The Effect of Residential Properties on Breeding Bird Diversity in Urban Forest Patches

1. The Effect of Residential Properties on Breeding Bird Diversity in UrbanForest Patches Chrissa Carlson1, Mary Cadenasso2, Gary Barrett1 Institute of Ecology, University of Georgia Department of Plant Sciences, University of California, Davis Submitted to Ecological Applications

2. Urban Habitats: • Not all are created equal How is biodiversity is impacted by surrounding urban development?

3. Urban Habitats: • Residential areas: top-down vs. bottom-up management (Melles 2005) • Interaction between landscape elements under different management regimes

4. Birds and urban biodiversity • Quality of life (Clergeau et al. 2001) • Biological poverty (Turner et al. 2004) • Respond to environmental variables at multiple scales (Hostetler 2001) • Conservation of metapopulations (Fernandez-Juricic 2004)

5. Major research question • Can homeowners modify avian diversity in forest fragments from the outside-in?

6. Major research question • Is there a relationship between breeding bird community structure within forest habitat fragments and the resources located in the surrounding residential matrix, managed by humans at the scale of the individual land parcel? • Resources=tree and other vegetation cover, bird feeders, baths, etc.

7. Birds in urban forest fragments: • Island biogeography theory (Robbins et al. 1989) but… • Patches of equal area often differ in species richness (Dawson et al. 1993) • Isolation not as important as in agricultural landscapes (Watson et al. 2005) • Landscape context matters (Bennett et al. 2004, Park and Lee 2000, Nilon and Pais 1997, Andren 1994) • Land-use is a poor predictor of bird occurrence (Hostetler and Knowles-Yanez 2003)

8. Hypotheses: Total species richness is best explained by patch-level features (area, vegetation structure), but additional variation may be explained by: • Neighborhood age (+) • Variation in the distribution of landcover types in the surrounding neighborhood

9. Methods: Site Selection n=15 • 2-10 ha forest patches in Gwynns Falls Watershed • Surrounding landuse primarily residential • National Landcover Dataset (NLCD) 2000 and EMERGE 2004 aerial imagery

10. Methods: Bird Surveys • Territory mapping method

11. Methods: Bird Surveys • Territory mapping method • Each site visited six times • Clusters of detections used to estimate relative density of breeding territories D C B A A Patch 12: Northern Cardinal

12. Methods: Forest Patch Characterization • Patch area • Modified UFORE surveys on 5 m radius plots centered at random points • tree species richness • tree density • max DBH • foliage height diversity • stem size diversity • Principle Components Analysis performed on vegetation structure variables to capture variation in forest structure among sites

13. Methods: Neighborhood Characterization • HERCULES classification (Cadenasso et al. in press) applied to surrounding neighborhoods within 100 m buffer

14. Bldg type: 1 Bldg cover: 3 CV cover: 1 FV cover: 3 Pavement cover: 2 Bare soil cover: 0 Bldg type:2 Bldg cover:3 CV cover:1 FV cover:3 Pavement cover:2 Bare soil cover:0 Methods: Neighborhood Characterization Bldg type: 0 Bldg cover: 0 CV cover: 0 FV cover: 2 Pavement cover: 1 Bare soil cover: 1 Bldg type:1 Bldg cover:3 CV cover:1 FV cover:2 Pavement cover:2 Bare soil cover:0 Bldg type: 2 Bldg cover: 3 CV cover: 1 FV cover: 1 Pavement cover: 2 Bare soil cover: 0 Bldg type:1 Bldg cover:3 CV cover:1 FV cover:3 Pavement cover:2 Bare soil cover:0

15. Bldg type: 1 Bldg cover: 3 CV cover: 1 FV cover: 3 Pavement cover: 2 Bare soil cover: 0 Bldg type:2 Bldg cover:3 CV cover:1 FV cover:3 Pavement cover:2 Bare soil cover:0 Methods: Neighborhood Characterization • Area-weighted mean calculated for each cover variable in each buffer • PCA performed on area-weighted means to capture variation in distribution of landcovers Bldg type: 0 Bldg cover: 0 CV cover: 0 FV cover: 2 Pavement cover: 1 Bare soil cover: 1 Bldg type:1 Bldg cover:3 CV cover:1 FV cover:2 Pavement cover:2 Bare soil cover:0 Bldg type: 2 Bldg cover: 3 CV cover: 1 FV cover: 1 Pavement cover: 2 Bare soil cover: 0 Bldg type:1 Bldg cover:3 CV cover:1 FV cover:3 Pavement cover:2 Bare soil cover:0

16. Methods: Neighborhood Age • Used HERCULES classification to calculate area-weighted median neighborhood age

17. Methods: Data Analysis • Information-Theoretic Model Selection using Akaike’s Information Criterion • Linear regression models

18. Total species richness is best explained by patch-level features (area, vegetation structure), but additional variation may be explained by: • Neighborhood age (+) • Variation in the distribution of landcover types in the surrounding neighborhood Multiple working hypotheses: Total Species Richness (TSR) • TSR=ßo+ß1(Area)+ß2(PCAveg)+ß3(Age) • TSR=ßo+ß1(Area)+ß2(PCAveg)+ß3(Age)-ß4(Age2) • TSR=ßo+ß1(Area)+ß2(PCAveg)+ß3(PCAHERC1) • TSR=ßo+ß1(Area)+ß2(PCAveg)+ß3(PCAHERC1)+ ß4(PCAHERC2) • TSR=ßo+ß1(Area)+ß2(Age) • TSR=ßo+ß1(Area)+ß2(Age)-ß3(Age2) • TSR=ßo+ß1(Area)+ß2(PCAHERC1) • TSR=ßo+ß1(Area)+ß2(PCAHERC1)+ß3(PCAHERC2) • TSR=ßo+ß1(Area)+ß2(PCAveg) • TSR=ßo+ß1(Area)

19. Results: Bird Species Detected

20. Results: Neighborhood Characterization

21. Results: Neighborhood Characterization Bunch o’ bare soil Plenty o’ pavement Tons o’ trees Gobs o’ grass

22. Results: Neighborhood Characterization 6.46 - 60.02 years 32.49 [mean] ± 14.73 [S.D.]

23. Results: Model Selection Model AICc ωi 0.01 69.45 TSR I 0.02 67.90 TSR II 0.12 63.76 TSR III TSR IV 0.01 68.02 TSR V 0.02 66.97 0.13 TSR VI 63.60 TSR VII 0.47 61.11 TSR=ßo+ß1(Area)-ß2(PCAHERC1) TSR VIII 0.11 64.08 TSR IX 0.03 66.56 TSR X 0.08 64.62

24. Results: Model Selection Model AICc ωi 0.01 69.45 TSR I 0.02 67.90 TSR II 0.12 63.76 R2=0.69 • TSR=ßo+ß1(Area)+ß2(PCAveg)-ß3(PCAHERC1) TSR III TSR IV 0.01 68.02 TSR V 0.02 66.97 TSR VI 0.13 63.60 R2=0.69 • TSR=ßo+ß1(Area)+ß2(Age)-ß3(Age2) TSR=ßo+ß1(Area)-ß2(PCAHERC1) R2=0.68 TSR VIII 0.11 64.08 TSR IX 0.03 66.56 TSR X 0.08 64.62

25. Conclusions • Breaking news: Forest birds like trees • The real kicker: they like them in their habitat, but also surrounding it. Evidence from the analysis… • PCAHERC1 (negative) appeared in two of three best models, this axis represented the tendency for tree cover in the neighborhood to decrease as pavement increases • The quadratic transformation of neighborhood age (AGE-AGE2) appeared in the second best species richness model; neighborhood canopy cover has an inverse parabolic relationship with neighborhood age (Grove et al. 2006) R2=0.60 Coarse veg cover ~40 years Neighborhood Age

26. Conclusions • Neighborhood age alone did not appear in any of the top models; time since disturbance does not allow more species to colonize • The structure of the forest itself explained less variation in breeding bird diversity than the structure of the neighborhood surrounding the forest

27. Conclusions • Diverse household land-management practices collectively shape urban landscapes • Relationships were observed at very narrow buffer width individual landowners can impact habitats from the outside-in • Neighborhoods can be managed as a buffers to forest habitat (Watson et al. 2005)

28. Conservation value? • Biodiversity can be used as a tool to inform land management practices that effect multiple environmental issues • Confronting the culture of status associated with big green lawns is a challenge for many aspects of conservation • Emphasize aesthetic/ecological value of a complex yard habitat, particularly adjacent to forest

29. Further research • Different buffer widths • Change across years • Habitat quality: productivity/survivorship • Test models in different landscapes

30. Acknowledgements • Graduate Committee: Gary Barrett, Roarke Donnelly, Robert Cooper • BES: Paige Warren, Charlie Nilon, Morgan Grove, Jarlath O’Neil-Dunne, Mike McGuire, Kirsten Schwartz • Field Assistance: Andy Flies • NSF Graduate Research Fellowship Questions?