Emergence of Landscape Ecology

1. Structure Function Emergence of Landscape Ecology ? Equilibrium View • Constant species composition • Disturbance & succession = subordinate factors • Ecosystems self-contained • Internal dynamics shape trajectory • No need to look outside boundaries to understand ecosystem dynamics ? ? ?

2. Structure Function Emergence of Landscape Ecology Dynamic View • Disturbance & ecosystem response = key factors • Disturbance counter equilibrium • Ecosystems NOT self-contained • Multiple scales of processes, outside & inside • Essential to examine spatial & temporal context

3. 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

4. Long Temporal Scale Short Fine Coarse Spatial Scale 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 Speciation Extinction Species Migrations Secondary Succession Windthrow Fire Treefalls Recruitment

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

6. 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

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

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

9. Ecological Scaling: Components of Scale • Minimum Patch Size: min. size considered >resolution of data (defined by grain) • Size of landscape or study area

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

11. Scale in Ecology & Geography • ecological vs. cartographic scale

12. Scale in Ecology & Geography • ecological vs. cartographic scale • e.g., map scale 1:24,000 vs. 1:3,000 fine vs. coarse large vs. small extent

13. 1:24,000 1:200,000

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

15. 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

16. 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 Extent Grain Coarse Fine Scale

17. 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)

18. 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

19. 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

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

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

28. 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,

29. Implications of Changes in Scale Insects sampled at 10-m intervals for 100 m

30. Implications of Changes in Scale Insects sampled at 2000-m intervals for 20,000 m

31. 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

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

33. Hierarchy Theory • Lower levels provide mechanistic explanations • Higher levels provide constraints

34. 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

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

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

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

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

39. Scale & Hierarchy Theory • Change scale: • influential variables might not change, but • shift in relative importance likely Example: Predicting rate of decomposition of plant matter Local scale = lignin content & environ. variability Global scale = temperature & precip.