AVIAN DIVERSITY AND LANDSCAPE AVIAN DIVERSITY AND LANDSCAPE RISK FACTORS FOR WEST NILE VIRUS RISK FACTORS FOR WEST NILE VIRUS

INFECTION IN HOUSE SPARROWSINFECTION IN HOUSE SPARROWS

ByBy

Lara M. JuliussonLara M. Juliusson

An Honors Thesis An Honors Thesis Submitted to the Department of Ecology and Evolutionary BiologySubmitted to the Department of Ecology and Evolutionary Biology

in partial fulfillment for departmental honors for the degree ofin partial fulfillment for departmental honors for the degree ofBACHELOR OF ARTSBACHELOR OF ARTS

University of Colorado, BoulderUniversity of Colorado, Boulder

– WNV Emerging zoonosis in North and South America– Exotic pathogen– Example, Yellow-billed magpie (Pica nuttalli)

IntroductionIntroduction

www.mcssb.com/photos/birds.htmKoenig et al., 2007

% WNV prevalence

Conservation Implications of West Nile Virus for American Birds

Culex tarsalisBreeding habitats:– wetlands – flood-irrigated crops – hoof prints– new water sources

with high nutrient content

Host seeking: – elevated canopy

cover

IntroductionIntroductionWNV Transmission Dynamics – Focal Vector

www.smcmad.org

– Predominant WNV host in rural CO

– resident all-year in study foci

– moderately high reservoir competence

– sometimes open-cup nester (trees & hedges)

IntroductionIntroductionWNV Transmission Dynamics – Focal Host

House sparrow (Passer domesticus)

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

4) highly fertilized crops in Interaction with flood irrigated crops

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

4) highly fertilized crops in Interaction with flood irrigated crops

5) high total nitrogen input from all crops, and

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

4) highly fertilized crops in Interaction with flood irrigated crops

5) high total nitrogen input from all crops, and

6) tree canopy

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

4) highly fertilized crops in Interaction with flood irrigated crops

5) high total nitrogen input from all crops, and

6) tree canopy

II. WNV infection is predicted to be positively associated with greater numbers of :

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

I. WNV infection is predicted to be positively associated with greater percent surrounding area covered by:

1) perennial water, wetlands, and intermittent water

2) sod, corn, and vegetable crop production (highly inorganic N fertilized crops)

3) flood irrigated crops

4) highly fertilized crops in Interaction with flood irrigated crops

5) high total nitrogen input from all crops, and

6) tree canopy

II. WNV infection is predicted to be positively associated with greater numbers of :

1) livestock confinement areas

Vector feeding preference

IntroductionIntroductionHypotheses: LandscapeHypotheses: Landscape

III. WNV infection is predicted to be negatively associated with:

Vector feeding preference

IntroductionIntroductionHypotheses: Avian DiversityHypotheses: Avian Diversity

III. WNV infection is predicted to be negatively associated with:

1) high relative abundance, species richness, and diversity of a group of low reservoir-competent avian orders: Columbiform, Piciform, and Anseriform,

Vector feeding preference

IntroductionIntroductionHypotheses: Avian DiversityHypotheses: Avian Diversity

Reservoir competence =Low: Diluters, e.g.

Mallard Mourning dove

Rock dove

Northernflicker

III. WNV infection is predicted to be negatively associated with:

1) high relative abundance, species richness, and diversity of a group of low reservoir-competent avian orders: Columbiform, Piciform, and Anseriform,

2) higher density proportions of diluter orders to a group of all Passeriform species.

Vector feeding preference

IntroductionIntroductionHypotheses: Avian DiversityHypotheses: Avian Diversity

Reservoir competence =High: Spreaders, e.g.

Low: Diluters, e.g.

Mallard Mourning dove

Rock dove

Northernflicker

Blue jay

House sparrow

IV. WNV infection is predicted to be:

Vector feeding preference

IntroductionIntroductionHypotheses: ControlsHypotheses: Controls

IV. WNV infection is predicted to be:

1) Positively associated with high vector densities,

Vector feeding preference

IntroductionIntroductionHypotheses: ControlsHypotheses: Controls

Vector density (+)

IV. WNV infection is predicted to be:

1) Positively associated with high vector densities,

2) Negatively associated with application of adulticide and larvacide control measures, and

Vector feeding preference

IntroductionIntroductionHypotheses: ControlsHypotheses: Controls

Adulticide & Larvacide

(-)

Vector density (+)

IV. WNV infection is predicted to be:

1) Positively associated with high vector densities,

2) Negatively associated with application of adulticide and larvacide control measures, and

3) Negatively associated with high preepizotic House sparrow immunity.

Vector feeding preference

IntroductionIntroductionHypotheses: ControlsHypotheses: Controls

Adulticide & Larvacide

(-)

Vector density (+)

Immunity (-)

Study Area• 23 small, agricultural

town cores, in Weld County, CO

• 2-kilometer surrounding regions provide independent land cover / land use context for 22 sites

MethodsMethods

I-25

• The Centers for Disease Control and Prevention provided raw WNV seroprevalence data

• Collected all season• Infection rate from HY sparrow

seroprevalence and AHY birds negative in spring, but positive in fall

• N=23 for each year

MethodsMethodsOutcome Variable: 2004 and 2005 house sparrow infection rate at each study site

• 2004 Model Land Cover: – Perennial water– Intermittent water– Wetlands– Tree canopy– From the National Land Cover

Dataset, 2001 GIS grid • 2005 Model Land Use:

– Crop type – Irrigation type – From the Colorado Department

of Water Resources, 2005 GIS layer

– Derived flood-irrigated acreage of corn, sod, and vegetable crops

– Estimated pounds of inorganic nitrogen applied to corn, sod, and vegetable crops which were flood-irrigated

MethodsMethodsPredictor Variables:Land Cover / Land Use

Estimated N for 2005Example Gilcrest: 12 acres F-I Sod x 125 lbs / acre = 1,486 lbs

• 2005 Model Land Use: – Livestock Confinement

Operations (LCOs)– Uses requiring special permits

GIS layer from Weld Co. permitting

– Verified and improved with digitized LCOs from 2004 aerials, and online business databases

MethodsMethodsPredictor Variables:Land Cover / Land Use

• 2005 Model Land Use: – Livestock Confinement

Operations (LCOs)– Uses requiring special permits

GIS layer from Weld Co. permitting

– Verified and improved with digitized LCOs from 2004 aerials, and online business databases

MethodsMethodsPredictor Variables:Land Cover / Land Use

• 2004 Model: – CDC provided in-town bird survey

of all birds seen or heard during four 1-minute observation intervals

– Program MARK closed capture models used to estimate population abundance and density for:1. Group of diluter orders

– Species richness– Shannon’s diversity

2. Group of Passeriformes, and3. Proportion of diluter density /

hectare per 100,000 Passeriformes per hectare

MethodsMethodsPredictor Variables: Avian Diversity

• 2004 Model: – CDC provided in-town bird survey

of all birds seen or heard during four 1-minute observation intervals

– Program MARK closed capture models used to estimate population abundance and density for:1. Group of diluter orders

– Species richness– Shannon’s diversity

2. Group of Passeriformes, and3. Proportion of diluter density /

hectare per 100,000 Passeriformes per hectare

Percent of Each Order in the Diluter Group

98%

1%

1%

Columbiform

Anseriform

Piciform

MethodsMethodsPredictor Variables: Avian Diversity

• 2004 and 2005 Models: – Cx. tarsalis density data collected by the

CDC, 2004 and 2005. – Mosquito control measures for each town

(Y/N) provided by CMC, 2004, 2005– Immunity rate: spring seroprevalence

data for AHY sparrows collected by the CDC, 2004 and 2005

MethodsMethodsPredictor Variables: Controls

http://www.chesapeake.va.us/

• Poisson single variable regression • Akaike Information Criterion (AICc) model ranking

– Screened for best predictors from:• Land Cover predictors (2004 model)• Avian diversity metrics (2004 model)• Land Use predictors (2005 model)

• Two separate regression models (ranked by AICc): – 2004: Land cover, avian diversity, and control predictors, plus global model

multiple regression– 2005: Land use, and control predictors, plus global model multiple

regression• Used “R” statistical software

MethodsMethodsStatistical Analyses

Results: Variable ScreeningResults: Variable Screening

Land Cover CandidatesAkaike Weight Avian Diversity Candidates

Akaike Weight Land Use Candidates

Akaike Weight

Percent perennial water (-) 0.307 Diluter group density (+) 0.636Estimated N application for flood irrigated sod crops (-) 0.696

Percent wetland (+) 0.288Proportion diluters to Passeriformes (+) 0.237

Estimated N application for flood irrigated corn crops (-) 0.159

Percent intermittent water (-) 0.285 Diluter species richness (+) 0.060Total estimated N application for all flood irrigated crops (-) 0.135

Percent canopy (-) 0.095 Passeriform density (+) 0.034Number of LCOs within 2 km (+) 0.006

Diluter group Shannon's Diversity Index (+) 0.029

Index of distance and size of LCOs within 2 km (+) 0.002Estimated N application for flood irrigated vegetable crops (+) 0.001

Results: Variable ScreeningResults: Variable Screening

Land Cover CandidatesAkaike Weight Avian Diversity Candidates

Akaike Weight Land Use Candidates

Akaike Weight

Percent perennial water (-) 0.307 Diluter group density (+) 0.636Estimated N application for flood irrigated sod crops (-) 0.696

Percent wetland (+) 0.288Proportion diluters to Passeriformes (+) 0.237

Estimated N application for flood irrigated corn crops (-) 0.159

Percent intermittent water (-) 0.285 Diluter species richness (+) 0.060Total estimated N application for all flood irrigated crops (-) 0.135

Percent canopy (-) 0.095 Passeriform density (+) 0.034Number of LCOs within 2 km (+) 0.006

Diluter group Shannon's Diversity Index (+) 0.029

Index of distance and size of LCOs within 2 km (+) 0.002Estimated N application for flood irrigated vegetable crops (+) 0.001

Results: Variable ScreeningResults: Variable Screening

Land Cover CandidatesAkaike Weight Avian Diversity Candidates

Akaike Weight Land Use Candidates

Akaike Weight

Percent perennial water (-) 0.307 Diluter group density (+) 0.636Estimated N application for flood irrigated sod crops (-) 0.696

Percent wetland (+) 0.288Proportion diluters to Passeriformes (+) 0.237

Estimated N application for flood irrigated corn crops (-) 0.159

Percent intermittent water (-) 0.285 Diluter species richness (+) 0.060Total estimated N application for all flood irrigated crops (-) 0.135

Percent canopy (-) 0.095 Passeriform density (+) 0.034Number of LCOs within 2 km (+) 0.006

Diluter group Shannon's Diversity Index (+) 0.029

Index of distance and size of LCOs within 2 km (+) 0.002Estimated N application for flood irrigated vegetable crops (+) 0.001

Results: Variable ScreeningResults: Variable Screening

Land Cover CandidatesAkaike Weight Avian Diversity Candidates

Akaike Weight Land Use Candidates

Akaike Weight

Percent perennial water (-) 0.307 Diluter group density (+) 0.636Estimated N application for flood irrigated sod crops (-) 0.696

Percent wetland (+) 0.288Proportion diluters to Passeriformes (+) 0.237

Estimated N application for flood irrigated corn crops (-) 0.159

Percent intermittent water (-) 0.285 Diluter species richness (+) 0.060Total estimated N application for all flood irrigated crops (-) 0.135

Percent canopy (-) 0.095 Passeriform density (+) 0.034Number of LCOs within 2 km (+) 0.006

Diluter group Shannon's Diversity Index (+) 0.029

Index of distance and size of LCOs within 2 km (+) 0.002Estimated N application for flood irrigated vegetable crops (+) 0.001

Results: 2004 ModelResults: 2004 ModelLand Cover, Avian Diversity, and Controls

Land Cover, best candidate predictor:• Perennial water, 31% likelihood best model• Wetland, 29%• Intermittent water, 29%

Avian Diversity, best candidate predictor:• Diluter group density, 64% likelihood best model• Proportion diluters to Passeriformes, 24%

Candidate screening:

Results: 2004 ModelResults: 2004 ModelLand Cover, Avian Diversity, and Controls

Land Cover, best candidate predictor:• Perennial water, 31% likelihood best model• Wetland, 29%• Intermittent water, 29%

Avian Diversity, best candidate predictor:• Diluter group density, 64% likelihood best model• Proportion diluters to Passeriformes, 24%

Poisson Model of Infection Rate & Direction of Association

Hypothesized Direction

Akaike Weight

Diluter group density (+) - 0.649Percent perennial water (-) + 0.095Immunity rate (+) - 0.083Global model: diluter group density (+), percent perennial water (-), immunity rate (+), mosquito control (-), mosquito density (+) 0.064Mosquito control (-) - 0.064Mosquito density (+) + 0.046

Final model ranking:

Results: 2004 ModelResults: 2004 ModelLand Cover, Avian Diversity, and Controls

Land Cover, best candidate predictor:• Perennial water, 31% likelihood best model• Wetland, 29%• Intermittent water, 29%

Avian Diversity, best candidate predictor:• Diluter group density, 64% likelihood best model• Proportion diluters to Passeriformes, 24%

Poisson Model of Infection Rate & Direction of Association

Hypothesized Direction

Akaike Weight

Diluter group density (+) - 0.649Percent perennial water (-) + 0.095Immunity rate (+) - 0.083Global model: diluter group density (+), percent perennial water (-), immunity rate (+), mosquito control (-), mosquito density (+) 0.064Mosquito control (-) - 0.064Mosquito density (+) + 0.046

Final model ranking:

Results: 2004 ModelResults: 2004 Model

0 2 4 6 8 10

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Diluter Group Density (Ha)

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% Perennial Water (2 km)

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HOSP Preepizootic Immunity

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Mosquito Control

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Mosquito Density

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% Intermittent Water (2 km)

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Land Cover, Avian Diversity, and Controls

Results: 2004 ModelResults: 2004 Model

0 2 4 6 8 10

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Diluter Group Density (Ha)

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% Perennial Water (2 km)

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HOSP Preepizootic Immunity

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Mosquito Control

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Mosquito Density

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% Intermittent Water (2 km)

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Land Cover, Avian Diversity, and Controls

Results: 2005 ModelResults: 2005 ModelLand Use and Controls

Variable screening:

Land use, best candidate predictor:• N application from flood-irrigated sod crops, 70% likelihood best model• N application from flood-irrigated corn crops, 16%• N application from all flood-irrigated sod 14%

Results: 2005 ModelResults: 2005 ModelLand Use and Controls

Land use, best candidate predictor:• N application from flood-irrigated sod crops, 70% likelihood best model• N application from flood-irrigated corn crops, 16%• N application from all flood-irrigated sod 14%

Final model ranking:Poisson Model of Infection Rate &

Direction of AssociationHypothesized

DirectionAkaike Weight

Estimated N application for flood-irrigated sod crops (-) + 0.954Global Model: N sod (-), LCO count (+), mosquito density (-), immunity rate (+), mosquito control (+) 0.030Number of LCOs within 2 km (+) + 0.008Immunity rate (+) - 0.005Mosquito density (-) + 0.001Mosquito control (+) - 0.001

Results: 2005 ModelResults: 2005 ModelLand Use and Controls

0 500 1500 2500 3500

0.00

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Sod Farm Estimated N (Lbs)

Infe

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a.

0 1 2 3 4 5 6 7

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Number of LCOs in 2 km

Infe

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b.

0.00 0.05 0.10 0.15 0.20

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HOSP Preepizootic Immunity

Infe

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0 50 100 150 200

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Mosquito Density

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0.0 0.2 0.4 0.6 0.8 1.0

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Mosquito Control

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Total Estimated N (Lbs)

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DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection.

DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection. • Are nestling Columbids competent WNV hosts?

DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection. • Are nestling Columbids competent WNV hosts?

o Possibly, Mahmood et al. (2004), found nestling mourning doves competent hosts for St. Louis Encephalitis

DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection. • Are nestling Columbids competent WNV hosts?

o Possibly, Mahmood et al. (2004), found nestling mourning doves competent hosts for St. Louis Encephalitiso Columbids are multiple brooders throughout a long breeding season

DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection. • Are nestling Columbids competent WNV hosts?

o Possibly, Mahmood et al. (2004), found nestling mourning doves competent hosts for St. Louis Encephalitiso Columbids are multiple brooders throughout a long breeding seasono Long breeding season overlaps with WNV transmission season

DiscussionDiscussionAvian Diversity

2004 Model: Diluter density a 65% likelihood of being the best model: associated with increasing house sparrow WNV infection. • Are nestling Columbids competent WNV hosts?

o Possibly, Mahmood et al. (2004), found nestling mourning doves competent hosts for St. Louis Encephalitiso Columbids are multiple brooders throughout a long breeding seasono Long breeding season overlaps with WNV transmission season

• Are eurasian collared-dove adults competent WNV hosts?

DiscussionDiscussionPerennial Water

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection.

DiscussionDiscussionPerennial Water

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Is there a threshold effect with increasing percent water cover?

DiscussionDiscussionPerennial Water

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Is there a threshold effect with increasing percent water cover?

o The Lowess curves suggest that this is possible.

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection.

Perennial Water

- Continued -

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

Perennial Water

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

Perennial Water

Windsor

Wellington

Severance

Berthoud

Fort Lupton

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

Perennial Water

Windsor

Wellington

Severance

Berthoud

Fort Lupton

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

o Visual review suggests that this is possible.

Perennial Water

Windsor

Wellington

Severance

Berthoud

Fort Lupton

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

o Visual review suggests that this is possible.• Indicative of a “dilution effect”?

Perennial Water

Windsor

Wellington

Severance

Berthoud

Fort Lupton

DiscussionDiscussion

2004 Model: % surrounding perennial water had a 10% likelihood of being the best model: associated with decreasing sparrow infection. • Does water body size, and not just total % area in 2-km matter?

o Visual review suggests that this is possible.• Indicative of a “dilution effect”?

o Additional bird surveys within 2-km region will be conducted.

Perennial Water

Windsor

Wellington

Severance

Berthoud

Fort Lupton

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.• Are smaller females emerging due to larval crowding?

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.• Are smaller females emerging due to larval crowding?

o Reisen (1984)

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.• Are smaller females emerging due to larval crowding?

o Reisen (1984)• Are there changes in vector competence due to larval crowding?

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.• Are smaller females emerging due to larval crowding?

o Reisen (1984)• Are there changes in vector competence due to larval crowding?

o Alto et al. (2005)

DiscussionDiscussionNitrogen Application

2005 Model: Inorganic nitrogen application due to flood-irrigated sod crops had a 95% likelihood of being the best model: associated with a decrease in house sparrow WNV infection.

• Lowess lines suggest a non-linear relationship• Are less female cx. tarsalis emerging due to toxins associated with nitrogenous fertilizer?

o 2005 data do not support this.• Are smaller females emerging due to larval crowding?

o Reisen (1984)• Are there changes in vector competence due to larval crowding?

o Alto et al. (2005)• Why was sod more important than other highly fertilized crops?

DiscussionDiscussionControls

2004 and 2005 Models: House sparrow immunity rate in 2004 had an 8% likelihood of being the best model: associated with an increase in house sparrow WNV infection.

DiscussionDiscussionControls

2004 and 2005 Models: House sparrow immunity rate in 2004 had an 8% likelihood of being the best model: associated with an increase in house sparrow WNV infection.

• Are there increased vector feeding rates due to improved sparrow defense mechanisms?

DiscussionDiscussionControls

2004 and 2005 Models: House sparrow immunity rate in 2004 had an 8% likelihood of being the best model: associated with an increase in house sparrow WNV infection.

• Are there increased vector feeding rates due to improved sparrow defense mechanisms?

•Edman and Scott (1987), Darbro and Harrington (2007)

DiscussionDiscussionControls

2004 and 2005 Models: House sparrow immunity rate in 2004 had an 8% likelihood of being the best model: associated with an increase in house sparrow WNV infection.

• Are there increased vector feeding rates due to improved sparrow defense mechanisms?

•Edman and Scott (1987), Darbro and Harrington (2007) • Effects of other host species not considered.

DiscussionDiscussionControls

2004 and 2005 Models: House sparrow immunity rate in 2004 had an 8% likelihood of being the best model: associated with an increase in house sparrow WNV infection.

• Are there increased vector feeding rates due to improved sparrow defense mechanisms?

•Edman and Scott (1987), Darbro and Harrington (2007) • Effects of other host species not considered.• Effects of nestlings not considered.

ConclusionsConclusions

ConclusionsConclusions

• Avian diversity and Landscape characteristics have complex interactions and non-linear relationships with WNV infection rate and transmission risk in house sparrows

ConclusionsConclusions

• Avian diversity and Landscape characteristics have complex interactions and non-linear relationships with WNV infection rate and transmission risk in house sparrows

• Columbid nestlings are likely to be important amplifiers of WNV infection

ConclusionsConclusions

• Avian diversity and Landscape characteristics have complex interactions and non-linear relationships with WNV infection rate and transmission risk in house sparrows

• Columbid nestlings are likely to be important amplifiers of WNV infection

• Size-dependent water body thresholds were suggested for perennial water cover effects

ConclusionsConclusions

• Avian diversity and Landscape characteristics have complex interactions and non-linear relationships with WNV infection rate and transmission risk in house sparrows

• Columbid nestlings are likely to be important amplifiers of WNV infection

• Size-dependent water body thresholds were suggested for perennial water cover effects

• Certain flood-irrigated crops with high nitrogen fertilizer application rates showed important associations with infection rate

ConclusionsConclusions

• Avian diversity and Landscape characteristics have complex interactions and non-linear relationships with WNV infection rate and transmission risk in house sparrows

• Columbid nestlings are likely to be important amplifiers of WNV infection

• Size-dependent water body thresholds were suggested for perennial water cover effects

• Certain flood-irrigated crops with high nitrogen fertilizer application rates showed important associations with infection rate

• Often assumed predictors of WNV transmission showed few important associations with house sparrow infection

AcknowledgementsAcknowledgementsI thank Dr. Nicholas Komar of the Centers for Disease Control and Prevention for the wonderful opportunity to work on this project, and the support he provided while undertaking it. I also thank my committee members, Drs. Sharon Collinge, Alexander Cruz, and Barbara Demmig-Adams, who provided advice to me on subject content, relevant disease ecology questions, and writing and revision.

I also thank GIS personnel from several agencies who provided data to me for free, or before it was available to the public. I additionally thank the CDC staff who collected the data I used. I give special thanks to the Fort Collins Audubon Society for their generous grant that provided gas money for field studies that will extend this research. Lastly, I thank my friends, family, and pets for putting up with me, and Carmen for her love and support.