BriefAvian Host Diversity and Landscape Characteristics as Predictors_Split
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Transcript of BriefAvian Host Diversity and Landscape Characteristics as Predictors_Split
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
0.00
0.05
0.10
0.15
0.20
Diluter Group Density (Ha)
Infe
ctio
n R
ate
a.
0 1 2 3 4 5 6
0.00
0.05
0.10
0.15
0.20
% Perennial Water (2 km)
Infe
ctio
n R
ate
b.
0.1 0.2 0.3 0.4 0.5
0.00
0.05
0.10
0.15
0.20
HOSP Preepizootic Immunity
Infe
ctio
n R
ate
c.
0.0 0.2 0.4 0.6 0.8 1.0
0.00
0.05
0.10
0.15
0.20
Mosquito Control
Infe
ctio
n R
ate
d.
0 500 1500 2500 3500
0.00
0.05
0.10
0.15
0.20
Mosquito Density
Infe
ctio
n R
ate
e.
0.0 0.1 0.2 0.3 0.4 0.5
0.00
0.05
0.10
0.15
0.20
% Intermittent Water (2 km)
Infe
ctio
n R
ate
f.
Land Cover, Avian Diversity, and Controls
Results: 2004 ModelResults: 2004 Model
0 2 4 6 8 10
0.00
0.05
0.10
0.15
0.20
Diluter Group Density (Ha)
Infe
ctio
n R
ate
a.
0 1 2 3 4 5 6
0.00
0.05
0.10
0.15
0.20
% Perennial Water (2 km)
Infe
ctio
n R
ate
b.
0.1 0.2 0.3 0.4 0.5
0.00
0.05
0.10
0.15
0.20
HOSP Preepizootic Immunity
Infe
ctio
n R
ate
c.
0.0 0.2 0.4 0.6 0.8 1.0
0.00
0.05
0.10
0.15
0.20
Mosquito Control
Infe
ctio
n R
ate
d.
0 500 1500 2500 3500
0.00
0.05
0.10
0.15
0.20
Mosquito Density
Infe
ctio
n R
ate
e.
0.0 0.1 0.2 0.3 0.4 0.5
0.00
0.05
0.10
0.15
0.20
% Intermittent Water (2 km)
Infe
ctio
n R
ate
f.
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
0.05
0.10
0.15
0.20
Sod Farm Estimated N (Lbs)
Infe
ctio
n R
ate
a.
0 1 2 3 4 5 6 7
0.00
0.05
0.10
0.15
0.20
Number of LCOs in 2 km
Infe
ctio
n R
ate
b.
0.00 0.05 0.10 0.15 0.20
0.00
0.05
0.10
0.15
0.20
HOSP Preepizootic Immunity
Infe
ctio
n R
ate
c.
0 50 100 150 200
0.00
0.05
0.10
0.15
0.20
Mosquito Density
Infe
ctio
n R
ate
d.
0.0 0.2 0.4 0.6 0.8 1.0
0.00
0.05
0.10
0.15
0.20
Mosquito Control
Infe
ctio
n R
ate
e.
0 5000 10000 15000
0.00
0.05
0.10
0.15
0.20
Total Estimated N (Lbs)
Infe
ctio
n R
ate
f.
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.