1. Air Quality Performance Alan Collings Developing UK indicators for the Strategic Plan for Biodiversity 2011-2020: Habitat Connectivity

2. Data issues Any measure of habitat connectivity is only as good as land-cover data on which it is based: Countryside Survey (CS) sample square data and Land Cover Map (LCM) only updated every c.10 years. Species respond at a landscape-scale > CS 1km sample squares. Accuracy/inter-comparability of succeeding editions of LCM hamper detection of change National Forest Inventory is only dataset currently maintained allowing annual measurement of change Indicator-specific land-cover maps could be produced annually from SPOT scenes and Landsat (or GMES) data. Change in number/area of landscape-scale initiatives as a proxy is not a feasible option as lack standard definitions and monitoring.

3. Option A: Species-based indicator of habitat connectivity Most obvious measure of habitat connectivity may be to base it on changes in species distributions but fraught with challenges: At a local scale may reflect other drivers of change Over short timescales may be due to stochastic events At a regional/national level and over longer timescales may be driven by changes in climate rather than habitat connectivity. No methods suitable for immediate implementation identified Potential methods might be developed within five years, subject to funding of research on: Population synchrony Correlations between changes in species distribution and phenology Costs of further research could be substantial.

4. Option B: Indicator of structural connectivity Based on: Simple structural metrics (number of patches, total area and core area – fixed edge width) A structural version of the existing UK Biodiversity Indicator of habitat connectivity Applied to the National Forest Inventory and focused on woodland It could be deployed immediately. Annual costs of either option would be ‘minor’.

5. Option C: Indicator of functional connectivity Based on the existing UK Biodiversity Indicator of habitat connectivity. Applied to an indicator-specific land-cover map, which could be produced within one year. Could be presented: For nested habitats With a breakdown of values for its structural and functional elements. Costs of developing a baseline land-cover map may be substantial and annual costs may be significant.

6. Questions For indicator option A: Can timescales and/or costs of research be reduced? Have other realistic methods been overlooked? For indicator option B: Is the National Forest Inventory fit-for-purpose for this indicator? Are there other simple metrics that should also be included? Should the evaluation scores for the two methods be the same? For indicator option C: Does it address concerns about the existing indicator’s application to 1km squares, reliance on expert judgement and complexity? Is development of an indicator-specific spatial land-cover dataset realistic? Are there other ways in which its costs might be further reduced?

7. Richard Smithers Principal Consultant: Biodiversity & Ecosystem Services Ricardo-AEA The Gemini Building Fermi Avenue Harwell Didcot OX11 0QR Tel: +44 (0)870 190 6726 Mob: +44 (0)7968 707145 E: Richard.Smithers@ricardo-aea.com W: http://www.ricardo-aea.com Copyright Ricardo-AEA Ltd This presentation is submitted by Ricardo-AEA. It may not be used for any other purposes, reproduced in whole or in part, nor passed to any organisation or person without the specific permission in writing of the Commercial Manager, Ricardo-AEA Ltd.