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Timetable (EBDW01)

Current status and key questions in Landscape Decision making

Wednesday 3rd July 2019 to Friday 5th July 2019

Wednesday 3rd July 2019
09:30 to 18:00 Challenges in Landscape Decision-making
Thursday 4th July 2019
09:00 to 09:30 Paula Harrison ; Peter Cox
Introduction to the Workshop and Programme
Workshop aims:
- Review the state-of-the-art in modelling land systems;
- Identify key knowledge gaps where collaboration between different environmental, mathematical and social science disciplines may lead to new insights, methods and tools.
09:30 to 10:00 Bill Kunin
Scaling populations and communities
Session: Spatial/temporal scaling in landscape modelling
Spatial population and community patterns are bedevilled by issues of spatial (and temporal) scaling.  While it is sometimes convenient to consider local (alpha) and landscape (gamma) scales of abundance or diversity separately, we need to develop approaches that can consider ranges of scales as a continuum.  This talk will focus on the scaling properties of population and community patterns, and on tools to translate information across scales. These may lead to new approaches to measuring, modelling and managing spatial ecological systems.
10:00 to 10:30 Justin Sheffield
Scaling Challenges in Hydrology and Applications to Water Resources and Food Security
Session: Spatial/temporal scaling in landscape modelling
10:30 to 11:00 Morning Coffee
11:00 to 11:30 Panel discussion on “Spatial/temporal scaling in landscape modelling” INI 1
11:30 to 11:50 Henry Wynn
Smart Landscapes
Session: Decision-making in the face of uncertainty
The EU Smart Cities programme and sub programmes such as those on district heating and cooling (DHC), together with technological innovations such as electric cars and pollution free zones present a  vision of the modern city which may or may not be realised. But there are many lessons for similar visions of landscapes. In some sense the technology is the easy part. The real challenge, for modelling, is to integrate the technological, economic, social and environmental. There are matters of ownership, the development of new business models, public-private funding and  scale (national/regional/local). Contracts play a key part and we will advocate, as with cities, model-based contract design, to cope with the tensions between long-term and short-term investment and between CAPEX and OPEX. Some exemplar issues will be mentioned: the economic and social aspects of flooding, the use of wetlands for carbon capture and the citizen as energy prosumer.
11:50 to 12:10 Gavin Stewart
Decision making in the face of uncertainty: improving the evidence base to support landscape decisions
Session: Decision-making in the face of uncertainty
This talk will discuss the need to adopt a decision-theoretic approach to handling uncertainty both to support policy and drive future needs-led research agendas. I argue that the operational steps required to handle uncertainty are generally known, but rarely combined judiciously.  This has deleterious ramifications because uncertainties are not coherently considered in decision-making and are often downplayed in expert led science-policy interactions.
12:10 to 12:30 Martine Barons
Decision-making under uncertainty: Using subjective probabilistic judgements for decision support in pollinator abundance and food security
Session: Decision-making in the face of uncertainty
Hunger and food poverty is on the increase even in developed nations like the UK, USA, Canada & Australia. With a growing population and a finite planet, there is urgent need for action, but in such a large, complex system identifying the most effective action requires decision support.
Food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life.
In order to provide decision support, it is necessary to elicit probability distributions to evaluate subjective expected utility scores associated with ameliorating policies that might be enacted. When the underlying process model is extremely large and complex, this brings its own peculiar challenges. It is first necessary to elicit the overall, agreed structure describing in broad terms the underlying nature of the system from representatives of all domain experts across the system as a whole. We have now shown that this can be done formally and consistently with probability models if the elicitations concern the elicitation of dependences – formally termed irrelevances (Smith, Barons and Leonelli (2016)). Within a probability model, these irrelevance statements then transform into assertions about various conditional independence statements. These, in turn, can be used to determine how the system can be divided up into (conditionally) independent segments. The quantitative expert judgements associated with each segment of the process can then be delegated to a relevant panel of experts. The implicit (albeit virtual) owner of beliefs expressed in the system will be referred to as the supraBayesian , meaning that the decision-making group acts as a single person would and it is her coherence that we are concerned with. Under suitable conditions it can then be shown that the elicited overarching structure can compose these judgments together to form a coherent probabilistic model to score different options available to the user, termed an integrating decisions support system (IDSS).

One element of the overarching food poverty models is food supply, and key to parts of this is an abundant and healthy population of pollinating insects to pollination services for food. In 2014 the UK government undertook a consultation and produced their pollinator strategy for the next 10 years “to see pollinators thrive, providing essential pollination services and benefits for food production, the wider environment and everyone.” However, the evidence base on the complex system driving pollinator vigour and numbers is patchy and held in disparate domains of expertise, making the evaluation of policy options problematic. In this talk I will describe how we are in the process of developing an IDSS based on these theoretical developments, and how a probabilistic model for pollinator abundance incorporating structured expert elicitation will then form a sub-module of this IDSS for policies relating to household food insecurity.

J. Q. Smith, M.J. Barons, and M. Leonelli. Coherent inference for integrating decision support systems. arXiv, 2016.

Co-authors: Jim Q. Smith, Manuele Leonelli
12:30 to 14:00 Lunch at Robinson College
14:00 to 14:30 Panel discussion on “Decision-making in the face of uncertainty” INI 1
14:30 to 15:00 Calum Brown
The need (and opportunity) for improved modelling of land use decision-making
Session: Modelling social/human processes in landscapes
Computational modelling is a key tool in efforts to understand the dynamics of socio-ecological systems. Many models, however, tightly constrain those dynamics by making assumptions about economic equilibrium and optimisation in social systems, and mean-field or trend-based behaviour in ecological systems. Recent research has revealed that, contrary to these assumptions, small-scale behavioural processes shape the dynamics and interactions in socio-ecological systems across scales. Concurrently, data resources and computational tools have advanced to the point that simulation of these processes is increasingly feasible. I will present some recent advances, opportunities and challenges for simulating the role of human behaviour in land use change, building on conceptual and computational examples from both ecology and social science.
15:00 to 15:30 Adam Kleczkowski
Weakest-link control of invasive species: Impacts of memory, bounded rationality and network structure in repeated cooperative games
Session: Modelling social/human processes in landscapes
The nature of dispersal of many invasive pests and pathogens in agricultural and forestry makes it necessary to consider how the actions of one manager affect neighbouring properties. In addition to the direct effects of a potential spread of a pest and the resulting economic loss, there are also indirect consequences that affect whole regions and that require coordinated actions to manage and/or to eradicate it (like movement restrictions). In this talk we address the emergence and stability of cooperation among agents who respond to a threat of an invasive pest or disease. The model, based on the weakest-link paradigm, uses repeated multi-participant coordination games where players’ pay-offs depend on management decisions to prevent the invasion on their own land as well as of their neighbours on a network. We show that for the basic cooperation game agents select the risk-dominant strategy of a Stag hunt game over the pay-off dominant strategy of implementing control measures. However, cooperation can be achieved by the social planner offering a biosecurity payment. The critical level of this payment depends on the details of the decision-making process, with higher trust (based on reputation of other agents reflecting their past performance) allowing significant reduction in necessary payments and slowing down decay in cooperation when the payment is low. We also find that allowing for uncertainty in decision-making process can enhance cooperation for low levels of payments. Finally, we show the importance of industry structure to the emergence of cooperation, with increase in the average coordination number of network nodes leading to increase in the critical biosecurity payment.
15:30 to 16:00 Afternoon Tea
16:00 to 16:30 Panel discussion on “Modelling social/human processes in landscapes” INI 1
16:30 to 16:50 Ian Holman
Model(er) coupling in integrated modelling platforms
Session: Model coupling
There is increasing recognition that simulating the complexity of human-environmental landscapes and associated decision making requires the integration of models or numerical representation of the processes influencing competition for, or access to, space, water etc and their interactions, inter-dependencies and feedbacks. Coupling of pre-existing models is one approach to providing this integration. This presentation will discuss the practical approaches taken to facilitate model coupling in the UK/European scale CLIMSAVE and IMPRESSIONS integrated modelling platforms, and how uncertainty and error propagation were evaluated. It will also consider the importance of modellers as sources of uncertainty within the projections from such coupled modelling systems.
16:50 to 17:10 Mark Rounsevell
Model coupling in land system science
Session: Model coupling
The land system is a complex system. It depends on a miriad of interactions between individual, heterogenous land users, on the variability of the physical environment (soils, climate, …) and on the diversity of societal structures including communities, institutions and public policy organisations. Many modelling approaches have been proposed to represent land systems, with the dominant paradigm based on economic optimisation. However, assuming that individual land managers make decisions about land use based on economic rational alone is a serious simplication of the complex land system. In practice, we know that individuals make land use decisions based on many, often conflicting factors such as risk aversion, social standing, tradition and environmental impact within the context of having imperfect access to knowledge. And that many of these processes play out at different spatial scale levels. In this presentation I will explore how different approaches to modelling land systems can be coupled across scales in order to capture the salient processes at each scale level. This includes modelling of land-based commodity trade-flows at the global scale, sub-national agent-based modelling of land use decision making, and the representation of public policy organisations that influence land users locally.
17:10 to 17:30 Gordon Blair
Middleware to Support Model Coupling in Landscape Decision Making
Session: Model coupling
Middleware is a term that refers to a layer of software that sits on top of an underlying computational infrastructure, providing a programming model to support the development of applications and services, and hiding the complexity of the underlying (inevitably distributed) infrastructure. This has been an area of intense activity both in academia and industry and a number of solutions and associated platforms have been proposed. Middleware has significant advantages in terms of interoperability and reduction in development time through re-use. This talk will pose the question of the role of middleware in supporting integrated environmental modelling, with a particular focus on supporting model coupling. The talk will highlight a significant gap between the functionality of existing middleware standards and platforms and the needs of the environmental sciences community, including in the important and demanding area of landscape decision-making. This is partially down to the focus of middleware on representing the end system behaviour, e.g. in service-oriented architecture, when in fact much of the complexity is in the interconnection or coupling between services. A further key reason is the domain specific requirements of modelling in terms of, for example: i) the need to understand the semantics of environmental concepts; ii) the subsequent need to manage mappings between the outputs of one model and the inputs of another, e.g. using arbitrary transfer functions; iii) the need to support reasoning across scales; iv) the important requirement to understand uncertainty in model chains including the propagation of uncertainty; v) the need to offer potentially sophisticated management of the underlying network/distributed system to deliver the right quality of service in terms of data transfer when dealing with potentially very large data sets. This talk will argue that there is an urgent need for middleware to support integrated environmental modelling, with specific focus on supporting model coupling. Furthermore, the talk will argue that this requires a fundamental rethink of middleware in terms of supporting the domain specific needs of environmental science [1].

[1] Blair, G.S. (2018). Complex distributed systems: The need for fresh perspectives. 38th IEEE International Conference on Distributed Computing Systems (ICDCS), 1410-1421, 10.1109/ICDCS.2018.00142
17:30 to 18:00 Panel discussion on “Model coupling” INI 1
19:30 to 22:00 Formal Dinner at Emmanuel College

Emmanuel College 
St Andrew's St, Cambridge CB2 3AP

Smart casual

Chilled Pea & Broad Bean Soup, Mint Oil  
Main course
Supreme of Guinea Fowl, Herb Gnocchi with Spinach, Wild Mushroom Cream
Brie and Cranberry Tart, Walnut and Rocket Pesto (V)  
Lemon Posset

Friday 5th July 2019
09:00 to 09:30 Recap on the previous day INI 1
09:30 to 10:00 John Dearing
Revealing the complex dynamics of real landscape systems
Session: Non-linearities
This talk examines landscape change from the perspective of complex social-ecological systems evolving through time. Such a perspective can reveal ‘hidden’ complex behaviour that may interact unpredictably with decision-making. These include feedback loops, system instabilities, critical transitions and trade-offs. Knowing the complex behaviours, such as feedback loops, within a system can help decision-makers avoid tipping points and traps in order to keep within ecologically sustainable and socially acceptable limits. There are two parts to the talk. a) Multiple time-series. Here, research analyses multiple time-series of social, economic, ecological, and climate variables covering the past few decades to help elucidate important changes in system interactions. In eastern China, studies at several sites show long term economic growth since 1950 as a trade-off with environmental deterioration, especially water quality. In western China, detailed studies of the lake Erhai lake-catchment system reveal the interactions between agriculture, climate and water management that led to a critical transition in the aquatic ecosystem in 2001. In the UK, a similar approach shows rapid agricultural intensification driving significant environmental degradation in England in the early 1980s, but with a recovery in most ecosystem services after 2000. However, the lack of recovery in farmland biodiversity and the ‘offshoring’ of some impacts represent major negative trade-offs. b) Systems modelling. Here, a case-study describes a systems model designed to guide decision-makers in the setting of ‘safe and just operating spaces’ for sustainable management. Monte Carlo simulations of fish catch from India's Chilika lagoon over the next 40 years are compared to conditions that are ecologically and socio-economically desirable. Akin to a satellite-navigation system, the model identifies multidimensional pathways giving at least a 75% chance of achieving the desirable future.
10:00 to 10:30 Peter Ashwin
Nonlinearities, tipping points and regime shifts
Session: Non-linearities
10:30 to 11:00 Panel discussion on “Non-linearities” INI 1
11:00 to 11:30 Morning Coffee
11:30 to 11:50 Daniel Williamson
Scalable Uncertainty Quantification for calibrating spatio-temporal models
Session: Benchmarking and calibration of landscape models, including model emulation and uncertainty assessment
I'll present work on emulating and calibrating the spatial fields output by climate models in the hope that participants who run or develop land models see natural crossovers and uses for our technology in quantifying uncertainty to support decision makers.
11:50 to 12:10 Chris Dent
Recent scoping studies in evidence based decision making against complex backgrounds
Session: Benchmarking and calibration of landscape models, including model emulation and uncertainty assessment
This talk will discuss research needs in evidence based decision making, based on scoping studies for the Centre for Digital Built Britain and the Supergen Hubnet project, the current Alan Turing Institute "Managing Uncertainty in Government Modelling" and "Use of Multiple Models Within and Organisation" project, and the presenter's own experience. This will be synthesised into suggestions of key topics for discussion during the subsequent four weeks of the Programme.
12:10 to 12:30 Ben Marchant
Issues of scale and uncertainty in landscape scale data products
Session: Benchmarking and calibration of landscape models, including model emulation and uncertainty assessment
Policy-makers often exploit gridded data products when making land-use decisions. These products provide information about the spatial variation of many factors associated with geology, natural resources, soil health, climate, topography and the potential occurrence of natural hazards. These products might be integrated within mathematical, statistical or machine learning models to answer specific questions regarding the need to protect the land because of its value for productive agriculture or mineral exploitation, the potential hazards associated with developing the land and the suitability of sites for particular types of infrastructure. The British Geological Survey produces many two- and three-dimensional data products (see We also integrate these products in decision support tools addressing many land-use questions such as the suitability of land for sustainable drainage schemes, the need for remediation of brownfield sites, the suitability of land for renewable energy production and queries regarding the cost and environmental impacts of major infrastructure projects. I will describe examples of such decision support tools particularly focusing on the issues of uncertainty in the products used to create them, the propagation of this uncertainty upon integration of these products and the potential for a mismatch of scales between the different products and the policy question being addressed. I will discuss strategies to address these issues and the information and metadata that must be provided with data products to facilitate such strategies.
12:30 to 13:00 Panel discussion on “Benchmarking, calibration and uncertainty" INI 1
13:00 to 14:00 Lunch at Robinson College
14:00 to 15:30 Closing Panel Discussion (tbc) INI 1
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons