Publications and presentations

Policy briefs

Policy Brief - Reaching Good Environmental Status and Blue Growth - in a novel future (pdf)

Peer-reviewed articles

Laurila-Pant, M., Mäntyniemi, S., Östman, Ö., Olsson, J., Uusitalo, L., Lehikoinen, A. 2021. A Bayesian approach for assessing the boundary between desirable and undesirable environmental status - an example from a coastal fish indicator in the Baltic Sea. Ecological Indicators 120: 106975. doi: 10.1016/j.ecolind.2020.106975

Kaikkonen, L., Parviainen, T., Rahikainen, M., Uusitalo, L. and Lehikoinen, A., 2021. Bayesian networks in environmental risk assessment: A review. Integrated Environmental Assessment and Management, 17(1), pp.62-78. doi: 10.1002/ieam.4332

Uusitalo, L., Jernberg, S., Korn, P., Puntila-Dodd, R., Skyttä, A., & Vikström, S. 2020. Fuzzy cognitive mapping of Baltic Archipelago Sea food webs reveals no cliqued views of the system structure between stakeholder groups. Socio-Environmental Systems Modelling 2 (16343). doi:10.18174/sesmo.2020a16343

Otto, S.A., Kadin, M., Casini, M., Torres, M.A. and Blenckner, T., 2018. A quantitative framework for selecting and validating food web indicators. Ecological Indicators, 8Otto, S.A., Kadin, M., Casini, M., Torres, M.A. and Blenckner, T., 2018. A quantitative framework for selecting and validating food web indicators. Ecological Indicators, 84, pp.619-631.

Uusitalo, L., Tomczak, M.T., Müller-Karulis, B., Putnis, I., Trifonova, N. and Tucker, A., 2018. Hidden variables in a Dynamic Bayesian Network identify ecosystem level change. Ecological informatics, 45, pp.9-15.

Smoliński, S., 2019. Sclerochronological approach for the identification of herring growth drivers in the Baltic Sea. Ecological indicators, 101, pp.420-431.

Voss, R., Quaas, M.F., Stiasny, M.H., Hänsel, M., Pinto, G.A.S.J., Lehmann, A., Reusch, T.B. and Schmidt, J.O., 2019. Ecological-economic sustainability of the Baltic cod fisheries under ocean warming and acidification. Journal of environmental management, 238, pp.110-118.

Lehikoinen, A., Olsson, J., Bergström, L., Bergström, U., Bryhn, A., Fredriksson, R. and Uusitalo, L., 2019. Evaluating complex relationships between ecological indicators and environmental factors in the Baltic Sea: A machine learning approach. Ecological indicators, 101, pp.117-125.

Maldonado, A.D., Uusitalo, L., Tucker, A., Blenckner, T., Aguilera, P.A. and Salmerón, A., 2019. Prediction of a complex system with few data: Evaluation of the effect of model structure and amount of data with dynamic bayesian network models. Environmental Modelling & Software, 118, pp.281-297.

Kadin, M., Blenckner, T., Casini, M., Gårdmark, A., Torres, M.A. and Otto, S.A., 2019. Trophic interactions, management trade-offs and climate change: the need for adaptive thresholds to operationalize ecosystem indicators. Frontiers in Marine Science.

McQuatters-Gollop, A., Mitchell, I., Vina-Herbon, C., Bedford, J., Addison, P.F., Lynam, C.P., Geetha, P.N., Vermeulan, E.A., Smit, K., Bayley, D.T. and Morris-Webb, E., 2019. From science to evidence–how biodiversity indicators can be used for effective marine conservation policy and management. Frontiers in Marine Science, 6, p.109.

Rickels, W., Weigand, C., Grasse, P., Schmidt, J. and Voss, R., 2019. Does the European Union achieve comprehensive blue growth? Progress of EU coastal states in the Baltic and North Sea, and the Atlantic Ocean against sustainable development goal 14. Marine Policy, 106, p.103515.

Niiranen, S., Orio, A., Bartolino, V., Bergström, U., Kallasvuo, M., Neuenfeldt, S., Ustups, D. and Casini, M., 2019. Predator-prey body size relationships of cod in a low-diversity marine system. Marine Ecology Progress Series, 627, pp.201-206.

Kiljunen, M., Peltonen, H., Lehtiniemi, M., Uusitalo, L., Sinisalo, T., Norkko, J., Kunnasranta, M., Torniainen, J., Rissanen, A.J. and Karjalainen, J., 2020. Benthic‐pelagic coupling and trophic relationships in northern Baltic Sea food webs. Limnology and Oceanography.

Martin, R., Schlüter, M. and Blenckner, T., 2020. The importance of transient social dynamics for restoring ecosystems beyond ecological tipping points. Proceedings of the National Academy of Sciences, 117(5), pp.2717-2722.