Abstract
Red crossbills (Loxia curvirostra) are the archetypal example of a taxon with high infraspecific diversity in traits including bill size and especially vocal characteristics. Currently, at least 11 different call types in North America have been recognized. We hypothesize that a variant call within type 10 has been overlooked and is a distinct type. Principal component analysis showed that the inverted “V” of these calls is consistently and demonstrably different from similar calls of birds previously categorized as Type 10 variants. We argue these calls should be treated separately as a distinct type, Type 12. Due to increasingly available recordings of crossbills gathered and archived into public databases by birders, our analyses reveal that this call type is predominantly distributed across northeastern North America. Although crossbill types do not always map to formerly described subspecies, we also argue that Type 12 likely matches the historically described L. c. neogaea, the “old Northeastern subspecies”.
1 Introduction
The crossbill genus Loxia represents enigmatic but widespread birds that inhabit much of the Northern Hemisphere. Across this range, two species of wing-barred crossbills (L. leucoptera, L. megaplaga) and four species of red crossbills (L. curvirostra, L. sinesciuris, L. scotica, L. pytyopsittacus) have evolved bills with crossed mandibles and varying sizes suited for prying open the scales of different conifer cones to feed on the seeds therein (). Given the ephemeral and erratic pattern of conifer masting, some crossbill species are well-known for their nomadic behavior and irruptions, where they travel far beyond their expected range in search of food (; ).
During the late 1980s and early 1990s, the red crossbill (Loxia curvirostra) in the United States, Canada, and Mexico was recognized as consisting of several different “call types” (), or ecotypes based on flight calls. Although some crossbill vocalizations are variable, flight calls have been found to reliably identify individuals as belonging to a particular call type (, ; ). Call types also correlate with slight differences in bill depth morphology which correspond to optimal feeding on preferred sized cones (; ). noted that call types can display “species-like” behavior, noting that Types 1 and 2 bred side-by-side in Virginia but did not interbreed. Another study showed that females presented with males of Type 2 or 9 preferred to associate males of their own call type (Snowberg and Benkman, 2007) and Type 9 was subsequently promoted to the species level (Cassia crossbill, L. sinesciuris) due to differences in genetics, vocalizations, morphology, and a limited range (). Although overall the situation is complex and genetic differences between types may be small (), there is certainly more work to be done on understanding call types, their interactions, and the degree to which these populations should be considered cryptic or incipient species (; Smith and Benkman, 2007; ). Distinct flight calls are apparently a mechanism used to help to maintain differentiation in crossbills even in sympatry when flocks of red crossbill types leave their core ranges to roam the continent.
Over time, the number of recognized call types has expanded as researchers have analyzed sound recordings and other data gathered in the field, both in the Nearctic and Palearctic. As of this research, 11 call types range from Alaska to Newfoundland and south to Nicaragua in North America, and at ~20 types have been reported from the Palearctic ().
In the period between 2012 and today, red crossbill recordings in the Macaulay Library archive increased by > 4000%, enabling much learning about the status and distribution of these birds. The impetus for the work in this paper began as we were engaged in audiospectographically classifying to type these recordings. This endeavor led to the identification of Type 11 red crossbills which inhabit Central America (Young and Spahr, 2017).
Analyses of crossbill flight call recordings over the last 60 years indicate noticeable variation in call structure, sometimes leading to the discovery of new types. For example, described Type 10 in the Pacific Northwest USA, which has a relatively restricted range and is most closely associated with Sitka spruce (Picea sitchensis) along the Pacific coast. Yet recordings from there and elsewhere across North America, especially the northeast, contained calls thought to be either odd variants of Type 10 or possibly an unrecognized call type. Such variants are present in recordings dating back to at least the 1960s.
These variant flight calls, which look like an inverted “V” in spectrograms (Figure 1A), appear distinct from typical Type 10 birds (Figure 1B). Looking back into historical recordings, a single bird making similar flight calls was recorded in Klamath County Oregon in August 1986 (aF497 in , Figure 1C) and at the time was classified as Type 7, the most poorly understood type. In the early 2000s, several birds were recorded in Humbolt County California, (variants #30 through #33 in ), then thought to be a rare variant of Type 10. In the last decade, research into red crossbill call types has gained momentum with the proliferation of smartphones, the relative ease of audiospectrographic analysis, and the popularization of centralized audio archives such as xeno-canto.org and ebird.org (). As red crossbill recording has increased, so, too, has the detection of these unknown birds showing the inverted “V”-shaped spectra, especially in the northeast. In recent years, there has been wider recognition that these birds were not Type 10, for example, a dozen similar birds recorded in northern Wisconsin in 2017–2018 were provisionally labeled “eastern Type 10” (ML89997101 in , Figure 1D).
Figure 1
Literature reports indicate red crossbills were common across the northeastern U.S. and southern Canada approximately 100 years ago, but drastic overlogging of vast eastern white pine (Pinus strobus), eastern hemlock, (Tsuga canadensis), and red spruce (Picea rubens) forests during the late 1800s and early 1900s may have led to a decline in numbers or driven this population of crossbills from its historical core range (
Figure 2

All Type 12 red crossbill records reported to
Here, we hypothesize that these variant calls represent a distinct red crossbill call type that can be identified based on quantitative characteristics of its flight calls, which we term Type 12. We further hypothesize that this distinct call type is a good fit formerly proposed northeastern subspecies L. c. neogaea (
2 Methods
We focused the principal component analysis (PCA) on 57 flight call recordings from across North America from the
For our analysis of these flight calls, we employed an innovative approach utilizing feature embeddings derived from a machine learning model. The application of machine learning to the study of bird vocalizations is growing (e.g., Yang et al., 2024). Within this framework, feature embeddings are vectors produced by an intermediate layer of a trained machine learning model (Stowell, 2022). These vectors capture abstract yet semantically significant features that extend beyond traditional human-engineered metrics such as note sequences or signal shapes. Despite their abstract nature, these features efficiently represent the input audio signal and can distinguish between different call types or dialects, which often vary only subtly. Additionally, feature embeddings have the capability to support cross-taxa classification, as they can generalize across various acoustic domains and events. The machine learning algorithm utilized in this study is BirdNET v2.3 (
We used the BirdNET-Analyzer GUI which is openly available online at GitHub (
To evaluate whether Type 12 is a good fit for L. c. neogaea (
3 Results
Figure 3 shows a standard PCA plot—with component 1 on the X-axis and component 2 as the Y-axis. Types 10 and 12 are easily separated based on this analysis, with a clear demarcation between the types. Only 3 of 57 recordings differ in assignment between the PCA and the manual assignment by the authors, and those 3 had PC1 values very close to zero. The fraction of the variance explained by PC1 is 14.8%; the fraction explained by PC2 is 8.0%. These numbers are lower than one would expect from a standard PCA analysis, but we must remember that instead of using hand-selected inputs to the PCA analysis (e.g. call duration or mean frequency), we are using the embeddings from BirdNET. These embeddings are meant to capture the variability in birdsong in a broad sense and therefore are likely picking up on more variation in the calls than just the main spectrographic features that our eyes are drawn to.
Figure 3

Principal component analysis of 27 Type 10 and 30 Type 12 recordings from the Macaulay Library. The two types separate into two unique clusters deliniated by a positive or negative component 1.
Despite the challenge of specifically assigning a feature embedding to a variable we can gain some insight into the characteristic of this first component by looking at the 57 spectrograms, ordered by their value of the first component (Figure 4). These spectrograms suggest that the first component of the PCA describes whether the tail of the spectrogram sweeps up or plunges down. There is slight overlap between these labeled groups; the three spectrograms with Component 1 values closest to zero are probably out of order. The best division between Type 10 and Type 12 in this analysis may simply be positive or negative values for PC 1.
Figure 4

Spectrograms of Type 10 and Type 12 flight calls used for principal component analysis. Spectrograms are ordered by their value of component 1. Time axis is in seconds; Frequency axis is in kilohertz.
Records of Type 12 birds in the eBird and Macaulay Library archives produced a picture of their movements and locations throughout the year. Specifically, in late summer, when crossbills generally return to their primary core range, Type 12 largely overlaps the eastern range ranges mapped for neogaea (Figure 2; see Figure 5 for a generalized view). Birds were most commonly found in Massachusetts, New Hampshire, Maine, New York, Vermont, and Nova Scotia. Secondary range appears to be south to North Carolina and west to Minnesota, in some seasons. There were few records of Type 12 birds are occupying the northern and westernmost extents of the hypothesized neogaea range.
Figure 5

Hypothetical range for Type 12 red crossbill, based on known records from
4 Discussion
Our analyses of the call structures reveal distinctive and repeatable differences leading us to propose formal recognition of this call type as North American Call Type 12, or “Northeastern” red crossbill. The flight calls are clearly separable and in 54 of 57 cases, the PCA agreed with our manual auditory and spectrographic assessment. The agreement of the PCA and manual methods supports our methods for classifying these birds auditorily and by spectrogram. The PCA also affirms that the feature of the flight calls that was most significant for separation was the presence of the downward inflection at the end of the Type 12 calls.
In July and August, Type 12 crossbills move back to their core range, which appears to be extensively the northeastern United States, and to a lesser extent, the central Atlantic states and the western Great Lakes (Figure 5; see Figure 2 for a detailed, point-by-point view). When we compare current records to historical predicted ranges of neogaea, we find a good match for the eastern part of that range. However, birds appear to be further south than predicted by
The taxonomy of crossbills has long been confusing. Matching conventional subspecies determined via museum skins with call types from live birds has been a challenge with this species (or species complex) because types are not necessarily diagnosable from museum skins with simple measurements (
Clearly, establishing Type 12 red crossbill as its own type is the first step to learning more about it. Bill morphology is thought to be a critical aspect of red crossbill types (
Based on our own limited observations and conifers available in its core breeding range, we suspect important trees include red spruce, white spruce (Picea glauca), and red (Pinus resinosa), jack (Pinus banksiana), pitch pine (Pinus rigida) and white pine. We have also observed them feeding on tamarack (Larix laricina), Eastern hemlock, Japanese black pine (Pinus thunbergii), and Norway spruce (Picea abies). Based on records in eBird and patterns of other types, we would expect them to shift seasonally with cone ripening phenologies. The cone cycle year starts approximately July 1 when new cone crops are developing. Type 12 (like almost all North American crossbills) first forages on soft-coned conifers (i.e. white and red spruces) when seeds ripen. As those seeds are dropped, Type 12 may move to eastern white pine, and eventually to species that hold their seeds the longest such as the hard-coned red, jack and pitch pines.
Based on eBird records, the core zone of occurrence for Type 12 includes Maine, New Hampshire, western Massachusetts, Nova Scotia and the Adirondack region of New York. Type 12 also occurs with frequency in eastern Massachusetts, Vermont, central New York, Ontario, and Michigan, Wisconsin, and eastern Minnesota—this would be its secondary core zone of occurrence. This type apparently also sometimes migrates down the east coast to Cape Cod, Long Island, New Jersey, Delaware. In late summer 2020, Type 12 south along the coast to North Carolina and in the interior to the southern Appalachians (
5 Conclusions
We have shown that calls formerly considered as variants of types 7 and 10 found in Western North America are consistently different from calls of the already described types and are consistently associated with birds recorded in Northeastern North America. There have been over 3,800 recordings of Type 12 as of this writing (
More work is needed on red crossbill call types, including exploring morphological and genetic variation within and between types, and long-term persistence of flight call characteristics, and studies on assortative mating. We encourage everyone to record and archive audio of red crossbills, as they too could be part of new and exciting discoveries.
Statements
Data availability statement
The dataset presented in this study is available to the public and can be found online at Macaulay Library at the Cornell Lab of Ornithology (https://www.macaulaylibrary.org). We used the following recordings: ML52172751, ML123435191, ML146363001, ML302385451, ML166741681, ML251384271, ML291596351, ML251382691, ML104487211, ML73216801, ML284673751, ML302447281, ML261216601, ML143501131, ML309922261, ML140552761, ML257204411, ML146361771, ML254305011, ML79681201, ML68288161, ML126076831, ML184495481, ML290406691, ML255180601, ML280405751, ML146362951, ML146362991, ML255361541, ML166639471, ML125804521, ML247473351, ML278091551, ML281116501, ML321335001, ML149109121, ML266676901, ML252688821, ML256238321, ML252596091, ML84149341, ML262064191, ML102344491, ML71662361, ML281740721, ML84149391, ML209409041, ML315802411, ML93542171, ML78834791, ML290480061, ML88552971, ML146057101, ML126076841, ML285808521, ML64984631, ML23032596.
Author contributions
MY: Writing – original draft, Writing – review & editing. KM: Formal analysis, Visualization, Writing – original draft, Writing – review & editing. TR: Writing – original draft, Writing – review & editing. SK: Formal analysis, Writing – original draft, Writing – review & editing. NA: Visualization, Writing – original draft, Writing – review & editing. RB: Writing – original draft, Writing – review & editing. DY: Writing – original draft, Writing – review & editing. RM: Writing – original draft, Writing – review & editing. TS: Visualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Details of all funding sources should be provided, including grant numbers if applicable. Please ensure to add all necessary funding information, as after publication this is no longer possible. The development of BirdNET is supported by Jake Holshuh (Cornell class of ‘69) and The Arthur Vining Davis Foundations). The German Federal Ministry of Education and Research is funding the development of BirdNET through the project “BirdNET+” (FKZ 01|S22072). Additionally, the German Federal Ministry of Environment, Nature Conservation and Nuclear Safety is funding the development of BirdNET through the project “DeepBirdDetect” (FKZ 67KI31040E).
Acknowledgments
We thank the Macaulay Library at the Cornell Lab of Ornithology for use of audio recordings. The authors would like to thank each recordist for providing the time and effort required to assemble a library sufficiently detailed and voluminous to allow machine learning and principal component analysis on thousands of bird species (including red crossbills). We also acknowledge pioneers in the field of call type research—Jeff Groth, Tom Hahn, and Craig Benkman. W. Douglas Robinson and three reviewers provided comments that improved this paper.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1
American Ornithologists’ Union. (1931). Check-list of North American birds. 4th ed. (Lancaster, PA: The American Ornithologists’ Union).
2
American Ornithologists’ Union. (1957). Check-list of North American birds. 5th ed. (Ithaca, NY: American Ornithologists’ Union).
3
Avibase. (2024). The world bird database. Available online at: https://avibase.bsc-eoc.org (Accessed April 12, 2024).
4
BenkmanC. W. (1993). Adaption to single resources and the evolution of crossbill diversity. Ecol. Monogr.63, 305–325. doi: 10.2307/2937103
5
BenkmanC. W. (2020). “White-winged Crossbill (Loxia leucoptera), version 1.0,” in Birds of the World. Ed. BillermanS. M. (Cornell Lab of Ornithology, Ithaca, NY, USA). doi: 10.2173/bow.whwcro.01
6
BenkmanC. W.BrockC. D.ParchmanT. L.PorterC. K. (2022). Response to Hill and Powers: It is irrelevant that the mode and tempo of Cassia crossbill speciation is not typical for birds. J. Avian Biol.2022, e02967. doi: 10.1111/jav.v2022.i5
7
BenkmanC. W.SmithJ. W.KeenanP. C.ParchmanT. L.SantistebanL. (2009). A new species of the Red Crossbill (Fringillidae: Loxia) from Idaho. Condor111, 169–176. doi: 10.1525/cond.2009.080042
8
BenkmanC. W.YoungM. A. (2020). “Red Crossbill (Loxia curvirostra), version 1.0,” in Birds of the World. Eds. BillermanS. M.KeeneyB. K.RodewaldP. G.SchulenbergT. S. (Cornell Lab of Ornithology, Ithaca, NY, USA). doi: 10.2173/bow.redcro.01
9
BradyR. S.AnichN. M.YoungM. A. (2019). Wisconsin’s Red Crossbill Irruption of 2017–18: Distribution, abundance, and breeding behavior of multiple call types. Passenger Pigeon81, 215–240.
10
del HoyoJ. (2020). All the Birds of the World (Barcelona: Lynx Edicions), 967.
11
DickermanR. W. (1987). The “old northeastern” subspecies of Red Crossbill. Am. Birds41, 188–194.
12
eBird. (2022). 2022 eBird taxonomy update (Ithaca, NY: Cornell Lab of Ornithology). Available at: https://science.ebird.org/en/use-ebird-data/the-ebird-taxonomy/2022-ebird-taxonomy-update.
13
eBird. (2024). An online database of bird distribution and abundance (Ithaca, NY: Cornell Lab of Ornithology). Available at: www.ebird.org.
14
GhaniB.DentonT.KahlS.KlinckH. (2023). Global birdsong embeddings enable superior transfer learning for bioacoustic classification. Sci. Rep.13, 22876. doi: 10.1038/s41598-023-49989-z
15
GoffinetJ.BrudnerS.MooneyR.PearsonJ. (2021). Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires. eLife10, e67855. doi: 10.7554/eLife.67855.sa2
16
GriscomL. (1937). A monographic study of the red crossbill. Proc. Boston Soc. Natural History41, 77–209.
17
GrothJ. G. (1988). Resolution of cryptic species in Appalachian Red Crossbills. Condor90, 745–760. doi: 10.2307/1368832
18
GrothJ. G. (1993). Evolutionary differentiation in morphology, vocalizations, and allozymes among nomadic sibling species in the North American Red Crossbill (Loxia curvirostra) complex Vol. 127 (Berkeley: Univ of California Press).
19
IrwinK. (2010). A new and cryptic call type of the Red Crossbill. Western Birds41, 10–15.
20
KahlS.WoodC. M.EiblM.KlinckH. (2021). BirdNET: A deep learning solution for avian diversity monitoring. Ecol. Inf.61, 101236. doi: 10.1016/j.ecoinf.2021.101236
21
KahlS.WoodC. M.EiblM.KlinckH. (2024). BirdNet-analyzer. Available online at: https://github.com/kahst/BirdNET-Analyzer (Accessed April 12, 2024).
22
KathH.SerafiniP. P.CamposI. B.GouvêaT. S.SonntagD. (2024). Leveraging transfer learning and active learning for data annotation in passive acoustic monitoring of wildlife. Ecol. Inf. 82, 102710. doi: 10.1016/j.ecoinf.2024.102710
23
LovettE. L. (2016). Population genetic structure and parasite communities in a nomadic songbird, the Red Crossbill (Loxia curvirostra). University of Western Ontario, London, ON.
24
Macaulay Library. (2024). Cornell lab of ornithology (Ithaca, NY). Available at: www.macaulaylibrary.org.
25
MartinR.RochefortJ.MundryR.SegelbacherG. (2019). Delimitation of call types of Red Crossbill (Loxia curvirostra) in the Western Palearctic. Ecoscience26, 177–194. doi: 10.1080/11956860.2018.1564483
26
ParchmanT. L.BenkmanC. W. (2002). Diversifying coevolution between crossbills and black spruce on Newfoundland. Evolution56, 1663–1672. doi: 10.1111/j.0014-3820.2002.tb01478.x
27
PedregosaF.VaroquauxG.GramfortA.MichelV.ThirionB.GriselO.et al. (2011). Scikit-learn: machine learning in python. J. Mach. Learn. Res.12, 2825–2830.
28
PieplowN. (2017). Peterson Field Guide to Bird Sounds of Eastern North America.Boston: Houghton Mifflin Harcourt.
29
RidgwayR. (1885). Some emended names of North American birds. Proc. United States Natl. Museum. 8, 354–356. doi: 10.5479/si.00963801.524.354
30
RussellE. W. B.DavisR. B.AndersonR. S.RhodesT. E.AndersonD. S. (1993). Recent centuries of vegetational change in the glaciated north-eastern United States. J. Ecol.81, 647–664. doi: 10.2307/2261663
31
SainburgT.TheilmanB.ThielkM.GentnerT. Q. (2019). Parallels in the sequential organization of birdsong and human speech. Nat. Commun.10, 3636. doi: 10.1038/s41467-019-11605-y
32
SmithJ. W.BenkmanC. W. (2007). A coevolutionary arms race causes ecological speciation in crossbills. Am. Nat.169, 455–465. doi: 10.1086/511961
33
SnowbergL. K.BenkmanC. W. (2007). The role of marker traits in the assortative mating within red crossbills, Loxia curvirostra complex. J. Evolutionary Biol.20, 1924–1932. doi: 10.1111/j.1420-9101.2007.01372.x
34
StowellD. (2022). Computational bioacoustics with deep learning: a review and roadmap. PeerJ10, e13152. doi: 10.7717/peerj.13152
35
WilliamsB.van MerriënboerB.DumoulinV.HamerJ.TriantafillouE.FleishmanA. B.et al. (2024). Leveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics. arXiv preprint arXiv:2404.16436.
36
YangJ.CarstensB. C.ProvostK. L. (2024). Machine learning reveals that climate, geography, and cultural drift all predict bird song variation in coastal Zonotrichia leucophrys. Ornithology141, ukad062. doi: 10.1093/ornithology/ukad062
37
YoungM. (2011). Red Crossbill (Loxia curvisrotra) call-types of New York: their taxonomy, flight call vocalizations, and ecology. Kingbird61, 106–123.
38
YoungM.SpahrT. (2017). Crossbills of North America: Species and Red Crossbill call types. Available online at: https://ebird.org/news/crossbills-of-north-america-species-and-red-crossbill-call-types/ (Accessed April 12, 2024).
Summary
Keywords
crossbill, finch, machine learning, cryptic species, conifer, red crossbill, Loxia curvirostra
Citation
Young MA, Spahr TB, McEnaney K, Rhinehart T, Kahl S, Anich NM, Brady R, Yeany D and Mandelbaum R (2024) Detection and identification of a cryptic red crossbill call type in northeastern North America. Front. Bird Sci. 3:1363995. doi: 10.3389/fbirs.2024.1363995
Received
31 December 2023
Accepted
26 August 2024
Published
06 November 2024
Volume
3 - 2024
Edited by
Scott Rush, Mississippi State University, United States
Reviewed by
Melissa Lin Grunst, Université de la Rochelle, France
Yoni Vortman, Tel-Hai College, Israel
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Copyright
© 2024 Young, Spahr, McEnaney, Rhinehart, Kahl, Anich, Brady, Yeany and Mandelbaum.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Timothy B. Spahr, tspahr44@gmail.com
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.