{"id":412,"date":"2023-08-09T15:57:00","date_gmt":"2023-08-09T19:57:00","guid":{"rendered":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/ecosim-model-construction\/"},"modified":"2025-10-30T08:56:43","modified_gmt":"2025-10-30T12:56:43","slug":"ecosim-introduction","status":"publish","type":"chapter","link":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/ecosim-introduction\/","title":{"raw":"An introduction to Ecosim","rendered":"An introduction to Ecosim"},"content":{"raw":"Ecosim provides a dynamic simulation capability at the ecosystem level, with key initial parameters inherited from the base Ecopath model.\r\n\r\nThe key computational aspects are in summary form,\r\n<ul>\r\n \t<li>Use of mass-balance results (from Ecopath) for parameter estimation;<\/li>\r\n \t<li>Variable speed splitting enables efficient modelling of the dynamics of both \"fast\" (e.g., phytoplankton) and \"slow\" groups (e.g., whales);<\/li>\r\n \t<li>Effects of micro-scale behaviours on macro-scale rates: top-down vs. bottom-up control incorporated explicitly.<\/li>\r\n \t<li>Includes biomass and size structure dynamics for key ecosystem groups, using a mix of differential and difference equations. As part of this EwE incorporates:<\/li>\r\n \t<li>Multi-stanza life stage structure by monthly cohorts, density- and risk-dependent growth \u2013 described in the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/age-structured-dynamics\/\">Age-structured dynamics<\/a> chapter;<\/li>\r\n \t<li>Stock-recruitment relationship as \"emergent\" property of competition\/predation interactions of juveniles.<\/li>\r\n<\/ul>\r\nEcosim uses a system of differential equations that expresses biomass flux rates among pools as a function of time varying biomass and harvest rates, (for equations see Walters et al., 1997[footnote]Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. <a href=\"https:\/\/link.springer.com\/article\/10.1023\/A:1018479526149\">Reviews in Fish Biology and Fisheries<\/a> 7:139-172.[\/footnote]; Walters et al., 2000[footnote]Walters, C.J., J.F. Kitchell, V. Christensen and D. Pauly. 2000. Representing density dependent consequences of life history strategies in aquatic ecosystems: Ecosim II. <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s100210000011\">Ecosystems<\/a> 3: 70-83.[\/footnote]; Christensen and Walters, 2004[footnote]Christensen, V. and C. J. Walters. 2004. Ecopath with Ecosim: methods, capabilities and limitations. <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S030438000300365X\">Ecol. Model.<\/a> 172:109-139[\/footnote]). Predator prey interactions are moderated by prey behaviour to limit exposure to predation, such that biomass flux patterns can show either bottom-up or top down (trophic cascade) control. By doing repeated simulations, Ecosim allows for the fitting of predicted biomasses to time series data.\r\n\r\nThe simplest, default version of Ecosim represents biomass dynamics using a series of coupled differential equations. The equations are of the basic form:\r\n<p style=\"text-align: left\">[latex]\\frac{dB_i}{dt}=g_i\\sum\\limits_{j=1}^{n}Q_{ij}-\\sum\\limits_{j=1}^{n}Q_{ji}+I_i-(F_i+e_i+M0_i) B_i\\tag{1}[\/latex]<\/p>\r\nwhere <em>dB<sub>i<\/sub>\/dt<\/em> represents the growth rate during the time interval <em>dt<\/em> of group <em>i<\/em>\u00a0in terms of its biomass, <em>B<sub>i<\/sub><\/em>, <em>g<sub>i<\/sub><\/em> is the net growth efficiency (production\/consumption ratio), <em>M0<sub>i<\/sub><\/em> the non-predation (\"other\") natural mortality rate, <em>F<sub>i<\/sub><\/em> is fishing mortality rate, <em>e<sub>i<\/sub><\/em> is emigration rate, <em>I<sub>i<\/sub><\/em> is immigration rate, (and <em>e<sub>i<\/sub>\u00b7B<sub>i<\/sub>-I<sub>i<\/sub><\/em> is the net migration rate). The two summations estimate consumption rates, the first expressing the total consumption by group <em>i<\/em>, and the second the predation by all predators <em>j<\/em> on the prey group.\r\n\r\nEcopath is used to provide the initial (t=0) biomasses, and some of the rate parameters (like MO).\u00a0 Ecosim parameters for the flow or consumption rates Q<sub>ij<\/sub> are set partly from Ecopath base estimates of those flows, with addition information needed to represent how the flow rates vary with biomasses and other circumstances.\r\n\r\nThe consumption rates, <em>Q<sub>ji<\/sub><\/em> and <em>Q<sub>ij<\/sub><\/em>, represent consumption by group <em>j<\/em> on <em>i<\/em> and by <em>i<\/em> on <em>j<\/em>, respectively, and are calculated based on foraging arena theory, where <em>B<sub>i<\/sub><\/em>\u2019s are divided into vulnerable and invulnerable components[footnote]Figure 1 in Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7:139-172. <a href=\"https:\/\/doi.org\/10.1023\/A:1018479526149\">https:\/\/doi.org\/10.1023\/A:1018479526149<\/a>[\/footnote], and it is the transfer rate (<em>v<sub>ij<\/sub><\/em>) between these two components that determines if control is top-down (i.e., Lotka-Volterra), bottom-up (i.e., donor-driven), or of an intermediate type. See the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/density-dependence-carrying-capacity-and-vulnerability-multipliers\/\">vulnerability multiplier<\/a> chapter.\r\n\r\nThe set of differential equations is solved in Ecosim using a 4<sup>th<\/sup> order Runge-Kutta routine (see the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/a-primer\/\">A primer on dynamic modelling<\/a> chapter).\u00a0 For groups like phytoplankton and small zooplankton that turn over (have <em>P\/B<\/em>) greater than 10 and are likely to exhibit boom-bust dynamics on time scales shorter than one month, the numerical integration prediction is replaced with a prediction based on the equilibrium of the Ecosim rate equation of the likely average over the month.\r\n<div class=\"textbox shaded\">\r\n\r\n<strong>Attribution <\/strong>This chapter is in part adapted from the unpublished EwE User Guide: Christensen V, C Walters, D Pauly, R Forrest. Ecopath with Ecosim. User Guide. November 2008.\r\n\r\n<\/div>","rendered":"<p>Ecosim provides a dynamic simulation capability at the ecosystem level, with key initial parameters inherited from the base Ecopath model.<\/p>\n<p>The key computational aspects are in summary form,<\/p>\n<ul>\n<li>Use of mass-balance results (from Ecopath) for parameter estimation;<\/li>\n<li>Variable speed splitting enables efficient modelling of the dynamics of both &#8220;fast&#8221; (e.g., phytoplankton) and &#8220;slow&#8221; groups (e.g., whales);<\/li>\n<li>Effects of micro-scale behaviours on macro-scale rates: top-down vs. bottom-up control incorporated explicitly.<\/li>\n<li>Includes biomass and size structure dynamics for key ecosystem groups, using a mix of differential and difference equations. As part of this EwE incorporates:<\/li>\n<li>Multi-stanza life stage structure by monthly cohorts, density- and risk-dependent growth \u2013 described in the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/age-structured-dynamics\/\">Age-structured dynamics<\/a> chapter;<\/li>\n<li>Stock-recruitment relationship as &#8220;emergent&#8221; property of competition\/predation interactions of juveniles.<\/li>\n<\/ul>\n<p>Ecosim uses a system of differential equations that expresses biomass flux rates among pools as a function of time varying biomass and harvest rates, (for equations see Walters et al., 1997<a class=\"footnote\" title=\"Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7:139-172.\" id=\"return-footnote-412-1\" href=\"#footnote-412-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a>; Walters et al., 2000<a class=\"footnote\" title=\"Walters, C.J., J.F. Kitchell, V. Christensen and D. Pauly. 2000. Representing density dependent consequences of life history strategies in aquatic ecosystems: Ecosim II. Ecosystems 3: 70-83.\" id=\"return-footnote-412-2\" href=\"#footnote-412-2\" aria-label=\"Footnote 2\"><sup class=\"footnote\">[2]<\/sup><\/a>; Christensen and Walters, 2004<a class=\"footnote\" title=\"Christensen, V. and C. J. Walters. 2004. Ecopath with Ecosim: methods, capabilities and limitations. Ecol. Model. 172:109-139\" id=\"return-footnote-412-3\" href=\"#footnote-412-3\" aria-label=\"Footnote 3\"><sup class=\"footnote\">[3]<\/sup><\/a>). Predator prey interactions are moderated by prey behaviour to limit exposure to predation, such that biomass flux patterns can show either bottom-up or top down (trophic cascade) control. By doing repeated simulations, Ecosim allows for the fitting of predicted biomasses to time series data.<\/p>\n<p>The simplest, default version of Ecosim represents biomass dynamics using a series of coupled differential equations. The equations are of the basic form:<\/p>\n<p style=\"text-align: left\">[latex]\\frac{dB_i}{dt}=g_i\\sum\\limits_{j=1}^{n}Q_{ij}-\\sum\\limits_{j=1}^{n}Q_{ji}+I_i-(F_i+e_i+M0_i) B_i\\tag{1}[\/latex]<\/p>\n<p>where <em>dB<sub>i<\/sub>\/dt<\/em> represents the growth rate during the time interval <em>dt<\/em> of group <em>i<\/em>\u00a0in terms of its biomass, <em>B<sub>i<\/sub><\/em>, <em>g<sub>i<\/sub><\/em> is the net growth efficiency (production\/consumption ratio), <em>M0<sub>i<\/sub><\/em> the non-predation (&#8220;other&#8221;) natural mortality rate, <em>F<sub>i<\/sub><\/em> is fishing mortality rate, <em>e<sub>i<\/sub><\/em> is emigration rate, <em>I<sub>i<\/sub><\/em> is immigration rate, (and <em>e<sub>i<\/sub>\u00b7B<sub>i<\/sub>-I<sub>i<\/sub><\/em> is the net migration rate). The two summations estimate consumption rates, the first expressing the total consumption by group <em>i<\/em>, and the second the predation by all predators <em>j<\/em> on the prey group.<\/p>\n<p>Ecopath is used to provide the initial (t=0) biomasses, and some of the rate parameters (like MO).\u00a0 Ecosim parameters for the flow or consumption rates Q<sub>ij<\/sub> are set partly from Ecopath base estimates of those flows, with addition information needed to represent how the flow rates vary with biomasses and other circumstances.<\/p>\n<p>The consumption rates, <em>Q<sub>ji<\/sub><\/em> and <em>Q<sub>ij<\/sub><\/em>, represent consumption by group <em>j<\/em> on <em>i<\/em> and by <em>i<\/em> on <em>j<\/em>, respectively, and are calculated based on foraging arena theory, where <em>B<sub>i<\/sub><\/em>\u2019s are divided into vulnerable and invulnerable components<a class=\"footnote\" title=\"Figure 1 in Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7:139-172. https:\/\/doi.org\/10.1023\/A:1018479526149\" id=\"return-footnote-412-4\" href=\"#footnote-412-4\" aria-label=\"Footnote 4\"><sup class=\"footnote\">[4]<\/sup><\/a>, and it is the transfer rate (<em>v<sub>ij<\/sub><\/em>) between these two components that determines if control is top-down (i.e., Lotka-Volterra), bottom-up (i.e., donor-driven), or of an intermediate type. See the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/density-dependence-carrying-capacity-and-vulnerability-multipliers\/\">vulnerability multiplier<\/a> chapter.<\/p>\n<p>The set of differential equations is solved in Ecosim using a 4<sup>th<\/sup> order Runge-Kutta routine (see the <a href=\"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/a-primer\/\">A primer on dynamic modelling<\/a> chapter).\u00a0 For groups like phytoplankton and small zooplankton that turn over (have <em>P\/B<\/em>) greater than 10 and are likely to exhibit boom-bust dynamics on time scales shorter than one month, the numerical integration prediction is replaced with a prediction based on the equilibrium of the Ecosim rate equation of the likely average over the month.<\/p>\n<div class=\"textbox shaded\">\n<p><strong>Attribution <\/strong>This chapter is in part adapted from the unpublished EwE User Guide: Christensen V, C Walters, D Pauly, R Forrest. Ecopath with Ecosim. User Guide. November 2008.<\/p>\n<\/div>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-412-1\">Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. <a href=\"https:\/\/link.springer.com\/article\/10.1023\/A:1018479526149\">Reviews in Fish Biology and Fisheries<\/a> 7:139-172. <a href=\"#return-footnote-412-1\" class=\"return-footnote\" aria-label=\"Return to footnote 1\">&crarr;<\/a><\/li><li id=\"footnote-412-2\">Walters, C.J., J.F. Kitchell, V. Christensen and D. Pauly. 2000. Representing density dependent consequences of life history strategies in aquatic ecosystems: Ecosim II. <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s100210000011\">Ecosystems<\/a> 3: 70-83. <a href=\"#return-footnote-412-2\" class=\"return-footnote\" aria-label=\"Return to footnote 2\">&crarr;<\/a><\/li><li id=\"footnote-412-3\">Christensen, V. and C. J. Walters. 2004. Ecopath with Ecosim: methods, capabilities and limitations. <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S030438000300365X\">Ecol. Model.<\/a> 172:109-139 <a href=\"#return-footnote-412-3\" class=\"return-footnote\" aria-label=\"Return to footnote 3\">&crarr;<\/a><\/li><li id=\"footnote-412-4\">Figure 1 in Walters, C., V. Christensen and D. Pauly. 1997. Structuring dynamic models of exploited ecosystems from trophic mass-balance assessments. Reviews in Fish Biology and Fisheries 7:139-172. <a href=\"https:\/\/doi.org\/10.1023\/A:1018479526149\">https:\/\/doi.org\/10.1023\/A:1018479526149<\/a> <a href=\"#return-footnote-412-4\" class=\"return-footnote\" aria-label=\"Return to footnote 4\">&crarr;<\/a><\/li><\/ol><\/div>","protected":false},"author":1909,"menu_order":3,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-412","chapter","type-chapter","status-publish","hentry"],"part":411,"_links":{"self":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/412","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":25,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/412\/revisions"}],"predecessor-version":[{"id":2838,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/412\/revisions\/2838"}],"part":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/parts\/411"}],"metadata":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapters\/412\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/media?parent=412"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/pressbooks\/v2\/chapter-type?post=412"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/contributor?post=412"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/wp-json\/wp\/v2\/license?post=412"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}