Introduction

The Odonata collections of Quebec

The Ouellet-Robert Entomological Collection at the University of Montreal has an exceptionally large holding of Odonata, so when the opportunity presented itself to digitise insect specimen data, this group was an obvious choice (Favret et al. 2019). Of the 33,122 Odonata specimen occurrence records in the Ouellet-Robert Collection, 31,595 (95%) are from the Canadian province of Quebec. However, of the 150 species of Odonata known from Quebec, the Ouellet-Robert Collection houses only 128 and their distribution records exhibit a "collection bias" (Ferro and Flick 2015) for the Montreal region (Fig. 1). Additionally, despite the large number of records, they are concentrated in a relatively small number of collection localities (222). In order to perform more rigorous distribution modelling and other computational analyses in the future, we sought to broaden the sampling, both geographically and taxonomically, by adding the specimen occurrence records from the other public research collections in Quebec. These include three other university collections and three governmental collections at the city, provincial and federal levels: McGill University's Lyman Museum, Bishop's and Laval Universities, the Insectarium of Montreal, the Government of Quebec and Natural Resources Canada's Laurentian Forestry Centre's Insectarium René Martineau (Table 1).

Table 1.

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Summary of Quebec insect research collections and their Quebec Odonata holdings.

Institution	Collection	Location	Canadensys DOI	No. occurrence records	No. species-level records	No. species	No. unique species	No. species-level collection localities
University of Montreal	Ouellet-Robert Collection (QMOR)	Montreal	10.5886/qwvt63fz	31,595	29,982	128	3	222
Laval University	Collection entomologique de l'Université Laval (ULQC)	Quebec City	10.5886/bxbpry	4,994	4,993	122	2	296
McGill University	Lyman Entomological Museum (LEMQ)	Sainte-Anne-de-Bellevue	10.5886/q79vhp1e	1,841	270	45		39
Insectarium of Montreal	(IMQC)	Montreal	10.5886/i6z1vo	922	782	110	1	109
Government of Quebec	Collection d'Insectes du Québec (CIQ)	Quebec City	10.5886/msuujw	655	653	71	1	59
Bishop's University	Bishop's University Insect Collection (BUIC)	Sherbrooke	10.5886/nmcxfj	228	62	19		14
Laurentian Forestry Centre	Insectarium René-Martineau (IRM)	Quebec City	10.5886/d6vnc2	212	209	50		43
		TOTAL		40,459	36,963	137	7	616

Figure 1.  

Collection localities of the Ouellet-Robert Collection specimens.

General description

Project description

Sampling methods

Sampling description: 

Data capture followed two distinct protocols. Prior to 2012 (Method 1), the Ouellet-Robert Collection specimen label data were parsed and captured manually and verbatim into an Excel spreadsheet. No photographs were taken. After import into a custom FileMaker Pro (FileMaker, Inc., Santa Clara, California, USA) relational database, locality georeferencing was conducted with reference to a downloaded gazeteer, the Canadian Geographical Names Data Base at Natural Resources Canada. Both the verbatim locality description and the gazeteer's locality name were recorded in the FileMaker database.

For the other six collections, after 2012 (Method 2), the digitisation process largely followed that described by Nelson et al. (2012). Labels of pinned specimens were removed and placed alongside the specimen, a unique identifier label was added and the ensemble was photographed (Fig. 2). Glassine envelopes were photographed as found, with the occasional displacement of the specimens in cases where they obstructed the labels (Fig. 3). Unfortunately, we were inconsistent in our use of callibration scale. We found that the rate of photography was optimal with three workers, the first preparing the specimens, the second photographing them, the third replacing them. With this set-up, we photographed an average of 1.2 pinned specimens and 4.0 envelopes per minute. Photograph files were renamed, either manually or with a simple perl script that added the collection code and sequential numbers, to correspond to each specimen's unique identifier, allowing for batch importation into a rapid-input FileMaker database.

Figure 2.  

Example of pinned specimen photograph with labels removed.

Figure 3.  

Example of specimens in glassine envelope, photographed in situ.

In order to accelerate data input, only three numbers and one date were captured manually: 1) The taxon, based on the most recent determination, was captured with a reference ID to a nomenclator built on several taxonomic checklists (Paulson and Dunkle 2018, Garrison and von Ellenrieder 2016). 2) The collection locality, with its geoposition coordinates, was recorded with another reference ID to the same gazeteer mentioned above. Finally, 3) the collection date and 4) the number of specimens represented by each museum object (e.g. several specimens in a single glassine envelope (Fig. 3)) were recorded. Taxonomic data were added during batch import of the photographs. The other three data fields were added by hourly undergraduate employees, referencing the photos and the gazeteer. Their average data capture rate of 106 museum objects per hour was speeded up when multiple specimens in a row had been collected at the same locality.

Figures for the efficiency of the Ouellet-Robert Collection data capture are unavailable (Method 1). However, based on previous experience (Favret and Dewalt 2002), we estimate that it proceeded at approximately 12 museum objects per hour. On the other hand, photographing the museum objects first and then choosing to capture only the most critical data assured a higher rate (Method 2). Including photography, file naming and import and data capture, but excluding time for set-up, we averaged 19 objects per person-hour for pinned specimens, 44 for glassine envelopes. Although some data were not captured in the database, for example, the collector and determiner, these are available on the photographs and can be incorporated into the database in the future, as resources allow, without having to re-access the actual physical specimen.

Geographic coverage

Taxonomic coverage

Traits coverage

Temporal coverage

Collection data

Usage rights

Data resources

Additional information

Although the Ouellet-Robert Collection accounted for 81% of all the species-level occurrence records (Fig. 4, Table 1), these specimens were collected in a relatively small number of localities, averaging only 45% of all unique localities per species (Figs 1, 5). Adding the other six collections dramatically increased the geographic coverage, especially the University of Laval Collection with as many localities as the Ouellet-Robert Collection (Table 1), including a nice series of specimens from Anticosti Island in the Gulf of Saint Lawrence (Fig. 6). The Insectarium of Montreal and Quebec Insect Collection both have broad geographic sampling (Figs 7, 8), whereas that of the other three collections is narrower, concentrated near Montreal, Sherbrooke and Quebec City (Fig. 9).

Figure 4.  

Number of specimen occurrence and unique locality records per species for 137 Quebec Odonata species found in all seven collections (black and grey lines) and 128 species found in the Ouellet-Robert Collection (blue and red lines). The dashed line indicates the conservative 25-record threshold calculated by van Proosdij et al. (2015) for developing species distribution models.

Figure 5.  

Proportion of unique localities per species provided by Ouellet-Robert Collection specimens versus material provided by all other collections. The first three species are those present at the Ouellet-Robert Collection, but absent elsewhere and the last nine are those present elsewhere, but absent from the Ouellet-Robert Collection.

Figure 6.  

Collection localities of the Laval University specimens.

Figure 7.  

Collection localities of the Insectarium of Montreal specimens.

Figure 8.  

Collection localities of the Quebec Insect Collection specimens.

Figure 9.  

Collection localities of the Lyman Museum (circles), Bishop's University (squares) and Insectarium René-Martineau (triangles) specimens, concentrated in the regions of Montreal, Sherbrooke and Quebec City, respectively.

Adding the other collections also increased the taxonomic coverage. Whereas specimens of three species are held only at the Ouellet-Robert Collection, nine species, absent from this collection, are held elsewhere (Fig. 5), including four held only in a single other collection (Table 1). In all, seven species are present in a single collection each, whereas only seven are present in all seven collections (Table 2). The temporal coverage also broadened considerably with the addition of the other six collections. Whereas overall sampling is dominated by the Ouellet-Robert Collection, mostly thanks to the efforts of its long-time curator, Adrien Robert (Robert 1963), there is almost no material from the mid-1970s onwards (Fig. 10). It is the Laval University Collection that provides the vast majority of the material collected during the 1970s and then especially from the 1990s to 2010. This latter collection is in especially nice curatorial condition thanks to the work of Jean-Marie Perron.

Table 2.

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Number of Quebec Odonata species deposited in no collection (absent from all collections), a single collection, two to six collections or all seven collections.

Number of collections	Number of species
No collections	13
1 collection	7
2 collections	21
3 collections	30
4 collections	28
5 collections	19
6 collections	25
All 7 collections	7
TOTAL	150

Figure 10.  

Number of species-level occurrence records from the four largest collections collected in each five-year interval.

The volume of material in the combined dataset should be useful for future modelling and other distribution-related analyses. More than half of the species are represented by over 100 specimens in the combined dataset (Fig. 4). If we restrict future work to only those species for which we have the conservative estimate of 25 unique records suggested by van Proosdij et al. (2015), 25 species at the Ouellet-Robert Collection and 57 across all collections are suitable for distribution modelling (Fig. 4). Using this admittedly somewhat arbitrary metric, the additional 19% of material gained by digitising the Odonata in the six other collections represents a two-fold improvement.

Acknowledgements

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Supplementary material