Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
madcap_manuscript [2008/08/22 14:08]
waltfinsi
madcap_manuscript [2015/06/23 17:22] (current)
Line 1: Line 1:
 +The final version of this manuscript is published in "​Vegetation History and Archaeobotany",​ Online First with Open Access and is free for[[http://​springerlink.metapress.com/​content/​m25w02n1m5429362/?​p=0211667d1f28445db5f8a443b83fded8&​pi=9|download here.]]
 +
 ====A review of the European Pollen Database==== ====A review of the European Pollen Database====
  
-R M Fyfe, J-L de Beaulieu, H Binney, S Brewer, A Le Flao, W Finsinger, T Giesecke, G Gil-Romera, P Kunes, N Kühl, M Leydet+R M Fyfe, J-L de Beaulieu, H Binney, R H W Bradshaw, S Brewer, A Le Flao, W Finsinger, T Giesecke, G Gil-Romera, P Kunes, N Kühl, M Leydet
  
  
 ===Abstract=== ===Abstract===
-Pollen stratigraphies are the most spatially-extensive data available for the reconstruction of past land-cover change. ​ Detailed knowledge of past land cover is becoming increasingly important to evaluate the present trends in and future threats to vegetation composition. ​ The European Pollen Database (EPD) was established in the late 1980s and developed in the early 1990s to provide a structure for archiving, exchanging, and analysing pollen data from throughout Europe. ​ It provides a forum for scientists to meet and engage in collaborative investigations or data analysis. ​ In May 2007 a number of EPD support groups ​was developed to assist in the task of maintaining and updating the database. ​ The mapping and data accuracy work group (MAPCAP) aims to produce an atlas of past plant distributions for Europe, in order to meet the growing need for these data from palaeoecologists, as well as amongst ​the wider scientific community. ​ Due to data handling problems in the past a significant number of datasets that are in the EPD have errors. ​ The initial task of the work group, therefore, was a systematic review of pollen sequences, in order to identify and repair ​errors. ​ The EPD currently (June 2008) archives 1001 pollen sequences, of which 671 sequences have age–depth models that allow chronological comparison.  ​A large number of errors ​has been identified and corrected, or flagged for users, most notably errors in the pollen count data; we discuss here the types of errors encountered. ​ The application of spatial analyses to pollen data is related to the number of data points that are available for analysis. ​ We therefore take this opportunity to encourage the submission of pollen analytical results to the relevant pollen database. ​ Only in this way will the wider scientific community be able to gain a better understanding of the past vegetation dynamics.+Pollen stratigraphies are the most spatially-extensive data available for the reconstruction of past land-cover change. ​ Detailed knowledge of past land cover is becoming increasingly important to evaluate the present trends in and drivers of vegetation composition. ​ The European Pollen Database (EPD) was established in the late 1980s and developed in the early 1990s to provide a structure for archiving, exchanging, and analysing pollen data from throughout Europe. ​ It provides a forum for scientists to meet and engage in collaborative investigations or data analysis. ​ In May 2007 several ​EPD support groups ​were developed to assist in the task of maintaining and updating the database. ​ The mapping and data accuracy work group (MAPCAP) aims to produce an atlas of past plant distributions for Europe, in order to meet the growing need for these data from palaeoecologists ​and the wider scientific community. ​ Due to data handling problems in the past a significant number of datasets that are in the EPD have errors. ​ The initial task of the work group, therefore, was a systematic review of pollen sequences, in order to identify and correct ​errors. ​ The EPD currently (June 2008) archives 1001 pollen sequences, of which 671 sequences have age–depth models that allow chronological comparison.  ​Many errors ​have been identified and corrected, or flagged for users, most notably errors in the pollen count data. We discuss here the types of errors encountered. ​ The application of spatial analyses to pollen data is related to the number of data points that are available for analysis. ​ We therefore take this opportunity to encourage the submission of pollen analytical results to the relevant pollen database. ​ Only in this way will the wider scientific community be able to gain a better understanding of past vegetation dynamics.
  
 ===Introduction=== ===Introduction===
-The intention of this paper is (i) to review the development of the European Pollen Database (EPDand (ii) to highlight efforts made and solutions found to improve this data archive such that it may better serve the wider scientific community in the future. ​ The decision to produce such a paper was driven by the combined aims of (1) presenting the work of a Mapping and Data Accuracy Support Group established in 2007; and (2) setting a background for important discussions surrounding the future development of the EPD.  It is not intended as a definitive review, and parts may not reflect the views of the EPD community, Advisory Board or Executive Committee.+The potential value of palaeoecological and geological databases has increased considerably in recent years, driven by increasing amounts of data and the use of dynamic vegetation models to study the past and forecast the future (Miller et al. 2008, Sitch et al. 2008). Databases such as the European Pollen Database (www.europeanpollendatabase.net)(EPD) are now considerably more than long-term data repositories and have become important tools in multi-disciplinary research projects. The large body of European pollen data is widely dispersed in the literature, but when organised into a common format becomes accessible for research into broad-scale vegetation dynamics and its interactions with climate and long-term development of human societies. ​The intention of this paper is (i) to review the development of the EPD and (ii) to highlight efforts made and solutions found to improve this data archive such that it may better serve the wider scientific community in the future. ​ The decision to produce such a paper was driven by the combined aims of (1) presenting the work of a Mapping and Data Accuracy Support Group established in 2007; and (2) setting a background for important discussions surrounding the future development of the EPD.  It is not intended as a definitive review, and parts may not reflect the views of the EPD community or those involved in its management.
  
 ===Role of the EPD=== ===Role of the EPD===
-Pollen stratigraphies are probably the most spatially-extensive data available for the reconstruction of past changes in terrestrial and aquatic vegetation composition. ​ In addition to using pollen records to investigate vegetation dynamics at individual sites through time, paleoecologists have used the large amount of information stored in the database to address a range of scientific questions at regional or continental scales, such as i) the reconstruction of patterns of past climate change through time and space (e.g. Davis et al. 2003), that in turn is important in hindcasting studies evaluating general circulation models (Bonfils et al. 2004); ​ ii) studies on the spread of plants, especially trees, since the last glaciation (e.g. Brewer et al. 2002; Terhürne-Berson et al., 2004; Giesecke and Bennett, 2004; Conedera et al., 2004; Krebs et al., 2004; van der Knaap et al, 2005; Magri, 2008); ​ iii) reconstructions of past plant distribution patterns which allow to test our understanding of factors limiting these and models that attempt to capture them (e.g. Giesecke et al. 2007). In addition, knowledge of pollen-inferred past land-cover changes makes it possible to evaluate the consequences and legacies of past land use and it provides information on the dynamic responses of vegetation with regard to a constantly changing environment. This may allow us to evaluate threats to our natural environment and define aims for the conservation and management of Europe’s landscape (Anderson et al. 2006; Willis et al. 2007).+Pollen stratigraphies are probably the most spatially-extensive data available for the reconstruction of past changes in terrestrial and aquatic vegetation composition. ​ In addition to using pollen records to investigate vegetation dynamics at individual sites through time, paleoecologists have used the large amount of information stored in the database to address a range of scientific questions at regional or continental scales, such as i) the reconstruction of patterns of past climate change through time and space (e.g. Davis et al. 2003), that in turn is important in hindcasting studies evaluating general circulation models (Bonfils et al. 2004); ​ ii) studies on the spread of plants, especially trees, since the last glaciation (e.g. Brewer et al. 2002; Terhürne-Berson et al., 2004; Giesecke and Bennett, 2004; Conedera et al., 2004; Krebs et al., 2004; van der Knaap et al, 2005; Magri, 2008); ​ iii) reconstructions of past plant distribution patterns which allow to test our understanding of factors limiting these and models that attempt to capture them (e.g. Giesecke et al. 2007) and increased precision of reconstruction POLLANDCAL activities (others to add, Sugita refs). In addition, knowledge of pollen-inferred past land-cover changes makes it possible to evaluate the consequences and legacies of past land use and it provides information on the dynamic responses of vegetation with regard to a constantly changing environment. This may allow us to evaluate threats to our natural environment and define aims for the conservation and management of Europe’s landscape (Anderson et al. 2006; Willis et al. 2007).
  
 {{figure1_1.jpg?​400*400}} {{figure1_1.jpg?​400*400}}
Line 17: Line 19:
  
  
-The increasing understanding of these topics, and the need to analyse spatial patterns, makes it necessary to draw information from more than a single pollen record. ​ Many of these investigations require the availability of datasets because only limited information can be extracted from published printed pollen diagrams. ​ Data archives such as the European Pollen Database (EPD) and other global databases thus play an important role in the collation and archiving of data at the extensive spatial scales needed for analyses at regional or continental scales. ​ The storage of original pollen count data and their associated metadata is therefore important for between site comparisons and spatial analyses. ​ The EPD has become the main archive ​to provide ​the above functions for pollen analytical results from western Eurasia. ​ In addition to serving as a data archive for extensive spatial analyses, the EPD also plays an important role for individual data contributors in mitigating against the inevitable metadata loss (“information-entropy”,​ sensu Michener et al., 1997) that occurs through time (Figure 1).  Both count data and metadata have a natural decay function through time as a result of memory recall, accidental data loss, changes in storage media and subsequent incompatibility,​ and retirement or death of the original investigators.  ​+The increasing understanding of these topics, and the need to analyse spatial patterns, makes it necessary to draw information from more than a single pollen record. ​ Many of these investigations require the availability of datasets because only limited information can be extracted from published printed pollen diagrams. ​ Data archives such as the European Pollen Database (EPD) and other global databases thus play an important role in the collation and archiving of data at the extensive spatial scales needed for analyses at regional or continental scales. ​ The storage of original pollen count data and their associated metadata is therefore important for between site comparisons and spatial analyses. ​ The EPD has become the main archive ​for provision of the above functions for pollen analytical results from western Eurasia. ​ In addition to serving as a data archive for extensive spatial analyses, the EPD also plays an important role for individual data contributors in mitigating against the inevitable metadata loss (“information-entropy”,​ sensu Michener et al., 1997) that occurs through time (Figure 1).  Both count data and metadata have a natural decay function through time as a result of memory recall, accidental data loss, changes in storage media and subsequent incompatibility,​ and retirement or death of the original investigators.  ​
  
 ===Short history of the EPD=== ===Short history of the EPD===
-Towards the end of the 1980s the IGCP 158b working group led by B. Berglund and M. Ralska-Jaziewiszova,​ and palynologists involved in EU research programs on palaeoclimatology (A. Pons, W. Watts, B. Huntley) both needed improved maps of palaeovegetation based on the large sets of pollen data acquired since the 1960s. ​ The work of Huntley and Birks (1983) had demonstrated the value of spatial analysis of pollen data, and had a great influence on many European palynologists. ​ These groups realised the need for a pollen database (the EPD).  In 1988 the first EPD-related discussions and meetings took place involving, amongst others, J. Guiot, C. Prentice, B. Huntley, B. Berglund and G, Jacobson. ​ These discussions resulted in a meeting, convened by B. Berglund, to discuss the organisation of the database. ​ The proposal by A. Pons to host the EPD in Arles was accepted. ​ Two subsequent workshops in Arles (1989) and Wilhelmshaven (1990) led to the definition of the database software, the administrative structure (an Advisory Board representative of the different European regions, and an Executive Committee of three persons invited to meet every year to review EPD progress: Table 1) and the “protocol” ruling the rights and the duties of data contributors and users. ​ The EPD and the North American Pollen Database (NAPD) were established simultaneously through active collaboration with Eric Grimm and John Keltner. ​ This was done to ensure compatibility and to contribute towards the ultimate goal of a Global Pollen Database. ​ In 1990, thanks to temporary CCE (CCE = :?:) funding, R. Cheddadi was appointed to work alongside Joel Guiot as EPD Manager, and in January 1991 the first newsletter was sent to European Quaternary palynologists asking them to contribute their data to the EPD.+Towards the end of the 1980s the IGCP 158b working group led by B. Berglund and M. Ralska-Jaziewiszova,​ and palynologists involved in EU research programs on palaeoclimatology (A. Pons, W. Watts, B. Huntley) both needed improved maps of palaeovegetation based on the large sets of pollen data acquired since the 1960s. ​ The work of Huntley and Birks (1983) had demonstrated the value of spatial analysis of pollen data, and had a great influence on many European palynologists. ​ These groups realised the need for a pollen database (the EPD).  In 1988 the first EPD-related discussions and meetings took place involving, amongst others, J. Guiot, C. Prentice, B. Huntley, B. Berglund and G, Jacobson. ​ These discussions resulted in a 1989 meeting, convened by B. Berglund, to discuss the organisation of the database, which was attended by representatives of 18 European countries.  The proposal by A. Pons to host the EPD in Arles was accepted. ​ Two subsequent workshops in Arles (1989) and Wilhelmshaven (1990) led to the definition of the database software, the administrative structure (an Advisory Board representative of the different European regions, and an Executive Committee of three persons invited to meet every year to review EPD progress: Table 1) and the “protocol” ruling the rights and the duties of data contributors and users. ​ The EPD and the North American Pollen Database (NAPD) were established simultaneously through active collaboration with Eric Grimm and John Keltner. ​ This was done to ensure compatibility and to contribute towards the ultimate goal of a Global Pollen Database. ​ In 1990, thanks to European and French national ​funding, R. Cheddadi was appointed to work alongside Joel Guiot as EPD Manager, and in January 1991 the first newsletter was sent to European Quaternary palynologists asking them to contribute their data to the EPD.
  
 The EPD was constructed to provide an inclusive and permanent archival facility to all palynologists for storing the basic data that had been generated within European research. ​ It was anticipated that the EPD would also become a tool by means of which further research on biogeographical,​ palaeoclimatological and palaeoecological problems could be addressed, at a variety of different spatial and temporal scales. ​ The role of past environmental archives in the understanding of global climate change was clear from the early 1980s; ​ contemporary societal concerns surrounding climate change have resulted in an even greater role for archives of past environments. The EPD was constructed to provide an inclusive and permanent archival facility to all palynologists for storing the basic data that had been generated within European research. ​ It was anticipated that the EPD would also become a tool by means of which further research on biogeographical,​ palaeoclimatological and palaeoecological problems could be addressed, at a variety of different spatial and temporal scales. ​ The role of past environmental archives in the understanding of global climate change was clear from the early 1980s; ​ contemporary societal concerns surrounding climate change have resulted in an even greater role for archives of past environments.
  
-The 1990s was a very busy time for the EPD, with numerous training courses organised in Arles and elsewhere. ​ The BIOME6000 initiative stimulated palynologists to share pollen data, and much of the former Soviet Union and Mongolian data was compiled as part of this project, facilitated by funds obtained from the EU (INTAS) to promote the participation of these partners (Prentice et al., 1996; Tarasov et al., 1998). ​ Unfortunately,​ the team hosting the EPD (IMEP) did not succeed in securing a permanent position for a database manager from their French administration. ​ From 1995 to 2003 funding for the further development and management of the EPD was dependent upon collaboration with foresters involved in EU research projects (Fairoak, Cytofor and Fossilva) that used the EPD as a tool linking phylogeography and palaeobiogeography of forest trees (Petit et al., 2002; Cheddadi et al., 2006; Magri et al., 2006). ​ A consequence of tying the funding of the EPD to research projects was that the database manager became the principal user of the EPD, resulting in less of his time being available to undertake data compilation tasks. ​ When the Fossilva project ended in the early 2000s the EPD was unfunded. ​ It managed to survive thanks to the altruistic contribution of R. Cheddadi, whose position was now supported by other projects, thus limiting his ability to commit time to the EPD.  The EPD became a relict database, with no development or incorporation of new data.  At the end of 2006 IMEP obtained a permanent position for a new database manager (M. Leydet) from the University of Aix-Marseille and data compilation resumed, with the support of the NOE EVOLTREE project.+The 1990s was a very busy time for the EPD, with numerous training courses organised in Arles and elsewhere. ​ The BIOME6000 initiative stimulated palynologists to share pollen data, and much of the former Soviet Union and Mongolian data was compiled as part of this project, facilitated by funds obtained from the EU (INTAS) to promote the participation of these partners (Prentice et al., 1996; Tarasov et al., 1998). ​ Unfortunately,​ the team hosting the EPD (IMEP) did not succeed in securing a permanent position for a database manager from their French administration. ​ From 1995 to 2003 funding for the further development and management of the EPD was dependent upon collaboration with foresters involved in EU research projects (Fairoak, Cytofor and Fossilva) that used the EPD as a tool linking phylogeography and palaeobiogeography of forest trees (Petit et al., 2002; Cheddadi et al., 2006; Magri et al., 2006). ​ A consequence of linking ​the funding of the EPD to research projects was that the database manager became the principal user of the EPD, resulting in less of his time being available to undertake data compilation tasks. ​ When the Fossilva project ended in the early 2000s the EPD was unfunded. ​ It managed to survive thanks to the altruistic contribution of R. Cheddadi, whose position was now supported by other projects, thus limiting his ability to commit time to the EPD.  The EPD became a relict database, with no development or incorporation of new data.  At the end of 2006 IMEP obtained a permanent position for a new database manager (M. Leydet) from the University of Aix-Marseille and data compilation resumed, with the support of the NOE EVOLTREE project.
  
-In May 2007 a special open meeting to discuss the future of the EPD was convened by Richard Bradshaw in Arbois (France) under the auspices of a EuroCLIMATE workshop. ​ The workshop, attended by 78 European palynologists,​ had a range of outputs that can be reviewed on the EPD website (http://​www.europeanpollendatabase.net).  ​Recognising that maintaining and updating the database requires constant work, one of these outputs ​was the formation of a range of support and working groups. ​ The Mapping and Data Accuracy working group (MADCAP) is one of these EPD support groups formed at the 2007 meeting, with representatives from across Europe (Table 1).  The aim of MADCAP is the production of a palaeovegetation atlas, based on the EPD.+In May 2007 a special open meeting to discuss the future of the EPD was convened by Richard Bradshaw in Arbois (France) under the auspices of a EuroCLIMATE workshop. ​ The workshop, attended by 78 European palynologists,​ had a range of outputs that can be reviewed on the EPD website (http://​www.europeanpollendatabase.net).  ​One output ​was the formation of a range of support and working groups ​to help maintain and update the database.  The Mapping and Data Accuracy working group (MADCAP) is one of these EPD support groups formed at the 2007 meeting, with representatives from across Europe (Table 1).  The aim of MADCAP is the production of a palaeovegetation atlas, based on the EPD. These working groups reported to a well-attended open meeting of the EPD at the International Palynological Congress, Bonn in 2008 where a new administrative structure for the EPD was proposed and accepted. It was decided that the EPD would be managed by a board comprising an elected chairperson and the spokespersons of the working groups. The term of office of the chairperson would be four years
  
 ===Status of the EPD=== ===Status of the EPD===
Line 48: Line 50:
  
 ===MADCAP activities=== ===MADCAP activities===
-The mapping and data accuracy work group of the EPD was established at the open meeting in France in 2007 and aims to make the data in the EPD more available to the scientific community and thus to enhance their use.  The key goal of the group is to produce a new web-based version of a European palaeovegetation atlas that provides maps of past pollen percentages for visualisation,​ teaching purposes and as a basis for data–model comparisons. ​ In order to achieve this goal the group has undertaken a systematic review of the data currently held in the EPD with the aim of identifying problems with individual site records, and of flagging errors for correction within the database (see below). ​ This process has followed a standardized protocol. ​ Data have been downloaded from the EPD, pollen diagrams constructed and, wherever possible, checked against the original publications. ​ In the first instance sites that have some chronological control were targeted and age–depth models were included in the review process, as these will form the basis for the palaeovegetation atlas. ​ The age–depth models for each site within the database have also been checked. ​ Members of the group combine different regional expertise so that diagrams from most European regions were checked by a person with knowledge about their regional vegetation history. ​ Where the types of data handling errors described above have been identified, this has been fed back to the database Manager, who is a member of the group, for flagging or, where possible, correction.+The mapping and data accuracy work group of the EPD was established at the open meeting in France in 2007 and aims to make the data in the EPD more available to the scientific community and thus to enhance their use.  The key goal of the group is to produce a new web-based version of a European palaeovegetation atlas that provides maps of past pollen percentages for visualisation,​ teaching purposes and as a basis for data–model comparisons. ​ In order to achieve this goal the group has undertaken a systematic review of the data currently held in the EPD with the aim of identifying problems with individual site records, and of flagging errors for correction within the database (see below). ​ This process has followed a standardized protocol. ​ Data have been downloaded from the EPD, pollen diagrams constructed and, wherever possible, checked against the original publications. ​ In the first instance sites that have some chronological control were targeted and age–depth models were included in the review process, as these will form the basis for the palaeovegetation atlas. ​ The age–depth models for each site within the database have also been checked. ​ Members of the group combine different regional expertise so that diagrams from most European regions were checked by a person with knowledge about their regional vegetation history. ​ Where the types of data handling errors described above have been identified, this has been fed back to the database Manager, who is a member of the group, for flagging or, where possible, correction. Until present, Madcap members have checked 711 pollen sequences.
  
 Generation of the new palaeovegetation atlas is in progress using the dated sites from within the EPD.  At the present time age–depth models are being constructed. ​ The final dataset used to compile the atlas will be made available to the wider community following completion of the project, as will gridded results for each taxonomic unit. Generation of the new palaeovegetation atlas is in progress using the dated sites from within the EPD.  At the present time age–depth models are being constructed. ​ The final dataset used to compile the atlas will be made available to the wider community following completion of the project, as will gridded results for each taxonomic unit.
  
 ===Errors within the EPD=== ===Errors within the EPD===
-The EPD evolved at a time when personal computing was an emerging growth area rather than a matter of routine. ​ A consequence of this is that there are a number of errors within the EPD that result from data entry, handling, and conversion. ​ Errors are manifest in both the metadata and in the raw count data. Although these errors are more common within older datasets, they still occur within datasets that have been submitted more recently, and are inevitable. The most severe errors in the metadata are incorrect latitude/​longitude information that may lead to site offsets of hundreds of kilometres, and incorrect or missing site references. ​ With regional knowledge these errors generally are easily detected and correctable.+The EPD evolved at a time when personal computing was an emerging growth area rather than a matter of routine. ​ A consequence of this is that there are a number of errors within the EPD that result from data entry, handling, and conversion. ​ Errors are manifest in both the metadata and in the raw count data. Although these errors are more common within older datasets, they still occur within datasets that have been submitted more recently, and are inevitable. The most severe errors in the metadata are incorrect latitude/​longitude information that may lead to site offsets of hundreds of kilometres, and incorrect or missing site references.  ​These errors were encountered in ca. 1.1% and in ca. 6.6% of the sequences checked, respectively (Table 2). A less severe error for the production of a palaeovegetation atlas is the incorrect or missing elevation of a site. With regional knowledge these errors generally are easily detected and correctable.
  
 ^                          ^  error types/​corrections made  ^  # of errors ​ ^  % of entities checked ​ ^  % of entities with errors ​ ^ ^                          ^  error types/​corrections made  ^  # of errors ​ ^  % of entities checked ​ ^  % of entities with errors ​ ^
-| Errors in the count data |  counts ​switched  ​ ​5 ​           ​0.6 ​                  ​| ​ 10.9  |  +| Errors in the count data |  ​Error in counts ​              ​   ​26 ​        |   3.7              ​|  ​56. |  
-|                          |  typing errors ​  ​|  21          |  2.6                   |  ​45. |  +|        |  samples switched or assigned ​incorrect ​depth   ​|  5             ​|  0.7               |  10.9  |  
-|        |  samples switched or assigned ​wrong depth  |  5  |  0.6                    ​|  10.9  |  +       |  flag sample/​record ​                                        ​|  15           ​|  ​2.              ​|  32.6  |  
-     |  flag sample/​record ​ |  15  |  1.8                    ​|  32.6  |  +| Chronology ​                         |  Change suggested ​   |  20            |  2.8               |         | 
-| Chronology ​            ​|  Change suggested ​  ​|  20            |  2.4                    ​|         | +                                      ​|  New chronology made    |  9              |  1.                   ​| ​ | 
-                       |  New chronology made   ​|  9          |  1.                   ​| ​ | +                                       |  Chronology flagged ​      ​|  75            |  ​10.5                ​|   | 
-                       |  Chronology flagged ​ |  75          |  ​9.1                    ​|   | +| Coordinates ​                   |  ​incorrect ​long/​lat ​corrected ​              |  8              |  1.1           |   | 
-| Coordinates ​           |  ​wrong long/​lat ​ |  8             ​|  1.0                     |   | +                                        ​|  ​incorrect ​elevation  ​corrected ​  |  3              |  0.4              |  | 
-                       |  ​wrong elevation ​ |  3           ​|  0.4                  |  | +                                      ​|  No elevation ​                   |  24           ​|  ​3.4              ​|   | 
-                       |  No elevation ​ |  24                |  ​2.9                   |   | +| References ​                  ​|  ​incorrect/missing reference ​corrected ​ ​| ​ 47            |  ​6.                  |   | 
-| References ​            ​|  ​wrong/missing reference ​ |  47            |  ​5.                  |   | +                                    ​|  No reference ​                    ​|  58           ​|  ​8.2               |   | 
-                       |  No reference ​ |  58           ​|  ​7.1                     |   |+
  
 Table 2 Table 2
  
  
-Errors within the raw counts are typically the result of the process of conversion of the dataset into the EPD.  Errors may be systematic within sites (e.g. switching of count data between taxon A and B), or random (e.g. one taxon for an individual sample swapped for another). ​ These errors are usually obvious: ​ The count for Artemisia may be switched for Alnus for a single sample, for example, resulting in an isolated high value associated with an atypical low value in the other. ​ These errors can be confirmed by checking against the original publication. ​ It is possible that count data for individual taxa are missed through the data conversion. ​ In cases such as this the original data contributor may need to be contacted to refresh the dataset, where that is still possible.+Errors within the raw counts are typically the result of the process of conversion of the dataset into the EPD.  Errors may be systematic within sites (e.g. switching of count data between taxon A and B), or random (e.g. one taxon for an individual sample swapped for another). ​ These errors are usually obvious: ​ The count for Artemisia may be switched for Alnus for a single sample, for example, resulting in an isolated high value associated with an atypical low value in the other. ​In very few cases, entire samples were switched (e.g. switching of depth between sample X and Y) or assigned an incorrect depth. ​These errors can be confirmed by checking against the original publication. ​ It is possible that count data for individual taxa are missed through the data conversion. ​ In cases such as this the original data contributor may need to be contacted to refresh the dataset, where that is still possible.
  
-The errors described so far are grave and unfortunate because they are situated in the archival tables. ​ Less serious for the database, but important for users, are errors, misjudgements or misinterpretations in the construction of age–depth models. ​ Age–depth models that are based on very few age determinations often interpolate and/or extrapolate over many thousands of years. ​ This can result in errors that sometimes may be obvious, for example, where a late-glacial pollen spectrum is assigned to a Holocene age or vice versa.  ​Users are encouraged to be critical of the available age–depth models and where necessary to construct their own.  Users that construct new age–depth models are encouraged to submit these to the EPD where they will be stored in research tables.+The errors described so far are grave and unfortunate because they are situated in the archival tables. ​ Less serious for the database, but important for users, are errors, misjudgements or misinterpretations in the construction of age–depth models. ​ Age–depth models that are based on very few age determinations often interpolate and/or extrapolate over many thousands of years. ​ This can result in errors that sometimes may be obvious, for example, where a late-glacial pollen spectrum is assigned to a Holocene age or vice versa.  ​Madcap members have, until present, suggested changes to the chronologies or already made new ones for a number of sequences (Table 2). Chronologies based on only one or two radiocarbon dates have been flagged due to their potentially low precision. However, users are encouraged to be critical of the available age–depth models and where necessary to construct their own.  Users that construct new age–depth models are encouraged to submit these to the EPD where they will be stored in research tables.
  
 All contributors and users of the EPD are strongly encouraged to report any errors they encounter to the database Manager. ​ Each error should be clearly described and, if possible, suggestions made as to how it may be resolved. All contributors and users of the EPD are strongly encouraged to report any errors they encounter to the database Manager. ​ Each error should be clearly described and, if possible, suggestions made as to how it may be resolved.
Line 104: Line 106:
   * Petit RJ, Brewer S, Bordács S, Burg K, Cheddadi R, Coart E, Cottrell J, Csaikl UM, van Dam B, Deans JD, Espinel S, Fineschi S, Finkeldey R, Glaz I, Goicoechea PG,   * Petit RJ, Brewer S, Bordács S, Burg K, Cheddadi R, Coart E, Cottrell J, Csaikl UM, van Dam B, Deans JD, Espinel S, Fineschi S, Finkeldey R, Glaz I, Goicoechea PG,
   * Jensen JS, König AO, Lowe AJ, Madsen SF, Mátyás G, Munro RC, Popescu F, Slade D, Tabbener H, de Vries SGM, Ziegenhagen B, de Beaulieu J-L, Kremer A. (2002) Identification of refugia and post-glacial colonisation routes of European white oaks based on chloroplast DNA and fossil pollen evidence. Forest Ecology and Management, 156: 49-74.   * Jensen JS, König AO, Lowe AJ, Madsen SF, Mátyás G, Munro RC, Popescu F, Slade D, Tabbener H, de Vries SGM, Ziegenhagen B, de Beaulieu J-L, Kremer A. (2002) Identification of refugia and post-glacial colonisation routes of European white oaks based on chloroplast DNA and fossil pollen evidence. Forest Ecology and Management, 156: 49-74.
-  * Prentice, C.I., Guiot, J., Huntley, B., Jolly D. and Cheddadi, R., 1996Reconstructing biomes from palaeoecological data: a general method and its application to European pollen data at 0 and 6 ka. Climate Dynamics 12:185-194.+  ​* Miller, P., Giesecke, T., Hickler, T., Bradshaw, R.H.W., Smith, B., Seppä, H., Valdes, P., Sykes, M. (2008) Exploring climatic and biotic controls on Holocene vegetation change in Fennoscandia. Journal of Ecology, 96: 247-259. 
 +  ​* Prentice, C.I., Guiot, J., Huntley, B., Jolly D. and Cheddadi, R., (1996Reconstructing biomes from palaeoecological data: a general method and its application to European pollen data at 0 and 6 ka. Climate Dynamics 12:185-194. 
 +  * Sitch, S., Huntingford,​ C., Gedney, N., Levy, P.E., Lomas, M., Piao, S.L., Betts, R., Ciais, P., Cox, P., Friedlingstein,​ P., Jones, C.D., Prentice, I.C., Woodward, F.I. (2008). Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global Change Biology, 14: 2015-2039. 
 + (RHWB to add)
   * Stefanova I, van Leeuwen JFN, van der Knapp WO (2008) Loch Laxford (north-west Scotland, UK). Grana 48: 78-79   * Stefanova I, van Leeuwen JFN, van der Knapp WO (2008) Loch Laxford (north-west Scotland, UK). Grana 48: 78-79
   * Tarasov, P.E., Webb III, T., Andreev, A.A., Afanas'​eva,​ N.B., Berezina, N.A., Bezusko, L.G., Blyakharchuk,​ T.A., Bolikhovskaya,​ N.S., Cheddadi, R., Chernavskaya,​ M.M.,        * Tarasov, P.E., Webb III, T., Andreev, A.A., Afanas'​eva,​ N.B., Berezina, N.A., Bezusko, L.G., Blyakharchuk,​ T.A., Bolikhovskaya,​ N.S., Cheddadi, R., Chernavskaya,​ M.M.,     
madcap_manuscript.1219406931.txt.gz · Last modified: 2015/06/25 16:07 (external edit)
Back to top
chimeric.de = chi`s home Creative Commons License Valid CSS Driven by DokuWiki do yourself a favour and use a real browser - get firefox!! Recent changes RSS feed Valid XHTML 1.0