Relative influence of local and landscape factors on bird communities vary by species and functional group
Both fine scale patterns of vegetation and coarser scale landscape patterns affect bird community composition, but the relative importance of these two sets of patterns tends to be context dependent, varying by location and taxonomic group. Here, we explore the relative roles of landscape pattern and stand structure and composition in defining bird communities in 44 remnant oak stands in the Willamette Valley, Oregon. We focused on: (1) whether bird communities are influenced more by landscape (matrix and patch) patterns or stand composition and structure, and (2) in what contexts each of these spatial scales are more important. Specifically, we focused on how different groups of bird species (functional groups, synanthropic and non-synanthropic species, and individual species) were differentially influenced by landscape and more local patterns.
We conducted point counts to determine avian abundance, richness and evenness and categorized birds into functional groups based on diet and foraging tactics. We then used canonical correspondence analysis and generalized linear models to analyze overall community patterns, functional group diversity, synanthropic and non synanthropic species diversity and individual species’ abundances.
Both local and landscape factors significantly influenced each group of avian species for every measure of diversity we tested, but their relative importance varied markedly. Local factors explained four times more variance than landscape factors for overall species diversity, whereas for functional groups, landscape factors explained one quarter to ten times the variance of local factors, depending on the group. For example, landscape factors were five times more important for the corvidae omnivores and ten times more important for the flycatchers than were local factors. By contrast, local factors were twice as important for seed eaters, frugivores and ground foragers, and bark foragers than were landscape patterns. We found the same high variability for individual species.
We conclude that the relative contribution of factors at different scales to the structuring of bird communities (as with the effects of so many other ecological processes and patterns) strongly depends on context—in this case, the specific group of species being considered.
KeywordsAvian Birds Matrix Scale Functional groups Habitat Community composition
We gratefully acknowledge support for this research from the National Science Foundation’s Coupled Natural–Human Systems Program. The authors also thank Aaron Wirsing and John Marzluff; Bob Altman for guidance on field work; Monte Mattsson and Candace Fallon for assistance in the field; and many people who helped identify and provide access to the field sites.
- Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: Petro BN, Caski F (eds) Proceedings of the second international symposium on information theory. Akademiai Kiado, Budapest, pp 267–281Google Scholar
- Askins RA, Philbrick MJ (1987) Effect of changes in regional forest abundance on the decline and recovery of a forest bird community. Wilson Bull 99:7–21Google Scholar
- Beyer HL (2006) Hawth’s analysis tools v. 3.27. Sept 2007. Open source software available at http://www.spatialecology.com/htools/. Accessed June 2012
- Bibby CJ, Burgess ND, Hill DA, Mustoe SH (2000) Bird census techniques, 2nd edn. Academic Press, LondonGoogle Scholar
- Bollmann K, Weibel P, Graf RF (2005) An analysis of central Alpine capercaillie spring habitat at the forest stand scale. For Ecol Manag 215:307–318Google Scholar
- Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, New YorkGoogle Scholar
- Butcher GS, Niven DK (2007) Combining data from the Christmas bird count and the breeding bird survey to determine the continental status and trends of North America birds. National Audubon Society, New York, p 34Google Scholar
- Ehrlich PR, Dobkin DS, Wheye D (1988) The Birder’s Handbook: A Field Guide to the Natural History of North American Birds: including all species that regularly breed north of Mexico. Simon and Schuster, New YorkGoogle Scholar
- Environmental Systems Resource Institute, ESRI (2009) ArcMap 9.2. ESRI (Environmental Systems Resource Institute), RedlandsGoogle Scholar
- Freemark K, Dunning JB, Hejl SJ, Probst JR (1995) A landscape ecology perspective for research, conservation, and management. In: Martin TE, Finch DM (eds) Ecology and management of neotropical migrant birds. Oxford University Press, New York, pp 381–421Google Scholar
- Hodgkison S, Hero JM, Warnken J (2007) The efficacy of small-scale conservation efforts, as assessed on Australian golf courses. Biol Conserv 135:576–586Google Scholar
- Huff MH, Bettinger KA, Ferguson HL, Brown MJ, Altman B (2000) A habitat-based point-count protocol for terrestrial birds, emphasizing Washington and Oregon. US Department of Agriculture, Forest Service, Pacific Northwest Research Station, PortlandGoogle Scholar
- Huff MH, Seavy NE, Alexander JD, Ralph CJ (2005) Fire and birds in maritime Pacific Northwest. Stud Avian Biol 30:46Google Scholar
- James FC, Shughart HH (1970) On understanding quantitative surveys of vegetation. Audubon Field Notes 24:727–736Google Scholar
- Jensen JR (2004) Chapter 13: thematic map accuracy assessment. In: Introductory digital image processing: a remote sensing perspective, 2nd edn. Prentice Hall, Upper Saddle River, pp 495–515Google Scholar
- Marzluff J (ed) (January 2014) Personal communication. In: Urban Ecosystems (in press)Google Scholar
- NatureServe (2005) International ecological classification standard: terrestrial ecological classifications. Oregon ecological systems 2008. Raster digital data set created for use in Northwest ReGap. University of Idaho. Available at http://gap.uidaho.edu/index.php/nw-gap/
- Noss RF, LaRoe ET, Scott JM (1995) Endangered ecosystems of the United States: a preliminary assessment of loss and degradation. National Biological Service, Moscow, p 76Google Scholar
- Oksanen J (2011) Multivariate analysis of ecological communities in R: vegan tutorial. http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf. Accessed June 2012
- Oksanen J (2014) Cluster analysis: tutorial with R. http://cc.oulu.fi/~jarioksa/opetus/metodi/sessio3.pdf. Accessed June 2012
- Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'Hara RB, Simpson GL, Solymos P, Stevens MHH, Wagner H (2011) Vegan: community ecology package. R package version 2.0-2 November 2014. Open source software available at http://cran.r-project.org/web/packages/vegan/index.html. Accessed June 2012
- Poole A (2005) The birds of North America online. Cornell Laboratory of Ornithology, Ithaca. http://bna.birds.cornell.edu/BNA/. Accessed June 2012
- R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Riitters KH, O’neill RV, Hunsaker CT, Wickham JD, Yankee DH, Timmins SP, Jones KB, Jackson BL (1995) A factor analysis of landscape pattern and structure metrics. Landscape Ecol 10:23–39Google Scholar
- Roberts LJ (2001) Habitat and landscape associations of bird populations in the Nicolet National Forest, Wisconsin. University of Wisconsin, Green BayGoogle Scholar
- Zar JH (1998) Biostatistical analysis, 4th edn. Prentice Hall, Upper Saddle RiverGoogle Scholar