Components of plant species diversity in the New Zealand forest

1. Components of plant species diversity in the New Zealand forest Jake Overton Landcare Research Hamilton

2. Acknowledgements NVS data contributors and curators Simon Ferrier and Glenn Manion for development of GDM and collaboration on modelling

3. General Question Investigate components of richness Alpha diversity Beta diversity Gamma diversity How do these compare between groups? Approach: Use a new modelling technique, Generalised Dissimilarity Modelling (GDM) to estimate components of diversity

4. Components of diversity (sensu Cody 1986) Alpha diversity = local richness Beta diversity = turnover in species due to habitat or environment Gamma diversity = turnover in species due to geographic distance or barriers All three components contribute to regional richness

5. NVS recce (= recon) plots Biotic Data Almost 20000 plots 1220 species Presence-absence of all vascular plant species in each plot Plots approx 20x20 m (sometimes unbounded)

8. Mocoto herbs Environmental variables (spatial)

9. What is Generalised Dissimilarity Modelling? alpha diversity (local richness) beta diversity ‘dissimilarity’ ‘turnover’ ‘complementarity’ gamma diversity Modelling of richness: richness = f(rainfall, temperature, veg type …) can be supplemented by modelling of compositional dissimilarity between locations: dissimilarity = f ( (rainfall, temperature, veg type …), geographical separation)

10. Generalised dissimilarity modelling (GDM) Environmental & geographical separation Compositional dissimilarity between pairs of survey sites Biotic Information Environmental and Geog Space Ecological Space Same units scaled by importance Differing units and importance

11. All species model

12. Results 1 All species validation

13. Mocoto herbs Unexplained component = 1 – proportion deviance explained Alpha diversity component = Proportion accounted for by local richness = Mean plot richness/ Total species pool All species Gamma Diversity component = Proportion deviance explained by geography Beta Diversity component = Deviance explained by environment Total species pool 1020 species

14. Mocoto herbs Snails All plant species

16. Results 1

17. Mocoto herbs Ferns Shrubs Trees Monocot herbs All Dicot Herbs

18. Mocoto herbs Monocot herbs Dicot Herbs Ferns All species Trees Shrubs

19. Predicted distributions of species Constrained environmental classification Biological survey data Visualisation of spatial pattern in community composition Generalised dissimilarity modelling Conservation assessment Environmental predictors Climate-change impact assessment Survey gap analysis Ferrier, S. et al (in press) Using generalised dissimilarity modelling to analyse and predict patterns of beta-diversity in regional biodiversity assessment. Diversity & Distributions

20. Ferrier, S. et al (2004) Mapping more of terrestrial biodiversity for global conservation assessment. BioScience 54:1101-1109

21. Conclusions GDM is an exciting new tool for biodiversity analyses Its main application is for biodiversity modelling and planning, but it has promise for untangling components of diversity Plant species show relatively strong environmental influence and some geographic influence on turnover Groups differ in the explained turnover, and in relative importance of different variables.

22. test

23. Dense sampling relative to grain of compositional turnover - relatively few species, each with many records Sparse sampling relative to grain of compositional turnover - huge number of species, each with very few (or no) records Geographical space (gamma diversity) Geographical space (gamma diversity) Environmental space (beta diversity) Environmental space (beta diversity)

24. An example from the arid rangelands of central Australia

25. Mocoto herbs All species

26. Mocoto herbs

27. Mocoto herbs All species

28. f (Tc10d) f (Wetness) Biological response Bray-Curtis compositional dissimilarity between all pairs of 248 field survey sites (based on perennial woody plant species) • Environmental predictors • Radiometrics – Total Count • Landsat TM – Band 2 • Radiation of Warmest Quarter • Topographic Wetness Index • Precipitation of Driest Period • Isothermality • Minimum Temperature of Coldest Period • Elevation Diversity for 300m radius • Landsat TM – PD54 vegetation index • Mean Temperature of Wettest Quarter • Radiometrics – Uranium

29. What is Generalised Dissimilarity Modelling? Models species turnover (dissimilarity) between locations as a function of geography and environment Uses matrix regression, using GLMs. Developed by Simon Ferrier, (Department of Environment and Conservation, Armidale New South Wales, Australia) Programmed by Glenn Manion, DEC, Armidale.

30. Mocoto herbs Monocot herbs Dicot Herbs Ferns All species Trees Shrubs

31. Ferns Ferns

32. L-E-P test

33. Monocot herbs Monocot herbs

34. Shrubs Shrubs

35. Trees

36. test Dicot Herbs

37. Ferns

38. L-E-P test

39. Monocot herbs

40. Shrubs

41. Trees Trees