1. Biodiversity metrics – a way forward Ed Rowe

2. Let’s GROW Goal Reality Options Way forward

3. Principles “Biodiversity” means different things to different people We need an operational definition...on a single axis Wilfried Winiwarter: “only one dimension (endpoint) possible”

4. Goal: one metric (per habitat) Index reflecting no net loss of biodiversity N deposition EUNIS class Lv 3? (G1.6)

5. Reality Biodiversity is not easy to define We have been discussing this topic for many years The Call for Data 2012-14 gave us the opportunity to escape

6. Reality slope Ndep (eq ha -1 yr -1 ) average of range studied R 2 = 0.0001 Predicted by regression Slope of Biodiversity Metric vs. N deposition plot Jaap Slootweg Summary of NFC responses to CCE Call for Data 2012-14

7. Are we using the right metrics? Dani Kurz, Beat Achermann (Preliminary results, will be updated!)

8. Must N deposition damage biodiversity? For the N pollution impacts research community – yes, obviously  we could just use deposition rate as an impact metric...but, biodiversity specialists and the public don’t think of biodiversity in terms of nitrogen – sorry. Although, nutrient-poor, less-productive habitats are usually thought of as having greater nature conservation value

9. “Why don’t we just...”...use species-richness? valued habitats are sometimes relatively species-poor...use an index of even-ness, e.g. Shannon or Simpson? valued habitats are sometimes dominated by one species...use scarce / protected species scarce species are often not present

10. Limitations of current models Niches for scarce species are usually less well-defined  we can’t predict values for metrics based on scarce species. We can predict species-richness, at least statistically... although mechanisms are not yet well-understood We can predict habitat-suitability (MOVE, PROPS, MultiMOVE)... but we can’t yet predict probability of occurrence – this would need dynamic modelling of extinction / seedbank persistence / dispersal  we should be a bit careful with language Predicting abundance (e.g. cover) is really hard  we can’t reliably predict values for metrics based on: functional-group abundance (cover of Sphagnum, ericoids etc.) relative abundance of species (e.g. Simpson, Shannon) Although, these could be foci for model development

11. Options Need to be discussed

12. Way forward Accept that there is no “objective”, “scientific”, “value-free” definition of biodiversity Find the people who should define biodiversity for your country Maybe call it “habitat quality” rather than “biodiversity” Allow them to discuss the topic freely Remind them that we need a one-dimensional metric Remind them that we need an answer within this century Maybe ask them to rank a set of real examples of the habitat Agreeing on a metric – things that might help

13. 12 examples of “dry grasslands” Species-richness Ranking according to metric Ranking according to specialists CSM positivesCSM negatives CSM +ves minus -ves Forb / Total cover Similarity to reference (mean)Similarity to reference (max) Mean Ellenberg N Rowe et al. 2014 DivMet/AQ0828 report E1 Dry grasslands

14. Way forward If you really can’t get your biodiversity experts to engage... maybe you will have to decide. UK and NL seem to be settling on “positive indicator-species”, a small set of typical/distinctive species for each EUNIS class Conveniently, values for metrics based on these usually decrease with more deposition Other metrics are available

15. ecro@ceh.ac.uk Thankyou