Red Knot (Calidris canutus) Research—Preliminary Results 

and Future Opportunities

Open-File Report 2020–1050

U.S. Department of the Interior

U.S. Geological Survey

Red Knot (Calidris canutus) Research—

Preliminary Results and Future 

Opportunities

By David Kazyak, Aaron Aunins, and Robin Johnson

Open-File Report 2020–1050

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Kazyak, D., Aunins, A., and Johnson, R., 2020, Red Knot (Calidris canutus) research—Preliminary results and future 

opportunities: U.S. Geological Survey Open-File Report 2020–1050, 6 p., https://doi.org/10.3133/ofr20201050.

ISSN 2331-1258 (online)
iii

Acknowledgments

Dr. Tim King (Leetown Science Center King Conservation Genetics Laboratory) initiated this 

study, but unfortunately passed away prior to its completion. This report represents an effort 

to publicly release key findings from his work. We thank the U.S. Fish and Wildlife Service for 

providing funding to support this research, and two anonymous reviewers for providing helpful 

feedback.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Project Background.......................................................................................................................................1

Methods...........................................................................................................................................................1

Preliminary Results........................................................................................................................................2

Ideas for Additional Red Knot Genetic Research .....................................................................................3

Summary..........................................................................................................................................................5

References Cited............................................................................................................................................6

Figures

1. Graph showing principal coordinates analysis plot of microsatellite genotypes

at 24 loci of C.c. roselaari and C.c. rufa collections from Massachusetts,

Virginia, Alaska, and Quebec ......................................................................................................3

2. Graph showing Bayesian clustering results from the program STRUCTURE

based on two assumed clusters ................................................................................................4

Table

1. Samples of 13 C.c. islandica, 508 C.c. rufa, and 37 C.c. roselaari received by the

Leetown Science Center King Conservation Genetics Laboratory between 2009

and 2016 for genetic analyses ....................................................................................................2

Abbreviations

AFLP amplified fragment length polymorphism

DNA deoxyribonucleic acid

ETOH ethanol

GBS genotyping by sequencing

km kilometer

LSC-KCGL Leetown Science Center King Conservation Genetics Laboratory

mtDNA mitochondrial DNA

PCR polymerase chain reaction

RAD-Seq restriction site associated sequencing

RNA ribonucleic acid

USFWS U.S. Fish and Wildlife Service

USGS U.S. Geological Survey

Red Knot (Calidris canutus) Research—Preliminary 

Results and Future Opportunities

By David Kazyak, Aaron Aunins, and Robin Johnson

Abstract

The Red Knot, Calidris canutus, is a highly migratory 

shorebird with a cosmopolitan distribution. Six subspecies 

have been identified, two of which occur regularly in North 

America (C.c. rufa and C.c. roselaari). Given their longdistance migrations through many jurisdictions and conservation status, tools are needed to reliably distinguish the subspecies when captured away from their breeding areas and to 

examine potential population substructure within each taxa. 

We used a suite of molecular approaches to develop tools to 

support Red Knot research and management. Although our 

microsatellite markers were not able to reliably distinguish 

C.c. rufa and C.c. roselaari, we did find evidence of population substructure within C.c. rufa. 

Project Background

The Red Knot, Calidris canutus, is a highly migratory 

shorebird with a cosmopolitan distribution. Six subspecies 

have been identified, two of which occur regularly in North 

America (C.c. rufa and C.c. roselaari). The annual migrations 

of this species may exceed 30,000 kilometers (U.S. Fish and 

Wildlife Service, 2014). Along their migration routes, these 

birds pass through many jurisdictions and face a complex suite 

of threats, including environmental change and reduction of 

food resources at key stopover sites (Morrison and others, 

2004; Atkinson and others, 2007). Consequently, the Red Knot 

has become the focus of considerable conservation efforts 

and the C.c. rufa subspecies was listed as threatened by the 

U.S. Fish and Wildlife Service (USFWS). However, tools are 

needed to reliably distinguish the subspecies when captured 

away from their breeding areas, and to examine possible population structure within each taxa. 

In response to these research and management needs, 

U.S. Geological Survey (USGS) initiated a study with USFWS 

in 2009 to develop molecular tools to support Red Knot conservation. This report is intended to summarize the preliminary findings from that study and identify potential directions 

for continued research.

Methods

Between 2009 and 2016, the USGS Leetown Science 

Center King Conservation Genetics Laboratory (LSCKCGL) received Red Knot samples from USFWS, including 

14 Calidris canutus islandica, 452 Calidris canutus rufa, and 

37 Calidris canutus roselaari samples (hereafter referred to as 

C.c. islandica, C.c. rufa, and C.c. roselaari, respectively) for 

genetic analyses from various U.S. and international partners (table 1). Blood or buccal swab samples were preserved 

in RNAlater (Ambion, Austin, Tex.) or on Whatman FTA 

cards (GE Healthcare, Buckinghamshire, United Kingdom). 

Additional samples were received in the form of extracted 

deoxyribonucleic acid (DNA). Several high throughput shotgun genomic sequencing runs (using multiple instruments, 

including Illumina GAIIX, Ion Torrent PGM, Ion Proton, and 

Roche 454 Jr.) of a few individuals of each subspecies were 

performed to obtain sequence data for microsatellite marker 

development.

Twenty-four microsatellite loci were optimized for 

population genetic analyses from C.c. rufa sequencing data. 

Genotypes were determined for 72 C.c. rufa and 20 C.c. roselaari samples at these 24 newly developed microsatellite loci 

for preliminary population genetic analyses (table 1). We 

used principal coordinates analysis and a Bayesian clustering 

program (STRUCTURE; Pritchard and others, 2000) to assess 

the ability of the microsatellite markers to distinguish between 

C.c. rufa and C.c. roselaari, and to examine potential substructure within C.c. rufa. For all STRUCTURE runs, we used 

a burn-in period of 200,000 steps followed by 200,000 iterations for data collection, and admixture was allowed but capture location was not considered as a prior. Structure Harvester 

(Earl and vonHoldt, 2012) was used to evaluate model results 

across k values using likelihoods and Evanno’s Δk methods 

(Evanno and others, 2005).
2 Red Knot (Calidris canutus) Research—Preliminary Results and Future Opportunities

Table 1. Samples of 13 C.c. islandica, 508 C.c. rufa, and 37 C.c. roselaari received by the Leetown Science Center King Conservation 

Genetics Laboratory between 2009 and 2016 for genetic analyses. The Number genotyped column indicates what samples were 

genotyped at 24 microsatellite loci developed in this study.

[DNA, deoxyribonucleic acid; ETOH, ethanol; Va., Virginia; Mass., Massachusetts; --, not applicable] 

Date received Location sampled Sample type Quantity Subspecies Number genotyped

3/26/2009 Europe Blood in RNAlater1 5 C.c islandica --

5/28/2009 Delaware Blood on FTA card1 4 C.c rufa --

5/28/2009 Delaware Buccal swab in RNAlater 20 C.c rufa --

5/28/2009 New Jersey Blood on FTA card 5 C.c rufa --

5/28/2009 New Jersey Buccal swab in RNAlater 19 C.c rufa --

6/4/2009 Hog Island, Va. Blood on FTA card 2 C.c rufa --

6/2/2010 Florida DNA 3 C.c rufa --

6/2/2010 Argentina DNA 3 C.c rufa --

6/2/2010 Brazil DNA 2 C.c rufa --

6/2/2010 Netherlands DNA 8 C.c islandica --

6/2/2010 Mexico DNA 8 C.c roselaari --

4/29/2011 Alaska Blood on FTA card 29 C.c roselaari 20

1/8/2013 New Jersey Blood on FTA card 67 C.c rufa --

2008–2014 Quebec Blood on FTA card and blood in ETOH 307 C.c rufa 362

6/6/2014 Hog Island, Va. Blood on FTA card 16 C.c rufa 16

12/9/2014 Cape Cod, Mass. Blood on FTA card 20 C.c rufa 20

1/25/2016 Cape Cod, Mass. Blood on FTA card 41 C.c rufa --

1RNAlater and FTA cards are proprietary products.

2There were 32 samples genotyped from 2010 and 4 samples genotyped from 2013. Samples from the other years were not genotyped.

Preliminary Results

Although the number of individuals and collections genotyped so far is a small proportion of the total received, we can 

begin to assess the level of genetic differentiation uncovered 

by these microsatellite loci between C.c. rufa and C.c. roselaari. A principal coordinates plot of the genotyped samples 

indicates some separation of the Alaska C.c. roselaari and 

Quebec C.c. rufa samples, but there is still substantial overlap 

between the two collections, which suggests that the markers 

we developed cannot be used to reliably distinguish C.c. rufa

from C.c. roselaari with a high level of confidence (fig. 1).

Our microsatellite markers support the presence of at 

least two populations of C.c. rufa with different migratory 

behaviors (route and [or] phenology). Bayesian clustering 

analysis using the program STRUCTURE indicated that collections from Massachusetts and Virginia represent a different 

population than collections from the Mingan Archipelago in 

Quebec (fig. 2). Although Red Knots routinely migrate long 

distances, it appears that there are mechanisms that limit gene 

flow among populations on the breeding grounds, such as 

geographic isolation or positive assortative mating.

Since the LSC-KCGL study was initiated in 2009, other 

unpublished genetic results have been presented by various 

groups investigating population structure within Red Knots. 

This information was provided by Anne Hecht, U.S. Fish and 

Wildlife Service (USFWS), and provides important context 

for our results. Verkuil and others presented results at the 

Western Hemisphere Shorebird Group meeting in Peru in 

November 2017, which indicated that they have developed 

genetic markers that can separate all six subspecies of Red 

Knots worldwide and have identified Alaskan and Wrangel 

Island breeding populations of C.c. roselaari as genetically 

distinguishable (G. Morrison, Environment and Climate 

Change Canada, written commun., April 2018; Verkuil and 

others presentation is summarized in Tavera and López 

[2018]). In addition, unpublished work by Baker and others 

suggests that a panel of 410 amplified fragment length 

polymorphism (AFLP) loci can unambiguously identify 

C.c. rufa from Tierra del Fuego (Argentina/Chile), Maranhao 

(Brazil), and Florida (Allan Baker, Royal Ontario Museum, 

written commun., January 29, 2013). Clearly, multiple 

research groups continue to pursue genetic investigations 

of C.c. rufa and C.c. roselaari, but there is no apparent 

coordinated collaboration among laboratories to avoid 

duplication of effort or share results.
Ideas for Additional Red Knot Genetic Research 3

Coordinate 2

Coordinate 1

EXPLANATION

C. c. rufa-MA

C. c. rufa-VA

C. c. rufa-QC

C. c. roselaari-AK

Figure 1. Principal coordinates analysis (PCoA) plot of microsatellite genotypes at 24 loci of 

C.c. roselaari and C.c. rufa collections from Massachusetts (MA), Virginia (VA), Alaska (AK), and Quebec 

(QC) (see table 1).

Ideas for Additional Red Knot Genetic 

Research

When the USFWS funded the original genetic study 

at LSC-KCGL in 2009, the agency was interested in three 

primary objectives, which remain relevant today. Although 

conference proceedings and unpublished reports suggest there 

have been significant advancements towards meeting these 

objectives, these results remain unpublished to date. Here, 

we discuss each objective individually and offer research 

recommendations.

1. Determine if there are genetic differences that can 

be used to reliably distinguish among the C.c. rufa, 

C.c. roselaari, and C.c. islandica subspecies.

Verkuil and colleagues have apparently developed molecular markers that can separate C.c. rufa and C.c. roselaari (a 

presentation by Verkuil and others is summarized in Tavera 

and López [2018]), whereas our preliminary microsatellite 

analyses show limited resolution for unambiguous differentiation between collections of C.c. rufa and C.c. roselaari from 

Quebec and Alaska, respectively (fig. 1). As the results from 

Verkuil and others are unpublished, it is currently unknown 

what molecular markers they are using, and their results cannot readily be tested or confirmed.

Additional data from more nuclear and mitochondrial 

markers would help assess the level of genetic divergence 

between C.c. rufa and C.c. roselaari. We have mitochondrial 

deoxyribonucleic acid (mtDNA) sequence data from each 

of these subspecies yet to be analyzed, but only for a limited 

number of individuals. New genomic techniques such as 

reduced representation sequencing (for example, genotyping 

by sequencing [GBS] or restriction site associated sequencing 

[RAD-Seq]) have become commonly used molecular tools in 

the last few years and enable the genotyping of thousands of 

single nucleotide polymorphisms from throughout the entire 

genome for multiple individuals. This approach has been used 

successfully to delineate subspecies in many taxa and would 

be applicable to addressing the subspecific status of C.c. rufa

and C.c. roselaari (Dierickx and others, 2015; Harvey and 

Brumfield, 2015; Lim and others, 2017). If the DNA of existing samples is of sufficient quantity and quality, GBS libraries of C.c. rufa and C.c. roselaari could be developed from 

the current Alaska and Quebec collections to complement 

the existing microsatellite dataset. This type of genome-wide 

approach should have the highest resolution among contemporary genomic methods (besides complete genome sequencing) 

to determine the extent of differentiation between C.c. rufa

and C.c. roselaari.
1.00 0.80 0.60 0.40 0.20 0.00 2 Virginia May 2014 3 Quebec December 2010 

1 Massachusetts September 2014 Q Score Figure 2. Bayesian clustering results from the program STRUCTURE based on two assumed clusters (k=2). Model runs used 200,000 burn-in iteratio

repetitions, allowed for admixture, and did not incorporate collection location as prior information. Structure Harvester (Earl and vonHoldt, 2012) suplikelihoods and Evanno’s Δk methods (Evanno and others, 2005). The colors reflect the admixture proportions for each individual to the two inferred c
Summary 5

2. Characterize the nonbreeding distributions of the 

C.c. rufa and C.c. roselaari subspecies.

The sample sizes that were available for C.c. rufa and 

C.c. roselaari at wintering areas were exceedingly small 

(table 1), and more samples would be needed for additional 

analyses. Microsatellite-based analyses generally benefit from 

sample sizes of at least 20–30 per population so that allele 

frequency distributions can be accurately characterized.

Baker and colleagues compared the ability of a panel of 

10 microsatellites and ~400 AFLP loci to differentiate nonbreeding C.c. rufa from Tierra del Fuego (Argentina/Chile), 

Maranhao (Brazil), and Florida (Allan Baker, Royal Ontario 

Museum, written commun., January 29, 2013). Although 

the microsatellite analyses did allow some individuals to 

be assigned to their collection of origin, the assignments 

based on the ~400 AFLP loci were completely unambiguous. 

Although AFLP and GBS sample loci from throughout the 

genome, GBS has many advantages over AFLP: GBS can 

score many more loci reliably than AFLP, the loci are easily 

scored as codominant in GBS, and GBS costs substantially 

less per sample.

We do not currently possess enough samples of C.c. rufa

or C.c. roselaari from the wintering grounds to effectively 

analyze with microsatellites, GBS, or any other technique. 

Given the results of Baker and others (Allan Baker, Royal 

Ontario Museum, written commun., January 29, 2013), a 

genomic approach like GBS may have more resolving power 

to assess differences among collections if samples become 

available.

3. Determine if C.c. rufa Red Knots from different wintering regions segregate on the breeding grounds (in other 

words, determine whether there are identifiable genetic 

differences among C.c. rufa Red Knots using four different wintering areas: Argentina/Chile, Brazil, southeastern United States/Caribbean, northwest Gulf of Mexico).

Unpublished work by Baker and others found genetic differentiation among Red Knots from different wintering locations (Allan Baker, Royal Ontario Museum, written commun., 

January 29, 2013). This indicates that there is population structure (in other words, multiple populations) within C.c. rufa, 

with these populations wintering in different areas (or at least 

occurring in different proportions at different wintering areas). 

We used our microsatellite markers to examine population structure among C.c. rufa stopover locations and found 

clear genetic differences among collections in Virginia and 

Massachusetts in comparison to collections from the Mingan 

Archipelago (Quebec). To maintain the observed population 

structure, birds from different populations would either need to 

be spatially isolated in breeding areas or exhibit some form of 

assortative mating. Given the difficulty of obtaining samples 

from the breeding grounds, this type of analysis might best be 

conducted using a combination of genetics and telemetry.

Currently, we have genotyped a relatively modest number 

of individuals from three stopover areas. Moving forward, 

microsatellite markers could be applied to a larger number 

of individuals from more stopover/overwinter locations to 

attempt to understand when and where each C.c. rufa population occurs, and their relative abundance at different locations. 

If historical samples were available, those samples could be 

run to see if the relative abundance or migratory corridors of 

the populations have changed through time.

Summary

Overall, additional genetic work is needed to address the 

research needs of the U.S. Fish and Wildlife Service regarding 

C.c. rufa and C.c. roselaari. The following opportunities may 

warrant consideration:

1. Additional microsatellite genotyping of existing 

C.c. rufa and C.c. roselaari samples, such as the 

411 specimens currently at the USGS LSC-KCGL 

(table 1). Additional samples from the breeding sites or 

overwintering sites may improve our understanding of 

population structure within C.c. rufa and C.c. roselaari. 

In particular, the migratory pattern and relative abundance of each C.c. rufa population could be inferred if 

enough samples were available.

2. Genotyping by sequencing (GBS) of C.c. rufa and 

C.c. roselaari samples could be used to better understand 

genetic differentiation between C.c. rufa and C.c. roselaari, as well as population-level structure within each 

subspecies. Additional samples from the breeding sites 

or terminal overwintering sites would be provide additional insight if included in a GBS analysis.

To avoid redundant efforts, it would be beneficial to have 

a discussion among the broader Red Knot genetics research 

community to update the unpublished results noted and identify the most effective approaches before initiating any new 

genetic studies.
6 Red Knot (Calidris canutus) Research—Preliminary Results and Future Opportunities

References Cited

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Clark, J.A., Cole, K.B., Dekinga, A., Dey, A., Gillings, S., 

Gonzalez, P.M., Kalasz, K., Minton, C.D.T., Newton, J., 

Niles, L.J., Piersma, T., Robinson, R.A., and Sitters, H.P., 

2007, Rates of mass gain and energy deposition in red knot 

on their final spring staging site is both time- and conditiondependent: Journal of Applied Ecology, v. 44, no. 4, 

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10.1111/j.1365-2664.2007.01308.x.

Dierickx, E.G., Shultz, A.J., Sato, F., Hiraoka, T., and 

Edwards, S.V., 2015, Morphological and genomic comparisons of Hawaiian and Japanese Black-footed Albatrosses 

(Phoebastria nigripes) using double digest RADseq—

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v. 8, no. 7, p. 662–678, accessed September 2018 at 

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Earl, D.A., and vonHoldt, B.M., 2012, STRUCTURE 

HARVESTER—A website and program for visualizing STRUCTURE output and implementing the Evanno 

method: Conservation Genetics Resources, v. 4, no. 2, 

p. 359–361, accessed September 2018 at https://doi.org/

10.1007/s12686-011-9548-7.

Evanno, G., Regnaut, S., and Goudet, J., 2005, Detecting 

the number of clusters of individuals using the software 

STRUCTURE—A simulation study: Molecular Ecology, 

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Rahman, M.A., 2017, Sundaland’s east-west rain forest population structure—Variable manifestations in four 

polytypic bird species examined using RAD-Seq and 

plumage analysis: Journal of Biogeography, v. 44, no. 10, 

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Morrison, R.I.G., Ross, R.K., and Niles, L.J., 2004, Declines 

in wintering populations of red knots in southern South 

America: The Condor, v. 106, no. 1, p. 60–70, accessed 

September 2018 at https://doi.org/10.1093/condor/106.1.60.

Pritchard, J.K., Stephens, M., and Donnelly, P., 2000, 

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April 2020 at https://www.genetics.org/content/155/2/945.

Tavera, E.A., and López, E.O., 2018, Seventh meeting of the Western Hemisphere Shorebird Group, 

10–14 November 2017, Paracas, Peru: Wader Study, 

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https://www.waderstudygroup.org/article/10720/.

U.S. Fish and Wildlife Service, 2014, Rufa Red Knot background information and threats assessment—Supplement 

to endangered and threatened wildlife and plants; final 

threatened status for the Rufa Red Knot (Calidris canutus 

rufa): U.S. Fish and Wildlife Service web page, 383 p., 

accessed April 2020 at https://fws.gov/northeast/red-knot/

pdf/20141125_REKN_FL_supplemental_doc_FINAL.pdf.
For more information, contact:

Director, Leetown Science Center

U.S. Geological Survey

11649 Leetown Road

Kearneysville, WV 25430

Publishing support provided by the 

West Trenton and Pembroke Publishing Service Centers
Kazyak and others—Red Knot (Calidris canutus) Research—Preliminary Results and Future Opportunities—OFR 2020–1050

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201050