A Framework for Simulating Ecosystem Effects in Data-Poor Small-Scale Fisheries Using Science-Based and Local Ecological Knowledge-Based Models

The constant demand for seafood products and the undeniable effects of fishing on marine ecosystems make it urgent to implement an ecosystem approach, even in data-poor scenarios such as small-scale fisheries. Understanding the impacts of fishing is essential for promoting management strategies that prevent irreversible damage to marine ecosystems. Thus, ecosystem quantitative science-based models have been frequently used to evaluate the effects of fishing, although fishers’ local ecological knowledge (LEK) can aid the implementation of qualitative models, particularly in data-poor conditions. Here, we present a framework for simulating and assessing the effects of fishing following two strategies: (1) for both types of models, we simulated species removal scenarios, and (2) for quantitative science-based models, we fitted time series to dynamically assessed impacts. The impacts were analyzed through ecological indicators commonly used for quantitative models, and because these indicators cannot be easily estimated for qualitative models, we propose the use of topological indicators in both types of models. The approach was applied to three case studies of small-scale finfish fisheries in northwestern Mexico. We found that the ecosystem response to species removal was different in each case study and that the target species can play an important role in ecosystems, but their removal does not generate abrupt changes in the ecosystem structure. The quantitative science-based models were able to reproduce the historical catch trends, which allowed us to reveal that changes in ecosystems are indeed influenced by fishing effort but also by underlying primary productivity. Furthermore, topological and ecological indicators showed similar trends in the quantitative models, which suggests that the former could be useful when data-poor conditions allow only qualitative models. This result confirms the relevance of the participation of fishers in generating qualitative models and their decisive role in the discussion of co-management strategies and risk scenarios in a better-informed manner.

A Novel Hybrid Logic-ODE Modeling Approach to Overcome Knowledge Gaps

Mathematical modeling allows using different formalisms to describe, investigate, and understand biological processes. However, despite the advent of high-throughput experimental techniques, quantitative information is still a challenge when looking for data to calibrate model parameters. Furthermore, quantitative formalisms must cope with stiffness and tractability problems, more so if used to describe multicellular systems. On the other hand, qualitative models may lack the proper granularity to describe the underlying kinetic processes. We propose a hybrid modeling approach that integrates ordinary differential equations and logical formalism to describe distinct biological layers and their communication. We focused on a multicellular system as a case study by applying the hybrid formalism to the well-known Delta-Notch signaling pathway. We used a differential equation model to describe the intracellular pathways while the cell–cell interactions were defined by logic rules. The hybrid approach herein employed allows us to combine the pros of different modeling techniques by overcoming the lack of quantitative information with a qualitative description that discretizes activation and inhibition processes, thus avoiding complexity.

Participatory Qualitative Modeling to Assess the Sustainability of a Coastal Socio-Ecological System

Assessing the sustainability of socio-ecological systems requires understanding the interactions between numerous ecological, economic and social components. Models are often used to investigate how interactions shape system feedbacks and drive the complex dynamics at play in such systems. However, building these models is a non-trivial exercise, which often neglects stakeholder knowledge and perceptions. We adopted a participatory approach that relies on conducting workshops to engage stakeholders into the development of qualitative models of system feedback. This type of participatory qualitative modeling is well suited to address the complexity of socio-ecological systems in a holistic manner, identify key stakes and feedbacks, and predict responses to perturbations. We use this approach to investigate the factors that condition sustainability of the socio-ecological system associated with shellfish aquaculture in the Normand-Breton Gulf in France. Six region-specific workshops were organized with shellfish producers, managers and other stakeholders to identify and describe key components, interactions and pressures that contribute to overall socio-ecological dynamics. Differences and commonalities in system perceptions were identified across the different regions and focus groups. We reconciled stakeholder-specific discrepancies in model structure into a synthetic representation that conciliates alternative views of the system. Next, we predicted how the system might respond to alternative scenarios of change. Overall, our participatory qualitative modeling exercise identified key drivers of the system under study that constitute effective management levers to maintain system sustainability. For instance, low social acceptability of the aquaculture industry generally appears to be a major constraint on the sustainability of shellfish aquaculture in the Normand-Breton Gulf, while reducing rearing density appears to be a key driver of sustainability.

Logic-based Robotics

This chapter explores methods for combining symbolic and sub-symbolic reasoning and learning systems to take advantage of the strengths of each approach in challenging tasks in robotics. In perception, Inductive Logic Programming (ILP) can be used to learn descriptions of classes of objects and to find relations between objects. Examples are given of perception for robots in urban search and rescue. We also describe systems for learning plans and behaviours for robots. Relational learning is used to acquire abstract model of robot actions that are then used to constrain sub-symbolic learning for low-level control. Models can be variously expressed in the classical STRIPS representation or as qualitative models. A STRIPS-like model is acquired by a robot that learns to use tools and also designs new tools. A qualitative model is constructed by a robot that learns to traverse uneven terrain in urban search and rescue. The model is refined by reinforcement learning.

Steric effects vs. electron delocalization: a new look into stability of diastereomers, conformers and constitutional Isomers

<div> <p>A quantum chemical investigation of the stability of compounds with identical formulas was carried out on 23 classes of compounds made of C, N, P, O, S atoms as core structures and halogens H, F, Cl, Br, I as substituents. All possible structures were generated and investigated by quantum mechanical methods. The prevalence of a formula in which its <i>Z</i> configuration, <i>gauche</i> conformation or <i>meta</i> isomer is the most stable form is calculated and discussed. Quantitative and qualitative models to explain the stability of 23 classes of halogenated compounds were also proposed.</p></div>

Steric effects vs electron delocalization: a new look into stability of diastereomers, conformers and constitutional Isomers

A quantum chemical investigation of the stability of compounds with identical formulas was carried out on 23 classes of compounds made of C, N, P, O, S atoms as core structures and halogens H, F, Cl, Br, I as substituents. All possible structures were generated and investigated by quantum mechanical methods. The prevalence of formula in which its <i>Z</i> configuration, <i>gauche</i> conformation and meta isomer are the most stable forms is calculated and discussed. Quantitative and qualitative models to explain the stability of the 23 classes of halogenated compounds were also proposed.<br>

Steric effects vs electron delocalization: a new look into stability of diastereomers, conformers and constitutional Isomers

A quantum chemical investigation of the stability of compounds with identical formulas was carried out on 23 classes of compounds made of C, N, P, O, S atoms as core structures and halogens H, F, Cl, Br, I as substituents. All possible structures were generated and investigated by quantum mechanical methods. The prevalence of formula in which its <i>Z</i> configuration, <i>gauche</i> conformation and meta isomer are the most stable forms is calculated and discussed. Quantitative and qualitative models to explain the stability of the 23 classes of halogenated compounds were also proposed.<br>

The study of mixed assets allocation based on Black–Litterman model

With Private Funds having a new type of license for asset allocation practice in China, comprehensive asset allocation cross private equity and stock market has received more attention. However, most of the studies focus more on the stock market, and asset allocation models for private equity market that are mainly made based on experience. Thus, the joint allocation of assets crosses both markets making it a challenging research topic. This paper introduces the Black–Litterman model into the private equity market, realizing the transition from qualitative models to quantitative models. It lays a solid quantitative ground for the mixed asset allocation model in both the markets.

Steric vs Electronic Effects: A New Look into Stability of Diastereomers, Conformers and Constitutional Isomers

A quantum chemical investigation of the stability of compounds with identical formulas was carried out on 23 classes of halogenated compounds made of H, F, Cl, Br, I, C, N, P, O and S atoms. All possible structures were generated by combinatorial approach and studied by statistical methods. The prevalence of formula in which its <i>Z</i> configuration, <i>gauche</i> conformation and meta isomer are the most stable forms is calculated and discussed. Quantitative and qualitative models to explain the stability of the 23 classes of halogenated compounds were also proposed.<br>