Sources of confidence in value-based choice

Confidence, the subjective estimate of decision quality, is a cognitive process necessary for learning from mistakes and guiding future actions. The origins of confidence judgments resulting from economic decisions remain unclear. We devise a task and computational framework that allowed us to formally tease apart the impact of various sources of confidence in value-based decisions, such as uncertainty emerging from encoding and decoding operations, as well as the interplay between gaze-shift dynamics and attentional effort. In line with canonical decision theories, trial-to-trial fluctuations in the precision of value encoding impact economic choice consistency. However, this uncertainty has no influence on confidence reports. Instead, confidence is associated with endogenous attentional effort towards choice alternatives and down-stream noise in the comparison process. These findings provide an explanation for confidence (miss)attributions in value-guided behaviour, suggesting mechanistic influences of endogenous attentional states for guiding decisions and metacognitive awareness of choice certainty.

Synthesising the multiple impacts of climatic variability on community responses to climate change

Recent developments in understanding and predicting species responses to climate change have emphasised the importance of both environmental variability and consideration of the wider biotic community. To date, the interaction between the two has received less attention. However, considerable bodies of theory and empirical results suggest that multi-species consequences of variability can have strong impacts on range limits and the speed of range shifts. Here we demonstrate how biotic interactions and temporal variability can act together to influence range shift dynamics and highlight the need to understand these interactions in order to predict how species will respond to global change. We emphasise the value and utility of partitioning approaches applied to parameterised models to determine the direction and relative importance and direct of these forces in empirical systems.AuthorshipJCDT wrote the manuscript and built the models. All authors contributed significantly to the editing and manuscript development.FundingThe work was supported by NERC grant NE/T003510/1Data Sharing and Data AccessibilityCode to generate all results is publicly available at https://github.com/jcdterry/ClimateVar_BioticInts and should the manuscript be accepted will be permanently archived. The paper contains no new datasets.

#Brexit: Leave or remain? the role of user’s community and diachronic evolution on stance detection

Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users’ opinion. Furthermore, stance should be studied in a diachronic perspective, since it could help to shed light on users’ opinion shift dynamics that can be recorded during the debate. We analyzed the political discussion in UK about the BREXIT referendum on Twitter, proposing a novel approach and annotation schema for stance detection, with the main aim of investigating the role of features related to social network community and diachronic stance evolution. Classification experiments show that such features provide very useful clues for detecting stance.

Dynamics and topological entropy of 1D Greenberg–Hastings cellular automata

In this paper we analyse the non-wandering set of one-dimensional Greenberg–Hastings cellular automaton models for excitable media with $e\geqslant 1$ excited and $r\geqslant 1$ refractory states and determine its (strictly positive) topological entropy. We show that it results from a Devaney chaotic closed invariant subset of the non-wandering set that consists of colliding and annihilating travelling waves, which is conjugate to a skew-product dynamical system of coupled shift dynamics. Moreover, we determine the remaining part of the non-wandering set explicitly as a Markov system with strictly less topological entropy that also scales differently for large $e,r$ .

Bridging theories for ecosystem stability through structural sensitivity analysis of ecological models in equilibrium

Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from a different angle. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitive analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into linear ones, while maintaining the equilibrium biomass densities and flux of matter, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the linearized versions, even though they describe the same biomass values and material flows. We use these findings to discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.

A palaeolimnological perspective to understand regime-shift dynamics in two Yangtze-basin lakes

Natural and human disturbances have caused widespread regime shifts in shallow lakes of the lower Yangtze basin (LYB, China) resulting in a severe decline of ecosystem services. Improved understanding of the relationship between environmental forcing and ecosystem response, and the mechanisms behind regime shifts has significant implications for management. However, the patterns of these regime shifts and the underlying internal mechanisms are less known. In this study, two typical lakes (Chaohu and Zhangdu) from the LYB were selected to determine the trajectories of ecological regime shifts, both of which transitioned from vegetation- to plankton-dominated states several decades ago. Ecological trajectories since the 1900s in both lakes were reconstructed using palaeolimnological proxies, mainly diatom assemblages. Although results show that regime shifts occurred in both lakes in the 1970s and the 1950s, respectively, their inherent mechanisms were different. In Lake Zhangdu, altered hydrological conditions pushed the ecosystem across an ecological threshold, providing an example of a driver-mediated regime shift. In Lake Chaohu, ongoing nutrient loading influenced ecosystem processes and drove the lake to an alternative stable state, potentially presenting an example of a critical transition after a loss of resilience. This research indicates that palaeolimnological perspectives can provide insights into regime shift changes, as well as important information regarding which restoration methods should be tailored to individual lakes.