1. Who Owns Biodiversity? Land accounts for Biodiversity Using Geospatial Information Jerker Moström Dept. Regions and Environment Statistics Sweden EFGS Krakow 2014

2. Why?  Assumption: Ownership reveals different spatial and economic settings for managing land  Agriculture, forestry, industries, private persons, government, etc – different land use regimes  By describing and defining actors, whose actions affects the condition for biodiversity, better policy for safeguarding ecological values can be achieved

3. Aim of project  Find a way to combine data about land valuable for biodiversity with data related to the economy.  EU Habitats directive point of departure – member states are responsible for monitoring certain habitats  Disaggregation of data by industry (NACE/ISIC)  To develop a new statistical module within the environmental accounts in Sweden.

4. Previous efforts Analysis on land ownership has been undertaken previsously From a ”taxation perspective” No disaggregation by industry Entire land area No specific habitats

5. Source data for ownership and industry  Cadastral Map with Real Estate Units (NMCA)  Real Estate Tax Assessment Register (Tax Administration/Statistics Sweden)  Enterprise register with NACE codes, number of employees, revenue etc (Tax Administration /Statistics Sweden)

6. Source data for habitats  kNN database, forest characterisation (Swedish Univesity of Agricultural Sciences)  Wetland inventory (Swedish EPA)  Inventory of grazing land and meadows (Board of Agriculture)  Key Habitat inventory in forest (Board of Forestry)

7. Real estate unit Habitat patch Real estate parcel + Habitat unit Register information linked to geodata via real estate ID + = Selection of objects and habitat areas from geodata back to registers A B Geospatial dataRegisters C Disaggregate habitat areas to industry (by NACE/ISIC) Additional information Statistics Taxation Enterprise

8. Example - Taiga

9.  Western Taïga according to the Habitats directive = Older, mainly coniferous (pine or spruce) forest with a high degree of naturalness  Not possible to use data from the official reporting unit in Sweden because their data is based on estimations and sampling – too coarse  KNN databse on forest characteristics  Hybrid of remote sensing and NFI data  Tree types, height and age.  25 x 25 grids

12. Some results Western Taiga, disaggregation by industry

13. Problems and opportunities ahead  Results experimental – needs further development  Method to connect land use/habitat with data on ownership and industry is successful  Generic model, possible to apply in other studies  We wish to use the method for land accounts on more general land categories  Habitat data is the weak spot!  No high resolution, particularly delimitated data on habitats correspondig to the definitions of the Habitats directive

14. Thank you! jerker.mostrom@scb.se