Do Species Interactions and Stochasticity Matter to Optimal Management of Multispecies Fisheries?

Poudel, Diwakar; Sandal, Leif Kristoffer; Steinshamn, Stein Ivar; Kvamsdal, Sturla F.

doi:10.4027/gpebfm.2012.011

Cited by 6 publications

(10 citation statements)

References 35 publications

(59 reference statements)

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“…The diagonal elements are also relatively small, at least when compared to hypothetical scenarios studied in theoretical work (Poudel et al. []). The standard errors do not give a correct measure of the significance of the diagonal elements, as the elements are positive by definition, but nevertheless show that the system is stochastic.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

The Ensemble Kalman Filter for Multidimensional Bioeconomic Models

Kvamsdal¹,

Sandal

2015

Natural Resource Modeling

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SNF SAMFUNNS-OG NAERINGSLIVSFORSKNING AS-er et selskap i NHH-miljøet med oppgave å initiere, organisere og utføre eksternfinansiert forskning. Norges Handelshøyskole og Stiftelsen SNF er aksjonaerer. Virksomheten drives med basis i egen stab og fagmiljøene ved NHH.SNF er ett av Norges ledende forsk ningsmiljø innen anvendt økonomisk -administrativ forskning, og har gode samarbeidsrelasjoner til andre forskningsmiljøer i Norge og utlandet. SNF utfører forskning og forsknings baserte utredninger for sentrale beslutningstakere i privat og offentlig sektor. Forskningen organiseres i programmer og prosjekter av langsiktig og mer kortsiktig karakter. Alle publikasjoner er offentlig tilgjengelig. SNF CENTER FOR APPLIED RESEARCH AT NHH-is a company within the NHH group. Its objective is to initiate, organize and conduct externally financed research. The company shareholders are the Norwegian School of Economics (NHH)and the SNF Foundation. Research is carried out by SNF´s own staff as well as faculty members at NHH. SNF is one of Norway´s leading research environment within applied economic administrative research. It has excellent working relations with other research environments in Norway as well as abroad. SNF conducts research and prepares research-based reports for major decision-makers both in the private and the public sector. Research is organized in programmes and projects on a long-term as well as a short-term basis. All our publications are publicly available. AbstractTo serve the needs for integrating economic considerations into management decisions in ecosystem frameworks, we need to build models that capture observed system dynamics and incorporate existing knowledge of ecosystems while at the same time serve the needs of economics analysis. The main constraint for models to serve in economic analysis is dimensionality. In addition, models should be stable in order to apply in long-term management analysis. We use the ensemble Kalman filter to fit relatively simple models to ecosystem or foodweb data and estimate parameters that are stable over the observed variability in the data. The filter also provides a lower bound on the noise terms that a stochastic analysis require. In the present article, we apply the filter to model the main interactions in the Barents Sea ecosystem.

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Section: Resultsmentioning

confidence: 99%

“…We have in mind the type of analysis carried out in Sandal and Steinshamn [] and Poudel et al. []; see also Kugarajh et al. [].…”

Section: The Barents Sea Modelmentioning

confidence: 99%

The Ensemble Kalman Filter for Multidimensional Bioeconomic Models

Kvamsdal¹,

Sandal

2015

Natural Resource Modeling

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“…The model captures much of the observed dynamics in the modelled populations, also in forecasting (an earlier study of the model that calculated two-year-ahead forecasts found that the main, dynamic features were picked up, but that forecasts tended to be low; see Ekerhovd and Kvamsdal, 2013). The low dimensionality is a key feature in that it makes economic analysis (that is,dynamic decision analysis; see Sandal and Steinshamn, 2010;Poudel et al, 2012) feasible, see Kvamsdal and Sandal (2014) for further discussion. Our e orts to model and estimate the Norwegian Sea pelagic complex combines a biological and ecological familiarity and understanding, the use of recent advances in data improvement (Ekerhovd and Gordon, 2013), and application of data assimilation methods (Evensen, 2003) that have seen little use in our eld.…”

Section: Resultsmentioning

confidence: 99%

“…We think there is a need for an explicit focus on modeling of biology and ecology that provides relevant structures for further, economic analysis (sensu Sandal and Steinshamn, 2010;Poudel et al, 2012). In our experience, biologists and ecologists have limited inherent interest in providing the necessary models, data, and structures.…”

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confidence: 99%

Up the ante on bioeconomic submodels of marine food webs: A data assimilation-based approach

Ekerhovd¹,

Kvamsdal²

2017

Ecological Economics

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SNF SAMFUNNS-OG NAERINGSLIVSFORSKNING AS-er et selskap i NHH-miljøet med oppgave å initiere, organisere og utføre eksternfinansiert forskning. Norges Handelshøyskole og Stiftelsen SNF er aksjonaerer. Virksomheten drives med basis i egen stab og fagmiljøene ved NHH.SNF er ett av Norges ledende forsk ningsmiljø innen anvendt økonomisk-administrativ forskning, og har gode samarbeidsrelasjoner til andre forskningsmiljøer i Norge og utlandet. SNF utfører forskning og forsknings baserte utredninger for sentrale beslutningstakere i privat og offentlig sektor. Forskningen organiseres i programmer og prosjekter av langsiktig og mer kortsiktig karakter. Alle publikasjoner er offentlig tilgjengelig. SNF CENTRE FOR APPLIED RESEARCH AT NHH-is a company within the NHH group. Its objective is to initiate, organize and conduct externally financed research. The company shareholders are the Norwegian School of Economics (NHH) and the SNF Foundation. Research is carried out by SNF´s own staff as well as faculty members at NHH. SNF is one of Norway´s leading research environment within applied economic administrative research. It has excellent working relations with other research environments in Norway as well as abroad. SNF conducts research and prepares research-based reports for major decision-makers both in the private and the public sector. Research is organized in programmes and projects on a long-term as well as a short-term basis. All our publications are publicly available. While economists have discussed ecosystem-based management and similar concepts, little attention has been devoted to the art of modeling. Models of ecosystems or foodwebs that make economic analysis viable should capture as much as possible of system structure and dynamics while balancing biological and ecological detail against dimensionality and model complexity. Relevant models need a strong, empirical content, but data availability may inhibit modeling e orts. Models are bound to be nonlinear, and model and observational uncertainty should be observed. We suggest the data assimilation method ensemble Kalman ltering to improve modeling of ecosystems or foodwebs. To illustrate the method, we model the dynamics of the main, pelagic species in the Norwegian Sea. In order to reduce the parameter dimensionality, the species are modeled to rely on a common carrying capacity.We also take further methodological steps to deal with a still high number of parameters.Our best model captures much of the observed dynamics in the sh stocks, but the estimated model error is moderate.

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“…Therefore, it is a key approach for sustainable management (Hollowed et al, 2000) and consideration of multispecies interaction in fishery model is increasing in recent years (for example, see Agnarsson et al, 2008;Bogstad et al, 1997;Clark, 1990;Fleming & Alexander, 2003;Iversen, 2006;Kar & Chaudhuri, 2004;May et al, 1979;Poudel, Sandal, Steinshamn, & Kvamsdal, 2012;Sandal & Steinshamn, 2010;Woodward & Bishop, 1999;Yodzis, 1994). However, most of the studies focused on predators prey interactions between two species while three species continuous time interaction models are very few, although there is increasing interest in multispecies model in recent years (for example, Aanestad et al, 2009;Das, Srinivas, Srinivas, & Gazi, 2012;Nieminen, Lindroos, & Heikinheimo, 2012;Samanta, Manna, & Maiti, 2003;Sharma & Samanta, 2013).…”

Section: Introductionmentioning

confidence: 99%

Stochastic Optimization for Multispecies Fisheries in the Barents Sea

Poudel

Sandal

2014

SSRN Journal

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This study presents a multispecies stochastic model. The model suggests optimal fishing policy for two species in a three species predator prey ecosystem in the Barents Sea. We have employed stochastic dynamic programing to solve a three dimensional model, where catch is optimized by a multispecies feedback strategy. Application of the model in cod, capelin and herring ecosystem in the Barents Sea shows that the optimal catch for stochastic interaction model is more conservative compared to deterministic policy. Furthermore, we found that stochasticity has strong effect on optimal exploitation policy in the prey (capelin) compared to the predator (cod) species.

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Do Species Interactions and Stochasticity Matter to Optimal Management of Multispecies Fisheries?

Abstract: The

Cited by 6 publications

References 35 publications

The Ensemble Kalman Filter for Multidimensional Bioeconomic Models

The Ensemble Kalman Filter for Multidimensional Bioeconomic Models

Up the ante on bioeconomic submodels of marine food webs: A data assimilation-based approach

Stochastic Optimization for Multispecies Fisheries in the Barents Sea

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