Great Lakes Avian Radar

Technical Report

Lake Ontario Shoreline:

Jefferson, Wayne and 

Niagara Counties, New York

Fall 2016

Biological Technical Publication

BTP-R3017-2018

U.S. Fish & Wildlife Service, Region 3

Funding Provided by the Great Lakes Restoration Initiative

U.S. Fish & Wildlife Service

Great Lakes Avian Radar

Technical Report

Lake Ontario Shoreline:

Jefferson, Wayne and 

Niagara Counties, New York

Fall 2016

Biological Technical Publication

BTP-R3017-2018

January 2018 

Principle Investigator: 

Jeff Gosse, Regional Energy Coordinator, USFWS Region 3 

Authors:

Kevin W. Heist, Fish and Wildlife Biologist, USFWS Region 3

Nathan Rathbun, Fish and Wildlife Biologist, USFWS Region 3

Michael Wells, Fish and Wildlife Biologist, USFWS Region 3

Erik Olson, Fish and Wildlife Biologist (GIS), USFWS Region 3

U.S. Fish & Wildlife Service, Region 3

Funding Provided by the Great Lakes Restoration Initiative

U.S. Fish & Wildlife Service Region 3
Corresponding Author:

Kevin W. Heist

U.S. Fish and Wildlife Service

Fish and Wildlife Biologist

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: (612) 713-5196

Email: kevin_heist@fws.gov

Authors’ Complete Contact Information:

Jeffrey C. Gosse

U.S. Fish and Wildlife Service

Regional Energy Coordinator

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: 612/713 5138

Email: jeff_gosse@fws.gov

Kevin W. Heist

U.S. Fish and Wildlife Service

Fish and Wildlife Biologist

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: (612) 713-5196

Email: kevin_heist@fws.gov

Erik C. Olson

U.S. Fish and Wildlife Service

Fish and Wildlife Biologist (GIS)

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: 612/713 5488

Email: erik_olson@fws.gov

Nathan A. Rathbun

U.S. Fish and Wildlife Service

Fish and Wildlife Biologist

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: 612/713 5182

Email: nathan_rathbun@fws.gov

Michael T. Wells

U.S. Fish and Wildlife Service

Fish and Wildlife Biologist

Ecological Services

5600 American Blvd. West, Suite 990

Bloomington, MN 55437

Phone: (612) 713-5336

Email: michael_wells@fws.gov 
Funding for this study was provided by the Great Lakes Restoration Initiative 

Disclaimer: The findings and conclusions in this article are those of the authors and do not 

necessarily represent the views of the U.S. Fish and Wildlife Service. The mention of trade names or 

commercial products in this report does not constitute endorsement or recommendation for use by 

the Federal government.

Key words: Great Lakes, migration, avian radar, wind energy, birds, bats, 

Lake Ontario 

Recommended citation: 

Heist, K.W., N.A. Rathbun, M.T. Wells, E. Olson, and J. C. Gosse. 2018. Great Lakes Avian Radar Technical 

Report Lake Ontario Shoreline, Jefferson County, Niagara County, and Wayne County, New York, Fall 2016. 

U.S. Department of Interior, Fish and Wildlife Service, Biological Technical Publication 

FWS/BTP-BTP-R3017-2018
ISSN-978-1-938956-10-2

Biological Technical Publications online: 

http://digitalmedia.fws.gov/cdm/search/collection/document/searchterm/Biological%20Technical%20Publications/field/collec/mode/exact/conn/and/order/nosort
 i

Table of Contents

List of Figures ......................................................................................................................................................... ii 

List of Tables .......................................................................................................................................................... iv

Acknowledgements............................................................................................................................................... v

Executive Summary................................................................................................................................................vi

Introduction............................................................................................................................................................. 1

 Objectives .................................................................................................................................................. 2

Methods................................................................................................................................................................... 3

 Study Area and Site Selection .......................................................................................................... 3

 Equipment ........................................................................................................................................ 6

 Description of radars............................................................................................................................... 6

 Weather Station ........................................................................................................................................................ 6

 Radar Setup and Data Collection ................................................................................................................................ 7

 Radar System Outputs .................................................................................................................................................. 9

 Data Processing and Quality Control .............................................................................................. 9

 Biological Time Periods ....................................................................................................................... 9

 Data Summary and Trends Analysis ................................................................................................ 9 

 Directional Trends ........................................................................................................................ 10

 Temporal Trends ............................................................................................................................11

 Altitudinal Trends ......................................................................................................................... 11

 Density per Altitude Band........................................................................................................... 11

Results ...................................................................................................................................................................14

 Qualitative Assessments ..................................................................................................................... 14

 Directional Trends .............................................................................................................................. 18

 Temporal Trends ................................................................................................................................ 23

 Time Series ................................................................................................................................... 23

 Target Passage Rate .................................................................................................................... 29

 Weekly Mean Target Passage Rates............................................................................................30

 Seven Day Moving Average ......................................................................................................... 30

 Altitudinal Trends .......................................................................................................................... 33

Discussion ........................................................................................................................................................... 48

 Sampling Regime .................................................................................................................................48

 Target Counts ........................................................................................................................................48

 Migration Patterns ...............................................................................................................................49

 Flight Altitude ................................................................................................................................... 50

 Radar Study and Management Considerations ............................................................................... 50

 Conclusions ........................................................................................................................................... 51

Literature Cited ..................................................................................................................................................... 52

Appendices .......................................................................................................................................................... 57
ii

List of Figures

Figure 1. Fall 2016 radar locations............................................................................................................................... 4

Figure 2. Land cover within horizontal radar scan ................................................................................................... 5

Figure 3. Graphic of volume scanned by the horizontal and vertical radars .......................................................... 6 

Figure 4. Clutter maps ................................................................................................................................................. 8 

Figure 5. Schematic of vertical scanning radar beam ............................................................................................. 10 

Figure 6. Sample volume estimation for vertical scanning radar within the standard front. ............................ 12 

Figure 7. Volume of 50-m altitude bands within the standard front ...................................................................... 13

Figure 8. Sample Trackplots from Jefferson County. ............................................................................................. 15

Figure 9. Sample Trackplots from Wayne County. .................................................................................................. 16

Figure 10. Sample Trackplots from Niagara County. ........................................................................................ .... 17

Figure 11. Direction of target movement at Jefferson County ............................................................................. 19

Figure 12. Direction of target movement at Wayne County .................................................................................. 20

Figure 13. Direction of target movement at Niagara County ............................................................................... 21

Figure 14. Direction of origination, Jefferson County............................................................................................. 23

Figure 15. Direction of origination, Wayne County.................................................................................................. 24

Figure 16. Direction of origination, Niagara County .............................................................................................. 25

Figure 17. Hourly target counts in Jefferson County ............................................................................................ 26

Figure 18. Hourly target counts in Wayne County ................................................................................................. 27

Figure 19. Hourly target counts in Niagara County . ............................................................................................. 28

Figure 20. Box plots of target passage rates. ........................................................................................................... 29

Figure 21. Mean hourly target passage rate ............................................................................................................ 30

Figure 22. Weekly mean of nocturnal and diurnal target passage rates ................................................................... 31

Figure 23. Seven-day moving mean target passage rate ....................................................................................... 32

Figure 24. Diurnal and nocturnal seven-day moving means .................................................................................. 33

Figure 25. Altitude profile of targets at Jefferson County...................................................................................... 35
Figure 26. Altitude profile of targets at Wayne County ......................................................................................... 36

Figure 27. Altitude profile of targets at Niagara County ...................................................................................... 37

Figure 28. Sample of hourly altitude profiles in Jefferson County ....................................................................... 38

Figure 29. Sample of hourly altitude profiles in Wayne County ............................................................................ 39

Figure 30. Sample of hourly altitude profiles in Niagara County ........................................................................ 40

Figure 31. Altitude profile of corrected target density below 500 m. ................................................................... 41

Figure 32. Maximum density by night ...................................................................................................................... 42

Figure 33. Maximum density by night hour ............................................................................................................. 43

Figure 34. Hourly altitude heatmap for Jefferson County .................................................................................... 44

Figure 35. Hourly altitude heatmap for Wayne County ......................................................................................... 45

Figure 36. Hourly altitude heatmap for Niagara County ....................................................................................... 46

Figure 37. Mean hourly target height ....................................................................................................................... 47

Figure 38. Hypothetical non-continuous sampling schedule ................................................................................. 49

iii
List of Tables

Table 1. Land cover ...................................................................................................................................................... 4 

Table 2. Survey effort ................................................................................................................................................ 14

Table 3. Directionality of target movement ............................................................................................................ 22

Table 4. Mean target passage rate ........................................................................................................................... 29

Table 5. Altitude summary statistics........................................................................................................................ 34

iv
v

Acknowledgements

This project would not have been possible without 

the funding provided through the Great Lakes 

Restoration Initiative for which we are very 

appreciative. We are grateful for the advice, 

technical assistance, and contributions of our 

collaborators Doug Johnson (U.S. Geological 

Service), and Anna Peterson (University of 

Minnesota). Jake Ferguson’s (University of Florida) 

statistical and programming expertise provided our 

model of the geometric shape of the radar beam. We 

also thank the landowners that provided space for 

our radar units; Robert De Badts, William Haller, 

and others. We also want to thank other programs 

for their assistance during this season including 

the New York Department of Environmental 

Conservation, U.S. Army at Fort Drum, and the 

USFWS New York Field Office. This manuscript 

benefited from external reviews and we thank those 

that contributed, which included: Tim Sullivan, Fish 

and Wildlife Biologist at the USFWS New York 

Field Office; and Jeff Bolsinger, Migratory Bird 

Biologist at Fort Drum, NY.
Executive Summary

Every spring and fall, millions of birds and bats 

migrate through the Great Lakes region where 

shorelines provide important stopover habitat.

Shorelines are thought to concentrate migrants as 

they offer the last refuge near a geographic obstacle 

and are likely used for navigation. Shorelines also 

offer areas attractive for the development of wind 

energy facilities, which may impact birds and bats 

through direct collision or barotrauma fatalities, 

avoidance or attraction of birds or bats in flight, 

or displacement of roosting, nesting, or rafting 

birds. With this potential for conflicting interests 

more information is needed on the aeroecology 

of the Great Lakes shorelines. We used two avian 

radar systems to identify activity patterns, timing, 

direction, and duration of migration that occurred 

along shorelines of the Great Lakes. 

We placed avian radar systems at two sites on 

the south shore of Lake Ontario and one site 

northeast of Lake Ontario, where the automated 

systems tracked and recorded target (bird and bat) 

movements continuously from early August to late 

October, 2016. We calculated direction of movement, 

target passage rates, and altitude profiles for 

targets moving through the air space above our 

study sites. We also used a model of our vertical 

sample volume that allowed us to correct for sample 

volume bias and report an estimate of target density 

by altitude band.

Migration along Lake Ontario’s southern and 

eastern coasts appeared strong at all three study 

sites. Mean nocturnal passage rates were greater 

than mean passage rates for dawn, day, and 

dusk combined at all three locations. Nocturnal 

movement was typically oriented in a southerly 

direction, but we also recorded other behaviors 

associated with migrants such as dawn ascent and 

dramatic changes in flight intensity and orientation 

shortly after sunset. After correcting for differing 

sample volumes among altitude bands, we found 

that peak density occurred between 100 – 400 m 

above ground level. However, density may have been 

underestimated at higher and lower altitudes. We 

documented migration activity in the air space above 

our study areas which indicates that the density of 

targets at low altitudes may present conservation 

concerns. The data we collected showed the ebb 

and flow of migration across the sampling period 

and documented that large nocturnal movements 

continued through late October. Given the amount 

of time that migration occurred in the sampled sites, 

it seems that curtailing wind energy operations to 

minimize bird and bat mortality during nocturnal 

pulses could result in limited operational time along 

shorelines during the migration season. Combining 

the results of radar studies and fatality searches 

would greatly improve risk assessments and assist 

with interpretation of standardized radar studies.

Avian radar is often relied upon to perform surveys 

for pre-construction risk analysis.

While an important tool, few regulatory agencies 

have experience implementing avian radar or 

otherwise recognize the strengths and limitations 

of the technology. This report highlights some 

considerations about avian radar and reviews some 

potentially confusing metrics. We also introduce 

some new metrics to report radar data. In addition 

to providing information relevant to wildlife 

conservation in the Great Lakes region, the concepts 

we present in this report are widely relevant to 

avian radar studies and provide methods that 

identify components of migration such as:

n Nocturnal pulses

n Season length 

n Estimated density per altitude band

n Migrant behavior near a geographical obstacle

Given the rapid growth of the wind energy sector, 

our most effective conservation effort might be our 

ability to identify and avoid development in locations 

where migrants concentrate. Our use of commercialgrade avian radar to document migration is a broadscale effort toward that end. To our knowledge, the 

Great Lakes radar monitoring project represents 

the first of its kind by the U.S. Fish and Wildlife 

Service. The results of our research highlight the 

potential role of radar in implementing the U.S. Fish 

and Wildlife Service’s Land-Based Wind Energy 

Guidelines and help to identify areas where impacts 

to wildlife could be minimized.

vi
Introduction

The Great Lakes are one of the largest freshwater 

systems on the planet and collectively represent a 

surface area of nearly 245,000 km2 with over 17,500 km 

of shoreline. Global wind patterns help to move millions 

of migrating birds and bats through the Great Lakes 

region (Rich et al. 2004, Liechti 2006, France et al. 2012) 

and lake shorelines feature widely recognized Important 

Bird Areas (Audubon 2013). Migrants passing through 

the region concentrate near shorelines (Ewert et al. 

2011, Peterson and Niemi 2011, Buler and Dawson 2012, 

France et al. 2012), which provide important stopover 

habitats – en route areas used temporarily for refueling, 

rest, and protection. These shorelines offer increased 

foraging opportunities relative to inland areas (Smith et 

al. 2004, 2007; Bonter et al. 2007, 2009) and may be used 

as a visual cue for navigation or for refuge prior to or 

after crossing open water (Buler and Moore 2011). 

Given their location and size, the Great Lakes likely 

represent a geographic obstacle that migrants choose to 

cross, or not, based on environmental and physiological 

conditions at the time of encounter (Faaborg et al. 2010, 

Schmaljohann et al. 2011). For migrants that rely on 

powered flight it is more efficient to make several short 

flights than a long flight due to the cost of carrying high 

fuel loads (Alerstam 1990). This is perhaps one reason 

why migrants partially circumnavigate the Great Lakes, 

though they have the physiological capability of crossing 

(Alerstam 1990, 2001, Ruth 2007). The decision to cross 

likely represents a trade-off between minimizing costs 

(e.g., energy and time) and exposure to risk factors 

(e.g., predation and fatigue) that are associated with 

migration (McGuire et al. 2012a). In this trade-off, 

shorelines offer refuge when conditions do not favor 

flights over water. 

Migrants challenged by an obstacle may temporarily 

reverse or deviate from seasonally appropriate flight 

directions or return to land to delay or recover from 

a crossing (Bruderer and Liechti 1998, Akesson 1999, 

Ewert et al. 2011). Schmaljohann and Naef-Daenzer 

(2011) found that birds with low fuel loads and/or facing 

unfavorable weather conditions returned to shoreline 

habitat rather than continue across open water in a 

direction appropriate for migration. For bats, migrants 

varied their choice to circumnavigate above shorelines 

or cross lakes and some long-distance migrants 

used torpor to postpone migration during periods of 

unfavorable conditions (McGuire et al. 2012b). These 

behavioral responses as well as the necessity of using 

stopover habitat during migration likely contribute 

to the increased use of shorelines and emphasize the 

importance of these areas for conservation. 

Migrants concentrated along shorelines can be very 

mobile. In addition to immediate refueling and rest, 

migrants make broad scale flights among habitat 

patches, explore wind conditions, and orient for 

migration. For example, radio tagged bird and bat 

migrants on the north shore of Lake Erie made 

repeated movements among habitat patches. Individuals 

relocated as far as 18 and 30 km from their capture site 

(maximum distance tracked for a bat and bird species, 

respectively) prior to resuming migration (Taylor et 

al. 2011). Nocturnal migrants such as warblers and 

other neotropical birds regularly engage in morning 

flights along shorelines (Wiedner et al. 1992). These 

flights typically occur within 2 hours of sunrise and are 

thought to represent reorientation along a geographic 

obstacle or movements among stopover habitats (Able 

1977, Moore et al. 1990, Wiedner et al. 1992). Flights 

of this nature often occur above tree line (Bingman 

1980) but lower than heights associated with nocturnal 

migration (Harmata et al. 2000, Mabee and Cooper 

2004, Newton 2008). Migrants have also been observed 

initiating nightly exploratory flights at stopover sites 

(Schmaljohann et al. 2011). These flights are thought 

to represent normal activity of migrants as they 

calibrate their internal compass and test wind speed 

and direction aloft. In addition to these activities 

while in stopover, migration flights follow north-south 

oriented shorelines en route to their destination (Buler 

and Dawson 2012) while east-west oriented shorelines 

may be used to circumnavigate open water or find 

narrow points for crossing (Alerstam 2001, Diehl et al. 

2003, France et al. 2012). Cumulatively, these types of 

activities define a use area near lake shores that include 

a variety of movements and altitudes for landscape 

level, exploratory, and migratory flights. These activities 

may increase vulnerability to collision risk with tall 

structures such as buildings, communication towers or 

wind turbines. 

Migrant populations may experience the greatest 

mortality pressure during migration (Newton 2006, 

2007; Sillett and Holmes 2002, Diehl et al. 2014) and the 

negative ramifications of compromised stopover habitat 

to migratory populations are becoming increasingly 

clear (Sillett and Holmes 2002, Mehlman et al. 2005, 

Faaborg et al. 2010). Shoreline habitats along the Great 

Great Lakes Avian Radar - Fall 2016 1
Lakes are subject to pressures from urban and energy 

development, land conversion, and environmental 

contamination that may limit habitat availability and/or 

reduce habitat quality (France et al. 2012). 

Of further concern, White-nose Syndrome is devastating 

hibernating bat populations and has increased the need 

to identify and protect high-use areas to bolster survival 

and recovery of cave bats, as several of these species 

face the risk of extirpation in the Great Lakes region 

(Turner et al. 2011). Adding further devastation to bat 

populations is the increase of wind energy installation 

within the U.S., which has resulted in high numbers 

of fatalities, most frequently impacting long-distance 

migratory tree bats (Kunz et al. 2007a, Cryan 2011, 

Arnett and Bearwald 2013, Hayes 2013, Smallwood 

2013, Frick et al. 2017). In response to factors such as 

these, substantial efforts are being made to identify 

and protect stopover habitat along the Great Lakes 

shorelines (Buler and Dawson 2012, Ewert et al. 2012, 

France et al. 2012, Johnson 2013). With climate change, 

considerations calling for both an increase in renewable 

energy development and conservation of migratory 

species, careful planning is needed to balance these 

demands. 

There is a national movement towards wind power 

supplying 20% of end-use electricity to the US market 

by 2030 (US DOE 2008, 2015) and 35% by 2050 (US 

DOE 2015). If achieved, this would represent nearly 

a five-fold increase in wind energy capacity during 

the next 13 years (Loss et al. 2013). Coinciding with 

this national effort, wind energy developments are 

increasing within the Great Lakes region where windy 

shorelines offer areas attractive for turbine placement 

(Mageau et al. 2008, Great Lakes Commission 2011). 

Utility-grade wind facilities have been associated with 

mortality events for migrating vertebrates (Newton 

2007, Arnett et al. 2008, Smallwood and Thelander 

2008) and chronic fatalities across the US, particularly 

for bats, are a concern (Timm 1989, Johnson 2005, 

Arnett and Bearwald 2013, Hayes 2013, Smallwood 

2013). Three species of long-distance migratory bats 

that are impacted by wind energy facilities account 

for approximately 75% of all bat mortalities (Cryan 

2011, Kunz et al. 2007a, Arnett and Baerwald 2013). 

These migrants, the hoary bat (Lasiurus cinereus), 

eastern red bat (Lasiurus borealis), and silver-haired 

bat (Lasionycteris noctivagans) typically make up the 

majority of bat fatalities at wind facilities in the Upper 

Midwest and elsewhere (Arnett et al. 2008). Three 

Wisconsin studies found high fatality rates for these 

same migrant species but also found that little brown bat 

(Myotis lucifugus) and big brown bat (Eptesicus fuscus)

fatalities were substantial (Gruver et al. 2009, BHE 

Environmental 2010, Grodsky et al. 2012). The presence 

of major hibernacula in the vicinity of these latter three 

studies may have contributed to high numbers of little 

brown and big brown bat fatalities at those sites. Low 

reproductive rates inhibit the ability of bats to rebound 

from population decline (Racey and Entwistle 2000) and 

these declines have already begun for several species 

(Kunz et al. 2007a, Cryan 2011). Cumulative impacts 

to bird and bat migrant species are a concern and this 

concern will increase with the growth of wind energy if 

methods to avoid or minimize mortality events are not 

established. Some promising conservation measures 

have been proposed to reduce mortality levels, however 

the greatest benefit to the conservation of migrants 

might lie in our ability to identify and avoid future 

growth in locations where migrants concentrate. 

To help meet the needs of both renewable energy 

development and wildlife conservation, we established 

this project to identify activity patterns, timing, and 

magnitude of migration that occurs along shorelines 

of the Great Lakes. This project has been collecting 

radar data on migration for six consecutive years 

(Bowden et al. 2015, Horton et al. 2016, Rathbun et 

al. 2016a, Rathbun et al. 2016b, Rathbun et al. 2016c). 

Because bats and many bird species migrate during the 

nighttime hours throughout the spring and fall seasons, 

documenting bird and bat migration is challenging 

due to the difficulty of observing nocturnal movements 

that occur sporadically over the course of a season. To 

address this we used two avian radar units that operated 

24 hours per day and simultaneously scanned horizontal 

and vertical planes. Our objectives for the portion of the 

study we are reporting on include:

Objectives

n Monitor locations along the Lake Ontario 

 shoreline using a consistent methodology.

n Maintain an archive of continuously recorded 

 radar data during the fall migration season.

n Identify the activity patterns captured by radar 

 that are diagnostic of migration.

n Estimate the duration of the migration season.

n Identify areas of concentrated migratory activity.

n Document changes in behavior of migrants 

 during different parts of the season.

2 Great Lakes Avian Radar - Fall 2016 
Methods

Study Area and Site Selection

During the fall 2016 season, we selected three sites 

in New York State, along southern and eastern Lake 

Ontario for radar placement; one site was on the 

western side of the south lakeshore in Niagara County, 

another site was located on the eastern side of the 

south lakeshore in Wayne County, and a third was 

inland from the St. Lawrence River outflow northeast 

of the lake in Jefferson County (Figure 1). We located 

the two southern shoreline sites within 1.5 km of Lake 

Ontario to monitor airspace above inland, shoreline, 

and lake areas. The Jefferson County site was 

approximately 25 km from Lake Ontario and 10 km 

from the St. Lawrence River. 

In Jefferson County, the radar unit was located at 

44.1746° N, -75.9850° W, in an open field within an area 

where agricultural fields and patches of deciduous 

forest were the predominant landscape features within 

range of the radar unit, according to our analysis 

using Esri ArcGIS software and the 2006 National 

Land Cover Database (Fry et al. 2011; Table 1, Figure 

2, Appendix 2). A small limestone quarry is located 

approximately 1 km north of the Jefferson County 

radar’s location. The other two sites in Niagara 

County (43.3401° N, -78.6591° W) and Wayne County 

(43.2755°N, -77.0919° W) were both located in apple 

orchards, with surrounding landscape that included a 

mix of agriculture (hay and fruit fields) and forested 

patches. Both southern sites also included substantial 

segments of coastlines as well as large areas of open 

water within the horizontal extent of radar coverage 

(Table 1, Figure 2, Appendix 2). The site in Niagara 

County was used in a previous season of our project 

(spring 2013), and the Wayne County Site was located 

within 1.6 km of our site used during that same season 

(Rathbun et al. 2016a).

One radar unit, “Batman” collected data at the 

Jefferson County site for entire study period (August 

4 – October 28). The other radar unit, “Robin” began 

collecting data at the Wayne County site and was 

moved to the Niagara County site on September 10, 

in accordance with our study plan. This monitoring 

regime enabled consistency and comparability without 

limiting the study to two locations. It allowed us to 

examine activity at two different locations near the 

coast, while monitoring throughout the season at an 

inland site to control for purely temporal variation.

Selection of radar monitoring sites was achieved 

through a combination of geographic modeling and 

on-site assessment to locate areas near shorelines with 

unimpeded views. First, large sections of Great Lakes 

shorelines were identified as potential study areas 

for the migration season. Esri ArcGIS software was 

used to model the areas of interest to find locations 

that could be suitable for radar siting. This suitability 

modeling incorporated datasets describing elevation, 

land cover, and shorelines of the Great Lakes. 

Additional landscape characteristics were derived 

from these datasets (elevation below local maximum 

elevation, percent forested, distance to forest, distance 

from shoreline, etc.) and ranked to create a continuous 

raster surface within the area of interest with 

estimated suitability values. Contiguous areas with 

high suitability identified through the GIS modeling 

process were targeted for on-site assessment.

Biologists were dispatched to areas of interest to do a 

more thorough assessment of potential sites identified 

by the modeling effort. This assessment included 

evaluating the land use, visual obstructions, and 

accessibility for placement of radar units. Additional 

locations not identified through the modeling were 

frequently discovered through this process and 

evaluated as well. When a location was determined 

by field biologists to be highly suitable relative to the 

other locations visited in the field, contact was initiated 

with property owners to obtain permission to set up 

the radar units.

Great Lakes Avian Radar - Fall 2016 3
Figure 1. Fall 2016 radar locations in Jefferson, Wayne, and Niagara Counties, New York. The map image is 

the intellectual property of Esri and is used herein under license. Copyright © 2016 Esri and its licensors. 

All rights reserved.

Table 1. Predominant land cover types found within a 3.7 km radius of the radar locations located in New 

York during fall 2016.

National Land Cover Class Jefferson Wayne Niagara

Cultivated Crops, Hay/Pasture 60.14% 46.69% 39.23%

Developed1 4.84% 2.99% 3.84%

Forest2 24.29% 10.59% 17.72%

Open Water 0.27% 31.68% 34.70%

Other3 10.46% 8.05% 4.51%

1 Includes low, medium and high intensity development and developed open space.

2 Includes Deciduous, Evergreen and Mixed Forests.

3 Includes barren land, grassland/herbaceous, shrub/scrub and woody and emergent 

herbaceous wetlands.

4 Great Lakes Avian Radar - Fall 2016 
Figure 2. Land cover within approximate horizontal 

radar range. National Landcover Dataset land 

cover types within a circle of radius 3.7 km, 

approximating the horizontal coverage of radar 

units located in New York during fall 2016. Map 

image is the intellectual property of Esri and is 

used herein under license. Copyright © 2014 Esri 

and its licensors. All rights reserved.

Great Lakes Avian Radar - Fall 2016 5
Equipment

We used two model SS200DE MERLIN Avian 

Radar Systems (DeTect Inc., Panama City, FL) to 

document migration movements. This systems was 

selected because it is a self-contained mobile unit 

specifically designed to detect, track, and count 

bird and bat targets. The tracking capabilities of 

the MERLIN system have been independently 

evaluated (Gerringer et al. 2015, May et al. 2017). 

Each system employed two marine radar antennae 

that operated simultaneously, one that scanned the 

horizontal plane while the other scanned vertically 

(Figure 3). Additionally, each unit contained four 

computers for real-time automated data processing, 

storage, and review. The units were configured 

with a wireless router to allow remote access to the 

computers and automated status updates.

Description of radars. Solid state marine radar 

antennas (Kelvin Hughes, London, UK) employed 

by our systems were 3.9 m in length, with 170 W 

peak power, S-band (10 cm) wavelength, 2.92 – 3.08 

GHz frequency range, and were configured to 

operate with both short and medium pulse (0.1 and 5 

microseconds, respectively). The horizontal radar was 

also equipped with Doppler to help filter stationary 

targets. The radars emanated a fan-shaped beam 

which had an approximate 1° horizontal and 25° 

vertical span when operated in the horizontal plane. 

S-band radar (approximately 10 cm wavelength) 

was selected because the longer wavelength is less 

sensitive to insect and weather contamination than 

X-band radar (approximately 3 cm wavelength; 

Bruderer 1997). It is also less sensitive to signal 

attenuation from ground clutter such as vegetation 

and structures (DeTect Inc., unpublished data, 2009). 

The radars spin perpendicular to each other at a rate 

of 20 revolutions per minute and were synchronized 

so as not to emit over one another. The horizontal 

scanning radar (HSR) was affixed to a telescoping 

base that was raised to approximately 7 m above 

ground for operation. This radar rotated in the x-y 

plane with a 7° tilt to reduce the amount of ground 

clutter included within its view. While the radar had 

the capability to scan longer distances, we selected 

a 3.7 km range setting for data collection in order to 

have higher resolution and identify smaller targets 

such as passerines and bats. The HSR was primarily 

used to provide information on target direction. The 

vertical scanning radar (VSR) rotated in the x-z 

plane and scanned a 1° x 25° span of the atmosphere. 

We selected a 2.8 km range setting for this radar for 

increased resolution and used the VSR to provide 

information on the number and height of targets.

Weather Station. Each system was equipped 

with a weather station (Davis Vantage Pro 2, 

Hayward, CA) that recorded wind speed and 

direction, humidity, temperature, precipitation, 

and barometric pressure. Weather data were 

summarized and stored every 5 minutes. The 

anemometer was attached to the radar unit and 

measured wind speed at a height of about 6 m above 

ground level.

Figure 3. Graphic of volume scanned by horizontal and vertical radars. Blue represents the horizontal radar 

(HSR) and green represents the vertical radar (VSR). Graphic provided by DeTect, Inc.

6 Great Lakes Avian Radar - Fall 2016
Great Lakes Avian Radar - Fall 2016 7

Radar Set Up and Data Collection

The two radar systems were deployed during the 

first week of August at the Jefferson and Wayne 

County sites. In the second week of September, the 

radar unit in Wayne County was relocated to the 

study site in Niagara County, while the Jefferson 

County radar remained in its location. Both radar 

systems were operational into the last week of 

October to capture the anticipated end dates of the 

migration season.

Establishing radar systems at a selected site 

involved several activities including orienting 

the VSR, micro-site selection, and adjusting to 

ensure adequate information was captured. We 

anticipated a primarily southbound direction of 

migration during fall and oriented the beam of 

the vertical radars to an angle that was slightly 

off of perpendicular to anticipated direction of 

traffic. This orientation was a compromise between 

a perpendicular angle that would intercept the 

greatest number of targets (birds or bats) and a 

parallel angle that would maximize the amount of 

travel time within the radar beam. The orientation 

was also influenced by micro-site selection. Microsite selection is important in that positioning 

the radar can affect the amount of interference 

from ground clutter or other sources of radar 

interference. If large areas were obstructed from 

the radar view or if substantial amounts of clutter 

impeded data collection, systems were rotated 

incrementally to improve the radar’s view and/or 

reduce interference. 

The radar’s view of sample airspace can be obscured 

by two main sources of interference, both of which 

can be seen on the clutter maps (Figure 4). 1) 

Ground clutter is produced by static returns from 

ground-based objects such as trees, buildings, 

towers, and topographical features. Ground clutter 

is more prevalent on the horizontal antenna due 

to its low beam angle, and creates “blind spots” in 

which target detection is partially or totally blocked. 

2) Side lobes are more prevalent on the vertical 

antenna, and take the form of low-elevation patches 

or arcs, indicating return energy from airspace that 

is actually empty. Side lobes result from irregular 

and unpredictable refractions of the radar beam 

off the surrounding landscape or atmosphere. Side 

lobes can be reduced by making small adjustments 

to the radar’s orientation, but can rarely be 

eliminated. 

To improve radar tracking performance, tracking 

software analyzed the site’s airspace prior to data 

collection to “map” areas of clutter that would be 

removed from target tracking. Clutter maps (Figure 

4) were generated using 60-scan composite images, 

taken at time periods with low biological activity in 

order to identify areas with constant returns (white) 

associated with ground clutter or side lobes. These 

areas were assigned a reflectivity threshold that 

precluded the constant returns from being included 

in the data used for target tracking, and as a result, 

also reduced our ability to detect targets in these 

areas. 

Whereas the vertical scan at Wayne was relatively 

clean, the Jefferson site had some interference 

at low altitudes near the radar, and Niagara had 

several side lobe arcs at various distances from 

the radar. Clutter on the horizontal antenna was 

worst at the Jefferson site, and relatively clean at 

Wayne and Niagara. However, the Wayne site had 

an obstruction to the south that created a blind spot 

to the south and southwest of the radar unit. Clutter 

on the horizontal antenna is more likely to prevent 

target detection, and is one reason horizontal data 

include numerous broken tracks in which a single 

animal is counted multiple times. Data from the 

vertical antenna are more reliable for counts. The 

vertical sample volume is cleaner overall, and 

especially at high altitudes. Side lobes on the vertical 

antenna can reduce detection rates in certain areas, 

but do not completely block detection except in very 

high-return areas near the ground (bright white), 

and do not prevent detection of targets behind the 

obscured area, as ground clutter does. Variation 

in detection rates among sites can have an effect 

on results, but we currently have no means of 

correcting for these effects.

Once a position was established, clear-air thresholds 

and the radar’s built-in sensitivity time control 

(STC) filters were employed to reduce small nontarget returns and improve tracking of distant 

targets. These settings are needed as an object 

reflects more energy at close range than it does 

when it is further from the radar. For example, an 

object at a 50 m range will return about 16-times 

more energy than when it is at 100 m range 

(Bruderer 1997, Schmaljohann et al. 2008). 

Following initial set up, MERLIN software was 

fitted to site conditions. The MERLIN software 

provides real-time processing of raw radar data 

to locate and track targets while excluding nontargets and rain events. However, parameters used 

by the tracking software require adjustments to 

account for site specific conditions. DeTect personnel 

trained our biologists in establishing these settings 

during previous seasons of this project with the 

goal of minimizing inclusion of non-targets while 

maximizing cohesive tracks of targets. 

Processed data from each day were stored in Access 

databases, which were regularly transferred into a 

cumulative SQL database containing data for the 
Figure 4. Clutter maps for horizontal antenna (left, radar at center) and vertical antenna (right, radar at 

bottom middle). Brighter areas represent static returns from stationary objects such as tree lines and 

fencerows. Detection of targets may be lost in these areas due to obstruction from these objects.

8 Great Lakes Avian Radar - Fall 2016 

Jefferson County Clutter Maps

Wayne County Clutter Maps

Niagara County Clutter Maps
Great Lakes Avian Radar - Fall 2016 9

entire season. SQL databases were later queried 

for data analysis. In addition to processed data, we 

maintained all raw radar image data for potential 

reprocessing until the end of the migration season. 

Raw radar data were temporarily stored in the field 

on external hard drives and regularly transported 

back to the USFWS Regional Office (Region 3) on 

external drives.

Biologists visited each site periodically during the 

data collection period to ensure continuous function, 

monitor raw (unprocessed analog radar returns) 

and processed radar outputs, provide routine 

maintenance (such as re-fueling and oil changes), 

and manage data storage.

Radar System Outputs

The MERLIN software generates more than 30 

measurements to describe the size, shape, location, 

speed, and direction of movement of each target 

detected. These data are of the same type used by 

biologists when identifying biological targets on a 

radar screen (DeTect Inc., unpublished data, 2009) 

and this information was stored to the database for 

later analysis. To reduce potential false tracking, the 

MERLIN tracking algorithm removed tracks with 

fewer than five observations. As well, an automated 

filter was used to remove sectors of the sample 

volume that were dominated by rain. 

In addition to storing target attribute data, DeTect 

software outputs included a two-dimensional digital 

display of targets being tracked in real-time and 

static images of tracked targets over a specified 

period of time (Trackplots) for both vertical and 

horizontal radars. During each site check, we viewed 

the real-time digital display to ensure it agreed with 

the raw radar display. We later viewed 15-minute 

and 1-hour Trackplots to assess target direction and 

height during the previous day’s activity.

Data Processing and Quality Control

Prior to data analysis, data processed by MERLIN 

software was further evaluated for potential 

contamination by non-targets. While an automated 

rain filter was used, during some time periods it did not 

remove all rain from the recorded outputs. In addition, 

insects and various forms of transient clutter may be 

recorded during data collection. We relied on visual 

inspection of track patterns to discern contamination 

events. Rain and insect events form diagnostic patterns 

(Detect Inc., personal communication, 2011) and time 

periods with these types of track patterns can be removed 

when present. Biologists reviewed all data in 15-minute 

time increments and removed time periods that were 

dominated by rain; data were also reviewed for time 

periods dominated by insects or other clutter, but there 

were no time periods where these types of non-desirable 

targets needed to be removed from the dataset.

Unknown contamination that mimicked patterns of 

desired targets was not removed from the database 

and, to the extent that this occurred, contributed to 

error associated with indices. In addition to visual 

review, we evaluated initial counts by generating 

a time series to show the number of targets per 

hour across the season for both HSR and VSR 

radars. In general, the HSR and VSR hourly 

counts are positively correlated, with the HSR 

having higher counts. In situations where the VSR 

resulted in higher counts than the HSR or where 

peak counts appeared to be outliers, the data was 

further investigated for evidence of contamination 

or potential issues with radar performance. On 

rare occasions when time periods with anomalies 

appeared to represent artifacts not related to 

target movement (e.g., rain events, insects or data 

processing errors) they were removed from further 

analysis.

Once contaminated time periods were removed 

we summarized data using SQL queries provided 

with the MERLIN radar system. Data from the 

HSR were used to calculate hourly counts and 

target direction. All targets within 3.7 km of the 

radar unit were included in the analysis. Data from 

the VSR were used to calculate hourly counts and 

height estimates and these data were truncated to 

a 1-km front or “standard front”. We adopted this 

sampling technique as it is the method used by the 

manufacturer of the MERLIN units and this metric 

is also reported by other researchers (Lowery 

1951, Liechti et al. 1995, Kunz et al. 2007b). The 

standard front was defined by a volume of space 

that extended 500 m to either side of the radar and 

continued up to 2800 m, the maximum height of data 

collection (Figure 5). 

Biological Time Periods. For each site location, 

sunrise and sunset times were calculated and 

target counts were further segregated into four 

biological time periods: dawn, day, dusk, and night.

“Dawn” was defined as 30 minutes before sunrise 

to 30 minutes after sunrise, “day” as 30 minutes 

after sunrise to 30 minutes before sunset, “dusk” 

as 30 minutes before to sunset to 30 minutes after 

sunset, and “night” as 30 minutes after sunset to 30 

minutes before sunrise. 

Data Summary and Trends Analysis

We used the processed data to assess activity 

patterns that are associated with migration.

Horizontal Trackplots were viewed to identify 

changes in activity and to investigate migrant 

behaviors such as reverse migration (Akesson 

1999) and migrants moving toward shore at dawn; 

Vertical Trackplots were viewed to investigate 

changes in activity such as dawn ascent (Myres 

1964, Diehl et al. 2003). Target counts represented 
10 Great Lakes Avian Radar - Fall 2016 

an index of abundance and we used these indices 

to identify directional, temporal, and altitudinal 

trends.

 

Directional Trends. Mean angle and concentration 

(r) of target directions were analyzed following 

methodology for circular statistics (Zar 1999) 

provided within DeTect SQL queries. The angular 

concentration value is 1 when all angles are the 

same and 0 when all angles cancel each other (e.g., 

if 50% of the vectors are 180° and 50% are 360°, then 

there is not a predominate direction because there 

were as many targets heading south as there were 

heading north, thus the angular concentration is 0). 

We anticipated a generally southward direction of 

movement from nocturnal targets during the fall 

migration season and report the mean direction of 

nocturnal targets and the percent of nights targets 

Figure 5. Schematic of vertical scanning radar beam. Graphical representations (left) pair with photos 

(right) of the radar unit aligned perpendicular (top) and parallel (bottom) to rotational plane. The standard 

front used for data analysis is marked on the top left image. The standard front extends to 500 m on either 

side of the radar and up to a height of 2800 m. In this graphic the radar is situated at the bottom center and 

the red dashed lines represent the lateral limits of the standard front. In the bottom graphic the radar rotation is suspended so that the beam emits directly upward; this view is an approximation of the beam dispersion as it travels away from the radar unit (schematic not drawn to scale).
Great Lakes Avian Radar - Fall 2016 11

traveled in a direction between east-southeast and 

west-southwest (112.5° – 247.5°). We used radial 

graphs to plot the number of targets per 8-cardinal 

directions (i.e., eight groups centered on N, NE, E, 

SE, S, SW, W, NW) during the four biological time 

periods dawn, day, dusk, and night. 

Temporal Trends. We plotted counts of targets 

per hour processed by MERLIN software for both 

HSR and VSR antennas as a time series to identify 

pulses of nocturnal activity, season duration, and 

changes in patterns of activity over time. The HSR 

and VSR radars have different strengths that 

complement one another; these indices were plotted 

together. The HSR index tracks low flying targets 

in a 360° span around the radar unit and detection 

is not affected by the target’s direction of travel 

as with the VSR. However, the HSR is much more 

affected by ground clutter than the VSR, which 

affects target detection and tracking. Errors caused 

by ground clutter lead to both under- and overcounting; targets blocked by ground clutter may not 

get counted, and targets that fly in and out of areas 

with ground clutter may get counted multiple times. 

This leads to HSR counts that are more influenced 

by site conditions than VSR counts. However, the 

HSR index better captures targets under certain 

conditions, such as when targets are primarily at 

low elevation and/or traveling parallel to the VSR. 

The HSR is also much more susceptible than the 

VSR to beam bending from dynamic atmospheric 

conditions; beam refraction in the VSR is minimal 

primarily due to its orientation. The VSR was used 

to track targets captured within the standard front 

and has more consistent detection than HSR as it 

mostly tracks against clear air, except in the lowest 

altitude bands. Its detection is affected by target 

direction and distance from the radar (Bruderer 

1997, Schmaljohann et al. 2008). The VSR is also 

impacted by ground clutter, particularly at low 

elevations. Plotting these indices together provided 

a more comprehensive understanding of changes in 

target activity over time.

We used the VSR data to calculate target passage 

rate (TPR). We calculated TPR as the number of 

targets per standard front per hour using DeTect 

SQL queries. Hours with less than 30 minutes of 

recording time were omitted from this calculation. 

For example, after removing all hours with less 

than 30 minutes of clean data, nocturnal TPR for a 

given night (biological time period) was calculated 

by dividing the target count by the number of 

nighttime minutes and multiplying by 60 to 

provide the number of targets per hour during that 

night. We extended this metric to the season and 

calculated mean TPR for biological time periods 

and hours of the season. Mean nocturnal TPR for 

the season is the sum of night TPRs divided by the 

number of nights sampled. Similarly, mean hourly 

TPR for the season is the sum of TPRs for an hour 

period divided by the number times that hour 

was sampled. We also calculated mean nocturnal 

(night biological period) and diurnal (day biological 

period) TPR for weeks during the sampling period. 

These were calculated in two ways. To show the 

variability among sampled weeks we divided the 

sum of the TPRs for a week (nocturnal or diurnal) 

by seven and reported the weekly mean TPR and 

its standard deviation. To better illustrate nocturnal 

and diurnal trends in TPR across the season we 

plotted 7-day moving means of TPR as line graphs. 

Altitudinal Trends. DeTect SQL queries calculated 

height estimates from the VSR data of targets 

tracked within the standard front. Height estimates 

were calculated based on the range and bearing 

of the target location with the largest radar echo 

and reported as the height above ground level as 

measured at the radar unit; this measurement does 

not take into account changes in topography as you 

move across the landscape. We used these estimates 

to calculate mean altitude of targets above ground 

level by biological time period and hour and report 

mean and median altitudes for the season. 

Density per Altitude Band. In order to provide 

information on the density of targets per 50-m 

altitude band per hour within the standard 

front, we first estimated the volume of the radar 

beam’s approximate geometric shape. The width 

of the radar beam expands as it travels from the 

radar resulting in increased survey volume with 

distance from origin. The shape of the survey 

volume contains the space in which targets have 

the potential of being detected and represents 

one of several considerations that define the 

realized or actual survey volume (Bruderer 1997, 

Schmaljohann et al. 2008). We calculated the volume 

contained by the shape of the radar beam and 

report density of targets (targets per 1,000,000 m3) 

per 50-m altitude band per hour for each biological 

period. This was calculated by dividing the number 

of targets per volume of an altitude band by the 

number of minutes with clean data during the 

biological time period of interest and multiplied 

by 60.

To estimate the volume of 50-m altitude bands that 

are constrained by the standard front we used 

Monte Carlo integration (Press et al. 2007). The 

volume contained by the shape of the radar beam 
12 Great Lakes Avian Radar - Fall 2016 

can be calculated using spherical coordinates and 

multiple integration. However, subjecting this 

volume to Cartesian constraints (i.e., the standard 

front and altitude bands) complicates the calculation 

and the volume bands are more easily estimated 

using Monte Carlo integration. Monte Carlo 

integration is a method to calculate an unknown 

volume by enclosing it in a known volume and 

saturating the space with random points. Monte 

Carlo integration requires rules that determine 

whether the randomly drawn points are inside or 

outside of the unknown volume. The proportion of 

points that fall within these constraints multiplied 

by the volume of the known space is approximately 

equal to the unknown volume. In Monte Carlo 

integration, as the number of random points 

approaches infinity the estimation approaches truth 

(an exact calculation). 

We used R software (R Core Team 2012) to describe 

a box of known volume that was large enough to 

enclose the radar beam and saturated this space 

with 10 million random points. For the radar beam, 

we determined two simple rules that defined 

whether a point was in the survey volume. The 

first rule was that the distance of the randomly 

drawn point from the origin was less than 2.8 

km, the second rule was that the angle between 

a randomly drawn point and the vertical plane 

(the x-z axis in Figure 6) was less than 12.5o (i.e., 

half the angle of beam width). The volume of a full 

sweep of the radar beam as estimated via Monte 

Carlo integration was within 5% of the analytical 

solution using spherical coordinates, thus, the 

number of random points that we used provided a 

reasonable approximation of the volume. With the 

volume of a full sweep of the radar beam described 

we were able to further constrain the Monte Carlo 

integration to describe the structural volume of the 

radar beam within a standard front (Figure 6) and 

within altitude bands (Figure 7). 

Figure 6. Sample volume estimation for the vertical scanning radar within the standard front. In this graphic 

the radar unit is located at the origin and the radar beam extends to 500 m on either side of the radar unit 

(x-axis) and up to a maximum height of 2800 m (z-axis). The y-axis represents the spread of the radar beam 

as it extends away from the origin. The orange semi-transparent points represent the volume contained by 

the structure of the radar beam. Dark gray points represent the volume that is within the box but are not 

included in the volume of the radar beam.
Great Lakes Avian Radar - Fall 2016 13

Figure 7. Volume of 50 m altitude bands within the standard front. Volumes were estimated with Monte 

Carlo integration. Altitude band intervals represent the upper band limit. Target counts provided by the 

vertical scanning radar are limited to the structure of the standard front. The red line represents the top of 

the rotor swept zone at 200 m.

The number of targets per altitude band is often 

reported by other researchers; however, these 

numbers are commonly reported without a volume 

correction. We wanted to compare our correction 

to the uncorrected method, however count data 

and volume data are on different scales. For this 

reason, we compare our density estimate to a 

density estimate based on the number of targets 

per 50-m altitude band per hour while assuming 

that there is an equal amount of volume within 

each altitude band (the volume of each altitude 

band is equal to the total volume divided by the 

number of altitude bands). An assumption implicit 

to reporting the number of targets per altitude 

band is that comparisons among bands can be 

made directly (i.e., that altitude bands are equal). 

For our comparison metric we made this implicit 

assumption explicit (see Appendix 4).
14 Great Lakes Avian Radar - Fall 2016 

Results

During the fall 2016 season we began data collection 

on August 3 and 4 at the Wayne and Jefferson County 

sites, respectively. Data collection at Wayne ended 

on September 9, 2016, at which point this radar unit 

was relocated to Niagara County. Data collection at 

the Niagara site began on September 10. The radars 

remained operational until October 27, resulting in a 

survey period of 2042 hours at the Jefferson site, 924 

hours at the Wayne site, and 1177 hours at the Niagara 

site (Table 2). Data were recorded continuously while 

the radar units were operational. Gaps in analyzed 

data occurred mostly during rain events. Limited 

radar downtime occurred when the radar units were 

not operational due to computer hardware or software 

malfunction, and/or maintenance. Minor data gaps 

occurred at Jefferson County on August 22 (HSR 

only), September 2, and October 21 (VSR only); 

Wayne County on August 4; and Niagara County on 

September 24 (HSR only) and October 20 (VSR only).

When correcting for radar downtime and removal 

of periods with rain, the radars collected useable 

data 86% and 94% of the season in Jefferson County, 

88% and 93% in Wayne County, and 87% and 93% 

in Niagara County, with the vertical and horizontal 

radars, respectively.

Table 2. Survey effort (hours) by vertical and horizontal scanning radars during fall 2016 at our radar sites 

in Jefferson, Wayne, and Niagara Counties in New York. Vertical and horizontal radars are not equally impacted by rain events or downtime.

Site Radar

Survey 

Period

Radar 

Downtime

Data 

Collected 

Data 

w/Rain

Usable

Data

% Data

Collected

% Usable 

Data

Jefferson VSR 2,042 67 1,975 214 1,761 97% 86%

Jefferson HSR 2,042 91 1,951 22 1,929 96% 94%

Wayne VSR 924 45 879 69 809 95% 88%

Wayne HSR 924 52 872 9 863 94% 93%

Niagara VSR 1,177 35 1,142 124 1,018 97% 87%

Niagara HSR 1,177 77 1,100 5 1,095 93% 93%

Qualitative Assessments 

Plots of tracked targets showed nocturnal migration 

events at all three locations (Figures 8, 9, and 10). 

Examples of a single night from each site are included 

on the following pages. Each page displays eight 

one-hour periods of target tracking that display the 

increase and decrease of flight activity over the course 

of a day: noon, 18:00, 20:00, 23:00; and 1:00, 4:00, 5:00, 

and noon the following day are included. Times are in 

Eastern Standard Time (UTC – 5:00), not adjusted for 

daylight saving time.

On September 1 at the Jefferson County site, we 

can see light traffic at noon, with little concentration 

of direction (scattered flights of various colors) and 

mostly low elevations. These tracks may represent 

short-distance daily movements. At 18:00, flight 

activity is still light, but some southward concentration 

is beginning to occur, which may indicate that some 

early departures for migratory flights are starting. 

Sunset on September 1 at this site was at 18:39 (EST). 

By 20:00, the horizontal radar image shows mass 

migration in the south and southeast directions (red 

and yellow respectively). The vertical image shows 

the most intense movement at about 750 m above the 

radar, with most activity occurring below 2000 m. 

Heavy migration continues through the 23:00 hour 

at the Jefferson County site, with flight directions 

still concentrated to the south, but a shift to more 

southwesterly (orange) routes. Altitudes appear more 

concentrated at this hour as well, with the most intense 

activity around 600 m and 1300 m. Low-elevation 

flights have become relatively sparse. Activity 

decreases slightly by the 1:00 hour, with flights still 

predominantly towards the southwest. High-elevation 
Great Lakes Avian Radar - Fall 2012 15

Figure 8. Sample Trackplots at Jefferson County. Flight tracks during 1 hour increments recorded by horizontal (first and third columns) and vertical (second and fourth columns) radars during a migration event at 

the study site in Jefferson County. Colors on the horizontal radar images show direction of flights as indicated on the color wheel (dark blue indicates a direction of travel to the north and red travel to the south). 

Vertical radar images show target heights (colors do not indicate direction). 
16 Great Lakes Avian Radar - Fall 2016

Figure 9. Sample Trackplots at WayneCounty. Flight tracks during 1 hour increments recorded by horizontal 

(first and third columns) and vertical (second and fourth columns) radars during a migration event at the 

study site in Wayne County. Colors on the horizontal radar images show direction of flights as indicated on 

the color wheel (dark blue indicates a direction of travel to the north and red travel to the south). Vertical 

radar images show target heights (colors do not indicate direction). The coastline is highlighted in white on 

the first horizontal image.
Great Lakes Avian Radar - Fall 2012 17

Figure 10. Sample Trackplots at Niagara County. Flight tracks during 1 hour increments recorded by horizontal (first and third columns) and vertical (second and fourth columns) radars during a migration event at 

the study site in Niagara County. Colors on the horizontal radar images show direction of flights as indicated 

on the color wheel (dark blue indicates a direction of travel to the north and red travel to the south). Vertical 

radar images show target heights (colors do not indicate direction). The coastline is highlighted in white on 

the first horizontal image.
18 Great Lakes Avian Radar - Fall 2016 

flights have mostly stopped, and flights appear 

clustered between 500 m and 750 m. A similar pattern 

is apparent at 4:00, with moderate southwestern flight 

activity concentrated around 600 m. At 5:00, activity 

has significantly dropped, directions are more mixed, 

and there is little altitudinal concentration. Sunrise was 

at 05:29 (EST) at this site on September 2. By noon, 

flight activity is sparse and directionally scattered, 

similar to the same time period the day before.

At the Wayne County site on August 28-29, another 

typical migration event was captured. The pattern is 

somewhat similar to the sequence from September 

1-2 in Jefferson County, however here the effect of the 

coastline can be seen. In daytime flights (12:00), several 

birds fly parallel to the coast in an east-west direction. 

The coastline runs approximately WNW to ESE, 

with the Lake in the top 1/3 of the image. At 18:00, 

traffic is still light, but most flights are to the east and 

southeast. At 20:00, activity increases dramatically, 

with targets near the coast flying east and targets 

south of the coast flying southeast. A directional 

shift is apparent at 23:00, with most targets flying 

south or southeast. Flight heights are generally low 

throughout this night, with concentration below 750 m. 

Southerly flights continue at 1:00, but targets are now 

concentrated between 750 and 1000 m above the radar. 

Activity decreased during the 4:00 and 5:00 hours, but 

still strongly directional to the south; the altitudinal 

concentration has dispersed. By noon, activity is again 

sparse and scattered.

The trackplot sequence for the Niagara County 

study site on October 22-23 shows another episode 

of nocturnal migration. Flight activity increases 

dramatically after nightfall (sunset at 17:19), then 

decreases through the early morning and returns 

to low levels by midday. Directionality of flights at 

the Niagara site was more heavily concentrated to 

the southeast on this night, which is approximately 

perpendicular to the coastline at this site. Some 

concentration of flights near the coastline in the NESW direction can be seen on the daytime images. 

Images from high-activity time periods during the 

night also illustrate the patterns of high and low 

detection on both horizontal and vertical radars. These 

patterns result from three different phenomena. First, 

both antennae have a blind spot immediately around 

the radar, out to a distance of about 300 m. This initial 

“main bang” is an area of high energy return that 

occurs close to the radar antenna, and is common to 

all radars. To prevent constant overwhelming returns 

from this region, it is masked (excluded from target 

tracking) on both HSR and VSR using site-specific 

clutter maps discussed earlier in this report (Figure 

4). Second, topographical features, vegetation, and 

other structures can also prevent target detection 

by blocking the radar signal along the line-of-sight 

between the radar and target. Because this ground 

clutter is typically stationary, it will prevent target 

detection in the same area on successive radar scans, 

resulting in distinct blind spots or “shadows,” which 

are particularly evident during times of high activity. 

These shadows can be seen as white areas on the 

clutter maps, for example forested hills to the west 

and south-southeast of the Jefferson radar, to the 

south of the Wayne radar, and to the east and west 

of the Niagara radar. Third, this particular radar 

system uses two different radio frequencies to detect 

targets at different distances. Maximum detection of 

birds and bats occurs at different distances from the 

radar depending on the specific frequency used. To 

increase target detection over a larger area, Merlin 

uses two different frequencies, one with maximum 

detection at about 500 m, the other with maximum 

detection at about 1000 m or more. To enable the use of 

both frequencies in the same scan, the radar receiver 

switches between listening for short-distance signal 

returns and long-distances signal returns in quick 

succession. This produces a circle (on HSR) or arc (on 

VSR) where the detection rate shifts from low to high, 

at about 1600 m and 1300 m from the HSR and VSR 

antennae, respectively.

Directional Trends

During the fall 2016 season, nocturnal target flight 

directions were mixed during the dawn, day, and 

dusk periods, but were predominantly oriented in a 

southern (southwest, south, or southeast) direction 

during nocturnal activity at all three sampled locations 

(Figures 11-13, Table 3). Night was the biological 

time period with the most flight activity, with target 

numbers (n, Table 3) substantially exceeding those 

of dawn, day and dusk combined. Mean direction of 

nocturnal flights was close to south (180°) for all three 

locations: 188°, 189°, and 193° for Jefferson, Wayne, 

and Niagara respectively. Angular concentration (r), 

which is close to one if targets are flying in the same 

direction and close to zero if they are flying in different 

directions, was highest at night for all three sites as 

well. In addition, most targets were flying in a similar 

direction (r ≥ 0.5) during about 75% of the night, 

whereas times of common directional movements were 

much more infrequent during other biological time 

periods. The common directionality and southward 

orientation of flight is strong evidence that much of the 

nocturnal activity observed is associated with longdistance migratory flights.
Photo Credit: B. Thompson

Great Lakes Avian Radar - Fall 2016 19

Figure 11. Direction of targets during Dawn, Day, Dusk, and Night at the Jefferson County site. Each point on 

the perimeter of the rose graph indicates the average number of targets per hour moving in each of the eight 

directions. Axis scale is fixed, so the area of polygons also represents the relative amount of target activity during 

that period.

Jefferson County
20 Great Lakes Avian Radar - Fall 2016 

Figure 12. Direction of targets during Dawn, Day, Dusk, and Night at the Wayne County site. Each point on 

the perimeter of the rose graph indicates the average number of targets per hour moving in each of the eight 

directions. Axis scale is fixed, so the area of polygons also represents the relative amount of target activity during 

that period.

Wayne County
Great Lakes Avian Radar - Fall 2016 21

Figure 13. Direction of targets during Dawn, Day, Dusk, and Night at the Niagara County site. Each point on 

the perimeter of the rose graph indicates the average number of targets per hour moving in each of the eight 

directions. Axis scale is fixed, so the area of polygons also represents the relative amount of target activity during 

that period.

Niagara County
22 Great Lakes Avian Radar - Fall 2016 

Table 3. Mean direction, angular concentration (r), and percent of biological time periods with strong directionality 

(r ≥ 0.5) of targets during biological time periods at our sites in New York. 

To visualize the direction and magnitude of migration 

movements each night, we plotted mean orientation 

angle and target count as lines on a map of the region 

(Figures 14-16). These lines approximate the origin 

of migrant targets, assuming that targets maintain 

a relatively constant heading throughout nighttime 

flights. Mean flight directions were highly variable at 

the Jefferson County site (Figure 14), but typically 

indicated origination from the northeast, north, or 

west. Heavy movement during late August and early 

September was observed both from the direction of 

the St. Lawrence River to the northeast, as well as 

from the north shore of Lake Ontario to the west. 

Several nights of “reverse migration” early in the 

season were observed at the Jefferson County site 

as well. Flights directly from the north were most 

frequent during the latest nights in mid to late 

October. At the Wayne County site (Figure 15), many 

of the flight directions throughout the first half of the 

season indicate flights over Lake Ontario, originating 

to the north or northwest of the radar location. A 

few large flights from the east and southwest were 

observed, and very little activity moving north from 

the Finger Lakes region was seen. At the Niagara 

County site (Figure 16), flight directions from many 

nights, especially late in the season, indicate flight 

over Lake Ontario. Several of the largest flights had 

average origination from the southeast or southwest.
Great Lakes Avian Radar - Fall 2016 23

Figure 14. Average direction of target origin, Jefferson County. The angle of each line represents the mean orientation of targets each night, approximating the direction of flight origination. The length of each line indicates the 

target count for one night, and the color of line indicates the date. 

Temporal Trends

Time Series. Hourly target counts provided by 

horizontal and vertical radars showed nightly pulses 

of elevated activity with peaks occurring a few hours 

before midnight at our study sites (Figures 17 – 19). 

Across our sampling period these events would often 

occur over a series of 2 to 3 nights at the beginning 

and end of the season (August and October), and 

more consistently, for periods of five consecutive 

days or more, during the middle of the season 

(September). At Jefferson and Wayne County sites, 

consistent nightly migration activity began in late 

August. In Jefferson County, the magnitude of 

pulses decreased in the second half of October, but 

at the Niagara County site, strong pulses continued 

to be observed into the end of October (data 

collection ended October 28). 

Nightly pulses in target counts on the vertical radar 

typically corresponded to pulses on the horizontal 

radar, although the vertical radar records far fewer 

targets overall, due to sample volume and detection 

differences discussed earlier. Even though the 

vertical and horizontal antennae are two parts of the 

same machine, their measurements are somewhat 

independent in that they observe mostly nonoverlapping volumes of air, especially when limiting 

the vertical scan to a standard front. To some extent, 

horizontal and vertical radars can each be used to 

support the other’s general observations regarding 

the amount of bird-sized targets moving at bird-like 

speeds through the airspace in the vicinity of the 

radar. 
24 Great Lakes Avian Radar - Fall 2016 

Figure 15. Average direction of target origin, Wayne County. The angle of each line represents the mean orientation 

of targets each night, approximating the direction of flight origination. The length of each line indicates the target 

count for one night, and the color of line indicates the date. 

The orientation of the vertical antenna affects the 

relationship between vertical radar target counts 

and horizontal radar target counts, especially during 

periods when flights directions are concentrated 

(r > 0). If the plane of the vertical radar aligns 

with the predominant direction of flight, targets 

flying to either side will be missed, but if the plane 

is perpendicular to the predominant direction of 

flight, most flights will intersect the sample volume. 

Horizontal radar detection rates are the same for all 

flight directions. When flight directions run parallel 

to the vertical radar, it is possible that the HSR will 

detect proportionately more targets than would be 

expected given activity observed on the VSR. For 

an example of this, see August 28, 18:00 at Wayne 

County (Figure 9). The vertical radar is oriented 

east-west, parallel to shore and orthogonal to the 

expected direction of migratory flights. Many of the 

HSR tracks run west-east, and only a few tracks 

show up on VSR.
Great Lakes Avian Radar - Fall 2016 25

Figure 16. Average direction of target origin, Niagara County. The angle of each line represents the mean 

orientation of targets each night, approximating the direction of flight origination. The length of each line indicates 

the target count for one night, and the color of line indicates the date. 
26 Great Lakes Avian Radar - Fall 2016 

Figure 17. Hourly target counts in Jefferson County by horizontal and vertical radars from August 4 – 

October 27, 2016 Jefferson County. Vertical lines represent midnight.

Hourly Counts by Horizontal and Vertical Radars in Jefferson County
Great Lakes Avian Radar - Fall 2016 27

Figure 18. Hourly target counts in Wayne County by horizontal and vertical radars from August 3 – 

September 10, 2016 in Wayne County. Vertical lines represent midnight. 

Hourly Counts by Horizontal and Vertical Radars in Wayne County
28 Great Lakes Avian Radar - Fall 2016 

Figure 19. Hourly target counts in Niagara County by horizontal and vertical radars from September 10 – 

October 28, 2016 in Niagara County. Vertical lines represent midnight. 

Hourly Counts by Horizontal and Vertical Radars in Niagara County
Great Lakes Avian Radar - Fall 2016 29

Target Passage Rate. The pattern of mean TPR 

during the four biological time periods was similar 

among the three study sites (Figure 20). Mean TPR 

at night was greater than the combined means of the 

other three biological time periods (Table 4). Mean 

nocturnal TPR in Jefferson County was 427± 439 

SD (n = 80 nights), 338 ± 263 SD (n= 39 nights) 

in Wayne County, and 412 ± 476 SD (n= 46 nights) 

at the Niagara County site. Mean TPR varied by 

hour with peak numbers reached during the 21:00, 

22:00 and 23:00 hours at Jefferson, Wayne, and 

Niagara sites, respectively. At all three locations, 

mean TPR decreased almost linearly after midnight, 

until leveling out at a low activity level around 6:00, 

which roughly corresponds with dawn (Figure 21). 

Variation between day and night TPR was greatest 

at Jefferson and Niagara sites, where peak TPR 

was higher than that of Wayne County and dropped 

to near zero during the day. Activity peaked earlier 

and faded earlier at Jefferson County than at 

Niagara, where the peak came later in the night and 

remained higher in the early morning. TPR at the 

Wayne site still showed a large difference between 

day and night, but the change was more moderate 

than the other two sites, with lower nightly peaks 

and substantial activity during the day.

Figure 20. Box plots of target passage rates (TPR) showing variability during four biological periods for fall 

2016 in Jefferson, Wayne, and Niagara Counties, New York. Whiskers extend to the minimum and maximum 

TPR. Boxes span from the 1st quartile to the 3rd quartile, with a line at the median. Blue diamonds are the 

seasonal mean for the biological period.

Table 4. Mean target passage rate (TPR) with standard deviations during four biological periods in New 

York during fall 2016.

Mean Target Passage Rate

Biological Period Jefferson Wayne Niagara

Dawn 36 ± 30 70 ± 63 67 ± 74

Day 14 ± 12 50 ± 24 14 ± 7

Dusk 10 ± 10 52 ± 31 18 ± 23

Night 427 ± 439 338 ± 263 413 ± 476
Weekly Mean of Target Passage Rates. At all three 

sites weekly means of nocturnal target passage 

rates were about 10 to 20 times higher than diurnal 

rates. Over the course of the season, weekly passage 

rates rose into October then declined in the second 

half of October (Figure 22). The lower TPR during 

the last week of October is likely due to a change in 

weather conditions, with lower temperatures and a 

mix of sleet and snow. 

Seven Day Moving Average. A seven-day moving 

average was used to smooth out daily variation, 

eliminate minor data gaps, and examine broader 

patterns in activity over the course of the season. After 

smoothing, patterns in nocturnal TPR are strikingly 

similar between Jefferson and the other two sites 

(Figure 23, top). Using seven-day average of nocturnal 

TPR, the temporal correlation between Jefferson and 

Wayne during the first half of the season was 0.91, 

and the correlation between Jefferson and Niagara 

during the second half of the season was 0.87 (versus 

the correlation of non-smoothed nightly TPR 0.87 

and 0.76 between Jefferson and Wayne, and Jefferson 

and Niagara, respectively). The overall seasonal rise 

and fall, as well as shorter-term peaks and dips in 

nocturnal activity are consistent between sites. TPR 

at Wayne and Jefferson match closely. Niagara’s 

numbers are generally lower than Jefferson, but nearly 

every increase and decrease is echoed, even though 

these sites are over 200 km apart. Diurnal patterns 

are less closely associated, although some increases 

and decreases are echoed between sites. Correlation 

between seven-day average TPR at Jefferson and 

Wayne was 0.04, and was 0.55 between Jefferson and 

Niagara (correlation of non-smoothed daily TPR 0.31 

and 0.49 between Jefferson and Wayne, and Jefferson 

and Niagara, respectively).

Nocturnal patterns at each site track much more 

closely with their counterpart radar site than with 

diurnal patterns at the site itself (Figures 23, 24). For 

example, nocturnal activity at Jefferson and Wayne 

Counties covary closely, but neither corresponds 

closely with its own diurnal activity rates. Niagara’s 

nocturnal rates reflect the general pattern in diurnal 

rates over the season, but individual peaks and lulls 

are more closely linked to nocturnal rates at Jefferson. 

To facilitate comparisons of daytime and nighttime 

passage rates given the large difference in activity 

levels (e.g., Figure 20), proportional passage rates, 

equaling each day’s target count as a proportion of the 

total target count for the season, within the biological 

period, were used. Correlation between daytime and 

nighttime proportional TPR was -0.24, -.031, and 0.82 

for Jefferson, Wayne, and Niagara, respectively.

Figure 21. Mean hourly target passage rate (TPR) during fall 2016 at sites in Jefferson, Wayne, and Niagara 

Counties, New York.

30 Great Lakes Avian Radar - Fall 2016 
Figure 22. Weekly mean of nocturnal and diurnal target passage rates (targets/km/hr) in Jefferson (top row), 

Wayne (middle row) and Niagara (bottom row) counties from August to October, 2016. Error bars represent 

one standard deviation. Note different scales on nocturnal and diurnal plots.

Jefferson County

Wayne County

Niagara County

Great Lakes Avian Radar - Fall 2016 31
32 Great Lakes Avian Radar - Fall 2016

Figure 23. Seven-day moving mean TPR for nocturnal (top) and diurnal (bottom) target passage trends 

during fall 2016 in Jefferson, Wayne, and Niagara County radar sites. 
Figure 24. Proportional diurnal and nocturnal seven-day moving means at Jefferson (top), Wayne (middle), 

and Niagara (bottom) sites, New York during fall 2016. Proportions (single day or night target count divided 

by the sum of day or night target counts for the entire season) are used rather than TPR to account for the 

large difference between nocturnal and diurnal flight intensity, allowing comparisons between daytime and 

nighttime relative activity levels over the course of the season.

Great Lakes Avian Radar - Fall 2016 33

Altitudinal Trends

At all three sites, targets were observed within 

the entire range of altitude bands sampled. Mean 

altitude of nocturnal targets was 779 m ± 481 m SD 

at Jefferson County, 521 m ± 437 m SD at Wayne 

County, and 675 m ± 520 m SD at Niagara County. 

Median altitude at night was 644 m, 385 m, and 

508 m above ground level at the Jefferson, Wayne, 

and Niagara sites, respectively. All three sites had 

their highest median flight heights during night and 

dawn, and lowest flight heights during the day or 

dusk. 

Activity at the Jefferson site was low during dawn, 

day, and dusk, but flight heights during these 

periods were bimodal, with highest concentrations 

at about 100 m and 400 m for all three periods 

(Figure 25). Flight heights during the highly active 

night period also showed high concentrations at 100 

m and 400 m, but there was also substantial activity 

at much higher elevations, including above 2000 

m. This is reflected in the higher mean and median 

flight heights at this site (Table 5). Relatively high 

target detection rates during non-night periods at 

the Wayne County site are reflected in the altitude 

profiles as well (Figure 26). Unlike Jefferson and 

Niagara, the flight height profiles at Wayne are 

relatively consistent among biological periods, 

with little increase in heights during the night, and 

median heights for all periods under 400 m. Flight 

heights at Niagara are similar to those of Jefferson 

in that the high-activity night period had a higherelevation distribution of flights (Figure 27). 

Mean altitude per hour during the season showed 

a similar pattern at all three locations (Figure 
34 Great Lakes Avian Radar - Fall 2016

37). Mean altitude was lowest during the daytime, 

increased during the dusk hour (blue boxes are 

hours that contained dusk during the season) until 

reaching a maximum 1-3 hours before midnight, and 

decreased following midnight. A temporary increase 

in mean altitude occurred during the dawn hours of 

05:00 – 06:00 (orange boxes) at all three sites.

Whereas many radar reports include estimates of 

mean and median altitude of targets, we found that 

these estimates were poor indicators of maximum 

density (Table 5) due to the difference in volume of 

sampled air space at various altitude bands. The 

altitude profile graphs in Figures 25–27 display the 

limitations of both mean and median in representing 

typical flight heights, especially with uncorrected 

density estimates. To provide more realistic 

estimates of activity at various heights, we corrected 

VSR data for volume sample bias resulting from 

large differences in the volume of sampled airspace 

at different altitudes. Targets were classified by 

50-meter altitude band according to observed height 

above ground level. Each band is a horizontal slice of 

the scanned airspaces that has a unique volume, as 

the 3-dimensional shape of the radar beam changes 

with height. We estimated the volume of each band 

via Monte Carlo simulation (see Figures 6 and 7) and 

calculated a volume-corrected density estimate that 

accounted for the geometric shape of the sample 

volume. This correction resulted in a substantially 

different density estimate than one assuming an 

equal amount of sample volume per altitude band 

(e.g., Figures 25-27). The altitude band with the 

highest density during each biological period is 

reported as Max Density Band in Table 5. The Max 

Density Band was consistently lower than mean and 

median flight heights, indicating concentration of 

activity at lower altitudes than would otherwise be 

apparent from summary statistics, and was often at 

altitudes near or within the rotor-swept zone. 

Table 5. Altitude summary statistics. Comparison of mean altitude (m) with standard deviations, median 

altitude, and 50 m altitude band that contained the maximum target density during four biological periods at 

our sites in Jefferson, Wayne, and Niagara Counties during fall 2016. Max band density values represent the 

top of the altitude band.

Jefferson Wayne

Biological 

Period

Mean ± 

SD Median

Max

Density

Band

Mean ± 

SD Median

Max 

Density 

Band 

Dawn 637 ± 429 522 400 535 ± 460 376 300

Day 501 ± 410 388 100 386 ± 371 288 250

Dusk 675 ± 540 440 400 349 ± 373 241 200

Night 779 ± 481 644 350 521 ± 437 385 200

Niagara

Biological 

Period

Mean ±

SD Median

Max 

Density 

Band 

Dawn 630 ± 524 494 100

Day 373 ± 481 188 100

Dusk 365 ± 407 258 100

Night 675 ± 520 508 150
Figure 25. Altitude profile of targets at Jefferson County. Corrected lines depict target density 

(targets/1,000,000 m3) within each 50-m altitude band per hour after adjusting for the sample volume within 

the band. Uncorrected lines depict target density per 50-m altitude band per hour without adjusting for 

volume (i.e., under the assumption that each band’s volume is equal to the total volume divided by the 

number of bands). Shaded area represents the rotor swept zone (RSZ) between 30 - 200 m. Y-axis labels 

represent the top of the altitude band.

Great Lakes Avian Radar - Fall 2016 35

Altitude Profile, Jefferson
Figure 26. Altitude profile of targets at Wayne County. Corrected lines depict target density 

(targets/1,000,000 m3) within each 50-m altitude band per hour after adjusting for the sample volume within 

the band. Uncorrected lines depict target density per 50-m altitude band per hour without adjusting for 

volume (i.e., under the assumption that each band’s volume is equal to the total volume divided by the 

number of bands). Shaded area represents the rotor swept zone (RSZ) between 30 - 200 m. Y-axis labels 

represent the top of the altitude band.

36 Great Lakes Avian Radar - Fall 2016 

Altitude Profile, Wayne
Great Lakes Avian Radar - Fall 2016 37

Figure 27. Altitude profile of targets at Niagara County. Corrected lines depict target density 

(targets/1,000,000 m3) within each 50-m altitude band per hour after adjusting for the sample volume within 

the band. Uncorrected lines depict target density per 50-m altitude band per hour without adjusting for 

volume (i.e., under the assumption that each band’s volume is equal to the total volume divided by the 

number of bands). Shaded area represents the rotor swept zone (RSZ) between 30 - 200 m. Y-axis labels 

represent the top of the altitude band.

Altitude Profile, Niagara
Figure 28. A sample of hourly altitude profiles in Jefferson County, corrected for the shape of the sample 

volume from October 3 – 4, 2016. The x-axis represents target density. The red line represents the top of the 

rotor swept zone from 150 m to 200 m. Y-axis labels represent the top of the altitude band.

38 Great Lakes Avian Radar - Fall 2016 

Hourly Variation in Altitude Profiles October 3-4, 2016, Jefferson County
Figure 29. A sample of hourly altitude profiles in Wayne County, corrected for the shape of the sample 

volume From August 27 – 28, 2016. The x-axis represents target density. The red line represents the top of 

the rotor swept zone from 150 m to 200 m. Y-axis labels represent the top of the altitude band.

Great Lakes Avian Radar - Fall 2012 36

Hourly Variation in Altitude Profiles August 27-28, 2016, Wayne County
40 Great Lakes Avian Radar - Fall 2016 

Figure 30. A sample of hourly altitude profiles in Niagara County, corrected for the shape of the sample 

volume on October 8 – 9, 2016. The x-axis represents target density. The red line represents the top of the 

rotor swept zone from 150 m to 200 m. Y-axis labels represent the top of the altitude band.

Hourly Variation in Altitude Profiles October 8-9, 2016, Niagara County
Great Lakes Avian Radar - Fall 2016 41

Figure 31. Altitude profile of corrected target density below 500 m in Jefferson, Wayne, and Niagara 

Counties, New York. The x-axis represents target density (targets/1,000,000 m3) per 50-m altitude band. 

Y-axis labels represent the top of the altitude band.

Jefferson County Low-Altitude Profile

Wayne County Low-Altitude Profile

Niagara County Low-Altitude Profile
42 Great Lakes Avian Radar - Fall 2016 

Figure 32. Maximum density by night. Percent of nights when the maximum density (targets/1,000,000 m3/ 

altitude band) or count (targets/altitude band) occurred within 50-m altitude bands in Jefferson, Wayne, and 

Niagara County study sites during fall 2016. X-axis labels represent the top of the altitude band.
Figure 33. Maximum density by night hour. Percent of night hours (20:00 – 04:00) when the maximum density 

(targets/1,000,000 m3/ altitude band) or count (targets/altitude band) occurred within 50-m altitude bands 

in Jefferson, Wayne, and Niagara Counties during fall 2016. X-axis labels represent the top of the altitude 

band. 

Great Lakes Avian Radar - Fall 2016 43
Figure 34. Heatmap for Jefferson County, representing variation in flight altitudes based on target density 

(targets per million cubic m). Altitude bands are in meters and labels represent the max value of each 

altitude band. Density of targets is in targets per million cubic meters. Colors shown in each rectangle 

indicate the relative density observed for that altitude (key shown on the right) and time. The dark blue and 

light blue lines represent the nocturnal mean and median target heights, respectively. The black line at 200 

m represents the max height of a turbine with a RSZ of 30 – 200 m. Note the difference in density scale used 

in Figures 35 and 36. Some of the lack of low-altitude activity at this site may be attributable to relatively 

high clutter on the vertical antenna, which can be seen as white areas on the clutter map in Figure 4. 

44 Great Lakes Avian Radar - Fall 2016 
Figure 35. Heatmap for Wanye County, representing variation in flight altitudes based on target density 

(targets per million cubic m). Altitude bands are in meters and labels represent the max value of each 

altitude band. Density of targets is in targets per million cubic meters. Colors shown in each rectangle 

indicate the relative density observed for that altitude (key shown on the right) and time. The dark blue and 

light blue lines represent the nocturnal mean and median target heights, respectively. The black line at 200 

m represents the max height of a turbine with a RSZ of 30 – 200 m. Note the difference in density scale used 

in Figures 34 and 36. 

Great Lakes Avian Radar - Fall 2016 45
46 Great Lakes Avian Radar - Fall 2016 

Figure 36. Heatmap for Niagara County, representing variation in flight altitudes based on target density 

(targets per million cubic m). Altitude bands are in meters and labels represent the max value of each 

altitude band. Density of targets is in targets per million cubic meters. Colors shown in each rectangle 

indicate the relative density observed for that altitude (key shown on the right) and time. The dark blue and 

light blue lines represent the nocturnal mean and median target heights, respectively. The black line at 200 

m represents the max height of a turbine with a RSZ of 30 – 200 m. Note the difference in density scale used 

in Figures 34 and 35. 
Great Lakes Avian Radar - Fall 2016 47

Figure 37. Mean hourly target height (m) during fall 2016 in Jefferson, Wayne, and Niagara Counties New 

York. Orange and blue markers indicate the hours in which sunrise and sunset occurred during the season, 

respectively. Error bars represent one standard deviation.
48 Great Lakes Avian Radar - Fall 2016 

Discussion

We undertook this study to document migration along 

the shorelines of the Great Lakes. What we found 

indicates migration movements were common along 

the southern and eastern shorelines of Lake Ontario 

where we established our study sites. We believe that 

some aspects of data collected at these three sites 

are representative of migration along the rest of the 

Lake Ontario shorelines. Our research contributes 

to a growing body of literature that documents 

various aspects of migration and identifies Great 

Lake shorelines as areas important for conservation 

of migratory species. Our data provide unique 

observations about the magnitude, timing, and altitude 

of nocturnal migration that could not be observed 

without the aid of radar.

Sampling Regime 

Sampling regime is an important consideration for 

migration studies. Migratory movements are guided, 

in part, by environmental conditions and occur in 

pulses across the migratory season (Alerstam 1990). 

Our continuous sampling scheme captured the timing 

of migration events and provided a more complete 

picture of the migratory season than an intermittent 

systematic (e.g., once per week) or random sampling 

scheme, which may result in missing pulses of activity 

(Figure 38). Monitoring during both day and night is 

important as well. We used diurnal radar observations 

to provide a baseline for comparing nocturnal activity 

and including this time period in the sampling 

scheme helped to determine the relative magnitude 

of nocturnal migration events (Figures 17-19). Our 

sampling regime was also useful in showing when 

major migration pulses began in early August, but 

ending data collection in late October may have been 

too early to capture all the migratory pulses at the end 

of the 2016 migration. As more data are collected we 

will be able to better describe the migration season and 

how it varies with location and year. This information 

will help to tailor conservation efforts to appropriate 

time frames. 

Target Counts

Target counts provided by radar are influenced 

by radar type, calibration, filtering of clutter and 

non-biological targets, count algorithms, frequency 

band, antenna orientation, sampling scheme, and 

how researchers account for variation in detection 

probability and sample volume (Bruderer 1997, 

Harmata et al. 1999, Schmaljohann et al. 2008). Even 

when the same equipment and methodology are 

used among sites or studies, comparisons should be 

made cautiously if the probability of detection and 

sampling volume are ignored (Schmaljohan et al. 2008). 

Recognizing that our counts represent indices of target 

passage relative to specific sites, we are cautious about 

making comparisons among sites or studies. Rather 

than relying solely on the magnitude of target passage 

as an indication of migration, we assess the patterns of 

activity among sites to compare the relative strength 

of migration. For example, a site with a nocturnal 

passage rate having peaks multiple times larger than 

lulls for the majority of the sampling period would be 

considered to have more migration activity than a site 

with less of a discrepancy between nocturnal peaks and 

lulls or a site that had a nocturnal passage rate that 

only occasionally spiked above a baseline of nocturnal 

passage rates.
Great Lakes Avian Radar - Fall 2016 49

Figure 38. Results of hypothetical non-continuous sampling schedule where data were collected on a 

continuous sampling schedule (top graphic) versus a weekly sampling schedule (bottom graphic). Red 

lines represent the number of targets counted per hour by the vertical scanning radar in October 2016 in 

Jefferson County, New York.

Migration Patterns

Patterns of movement we recorded were consistent 

with other observations of migration (Newton 2008, 

Bowden et al. 2015, Horton et al. 2016, Rathbun 

et al. 2016a, Rathbun et al. 2016b, Rathbun et al. 

2016c) and indicated that nocturnal migratory 

flights occurred regularly during fall 2016 at all 

three of our surveyed locations. The nocturnal 

activity we observed was typically oriented in a 

southern direction (Figures 11-13) and occurred 

in nightly pulses across the season that were 

captured by horizontal and vertical radars (Figures 

8 - 10). We observed targets in the vicinity of the 

shoreline flying parallel to shore during daylight, 

and then shifting to southbound flight after dark 

(e.g., Figure 9, Wayne County, August 28th). Target 

passage rates were about 10 times higher during 

night (between 30 minutes after sunset and 30 

minutes before sunrise) than during dawn, dusk, 

or day at all three locations (Table 4, Figure 20). 

Mean hourly heights showed a pattern previously 

associated with migration (Harmata et al. 2000, 

Mabee and Cooper 2004) in which heights increase 

near dusk, peak a few hours before midnight, and 

begin to decrease prior to dawn (Figure 37). The 

slight increase in mean height near dawn at the 

three sites is consistent with a migratory behavior 

described as dawn ascent (Myres 1964, Diehl et 

al. 2003). This behavior is attributed to migrants 

increasing altitude to gain a broader view of the 

surrounding landscape before selecting stopover 

habitat or returning to the shoreline if they were 

flying over water. Taken together, we attribute these 

nocturnal observations to migrants and suggest that 

the shorelines we studied are important for their 

conservation.

Large migratory flights occurred regularly 

on successive nights during peak migration in 

September and early October. At these times, 

migration pulses occurred most nights, with 

occasional lulls in activity, and lulls tended to occur 

at the same times at both radar sites (Jefferson 

coinciding with Wayne in the first half of the season, 

and Jefferson coinciding with Niagara during the 
50 Great Lakes Avian Radar - Fall 2016

second half of the season). Migratory pulses outside 

of peak migration were more sporadic, but also 

generally occurred on the same nights at Jefferson 

and the corresponding site, both early and late in 

the season (at Wayne and Niagara respectively). 

Migratory flight intensity, as measured by mean 

target passage rate, was highly correlated among 

nights (correlation of 0.87 between Jefferson and 

Wayne, and 0.76 between Jefferson and Niagara), 

but not as much among days (correlations of 0.31 

and 0.49 respectively). Additionally, nocturnal 

migration was much more closely related to night 

time flight intensity at the other site than to daytime 

flight intensity at the same site. As seen in Figure 

23, broader trends were also similar between 

Jefferson and the other site during the night and 

less so during the day. 

Contemporaneous rapid increases in flight activity 

after sunset may suggest broad front migration 

events in response to regional environmental factors 

such as the movement of weather fronts, or variation 

in timing among guilds of migrants, or a combination 

of these and other factors (Newton 2008). The close 

relationship between migration patterns at distant 

locations could indicate that further investigation 

into their cause would allow prediction of high 

migration events. 

Flight Altitude

Altitude profiles indicated that there was activity 

well above 1 km, particularly during the night; 

however, most targets passed below 1 km with 

peak density typically below 600 m (Figures 25-

27). Maximum target densities occurred more 

frequently at the lower elevations, with most 

common peak densities falling between 100 m and 

400 m among night and nocturnal hours (Figures 

32 and 33). We corrected for the approximate shape 

of the survey volume and included this correction 

in our density estimates. This correction is based 

on the manufacturer’s estimate of beam geometry, 

which may not be precise, and beam propagation 

is not consistent over time. Beam propagation is 

affected by side lobes (arc-shaped static return 

patterns resulting from unpredictable reflections 

off the surrounding landscape), target size and 

distance, and atmospheric conditions. Nonetheless, 

we think the correction was an improvement over 

altitude profiles that ignore beam geometry and 

sampling effort. We were not able to correct for 

variation in detection rates with distance from 

the radar (Schmaljohann et al. 2008); in addition, 

detection on our vertical scanning radars decreased 

significantly at a range of about 1,600 m where the 

radar transitioned from short to medium pulse. For 

these reasons, our estimates likely under-represent 

density as altitude increases. However, we observed 

densities decreasing well before the 1,600 m band 

(Figures 25- 27), so this undercounting is unlikely to 

change the overall picture.

Altitude profiles varied considerably among 

nocturnal hours at our sites in Jefferson, Wayne, 

and Niagara Counties (Figures 28-30). Migrants 

adjust flight altitude with wind direction and 

speed, visibility, time, and the landscape below 

flight trajectory (Alerstam 1990, Hueppop et al. 

2006, Liechti 2006). For example, head winds aloft 

have resulted in migrants moving en masse to 

lower altitudes where wind speeds were reduced 

(Gauthreaux 1991). Also, migrants ascend and 

descend between land and migration flight heights 

during each flight, and changes in flight altitude can 

occur at various times within each leg of a migratory 

flight. Depending on location, these altitude changes 

may place migrants at risk of collision with wind 

turbines and other tall anthropogenic structures 

multiple times every night. 

Radar Study and Management Considerations

Whereas radar may be the best tool available for 

gathering large amounts of data on nocturnal 

migration, the interpretation of radar data can be 

challenging. Marine radar is the most common 

type used to track bird and bat movements (Larkin 

2005) and its use to assess risk will likely increase 

with wind energy development. Unlike largerscale systems such as NEXRAD weather radar, 

the sample volume of mobile marine radar units 

overlap wind turbine rotor-swept zones (30 to 200 m 

above ground) across much of their detection range. 

Despite the trend of increasing use of marine radar 

for impact assessment, standardized equipment and 

methodology for establishing radar settings, and 

collecting and processing radar data have not been 

adopted. These considerations can substantially 

affect the quality of data. This presents a challenge 

that is not easily solved. However, without 

standards, comparisons among studies may be more 

reflective of changes in equipment, methodology, 

and site conditions rather than in differences in 

migration activity among sites. 

Additionally, metrics reported in radar surveys can 

be misleading to someone unfamiliar with avian 

radar. For example, mean altitude of target passage 

is often reported to be above the rotor swept zone 

and has been interpreted as indication of low risk. 

However, mean altitude can be well above the rotor 

swept zone even when there is a high rate of target 

passage within the rotor swept zone. This is due to 

the long range at which radars collect altitude data, 

up to 3 km above ground level in our study, where 

high flying targets inflate the mean altitude. This 

skew is apparent in our data and can be seen by 

comparing the mean altitude of nocturnal targets to 
Great Lakes Avian Radar - Fall 2016 51

the most densely populated altitude band (Table 5, 

Figures 34 - 36). It is also misleading to compare the 

percent of targets below and above the height of the 

rotor swept zone without addressing the inherent 

difference in radar sampling effort at various 

altitude bands. Within our sampling framework, 

there are three 50-m altitude bands below 200 m (an 

estimate for the height of the rotor swept zone) and 

53 altitude bands above 200 m. Based on our model, 

we estimated that about 2 percent of the survey 

volume is below 200 m. Given that information, we 

would expect a small percentage of targets to be 

recorded at or below the rotor swept zone. This 

indicates only low detection, not low risk.

When examining general migration patterns, high 

nighttime migrant activity was documented at our 

three Lake Ontario radar sites. This is evident 

from our Trackplots (Figures 8-10), the time series 

plots from each site (Figures 17-19) and high 

target passage rates (Figures 20– 22 and Table 4). 

Densities of nighttime targets within a 30 – 200 m 

rotor swept zone were also high, when compared 

to the dawn, day and dusk time periods (Figures 

25-27). Throughout the migration season, nocturnal 

targets were recorded flying both across the lake 

and along the shorelines (Figures 14-16). The 

combination of these behaviors indicates that high 

numbers of night time migrants may be at risk of 

collision with wind turbines, communication towers 

or other tall structures placed along the shorelines 

of Lake Ontario. 

While target passage rate and target density is 

lower during the dawn, day, and dusk time periods, 

migrants may be at risk of collision during these 

time periods as well. Targets were recorded flying 

along the lakeshore, flying out over the lake from 

shore, and returning to shore from over the lake 

during these time periods, indicating the Lake 

Ontario shoreline is used by migrants during all 

times of the day and the migration season, providing 

flightpaths and stopover habitat. 

Conclusions

In this report, we provide examples of methodology 

and analyses that we find helpful in interpreting 

radar data. We suggest the relative change in counts 

at a single site indicates the level of migration 

activity and this is a better indicator than comparing 

the magnitude of counts among studies. Careful 

attention should be given to how these indices 

fluctuate over fine temporal scales, such as hourly, 

as opposed to monthly or seasonal summaries. The 

clutter maps we include provided information about 

our ability to detect targets at various altitudes 

and we think it is important, particularly for risk 

assessment, that radar operators address their 

ability to detect targets at low altitude. We provide 

a concept for a method to account for the structure 

of the sample volume that, while not without 

limitations, provided a partial solution rather than 

ignoring the biases associated with sampling effort. 

Overall, we found that radar provided insight 

into nocturnal migration that would otherwise 

be unattainable and we think that its continued 

development and careful interpretation will result 

in valuable contributions to the management and 

conservation of migrating birds and bats.

The results of our research highlight the potential 

role of radar in implementing recommendations 

from the wind energy guidelines (USFWS 2012) 

to identify areas where impacts to wildlife would 

be minimized. We documented clear examples of 

migrant activity around Lake Ontario at our study 

sites in Jefferson, Wayne, and Niagara Counties, and 

the density of targets at lower altitudes is a concern. 

An additional concern is that turbine height and 

blade length continues to grow, with that the rotor 

swept zone is growing as well, creating larger areas 

of flight risk for birds and bats passing through an 

area. The data we collected may be of interest to 

public and private entities that are involved with 

wind energy development and potential placement 

of turbines in the Great Lakes region. Coupling 

avian radar systems with other forms of research 

or using radar in conjunction with post construction 

fatality searches may broaden the utility of its use in 

making risk assessments and assessing wind energy 

developments. 
52 Great Lakes Avian Radar - Fall 2016 

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Great Lakes Avian Radar - Fall 2016 57

Appendices

Appendix 1: Fall 2016 Report Summary

Appendix 2: Percent Land Cover Associated with Study Sites 

Appendix 3: Corrected Density per Hour by Biological Period

Appendix 4: Comparison of Static and Corrected Density Estimates
Appendix 1

Fall 2016 Report Summary

n Migration occurred on the southern shoreline, and on the eastern end of Lake Ontario during fall 2016 

	 •	Migration is identified by general direction of movement (southwards) at night, high target

 passage rate, and nighttime peaks

	 •	Patterns and timing of migration were similar between the sites

	 	 	 • 	Consistent waves of migration with high concentrations of migrants in late August,

 throughout September, and during the first half of October occurred at both radar units 

 (one unit switched sites on September 10)

	 	 	 •	Waves of migration also occurred early August and late October, at Jefferson and Wayne,

 and Jefferson and Niagara, respectively; however, nightly pulses were less consistent and 

 of lesser magnitude than those in the middle of the season. 

n General date range of pulses that occurred during the migration season

	 •	Jefferson County, New York (field season August 4 – October 27)

	 	 	 •	August 26 - September 2

	 	 	 •	September 9 - 26

	 	 	 •	September 29 - October 5

	 •	Wayne County, New York (field season August 3 – September 10)

	 	 	 •	August 27 - 30

	 	 	 •	September 3 - 10

	 •	Niagara County, New York (field season September 10 – October 28)

	 	 	 •	August 15 - 16

	 	 	 •	October 9 - 10

	 	 	 •	October 19 - 20

n Patterns of activity were different between Dawn, Day, Dusk, and Night time periods

	 •	Nocturnal movement south:

	 	 	 •	Flight directions were oriented south, southeast, or southwest more frequently than

 random (37.5% expected with no directionality). 

	 	 	 	 	 •	 64% of nights surveyed the mean direction of travel was generally southerly

 at Jefferson County, New York

	 	 	 	 	 •	 52% of nights surveyed the mean direction of travel was generally southerly

 at Wayne County, New York 

	 	 	 	 	 •	 56% of nights surveyed the mean direction of travel was generally southerly at

 Niagara County, New York

58 Great Lakes Avian Radar - Fall 2016 
 

	 •	Flights influenced by shoreline

	 	 	 •	Longshore flights observed at near-coast study sites (Wayne and Niagara)

	 	 	 •	Heavy concentration of nocturnal flights to the south at all three sites, with strong

 southwest component at Jefferson and Wayne

	 	 	 •	At dawn, flights at shoreline sites (Wayne and Niagara) remained oriented to the south

 while flights at inland site (Jefferson) were more uniform (non-directional)

	 •	Movement concentrated at night

	 	 	 •	Target passage rates increased dramatically at night, compared to day, dawn,

 and dusk periods 

	 •	Dawn ascent

	 	 	 •	Increase in height around dawn hours observed at all three sites

n Peak density of targets in volume-corrected counts

	 •	Max density below 400 m 92% of nights and 54% of night hours at Jefferson County, New York

	 •	Max density below 300 m 100% of nights and 86% of night hours at Wayne County, New York

	 •	Max density below 300 m 94% of nights and 72% of night hours at Niagara County, New York

n Standards for radar studies need to be established and recommendations are included in this report

	 •	Using radar counts as an index of activity and not a population estimate

	 •	Surveying continuously over the whole migration season

	 •	Examining smaller time periods (Dawn/Day/Dusk/Night or hourly) in addition to seasonal metrics

	 •	Using volume-corrected counts on the vertical radar to better estimate use of low altitudes

 and the rotor swept zone

	 •	Using 50-m altitude bands to represent height distributions rather than mean or median heights

	 •	Examining the most densely populated altitude bands rather than comparing numbers or

 percentages of targets below, within, and above the rotor swept zone

	 •	Recognizing that migrants change altitude for various reasons over time (for example, due to wind,

 weather, topography, and time of day) and that targets flying well above the rotor swept zone 

 may still be at risk.

Great Lakes Avian Radar - Fall 2016 59
Appendix 2

Percent Land Cover Associated with Study Sites from the 

2011 National Land Cover Database

National Land Cover Class

Jefferson Wayne Niagara

% of Land Cover % of Land Cover % of Land Cover

Barren Land 0.13% 0.00% 0.00%

Cultivated Crops 16.61% 20.67% 0.93%

Deciduous Forest 21.20% 10.26% 13.60%

Developed* 4.84% 2.99% 3.84%

Evergreen Forest 2.39% 0.15% 0.74%

Hay/Pasture 43.53% 26.02% 38.31%

Herbaceous 3.46% 0.04% 0.02%

Mixed Forest 0.71% 0.18% 3.38%

Open Water 0.27% 31.68% 34.70%

Shrub/Scrub 1.49% 0.12% 0.52%

Wetlands** 5.37% 7.88% 3.97%

* Includes low, medium and high intensity development and developed open space.

** Includes woody and emergent herbaceous wetlands.

Percent land cover found within 3.7 km of radar locations in Jefferson, Wayne, 

 and Niagara Counties, New York.

Classification Description for the 2011 National Land Cover Database 

(http://www.mrlc.gov/nlcd2011.php).

60 Great Lakes Avian Radar - Fall 2016

Water

Open Water - areas of open water, generally with less than 25% cover of vegetation or soil.

Perennial Ice/Snow - area characterized by a perennial cover of ice and/or snow, generally 

greater than 25% of total cover.

Developed

Developed, Open Space - areas with a mixture of some constructed materials, but mostly 

vegetation in the form of lawn grasses. Impervious surfaces account for less than 20% of total 

cover, These areas most commonly include large-lot single family housing units, parks, golf 

courses, and vegetation planted in developed settings for recreation, erosion control, or aesthetic purposes.

Developed, Low Intensity - areas with a mixture of constructed materials and vegetation. 

Impervious surfaces account for 20% to 49% percent of total cover. These areas most commonly 

include single-family housing units.

Developed, Medium Intensity - areas with a mixture of constructed materials and vegetation. 

Impervious surfaces account for 50% to 79% of total cover. These areas most commonly include 

single-family housing units.

Developed, High Intesity - highly developed areas where people reside or work in high 

numbers. Examples include apartment complexes, row houses and commercial/industrial. 

Impervious surfaces account for 80% to 100% of the total cover.

Classification Description
(Appendix 2 continued)

Great Lakes Avian Radar - Fall 2016 61

Barren

Barren Land (Rock/Sand/Clay) - areas of bedrock, desert pavement, scarps, talus, slides, 

volcanic material, glacial debris, sand dunes, strip mines, gravel pits and other accumulations of 

earthen material. Generally, vegetation accounts for less than 15% of total cover.

Forest

Deciduous Forest - areas dominated by trees generally greater than 5 meters tall, and greater 

than 20% of total vegetation cover. More than 75% of the tree species shed foliage 

simultaneously in response to seasonal change.

Evergreen Forest - areas dominated by trees generally greater than 5 meters tall, and greater 

than 20% of total vegetation cover. More than 75% of the tree species maintain their leaves all 

year. Canopy is never without green foliage.

Mixed Forest - areas dominated by trees generally greater than 5 meters tall, and greater than 

20% of total vegetation cover. Neither deciduous nor evergreen species are greater than 75% of 

total tree cover.

Shrubland

Dwarf Scrub - Alaska only areas dominated by shrubs less than 20 centimeters tall with shrub 

canopy typically greater than 20% of total vegetation. This type is often co-associated with 

grasses, sedges, herbs, and non-vascular vegetation.

Shrub/Scrub - areas dominated by shrubs; less than 5 meters tall with shrub canopy typically 

greater than 20% of total vegetation. This class includes true shrubs, young trees in an early 

successional stage or trees stunted from environmental conditions.

Herbaceous

Grassland/Herbaceous - areas dominated by gramanoid or herbaceous vegetation, generally 

greater than 80% of total vegetation. These areas are not subject to intensive management such 

as tilling, but can be utilized for grazing.

Sedge/Herbaceous - Alaska only areas dominated by sedges and forbs, generally greater than 

80% of total vegetation. This type can occur with significant other grasses or other grass like 

plants, and includes sedge tundra, and sedge tussock tundra.

Lichens - Alaska only areas dominated by fruticose or foliose lichens generally greater than 

80% of total vegetation.

Moss - Alaska only areas dominated by mosses, generally greater than 80% of total vegetation.

Planted/Cultivated

Pasture/Hay – areas of grasses, legumes, or grass-legume mixtures planted for livestock 

grazing or the production of seed or hay crops, typically on a perennial cycle. Pasture/hay 

vegetation accounts for greater than 20% of total vegetation.

Cultivated Crops – areas used for the production of annual crops, such as corn, soybeans, 

vegetables, tobacco, and cotton, and also perennial woody crops such as orchards and vineyards. 

Crop vegetation accounts for greater than 20% of total vegetation. This class also includes all 

land being actively tilled.

Wetlands

Woody Wetlands - areas where forest or shrubland vegetation accounts for greater than 20% of

vegetative cover and the soil or substrate is periodically saturated with or covered with water.

Emergent Herbaceous Wetlands - Areas where perennial herbaceous vegetation accounts for 

greater than 80% of vegetative cover and the soil or substrate is periodically saturated with or 

covered with water.
Appendix 3

Corrected Density per Hour by Biological Period

Jefferson

Altitude Band Dawn Day Dusk Night

50 0.0 0.0 0.0 0.0

100 0.3 0.2 0.1 0.8

150 0.1 0.1 0.0 0.4

200 0.1 0.0 0.0 0.6

250 0.1 0.1 0.1 1.4

300 0.2 0.1 0.1 2.5

350 0.3 0.2 0.1 3.0

400 0.4 0.2 0.1 2.9

450 0.3 0.1 0.1 2.4

500 0.1 0.1 0.0 2.0

550 0.1 0.0 0.0 1.8

600 0.1 0.0 0.0 1.7

650 0.1 0.0 0.0 1.5

700 0.1 0.0 0.0 1.3

750 0.1 0.0 0.0 1.1

800 0.1 0.0 0.0 0.9

850 0.1 0.0 0.0 0.8

900 0.1 0.0 0.0 0.6

950 0.0 0.0 0.0 0.5

1000 0.0 0.0 0.0 0.4

Wayne

Altitude Band Dawn Day Dusk Night

50 0.0 0.0 0.0 0.0

100 0.8 0.6 0.7 2.1

150 0.9 0.6 1.0 4.5

200 0.7 0.7 1.4 5.0

250 0.9 0.9 1.3 4.3

300 0.9 0.7 0.8 3.3

350 0.8 0.6 0.6 2.7

400 0.6 0.4 0.3 2.2

450 0.4 0.2 0.2 1.8

500 0.3 0.2 0.1 1.5

550 0.2 0.1 0.1 1.3

600 0.2 0.1 0.0 1.1

650 0.2 0.0 0.0 0.8

700 0.2 0.0 0.0 0.6

750 0.1 0.0 0.0 0.5

800 0.1 0.0 0.0 0.4

850 0.1 0.0 0.0 0.4

900 0.1 0.0 0.0 0.3

950 0.0 0.0 0.0 0.2

1000 0.0 0.0 0.0 0.1

Estimated density of targets by altitude band during 

spring biological time periods (dawn, day, dusk, night) 

in New York (targets/1,000,000 m3/hour). 

Estimated density of targets by altitude band during 

spring biological time periods (dawn, day, dusk, night) 

in New York (targets/1,000,000 m3/hour).

62 Great Lakes Avian Radar - Fall 2016 
Niagara

Altitude Band Dawn Day Dusk Night

50 0.2 0.1 0.1 0.1

100 1.1 0.6 0.3 2.0

150 0.9 0.3 0.3 3.4

200 0.4 0.2 0.3 3.3

250 0.3 0.1 0.3 3.2

300 0.4 0.1 0.3 3.4

350 0.4 0.1 0.2 3.0

400 0.2 0.0 0.1 1.8

450 0.2 0.0 0.1 1.7

500 0.2 0.0 0.1 1.7

550 0.2 0.0 0.0 1.3

600 0.2 0.0 0.0 1.3

650 0.2 0.0 0.0 0.9

700 0.1 0.0 0.0 0.8

750 0.1 0.0 0.0 0.8

800 0.1 0.0 0.0 0.5

850 0.1 0.0 0.0 0.3

900 0.0 0.0 0.0 0.4

950 0.1 0.0 0.0 0.4

1000 0.0 0.0 0.0 0.3

Estimated density of targets by altitude band during 

spring biological time periods (dawn, day, dusk, night) 

in New York (targets/1,000,000 m3/hour).

Great Lakes Avian Radar - Fall 2016 63
Appendix 4

Comparison of Static and Corrected Density Estimates

Comparison of methods to estimate target density by altitude band during the dawn biological period in Jefferson 

County, NY, fall 2016.

64 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the day biological period in Jefferson 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 17 17 31.3 5.6 0.0 0.0 0.1% 1.5% 2.7%

100 138 155 31.3 5.9 0.0 0.2 1.1% 8.6% 15.3%

150 34 189 31.3 6.5 0.0 0.1 0.3% 2.3% 3.8%

200 37 226 31.3 7.1 0.0 0.0 0.3% 2.3% 3.4%

250 74 300 31.3 7.9 0.0 0.1 0.6% 4.0% 5.3%

300 137 437 31.3 8.5 0.0 0.1 1.1% 7.6% 9.4%

350 214 651 31.3 9.5 0.1 0.2 1.7% 12.6% 14.0%

400 291 942 31.3 10.3 0.1 0.2 2.3% 14.2% 14.5%

450 220 1,162 31.3 11.2 0.0 0.1 1.8% 9.3% 8.7%

500 137 1,299 31.3 12.2 0.0 0.1 1.1% 5.4% 4.7%

550 145 1,444 31.3 13.3 0.0 0.0 1.2% 4.3% 3.4%

600 147 1,591 31.3 14.1 0.0 0.0 1.2% 3.7% 2.8%

650 116 1,707 31.3 15.3 0.0 0.0 0.9% 3.2% 2.2%

700 107 1,814 31.3 16.2 0.0 0.0 0.9% 2.8% 1.8%

750 110 1,924 31.3 17.2 0.0 0.0 0.9% 2.4% 1.5%

800 87 2,011 31.3 18.2 0.0 0.0 0.7% 2.0% 1.2%

850 75 2,086 31.3 19.4 0.0 0.0 0.6% 1.4% 0.8%

900 80 2,166 31.3 20.4 0.0 0.0 0.6% 1.2% 0.6%

950 68 2,234 31.3 21.4 0.0 0.0 0.5% 1.2% 0.6%

1000 38 2,272 31.3 22.4 0.0 0.0 0.3% 1.0% 0.4%

1 Total target counts recorded up to 2,800m band during the day time period was 12443.

2 Total density of targets per hour recorded up to the 2,800 m band during the day time period was 1.425.

Great Lakes Avian Radar - Fall 2016 65
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the dusk biological period in Jefferson 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 10 10 31.3 5.6 0.0 0.0 1.3% 1.3% 2.8%

100 47 57 31.3 5.9 0.0 0.1 6.1% 6.1% 12.3%

150 9 66 31.3 6.5 0.0 0.0 1.2% 1.2% 2.2%

200 12 78 31.3 7.1 0.0 0.0 1.6% 1.6% 2.6%

250 39 117 31.3 7.9 0.0 0.1 5.0% 5.0% 7.7%

300 69 186 31.3 8.5 0.0 0.1 8.9% 8.9% 12.6%

350 74 260 31.3 9.5 0.0 0.1 9.6% 9.6% 12.1%

400 85 345 31.3 10.3 0.0 0.1 11.0% 11.0% 12.8%

450 60 405 31.3 11.2 0.0 0.1 7.8% 7.8% 8.3%

500 24 429 31.3 12.2 0.0 0.0 3.1% 3.1% 3.0%

550 19 448 31.3 13.3 0.0 0.0 2.5% 2.5% 2.2%

600 20 468 31.3 14.1 0.0 0.0 2.6% 2.6% 2.2%

650 21 489 31.3 15.3 0.0 0.0 2.7% 2.7% 2.1%

700 25 514 31.3 16.2 0.0 0.0 3.2% 3.2% 2.4%

750 16 530 31.3 17.2 0.0 0.0 2.1% 2.1% 1.4%

800 13 543 31.3 18.2 0.0 0.0 1.7% 1.7% 1.1%

850 15 558 31.3 19.4 0.0 0.0 1.9% 1.9% 1.2%

900 12 570 31.3 20.4 0.0 0.0 1.6% 1.6% 0.9%

950 10 580 31.3 21.4 0.0 0.0 1.3% 1.3% 0.7%

1000 9 589 31.3 22.4 0.0 0.0 1.2% 1.2% 0.6%

1 Total target counts recorded up to 2,800m band during the dusk time period was 774.

2 Total density of targets per hour recorded up to the 2,800 m band during the dusk time period was 0.8558.

66 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the night biological period in Jefferson 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 216 216 31.3 5.6 0.0 0.0 0.1% 0.1% 0.2%

100 3,916 4,132 31.3 5.9 0.2 0.8 1.1% 1.1% 2.8%

150 2,051 6,183 31.3 6.5 0.1 0.4 0.6% 0.6% 1.3%

200 3,584 9,767 31.3 7.1 0.1 0.6 1.0% 1.0% 2.1%

250 8,838 18,605 31.3 7.9 0.4 1.4 2.6% 2.6% 4.7%

300 16,346 34,951 31.3 8.5 0.7 2.5 4.7% 4.7% 8.1%

350 21,958 56,909 31.3 9.5 0.9 3.0 6.4% 6.4% 9.8%

400 23,103 80,012 31.3 10.3 0.9 2.9 6.7% 6.7% 9.5%

450 21,204 101,216 31.3 11.2 0.9 2.4 6.1% 6.1% 8.0%

500 19,122 120,338 31.3 12.2 0.8 2.0 5.5% 5.5% 6.6%

550 18,838 139,176 31.3 13.3 0.8 1.8 5.5% 5.5% 6.0%

600 18,487 157,663 31.3 14.1 0.8 1.7 5.4% 5.4% 5.5%

650 17,540 175,203 31.3 15.3 0.7 1.5 5.1% 5.1% 4.8%

700 16,406 191,609 31.3 16.2 0.7 1.3 4.8% 4.8% 4.3%

750 14,857 206,466 31.3 17.2 0.6 1.1 4.3% 4.3% 3.7%

800 13,499 219,965 31.3 18.2 0.6 0.9 3.9% 3.9% 3.1%

850 11,556 231,521 31.3 19.4 0.5 0.8 3.3% 3.3% 2.5%

900 10,300 241,821 31.3 20.4 0.4 0.6 3.0% 3.0% 2.1%

950 8,824 250,645 31.3 21.4 0.4 0.5 2.6% 2.6% 1.7%

1000 7,531 258,176 31.3 22.4 0.3 0.4 2.2% 2.2% 1.4%

1 Total target counts recorded up to 2,800m band during the night time period was 345,226.

2 Total density of targets per hour recorded up to the 2,800 m band during the night time period was 30.192.

Great Lakes Avian Radar - Fall 2016 67
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the dawn biological period in Wayne 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 6 6 31.3 5.6 0.0 0.0 0.2% 0.2% 0.4%

100 153 159 31.3 5.9 0.2 0.8 5.8% 5.8% 10.3%

150 178 337 31.3 6.5 0.2 0.9 6.8% 6.8% 11.0%

200 150 487 31.3 7.1 0.1 0.7 5.7% 5.7% 8.4%

250 230 717 31.3 7.9 0.2 0.9 8.7% 8.7% 11.6%

300 256 973 31.3 8.5 0.3 0.9 9.7% 9.7% 12.0%

350 243 1,216 31.3 9.5 0.2 0.8 9.2% 9.2% 10.2%

400 203 1,419 31.3 10.3 0.2 0.6 7.7% 7.7% 7.8%

450 157 1,576 31.3 11.2 0.2 0.4 6.0% 6.0% 5.6%

500 120 1,696 31.3 12.2 0.1 0.3 4.6% 4.6% 3.9%

550 94 1,790 31.3 13.3 0.1 0.2 3.6% 3.6% 2.8%

600 100 1,890 31.3 14.1 0.1 0.2 3.8% 3.8% 2.8%

650 79 1,969 31.3 15.3 0.1 0.2 3.0% 3.0% 2.1%

700 81 2,050 31.3 16.2 0.1 0.2 3.1% 3.1% 2.0%

750 51 2,101 31.3 17.2 0.1 0.1 1.9% 1.9% 1.2%

800 48 2,149 31.3 18.2 0.0 0.1 1.8% 1.8% 1.1%

850 51 2,200 31.3 19.4 0.1 0.1 1.9% 1.9% 1.0%

900 39 2,239 31.3 20.4 0.0 0.1 1.5% 1.5% 0.8%

950 26 2,265 31.3 21.4 0.0 0.0 1.0% 1.0% 0.5%

1000 27 2,292 31.3 22.4 0.0 0.0 1.0% 1.0% 0.5%

1 Total target counts recorded up to 2,800m band during the dawn time period was 2637.

2 Total density of targets per hour recorded up to the 2,800 m band during the dawn time period was 7.82116.

68 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the day biological period in Wayne 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 19 19 31.3 5.6 0.0 0.0 0.1% 0.1% 0.2%

100 1,471 1,490 31.3 5.9 0.1 0.6 7.3% 7.3% 11.2%

150 1,673 3,163 31.3 6.5 0.1 0.6 8.3% 8.3% 11.7%

200 2,193 5,356 31.3 7.1 0.2 0.7 10.9% 10.9% 13.9%

250 2,812 8,168 31.3 7.9 0.2 0.9 14.0% 14.0% 16.0%

300 2,418 10,586 31.3 8.5 0.2 0.7 12.0% 12.0% 12.8%

350 2,188 12,774 31.3 9.5 0.2 0.6 10.9% 10.9% 10.4%

400 1,679 14,453 31.3 10.3 0.1 0.4 8.4% 8.4% 7.3%

450 1,153 15,606 31.3 11.2 0.1 0.2 5.7% 5.7% 4.6%

500 897 16,503 31.3 12.2 0.1 0.2 4.5% 4.5% 3.3%

550 647 17,150 31.3 13.3 0.0 0.1 3.2% 3.2% 2.2%

600 463 17,613 31.3 14.1 0.0 0.1 2.3% 2.3% 1.5%

650 316 17,929 31.3 15.3 0.0 0.0 1.6% 1.6% 0.9%

700 253 18,182 31.3 16.2 0.0 0.0 1.3% 1.3% 0.7%

750 222 18,404 31.3 17.2 0.0 0.0 1.1% 1.1% 0.6%

800 161 18,565 31.3 18.2 0.0 0.0 0.8% 0.8% 0.4%

850 134 18,699 31.3 19.4 0.0 0.0 0.7% 0.7% 0.3%

900 100 18,799 31.3 20.4 0.0 0.0 0.5% 0.5% 0.2%

950 82 18,881 31.3 21.4 0.0 0.0 0.4% 0.4% 0.2%

1000 55 18,936 31.3 22.4 0.0 0.0 0.3% 0.3% 0.1%

1 Total target counts recorded up to 2,800m band during the day time period was 20,068.

2 Total density of targets per hour recorded up to the 2,800 m band during the day time period was 5.3306.

Great Lakes Avian Radar - Fall 2016 69
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the dusk biological period in Wayne 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 2 2 31.3 5.6 0.0 0.0 0.1% 0.1% 0.2%

100 147 149 31.3 5.9 0.1 0.7 7.3% 7.3% 10.5%

150 224 373 31.3 6.5 0.2 1.0 11.2% 11.2% 14.7%

200 342 715 31.3 7.1 0.3 1.4 17.0% 17.0% 20.4%

250 354 1,069 31.3 7.9 0.3 1.3 17.6% 17.6% 18.9%

300 251 1,320 31.3 8.5 0.2 0.8 12.5% 12.5% 12.5%

350 185 1,505 31.3 9.5 0.2 0.6 9.2% 9.2% 8.3%

400 119 1,624 31.3 10.3 0.1 0.3 5.9% 5.9% 4.9%

450 87 1,711 31.3 11.2 0.1 0.2 4.3% 4.3% 3.3%

500 63 1,774 31.3 12.2 0.1 0.1 3.1% 3.1% 2.2%

550 31 1,805 31.3 13.3 0.0 0.1 1.5% 1.5% 1.0%

600 18 1,823 31.3 14.1 0.0 0.0 0.9% 0.9% 0.5%

650 11 1,834 31.3 15.3 0.0 0.0 0.5% 0.5% 0.3%

700 10 1,844 31.3 16.2 0.0 0.0 0.5% 0.5% 0.3%

750 4 1,848 31.3 17.2 0.0 0.0 0.2% 0.2% 0.1%

800 2 1,850 31.3 18.2 0.0 0.0 0.1% 0.1% 0.0%

850 2 1,852 31.3 19.4 0.0 0.0 0.1% 0.1% 0.0%

900 7 1,859 31.3 20.4 0.0 0.0 0.3% 0.3% 0.1%

950 3 1,862 31.3 21.4 0.0 0.0 0.1% 0.1% 0.1%

1000 3 1,865 31.3 22.4 0.0 0.0 0.1% 0.1% 0.1%

1 Total target counts recorded up to 2,800m band during the dusk time period was 2006.

2 Total density of targets per hour recorded up to the 2,800 m band during the dusk time period was 6.70436

70 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the night biological period in Wayne 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 11 11 31.3 5.6 0.0 0.0 0.0% 0.0% 0.0%

100 4,136 4,147 31.3 5.9 0.4 2.1 3.5% 3.5% 6.2%

150 9,432 13,579 31.3 6.5 0.9 4.5 8.0% 8.0% 13.0%

200 11,663 25,242 31.3 7.1 1.1 5.0 9.9% 9.9% 14.6%

250 11,144 36,386 31.3 7.9 1.1 4.3 9.5% 9.5% 12.5%

300 9,241 45,627 31.3 8.5 0.9 3.3 7.9% 7.9% 9.7%

350 8,192 53,819 31.3 9.5 0.8 2.7 7.0% 7.0% 7.7%

400 7,322 61,141 31.3 10.3 0.7 2.2 6.2% 6.2% 6.3%

450 6,725 67,866 31.3 11.2 0.7 1.8 5.7% 5.7% 5.3%

500 6,137 74,003 31.3 12.2 0.6 1.5 5.2% 5.2% 4.5%

550 5,459 79,462 31.3 13.3 0.5 1.3 4.6% 4.6% 3.6%

600 4,907 84,369 31.3 14.1 0.5 1.1 4.2% 4.2% 3.1%

650 4,055 88,424 31.3 15.3 0.4 0.8 3.4% 3.4% 2.4%

700 3,374 91,798 31.3 16.2 0.3 0.6 2.9% 2.9% 1.8%

750 2,895 94,693 31.3 17.2 0.3 0.5 2.5% 2.5% 1.5%

800 2,669 97,362 31.3 18.2 0.3 0.4 2.3% 2.3% 1.3%

850 2,246 99,608 31.3 19.4 0.2 0.4 1.9% 1.9% 1.0%

900 1,866 101,474 31.3 20.4 0.2 0.3 1.6% 1.6% 0.8%

950 1,355 102,829 31.3 21.4 0.1 0.2 1.2% 1.2% 0.6%

1000 1,021 103,850 31.3 22.4 0.1 0.1 0.9% 0.9% 0.4%

1 Total target counts recorded up to 2,800m band during the night time period was 117,691.

2 Total density of targets per hour recorded up to the 2,800 m band during the night time period was 34.4771

Great Lakes Avian Radar - Fall 2016 71
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the dawn biological period in Niagara 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 36 36 31.3 5.6 0.0 0.2 1.3% 1.3% 2.5%

100 279 315 31.3 5.9 0.2 1.1 9.9% 9.9% 18.6%

150 250 565 31.3 6.5 0.2 0.9 8.9% 8.9% 15.3%

200 126 691 31.3 7.1 0.1 0.4 4.5% 4.5% 7.0%

250 103 794 31.3 7.9 0.1 0.3 3.7% 3.7% 5.2%

300 143 937 31.3 8.5 0.1 0.4 5.1% 5.1% 6.7%

350 159 1,096 31.3 9.5 0.1 0.4 5.7% 5.7% 6.6%

400 94 1,190 31.3 10.3 0.1 0.2 3.3% 3.3% 3.6%

450 102 1,292 31.3 11.2 0.1 0.2 3.6% 3.6% 3.6%

500 125 1,417 31.3 12.2 0.1 0.2 4.4% 4.4% 4.0%

550 113 1,530 31.3 13.3 0.1 0.2 4.0% 4.0% 3.4%

600 143 1,673 31.3 14.1 0.1 0.2 5.1% 5.1% 4.0%

650 128 1,801 31.3 15.3 0.1 0.2 4.6% 4.6% 3.3%

700 100 1,901 31.3 16.2 0.1 0.1 3.6% 3.6% 2.4%

750 95 1,996 31.3 17.2 0.1 0.1 3.4% 3.4% 2.2%

800 57 2,053 31.3 18.2 0.0 0.1 2.0% 2.0% 1.2%

850 45 2,098 31.3 19.4 0.0 0.1 1.6% 1.6% 0.9%

900 41 2,139 31.3 20.4 0.0 0.0 1.5% 1.5% 0.8%

950 46 2,185 31.3 21.4 0.0 0.1 1.6% 1.6% 0.9%

1000 28 2,213 31.3 22.4 0.0 0.0 1.0% 1.0% 0.5%

1 Total target counts recorded up to 2,800m band during the dawn time period was 2813.

2 Total density of targets per hour recorded up to the 2,800 m band during the dawn time period was 6.0900.

72 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the day biological period in Niagara 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 356 356 31.3 5.6 0.0 0.1 5.7% 5.7% 8.3%

100 1,525 1,881 31.3 5.9 0.1 0.6 24.3% 24.3% 33.4%

150 834 2,715 31.3 6.5 0.1 0.3 13.3% 13.3% 16.8%

200 473 3,188 31.3 7.1 0.0 0.2 7.5% 7.5% 8.7%

250 502 3,690 31.3 7.9 0.0 0.1 8.0% 8.0% 8.3%

300 530 4,220 31.3 8.5 0.0 0.1 8.4% 8.4% 8.1%

350 306 4,526 31.3 9.5 0.0 0.1 4.9% 4.9% 4.2%

400 123 4,649 31.3 10.3 0.0 0.0 2.0% 2.0% 1.6%

450 126 4,775 31.3 11.2 0.0 0.0 2.0% 2.0% 1.5%

500 133 4,908 31.3 12.2 0.0 0.0 2.1% 2.1% 1.4%

550 95 5,003 31.3 13.3 0.0 0.0 1.5% 1.5% 0.9%

600 121 5,124 31.3 14.1 0.0 0.0 1.9% 1.9% 1.1%

650 80 5,204 31.3 15.3 0.0 0.0 1.3% 1.3% 0.7%

700 84 5,288 31.3 16.2 0.0 0.0 1.3% 1.3% 0.7%

750 75 5,363 31.3 17.2 0.0 0.0 1.2% 1.2% 0.6%

800 49 5,412 31.3 18.2 0.0 0.0 0.8% 0.8% 0.4%

850 39 5,451 31.3 19.4 0.0 0.0 0.6% 0.6% 0.3%

900 52 5,503 31.3 20.4 0.0 0.0 0.8% 0.8% 0.3%

950 46 5,549 31.3 21.4 0.0 0.0 0.7% 0.7% 0.3%

1000 43 5,592 31.3 22.4 0.0 0.0 0.7% 0.7% 0.3%

1 Total target counts recorded up to 2,800m band during the day time period was 6281.

2 Total density of targets per hour recorded up to the 2,800 m band during the day time period was 1.7477

Great Lakes Avian Radar - Fall 2016 73
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the dusk biological period in Niagara 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 17 17 31.3 5.6 0.0 0.1 2.1% 2.1% 3.2%

100 88 105 31.3 5.9 0.1 0.3 10.9% 10.9% 15.7%

150 73 178 31.3 6.5 0.1 0.3 9.0% 9.0% 12.0%

200 98 276 31.3 7.1 0.1 0.3 12.1% 12.1% 14.6%

250 114 390 31.3 7.9 0.1 0.3 14.1% 14.1% 15.3%

300 107 497 31.3 8.5 0.1 0.3 13.3% 13.3% 13.3%

350 97 594 31.3 9.5 0.1 0.2 12.0% 12.0% 10.9%

400 40 634 31.3 10.3 0.0 0.1 5.0% 5.0% 4.1%

450 27 661 31.3 11.2 0.0 0.1 3.3% 3.3% 2.5%

500 33 694 31.3 12.2 0.0 0.1 4.1% 4.1% 2.9%

550 12 706 31.3 13.3 0.0 0.0 1.5% 1.5% 1.0%

600 12 718 31.3 14.1 0.0 0.0 1.5% 1.5% 0.9%

650 9 727 31.3 15.3 0.0 0.0 1.1% 1.1% 0.6%

700 7 734 31.3 16.2 0.0 0.0 0.9% 0.9% 0.5%

750 2 736 31.3 17.2 0.0 0.0 0.2% 0.2% 0.1%

800 8 744 31.3 18.2 0.0 0.0 1.0% 1.0% 0.5%

850 6 750 31.3 19.4 0.0 0.0 0.7% 0.7% 0.3%

900 2 752 31.3 20.4 0.0 0.0 0.2% 0.2% 0.1%

950 1 753 31.3 21.4 0.0 0.0 0.1% 0.1% 0.0%

1000 2 755 31.3 22.4 0.0 0.0 0.2% 0.2% 0.1%

1 Total target counts recorded up to 2,800m band during the dusk time period was 807.

2 Total density of targets per hour recorded up to the 2,800 m band during the dusk time period was 2.1917.

74 Great Lakes Avian Radar - Fall 2016 
(Appendix 4 continued)

Comparison of methods to estimate target density by altitude band during the night biological period in Niagara 

County, NY, fall 2016.

Altitude 

Band 

(m)

Target 

Count

Running 

Total 

Target 

Count1

Static 

Volume

Corrected 

Volume

Static 

Target 

Density 

per 

Hour

Corrected 

Target Density 

per Hour2

% 

Total 

Targets

% 

Static 

Density

% 

Corrected 

Density

50 414 414 31.3 5.6 0.0 0.1 0.2% 0.2% 0.4%

100 5,883 6,297 31.3 5.9 0.4 2.0 3.0% 3.0% 6.0%

150 10,893 17,190 31.3 6.5 0.7 3.4 5.5% 5.5% 10.2%

200 11,484 28,674 31.3 7.1 0.7 3.3 5.8% 5.8% 9.8%

250 12,348 41,022 31.3 7.9 0.8 3.2 6.2% 6.2% 9.5%

300 14,281 55,303 31.3 8.5 0.9 3.4 7.2% 7.2% 10.2%

350 14,062 69,365 31.3 9.5 0.9 3.0 7.1% 7.1% 9.0%

400 9,288 78,653 31.3 10.3 0.6 1.8 4.7% 4.7% 5.5%

450 9,224 87,877 31.3 11.2 0.6 1.7 4.6% 4.6% 5.0%

500 10,258 98,135 31.3 12.2 0.7 1.7 5.2% 5.2% 5.1%

550 8,639 106,774 31.3 13.3 0.6 1.3 4.3% 4.3% 3.9%

600 8,978 115,752 31.3 14.1 0.6 1.3 4.5% 4.5% 3.9%

650 6,946 122,698 31.3 15.3 0.4 0.9 3.5% 3.5% 2.8%

700 6,424 129,122 31.3 16.2 0.4 0.8 3.2% 3.2% 2.4%

750 6,587 135,709 31.3 17.2 0.4 0.8 3.3% 3.3% 2.3%

800 4,678 140,387 31.3 18.2 0.3 0.5 2.4% 2.4% 1.6%

850 3,057 143,444 31.3 19.4 0.2 0.3 1.5% 1.5% 1.0%

900 3,908 147,352 31.3 20.4 0.3 0.4 2.0% 2.0% 1.2%

950 4,225 151,577 31.3 21.4 0.3 0.4 2.1% 2.1% 1.2%

1000 3,262 154,839 31.3 22.4 0.2 0.3 1.6% 1.6% 0.9%

1 Total target counts recorded up to 2,800m band during the night time period was 198,703. 

2 Total density of targets per hour recorded up to the 2,800 m band during the night time period was 33.2376.

Great Lakes Avian Radar - Fall 2016 75
Fall 2016