1. Key Evidence Needed for Informed Policy Formulation Understanding the relationship between biodiversity and ecosystem services Assessing the response of habitats and biodiversity to the indirect and direct drivers of change, e.g., response to climate change and other stressors Linking changes in habitat condition and biodiversity to ecosystem services and then to human well-being Quantifying changes in ecosystem services in order to assess changes in value (economic and social) Assessing how to get the economics right, e.g., elimination of subsidies and payment for ecosystem services Assessing how to appropriate the true economic value (market and non-market) of an ecosystem services to the local land owner A set of plausible futures (using an internally consistent set of direct and indirect drivers) using ecological process models to assess the response, spatially and temporally Evaluating the effectiveness of response options (policies, technologies, practices and behaviour change) for different decision-makers – what is endogenous to a decision-maker and what is exogenous at different spatial scales

2. Group 1: Key questions What are the key questions? Do we need ecology to answer them (or are they social or political)? Do we need systems ecology to answer them?

3. Environment Ecosystems including people Ecosystem, goods, values, benefits Important interactions across boundaries Most env changes are mediated through ecosystems Can only get right answer through understanding whole system Make it matter to people – society + policy makers – testing policy ideas Thresholds/sudden changes/non-linearities Emergent properties heterogeneities

4. Group 2: Defining Systems Ecology What is systems ecology? What bits of ecology are useful? Why is systems ecology useful – Promoting understanding – Understanding uncertainty – Understanding indirect effects – Crossing scales (levels, time, space)

5. Defining systems ecology Systems ecology has a history – Odum, watt – Levins criticism Systems ecology 2.0 could/should be different – Process-based....emergent properties – Mulit-scale – Intelligently selective about which components to include – Focussed on prediction – Studies set within a wider/global context Why now? – Better tools Computing power Data Rigour Societal demand – Development of sub-disciplines Behavioural ecology, life-history theory Individual-based models Modern systems ecology is already happening – Resiliance alliance – Stockholm – End-to-end modelling in marine systems

6. Defining systems ecology Definition – ‘the integrated analysis of interactions and feedbacks across different levels of biological and ecological organisation and scale and their relationships with their abiotic and biotic environments, to understand and predict system properties’ Needs – Holism-reductionism-induction-deduction – Inherit insights from key disciplines – A coherent framework for setting work in context – Doesn’t exclude humans Useful for – Branding – Development of tools and methods – Identification as a socio-economic phenomenon

7. Gp 3: Developing systems ecology To what extent can we learn from similar exercises? Should we be afraid of process or data uncertainty? How much can we learn from different sub-disciplines or biomes? What disciplines are needed? – Communication – Science Achievement: maths, computer, “wet” What are the incentives? How do we build a community?

8. Developing systems ecology Learning from other disciplines – From systems biology and climate modelling (maybe DGVMs) – Can learn from organisation Distributed methods versus concentration in single location What type of funding mechanism worked Came together around a big question Balance between dry and wet scientists Systems biology have trained a new set of theoreticians/modellers

9. Developing systems ecology Incentives and barriers – Barriers Resistance to addressing the complexity of systems (but not in the marine world where necessity to work together on ships) Cultural change is needed as ecologists work on small issues and slam each others grants Need a big question to coalesce around – Incentives We can use systems ecology to solve the big question(s) Access to grant funding Community and individual benefits from data/model sharing More and higher profile papers Should we be afraid of uncertainty – NO! – Systems ecology framework needs uncertainty at its heart – Systems ecology should seek to formalize treatment of uncertainty both in terms of scientific treatment and its communication – Interesting theory to be developed here – need to engage with statistics and AI community (something systems biology has not yet done well)

10. Gp 4: Mechanics Data and model sharing – Standards – Culture Understanding and communicating uncertainty Developing tools and transferring them from other disciplines Need for training?

11. Mechanics Language standards needed for – Data and uncertainty – Models (algorithms and concepts) – Note this has been done elsewhere Systems ecology should sort out what is useful/needed Studies translating existing methods into language ecologists understand Standards aided by common big umbrella question over sub-research efforts Train new ecologists in the cycle – Especially the importance of prediction Prediction Hypothesis Test/ analyse/refine Global ecosystem change Terrestrial Marine Natural Agri-environment Coastal Open Ocean