). Explained variance=47·1%, degrees of freedom=2342. ‡Explanation of variables: ammonia=mean ammonia (NH3) air concentration per 55 km2 (ìg . m3) [taken from the National Institute of Public Health and Environmental Protection (RIVM)]; ammonium=mean ammonium (NH4 + ) air concentration per 55 km2 (ìg . m3) (taken from RIVM); girth of trees=girth of the sampled trees (dm); landscape=‘ roughness ’ of the landscape, parameter to express to what rate the landscape causes turbulence and dilution (taken from RIVM); maize fields=presence of maize fields in the surroundings (—m distance); livestock farms=presence of livestock farms in the surroundings (—m distance); sulphur dioxide=mean SO2 air concentration per 55 km2 (ì . m3) (taken from RIVM); X-co-ordinate/Y-co-ordinate=West-East/North-South position in the Netherlands.
Other calculations (Table 2) make clear that Q. robur is very useful for mapping ammonia. Unfortunately, Q. robur is absent or sparse in the western part of the Netherlands. Investigations are being carried out to find whether Populus is an appropriate alternative in areas where Quercus does not occur. Figure 4 shows the abundance of nitrophytes in the area mapped so far. Detailed patterns of NIW are notable; areas with high and low values are situated close to each other. The overall similarity of the spatial patterns of NIW and the ammonia air concentration (Fig. 3A) is striking. There is not only a good correspondence concerning the polluted areas (e.g. Gelderse
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Vallei) and the cleaner areas (e.g. Drenthe). The size and position of the smaller polluted regions like Friese Wouden and Kempen is also clearly visible. It was not attempted to map individual livestock farms, although clusters of big farms are often visible in Fig. 4. The pattern derived from the lichen composition (Fig. 4) is obviously much more detailed than the pattern calculated using cattle density (Fig. 3A). Therefore, the lichen method is much more informative. The similarity between the NIW and the ammonium air concentration (Fig. 3B) is only slight. Multiple regression confirms this. The ammonia air concentration contributes considerably to the explained variance of the NIW, but the contribution of the ammonium air concentration is not significant (Table 2). The explanation is that ammonium has no effect on bark pH. Thus, only the effects of ammonia are visible with nitrophytes because ammonia gives rise to an increase in the pH. The increased nitrogen availability caused by ammonium apparently has no effect on the occurrence of nitrophytes, as already concluded in connection with bark chemistry. Neither has nitrogen oxide (NOx), emitted mainly by traffic, any effect on the occurrence of nitrophytes (statistical calculation not presented). The presence of livestock farms in the surroundings adds considerably to the variance (Table 2). Both parameters ‘ ammonia ’ and ‘ livestock farms ’ are good for 43% explained variance. The remaining four variables with a significant contribution in Table 2 add only 4%. Maize fields are usually spread heavily with slurry. The presence of maize fields, however, has only a slight effect on the presence of nitrophytes (Table 2). Perhaps only sources of ammonia with a continuous character have a clear effect, as maize fields are spread with slurry only once or twice a year. More important is the structure of the landscape. Very open ‘ windy ’ landscapes with only exposed trees yield more nitrophytes than landscapes with many hedges, bushes and ‘ hidden ’ rows of trees. In the last case the ammonia is probably spread over a lot of objects resulting in a dilution effect. An important cause of interference is the age of the trees. The NIW appears to be higher on young (slender) trees (see below). Nitrophytes (NIW) and acidophytes (AIW) appear to have oppositing behaviour (r= 0·64, P<0·0001). Thus, on trees with high NIW values, AIW values are usually low and vice versa. There are also other differences in behaviour between nitrophytes and acidophytes. Multiple regression shows that acidophytes are sensitive to both ammonia and ammonium (whereas nitrophytes react only to ammonia). This phenomenon is confirmed by field observations. At a lot of stations acidophytes (e.g. Hypogymnia physodes and Pseudevernia furfuracea) have disappeared on a large scale without any or only a small increase of nitrophytes. This is especially the case at some distance from the well-known areas with a high cattle density. (Fig. 3A) but within the areas for which a high ammonium deposition is calculated (Fig. 3B). This suggests that (at least some) acidophytes are not only sensitive to a rise of the pH, but also sensitive to an increase in the ammonium content of the bark. Competition with other lichens, for instance increasing nitrophytes, is in most cases not an important reason for their disappearance.
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Discussion The abundance of epiphytic nitrophytes can be used effectively to map spatial patterns of ammonia pollution. Lichens have the advantage that very detailed maps can be produced at relatively low costs. Only (expensive) direct measurement of the ammonia air concentration reveals comparable detailed information. At this moment permanent measurements are carried out at about 100 lichen monitoring stations by a Dutch institute for technical research (TNO). For this purpose special measuring tubes were developed, which can be suspended from a monitored tree. Once a month these tubes are collected and the mean ammonia concentration during the preceding month can be calculated. In the near future a comparison between lichen composition and these ammonia air concentrations will be carried out. These calculations are important for a further validation of the detailed patterns of ammonia pollution observed with nitrophytic lichens (Fig. 4). In other countries, on other substrata, or under other circumstances the occurrence of nitrophytes may be less obviously linked to nitrogenous emissions. The way in which nitrophytes react to the pH of the substratum means that the observations cannot be compared with the straight reaction of lichens to SO2. Interference from other factors, which might even be dominant must be considered. To avoid interference it is important to consider the influence of other factors such as climate, dust, the age of the trees, other pollutants, dogs, bark wounds, and salt spray. Each of these will be discussed. Climate is considered to be an important interfering factor. Within the Netherlands a slight shift in climatic conditions is evident, from dry in the South and East to slightly wetter near the coast and in the North. Some species are more drought resistant (Xanthoria parietina, Physcia adscendens), whereas other species are slightly more common in areas with higher precipitation (P. tenella, X. polycarpa). Within the area studied the effect of the climate as a whole is probably negligible on the NIW. However a slight shift along the Y-co-ordinate is apparent (Table 2), which might be due to climatic interference. Epiphytic nitrophytes also occur on the base of trees on calcareous soils, especially under dusty circumstances. As most of the soils in the Netherlands are non-calcareous and oligotrophic, dust is probably only a minor cause of interference in the area studied. In countries with a very dry climate, drought and dust might be dominant factors, preventing the use of nitrophytes as indicators of ammonia pollution. The age of the trees investigated appears to be important. Multiple regression shows that on old trees fewer nitrophytes occur than on young trees with the same NH3 pollution (Table 2). On young trees the NIW is about 0·7 NIW unit higher than on old trees. To avoid interference, trees with only slight differences in age should be compared. Nitrophytes are also common on trees polluted by dogs. In built-up areas it is sometimes difficult to find ‘ clean ’ trees. A practical solution might be not to use the base of trees since such pollution generally reaches no higher than 50 cm. Near bark wounds nitrophytes are also common, especially on Populus, Ulmus, Fraxinus, Acer and Fagus. Trees with bark wounds should be avoided.
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However, on Q. robur usually very few nitrophytes are to be found near bark wounds. Finally, salt spray causes some influence in coastal areas, but the effects seem to be restricted to a few kilometres along the coast. Table 2 shows that there appears to be no effect of SO2 on the NIW: in areas with a high SO2 concentration there is no ‘ deficit ’ of nitrophytes. If the (not significant) effect is calculated in a regression equation, the effect appears to be only 0·01 unit, thus negligible. It is surprising that SO2 levels have no effect on the spatial pattern of nitrophytes on oaks (NIWQu) in the Netherlands. At the moment the SO2 level is very low; even in the most polluted areas the concentration now rarely exceeds 30 ìg m 3. It is likely that SO2 is not limiting the occurrence of common nitrophytes any more. Furthermore no effect of SO2 on the pH of the bark of Q. robur could be traced (van Herk 1990). Even trees in the centre of cities with only Lecanora conizaeoides appeared to have the same pH as trees in large woods with lush Usnea (both pH 3·9). Only the effect of ammonia on the pH is apparent. However, the pH of tree species with neutral bark may be influenced by SO2 levels. A calculation carried out with Populus shows that this indeed seems to be the case. Multiple regression with SO2 and NH3 on NIWPo shows a just significant (but not dominant) effect of SO2 (van Herk 1997). A sensitivity scale based on separate species has not been used to estimate ammonia pollution, although clear differences in the species response exist (Fig. 2). It is obvious that in the area studied the total quantity of nitrophytes and acidophytes (NIW and AIW) at sampling sites are useful and sufficient indicators. The use of separate species as indicators of pollution zones has the disadvantage that a shift in response of a single species can disrupt the scale units. Such a shift could be caused by spatial differences of other pollutants, the climate or the ecology, as stated for X. parietina in connection with drought. I am grateful to Dr A. Aptroot and L. Spier for discussions on this subject and useful comments on the manuscript. Furthermore, I am grateful to the provincial administrations of Groningen, Friesland, Drenthe, Overijssel, Gelderland, Utrecht and Noord-Brabant for making this research possible and giving me the opportunity to publish this paper. R Aptroot, A. (1989) Veranderingen in de epifytenflora van de Provincie Utrecht over de periode 1984–1989. Utrecht: Provincie Utrecht. Aptroot, A. & van Herk, C. M. (1998) Lecanora barkmaneana, a new nitrophilous sorediate corticolous lichen from The Netherlands. Lichenologist 31: 3–8. Asman, W. A. H. & van Jaarsveld, J. A. (1990a) Gedrag van atmosferisch ammoniak. Proceedings Symposium Dierlijke Mest: Problemen en oplossingen. Den Haag: K. N. C. V. Asman, W. A. H. & van Jaarsveld, J. A. (1990b) A Variable-Resolution Statistical Transport Model Applied for Ammonia and Ammonium. RIVM report no. 228471007. Bilthoven. Barkman, J. J. (1958) Phytosociology and Ecology of Cryptogamic Epiphytes. Assen: Van Gorcum. Benfield, B. (1994) Impact of agriculture on epiphytic lichens at Plymtree, East Devon. Lichenologist 26: 91–96. de Bakker, A. J. (1987) Verslag van de herinventarisatie van Noord-Brabant en Limburg op epifytische lichenen in 1986. Buxbaumiella 20: 36–39. de Bakker, A. J. (1989) Monitoring van epifytische korstmossen in 1988. RIN-rapport 89/14: 1–53. Leersum: Rijksinstituut voor Natuurbeheer.
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de Bakker, A. J. & van Dobben, H. F. (1988) Effecten van ammoniakemissie op epifytische korstmossen, een correlatief onderzoek inde Peel. RIN-rapport 88/35: 1–48. Leersum: Rijksinstituut voor Natuurbeheer. de Wit, T. (1976) Epiphytic lichens and air pollution in The Netherlands. Bibliotheca Lichenologica 5: 1–115. Hoffmann, M. (1993) Verspreiding, Fytosociologie en Ecologie van Epifyten en Epifytengemeenschappen in Oost- en West-Vlaanderen. Proefschrift Universiteit Gent. van Dijk, H. W. J. (1988) Epifytische Kortstmossen, zure Regen en Ammoniak. Zwolle: Provincie Overijssel. van Dobben, H. F. (1991) Monitoring van epifytische korstmossen in 1989. RIN-rapport 91/8: 1–62. Leersum: Rijksinstituut voor Natuurbeheer. van Dobben, H. F. (1993) Vegetation as a monitor for deposition of nitrogen and acidity. Proefschrift RUU. Utrecht. van Dobben, H. F. & Wamelink, W. (1992) Effects of atmospheric chemistry and bark chemistry on epiphitic lichen vegetation in The Netherlands. RIN-rapport 92/23: 1–34. Wageningen: Instituut voor Bos- en Natuuronderzoek. van Herk, C. M. (1990) Epifytische Korstmossen in de Provincies Drenthe, Overijssel en Gelderland. Zwolle: Provincie Overijssel. van Herk, C. M. (1991) Korstmossen als Indicator voor zure Depositie, Basisrapport. Arnhem: Provincie Gelderland. van Herk, C. M. (1993) Korstmossen en zure Depositie in Drenthe en Friesland. Assen/Leeuwarden: Provincie Drenthe & Provincie Friesland. van Herk, C. M. (1995) Korstmossen en ammoniak. Buxbaumiella 36: 43–49. van Herk, C. M. (1996) Monitoring van Ammoniak en Zwaveldioxide met Korstmossen in de Provincie Utrecht. Soest: LON by order of Provincie Utrecht. van Herk, C. M. (1997) Monitoring van Ammoniak met Korstmossen in Zeeland. Soest: LON by order of Provincie Zeeland. van Herk, C. M. & Aptroot, A. (1996) Epifytische korstmossen komen weer terug. Natura 93: 130–132. van der Knaap, W. O. (1984) Epifyten in de provincie Utrecht 1979–1984. Buxbaumiella 16: 15–17. Accepted for publication 16 January 1998