Reconstructing pre-acidification pH for an acidified Scottish loch: A comparison of...

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Environmental Pollution 137 (2005) 135e149

www.elsevier.com/locate/envpol

Reconstructing pre-acidification pH for an acidified Scottish loch:A comparison of palaeolimnological and modelling approaches

R.W. Battarbeea,*, D.T. Monteitha, S. Jugginsb, C.D. Evansc,A. Jenkinsd, G.L. Simpsona

aEnvironmental Change Research Centre, University College London, London WC1H 0AP, UKbDepartment of Geography, University of School of Geography, Politics and Sociology, Newcastle University,

Newcastle upon Tyne NE1 7RU, UKcCentre for Ecology and Hydrology, Bangor, Gwynedd LL57 2UP, UK

dCentre for Ecology and Hydrology, Wallingford, Oxfordshire OX10 8BB, UK

Received 31 October 2004; accepted 17 December 2004

Methods of reconstructing pre-acidification pH for an acidified Scottish loch compared.

Abstract

We reconstruct the pre-acidification pH of the Round Loch of Glenhead for 1800 AD using three diatom-pH transfer functions

and a diatom-cladocera modern analogue technique (MAT), and compare these palaeo-data with hindcast data for the loch usingthe dynamic catchment acidification model MAGIC. We assess the accuracy of the transfer functions by comparing pH inferencesfrom contemporary sediment and sediment trap diatom samples from the lake with measured pH from the UK Acid WatersMonitoring Network. The results from the transfer functions estimate the pH in 1800 to have been between 5.5. and 5.7, the MAT

approach estimates pH at 5.8 and the MAGIC hindcast (for 1850) is pH 6.1. Whilst we have no independent method of assessingwhich of these values is most accurate, the disagreement between the two approaches indicates that further work is needed to resolvethe discrepancies.

� 2005 Published by Elsevier Ltd.

Keywords: Diatoms; Cladocera; Palaeolimnology; Modern analogue; Sediment traps; Lake acidification; Dynamic modelling; Monitoring; Lake

restoration; pH; Transfer functions

1. Introduction

Surface water acidification became a prominentenvironmental issue in Europe and North America inthe 1980s following observations of declining fish popu-lations in rivers and lakes in Scandinavia (Hesthagenand Hansen, 1991) and Canada (Beamish and Harvey,1972) coupled with claims that long-range transportedair pollutants, principally sulphur, were to blame (Oden,1968). Despite the detailed examination of alternative

* Corresponding author.

E-mail address: rbattarb@geog.ucl.ac.uk (R.W. Battarbee).

0269-7491/$ - see front matter � 2005 Published by Elsevier Ltd.

doi:10.1016/j.envpol.2004.12.021

hypotheses primarily related to the role of land-usechange (Rosenqvist, 1977, 1978; Krug and Frink, 1983),and natural acidification processes (Pennington, 1984),the evidence overwhelmingly supported the originalclaims (e.g. Mason, 1990). The key processes were wellsimulated by the MAGIC model (Cosby et al., 1985)and palaeolimnological studies provided the key spaceand time evidence for the ecological impact of aciddeposition (Battarbee et al., 1990; Charles et al., 1990;Cumming et al., 1992) to be recognised.

Following international agreements on S and Nabatement (LRTAP), and the newer demands in Europeof the EU Water Framework Directive (WFD), current

136 R.W. Battarbee et al. / Environmental Pollution 137 (2005) 135e149

research andmanagement interest focuses on remediationstrategy and recovery. Whilst this agenda looks to thefuture and principally requires the use of dynamicmodelling to evaluate the response of surface waters toacid deposition reduction, questions consequently ariserelated to (i) the reliability of themodels used in predictingthe behaviour of S and N in river and lake catchmentscurrently and in future, and (ii) the chemical andbiological conditions to be used as targets for restoration,whether these are expressed chemically in terms of pHandAcid Neutralising Capacity (ANC), or biologically interms of ecosystem structure/function and the presence/absence of key species or functional groups.

In this paper we restrict ourselves to chemistry as herewe are principally concerned with the relative accuracyof the different methods used for reconstructingbackground pH. The use of palaeolimnological techni-ques for assessing past biological status directly areconsidered elsewhere (Simpson et al., 2005, this issue).Consequently here we address how well we can definethe chemical restoration target for an acidified lake,assuming that this is equivalent to the pre-acidificationstatus (or reference state). Specifically, we examinehow our estimates of pH for the reference state varydepending on the transfer function or sediment core wechoose and how these values then compare with otherestimates of background pH using the modern analoguetechnique, an independent palaeolimnological ap-proach, and dynamic model hindcast. Comparingdynamic model output with palaeolimnological data isespecially important in cases where such a comparisonleads to model improvement.

There have been previous comparisons of diatom-inferred pH and dynamic model hindcasts usingMAGIC by Jenkins et al. (1990) and Sullivan et al.(1996). The Jenkins et al. (1990) paper specificallyaddressed the pH history of the Round Loch ofGlenhead, the site we focus on here. We are re-visitingthis comparison principally because the Round Lochof Glenhead is a key site in the UK Acid WatersMonitoring Network (see below) and because over thelast 15 years there have been some significant changes inour methods. In particular some aspects of the MAGICmodel have been re-configured and we now have bettermeans of assessing uncertainty in the palaeo-pH re-construction including the availability of alternativetraining sets for pH reconstruction, multiple cores fromthe loch that enable between-core comparisons, and,most crucially, the availability of a long-term instru-mental data-sets that can be used to validate thepalaeolimnological reconstructions.

Our approach is to use contemporary time-series data(pH and diatoms) from the loch from 1991 to thepresent day together with a large UK-wide spatialdataset, to evaluate the performance of a range of pHinference models. These are then used to estimate pre-

acidification (1800 AD) pH for the Round Loch ofGlenhead, and this is compared with the contemporarychemistry of sites which are biologically (diatoms andcladocera) most analogous to the loch at this time, usinga modern analogue technique (MAT; Simpson, 2004;Simpson et al., 2005, this issue). Finally, we makea comparison between these palaeolimnologically-basedestimates of past pH with hindcast values of pH usingthe MAGIC model.

2. Site details

Details of the loch and its catchment are given inPatrick et al. (1991), Monteith and Evans (2005, thisissue) and elsewhere in this issue. Briefly, the loch covers12.5 ha and is located at 295 masl in the Galloway Hillsof south-west Scotland. It has a single basin anda maximum depth of 13.5 m. It is naturally acidic(Jones et al., 1989) but suffered further acidification asa result of acid deposition from the mid-nineteenthcentury through to the 1980s (Flower and Battarbee,1983). A slight increase in pH has occurred since then(Battarbee et al., 1988; Allott et al., 1992; Harrimanet al., 2001; Evans and Monteith, 2001; Davies et al.,2005, this issue) to its current value of about 5.1.

The Round Loch of Glenhead has played a key rolein UK acid waters research for over 25 years. It was firstsampled for water chemistry in 1978 by Harriman(Harriman, personal communication) and first cored fordiatom analysis by Battarbee in May 1981 (Flower andBattarbee, 1983, core RLGH 81). Since 1978, monitor-ing of water chemistry was conducted on an irregularbasis (e.g. Wright and Henriksen, 1980; Flower et al.,1987) until 1988 when the loch was included in theAWMN. Consequently, annual biological data forepilithic diatoms, macro-invertebrates, aquatic macro-phytes and fish (in the outflow stream only) are now alsoavailable, while annual samples of diatoms in sedimenttraps have been collected since 1991. Palaeolimnologicalresearch has also continued at the site especially withrespect to long term post-glacial acidification history(Jones et al., 1986, 1989) and with respect to evidence forrecovery (Allott et al., 1992).

3. Methods

The data used in this paper are derived from severaldifferent sources, principally the chemical and biologicaldata from the AWMN from 1988 onwards (Monteithand Evans, 2005, this issue), the data from the diatomanalysis of cores taken in 1981 (RLGH 81, Flower andBattarbee, 1983), 1984 (RLGH 3, Jones et al., 1989) and1989 (K05, Allott et al., 1992), the data used in analogue

137R.W. Battarbee et al. / Environmental Pollution 137 (2005) 135e149

matching (Simpson, 2004; Simpson et al., 2005, thisissue) and the output from the dynamic model MAGIC.

3.1. Chemical data

The AWMN was used to supply water chemistry datafrom 1988 to the present day (2003). Measurements weremade on a quarterly basis on samples taken from theoutflow. The principal methods conform with thosedescribed by Monteith and Evans (2005, this issue),while Acid Neutralising Capacity has been determinedaccording to the method described by Evans et al. (2001)and Davies et al. (2005, this issue).

In addition, diatom data from the annually exposedAWMN sediment trap samples (from 1991e2002) wereused to infer pH using different statistical modelsdescribed below.

3.2. Diatom data

Epilithic diatom samples were collected each summer,between June and August, from three fixed locationsaround the loch shore. Each sample comprises the algalgrowth on the upper surfaces of 3e5 cobble-sized stonesremoved from a water depth of ca. 0.5 m. All sampleswere preserved using Lugol’s iodine. 300 diatomindividuals were counted and identified to species levelin each sample, using phase contrast microscopy anda !100 oil immersion objective, providing a magnifica-tion of !1000.

Diatom analysis of the sediment cores RLGH 81,RLGH 3 and KO5 is described in Flower and Battarbee(1983), Jones et al. (1989), Allott et al. (1992) and Jugginset al. (1996). Sediment trap samples were collectedannually between 1991e2002 and diatom assemblageswere analysed using the same techniques describedabove. While the numerical data presented here arecalculated as the percentage of all taxa found in eachsample, only data for the most abundant taxa are shown.

3.3. Diatom-inferred pH

Diatom-inferred pH values were generated usingthree different transfer functions based on (i) the SWAPtraining set, representing 138 acid-sensitive lakes fromacross the UK and Scandinavia, using weightedaveraging with inverse deshrinking (Stevenson et al.,1991); (ii) a 163-sample UK acid waters training set(Simpson, 2004) using a 2-component weighted averag-ing partial least squares model; and (iii) a Europeantraining set of 693 samples derived form the EuropeanDiatom Database EDDI (Battarbee et al., 2000, http://craticula.ncl.ac.uk). Because of the large size of thelatter we are able to use a dynamic approach that createsa weighted-averaging transfer function based on the 50closest analogues to each sediment sample assemblage.

In order to test the accuracy of these models wecompared:

(a) the pH reconstructions of surface sediments of118 soft water UK lakes against measured modernwater column pH for each site;(b) the minimum inferred pH values, as representedby the upper levels of the three sediment cores,against the earliest (and lowest) pH measurements,made between 1978 and 1982;(c) the pH reconstructions of annually collectedsediment trap samples against measured pH for theRound Loch of Glenhead from 1991e2002.

As a final test of the suitability of the three trainingsets we compared the floristic similarity of the diatomassemblages in each sample from core K05 against thoseused to generate the pH reconstructions, using a chi-square dissimilarity function.

3.4. Analogue matching using diatoms and cladocera

A second palaeolimnological technique used to inferpre-acidification values of pH was analogue matchingusing the method developed by Simpson (2004; Simpsonet al., 2005, this issue). In this approach a squared-chorddistance statistic was used to identify lakes from a largecontemporary training set of acid-sensitive lakes thathave chemical and biological characteristics most similarto the pre-acidification status of the acidified lake (i.e.the Round Loch of Glenhead). For the RLGH thematch has been made between the species compositionof diatoms and cladocera in the sediment correspondingapproximately to the year 1800 in core K05 and thesurface sediments of the UK acid waters training set(Simpson et al., 2005, this issue).

3.5. pH reconstruction using MAGIC

The MAGIC model simulates soil solution andsurface water chemistry to predict the monthly andannual average concentrations of the major ions in lakesand streams (Cosby et al., 2001). In this study theapplication utilised detailed soil information (Jenkinsand Cullen, 1999) and was calibrated to match theobserved water chemistry reported for the site within theAWMN. Because of the annual variation in chemistrythe calibration target was calculated as the mean of thefirst five years of data (1988e1992), a period in which notrend was observed. Deposition chemistry from thenearest located deposition collector in the UK AcidDeposition Monitoring Network (Jenkins et al., 1998)was used to drive the model from 1988 to 2002. Becausethe deposition collector is not directly co-located at themonitoring site and since wet deposition does notaccurately reflect dry and occult deposition inputs, the

annual wet deposition concentrations at each site werecorrected to match the observed Cl� and SO4

2� insurface water. This is calculated for the five-year meandata used in the initial calibration and the sameadjustment is then applied to the marine ions andSO4

2� for each year of record. The historical (pre-1988)deposition sequences for SO4

2�, NO3� and NH4

C areestimated by scaling currently observed deposition toreconstructions of S emissions (Warren Spring Labora-tory, 1983) and N emissions (Wright et al., 1998). Allother ions in deposition are assumed to remain constantthroughout the simulation. Soil water DOC concentra-tion and surface water CO2 partial pressure were set at40 mg l�1 and 2 atmospheres, respectively.

4. Results

4.1. Water chemistry for the RLGH

Fig. 1 shows time series for some key chemicaldeterminands over the 1988e2003 period. While nitrateconcentrations have remained relatively constant sul-phate concentrations have fallen substantially since1996. pH and ANC show strong seasonality, with themost acidic samples normally occurring during winter,as a result of higher precipitation and increased seasaltinputs at this time. Between 1990e1995, a period wherethere is no chemical trend, mean March pH and ANCwere, 4.8 and �11 meq l�1 respectively, as comparedwith 5.1 and 6 meq l�1 for September samples. Since1996 there is evidence for an increase in both variableswhich broadly follows the decline in sulphate. The trend

0102030405060708090

I -1pH

1988 1990 1992 1994 1996 1998 2000 2002

Fig. 1. Water chemistry time series for the Round Loch of Glenhead

(June 1988eMarch 2003). Non-marine sulphate concentration (filled

circles), nitrate concentration (open circles) and pH (squares).

in both pH and ANC, over the entire period ofmonitoring (1988e2003), are statistically significantaccording to the Seasonal Kendal Test (Davies et al.,2005, this issue).

4.2. Diatom compositional changes

4.2.1. Contemporary diatomsThe diatom flora of the Round Loch of Glenhead has

been extensively studied since the first samples weretaken in 1981. The flora comprises taxa typical ofepilithic, epipsammic, epiphytic and epipelic communi-ties in acid waters, and over the period of recentsampling there have been no planktonic diatomsrecorded. A comparison of the epilithic flora withsediment samples by Jones and Flower (1986) showedthat taxa dominant in the surface sediment microfossilassemblage, principally Eunotia incisa, Tabellaria quad-riseptata, and Frustulia rhomboides var. saxonica, werethe same as those dominant in the epilithon andconcluded that the epilithon contributed more diatomsto the sediment assemblage than other habitats.Consequently, the epilithic flora has been used fordiatom monitoring in the AWMN, and has beensampled systematically since 1988 (Fig. 2). Again,comparison with diatoms from sediment trap samples(cf. Fig. 3), show a strong similarity with the epilithon,reinforcing the conclusions of Jones and Flower (1986).The exception is the higher percentage of Naviculahoefleri in the sediment trap samples, probably derivedfrom the epipelon rather than the epilithon. Since 1996there has been a gradual reduction in the relativeabundance of T. quadriseptata in the epilithon, and anincrease in Navicula leptostriata. This probably reflectsthe gradual improvement in water chemistry describedabove related to national scale reductions in S de-position over the same time period (Fowler et al., 2005,this issue; Cooper et al., 2005, this issue) and isevident despite the fact that linear change in speciescomposition as a whole over the 1988e2002 period isnot statistically significant (Monteith and Evans, 2005,this issue).

4.2.2. Diatoms from sediment trap samples(1991e2002) and from core K05

Changes in the composition of diatom assemblagescollected in the sediment traps from 1991 to 2002 areshown in Fig. 3 together, for comparison, with diatomsfrom the K05 core. Only the dominant taxa are shown.The composition of the diatom assemblages from thetraps in the early part of the trap sequence is almostidentical to that of the uppermost sediment from thesediment cores indicating that the trapped material andthe sediment core material are directly comparable, andthat the traps are not receiving resuspended sedimentcontaining diatoms from an earlier period to any

1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

20Navicula leptostriata

0Eunotia vanheurckii var. intermedia0Navicula subtilissima0

20Tabellaria flocculosa

0Tabellaria binalis0Peronia fibula0

20Eunotia naegelii

0Eunotia sp.0Eunotia denticulata0

20Frustulia rhomboides var. saxonica

0Brachysira serians0Navicula mediocris0

20Tabellaria binalis f. elliptica

Eunotia incisa

20Brachysira brebissonii

20Navicula cumbriensis

0Achnanthes marginulata0

Tabellaria quadriseptata

0Navicula hoefleri0

20Eunotia rhomboidea

0Eunotia [sp. 10 (minima)]0

20Synedra sp.

0Eunotia vanheurckii0

20Eunotia [vanheurckii var. 1]

0Eunotia pectinalis var. minor

Fig. 2. Percentage species composition of epilithic diatoms sampled each summer between 1988 and 2002. Data for each year represent samples from

three locations around the lake shoreline taken on a single site visit.

noticeable degree. The only apparent discrepancy is thatthe early trap samples contain slightly higher (circa 5%)abundances of T. quadriseptata than in the core top. Interms of recent trends there is relatively little changeover time although there is a general decrease inT. quadriseptata and an increase in N. leptostriata whichmatch the observed changes in the epilithon. There is,however, little evidence for increases in any specieswhich were abundant prior to the later stages ofacidification during the 20th century such as Brachysiravitrea and Tabellaria flocculosa.

4.2.3. Diatom assemblages for three sediment coresFig. 4 shows summary diatom diagrams for the three

independently dated cores that have been taken fromapproximately the deepest point in the loch (circa.13 m), in 1981, 1984, and 1988 respectively. They differin length and the period of time covered, but in all casesgo back well before the beginning of the period of rapidacidification that dates to the mid to late nineteenthcentury (Flower and Battarbee, 1983).

Whilst the comparison between the core data,sediment trap data and diatom epilithon presented above

0102030

Brachysira brebissonii

Brachysira vitrea

Eunotia incisa

Eunotia naegelii

Navicula hoefleri

Tabellaria binalis

Navicula leptostriata

Tabellaria quadriseptata

Frustulia rhomboides var. saxonica

Tabellaria flocculosa

core K05 traps

Fig. 3. Percentage species composition of diatoms in a 210Pb dated sediment core (K05) taken in 1989 and in annually retrieved sediment trap samples

(1991e2002) from the Round Loch of Glenhead.

indicates how well the fossil diatom record reflectsobserved changes, we compare these three cores toillustrate how variable the sediment record is itself.Again, the rarer taxa are not shown but it is clear that thechanges in the relative abundance of dominant taxathrough time between cores are all but identical witha switch between the Brachysira vitrea-dominated assem-

blage of the mid-nineteenth century being replaced bya T. quadriseptata-dominated assemblage of the presentday. Peak abundances ofT. quadriseptata at the top of thecores are consistently slightly lower than in the earlysediment trap samples. The only substantial differencebetween the three cores is the apparent under-represen-tation of Eunotia naegelli in the 1981 core (RLGH 81).

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tissim

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0 20 0 0 0 20 20 0 20 20 0 0 0 20

% Frequency

Fig. 4. A comparison of diatom percentage species composition in three 210Pb dated sediment cores (RLGH 81, RLGH 3 and K05) taken in 1981,

1984 and 1989 respectively from the Round Loch of Glenhead.

4.3. pH transfer functions

We compare the performance of the three trainingsets in two different ways, spatially from a comparisonof core top inferred pH with measured pH for 118 lakesacross the UK, and temporally against measured pH forthe Round Loch of Glenhead itself.

Fig. 5 shows the results of the reconstructions usingthe 118 lake dataset. All three methods perform well,

with high squared correlation between observed andinferred values (0.79, 0.83 and 0.88 for SWAP, UK, andEDDI transfer functions respectively), although the rootmean squared error of prediction (RMSEP, cf. Birkset al., 1990) is significantly lower for EDDI (0.25compared to 0.31 and 0.38 for UK and SWAPrespectively). In this test, therefore, EDDI perfoms best.The complete EDDI training set contains a much largernumber of surface samples (693) than SWAP (174) or

Measured pH4.0 4.5 5.0 5.5 6.0 6.5 7.0

Fig. 5. Scatterplot comparisons of diatom inferred pH against measured pH for 118 UK soft water lakes using three transfer functions based on: (a)

the SWAP training set e weighted averaging and inverse deshrinking (SWAP); (b) a UK acid waters set e 2 component weighted averaging partial

least squares model (UK); and, (c) a dynamic training set based on 50 lakes (selected for each sample) drawn from 693 samples from the EDDI

database e optimised weighted averaging model (EDDI).

UK (163) and is derived from a wider geographical area.Consequently, the process of selecting a dynamictraining set based on a subset of 50 samples that aremost similar to a fossil sample, in diatom compositionalterms, is able to take advantage of the greater floristicand chemical diversity offered by this dataset, thusavoiding the increased errors associated with the fittingof a single ‘‘universal’’ model to such a large andheterogeneous training set.

The performance of the three transfer functionsagainst measured pH for the Round Loch of Glenheaddata is illustrated in Figs. 6 and 7. Fig. 6 shows pHreconstructions for the three sediment cores (cf. Fig. 3).The upper levels of these can be compared with theearliest pre-AWMN pH measurements from the loch in1978 and 1979 (Harriman, personal communication,Wright and Henriksen, 1980) and 1980e1981 (Floweret al., 1987), which range from pH 4.5 to 4.86 (mean4.70). Reconstructed pH for this period for the earliestcore, RL81 (Fig. 6a), is about 0.1 pH units higher thanfor the other cores. For cores RL3 (Fig. 6b) and K05(Fig. 6c) the lowest reconstructed pH in the uppermostcore samples (representing the late 1970s) using theSWAP model is approximately 0.1 pH unit higher thanthe measured mean pH, while the EDDI and UKmodels for the same samples are approximately 0.1 pHunits higher than the SWAP estimate. In this respect,therefore, SWAP provides the best agreement with theinstrumental record for the most acidic period in theloch’s history.

Fig. 7 shows a comparison of measured pH (seasonaldata and annual means) and diatom-inferred pH from1991 to 2002 from sediment trap samples. The UK andEDDI reconstructions almost invariably fall within theannual range of pH measurements and in most years arewithin 0.1 pH units of the annual mean. EDDI mostclosely approximates the annual measured mean but ispoorest of the three in matching interannual variability;

importantly it is the only model not to show the upwardtrend which is evident in the measured data. The SWAP-based reconstruction systematically under-estimatesmeasured mean pH by approximately 0.2 pH unitsand usually falls slightly beneath the minimum annualvalue (mostly representing March samples), but doesfollow the upward trend.

1800 1850 1900 1950 2000

Fig. 6. pH reconstructions according to the three models: SWAP (open

squares); EDDI (triangles); UK (filled circles), for the three 210Pb

dated sediment cores: (a) RL81; (b) RL3; (c) K05 from the Round

Loch of Glenhead. The minimum measured annual mean pH for the

site (pH 4.7 for 1979) is indicated by the thickened line in each plot.

Fig. 8 provides a comparison of inferred pH for thethree models and three different seasonal averages ofpH, annual mean pH (SeptembereJune); the Decemberto June average and the MarcheJune average. Thissupports the above observations in that, although theEDDI reconstructions fall close to the 1:1 line, there islittle evidence of linearity with the measured chemistry.SWAP does show some linearity but tends to un-derestimate. The best agreement overall is for the UKmodel, in particular when compared against theDecembereJune average measured pH.

A comparison of chi-squared dissimilarity coefficientsfor the samples used in the three models against theRLGH K05 core samples is presented in Fig. 9. Theresults show that there are close analogues in all trainingsets for all the sediment core samples, but that EDDIperforms somewhat better than the other two, especiallyfor samples from the late nineteenth and early twentiethcentury (Fig. 9). Most importantly, however, there is

1990 1992 1994 1996 1998 2000 2002

Fig. 7. Round Loch of Glenhead time series of quarterly outflow pH

(March (filled squares); June (open circles); September (open

diamonds); December (filled diamonds)) mean annual pH (dotted

line), and diatom inferred pH of annually retrieved sediment trap

samples (1991e2002) according to the three transfer functions (SWAP

(open squares); UK (closed circles); EDDI (open triangles)).

little difference in coefficients for circa 1850, when in allcases these are relatively high, indicating a relativelypoor selection of analogues.

4.4. Establishing pre-acidification pH for the RLGH

Having assessed the performance of the differenttraining sets in reproducing measured pH we now usethese techniques to estimate the pH of the Round Lochof Glenhead for the period before the loch’s acidifica-tion, taken here to be approximately 1800 AD. We thencompare these estimates with the contemporary chem-istry of sites deemed to be biologically most analogouswith the pre-acidification state of the loch, using theMAT technique, and then with estimates from MAGICmodel simulations.

4.4.1. pH reconstruction for three cores from theRound Loch of Glenhead using all three training sets

Not surprisingly, given the similarity in their diatomassemblages (cf. Fig. 3), the reconstructed pH valuesand trends are quite similar between cores. All threecores show progressive acidification from the late 1800sto the 1970s after which the trends flatten out. The 1981and 1984 cores were perhaps taken too early to indicatechemical recovery. The 1988 core, however, shows someevidence of a recent rise in diatom-inferred pH, with the

19001850 1950 2000Age

Fig. 9. Time series of chi-squared dissimilarity coefficient between

samples from core KO5 and those used in the three models, SWAP,

UK and EDDI, defined in Fig. 5.

September−June mean pH

5.25.15.04.94.84.7

December−June mean pH

5.25.15.04.94.84.7

March−June mean pH

5.25.15.04.94.84.7

Fig. 8. Comparison of diatom inferred pH from sediment trap samples according to three models (SWAP (open squares); UK (closed circles); EDDI

(open triangles) and three seasonal averages of measured pH (a) SeptembereJune; (b) DecembereJune; (c) MarcheJune). Diagonal line represents

1:1 relationship.

last four samples (post 1982) showing a progressiveupward trend in inferred pH according to UK andSWAP but not EDDI.

The slight differences between the cores through timereflect the between core differences in diatom assem-blage described above. In this case there is morevariation observed between training sets than betweencores, due mainly to the systematically lower valuesfrom the use of the SWAP training set.

4.4.2. Contemporary pH of lakes biologicallyanalogous to the pre-acidification state of theRound Loch of Glenhead, according to MAT

In this analysis nine good analogues (squared chorddistance !0.475) were found and these are listed inTable 1 together with their modern pH. The meanannual pH for these sites ranges from 5.55e6.30(squared chord distance weighted averageZ5.82). Thesedata are also plotted in Fig. 10 to provide a directcomparison with pH reconstructions. Importantly, pre-acidification pH inferred by SWAP in all three coresfalls slightly beneath the range of modern annual pH ofthis range of all the analogues, while the EDDI pHinferences fall within the range of the three most acidicof these. The UK pre-acidification reconstructions arethe highest of the three models and fall approximately0.1e0.2 pH units below the weighted average pH whichwe may use as a MAT ‘‘best-estimate’’.

4.4.3. MAGICThe longer term aim of this study is to assess the

degree of concordance between palaeo data andMAGIC model reconstructions of historic changes inacidity. Clearly, good agreement between the differentapproaches would increase confidence in both, whilstmismatches would suggest problems with one or bothtechniques. Since MAGIC is also used to predict future

Table 1

The nine lakes in the UK acid waters training set with modern

sediment diatom and cladoceran assemblages similar to those of pre-

acidification sediment from the Round Loch of Glenhead (squared

chord distance !0.475)

Analogue site UK grid

reference

Squared chord

distance

Mean pH

Loch Nan Eion NG 925508 0.387 5.74

Lochan an Dubha NC 147055 0.388 5.62

Loch Clair NG 999574 0.407 6.13

Lochan Lairig Cheile NN 558278 0.411 5.92

Loch Doilet NM 808678 0.441 5.77

Loch Laidon NN 380542 0.455 5.79

Llyn Hir SN 789675 0.469 5.55

Loch a Cham Alltain NC 283446 0.474 5.60

Loch Coire

Nan Arr

NG 808422 0.474 6.30

Weighted average pH 5.82

Mean pH represents four quarterly samples.

change, good agreement between the two hindcastswould also provide increased confidence in MAGICforecasts. The MAGIC model was applied to RoundLoch using standard calibration procedures described inSection 3.5, and key parameters set to ‘best estimates’for the UK (Evans et al., 2001).

For the Round Loch of Glenhead (Fig. 10) theMAGIC data closely match the observed concentrations(1988e2002) of all ions and are in agreement with theobserved declining trend in lake water SO4

2� concentra-tion (Cooper and Jenkins, 2003). Further the modelsatisfactorily replicates the earliest pH measurements, ofaround pH 4.7, made in the late 1970s (see above).However, discrepancies between the diatom-inferredreconstructions and with the pH of the biologicalanalogue sites are apparent. MAGIC generates greaterextremes, both for the period of peak S deposition (circa1970e1980) and the pre-acidification period.

For the peak deposition period the observed dataclearly show that MAGIC provides a better pH modelfor this site than the diatom-based reconstructionsalthough there is better agreement with SWAP thanfor UK and EDDI. However, MAGIC should beexpected to perform well, at least in reproducingconditions between 1988 and 1992, as the model iscalibrated using data from this five year period.

The MAGIC loch water pH reconstruction for 1850of 6.1 is higher than the diatom-inferred values for thepre-acidification period compared with both the transferfunction (pH 5.50 to 5.70) and the weighted average pHof the biological analogues (5.82), although it lies withinthe range of analogue values (pH 5.55 to 6.33). In the

1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1990

Fig. 10. Comparison of pH reconstruction outputs and annual

measured pH. Chronology of diatom inferred pH according to SWAP,

UK and EDDI models (fine lines) for 210Pb dated samples from three

sediment cores (RLGH 81, RLGH 3 and K05). The RMSEP of the

SWAP, UK and EDDI training sets are 0.38, 0.31, and 0.25 pH units

respectively. Modern annual pH of nine lakes providing the strongest

biological analogues for a pre-acidification (circa 1800) sediment

sample (open triangles) and the weighted average of these (filled

triangle). MAGIC model pH reconstruction (open circles) and mean

annual average pH for the period 1988e2000 and the year 1979 (open

squares).

absence of direct measurements for 1850 there is no wayof knowing which is the most accurate, especially giventhe statistical uncertainties of the reconstructions (e.g.about G0.25 pH units (cf. Birks et al., 1990)). However,the apparently high MAGIC estimate relative to diatomreconstructions at this site is matched by relatively highmodel-based estimates at a number of other sites in theAWMN (unpublished data) indicating that the MAGICvalues may consistently predict higher background pHthan the palaeo-reconstructions. Similar observationshave also been made elsewhere (e.g. Sullivan et al.,1996).

5. Discussion

In this paper we investigate the extent of agreement intechniques needed both to establish pre-acidificationreference conditions for the Round Loch of Glenheadand set restoration targets for future recovery. Theexercise requires a combination of approaches usingpalaeolimnological techniques for past reconstruction,dynamic modelling for future prediction and regularcontemporary monitoring to provide data not only onpresent day status but also to calibrate and verify themodels.

5.1. Contemporary data

Water chemistry data provided by the AWMN showvariability from year to year but also a gradual butdistinct increase in measured pH since 1996 which isconcomitant with declines in S deposition and surfacewater concentration, and reflects falling S emissionlevels. Gradual change in the epilithic diatom flora overthe same period indicates improvement in the ecologicalstatus of the loch in recent times. Key questions now arewhether such improvement will be sustained, what arethe chemical and biological characteristics of a fullyrestored lake, and how can we use a knowledge of thepre-acidification status of the loch for reference.

5.2. Using sediment cores to establish pastecological conditions

The use of sediment cores to reconstruct pastecological conditions for acidified waters is very wellestablished (e.g. Battarbee et al., 1990; Charles et al.,1990), although the method has a number of uncertain-ties associated principally with the faithfulness of thefossil record and with the accuracy of sediment coredating. For acid waters, however, diatom preservationis usually excellent and the comparisons presented herefor the Round Loch between the modern epilithic flora,the sediment trap assemblages and the core top as-semblages demonstrate a close correspondence between

the composition of the living and fossil assemblages thatsupport this observation. The only exception here is theslightly elevated abundance of T. quadriseptata found inthe early sediment trap samples relative to the top of thesediment cores which is the probable cause of thedifference in inferred pH of approximately 0.1 pH units.As the state of diatom preservation at this site is alsoexcellent down-core we can assume that these relation-ships hold true for earlier periods. Moreover, a compar-ison of the three sediment cores taken independently in1981, 1984 and 1989 show that variability between coresis not a significant source of uncertainty. Consequentlythe composition of the loch diatom flora in 1800, priorto acidification, can be very confidently inferred fromthe sediment record, and used as a restoration target fordiatom recovery in the future. Quite simply, the diatomtarget would be the replacement of T. quadriseptata byB. vitrea as the most abundant species (cf. Fig. 4). Here,however, we are concerned not with biological targetsbut with chemical ones, specifically how well we caninfer the pH in 1800 using the diatom record.

5.3. Comparing transfer function performance

Converting the biological record from sediment coresinto past hydrochemical data requires the use of transferfunctions or similar statistical models. Considerableeffort has been applied in the determination of statisticaluncertainties in these models with respect to theirprecision, using a variety of permutation testingtechniques (cf. Birks et al., 1990). However, lessemphasis has been placed on their accuracy, an attributethat is crucial in current debates on reference conditionsand restoration targets. Here we have attempted toidentify the best methodology for pH reconstruction bycomparing both the degree of floristic similarity betweensamples used in the models and those being recon-structed, and the performance of three different trainingsets with respect to temporal and spatial comparisonswith measured chemistry.

The evidence from the comparison of RMSEPs forthe relationship between inferred and measured pHfor the 118 sites suggests that of the three transferfunctions the SWAP method is least accurate witha tendency to underestimate throughout the pH range.The EDDI method performs best here, a not unexpectedresult as the method draws upon a very large data-set of693 sites with a wide range of pH and lake type.However, there is an indication of bias in inferred pHacross the measured pH gradient in comparison with theUK method with a tendency to over-predict in the rangepH 4.5e5.2 and under-predict in the range 5.8e6.5.These are the most relevant ranges in assessing thecurrent and pre-acidification status of the Round Lochof Glenhead. Consequently, as the UK dataset has less

bias it may be more accurate than EDDI in predictingthe background pH for the Round Loch, despite itspoorer RMSEP.

Comparison of the diatom-inferred pH of thesediment trap samples with measured pH supports theobservation above of a tendency for the SWAP model tounder-predict pH. The EDDI and UK reconstructionsalways fall within the annual range of measurements,with the exception of 2001 when no March sample(normally the most acidic of the year) was taken. Bothreconstructions normally fall within 0.1 pH of theannual mean, although the UK model is better atreplicating inter-annual variability.

Comparison between EDDI and UK diatom-inferredpH values toward the top of the most recently takensediment core (K05) and the early sediment trap samplesreveals a slight discrepancy as the trap samples tend toreconstruct at a slightly lower pH (about 0.1 unit). Thisis probably caused by the relatively high abundance ofT. quadriseptata in the trap samples and may at least inpart reflect differences in depositional environments ofthe traps and the loch bottom. However, there is notemporal overlap between these two sources, and there isevidence for a slight decline in pH from 1987 to 1991(see longer term datasets in Monteith and Evans, 2000).

Comparisons between the sediment core tops and theearliest pH measurements reveal a more significantdiscrepancy. At this time in the early 1980s pH averagedabout 4.7 yet reconstructions for the tops of all threecores using the EDDI and UK methods do not fallmuch lower than pH 4.9. This difference most likelyreflects a relative lack of very acidic sites in the EDDIand UK databases which results in an over-estimate ofthe pH optima of the most acid-tolerant species used inthese models. This supposition is supported by Fig. 5b,c,which indicate a positive bias at very low pH.

5.4. Comparing transfer function and analoguematching approaches

The technique of modern analogue matching (MAT)was pioneered in palynology and palaeoceanography(Overpeck et al., 1985; Prell, 1985) and introduced intopalaeolimnology by Flower et al. (1997). In the Floweret al. (1997) study diatom assemblages were used foranalogue matching. This approach was only partiallysuccessful as some potential analogue sites were deemedinappropriate due to their high base cation concentra-tion, a finding that suggested that diatoms were goodindicators of pH but not necessarily of base cations. In amodification of this approach Simpson (2004) repeatedthe exercise but added more sites to the contemporarydata set and included Cladocera as a second biologicalgroup to further constrain the matching routine. Thesuccess of this study now enables this approach to beused more confidently, and can potentially be used to

hindcast a full range of chemical variables includingANC, calcium (Ca), dissolved organic carbon (DOC), aswell as pH.

Comparing pH inferred for the Round Loch ofGlenhead in 1800 using MAT with the diatom-pHtransfer function results reveals further discrepancies.MAT identifies nine good analogues for the 1800reference sample and these give a weighted average pHof 5.82, a value higher than any of the transfer functionbased methods. However, this is not unexpected at leastfor the SWAP-based reconstructions as this methodclearly under-estimates measured pH in most circum-stances. For EDDI some of the mismatch can beexplained by the tendency of this method to show biasto lower values in this pH range (discussed above). Theclosest match to the MAT value is provided by the UKtraining set method which gives pH 5.66, 5.60 and 5.69for the RL81, RL3 and K05 cores respectively, approx-imately 0.1e0.2 pH unit below the MAT best estimate.

5.5. Comparisons between diatom reconstructionsand MAGIC

The MAGIC reconstruction of pH for the RoundLoch of Glenhead shows a number of differences withthe palaeo reconstructions. It predicts more acidicconditions during the peak sulphur deposition periodand more alkaline pre-acidification conditions (taken as1850 AD). MAGIC is more successful in replicatingrecent chemistry, although this is unsurprising since themodel is calibrated using contemporary data from theloch itself, whereas the diatom data are calibrated usingdata external to the site. Assessing the likely accuracy ofthe pre-acidification MAGIC predictions is moredifficult, although the discrepancies between the palaeodata and the model data highlight the need to assessuncertainty in all methods.

On the basis of the comparisons (Fig. 10) theMAGIC pre-acidification hindcast of pH 6.1 is 0.3 pHunits higher than MAT and up to 0.5 pH units higherthan some of the EDDI and UK-based reconstructions,clearly outside the RMSEP of both those methods. Twoof the nine biological analogues exhibit modern meanannual pH between 6.1 and 6.3 but the pH of themajority of sites (nZ5) range between 5.6 and 5.8, whilethe weighted average of the nine sites is 5.82.

Uncertainties in the application of the MAGICmodel for present and future prediction stem mainlyfrom the extrapolation of spatial and time-series databecause the model is a lumped representation ofa catchment, and detailed physico-chemical data rarelyexist at the required scale. However, uncertainties inreconstructing past background chemistry have gener-ally received less attention, but are in some respectsgreater due to the sensitivity of background chemistry toweak acid concentrations in the absence of strong acids.

Particular uncertainties are associated with soil waterDOC concentrations (surface water concentrations aregenerally measured) and soil and surface water partialpressures of CO2. Fully exploring these uncertainties isbeyond the remit of this paper although sensitivity testsusing different coefficients for lake pCO2 and soil waterDOC (Evans, unpublished) demonstrate that both lowersoil water DOC concentration and higher lake pCO2

cause lower background pH which is more consistentwith the diatom reconstruction. A further explanationfor the mismatch may be related to holding DOC in themodel at a constant concentration through time. Thereis increasing evidence to suggest that the recent, widelyobserved increase in DOC concentrations in surfacewaters (Evans and Monteith, 2001) is, to some extent,linked to falling sulphur deposition levels, perhapsthrough changes in soil acidity or the ionic strength ofdeposition, (Evans et al., 2005, this issue). Soil DOCconcentrations may, therefore, have been considerablyhigher in the pre-acidification period than they wereover the period of the model calibration. Were this to bethe case, some degree of over-estimate of pH byMAGIC is inevitable. Investigations over the possiblemechanisms linking deposition and DOC concentrationare continuing and as yet we do not have sufficient datato allow any quantification of this relationship.

6. Conclusions

The Round Loch of Glenhead is an acidified uplandlake in south-west Scotland, typical of many in the UK.As a result of reductions in sulphur emissions over thelast decade a recovery process appears to be underway.We can now ask what chemical and biological charac-teristics we should expect for a fully restored lake andwhether current emission reduction plans, all thingsbeing equal, are adequate to allow such restorationtargets to be achieved. To answer these questions weneed to assess the validity and accuracy of the palaeo-techniques we use to define pre-acidification referenceconditions, and the accuracy of the dynamic models (inthis case MAGIC) used both to reconstruct pastconditions, and to predict the timing and extent offuture recovery.

Comparison of different diatom-pH transfer func-tions against instrumental pH data both in space and,for the Round Loch of Glenhead, in time, highlight thestrengths and weaknesses of the different methods usedbut all indicate that the pre-acidification pH (for 1800AD) was between 5.5 and 5.7, slightly more acidic thanthe 5.8 value derived from the modern analogue method(using a combined data set of diatoms and cladocera)and substantially more acidic than the pH 6.1 valueprovided by the MAGIC model hindcast. Althoughthere is no way to ascertain which estimate is the most

accurate, possible reasons for discrepancies may beidentified for each approach. For MAGIC, one possibleexplanation is that DOC concentrations in catchmentsoils may have been higher in the past, a condition notcurrently included in the model. However, not enoughis known about the relationship between sulphurdeposition and soil water DOC concentration for theprocess to be reliably incorporated at this stage.Similarly, improved information on appropriate lakepCO2 values would increase the accuracy of the modelpH prediction. With regard to pH reconstruction usingsediment records there is still room for improvementwith respect to both the transfer function and themodern analogue approaches. In the case of the latter,there is a need to increase the size of the reference data-set to improve the probability of finding good ana-logues. In the case of the former, the continuation of thecurrent sediment trapping programme across a range ofchemically recovering sites, in conjunction with contin-ued chemical monitoring, is seen as essential in verifyingoutput from transfer functions and other palaeoapproaches.

Acknowledgements

We are very grateful to all in the ECRC, especiallyRoger Flower, Viv Jones and Annette Kreiser, and toTim Allott, now of Manchester University, whocontributed diatom data to this paper, and to the UKDEFRA over many years for financial support. DickWright and Brian Cumming provided incisive andvaluable comments on the manuscript at the reviewingstage. The paper is a contribution to the EU FP6Integrated Project Euro-limpacs (Contract 505540) andto the UK DEFRA Acid Waters Monitoring Networkprogramme.

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