Corresponding author: Joan E. Ball-Damerow (
Academic editor: L. Penev
The recently completed
Ball-Damerow JE, Oboyski PT, Resh VH (2015) California dragonfly and damselfly (Odonata) database: temporal and spatial distribution of species records collected over the past century. ZooKeys 482: 67–89. doi:
Natural history specimens are arguably the most valuable records of the historical occurrence of organisms. In contrast to scientific publications, which usually are most relevant for the first ten years following their appearance, information from specimens becomes more valuable with age (
Many vertebrate collections have complete or near-complete databases of their specimens, along with ancillary information such as photos, field notes, and published manuscripts associated with particular specimens (e.g.
Along with digitization, however, comes the responsibility of database curators and data-users to acknowledge and address the many biases that exist in specimen data. Because the approach of natural history collection acquisition and management has traditionally focused on taxonomic work and the special interests of curators and enthusiasts (
The present study summarizes a recently completed database of
We developed a database of
In addition to the Calbug institutions, we obtained specimen data from the two largest
All contributing data sources, abbreviations, and total number of specimens.
Source collection | Abbreviation | # Specimens |
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CalBug Institutions | 14,207 | |
California Academy of Science | CASENT | 2,876 |
UC Riverside | CIS | 531 |
California State Collection of Arthopods | CSCA | 24 |
Essig Museum | EMEC | 5,550 |
LA County Museum | LACMENT | 2,032 |
Oakland Museum | OMC | 107 |
Santa Barbara Museum of Natural History | SBMNHENT | 153 |
San Diego Natural History Museum | SDNHM | 88 |
UC Bohart Museum | UCBME | 2,776 |
UC Riverside | UCRCENT | 70 |
non-CalBug Institutions | 5,803 | |
Florida State Collection of Arthropods | FSCA | 65 |
International |
IORI | 3,230 |
Louisiana State University | LSUC | 48 |
Museum of Zoology - Pontifical Catholic University of Ecuador (P.U.C.E) | QCAZ | 12 |
Illinois Natural History Survey | INHS | 96 |
University of Michigan Museum | UMMZI | 1,425 |
US National Museum | USNM | 927 |
Personal | 3,746 | |
C.H. Kennedy | CHK | 1,190 |
D.R. Paulson | DRPC | 930 |
R.W. Garrison | RWGC | 576 |
S.D. Gaimari | SDGC | 132 |
J.E. Ball-Damerow field collections | JEBD | 918 |
Observations | 8,269 | |
Cal Odes | Cal Odes | 6,777 |
1,492 | ||
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Since 2011, we have photographed specimens with their collection labels as the first stage of the data collection process. Further details on the imaging process are described on the Calbug website (
In addition to specimen collections, we also included occurrence data from
To facilitate quality control during data entry, the Essig database uses controlled vocabularies, such as dropdown lists, date range validation, and species name authority files to validate names. Hierarchical information is automatically filled in for geography and taxonomy.
Following data entry, we conducted a data checking procedure to minimize likely data-entry errors. This included an assessment of records with the same localities for spelling errors and to determine whether locations were associated with the correct county in the state. The data entry form of the database automatically filled information from one record to the next so that records with the same information in a series did not have to be entered multiple times. To minimize carry-over errors, we therefore checked records with adjacent UIDs for questionable repeated fields, such as collector or date. Finally, we spot checked all fields for a portion of specimens against the specimen label photograph.
We compared all specimen records to current county records and known distribution ranges as a method to check for outliers. Each specimen that fell outside of current county records for the species was checked for accurate identification and potential data entry errors. From these records, we retained only those with verified species identification and locality information. Finally, we corrected any species with outdated names, based on taxonomic classifications in
We georeferenced occurrence localities using the standardized point-radius method (
After all records were georeferenced, we spot checked a portion of records for accuracy. In addition, we checked all localities with listed counties that did not match county polygons using ArcGIS Desktop, release 10.1 (
We first summarized the number of species within each of the families found in the state. To demonstrate the temporal and spatial coverage of species occurrence records, we then summarized records by decade, by county, and in maps of occurrence locations. For this and all subsequent analyses, we removed any species considered to be vagrant, with only one sighting in the state. We determined species richness and the total number of specimens before 1900 and by decade in the following years. We then calculated species richness and total number of records by county for the entire period of record. In order to assess the effect of effort on species richness by county, we plotted the total number of species against the number of records for each county. We also used this information to identify regions that are currently underrepresented in the collections. Finally, we mapped all
The four collection types included in the database were the Calbug institutions (California University and government collections), non-Calbug (non-California) institutions, private collections of odonate specialists, and observation-based records. We first summarized the total number of records from each data source. To illustrate how different collections have contributed to our knowledge of spatial distribution of odonates in the state, we determined the number of unique county records from each of the major collection types. We summarized the number of unique county records (by species and county) shared by one, two, three, or all four types.
The final goal of this paper was to assess the prevalence of records for individual
To determine whether species have expanded to higher latitudes or elevations, we calculated the average and range of latitude and elevation for each species before 1976 and after 1979. Any records with greater than 4 km error radius were removed from this analysis. Wilcoxon signed-rank tests were performed to determine whether the median difference in latitude and elevation means between the two time periods were significantly different.
There were 32,025 records from all combined sources (Suppl. material
Summary of total California
Data source | Total records | Unique locality records | Unique county records |
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Specimen database | 21,648 | 11,149 | 8,716 |
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1,190 | 527 | 404 |
J.E. B-D field collections | 918 | 856 | 514 |
CalOdes | 6,777 | 5,463 | 2,698 |
1,492 | 1,005 | 923 | |
Totals | 32,025 | 19,000 | 13,255 |
There are currently 106 species within nine families that are known to occur in the state, including nine species of
The first peak in
Total number of California
The total number of species found throughout the state varied only slightly by decade, except for time periods when there were less than ~ 1,200 total records, e.g. before 1900 and 1900–1910. The time period with the highest number of records and species was 2000–2013, with 9,535 records and 106 species, followed by the 1990s, with 99 species and only 1,623 total records (Fig.
Total number of records and number of species by decade.
There was an exponential relationship between the total number of unique records from a given county and species richness observed (Fig.
Relationship between species richness and total number of records by county, where each point represents a California county.
Total number of records and species for each county.
County | Total records | Species richness | County | Total records | Species richness |
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Kings | 28 | 22 | Napa | 492 | 47 |
Sutter | 33 | 17 | Alameda | 496 | 47 |
San Benito | 56 | 25 | San Mateo | 504 | 45 |
Alpine | 93 | 30 | Shasta | 514 | 78 |
Amador | 109 | 41 | Sacramento | 524 | 46 |
Glenn | 111 | 33 | Plumas | 530 | 55 |
Tehama | 123 | 46 | Placer | 533 | 65 |
Lake | 153 | 48 | Fresno | 547 | 54 |
San Joaquin | 157 | 31 | Imperial | 562 | 39 |
Madera | 169 | 41 | Modoc | 580 | 64 |
San Francisco | 177 | 23 | Mono | 598 | 46 |
Calaveras | 179 | 39 | Butte | 664 | 56 |
San Luis Obispo | 180 | 37 | Lassen | 668 | 68 |
Santa Cruz | 191 | 45 | Santa Barbara | 701 | 44 |
Merced | 199 | 21 | Yolo | 710 | 44 |
Mariposa | 209 | 39 | Humboldt | 731 | 57 |
Del Norte | 211 | 41 | Colusa | 776 | 53 |
Solano | 235 | 38 | Nevada | 777 | 56 |
Sierra | 268 | 48 | Mendocino | 892 | 54 |
Yuba | 283 | 40 | Stanislaus | 904 | 42 |
Trinity | 306 | 50 | El Dorado | 924 | 57 |
Marin | 314 | 40 | Sonoma | 956 | 58 |
Monterey | 332 | 48 | San Bernardino | 1038 | 57 |
Tulare | 372 | 46 | Siskiyou | 1136 | 68 |
Tuolumne | 372 | 45 | Santa Clara | 1202 | 51 |
Orange | 437 | 35 | Inyo | 1548 | 59 |
Contra Costa | 445 | 39 | San Diego | 1759 | 58 |
Ventura | 474 | 35 | Los Angeles | 1804 | 45 |
Kern | 487 | 49 | Riverside | 2108 | 58 |
Most counties supported 40–60 species. Counties that were well above or below the confidence interval may be either relatively species-rich or species-poor (Fig.
A map of specimen localities for both time periods demonstrates some additional spatial bias and data gaps (Fig.
Spatial distribution of California records before 1976, and after 1979.
Calbug institutions contributed the highest number of total records with 14,207 total records, followed by observation-based records with 8,269 total records (Table
The observation-based records contributed the highest number of unique county records with 538 (by species and county only), followed by the Calbug institutions with 353 unique records (Fig.
Number of unique county records for each collection type (Calbug collaborating institutions, non-Calbug institutions, observations - Cal Odes and
There were 8,642 unique species occurrence records (i.e. unique locality and date) before 1976, and 9,175 unique occurrence records after 1979. The most commonly sampled species before 1976 were
Thirty-seven species decreased in relative occurrence in the two time periods examined, while 66 species increased (Table
Summary of species records, including earliest and latest observation or specimen collection date, unique occurrences (by site and year) before 1976 and after 1979, and the change in relative occurrence in unique records. Bolded records show the same relationship (i.e. increase or decrease in species prevalence) reported in
Family | Species | Earliest year | Latest year | Before 1975 | After 1980 | Change |
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1879 | 2013 | 767 | 535 | -232 | |
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1892 | 2013 | 612 | 414 | -198 | |
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1900 | 2013 | 268 | 134 | -134 | |
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1900 | 2013 | 256 | 126 | -130 | |
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1900 | 2013 | 329 | 218 | -111 | |
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1904 | 2013 | 168 | 70 | -98 |
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1894 | 2013 | 115 | 35 | -80 | |
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1900 | 2013 | 103 | 67 | -36 | |
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1926 | 2013 | 195 | 167 | -28 | |
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1912 | 2013 | 141 | 114 | -27 | |
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1900 | 2013 | 86 | 63 | -23 |
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1903 | 2013 | 92 | 71 | -21 | |
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1914 | 2013 | 103 | 84 | -19 | |
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1914 | 2013 | 50 | 38 | -12 |
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1914 | 2013 | 42 | 32 | -10 |
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1915 | 2012 | 26 | 19 | -7 | |
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1938 | 2013 | 19 | 12 | -7 | |
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1915 | 2013 | 34 | 28 | -6 |
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1897 | 2013 | 59 | 55 | -4 |
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1914 | 2013 | 22 | 19 | -3 |
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1900 | 2013 | 41 | 40 | -1 |
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1897 | 2012 | 25 | 24 | -1 |
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1900 | 2013 | 216 | 227 | 11 | |
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1914 | 2013 | 50 | 53 | 3 |
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1912 | 2013 | 62 | 66 | 4 |
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1900 | 2013 | 12 | 13 | 1 | |
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1915 | 2012 | 6 | 7 | 1 |
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1914 | 2013 | 48 | 52 | 4 |
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1914 | 2013 | 10 | 13 | 3 |
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1974 | 2012 | 1 | 4 | 3 |
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1914 | 2013 | 32 | 37 | 5 |
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1915 | 2013 | 12 | 16 | 4 |
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1965 | 2013 | 4 | 8 | 4 | |
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1914 | 2013 | 2 | 6 | 4 |
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1952 | 2013 | 1 | 5 | 4 |
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1938 | 2013 | 17 | 22 | 5 |
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1935 | 2013 | 16 | 21 | 5 |
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1914 | 2013 | 3 | 8 | 5 | |
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1914 | 2013 | 12 | 18 | 6 | |
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1915 | 2013 | 19 | 26 | 7 |
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1973 | 2013 | 1 | 9 | 8 | |
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1915 | 2013 | 10 | 19 | 9 |
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1914 | 2013 | 23 | 33 | 10 | |
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1897 | 2013 | 59 | 72 | 13 | |
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1914 | 2013 | 21 | 32 | 11 |
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1914 | 2013 | 80 | 95 | 15 |
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1945 | 2013 | 26 | 38 | 12 |
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1911 | 2013 | 51 | 65 | 14 |
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1915 | 2013 | 11 | 23 | 12 | |
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1998 | 2012 | 0 | 12 | 12 |
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1900 | 2013 | 15 | 29 | 14 |
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1938 | 2013 | 4 | 18 | 14 |
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1988 | 2011 | 0 | 14 | 14 |
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1914 | 2012 | 5 | 21 | 16 | |
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1947 | 2013 | 2 | 19 | 17 |
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1914 | 2013 | 15 | 33 | 18 | |
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1934 | 2013 | 11 | 29 | 18 | |
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1914 | 2013 | 34 | 54 | 20 | |
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1914 | 2013 | 17 | 36 | 19 | |
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1980 | 2012 | 0 | 19 | 19 |
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1951 | 2013 | 7 | 27 | 20 |
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1930 | 2013 | 7 | 28 | 21 |
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1953 | 2013 | 4 | 25 | 21 |
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1915 | 2012 | 16 | 40 | 24 |
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1930 | 2013 | 7 | 32 | 25 |
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1918 | 2013 | 15 | 44 | 29 |
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1907 | 2013 | 71 | 104 | 33 |
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1934 | 2013 | 8 | 38 | 30 |
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1905 | 2013 | 68 | 104 | 36 |
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1900 | 2013 | 27 | 61 | 34 | |
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1915 | 2013 | 20 | 55 | 35 |
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1901 | 2013 | 86 | 126 | 40 |
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1915 | 2013 | 19 | 56 | 37 | |
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1901 | 2013 | 31 | 69 | 38 |
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1907 | 2013 | 31 | 69 | 38 |
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1918 | 2013 | 22 | 61 | 39 | |
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1912 | 2013 | 157 | 208 | 51 |
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1897 | 2013 | 92 | 144 | 52 |
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1914 | 2013 | 16 | 77 | 61 |
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1905 | 2013 | 84 | 166 | 82 |
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1900 | 2013 | 85 | 220 | 135 |
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Total number of unique occurrences: | 8642 | 9175 |
In comparing the average and range of latitude and elevation across individual species occurrence localities, we excluded all records with an error radius of greater than 4 km. The total number of unique records before 1976 available was then 5,142 and the total number of unique records after 1979 was 7,785. The median average latitude across all species increased by 0.7° (±0.82, p<0.001), indicating an average shift of around 78 km northwards (Table
Summaries of change in unique species latitude and elevation values before 1976 and after 1979. Unique records represent unique combinations of species, locality coordinates, and year. Records included in this assessment have an error radius ≤ 4 km.
Average change | Standard deviation | Wilcoxon rank-sign test | P-Value | |
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Avg Elevation (m) | -49 | 248 | V = 2730 | 0.37 |
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Max Elevation (m) | 49 | 613 | V = 2099 | 0.19 |
The California
Previous work has noted a decline in specimen acquisition of natural history museums over the past 30–40 years that corresponds with declines in funding for many of these institutions (
The present study also identified spatial biases and data gaps, which should be addressed in any distributional analyses and in designing future sampling investigations of California odonates. As demonstrated in a previous spatial analysis of
Species richness is not strongly associated with total number of records at the statewide scale (Fig.
Each of the different collection types—Calbug (i.e. California) institutions, non-Calbug institutions, private collections, and observation-based records—contributed significantly to the total number of records and to county records for species. The Calbug institutions had the highest total number of records, followed by observation-based records, which had just over half the number of total records as Calbug. However, observations contributed significantly more county records for species. The goal of many enthusiasts is to find new county records, which likely explains this difference. We find that recent observation-based records have greatly contributed to our knowledge of the spatial distribution of odonate species in California.
Apparent changes in species prevalence according to occurrence records are sometimes the result of variation in taxonomic biases, particularly in comparing natural history specimens and observation-based records (Table
Species that have increased in prevalence over time, however, often demonstrate more reliable results than those with apparent declines (
However, we also observed a decline in the average minimum elevation across species. This could be the result of increases in dry-season water habitats throughout low elevation areas of the Central Valley with increased irrigation for agriculture (
The California
We first thank the reviewers of this manuscript for their valuable feedback, especially E. DeWalt. This research was supported in part by the National Science Foundation under Grant No. DBI 0956389 to R.G. Gillespie, K. Will, G.K. Roderick, and V.H. Resh, and the Margaret C. Walker Fund for teaching and research in systematic entomology. We thank D.R. Paulson, R.W. Garrison, S.D. Gaimari, T.D. Manolis, and K. Biggs for contribution of data, and Gordon Nishida, Jessica Rothery, among others, for assistance with georeferencing species occurrence localities. We also thank M.F. O’Brien, W.F Mauffray, N.D. Penny, D. Yanega, S. Heydon, M.S. Caterino, B.V. Brown, and M.A Wall. Wall for providing
California
occurence