Predicting Effort and Protected Species Bycatch Under an Effort Limit or Take Caps

Many production processes feature joint production of a desirable output with an undesirable byproduct. Producers and consumers of the desirable output mutually benefit at the expense of non-consumers, who bear external damage costs imposed by production of the undesirable byproduct. A standard approach to regulating such production activities is through the combination of a limit on allowable production effort in conjunction with a cap on the level of the undesirable output. The situation is greatly complicated when the production externality is a random function which depends on the level of production effort. In this case, capping undesirable output induces a random limit on the level of the production effort, assuming further production is prohibited once the undesirable output cap is reached. One situation which fits the above description is that of controlling protected species bycatch in commercial fisheries management. Because protected species are typically rare or endangered, and hence limited in population size and distribution, protected species bycatch is by nature a rare event, subject to random variation over time periods or areas where fishing effort occurs. A standard approach to protected species bycatch mitigation is to employ some combination of effort limit and protected species take caps within a given fishing season, in order to ensure that fishing effort ends before an unacceptably large number of protected species takes has occurred. Given the inherent randomness of protected species bycatch for a given level of fishing effort, a number of questions of interest arise in comparing alternative bycatch management regimes, including: 1. If effort reaches the regulatory limit, what is the likely range of variation in bycatch? 2. What is the likely range of effort under regulation by protected species take caps? 3. What is the effect on the allowable range of effort if take caps are simultaneously implemented for multiple protected species? 4. With multiple take caps and an overall effort limit, what are the probabilities for hitting each of the different possible caps or limit? A probabilistic framework is developed herein to address these and related questions. I use a Poisson distribution to model the probability distribution of bycatch conditional on a given level of effort. A Bayesian framework for deriving predictive distributions of bycatch conditional on fishing effort is used to obtain the stochastic effort limit for a given specified limit and take caps. The methodology is applied to observer data from the Hawaii-based longline fishery for swordfish in order to address the questions posed above.Resource /Energy Economics and Policy,

A Semiparametric Test for Heterogeneous Risk

Risk and Uncertainty,

A Market-Based Approach to Manage Endangered Species Interactions

An economic activity interacts with an endangered species. The activity can be divided into mutually exclusive strata with different levels of interaction. Observing the activity in order to monitor interactions is costly. It may be desirable to manage the activity with a probability model which balances the benefit from the activity against the cost of the interaction with the endangered specie instead. The model gives rise to a permit scheme which fixates the risk of interaction over all strata and which uses the market mechanism to optimally allocate the activity between strata. The model can facilitate uncertainty in interaction rate estimates.Endangered species interactions; permit scheme; probability model

A Poisson Probability Model of Protected Species Take Risk

Resource /Energy Economics and Policy,

A market-based approach to manage endangered species interactions

An economic activity interacts with an endangered species. The activity can be divided into mutually exclusive strata with different levels of interaction. Observing the activity in order to monitor interactions is costly. It may be desirable to manage the activity with a probability model which balances the benefit from the activity against the cost of the interaction with the endangered specie instead. The model gives rise to a permit scheme which fixates the risk of interaction over all strata and which uses the market mechanism to optimally allocate the activity between strata. The model can facilitate uncertainty in interaction rate estimates

Encouraging Creativity and Intellectual Stimulation: An Exercise that Forces Students to Think Outside the Box

This exercise involves a hands-on approach to generating innovation and creativity in the workplace. It is feasible as a follow-up, special-topic activity in intellectual stimulation in full-range or transformational leadership training. Participants are presented with the seemingly impossible task of integrating diverse products or services into a single business plan, forcing them to think outside the box. This exercise features lateral and innovative thinking in a highly interactive session, producing innovative and creative solutions from participants. After successfully completing this exercise, participants will be more confident in their ability to creatively solve many challenges that at first glance seem impossible. The paper provides theoretical background, objectives, complete instructions, processing information, and some suggestions for advancing the concepts

Collateral and Debt Maturity Choice. A Signaling Model

This paper derives optimal loan policies under asymmetric information where banks offer loan contracts of long and short duration, backed or unbacked with collateral. The main novelty of the paper is that it analyzes a setting in which high quality firms use collateral as a complementary device along with debt maturity to signal their superiority. The least-cost signaling equilibrium depends on the relative costs of the signaling devices, the difference in firm quality and the proportion of good firms in the market. Model simulations suggest a non-monotonic relationship between firm quality and debt maturity, in which high quality firms have both long-term secured debt and short-term secured or non-secured debt.

Feeding ecology of broadbill swordfish (Xiphias gladius) in the California current

Funding: Support for our study includes salary funding from the NOAA Fisheries’ Office of Science and Technology and contract funds from the Cooperative Institute for Marine, Earth, and Atmospheric Systems. The National Observer Program within NOAA Fisheries’ Office of Science and Technology carried out sample collection. While the study fits the scope of work under the coauthors’ performance plans, they received no specific funding for this work. The funders had no role in study design, analysis, decision to publish, or preparation of the manuscript. Acknowledgments This work would not have been possible without the assistance and samples provided by the NMFS Southwest Region Fishery Observer Program and the participating drift gillnet fishermen. We thank several assistant volunteers who helped process the stomach samples. Alexandra Stohs provided research assistance. Mark Lowry, Eric Hochberg and John Hyde helped identify some prey specimens. John Field, Chugey Sepulveda and Scott Aalbers offered science feedback. Barbara Muhling helped create the map. Kristen Koch, Annie Yau, Brad Erisman, Heidi Dewar, Stephanie Flores, Crystal Dombrow, Elan Portner and Ruben Bergtraun provided useful comments on the draft. Debra Losey assisted with library research. We also thank Hiroshi Ohizumi and two anonymous reviewers for their careful critiques that helped improve the manuscript.Peer reviewedPublisher PD

Modelling interactions of acid–base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology 155 (2010): 341-349, doi:10.1016/j.cbpa.2009.11.019.Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001 – 0.400 μM), Zn (0.001 – 3.059 μM) or Cu (0.002 – 0.787 μM), either alone or in combination for 1 to 27 days. We measured indicators of acid-base balance (hemolymph pH and total CO2), gas exchange (Po2), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid-base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.This study was supported by NOAA’s Center of Excellence in Oceans and Human Health at HML and the National Science Foundation

Law professors want hearing, vote on Garland

Dear Senator Fischer and Senator Sasse, We write this as citizens, but we all teach at the University of Nebraska College of Law. We hold different political viewpoints and disagree frequentIy with each other on political and legal issues. As law professors, however, we share a deep commitment to the rule of law and an impartial judiciary. We therefore urge you to hold confirmation hearings and a vote on President Obama\u27s Supreme Court nominee, Chief Judge Merrick B. Garland