BEHAVIORAL CHARACTERISTICS OF LANDSCAPE STRUCTURE METRICS IN NEUTRAL LANDSCAPES

1. BEHAVIORAL CHARACTERISTICS OF LANDSCAPE STRUCTURE METRICS IN NEUTRAL LANDSCAPES FRAGSTATS Workshop18, July 2003IALE World Congress Darwin, Australia

2. Increasing area (P) 95% Step 1: Generate binary neutral landscapes using the computer program RULE (Gardner 1999). Increasing aggregation (H) 0 1 5% 256 x 256 cell grids Factorial Design H (n = 21) x P (n = 19) 100 replicates of each of 399 H x P combinations

3. Step 2: Calculate 55 applicable class-level metrics on all 39,900 neutral landscapes using FRAGSTATS. FRAGSTATS Specifications: • 30 m cell size • 90 m edge depth • 500 m search radius • 8 cell neighbor rule • No border • No background • Boundary not included as edge

4. Conceptual Metric Classification Isolation/ Proximity Proximity Index* Similarity Index* Euclidean Nearest Neighbor* Shape Perimeter Area Fractal Perimeter Area Ratio* Shape Index* Fractal Dimension Index* Core Area Total Core Area Core Percent of Landscape # Disjunct Core Areas Disjunct Core Area Density Core Area Disjunct Core Area* Core Area Index* Area/Edge/ Density Class Area Percent of Landscape Patch Density Edge Density Landscape Shape Index Largest Patch Index Normalized Shape Index Patch Area* Radius of Gyration* Contagion/ Interspersion Percent Like Adjacencies Clumpiness Index Aggregation Index Intersperson and Juxtapostion Index Landscape Division Splitting Index Effective Mesh Size Contrast Contrast Weighted Edge Density Total Edge Contrast Index Edge Contrast* Connectivity Patch Cohesion Index

5. Conceptual Metric Classification Isolation/ Proximity PROX* SIMI* ENN* Shape PAFRAC PARA* SHAPE* FRAC* Core Area TCA CPLAND NDCA DCAD CORE* DCORE* CAI* Area/Edge/ Density CA PLAND PD ED LSI LPI nLSI AREA* GYRATE* Contagion/ Interspersion PLADJ CLUMPY AI IJI DIVISION SPLIT MESH Contrast CWED TECI ECON* Connectivity COHESION

6. Metric Behavior H P

7. Step 4: Plot the range of the H x P space that real landscapes occupy • Calculate metrics in landscapes from three geographically distinct regions in the United States: • Idaho (221 landscapes, 5 classes) • Western Massachusetts (155 landscapes, 7 classes) • Colorado (152 landscapes, 4 classes) • Superimpose values from real landscapes onto values from neutral landscapes.

9. Metric Behavior H P

12. Step 5: Evaluate patterns of class-level metric behavior in using mean metric values for 48 metrics. • Use cluster analysis to classify metrics based on behavior along P and H gradients. • Graphically compare behavior of metrics.

13. Primarily a Function of P LPI AREA_AM AREA_SD GYRATE_AM GYRATE_SD CORE_AM CORE_SD TCA DCORE_AM DCORE_SD PROX_MN PROX_CV PROX_SD DIVISION MESH H P

14. Primarily a Function of H:Strongly Related to H PAFRAC nLSI PARA_SD FRAC_CV FRAC_SD CAI_SD CLUMPY

15. CLUMPY

16. Related to Interaction of P and H Parabolic Response Along P LSI PD GYRATE_CV FRAC_AM SHAPE_AM SHAPE_CV SHAPE_SD PROX_AM DCORE_CV DCAD ED

17. FRAC_AM DCAD SHAPE_SD

18. Related to Interaction of P and H GYRATE_MN PARA_AM CORE_MN DCORE_MN CAI_AM CAI_MN SPLIT PLADJ AI COHESION ENN_AM ENN_MN ENN_CV ENN_SD AREA_MN

19. ENN_AM GYRATE_MN PARA_AM COHESION

20. P = 5% P = 50% P = 95% H = 0 P = 5% P = 50% P = 95% H = 1 Differential Metric Sensitivity AREA_MN AREA_AM

21. Main Points **Limitations** • Results are based on • binary neutral landscapes. • at one scale. • only one configuration gradient (H). Varying shape, inter-patch distance, etc. would yield different behavior. • Identified 7 behavioral groups with varying relationships with P and H. • Conceptual similarity ≠ behavioral similarity. • Many metrics have non-linear behavior and lack of sensitivity in at least part of the H x P space. • Problematic conditions do not always exist in real landscapes. • Very few metrics measure configuration independent of area – most confound P & H.