{"id":3393,"date":"2024-04-25T12:08:19","date_gmt":"2024-04-25T16:08:19","guid":{"rendered":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/?post_type=chapter&p=3393"},"modified":"2025-10-30T08:57:39","modified_gmt":"2025-10-30T12:57:39","slug":"revenue-and-profits","status":"publish","type":"chapter","link":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/revenue-and-profits\/","title":{"raw":"Revenue and profits","rendered":"Revenue and profits"},"content":{"raw":"

EwE can directly produce multiple socio-economic indicators. Nonetheless, EwE models can also be linked to, or coupled with, external bioeconomic models to expand its capabilities. A first step, however, is the identification of ex-vessel prices for the multiple functional groups included in the model. These data can be obtained from local or national reports, as well as from existing regional (e.g.<\/em>, EU\u2019s Scientific, Technical and Economic Committee for Fisheries) and global (e.g.<\/em>, Sea Around Us) databases.<\/p>\r\n

Users should begin by defining the currency to be used in the model by selecting the correct monetary units (e.g.<\/em>, USD, EUR, CNY) while setting the models\u2019 parameters (Ecopath > Input > Model parameters<\/em>). Then, after defining the model\u2019s functional groups and fishing fleets, and including the corresponding landings data, users will be able to input price data for each functional group \u2013 fishing fleet combination with catches. This is achieved in the off-vessel prices form (Ecopath > Input > Fishery > Off-vessel prices<\/em>), and the data included should reflect the value of a ton of fish or shellfish caught within the model area in the base year. Based on this data, the model can estimate three socio-economic indicators pertaining to revenue by multiplying the off-vessel prices with the corresponding landed amounts for each functional group \u2013 fishing fleet combination and adding these values across: (i) functional groups (i.e., the landed value per functional group), (ii) fishing fleets (i.e., fleet level revenue), and (iii) across functional groups and fishing fleets (i.e., total landed value or total producer revenue).<\/p>\r\n

If multiple Ecopath models are available for the same project area, then the landed value per functional group, the fleet level revenue, and the total producer revenue can be used to compare the fisheries over time. Moreover, if time series data for off-vessel prices is available, then the outputs from Ecosim and Ecospace runs (e.g., time series data of catches per fleet) can be used to estimate these three indicators externally. Yet, EwE can also model these internally, if information is available on how sensitive off-vessel prices are to changes in landed quantities. This can be achieved through price elasticities (Ecosim > Input > Price elasticity<\/em>). For more information on this see the chapter on Price elasticity<\/a>.<\/strong><\/p>\r\n

In some cases, the value of a fishery may increase over time (due to higher catches or off-vessel prices). However, the fleets\u2019 profitability might not follow the same trend if fishing costs (e.g., wages, fuel) have increased at a much faster rate. Indicators related to profits (i.e., Profits = Revenue \u2013 Costs<\/em>) are thus useful for capturing these changes, particularly if multiple fleets are involved. This is also a relevant concern for modelling the consequences policies pertaining to fisheries subsidies.[footnote]Sumaila U.R., N. Ebrahim, A. Schuhbauer, D. Skerritt, Y. Li, H.S. Kim, T.G. Mallory, V.W.L. Lam, D. Pauly, Updated estimates and analysis of global fisheries subsidies, Mar Policy 109 (2019) 103695. https:\/\/doi.org\/10.1016\/j.marpol.2019.103695<\/a>[\/footnote]<\/p>\r\n

There are multiple ways by which EwE allows users to get a grasp of profitability. It begins by obtaining information about the cost-income structures of the fishing fleets. These data can be directly collected using surveys or semi-structured interviews[footnote]Bennett N.J., A. Schuhbauer, D. Skerritt, N. Ebrahim, Socio-economic monitoring and evaluation in fisheries, Fish Res 239 (2021) 105934. https:\/\/doi.org\/10.1016\/j.fishres.2021.105934<\/a>[\/footnote] [18], extracted from secondary literature (mainly grey literature), or requested to the government bodies responsible for its collection at subnational or national levels. EwE allows users to input cost-income data by expressing it as a percentage of the fleet level revenue, where: Total Value of the fleet = Fixed costs + Cost per unit of effort + Cost of sailing + Profit<\/em>. This information can be included in the model in the same form used to define the fleets (Ecopath > Input > Fishery > Fleets<\/em>).<\/p>\r\n

Here, Fixed costs<\/em> include costs that are independent of changes in effort levels at the fleet scale (e.g.<\/em>, capital investments, management, and monitoring costs). Cost per unit of effort<\/em> and Cost of sailing<\/em> are both used to express variable costs, or costs that change proportionally to changes in fishing effort (e.g., fuel, food for the crew, wages). If the user only plans to use Ecopath or Ecosim, then all variable costs should be included as Cost per unit of effort <\/em>(i.e., Cost of sailing<\/em> should be left empty). Only if the intention is to build an Ecospace model, then variable costs should be split, highlighting the cost fraction that will vary directly depending on the spatial allocation of fishing effort (e.g., fuel costs). These costs should be included as Cost of sailing<\/em>, while all other variable cost should be entered as Cost per unit of effort<\/em>. The default settings for all fleets places Fixed costs<\/em> at 0%, Cost per unit of effort<\/em> at 40%, Cost of sailing<\/em> at 40% and Profit<\/em> at 20%. These defaults might be representative for some fleets, yet for most they will not (e.g., STECF 22-06<\/a>).<\/p>\r\n

Understanding what proportion of the fleet level revenues correspond profits allows users to estimate fleet level profits out of Ecosim and Ecospace runs.[footnote]Wang Y., S.Y. Li, L.J. Duan, Y. Liu, Fishery policy exploration in the Pearl River Estuary based on an Ecosim model, Ecol. Model. 230 (2012) 34\u201343. https:\/\/doi.org\/10.1016\/j.ecolmodel.2012.01.017<\/a>[\/footnote] [footnote]Ram\u00edrez A., M. Ortiz, J. Steenbeek, V. Christensen, Evaluation of the effects on rockfish and kelp artisanal fisheries of the proposed Mejillones Peninsula marine protected area (northern Chile, SE Pacific coast), Ecol. Model. 297 (2015) 141\u2013153. https:\/\/doi.org\/10.1016\/j.ecolmodel.2014.11.012<\/a>[\/footnote] [footnote]Izquierdo-Gomez D., J.T. Bayle-Sempere, F. Arregu\u00edn-S\u00e1nchez, P. S\u00e1nchez-Jerez, Modeling population dynamics and small-scale fisheries yields of fish farming escapes in Mediterranean coastal areas, Ecol. Model. 331 (2016) 56\u201367. https:\/\/doi.org\/10.1016\/j.ecolmodel.2016.01.012<\/a>[\/footnote] [footnote]Bacalso R.T.M., M. Wolff, R.M. Rosales, N.B. Armada, Effort reallocation of illegal fishing operations: A profitable scenario for the municipal fisheries of Danajon Bank, Central Philippines, Ecol. Model. 331 (2016) 5\u201316. https:\/\/doi.org\/10.1016\/j.ecolmodel.2016.01.015<\/a>[\/footnote] [footnote]Rehren J., M. Wolff, N. Jiddawi, Holistic assessment of Chwaka Bay\u2019s multi-gear fishery \u2013 Using a trophic modeling approach, J. Mar. Syst. 180 (2018) 265\u2013278. https:\/\/doi.org\/10.1016\/j.jmarsys.2018.01.002<\/a>[\/footnote] [footnote]Armada N.B., R.T.M. Bacalso, R.M.P. Rosales, A.T. Lazarte, Right-sizing as a strategy for allocating fishing effort in a defined marine ecosystem: A Philippines case study, Ocean Coast. Manag. 165 (2018) 167\u2013184. https:\/\/doi.org\/10.1016\/j.ocecoaman.2018.08.018<\/a>[\/footnote] [footnote]Alms V., G. Romagnoni, M. Wolff, Exploration of fisheries management policies in the Gulf of Nicoya (Costa Rica) using ecosystem modelling, Ocean Coast. Manag. 230 (2022) 106349. https:\/\/doi.org\/10.1016\/j.ocecoaman.2022.106349<\/a>[\/footnote]. Moreover, if additional information is available of what percentage of the fleet level revenue is used for wages, how many vessels are operating and how many people are employed per vessel, then modelers can also estimate fishers\u2019 average salaries per fleet. This information could then be used to compare it with annual country level minimum wages to assess if, and under which scenarios, fishers operate below the poverty line. Additionally, having information about fishing costs and profits is essential for modelling effort dynamics within EwE (see the chapter on Fleet effort dynamics<\/a>), as well as for fishing policy exploration (see chapter on Fishing policy exploration<\/a>). An alternative way to parametrize fishing costs is described in the Value chain modelling<\/a> chapter.<\/p>","rendered":"

EwE can directly produce multiple socio-economic indicators. Nonetheless, EwE models can also be linked to, or coupled with, external bioeconomic models to expand its capabilities. A first step, however, is the identification of ex-vessel prices for the multiple functional groups included in the model. These data can be obtained from local or national reports, as well as from existing regional (e.g.<\/em>, EU\u2019s Scientific, Technical and Economic Committee for Fisheries) and global (e.g.<\/em>, Sea Around Us) databases.<\/p>\n

Users should begin by defining the currency to be used in the model by selecting the correct monetary units (e.g.<\/em>, USD, EUR, CNY) while setting the models\u2019 parameters (Ecopath > Input > Model parameters<\/em>). Then, after defining the model\u2019s functional groups and fishing fleets, and including the corresponding landings data, users will be able to input price data for each functional group \u2013 fishing fleet combination with catches. This is achieved in the off-vessel prices form (Ecopath > Input > Fishery > Off-vessel prices<\/em>), and the data included should reflect the value of a ton of fish or shellfish caught within the model area in the base year. Based on this data, the model can estimate three socio-economic indicators pertaining to revenue by multiplying the off-vessel prices with the corresponding landed amounts for each functional group \u2013 fishing fleet combination and adding these values across: (i) functional groups (i.e., the landed value per functional group), (ii) fishing fleets (i.e., fleet level revenue), and (iii) across functional groups and fishing fleets (i.e., total landed value or total producer revenue).<\/p>\n

If multiple Ecopath models are available for the same project area, then the landed value per functional group, the fleet level revenue, and the total producer revenue can be used to compare the fisheries over time. Moreover, if time series data for off-vessel prices is available, then the outputs from Ecosim and Ecospace runs (e.g., time series data of catches per fleet) can be used to estimate these three indicators externally. Yet, EwE can also model these internally, if information is available on how sensitive off-vessel prices are to changes in landed quantities. This can be achieved through price elasticities (Ecosim > Input > Price elasticity<\/em>). For more information on this see the chapter on Price elasticity<\/a>.<\/strong><\/p>\n

In some cases, the value of a fishery may increase over time (due to higher catches or off-vessel prices). However, the fleets\u2019 profitability might not follow the same trend if fishing costs (e.g., wages, fuel) have increased at a much faster rate. Indicators related to profits (i.e., Profits = Revenue \u2013 Costs<\/em>) are thus useful for capturing these changes, particularly if multiple fleets are involved. This is also a relevant concern for modelling the consequences policies pertaining to fisheries subsidies.[1]<\/sup><\/a><\/p>\n

There are multiple ways by which EwE allows users to get a grasp of profitability. It begins by obtaining information about the cost-income structures of the fishing fleets. These data can be directly collected using surveys or semi-structured interviews[2]<\/sup><\/a> [18], extracted from secondary literature (mainly grey literature), or requested to the government bodies responsible for its collection at subnational or national levels. EwE allows users to input cost-income data by expressing it as a percentage of the fleet level revenue, where: Total Value of the fleet = Fixed costs + Cost per unit of effort + Cost of sailing + Profit<\/em>. This information can be included in the model in the same form used to define the fleets (Ecopath > Input > Fishery > Fleets<\/em>).<\/p>\n

Here, Fixed costs<\/em> include costs that are independent of changes in effort levels at the fleet scale (e.g.<\/em>, capital investments, management, and monitoring costs). Cost per unit of effort<\/em> and Cost of sailing<\/em> are both used to express variable costs, or costs that change proportionally to changes in fishing effort (e.g., fuel, food for the crew, wages). If the user only plans to use Ecopath or Ecosim, then all variable costs should be included as Cost per unit of effort <\/em>(i.e., Cost of sailing<\/em> should be left empty). Only if the intention is to build an Ecospace model, then variable costs should be split, highlighting the cost fraction that will vary directly depending on the spatial allocation of fishing effort (e.g., fuel costs). These costs should be included as Cost of sailing<\/em>, while all other variable cost should be entered as Cost per unit of effort<\/em>. The default settings for all fleets places Fixed costs<\/em> at 0%, Cost per unit of effort<\/em> at 40%, Cost of sailing<\/em> at 40% and Profit<\/em> at 20%. These defaults might be representative for some fleets, yet for most they will not (e.g., STECF 22-06<\/a>).<\/p>\n

Understanding what proportion of the fleet level revenues correspond profits allows users to estimate fleet level profits out of Ecosim and Ecospace runs.[3]<\/sup><\/a> [4]<\/sup><\/a> [5]<\/sup><\/a> [6]<\/sup><\/a> [7]<\/sup><\/a> [8]<\/sup><\/a> [9]<\/sup><\/a>. Moreover, if additional information is available of what percentage of the fleet level revenue is used for wages, how many vessels are operating and how many people are employed per vessel, then modelers can also estimate fishers\u2019 average salaries per fleet. This information could then be used to compare it with annual country level minimum wages to assess if, and under which scenarios, fishers operate below the poverty line. Additionally, having information about fishing costs and profits is essential for modelling effort dynamics within EwE (see the chapter on Fleet effort dynamics<\/a>), as well as for fishing policy exploration (see chapter on Fishing policy exploration<\/a>). An alternative way to parametrize fishing costs is described in the Value chain modelling<\/a> chapter.<\/p>\n

  1. Sumaila U.R., N. Ebrahim, A. Schuhbauer, D. Skerritt, Y. Li, H.S. Kim, T.G. Mallory, V.W.L. Lam, D. Pauly, Updated estimates and analysis of global fisheries subsidies, Mar Policy 109 (2019) 103695. https:\/\/doi.org\/10.1016\/j.marpol.2019.103695<\/a> ↵<\/a><\/li>
  2. Bennett N.J., A. Schuhbauer, D. Skerritt, N. Ebrahim, Socio-economic monitoring and evaluation in fisheries, Fish Res 239 (2021) 105934. https:\/\/doi.org\/10.1016\/j.fishres.2021.105934<\/a> ↵<\/a><\/li>
  3. Wang Y., S.Y. Li, L.J. Duan, Y. Liu, Fishery policy exploration in the Pearl River Estuary based on an Ecosim model, Ecol. Model. 230 (2012) 34\u201343. https:\/\/doi.org\/10.1016\/j.ecolmodel.2012.01.017<\/a> ↵<\/a><\/li>
  4. Ram\u00edrez A., M. Ortiz, J. Steenbeek, V. Christensen, Evaluation of the effects on rockfish and kelp artisanal fisheries of the proposed Mejillones Peninsula marine protected area (northern Chile, SE Pacific coast), Ecol. Model. 297 (2015) 141\u2013153. https:\/\/doi.org\/10.1016\/j.ecolmodel.2014.11.012<\/a> ↵<\/a><\/li>
  5. Izquierdo-Gomez D., J.T. Bayle-Sempere, F. Arregu\u00edn-S\u00e1nchez, P. S\u00e1nchez-Jerez, Modeling population dynamics and small-scale fisheries yields of fish farming escapes in Mediterranean coastal areas, Ecol. Model. 331 (2016) 56\u201367. https:\/\/doi.org\/10.1016\/j.ecolmodel.2016.01.012<\/a> ↵<\/a><\/li>
  6. Bacalso R.T.M., M. Wolff, R.M. Rosales, N.B. Armada, Effort reallocation of illegal fishing operations: A profitable scenario for the municipal fisheries of Danajon Bank, Central Philippines, Ecol. Model. 331 (2016) 5\u201316. https:\/\/doi.org\/10.1016\/j.ecolmodel.2016.01.015<\/a> ↵<\/a><\/li>
  7. Rehren J., M. Wolff, N. Jiddawi, Holistic assessment of Chwaka Bay\u2019s multi-gear fishery \u2013 Using a trophic modeling approach, J. Mar. Syst. 180 (2018) 265\u2013278. https:\/\/doi.org\/10.1016\/j.jmarsys.2018.01.002<\/a> ↵<\/a><\/li>
  8. Armada N.B., R.T.M. Bacalso, R.M.P. Rosales, A.T. Lazarte, Right-sizing as a strategy for allocating fishing effort in a defined marine ecosystem: A Philippines case study, Ocean Coast. Manag. 165 (2018) 167\u2013184. https:\/\/doi.org\/10.1016\/j.ocecoaman.2018.08.018<\/a> ↵<\/a><\/li>
  9. Alms V., G. Romagnoni, M. Wolff, Exploration of fisheries management policies in the Gulf of Nicoya (Costa Rica) using ecosystem modelling, Ocean Coast. Manag. 230 (2022) 106349. https:\/\/doi.org\/10.1016\/j.ocecoaman.2022.106349<\/a> ↵<\/a><\/li><\/ol><\/div>","protected":false},"author":1909,"menu_order":2,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":["santiago-de-la-puente"],"pb_section_license":""},"chapter-type":[],"contributor":[66],"license":[],"class_list":["post-3393","chapter","type-chapter","status-publish","hentry","contributor-santiago-de-la-puente"],"part":438,"_links":{"self":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/3393","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/users\/1909"}],"version-history":[{"count":6,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/3393\/revisions"}],"predecessor-version":[{"id":3518,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/3393\/revisions\/3518"}],"part":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/parts\/438"}],"metadata":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/3393\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/media?parent=3393"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapter-type?post=3393"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/contributor?post=3393"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/license?post=3393"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}