The European Diatom Database - Steve Juggins - Newcastle

The European Diatom Database

User Guide

Version 1.0 October 2001

Steve Juggins Department of Geography University of Newcastle Newcastle upon Tyne NE1 7RU, UK [email protected]

European Diatom Database User’s Guide

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Contents

1 Introduction ............................................................................................... 3

2 Diatom taxon information.......................................................................... 4

2.1 Taxonomic harmonisation.......................................................................... 4

2.2 Taxon search ............................................................................................. 5

2.3 Taxon home page....................................................................................... 7

2.4 Taxonomy description ............................................................................... 9

3 Dataset information ................................................................................. 10

3.1 Dataset information ................................................................................. 10

3.2 Dataset sample list ................................................................................... 12

3.3 Sample information ................................................................................. 12

3.4 Environmental variable list ...................................................................... 13

3.5 Diatom taxon list ..................................................................................... 13

4 Environmental reconstructions................................................................. 14

4.1 Transfer function description ................................................................... 15

4.2 On-line environmental reconstructions..................................................... 16

4.2.1 File upload............................................................................................... 16

4.2.2 Verify core data ....................................................................................... 17

4.2.3 Output file list.......................................................................................... 18

4.2.4 Environmental reconstructions................................................................. 18

4.3 Stand-alone reconstruction software (ERNIE).......................................... 19

5 Transfer function output .......................................................................... 20

5.1 Verify ...................................................................................................... 20

5.2 Weighted-averaging (WA)....................................................................... 20

5.3 Weighted-averaging partial least squares (WAPLS)................................. 21

5.4 Modern Analog Technique (MAT) .......................................................... 22

5.5 Locally-weighted weighted averaging (LWWA)...................................... 23

6 Choosing a transfer function .................................................................... 23

6.1 Which training set should I use? .............................................................. 23

6.2 Which numerical method should I use?.................................................... 24

Appendix 1 List of EDDI participants......................................................................... 25

Appendix 2 List of EDDI datasets............................................................................... 25


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1 Introduction

EDDI is a web-based information system for diatoms designed to enhance the application of diatom analysis to problems of surface water acidification, eutrophication and climate change. It has been produced by combining and harmonising data from a series of smaller datasets from across Europe (and parts of Africa and Asia), and it includes electronic images of diatoms, new training sets for environmental reconstruction, a diatom slide archive, and applications software for manipulating data. It is the result of a three-year collaboration between over 40 diatom taxonomists, palaeolimnologists, statisticians and database experts from 13 countries. EDDI was funded by the European Commission under the IV framework Environment and Climate Programme (Grant No. ENV4-CT97-0562).

The datasets used in EDDI to create a single harmonised database each consist of modern (largely surface sediment, but with a small number of benthic or planktonic) diatom samples and associated environmental data. Each is relatively small (mainly less than 100 lakes), regionally based and concerned with only a single environmental gradient (pH, TP, or salinity). They were created over the last 20 years or so by different laboratories using different methodologies, and many are not publicly available for use by scientists outside the specialist laboratories involved in their creation. These datasets have now been harmonised with respect to both diatom taxonomy and environmental data.

In EDDI taxonomic harmonisation was a two step process, first within the pH, TP and salinity datasets, and second, between them. The harmonisation process involved the standardisation of taxon nomenclature and codes, the screening of slides from the datasets to assess consistency between analysts, full documentation of decisions supported by hard copy micrographs and stored electronic images of all taxa and the archiving of slides for future inspection. No re-counting of slides was carried out and, therefore, harmonisation was largely the result of synonymy identification and merging of entities to the lowest common taxonomic denominator used during the original counting. The original data are preserved in the system. This user’s guide describes the EDDI system. Operation of the system is the same for the web and CDROM versions except that on-line reconstructions are not available on the CDROM version. CDROM users should use the stand-alone software to implement the EDDI transfer functions.

EDDI contains three main types of information:

1. Diatom taxon descriptions, including images.

2. Dataset information, including diatom percentages environmental information (water chemistry) for each sample.

3. Methods for environmental reconstructions consisting of diatom training sets, transfer functions and software for hydrochemical reconstructions.

The EDDI web-based system is organised under these three headings, listed as Taxa, Datasets, and Reconstructions on the main EDDI menu. This guide describes the EDDI system under these three headings.


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2 Diatom taxon information

2.1 Taxonomic harmonisation

The taxonomic harmonisation procedure was as follows. Lists of all taxa used within each of the pH, TP and salinity datasets were generated. These were then manipulated by the diatom harmonisation coordinators to produce ordered lists of the most numerically important names, and were further stratified into taxonomic groups which were either known to be synonymous with, or that could be confused with, the main taxon of each group. Subsequently, taxonomic groups were selected for discussion during a series of workshops for pH, TP and salinity dataset harmonisation, independently. The taxonomists who had counted the original dataset slides, or who had worked closely with the original taxonomist, participated in these workshops. Electronic images were captured using a video link to the microscope. A set of minutes was produced, documenting the decisions reached, which then formed the basis for the merging process. A further three workshops were held to harmonise between the pH, TP and salinity datasets. Again, taxa were ranked according to numerical importance as for the first merging exercise and a cut-off of 4% in any single sample was selected as the criterion for inclusion of a taxon. Of the 2163 original names used among all datasets within EDDI (pH, TP and Salinity), 1303 did not feature above 4% in any sample, and a further 54 were considered “unknown”.

Merging both within and between the pH, TP and salinity datasets involved a six level taxonomic coding system, as shown in Table 1.

EDDI taxonomic coding system used in the harmonisation procedure. Merge levels increase from 0 to 5.

0 No change Original name and code are unchanged. 1 Code change Original name is valid, code change only. 2 Name / code error Technical error - miscode/synonym/old name/different

name used between workers for same discreet, unique entity.

2A Misidentification Corrects misidentification. 3A Sub-specific merging Upgrade status of "aff." Codes, merge varieties etc. into

higher level, where the different varieties are not consistently identified across different datasets, and where the different taxa are not considered morphologically different.

3B Sub-specific merging As 3A but where the different varieties etc. are considered morphologically different.

3C Sub-specific merging As 3B but where the different varieties etc. have been identified across different datasets and are merged to rationalise data analysis.

4 Taxonomic concepts start to differ

Medium level merging. Some differences in taxonomic concept here, across datasets, and there is some overlap in usage between workers. The same name may be used for different taxonomic entities across datasets: there is at least a systematic offset between datasets.

5 Lowest High level merging. Some considerable confusion here, both between workers and often in the literature at large. A large range of variation is covered as different taxonomists have used the same name to cover different


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entities, with often large differences in concepts, and often without the major splits coinciding. As a result, many forms may be included in this umbrella name & code. Treat with caution & refer to images for different workers' concepts!

X Indeterminate species 9999 code used, valves not identified below generic (or higher) level.

Existing codes and names were supplied to merged taxa where these could be reconciled with unique concepts from the literature, generally with taxonomic level 3A and below. New codes were allocated in cases where merging created broader taxonomic units than fitted into single taxonomic concepts in the general literature, generally at level 3B and above. Within each of the pH, TP and salinity datasets, the new codes reflected the laboratory in charge of the harmonisation: XXUnnn for pH at UCL, XXGnnn for TP at GEUS and XXCnnn for Salinity taxa at CEREGE. Numbers (nnn) began at 999 and decreased by one for each new taxon. For the between-dataset merges, similar guidelines were followed, such that taxa adopted the least specific code found within the pH, TP and salinity datasets, or if new amalgamations of taxa were involved, new XXAnnn codes were introduced.

The combination of EDDI taxon code and taxonomy class can then be used to determine the degree of merging involved in any particular EDDI taxon. Together with the linked digital images and a description of what has been merged (or reference to a published description), this allows users to decide for themselves how appropriate any particular EDDI taxonomy is for their purpose. Sites can thus be selected or excluded on the basis of the taxonomic implications of resultant merges, and the effect this has on net ecological information gain or loss, whether for model building and down-core reconstruction of parameters, or present-day species distributions across gradients, for example.

2.2 Taxon search

EDDI contains information on over 2000 diatom taxa. Selecting [Taxa] from the main menu links to the Taxon search page:

Enter a taxon name to search. * can be used as a wild card – Cyclotella * thus finds all species of the genus Cyclotella. A search for taxon name can also be entered in the Quick Search box on the left from any page in the EDDI system. Pressing the Genera button links to a page listing all EDDI diatom genera and the number of taxa in each genus:


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Selecting a genus links back to the Taxon search page and finds all taxa in a genus.

The Taxon search page lists all search hits. It shows the taxon code, name, number of occurrences and maximum percentage abundance across all EDDI datasets:

By default the list shows all hits and lists 30 rows of taxa. Click [next] to view more. These defaults can be changed for the whole session by changing the values in the Table Summary boxes on the left. For example, to limit the listing to taxa with more than 5 occurrences change N to 5, or to limit to taxa with a maximum percentage greater than 5% change max to 5.0. This provides a quick way to limit table listing to screen out rare taxa. Note that these values will be applied to all tables viewed in this session.

Clicking on a diatom taxon will link to the taxon’s home page.


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2.3 Taxon home page

The taxon home page lists the flowing information:

• Taxon name and authority

• Unique EDDI taxon code

• An image of the diatom (if present). The system does not contain images for all taxa, some rare non-problematic common forms are omitted.

• For some taxa additional images are also available to describe the full range of morphologies found in the EDDI datasets. A summary of these is given below the main image (working images = images collected by the dataset coordinators, high-quality images are images of selected specimens collected by the Royal Botanic Gardens Edinburgh).

• If the taxon has been merged a summary of the merges are given. For the example above the taxon C. cf. distinguenda var. unipunctata (>8µm) (the name given by the original diatomist) has been recorded only in the Central European dataset and has been merged into C. distinguenda var. unipunctata (agg.) with a merge code of 3A (see section 2.1). Following a link to the latter will take you to the home page for C. distinguenda var. unipunctata (agg.).

• Distribution in EDDI datasets. For the example above C. cf. distinguenda var. unipunctata (>8µm) is recorded in the Central European dataset in 57 samples and with a maximum abundance of 44.4%. The Taxonomy = Original means that this taxon only exists in this


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datasets under the concepts applied by the diatomists original taxonomy. Following a link to the dataset will take you to the dataset’s home page (section 3). Following a link to the Taxonomy will take you to a definition of the taxonomy.

• A map of the taxon’s distribution or plot against TP, conductivity or pH can be obtained by following the links at the bottom of the page.

Following the link to the merged taxon C. distinguenda var. unipunctata (agg.):

• This page contains the same information as above except that this is a merged taxon and this time the table gives a list of the taxa that have been merged into this form, with their merge codes. In this case we see that C. distinguenda var. unipunctata (agg.) is a composite taxon created by merging four separate original names.

• Under distribution we see that this taxon is recorded in four datasets. For the Combined TP and Central European datasets it is recorded only under the TP taxonomy. This means that this taxon is only defined in these datasets under the mergings defined in the TP taxonomy. For the French and Swiss datasets it is defined in the original and TP taxonomies.


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2.4 Taxonomy description

Following a link to taxonomy takes you to the Taxonomy description page. This displays a listing of all the merges defined for a particular taxonomy:

For example, in the merged TP datasets, A. lanceolata, A. lanceolata subsp. biporoma, A. lanceolata var. elliptica and A. lanceolata subsp. frequentissima have all be merged into A. lanceolata (agg.).

Following the link to A. lanceolata (agg.) takes us to the home page for this taxon.

In this case we have additional information:

• An EDDI description, detailing the rational for merging.

• List of relevant publications for identification.


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3 Dataset information

EDDI contains full counts and environmental information for 22 original and four merged regional diatom datasets. Selecting [Datasets] from the main menu displays a list of EDDI datasets along with the number of diatom samples in each:

Full details of each dataset is given in Appendix 2.

3.1 Dataset information

Clicking on the dataset name links to the dataset home page:


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This page contains the following information:

• Dataset name and EDDI code.

• Dataset type (pH, TP or salinity).

• Number of samples and date(s) of collection.

• The contributor and contact person for this dataset, linked to contact details (address, email etc.).

• A description of the dataset.

• A summary of the environmental data available for the dataset. Environmental data were harmonised in EDDI by ensuring that the numerical data were expressed in common units of measurement. The number of samples on which the mean data are based is recorded in EDDI for each site so that the user has information on data frequency (quality). For the African sites in the salinity datasets, where there is great intra- and inter-annual climatic variability, all available published data (largely pH and conductivity) were compiled to derive the best estimates of modern environmental conditions.

• A list of publications for the dataset.

The page also contains links to a full taxon list, sample list and a map of the dataset:

Following the link from Full taxon list takes you to the Taxon list page and displays a full list of all taxa recorded in the dataset, with number of occurrences and maximum percentage, sorted alphabetically:


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3.2 Dataset sample list

Following the link from sample list, or by clicking on the dataset code on the EDDI datasets page takes you to a list of samples for the dataset:

This shows for each sample the EDDI sample code, the original sample code used by the author, the country and name of site, and the type of sample.

3.3 Sample information

Clicking on the SampleId takes you to the Sample information page:

This shows details of site and sample location, collection date, and a listing of chemical and other environmental information available for this sample.


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3.4 Environmental variable list

Clicking on an environmental variable takes you to the Environmental variable list page which lists the values of the selected variable for all samples in the dataset:

3.5 Diatom taxon list

Clicking on the magnifying glass on the Dataset sample list page takes you to the Diatom sample list page, which lists all taxa recorded in the sample, in descending order of percentage abundance.


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4 Environmental reconstructions

The EDDI system contains 20 screened training sets for reconstructing pH, conductivity, TP, TOC and Anion ration (Alkalinity / (Cl+SO4)) using different numerical methods. The system also provides two ways to performa reconstruction: either on-line, or using downloaded software. To perform reconstructions on-line the user simply uploads their core-data to the EDDI server, selects the transfer function and downloads the results. This is the simplist solution for the casual user. To perform reconstructions on a local computer the user must first download and install customs transfer function software and datasets. The process of applying the transfer functions is the same in both cases, and the software for on-line and local reconstructions produces exactly the same output.

When using an EDDI transfer function it is essential that the taxonomy of the core matches that of the training set. In EDDI this means that the taxon codes used in the core and training set much match in terms of the codes themselves, and in the taxonomic concepts applied to the codes. In EDDI there are two ways to ensure agreement between training set and core taxonomy. The first and most straightforward is for the diatomist to use exactly the same codes in their core as are used in the training set. EDDI contains pages devoted to describing the taxonomy of the training sets to aid in this process. The second way to ensure compatibility is to use a conversion dictionary to convert between local codes and EDDI codes. This requires more work initially to setup the dictionary but is the most convenient if many cores are to be reconstructed as the same dictionary can be applied to each core. The text below describes both methods although on-line reconstructions are not available to CDROM users (the stand-alone software is more convenient for these users) and the use of a conversion dictionary is currently only supported by the stand-alone software.

Currently EDDI accepts core data in Cornell FULL or Condensed format. This format is used by other transfer function and ecological-statistical software. WinTran, a program to convert from Excel, Tilia and other common spreadsheet and database formats into Cornell format is available for download under the help menu option.

The main Environmental reconstruction page list the available variable / training set combinations (transfer functions) and numbers of samples in each training set. It also


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contains a link to the on-line reconstruction pages. Clicking on a training set links to the transfer function description page.

4.1 Transfer function description

This page lists details of each transfer function: number of samples, number of taxa (all training sets are screened to removed taxa less than 0.5% in any one sample), and the range, units and transformation of the environmental variable. If transformed all subsequent output and the summary performance statistics are cited in transformed units. The table also contains a link to the data page for the training set and the number of outliers removed (screened). In EDDI we have taken a conservative approach to screening and only removed gross outliers.

The page also lists the performance of the transfer function for various numerical methods under leave-one-out cross-validation. In EDDI we have compared four different numerical methods: Weighted averaging (WA), weighted averaging partial least squares (WAPLS), modern analog technique (MAT), and locally-weighted weighted averaging (LWWA). The latter is a new method of dynamically generating a training set optimised for each fossil sample – the method chooses the 50 closest (smallest chi-squared distance) modern samples to each fossil sample and uses these in a weighted averaging reconstruction. Comparisons suggest that this method is more effective when applied to the large merged datasets that simply fitting a single global transfer function.

Where the performance statistics are listed as N/A that method does not improve over simple weighted averaging for that dataset and is thus not available in EDDI.


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4.2 On-line environmental reconstructions

Performing an on-line reconstruction is a four step-process:

• Upload fossil data to server

• Verify taxonomy against an EDDI transfer function

• Perform a reconstruction

• View or download results

Uploaded files and results are stored on the EDDI system so a user may return at any time to re-process and analyse their data. To use the on-line facilities users must log into the system using a unique username and password – data is stored under this name so users can only access their own files. Currently you must apply to Steve Juggins for a user name and password – soon we will have an on-line registration system. If you have not logged-on selecting any of the above options will take you to a log-in screen. The log-in screen will show a username and password that can be used to test the system.

4.2.1 File upload

Select a file to upload to the server using the browse button.


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Once uploaded click your browser’s refresh button. The page will then list all uploaded files. You can delete unwanted files by checking and hitting delete.

4.2.2 Verify core data

This page shows a list of EDDI environmental variable / training sets and the users uploaded core data files. Select a training set and a core file and click submit.

The analysis will be run on the server and when finished you will be returned to the On-line environmental reconstructions page.


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4.2.3 Output file list

Click on View or download results to go to the Output file list page.

This page lists the results for all verify and reconstructions, showing the uploaded core file name used, the analysis type (Verify, WA, WAPLS etc.), the training set used, and the time and date of the analysis. Results are sorted in data order with the newest analysis at the top. The page also has the option to delete unwanted analyses.

Details and interpretation of the output files are given below in Section 5.

4.2.4 Environmental reconstructions

Once the taxonomy of the core files has been verified you are ready to do a reconstruction – select Reconstructions from the On-line environmental reconstructions page.

This page shows a list of environmental variables / training sets and numerical methods. WAPLS and LWWA are not available for all methods – only EDDI recommended options are available.

Choose a training set and method and click submit. Calculations are performed on the server and you are returned to the On-line reconstructions page when complete. Note that for some methods with large datasets the calculations may take some minutes. Onec complete the


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results can be viewed from the Output file list page. Alternatively the results can be downloaded by right-clicking and choosing save-as in you browser.

4.3 Stand-alone reconstruction software (ERNIE)

Microsoft Windows software for performing reconstructions on a user’s PC can be downloaded from the EDDI system under the Help page. Installing the software will install two programs and the data files for the different transfer functions. The software runs on Windows 95, 98, ME, NT and 2000. The first program, ERNIE – short for “Environmental Reconstructions using the European Diatom Database” – provides the user interface. It displays a list of available training sets, a list of numerical methods. Simply choose a training set, numerical method, specify the fossil data file and output file and press Run.

Optionally a translation dictionary may be supplied to convert codes in the fossil data file to EDDI codes. The dictionary should contain two columns of codes and be in simple text or ASCII format. The first column should contain the old code, the second column the new code. For example, the list:

AC001B AC001A

AC001C AC001A

Etc.

Converts taxon code AC001B to code AC001A etc, before applying the transfer functions.


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5 Transfer function output

Output from the web-based and stand-alone reconstruction software is identical and described below.

5.1 Verify

All results files contain a header with the program name and run date / time and a summary of the input data file, training set and environmental variable, and analysis method (including verify): Output from program ERNIE: Environmental Reconstructions using the European Diatom Database Version 1.0: November 2001 Program run on Sun Nov 11 17:00:02 2001 Fossil data file: C:\temp\EDDI\uploads\DKSOB2.txt Environmental variable: TP Training data set: NW European Method: Validation

For the Verify analysis the output lists all taxa in the core file, along with their taxon number in the file (#), and the number of occurrences and maximum percentage in the core file and training set. This list should be checked for taxa that are only present in the core – indicating possible no-analog situation, or more likely, mis-coding and mis-matching between core and training set taxonomy and codes. Summary of taxa Fossil Modern Name # No.Occ Max No.Occ Max AC001A 1 7 1.15 0 0.00 AC006A 2 3 0.31 47 2.31 AC013A 3 8 0.77 0 0.00 ……………………………… ST009A 85 3 0.66 0 0.00 SY017A 94 3 0.62 0 0.00 UN9995 95 3 0.45 39 2.73 UN9999 96 9 1.43 67 2.07

The Verify output also lists for each fossil sample the number of taxa (N), effective number of taxa (Hill’s N2) and the sum of all taxa for each fossil sample. It also lists the number of fossil taxa at each level that are present in the training set, and the sum of taxa at each level present in the training set. In the first core sample in the example below only 14 of the 28 taxa are present in the training set, and these 14 only account for 12% of the assemblage. Again this suggests a no-analog situation or taxon mis-coding. Summary of fossil samples Sample Data Calibration Set N N2 Sum N Sum 1 s03 28 4.66 99.99 14 11.81 2 s04 33 7.42 100.04 15 20.03 3 s05 35 6.08 99.99 19 24.08 ………. 18 s20 40 11.52 99.98 24 46.11 19 s21 34 8.91 100.08 16 44.34

5.2 Weighted-averaging (WA)

After the initial headers the WA output lists the coefficients of the deshrinking regression equation for classical and inverse deshrinking and the performance statistics of the training set in terms of apparent and cross-validation (leave-one-out) errors. Inverse Classical b0 -1.5946 1.1085 b1 1.8086 0.43781


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"Apparent" errors or errors of "estimation" Inverse Classical RMSE 0.23369 0.26262 r2 0.79181 0.79181 Ave Bias 2.6584e-007 2.9638e-007 Max Bias 0.57059 0.44871 "Jackknife" errors or errors of "prediction" Inverse Classical RMSE 0.26927 0.29228 r2 0.72367 0.725 Ave Bias 0.0047569 0.0066614 Max Bias 0.78017 0.71255

The output then lists the number of occurrences, maximum percentage, Hill’s N2 and the environmental optimum for all taxa in the training set. Species summary N. occur Max N2 Optima 1 AC002A 26.0000 10.3806 8.5877 1.5222 2 AC004A 4.0000 0.9158 2.7559 0.9978 3 AC006A 47.0000 2.3140 28.7813 2.1742 4 AC008A 10.0000 3.5313 3.8759 2.0393 ………. 332 XXG998 20.0000 40.0411 4.9214 1.1546 333 XXG999 32.0000 13.2554 13.1181 1.8302

The output then lists the reconstructed environmental values for each level using both classical and inverse deshrinking, along with the sample-specific standard errors estimated by Monte-Carlo simulation. Environmental reconstructions: Inverse Classical Estimate Std. Error Estimate Std. Error 1 s03 2.2800 0.2939 2.3614 0.3279 2 s04 2.2134 0.3017 2.2773 0.3390 …… 18 s20 1.9702 0.3016 1.9701 0.3390 19 s21 1.9648 0.2775 1.9633 0.3043

5.3 Weighted-averaging partial least squares (WAPLS)

After the initial headers the WAPLS output lists the performance statistics of the training set in terms of apparent and cross-validation (leave-one-out) errors. "Apparent" errors or errors of "estimation" Comp RMSE R-squared Avg-Bias Max-Bias 1 0.2337 0.7918 0.0000e+000 0.5701 2 0.1882 0.8650 1.0309e-004 0.2659 "Prediction" errors Comp RMSEP R-squared Avg-Bias Max-Bias 1 0.2683 0.7258 0.0000e+000 0.7800 2 0.2597 0.7439 0.0000e+000 0.6896


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The output then lists the number of occurrences, maximum percentage, Hill’s N2 and the WAPLS coefficients and their standard errors for the first 2 WAPLS components. Species summary N. occur Max N2 Beta1 Beta2 SE1 SE2 1 AC002A 26.0000 10.3806 8.5877 1.1570 0.6736 9.1619e-002 0.1934 2 AC004A 4.0000 0.9158 2.7559 0.2071 5.2799e-002 0.3775 0.6227 3 AC006A 47.0000 2.3140 28.7813 2.3381 2.5887 0.1875 0.4134 ………………………. 331 XXG997 138.0000 40.9556 41.6971 1.2266 1.0484 0.1008 9.4087e-002 332 XXG998 20.0000 40.0411 4.9214 0.4910 0.7731 0.3103 0.4087 333 XXG999 32.0000 13.2554 13.1181 1.7150 1.2671 0.1339 0.2553

The output then lists the reconstructed environmental values for each level for components 1 and 2, along with the sample-specific standard errors estimated by Monte-Carlo simulation. Environmental reconstructions: Comp 1 Comp 2 Estimate Std. Error Estimate Std. Error 1 s03 2.3124 0.2840 2.4650 0.3167 2 s04 2.1828 0.2818 2.2573 0.3073 ………. 18 s20 1.9575 0.2989 1.9236 0.3620 19 s21 1.9689 0.2749 1.8727 0.2755

5.4 Modern Analog Technique (MAT)

After the initial headers the MAT output lists the dissimilarity coefficient and number of analogs used. The default at present is the Squared ch-sqaured distance and to take the mean or weighted mean of the 5 nearest analogs.

Using Squared Chi-squared Distance measure and 5 nearest analogs

The MAT output then lists the reconstructed environmental value for each fossil sample as either the mean or weighted mean of the 5 nearest analogs, and the standard deviation (or weighted standard deviation) of the environmental value of these analogs. The output also lists the distance to the closest analog (minDC), which can be used as a measure of how good the analogs are (see section 6). Results for Fossil data Sample Mean SD Wt-Mean SD minDC N 1 s03 2.4711 0.2607 2.4705 0.2605 177.4061 5.0000 2 s04 2.2262 0.4266 2.2289 0.4243 160.8533 5.0000 3 s05 2.0136 0.4452 2.0127 0.4460 160.7379 5.0000 …….. 18 s20 1.9715 0.0791 1.9726 0.0779 128.0576 5.0000 19 s21 1.9715 0.0791 1.9739 0.0763 115.0799 5.0000

The MAT output also lists the 5 closest analogs for each fossil sample, their squared chi-squared distance, and their environmental value. List of closest analogs for each fossil sample s03 DK020 SCM043 DK003 SCM016 SCM014 Distance 177.4 181.3 182.9 183.1 183.6 Value 2.542 1.996 2.422 2.741 2.655 s04 DK020 DK015 NI016 SWAP137 SCM016 Distance 160.9 166.1 166.7 169 169.3 Value 2.542 2.193 2.163 1.491 2.741 ………… s20 SCM043 SCM035 DK023 DK024 SE042 Distance 128.1 133.5 136.6 142.3 143.2 Value 1.996 1.948 2.064 2.017 1.832


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s21 SCM043 SCM035 DK023 DK024 SE042 Distance 115.1 118.1 127.3 132.4 140.6 Value 1.996 1.948 2.064 2.017 1.832

5.5 Locally-weighted weighted averaging (LWWA)

After the initial headers the LWWA output lists the leave-one-out cross-validation errors for the training set. "Jackknife" errors or errors of "prediction" Inverse Classical RMSE 0.25747 0.26083 r2 0.7543 0.74133 Ave Bias 0.0046723 0.011378 Max Bias 0.61866 0.55922

The LWWA output then lists the environmental reconstructions for each fossil sample, along with an estimate of the sample-specific standard error, estimated using Monte-Carlo simulation, for LWWA under inverse and classical dishrinking. Environmental reconstructions: Inverse Classical Estimate Std. Error Estimate Std. Error 1 s03 2.3413 0.2456 2.3660 0.2432 2 s04 2.3076 0.2718 2.3734 0.2788 3 s05 2.1168 0.2545 2.1533 0.2567 4 s06 2.0454 0.2624 2.0552 0.2751 5 s07 1.9256 0.2756 1.9183 0.2960 6 s08 1.9908 0.2689 2.0094 0.2832 7 s09 1.8892 0.2755 1.8652 0.2945 8 s10 2.0529 0.2477 2.0686 0.2532 9 s11 1.9304 0.2515 1.9236 0.2544 10 s12 2.0157 0.2496 2.0265 0.2494 11 s13 1.9507 0.2418 1.9483 0.2377 12 s14 1.9264 0.2571 1.9206 0.2553 13 s15 2.0016 0.2560 2.0079 0.2545 14 s16 2.0974 0.2601 2.1198 0.2591 15 s17 2.1982 0.2621 2.2407 0.2615 16 s18 2.1331 0.2564 2.1616 0.2544 17 s19 1.9991 0.2538 2.0007 0.2515 18 s20 2.0347 0.2455 2.0541 0.2433 19 s21 1.9629 0.2562 1.9620 0.2540

6 Choosing a transfer function

6.1 Which training set should I use?

There is no single training set in EDDI that is the best for a particular environmental variable – indeed this is why we have included a range of regional training sets as well as the combined training sets. Where a core site is well-represented by a local regional dataset in terms of taxon coverage, and where the regional dataset covers the range of past environments likely to be represented in the core then it would be appropriate to use a regional dataset. When there is no obvious regional dataset that is appropriate for the whole of the core then we recommend the use of a larger merged pH, TP or salinity dataset. Numerical comparisons so far carried out indicate that the merging (lumping) of taxa to higher taxonomic units has not degraded the performance of the transfer functions to any significant extent. The benefits of merging in terms of grater range of environments and taxonomic diversity appear to outweigh the disadvantages of reduction of taxonomic precision. Even where a local dataset might be appropriate we recommend the use of the MAT technique using a large merged dataset to identify the datasets with the closest matches for the fossil sample as a check that the regional dataset is really the most appropriate.


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6.2 Which numerical method should I use?

Eddi contains software to perform reconstructions using 4 different numerical methods. For most regional datasets simple weighted averaging is recommended. Where the reconstructed values lie close to the mean of the training set values we recommend inverse deshrinking as this gives an overall lower RMSE of prediction. Where the reconstructed values lie towards the ends of the gradient sampled by the training set we recommend classical deshrinking as this produces more accurate reconstructions at the gradient ends (see discussion in Birks et al. 1990).

For two regional training sets and the combined pH dataset a 2-component WAPLS model is able to improve on WA (see ter Braak and Juggins 1993 and Birks 1995 for a description of WAPLS). WAPLS could be used with these training sets though we urge caution and careful screening of results as WAPLS can to extrapolate under no-analog situations.

For the larger merged datasets LWWA is also available. This method dynamically generates a “local” training set for each fossil sample based on the 50 closest analogs defined by the minimum squared chi-squared distance. Although the merged dataset have greater environmental and taxonomic diversity, making them more applicable to a wider range of core material, the additional diversity can introduce effects of secondary environmental gradients and other “noise” into the transfer function models. Numerical comparisons suggest that the LWWA approach can take advantage of the greater environmental and taxonomic diversity of the large training sets and avoid the problems of additional noise. LWWA out-performs traditional WA or WAPLS for the merged datasets and is the recommended method for these.

For all training sets we also recommend performing a MAT analysis. This will yield an additional environmental reconstruction for comparison and will also give a measure of the floristic match between the fossil sample and it’s closest analog in the training set. Precise interpretation of this analog measure is difficult but a rule of thumb is to suggest that any fossil sample that lies beyond a value of 100-150 has no close analogs in the training set (this estimate is based on the distribution of dissimilarities within the training set – see Juggins and Jones 1995 for a discussion). Output from the verification analysis can also help to identify no-analog samples. Reconstructions for such samples should probably be treated with caution, although as long as the majority of taxa in the fossil samples are present in the training set there are no a-priori reasons for suspecting the reconstructions to be in error.

Birks, H. J. B., Line, J. M., Juggins, S., Stevenson, A. C., and ter Braak, C. J. F. (1990). Diatoms and pH reconstruction. Philosophical Transactions of the Royal Society of London, B 327, 263-278.

Birks, H. J. B. (1995). Quantitative palaeoenvironmental reconstructions. In Statistical modelling of Quaternary Science Data, D. Maddy and J. Brew, eds. (Cambridge: Technical Guide 5, Quaternary Research Association), pp. 161-254.

Jones, V., and Juggins, S. (1995). The construction of a diatom-based chlorophyll a transfer function and its application at three lakes on Signy Island (maritime Antarctic) subject to differing degrees of nutrient enrichment. Freshwater Biology 34, 433-445.

ter Braak, C. J. F., and Juggins, S. (1993). Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269/270, 485-502.


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Appendix 1 List of EDDI participants

EDDI was coordinated by Rick Battarbee and Helen Bennion of the Environmental Change Research Centre, University College London in partnership with Steve Juggins (University of Newcastle), Françoise Gasse (CEREGE, Aix-en-Provence) and John Anderson (GEUS, Copenhagen).

Diatom harmonisation was carried out by Nigel Cameron (pH), Dave Ryves, John Anderson and Helen Bennion (TP) and Christine Paillès, Françoise Gasse and Françoise Chal(salinity), with the help of Jorunn Larsen, Jan Weckström, Peter Rosen, Nadia Solovieva, Viv Jones, Roger Flower, Phil Barker, Jane Reed, Laurence Carvalho, Sonja Hausmann, Patrick Rioual and Sybille Wunsam.

Numerical techniques, database development and data re-formatting and checking were the responsibility of Steve Juggins, assisted by Richard Telford, Anne-Marie Clarke, Kathryn Lyttle, and Emma Pearson. The Newcastle group also coordinated the integration of the raw diatom and environmental datasets, diatom images and taxonomic information, and were responsible for the statistical analysis of the new merged EDDI datasets and transfer functions. Dave Ryves also took responsibility for the final merging of the combined pH, salinity and TP datasets.

The three harmonisation centres (UCL, CNRS-CEREGE and GEUS) collected over 2000 digital images to document taxonomic concepts used in EDDI. A large number of these specimens were re-scanned by Shirin Rezai at the Royal Botanic Garden, Edinburgh under the supervision of David Mann and Micha Bayer. Stephen Droop and Micha Bayer also provided invaluable advice on microscopy and image capture protocols, and David Mann provided guidance on taxonomic and nomenclatural issues, while Eileen Cox of the Natural History Museum is responsible for archiving and curating the EDDI diatom slide collection. John Birks, Cajo ter Braak, Joel Guiot, Andy Lotter, Atte Korhola and Hannu Toivonen provided expert advice and guidance on statistical issues and transfer function development, and Don Charles (Academy of Natural Sciences, Philadelphia) provided comments on the web system and discussed issues of compatibility with the US Diatom Paleolimnological Data Cooperative. Gerard Begni and colleagues at Medias France provided additional web-based support for the salinity datasets.

The taxonomic, distributional, ecological and palaeoecological information contained in the EDDI system is ultimately derived from individual diatom training sets that have been collected by diatomists working in laboratories across Europe. EDDI gratefully acknowledges the following people for generously donating their datasets to the project as follows:

John Anderson Northern Irish, Danish and Northwest European TP datasets and SWAP pH dataset

Leila Ben Khelifa North African Salinity dataset Helen Bennion Welsh CCW, Shropshire / Cheshire Meres, Southern England,

and Northwest European TP datasets Frode Berge Norwegian and SWAP pH datasets John Birks Norwegian and SWAP pH datasets John Boyle Norwegian pH dataset Nigel Cameron UCL and combined ALPE mountain lake pH datasets Jordi Catalan Spanish mountain lake pH dataset Roger Flower SWAP pH dataset Joan Garcia Spanish mountain lake pH dataset Francoise Gasse North, East and combined African salinity datasets


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Liz Haworth SWAP pH dataset Vivienne Jones Svalbard pH dataset Steve Juggins Caspian salinity dataset and Northwest European TP dataset Atte Korhola Finnish pH dataset Tom Korsman Swedish pH dataset Andy Lotter Swiss TP dataset Aldo Marchetto Italian mountain lake pH dataset Jane Reed Spanish and Caspian salinity datasets Sergi Pla Spanish mountain lake dataset Ingemar Renberg SWAP pH dataset Patrick Rioual French Massif Central TP dataset Peter Rosén Swedish pH dataset Roland Schmidt Central European TP dataset Nadia Solovieva Kola pH dataset Jan Weckström Finnish pH dataset Sybille Wunsam Central European TP dataset


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Appendix 2 List of EDDI datasets EDDI contains a total of 26 datasets. Each is described on the following pages.


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European Diatom Database On the web at Newcastle University

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ALPE mountain lake dataset

EDDI dataset code ALPE Dataset type pH Number of samples 118 Collection date 1986 - 1993 Contributor The ALPE Participants Contacts John Birks, Nigel Cameron

The ALPE diatom-pH calibration data-set consists of surface-sediment diatom assemblages from 118 lakes and contains 530 taxa. The ALPE training set is from high-altitude or high-latitude lakes in the Alps, Norway, Svalbard, Kola Peninsula, UK, Slovenia, Slovakia, Poland, Portugal, and Spain. Gravity or piston corers were used to collect surface-sediment samples of 0.25 or 0.5 cm thickness, usually from the deepest point in each lake and a total of at least 500 valves were counted from each sample. A large number of possible sites in existing calibration sets, plus new ALPE project sites, were first screened carefully to select a set of lakes meeting the criteria of an alpine or remote location and an undisturbed catchment. The resulting ALPE data set of 118 lakes is derived from the whole or parts of 5 data-sets. These are 31 lakes from a Central Alps data set (Marchetto & Schmidt, 1993), 28 lakes from a Pyrenean data set (Garcia & Catalan, unpub.), 30 AL:PE 1 and AL:PE 2 lakes in various countries, 9 lakes from a Norwegian diatom-pH data set (Birks, Boyle & Berge, unpub.), and 20 Norwegian, Welsh, and Scottish lakes from the SWAP calibration set (see above). These 118 lakes have an altitudinal range of 20 m (northern Svalbard 79o40'N, 10o45'E) to 3050 m (mean = 1762 m median = 2091 m).

• Full taxon list for this dataset. • Full sample list for this dataset. • Plot a map of this dataset.

This is a composite dataset derived from the following original datasets:

Summary of environmental data for this dataset: Variable Units N Min Max Mean

Alkalinity µeq/l 104 -31.75 630 67.6

Aluminium (labile) µg/l 22 3.51 176 48.2 Aluminium (monomeric) µg/l 24 3 147 42.5

Aluminium (total) µg/l 43 10 256 61.9

Ammonium µg/l 80 0 6120 1198 Calcium µeq/l 118 6.17 519 88.8

Chloride µeq/l 118 0 350 34.3

Conductivity µS/cm 118 4.4 74.4 19.4 Iron µg/l 20 5 471 75.2

Magnesium µeq/l 118 4 222 24

Dataset Id Name N ALPI Italian mountain lake dataset 31 ALPS Spanish mountain lake dataset 28 ALPU UCL mountain lake dataset 30 Bergen Norwegian dataset 9 SWAP SWAP dataset 20


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Manganese µg/l 15 1.5 17 7.2 Maximum depth of lake m 118 1 73 15.5

Nitrate µg/l 102 0.7 41000 8708

Nitrite µg/l 28 40 190 95 pH pH units 118 4.48 8.04 6.15

Potassium µeq/l 118 0.89 48 6.09

Silica mg/l 52 0.19 2.22 0.764 Sodium µeq/l 118 4.57 309 39.8

Sulphate µeq/l 118 13.8 198 50.3

Total nitrogen µg/l 37 3.22 770 202 Total organic carbon mg/l 50 0.2 4.87 1.32

Total phosphorus µg/l 91 0.5 43 7.18

Water depth of diatom sample m 118 1 73 15.5 Zinc µg/l 21 0.36 14 6.75

Publications for this dataset:

Cameron, N.G., H.J.B. Birks, V.J. Jones, F. Berge, J. Catalan, R.J. Flower, J. Garcia, B. Kawecka, K.A. Koinig, A. Marchetto, P. Sánchez-Castillo, R. Schmidt, M. ?i?ko, N. Solovieva, E. ?tefková & M. Toro, 1999. Surface-sediment and epilithic diatom pH calibration sets for remote European mountain lakes (AL:PE project) and their comparison with the Surface Waters Acidification Programme (SWAP) calibration set. J. Paleolim. 22: 291-317.


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Italian mountain lake dataset

EDDI dataset code ALPI Dataset type pH Number of samples 31 Collection date 1989 - 1990 Contributor Aldo Marchetto Contact Aldo Marchetto

Surface sediment samples and lakewater chemical data from thirty-one high mountain lakes were used to derive a lakewater pH transfer function. The lakes selected lie along a pH gradient on the southern side of the Central Alps in South Tyrol, in the Ossola Valley, Italy and in Canton Ticino, Switzerland. The lakes selected are small (up to 0.2 km2) clearwater lakes most of which are located above the timberline. Samples were collected using gravity corers and the surface (0-0.5cm) was used to prepare a diatom sample. A total of approximately 600 diatom valves per sample was counted.



Alkalinity µeq/l 31 0 630 78.2

Ammonium µg/l 30 0 6000 1367 Calcium µeq/l 31 26 519 114


Conductivity µS/cm 31 8.3 74.4 20.6 Magnesium µeq/l 31 6 222 28.7

Maximum depth of lake m 31 2 28 8.32

Nitrate µg/l 31 1000 41000 18516 pH pH units 31 5.3 7.9 6.3

Potassium µeq/l 31 3 48 9.52

Silica mg/l 31 0.19 1.45 0.704 Sodium µeq/l 31 5 26 15.7

Sulphate µeq/l 31 34 198 73.4

Total phosphorus µg/l 31 2 43 7.26 Water depth of diatom sample m 31 2 28 8.32


Marchetto, A. & R. Schmidt, 1993. A regional calibration data set to infer lake water pH from sediment diatom assemblages in alpine lakes. Mem.Ist. ital. Idrobiol. 51: 115-125.


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Spanish mountain lake dataset

EDDI dataset code ALPS Dataset type pH Number of samples 28 Collection date 1992 Contributors Jordi Catalan, Joan Garcia Contact Jordi Catalan

The Pyrenees diatom-water chemistry dataset comprises surface sediment diatom samples and water-chemistry data from 98(?) lakes. The chemical data are published in Catalan et al. (1993) and a 28 lake sub-set of these data were used in the ALPE training set (see above). The full diatom/water-chemistry training set, however, remains unpublished. Diatom counts were made by Joan Garcia.


Summary of environmental data for this dataset:

Variable Units N Min Max Mean Alkalinity µeq/l 28 9 400 127

Ammonium µg/l 28 220 3080 1156 Calcium µeq/l 28 16 346 124




Nitrate µg/l 26 400 18120 8100


Potassium µeq/l 28 1 11 5.11

Sodium µeq/l 28 7 46 20.2 Sulphate µeq/l 28 16 72 35

Total phosphorus µg/l 28 2.17 23.5 9.07

Water depth of diatom sample m 28 1 44 11.9


Catalan, J., E. Ballesteros, E. Gacia, A. Palau & L. Camarero, 1993. Chemical composition of disturbed and undisturbed high-mountain lakes in the Pyrenees: a reference for acidified sites. Wat. Res. 27: 133-141.


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UCL mountain lake dataset

EDDI dataset code ALPU Dataset type pH Number of samples 30 Collection date 1991 - 1993 Contributor Nigel Cameron Contact Nigel Cameron

Description not yet available for this dataset



Alkalinity µeq/l 20 2.13 194 42.2

Aluminium (labile) µg/l 6 13.8 176 52.7 Aluminium (monomeric) µg/l 9 3 45.8 16.1

Aluminium (total) µg/l 15 10 186 39

Ammonium µg/l 22 60 6120 1020 Calcium µeq/l 30 6.5 278 76.3

Chloride µeq/l 30 0.99 350 41.3

Conductivity µS/cm 30 6.25 55.7 19.6 Magnesium µeq/l 30 5.76 172 26.5

Maximum depth of lake m 30 4.2 73 20.6


Potassium µeq/l 30 0.89 9.62 4.41

Sodium µeq/l 30 4.57 309 44.3 Sulphate µeq/l 30 13.8 106 46

Total nitrogen µg/l 20 58.5 770 300

Total organic carbon mg/l 23 0.23 3.22 0.991 Total phosphorus µg/l 23 0.5 20.4 5.15

Water depth of diatom sample m 30 4.2 73 20.6


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Norwegian dataset

EDDI dataset code Bergen Dataset type pH Number of samples 96 Collection date 1989 - 1990 Contributors Frode Berge, John Birks, John Boyle Contact John Birks

Ninety-six sites are included from a Norwegian data set developed by Birks et al. (unpublished). Of these, ninety-two samples from lakes in southern and central Norway have been applied as a training set (ter Braak & Juggins 1993, Larsen 2000).



Alkalinity µeq/l 96 -51 2755 226

Aluminium (labile) µg/l 96 -1.08 281 70.9 Aluminium (monomeric) µg/l 96 10.5 135 42.8

Aluminium (total) µg/l 96 12.7 339 114

Calcium µeq/l 96 7.35 2639 265 Chloride µeq/l 96 17.3 278 86.3

Conductivity µS/cm 96 12.8 339 47.8

Iron µg/l 87 10 750 147 Magnesium µeq/l 96 12.7 830 61.4

Manganese µg/l 81 10 90 24.3

Maximum depth of lake m 95 3 34 13.5 pH pH units 96 4.32 8.29 5.84


Silica mg/l 96 0.28 4.59 1.58 Sodium µeq/l 96 22.8 202 80.3

Sulphate µeq/l 96 20.6 461 86.1

Total nitrogen µg/l 96 1.12 1159 97.9 Total organic carbon mg/l 96 0.9 8.58 3.29

Total phosphorus µg/l 96 3 107 8.52

Water depth of diatom sample m 95 3 34 13.5

Zinc µg/l 96 0.36 36.4 7.74


Larsen, J. 2000. Recent changes in diatom-inferred pH, heavy metals, and spheroidal carbonaceous particles in lake sediments near an oil refinery at Mongstad, Western Norway. Journal of Paleolimnology 23: 343-363.

ter Braak, C.J.F. & S. Juggins, 1993. Weighted averaging partial least squares regression (WA-PLS): an improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269/270: 485-502.


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from species assemblages. Hydrobiologia 269/270: 485-502.


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Finnish dataset

EDDI dataset code Finland Dataset type pH Number of samples 98 Collection date 1995 - 1996 Contributors Atte Korhola, Jan Weckström Contact Atte Korhola

The Finish Lapland training set comprises 151 samples from lakes in the pH range 5.0-8.3. A sub-set of 30 of these lakes has been published as a training set (Weckström et al. 1997). These lakes are distributed across the treeline, spanning boreal forest to tundra along a steep climatic gradient. The extended training set was produced with the intention of creating a transfer function for temperature. Surface sediment samples (0-1cm) were collected using a gravity corer during summer 1994 and 1995. Samples for analysis of water chemistry were collected during July 1995. Approximately 500 diatom valves per sample were counted. Only those species present at greater than 1% in any single sample and with >3 occurrences and that are identified to species level or better were included in the model (118 taxa).



Alkalinity µeq/l 98 20 340 152 Calcium µeq/l 98 13 288 105

Conductivity µS/cm 98 6.4 48.6 25.2

Iron µg/l 98 10 1200 126 Magnesium µeq/l 98 4.94 106 33.3


pH pH units 98 5 7.8 7 Potassium µeq/l 98 1.79 24 8.27

Secchi depth m 98 0.85 10.7 5.53

Sodium µeq/l 98 7.83 74.8 42.3 Total organic carbon mg/l 98 1.3 12.6 5.35



Weckström, J., Korhola, A. & T. Blom. 1997. The relationship between diatoms and water temperature in thirty subarctic Fennoscandian Lakes. Arctic and Alpine Research 29: 75-92.


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Dataset information

Kola penninsula pH dataset

EDDI dataset code Kola Dataset type pH Number of samples 25 Collection date 1995 Contributor Nadia Solovieva Contact Nadia Solovieva

The Kola diatom-pH training set comprises 24 small oligotrophic lakes located along a vegetation gradient in the central and western parts of the Kola Peninsula, Russia. The surface sediment diatom flora from the KOLA lakes is typical for oligotrophic, diluted arctic and alpine lakes. The diatom assemblages from the KOLA lakes are close floristically to the assemblages from the ALPE lakes (Cameron et al., 1999) and to the assemblages from northern Sweden (Korsman and Birks, 1996). The diatom optima generated by the KOLA model are generally in agreement with the optima derived by other models (e.g. ALPE) although KOLA diatom optima are generally higher compared to the ALPE and SWAP.


Summary of environmental data for this dataset: Variable Units N Min Max Mean Alkalinity µeq/l 25 0 283 72.8

Aluminium (labile) µg/l 25 0.1 46.8 11.4 Aluminium (monomeric) µg/l 25 0.1 92.9 28.3

Calcium µeq/l 25 15 209 70

Chloride µeq/l 25 17.5 617 147 Colour mg Pt/l 25 3 240 63.4

Conductivity µS/cm 25 8 88 32.7

Iron µg/l 25 1.8 320 72.4 Magnesium µeq/l 25 11.5 115 61

Maximum depth of lake m 25 1.5 19.2 6.51

pH pH units 25 5 7.44 6.35

Potassium µeq/l 25 1.02 29.9 10.1 Silica mg/l 25 0.04 2.91 0.946

Sodium µeq/l 25 19.1 491 153

Sulphate µeq/l 25 22.1 104 51.7 Total nitrogen µg/l 25 94 470 226

Total organic carbon mg/l 25 0.73 20.2 6.6

Total phosphorus µg/l 25 2 17 7.44 Water depth of diatom sample m 25 1.5 19.2 6.51



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Solovieva, N (2000) A palaeoecological study of Holocene envionmental change in a small upland lake from the Kola peninsula, Russia. Unpublished PhD Thesis, University of London.


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Combined pH dataset

EDDI dataset code pH Dataset type pH Number of samples 627 Collection date 1979 - 1996 Contributor The EDDI Participants Contact Steve Juggins




Alkalinity µeq/l 599 -51 2755 120

Aluminium (labile) µg/l 179 -1.08 333 56.3 Aluminium (monomeric) µg/l 150 0.1 469 45


Ammonium µg/l 80 0 6120 1198 Calcium µeq/l 510 6.17 3004 153

Calcium + Magnesium µeq/l 28 20 400 109

Chloraphyll-a µg/l 23 0.1 6.2 1.33 Chloride µeq/l 408 0 2342 128

Colour mg Pt/l 143 3 240 50.7

Conductivity µS/cm 540 4.4 367 38.5 Iron µg/l 372 1.8 1200 133

Magnesium µeq/l 509 4 930 59.3

Manganese µg/l 240 0.5 602 40.1 Maximum depth of lake m 625 0.9 73 11.6

Nitrate µg/l 227 0.5 41000 3918



Secchi depth m 98 0.85 10.7 5.53 Silica mg/l 289 0.04 7 1.31

Dataset Id Name N ALPI Italian mountain lake dataset 31 ALPS Spanish mountain lake dataset 28 ALPU UCL mountain lake dataset 30 Bergen Norwegian dataset 96 Finland Finnish dataset 98 Kola Kola penninsula pH dataset 25 SWAP SWAP dataset 178 Sweden Swedish dataset 118


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Silica mg/l 289 0.04 7 1.31

Sodium µeq/l 475 4.57 2127 102 Sulphate µeq/l 408 7.3 1226 86.8

Total nitrogen µg/l 258 1.12 1159 205

Total organic carbon mg/l 390 0.12 20.2 4.13 Total phosphorus µg/l 238 0.5 396 10.1


Zinc µg/l 205 0.36 730 17.5


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SWAP dataset

EDDI dataset code SWAP Dataset type pH Number of samples 178 Collection date 1979 - 1987 Contributor The SWAP Participants Contacts Rick Battarbee, John Birks, Steve Juggins

The Surface Waters Acidification Programme (SWAP) calibration training set included initially 178 surface sediment diatom assemblages and the associated environmental variables from 170 sites. Data-screening reduced these to 167 lakes, which using weighted averaging give superior results in terms of lowest root mean squared errors of prediction in cross-validation (Birks et al. 1990a; Birks et al. 1990b). The refined diatom/water chemistry training set used within the SWAP project is derived from five regional datasets (number of samples in parentheses) from Sweden (30), Norway (51), Scotland (60), Wales (32) and the English Lake District (5). These sites represent upland lakes in Britain and both upland and lowland lakes in Scandinavia with a bias towards acidic waters. Using gravity or a piston corer, surface sediment samples were usually taken from the deepest point in each lake and in all cases the top 0.5 cm was used for diatom preparation. A total of approximately 500 diatom valves per sample were counted. As a result of the considerable variation in taxonomic and nomenclatural usage between diatomists in different laboratories a programme of taxonomic harmonisation was undertaken to construct a common diatom dataset (Munro et al. 1990). The development and application of the SWAP training set is very well documented in the publications cited below and in many subsequent projects which have applied SWAP training set in other contexts or compared its performance with that of new training sets.



Alkalinity µeq/l 160 0 903 57.7

Aluminium (labile) µg/l 52 2 333 51.2 Aluminium (monomeric) µg/l 20 14 469 89.8


Calcium µeq/l 175 6.17 938 109 Chloride µeq/l 175 10.4 1160 187

Conductivity µS/cm 177 7.37 154 44.5

Iron µg/l 139 3.5 838 143 Magnesium µeq/l 174 7.81 337 67.5

Manganese µg/l 136 1.5 602 54.9

Maximum depth of lake m 177 1 61 15.9 Nitrate µg/l 125 0.6 91.5 10.5

pH pH units 178 4.33 7.25 5.59

Potassium µeq/l 174 2.01 54.1 9.8 Silica mg/l 137 0.179 7 1.33

Sodium µeq/l 144 16.5 1004 172

Sulphate µeq/l 175 18.7 352 107


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Sulphate µeq/l 175 18.7 352 107

Total nitrogen µg/l 117 10 982 272 Total organic carbon mg/l 148 0.12 17 3.94


Water depth of diatom sample m 177 1 61 15.9 Zinc µg/l 109 2 730 26.2


Birks, H. J. B., S. Juggins, et al. (1990). Lake surface water chemistry reconstructions from palaeolimnological data. The Surface Waters Acidification Programme. B. J. Mason, Cambridge University Press: 301-313.

Birks, H. J. B., J. M. Line, S. Juggins, A.C. Stevenson & C.J.F. ter Braak. (1990). Diatoms and pH reconstruction. Philosophical Transactions of the Royal Society of London, B 327: 263-278.

Stevenson, A.C., S. Juggins, H.J.B. Birks, D.S. Anderson, N.J. Anderson, R.W. Battarbee, F. Berge, R.B. Davis, R.J. Flower, E.Y. Haworth, V.J. Jones, J.C. Kingston, A.M. Kreiser, J.M. Line, M. M.A.R. & I. Renberg, 1991. The Surface Waters Acidification Project Palaeolimnology Programme: Modern Diatom/ Lake-Water Chemistry Data-Set. ENSIS Ltd., London: 86 pp.


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Swedish dataset

EDDI dataset code Sweden Dataset type pH Number of samples 118 Collection date 1989 - 1990 Contributors Tom Korsman, Peter Rosén Contact Tom Korsman

The training set from northern Sweden is an extended 151 sample set that includes the 119 lakes published in the training set assembled by Korsman & Birks (1996). The lakes are head-water sites (maximum depth > 2m; 0.04-2 km2; altitude > 5m; not limed). Sediment samples were taken with a gravity corer from the deepest point of each lake. With a few exceptions, that were analysed only once, water chemistry data were means of summer and winter values for the period 1985-1989. 200-300 diatom valves were counted per surface sediment sample. Only diatom taxa occurring in at least 5 lakes with a relative abundance of more than 2% in at least one lake were included in the analyses, giving at total of 115 taxa in the training set. This calibration set was developed for a palaeolimnological study of lake acidification in northern Sweden.



Variable Units N Min Max Mean Alkalinity µeq/l 118 0 290 81.3

Calcium µeq/l 4 110 140 128 Calcium + Magnesium µeq/l 28 20 400 109

Colour mg Pt/l 118 5 200 48



pH pH units 118 5 8.3 6.5 Water depth of diatom sample m 118 1.5 23 7.46


Korsman, T. & Birks, H.J.B., 1996, Diatom-based reconstruction from northern Sweden: a comparison of reconstruction techniques, Journal of Paleolimnology 15: 65-77.


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African dataset

EDDI dataset code Africa Dataset type Salinity Number of samples 284 Collection date 1960 - 1986 Contributor Francoise Gasse Contacts Francoise Gasse, Steve Juggins

These two data sets have been harmonized to construct a unified African data set. Transfer functions were developed from the subsequent training set for inferring past conductivity (r2= 0.87), pH (r2= 0.77), and ratios between alkali and alkaline earth metals (r2 = 0.81) and carbonate-bicarbonate and sulphate + chloride ions (r2 = 0,82) (Gasse et al., 1995) and the model has subsequently been applied to several diatom sequences to reconstruct lake chemistry (e.g. Fritz et al., 1999; Dagnachew et al., in press ; Chalié and Gasse, in press ; Gasse, 2001 ; Gasse, in press ; Verschuren et al., 2000 ).





Calcium µeq/l 259 10 224550 7476

Chloride µeq/l 259 40 1248240 62890 Conductivity µS/cm 275 40 400000 13067

Magnesium µeq/l 260 10 183600 6296


pH pH units 268 5.5 10.9 7.93 Potassium µeq/l 253 0.8 35300 1937

Salinity g/l 78 288 74300 11503

Silica mg/l 131 0.1 320 42.2 Site surface area at time of sampling

km2 136 0.01 68800 5115

Sodium µeq/l 254 110 1222300 74446

Sulphate µeq/l 232 10 306100 12930

Total phosphorus µg/l 91 16 50 25.7 Water depth of diatom sample m 180 0.05 176 7.75


Barker, P., Telford, R., Gasse, F., & Thévenon, F.. in press. Late Pleistocene and

Dataset Id Name N AfricaE East African dataset 187 AfricaN North African dataset 97


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Barker, P., Telford, R., Gasse, F., & Thévenon, F.. in press. Late Pleistocene and Holocene paleohydrology of Lake Rukwa, Tanzania, inferred from diatom analysis. Palaeogeography, Palaeoclimatology, Palaeoecology.

Chalié, F. and Gasse, F., in press. A 13,500 years diatom record from the tropical East African Rift Lake Abiyata (Ethiopia). Palaeogeogr., Palaeoclim., Palaeoecol..

Dagnachew Legesse, F. Gasse, O. Radakovitch, C. Vallet-Coulomb, R. Bonnefille, D. Verschuren, E. Gibert, P. Barker. Sous presse. Environmental nvironmental changes in a tropical lake (Abiyata, Ethiopia) during recent centuries. Palaeogeogr., Palaeoclim., Palaeoecol.

Fritz S, Cumming B.F., Gasse F.,Laird K.R., 1999. Diatoms as indicators or Hydrologic and climatic change in saline lakes. In E. Stoermer and J.P. Smol (Eds.) , The Diatoms: Applications to Environmental and Earth Science. Cambridge University Press, Cambridge, 41-72.

Gasse, F., in press. Diatom-inferred salinity and oxygen isotopes in Holocene waterbodies of the Western Sahara and Sahel (Africa).Implications for climate and water resource variability, Quaternary Sciences Reviews.

Gasse, F., Barker, Ph., Gell, P.A., Fritz, S.C. and Chalié, F., 1997 -Diatom-inferred salinity in palaeolakes, an indirect tracer of climate change. Quaternary Science Review, vol. 15:1-19.

Gasse, F., 1998. Water resources variability in tropical and subtropical Africa in the past. In: E. Servat et al. (Eds), Water resources variability in Africa during the Xxth Century. IAHS, 252, 97-106.

Gasse, F., 2000. Hydrological changes in the African tropics since the last glacial maximum ; Quaternary Sciences Reviews, 19, 189-211.

Gasse, F., 2001. Perspectives. Hydrological Changes in Africa. Science, 293, 2259-2260.

Verschuren, D., Laird, K.R. and Cumming, B.F., 2000. Rainfall and drought in equatorial east Africa during the past 1,100 years. Nature, 403: 410-414.


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Dataset information

East African dataset

EDDI dataset code AfricaE Dataset type Salinity Number of samples 187 Collection date 1960 - 1986 Contributor Francoise Gasse Contact Francoise Gasse

The East African training set includes samples from 98 sites situated between 19°N and 14°S in latitude, 27°N and 43°E in longitude. They range from afro-alpine bogs at altitude of up to 4000 m to hypersaline lakes lying below sea-level. The conductivity ranges from 40 to 50,000 µS cm-1 and the pH from 5 to 10.9. The chemical facies is of the alkaline earths/bicarbonate type for freshwaters, to the Na/carbonate or Na/chloride type for highly concentrated waters. The training set consists of 187 samples. Most samples have been collected by F. Gasse (98) from 1970, P. Kilham (19), J.-F. Talling (14) and R.B. Wood (14). Other collaborators in collecting diatom samples have been C. Barton, R.M. Baxter, J. Green, J. Kalff, ad J. L. Richardson. All diatom samples were counted by F. Gasse. Detailed descriptions of the diatom samples and chemical analyses were published by Gasse et al. (1983). This paper also provides a numerical classification of the diatom assemblages. A total of 579 taxa was identified in the data set, the taxonomy and ecology of which are discussed and illustrated by Gasse (1986a). This data set was used to develop transfer functions for estimating pH (Gasse and Tekaia, 1983) and conductivity (Gasse and Tekaia, unpublished) and the model has subsequently been applied to diatom sequences to reconstruct lake pH and salinity histories and related changes in the water balance (e.g. Gasse, 1986b ; Barker, 1990 ; Barker et al., 1991).



Variable Units N Min Max Mean

Alkalinity µeq/l 174 160 968000 35601 Calcium µeq/l 175 10 224550 4366

Chloride µeq/l 170 40 1248240 46647

Conductivity µS/cm 180 40 47680 5195 Magnesium µeq/l 176 10 102790 2488


pH pH units 178 5.5 10.9 8.02 Potassium µeq/l 169 10 30690 2088

Salinity g/l 18 288 59600 14865


km2 110 0.01 68800 6320

Sodium µeq/l 170 110 1110000 78904 Sulphate µeq/l 152 10 232000 7976





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Barker, P.A., 1990. Diatoms as palaeolimnological indicators : A reconstruction of late Quaternary environments in two East African salt lakes. Thesis. Loughbourough Univ., 267 pp.

Barker, P., Gasse, F., Roberts, N., et Taieb, M., 1991. Taphonomy and diagenesis in diatom assemblages: a Late Pleistocene palaeoecological study from Lake Magadi, Kenya. In E. Smith (Ed), Environmental History and Paleolimnology, Kluwer Ac. Press., Dordrecht.

Gasse, F., Talling, J.F. & Kilham, P., 1983. Diatom assemblages in East Africa: classification, distribution and ecology. Rev. Hydrobiol. Trop. ,16, 1, 3-34.

Gasse, F. & Tekaia, F., 1983. Transfer functions for estimating paleocological conditions (ph) from East African diatoms. Hydrobiologia, 103, 85-90.

Gasse, F., 1986b. East African diatoms and water pH. In: Smol et al. Eds., Diatoms and Lake Acidity. Developments in Hydrobiology, 29, 149-168. Junk Publ., Dordrecht.

Gasse, F., 1986a. East African Diatoms. Taxonomy, ecological distribution. Bibliotheca Diatomologica. Bd 11, 202 pp. .J. Cramer, Stuttgart.


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Dataset information

North African dataset

EDDI dataset code AfricaN Dataset type Salinity Number of samples 97 Collection date 1975 - 1986 Contributors Leila Ben Khelifa, Francoise Gasse Contact Francoise Gasse

The North African dataset consists from samples from Tunisia (66), Algeria (3), Morocco (26), and Niger (20). In Tunisia, samples were collected from the Mediterranean northern regions to the margins of the Sahara southwards by L. Ben Khelifa and F. Gasse (1985-1989). In southern Tunisia, samples were taken from small permanent groundwater-fed waterbodies and temporary salt lakes, small artificial ponds developed around boreholes, and in mini reservoir lakes and swamps along Wadi el Akarit. Samples from hydrothermal springs have been collected throughout the country. In northern Tunisia, freshwater samples were also taken from the Mejerda Channel. Waters range from fresh to metasaline. Most samples are of the sodium/chloride or calcium-magnesium/ sulphate type. Diatoms were counted by L. Ben Khelifa. Details of diatom and hydrochemical analyses are given in Ben Khelifa (1989). Sites from southern Algeria, collected by F. Gasse en 1985, show clear similarities with the waterbodies of southern Tunisia. The 26 samples from Morroco were collected by F. Gasse in 1989 from 17 localities situated between 30°30?-34°30?N and 5°-7°30?E, at altitude ranging from 300 to 2050 m. Sites are distributued in the western plains close to Casablanca, the Middle Atlas mountains, and the more arid southweast margins of the Atlas ranges, from a large variety of waterbodies (permanent and temporary natural lakes, man-made lakes, and wadis. Conductivities range from 195 to 3900 µS cm-1. Freshwaters are of the calcium-sodium/bicarbonate type, while oligosaline waters are of the sodium/chloride type. Diatom samples were counted by F. Gasse. In southern Niger, samples were collected from the Niger River, the Bara salt pond near Niamey, and from interdunal depressions on the Manga Plateau occupied by permanent or ephemeral waterbodies. A few samples from northern Niger (Aïr) have also been collected from groundwater-supplied ponds. Most waterbodies are of the sodium/carbonate-bicarbonate type. Samples from Niger were collected and analyzed by F. Gasse, except those from the Bara pond (M.-C. Lang). The main characteristics of the water chemistry and diatom communities of the Niger samples are presented in Gasse (1987).



Alkalinity µeq/l 83 100 40110 4515

Calcium µeq/l 84 11.2 83800 13955 Chloride µeq/l 89 200 930800 93916

Conductivity µS/cm 95 345 400000 27981

Magnesium µeq/l 84 830 183600 14274 Maximum depth of lake m 29 0.1 20 4.58

pH pH units 90 5.5 9.1 7.75


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pH pH units 90 5.5 9.1 7.75

Potassium µeq/l 84 0.8 35300 1635 Salinity g/l 60 441 74300 10494

Silica mg/l 14 0.1 27 10.7

Site surface area at time of sampling

km2 26 10 18 13.5

Sodium µeq/l 84 780 1222300 65424

Sulphate µeq/l 80 50 306100 22343 Total phosphorus µg/l 1 20 20 20



Ben Khelifa, L., 1989. Diatomées continentales et paléomilieux du Sud-Tunisien (Palhydaf Site 1) au Quaternaire supérieur. Approche statistique basée sur les diatomées et les milieux naturels. Thesis. Univ. Paris-Sud, 233 pp.

Carvalho, L.R., Cox, E.J., Fritz, S.C., Juggins, S., Sims, PA., Gasse, F., and Battarbee, R.W., 1995, Standardizing the taxonomy of saline lake Cyclotella spp. Diatom Research, 10 (2) 229-240.

El Hamouti, N., Lamb, H., Fontes, J.Ch. et Gasse, F., 1991. Changements hydroclimatiques abrupts dans le Moyen Atlas marocain depuis le dernier maximum glaciaire. C. R. Acad. Sci., Paris. 313 , 259-265.

Fontes, J.Ch., Gasse, F., Callot, Y., Plaziat, J.C., Carbonel, P., Dupeuple, P.A. & Kaczmarska, I., 1985. Freshwater to marine-like environments from holocene lakes in Northern Sahara. Nature, 317, 608-610.

Gasse, F., Fontes, J.Ch., Plaziat, J.C., Carbonel, P., Kaczmarska, I. , De Deckker, P., Soulié-Marsche, I., Callot, Y., & Dupeuple, P.A., 1987. Biological remains, geochemistry and stable isotopes for the reconstruction of environmental and hydrological changes in the Holocene lakes from North Sahara. Paleoecol., Palaeogeogr , Palaeoclimat., 60, 1-46.

Gasse, F., 1987. Diatoms for reconstructing palaeoenvironments and palaeohydrologyn tropical semi-arid zones. Example of some lakes from Niger since 12,000 BP. Hydrobiologia, 154 : 127-163.

Gasse, F., Téhet, R., Durand, A., Gibert, E., Fontes, J.Ch., 1990. The arid-humid transition in the Sahara and the Sahel during the last deglaciation. Nature, vol. 346(6280):141-156.

Gasse, F., Van Campo, E., 1994. Abrupt post-glacial climate events in West Asia and North Africa monsoon domains. EPSL, 126, 435-456.

Lamb, H.F., Gasse, F., Ben Kaddour, A., El Hamouti, N., Van der Kaars, S., Perkins, W.T., Pearce, N.J., Roberts, C.N., 1995. Relation between century-scale Holocene arid intervals in tropical and temperate zones. Nature, 373,134-137.


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Dataset information

Caspian saline lake dataset

EDDI dataset code Caspian Dataset type Salinity Number of samples 29 Collection date 1996 Contributors Steve Juggins, Jane Reed Contact Steve Juggins

The Caspian dataset consists of 29 benthic and plankton samples lakes in the Berouskije Bugri area of the Caspian Lowlands, S. Russia. The samples were collected summer 1996 by K. Labunskaya of the Astrakhan State Technical University and Steve Juggins, and diatoms were counted by Jane Reed. The dataset spans a gradient from permanent slightly brackish lakes (salinity < 2 g/l) to shallow, ephemeral hypersaline saline playas (salinity > 100 g/l). The majority of lakes are of the NaMg-Cl brine types, although sulphate is an important secondary anion for five sites, and three sites show elevated calcium concentrations. Although there is a very strong relationship between diatom composition and salinity this dataset is considered too small to use for a local transfer function and so samples are only used in the larger combined Salinity transfer function.




Calcium µeq/l 29 980 3152210 365892 Chloride µeq/l 29 14230 5103420 886498


Magnesium µeq/l 29 1280 933740 174194 Maximum depth of lake m 29 0.1 0.5 0.338

Nitrate µg/l 29 110 1220 680

pH pH units 29 6.85 8.15 7.52 Potassium µeq/l 29 8680 776320 174032

Salinity g/l 29 1820 325857 58927

Sodium µeq/l 29 12280 1241320 259080

Soluable reactive phosphorus µg/l 29 20 490 148 Sulphate µeq/l 29 9680 397280 99766

Water depth of diatom sample m 29 0.1 0.5 0.338


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Dataset information

Combined salinity dataset

EDDI dataset code Salinity Dataset type Salinity Number of samples 387 Collection date 1960 - 1996 Contributor The EDDI Participants Contact Steve Juggins




Alkalinity µeq/l 360 100 968000 20074



Magnesium µeq/l 363 10 2169880 69291 Maximum depth of lake m 279 0.02 266 13.7

Nitrate µg/l 29 110 1220 680

pH pH units 371 5.5 10.9 7.97 Potassium µeq/l 356 0.8 776320 18170

Salinity g/l 181 133 333021 29699


km2 136 0.01 68800 5115

Sodium µeq/l 357 110 3872380 135409 Soluable reactive phosphorus µg/l 29 20 490 148

Sulphate µeq/l 335 10 1765300 64221


Dataset Id Name N AfricaE East African dataset 187 AfricaN North African dataset 97 Caspian Caspian saline lake dataset 29 Spain Spanish saline lake dataset 74


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Dataset information

Spanish saline lake dataset

EDDI dataset code Spain Dataset type Salinity Number of samples 74 Collection date 1990 - 1993 Contributor Jane Reed Contact Jane Reed

The Spanish training set includes 74 samples from 57 sites situated between 42°N and 36°S in latitude, 6°W and 2°E in longitude. Sampling was restricted to endorheic zones of flat topography, from the interior plateau: La Mancha and Albacete (central Spain) and Zamora (northeastern Spain), and from the lowlands of Andalucía (southern Spain) and the Ebro basin (northeastern Spain), at altitudes ranging from 2-1020m asl. Conductivity ranges from 150 to 338,000 µS cm-1. There is a tendency for water chemistry to be dominated by sulphates in the central plateau region, chlorides in Andalucía, and mixed chloride- or sulphate-dominance in the Ebro basin, dependent on the mineralogy of underlying Tertiary or Triassic marine or continental evaporites. Carbonate-dominated waters are rare, comprising a small number of freshwater, karstic systems. Samples were collected by J. Reed during her PhD (UCL Geography). Following removal of four outliers from the training set, a conductivity transfer function (r2 = 0.91) was derived for Spanish salt lakes (Reed 1995, 1998), which has been applied to one Spanish sequence (Reed 1995, Reed in press, Reed et al., 2001) and in unpublished work in Mexico. Based mainly on the above combined African transfer function, optima from the Spanish transfer function were also used in conductivity reconstruction for sites in Turkey (Reed et al. 1999, Roberts et al. 2001).






Magnesium µeq/l 74 70 2169880 249512 Maximum depth of lake m 74 0.02 9.5 1.42

pH pH units 74 6.33 9.92 8.27

Potassium µeq/l 74 100 487200 12586

Salinity g/l 74 133 333021 37426 Sodium µeq/l 74 220 3872380 296193

Sulphate µeq/l 74 450 1765300 211095



Reed, J. (1995). The potential of diatoms, ostracods and other palaeolimnological indicators for Holocene palaeoclimate research in southern Spanish salt lakes. Limnetica 12: 25-39.

Reed, J. (1995). The potential of diatoms and other palaeolimnological indicators for Holocene palaeoclimate reconstruction from Spanish salt lakes, with special reference


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Holocene palaeoclimate reconstruction from Spanish salt lakes, with special reference to the Laguna de Medina (Cadiz, southwest Spain). Unpublished PhD, University College London.

Reed, J. M. (1998). Diatom preservation in the recent sediment record of Spanish lakes: implications for palaeoclimate study. Journal of Paleolimnology 19: 129-137.

Reed, J. M. (1998). A diatom-conductivity transfer function for Spanish salt lakes. Journal of Paleolimnology 19: 399-416.

Reed, J.M., Roberts, N. and Leng, M.J., 1999. An evaluation of the diatom response to Late Quaternary environmental change in two lakes in the Konya Basin, Turkey, by comparison with stable isotope data. Quaternary Science Reviews 18: 631-647.

Reed, J.M., Stevenson, A.C. and Juggins, S., 2001. A multi-proxy record of Holocene climate change in southwest Spain: the Laguna de Medina, Cádiz. The Holocene 11: 705-717.

Roberts, N., Reed, J., Leng. M.J., Kuzucuoglu, C., Fontugne, M., Bertaux, J., Woldring, H., Bottema, S., Black, S., Hunt, E. and Karabiyikoglu, M.., 2001. The tempo of Holocene climatic change in the eastern Mediterranean region: new high-resolution crater-lake sediment data from central Turkey. The Holocene 11.


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Dataset information

Welsh TP dataset

EDDI dataset code CCW Dataset type TP Number of samples 11 Collection date 1993 - 1994 Contributor Helen Bennion Contact Helen Bennion

This dataset includes 11 lakes distributed throughout Wales including small, shallow and large, deep waterbodies. All lakes are circumneutral to alkaline and cover a long total phosphorus gradient. Surface sediment samples were collected by University College London during 1993-1994 and diatoms were counted by Helen Bennion and Tim Allott. The dataset is part of a project which aimed to develop an integrated biological classification scheme for 30 Welsh lakes (Allott & Monteith, 1999). These sites form part of a larger diatom-total phosphorus training set of 152 NW European lakes (Bennion et al., 1996a). Palaeolimnological studies have been undertaken at a number of these sites (e.g. Bennion, 1995, 1996; Bennion & Appleby, 1999; Bennion et al., 1996b, 1997a. 1997b, 1998).




Calcium µeq/l 11 88.8 2202 735

Chloraphyll-a µg/l 11 1.07 24.5 9.87

Chloride µeq/l 11 105 1824 583 Conductivity µS/cm 11 27.5 442 151

Magnesium µeq/l 11 33.5 634 258

Maximum depth of lake m 11 1.8 36 8.15 Nitrate µg/l 11 20 700 125

pH pH units 11 6.35 8.61 7.17

Potassium µeq/l 11 4 134 35.3 Silica mg/l 11 0.84 7.79 2.65

Sodium µeq/l 11 109 1846 554

Soluable reactive phosphorus µg/l 11 1.75 1016 109 Sulphate µeq/l 11 64 449 181

Total phosphorus µg/l 11 5.28 1085 145



Allott, T.E.H. & Monteith, D.T. (1999). Classification of lakes in Wales for conservation using integrated biological data.. CCW Contract Science Report No. 314.

Bennion, H. (1995). Quantitative reconstructions of the nutrient histories of three Anglesey lakes. CCW Contract Science Report No. 87.


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Bennion, H., Duigan, C. A., Haworth, E. Y., Allott, T. E. H., Anderson, N. J., Juggins, S. & Monteith, D. T. (1996b) The Anglesey Lakes, Wales, UK- Changes in trophic status of three standing waters as inferred from diatom transfer functions and their implications for conservation. Aquatic Conservation: Marine and Freshwater Ecosystems, 6, 81-92.

Bennion, H., Juggins, S. & Anderson, N. J. (1996a) Predicting epilimnetic phosphorus concentrations using an improved diatom-based transfer function and its application to lake eutrophication management. Environmental Science and Technology, 30, 2004-2007.

Bennion, H. (ed). (1996) A study of recent environmental change within selected standing waters proposed as Special Areas of Conservation. A report to the Countryside Council for Wales by ENSIS Ltd. Environmental Change Research Centre, Research Report No. 22, University College London.

Bennion, H., Shilland, E. & Appleby, P.G. (1997b) A study of recent environmental change at Llyn Tegid (Lake Bala), Wales. A Report to the Environment Agency. Environmental Change Research Centre, Research Report No. 36, University College London.

Bennion, H., Allott, T.E.H., Appleby, P.G., Hunt, M., Oliver, E. & Patrick, S.T. (1997a) A study of recent environmental change within selected standing waters proposed as Special Areas of Conservation (SAC) in Wales - Llyn Idwal, Llyn Cwellyn and Llyn Safadden (Llangorse Lake) Phase II. CCW Research Report No. 187.

Bennion, H., Allott, T.E.H. & Shilland, E. (1998). Investigation of environmental change in two mesotrophic lakes in Mid-Wales: Llyn Eiddwen and Llyn Fanod. Final report to CCW by ENSIS Ltd. Environmental Change Research Centre, Research Report No. 46, University College London.

Bennion, H. & Appleby, P.G. (1999) An assessment of recent environmental change in Llangorse Lake using palaeolimnology. Aquatic Conservation: Marine and Freshwater Ecosystems, 9, 361-375.


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Dataset information

Central European dataset

EDDI dataset code CEuro Dataset type TP Number of samples 86 Collection date 1900 - 1994 Contributors Roland Schmidt, Sybille Wunsam Contact Sybille Wunsam

This dataset includes 86 lakes from the Northern (Austria, Germany) and Southern Alps (Northern Italy), their pre-alpine lowlands, and Carinthia, Austria. The lakes are diverse in their types but are mostly large, deep, upland waters. The lakes have circumneutral to alkaline pH and cover a long total phosphorus gradient from oligotrophic to hypertrophic conditions. Surface sediment samples were collected by the Institute of Limnology, Mondsee between 1990 and 1994 and diatoms were counted by Sybille Wunsam. A WA diatom-total phosphorus transfer function was developed from these data and details are given in Wunsam & Schmidt (1995) and Wunsam et al. (1995). The WA model with tolerance downweighting and classical deshrinking performed best (apparent r2=0.57; RMSE=0.318 log10TP µg l-1; RMSEP=0.346 log10TP µg l-1). Palaeolimnological studies have been undertaken at a number of these sites (e.g. Alefs et al., 1996; Bennion et al., 1995; Marchetto & Bettinetti, 1995; Schmidt et al., 1998; Wunsam & Schmidt, 1995).


Summary of environmental data for this dataset: Variable Units N Min Max Mean Ammonium µg/l 86 0.01 879 88.9


Maximum depth of lake m 86 2.1 410 52.6 Nitrite µg/l 86 20 4320 545

pH pH units 86 6.8 8.5 8.11

Secchi depth m 86 0.6 10.6 3.99 Total phosphorus µg/l 86 2 266 23.5



Alefs, J., J. Müller & S. Wunsam 1996. Die Rekonstruktion der epilimnischen Phosphorkonzentrationen im Ammersee seit 1958. GWF Wasser Abwasser 137/8: 443-447.

Bennion, H., Wunsam, S. & Schmidt, R. (1995) The validation of diatom-phosphorus transfer functions: an example from Mondsee, Austria. Freshwater Biology, 34, 271-283.

Marchetto, A. and R. Bettinetti. 1995. Reconstruction of the phosphorus history of two deep, subalpine Italian lakes from sedimentary diatoms, compared with long-term


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deep, subalpine Italian lakes from sedimentary diatoms, compared with long-term chemical measurements. Mem. Ist. ital. Idrobiol., 53: 27-38.

Schmidt, R., S. Wunsam, U. Brosch, J. Fott, A. Lami, H. Löffler, A. Marchetto, H W.

M. Prazaková & B. Schwaighofer 1998. Late and post-glacial history of meromictic Längsee (Austria), in respect to climate change and anthropogenic impact. Aquatic Sciences 60: 56-88.

Wunsam, S., R. Schmidt & R. Klee 1995. Cyclotella-taxa (Bacillariophyceae) in lakes of the Alpine region and their relationship to environmental variables. Aquatic Sciences 57/4: 360-386.

Wunsam, S. & Schmidt, R. 1995. A diatom-phosphorus transfer function for Alpine and pre-alpine lakes. Memorie dell?Istituto Italiano di Idrobiologia 53: 85-99.


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Dataset information

Danish TP dataset

EDDI dataset code DK Dataset type TP Number of samples 28 Collection date 1991 Contributor John Anderson Contact John Anderson

This dataset includes 28 relatively small, shallow lakes from Denmark. All sites are lowland, alkaline and nutrient-rich. Surface sediment samples were collected during 1991 and diatoms were counted by John Anderson. The Danish data set is not published but is based on the Water Environment Survey lakes (Kristensen et al., 1991). These sites form part of a larger training set used to develop a NW European diatom-total phosphorus inference model (Bennion et al., 1996). Palaeolimnological studies have been undertaken at a number of these sites (Anderson & Odgaard, 1994; Bennion et al., 1996a).




Chloraphyll-a µg/l 28 9 351 91.5

Conductivity µS/cm 10 294 782 440 Maximum depth of lake m 28 1.5 37.7 7.8

pH pH units 28 7.85 9.45 8.42

Secchi depth m 28 0.32 3.5 1.33

Silica mg/l 28 0.53 8.26 3.37 Total K nitrogen µg/l 28 970 8840 3871

Total phosphorus µg/l 28 27 1189 230



Anderson, N.J. & Odgaard, B.V. 1994. Recent palaeolimnology of three shallow Danish lakes. Hydrobiologia 275/6, 411-422.


Kristensen, P., Jensen, J.P., Jeppesen, E., Erlandsen, M. 1991. Ferske vandområ der-sø er. Vandmiljø planens Overvå gningsprogram 1990. DMU Faglig rapport nr. 38, 104 pp + appendices (in Danish).


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Dataset information

French Massif Central TP dataset

EDDI dataset code French Dataset type TP Number of samples 28 Collection date 1996 - 1998 Contributor Patrick Rioual Contact Patrick Rioual

This dataset includes 28 surface sediment samples from lakes in the Massif Central region of France. The lakes are diverse in their origin, volcanic or glacial, and their morphometry, size and depth, from deep crater lakes to shallow glacial lakes. They are situated along an altitudinal gradient from 630-1250 m a.s.l. The lakes have circumneutral to alkaline pH and cover a long total phosphorus gradient from ultra-oligotrophic to hypertrophic conditions. Surface sediment samples were collected between 1996 and 1998 and diatoms were counted by Patrick Rioual. A diatom-alkalinity transfer function was developed from these data and details are given in Rioual (2000). Palaeolimnological studies of long sediment cores, spanning at least the last glacial/interglacial cycle, have been undertaken at a number of these sites (Pailles, 1989; Reille et al., 2000; Rioual et al., 2001).



Alkalinity µeq/l 28 44.5 1728 459

Aluminium (total) µg/l 28 20 90 54.6 Calcium µeq/l 28 12.5 740 225

Chloraphyll-a µg/l 19 0.43 19.6 5.38

Chloride µeq/l 28 28.5 727 106 Conductivity µS/cm 28 16.5 211 59.4

Iron µg/l 24 10 2920 227

Magnesium µeq/l 28 21.4 722 177 Manganese µg/l 14 10 60 17.1



Potassium µeq/l 28 2.05 78 28

Secchi depth m 21 0.4 11.8 3.73 Silica mg/l 19 0.9 21.2 6.79

Sodium µeq/l 28 6.52 645 118

Soluable reactive phosphorus µg/l 19 2.33 57 8.64 Sulphate µeq/l 28 4.37 184 51.3


Water depth of diatom sample m 28 1 109 29 Zinc µg/l 27 10 120 68.1



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Pailles, C. 1989. Les diatomées du lac du Bouchet (Massif-Central, France): reconstruction des paléoenvironments au cours des 120 derniers millénaires. Unpublished PhD (Thèse de Doctorat en Science), Université Aix-Marseille II.

Reille, M., Beaulieu, J.-L. de, Svobodova, H., Andrieu-Ponel, V. & Goeury, C. 2000. Pollen analytical biostratigraphy of the last five climatic cycles from a long continental sequence from the Velay region (Massif Central, France). Journal of Quaternary Science 15, 665-685.

Rioual, P. 2000. Diatom assemblages and water chemistry of lakes in the French Massif Central: a methodology for reconstruction of past limnological and climate fluctuations during the Eemian period. Unpublished PhD, University College London.

Rioual, P., Andrieu-Ponel, V., Rietti-Shati, M., Battarbee, R.W., Beaulieu, J.-L. de, Cheddadi, R., Reille, M., Svobodova, H. & Shemesh, A. 2001. High-resolution record of climate stability in France during the Last Interglacial. Nature (in press).


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Dataset information

Northern Irish dataset

EDDI dataset code NI Dataset type TP Number of samples 54 Collection date 1990 - 1992 Contributor John Anderson Contact John Anderson

This dataset includes 54 relatively small, shallow lakes from Northern Ireland. All sites are lowland, alkaline and cover a wide range of phosphorus concentrations. Surface sediment samples were collected during April 1990 and May 1991 and diatoms were counted by John Anderson. A regional diatom-total phosphorus transfer function was developed from these data and details are given in Anderson et al. (1993) and Anderson & Rippey (1994). These sites also form part of a larger training set used to develop a NW European diatom-total phosphorus inference model (Bennion et al., 1996). Palaeolimnological studies have been undertaken at a number of these sites (e.g. Anderson, 1989, 1997; Anderson & Rippey, 1994; Anderson et al., 1993; Rippey et al., 1997).




Ammonium µg/l 49 7.5 1107 99.9

Calcium µeq/l 54 170 3862 1378

Chloraphyll-a µg/l 54 2.54 201 30.5 Chloride µeq/l 54 274 1395 647


Magnesium µeq/l 54 98.8 1292 508 Maximum depth of lake m 54 1.1 20 7.31

Nitrate µg/l 54 30 3260 764

pH pH units 54 7.09 8.6 7.81 Potassium µeq/l 54 5.12 204 66.1

Silica mg/l 54 1.23 10.9 3.66

Sodium µeq/l 54 176 872 428 Soluable reactive phosphorus µg/l 49 5.14 514 50.2

Sulphate µeq/l 54 74.9 1064 340

Total K nitrogen µg/l 49 330 2230 1025 Total phosphorus µg/l 54 11 800 108



Anderson, N. J. 1989. A whole-basin diatom accumulation rate for a small eutrophic lake in Northern Ireland and its palaeoecological implications. Journal of Ecology, 77, 926-946.


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Anderson, N. J., Rippey, B. & Gibson, C.E. 1993. A comparison of sedimentary and diatom-inferred phosphorus profiles: implications for defining pre-disturbance nutrient conditions. Hydrobiologia, 253, 357-366.

Anderson, N.J. & Rippey, B. 1994. Monitoring lake recovery from point-source eutrophication: the use of diatom-inferred epilimnetic total phosphorus and sediment chemistry. Freshwater Biology, 32, 625-639.

Anderson, N. J. 1997. Historical changes in epilimnetic phosphorus concentrations in six rural lakes in Northern Ireland. Freshwater Biology, 38, 427-440.


Rippey, B., Anderson, N.J. & Foy, R.H. 1997. Accuracy of diatom-inferred total phosphorus concentrations and the accelerated eutrophication of a lake due to reduced flushing and increased internal loading. Canadian Journal of Fisheries and Aquatic Sciences 54: 2637-2646.


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Dataset information

NW Europe dataset

EDDI dataset code NWEuro Dataset type TP Number of samples 164 Collection date 1987 - 1994 Contributors John Anderson, Helen Bennion, Steve Juggins Contacts John Anderson, Helen Bennion, Steve Juggins

The Northwest European dataset is an amalgamation of six smaller regional datasets from southeast England, the English Midlands, Wales, Northern Ireland, Denmark, and Sweden. The lakes are mostly lowland, shallow, small, slightly acid to alkaline waters with agricultural activity and/or forestry in the catchments. The combined dataset spans a long TP gradient from oligotrophic to hypertrophic waters. Surface sediment samples (0-1 cm) were collected from the deepest point of each lake over the period 1990-1993 and diatoms were counted by either Helen Bennion (southeast England, meres, Wales), John Anderson (Northern Ireland, Denmark, Sweden) or Tim Allott (Wales). A program of taxonomic harmonisation was undertaken to construct a unified database of diatom data. The full dataset consists of 164 lakes but this was reduced to a training set of 152 lakes following data screening. This training set was used to develop a WAPLS diatom-TP transfer function and component 2 gave the lowest prediction error (RMSEP=0.21 log10TP µg l-1, apparent r2=0.91). Further details of the training set and transfer function are given in Bennion et al., 1996) and the model has subsequently been applied to numerous diatom sequences to reconstruct lake nutrient histories (e.g. Bennion et al., 1996, 1999, 2000, 2001).





Aluminium (total) µg/l 12 33 171 83.1 Ammonium µg/l 49 7.5 1107 99.9

Calcium µeq/l 136 88.8 5599 1909

Chloraphyll-a µg/l 137 1.07 351 41 Chloride µeq/l 136 24 8525 870

Conductivity µS/cm 146 25.2 1327 339

Iron µg/l 12 30 487 158 Magnesium µeq/l 136 33 4186 612

Dataset Id Name N CCW Welsh TP dataset 11 DK Danish TP dataset 28 NI Northern Irish dataset 54 SCM UK meres TP dataset 33 SEng Southern England dataset 26 SWAP SWAP dataset 12


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Manganese µg/l 12 8 306 57.5 Maximum depth of lake m 164 0.7 37.7 6.82

Nitrate µg/l 136 0.8 7620 1099

pH pH units 164 5.75 9.45 7.74 Potassium µeq/l 136 4 624 97.6

Secchi depth m 87 -1 3.5 1

Silica mg/l 164 0.22 10.9 3.11 Sodium µeq/l 124 109 7948 729

Soluable reactive phosphorus µg/l 119 1.75 1016 87.5

Sulphate µeq/l 136 55 4496 696 Total K nitrogen µg/l 77 330 8840 2060

Total nitrogen µg/l 12 262 982 490

Total organic carbon mg/l 12 3 17 8.28 Total phosphorus µg/l 164 5 1189 172




Bennion, H. & Appleby, P.G. (1999) An assessment of recent environmental change in Llangorse Lake using palaeolimnology. Aquatic Conservation: Marine and Freshwater Ecosystems, 9, 361-375.

Bennion, H., Monteith, D.T. & Appleby, P.G. (2000) Temporal and geographical variation in lake trophic status in the English Lake District: evidence from (sub)fossil diatoms and aquatic macrophytes. Freshwater Biology, 45, 394-412.

Bennion, H., Appleby, P.G. & Phillips, G.L. (2001) Reconstructing nutrient histories in the Norfolk Broads, UK: implications for the role of diatom-total phosphorus transfer functions in shallow lake management. Journal of Paleolimnology, 26, 181-204.


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UK meres TP dataset

EDDI dataset code SCM Dataset type TP Number of samples 33 Collection date 1993 Contributor Helen Bennion Contact Helen Bennion

This dataset includes 33 lakes from the Cheshire and Shropshire meres region of the English Midlands. They are all relatively small, shallow, lowland waterbodies. All lakes are alkaline and nutrient-rich with base-rich geology. Surface sediment samples were collected during February 1993 by University College London and diatoms were counted by Helen Bennion. These sites form part of a larger diatom-total phosphorus training set of 152 NW European lakes (Bennion et al., 1996) and have also been used to develop a chironomid-total phosphorus inference model (Brooks et al., 2001). Palaeolimnological studies have been undertaken at a number of these sites (e.g. Bennion et al., 1997, Brooks et al., 2001).




Calcium µeq/l 33 391 4840 2858 Chloraphyll-a µg/l 18 8.4 62.9 23.8

Chloride µeq/l 33 450 1838 1077

Conductivity µS/cm 33 118 724 461 Magnesium µeq/l 33 135 2340 1079

Maximum depth of lake m 33 0.9 29.5 7.08


Potassium µeq/l 33 41.5 496 163

Secchi depth m 33 0.4 3.1 1.22 Silica mg/l 33 0.25 8.31 3.66

Sodium µeq/l 33 312 1389 738

Soluable reactive phosphorus µg/l 33 4.73 907 141 Sulphate µeq/l 33 114 3119 1164

Total phosphorus µg/l 33 72.9 1169 289




Bennion, H., Monteith, D.T. & Appleby, P.G. (1997c) Nutrient reconstructions in


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Bennion, H., Monteith, D.T. & Appleby, P.G. (1997c) Nutrient reconstructions in standing waters. Final report to English Nature by ENSIS Ltd. Environmental Change Research Centre, Research Report No. 37, University College London.

Brooks S.J., Bennion, H. & Birks, H.J.B. (2001). Tracing lake trophic history with a chironomid-total phosphorus inference model. Freshwater Biology, 46, 513-533.


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Southern England dataset

EDDI dataset code SEng Dataset type TP Number of samples 26 Collection date 1990 Contributor Helen Bennion Contact Helen Bennion

The original dataset included 31 ponds and pools from southeast England. They are all relatively small, shallow, lowland, artificial waterbodies. All sites have circumneutral to alkaline pH and are nutrient-rich. Surface sediment samples were collected during July and August 1990 by University College London and diatoms were counted by Helen Bennion. Following removal of one outlier, a training set of the remaining 30 ponds was used to generate a diatom TP transfer function (Bennion, 1994, 1995; Bennion & Smith, 2000; Bennion et al., 1997). The diatom inference model had good predictive power (apparent r2=0.79; RMSE=0.161 log10TP µg l-1; RMSEP=0.279 log10TP µg l-1). A subset of 26 of these sites is included in EDDI and this forms part of the larger combined NW European training set (Bennion et al., 1996). Palaeolimnological studies have been undertaken at a number of the southeast England sites (Bennion, 1993, 1994).




Calcium µeq/l 26 1051 5599 3030

Chloraphyll-a µg/l 26 2.92 182 33.6

Chloride µeq/l 26 424 8525 1546 Conductivity µS/cm 26 206 1327 490


Maximum depth of lake m 26 0.7 12 2.19 Nitrate µg/l 26 690 5580 1864

pH pH units 26 6.83 8.59 7.7

Potassium µeq/l 26 30.5 624 143 Secchi depth m 26 -1 2.4 0.369

Silica mg/l 26 0.22 4.25 1.95

Sodium µeq/l 26 380 7948 1416 Soluable reactive phosphorus µg/l 26 3.28 520 80.9

Sulphate µeq/l 26 272 4496 1302

Total phosphorus µg/l 26 25.5 646 182 Water depth of diatom sample m 26 0.7 12 2.19


Bennion, H. (1993). A diatom-phosphorus transfer function for eutrophic ponds in southeast England. Unpublished PhD, University College London.


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Bennion, H. (1994). A diatom-phosphorus transfer function for shallow, eutrophic ponds in southeast England. Hydrobiologia, 275/276, 391-410.

Bennion, H. (1995). Surface-sediment diatom assemblages in shallow, artificial, enriched ponds, and implications for reconstructing trophic status. Diatom Research, 10, 1-19.


Bennion, H., Harriman, R. & Battarbee, R. W. (1997) A chemical survey of standing waters in south-east England, with reference to acidification and eutrophication. Freshwater Forum, 8, 28-44.

Bennion, H. & Smith, M. A. (2000). Variability in the water chemistry of ponds in south-east England, with special reference to the seasonality of nutrients and implications for modelling trophic status. Hydrobiologia, 436, 145-158.


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Swiss dataset

EDDI dataset code Swiss Dataset type TP Number of samples 69 Collection date 1993 - 1998 Contributor André Lotter Contact André Lotter

This dataset includes 68 small lakes situated on the Swiss Plateau, in the Jura mountains and the Alps, as well as the foreland of the southern Alps. Additionally nine well-dated sediment core samples are included. The samples cover a long gradient of total phosphorus concentrations from oligotrophic to hypertrophic conditions. The lakes range considerably in size and depth and are situated along an altitudinal gradient from 300-2350 m a.s.l. The lakes lie in areas of calcareous bedrock and are, therefore, alkaline. Surface sediment samples were collected between 1993 and 1994 (Lotter et al., 1997a); two of the core samples are from Rotsee (Lotter, 1998, 1989) and seven are from Baldegersee (Lotter et al., 1997b). All diatom analysis was undertaken by Andy Lotter. The final screened training set comprised of 72 samples and was used to develop a diatom-total phosphorus transfer function. The WA PLS second component model gave the best results (apparent r2=0.93; RMSE=0.11 log10TP µg l-1; RMSEP=0.19 log10TP µg l-1) and details are given in Lotter et al. (1998). Palaeolimnological studies have been undertaken at a number of these sites (e.g. Lotter, 1989, 1998; Lotter et al. 1997b).



Variable Units N Min Max Mean Alkalinity µeq/l 68 6.6 119 57.4

Calcium µeq/l 68 178 6482 2747 Chloraphyll-a µg/l 68 0.11 6.93 1.22

Conductivity µS/cm 67 20.5 565 274

Magnesium µeq/l 68 20.6 1918 582 Maximum depth of lake m 69 1.6 66 14.6

Nitrate µg/l 68 30 5400 776

pH pH units 68 7.65 8.9 8.21 Potassium µeq/l 68 3.58 123 31.6

Sodium µeq/l 68 10.4 874 131

Soluable reactive phosphorus µg/l 68 1 61.5 6.44 Total nitrogen µg/l 68 200 8360 1764

Total organic carbon mg/l 68 0.45 10.5 3.31




Lotter, A.F. (1989) Subfossil and modern diatom plankton and the paleolimnology of Rotsee (Switzerland) since 1850. Aquatic Sciences 51, 338-350.


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Lotter, A.F., Birks, H.J.B., Hofmann, W. & Marchetto, A. 1997a. Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. I. Climate. Journal of Paleolimnology 18, 395-420.

Lotter, A.F., Sturm, M., Teranes, J.L. & Wehrli, B. (1997b) Varve formation since 1885 and high-resolution varve analyses in hypertrophic Baldeggersee (Switzerland). Aquatic Sciences 59, 304-325.

Lotter, A.F., Birks, H.J.B., Hofmann, W. & Marchetto, A. 1998. Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. II. Nutrients. Journal of Paleolimnology 19, 443-463.

Lotter, A.F. (1998) The recent eutrophication of Baldegersee (Switzerland) as assessed by fossil diatom assemblages. The Holocene 8, 395-405.


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Dataset information

Combined TP dataset

EDDI dataset code TP Dataset type TP Number of samples 347 Collection date 1900 - 1998 Contributor The EDDI Participants Contact Steve Juggins



Summary of environmental data for this dataset: Variable Units N Min Max Mean Alkalinity µeq/l 260 6.6 7140 1256

Aluminium (total) µg/l 40 20 171 63.2

Ammonium µg/l 135 0.01 1107 92.9 Calcium µeq/l 232 12.5 6482 1951

Chloraphyll-a µg/l 224 0.11 351 25.9

Chloride µeq/l 164 24 8525 740 Conductivity µS/cm 327 16.5 1327 289

Iron µg/l 36 10 2920 204

Magnesium µeq/l 232 20.6 4186 551 Manganese µg/l 26 8 306 35.8


Nitrate µg/l 231 0.8 7620 890 Nitrite µg/l 86 20 4320 545

pH pH units 346 4.91 9.45 7.82

Potassium µeq/l 232 2.05 624 69.9 Secchi depth m 194 -1 11.8 2.62

Silica mg/l 183 0.22 21.2 3.5

Dataset Id Name N CCW Welsh TP dataset 11 CEuro Central European dataset 86 DK Danish TP dataset 28 French French Massif Central TP dataset 28 NI Northern Irish dataset 54 SCM UK meres TP dataset 33 SEng Southern England dataset 26 SWAP SWAP dataset 12 Swiss Swiss dataset 69


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Silica mg/l 183 0.22 21.2 3.5

Sodium µeq/l 220 6.52 7948 466 Soluable reactive phosphorus µg/l 206 1 1016 53.5

Sulphate µeq/l 164 4.37 4496 586

Total K nitrogen µg/l 77 330 8840 2060 Total nitrogen µg/l 80 200 8360 1573

Total organic carbon mg/l 80 0.45 17 4.06


Zinc µg/l 27 10 120 68.1

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The European Diatom Database - Steve Juggins - Newcastle

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