Environmental Risk Management Decision-Making in a Societal Context

Recent studies point to the need for improved understanding of environmental management frameworks designed to combine qualitative public and quantitative technical inputs in decision-making processes. Flux in public perception and concern about risks imply frameworks must be iterative in nature and incorporate a variety of assessment triggers in the form of decision points. A conceptual model is proposed here to explain the de facto operation of standard risk analytic frameworks within the broader sociopolitical milieu of public policy. The model is presented as a decision flow diagram that emphasizes setting environmental management goals based on societal input and the formulation of decision criteria for selecting management actions to achieve those goals. Prospective and retrospective decision control points operate to select management options that, respectively, avoid or reduce actual or predicted effects. Feedback loops that modify risk management outcomes are identified. Technical and scientific inputs (i.e., risk analysis) are assigned an essential information role within the framework and are responsible for informing the management process with the results of appropriately conducted and reviewed investigations. The proposed model is intended primarily to indicate how environmental risk management decision-making and associated technical assessments may be influenced by social pressures. It is hoped this understanding will lead to analytical transparency and better public communication of the environmental implications of policy options.     

A conceptual model of farmers' informational activity: a tool for improved support of livestock farming management

Farmers have been slow to adopt decision support system (DSS) models and their outputs, mainly owing to (i) the complexity of the data involved, which most potential users are unable to collect and process; and (ii) inability to integrate these models into real representations of their informational environments. This situation raises questions about the way farm management researchers have modelled information and information management, and especially about the quality of the information assessed by the farmers. We consider that to review advisory procedures we need to understand how farmers select and use farm management-related information, rather than focusing on decisions made in particular situations. The aim of this study was to build a conceptual model of the farmer-targeted farm management-related information system. This model was developed using data collected in commercial beef cattle farms. The design structure and operational procedures are based on (i) data categories representing the diversity of the informational activity; and (ii) selected criteria for supporting decisions. The model is composed of two subsystems, each composed of two units. First, an organizational subsystem organizes, finalizes and monitors informational activity. Second, a processing subsystem builds and exploits the informational resources. This conceptual model makes it possible to describe and understand the diverse range of farmers' informational activity by taking into account both the flow of information and the way farmers make sense of that information. This model could serve as a component of biodecisional DSS models for assigning information in the decision-making process. The next task will be to take into account the broad range of farmers' perceptions of the management situations in DSS models.     

Fast-starts in hunting fish: decision-making in small networks of identified neurons

Decision-making networks must be tuned according to the rules that govern which action will be rewarded for a given constellation of current sensory information. Somehow these rules must be implemented in the networks that translate the sensory cues to actions but the nature of this representation is enigmatic. Recent findings suggest that Mauthner-associated networks in some fish can govern surprisingly sophisticated and plastic decisions in which the rules of prey motion govern what speed and direction must be selected to be at the right point at the right time. With the key cellular players individually identifiable, fish can help us to discover the nature of how rules are represented in decision-making circuitry of the vertebrate brain.     

Model-based Conservation Decision Aiding in the Presence of Goal Conflicts and Uncertainty

Goal conflicts and uncertainty are two major problems in decision-making for conservation and species protection. Conflicts can often be found between ecological goals on the one hand and socio-economic goals on the other, but also among different ecological goals. They can be formally analysed by methods of multi-criteria analysis. As the solution of a multi-criteria decision problem usually depends on the weights put on the individual criteria (objectives), sensitivity and robustness analyses are necessary to understand the decision problem, concentrate on the essential aspects, and support actual decision processes fully. Uncertainty in the decision problem is often caused by scarcity of information needed to predict the consequences of management actions. The so-called outranking concept proved very useful in the consideration of such uncertainty. Based on a simple fictitious case study the paper demonstrates how multi-criteria decision analysis (in particular the PROMETHEE outranking method) in combination with population model analysis can assist in conservation biological decision-making.     

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation.     

An Italian tomato “Cuore di Bue” case study: challenges and benefits using subcategory assessment method for social life cycle assessment

Purpose

The main purpose of this study is to present an implementation of the subcategory assessment method (SAM) to the life cycle of an Italian variety of tomato called “Cuore di Bue” produced by an Italian cooperative. The case study was used to use the methodology proposed in compliance with the guidelines of social life cycle assessment (S-LCA) in order to highlight issues for the improvement of SAM. A summary of strengths and weaknesses of the methodology as well as the social performance of the considered Italian tomato is an important result of this case study.

Methods

The methodology used is based on SAM. The UNEP/SETAC guidelines of S-LCA and the complementary methodological sheets were used as main references to carry out SAM, and it was used to assess the social performances of Cuore di Bue. The focus was on the assessment of the following three out of five stakeholder groups presented in the guidelines: workers, local community and consumers. Specific questionnaires have been developed to collect the inventory data related to each stakeholder group and along the product life cycle.

Results and discussion

SAM of Cuore di Bue showed a range of values, between 2 and 3 (C-B) for consumer stakeholder group and mainly 3 (B) for the local community and worker stakeholders. Because the best performance (A) is related to a numerical value of 4, better performances were not identified, owing to no propagation of actions in the value chain. The collective bargaining, transparency, feedback mechanism and privacy are the subcategories with the worst performance, but at the same time with more potential for improvements.

Conclusions

The implementation of SAM on Cuore di Bue allowed us to demonstrate how SAM transforms qualitative data into semi-quantitative information through a score scale that can help a decision maker achieve a product overview. SAM has been implemented on Cuore di Bue; the product assessment, the strengths and weaknesses of the methodology are identified and discussed as well. It has been possible to present the best and worst performances in product life cycle, by identifying the phase or the subcategories with good or bad performance. However, in this case study, as the same company owns most of the product life cycle taken into account, the majority of social performances are identical, and this may represent a limit of the methodology or that more organisations along the life cycle must be taken into account (for example, energy, distribution).

     

On the Rationality of Decision-Making Studies: Part 2: Divergent Rationalities

A study of treatment decision making in an Anishinaabe community in Manitoba, Canada was designed to be comparable with an earlier project carried out in a Mexican town. One objective was to compare the resulting decision models. For both communities, a decision-making perspective was compatible with how individuals talked about actions taken in response to illness, and it proved to be a useful means for learning about the process of seeking care. At the same time, a decision-modeling approach is better suited to explaining treatment actions taken in the Mexican community than in the Anishinaabe community. I suggest that this finding reflects the variable potentiality, in the Anishinaabe community, for affliction and its treatment to be constructed within a cultural framework in which the underlying assumptions differ from those implicit in studies of decision modeling, [care seeking, decision models, decision making, Anishinaabe]     

Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making

Collective decision-making is a process whereby the members of a group decide on a course of action by consensus. In this paper, we propose a collective decision-making mechanism for robot swarms deployed in scenarios in which robots can choose between two actions that have the same effects but that have different execution times. The proposed mechanism allows a swarm composed of robots with no explicit knowledge about the difference in execution times between the two actions to choose the one with the shorter execution time. We use an opinion formation model that captures important elements of the scenarios in which the proposed mechanism can be used in order to predict the system??s behavior. The model predicts that when the two actions have different average execution times, the swarm chooses with high probability the action with the shorter average execution time. We validate the model??s predictions through a swarm robotics experiment in which robot teams must choose one of two paths of different length that connect two locations. Thanks to the proposed mechanism, a swarm made of robot teams that do not measure time or distance is able to choose the shorter path.     

A decision-making model based on a spiking neural circuit and synaptic plasticity

To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.     

Regulation of ants' foraging to resource productivity

We investigate the behavioural rule used by ant societies to adjust their foraging response to the honeydew productivity of aphids. When a scout finds a single food source, the decision to lay a recruitment trail is an all-or-none response based on the opportunity for this scout to ingest a desired volume acting as a threshold. Here, we demonstrate, through experimental and theoretical approaches, the generic value of this recruitment rule that remains valid when ants have to forage on multiple small sugar feeders to reach their desired volume. Moreover, our experiments show that when ants decide to recruit nest-mates they lay trail marks of equal intensity, whatever the number of food sources visited. A model based on the 'desired volume' rule of recruitment as well as on experimentally validated parameter values was built to investigate how ant societies adjust their foraging response to the honeydew productivity profile of aphids. Simulations predict that, with such recruiting rules, the percentage of recruiting ants is directly related to the total production of honeydew. Moreover, an optimal number of foragers exists that maximizes the strength of recruitment, this number being linearly related to the total production of honeydew by the aphid colony. The 'desired volume' recruitment rule that should be generic for all ant species is enough to explain how ants optimize trail recruitment and select aphid colonies or other liquid food resources according to their productivity profile.     

Determinants of Unlawful File Sharing: A Scoping Review

We employ a scoping review methodology to consider and assess the existing evidence on the determinants of unlawful file sharing (UFS) transparently and systematically. Based on the evidence, we build a simple conceptual framework to model the psychological decision to engage in UFS, purchase legally or do nothing. We identify social, moral, experiential, technical, legal and financial utility sources of the decision to purchase or to file share. They interact in complex ways. We consider the strength of evidence within these areas and note patterns of results. There is good evidence for influences on UFS within each of the identified determinants, particularly for self-reported measures, with more behavioral research needed. There are also indications that the reasons for UFS differ across media; more studies exploring media other than music are required.     

Controlling flexible manufacturing systems based on a dynamic selection of the appropriate operational criteria and scheduling policy

This study presents the development of a multi-criteria control methodology for flexible manufacturing systems (FMSs). The control methodology is based on a two-tier decision making mechanism. The first tier is designed to select a dominant decision criterion and a relevant scheduling rule set using a rule-based algorithm. In the second tier, using a look-ahead multi-pass simulation, a scheduling rule that best advances the selected criterion is determined. The decision making mechanism was integrated with the shop floor control module that comprises a real-time simulation model at the top control level and RapidCIM methodology at the low equipment control level. A factorial experiment was designed to analyze and evaluate the two-tier decision making mechanism and the effects that the main design parameters have on the system’s performance. Next, the proposed control methodology was compared to a selected group of scheduling rules/policies using DEA. The results demonstrated the superiority of the suggested control methodology as well as its capacity to cope with a fast changing environment.     

Embodied Choice: How Action Influences Perceptual Decision Making

Embodied Choice considers action performance as a proper part of the decision making process rather than merely as a means to report the decision. The central statement of embodied choice is the existence of bidirectional influences between action and decisions. This implies that for a decision expressed by an action, the action dynamics and its constraints (e.g. current trajectory and kinematics) influence the decision making process. Here we use a perceptual decision making task to compare three types of model: a serial decision-then-action model, a parallel decision-and-action model, and an embodied choice model where the action feeds back into the decision making. The embodied model incorporates two key mechanisms that together are lacking in the other models: action preparation and commitment. First, action preparation strategies alleviate delays in enacting a choice but also modify decision termination. Second, action dynamics change the prospects and create a commitment effect to the initially preferred choice. Our results show that these two mechanisms make embodied choice models better suited to combine decision and action appropriately to achieve suitably fast and accurate responses, as usually required in ecologically valid situations. Moreover, embodied choice models with these mechanisms give a better account of trajectory tracking experiments during decision making. In conclusion, the embodied choice framework offers a combined theory of decision and action that gives a clear case that embodied phenomena such as the dynamics of actions can have a causal influence on central cognition.     

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject''s learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.     

Statistical approaches for morphological continuous characters: a conceptual model applied to Phytoseiidae (Acari: Mesostigmata)

Marie‐Stephane, T. (2012). Statistical approaches for morphological continuous characters: a conceptual model applied to Phytoseiidae (Acari: Mesostigmata). —Zoologica Scripta, 42, 327–334. Species discrimination is certainly the most current and essential taxonomic task. Despite molecular development, species continue to be delimited using morphological characters. This study provides statistical approaches to assess decision rules, using continuous morphological characters, to determine whether specimens examined belong or not to a same species. As species discrimination is usually based on no overlapping between intraspecific distributions, a general statistical approach has been developed to assess, for a character x, the relation between intraspecific overlapping and (i) the differences between the means of specimen lots corresponding to two species and (ii) the differences between the values borne by two specimens belonging to two species. Then, this conceptual approach was applied to the predatory mite family Phytoseiidae, highlighting that the minimal difference between means of two specimen lots belonging to two species should be of 10.58 μm (for setae <65 μm) and 33.99 μm (for setae >65 μm). When no specimen sets are available but only two specimens compared, the model shows that a difference of 13.24 μm (for setae <65 μm) and 31.74 μm (for setae >65 μm) would be sufficient to conclude that these specimens belong to two species. The presently proposed decision rules are assumed to improve species discrimination and to limit synonymies. Further developments will consist in applying this approach to databases containing species features in order to automatically extract the putative synonyms. Furthermore, such decision rules would also be useful to determine whether a species newly described is really new for science.     

Wanting,liking and welfare: The role of affective states in proximate control of behaviour in vertebrates

Animals choose a course of action countless times each day. To do so, they need to prioritise their behaviour within a set of alternative actions and decide which of these actions to perform at any one time and for how long, that is, determine when the behaviour has reached its desired effect. This process has classically been called the proximate behavioural control mechanism. Several aspects contribute to this process: internal and external stimuli, the emotions that they elicit, motivation (wants), behavioural goals, valuation, decision‐making and its modulation by mood, and the assessment of behavioural outcomes (liking). I will address all these aspects in the form of an integrated conceptual model. In the process of behavioural control, options need to be valued, and I will refer to evidence showing that an affective hedonic process in respect to (future) reward and punishment heavily affects this value. Moreover, I view motivation, the force that finally drives a specific behavioural output, as being primarily influenced by affective states or even corresponding fully to them. Given the feedback in behavioural control by (dis‐)liking outcomes of behaviour, I reason that in respect to welfare it is more important for animals to reach proximate goals than to avoid negative stimuli. All behavioural choices are modulated, and I show how mood, a long‐term affective state, can cause such modulation. Proximate control of behaviour takes place in the brain, and I will briefly discuss how current and future brain research may elucidate how the brain computes these processes. Furthermore, the inclusion of affective states in the conceptual model raises the question of the subjective experience of animals, and I will address some of the important open questions in this area of research. I will conclude that neural studies cannot currently provide a detailed and general theory on the algorithms of proximate behavioural control. In parallel to further developing these approaches, I propose to strengthen a refined ethological approach with a focus on the states of “wanting” and “liking” in ecologically meaningful circumstances and with a strong ontogenetic (within species) and comparative (between species) component. I consider this ethological approach to be a highly promising step in understanding proximate behavioural control.     

Emergence of adaptive global movement from a subjective inference about local resource distribution

In animal foraging, the optimal search strategy in an unknown environment varies depending on the context, such as the resource density and season. When food is distributed sparsely and uniformly, superdiffusive walks outperform normal-diffusive walks. However, superdiffusive walks are no longer advantageous when random walkers forage in resource-rich environments. It is not currently clear whether a relationship exists between an agent's use of local information to make subjective inferences about global food distribution and the optimal random walk strategy. Therefore, I investigated how flexible exploration is achieved if an agent alters its directional rule based on the local resource distribution. In the proposed model, the agent, a Brownian-like walker, estimates whether an abundant or sparse area is nearby using local resource patterns and then makes a decision by altering its movement rules. I show that the agent can behave like a non-Brownian walker if it interacts with a prey distribution. The agent can adaptively switch between diffusive properties depending on the resource density. This leads to a more effective resource-searching performance than a simple random-walk model. These results demonstrate that optimal searching is a context-dependent process.     

Decision Rules and Group Rationality: Cognitive Gain or Standstill?

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.     

Linking Time-Use Data to Explore Health Outcomes: Choosing to Vaccinate Against Influenza

To inform public health and medical decision makers concerning vaccination interventions, a methodology for merging and analyzing detailed activity data and health outcomes is presented. The objective is to investigate relationships between individual’s activity choices and their decision to receive an influenza vaccination. Data from the Behavioral Risk Factor Surveillance System (BRFSS) are used to predict vaccination rates in the American Time Use Survey (ATUS) data between 2003 and 2013 by using combined socioeconomic and demographic characteristics. The correlations between the extensive (do or not do) and intensive (how much) decisions to perform activities and influenza vaccination are further explored. Significant positive and negative correlations were found between several activities and vaccination. For some activities, the sign of the correlation flips when considering either the intensive or the extensive decision. This flip occurs with highly studied activities, like smoking. Correlations between activities and vaccination can provide an additional metric for targeting those least likely to vaccinate. The methodology outlined in this paper can be replicated to explore correlation among actions and other health outcomes.     

Reaching a Consensus: Terminology and Concepts Used in Coordination and Decision-Making Research

Research on coordination and decision-making in humans and nonhuman primates has increased considerably throughout the last decade. However, terminology has been used inconsistently, hampering the broader integration of results from different studies. In this short article, we provide a glossary containing the central terms of coordination and decision-making research. The glossary is based on previous definitions that have been critically revised and annotated by the participants of the symposium “Where next? Coordination and decision-making in primate groups” at the XXIIIth Congress of the International Primatological Society (IPS) in Kyoto, Japan. We discuss a number of conceptual and methodological issues and highlight consequences for their implementation. In summary, we recommend that future studies on coordination and decision-making in animal groups do not use the terms “combined decision” and “democratic/despotic decision-making.” This will avoid ambiguity as well as anthropocentric connotations. Further, we demonstrate the importance of 1) taxon-specific definitions of coordination parameters (initiation, leadership, followership, termination), 2) differentiation between coordination research on individual-level process and group-level outcome, 3) analyses of collective action processes including initiation and termination, and 4) operationalization of successful group movements in the field to collect meaningful and comparable data across different species.