Bio-economic Modelling Approach Research Articles

Estimating the cost of young stock mortality in livestock systems-An application to sheep farming in Ethiopia.

In sub-Saharan Africa, pre-weaning young stock mortality (YSM) is in the order of 20 to 30% across most livestock species and production systems. High YSM has significant economic implications for livestock keepers, but few studies provide estimates of the "cost of YSM." This study explores a bio-economic herd modeling approach to estimate the "cost of YSM" at farming/livestock system level. The static zero-growth version of DYNMOD was used to calculate the annual physical and monetary output of a sheep flock consisting of 100 breeding females at different levels of lamb mortality. Production parameter values and prices were taken from recently published research. Calculations were carried out for values of lamb mortality decreasing from 30% to 0% in 5% intervals, with 20% representing the "baseline" YSM. Calculations were repeated for a "high" fertility scenario (100% vs. 59% parturition rate) to gauge the sensitivity of the cost of YSM to another parameter determining flock productivity. The relation of revenue per head and YSM is close to linear over the range of analyzed YSM with 1% decrease in YSM resulting in an increase in revenue per animal of approximately 1%. At the higher fertility rate, the absolute cost of YSM to sheep farmers is higher while the relative increase in revenue per animal resulting from YSM reduction is lower. The estimated difference in revenue of the 100-ewe flock between the 20% and 0% lamb mortality scenarios (at baseline fertility) amounts to approximately USD 90 per additionally surviving lamb, which is far above its market value. Reduced lamb mortality ultimately impacts flock revenue through increased sales of "mature" animals, which embody the value of a lamb plus the revenue/profit from raising it to marketable age/weight. The modeling results suggest that foregone profit is an important component of the systemic "cost of YSM." Consequently, expected profit per animal, in addition to its current market value, is essential for estimating the absolute cost of YSM at farming system level.

FARManalytics – A bio-economic model to optimize the economic value of sustainable soil management on arable farms

Soil quality is an important determinant of agricultural productivity and environmental quality. Despite its importance, few economic models incorporate sustainable soil management. The objective of this study is to develop and illustrate FARManalytics: a bio-economic model to gain quantitative insight in the economic value of sustainable soil management. First, we defined a comprehensive set of chemical, physical and biological soil quality indicators and quantitative rules on how these indicators respond to farmers’ production management over time. Second, we introduce an economic calculation framework that enables accurate calculation of the contribution of different production management decisions towards farm income using Activity-Based-Costing. The set of soil quality indicators and economic calculations serve as the basis for the bio-economic model FARManalytics, which consists of two modules: (1) the PMcalculator, a module that calculates the impact of current production management on soil quality and farm economics and (2) the PMoptimizer, a module that uses Mixed-Integer-Linear-Programming to maximize farm incomewithin predefined soil quality indicator constraints. The decision variables are the crop rotation, cover crops, manure & fertilizer application and crop residue management. We illustrate the added value of the model by applying it to an extensive and intensive farm type, both on clay and sandy soil. These farm types are derived from the Farm Accountancy Data Network (FADN) in the Netherlands. FARManalytics demonstrates that it is possible to increase farm income with up to €940 ha−1 year−1 on clay soil and up to €683 ha−1 year−1 on sandy soil, while meeting all soil quality targets except subsoil compaction vulnerability. The latter was among the most limiting soil quality indicators for the farm types in this study, together with soil organic matter input, wind erosion vulnerability and plant-parasitic nematodes. FARManalytics integrates the impact of production management decisions on soil quality and economics at farm level. Combined with representative farm types, the bio-economic modeling approach of FARManalytics can provide useful information for policy support. FARManalytics can also be tailored to provide decision support for individual farms, based on data that is commonly available on arable farms at low cost.

Assessment by bioeconomic modeling water price scenarios of the resilience of agricultural production systems in a semi-arid region: Case of Baalbeck El Hermel – Lebanon

Baalbeck El Hermel Governorate, particularly the semi-arid region is increasingly threatened by climate change. These disturbances, more specifically, concerning the limit in water resources generate problems for the agricultural systems constituting the principle source of families’ subsistence in this zone. This study was established to evaluate, via a bioeconomic modeling approach, the resilience of agricultural systems in Baalbeck El Hermel and perceive their adaptation techniques under conditions of water scarcity. In this context, we have selected three typical farms representative of the driest northern zone receiving the least precipitation.
 Several behaviors and levels of resilience of these farms were showed after analysis of the results: 1) farms specializing in market gardening or perennial crops are very sensitive to drought conditions and are not resilient in the face of water limit conditions; 2) the diversified farm with olive tree dominance is less sensitive and more resilient. The analysis of the water pricing scenario showed an improvement in water management but a limit in the adaptive capacity of farmers, hence the necessity to adapt resilience-building strategies for the targeted zone.

Economically optimised target state of uneven-aged forest management for main forest types in Slovakia

Abstract The study presented a bioeconomic modelling approach for an uneven-aged mixed forest management planning. Regression models for transition (increment), and ingrowth (regeneration) used the National Forest Inventory (NFI) of Slovakia and regional inventory data. Mortality was based on salvage logging records. Models were specific for five tree species within three forest types (FT) (oak with hornbeam and beech, beech, mixed fir-beech-spruce). Net timber prices were calculated with regard to stem quality. Tree growth depended on crown characteristics. The regression models were adjusted to three main geobiotope (GBT) sites per FT. Forest growth was simulated with the density-dependent stand-level matrix transition model. Financial optimisation of harvest was sensitive to an interest rate. Long-time optimisation stabilised in a steady state equilibrium characterised by a stable diameter distribution. Target diameters were specific for site and tree species, and were highest for fir, a dense crown, a good stem quality, and a lower interest rate. Standing timber volume varied from 150 m3 ha–1 (oak forests, 2% interest rate) to 400 m3 ha–1 (beech and fir-beech-spruce forests, 0.5% interest rate). Harvested volume varied from 38 to 93 m3 ha–1 per 10 years, stand basal area (ba) varied from 19 to 36 m2 ha–1 depending on the site, timber price, and interest rate. The discussion pointed out that the relative low volume of the oak FT resulted from the light-demanding characteristics of oak. The mean of oak mosaic structures was lower compared to the high level of more storeys present in the single tree selection structures in beech and mixed fir-beech-spruce forests.

Cost of lameness in dairy herds: An integrated bioeconomic modeling approach

Foot disorders are costly health disorders in dairy farms, and their prevalence is related to several factors such as breed, nutrition, and farmer's management strategy. Very few modeling approaches have considered the dynamics of foot disorders and their interaction with farm management strategies within a holistic farm simulation model. The aim of this study was to estimate the cost of foot disorders in dairy herds by simulating strategies for managing lameness. A dynamic and stochastic simulation model (DairyHealthSim) was used to simulate the herd dynamics, reproduction management, and health events. A specific module was built for lameness and related herd-level management strategies. Foot disorder occurrences were simulated with a base risk for each etiology [digital dermatitis (DD), interdigital dermatitis, interdigital phlegmon, sole ulcer (SU), white line disease (WLD)]. Two state machines were implemented in the model: the first was related to the disease-induced lameness score (from 1 to 5), and the second concerned DD-state transitions. A total of 880 simulations were run to represent the combination of the following 5 scenarios: (1) housing (concrete vs. textured), (2) hygiene (2 different scraping frequencies), (3) the existence of preventive trimming, (4) different thresholds of DD prevalence detected and from which a collective footbath is applied to treat DD, and (5) farmer's ability to detect lameness (detection rate). Housing, hygiene, and trimming scenarios were associated with risk factors applied for each foot disorder etiologies. The footbath and lameness detection scenarios both determined the treatment setup and the policy of herd observance. The economic evaluation outcome was the gross margin per year. A linear regression model was run to estimate the cost per lame cow (lameness score ≥3), per case of DD and per week of a cow's medium lameness duration. The bioeconomic model reproduced a lameness prevalence varying from 26 to 98% depending on the management scenario, demonstrating a high capacity of the model to represent the diversity of the field situations. Digital dermatitis represented half of the total lameness cases, followed by interdigital dermatitis (28%), SU (19%), WLD (13%), and interdigital phlegmon (4%). The housing scenarios dramatically influenced the prevalence of SU and WLD, whereas scraping frequency and threshold for footbath application mainly determined the presence of DD. Interestingly, the results showed that preventive trimming allowed a better reduction in lameness prevalence than spending time on early detection. Scraping frequency was highly associated with DD occurrence, especially with a textured floor. The regression showed that costs were homogeneous (i.e., did not change with lameness prevalence; marginal cost equals average cost). A lame cow and a DD-affected cow cost €307.50 ± 8.40 (SD) and €391.80 ± 10.0 per year on average, respectively. The results also showed a cost of €12.10 ± 0.36 per week-cow lameness. The present estimation is the first to account for interactions between etiologies and for the complex DD dynamics with all the M-stage transitions, bringing a high level of accuracy to the results.

Economic feasibility of glasshouse tomato production in China — A bio-economic stochastic modelling approach

Economic feasibility of glasshouse tomato production in China — A bio-economic stochastic modelling approach

Application of a multi-species bio-economic modelling approach to explore fishing traits within eligible cetacean conservation areas in the Northern Ionian Sea (Central Mediterranean Sea)

The assessment of the spatial overlap between eligible cetacean conservation areas (CCAs) and fishing grounds could be a strategic element in the implementation of effective conservation measures in the pelagic offshore areas. A multi-species bio-economic modelling approach has been applied to estimate the fishing traits in eligible CCAs in the Northern Ionian Sea (NIS, Central Mediterranean Sea) between 10-800 m of depth, adopting the Spatial MAnagement of demersal Resources for Trawl fisheries model (SMART). Four possible CCAs were defined according to the distribution of cetacean species, their bio-ecological needs, as well as socio-economic needs of human activities, identifying a Blue, Red, Orange and Green CCAs in the NIS. SMART spatial domain was a grid with 500 square cells (15×15 NM). The analysis was conducted for the period 2016-2019, considering the Otter Trawl Bottom (OTB) fleet activities in the study areas through the Vessel Monitoring System. The spatial extension of fishing activities, hourly fishing effort (h), landings (tons) and economic value (euros) for each CCA and the NIS were estimated as yearly median values. Fishing activities were absent in the Blue CCA, where the presence of the submarine canyon head does not offer accessible fishing grounds. The hourly fishing effort in the Green area accounted for about 22% (3443 h) of the total hourly effort of the NIS, while the Orange and Red areas were about 8% (1226 h) and 2% (295 h), respectively. The Green CCA corresponded to about 14% (36 tons) of the total landings in the NIS, whereas the Orange and Red areas represented about 9% (22 tons) and 6% (16 tons), respectively. The Green CCA accounted for about 13% (156 thousand euros) of the total economic value of the NIS, while the Orange and Red areas represented about 6% (69 thousand euros) and 4% (44thousand euros), respectively. Results showed no or negligible negative effects on trawl activities by potential spatial restrictions due to the establishment of CCAs highlighting the importance to consider spatially integrated information during the establishment process of conservation areas for cetacean biodiversity according to the principles of Ecosystem Based Management.

Evaluation of activity meters for estrus detection: A stochastic bioeconomic modeling approach

Although estrus detection makes a relevant contribution to the reproductive performance of dairy cattle, studies on the economic evaluation of automatic estrus detection systems are rare. The objective of the present study is to provide an economic evaluation of activity meters used for estrus detection. The effect of different estrus detection rates on gross margins was modeled with SimHerd (SimHerd A/S, Viborg, Denmark). The analysis considers all costs associated with the investment in activity meters. The economic evaluation was carried out through simulation of Simmental herds with yearly milk yields of 7,000 or 9,000 kg and Holstein Friesian herds with yearly milk yields of 9,000 or 11,000 kg, each with herd sizes of 70 or 210 cows. Furthermore, we distinguished between 2 investment scenarios. In scenario 1, only cows are equipped with activity meters for estrus detection, whereas scenario 2 assumes that cows and heifers are equipped with activity meters. Because existing empirical information for some variables shows significant variability (estrus detection rates, time for estrus detection), they were modeled with distributions using the Monte Carlo method in @RISK (Palisade Corporation, Ithaca, NY), allowing us to model a probability distribution of net returns (NR) of investment in activity meters for estrus detection. The simulation results show that the average NR of investment in activity meters for estrus detection over all scenarios ranges from +€7 to +€40 per cow per year for the Simmental breed, and from +€19 to +€46 per cow per year for the Holstein Friesian breed. Generally, the NR depends on the milk production level assumed. For the Simmental breed, depending on the scenario, the simulation results show a 54 to 200% larger average NR of investment in activity meters for estrus detection with a milk yield of 9,000 kg/yr compared with 7,000 kg/yr. For the Holstein Friesian breed, the effect of the modeled milk yield on the NR is much less pronounced. Average NR of investment in activity meters are greater for larger herd sizes because of cost degression effects. An additional equipping of heifers has, on average, a positive effect on the economics of activity meters for estrus detection because of the resulting reduction in the age at first calving. Considering all scenarios, the probability of a positive NR of investment in activity meters ranges between 74 and 98% for the Simmental breed and between 85 and 99% for the Holstein Friesian breed.

Simulating the Effects of Alternative Management Measures of Trawl Fisheries in the Central Mediterranean Sea: Application of a Multi-Species Bio-economic Modeling Approach

In the last decades, the Mediterranean Sea experienced an increasing trend of fish stocks in overfishing status. Therefore, management actions to achieve a more sustainable exploitation of fishery resources are required and compelling. In this study, a spatially-explicit multi-species bio-economic modelling approach, namely SMART, was applied to the case study of central Mediterranean Sea to assess the potential effects of different trawl fisheries management scenarios on the demersal resources. The approach combines multiple modelling components, integrating the best available sets of spatial data about catches and stocks, fishing footprint from VMS and economic parameters in order to describe the relationships between fishing effort pattern and impacts on resources and socio-economic consequences. Moreover, SMART takes into account the bi-directional connectivity between spawning and nurseries areas of target species, embedding the outcomes of a larvae transport Lagrangian model and of an empirical model of fish migration. Finally, population dynamics and trophic relationships are considered using a MICE (Models of Intermediate Complexity) approach. SMART simulates the fishing effort reallocation resulting from the introduction of different management scenarios. Specifically, SMART was applied to evaluate the potential benefits of different management approaches of the trawl fisheries targeting demersal stocks (deep-water rose shrimp P. longirostris, the giant red shrimp A. foliacea, the European hake M. merluccius and the red mullet M. barbatus) in the Strait of Sicily. The simulated management scenarios included both a reduction of the fishing capacity and effort, two different sets of temporal fishing closures and two sets of spatial fishing closures, defined involving fishers. Results showed that both temporal and spatial closures are expected to determine a significant improvement in the exploitation pattern for all the species, ultimately leading to the substantial recovery of spawning stock biomass for the stocks. Overall, one of the management scenario suggested by fishers scored better and confirms the usefulness of participatory approaches, suggesting the need for more public consultation when dealing with resource management at sea.

Assessing the contribution of artisanal fisheries to food security: A bio-economic modeling approach

Artisanal fisheries are an important food source in many developing regions. Quantitative bio-economic models are needed that comprehensively assess artisanal fisheries’ contribution to food security. Our model combines standard resource economics theory with the literature on food systems. It explains impacts of environmental variations and market development on output, prices and ultimately food security. The application to the Senegalese purse-seine fishery reveals that total sector rents account for 2% of per capita yearly food expenditures for the coastal inhabitants. We examine the relative importance of main drivers and the vulnerability of different regions. Market development plays a crucial role: The resource is of far greater relevance for remote regions.

Applied spatial approach of modelling field size changes based on a consideration of farm and landscape interrelations

Field sizes in agricultural production determine landscape characteristics and thus habitats. Yet, field sizes are not adequately considered in many theoretical landscape-oriented modelling approaches explaining habitats as well as biodiversity (BD). Our objective is to transfer theoretical model thinking into a practical approach with the focus on field and farm size changes. In our novel approach we model the impact of land consolidation driven by structural change, exchange of land between neighboring farmers and the participation in agri-environmental scemes. We work with a spatial representation of farming decisions and apply our model to a regional case study characterized as an intensively used agricultural area in Germany. Results are graphically translated via a geographical information system (GIS) and indicate that structural change leads to landscape homogeneity in our study region, and diversity of farming shrinks under the Common Agricultural Policy Reform 2009. Our model gives an idea of spatial variation in crop heterogeneity over time by conceptualizing spatial and temporal scales. In our stylized landscape visualization we prove the capabilities of a bio-economic modelling approach capturing economic resource allocation patterns and spatial representation of farming decisions in a perspective of sustainability analysis.

The management of marine protected area of Raja Ampat Regency, West Papua Province through bioeconomic model approach

Raja Ampat Regency in West Papua Province, Republic of Indonesia has abundant natural fishery resources. Marine Protected Area (MPA) has been established in marine areas of Raja Ampat Regency. To manage MPA better, measureable parameters and clear indicators are required. The decision on the indicators can be conducted by bioeconomic model approach. The results of research show that the establishment of MPA will increase harvest level and revenue. But “bigger is better” could not be adopted for the development of MPA. The optimal MPA size will contribute to increasing yields and revenue and can reduce the level of effort.

Herbicide free agriculture? A bio-economic modelling application to Swiss wheat production

Herbicide application in agricultural systems is currently critically discussed because of its possible adverse effects on the environment and human health. Currently, governments and food industry actors search for solutions to reduce herbicide use on farms. Yet, potential consequences of herbicide reductions on a farm-level are not well known. The goal of this article is to develop and apply a bio-economic modelling approach to simulate how farmers and agricultural systems react to a potential ban of glyphosate and eventually of all herbicides. We apply this approach for Swiss Extenso wheat production, which is a widespread form of wheat production in Switzerland, where pesticide use is currently limited to herbicides and seed treatments. Our modelling approach combines spatially explicit, detailed information on weed pressure, possible yield effects of weeds and efficacy and costs of 140 weed control strategies in a spatially explicit economic decision model. We assess the strategies optimal for farmers in response to i) glyphosate-free and ii) herbicide-free production requirements in terms of economic losses, yield reductions and environmental impacts. We find economic losses in the glyphosate-free production scenario of up to CHF 119/ha and in the herbicide-free scenario of up to CHF 192/ha, with respective yield reductions ranging between 0.8 and 2.7 dt/ha (i.e. of up to 6%). However, possible economic losses would be outweighed by existing Swiss agri-environmental direct payments for herbicide-free and reduced tillage production systems. We find that restrictions with respect to glyphosate and herbicide use imply trade-offs between the reduction in pesticide risks for the environment and human health versus higher energy consumption. Yet, these trade-offs can be limited if incentive schemes for glyphosate and herbicide reduction are combined with requirements to prevent more intensive tillage.

Climate change and mixed forests: how do altered survival probabilities impact economically desirable species proportions of Norway spruce and European beech?

Economic consequences of altered survival probabilities under climate change should be considered for regeneration planning in Southeast Germany. Findings suggest that species compositions of mixed stands obtained from continuous optimization may buffer but not completely mitigate economic consequences. Mixed stands of Norway spruce ( Picea abies L. Karst . ) and European beech ( Fagus sylvatica L.) (considering biophysical interactions between tree species) were found to be more robust, against both perturbations in survival probabilities and economic input variables, compared to block mixtures (excluding biophysical interactions). Climate change is expected to increase natural hazards in European forests. Uncertainty in expected tree mortality and resulting potential economic consequences complicate regeneration decisions. This study aims to analyze the economic consequences of altered survival probabilities for mixing Norway spruce (Picea abies L. Karst.) and European beech (Fagus sylvatica L.) under different climate change scenarios. We investigate whether management strategies such as species selection and type of mixture (mixed stands vs. block mixture) could mitigate adverse financial effects of climate change. The bio-economic modelling approach combines a parametric survival model with modern portfolio theory. We estimate the economically optimal species mix under climate change, accounting for the biophysical and economic effects of tree mixtures. The approach is demonstrated using an example from Southeast Germany. The optimal tree species mixtures under simulated climate change effects could buffer but not completely mitigate undesirable economic consequences. Even under optimally mixed forest stands, the risk-adjusted economic value decreased by 28%. Mixed stands economically outperform block mixtures for all climate scenarios. Our results underline the importance of mixed stands to mitigate the economic consequences of climate change. Mechanistic bio-economic models help to understand consequences of uncertain input variables and to design purposeful adaptation strategies.

Shea tree (Vitellaria paradoxa Gaertn. f.): from local constraints to multi-scale improvement of economic, agronomic and environmental performance in an endemic Sudanian multipurpose agroforestry species

Shea trees (Vitellaria paradoxa Gaertn. f.) have been for perhaps as long as 3000 years probably the most economically and culturally important tree species in Sudanian agroforestry systems. The existing studies show that the specific magnitude and limits of shea tree presence and shea products’ advantages are highly variable. This synthesis paper gathers and updates most of the scattered knowledge on shea trees and parklands, reported by category of knowledge: socio-economic potential of shea production, current means of enhancing shea domestication, tree impacts on environmental resources and associated crop production. It concludes with a proposal for a systemic and participative bio-economic modelling approach in order to simulate intensification of shea parklands’ production using process-based research results on their economic, agronomic and environmental performance.

Utilization and Management Model of Pelagic Fish Resources

Pelagic fish was the main raw material for fish processing industry. Rate of fishing that not equivalent with the growth of fish resources, eventually will decrease the catch of fishermen. Aims of the research were (1) to estimate the bioeconomic of pelagic fish resources on MSY (Maximum Sustainable Yield), MEY (Maximum Economic Yield) and OA (open Access) conditions; (2) to estimate the optimum utilization rate, (3) arrange the management model of sustainability pelagic fish resources in Pati regency. This research was descriptive quantitative and conducted in March until September 2017. Reseacrh location in Bajomulyo village and Bendar village Juwana Subdistrict with 35 samples. Data analysis : (1) gear standardization, (2) bioeconomic static optimation model approach, (3) bioeconomic dinamic optimation model approach, (4) reconstruction of in-depth interview results. Result of the research are (1) bioeconomic static optimation model approach namely, biomass MEY>MSY>OA, catch MSY>MEY>OA, effort OA>MSY>MEY, profit MEY>MSY>OA; (2) bioeconomic dinamic optimation model approach namely, biomass MEY>MSY>OSY>OA, catch MSY>MEY>OSY>OA, effort OA>MSY>OSY>MEY, profit MEY>>OSY>MSY>OA; (3) pelagic fish management model are input controlling, output controlling and technical provisions.

Can overexploited fisheries recover by self-organization? Reallocation of fishing effort as an emergent form of governance

Owing to high costs and difficulties in implement control, fisheries are less regulated than terrestrial activities. In areas of weak governance, self-regulation is often the rule. Understanding the underlying bio-economic mechanisms that drive such fishery systems is crucial for decision making on how to support real fishermen communities. Fishing effort reallocation occurs when economic yield drops, suggesting a feedback between fishermen's mobility and local overexploitation. The nature of this feedback is addressed here by using a bio-economic modelling approach applied to a Senegalese fishery. The white grouper is a highly valued commercial fish that has suffered intense exploitation in Senegal and was predicted to collapse due to a lack of fishery regulation combined with high demand. Surprisingly, our analysis of landings and associated price variability suggests that a slow recovery of this fishery is now underway. Motivated by this finding, two models were implemented that account for artisanal fishermen's mobility and variable prices. Both models provided the same insight: fishing effort mobility combined with variable fish prices induced a shift from local overexploitation to sub-regional sustainable exploitation. Considering that fishing effort mobility has steeply increased in recent years, this mechanism might have significantly contributed to the recent observed trends in prices and landings for this fishery. More generally, these bio-economic models suggest that spatial reallocation of fishing effort acts as emergent governance in under regulated areas that allows, in some cases, the recovery of an overexploited species.

The biophysical and socio-economic dimension of yield gaps in the southern Amazon – A bio-economic modelling approach

Farmers in the State of Mato Grosso are among Brazil's most productive soybean, maize and cotton producers, but are still far away from achieving potential yields as measured on experimental sites. The objective of this study was to decompose yield gaps in the Southern Amazon into their biophysical and socio-economic dimensions. In order to achieve this, the process-based MOdel of NItrogen and Carbon dynamics in Agro-ecosystems (MONICA) was coupled with the Mathematical Programming-based Multi-Agent Systems (MPMAS) software. Soybean, maize and cotton yield gaps were simulated for five macro-regions in Mato Grosso considering different climatic, edaphic and crop management conditions. The impact of socio-economic constraints on crop yields was assessed in form of full factorial design in which each factor was set to a baseline and unconstrained level. The simulation results show that biophysical yield gaps (due to water and nutrient deficit) account for 24% of potential yields (Yp), whereas an unrestricted access to machinery, labour, credit and technological innovation would lead to a reduction of yield gaps by 6.1% and an expansion of cropland by 22%. Yield gaps can be reduced through improved water- and nutrient management, appropriate cultivar-sowing date combinations and in part by a removal of socio-economic constraints. However, each solution comes with its own limitation either in form of increased pressure on limited environmental resources or incompatibility with individual farmer objectives. Future yield gap closure will depend on the access to arable land, environmental regulations preventing further deforestation as well as political and economic incentives for sustainable intensification.

Spillover from marine protected areas on the pacific coast in Colombia: A bioeconomic modelling approach for shrimp fisheries

Marine protected areas are currently recognized as an alternative for the conservation of marine ecosystems. Although the protection reduces the area available for fishing, it has been argued that the spillover effect can increase resources in the adjoining areas. The purpose of this study is to calculate the value of the provision of fishing resources resulting from an increase in the system of marine protected areas in Colombia. To do that, a surplus-production based dynamic bio-economic model is developed for white shrimp (Litopenaeus occidentalis), a species important socially and economically in Colombia. The model includes a protected area with essential habitats, a nonprotected area, and mobility of species between them. Changes in biomass, catch, effort and the economic benefits of fishing through time, under different protection scenarios, are analyzed. Despite the reduction of the area available for fishing, in the mid-term, the protected areas generate increased levels of biomass and greater benefits associated to the fishing activity, because of the spillover effect. In that sense, the marine protected areas constitute a valid alternative for fishery conservation with the potential to generate economic benefits in the midterm.

Optimal combinable and dedicated energy crop scenarios for marginal land

Modern biomass energy sources account for less than 2% of primary world energy supplies while major economies have enabled legislation that aims to increase bioenergy production. In response to controversies over first generation biofuel, it has been argued that ‘marginal land’ should be used to produce dedicated energy crops (DECs). However, defining marginality of agricultural land is complex, and moreover, DECs would have to out-compete current agricultural production in these areas. Utilising a bio-economic farm-level modelling approach we investigate the impact that crop yield penalties resulting from production in marginal land contexts have on financially optimal farm-level crop plans. Where farm businesses choose to de-invest in own farm machinery, yield reductions of less than 10% for winter wheat result in a financially optimal switch to 100% miscanthus production. By contrast, in the presence of own farm machinery, winter wheat yield penalties of 30% are required before 100% miscanthus production is financially optimal. However, under circumstances where DECs also suffer yield penalties on marginal land, the financially optimal crop mix includes combinable crops. The results demonstrate that the optimal crop mix is dependent upon the relative combinable and DEC yields, together with farm-level decisions towards machinery ownership. The focus of much policy attention relating to production of DECs on ‘marginal land’ is therefore argued to be incomplete. Policies which encourage farmers to de-invest in own farm machinery, or incentivise the purchase of specific DEC machinery, may play an important role in assisting the development of DEC production.