1. Line transect lecture

2. High seas salmon off BC’s Coast Vegetation transects (Offwell, UK) Duck transects along roads (N. Dakota)

3. Example 1: UK Butterfly monitoring scheme

4. Bald eagles Red-tailed hawks Short-eared owls Example 2: Raptor Census - Kyle Elliott (2002) and the Vancouver Natural History Society

5. Q1. Why transects, not always quadrats? Q2. What are potential biases in method?

6. Animals (in particular): detection bias

8. Example: VNHS Raptor census (Elliott, 2002)

9. Two general methods (see Krebs) 1.Distance from random point to organism. 2. Distance from randomly selected organism to neighbouring organism. 1 2

10. Two general methods (see Krebs) 1.Distance from random point to organism. r Area of circle (π r 2 ) contains one individual Inverse of: Density = individuals per unit area nearest

11. Two general methods (see Krebs) 1.Distance from random point to organism. r r r All methods: calculate area per individual for each circle, calculate mean area per indiv., invert = n π sum (r 2 ) byth-ripley

12. Two general methods (see Krebs) 1.Distance from random point to organism. r r r If look at third closest organism, we are calculating area per three organisms, or if divide by three, mean area per organism (n = 3). = 3n - 1 π sum (r 2 ) ordered distance

13. Two general methods (see Krebs) 1.Distance from random point to organism. 2. Distance from randomly selected organism to neighbouring organism. 1 2

14. Two general methods (see Krebs) 2. Distance from randomly selected organism to neighbouring organism. r Area per two individuals, but two circles: cancels out to same π r 2 formula as before

15. Two general methods (see Krebs) 2. Distance from randomly selected organism to neighbouring organism. r Area per two individuals, but two circles: cancels out to same π r 2 formula as before = n π sum (r 2 ) byth-ripley

16. Two general methods (see Krebs) 2. Distance from randomly selected organism to neighbouring organism. Problem: how to randomly select first individual? Nearest organism to a random point: BIASED Never selected Frequently selected

17. WAYS TO RESOLVE PROBLEM: 1.Mark all organisms with a number, and then randomly select a few. BUT if we could count all organisms, we wouldn’t need a census!

18. WAYS TO RESOLVE PROBLEM: 1.Mark all organisms with a number, and then randomly select a few. 2.Use a random subset of the area (mark organisms in random quadrats). Byth and Ripley

19. WAYS TO RESOLVE PROBLEM: 1.Mark all organisms with a number, and then randomly select a few. 2.Use a random subset of the area (mark organisms in random quadrats). 3.Use a random point to locate organisms, but then ignore area between it and organism (biased to emptiness). T-square

20. The 2 snipers Excellent aim, crooked sights Cross-eyed cat, Straight sights

21. Spatial pattern More uniformMore aggregatedRandom