The second substantive chapter explores the conservation potential of a whale permit market under bounded economic uncertainty. Pro- and anti-whaling stakeholders are concerned about a recently proposed, "cap and trade" system for managing the global harvest of whales. Supporters argue that such an approach represents a novel solution to the current gridlock in international whale management. In addition to ethical objections, opponents worry that uncertainty about demand for whale-based products and the environmental benefits of conservation may make it difficult to predict the outcome of a whale share market. In this study, I use population and economic data for minke whales to examine the potential ecological consequences of the establishment of a whale permit market in Norway under bounded but significant economic uncertainty. A bioeconomic model is developed to evaluate the influence of economic uncertainties associated with pro- and anti- whaling demands on long-run steady state whale population size, harvest, and potential allocation. The results indicate that these economic uncertainties, in particular on the conservation demand side, play an important role in determining the steady state ecological outcome of a whale share market. A key finding is that while a whale share market has the potential to yield a wide range of allocations between conservation and whaling interests - outcomes in which conservationists effectively "buy out" the whaling industry seem most likely.
The third substantive chapter examines the sea lice externality between farmed fisheries and wild fisheries. A central issue in the debate over the effect of fish farming on the wild fisheries is the nature of sea lice population dynamics and the wild juvenile mortality rate induced by sea lice infection. This study develops a bioeconomic model that integrates sea lice population dynamics, fish population dynamics, aquaculture and wild capture salmon fisheries in an optimal control framework. It provides a tool to investigate sea lice control policy from the standpoint both of private aquaculture producers and wild fishery managers by considering the sea lice infection externality between farmed and wild fisheries. Numerical results suggest that the state trajectory paths may be quite different under different management regimes, but approach the same steady state. Although the difference in economic benefits is not significant in the particular case considered due to the low value of the wild fishery, I investigate the possibility of levying a tax on aquaculture production for correcting the sea lice externality generated by fish farms.
The Yongding Corridor is meeting the final ecosystem service levels for landscape aesthetics, but the new ecosystems are falling short on meeting final ecosystem service levels for water storage, local climate regulation, water purification, and dust control. I used biophysical models (process-based and empirically-based), field data (biophysical and visitor surveys), and government datasets to create ecological production functions (i.e., regression models). I used the ecological production functions to evaluate how marginal changes in the ecosystems could impact final ecosystem service outcomes. I evaluate potential tradeoffs considering stakeholder needs to recommend synergistic actions for addressing priorities while reducing service shortfalls.
We formulate an in silico model of pathogen avoidance mechanism and investigate its impact on defensive behavioural measures (e.g., spontaneous social exclusions and distancing, crowd avoidance and voluntary vaccination adaptation). In particular, we use SIR(B)S (e.g., susceptible-infected-recovered with additional behavioural component) model to investigate the impact of homo-psychologicus aspects of epidemics. We focus on reactionary behavioural changes, which apply to both social distancing and voluntary vaccination participations. Our analyses reveal complex relationships between spontaneous and uncoordinated behavioural changes, the emergence of its contagion properties, and mitigation of infectious diseases. We find that the presence of effective behavioural changes can impede the persistence of disease. Furthermore, it was found that under perfect effective behavioural change, there are three regions in the response factor (e.g., imitation and/or reactionary) and behavioural scale factor (e.g., global/local) factors ρ–α behavioural space. Mainly, (1) disease is always endemic even in the presence of behavioural change, (2) behavioural-prevalence plasticity is observed and disease can sometimes be eradication, and (3) elimination of endemic disease under permanence of permanent behavioural change is achieved. These results suggest that preventive behavioural changes (e.g., non-pharmaceutical prophylactic measures, social distancing and exclusion, crowd avoidance) are influenced by individual differences in perception of risks and are a salient feature of epidemics. Additionally, these findings indicates that care needs to be taken when considering the effect of adaptive behavioural change in predicting the course of epidemics, and as well as the interpretation and development of the public health measures that account for spontaneous behavioural changes.
Tree-like structures are ubiquitous in nature. In particular, neuronal axons and dendrites have tree-like geometries that mediate electrical signaling within and between cells. Electrical activity in neuronal trees is typically modeled using coupled cable equations on multi-compartment representations, where each compartment represents a small segment of the neuronal membrane. The geometry of each compartment is usually defined as a cylinder or, at best, a surface of revolution based on a linear approximation of the radial change in the neurite. The resulting geometry of the model neuron is coarse, with non-smooth or even discontinuous jumps at the boundaries between compartments. We propose a hyperbolic approximation to model the geometry of neurite compartments, a branched, multi-compartment extension, and a simple graphical approach to calculate steady-state solutions of an associated system of coupled cable equations. A simple case of transient solutions is also briefly discussed.
Antiviral resistance in influenza is rampant and has the possibility of causing major morbidity and mortality. Previous models have identified treatment regimes to minimize total infections and keep resistance low. However, the bulk of these studies have ignored stochasticity and heterogeneous contact structures. Here we develop a network model of influenza transmission with treatment and resistance, and present both standard mean-field approximations as well as simulated dynamics. We find differences in the final epidemic sizes for identical transmission parameters (bistability) leading to different optimal treatment timing depending on the number initially infected. We also find, contrary to previous results, that treatment targeted by number of contacts per individual (node degree) gives rise to more resistance at lower levels of treatment than non-targeted treatment. Finally we highlight important differences between the two methods of analysis (mean-field versus stochastic simulations), and show where traditional mean-field approximations fail. Our results have important implications not only for the timing and distribution of influenza chemotherapy, but also for mathematical epidemiological modeling in general. Antiviral resistance in influenza may carry large consequences for pandemic mitigation efforts, and models ignoring contact heterogeneity and stochasticity may provide misleading policy recommendations.
Octopamine (OA) underlies reinforcement during appetitive conditioning in the honey bee and fruit fly, acting via different subtypes of receptors. Recently, antibodies raised against a peptide sequence of one honey bee OA receptor, AmOA1, were used to study the distribution of these receptors in the honey bee brain (Sinakevitch et al., 2011). These antibodies also recognize an isoform of the AmOA1 ortholog in the fruit fly (OAMB, mushroom body OA receptor). Here we describe in detail the distribution of AmOA1 receptors in different types of neurons in the honey bee and fruit fly antennal lobes. We integrate this information into a detailed anatomical analysis of olfactory receptor neurons (ORNs), uni- and multi-glomerular projection neurons (uPNs, and mPNs) and local interneurons (LNs) in glomeruli of the antennal lobe. These neurons were revealed by dye injection into the antennal nerve, antennal lobe, medial and lateral antenno-protocerbral tracts (m-APT and l-APT), and lateral protocerebral lobe (LPL) by use of labeled cell lines in the fruit fly or by staining with anti-GABA. We found that ORN receptor terminals and uPNs largely do not show immunostaining for AmOA1. About seventeen GABAergic mPNs leave the antennal lobe through the ml-APT and branch into the LPL. Many, but not all, mPNs show staining for AmOA1. AmOA1 receptors are also in glomeruli on GABAergic processes associated with LNs. The data suggest that in both species one important action of OA in the antennal lobe involves modulation of different types of inhibitory neurons via AmOA1 receptors. We integrated this new information into a model of circuitry within glomeruli of the antennal lobes of these species.