From Data to Decisions: Helping Crop Producers Build Their Actionable Knowledge

Recent advances in distributed information technologies are providing the means to capture and process abundant data, and to reveal associations between variables describing the crop-environment-management interaction. This review describes the determinants and moderating factors influencing how much value a crop producer and his or her advisor can derive from data, and information derived from data. We describe the social, technological, and entrepreneurial processes needed to progress the nonlinear pathway from data to an on-farm decision, and explore the meaning of actionable knowledge; that is, knowledge that can be acted upon and applied to solve a real-world problem. We argue that effective decision support is also a system that supports the learning needs of crop producers and their transactions with trusted advisors. Crop protection, the sub-set of crop management used to mitigate crop loss, is used to illustrate current approaches and technologies to support farmers' decisions. We describe how situational awareness and actionable knowledge could be improved through use of emerging platform technologies, advances in artificial intelligence, consideration of farmer decision style, knowledge capture and maintenance, and embedding technology in human-centered services. Implications for the conduct of research and development are discussed.     

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.     

Uncertainty Analysis in Life Cycle Assessment (LCA): Case Study on Plant-Protection Products and Implications for Decision Making (9 pp + 3 pp)

Goal, Scope, and Background Uncertainty analysis in LCA is important for sound decision support. Nevertheless, the actual influence of uncertainty on decision making in specific LCA case-studies has only been little studied so far. Therefore, we assessed the uncertainty in an LCA comparing two plant-protection products.Methods Uncertainty and variability in LCI flows and characterization factors (CML-baseline method) were expressed as generic uncertainty factors and subsequently propagated into impact scores using Monte-Carlo simulation. Uncertainty in assumptions on production efficiency for chemicals, which is of specific interest for the case study, was depicted by scenarios. Results and Discussion Impact scores concerning acidification, eutrophication, and global warming display relatively small dispersions. Differences in median impact scores of a factor of 1.6 were sufficient in the case study for a significant distinction of the products. Results of toxicity impact-categories show large dispersions due to uncertainty in characterization factors and in the composition of sum parameters. Therefore, none of the two products was found to be significantly environmentally preferable to the other. Considering the case study results and inherent characteristics of the impact categories, a tentative rule of thumb is put forward that quantifies differences in impact scores necessary to obtain significant results in product comparisons.Conclusion Published LCA case-studies may have overestimated the significance of results. It is therefore advisable to routinely carry out quantitative uncertainty analyses in LCA. If this is not feasible, for example due to time restrictions, the rule of thumb proposed here may be helpful to evaluate the significance of results for the impact categories of global warming, acidification, eutrophication, and photooxidant creation.     

Integrating Comparative Risk Assessment with Multi-Criteria Decision Analysis to Manage Contaminated Sediments: An Example for the New York/New Jersey Harbor

Current environmental challenges involve complex assessment and analysis of tradeoffs among differing criteria, expectations, and levels of certainty. Using multi-criteria decision analysis in combination with comparative risk assessment, a systematic and transparent framework can be created to integrate different types and sources of decision-relevant information. Although examples of decision analysis abound in the literature and academic efforts, its use within the practice of risk assessment and environmental management is still being established. This article provides an example of the use of decision analysis study that builds on a previous screening-level, comparative risk assessment of contaminated sediment from the New York/New Jersey harbor area. Using multi-criteria decision analysis, we explored the effect of different criteria weights, utility functions, and cost estimates on the ranking of seven contaminated sediment management alternatives. Values used in weighting decision criteria were surveyed from two interaction sessions with sediment management professionals.     

Multimodal signals enhance decision making in foraging bumble-bees

Multimodal signals are common in nature and have recently attracted considerable attention. Despite this interest, their function is not well understood. We test the hypothesis that multimodal signals improve decision making in receivers by influencing the speed and the accuracy of their decisions. We trained bumble-bees (Bombus impatiens) to discriminate between artificial flowers that differed either in one modality, visual (specifically, shape) or olfactory, or in two modalities, visual plus olfactory. Bees trained on multimodal flowers learned the rewarding flowers faster than those trained on flowers that differed only in the visual modality and, in extinction trials, visited the previously rewarded flowers at a higher rate than bees trained on unimodal flowers. Overall, bees showed a speed-accuracy trade-off; bees that made slower decisions achieved higher accuracy levels. Foraging on multimodal flowers did not affect the slope of the speed-accuracy relationship, but resulted in a higher intercept, indicating that multimodal signals were associated with consistently higher accuracy across range of decision speeds. Our results suggest that bees make more effective decisions when flowers signal in more than one modality, and confirm the importance of studying signal components together rather than separately.     

Visitor management and ecological integrity: one example of an integrated management approach using Decision Analysis

In this paper we argue in favour of using a decision analysis framework for more integrated decision-making when managing protected areas. Such an approach will enable agencies to balance between the frequently conflicting goals of visitor management and ecological integrity. We present a case study from the West Coast Trail in Pacific Rim National Park Reserve, BC, Canada, in which we use a hybrid of ELECTRE and AHP to establish a ranking of several management options. We conclude by suggesting that such a more formal framework constitutes a more objective decision support tool, assists in framing relevant management questions and tradeoffs, and at the same time provides guidance for data collection.     

Effect of acute exposure to a complex fragrance on lexical decision performance

This study tested the effect of acute exposure to a commercialair freshener, derived from fragrant botanical extracts, atan average concentration of 3.16 mg/m³ total volatile organiccompounds on the lexical decision performance of 28 naive participants.Participants attended two 18-min sessions on separate days andwere continuously exposed to the fragrance in either the first(F/NF) or second (NF/F) session. Participants were not instructedabout the fragrance. Exposure to the fragrance did not affecthigh-frequency word recognition. However, there was an orderof administration effect for low-frequency word recognitionaccuracy. When the fragrance was administered first before theno-odor control condition, it did not affect accuracy, but whenit was administered second after the control condition, it significantlydecreased low-frequency word recognition accuracy. Reactiontimes to low-frequency words were significantly slower thanthose for high-frequency words, but no effect of either fragranceor order of administration on reaction times was found. Thepresence of fragrance in the second session apparently servedas a distraction that impaired lexical task performance accuracy.The introduction of fragrances into buildings may not necessarilyfacilitate all aspects of work performance as anticipated.     

Collective behaviors of two-component swarms

We present a particle-based simulation study on two-component swarms where there exist two different types of groups in a swarm. Effects of different parameters between the two groups are studied systematically based on Langevin's equation. It is shown that the mass difference can introduce a protective behavior for the lighter members of the swarm in a vortex state. When the self-propelling strength is allowed to differ between two groups, it is observed that the swarm becomes spatially segregated and finally separated into two components at a certain critical value. We also investigate effects of different preferences for shelters on their collective decision making. In particular, it is found that the probability of selecting a shelter from the other varies sigmoidally as a function of the number ratio. The model is shown to describe the dynamics of the shelter choosing process of the cockroach–robot mixed group satisfactorily. It raises the possibility that the present model can be applied to the problems of pest control and fishing using robots and decoys.