Bioeconomic modelling

This paper uses a bio-economic model to analyze wildlife conservation in two habitats adjacent to a national park by two types of communities in Zimbabwe. One community is made up of peasant farmers operating under a benefit-sharing scheme such as CAMPFIRE, while the other is made up of commercial farmers practicing game farming in a conservancy. Both communities exploit wildlife by selling hunting licenses to foreign hunters but with different levels of success. The park agency plays a central role by authorizing the harvest quota for each community. We formulate a bio-economic model for the three agents, optimize the market problem for each agent and compare the outcomes with the social planner's solution. Our results show that the level of anti-poaching enforcement by the park agency is suboptimal, while anti-poaching effort exerted by the conservancy community achieves social optimality. CAMPFIRE communities exert more poaching effort than what the social planner would recommend. Our model shows that institutional reforms in benefit-sharing schemes could result in the decisions of CAMPFIRE communities gravitating towards the social optimum.

This study contributes to the quest for sustainable agricultural intensification through the development of a quantitative bio-economic modelling framework that allows assessment of new technology and policy measures in terms of household welfare and sustainability indicators. The main aim of the study is the development of a farm household model to aid policy dialogues. The study consists of three parts. The first part is a general introduction into the context of the research, a justification of the approach and a general description of issues underlying the modelling framework. The second part explains the methodological details of the modelling framework. The third part contains some applications of the approach to specific questions related to agricultural intensification in the Cercle de Koutiala in southern Mali.
The bio-economic model developed in this study combines elements from different existing methodologies into a flexible framework that is able to capture the peculiarities of household agriculture in West Africa. The methodology is sufficiently general to be applied in other settings as well, and contains a number of innovations, viz. a direct utility function, a robust goal weighting procedure and the use of metamodelling to analyse mathematical programming outcomes.


Part 1
Soil degradation is regarded as a serious problem threatening the livelihoods of present and future generations in West Africa. To bring soil degradation to a halt, a combination of appropriate technology and an enabling policy environment is needed (Chapter 1). To assess new technology and policy measures, information from biophysical and socio-economic disciplines are combined into a quantitative framework.
Over the past decade a number of quantitative studies have been conducted that aim at combining biophysical and socio-economic information in such a way that the results are relevant for both social and biophysical sciences. These approaches are termed bio-economic modelling. A review of the methodologies (Chapter 2) reveals that none of them are able to tackle simultaneously the analysis of the causes and effects of soil degradation in combination with household decision making to assess the effects of policy change. The studies do however provide valuable building blocks for the present methodology.
A framework to characterise the bio-economic models according to the spatial and temporal scales assists in finding appropriate methods for different research questions. Two critical issues emerge from the review. The first concerns the choice of objective function in economic models. The second refers to the interface between economic behaviour and biophysical processes.
This critical interface between biophysical processes and economic behaviour is wrought with difficulties due to differences in scientific paradigms (Chapter 3). Biophysical sciences use the concept of efficiency in the analysis of technology options. The concept differs from the way economists use it. As a result there is a disparity between the way biophysical scientists and economists view production and damage functions. Whereas economists tend to use well-behaved continuous Cobb-Douglas production functions, biophysical scientists describe production activities in terms of the outcomes of biophysical processes, which more often than not yield nasty functions. This is due to the synergistic effects of inputs and the interrelations between causes and effects of soil degradation.
The implications for bio-economic modelling are that Leontief production functions best describe the biophysical processes. Biophysical modelling frameworks exist that generate point data for this type of production function. One such framework, the technical coefficient generator (TCG) is used for generating the biophysical information needed in the household model.


Part 2
The household model is based on the standard theoretical model of a farm household (Chapter 4). The theoretical model although developed for econometric estimation is difficult to implement in such a way, due to the existence of failures and imperfections in commodity and input markets, the occurrence of risk, data limitations and the complexities in the production functions. As a result a complex non-separable household model is needed, which in turn cannot be estimated econometrically.
Instead of estimating a full econometric model the present methodology proposes an alternative through the use of mathematical programming models that have been parameterised with partial econometric studies and expert knowledge. The basic structure of this bio-economic model consists of six separate modules.
The production activities module describes the biophysical processes and their interrelationships using information generated by the TCG. Different technological options are defined in terms of input-output combinations for both current agricultural practices and alternative technologies.
The price module includes information on factor and commodity markets. Price bands are used to describe market imperfections and results from the household models in terms of aggregate supply are used to calculate new market-clearing prices.
A separate module describes different household types in terms of their resource endowments, real time preference and savings capacity. The savings capacity is linked to a savings and investment module that describes consumption smoothing and investment behaviour. Investment in soil conservation measures is one way of halting ongoing soil degradation.
The expenditure module warrants separate mention (Chapter 6). The use of non-separable farm household models implies that consumption and production decisions are considered simultaneously. As a result the commonly used profit maximisation objective function cannot be used. Instead a utility function is used that describes household preferences for consumables. The direct utility function is estimated econometrically from a cross-sectional budget survey that is considered the revealed preference generated by an underlying utility function.
The study develops a procedure to derive such a utility function. Because direct measurement of utility is impossible careful procedures are needed to test if the derived function is statistically robust.
Next to consumption households also consider soil degradation in their decision making. The consequence is that multiple objectives have to be considered and a procedure is needed to combine those objectives (Chapter 5). The study presents a methodology for estimating the weights of different household objectives by comparing simulation model results with empirical evidence. To obtain statistically robust results maximum entropy econometrics is used.

Part 3
Application of the modelling framework to the case study area of Cercle de Koutiala in southern Mali is done for specific research questions. The first question concerns the validity of the model itself (Chapter 7). The model generates a base run that is consistent with empirical evidence. Applying sensitivity analysis to key parameters, analysing the near-optimal solution space and by applying the model to a separate data-set tests the robustness of those results. The model turns out to be robust for the most important variables while insight is gained into those areas for which the model does not give adequate answers.
The model is also used to analyse new technology (Chapter 8). New technologies were chosen on biophysical grounds. Using partial budget analysis a first indication of the possibilities of the new technology is obtained. The approach is too partial to capture farm household goals and aspirations nor the resource constraints they face. Bio-economic model results indicate that most of the alternative technologies that seemed promising from a biophysical point of view do not fit well into the production systems of farm households in Cercle de Koutiala. A metamodelling approach is used to analyse the outcomes of the farm household model for a large number of variations in key exogenous parameters, thus obtaining fluid response surfaces.
The model is also used to assess the possibilities of using policy instruments to create an enabling environment to induce farm households to adopt more sustainable technologies (Chapter 9). Two key instruments that figure in the forefront of policy debates in West Africa are analysed, viz. fertiliser price subsidies and infra-structural development resulting in lower transaction costs. Model results analysed in a metamodelling framework indicate that although the direction of the change in both income and soil organic matter balance is as would be expected, viz. simultaneous improvement of household-welfare and agro-ecological sustainability indicators, the magnitude of the improvements is limited. The policy measures in combination with the available new technologies are effective but not efficient.

El cambio climático provocado por las actividades antrópicas desde el periodo preindustrial es una realidad latente que amenaza el equilibrio natural del planeta. El incremento de la temperatura a causa de las emisiones de gases de efecto invernadero está teniendo efectos irreversibles que perjudican a todas las formas de vida. Ante este panorama es necesario plantear nuevas alternativas que sean resilientes ante los efectos del calentamiento global, y la bioeconomía puede ser una estrategia para disminuir la huella de carbono y transitar hacia un modelo de producción sostenible basado en el aprovechamiento de la biodiversidad. La bioeconomía es un término que ha venido desarrollándose con mucha fuerza en la última década, teóricamente se fundamenta en el principio del origen biológico de los procesos económicos gobernados por una ley límite. En un mundo donde los recursos son finitos y están en constante presión debido al crecimiento poblacional y a la creciente demanda de alimentos, es necesario establecer mecanismos que amortigüen las actividades antrópicas. En este proceso, la agroecología juega un rol importante para mejorar el acceso a productos saludables y que mejore la conservación de la biodiversidad. El planteamiento y ejecución de la bioeconomía depende de la visión e intereses que persigue cada país o región. Ecuador debe buscar su propio modelo alejado de las lógicas expansionistas de cultivos energéticos y enfocarse en el desarrollo e innovación aprovechando la riqueza de su biodiversidad.

Traceability of canned abalone is not only being demanded to protect quality and certification of safety,
but also to uncover black market or fraudulent practices, such as canning other gastropods sold as
abalone, ‘abalone style’, or showing an abalone shell picture on the label. A forensic method for genetic
differentiation of three species of abalone from other gastropods was developed with 18S rDNA analysis
by PCR-SSCP. A lysin gene marker was also developed to identify abalone species in Mexico. Both markers
worked correctly in raw, frozen, and canned products. In a forensic analysis, two out of seven canned
brands that claimed to contain abalone contained other gastropods. None of three other brands that
showed the legend ‘Abalone’ or an abalone shell picture contained abalone. The Chilean ‘loco’ Concholepas
concholepas is the most common product used in abalone substitution. The lysine gene was
capable of separating canned abalone based on the species. Both methods proved reliable and useful for
identifying abalone and can be used to certify the authenticity of the Mexican commercial product or
identify commercial fraud. By this genetic approach, the Mexican abalone industry could guarantee
authenticity

The science and management of infectious disease are entering
a new stage. Increasingly public policy to manage epidemics
focuses on motivating people, through social distancing policies,
to alter their behavior to reduce contacts and reduce public disease risk. Person-to-person contacts drive human disease dynamics.
People value such contacts and are willing to accept some disease risk to gain contact-related benefits. The cost–benefit trade-offs that shape contact behavior, and hence the course of epidemics, are often only implicitly incorporated in epidemiologicalmodels. This approach creates difficulty in parsing out the effects of adaptive behavior. We use an epidemiological–economic model of disease dynamics to explicitly model the trade-offs that drive person-toperson
contact decisions. Results indicate that including adaptive
human behavior significantly changes the predicted course of epidemics and that this inclusion has implications for parameter estimation and interpretation and for the development of social distancing policies. Acknowledging adaptive behavior requires a shift in thinking about epidemiological processes and parameters.

A bio-economic model was used to analyse the risks of intensive production of shrimp and to propose alternative schemes of risk management by controlling aeration, pond size, stocking density and duration of cultivation. The model was calibrated from databases of farm operations in the State of Nayarit, Mexico. Improving management allowed us to project an increase in the annual net revenue from $3900 to $26 600 ha À1 and to improve the benefit–cost ratio from 1.14 to 1.55. Managing an early start of aeration, small-sized ponds, high stocking densities and long cultivation periods maximized economic outcomes. Operating a small farm (consisting of a single 2.5 ha pond) involves more risk than operating a large one (50 ha, consisting of 20 ponds of 2.5 ha each). Improving management also resulted in diminished risk, as indicated by increased values of return per unit risk from 0.14 to 0.21 or from 0.42 to 0.51 (depending on farm size). From sensitivity analysis, we concluded that small ponds are recommended for intensive production of Litopenaeus vannamei and that white spot disease is a major risk factor that can be partly controlled by managing dissolved oxygen levels and aeration.

With the overexploitation of many conventional fish stocks, and growing interest in harvesting new kinds of food from the sea, there is an increasing need for managers of fisheries to take account of interactions among species. In this work we define a bioeconomic equilibrium model for 'n' fishermen who catch three species; these species compete with each other for space or food. The natural growth of each species is modeled using a logistic law. The objective of the work is to find the fishing effort that maximizes the profit of each fisherman constrained by the conservation of the biodiversity. The existence of the steady states and its stability are studied using eigenvalue analysis. The problem of determining the equilibrium point that maximizes the profit of each fisherman is then solved by using the generalized Nash equilibrium problem. Finally, some numerical simulations are given to illustrate the results.

Cod and haddock are two of the “big 5” UK supermarket fish species and intrinsic to fish and chip shops nationwide. UK whitefish fleets produce a significant amount, however there is a reliance on imports to maintain supply. The UK is in a strong position to compete for raw material from Iceland and Norway given high prices paid for imports and investment by Icelandic and Norwegian companies in the UK. Regarding UK production of whitefish, the European Common Fisheries Policy landing obligation has introduced significant uncertainty. To avoid discarding of any quota stock, fishing may be stopped before all target stocks quota is reached. For demersal fleets, there is a transition period between 2016 and 18 where target stocks are introduced according to Advisory Council and EU agreement and Article 15, with all quota stocks from 2019. As the capacity of the fleets balance to the new regulations, supply will likely return and if maximum sustainable yield (MSY) is reached in 2020 then an increase in TACs from current levels is likely too. However, markets and industries can change in a short period. Particularly, most processing companies are small to medium size enterprises and those that concentrate on cod and haddock may have to adjust their business. Fleets could be resilient to such short term reductions in landings however this cannot be assumed. The competitiveness of producers will surely be affected in the short to medium term as a result.

Although much effort has been dedicated to the management of the red octopus fishery on the Yucatan Peninsula (Mexico), managers have yet to incorporate economic aspects to ensure sustainable and profitable exploitation of this fishery resource. We developed a bioeconomic model that incorporated the uncertainty for the r and K parameters. We fit 3 models (Schaefer, Fox, and Pella-Tomlinson) to abundance index survey data and used the Akaike information criterion for model selection. The best fit corresponded to the Schaefer model. We built deterministic and stochastic versions of the Gordon-Schaefer model. Economic data (costs and prices) were determined from interviews with fishermen. To estimate the posterior distributions of parameters and indicators, we used Bayesian methods with Markov chain Monte Carlo (MCMC) simulations. The deterministic results suggested that the maximum sustainable income was Mex$851.70 million, with a fishing effort of 3,650 fishing boats, while the maximum sustainable profit was $390.8 million, with a fishing effort of 2,472 fishing boats. The equilibrium point corresponded to an effort of 4,945 fishing boats. Regarding the stochastic model, the MCMC simulation results suggest that the maximum sustainable income distribution was not normal; its average was $856.1 million (SE 1.8) and the most likely value was $849.50 million. The most likely fishing effort at equilibrium was 4,970 fishing boats. Our results suggest the fishery could be operating close to the economic equilibrium point; if this is the case, fishing effort must decrease in order for annual profit to increase. Our approach will help make periodical re-evaluations of the fishery and establish management strategies to ensure the profitable and sustainable exploitation of the red octopus on the Yucatan Peninsula.

This paper uses a bioeconomic model to analyse wildlife conservation in two habitats adjacent to a national park by two types of communities in the context of Southern Africa. One community is made up of peasant farmers operating under a benefit-sharing scheme (CAMPFIRE) while the other is made up of commercial farmers practising game farming in a conservancy (the Save Valley Conservancy). Both communities exploit wildlife by selling hunting licenses to foreign hunters but with different levels of success. The park agency plays a central role by authorizing the harvest quota for each community. We formulate a bioeconomic model for the three agents, optimize the market problem for each agent and compare the outcomes with the social planner’s solution. Our results show that the level of anti-poaching enforcement by the park agency is suboptimal, while anti-poaching effort exerted by the conservancy community achieves social optimality. CAMPFIRE communities exert more poaching effort t...

The science and management of infectious disease are entering a new stage. Increasingly public policy to manage epidemics focuses on motivating people, through social distancing policies, to alter their behavior to reduce contacts and reduce public disease risk. Person-to-person contacts drive human disease dynamics. People value such contacts and are willing to accept some disease risk to gain contact-related benefits. The cost-benefit trade-offs that shape contact behavior, and hence the course of epidemics, are often only implicitly incorporated in epidemiological models. This approach creates difficulty in parsing out the effects of adaptive behavior. We use an epidemiological-economic model of disease dynamics to explicitly model the trade-offs that drive person-to-person contact decisions. Results indicate that including adaptive human behavior significantly changes the predicted course of epidemics and that this inclusion has implications for parameter estimation and interpre...

We used a bio-economic model to analyze the role that alternative seeding-harvesting schedules, temperature, dissolved oxygen, stocking density, and duration of cultivation play in the economic performance of semi-intensive shrimp cultivation in Mexico. The highest production was predicted for