copyright 2019, jessica mehta

An Examination of Juvenile Northern Bobwhite Survival and Movement Patterns in

Late Summer and Early Fall on the Rolling Plains of Texas

by

Jessica Ann Mehta, B.S.

A Thesis

In

Wildlife, Aquatic, and Wildlands Science and Management

Submitted to the Graduate Faculty

of Texas Tech University in

Partial Fulfillment of

the Requirements for

the Degree of

MASTER OF SCIENCES

Approved

Dr. Brad Dabbert

Chair of Committee

Dr. Clint Boal

Dr. Kevin Mulligan

Mark Sheridan

Dean of the Graduate School

May, 2019

Texas Tech University, Jessica Mehta, May 2019

ii

ACKNOWLEDGMENTS

This research would not have been possible without the help of many amazing

and hard-working people. To my advisor, Dr. Brad Dabbert: thank you for taking me

on as a graduate student with the Quail-Tech Alliance, as well as for your guidance

and never-ending patience with me as I learned the ropes of being a graduate student.

I would like to thank my committee members, Dr. Clint Boal and Dr. Kevin Mulligan,

for their guidance during my thesis writing process.

I would like to thank all the people from the Quail-Tech Alliance for assisting

me in my research, especially Matthew McEwen, Rowdy White, and Byron Buckley

for always being there for me- on my best days and my worst. To Dr. Daniel Greene,

Dr. Blake Grisham, Natasia Mitchell, and Shea Mullican: this thesis would not have

been possible without you all. Most of all, I would like to thank my family, especially

my parents, and my dear friends who always gave me support to infinity and beyond

during the last three years.

Thank you to the landowners of the Quail-Tech Alliance Anchor Ranches for

participating in my study. Thank you to the Burnett Foundation and Quail First for

providing the funding for this research.


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TABLE OF CONTENTS

ACKNOWLEDGMENTS ...................................................................................... ii

ABSTRACT ........................................................................................................... iv

LIST OF TABLES .................................................................................................. v

I. ECOLOGY AND HISTORY OF NORTHERN BOBWHITES ON THE

ROLLING PLAINS OF TEXAS ........................................................................... 1

Ecology ................................................................................................................... 1

History to Present .................................................................................................... 5

Literature Cited ..................................................................................................... 10

II. SURVIVAL AND HOME RANGE ESTIMATES OF JUVENILE ...................

NORTHERN BOBWHITE ON THE ROLLING PLAINS OF TEXAS .............. 14

Introduction ........................................................................................................... 14

Methods ................................................................................................................. 17

Study Area ................................................................................................. 17

Field Methods ........................................................................................... 18

Analysis ..................................................................................................... 21

Survival Analysis ............................................................................ 21

Home Range .................................................................................... 22

Results ................................................................................................................... 23

Survival Analysis ...................................................................................... 23

Home Range .............................................................................................. 26

Discussion ............................................................................................................. 26

Literature Cited ..................................................................................................... 34


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ABSTRACT

The Rolling Plains of Texas have long been known for its diverse abundance

of wildlife, which include northern bobwhite. Landowners and wildlife managers

commonly report observing significant northern bobwhite numbers present in August

and September but observe an apparent decrease in quail numbers by November.

While many survival studies have been conducted on northern bobwhite in the past,

however, there is a dearth of information available regarding survival or home range

of the juvenile age class during late summer and early fall months.

I conducted a telemetry study from July-December during 2016 and 2017 to

analyze survival and home range of juvenile Northern bobwhite on the Rolling Plains

of Texas. My goal was to provide a possible explanation for the perceived

disappearance of Northern bobwhite observed by landowners. I used Program MARK

to generate survival estimates, and I found that weekly survival was 0.97 in 2016 and

0.91 in 2017. I used ArcMap 10.5 to analyze home ranges, and I found that home

ranges in 2016 across my study sites were larger than home ranges in 2017.

Ultimately, I concluded that while juvenile northern bobwhite survival and home

range are influenced by a variety of factors, rainfall is the most important factor

driving juvenile northern bobwhite demographics.


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LIST OF TABLES

2.1 List of individual covariates classified by study site used in

Program MARK analysis for 2016 survival estimates. Each

study site had a total of 18 covariates. All covarites were named

using the concatenate function in Microsoft Excel, where

month, temperature, precipitation, and name of ranch are

abbreviated. ............................................................................................... 38

2.2 List of individual covariates classified by study site used in

Program MARK analysis for 2017 survival estimates. Each

study site had a total of 18 covariates. All covarites were named

using the concatenate function in Microsoft Excel, where

month, temperature, precipitation, and name of ranch are

abbreviated. ............................................................................................... 39

2.3 Statistics for tagged birds by study site on the Rolling Plains of

Texas in 2016. Statistics include the totals for birds alive at the

end of the study, birds that died during the study, birds that

were censored from the study, and birds captured per study site .............. 40

2.4 Statistics for tagged birds by study site on the Rolling Plains of

Texas in 2017. Statistics include the totals for birds alive at the

end of the study, birds that died during the study, birds that

were censored from the study, and birds captured per study site .............. 40

2.5 Survival models and corresponding results generated by

Program MARK ........................................................................................ 41

2.6 Beta estimates for the Year survival model. Each parameter is

listed with its corresponding beta estimate, standard error, and

95% confidence intervals .......................................................................... 42

2.7 Beta estimates for the 2016 October Rainfall by Ranch model.

Each parameter is listed with its corresponding beta estimate,

standard error, 95% confidence intervals, and logistic regression

equation ..................................................................................................... 43

2.8 Beta estimates for the 2016 September Rainfall by Ranch

model. Each parameter is listed with its corresponding beta

estimate, standard error, 95% confidence intervals, and logistic

regression equation.................................................................................... 44

2.9 Beta estimates for the 2016 December Rainfall by Ranch

model. Each parameter is listed with its corresponding beta

estimate, standard error, 95% confidence intervals, and logistic

regression equation.................................................................................... 45


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2.10 Beta estimates for the 2016 August Rainfall by Ranch model.

Each parameter is listed with its corresponding beta estimate,

standard error, 95% confidence intervals, and logistic regression

equation ..................................................................................................... 46

2.11 Beta estimates for the 2016 June Rainfall by Ranch model. Each

parameter is listed with its corresponding beta estimate,

standard error, 95% intervals, and logistic regression equation................ 47

2.12 Minimum, maximum, and average home range sizes for

radiotagged birds from 2016-2017 by study site. Home range

values are measured in hectares. ............................................................... 48

2.13 Comparison of average adult and juvenile home ranges on the

Indian Canyon ranch on the Rolling Plains in 2017. Home

range values are measured in hectares ...................................................... 48

2.14 Weekly survival estimates generated by Program MARK for the

Year model. Each parameter is listed with its corresponding

beta estimate, standard error, and 95% confidence intervals .................... 49

2.15 Weekly survival estimates generated by Program MARK for the

5 competing models. Each estimate is listed with its

corresponding 95% confidence intervals .................................................. 49


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CHAPTER I

ECOLOGY AND HISTORY OF NORTHEN BOBWHITES ON THE ROLLING

PLAINS

ECOLOGY

The Rolling Plains of Texas is bordered by the Edwards Plateau ecoregion in the

south, the High Plains ecoregion in the west, and the Cross Timbers and Prairies

ecoregion in the east (Rollins 2007, Texas Parks and Wildlife Department 2019).

Precipitation for this ecoregion averages about 40-75 centimeters annually, with the

heaviest precipitation levels occurring in spring and summer. Temperatures in this

ecoregion often fluctuate between extremes, with blistering summers and mild to frigid

winters (Rollins 2007). Fine sand, clay, and loamy soils have given rise to a landscape

covered by rangelands and croplands (Rollins 2007, Texas Parks and Wildlife

Department 2019).

Mesquite (Prosopsis glandulosa) is the dominant plant across the Rolling Plains,

alongside junipers (primarily Juniperus pinchotii) and prickly pear (Opuntia spp.)

(Rollins 2007). The Rolling Plains is also home to various woody plants and grasses,

including lotebush (Ziziphus Obtusifolia), sand shinnery oak (Quercus havardii), catclaw

(Acacia spp.), netleaf hackberry (Celtis reticulatus), buffalograss (Buchloe dactyloides),

sideoats gramma (Bouteloua curtipendula), and silver bluestem (Bothricola

saccharoides) (Rollins 2007).

Among the four species of quail that inhabit Texas, northern bobwhites (Colinus

virginanus) are by far the most familiar to landowners and residents across the Rolling

Plains, along with scaled quail (Calipepla squamata) (Brennan et al. 2005). Northern

bobwhites are most often associated with the “ah, bob-white” call made by males during


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the breeding season and occur statewide, with populations present across all 10

ecoregions of Texas (Gould 1975b, Hernàndez and Peterson 2007, Agrilife Extension

Wildlife and Fisheries 2019).

A small galliform bird averaging 20.3 to 24.7 centimeters in length and weighing

between 140-190 grams, northern bobwhites have a physical structure built for short,

rapid bursts of flight (Chumchal 2000, Cornell Lab of Ornithology 2017, Agrilife

Extension Wildlife and Fisheries 2019). Their bodies are short and rounded, with a

wingspan ranging from 9 to 12 centimeters (Chumchal 2000, Hernàndez and Peterson

2007, Agrilife Extension Wildlife and Fisheries 2019).

Northern bobwhites have an overall mottled appearance, exhibiting a color pattern

of rufous, white, and black (Cornell Lab of Ornithology 2017, Agrilife Extension

Wildlife and Fisheries 2019). Males are the more colorful sex and are easily

distinguishable from females by their bright facial patterning, with a vivid black-and-

white striped face and a white throat. Females have a more subtle appearance, with a

buff-colored throat and eye stripe (Chumchal 2000, Cornell Lab of Ornithology 2017,

Agrilife Extension Wildlife and Fisheries 2019). Both males and females have a tufted

crest on the crown of their heads, which is used for various purposes, including attracting

a mate and displaying dominance (Agrilife Extension Wildlife and Fisheries 2019).

Habitat is a driving force for northern bobwhite populations, with numbers often

fluctuating due to habitat quality, habitat accessibility, and availability of sufficient food

and nesting resources (Rollins 2007, Mississippi State University 2019). On the Rolling

Plains, quail habitat is primarily influenced by rainfall and rangeland management

(Jackson 1962, Rollins 2007). Northern bobwhite habitat is mostly comprised of patchy


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areas that are a mosaic of woody edges, grasslands, shrublands, herbaceous cover, and

areas of bare ground (Roseberry and Sudkamp 1998, Rollins 2007, Cornell Lab of

Ornithology 2017, Agrilife Extension Wildlife and Fisheries 2019).

Northern bobwhites require five types of cover in order to survive and reproduce

successfully: nesting cover, loafing cover, escape cover, roosting cover, and brooding

cover (Rollins 2007). Breeding occurs during the months of February-October, with

clutch sizes consisting of 12-14 eggs per nest (Chumchal 2000, Hernàndez and Peterson

2007, Cornell Lab of Ornithology 2017, Agrilife Extension of Wildlife and Fisheries

2019). Nesting cover is the most important habitat requirement for northern bobwhite

and consists of a small bowl-shaped depression surrounded by bunchgrasses positioned in

a circle approximately 12 inches wide and 12 inches tall (Rollins 2007). The most

common bunchgrass used by northern bobwhite for nesting is little bluestem

(Schizachyrium scoparium) (Hernàndez 1999, Townsend et al. 2001, Rollins 2007).

Loafing cover contains dense vegetation approximately 1-3 meters high and

provides protection from avian predators while simultaneously permitting quail clear

visibility at ground level (Rollins 2007). Acceptable loafing cover for northern

bobwhites include lotebush, elbowbush (Forestieria pubescens), and fourwing saltbush

(Atriplex canescens) (Rollins 2007). Escape cover consists of mostly dense, usually

prickly brush that allows quail to escape and hide from predators (Rollins 2007). Some

forms of escape cover used by Northern bobwhites on the Rolling Plains include

mesquite, prickly pear, and various bunchgrasses (Rollins 2007).

Roosting cover, unlike the other types of cover, requires little to no overhead

vegetation (Virginia Department of Game and Inland Fisheries 2019). When roosting


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during the evening, quail sit in a circle in a relatively open area in order to a) retain good

visibility and watch for predators and b) flush quickly if a predator is spotted (Virginia

Department of Game and Inland Fisheries 2019).

Brooding cover is a primary concern for quail chicks, particularly during the

initiation of the breeding season in February-March (Hernàndez and Peterson 2007,

Rollins 2007, Agrilife Extension Wildlife and Fisheries 2019). This cover type must

provide ample sources of food (e.g. insects), especially protein- which is critical for

growing quail chicks- and protection from predators (Hernàndez and Peterson 2007,

Rollins 2007). Acceptable plants for brooding cover include pigweed (Amaranthus spp.),

kochia (Kochia scoparia), and Russian thistle (Salsola iberica) (Rollins 2007).

In addition to providing protection and reproductive sites, vegetation used by

northern bobwhite also provides a significant amount of their diet (Hernàndez and

Peterson 2007, Rollins 2007). Northern bobwhites are primarily granivorous. Seeds

from various forbs, woody plants, and grasses make up almost 90% of northern bobwhite

diet during the fall and winter, along with varying amounts of greens and insects,

particularly during the Spring (Rollins 2007). Some common staples for northern

bobwhite include seeds of western ragweed (Ambrosia cumanensis), mesquite,

Johnsongrass (Sorghum halepense), and buffalobur (Solanum rostratum) (Rollins 2007).

Grasshoppers are the most frequently consumed insect, especially for bobwhite chicks

and adult females during the spring (Hernàndez and Peterson 2007, Rollins 2007).

Northern bobwhites do not require standing water, as they often use preformed water

(Guthery 2000, Rollins 2007, Agrilife Extension of Wildlife and Fisheries 2019).


5

Northern bobwhites are a relatively short-lived bird, usually capable of living up

to 6-12 months in the wild (Chumchal 2000, Hernàndez and Peterson 2007). Numerous

studies have examined survival in northern bobwhite adults and chicks (Burger et al.

1995, Dixon 1996, DeMaso 1997, Brennan 1999). However, there are currently little

data on northern bobwhite survival or dispersal over the late summer and early fall

periods, during which chicks are transitioning into juveniles.

The available literature suggests that juvenile northern bobwhites are capable (or

more inclined) of dispersing for longer distances than adult northern bobwhites (Fies et

al. 2002, Townsend et al. 2003). Fies et al. (2002) in Virginia reported that a) a higher

portion of juveniles (28%) dispersed more than 2 km compared to adults (10%), b)

juveniles moved farther between wintering and breeding regions than adults, c) juvenile

males were the most inclined to disperse, and d) adult males were the least inclined to

disperse. Howard (1960) suggested that juveniles are more inclined to disperse to avoid

inbreeding in populations. Fies et al. (2002) also suggested that adult males may be less

likely to disperse if they have success in obtaining a mate close to their area of residence.

Based on the available literature, I believe that the disappearance of northern bobwhites

observed by landowners and hunters could be explained by long-distance movements of

juvenile birds during the late summer and early fall periods.

HISTORY TO PRESENT

The northern bobwhite is one of North America’s most heavily researched birds

(Guthery 1997, Rollins 2007, Brennan et al. 2014). Additionally, as one of the most

hunted game birds, it is of critical economic importance, particularly in the southern and

midwestern regions of the United States (Chumchal 2000, Rollins 2007). Northern


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bobwhites used to occur in Texas on an unprecedented scale, with populations numbering

into the millions (Dimmick et al. 2002). In 1960, the Bureau of the Census put the

number of bagged quails during the hunting season at 98 million birds, most of which

were northern bobwhites (Jackson et al.1990).

By the start of the 1980s, northern bobwhite populations began to decline sharply.

The Northern Bobwhite Conservation Initiative calculated that northern bobwhite

populations fell drastically from 58,857,000 to 20,241,000 birds from 1980-1999

(Dimmick et al. 2002). Rollins (2007) noted that, per Texas Parks and Wildlife

Department data, northern bobwhite harvest declined across the Rolling Plains from

1981-2001; harvest was high (668,167 birds) in 1982, compared to a much lower harvest

(87,570 birds) in 1996. Additionally, Rollins (2007) noted that northern bobwhite

populations had declined annually by 3.5% from 1980-2001. This is in keeping with the

trend observed by Jackson (1962), who stated that northern bobwhites exhibit a “boom

and bust” growth cycle that is correlated directly to annual precipitation averages (Koerth

and Guthery 1991, Rollins 1999, Hernàndez et al. 2005, Tri et al. 2013).

Rollins (1999) cited Jackson (1962) while dividing this “boom and bust” cycle

into 5 steps: a) periods of extreme drought are followed by b) a year of average rainfall,

which is then followed by c) a year of excessive rainfall, and d) a year of normal rainfall,

which can all lead to e) a crash in Northern bobwhite populations if food or cover is not

built up adequately before the breeding season in Spring. A study by Koerth and Guthery

(1991) found that a substantial decrease in water can lead to decreased (and perhaps

cause a cessation of) reproduction in northern bobwhite populations. Clearly, northern


7

bobwhite demographics and annual precipitation unequivocally have a direct relationship

(Koerth and Guthery 1991, Rollins 1999, Hernàndez et al. 2005, Tri et al. 2013).

Numerous studies have been conducted to address the decline in northern

bobwhite populations (Brennan et al. 2014). The introduction of radio telemetry has been

an incredible asset to northern bobwhite studies (White and Garrot 1990). Through the

use of radio telemetry, researchers have been able to examine a myriad of aspects

concerning northern bobwhite demographics, including habitat use, dispersal patterns,

survival, reproduction, mating systems, and more (White and Garrot 1990, Burger et al.

1995, Dixon et al. 1996,Townsend et al. 2003, Cox et al. 2004, Cook et al. 2009, Buckley

et al. 2015). However, over the years, there has been much controversy within the

scientific community about whether this method of analyzing survival should be used.

Per White and Garrot (1990), some noticeable effects on animals from radiotags

(particularly in avian studies) have included aggravation of the skin (Bartholomew 1967,

Hessler et al. 1970), hair and/or feather loss (Bartholomew 1967, Hessler et al. 1970),

snagging of the antenna on vegetation or other objects (Burger et al. 1995), and the

possibility of electrocution for birds perched on telephone poles and power lines

(Dunstan 1977). Guthery and Lusk (2004) also observed that the estimates of survival

from radio telemetry studies tend to be extremely low and therefore these estimates

shouldn’t be used as a valid source of data. However, White and Garrot (1990) argue that

there is plenty of good information available when it comes to survival studies of various

animals, including northern bobwhites.

Despite the possible impacts of these effects on radiotagged animals, there has

been much support for the use of radiotelemetry in northern bobwhite survival studies. A


8

study by Mueller et al. (1988) using only male northern bobwhites reported that survival

rates did not differ between marked and un-marked males. Terhune et al. (2007) found

that there was no evidence for adverse effects of radiotransmitters while measuring

factors effecting northern bobwhite survival in Georgia. I chose to use radio telemetry to

conduct my study because a) it has been used by my colleagues in the past with reliable

results, b) it is the most financially feasible and updated technology available to us, and

c) it can be used on a broad scale, without which this project could not be done.

Prior to the start of 2016, landowners and hunters reported to the Quail-Tech

Alliance that they would see lots of northern bobwhite in August and September, but very

few during the start of hunting season (late October-February). While numerous studies

have indicated that northern bobwhite populations exhibit a “boom and bust” growth

cycle, indicating that fluctuations in populations is a natural occurrence, this

disappearance of quail during the late summer to early fall periods remains unexplained

(Koerth and Guthery 1991, Rollins 1999, Hernàndez et al. 2005, Tri et al. 2013).

In this study, I addressed two major aspects of northern bobwhite populations.

Firstly, I examined survival of young-of-the-year (i.e. juvenile) birds during the late

summer to early fall. Secondly, I examined home range among young-of-the-year birds

(i.e., where do they move during the late summer and early fall). The results of each

component are presented in chapter 2. My results should give valuable information

concerning a) possible factors contributing to the reduced sightings of northern bobwhite

during this late summer to early fall period, b) survival of young-of-the year birds during

this period, and c) associated movement patterns of young-of the year birds during this


9

period in an effort to provide an explanation for these reduced sightings, and conversely,

to provide vital information that could aid in management solutions.


10

LITERATURE CITED

Agrilife Extension Wildlife and Fisheries. 2019. Northern bobwhite.

<https://wildlife.tamu.edu/quail/northern-bobwhites/>. Accessed 8 March 2019.

Bartholomew, R.M. 1967. A study of the winter activities of bobwhites through the use

of radiotelemetry. Occasional Papers of the C.C. Adams Center for Ecological

Studies 17:1-25.

Brennan, L.A. 1999. Northern bobwhite (Colinus virginianus). Account 397 in A. Poole

and F. Gill, editors. The birds of North America. The Academy of Natural

Sciences, Philadelphia, Pennsylvania, and The American Ornithologists’ Union,

Washington, D.C., USA.

Brennan, L.A., S. DeMaso, F. Guthery, J. Hardin, C. Kowaleski, S. Lerich, R. Perez, M.

Porter, D. Rollins, M. Sams, T. Trail, and D. Wilhelm. 2005. Where have all the

quail gone. The Texas Quail Conservation Initiative, Texas, USA.

Brennan, L. A., F. Hernandez, and D. Williford. 2014. Northern Bobwhite (Colinus

virginianus). Version 2.0. in A. Poole and F. Gill, editors. The birds of North

America. The Academy of Natural Sciences, Philadelphia, Pennsylvania, and The

American Ornithologists’ Union, Washington, D.C., USA.

Buckley, B.R., A.K. Andes, B.A. Grisham, and C.B. Dabbert. 2015. Effects of

broadcasting supplemental feed into roadside vegetation on home range and

survival of female northern bobwhite. Journal of Wildlife Management 39(2):

301-309.

Burger, L.W. Jr., T.V. Dailey, E.W. Kurzejeski, and M.R. Ryan. 1995. Survival and

cause-specific mortality of northern bobwhite in Missouri. Journal of Wildlife

Management 59(2):401-410.

Chumchal, M. 2000. Colinus virginianus. Animal Diversity Web.

<https://animaldiversity.org/accounts/Colinus_virginianus/>. Accessed 1 March

2019.

Cook, P.M., R.G. Hamrick, and J.P. Carroll. 2009. Effects of sex, age, and habitat on

northern bobwhite spring dispersal patterns. Gamebird 135-145.

Cornell Lab of Ornithology. 2017. Northern bobwhites.

<https://www.allaboutbirds.org/guide/Northern_Bobwhite/id>. Accessed 9 March

2019.


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Cox, S.A., A.D. Peoples, S.J. DeMaso, J.R. Lusk, and F.S. Guthery. 2004. Survival and

cause-specific mortality of northern bobwhites in western Oklahoma. Journal of

Wildlife Management 68(3):663-671.

DeMaso, S.J., A.D. Peoples, S.A. Cox, and E.S. Perry. 1997. Survival of northern

bobwhite chicks in western Oklahoma. Journal of Wildlife Management 61(3):

846-853.

Dimmick, R.W., M.J. Gudlin, and D.F. McKenzie. 2002. The northern bobwhite

conservation initiative. Miscellaneous publication of the Southeastern

Association of Fish and Wildlife Agencies, South Carolina. 96 pp.

Dixon, K.R., M.A. Horner, S.R. Anderson, W.D. Henriques, D. Dunham, and R.J.

Kendall. 1996. Northern bobwhite habitat use and survival on a South Carolina

plantation during winter. Wildlife Society Bulletin 24(4):627-635.

Dunstan, T.C. 1977. Types and uses of radio packages for North American Falconiform

and Strigiform birds. Pages 30-39 in F.M. Long, editor. Proceedings of the 2nd

International Conference of Wildlife Biotelemetry. University of Wyoming,

Laramie, USA.

Fies, M.L., K.M. Puckett, and B. Larson-Brogdon. 2002. Breeding season movements

and dispersal of northern bobwhites in fragmented habitats of Virginia. Pages

173-179 in S.J. DeMaso, W.P. Kuvlesky Jr., F. Hernàndez and M.E. Burger,

editors. Quail V Proceedings of the Fifth National Quail Symposium. Texas

Parks and Wildlife Department, Austin, Texas, USA.

Gould, F.W. 1975b. Texas plants- a checklist and ecological summary. Texas

Agricultural Experiment Station Miscellaneous Publication 585- revision.

College Station, Texas, USA.

Guthery, F.S. 1997. A philosophy of habitat management for northern bobwhites. Journal

of Wildlife Management 61:291-301.

Guthery, F. S., N.M. King, K.R. Nolte, W.P. Kuvlesky Jr., S. DeStefano, S.A. Gall, and

N.J. Silvy. 2000. Comparative habitat ecology of Texas and masked bobwhites.

Journal of Wildlife Management 64:407-420.

Guthery, F. S. and J.L. Lusk. 2004. Radiotelemetry studies: are we radio-handicapping

northern bobwhites? Wildlife Society Bulletin 32(1):194-201.

Hernàndez, F. 1999. The value of prickly pear cactus as nesting cover for northern

bobwhite. Dissertation, Texas A & M University-Kingsville, College Station,

Texas, USA.


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Hernàndez, F., F. Hernàndez, J.A. Arredondo, F.C. Bryant, L.A. Brennan, and R.L.

Bingham. 2005. Influence of precipitation on demographics of northern bobwhite

in southern Texas. Wildlife Society Bulletin 33(3):1071-1079.

Hernàndez, F., and M.J. Peterson. 2007. Northern bobwhite ecology and life history.

Pages 117–141. in Texas Quails:Ecology and Management, Chapter 4, Texas

A&M University, College Station, USA.

Hessler, E., J.R. Tester, D.B. Siniff, and M.M. Nelson. 1970. A biotelemetry study of

survival of pen-reared pheasants in selected habitats. Journal of Wildlife

Management 34:267-274.

Howard, W.E. 1960. Innate and environmental dispersal of individual vertebrates.

American Midland Naturalist 63(1):152-161.

Jackson, A.S. 1962. A pattern to population oscillations of the bobwhite quail in the

lower plains grazing regions of northwest Texas. Proceedings Southeastern

Association Game and Fish Commissioners 16:120-126.

Jackson, A. S., Clyde Holt., and D.W. Lay. 1990. Bobwhite quail in Texas. Texas Parks

and Wildlife Publication.

Koerth, N.E. and F.S. Guthery. 1991. Water restriction on northern bobwhite

reproduction. Journal of Wildlife Management 55:132-137.

Mississippi State University. 2019. Bobwhite quail (Colinus virginianus).

<http://www.naturalresources.msstate.edu/wildlife/northern-bobwhite-quail.asp>.

Accessed 12 March 2019.

Mueller, B. S., J. B. Atkinson Jr., and T. DeVos. 1988. Mortality of radio-tagged and

unmarked northern bobwhite quail. Biotelemetry X: Proceedings of the Tenth

Symposium on Biotelemetry 10:139–144.

Rollins, D. 1999. A pattern to quail irruptions in the rolling plains of Texas. Texas

Agricultural Extension Service, San Angelo.

Rollins, D. 2007. Quails on the rolling plains. Pages 117–141. in Texas Quails: Ecology

and Management, Chapter 7, Texas A&M University, College Station, USA.

Roseberry, J. L., and S.D. Sudkamp. 1998. Assessing the Suitability of Landscapes for

Northern Bobwhite. The Journal of Wildlife Management 62(3):895-902.

Terhune, T.M., D.C. Sisson, J.B. Grand, and H.L.Stribling. 2007. Factors influencing

survival of radiotagged and banded northern bobwhites in Georgia. Journal of



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Texas Parks and Wildlife Department. 2019. Quail forecast 2018-2019.

<http://tpwd.texas.gov/huntwild/hunt/planning/quail_forecast/forecast/>.


Townsend, D.E., II, R.E. Masters, R.L. Lochmiller, D.M. Leslie Jr., S. J. DeMaso, and

A.D. Peoples. 2001. Characteristics of nest sites of northern bobwhites in western

Oklahoma. Journal of Range Management 54:260-264.

Townsend, D. E., II, D.M. Leslie Jr., R.L. Lochmiller, S.J. DeMaso, S.A. Cox, and A.D.

Peoples. 2003. Fitness costs and benefits associated with dispersal in northern

bobwhites (Colinus virginianus). American Midland Naturalist 150(1):73-82.

Tri, A.N., J.P. Sands, M.C. Buelow, D.W., E.M. Wehland, J.A. Larson, K.A. Brazil, J. B.

Hardin, F. Hernàndez, and L.A. Brennan. 2013. Impacts of weather on northern

bobwhite sex ratios, body mass, and annual production in south Texas. Journal of


Virginia Department of Game and Inland Fisheries. 2019. Roosting.

<https://www.dgif.virginia.gov/quail/get-to-know-bobwhite/roosting/>. Accessed

15 March 2019.

White, G.C., and R.A. Garrot. 1990. Analysis of wildlife radio-tracking data. Academic

Press, Inc., San Diego, California, USA.


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CHAPTER II

SURVIVAL AND HOME RANGE ESTIMATES OF JUVENILE NORTHERN

BOBWHITE ON THE ROLLING PLAINS OF TEXAS

INTRODUCTION

The northern bobwhite (Colinus virginianus) is one of the most commonly

recognized game birds in North America, with its range extending to the midwestern and

southeastern regions of the United States, the Caribbean, and Mexico (American Bird

Conservancy 2017). Since the late 1960’s, population trend estimates for northern

bobwhite have declined sharply (Brennan 1991, United States Geological Survey 2015,

American Bird Conservancy 2017). Texas Parks and Wildlife Department data stated

that the mean number of northern bobwhites observed per survey route for 2018 was

5.43, a drastic drop compared to 2017 (26.72) and 2016 (53.89) (Texas Parks and

Wildlife Department 2019). The mean number of northern bobwhites observed per

survey route for 2018 is comparable to observations in 2011 (5.39) and 2012 (3.80),

which were years of severe drought in the Rolling Plains (Texas Parks and Wildlife

Department 2019). Many causes have been linked to these declines, including habitat

loss and/or degredation, predation (avian and mammal), poor land management (i.e.

overgrazing by cattle), and drought (Brennan et al. 2005, American Bird Conservancy

2017).

Drought and quail population fluctuations are not new phenomena in the Rolling

Plains. In fact, Jackson (1962) described this boom and bust sequence and referred to the

large population response to plentiful precipitation after drought as a quail irruption.

Unfortunately, analyses of data from the past 2 decades in the Rolling Plains of Texas

suggests quail populations are not responding with the same magnitude of population


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increase upon receiving above “normal” precipitation following drought (Texas Parks

and Wildlife Department 2013). Some evidence from field observations suggests

bobwhites might be successfully breeding but then disappearing before the hunting

season. Landowners commonly report observing significant quail populations present in

August and September, but few to no quail in November. However, no data are available

that documents this late summer to early fall bobwhite disappearance in the Rolling

Plains of Texas. The length of bobwhite telemetry studies is limited by radiotransmitter

life, which is usually 9 to 11 months. Most studies concentrate on the wintering period or

a reproductive period that ends in late July or August. These constraints prevent

monitoring from occurring during the critical period of late August to early October.

Data concerning the precise timing, geographic extent, incidence within and

among coveys, and corresponding environmental conditions of bobwhite mortalities

might provide essential evidence that explains the cause or causes of this decline. These

data could be obtained by radiomarking and monitoring bobwhites prior to the typical

period of disappearance. For instance, radiotelemetry studies were instrumental in

revealing the influence of West Nile Virus on Greater Sage Grouse (Centrocercus

urophasianus) survival (Walker et al. 2007) and the influence of cecal nematodes on Red

Grouse (Lagopus lagopus) survival (Hudson et al. 1992). These studies documented

mortality in the field that led to identification and understanding of the specific causes of

mortality. The specific timing, rate of spread, or spatial extent of the bobwhite

disappearance is unknown. The current uncertainty concerning the cause of the late

summer and early fall disappearance of bobwhites could lead to missteps in how we use

our limited resources (Johnson et al. 2014). A telemetry study that monitors bobwhite


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survival across the landscape during this period of disappearance could reduce this

uncertainty in our knowledge and improve our ability to manage bobwhite populations in

the Rolling Plains of Texas.

Alternative to large scale mortality, movement or dispersal of bobwhites away

from an area could explain local disappearance on a property. A fall shuffle dispersal

event is known to occur in bobwhites (Hernàndez and Peterson 2007) and could be a

possible explanation for the reduced sightings of northern bobwhites in early fall. Many

investigators have examined northern bobwhite movement (Townsend et al. 2003, Cook

et al. 2009). However, few studies have been conducted to determine home range and

dispersal patterns of juvenile northern bobwhites. Based on the available literature, I

hypothesize that the disappearance of northern bobwhites observed by landowners and

hunters could be due to long-distance movements of the birds during the late summer and

early fall periods.

Survival estimates for northern bobwhite adults (Dixon et al. 1996, Sisson et al.

2000, Taylor et al. 2000, Cox et al. 2004, Buckley et al. 2015) and chicks (Lochmiller et

al. 1993, DeMaso et al. 1997, Mueller et al. 1999) have been thoroughly examined for

years. Adult survival generally averages between 18 to 30 percent annually (Jackson

1962, Roseberry and Klimstra 1984, Hernàndez and Peterson 2007), while chick survival

has been estimated as high as 36.7% (DeMaso et al. 1997). Additionally, many studies

have examined home range of adult northern bobwhites (Sisson et al. 2000, Townsend et

al. 2003, Buckley et al. 2015). Little to no research, however, has been conducted to

evaluate survival and home range for young-of-the year (i.e. juvenile) birds. Research in

this area could aid in land management techniques and could provide insights to


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enhancing northern bobwhite populations. Consequently, I conducted a 6-month broad-

scale telemetry study during 2016 and 2017 to estimate home range and survival rates for

juvenile northern bobwhites during the late summer and early fall on the Rolling Plains of

Texas. My objective for this study was to find a possible explanation for the reduced

sightings of northern bobwhites during this late summer to early fall period.

METHODS

Study Area

My study sites were chosen because of their availability and degree of spread

across the landscape. This spread allowed me to examine the spatial extent of this

disappearance in Northern bobwhites. Additionally, one study site (the Clark Ranch) was

chosen because several dead Northern bobwhites had been found intact on the property.

All study sites are Quail-Tech Alliance Anchor Ranches, and all study sites are

dispersed across the Rolling Plains of Texas. The study site names and locations are as

follows: the Esperanza Ranch in Spur, the Indian Canyon Ranch in Lamesa, the

Pitchfork Ranch in Guthrie, the Double Fork Ranch in Clairemont, and the Clark Ranch

in Sweetwater. In 2016, birds were captured and monitored at all 5 study sites. In 2017,

birds were captured and monitored at only 3 of the 5 study sites (the Esperanza Ranch,

the Indian Canyon Ranch, and the Pitchfork Ranch). All 5 study sites exhibit weather

patterns that reflect the trend of extremes in the Rolling Plains; the climate in these areas

is mixed, ranging from searing hot temperatures in the summer to quite lower

temperatures during the early winter (Rollins 2007). The average precipitation in the

Rolling Plains is extremely variable, fluctuating from 40.64 centimeters in the western

areas to as much as 76.20 centimeters in the eastern areas (Rollins 2007). The wet season


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for the Rolling Plains is often during the spring and summer months, with occasional

apexes in May and September (Rollins 2007).

Dominant plants in the Rolling Plains that are known for high use by northern

bobwhite include mesquite (Prosopsis glandulosa), junipers (mainly Juniperus pinchotii),

prickly pear (Optunia spp.), lotebush (Ziziphus Obtusifolia), sand shinnery oak (Quercus

havardii), catclaw (Acacia spp.), and netleaf hackberry (Celtis reticulatus) (Rollins

2007). Common grasses in the Rolling Plains that are known for high use by Northern

bobwhite include buffalograss (Buchloe dactyloides), sideoats gramma (Bouteloua

curtipendula), and silver bluestem (Bothricola saccharoides) (Rollins 2007).

The Esperanza Ranch in Spur is mostly dominated by 16-21″ deep hardland and

limey upland ecological systems. The Indian Canyon Ranch in Lamesa is mostly

dominated by 16-21″ shallow and hardland slopes ecological systems. The Pitchfork

Ranch in Guthrie is mostly dominated by 19-26″ lakebed and loamy bottomland

ecological systems. The Double Fork Ranch in Clairemont is mostly dominated by 16-

24″ hardland slopes and 20-24″ gravelly ecological systems. The Clark Ranch in

Sweetwater is mostly dominated by 19-26″ loamy bottomland and 23-31″ clay loam

ecological systems (Web Soil Survey 2017).

Field Methods

I conducted a telemetry study running from July-December of 2016 and 2017,

thus encompassing the periods of late summer and early fall in which disappearances of

northern bobwhites were noted. All birds were trapped under the authority of a Texas

Parks and Wildlife Scientific Collecting Permit. Birds were trapped using wire funnel

traps (Stoddard 1931). In order to place emphasis on young-of-the year (i.e. juvenile)


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birds, I began trapping in late July through the end of August (or until I reached my

minimum sample size of 100 birds). To get a statistically appropriate sample size, I

attempted to capture 20-30 birds per study site (Krejcie and Morgan 1970). Traps were

baited with milo, a type of supplemental feed commonly used and preferred by quail

(Michael and Beckwith 1955).

Traps were set around dawn (around 6:00-6:30 a.m.) in correlation with northern

bobwhite covey movements and early morning feeding times (Pierce and Gallagher

2005). To protect birds from predators and provide sufficient cover from the summer

heat, all traps were covered with available vegetation (i.e. grasses, junipers, mesquite

branches). Traps were checked at least 2 times per day and monitored frequently to

reduce risk of injury (American Ornithologists Union 1988). No water was placed in the

traps based on the ecological premise that quail do not need surface water (Hernàndez et

al. 2005).

Upon checking the traps, I immediately transferred all bobwhites into a ventilated

box that was placed either under the truck bed (or in another thoroughly shaded area) or

inside the truck where there was sufficient air conditioning. All non-target species were

released immediately. Birds were taken from the ventilated box and placed individually

into a ventilated bag until processing began. Birds were held with the neck between the

first and second fingers, with the other fingers gently encompassing the rest of the body

(American Ornithologists Union 1988).

I recorded the sex (when possible) and age of each bird (Rosene 1969). Each bird

was weighed to the nearest gram using an Ohaus HH120 digital pocket scale (Ohaus

Corporation, Parsippany NJ). Age was determined using primary coverts (i.e., juvenile


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birds have buffy-tipped primary coverts) (Koerth et al.1991, Pierce and Gallagher 2005).

All juvenile birds weighing ≥120 grams were banded with an aluminum band (National

Band Tag & Co, No. 8 bands) and fitted with a 6.0 necklace-style radiostransmitter

(American Wildlife Enterprises). This insured that transmitters weighed ≤ 5% of the

bobwhites body weight. After the radiotransmitter and band were secured, I drew blood

from the brachial vein by gently poking it with a sterile needle. Blood was then

transferred into tubes labeled with the band number, ranch name, and date.

I used radiotelemetry to monitor survival and movement of radio-marked juvenile

northern bobwhites from late July until the first week of December (White and Garrot

1990). Birds were tracked using a hand-held yagi (AF Antronics, Inc) and a receiver

(Communication Specialists, Inc). Birds at each study site were checked 1-2 times a

week, time and weather permitting. Birds were tracked as early in the day as possible to

account for unexpected and/or long-distance movement. Birds were not flushed, if

possible, to prevent movement bias (White and Garrot 1990). To get an exact location

without flushing the birds, I would circle an individual bird, get a visual, and use a

rangefinder. I recorded the new location and status of each bird, and maps were made

using Google Maps for day-to-day monitoring purposes.

Birds were not tracked up to 7 days after capture to account for capture myopathy

and adjustment to the radiotransmitter (Kurzejeski et al. 1987, Pollock et al. 1989, White

and Garrot 1990). Due to time constraints and limited manpower, this period was

extended up to more than 7 days for some birds. During this time, I checked birds’

frequencies to make sure that no mortality signal was detected, but I did not get an exact

location. Birds who did not survive this period were removed from the study and any


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statistical analysis (Kurzejeski et al. 1987, Burger et al. 1995, Pollock et al. 1989, White

and Garrot 1990).

I assigned three possible fates: dead, alive, or unknown. I took photos of any

dead birds or kill sites. When possible, the cause of death was determined using physical

evidence at the kill site (Dumke and Pils 1973). I categorized cause(s) of death as

follows: mammalian predation, raptor predation, other (e.g. death from weather

conditions), and unknown.

Analysis

Survival Analysis

Because the fate of each bird was known during the study, I ran a known-fate

analysis in Program MARK to estimate survival rate (Cooch and White 2006). The study

periods for 2016 and 2017 lasted 19 weeks each (i.e. 19 intervals). I set up my analysis

using a staggered entry design, in which a bird received a coding of 00 for each interval

until it was tagged. Additionally, a coding of 00 was entered for each interval following

the death of a bird. Birds that were removed or censored from the study followed the

guidelines set in previous survival studies (Burger et al. 1995, Curtis et al. 1988,

Kurzejeski et al. 1987). Birds were removed from the study if they did not survive the 7-

day conditioning period following capture, and birds were censored from the study if

there was a radio failure, radio loss, or they emigrated from the study site.

I recorded 136 individual encounter histories, and I recorded 11 attribute groups

categorized by study site, year, and month of capture (Esperanza, Indian Canyon,

Pitchfork, Clark, Double Fork, 2016, 2017, July, August, September, October).

Additionally, I recorded 144 individual covariates (90 in 2016, 54 in 2017) (Table 2.1,


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Table 2.2). My covariates were chosen based on factors known to influence northern

bobwhite survival such as year, temperature, precipitation, and month/season (Jackson

1962, Hernàndez et al. 2005, Rollins 2007). All temperature and precipitation data were

obtained from the West Texas Mesonet National Wind Institute (2016 and 2017). Data

for each study site was retrieved from the Mesonet station in the nearest county

(Aspermont for the Double Fork Ranch, Guthrie for the Pitchfork Ranch, Lamesa for the

Indian Canyon Ranch, Spur for the Esperanza Ranch, Sweetwater for the Clark Ranch).

Initially, I ran models for year, ranch, month of capture, temperature, precipitation, and a

time constant model (in which each day held the same probability of survival). In total, I

created 56 models in Program MARK. Competing models are discussed further for

models with a ΔAIC ≤ 3.0 (Burnham and Anderson 2002).

Home Range

I used Arc Map 10.5 to calculate an MCP (Minimum Convex Polygon) and

determine a home range size for each radiotagged individual. To generate each MCP, I

firstly uploaded a Microsoft spreadsheet containing bird ID (i.e. leg band number),

date(s) located, latitude coordinates, and longitude coordinates into Arc Map. Using the

“Display XY Data” function, I displayed the coordinates for each individual on a county

basemap supplied by the Quail-Tech Alliance (Dickens County for the Esperanza Ranch,

Dawson County for the Indian Canyon ranch, Kent County for the Double Fork Ranch,

King County for the Pitchfork Ranch, Nolan County for the Clark Ranch). All

coordinates were projected using the WGS_1984 Geographic Coordinate System.

To maintain consistency, any birds that were removed from the MARK survival

analysis were also excluded from the home range analysis. Additionally, I censored any


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birds that had ≤ 2 locations. For this reason, there are no results for my home range

analysis at the Pitchfork Ranch in 2017, as the one bird I captured had only 2 locations.

After I displayed the coordinates for an individual bird, I generated an MCP by using the

“Minimum Bounding Geometry” option located in the Data Management section of

ArcToolbox. Each MCP was labeled with the ranch, year, and bird ID. To calculate area

of each MCP (i.e. home range), I used the “Calculate Geometry” function. The area of

each MCP was calculated in hectares.

Once I calculated the home ranges of the individuals in a study site, I put all the

home range values into a Microsoft Excel spreadsheet and calculated the average home

range size for that study site using the “AVG” function. Additionally, I recorded the

individuals with the smallest and largest home ranges and calculated the corresponding

values using the “MIN” and “MAX” functions in Microsoft Excel. For the 2017 data, I

had 9 radiotagged adults in my sample at the Indian Canyon Ranch due to the limited

capture success of juvenile birds. To test the observations found in the current literature

concerning adult and juvenile Northern bobwhite home range sizes, I averaged both the

adult and juvenile home range sizes within this study site for comparison.

RESULTS

Survival Analysis

I tagged 145 birds during 2016 and 2017 (104 in 2016, 41 in 2017, Table 2.3,

Table 2.4). I tagged birds across all 5 study sites during my 2016 field season. I tagged

birds across only 3 of my 5 study sites during my 2017 field season due to limited capture

success. All tagged birds in 2016 were juveniles. In 2017, I used 10 adults in my sample


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due to the limited abundance of juvenile birds. Of the 104 birds tagged in 2016, 24 birds

(23.1%) died during the study, 45 birds survived the study (43.2%), 35 birds were

censored from the study (33.7%) and 5 (4.8%) birds were removed from the study and

any subsequent analyses (Table 2.3). Of the 41 birds tagged in 2017, 26 (63.4%) birds

died during the study, 10 (24.3%) birds survived the study, 5 birds (12.1%) were

censored from the study, and 4 (9.8%) birds were removed from the study and any

subsequent analyses (Table 2.4).

Of the 56 models I ran in Program MARK, I am reporting the first 16, as they fall

within 3 ΔAICc units of the top competing model (Table 2.5). Of those 16 models, I will

be discussing the top 6 competing models, as they are the most relevant to the results of

this study. Each model generated Beta estimates for survival probability across each

study site and included a constant regression line. The beta estimates were graphed

following the logistic regression formula below, where P represents the probability of

survival, e represents the base of the natural logarithm, and a and b represent the

parameters of the model (University of South Florida 2019).

For each model, the logistic regression equation line is represented by the following

equation: logit survival= (beta estimate of study site) + [(monthly beta estimate for

rainfall or temperature) x (total monthly rainfall or temperature)] (Table 2.6-2.11). This

equation ultimately states that for X inches of rainfall, survival increases by a given

percentage.

The Year model carried the most weight, suggesting that year is most likely the

biggest factor driving juvenile northern bobwhite survival (Table 2.5). The confidence


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intervals for the Year model did not overlap, demonstrating that there is a significant

difference in survival between 2016 and 2017 (Table 2.5, Figure 2.2). The Year model

was followed in weight by the 2016 October Rainfall by Ranch, the 2016 September

Rainfall by Ranch, the 2016 December Rainfall by Ranch, the 2016 August Rainfall by

Ranch, and the 2016 June Rainfall by Ranch models. It is important to note that of the 6

competing models, 5 of the models included rainfall as a covariate.

In terms of juvenile survival, the 2016 October Rainfall by Ranch model showed

that the Clark Ranch had the highest beta estimate, while the Double Fork Ranch had the

lowest beta estimate (Table 2.7). The 2016 September Rainfall by Ranch model showed

that the Indian Canyon Ranch had the highest beta estimate, while the Clark Ranch had

the lowest beta estimate (Table 2.8). The 2016 December Rainfall by Ranch model

showed that the Indian Canyon Ranch had the highest beta estimate, while the Double

Fork Ranch had the lowest beta estimate (Table 2.9). The 2016 August Rainfall by

Ranch model showed that the Clark Ranch had the highest beta estimate, while the

Double Fork Ranch had the lowest beta estimate (Table 2.10). The 2016 June Rainfall by

Ranch model showed that the Indian Canyon Ranch had the highest beta estimate, while

the Clark Ranch (Table 2.11).

The AIC weights (Table 2.5) and beta estimates for the 6 competing models

(Table 2.6-2.11) collectively demonstrate that juvenile survival is driven by year and

rainfall levels. The beta estimates also clearly show that winter rainfall levels are more

important to juvenile survival than summer rainfall levels, results of which are

substantiated by current literature (Hernàndez et al. 2005). Additionally, the beta


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estimates from the competing models demonstrate that warm, wet winters have the

potential for greater juvenile survival rates of Northern bobwhite within these study sites.

Home Range

The average home range sizes for juvenile northern bobwhites varied across study

sites from 2016-2017 (Table 2.12). The average home range size of juvenile northern

bobwhite was smallest (3.67 hectares) at the Double Fork Ranch and largest at the

Pitchfork Ranch (112.11 hectares) in 2016 (Table 2.12). In 2017, the average home

range size of juvenile northern bobwhite was smallest (6.32 hectares) at the Esperanza

Ranch and largest at the Indian Canyon Ranch (11.91 hectares) (Table 2.12). The

minimum and maximum home range sizes for individuals between ranches was

extremely variable (Table 2.12). Furthermore, the comparison analysis of adult and

juvenile home range sizes from 2017 data at the Indian Canyon Ranch revealed that the

average adult home range was larger (15.11 hectares) than the average juvenile home

range (9.35 hectares) (Table 2.13).

DISCUSSION

In 2016, ranch owners came to the Quail-Tech Alliance when they started

noticing local disappearances of northern bobwhite on their properties, and my study was

designed to identify possible explanations for these observations. Based on the available

literature, I believed that these observed disappearances of northern bobwhite could be

due to either large-scale movements, especially during October when the Fall shuffle

occurs, or large-scale mortality (Hernàndez and Peterson 2007). In my discussion, I

address 4 major questions based off my data and personal observations:

a) Was a sudden die-off of quail observed over the 2 years of my study?


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b) Did quail move from the area where they were originally trapped and did not return?

c) Did quail display a Fall shuffle?

d) What did my statistical survival analysis show as a driving force of juvenile survival?

While northern bobwhites are one of the most studied birds in the world, little to

no research exists concerning the juvenile age class, presumably because it is difficult to

catch birds during the specified time period in which I was trapping, many survival

studies for Northern bobwhite conclude around July or August, and the limitations posed

by technology and/or radio size (Burger et al. 1995, Dixon et al. 1996). Based on my

data and personal observations over the 2 years of my study, I believe no sudden die-off

was observed during either my 2016 or my 2017 study periods. While the percentage of

birds that survived during my study in 2016 was noticeably higher (43%) than 2017

(24.3%), the number of deaths across the 2 study periods was relatively similar (24 in

2016 and 26 in 2017) (Table 2.3, Table 2.4). It is important to note that the sample sizes

were different for each year (104 birds in 2016 and 41 birds in 2017), so this could be as

cause of the observed differences in survival between years as opposed to large-scale

mortality.

In addition to survival, other aspects of northern bobwhite ecology that have been

frequently studied are home range and dispersal (Howard 1960, Fies et al. 2002,

Townsend et al. 2003, Cook et al. 2009, Buckley et al. 2015). For the purposes of this

study, I examined home range of juvenile Northern bobwhites. I made note of any

radiotagged quail that moved from the area in which they were trapped and did not

return, as well as any large-scale movements during October and November, the months


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during which the Fall shuffle occurs in which landowners noted disappearances of

Northern bobwhite.

In my 2016 field season, I noted that 14 birds at the Clark and Pitchfork ranches

in August and September moved from the area in which they were trapped and did not

return. I was unable to locate or pick up a radio signal on any of these birds for the

remainder of the 2016 study period following their day of capture, and I classified their

fate as “unknown”. Subsequently, they were censored from my known-fate survival

analysis in Program MARK (Burger et al. 1995, Curtis et al. 1988, Kurzejeski et al.

1987).

Additionally, I was unable to locate 15 other birds throughout my 2016 study.

These 15 birds disappeared from my study sites during my 2016 field season in the

months of September, October, and November. Interestingly, my observations matched

the months in which landowners noted disappearances of northern bobwhite. Of the 15

birds, 8 of them moved off Clark Ranch to an adjacent property in October. I was able to

pick up radio signals on these 8 birds until the end of my study. However, due to

property boundaries, I could not physically locate them.

Of these 15 birds from my 2016 study, 2 birds moved off the Pitchfork Ranch (1

in October and 1 in November), 1 moved off the Indian Canyon Ranch in October, 1 bird

moved off the Esperanza Ranch in September, and 3 birds moved off the Double Fork

Ranch in September. I could not pick up radio signals on any of these 7 birds, and I did

not locate them for the remainder of my 2016 study. Their fates were classified as

“unknown”.


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The movement of my radiotagged birds from these properties in 2016 during

these 3 months, especially the Clark Ranch, could be indicative of a Fall shuffle. The 8

birds at the Clark Ranch for which I was able to obtain radio signals throughout the study

were all observed in the western portion of the ranch and simultaneously emigrated to an

adjacent property in the same week of October. As for the remaining 7 birds across the

other properties, I could not definitively state that their disappearance was due to the Fall

shuffle, as I was unable to obtain a radio signal or physically locate them for the

remainder of my 2016 study. However, the fact that they moved off their respective

study sites during September through November could suggest evidence of a Fall shuffle.

In my 2017 field season, I only had 1 bird disappear from the Indian Canyon

Ranch during October. I could not pick up a radio signals on this bird, and I did not

locate it for the remainder of my 2017 study. Therefore, its fate was classified as

“unknown”. I do not have a definitive explanation as to why the number of birds that left

the study sites was higher in 2016 than in 2017. However, additional studies that

examine other factors such as vegetation use and availability across the individual

properties could lend evidence as to why northern bobwhite are inclined to move from

one property to another.

In addition to addressing my personal observations in the field, I also ran a

known-fate analysis for survival in Program MARK. Of the 56 models I ran, I was

required to report 16 models from my Program MARK results that were within ≤3

ΔAICc units of the top competing model. The weekly survival estimates for the 6

competing models was variable between the 5 study sites (Table 2.15). Of the 6

competing models generated by Program MARK that I discussed in this study, 5 of the


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models included rainfall as a covariate (Table 2.5). This suggests there is a rainfall effect

and that rainfall could be driving the differences in survival estimates observed between

2016 and 2017. Additionally, my results showed which specific times of the year rainfall

is important for survival of juvenile northern bobwhite. In this case, my results showed

that rainfall during fall and winter months (September, October, December) were more

important to juvenile survival than rainfall in summer months (August and June) (Table

2.5).

The available literature supports both my statistical results as well as my personal

observations during my 2 field seasons. In 2016, which was a year of high precipitation,

I had high capture success (Table 2.3). In 2017, which had substantially less

precipitation, I had limited capture success (Table 2.4). The reduced capture success

during my 2017 field season could possibly be explained by the limited amount of

precipitation during that year (West Texas Mesonet). Additionally, my weekly survival

estimate for 2016 was higher (0.97) than 2017 (0.91) (Table 2.14). Because 2017 was

dry year (West Texas Mesonet National Wind Institute), there was presumably less

vegetation growth, which means that there were reduced levels of available food, cover,

and nesting sites in 2017. Not only could a reduction in precipitation lower reproduction

levels, but it could also negatively impact the physiological condition of the birds due to

the limited presence of food (Buckley et al. 2018). Therefore, the lack of precipitation in

2017 could be a possible explanation for why the yearly survival estimate for 2017 was

lower than 2016.

For my home range analysis, I used 100% MCP’s to examine how much area

Northern bobwhite were using during the duration of my study. My home range results


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across the 5 study sites were variable. Overall, the study site with the largest home range

average was the Pitchfork Ranch in 2016 and the Indian Canyon Ranch in 2017 (Table

2.12). Overall, the home range averages in 2016 across my study sites were all larger

than the home range averages in 2017 (Table 2.12).

This goes against the findings of the available literature, which suggests that

northern bobwhite will often travel farther in dry years to locate food and cover (Miller et

al. 2017). However, the reduced movements during the 2017 field season could still be

explained by reduced precipitation levels. Townsend et al. (2003) proposed that

northern bobwhite in high-quality condition could increase their survival by a) by being

able to successfully evade predators and b) having enough remaining energy to start

building a nest immediately after dispersal. If the birds in my sample in 2017 were in

poor physiological condition due to lack of food availability caused by low precipitation

levels, this could explain why they did not disperse as much compared to 2016.

Because I had adults in my 2017 sample, I calculated the home range averages of

the adults and juveniles for comparison (Table 2.13). Surprisingly, the average home

range of adults was larger (15.11 hectares) than that of juveniles (9.34 hectares), which

goes against the findings of the available literature. Fies et al. (2002) in Virginia reported

that a) a higher portion of juveniles (28%) dispersed more than 2 km compared to adults

(10%), b) juveniles moved farther between wintering and breeding regions than adults, c)

juvenile males were the most inclined to disperse, and d) adult males were the least

inclined to disperse. Howard (1960) suggested that juveniles are more inclined to

disperse to avoid inbreeding in populations. I am not certain as to why adults dispersed

farther than juveniles. However, I believe a possible explanation for this could be that


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the adults were in better physiological condition than the juveniles and could therefore

disperse further (Townsend et al. 2003).

While I did not observe a die-off of quail between my 2016 and 2017 field

seasons, the findings of my study showed that weekly survival was higher in 2016 (0.97)

than 2017 (0.91) (Table 2.14). Of the many survival studies that have been done on

northern bobwhite, rainfall has been identified as an essential factor driving both northern

bobwhite survival and reproduction (Rollins 1999, Hernàndez et al. 2005, Tri et al. 2013,

Buckley et al. 2018). Rainfall promotes vegetation growth, which contributes

significantly to Northern bobwhite survival in terms food, cover, and nesting sites

(Rollins 2007).

Buckley et al. (2018) observed that wild female northern bobwhite did not

reproduce following a significant drought during 2011. Additionally, Koerth and

Guthery (1991) observed that a substantial decrease in water can lead to decreased (and

perhaps cause a cessation of) reproduction in Northern bobwhite populations. I believe

that the differences in my yearly survival rates could be explained by the vast differences

in precipitation between 2016 and 2017. Low precipitation levels in 2017 could not have

only limited the amount of food and cover that my birds had access to, thus reducing

survival levels, but could also have subsequently affected reproduction levels for that

year. This could have resulted in my lowered capture success (Table 2.4), as well as

lower weekly survival estimate for 2017.

My birds dispersed farther in 2016 than 2017 (Table 2.12), and I observed many

birds move from my study sites after capture and throughout the duration of my study

periods, especially during 2016 (29 in 2016, 1 in 2017). I believe these movements could


33

be due to a Fall shuffle, as I observed several birds move off my respective study sites in

the months of September through November. The 8 birds that moved off the Clark

Ranch in October strongly suggested evidence of a Fall shuffle. However, due to

restricted property access, I could not assess if these birds moved from the property for

the purpose of forming new coveys.

Ultimately, based on my data and personal observations from my 2016 and 2017

field seasons, I believe the results of my survival analysis did not show evidence of a die-

off of Northern bobwhite on these respective properties. However, my survival analysis

indicated that rainfall is a driving factor for juvenile Northern bobwhite populations on

these ranches. Specifically, my results suggested that rainfall levels are more important

to juvenile Northern bobwhite survival during the fall and winter months as opposed to

the summer months (Table 2.5). Additionally, my home range analysis did suggest

evidence of a Fall shuffle. Because my study was done solely on juvenile populations

within each of my 5 study sites, I believe that my results are not necessarily

representative of other quail populations outside of these properties. As such, I believe

further survival and home range studies outside of the given spatial scope of my study

could examine other individuals within Northern bobwhite populations, such as males

and females.


34

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Illinois University, Carbondale. 259pp.

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Press, New Brunswick, New Jersey, USA.

Sisson, C.D., L.H. Stribling, and D.W. Speake. 2000. Effects of supplemental feeding on

home range size and survival of northern bobwhites in south georgia. National

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37







Townsend, D. E., II, D.M. Leslie Jr., R.L. Lochmiller, S.J. DeMaso, S.A. Cox, and A.D.

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Press, Inc., San Diego, California, USA.


38

Table 2.1. List of individual covariates classified by study site used in Program MARK

analysis for 2016 survival estimates. Each study site had a total of 18 covariates. All

covariates were named using the concatenate function in Microsoft Excel, where month,

temperature, precipitation, and name of ranch are abbreviated.*

Esperanza Indian Canyon Pitchfork Clark Double Fork

EJanTemp16 IJanTemp16 PJanTemp16 CJanTemp16 DJanTemp16

EJanRain16 IJanRain16 PJanRain16 CJanRain16 DJanRain16

EFebTemp16 IFebTemp16 PFebTemp16 CFebTemp16 DFebTemp16

EFebRain16 IFebRain16 PFebRain16 CFebRain16 DFebRain16

EJunTemp16 IJunTemp16 PJunTemp16 CJunTemp16 DJunTemp16

EJunRain16 IJunRain16 PJunRain16 CJunRain16 DJunRain16

EJulTemp16 IJulTemp16 PJulTemp16 CJulTemp16 DJulTemp16

EJulRain16 IJulRain16 PJulRain16 CJulRain16 DJulRain16

EAugTemp16 IAugTemp16 PAugTemp16 CAugTemp16 DAugTemp16

EAugRain16 IAugRain16 PAugRain16 CAugRain16 DAugRain16

ESepTemp16 ISepTemp16 PSepTemp16 CSepTemp16 DSepTemp16

ESepRain16 ISepRain16 PSepRain16 CSepRain16 DSepRain16

EOctTemp16 IOctTemp16 POctTemp16 COctTemp16 DOctTemp16

EOctRain16 IOctRain16 POctRain16 COctRain16 DOctRain16

ENovTemp16 INovTemp16 PNovTemp16 CNovTemp16 DNovTemp16

ENovRain16 INovRain16 PNovRain16 CNovRain16 DNovRain16

EDecTemp16 IDecTemp16 PDecTemp16 CDecTemp16 DDecTemp16

EDecRain16 IDecRain16 PDecRain16 CDecRain16 DDecRain16

*E= Esperanza Ranch, I= Indian Canyon Ranch, P= Pitchfork Ranch, C= Clark Ranch,

and D= Double Fork Ranch.


39

Table 2.2. List of individual covariates classified by study site used in Program MARK

analysis for 2017 survival estimates. Each study site had a total of 18 covariates. All

covariates were named using the concatenate function in Microsoft Excel, where month,

temperature, precipitation, and name of ranch are abbreviated. *

Esperanza Indian Canyon Pitchfork

EJanTemp17 IJanTemp17 PJanTemp17

EJanRain17 IJanRain17 PJanRain17

EFebTemp17 IFebTemp17 PFebTemp17

EFebRain17 IFebRain17 PFebRain17

EJunTemp17 IJunTemp17 PJunTemp17

EJunRain17 IJunRain17 PJunRain17

EJulTemp17 IJulTemp17 PJulTemp17

EJulRain17 IJulRain17 PJulRain17

EAugTemp17 IAugTemp17 PAugTemp17

EAugRain17 IAugRain17 PAugRain17

ESepTemp17 ISepTemp17 PSepTemp17

ESepRain17 ISepRain17 PSepRain17

EOctTemp17 IOctTemp17 POctTemp17

EOctRain17 IOctRain17 POctRain17

ENovTemp17 INovTemp17 PNovTemp17

ENovRain17 INovRain17 PNovRain17

EDecTemp17 IDecTemp17 PDecTemp17

EDecRain17 IDecRain17 PDecRain17

*E= Esperanza Ranch, I= Indian Canyon Ranch, P= Pitchfork Ranch.


40

Table 2.3. Statistics for tagged birds by study site on the Rolling Plains of Texas in 2016.

Statistics include the totals for birds alive at the end of the study, birds that died during

the study, birds that were censored from the study, and birds captured per study site.

Fate Esperanza Indian Canyon Clark Pitchfork Double Fork Total

Survived Study 12 10 9 8 6 45

Died 11 4 3 3 3 24

Censored 3 9 9 11 3 35

Total 26 23 21 22 12 104

Table 2.4. Statistics for tagged birds by study site on the Rolling Plains of Texas in 2017.

Statistics include the totals for birds alive at the end of the study, birds that died during

the study, birds that were censored from the study, and birds captured per study site.

Fate Esperanza Indian Canyon Pitchfork Total

Survived Study 4 6 0 10

Died 11 14 1 26

Censored 3 2 0 5

Total 18 22 1 41


41

Table 2.5. Survival models and corresponding results generated by Program MARK.

Model AICc Delta AICc AICc Weight Model Likelihood No. Par.

Year 985.8418 0.0000 0.1608 1.0000 4

2016 October Rainfall by Ranch 987.8624 2.0206 0.0585 0.3641 7

2016 September Rainfall by Ranch 987.8718 2.0300 0.0583 0.3624 7

2016 December Rainfall by Ranch 988.1791 2.3373 0.0500 0.3108 7

2016 August Rainfall by Ranch 988.2509 2.4091 0.0482 0.2998 7

2016 June Rainfall by Ranch 988.3263 2.4845 0.0464 0.2887 7

2016 January Temperature by Ranch 988.3897 2.5479 0.0450 0.2797 7

2016 December Temperature by Ranch 988.4739 2.6321 0.0431 0.2682 7

2016 February Temperature by Ranch 988.5150 2.6732 0.0422 0.2627 7

2016 November Temperature by Ranch 988.6136 2.7718 0.0402 0.2501 7

2016 October Temperature by Ranch 988.6758 2.8340 0.0390 0.2425 7

2016 July Rainfall by Ranch 988.7142 2.8724 0.0382 0.2378 7

2016 June Temperature by Ranch 988.7150 2.8732 0.0382 0.2377 7

2016 July Temperature by Ranch 988.7153 2.8735 0.0382 0.2377 7

2016 August Temperature by Ranch 988.7161 2.8743 0.0382 0.2376 7

2016 September Temperature by Ranch 988.7178 2.8760 0.0382 0.2374 7


42

Table 2.6. Beta estimates for the Year survival model. Each parameter is listed with its corresponding beta estimate, standard error,

and 95% confidence intervals. *

* Parameter 2:S represents 2016, and parameter 3:S represents 2017. Parameters 1:S and 4:S are constants.

Parameter Beta Standard Error Lower CI Upper CI

1:S 1.1568054 0.0324956 1.093114 1.2204968

2:S 1.2527639 0.0384048 1.1774905 1.3280372

3:S 0.9773105 0.0609711 0.8578072 1.0968138

4:S 1.1541184 0.0327035 1.0900195 1.2182172


43

Table 2.7: Beta estimates for the 2016 October Rainfall by Ranch model. Each parameter is listed with its corresponding beta

estimate, standard error, 95% confidence intervals, and logistic regression equation. *

Parameter Beta Standard Error Lower CI Upper CI Logistic Regression Equation

1:ESP 2.0274915 0.2839172 1.4710137 2.5839693 logit Survival = 2.02 + 3.38 (October Rainfall)

2:IC 2.6861837 0.2926842 2.1125227 3.2598447 logit survival = 2.68 + 3.38 (October Rainfall)

3:PF 1.3937865 0.8269192 -0.2269752 3.0145482 logit survival = 1.39 + 3.38 (October Rainfall)

4:CLK 2.9172964 0.6366735 1.6694162 4.1651765 logit survival = 2.91 + 3.38 (October Rainfall)

5:DF 0.7197365 0.8753015 -0.9958544 2.4353274 logit survival = 0.71 + 3.38 (October Rainfall)

6: Constant 3.1146258 0.1142582 2.8906797 3.3385719 logit survival = 3.11 + 3.38 (October Rainfall)

7:Oct 3.3819142 0.9107284 1.5968864 5.1669419 logit survival = 3.38 + 3.38 (October Rainfall)

*Parameters are arranged by study site where 1:ESP represents the Esperanza Ranch, 2:IC represents the Indian Canyon Ranch, 3:PF

represents the Pitchfork Ranch, 4:CLK represents he Clark Ranch, and 5: DF represents the Double Fork Ranch. Parameter 6:

Constant represents a constant model, and parameter 7:Oct represents October rainfall.


44

Table 2.8: Beta estimates for the 2016 September Rainfall by Ranch model. Each parameter is listed with its corresponding beta

estimate, standard error, 95% confidence intervals, and logistic regression equation.*


1:ESP 2.0774335 0.2852656 1.5183129 2.6365541 logit survival= 2.07 + 0.57 (September Rainfall)

2:IC 2.5972562 0.2940873 2.0208451 3.1736673 logit survival= 2.59 + 0.57 (September Rainfall)

3:PF 1.8489482 0.7742812 0.331357 3.3665395 logit survival= 1.84+ 0.57 (September Rainfall)

4:CLK -1.1274632 1.5213335 -4.1092769 1.8543505 logit survival= -1.12+ 0.57 (September Rainfall)

5:DF 1.5548731 0.7364374 0.1114558 2.9982905 logit survival= 1.55 + 0.57 (September Rainfall)

6: Constant 3.1146258 0.1142582 2.8906797 3.3385719 logit survival= 3.11 + 0.57 (September Rainfall)

7:Sept 0.5757435 0.1620575 0.2581107 0.8933762 logit survival= 0.57 + 0.57 (September Rainfall)


represents the Pitchfork Ranch, 4:CLK represents the Clark Ranch, and 5: DF represents the Double Fork Ranch. Parameter 6:

Constant represents a constant model, and parameter 7:Sept represents September rainfall.


45

Table 2.9: Beta estimates for the 2016 December Rainfall by Ranch model. Each parameter is listed with its corresponding beta



1:ESP 2.0432178 0.2865949 1.4814918 2.6049438 logit survival= 2.04 + 0.95 (December Rainfall)

2:IC 2.6374567 0.2940612 2.0610967 3.2138168 logit survival= 2.63 + 0.95 (December Rainfall)

3:PF 1.9383796 0.7603971 0.4480013 3.4287579 logit survival= 1.93 + 0.95 (December Rainfall)

4:CLK 2.3781067 0.7177935 0.9712313 3.784982 logit survival= 2.37 + 0.95 (December Rainfall)

5:DF 1.5388915 0.7390776 0.0902993 2.9874837 logit survival= 1.53 + 0.95 (December Rainfall)

6: Constant 3.1146258 0.1142582 2.8906797 3.3385719 logit survival= 3.11+ 0.95 (December Rainfall)

7:Dec 0.9587904 0.2698145 0.429954 1.4876269 logit survival= 2.04 + 0.95 (December Rainfall)


represents the Pitchfork Ranch, 4:CLK represents the Clark Ranch, and 5: DF represents the Double Fork Ranch. Parameter

6:Constant represents a constant model, and parameter 7:Dec represents December rainfall.


46

Table 2.10: Beta estimates for the 2016 August Rainfall by Ranch model. Each parameter is listed with its corresponding beta



1:ESP 2.1670311 0.2845656 1.6092826 2.7247796 logit survival= 2.16 + 0.40 (August Rainfall)

2:IC 2.5448441 0.2939901 1.9686235 3.1210647 logit survival= 2.54 + 0.40 (August Rainfall)

3:PF 1.93012 0.781579 0.3982252 3.4620148 logit survival= 1.93 + 0.40 (August Rainfall)

4:CLK 2.6525212 0.6868725 1.3062511 3.9987913 logit survival= 2.65 + 0.40 (August Rainfall)

5:DF 1.3910456 0.7848429 -0.1472466 2.9293377 logit survival= 1.39 + 0.40 (August Rainfall)

6:Constant 3.1146257 0.1142582 2.8906796 3.3385718 logit survival= 3.11 + 0.40 (August Rainfall)

7:Aug 0.4079835 0.1220823 0.1687021 0.6472649 logit survival= 0.40 + 0.40 (August Rainfall)

*Parameters are arranged by study site where 1:ESP the Esperanza Ranch, 2:IC represents for the Indian Canyon Ranch, 3:PF


Constant represents a constant model, and parameter 7:Aug represents August rainfall.


47

Table 2.11: Beta estimates for the 2016 June Rainfall by Ranch model. Each parameter is listed with its corresponding beta estimate,

standard error, 95% intervals, and logistic regression equation.*


1:ESP 2.2315032 0.2808079 1.6811197 2.7818867 logit survival= 2.23 + 1.11 (June Rainfall)

2:IC 2.5275294 0.2935757 1.952121 3.1029377 logit survival= 2.52 + 1.11 (June Rainfall)

3:PF 1.6481892 0.8370231 0.0076239 3.2887546 logit survival= 1.64 + 1.11 (June Rainfall)

4:CLK -0.0483219 1.3272203 -2.6496738 2.55303 logit survival= -0.04 + 1.11 (June Rainfall)

5:DF 1.6900184 0.7335653 0.2522304 3.1278064 logit survival= 1.69 + 1.11 (June Rainfall)

6: Constant 3.1146258 0.1142582 2.8906797 3.3385719 logit survival= 3.11+ 1.11 (June Rainfall)

7:June 1.1178723 0.3406102 0.4502764 1.7854682 logit survival= 1.11 + 1.11 (June Rainfall)



Constant represents a constant model, and parameter 7:June represents June rainfall.


48

Table 2.12. Minimum, maximum, and average home range sizes for radiotagged birds from 2016-2017 by study site. Home range

values are measured in hectares.*

Study Site

2016 Min home

range size (ha)

2016 Max home

range size (ha)

2016 Average home

range size (ha)

2017 Min home

range size (ha)

2017 Max home

range size (Ha)

2017 Average home

range size (ha)

Esperanza 0.05 42.87 8.27 0.18 13.43 6.32

Indian Canyon 0.37 78.74 16.12 0.85 41.36 11.91

Clark 2.79 16.96 7.10 N/A N/A N/A

Pitchfork 8.88 354.57 112.11 N/A N/A N/A

Double Fork 0.03 8.63 3.67 N/A N/A N/A

*No data for Clark, Pitchfork, or Double Fork ranches in 2017.

Table 2.13. Comparison of average adult and juvenile home ranges on the Indian Canyon ranch on the Rolling Plains in 2017. Home

range values are measured in hectares.

Age Class Average Home Range Size (Ha)

Adults 15.11

Juveniles 9.35


49

Table 2.14: Weekly survival estimates generated by Program MARK for the Year model. Each parameter is listed with its

corresponding beta estimate, standard error, and 95% confidence intervals. *

Parameter Estimate Standard Error Lower CI Upper CI

1:S 0.9577614 0.0065359 0.9429239 0.968869

2:S 0.9749263 0.0060046 0.96004 0.9843573

3:S 0.9144981 0.0170492 0.8746233 0.9425245

4:S 0.9572192 0.006618 0.942198 0.9684675

* Parameter 2:S represents 2016, and parameter 3:S represents 2017. Parameters 1:S and 4:S are constants.

Table 2.15. Weekly survival estimates generated by Program MARK for the 5 competing models. Each estimate is listed with its

corresponding 95% confidence intervals.

Study Site Oct16[CI] Sept16[CI] Dec16[CI] Aug16[CI] June16[CI]

Esperanza 0.91 [0.85-0.94] 0.91 [0.85-0.94] 0.91 [.85-0.94] 0.91 [0.86-0.94] 0.92 [0.86-0.94]

Indian Canyon 0.95 [0.90-0.96] 0.95 [0.90-0.96] 0.95 [0.90-0.96] 0.95 [0.90-0.96] 0.95 [0.90-0.96]

Pitchfork 0.86 [0.57-0.96] 0.90 [0.68-0.97] 0.90 [0.69-0.97] 0.90 [0.69-0.97] 0.88 [0.62-0.97]

Clark 0.95 [0.86-0.98] 0.41 [0.04-0.90] 0.93 [0.78-0.98] 0.94 [0.82-0.98] 0.64 [0.15-0.94]

Double Fork 0.72 [0.33-0.92] 0.84 [0.57-0.95] 0.84 [0.56-0.95] 0.82 [0.94-0.96] 0.86 [0.60-0.96]


50

Figure 2.1. Location of study sites in relation to Lubbock, Texas.


51

Figure 2.2. Line graph generated by Program MARK to show the differences between juvenile survival in 2016 and 2017. Parameter

2 represents 2016, and Parameter 3 represents 2017. Parameters 1 and 4 are constants.

copyright 2019, jessica mehta

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