Weather Influences on ABSTRACT Raptor Migration …gammathetaupsilon.org › ... › 2010s › volume53-2 › article2.pdfism is growing in hawk-watching sites such as Hawk Mountain

79

Weather Influences on Raptor Migration along the Kittatinny Ridge, PennsylvaniaTara E. GettigPennsylvania Department of Conservation

and Natural ResourcesPine Grove Furnace State ParkGardners, PA 17324E-mail: [email protected]

*Timothy W. HawkinsDepartment of Geography and Earth ScienceShippensburg UniversityShippensburg, PA 17257E-mail: [email protected]

The Geographical Bulletin 53: 79-92©2012 by Gamma Theta Upsilon

ABSTRACT

This paper analyzes the relationship be-tween weather patterns and bird migration to determine the feasibility of a site-specific migration forecast . Autumn migration data from Hawk Mountain Sanctuary, Pennsyl-vania for ten species were correlated with individual weather variables . Stepwise mul-tiple linear regressions revealed a positive relationship with raptor migration to north-westerly winds and wind speed and an inverse relationship to sea level pressure . Composite maps were created using data from days with the greatest migration counts for each spe-cies and categorized by synoptic situations . A relationship between bird migration and cold-front passage was revealed, with five of the species having their highest migration days after the recent passage of a cold front . Morphological differences are noted for birds in different synoptic groupings . The results suggest that a site-specific weather forecast for hawk watching sites is feasible .

Key Words: raptors, migration, weather patterns, Pennsylvania

INTRODUCTION

The goal of this study was to assess the weather that influences raptor migration at the Hawk Mountain Sanctuary on the Kittatinny Ridge in eastern Pennsylvania . Considerable research has been conducted on bird migration and various environmental conditions . Bildstein and Zalles (1998) pro-vides a summary of developments in raptor migration studies in the Western Hemisphere and Gauthreaux (1996) provides an overview of the methods involved in bird migration studies and advancements in this field . Of-ten, larger migrants, including raptors, are the focus of these migration studies due to their size and dependence on daytime soar-ing flight . Many factors including ecological and topographic considerations can have a significant impact on the raptor decisions to migrate and behavior while migrating . This

* corresponding author

80

Tara E. Gettig and Timothy W. Hawkins

study focuses on weather conditions that also can influence raptor migration behavior .

Numerous studies have been conducted to better understand the relationship between bird migration and weather; they vary greatly in purpose and scope . As outlined by Mueller and Berger (1967), the height of birds’ flight can be influenced by wind direction, wind speed, and the terrain or landforms below . For example, the Kittatinny Ridge, upon which Hawk Mountain sits (Fig . 1), creates updrafts of wind, causing soaring birds to fly at lower altitudes (i .e . less than 200 meters) so they can take advantage of these wind con-ditions (Kerlinger 1995) . The direction of winds has been shown to affect the altitude of soaring birds, which, in turn, can affect their probability for observation (Woltmann and Cimprich 2003) . Some theories state that migrating birds have a higher probability of observation under certain conditions because they will shift from spatially dispersed flight to concentrated flight along prominent geo-graphic features, such as the Kittatinny Ridge (Murray 1964) . Studies of autumn migration near Lake Michigan showed that northwest-erly winds concentrated randomly scattered birds at the shore of the lake, a prominent geographic feature, and the birds continued migration from that point in a more concen-trated fashion (Mueller and Berger 1961) .

Many studies correlating the movement of raptors with weather combine variables to create a representation of local weather that raptors react to . By grouping these vari-ables for analysis, one can correlate certain behaviors with climatic conditions (Stenseth and Mysterud 2005) . Specific combinations associated with fronts are commonly used in weather-migration studies and have been shown to explain variations in the passage of migrants at specific sites (Allen et al . 1996) .

For example, in the northeastern United States, northwesterly winds are favorable for migration and promote a faster flight because migrants do not need to expend as much energy as they are able to soar more effectively (Kerlinger 1995) . After the pas-sage of a cold front, the counter-clockwise

rotation associated with the storm system will produce the desirable northwesterly winds . The passage of cold fronts is also associated with rising pressure, clear skies and advection of cooler, drier air from the north . With the clear skies, the sun heats the surface, whereas the air temperature is relatively cool; these conditions create vertical air movements, also called thermals or updrafts . Updrafts aid soaring birds in a more efficient flight . Therefore, high migration numbers are cor-related with these conditions (Broun 1948; Mueller and Berger 1961) .

The high correlation between frontal move-ment and raptor migration is essentially a summarization of individual weather factors such as temperature, pressure, wind speed and moisture . Although some variables show higher correlation to the magnitude of bird migration, some factors associated with the passage of cold fronts work in conjunction to affect the local conditions .

Although large scale weather patterns can explain some comprehensive movement of birds, local weather is found to influence the number of passing raptors in site-specific studies (Hall et al . 1992) . Migrating birds use stopovers (periods when they are not progressing in their migration) when they encounter weather unfavorable for migration (Dennis 1954) . Thus, local weather condi-tions will be a variable in the continuation of the birds’ migration . It should be noted that physiological factors, such as fat reservesand the birds timing in relation to the migration season can be very strong factors in the birds’ decision to leave the stopover area (Alerstam and Linsdström 1990; Liechti and Bruderer 1998) . A bird that does not perceive a great risk in these other areas will be more likely to be affected by the localized weather .

Several studies have used specific weather variables in conjunction with raptor counts to determine a correlation between local weather and raptors sited . In studies of this kind, several aspects are mentioned repeat-edly as important considerations . Three as-pects have particular relevance to this study: (1) the importance of analyzing several years

81

Weather Influences on Raptor Migration along the Kittatinny Ridge, Pennsylvania

of data for patterns (Hall et al . 1992; Allen et al . 1996), (2) separation of bird species in analysis (Allen et al . 1996; Mueller and Berger 1967) and (3) the use of raptors rather than passerine birds due to their large size, specific aerodynamic abilities, soaring be-havior and tendency to fly in concentration (Allen et al . 1996; Mueller and Berger 1961) . The three methods mentioned above are used in this analysis, although the purpose of this study is unique .

Along with specific weather conditions as migration controls, scientists have recognized the role of adverse climatic conditions as a gross-scale control on migration (Gauthreaux 1996; Kerlinger 1995) . Through studies link-ing large scale weather data and bird migra-tion, it is known that the departure date for migration can be highly affected by weather (Hassler et al . 1963) . Jonzien et al . (2006)

demonstrate that since the departure date for migration depends on climate, the study of bird migration can reflect long-term climate change . Using long-term migratory data, Jonzien et al . (2006) show that migrants are advancing their spring arrival dates, indicat-ing a possible “climate-driven evolutionary change .” Bildstein (1997) suggests that rap-tor migration, specifically, has undergone a long term shift related to climate .

Recognizing that public interest and tour-ism is growing in hawk-watching sites such as Hawk Mountain Sanctuary, Pennsylvania (Fig . 1), this study aims to correlate local weather and regional weather with the mag-nitude of raptor migration for the purpose of determining whether a forecast for optimal hawk-watching opportunities is feasible . Hawk Mountain is on the prominent bird migration route established by the Kittatinny

Figure 1 . Hawk Mountain Sanctuary, Pennsylvania and its position in relation to the two weather data points .

82

Ridge which provides visual guidance to the migrants as well as enhanced uplift as north-westerly winds strike the ridge perpendicu-larly . Many studies regarding bird migration and weather attempt to make general state-ments about bird reactions to weather events . This study recognizes that bird behavior can be affected by weather conditions and inves-tigates the feasibility of a site-specific forecast to aid migration observers . Due to geogra-phy and topography, the birds’ reaction to weather may vary at another hawk-watching site; therefore, the results of this analysis are intended as a tool to create a forecast product at Hawk Mountain and should not necessar-ily be applied to other locations .

STUDY AREA

Hawk Mountain Sanctuary is on the Kit-tatinny Ridge, a ridgeline along which many raptors migrate . The Kittatinny is a long nar-row ridge stretching from Maryland to New York in a southwest-to-northeast orientation . The specific location of this ridge in relation to weather patterns creates an ideal route of transportation for migratory birds (Fig . 1) . The largely uninterrupted ridge covers more than 200 miles and crosses 11 coun-ties in Pennsylvania, picking up regional geographic labels along its span (National Audubon Society 2005; Weidensaul 1995) . In eastern Pennsylvania, from the New York border to Wind Gap, it is called Kittatinny Mountain and south of Wind Gap, in most of the state, it is known as Blue Mountain or North Mountain (National Audubon Society 2005; Weidensaul 1995) . In Franklin Coun-ty, Pennsylvania, the name shifts to Front Mountain and near the Maryland border, the identity changes to Broad Mountain (Na-tional Audubon Society 2005; Weidensaul 1995) .

The ridge also marks a border in physio-graphic provinces, which contributes to its effectiveness in bird migration patterns . To the southeast of the Kittatinny Ridge lies the Great Valley section of the Ridge and Valley province, making the Kittatinny the

eastern-most ridge in the province . North-west winds, hitting the ridge at almost a ninety degree angle, deflect upward and cre-ate an updraft that allows for soaring birds to stay aloft with minimal energy expenditure (Weidensaul 1995) . The ridge also offers a prominent “leading line,” a visual reference for migrating birds (Allen et al . 1996) . This combination of optimal wind direction and the leading line make an effective route for diurnal soaring migrants (Mueller and Berger 1967) .

The ridge’s importance for birds is rec-ognized in its designation as a “globally significant” migration route; it is one of 388 sites worldwide to be documented in Raptor Watch (http://www .hawkwatch .org/news-and-events/raptorwatch-newsletter), a publication with contributions from over 800 raptor experts (Hawk Mountain Sanctu-ary Assoc . 2006; National Audubon Society 2005) . The ridge is also Pennsylvania’s largest Important Bird Area (IBA), a program that attempts to identify and protect outstand-ing bird habitats, designated using specific criteria as defined by the National Audubon Society (National Audubon Society 2005) .

Hawk Mountain (Fig . 1), specifically, was known along the ridge for its excellent views of migrating birds . Before Hawk Mountain was established as a sanctuary in 1934, it was used by shooters as an ideal site to shoot thousands of migrating hawks (Weidensaul 1995) . At the time, birds of prey were seen as “pests” and bounty was rewarded by the Pennsylvania Game Commission on several species (Bildstein 1997) . A 1929 newspaper article reports that 300 hawks were killed at the site in a single day (Weidensaul 1995) . Reports such as these led New York conser-vationist Rosalie Edge to purchase the moun-taintop in 1934 for the purpose of creating a bird sanctuary (Bildstein 1997) . Edge, along with a group of others created Hawk Moun-tain Sanctuary as the world’s first refuge for migratory birds of prey (Bildstein 1997; Wei-densaul 1995) . Controversy over the new use of the site gained much publicity and it was the duty of the Sanctuary’s first ornithologist,


83

Maurice Broun, to confront local sportsmen and post the property marking its function as a refuge (Bildstein 1997) .

Counting of migrating birds began in 1934 and currently, the Sanctuary’s data on raptor migration are the most complete collection available . With the exception of the years 1943-46, during World War II, the Sanctuary has recorded data each migration season on the number of passing species and weather conditions (Bildstein 1997) .

Today, the Sanctuary has a facility and programs to accommodate visitors coming to observe bird migration . They offer hiking trails, educational programs and continue their research of raptors . Hawk watching as a tourist attraction is expanding worldwide and Hawk Mountain is representative of this trend, with the majority of visitors counted during the fall raptor migration season (Mac-Rae 1998; Hawk Mountain Sanctuary Assoc . 2006) . Recognizing that the interest in hawk watching is expanding, the results from this analysis will assess the feasibility of creating a weather forecast for optimal hawk-watching days .

BIRD SPECIES AND FLIGHT CHARACTERISTICS

The ten species of birds used in this study are classified as hawks (Family Accipitridae), falcons (Family Falconidae), osprey (Family Pandionidae) and New World vultures (Fam-ily Cathartidae) . Often, these types of large diurnal migrants are grouped as “raptors .” While recognizing that these birds have very different characteristics, they share the common characteristic of gliding and soar-ing flight, where the bird has the ability to fly with fixed wings (Kerlinger 1995) . Birds analyzed herein will be referred to as raptors .

The birds chosen for this study represent large diurnal migrants that use soaring and gliding flight, defined as covering a linear dis-tance without flapping their wings (Kerlinger 1995) . While gliding, birds lose altitude with respect to the ground . While soaring, birds gain altitude with respect to the ground to

rising air current (Kerlinger 1995) . Many complex factors determine the efficiency of a bird’s flight, but the mass, and wing and the tail configuration contribute greatly to the gliding efficiency, with a large surface area of wing and tail feathers contributing positively to gliding performance (Kerlinger 1995) . Raptors chosen for this study differ in their proficiency in soaring flight due to their adaptations for their specific habitat and hunting habits

The birds we chose for analysis are: Cathar-tes aura (Turkey Vultures) Coragyps atratus (Black Vultures), Accipiter striatus (Sharp-shinned Hawks), Accipiter cooperii (Coo-per’s Hawks), Buteo jamaicensis (Red-tailed Hawks), Buteo platypterus (Broad-winged Hawks), Haliaeetus leucocephalus (Bald Ea-gles), Aquila chrysaetos (Golden Eagles), Pan-dion haliaetus (Osprey) and Falco sparverius (American Kestrels), (Table 1) . The Turkey Vultures and Black Vultures were combined to represent total vultures, making nine bird types . These ten species, or nine types, com-prise 91% or more of all raptors counted for each year between August 15 and December 15 . In addition to representing the majority of raptors for the season, the species chosen represent major taxonomic classifications of North American raptors .

DATA AND METHODOLOGY

We obtained migration data from the Acopian Center for Conservation Learning at Hawk Mountain Sanctuary . The migration counts were conducted at the North Lookout at Hawk Mountain, near Kempton, PA . Each day, at least one counter recorded the number of migrants passing the site, using binoculars or a spotting scope . These counts were done each day from August 15 to December 15 each fall, with the exception of extenuating circumstances, including rain .

For this analysis, a time period too great in length would increase the probability of out-side influences on the data . In studies using migration data spanning several decades, long term shifts in bird populations or migration


84

behavior is recognized as an influence (Jonzin et al . 2006) . The time period we chose for this study, 1999-2005, maximizes the sample size while eliminating the influence of long term trends in the data . Since 1966, Hawk Mountain has employed a standard method of bird observation when collecting the migration data (Bildstein 1997) . The time period chosen also ensures that the data used were collected using this standardized format . For the years 1999-2005, thirteen days did not have migration counts . When narrowing the focus to the maximum migration days, all of these days were outside of the period of analyses, except October 17-18, 2000 and September 20, 2001 .

Daily observational data, such as those from Hawk Mountain, exclude the counts of nighttime migrants . While studies have shown that traditionally diurnal migrants also fly nocturnally (Russel 1991; Bellrose 1971, for the purpose of this study, daytime observational data are ideal . The intention is not to attempt to make statements on the movement of an entire population of birds, but to provide parameters for optimal hawk-watching . For this analysis, it is desirable to omit birds that cannot be observed with the

human eye through binoculars and spotting scopes .

We selected maximum magnitude migra-tion days for each species using an average of the six years . The range of maximum migration spanned from 21-76 days and the days chosen represent 75% or greater of the six year average fall migration between the periods of August 15 through December 15 (Table 1, Fig . 2) .

We obtained gridded weather data from the National Centers for Environmental Pre-diction and National Center for Atmospheric Research (NCEP/NCAR) 40-year reanalysis project (Kalnay et al . 1996) . Currently, data are available via the Earth System Research Laboratory of the National Oceanic and At-mospheric Administration’s (NOAA) . The variables from NOAA were as follows: 500 mb geopotential height, meridional wind, zonal wind and wind speed at 850 mb, lifted index, sea level pressure and surface tempera-ture . We used daily data for the grid point located at 40oN, 75oW that is approximately 109 .4 km from Hawk Mountain Sanctuary (Fig . 1) . Average daily temperature, relative humidity, pressure and wind speed were also used from the Allentown Automated Surface


Table 1 . Maximum migration for each species 1999-2005 .

Species Family Max Migration Days Number of Days

% of Average Season

TotalBird 1 Total Vultures Cathartidae 7-Oct 4-Nov 29 75

Bird 2 Sharp-Shinned Hawk Accipitridae 2-Sep 30-Oct 36 83

Bird 3 Cooper’s Hawk Accipitridae 28-Sep 30-Oct 33 77

Bird 4 Red-tailed Hawk Accipitridae 17-Oct 15-Nov 30 75

Bird 5 Broad-winged Hawk Accipitridae 8-Sep 28-Sep 21 93

Bird 6 Bald Eagle Accipitridae 29-Aug 12-Nov 76 76

Bird 7 Golden Eagle Accipitridae 18-Oct 20-Nov 34 75

Bird 8 Osprey Pandionidae 10-Sep 17-Oct 38 76

Bird 9 American Kestrel Falconidae 10-Sep 17-Oct 38 75

85

Observing System (ASOS) weather station located at Lehigh Valley Airport (40 .65oN, 74 .43oW), which is approximately 46 .8 ki-lometers from Hawk Mountain Sanctuary (Fig . 1) .

To eliminate redundancy and collinearity in the data set, we performed a principal component analyses (PCA) to reduce the variables from eleven to six . For all PCAs, we attempted varimax rotation . The rotation did not improve the relationships and therefore was not considered in the analyses .

We first performed PCA performed on the Allentown and NOAA data sets individually . We retained components with an eigenvalue greater than one in the Allentown data . We retained components with an eigenvalue greater than .996 in the NOAA data set . No components were carried forward in the analysis; however, three considerations were used as guidance for the succession of PCAs described below . First, we no longer considered Allentown pressure in the analyses as it did not load strongly onto either com-

ponent (Table 2) and did not have a strong individual correlation with the migration data . Second, we noted a strong relationship between Allentown temperature and relative humidity as indicated by the component loadings (Table 2) . Third, we noted a strong relationship between NOAA temperature and geopotential height (Table 3) . This third relationship was also corroborated by simple correlation analysis .


8/15 9/15 10/15 11/15 12/15

9. American Kestrel

8. Osprey

7. Golden Eagle

6. Bald Eagle

5. Broad-Winged Hawk

4. Red-Tailed Hawk

3. Cooper's Hawk

2. Sharp-Shinned Hawk

1. Total Vultures

% o

f Mig

ratin

g Ra

ptor

s

10. Total Raptors

Figure 2 . Average 10-day running average of percent of total migrants for the fall migration at Hawk Mountain Sanctuary, 1999-2005 . Note that the percent scales are not equal but have a maximum value that ranges from 3 .0 to 7 .5% .

Table 2 . Component loading matrix - Prin-cipal component analysis for Allentown station .

Component

1 2Temperature 0.973 0.060

Relative Humidity 0.967 0.038

Station Pressure 0.504 -0.249

Wind Speed 0.031 0.972

86

Based on a series of correlation analyses and PCAs (results not shown here), we com-bined NOAA temperature and Allentown temperature through a PCA to form a Tem-perature Component (TC) . We combined NOAA wind speed and Allentown wind speed through a PCA to form a Wind Speed Component (WSC) . Considering the strong relationships mentioned above, we combined TC, Allentown relative humidity and NOAA geopotential height through a PCA to form a Temperature, Pressure and Moisture Com-ponent (TPMC) .

There is a strong physical basis for the creation of this TPMC component . As temperatures rise, air warms and becomes less dense, causing the constant pressure surface to rise . Therefore, temperature and geopotential height are positively related . As temperatures rise, the saturation water vapor capacity increases and causes relative humid-ity to decrease; hence, temperature and rela-tive humidity are inversely related . Based on the PCAs, the six variables produced to be input into multiple linear regressions explain 76% of the original variance in the original data set of 11 variables .

After the PCAs, the weather variables that were entered into multiple linear regression (MLR) analyses included: lifted index (LI), sea level pressure (SLP), zonal wind (U), me-ridional wind (V), WSC and TPMC . Bird

migration data were the dependent variables . The entire data set of maximum migration days for all birds (Bird All) was considered as a whole using a MLR that included all independent variables . Each bird type was also considered separately using a stepwise MLR .

For each bird type, we extracted the five days with the highest magnitude migration counts within the maximum migration days data set to represent ideal migration days for that bird type . For each bird type, we used the five days to create a composite weather map of sea level pressure using the NCEP/NCAR reanalysis data .

RESULTS AND DISCUSSION

Table 4 shows the results from the MLRs . The adjusted R2 shows that 1-23% of the variance in bird migration can be explained by these weather factors . In some statistical analyses, these explained variances may be considered low . For this study, it is recognized that a host of other biological and physiologi-cal factors also might affect bird migration . This study focused on weather conditions . As the migration season progresses, the bio-logical urge to migrate will dominate over optimal weather conditions . Therefore, these explained variances are not surprising and are viewed as acceptable for consideration . For


Table 3 . Component loading matrix - Principle-component analysis for NOAA data .

Component1 2 3

Geopotential Height 0.903 0.189 -0.005Lifted Index 0.066 -0.088 0.994Sea Level Pressure 0.470 -0.614 -0.056Temperature 0.669 0.613 0.017Wind Vector U -0.642 0.395 0.068Wind Vector V 0.352 0.692 0.018Wind Speed -0.732 0.378 0.013

87

all birds, except for Broad-winged Hawks, the MLR models were statistically significant at the 95% confidence level .

As an independent variable, SLP is sig-nificant for Bald Eagles, Golden Eagles, and Osprey, and has a negative correlation to mi-gration counts . U is significant for Vultures, Sharp-shinned Hawks, Cooper’s Hawks, Golden Eagles, and American Kestrels with a positive correlation . V is significant and negatively correlated for Sharp-shinned Hawks, Cooper’s Hawks, Red-tailed Hawks, Bald Eagles, Golden Eagles, and American Kestrels . WSC is significant and positively correlated for Cooper’s Hawks, Red-tailed Hawks, and American Kestrels . TPMC is significant and positively correlated for Bald Eagles . For each bird type in which an inde-pendent weather variable was found signifi-cant, the β values were of the same sign for all birds . The sign of all the relationships makes physical sense as well . No weather variables were significant for Broad-winged Hawks .

The two variables that were significant for the most bird types were the positively

correlated U which indicates a westerly wind and the negatively correlated V, which indicates a northerly wind . These values were anticipated, since northwesterly winds will be perpendicular to and deflect off of the Kittatinny Ridge, causing good soaring conditions .

The next two variables that showed the most significance were WSC and SLP, each significant for three birds . The birds in which the WSC is significant, Cooper’s Hawks, Red-tailed Hawks, and American Kestrels, also show a significant correlation to the U and/or V wind component . For this analysis, birds that fly in concentrated numbers during higher wind speeds also make the decision to fly during optimal wind direction . However, not all birds that fly in concentration during optimal wind direction depend on higher wind speeds .

SLP was significant and negatively corre-lated with three birds . This drop in pressure related to higher migratory activity is not surprising, as many other studies correlate migration with low pressure cells . It is inter-


Table 4 . Stepwise multiple linear regression statistics . No variables were found to be significant for Broad-winged Hawks (5) . Dark shading represents positive β values and light shading represents negative β values .

β

Adj. R2 Sig. LI SLP U V WSC TPMC

Vulture ( 1) 0.06 0.00 0.245

SS Hawk (2) 0.24 0.00 0.417 -0.314

Coop Hawk (3) 0.19 0.00 0.258 -0.279 0.156

RT Hawk (4) 0.19 0.00 -0.373 0.168

BW Hawk (5) NA NA

Bald Eagle (6) 0.06 0.00 -0.179 -0.209 0.132

Gold Eagle (7) 0.18 0.00 -0.147 0.179 -0.405

Osprey (8) 0.01 0.04 -0.123

Am Kestrel (9) 0.12 0.00 0.169 -0.204 0.205

All Birds 0.00 0.09 -0.01 -0.039 0.018 -0.048 0.001 0.049

88

esting that it is only three of the bird types that were found to have this relationship while an individual weather variable, wind direction, was found to be the most signifi-cant . The weather variable that raptors find most favorable for migration (wind direc-tion) is associated with the passage of a cold front, but the birds will favor that variable regardless of frontal passage .

That the wind components are highly associated with migration counts demon-strates that the local weather plays an im-portant role on migrating raptors . These local weather patterns work in conjunction with the regional topography to create desirable migration conditions . When in other regions or faced with other large or distinct topo-graphic features such as bodies of water or mountain ranges, migrating birds may react differently to weather conditions (Hall et al . 1992; Mueller and Berger 1961; Woltmann

and Cimprich 2003) . These findings will be useful in creating a weather forecast for hawk watching at Hawk Mountain Sanctuary, but should be used with discretion when applied to other sites .

Local weather components work together to create a synoptic picture of the atmo-spheric conditions . Because of this, we as-sessed these statistical findings on a regional scale . Composite maps created from the top five days of migration counts for each bird type were analyzed and grouped into two categories: cold front recent and cold front approaching . Table 5 shows the five days of maximum migration for each bird and Fig . 3 shows the composite maps for each bird grouped by synoptic situation . Five of the bird types, Sharp-shinned Hawks, Cooper’s Hawks, Red-tailed Hawks, Bald Eagles, Golden Eagles, and American Kestrels, are categorized in the ‘cold fronts recent’ group

Table 5 . Top five days of migration counts for each bird type, 1999-2005 . Days are derived from the previously outlined maximum migration days data set (Table 1) .

Type Month Day Year Type Month Day Year Type Month Day YearVulture 10 31 2005 SS

Hawk 10 18 2005 Coop Hawk 10 18 2005

11 1 2005 10 7 2001 10 23 2005

10 30 2003 10 17 2005 10 17 2005

10 20 2001 9 30 1999 10 2 1999

10 20 2003 10 15 2001 10 7 2001

RT Hawk 10 29 2005 BW

Hawk 9 20 2002 Bald Eagle 9 17 1999

10 27 2001 9 19 2002 9 5 2003

11 8 2003 9 19 1999 9 17 2004

10 28 2001 9 26 2005 9 28 2000

10 30 2005 9 20 2000 9 11 2002

Gold Eagle 11 20 2003 Osprey 9 17 2004 All

Birds 9 30 1999

11 8 2003 9 14 2002 9 19 2001

11 14 2003 10 2 1999 10 17 2005

11 15 2003 9 30 1999 10 16 2005

11 11 2005 10 5 2002 10 5 2002


89

Figure 3 . Composite sea level pressure maps from the top five days of migration counts for each bird type, grouped by synoptic situation .

and show some similar characteristics from the statistical analyses . For Red-tailed Hawks, the cold front is further past than it is for other birds and high pressure is building much more strongly over the observations site . Therefore, Red-tailed Hawks are consid-ered separately . The zonal (U) and meridional (V) wind components are important in all of these birds except for Bald Eagles where only the meridional component is significant . The center of the high-pressure cell following the cold front in the Bald Eagles composite is to the north of Pennsylvania . Therefore, the

clockwise winds created by the cell would have a greater northerly component with this configuration . For the remainder of the birds in this category, the correlation between the northwesterly winds and the passing of the cold front is logical . The counter-clockwise winds associated with the midlatitude cy-clone passage will create northwesterly winds associated with the cold front passage . The five bird types (excluding Red-tailed Hawks) categorized in the ‘cold front recent’ group coincide with taxonomic classifications for these birds . Sharp-shinned Hawks and Coo-


90

Table 6 . Morphological characteristics of birds .

Species Average Length (cm)

Average Wing Span

(cm)Average

Weight (g)

Bird 1 Total Vultures 69 159 1950

Bird 2 Sharp-Shinned Hawk 29 50 153

Bird 3 Cooper’s Hawk 45 76 424

Bird 4 Red-tailed Hawk 56 124 1075

Bird 5 Broad-winged Hawk 39 91 413

Bird 6 Bald Eagle 84 204 4650

Bird 7 Golden Eagle 77 203 4563

Bird 8 Osprey 56 165 1700

Bird 9 American Kestrel 27 56 123

per’s Hawks are the only Accipiters consid-ered in the study, Bald Eagles and Golden Eagles are the only Eagles considered and American Kestrels represents the only Falcon considered .

Three bird types, Vultures, Broad-winged Hawks, and Ospreys, have high migration days when cold fronts are approaching . However, these types do not show strong statistical correlation to specific weather variables . Broad-winged Hawks did not have any significant independent weather variables and Ospreys and Vultures have the two lowest adjusted R2 values of .01 and .06 respectively . Vultures, Broad-winged Hawks, and Ospreys also coincide with taxonomic classifications; Broad-winged Hawks are one of two Buteos considered in the study . The other Buteo is the Red-tailed Hawk which as previously mentioned does not behave similarly to the other birds in the “cold front recent” group .

Red-tailed Hawks are unique in that they are associated with a pattern of rising pressure with a high pressure cell in closer proxim-ity and the low pressure cell further to the east when compared with the first synoptic grouping . Based on its frontal position, Red-tailed Hawks are classified with the

‘cold front recent’ group . However, based on the statistical analyses, Red-tailed Hawks are similar to the ‘cold front approaching’ group . The synoptic map for Red-tailed Hawks shows a less influential cold front as it is farther past and a more influential high pressure system similar to the ‘cold front ap-proaching’ group where the location of the high pressure is more important .

It is beyond the scope of this paper to adequately discuss the flight mechanics of the birds examined in this study as it relates to weather patterns, it is possible to provide a cursory analysis of flight mechanics as a possible line of future research . Table 6 lists morphological characteristics for the birds examined . Note that wing shape is also very important as it determines the bird’s ability to moderate the gliding speed and thus the amount of energy spent on powered flight . While all birds could certainly be aided by ideal migrating conditions, the smallest birds (Sharp-shinned Hawks, Cooper’s Hawks, and American Kestrels) all are classified as ‘cold front recent’, have significant correlations with wind speed and direction, and have some of the largest adjusted R2 values for their respec-tive MLR equations . These smaller birds are


91

less efficient soaring birds and flap their wings much more than other birds in the study (Hawk Mountain Sanctuary Association 2006) . Consequently, more ideal migrating conditions will aid these smaller birds .

Also in the ‘cold front recent’ group are the two largest birds in the study; both are eagles (Bald Eagles and Golden Eagles) . Due to their large size, these birds, while efficient soaring birds may actually require more ideal migrating conditions than the smaller effi-cient soaring birds that are classified as cold front ‘approaching’ (Vultures, Broad-winged Hawks, and Ospreys) or Red-tailed Hawks which as mentioned previously behaves simi-larly to the ‘cold front approaching’ birds . Vultures, Red-tailed Hawks, Broad-winged Hawks, and Ospreys are all efficient soar-ing birds (Kerlinger 1995), yet are relatively small and thus do not necessarily need ideal wind conditions . Furthermore, these birds may take advantage of the thermals gener-ated in the warm sector of the approaching cold front to soar at high altitudes not as favored by the birds in the ‘cold front recent’ group that are relying more on the updrafts generated by the northwest flow striking the Kittatinny Ridge .

CONCLUSION

Autumn migration data from Hawk Moun-tain Sanctuary from 1999-2005 for ten species of raptors was correlated with weather vari-ables to assess the relationship between bird migration and weather . When analyzed for the specific weather variables, a northwesterly wind was the most dominant weather compo-nent related to migration . When analyzed on a synoptic scale, the passage of cold fronts shows the greatest relationship with raptor migra-tion . The importance of individual variables was found to be significant, especially wind di-rection and wind speed . This confirms that the passage of a cold front creates conditions that are favorable to raptor migration, but it is not the event of the front, per se, that cause the raptors to migrate in higher concentrations . Furthermore, physiological considerations

such as body size and wing span make some species more dependent on favorable weather conditions .

This analysis enforces and statistically supports the notion that wind direction is significant to bird migration . It seems rea-sonable to assume that birds would fly more efficiently in tailwinds and in winds that are deflecting up and over the ridge . These winds are controlled by the larger synoptic patterns of cold front passage through the northeastern United States . Birds with high correlation to wind variables have higher migration counts following the passage of a cold front .

Considering that many other biological factors affect migrating birds, a more spe-cific analysis could be done to consider how weather affects birds as the migration season progresses . For example, it may be possible to quantify if and how weather variables ex-plain less variance in the migration counts as the migration season progresses . With this knowledge and knowing that correlating weather variables to bird migration counts should be considered based on geography, we suggest that a weather forecast for optimal hawk watching at Hawk Mountain Sanctu-ary is feasible . Although many factors act to modify migratory behavior, it is shown that weather is a significant aspect .

ACKNOWLEDGEMENTS

We obtained data from Dr . Christopher Farmer of the Acopian Center for Conserva-tion Learning at Hawk Mountain Sanctu-ary . Thank you to Dr . J .R . Stewart, Mary Linkevich, and Dr . Laurie Goodrich for helpful discussions .

REFERENCES

Alerstam, T ., and Lindström, A . 1990 . Op-timal Bird Migration: The Relative Im-portance of Time, Energy and Safety . In: Gwinner, E . (ed .), Bird Migration, Physiol-ogy and Ecophysiology. Berlin: Springer, pp . 331-351 .


92


Allen, P ., Goodrich, L ., and Bildstein, K . 1996 . Within- and Among-year Effects of Cold Front on Migrating Raptor at Hawk Mountain, Pennsylvania, 1934-1991 . Auk, 113(2): 329-338 .

Bellrose, F . 1971 . The Distribution of Noc-turnal Migrants in the Air Space . Auk, 88(2): 397-424 .

Bildstein, K . 1997 . Factors Influencing Short- and Long-Term Changes in Raptor Migration at Hawk Mountain Sanctuary, USA, 1934-1995 . Buteo, 9:5-15 .

Bildstein, K ., and Zales, J . 1998 . Moving Targets: The Science and Conservation of Migrating Raptors in the Western Hemi-sphere . Torgos, 29:97-108 .

Broun, M . 1948 . Hawks Aloft: The Story of Hawk Mountain . New York: Dodd, Mead Co .

Dennis, J . 1954 . Meteorological Analysis of Grounded Migrants at Smith Point, Texas, April 17- May 17, 1951 . The Wilson Bul-letin, 66(2): 102-111 .

Gauthreaux, S . 1996 . Historical Perspectives Bird Migration: Methodologies and Major Research Trajectories (1945-1995) . The Condor, 98: 442-453 .

Hall, L ., Fish, A ., and Morrison, M . 1992 . The Influence of Weather on Hawk Move-ments in Coastal Northern California . The Wilson Bulletin, 104(3): 447-461 .

Hassler, S ., Graber, R ., Bellrose, F . 1963 . Fall Migration and Weather, A Radar Study . The Wilson Bulletin, 75(1): 56-78 .

Hawk Mountain Sanctuary 2006 . Annual Raptor Migration Count Data, 1999-2005 . Hawk Mountain Sanctuary Associa-tion, Kempton, Pennsylvania, USA .

Hawk Mountain Sanctuary Association 2006 . Hawk Mountain [http://www .hawkmountain .org/default .shtml] (ac-cessed 9 September 2006) .

Jonzen, N ., Linden, A ., Egron, T ., Knudsen, E ., Vik, J ., Rubonlini, D ., Piacentini, D ., Brinch, C ., Spina, F ., Karlsson, L ., Ster-vander, M ., Andersson, A ., Waldenstrom, J ., Lehikoinen, A ., Edvardsen, E ., Solvang, R ., Stenseth, N . 2006 . Rapid Advance of

Spring Arrival Dates in Long-Distance Mi-gratory Birds . Science, 312(5782): 1959-61 .

Kalnay and others . 1996 . The NCEP/NCAR 40-Year Reanalysis Project . Bulletin of the American Meteorological Society, 77(3): 437-471 .

Kerlinger, P . 1995 . How Birds Migrate. Mechanicsburg, Pennsylvania: Stackpole Books .

Kerlinger, P ., Gauthreaux, S . 1984 . Flight Behaviour of Sharp-Shinned Hawks During Migration . I: Over Land . Animal Behaviour, 32(4): 1021-1028 .

Liechti, F ., Bruderer, B . 1998 . The Relevance of Wind for Optimal Migration Theory . Journal of Avian Biology, 29(4): 561-568 .

MacRae, D . 1998 . Marathon Hawkwatch . Wildlife Conservation, 102(1): 12 .

Mueller, C ., Berger, D . 1961 . Weather and fall Migration of Hawks at Cedar Grove, Wisconsin . The Wilson Bulletin, 73(2): 171-192 .

Mueller, H ., and Berger, D . 1967 . Wind Drift, Leading Lines and Diurnal Migra-tion . The Wilson Bulletin, 79 (1): 50-63 .

Murray, B . 1964 . A Review of Sharp-Shinned Hawk Migration along the Northeastern Coast of the United States . The Wilson Bul-letin, 73(3): 257-264 .

National Audubon Society . 2006 . Blue Mountain-Kittatinny Ridge Conserva-tion Project [http://pa .audubon .org/kit-tatinny/] (Accessed September 6, 2006) .

Russell, R . 1991 . Nocturnal Flight by Mi-grant ‘Diurnal’ Raptors . Journal of Field Ornithology, 62(4): 505-508 .

Stenseth, N ., and Mysterud, A . 2005 . Weath-er Packages: Finding the Right Scale and Composition of Climate in Ecology . Jour-nal of Animal Ecology, 74(6): 1195-1198 .

Weidensaul, S . 1995 . Appalachian Spine . Audubon, 97(4): 34 .

Woltmann, S ., and Cimprich, D . 2003 . Effects of Weather on Autumn Hawk Movements at Fort Morgan, Alabama . Southeastern Naturalist, 2(3): 317-326 .

Documents

Weather Influences on ABSTRACT Raptor Migration …gammathetaupsilon.org › ... › 2010s › volume53-2 › article2.pdfism is growing in hawk-watching sites such as Hawk Mountain