LepNet: The Lepidoptera of North America Network

Seltmann, Katja C.; Cobb, Neil S.; Gáll, Lawrence F.; Bartlett, Charles R.; Basham, M. Anne; Betancourt, Isabelle; Bills, Christy; Brandt, B. B.; Brown, Richard L.; Bundy, C. Scott; Caterino, Michael S.; Chapman, Caitlin; Cognato, Anthony I.; Colby, Julia; Cook, Stephen P.; Daly, Kathryn M.; Dyer, Lee A.; Franz, Nico M.; Gelhaus, Jon K.; Grinter, Christopher C.; Harp, Charles E.; Hawkins, Rachel; Heydon, S. L.; Hill, Geena M.; Huber, Stacey; Johnson, Norman J.; Kawahara, Akito Y.; Kimsey, Lynn S.; Kondratieff, Boris C.; Krell, Frank-Thorsten; Leblanc, Luc; Lee, Sangmi; Marshall, Christopher J.; McCabe, Lindsie M.; McHugh, Joseph V.; Menard, Katrina L.; Opler, Paul A.; Palffy-Muhoray, Nicole; Pardikes, Nicholas A.; Peterson, M. J.; Pierce, Naomi E.; Poremski, Andre; Sikes, Derek S.; Weintraub, Jason D.; Wikle, David; Zaspel, Jennifer M.; Zolnerowich, Gregory

doi:10.11646/zootaxa.4247.1.10

Cited by 22 publications

(25 citation statements)

References 13 publications

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“…The SCAN portal (Seltmann et al 2017; http://scan-bugs.org) was queried for "Tenebrionidae" specimen records (under taxonomic criteria and including synonyms) using the portal's Spatial Module, i.e. by specifying a geographic polygon that includes the Algodones Dunes and surrounding sandy flats.…”

Section: Checklist Generation Methodsmentioning

confidence: 99%

“…For instance, at the time of preparing this article (March, 2018), the "Symbiota Collections of Arthropods Network" portal (SCAN; Gries et al 2014, Seltmann et al 2017) returned nearly 6.65 million occurrence records for the query "Hexapoda, USA". However, this number may only represent 5-10% of the corresponding material (estimated: >110 million) stored in North American research collections (Cobb et al 2016).…”

Section: Introduction - the Branching Out Of Checklist Datamentioning

confidence: 99%

“…However, this number may only represent 5-10% of the corresponding material (estimated: >110 million) stored in North American research collections (Cobb et al 2016). Checklist authors who strive to balance taxonomic comprehensiveness with best data science practices therefore face pragmatic choices; in effect acting as filterers of available data sources that range from published literature that merely imply the existence of an occurrence record, to physically vouchered but non-digitized records, to digital records that may lack a uniquely identified physical voucher and finally, to aggregated, fully standard-compliant and, hence, "research-ready" specimens (Seltmann et al 2017). The latter often represent the most desirable minority of the available data.…”

Section: Introduction - the Branching Out Of Checklist Datamentioning

confidence: 99%

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An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Johnston

Aalbu²,

Franz

2018

BDJ

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Generating regional checklists for insects is frequently based on combining data sources ranging from literature and expert assertions that merely imply the existence of an occurrence to aggregated, standard-compliant data of uniquely identified specimens. The increasing diversity of data sources also means that checklist authors are faced with new responsibilities, effectively acting as filterers to select and utilize an expert-validated subset of all available data. Authors are also faced with the technical obstacle to bring more occurrences into Darwin Core-based data aggregation, even if the corresponding specimens belong to external institutions. We illustrate these issues based on a partial update of the Kimsey et al. 2017 checklist of darkling beetles - Tenebrionidae sec. Bousquet et al. 2018 - inhabiting the Algodones Dunes of California. Our update entails 54 species-level concepts for this group and region, of which 31 concepts were found to be represented in three specimen-data aggregator portals, based on our interpretations of the aggregators' data. We reassess the distributions and biogeographic affinities of these species, focusing on taxa that are precinctive (highly geographically restricted) to the Lower Colorado River Valley in the context of recent dune formation from the Colorado River. Throughout, we apply taxonomic concept labels (taxonomic name according to source) to contextualize preferred name usages, but also show that the identification data of aggregated occurrences are very rarely well-contextualized or annotated. Doing so is a pre-requisite for publishing open, dynamic checklist versions that finely accredit incremental expert efforts spent to improve the quality of checklists and aggregated occurrence data.

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Section: Checklist Generation Methodsmentioning

confidence: 99%

Section: Introduction - the Branching Out Of Checklist Datamentioning

confidence: 99%

Section: Introduction - the Branching Out Of Checklist Datamentioning

confidence: 99%

See 1 more Smart Citation

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Johnston

Aalbu²,

Franz

2018

BDJ

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“…Specifically, digitization standards include a color card for white balance correction and a scale bar for specimen size calibration (Figure ). These two features (in addition to a georeferenced location and collection date) are crucial for macroecological analyses using digitized image collections and, as such, their inclusion has been adopted by national initiatives like LepNet (Seltmann et al., ). In contrast, other large image collections like BOLD (Ratnasingham & Hebert, ) or investigator‐led image repositories (e.g., Janzen & Hallwachs, ) generally include only the specimen itself, making large‐scale image analyses challenging, if not impossible.…”

Section: Discussionmentioning

confidence: 99%

Using digitized museum collections to understand the effects of habitat on wing coloration in the Puerto Rican monarch

Ramos

Hulshof

2019

Biotropica

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Given the recent emphasis on Lepidoptera wing color and temperature in macroecology, we briefly describe known drivers of wing color and outline the use of images for understanding color variation across space and time. As a case study, we quantify wing color using museum specimens of the non‐migratory Puerto Rican monarch. In contrast to recent findings, we report darker individuals in coastal habitats, underscoring the need to include other selection factors. We detail how international digitization initiatives can resolve this paradox by adopting standards and protocols for high‐throughput image analysis. Abstract in Spanish is available with online material.

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“…Occurrence records were also gathered from the Global Biodiversity Information Facility and Lepidoptera of North America Network (LepNet). LepNet is a thematic collection network, whose data included human observations from community scientists and preserved specimens from natural history collections (Seltmann et al, 2017).…”

Section: Aggregating Poweshiek Skipperling Occurrence Datamentioning

confidence: 99%

Landscape‐level environmental stressors contributing to the decline of Poweshiek skipperling (Oarisma poweshiek)

Belitz

Monfils

Cuthrell

et al. 2019

Insect Conserv Diversity

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1. The Poweshiek skipperling [Oarisma poweshiek (Parker, 1870; Lepidoptera: Hesperiidae)] is a federally endangered butterfly that was historically common in prairies of the upper Midwestern United States and Southern Manitoba, Canada. Rapid declines over the last 20 years have reduced the population numbers to four verified extant sites. The causes of Poweshiek skipperling decline are unknown. 2. We aggregated all known Poweshiek skipperling occurrence records to examine the spatiotemporal patterns of Poweshiek skipperling decline. Ecological niche models were developed for five time frames (1985, 1990, 1995, 2000 and 2005) and three spatial extents (eastern occupied range, western occupied range and total occupied range). We used a backward elimination method to investigate the effects of climate and land use on the ecological niche of Poweshiek skipperling. 3. Predictors of occurrence changed over time and across the geographical extent of Poweshiek skipperling. Land use covariates were retained in east models. In the west and total extent, climate variables contributed the most to model predictive power for the 1985, 1990 and 1995 models; land use variables contributed the most to model predictive power in the 2000 and 2005 models. 4. During the rapid decline in Poweshiek skipperling population numbers occurring at the turn of the century, probability of Poweshiek skipperling presence was being driven by proportion of natural land cover and distance to nearest grassland/wetland. Our results suggest that these land use variables are important landscape‐level variables to consider when developing risk assessments of extant populations and potential reintroduction sites.

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LepNet: The Lepidoptera of North America Network

Cited by 22 publications

References 13 publications

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

An updated checklist of the Tenebrionidae sec. Bousquet et al. 2018 of the Algodones Dunes of California, with comments on checklist data practices

Using digitized museum collections to understand the effects of habitat on wing coloration in the Puerto Rican monarch

Landscape‐level environmental stressors contributing to the decline of Poweshiek skipperling (Oarisma poweshiek)

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