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The National Ecological Observatory Network (NEON) is a long-term monitoring program at the continental scale designed to understand and forecast ecological responses to environmental change at local to broad scales. However, despite robust and nearly continuous collections, NEON mosquito data have been underused in downstream analyses. Here, we provide species-level estimated abundances for nighttime collected female mosquitoes derived from the mosquitoes sampled from CO2 traps (DP1.10043.001) (RELEASE-2024; NEON, 2024). By including zero counts, our derived data complement existing data sets and provide an analysis-ready time series useful for investigating mosquito phenology, abundances, and diversity at the species or community level. We also outline a set of considerations specific to filtering NEON mosquito data by sex and for day or nighttime collections, highlighting factors that could introduce uncertainty to abundance estimates. Along with the data set, we provide an R Markdown file that includes annotated code and documents our data filtering and QC/QA steps, as well as data files used to filter the mosquito data based on QC/QA criteria. All files are freely available for download through the Environmental Data Initiative data portal. Our reproducible and fully documented workflow can be easily adapted for specific needs or other NEON surveillance data. Our work aims to enhance the accessibility and use of NEON’s rich, long-term monitoring data. 

Elaborate traits evolve via intense selective pressure, overpowering ecological constraints. Hindwing tails that thwart bat attack have repeatedly originated in moon moths (Saturniidae), with longer tails having greater anti-predator effect. Here, we take a macroevolutionary approach to evaluate the evolutionary balance between predation pressure and possible limiting environmental factors on tail elongation. To trace the evolution of tail length across time and space, we inferred a time-calibrated phylogeny of the entirely tailed moth group (Actias + Argema) and performed ancestral state reconstruction and biogeographical analyses. We generated metrics of predation via estimates of bat abundance from nearly 200 custom-built species distribution models and environmental metrics via estimates of bioclimatic variables associated with individual moth observations. To access community science data, we developed a novel method for measuring wing lengths from un-scaled photos. Integrating these data into phylogenetically informed mixed models, we find a positive association between bat predation pressure and moth tail length and body size, and a negative association between environmental factors and these morphological traits. Regions with more insectivorous bats and more consistent temperatures tend to host longer-tailed moths. Our study provides insight into tradeoffs between biotic selective pressures and abiotic constraints that shape elaborate traits across the tree of life. 

This Level 2 data package contains species level estimated abundances, including zero counts, and estimated mean number of female mosquitoes per trap derived from the NEON Mosquitoes sampled from CO2 traps (DP1.10043.001), RELEASE-2024 Level 0 data (https://doi.org/10.48443/3cyq-6v47). The data set includes mosquito records of traps collecting mosquito samples at night, for up to 24 trap hours, across a total of 20 terrestrial core and 27 terrestrial gradient sites from 2014 to 2022. To ensure high confidence in abundance estimates, records were only included when at least 90% of collected individuals were identified to sex, and 90% of female specimens were identified to species. Information across multiple QC/QA fields within the NEON mosquito data was evaluated to identify and exclude records where confidence in estimated abundances may have been compromised. Species level zero counts were added for all species collected at least once within the sampling year and trap location. Additionally, species level zero counts were included for trap events where only male mosquitoes had been collected or where QC/QA remarks indicated traps were inactive due to cold temperatures. The data set provides an analysis ready time series of estimated abundances across NEON sites and plots. An R Markdown file that contains descriptions of the QC/QA and data filtering steps along with annotated code, as well as data tables used to filter active and inactive trap events based on QC/QA fields, are published with the data package. Any questions about this data package should be directed to Amely Bauer listed under contacts. 

Abstract Mountains and islands provide an opportunity for studying the biogeography of diversification and population fragmentation. Aotearoa (New Zealand) is an excellent location to investigate both phenomena due to alpine emergence and oceanic separation. While it would be expected that separation across oceanic and elevation gradients are major barriers to gene flow in animals, including aquatic insects, such hypotheses have not been thoroughly tested in these taxa. By integrating population genomic from subgenomic Anchored-Hybrid Enrichment sequencing, ecological niche modeling, and morphological analyses from scanning-electron microscopy, we show that tectonic uplift and oceanic vicariance are implicated in speciation and population structure in Kapokapowai (Uropetala) dragonflies. Although Te Moana o Raukawa (Cook Strait) is likely responsible for some of the genetic structure observed, speciation has not yet occurred in populations separated by the strait. We find that the altitudinal gradient across Kā Tiritiri-o-te-Moana (the Southern Alps) is not impervious, but it significantly restricts gene flow between the aforementioned species. Our data support the hypothesis of an active colonization of Kā Tiritiri-o-te-Moana by the ancestral population of Kapokapowai, followed by a recolonization of the lowlands. These findings provide key foundations for the study of lineages endemic to Aotearoa. 

It was shown in [10] that that there exist strongly dense free subgroups in any semisimple algebraic group over a large enough field. These are nonabelian free subgroups all of whose subgroups are either cyclic or Zariski-dense. Here we show that the same is true for as long as the transcendence degree of the field is at least 1 in characteristic 0 and transcendence degree at least 2 in positive characteristic. 

Abstract Insects often exhibit irruptive population dynamics determined by environmental conditions. We examine if populations of theCulex tarsalismosquito, a West Nile virus (WNV) vector, fluctuate synchronously over broad spatial extents and multiple timescales and whether climate drives synchrony inCx. tarsalis, especially at annual timescales, due to the synchronous influence of temperature, precipitation, and/or humidity. We leveraged mosquito collections across 9 National Ecological Observatory Network (NEON) sites distributed in the interior West and Great Plains region USA over a 45-month period, and associated gridMET climate data. We utilized wavelet phasor mean fields and wavelet linear models to quantify spatial synchrony for mosquitoes and climate and to calculate the importance of climate in explainingCx. tarsalissynchrony. We also tested whether the strength of spatial synchrony may vary directionally across years. We found significant annual synchrony inCx. tarsalis, and short-term synchrony during a single period in 2018. Mean minimum temperature was a significant predictor of annualCx. tarsalisspatial synchrony, and we found a marginally significant decrease in annualCx. tarsalissynchrony. SignificantCx. tarsalissynchrony during 2018 coincided with an anomalous increase in precipitation. This work provides a valuable step toward understanding broadscale synchrony in a WNV vector. 

Abstract PremiseOne of the slowest steps in digitizing natural history collections is converting labels associated with specimens into a digital data record usable for collections management and research. Here, we address how herbarium specimen labels can be converted into digital data records via extraction into standardized Darwin Core fields. MethodsWe first showcase the development of a rule‐based approach and compare outcomes with a large language model–based approach, in particular ChatGPT4. We next quantified omission and commission error rates across target fields for a set of labels transcribed using optical character recognition (OCR) for both approaches. For example, we find that ChatGPT4 often creates field names that are not Darwin Core compliant while rule‐based approaches often have high commission error rates. ResultsOur results suggest that these approaches each have different strengths and limitations. We therefore developed an ensemble approach that leverages the strengths of each individual method and documented that ensembling strongly reduced overall information extraction errors. DiscussionThis work shows that an ensemble approach has particular value for creating high‐quality digital data records, even for complicated label content. While human validation is still needed to ensure the best possible quality, automated approaches can speed digitization of herbarium specimen labels and are likely to be broadly usable for all natural history collection types. 

Abstract The “small-eared” species group of Urocitellus ground squirrels (Sciuridae: Xerinae: Marmotini) is endemic to the Great Basin, United States, and surrounding cold desert ecosystems. Most specific and subspecific lineages in this group occupy narrow geographic ranges, and some are of significant conservation concern; despite this, current taxonomy remains largely based on karyotypic or subtle pelage and morphological characteristics. Here, we leverage 2 multilocus DNA sequence data sets and apply formal species delimitation tests alongside morphometric comparisons to demonstrate that the most widespread small-eared species (U. mollis Kennicott, 1863 sensu lato; Piute Ground Squirrel) is comprised of 2 nonsister and deeply divergent lineages. The 2 lineages are geographically separated by the east-west flowing Snake River in southern Idaho, with no sites of sympatry currently known. Based on robust support across the nuclear genome, we elevate populations previously attributed to U. mollis from north of the Snake River to species status under the name Urocitellus idahoensis (Merriam 1913) and propose the common name “Snake River Plains Ground Squirrel” for this taxon. We delimit 2 subspecies within U. idahoensis; U. i. idahoensis (Merriam 1913) in western Idaho and U. i. artemesiae (Merriam 1913) in eastern Idaho. Urocitellus idahoensis is endemic to Idaho and has a maximal range area of roughly 29,700 km2 spanning 22 counties but occurs discontinuously across this area. Our work substantially expands knowledge of ground squirrel diversity in the northern Great Basin and Columbia Plateau and highlights the difficulty in delimiting aridland mammals whose morphological attributes are highly conserved. 

Abstract Nitrogen (N)-fixing symbiosis is critical to terrestrial ecosystems, yet possession of this trait is known for few plant species. Broader presence of the symbiosis is often indirectly determined by phylogenetic relatedness to taxa investigated via manipulative experiments. This data gap may ultimately underestimate phylogenetic, spatial, and temporal variation in N-fixing symbiosis. Still needed are simpler field or collections-based approaches for inferring symbiotic status. N-fixing plants differ from non-N-fixing plants in elemental and isotopic composition, but previous investigations have not tested predictive accuracy using such proxies. Here we develop a regional field study and demonstrate a simple classification model for fixer status using nitrogen and carbon content measurements, and stable isotope ratios (δ¹⁵N and δ¹³C), from field-collected leaves. We used mixed models and classification approaches to demonstrate that N-fixing phenotypes can be used to predict symbiotic status; the best model required all predictors and was 80–94% accurate. Predictions were robust to environmental context variation, but we identified significant variation due to native vs. non-native (exotic) status and phylogenetic affinity. Surprisingly, N content—not δ¹⁵N—was the strongest predictor, suggesting that future efforts combine elemental and isotopic information. These results are valuable for understudied taxa and ecosystems, potentially allowing higher-throughput field-based N-fixer assessments.