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Table of Contents

  1. Introduction: AIACC: Climate Change and Conservation Planning
    1. Chapter1: Evidence for climate change
      1. Chapter 2: Global circulation models
        1. Chapter 4: Biodiversity responses to past changes in climate
          1. Slide 1: Biodiversity responses to past changes in climate
          2. Slide 2: Climate change is nothing new (Milankovitch theory)
          3. Slide 3: We live in an unusual, stable climate
          4. Slide 4: How do we know all this?
          5. Slide 5: Ice cores can tell us about prehistoric climate conditions
          6. Slide 6: Temperature change
          7. Slide 7 : Carbon dioxide
          8. Slide 8: How might these changes have affected biodiversity?
          9. Slide 9 : Migration
          10. Slide 10: Global features, Last Glacial Maximum (21-18 kbp)
          11. Slide 11: Residual plant populations in the Western Cape
          12. Slide 12: Historic pollen distributions
          13. Slide 13: Current biodiversity reveals the imprint of these changes
          14. Slide 14: Winter Rainfall
          15. Slide 15: Climate reconstruction - Temperature
          16. Slide 16: Climate reconstruction - Rainfall
          17. Slide 17: Climate space modeling, bioclimatic modeling, niche modelling
          18. Slide 18: Fynbos bioclimatic envelope
          19. Slide 19 : Succulent Karoo bioclimatic envelope
          20. Slide 20: The succulent Karoo biome advanced as temperature increased
          21. Slide 21: Pollen evidence?
          22. Slide 22: Centres of endemism and stable climate
          23. Slide 23: The Knersvlakte
          24. Slide 24: Karoo plants evolved incredibly fast
          25. Slide 25: Recent diversity is huge
          26. Slide 26: Mechanistic modelling
          27. Slide 27: Factors of a mechanistic model
          28. Slide 28 : DVM - dynamic vegetation model
          29. Slide 29: Sheffield DGVM
          30. Slide 30: Sheffield DGVM (Woodward)
          31. Slide 31: The role of fire in Savanna ecosystems
          32. Slide 32: Global distribution of fire in 1998
          33. Slide 33: CO2 crisis for C3, woody plants
          34. Slide 34: Low CO2 limits tree growth relatively more than herbaceous plant growth
          35. Slide 35: Under a fire regime, woody plants over a certain height may survive burning
          36. Slide 36: Simulated effects of CO2 on stem height (Mesic savanna)
          37. Slide 37: Implications and tests
          38. Slide 38: Modelled tree cover response to CO2
          39. Slide 39: Wonderkrater pollen Scott, L. (2002)
          40. Slide 40: Empirical experiments
          41. Slide 41: Low CO2 discriminates against woody plants
          42. Slide 42: High CO2 boosts productivity
          43. Slide 43: CO2 level controls, carbon investment in defenses
          44. Slide 44: Plant response
          45. Slide 45 : Conclusions
          46. Slide 46: Test yourself
          47. Slide 47: Links to other chapters
        2. Chapter 5: Adaptation of biodiversity to climate change
          1. Chapter 6: Approaches to niche-based modelling
            1. Chapter 7: Ecosystem function modelling
              1. Chapter 8: Climate change implications for conservation planning
                1. Chapter 9: The economic costs of conservation response options for climate change
                  1. Course Resources
                    1. Practical: Conservation for Climate Change
                      1. Tests to Assess your Understanding
                        1. How to run a GAM model in R

                          Slide 18: Fynbos bioclimatic envelope

                          Duration: 00:00:36

                          Notes:

                          This map shows how effective the system is at mapping the Fynbos biome. The blue is correctly predicted, and the green corresponds to areas in which the model either over- or under-predicts relative to the actual distribution. This model is very straightforward, using mean annual rainfall, minimum temperature, water balance and proportion of winter rain as predictors for distribution.