1. 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Predictive modeling of benthic macrofauna distribution: Data inventory and habitat suitability modeling for Baltic Sea macroinvertebrates in response to selected environmental factors Mayya Gogina Michael Glockzin Michael L. Zettler

2. Introduction 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Life history-population dynamics Low High Environmental conditions Biotic interactions 0.01 m 2 0.1 m 2 1.0 m 2 100 m 2 1 km 2 100 km 2 -2 Relative importance of factors influencing succession over spatial extents (Zajac et al., 1998; Gray and Elliott, 2009) Static distribution modeling - approach to study possible consequences Spatial and temporal scales of human disturbances which impact soft-sediment habitats (Zajac et al., 1998) food supply, T, S, O2, substrate, sedimentation, flow energy, bathymetry

3. Background 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Zettler 1996 - variation in distribution of M. viridis Ellis et al. 2006, Thrush et al. 2005 - New Zealand estuaries Meissner et al. 2008, Degraer et al. 2008 - habitat models, North Sea Glockzin and Zettler 2008 - Pomeranian Bay, southern BS Gogina et al. (subm.) - Mecklenburg Bay, southern BS Olenin 1997 - main factors driving biodiversity in the Baltic Proper Laine 2003 - soft-bottoms in deep open BS Bonsdorff 2006, Zettler et al. 2008 – Salinity, O 2 define BS diversity Meters Regional Baltic Sea Various scales: Zettler, 1996 Gogina et al. (subm.)Bonsdorff, 2006

4. Salinity and species richness in macrobenthos 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Projection: ERTS89_LAEA CRS (Lambert Azimuthal Equal Area projection, ETRS89 datum)

5. Questions How will biota respond to habitat changes (natural or anthropogenic) ? Can we predict the full coverage spatial distribution of macrobenthic communities (or specific species) within the Baltic Sea ? Goals compilation of an extensive list of taxa and an inventory dataset on species distribution for the whole Baltic Sea extraction of species distribution patterns regarding selected /available/ environmental parameters – salinity, bathymetry, sediment type modeling and mapping the probabilities of occurrence for exemplary species Problems and Goals www.awi-bre merhaven.de www.commons. wikimedia.org www.eumed.net www.marine. maine.edu www.conchology.be www.marlin.ac.uk www.marinebiodiversity.ca 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia

6. Materials and methods: Data inventory Taxonomic list 1110 taxa incl. freshwater species valid taxonomy, synonimy distribution autoecology – in progress 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Numerous literature sources IfAÖ autecological atlas HELCOM monitoring data (ICES-Database) Baltic Sea Alien Species Database IOW monitoring, research programmes over 160.000 entries (>12.000 stations) 1839-2009

7. 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Materials and methods: environmental factors Bathymetry IOWTOPO, Seifert & Kayser (2001) Initial resolution ≈ 1 nm Coordinate system: WGS_1984_UTM_Zone_34N

8. 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Materials and methods: environmental factors Bathymetry IOWTOPO, Seifert & Kayser (2001) Initial resolution ≈ 1 nm Modeled near-bottom salinity Neumann & Schernewski (2008) Averaged for years 1960-2005 Initial resolution ≈ 3 nm Coordinate system: WGS_1984_UTM_Zone_34N

9. 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Materials and methods: environmental factors Bathymetry IOWTOPO, Seifert & Kayser (2001) Initial resolution ≈ 1 nm Modeled near-bottom salinity Neumann & Schernewski (2008) Averaged for years 1960-2005 Initial resolution ≈ 3 nm Seabed sediments BALANCE Interim Report No. 10 Resolution 200 m Coordinate system: WGS_1984_UTM_Zone_34N 3 environmental variables for each grid cell 6858 x 7827, 200 m resolution

10. Exemplary species 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia nn Taxon Autor Feeding typeSubstratePenetrationSalinity (PSU)Freq. (%) CRUSTACEA 1Bathyporeia pilosa Lindström, 1855grazingfine sands0-3 cm7.3-14.77.3 2Corophium volutator (Pallas, 1766)deposit and suspension feedingmuddy sands2-5 cm5-3510.7 3Diastylis rathkei (Kröyer, 1841)deposit feedingmuddy sands and mud1-5 cm7.7-30.334.0 4Pontoporeia affinis Lindström, 1855deposit feedingmud to sand0-5 cm0-1014.3 5Pontoporeia femorata Krøyer, 1842deposit feedingmud to sand0-5 cm11.5-30.312.3 6Saduria entomon (Linnaeus, 1758)predationmud to sand, complex0-10 cm3-1313.7 MOLLUSCA 7Arctica islandica (Linnaeus, 1767)suspension feedingmud to sand0-14cm15-3121.2 8Astarte borealis (Schumacher, 1817)suspension feedingmud to sand0-1 cm15.8-4013.1 9Hydrobia ulvae (Pennant, 1777)grazingmud to sand0-1 cm10-3324.9 10Hydrobia ventrosa (Montagu, 1803)grazingmud to sand0-1 cm6-206.2 11Macoma balthica (Linnaeus, 1758)deposit and suspension feedingmud to sand5-6 cm4.6-30.348.4 12Mya arenaria Linnaeus, 1758suspension feedingfine and medium sandsup to 40 cm7.3-30.325.8 13Mytilus edulis Linnaeus, 1758suspension feedingmud to boulders0 cm6.8-30.334.5 POLYCHAETA 14Heteromastus filiformis (Claparède, 1864)deposit feedingmud to sandup to 30 cm15-30.318.4 15Lagis koreni Malmgren, 1866 deposit feedingmuddy sands0-10 cm15-30.316.4 16Pygospio elegans Claparède, 1863deposit and suspension feedingfine and medium sands4-6 cm7.2-29.328.9 17Scoloplos armiger (Müller, 1776)deposit feedingmuddy sands and mud5-15 cm11.5-32.430.7 18Terebellides stroemii Sars, 1835deposit feedingmud to gravel0 cm35-1016.7 PRIAPULIDA 19Halicryptus spinulosus von Siebold, 1849deposit feeding and predationmuddy sands and mud1-6 cm6.8-21.321.5 Various functional groups Marine and limnic species

11. Exemplary species vs. environmental factors 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia

12. Materials and methods: model building process 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Classification accuracy evaluated by AUC (Area under ROC-curve) Biotic data reduced to presence/absence where, Model selection based on information theoretic approach (Burnham and Anderson 2004) Models with lowest AIC (Akaike Information Criteria) value within a set are the most parsimonious Binary logistic regression (GLM) Salinity (S), Bathymetry (D) - simple polynomial response Sediment class (Sed) - 4-level categorical covariate Random split to calibration and evaluation datasets (50%) Probability of species occurrence modeled and mapped

13. Results: Predictive modeling of species distribution 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia AUC (95% Cl)ThresholdCCR [%]Sens. [%]Spec. [%] Ponaff0.942 (0.935-0.949)0.1687.492.182.8 Macbal0.746 (0.734-0.759)0.5067.472.262.4

14. 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia Results: Predictive modeling of species distribution AUC (95% Cl)ThresholdCCR [%]Sens. [%]Spec. [%] Halspi0.747 (0.733-0.761)0.3071.758.475.9 Arcisl0.917 (0.910-0.924)0.50 85.676.688.5

15. Salinity, bathymetry and sediment type are all important in determining the distribution of most characteristic macrobenthic species on a large scale of the whole Baltic Sea. Simple empirical (logistic regression based) habitat suitability models allow to satisfactorily predict the distribution of macrofaunal species even based solely on modeled salinity, bathymetry and rough sediment class information. Models performed comparatively well in the whole Sea, however their applicability outside the Baltic should be considered at least questionable. The present exercise is only a first step. Implementation of other variables (e.g. characterizing temperature fluctuations, total organic content, nutrient supply) would obviously increase the model applicability. Information on the ecological potential of a habitat suitability is utmost important for scientifically sound marine spatial planning (e.g. accounting for precautionary principal, high potential areas should be avoided when planning new marine constructions). Conclusion remarks 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia

16. Thank you for your attention! 7 th BSSC 2009 August 17-21, 2009, Tallinn, Estonia