1. Scale What’s the big deal? Seminal pubs –Allen & Starr (1982) – Hierarchy: perspectives for ecological complexity –Delcourt et al. (1983) – Quaternary Science Review 1:153-175 –O’Neill et al. (1986) – A hierarchical concept of ecosystems

2. Ecological Scaling: Scale & Pattern Acts in the “ecological theatre (Hutchinson 1965) are played out across various scales of space & time To understand these dramas, one must select the appropriate scale Temporal Scale Spatial Scale Fine Short Coarse Long Recruitment Treefalls Windthrow Secondary Succession Species Migrations Speciation Extinction Fire

3. Ecological Scaling: Scale & Pattern Different patterns emerge, depending on the scale of investigation American Redstart Least Flycatcher American Redstart Least Flycatcher Local Scale (4 ha plots) Regional Scale (thousands of ha)

4. Ecological Scaling: Components of Scale Grain: minimum resolution of the data –Cell size (raster data) –Min. polygon size (vector data) Extent: scope or domain of the data –Size of landscape or study area

5. Ecological Scale Scale characterized by: –grain: smallest spatial resolution of data e.g., grid cell size, pixel size, quadrat size (resolution) Fine Coarse

6. Ecological Scale Scale characterized by: –extent: size of overall study area (scope or domain of the data) Small Large

7. Ecological Scaling: Components of Scale Minimum Patch Size: min. size considered > resolution of data (defined by grain)

8. Ecological Scaling: Definitions Ecological scale & cartographic scale are exactly opposite –Ecological scale = size (extent) of landscape –Cartographic scale = ratio of map to real distance

9. Scale in Ecology & Geography ecological vs. cartographic scale EcologyGeography Small (Fine) Fine resolution Small Extent Coarse resolution Large Extent Large (Broad) Coarse resolution Large extent Fine resolution Small extent

10. Scale in Ecology & Geography ecological vs. cartographic scale –e.g., map scale 1:200,000 vs. 1:24,000 fine vs. coarse large vs. small extent

11. 1:24,000 1:200,000

12. Ecological Scaling: Components of Scale From an organism- centered perspective, grain and extent may be defined as the degree of acuity of a stationary organism with respect to short- and long-range perceptual ability What ecological concept is important here?

13. Ecological Scaling: Components of Scale Grain = finest component of environment that can be differentiated up close Extent = range at which a relevant object can be distinguished from a fixed vantage point Fine Coarse Scale Extent Grain

14. Ecological Scaling: Components of Scale From an anthropocentric perspective, grain and extent may be defined on the basis of management objectives Grain = finest unit of mgt (e.g., stand) Extent = total area under management (e.g., forest)

15. Ecological Scaling: Components of Scale In practice, grain and extent often dictated by scale of available spatial data (e.g., imagery), logistics, or technical capabilities

16. Ecological Scaling: Components of Scale Critical that grain and extent be defined for a study and represent ecological phenomenon or organism studied. Otherwise, patterns detected have little meaning and/or conclusions could be wrong

17. Scale: Jargon scale vs. level of organization Space - Time Individual Population Community

21. Ecological Scaling: Implications of Scale As one changes scale, statistical relationships may change: –Magnitude or sign of correlations –Importance of variables –Variance relationships

24. Implications of Changes in Scale Processes and/or patterns may change Hierarchy theory = structural understanding of scale-dependent phenomena Example Abundance of forest insects sampled at different distance intervals in leaf litter,

25. Implications of Changes in Scale Insects sampled at 10-m intervals for 100 m What’s the pattern?

26. Implications of Changes in Scale Insects sampled at 2000-m intervals for 20,000 m What’s the pattern?

27. Identifying the “Right” Scale(s) No clear algorithm for defining Autocorrelation & Independence Life history correlates Dependent on objectives and organisms Multiscale analysis! e.g., Australian leadbeater’s possum

28. Local Scale: old growth with den cavities Large Scale: proportion & connectivity of old growth forest

29. Multiscale Analysis Species-specific perception of landscape features : scale-dependent –e.g., mesopredators in Indiana Modeling species distributions in fragmented landscapes

31. Patches Matrix Corridors

32. Underlying Mechanisms Use of Spatial Elements Distribution Patterns Body Size Niche Breadth

33. Body Size Niche Breadth Mobility Predation Risk Landscape Perception Food Habits Habitat Use

34. Body Size & Niche Breadth

35. PREDICTIONS Species should view the landscape at different spatial scales. Presence of larger species predicted by element and landscape attributes, whereas smaller species correlated with site characteristics.

38. Variables Local Habitat: Ground Cover Canopy Cover Vertical Structure (4 levels from 0-3 m)

39. Variables Element-level: Area, Fractal Dimension, Distance Nearest Edge Landscape-level (1-km & 3-km buffers): NN Distance, Proportion Area, Shannon Diversity Index

41. Coyote Logistic Model 3-km 2 Landscape: Landscape-Element Model w i = 0.77; Relative Likelihood = 3.5 Lower proportion of forest Absence of forest patches & corridors Closer proximity to edge Greater fractal dimension

42. Raccoon Logistic Model 3-km 2 Landscape: Full Model w i >0.999; Relative Likelihood = 999 Lower proportion herb corridors & greater proportion of wooded corridors Greater proportion of forest and forest patches in closer proximity Greater fractal dimension Greater canopy closure & greater vertical structure

43. Long-tailed Weasel Logistic Model 3-km 2 Landscape: Full Model w i >0.999; Relative Likelihood = 999 Greater proportion herb & wooded corridor Presence of forest patches & corridors Closer proximity to edge Presence of small & medium prey Increased ground cover

47. Swihart et al. 2003. Diversity and Distributions 9:1-8.

48. Hierarchy Theory Lower levels provide mechanistic explanations Higher levels provide constraints

49. Scale & Hierarchy Theory Hierarchical structure of systems = helps us explain phenomena –Why? : next lower level –So What? : next higher level minimum 3 hierarchical levels needed

50. Constraints (significance) Level of Focus (level of interest) Components (explanation)

51. Constraints Why are long-tailed weasel populations declining in fragmented landscapes? Components Population Community Individual

52. Constraints Why are long-tailed weasel populations declining in fragmented landscapes? Small body size mobility Population Community Individual

53. Predators Competitors Prey dist’n Why are long-tailed weasel populations declining in fragmented landscapes? Components Population Community Individual

54. Ecological Scaling: Components of Scale Grain and extent are correlated Information content often correlated with grain Grain and extent set lower and upper limits of resolution in the data, respectively

57. Scale Dependence of Habitat Selection 1 st Order 2 nd Order 3 rd Order 4 th Order Macrohabitat vs. Microhabitat 1 st order – innate? 2 nd order –decisions 3 rd &4 th order –decisions