Nicola J. Grigg

The nonlocal model of porewater irrigation: Limits to its equivalence with a cylinder diffusion model

Burrows maintained by animals in aquatic sediments ventilate the sediment and can substantially alter the rates and pathways of biologically-mediated decomposition reactions. A well known and effective way of modeling the impact of such bioirrigation in sediment diagenetic models is to assume that solutes diffuse into an annulus of sediment surrounding the burrow; the reaction diffusion equations are represented in cylindrical polar co-ordinates. More commonly, bioirrigation of sediments is represented by one-dimensional “nonlocal” irrigation models. Their use is typically justified by the assertion that a nonlocal model is equivalent to a radially-integrated two-dimensional diffusion model in cylindrical-polar co-ordinates. In this paper we highlight limits to this equivalence, drawing on examples from both single-species and multiple-species reaction diffusion models. A modified derivation of the nonlocal model using a higher order Taylor series approximation was tested but found to provide little improvement over the original model. We suggest some approaches for choosing nonlocal coefficients and identify particular limitations to be alert to when applying the nonlocal model.

Testing the consistency between goals and policies for sustainable development: mental models of how the world works today are inconsistent with mental models of how the world will work in the future

Understanding complex problems such as climate change is difficult for most non‐scientists, with serious implications for decision making and policy support. Scientists generate complex computational models of climate systems to describe and understand those systems and to predict the future states of the systems. Non-scientists generate mental models of climate systems, perhaps with the same aims and perhaps with other aims too. Often, the predictions of computational models and of mental models do not correspond with important implications for human decision making, policy support, and behaviour change. Recent research has suggested non-scientists’ poor appreciation of the simple foundations of system dynamics is at the root of the lack of correspondence between computational and mental models. We report here a study that uses a simple computational model to ‘run’ mental models to assess whether a system will evolve according to our aspirations when considering policy choices. We provide novel evidence of a dual-process model: how we believe the system works today is a function of ideology and worldviews; how we believe the system will look in the future is related to other, more general, expectations about the future. The mismatch between these different aspects of cognition may prevent establishing a coherent link between a mental model’s assumptions and consequences, between the present and the future, thus potentially limiting decision making, policy support, and other behaviour changes.