The Common Nighthawk in Northern Minnesota a THESIS SUBMITTED to the FACULTY of the GRADUATE SCHOOL of the UNIVERSITY of MINNE

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The Common Nighthawk in northern Minnesota

A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY

Stephen Robert Kolbe

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

Dr. Gerald Niemi and Dr. Matthew Etterson

May 2018

Acknowledgments

I wish to thank the members of committee, Dr. Matthew Etterson, Dr. Gerald Niemi, and

Dr. Richard Green for advice and guidance from beginning to end of this project. I especially appreciate their patience during my “silent period” as I readjusted to academic life after five years in the field. I would also like to thank those who helped with surveys either on the breeding grounds or during migration: Karl Bardon, Josh Bednar, Annie

Bracey, Jessica Chatterton, Allison Coffman, Lizzie Condon, Paul Dolan, Laura

Erickson, Tom Erickson, Lance Gauer, Jan Green, John Green, Alexis Grinde, Ted

Keyel, Alex Lamoreaux, Carly Lapin, Julia Luger, Hannah Panci, Cameron Rutt, Sara

Schutte, Ryan Steiner, Nick Walton, and Ed Zlonis. Larry Snyder was instrumental in providing access to the count location – thank you. I thank the Integrated Biosciences graduate program at the University of Minnesota Duluth and the Biology Department for financial support by way of teaching assistantships and the Natural Resources Research

Institute for a research assistantship. Thanks to JG Bennett, Skye Haas, Kate Maley,

Stephen Nelson, John Richardson, Tom Reed, and Ryan Steiner. Finally, thank you to my family, especially Richard and Lois Kolbe, for their unwavering support and love.

Dedication

To the visible migration true believers.

Abstract

Developing methods for monitoring bird species that do not exhibit typical breeding behaviors is difficult. Species that do not sing, are sparsely distributed, are not active in the early morning, or are secretive are often impossible to monitor using traditional methods such as point counts. The Common Nighthawk (Chordeiles minor), like other species in the nightjar family, is a low-density breeder in the boreal forest and is not adequately surveyed by point counts due to its secretive nature and crepuscular activity. Specific surveys have been developed for nightjars, but never tested for utility with the Common Nighthawk. I compared nightjar survey routes censused during a crepuscular time period to those run during a nocturnal time period. Significantly more nighthawks were detected during the crepuscular window, a time period that is not used during the official survey. While the effect of time of survey was significant, the surveys were labor- intensive and relatively few observations of Common Nighthawks were made. However, large numbers of this species occur each autumn along the north shore of Lake Superior. With average annual counts of nearly 19,500 individuals, the autumn migration of Common Nighthawks is the largest known concentration of this species in the world. Visible migration counts of nighthawks were conducted for three weeks each year from 2008 to 2017 in Duluth, Minnesota, USA. This daily evening count has elucidated the weather variables that most often lead to large flights: lighter and westerly winds, and warmer temperatures. Many of these conditions are not often associated with autumn migration. These weather effects on nighthawk migration intensity may be tied to aerial insect availability during migration. While the precise geographic origin of these migrant birds is unknown, many arrive from the Canadian boreal forest, where this species has undergone a significant decline and is listed as threatened. Trend analysis from autumn migration counts does not show such a decline. Counts such as the annual autumn survey of migrating Common Nighthawks along the north shore of Lake Superior are likely the best and most cost-effective way to census the boreal forest breeding Common Nighthawks and determine population trends for this declining aerial insectivore.

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Table of Contents

Acknowledgements...... i

Dedication...... ii

Abstract...... iii

List of Tables...... v

List of Figures...... vi

List of Appendices...... vii

CHAPTER 1: TESTING BREEDING GROUND COMMON NIGHTHAWK

(CHORDEILES MINOR) SURVEY METHODOLOGY

Introduction...... 1

Methods...... 4

Results...... 7

Discussion...... 9

CHAPTER 2: VISIBLE MIGRATION COUNTS OF COMMON NIGHTHAWKS

(CHORDEILES MINOR) ALONG THE NORTH SHORE OF LAKE SUPERIOR

Introduction...... 12

Methods...... 15

Results...... 21

Discussion...... 34

Literature Cited...... 39

Appendices...... 43

List of Tables

Chapter 1

Table 1. Common Nighthawks detected along Nightjar Survey Network routes...... 8

Chapter 2

Table 1. Summary statistics of count data and weather variables...... 23-24

Table 2. Logistic regression model selection table...... 25

Table 3. Negative binomial model selection table...... 26

Table 4. Linear regression model selection table...... 27

Table 5. Top model coefficients...... 28

List of Figures

Chapter 1

Figure 1. Nightjar Survey Network route locations in northern Minnesota, USA...... 5

Chapter 2

Figure 1. Location of the count site...... 16

Figure 2. Daily distribution of Common Nighthawk counts...... 29

Figure 3. Predicted probability plots...... 30

Figure 4. Effect of wind direction on Common Nighthawk flights...... 31

Figure 5. Geometric mean trend 2008 to 2017...... 32

Figure 6. Date and weather adjusted geometric mean trend 2008 to 2017...... 33

List of Appendices

Appendix 1: Instructions for conducting the Nightjar Survey Network...... 43

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CHAPTER 1.

TESTING BREEDING GROUND COMMON NIGHTHAWK

(CHORDEILES MINOR) SURVEY METHODOLOGIES

INTRODUCTION

Collecting reliable data that can be used for developing population trends is a considerable challenge in ornithology (Rosenstock et al. 2002). Survey design and methodology have a large effect on bird detection, and improper methods can result in biased or inaccurate results that, in turn, cascade into implementation of poor management or conservation decisions (Romesburg 1981, Rosenstock et al. 2002). Time of survey is one of the most important methodological considerations because avian activity varies daily and seasonally (Ralph et al. 1995). Fortunately, many species are properly surveyed by “catch-all” methods such as the North American Breeding Bird

Survey (BBS), a survey that is conducted during early morning hours near the peak of the breeding season (Sauer et al. 2013). The BBS efficiently detects and monitors species that are visually or aurally conspicuous during this time period, but other methods are needed to survey for species that cannot be readily detected in this way (Dunn et al.

2005). A central tenet of the BBS is obtaining a large sample size (the number of routes with a given species present over multiple years) with a relatively small amount of effort

(Bart et al. 2004). This strategy is effective in areas where relative abundances for a given species are high, but can be challenging in regions where birds are rarely encountered.

Traditional population monitoring methods such as the BBS are often insufficient for monitoring species that are secretive (i.e. difficult to detect), occur at low densities, do not follow traditional paradigms of territorial singing in the early morning hours, and/or

1 have inaccessible breeding grounds (Dunn and Hussell 1995). BBS-based assessments are especially weak for populations that escape detection by both the BBS and Christmas

Bird Count (CBC) by breeding in the boreal forest and wintering in the Neotropics (Dunn et al. 2005, Sauer et al. 2017). It is essential to optimize survey methodologies for poorly- monitored species because conservation planning relies heavily on count data

(Rosenstock et al. 2002).

Multiple sources suggest an overall decline in Common Nighthawks (Chordeiles minor) throughout much of their North American breeding range (Brigham et al. 2011,

Sauer et al. 2013). From 1966 to 2015, BBS data show a 1.93% annual decline in North

American Common Nighthawk populations (Sauer et al. 2017). A 1.82% annual decline has been documented in the United States during this time period, along with a 3.41% decline in Canada (Sauer et al. 2017). All of these values were significant declines. Based on this alarming trend, the Common Nighthawk was listed as threatened in Canada in

2007 (COSEWIC 2007). Common Nighthawks are a member of the aerial insectivore guild that is exhibiting range-wide declines, with especially sharp declines in northeastern

North America (Nebel et al. 2010).

Confidence in BBS-produced population trends for Common Nighthawk is low because most surveys of breeding birds do not sample nighthawks and other nightjars

(family Caprimulgidae) at the appropriate times (Dunn et al. 2005). While BBS trends may show accurate population declines, the reliability of these trends is diminished due to low sample sizes, low precision, and low relative abundance, especially in the boreal forest (Dunn et al. 2005). Nevertheless, the BBS is the only source of long-term monitoring data for Common Nighthawks (Sauer et al. 2013). It is essential to remedy

2 this situation and develop a targeted long-term monitoring method to track population trends in the Common Nighthawk, especially in the poorly-surveyed northern portion of the range of this species, an area in which it may be undergoing the steepest declines

(Brigham et al. 2011).

To address some of the shortcomings with BBS and other typical point count data for nightjar population estimates and trends, a nationwide program called the Nightjar

Survey Network (NSN) was established in 2007 to collect baseline data specifically targeting nightjars (Wilson 2008). This survey was designed to maximize detections of

Eastern Whip-poor-wills (Caprimulgus vociferus), but it is uncertain whether the method is useful for Common Nighthawks (Wilson 2008). Surveys begin at least 30 minutes after sunset and end at least 15 minutes before sunrise. While the NSN protocol may be better suited to detect Common Nighthawks than the BBS, it may be failing to obtain the highest possible detection rates due to the natural history of this species.

Common Nighthawks are crepuscular and frequently forage for extended periods of time by hawking insects in flight, while Eastern Whip-poor-wills are nocturnal and typically forage from a low stationary perch, briefly sallying out to catch passing insects

(Brigham et al. 2011, Cink et al. 2017). These differences in foraging strategy and behavior influence an observer’s ability to detect these species during a survey. Common

Nighthawks are easily detected visually during their foraging flights whereas most other nightjars are rarely seen. Even a survey designed specifically for nightjars such as the

NSN may not be appropriate for sampling all members of the Caprimulgid family. The

NSN method may be inadequate for surveying Common Nighthawks because of this species’ crepuscular activity and the survey’s lack of opportunities for visual detection.

Because the BBS and NSN surveys used to determine the population status of Common

Nighthawk are likely unable to sample this species properly, the utility of these data is limited.

The objective of this study was to determine whether NSN surveys adequately survey Common Nighthawks. I developed an alternative crepuscular survey methodology using the same survey route to specifically target Common Nighthawks. I hypothesized that nocturnal surveys will inadequately detect nighthawks because of their crepuscular habits. Furthermore, the NSN survey is under-sampling Common Nighthawks because it does not take into account the differential foraging strategy and diel activity of this species. I predicted that surveys conducted during the crepuscular window of activity would detect more Common Nighthawks than those conducted during the nocturnal period.

METHODS

Study area

Nightjar surveys were conducted on secondary roads located in the Superior

(approximately 47.62 N, 91.35 W) and Chippewa (approximately 47.35 N, 94.22 W)

National Forests in the boreal hardwood transition bird conservation region of northern

Minnesota (U.S. Fish and Wildlife Service 1999). Routes were determined by the NSN and were placed on existing BBS routes (Figure 1). Common Nighthawks are not abundant breeders in this region, but can be observed foraging over bodies of water in the evening (S.K. personal observation).

Nightjar surveys

Nightjar Survey Network routes were surveyed twice during each visit: once during a crepuscular window (hereafter the crepuscular survey) and once during a nocturnal window (hereafter the nocturnal survey). Both surveys were conducted throughout June and each lasted approximately 90 minutes. Following NSN protocol

(Appendix 1), nocturnal surveys began at least 30 minutes after sunset and ended no later than 15 minutes before sunrise. Each survey required the moon to be above the horizon and not covered by clouds. Crepuscular surveys were initiated 60 minutes before sunset and concluded 30 minutes after sunset. In this way, the crepuscular survey and nocturnal survey could be run sequentially by a single observer.

Each route in this study consisted of ten survey points spaced one mile apart. Six minutes were spent at every survey point during which time all nightjars detected either visually or aurally from this stationary position were recorded. No playback, spotlighting, or any other means to attract or detect nightjars was utilized. The survey window at each point was partitioned into six one-minute segments. Detections of new and previously detected individuals were both recorded each minute. Every attempt was made to detect movement of individual birds during the survey to avoid double counting. Additionally, it was noted whether a bird detected was thought to be the same individual from a previous point. Standard meteorological and survey condition data were collected at each point regardless of visit protocol used. Surveys were not conducted in rain or strong wind.

Statistical analyses

I analyzed the influence of survey time (crepuscular versus nocturnal) on detection of Common Nighthawks. Comparisons between the crepuscular survey and the

6 nocturnal survey allowed examination of the influence of survey timing on detection of

Common Nighthawks. Wilcoxon signed-rank test was used to compare the incidence of detection between surveys. All statistical tests were performed in R (R Core Team 2013).

RESULTS

In June 2016 and June 2017, 18 nightjar routes were surveyed both during the crepuscular and nocturnal windows (Figure 1). Observers detected Common Nighthawks on six of the 18 routes (33%) in 2016 and 2017 (Table 1). However, nighthawks were only detected on 2.2% of all route stops. Eight total Common Nighthawks were counted during the surveys. Two Common Nighthawks were detected on two routes; the remaining four routes had single detections. Most of the routes on which nighthawks were detected were in the northeastern region of the state (Figure 1). All eight nighthawks were detected during the crepuscular survey and zero were detected during the nocturnal survey window. A Wilcoxon signed-rank test indicated a significant effect of time of survey (Z = -2.44, p = 0.03).

DISCUSSION

My results indicate that time of survey is critical when designing surveys specifically targeting Common Nighthawks, especially in regions where this species is uncommon such as the boreal forest. The crepuscular period is the optimal time to target

Common Nighthawks for the highest survey detection rates. My prediction was supported because nighthawks were only detected during the crepuscular surveys. Information about detection is essential to optimize survey methodology given limited resources and the importance of count data for conservation planning (Rosenstock et al. 2002).

Common Nighthawks rely on acute vision to forage for flying insects in the late evening and individuals are most active and vocal during the crepuscular period. The activity of

Common Nighthawks is constrained by the amount of ambient light as they do not utilize echolocation and are unable to see in complete darkness (Brigham et al. 2011). Neither

BBS routes nor NSN routes provide coverage during this time of day.

This study is one of the first to investigate timing of surveys aimed at detecting nightjars breeding in the boreal forest. More information about the threatened Canadian populations of Common Nighthawks is needed (Brigham et al. 2011), and this study presents useful findings about proper monitoring techniques in the region. It is necessary to increase the sample size and relative abundance measures for this species in the boreal forest (Dunn et al. 2005); increasing these metrics will provide more power and precision in analyzing population trends. This is especially essential for Common Nighthawks as this species is also inadequately surveyed by the CBC because it winters in South

America.

I suggest that observers conducting NSN routes run an antecedent route that specifically targets Common Nighthawks and other crepuscular nightjars, especially

Lesser Nighthawk (Chordeiles acutipennis). While this new method would double the amount of actual survey time required of volunteers, the number of visits to the survey location would not change. Especially in remote areas, the cost of conducting surveys lies in the logistics of reaching the survey location, not the survey itself. The amount of participation would be analogous to that of a volunteer-run BBS route, of which there are approximately 3,000 conducted each summer (Sauer et al. 2013).

I also suggest an expansion of the NSN in the boreal forest region. The boreal hardwood transition and the boreal forest host declining populations of Common

Nighthawks that are poorly surveyed and even more difficult to detect than in other regions due to the high percentage of survey locations situated in dense forest. It will require a concerted and substantial effort to survey Common Nighthawks properly in this region, but survey information is essential to understanding the decline of boreal forest breeding nighthawks.

In heavily forested areas like my study region, additional survey methods could be employed to increase Common Nighthawk detections. Conducting surveys in locations with views of the sky, especially near or over water, would greatly enhance nighthawk surveys, particularly if this species concentrates in these areas. Stationary surveys for Common Nighthawks over bodies of water (e.g. from boat launches or other public water access locations) during the short crepuscular activity window of this species would likely detect more nighthawks than roadside surveys through heavily forested areas. Telemetry data suggest that individuals in upland habitats will leave home

10 territories to forage over bodies of water (Brigham et al. 2011). Current methods for surveying Caprimulgids do not take advantage of the highly aerial and visible foraging strategy of Common Nighthawks.

Breeding surveys targeting aerial insectivores are limited or nonexistent, but the sharp decline within this guild points to the need for intensive and focused monitoring.

Aerial insectivores are likely environmental indicators whose declines may be used as an early warning about ecosystem health (Nebel et al. 2010, Smith et al. 2015). An integrated approach that combines BBS data, targeted surveys, migration surveys (e.g. visible migration counts; see Chapter 2), and wintering ground surveys will be the most useful and powerful tool for monitoring populations of aerial insectivores in the future.

CHAPTER 2.

VISIBLE MIGRATION COUNTS OF COMMON NIGHTHAWKS

(CHORDEILES MINOR) ALONG THE NORTH SHORE OF LAKE SUPERIOR

INTRODUCTION

Accurate estimates of long-term trends are important for providing assessments of population status, especially for species of conservation concern (Sauer et al. 2003).

Developing trends from traditional population monitoring methods such as breeding bird surveys is frequently challenging for species that are secretive (i.e. difficult to detect), occur in low densities, do not follow traditional paradigms of territorial singing in the early morning hours, and/or have inaccessible breeding grounds (Dunn and Hussell

1995). Assessments are especially weak for populations that escape detection during both the North American Breeding Bird Survey (BBS) and Christmas Bird Count (CBC) because they breed in remote boreal forest and winter in the Neotropics (Dunn et al.

2005, Sauer et al. 2017). In such cases, alternative methods have been used to detect population trends; visual counts of birds migrating between breeding and nonbreeding grounds are one such method.

Use of long-term visible migration counts for population monitoring in North

America has been largely limited to raptors and other taxa that utilize soaring flight (e.g.

Hoffman and Smith 2003, Farmer et al. 2007, Martín et al. 2016). Species or guilds that migrate diurnally and are poorly surveyed by traditional breeding bird surveys are candidates for monitoring via visible migration counts. While past population trends obtained from visible migration counts have generally corresponded with other population monitoring efforts, the utility and validity of migration count data has been a

12 source of contention (e.g. Kerlinger 1989). Migration counts have been criticized for reflecting variation caused by factors such as weather patterns that have little or no relation to underlying population levels and trends (Dunn and Hussell 1995). However, in recent years the use of migration counts has been more widely accepted as a way to either provide basic information or, at minimum, additional information for population trend development (Titus and Fuller 1990, Hoffman and Smith 2003).

Weather has large effects on bird migration, and the study of avian migration and weather conditions has been fruitful for decades (reviewed in Richardson 1978, 1990;

Liechti 2006, Newton 2007). The number of birds migrating on a given day is influenced by temperature, wind speed, wind direction, barometric pressure, humidity, precipitation, and thermal development, among other elements (Richardson 1990, Liechti 2006). It is difficult to assign causality because weather metrics are often strongly correlated

(Richardson 1990, Newton 2007). However, there is broad agreement that wind speed and direction, temperature, and precipitation are among the most important predictors of migratory activity. In autumn, birds are more likely to migrate during conditions with falling temperatures, light and/or tail winds, and no precipitation (Richardson 1990,

Liechti 2006). Weather conditions that affect the volume of diurnally migrating raptors and other soaring species have been well-studied, but those that affect other diurnally migrating groups are less well known, especially in North America. While some authors suggest it is not as important to account for weather in estimating trends as previously thought (Farmer et al. 2007), at least for novel taxa it is vital to understand weather influences on the migratory behavior of every species when using visible migration

13 counts to develop population trends (Hussell 1981, Richardson 1990, Shamoun-Baranes et al. 2010).

Common Nighthawks (Chordeiles minor) are declining throughout North

America (Brigham et al. 2011, Sauer et al. 2013). Nighthawks are aerial insectivores, a guild that may serve as biological indicators as they integrate ecosystem processes across large geographic regions (Nebel et al. 2010, Smith et al. 2015). Aerial insectivores are declining at a faster rate than other groups of birds in North America (Bohning-Gaese et al. 1993, Nebel et al. 2010, Smith et al. 2015). However, confidence in these BBS- derived population trends for Common Nighthawk is low because surveys of breeding birds do not sample nighthawks and other nightjars (Caprimulgidae) at the appropriate times (Dunn et al. 2005). Common Nighthawks breed in relatively low densities, are secretive and crepuscular, and are poorly surveyed by the BBS and CBC. Consequently, this species is insufficiently monitored, especially in the northern portion of its range

(Brigham et al. 2011). In this region, focused efforts to survey breeding nighthawks will be logistically and financially difficult due to low road density and the short nighthawk breeding season.

During early autumn, large numbers of Common Nighthawks habitually concentrate and migrate along the north shore of Lake Superior near Duluth, Minnesota

(Hendrickson and Eckert 1991). Single-day flights of over 5,000 nighthawks are nearly annual events, and these counts represent a sizeable portion of the northern Common

Nighthawk population. Common Nighthawks are a good candidate for use of visible migration counts to assess population trends, and the western Lake Superior region is a suitable location to study the effects of weather on migrating Common Nighthawks. The

14 migration and migratory behavior of Common Nighthawks has received little attention

(but see Taylor 1996, 2009).

I analyze visible migration counts of Common Nighthawks along the north shore of Lake Superior using a 10-year data set. My goals were: (1) describe the largest known migratory concentration of this species, (2) investigate and describe the relationship between weather and Common Nighthawk migration intensity, and (3) assess the trend of the population of nighthawks that moves through the region and if possible correct for weather effects. I hypothesize that weather conditions that typically stimulate autumn migration – falling temperatures, tailwinds, and light winds – will be correlated with nighthawk migration. Additionally, I hypothesize that population trends derived from visible migration counts of Common Nighthawks will mirror the significant decline for this species found by the BBS.

METHODS

Study Area

Visible migration counts were conducted from the third story rooftop of a condominium complex in Duluth, MN (46.83 N, 92.00 W) (Figure 1; Bardon 2012). At this site, most migrant birds appear from the northeast, and the count location provides an unobstructed view in this direction. Duluth sits at the western tip of Lake Superior, a large migration corridor, and many birds concentrate along the shore during southbound autumn migration as they avoid crossing the large body of water (Hofslund 1966).

Migration Counts

From 2008 to 2017, counts were conducted daily from August 15th to September

1st commencing at 16:00 CST and continuing until sunset; in some years counts were made outside of this window. Counts were halted during periods of precipitation. The number of nighthawks migrating per day was recorded by one or two experienced observers using 7x to 10x binoculars. On most days, nighthawks were counted individually, but during peak passage (e.g. 2,000+ birds/hour), large flocks were counted by fives or tens. Every effort was made not to double-count the migrating nighthawks, and this effort was aided by their straight-line flight during active migration – a behavior very much unlike their foraging flights. Counters recorded all nighthawks flying in a southwesterly direction. Historical counts of nighthawk flights in Duluth were compiled from published accounts (e.g. Hendrickson and Eckert 1991).

Local Weather

Weather conditions were recorded at 16:00 CST and obtained from the National

Centers for Environmental Information (NCEI; https://www.ncdc.noaa.gov/). These data were measured at the Duluth International Airport which is located 14 km west of the count location. Weather covariates predicted to influence the migration of Common

Nighthawks were measured: temperature (°C), percent relative humidity, wind direction

(degrees), wind speed (kph), and barometric pressure (in. Hg). Humidity and temperature values were highly correlated so humidity was eliminated from further consideration, as these metrics were likely describing similar weather phenomenon. Wind direction in degrees (polar degrees) was first converted into Cartesian degrees, then into radians, and finally transformed using sine and cosine transformations following Fisher (1993):

!"#$""% = 450 − +,-! !,$"/0,1- if wind direction ≥ 90 1

!"#$""% = 450 − +,-! !,$"/0,1- − 360 if wind direction < 90 2 D $C!,C- = !"#$""% 3 180

FC0,0G!,-CF +,-! HCFG" = sin $C!,C- 4

F1-#,0G!,-CF +,-! HCFG" = cos $C!,C- 5

This constrained wind direction to values between -1 and 1. To examine the effects of latitudinal (East/West) winds, cosine values range from W = -1 to E = 1.

Likewise, to examine the effects of longitudinal (North/South) winds, sine values range from S = -1 to N = 1. All meteorological values were normalized by z-score prior to inclusion in models.

Statistical Analysis

Regression Modeling

Three analytic methods were used to investigate the influence of weather on the migration of Common Nighthawks. I constructed generalized linear mixed effects models

(GLMMs) with weather and date variables as fixed effects and year as a random effect. I first modeled by maximum likelihood the odds of a nighthawk “flight day” by fitting binary logistic regression models on predictor weather variables. A flight day was defined as a day on which >1000 migrating nighthawks were counted. Logistic regression was employed to minimize concerns about modeling raw counts due to observer effects.

Additionally, logistic regression allowed inclusion of 21 historical flight days; I assumed that the binary nature of logistic regression would accommodate protocol and observer differences because any count method would be able to distinguish between a flight day and a non-flight day. I also modeled the raw count of systematically counted nighthawks

18 from 2008 to 2017 on the predictor weather variables using negative binomial regression.

I used this method because the dependent variable consists of over-dispersed count data.

Finally, I constructed linear mixed effects models to predict the number of nighthawks counted from 2008 to 2017. I log +1 transformed the dependent variable because it was highly skewed with many more small counts than large counts. The addition of one was to avoid problems associated with taking the log of zeros. I chose to investigate both raw and log-transformed count data regression because there is disagreement about which practice is best for count data (O’Hara and Kotze 2010, Ives 2015).

For all models, I included ordinal date (days from 1 January) and ordinal date2 as fixed effects due to the non-linear effect of date over the three week migration season.

Three interactions with possible biological significance identified a priori were also considered (latitudinal wind direction and wind speed, longitudinal wind direction and wind speed, and latitudinal and longitudinal wind directions). I also investigated a set of seven models developed a priori that were based on observations of migrating Common

Nighthawks, their natural history, and their aerial prey. For all models, I performed manual backward selection on the global model to identify a best model among the candidate set. Model selection was performed using AIC adjusted for small sample size

(AICc; Burnham and Anderson 2002). I considered a variable to have an effect on

Common Nighthawk migration if it was included in the top model and the 95% confidence interval for the model coefficient failed to overlap zero. I also compared the signs of coefficients from the various modeling techniques.

Trend Analysis

I used the daily visible migration counts to develop count indices and used these to develop population trends for Common Nighthawk from 2008 to 2017. Count effort varied among years, so a seasonal passage window of 95% was calculated and any counts outside of this window were excluded. To analyze the ten-year trend of Common

Nighthawk counts in the study area, I used a geometric mean passage rate index following Farmer et al. (2007):

F- JKL + 1 = CN + CLOL + "KL 6 LQR where JKL is the number of nighthawks counted on day i in year j, CN is the intercept estimated by the regression, CLis the year coefficient estimated by the regression for each year OL and "KL is the error of the regression. F- JKL + 1 is the transformed geometric mean (TGM)j of nighthawks in year j. The transformed geometric mean was then back- transformed into the geometric mean:

UVW X Y Z/\) ST L = " − 1 7 where V is the variance of the raw counts pooled over all years (Farmer et al. 2007).

To account for weather effects on the counts of migrating nighthawks, I also used a date-adjusted and weather-adjusted geometric mean daily count following Hussell

(1981) and Farmer et al. (2007) with the general model:

P d c ` F- JKL + 1 = CN + CLOL + _`, + !abaKL + "KL 8 LQR `QR aQR where JKL is the count of nighthawks on day i in year j; CN is the intercept estimated by the regression, CL, _`, and !a are parameters of year, day, and weather covariates estimated by the regression, respectively. The geometric mean was calculated as above

20 for each day and then averaged over each year. I analyzed both of these population trends using linear regression with standard t-tests to assess trend significance. I performed all statistical tests in R (R Core Team 2013).

RESULTS

Between 2008 and 2017, 194,721 migrating Common Nighthawks were counted in 645 hours and 202 observation days (containing 37 flight days), for an average yearly count of nearly 19,500. At least one nighthawk was detected on 76% of all days. The mean daily count was 937 ± 2182 sd nighthawks/day (Table 1). Peak flights during the ten-year study period included 28,054 on Sept 1, 2015; 14,081 on August 21, 2013; and

10,403 on August 19, 2016 (Table 1). Cedar Waxwings (Bombycilla cedrorum), Cliff

Swallows (Petrochelidon pyrrhonota), and dragonflies (order Odonata) were the only other taxa that strongly participated in concurrent evening flights.

An additional 21 flight days from years between 1985 and 2007 were added for use in logistic regression and at least one count was used from 22 different years. Peak historical flights included 43,690 on August 26, 1990 (the largest flight ever recorded;

Hendrickson and Eckert 1991) and 15,173 on August 23, 2000. Days of >1000 nighthawks occurred as early as August 15th and as late as September 2nd (Figure 2).

Table 1 shows annual and overall average nighthawk counts, temperature, humidity, wind speed, and pressure from 2008 to 2017. Additionally, conditions during all flight days during this time period are listed.

Logistic regression analysis identified weather factors associated with the occurrence of nighthawk flights. Results indicate that significant covariates were latitudinal and longitudinal wind direction and their interaction, wind speed, pressure, and

21 temperature (Table 2). Similarly, both negative binomial and linear mixed models indicated that latitudinal wind and wind speed and their interaction, as well as pressure, and temperature were significant (Table 3, Table 4). The best models from all analyses included latitudinal winds, wind speed, pressure, and temperature (Table 5).

I found effects of four model coefficients from all top models, including latitudinal winds, wind speed, pressure, and temperature (Table 5). Common Nighthawk counts were higher on days with westerly winds, lower wind speeds, lower pressure, and higher temperatures (Table 5, Figure 3, Figure 4). Westerly winds appear to be the most important weather variable in all top models followed by wind speed and finally temperature (Table 5). Regardless of assumed error distribution, all coefficients share the same sign for each covariate: negative for pressure, wind speed, and wind direction

(indicating westerly component), and positive for temperature. The coefficient for the interaction between longitudinal and latitudinal winds was negative in two models, perhaps indicating a slight preference for migration on northwesterly winds (Table 5).

The 95% passage window used for trend analysis from 2008 to 2017 fell between

August 15th and September 1st (ordinal days 227-244). Trends for Common Nighthawk migration in Duluth based on the geometric mean passage rate and the date-adjusted and weather-adjusted geometric daily count are shown in Figures 5 and 6. Both methods show stable or non-significantly increasing trends from 2008 to 2017.

DISCUSSION

I modeled the effects of weather on the visible migration counts of Common

Nighthawks along the north shore of Lake Superior during autumn. The overall agreement of my best models using various regression techniques adds confidence in my interpretations. Contrary to my predictions, Common Nighthawks preferred to migrate during days with warmer temperatures (Figure 3). This observation is surprising because the number of birds migrating in the autumn typically peaks during days of colder temperatures (Richardson 1990, Newton 2007). This species’ preference for westerly winds was also contrary to my predictions. Westerly winds act as a headwind for birds migrating in a southwesterly direction along the shore of Lake Superior, and migrant birds often avoid these conditions (Richardson 1990). In addition, it is surprising that no significant difference was detected between northerly and southerly winds because northerly winds are generally correlated with autumn migratory flights. Regional geography may partially explain the strong preference for wind with a westerly component: west winds push southerly migrating birds toward Lake Superior and east winds push them away from the lake and out of sight, no longer available to be counted.

Light wind speeds are often associated with larger migratory movements of non-raptors, and this holds true for Common Nighthawks migrating in this region (Figure 3).

Weather conditions associated with major flights of Common Nighthawks in the study area are also conducive to the presence of aerial insects in the migratory airspace

(e.g. Finlay 1976). A positive correlation between temperature and aerial insect abundance has been well established (Hardy and Milne 1938, Glick 1939). Abundance of flying insects decreases with increasing wind speed (Glick 1939, Møller 2013).

Richardson (1978) reviews observations of upwind movements of aerial insectivores that were presumably due to aerial prey availability or accessibility. These observations combined with results from my fitted models indicate the importance of aerial insects for migrating nighthawks. Common Nighthawks may time their migratory movements along the north shore of Lake Superior during the short migratory window each autumn to maximize foraging efficiency on days with large numbers of aerial insects. Migratory flight requires deposition of subcutaneous fat and thus a marked increase in food consumption (Newton 2007). Past reports have noted very large amounts of certain insect species in the guts of migrating Common Nighthawks, indicating the importance of insect hatches for autumn migratory movements (Blem 1972). Common Nighthawks may concentrate on the Lake Superior shore because of late summer insect hatches in this location, as this species seems to be an opportunistic predator of abundant aerial insects.

It is also conceivable that nighthawks are following migrating insects: on many days, large numbers of small unidentified insects were detected flying directionally (i.e. following the same path as migrating birds) along the shore of Lake Superior (S.K. personal observation). Future studies should focus on the insectivorous habits of this species during migration.

Peak Common Nighthawk movements along the North Shore of Lake Superior were highly synchronous. All large flights occurred between August 15th and September

2nd with a steep ramp-up and drop-off on either side of this window (Figure 2). This points to strong endogenous and/or exogenous control of migratory behavior (Newton

2007). Nighthawks appear to have a tightly regimented passage window in which they choose to migrate when conditions are optimal. These conditions may be weather and/or

35 food related. The distribution of nighthawk passage was highly clumped on days with certain weather characteristics. The current study is one of the first to quantify weather conditions that lead to a migratory flight of Common Nighthawks, and this information is useful for predicting likely peak passage days. Monitoring must occur on flight days, and a single count on these days would detect a high percentage of the annual seasonal nighthawk movement.

Contrary to my prediction, Common Nighthawk migratory counts in this region do not mirror the declines from BBS surveys with or without weather adjustments

(Figures 5, 6). The limited time period of my counts may be unable to detect a small decline, but should be able to detect a significant or catastrophic decline. There is some indication that Common Nighthawk populations are stabilizing, and this may also play a role in the ability to detect a trend. As with raptor trends (Farmer et al. 2007), adjusting for weather effects does not appear necessary for producing robust population trends for

Common Nighthawks in the study region.

Major knowledge gaps exist in the understanding of the migratory period in

Common Nighthawks that, if filled, would enhance the use of visible migration counts of nighthawks for trend development. For example, the catchment area of migrant nighthawks through this region in autumn is unknown. Additional research using tracking and/or modeling techniques is needed to address this issue. This region does not experience a concentrated return flight of Common Nighthawks in the spring. Research using tracking technology or exploratory spring visible migration counts to identify spring movement corridors would be beneficial in understanding the full life cycle of this species, especially during the migratory period. Limited anecdotal reports and the

36 continental trend of a more westerly spring migration point to river corridors west of the

Great Lakes region as the most likely geographic feature that would concentrate migrating Common Nighthawks in the spring. Investigation of return flights is especially important in population monitoring (Farmer and Smith 2010).

In this study, I describe the largest known concentration of Common Nighthawks in the world. The airspace over Duluth and the north shore of Lake Superior is disproportionally critical habitat to the conservation of Common Nighthawks during the autumn migratory period each year (Diehl 2013, Peterson et al. 2015), especially on peak flight days. Migration is the most dangerous season of the annual cycle for migrant birds

(Sillett and Holmes 2002, Klaassen et al. 2014). Specific dangers to Common

Nighthawks in the study region during migratory flight could include towers, wind turbines, and automobile collisions. On some days, Common Nighthawks have been struck by traffic in Duluth (S.K. personal observation). Thus, it is essential to understand where, when, and why threatened and declining species such as Common Nighthawks spend time and concentrate during migration.

The utility of visible migration counts for population monitoring is most obvious for diurnal migrants that are difficult to monitor with traditional methods. Migration counts can often be conducted by skilled volunteers and require little cost to implement

(Bildstein 1998). Migration counts are an efficient and cost-effective way to monitor the population of Common Nighthawks that migrates along the north shore of Lake Superior each autumn. Given that large concentrations of this species occur predictably each year in this region and that other monitoring efforts (such as the BBS or targeted surveys) are lacking, Common Nighthawks are an ideal species for which to utilize visible migration

37 counts for population monitoring. Common Nighthawk breeding surveys in the study region in 2016 and 2017 detected only eight individuals in 36 hours of surveying (S. K. unpublished data; see Chapter 1). To detect the seasonal migration average of 19,500 nighthawks would take a monumental effort on the breeding grounds, but can be achieved by one observer in less than three weeks in the autumn. Other locations that detect migrating Common Nighthawks should implement or continue nighthawk monitoring so that observers can form a network like that developed for hawk migration throughout North and Central America (Bildstein 1998). In fact, many hawk migration sites could be used for these counts in the evenings given the proper coverage. Using the study of migratory raptors as a guide, an integrated approach of breeding, nonbreeding, and migration surveys will enhance the reliability of population trends for this species

(Dunn and Hussell 1995, e.g. Paprocki et al. 2017).

Visible migration counts aimed at estimating population trends should not be limited to raptors and other soaring birds. This study is one of the first to use these types of counts to monitor populations of non-raptors in North America, and this method shows promise for other species or groups. Visible migration counts will be useful for avian species or families such as the rapidly declining aerial insectivores (swifts, swallows, other nighthawks), waxwings, Blue Jays (Cyanocitta cristata), and blackbirds because these species migrate diurnally and BBS-type surveys fail to monitor them effectively.

Migration counts can be a time-effective and cost-effective way to augment information about poorly surveyed species and, much like the BBS, can be accomplished through citizen science.

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