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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta name="generator" content="pandoc" />
<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
<meta name="author" content="Marta Cousido Rocha, Santiago Cerviño López, Maria Grazia Pennino" />
<title>Rfishpop (Fourth tutorial)</title>
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) 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P5wEBABkBAXAcIVHfzgDwr+ogoPDwoBXgoPDwqvrwoPAAMAFwAXBJkEmQAPABsAMQAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JgUzMhYVETMyFgcDBiInAyY2OwERNDYB4+rWm1tbm9bq1ptbW5sBv+jFcnLF6MVycv58lgoPiRUKDd8NJg3fDQoViQ8EmVub1urWm1tbm9bq1ps7csXoxXJyxejFDQ8K/u0XEP7tEBABExAXARMKDwAAAAMAFwAXBJkEmQAPABsAMQAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JiUTFgYrAREUBisBIiY1ESMiJjcTNjIB4+rWm1tbm9bq1ptbW5sBv+jFcnLF6MVycv7n3w0KFYkPCpYKD4kVCg3fDSYEmVub1urWm1tbm9bq1ps7csXoxXJyxejFAf7tEBf+7QoPDwoBExcQARMQAAAAAAIAAAAABLAEsAAZADkAABMhMhYXExYVERQGBwYjISImJyY1EzQ3Ez4BBSEiBgcDBhY7ATIWHwEeATsBMjY/AT4BOwEyNicDLgHhAu4KEwO6BwgFDBn7tAweAgYBB7kDEwKX/dQKEgJXAgwKlgoTAiYCEwr6ChMCJgITCpYKDAJXAhIEsA4K/XQYGf5XDB4CBggEDRkBqRkYAowKDsgOC/4+Cw4OCpgKDg4KmAoODgsBwgsOAAMAFwAXBJkEmQAPABsAJwAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JgUXFhQPAQYmNRE0NgHj6tabW1ub1urWm1tbmwG/6MVycsXoxXJy/ov9ERH9EBgYBJlbm9bq1ptbW5vW6tabO3LF6MVycsXoxV2+DCQMvgwLFQGQFQsAAQAXABcEmQSwACgAAAE3NhYVERQGIyEiJj8BJiMiDgEUHgEyPgE1MxQOAiIuAjQ+AjMyA7OHBwsPCv6WCwQHhW2BdMVycsXoxXKWW5vW6tabW1ub1nXABCSHBwQL/pYKDwsHhUxyxejFcnLFdHXWm1tbm9bq1ptbAAAAAAIAFwABBJkEsAAaADUAAAE3NhYVERQGIyEiJj8BJiMiDgEVIzQ+AjMyEzMUDgIjIicHBiY1ETQ2MyEyFg8BFjMyPgEDs4cHCw8L/pcLBAeGboF0xXKWW5vWdcDrllub1nXAnIYHCw8LAWgKBQiFboJ0xXIEJIcHBAv+lwsPCweGS3LFdHXWm1v9v3XWm1t2hggFCgFoCw8LB4VMcsUAAAAKAGQAAASwBLAADwAfAC8APwBPAF8AbwB/AI8AnwAAEyEyFhURFAYjISImNRE0NgUhIgYVERQWMyEyNjURNCYFMzIWHQEUBisBIiY9ATQ2MyEyFh0BFAYjISImPQE0NgczMhYdARQGKwEiJj0BNDYzITIWHQEUBiMhIiY9ATQ2BzMyFh0BFAYrASImPQE0NjMhMhYdARQGIyEiJj0BNDYHMzIWHQEUBisBIiY9ATQ2MyEyFh0BFAYjISImPQE0Nn0EGgoPDwr75goPDwPA/K4KDw8KA1IKDw/9CDIKDw8KMgoPD9IBwgoPDwr+PgoPD74yCg8PCjIKDw/SAcIKDw8K/j4KDw++MgoPDwoyCg8P0gHCCg8PCv4+Cg8PvjIKDw8KMgoPD9IBwgoPDwr+PgoPDwSwDwr7ggoPDwoEfgoPyA8K/K4KDw8KA1IKD2QPCjIKDw8KMgoPDwoyCg8PCjIKD8gPCjIKDw8KMgoPDwoyCg8PCjIKD8gPCjIKDw8KMgoPDwoyCg8PCjIKD8gPCjIKDw8KMgoPDwoyCg8PCjIKDwAAAAACAAAAAARMBLAAGQAjAAABNTQmIyEiBh0BIyIGFREUFjMhMjY1ETQmIyE1NDY7ATIWHQEDhHVT/tRSdmQpOzspA4QpOzsp/ageFMgUHgMgyFN1dlLIOyn9qCk7OykCWCk7lhUdHRWWAAIAZAAABEwETAAJADcAABMzMhYVESMRNDYFMhcWFREUBw4DIyIuAScuAiMiBwYjIicmNRE+ATc2HgMXHgIzMjc2fTIKD2QPA8AEBRADIUNAMRwaPyonKSxHHlVLBwgGBQ4WeDsXKC4TOQQpLUUdZ1AHBEwPCvvNBDMKDzACBhH+WwYGO1AkDQ0ODg8PDzkFAwcPAbY3VwMCAwsGFAEODg5XCAAAAwAAAAAEsASXACEAMQBBAAAAMh4CFREUBisBIiY1ETQuASAOARURFAYrASImNRE0PgEDMzIWFREUBisBIiY1ETQ2ITMyFhURFAYrASImNRE0NgHk6N6jYw8KMgoPjeT++uSNDwoyCg9joyqgCAwMCKAIDAwCYKAIDAwIoAgMDASXY6PedP7UCg8PCgEsf9FyctF//tQKDw8KASx03qP9wAwI/jQIDAwIAcwIDAwI/jQIDAwIAcwIDAAAAAACAAAA0wRHA90AFQA5AAABJTYWFREUBiclJisBIiY1ETQ2OwEyBTc2Mh8BFhQPARcWFA8BBiIvAQcGIi8BJjQ/AScmND8BNjIXAUEBAgkMDAn+/hUZ+goPDwr6GQJYeAcUByIHB3h4BwciBxQHeHgHFAciBwd3dwcHIgcUBwMurAYHCv0SCgcGrA4PCgFeCg+EeAcHIgcUB3h4BxQHIgcHd3cHByIHFAd4eAcUByIICAAAAAACAAAA0wNyA90AFQAvAAABJTYWFREUBiclJisBIiY1ETQ2OwEyJTMWFxYVFAcGDwEiLwEuATc2NTQnJjY/ATYBQQECCQwMCf7+FRn6Cg8PCvoZAdIECgZgWgYLAwkHHQcDBkhOBgMIHQcDLqwGBwr9EgoHBqwODwoBXgoPZAEJgaGafwkBAQYXBxMIZ36EaggUBxYFAAAAAAMAAADEBGID7AAbADEASwAAATMWFxYVFAYHBgcjIi8BLgE3NjU0JicmNj8BNgUlNhYVERQGJyUmKwEiJjURNDY7ATIlMxYXFhUUBwYPASIvAS4BNzY1NCcmNj8BNgPHAwsGh0RABwoDCQcqCAIGbzs3BgIJKgf9ggECCQwMCf7+FRn6Cg8PCvoZAdIECgZgWgYLAwkHHQcDBkhOBgMIHQcD7AEJs9lpy1QJAQYiBhQIlrJarEcJFAYhBb6sBgcK/RIKBwasDg8KAV4KD2QBCYGhmn8JAQEGFwcTCGd+hGoIFQYWBQAAAAANAAAAAASwBLAACQAVABkAHQAhACUALQA7AD8AQwBHAEsATwAAATMVIxUhFSMRIQEjFTMVIREjESM1IQURIREhESERBSM1MwUjNTMBMxEhETM1MwEzFSMVIzUjNTM1IzUhBREhEQcjNTMFIzUzASM1MwUhNSEB9GRk/nBkAfQCvMjI/tTIZAJY+7QBLAGQASz84GRkArxkZP1EyP4MyGQB9MhkyGRkyAEs/UQBLGRkZAOEZGT+DGRkAfT+1AEsA4RkZGQCWP4MZMgBLAEsyGT+1AEs/tQBLMhkZGT+DP4MAfRk/tRkZGRkyGTI/tQBLMhkZGT+1GRkZAAAAAAJAAAAAASwBLAAAwAHAAsADwATABcAGwAfACMAADcjETMTIxEzASMRMxMjETMBIxEzASE1IRcjNTMXIzUzBSM1M2RkZMhkZAGQyMjIZGQBLMjI/OD+1AEsyGRkyGRkASzIyMgD6PwYA+j8GAPo/BgD6PwYA+j7UGRkW1tbW1sAAAIAAAAKBKYEsAANABUAAAkBFhQHAQYiJwETNDYzBCYiBhQWMjYB9AKqCAj+MAgUCP1WAQ8KAUM7Uzs7UzsEsP1WCBQI/jAICAKqAdsKD807O1Q7OwAAAAADAAAACgXSBLAADQAZACEAAAkBFhQHAQYiJwETNDYzIQEWFAcBBiIvAQkBBCYiBhQWMjYB9AKqCAj+MAgUCP1WAQ8KAwYCqggI/jAIFAg4Aaj9RP7TO1M7O1M7BLD9VggUCP4wCAgCqgHbCg/9VggUCP4wCAg4AaoCvM07O1Q7OwAAAAABAGQAAASwBLAAJgAAASEyFREUDwEGJjURNCYjISIPAQYWMyEyFhURFAYjISImNRE0PwE2ASwDOUsSQAgKDwr9RBkSQAgFCgK8Cg8PCvyuCg8SixIEsEv8fBkSQAgFCgO2Cg8SQAgKDwr8SgoPDwoDzxkSixIAAAABAMj//wRMBLAACgAAEyEyFhURCQERNDb6AyAVHf4+/j4dBLAdFfuCAbz+QwR/FR0AAAAAAwAAAAAEsASwABUARQBVAAABISIGBwMGHwEeATMhMjY/ATYnAy4BASMiBg8BDgEjISImLwEuASsBIgYVERQWOwEyNj0BNDYzITIWHQEUFjsBMjY1ETQmASEiBg8BBhYzITI2LwEuAQM2/kQLEAFOBw45BhcKAcIKFwY+DgdTARABVpYKFgROBBYK/doKFgROBBYKlgoPDwqWCg8PCgLuCg8PCpYKDw/+sf4MChMCJgILCgJYCgsCJgITBLAPCv7TGBVsCQwMCWwVGAEtCg/+cA0JnAkNDQmcCQ0PCv12Cg8PCpYKDw8KlgoPDwoCigoP/agOCpgKDg4KmAoOAAAAAAQAAABkBLAETAAdACEAKQAxAAABMzIeAh8BMzIWFREUBiMhIiY1ETQ2OwE+BAEVMzUEIgYUFjI2NCQyFhQGIiY0AfTIOF00JAcGlik7Oyn8GCk7OymWAgknM10ByGT+z76Hh76H/u9WPDxWPARMKTs7FRQ7Kf2oKTs7KQJYKTsIG0U1K/7UZGRGh76Hh74IPFY8PFYAAAAAAgA1AAAEsASvACAAIwAACQEWFx4BHwEVITUyNi8BIQYHBh4CMxUhNTY3PgE/AQEDIQMCqQGBFCgSJQkK/l81LBFS/nk6IgsJKjIe/pM4HAwaBwcBj6wBVKIEr/waMioTFQECQkJXLd6RWSIuHAxCQhgcDCUNDQPu/VoByQAAAAADAGQAAAPwBLAAJwAyADsAAAEeBhUUDgMjITU+ATURNC4EJzUFMh4CFRQOAgclMzI2NTQuAisBETMyNjU0JisBAvEFEzUwOyodN1htbDD+DCk7AQYLFyEaAdc5dWM+Hy0tEP6Pi05pESpTPnbYUFJ9Xp8CgQEHGB0zOlIuQ3VONxpZBzMoAzsYFBwLEAkHRwEpSXNDM1s6KwkxYUopOzQb/K5lUFqBAAABAMgAAANvBLAAGQAAARcOAQcDBhYXFSE1NjcTNjQuBCcmJzUDbQJTQgeECSxK/gy6Dq0DAw8MHxUXDQYEsDkTNSj8uTEoBmFhEFIDQBEaExAJCwYHAwI5AAAAAAL/tQAABRQEsAAlAC8AAAEjNC4FKwERFBYfARUhNTI+AzURIyIOBRUjESEFIxEzByczESM3BRQyCAsZEyYYGcgyGRn+cAQOIhoWyBkYJhMZCwgyA+j7m0tLfX1LS30DhBUgFQ4IAwH8rhYZAQJkZAEFCRUOA1IBAwgOFSAVASzI/OCnpwMgpwACACH/tQSPBLAAJQAvAAABIzQuBSsBERQWHwEVITUyPgM1ESMiDgUVIxEhEwc1IRUnNxUhNQRMMggLGRMmGBnIMhkZ/nAEDiIaFsgZGCYTGQsIMgPoQ6f84KenAyADhBUgFQ4IAwH9dhYZAQJkZAEFCRUOAooBAwgOFSAVASz7gn1LS319S0sABAAAAAAEsARMAA8AHwAvAD8AABMhMhYdARQGIyEiJj0BNDYTITIWHQEUBiMhIiY9ATQ2EyEyFh0BFAYjISImPQE0NhMhMhYdARQGIyEiJj0BNDYyAlgVHR0V/agVHR0VA+gVHR0V/BgVHR0VAyAVHR0V/OAVHR0VBEwVHR0V+7QVHR0ETB0VZBUdHRVkFR3+1B0VZBUdHRVkFR3+1B0VZBUdHRVkFR3+1B0VZBUdHRVkFR0ABAAAAAAEsARMAA8AHwAvAD8AABMhMhYdARQGIyEiJj0BNDYDITIWHQEUBiMhIiY9ATQ2EyEyFh0BFAYjISImPQE0NgMhMhYdARQGIyEiJj0BNDb6ArwVHR0V/UQVHR2zBEwVHR0V+7QVHR3dArwVHR0V/UQVHR2zBEwVHR0V+7QVHR0ETB0VZBUdHRVkFR3+1B0VZBUdHRVkFR3+1B0VZBUdHRVkFR3+1B0VZBUdHRVkFR0ABAAAAAAEsARMAA8AHwAvAD8AAAE1NDYzITIWHQEUBiMhIiYBNTQ2MyEyFh0BFAYjISImEzU0NjMhMhYdARQGIyEiJgE1NDYzITIWHQEUBiMhIiYB9B0VAlgVHR0V/agVHf5wHRUD6BUdHRX8GBUdyB0VAyAVHR0V/OAVHf7UHRUETBUdHRX7tBUdA7ZkFR0dFWQVHR3+6WQVHR0VZBUdHf7pZBUdHRVkFR0d/ulkFR0dFWQVHR0AAAQAAAAABLAETAAPAB8ALwA/AAATITIWHQEUBiMhIiY9ATQ2EyEyFh0BFAYjISImPQE0NhMhMhYdARQGIyEiJj0BNDYTITIWHQEUBiMhIiY9ATQ2MgRMFR0dFfu0FR0dFQRMFR0dFfu0FR0dFQRMFR0dFfu0FR0dFQRMFR0dFfu0FR0dBEwdFWQVHR0VZBUd/tQdFWQVHR0VZBUd/tQdFWQVHR0VZBUd/tQdFWQVHR0VZBUdAAgAAAAABLAETAAPAB8ALwA/AE8AXwBvAH8AABMzMhYdARQGKwEiJj0BNDYpATIWHQEUBiMhIiY9ATQ2ATMyFh0BFAYrASImPQE0NikBMhYdARQGIyEiJj0BNDYBMzIWHQEUBisBIiY9ATQ2KQEyFh0BFAYjISImPQE0NgEzMhYdARQGKwEiJj0BNDYpATIWHQEUBiMhIiY9ATQ2MmQVHR0VZBUdHQFBAyAVHR0V/OAVHR3+6WQVHR0VZBUdHQFBAyAVHR0V/OAVHR3+6WQVHR0VZBUdHQFBAyAVHR0V/OAVHR3+6WQVHR0VZBUdHQFBAyAVHR0V/OAVHR0ETB0VZBUdHRVkFR0dFWQVHR0VZBUd/tQdFWQVHR0VZBUdHRVkFR0dFWQVHf7UHRVkFR0dFWQVHR0VZBUdHRVkFR3+1B0VZBUdHRVkFR0dFWQVHR0VZBUdAAAG/5wAAASwBEwAAwATACMAKgA6AEoAACEjETsCMhYdARQGKwEiJj0BNDYTITIWHQEUBiMhIiY9ATQ2BQc1IzUzNQUhMhYdARQGIyEiJj0BNDYTITIWHQEUBiMhIiY9ATQ2AZBkZJZkFR0dFWQVHR0VAfQVHR0V/gwVHR3++qfIyAHCASwVHR0V/tQVHR0VAlgVHR0V/agVHR0ETB0VZBUdHRVkFR3+1B0VZBUdHRVkFR36fUtkS68dFWQVHR0VZBUd/tQdFWQVHR0VZBUdAAAABgAAAAAFFARMAA8AEwAjACoAOgBKAAATMzIWHQEUBisBIiY9ATQ2ASMRMwEhMhYdARQGIyEiJj0BNDYFMxUjFSc3BSEyFh0BFAYjISImPQE0NhMhMhYdARQGIyEiJj0BNDYyZBUdHRVkFR0dA2dkZPyuAfQVHR0V/gwVHR0EL8jIp6f75gEsFR0dFf7UFR0dFQJYFR0dFf2oFR0dBEwdFWQVHR0VZBUd+7QETP7UHRVkFR0dFWQVHchkS319rx0VZBUdHRVkFR3+1B0VZBUdHRVkFR0AAAAAAgAAAMgEsAPoAA8AEgAAEyEyFhURFAYjISImNRE0NgkCSwLuHywsH/0SHywsBIT+1AEsA+gsH/12HywsHwKKHyz9RAEsASwAAwAAAAAEsARMAA8AFwAfAAATITIWFREUBiMhIiY1ETQ2FxE3BScBExEEMhYUBiImNCwEWBIaGhL7qBIaGkr3ASpKASXs/NJwTk5wTgRMGhL8DBIaGhID9BIaZP0ftoOcAT7+4AH0dE5vT09vAAAAAAIA2wAFBDYEkQAWAB4AAAEyHgEVFAcOAQ8BLgQnJjU0PgIWIgYUFjI2NAKIdcZzRkWyNjYJIV5YbSk8RHOft7eCgreCBJF4ynVzj23pPz4IIWZomEiEdVijeUjDgriBgbgAAAACABcAFwSZBJkADwAXAAAAMh4CFA4CIi4CND4BAREiDgEUHgEB4+rWm1tbm9bq1ptbW5sBS3TFcnLFBJlbm9bq1ptbW5vW6tab/G8DVnLF6MVyAAACAHUAAwPfBQ8AGgA1AAABHgYVFA4DBy4DNTQ+BQMOAhceBBcWNj8BNiYnLgInJjc2IyYCKhVJT1dOPiUzVnB9P1SbfEokP0xXUEm8FykoAwEbITEcExUWAgYCCQkFEikMGiACCAgFD0iPdXdzdYdFR4BeRiYEBTpjl1lFh3ZzeHaQ/f4hS4I6JUEnIw4IBwwQIgoYBwQQQSlZtgsBAAAAAwAAAAAEywRsAAwAKgAvAAABNz4CHgEXHgEPAiUhMhcHISIGFREUFjMhMjY9ATcRFAYjISImNRE0NgkBBzcBA+hsAgYUFR0OFgoFBmz9BQGQMje7/pApOzspAfQpO8i7o/5wpbm5Azj+lqE3AWMD9XMBAgIEDw4WKgsKc8gNuzsp/gwpOzsptsj+tKW5uaUBkKW5/tf+ljKqAWMAAgAAAAAEkwRMABsANgAAASEGByMiBhURFBYzITI2NTcVFAYjISImNRE0NgUBFhQHAQYmJzUmDgMHPgY3NT4BAV4BaaQ0wyk7OykB9Ck7yLml/nClubkCfwFTCAj+rAcLARo5ZFRYGgouOUlARioTAQsETJI2Oyn+DCk7OymZZ6W5uaUBkKW5G/7TBxUH/s4GBAnLAQINFjAhO2JBNB0UBwHSCgUAAAAAAgAAAAAEnQRMAB0ANQAAASEyFwchIgYVERQWMyEyNj0BNxUUBiMhIiY1ETQ2CQE2Mh8BFhQHAQYiLwEmND8BNjIfARYyAV4BXjxDsv6jKTs7KQH0KTvIuaX+cKW5uQHKAYsHFQdlBwf97QcVB/gHB2UHFQdvCBQETBexOyn+DCk7OylFyNulubmlAZCluf4zAYsHB2UHFQf97AcH+AcVB2UHB28HAAAAAQAKAAoEpgSmADsAAAkBNjIXARYGKwEVMzU0NhcBFhQHAQYmPQEjFTMyFgcBBiInASY2OwE1IxUUBicBJjQ3ATYWHQEzNSMiJgE+AQgIFAgBBAcFCqrICggBCAgI/vgICsiqCgUH/vwIFAj++AgFCq/ICgj++AgIAQgICsivCgUDlgEICAj++AgKyK0KBAf+/AcVB/73BwQKrcgKCP74CAgBCAgKyK0KBAcBCQcVBwEEBwQKrcgKAAEAyAAAA4QETAAZAAATMzIWFREBNhYVERQGJwERFAYrASImNRE0NvpkFR0B0A8VFQ/+MB0VZBUdHQRMHRX+SgHFDggV/BgVCA4Bxf5KFR0dFQPoFR0AAAABAAAAAASwBEwAIwAAEzMyFhURATYWFREBNhYVERQGJwERFAYnAREUBisBIiY1ETQ2MmQVHQHQDxUB0A8VFQ/+MBUP/jAdFWQVHR0ETB0V/koBxQ4IFf5KAcUOCBX8GBUIDgHF/koVCA4Bxf5KFR0dFQPoFR0AAAABAJ0AGQSwBDMAFQAAAREUBicBERQGJwEmNDcBNhYVEQE2FgSwFQ/+MBUP/hQPDwHsDxUB0A8VBBr8GBUIDgHF/koVCA4B4A4qDgHgDggV/koBxQ4IAAAAAQDIABYEMwQ2AAsAABMBFhQHAQYmNRE0NvMDLhIS/NISGRkEMv4OCx4L/g4LDhUD6BUOAAIAyABkA4QD6AAPAB8AABMzMhYVERQGKwEiJjURNDYhMzIWFREUBisBIiY1ETQ2+sgVHR0VyBUdHQGlyBUdHRXIFR0dA+gdFfzgFR0dFQMgFR0dFfzgFR0dFQMgFR0AAAEAyABkBEwD6AAPAAABERQGIyEiJjURNDYzITIWBEwdFfzgFR0dFQMgFR0DtvzgFR0dFQMgFR0dAAAAAAEAAAAZBBMEMwAVAAABETQ2FwEWFAcBBiY1EQEGJjURNDYXAfQVDwHsDw/+FA8V/jAPFRUPAmQBthUIDv4gDioO/iAOCBUBtv47DggVA+gVCA4AAAH//gACBLMETwAjAAABNzIWFRMUBiMHIiY1AwEGJjUDAQYmNQM0NhcBAzQ2FwEDNDYEGGQUHgUdFWQVHQL+MQ4VAv4yDxUFFQ8B0gIVDwHSAh0ETgEdFfwYFR0BHRUBtf46DwkVAbX+OQ4JFAPoFQkP/j4BthQJDv49AbYVHQAAAQEsAAAD6ARMABkAAAEzMhYVERQGKwEiJjURAQYmNRE0NhcBETQ2A1JkFR0dFWQVHf4wDxUVDwHQHQRMHRX8GBUdHRUBtv47DggVA+gVCA7+OwG2FR0AAAIAZADIBLAESAALABsAAAkBFgYjISImNwE2MgEhMhYdARQGIyEiJj0BNDYCrgH1DwkW++4WCQ8B9Q8q/fcD6BUdHRX8GBUdHQQ5/eQPFhYPAhwP/UgdFWQVHR0VZBUdAAEAiP/8A3UESgAFAAAJAgcJAQN1/qABYMX92AIoA4T+n/6fxgIoAiYAAAAAAQE7//wEKARKAAUAAAkBJwkBNwQo/dnGAWH+n8YCI/3ZxgFhAWHGAAIAFwAXBJkEmQAPADMAAAAyHgIUDgIiLgI0PgEFIyIGHQEjIgYdARQWOwEVFBY7ATI2PQEzMjY9ATQmKwE1NCYB4+rWm1tbm9bq1ptbW5sBfWQVHZYVHR0Vlh0VZBUdlhUdHRWWHQSZW5vW6tabW1ub1urWm7odFZYdFWQVHZYVHR0Vlh0VZBUdlhUdAAAAAAIAFwAXBJkEmQAPAB8AAAAyHgIUDgIiLgI0PgEBISIGHQEUFjMhMjY9ATQmAePq1ptbW5vW6tabW1ubAkX+DBUdHRUB9BUdHQSZW5vW6tabW1ub1urWm/5+HRVkFR0dFWQVHQACABcAFwSZBJkADwAzAAAAMh4CFA4CIi4CND4BBCIPAScmIg8BBhQfAQcGFB8BFjI/ARcWMj8BNjQvATc2NC8BAePq1ptbW5vW6tabW1ubAeUZCXh4CRkJjQkJeHgJCY0JGQl4eAkZCY0JCXh4CQmNBJlbm9bq1ptbW5vW6tabrQl4eAkJjQkZCXh4CRkJjQkJeHgJCY0JGQl4eAkZCY0AAgAXABcEmQSZAA8AJAAAADIeAhQOAiIuAjQ+AQEnJiIPAQYUHwEWMjcBNjQvASYiBwHj6tabW1ub1urWm1tbmwEVVAcVCIsHB/IHFQcBdwcHiwcVBwSZW5vW6tabW1ub1urWm/4xVQcHiwgUCPEICAF3BxUIiwcHAAAAAAMAFwAXBJkEmQAPADsASwAAADIeAhQOAiIuAjQ+AQUiDgMVFDsBFjc+ATMyFhUUBgciDgUHBhY7ATI+AzU0LgMTIyIGHQEUFjsBMjY9ATQmAePq1ptbW5vW6tabW1ubAT8dPEIyIRSDHgUGHR8UFw4TARkOGhITDAIBDQ6tBx4oIxgiM0Q8OpYKDw8KlgoPDwSZW5vW6tabW1ub1urWm5ELHi9PMhkFEBQQFRIXFgcIBw4UHCoZCBEQKDhcNi9IKhsJ/eMPCpYKDw8KlgoPAAADABcAFwSZBJkADwAfAD4AAAAyHgIUDgIiLgI0PgEFIyIGHQEUFjsBMjY9ATQmAyMiBh0BFBY7ARUjIgYdARQWMyEyNj0BNCYrARE0JgHj6tabW1ub1urWm1tbmwGWlgoPDwqWCg8PCvoKDw8KS0sKDw8KAV4KDw8KSw8EmVub1urWm1tbm9bq1ptWDwqWCg8PCpYKD/7UDwoyCg/IDwoyCg8PCjIKDwETCg8AAgAAAAAEsASwAC8AXwAAATMyFh0BHgEXMzIWHQEUBisBDgEHFRQGKwEiJj0BLgEnIyImPQE0NjsBPgE3NTQ2ExUUBisBIiY9AQ4BBzMyFh0BFAYrAR4BFzU0NjsBMhYdAT4BNyMiJj0BNDY7AS4BAg2WCg9nlxvCCg8PCsIbl2cPCpYKD2eXG8IKDw8KwhuXZw+5DwqWCg9EZheoCg8PCqgXZkQPCpYKD0RmF6gKDw8KqBdmBLAPCsIbl2cPCpYKD2eXG8IKDw8KwhuXZw8KlgoPZ5cbwgoP/s2oCg8PCqgXZkQPCpYKD0RmF6gKDw8KqBdmRA8KlgoPRGYAAwAXABcEmQSZAA8AGwA/AAAAMh4CFA4CIi4CND4BBCIOARQeATI+ATQmBxcWFA8BFxYUDwEGIi8BBwYiLwEmND8BJyY0PwE2Mh8BNzYyAePq1ptbW5vW6tabW1ubAb/oxXJyxejFcnKaQAcHfHwHB0AHFQd8fAcVB0AHB3x8BwdABxUHfHwHFQSZW5vW6tabW1ub1urWmztyxejFcnLF6MVaQAcVB3x8BxUHQAcHfHwHB0AHFQd8fAcVB0AHB3x8BwAAAAMAFwAXBJkEmQAPABsAMAAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JgcXFhQHAQYiLwEmND8BNjIfATc2MgHj6tabW1ub1urWm1tbmwG/6MVycsXoxXJyg2oHB/7ACBQIyggIagcVB0/FBxUEmVub1urWm1tbm9bq1ps7csXoxXJyxejFfWoHFQf+vwcHywcVB2oICE/FBwAAAAMAFwAXBJkEmQAPABgAIQAAADIeAhQOAiIuAjQ+AQUiDgEVFBcBJhcBFjMyPgE1NAHj6tabW1ub1urWm1tbmwFLdMVyQQJLafX9uGhzdMVyBJlbm9bq1ptbW5vW6tabO3LFdHhpAktB0P24PnLFdHMAAAAAAQAXAFMEsAP5ABUAABMBNhYVESEyFh0BFAYjIREUBicBJjQnAgoQFwImFR0dFf3aFxD99hACRgGrDQoV/t0dFcgVHf7dFQoNAasNJgAAAAABAAAAUwSZA/kAFQAACQEWFAcBBiY1ESEiJj0BNDYzIRE0NgJ/AgoQEP32EBf92hUdHRUCJhcD8f5VDSYN/lUNChUBIx0VyBUdASMVCgAAAAEAtwAABF0EmQAVAAAJARYGIyERFAYrASImNREhIiY3ATYyAqoBqw0KFf7dHRXIFR3+3RUKDQGrDSYEif32EBf92hUdHRUCJhcQAgoQAAAAAQC3ABcEXQSwABUAAAEzMhYVESEyFgcBBiInASY2MyERNDYCJsgVHQEjFQoN/lUNJg3+VQ0KFQEjHQSwHRX92hcQ/fYQEAIKEBcCJhUdAAABAAAAtwSZBF0AFwAACQEWFAcBBiY1EQ4DBz4ENxE0NgJ/AgoQEP32EBdesKWBJAUsW4fHfhcEVf5VDSYN/lUNChUBIwIkRHVNabGdcUYHAQYVCgACAAAAAASwBLAAFQArAAABITIWFREUBi8BBwYiLwEmND8BJyY2ASEiJjURNDYfATc2Mh8BFhQPARcWBgNSASwVHRUOXvkIFAhqBwf5Xg4I/iH+1BUdFQ5e+QgUCGoHB/leDggEsB0V/tQVCA5e+QcHaggUCPleDhX7UB0VASwVCA5e+QcHaggUCPleDhUAAAACAEkASQRnBGcAFQArAAABFxYUDwEXFgYjISImNRE0Nh8BNzYyASEyFhURFAYvAQcGIi8BJjQ/AScmNgP2agcH+V4OCBX+1BUdFQ5e+QgU/QwBLBUdFQ5e+QgUCGoHB/leDggEYGoIFAj5Xg4VHRUBLBUIDl75B/3xHRX+1BUIDl75BwdqCBQI+V4OFQAAAAADABcAFwSZBJkADwAfAC8AAAAyHgIUDgIiLgI0PgEFIyIGFxMeATsBMjY3EzYmAyMiBh0BFBY7ATI2PQE0JgHj6tabW1ub1urWm1tbmwGz0BQYBDoEIxQ2FCMEOgQYMZYKDw8KlgoPDwSZW5vW6tabW1ub1urWm7odFP7SFB0dFAEuFB3+DA8KlgoPDwqWCg8AAAAABQAAAAAEsASwAEkAVQBhAGgAbwAAATIWHwEWHwEWFxY3Nj8BNjc2MzIWHwEWHwIeATsBMhYdARQGKwEiBh0BIREjESE1NCYrASImPQE0NjsBMjY1ND8BNjc+BAUHBhY7ATI2LwEuAQUnJgYPAQYWOwEyNhMhIiY1ESkBERQGIyERAQQJFAUFFhbEFQ8dCAsmxBYXERUXMA0NDgQZCAEPCj0KDw8KMgoP/nDI/nAPCjIKDw8KPQsOCRkFDgIGFRYfAp2mBwQK2woKAzMDEP41sQgQAzMDCgrnCwMe/okKDwGQAlgPCv6JBLAEAgIKDXYNCxUJDRZ2DQoHIREQFRh7LAkLDwoyCg8PCq8BLP7UrwoPDwoyCg8GBQQwgBkUAwgWEQ55ogcKDgqVCgSqnQcECo8KDgr8cg8KAXf+iQoPAZAAAAAAAgAAAAwErwSmACsASQAAATYWFQYCDgQuAScmByYOAQ8BBiY1NDc+ATc+AScuAT4BNz4GFyYGBw4BDwEOBAcOARY2Nz4CNz4DNz4BBI0IGgItQmxhi2KORDg9EQQRMxuZGhYqCFUYEyADCQIQOjEnUmFch3vAJQgdHyaiPT44XHRZUhcYDhItIRmKcVtGYWtbKRYEBKYDEwiy/t3IlVgxEQgLCwwBAQIbG5kYEyJAJghKFRE8Hzdff4U/M0o1JSMbL0QJGCYvcSEhHjZST2c1ODwEJygeW0AxJUBff1UyFAABAF0AHgRyBM8ATwAAAQ4BHgQXLgc+ATceAwYHDgQHBicmNzY3PgQuAScWDgMmJy4BJyY+BDcGHgM3PgEuAicmPgMCjScfCic4R0IgBBsKGAoQAwEJEg5gikggBhANPkpTPhZINx8SBgsNJysiCRZOQQoVNU1bYC9QZwICBAUWITsoCAYdJzIYHw8YIiYHDyJJYlkEz0OAZVxEOSQMBzgXOB42IzElKRIqg5Gnl0o3Z0c6IAYWCwYNAwQFIDhHXGF1OWiqb0sdBxUknF0XNTQ8PEUiNWNROBYJDS5AQVUhVZloUSkAAAAAA//cAGoE1ARGABsAPwBRAAAAMh4FFA4FIi4FND4EBSYGFxYVFAYiJjU0NzYmBwYHDgEXHgQyPgM3NiYnJgUHDgEXFhcWNj8BNiYnJicuAQIGpJ17bk85HBw6T257naKde25POhwcOU9uewIPDwYIGbD4sBcIBw5GWg0ECxYyWl+DiINfWjIWCwQMWv3/Iw8JCSU4EC0OIw4DDywtCyIERi1JXGJcSSpJXGJcSS0tSVxiXEkqSVxiXEncDwYTOT58sLB8OzcTBg9FcxAxEiRGXkQxMEVeRSQSMRF1HiQPLxJEMA0EDyIPJQ8sSRIEAAAABP/cAAAE1ASwABQAJwA7AEwAACEjNy4ENTQ+BTMyFzczEzceARUUDgMHNz4BNzYmJyYlBgcOARceBBc3LgE1NDc2JhcHDgEXFhcWNj8CJyYnLgECUJQfW6l2WSwcOU9ue51SPUEglCYvbIknUGqYUi5NdiYLBAw2/VFGWg0ECxIqSExoNSlrjxcIB3wjDwkJJTgQLQ4MFgMsLQsieBRhdHpiGxVJXGJcSS0Pef5StVXWNBpacm5jGq0xiD8SMRFGckVzEDESHjxRQTkNmhKnbjs3EwZwJA8vEkQwDQQPC1YELEkSBAAAAAP/ngAABRIEqwALABgAKAAAJwE2FhcBFgYjISImJSE1NDY7ATIWHQEhAQczMhYPAQ4BKwEiJi8BJjZaAoIUOBQCghUbJfryJRsBCgFZDwqWCg8BWf5DaNAUGAQ6BCMUNhQjBDoEGGQEKh8FIfvgIEdEhEsKDw8KSwLT3x0U/BQdHRT8FB0AAAABAGQAFQSwBLAAKAAAADIWFREBHgEdARQGJyURFh0BFAYvAQcGJj0BNDcRBQYmPQE0NjcBETQCTHxYAWsPFhgR/plkGhPNzRMaZP6ZERgWDwFrBLBYPv6t/rsOMRQpFA0M+f75XRRAFRAJgIAJEBVAFF0BB/kMDRQpFDEOAUUBUz4AAAARAAAAAARMBLAAHQAnACsALwAzADcAOwA/AEMARwBLAE8AUwBXAFsAXwBjAAABMzIWHQEzMhYdASE1NDY7ATU0NjsBMhYdASE1NDYBERQGIyEiJjURFxUzNTMVMzUzFTM1MxUzNTMVMzUFFTM1MxUzNTMVMzUzFTM1MxUzNQUVMzUzFTM1MxUzNTMVMzUzFTM1A1JkFR0yFR37tB0VMh0VZBUdAfQdAQ8dFfwYFR1kZGRkZGRkZGRk/HxkZGRkZGRkZGT8fGRkZGRkZGRkZASwHRUyHRWWlhUdMhUdHRUyMhUd/nD9EhUdHRUC7shkZGRkZGRkZGRkyGRkZGRkZGRkZGTIZGRkZGRkZGRkZAAAAAMAAAAZBXcElwAZACUANwAAARcWFA8BBiY9ASMBISImPQE0NjsBATM1NDYBBycjIiY9ATQ2MyEBFxYUDwEGJj0BIyc3FzM1NDYEb/kPD/kOFZ/9qP7dFR0dFdECWPEV/amNetEVHR0VASMDGvkPD/kOFfG1jXqfFQSN5g4qDuYOCBWW/agdFWQVHQJYlhUI/piNeh0VZBUd/k3mDioO5g4IFZa1jXqWFQgAAAABAAAAAASwBEwAEgAAEyEyFhURFAYjIQERIyImNRE0NmQD6Ck7Oyn9rP7QZCk7OwRMOyn9qCk7/tQBLDspAlgpOwAAAAMAZAAABEwEsAAJABMAPwAAEzMyFh0BITU0NiEzMhYdASE1NDYBERQOBSIuBTURIRUUFRwBHgYyPgYmNTQ9AZbIFR3+1B0C0cgVHf7UHQEPBhgoTGacwJxmTCgYBgEsAwcNFB8nNkI2Jx8TDwUFAQSwHRX6+hUdHRX6+hUd/nD+1ClJalZcPigoPlxWakkpASz6CRIVKyclIRsWEAgJEBccISUnKhURCPoAAAAB//8A1ARMA8IABQAAAQcJAScBBEzG/p/+n8UCJwGbxwFh/p/HAicAAQAAAO4ETQPcAAUAAAkCNwkBBE392v3ZxgFhAWEDFf3ZAifH/p8BYQAAAAAC/1EAZAVfA+gAFAApAAABITIWFREzMhYPAQYiLwEmNjsBESElFxYGKwERIRchIiY1ESMiJj8BNjIBlALqFR2WFQgO5g4qDuYOCBWW/oP+HOYOCBWWAYHX/RIVHZYVCA7mDioD6B0V/dkVDvkPD/kOFQGRuPkOFf5wyB0VAiYVDvkPAAABAAYAAASeBLAAMAAAEzMyFh8BITIWBwMOASMhFyEyFhQGKwEVFAYiJj0BIRUUBiImPQEjIiYvAQMjIiY0NjheERwEJgOAGB4FZAUsIf2HMAIXFR0dFTIdKh3+1B0qHR8SHQYFyTYUHh4EsBYQoiUY/iUVK8gdKh0yFR0dFTIyFR0dFTIUCQoDwR0qHQAAAAACAAAAAASwBEwACwAPAAABFSE1MzQ2MyEyFhUFIREhBLD7UMg7KQEsKTv9RASw+1AD6GRkKTs7Kcj84AACAAAAAAXcBEwADAAQAAATAxEzNDYzITIWFSEVBQEhAcjIyDspASwqOgH0ASz+1PtQASwDIP5wAlgpOzspyGT9RAK8AAEBRQAAA2sErwAbAAABFxYGKwERMzIWDwEGIi8BJjY7AREjIiY/ATYyAnvmDggVlpYVCA7mDioO5g4IFZaWFQgO5g4qBKD5DhX9pxUO+Q8P+Q4VAlkVDvkPAAAAAQABAUQErwNrABsAAAEXFhQPAQYmPQEhFRQGLwEmND8BNhYdASE1NDYDqPkODvkPFf2oFQ/5Dg75DxUCWBUDYOUPKQ/lDwkUl5cUCQ/lDykP5Q8JFZWVFQkAAAAEAAAAAASwBLAACQAZAB0AIQAAAQMuASMhIgYHAwUhIgYdARQWMyEyNj0BNCYFNTMVMzUzFQSRrAUkFP1gFCQFrAQt/BgpOzspA+gpOzv+q2RkZAGQAtwXLSgV/R1kOylkKTs7KWQpO8hkZGRkAAAAA/+cAGQEsARMAAsAIwAxAAAAMhYVERQGIiY1ETQDJSMTFgYjIisBIiYnAj0BNDU0PgE7ASUBFSIuAz0BND4CNwRpKh0dKh1k/V0mLwMRFQUCVBQdBDcCCwzIAqP8GAQOIhoWFR0dCwRMHRX8rhUdHRUDUhX8mcj+7BAIHBUBUQ76AgQQDw36/tT6AQsTKRwyGigUDAEAAAACAEoAAARmBLAALAA1AAABMzIWDwEeARcTFzMyFhQGBw4EIyIuBC8BLgE0NjsBNxM+ATcnJjYDFjMyNw4BIiYCKV4UEgYSU3oPP3YRExwaEggeZGqfTzl0XFU+LwwLEhocExF2Pw96UxIGEyQyNDUxDDdGOASwFRMlE39N/rmtHSkoBwQLHBYSCg4REg4FBAgoKR2tAUdNfhQgExr7vgYGMT09AAEAFAAUBJwEnAAXAAABNwcXBxcHFycHJwcnBzcnNyc3Jxc3FzcDIOBO6rS06k7gLZubLeBO6rS06k7gLZubA7JO4C2bmy3gTuq0tOpO4C2bmy3gTuq0tAADAAAAZASwBLAAIQAtAD0AAAEzMhYdAQchMhYdARQHAw4BKwEiJi8BIyImNRE0PwI+ARcPAREzFzMTNSE3NQEzMhYVERQGKwEiJjURNDYCijIoPBwBSCg8He4QLBf6B0YfHz0tNxSRYA0xG2SWZIjW+v4+Mv12ZBUdHRVkFR0dBLBRLJZ9USxkLR3+qBghMhkZJCcBkCQbxMYcKGTU1f6JZAF3feGv/tQdFf4MFR0dFQH0FR0AAAAAAwAAAAAEsARMACAAMAA8AAABMzIWFxMWHQEUBiMhFh0BFAYrASImLwImNRE0NjsBNgUzMhYVERQGKwEiJjURNDYhByMRHwEzNSchNQMCWPoXLBDuHTwo/rgcPCgyGzENYJEUNy09fP3pZBUdHRVkFR0dAl+IZJZkMjIBwvoETCEY/qgdLWQsUXYHlixRKBzGxBskAZAnJGRkHRX+DBUdHRUB9BUdZP6J1dSv4X0BdwADAAAAZAUOBE8AGwA3AEcAAAElNh8BHgEPASEyFhQGKwEDDgEjISImNRE0NjcXERchEz4BOwEyNiYjISoDLgQnJj8BJwUzMhYVERQGKwEiJjURNDYBZAFrHxZuDQEMVAEuVGxuVGqDBhsP/qoHphwOOmQBJYMGGw/LFRMSFv44AgoCCQMHAwUDAQwRklb9T2QVHR0VZBUdHQNp5hAWcA0mD3lMkE7+rRUoog0CDRElCkj+CVkBUxUoMjIBAgIDBQIZFrdT5B0V/gwVHR0VAfQVHQAAAAP/nABkBLAETwAdADYARgAAAQUeBBURFAYjISImJwMjIiY0NjMhJyY2PwE2BxcWBw4FKgIjIRUzMhYXEyE3ESUFMzIWFREUBisBIiY1ETQ2AdsBbgIIFBANrAf+qg8bBoNqVW1sVAEuVQsBDW4WSpIRDAIDBQMHAwkDCgH+Jd0PHAaCASZq/qoCUGQVHR0VZBUdHQRP5gEFEBEXC/3zDaIoFQFTTpBMeQ8mDXAWrrcWGQIFAwICAWQoFf6tWQH37OQdFf4MFR0dFQH0FR0AAAADAGEAAARMBQ4AGwA3AEcAAAAyFh0BBR4BFREUBiMhIiYvAQMmPwE+AR8BETQXNTQmBhURHAMOBAcGLwEHEyE3ESUuAQMhMhYdARQGIyEiJj0BNDYB3pBOAVMVKKIN/fMRJQoJ5hAWcA0mD3nGMjIBAgIDBQIZFrdT7AH3Wf6tFSiWAfQVHR0V/gwVHR0FDm5UaoMGGw/+qgemHA4OAWsfFm4NAQxUAS5U1ssVExIW/jgCCgIJAwcDBQMBDBGSVv6tZAElgwYb/QsdFWQVHR0VZBUdAAP//QAGA+gFFAAPAC0ASQAAASEyNj0BNCYjISIGHQEUFgEVFAYiJjURBwYmLwEmNxM+BDMhMhYVERQGBwEDFzc2Fx4FHAIVERQWNj0BNDY3JREnAV4B9BUdHRX+DBUdHQEPTpBMeQ8mDXAWEOYBBRARFwsCDQ2iKBX9iexTtxYZAgUDAgIBMjIoFQFTWQRMHRVkFR0dFWQVHfzmalRubFQBLlQMAQ1uFh8BawIIEw8Mpgf+qg8bBgHP/q1WkhEMAQMFAwcDCQIKAv44FhITFcsPGwaDASVkAAIAFgAWBJoEmgAPACUAAAAyHgIUDgIiLgI0PgEBJSYGHQEhIgYdARQWMyEVFBY3JTY0AeLs1ptbW5vW7NabW1ubAob+7RAX/u0KDw8KARMXEAETEASaW5vW7NabW1ub1uzWm/453w0KFYkPCpYKD4kVCg3fDSYAAAIAFgAWBJoEmgAPACUAAAAyHgIUDgIiLgI0PgENAQYUFwUWNj0BITI2PQE0JiMhNTQmAeLs1ptbW5vW7NabW1ubASX+7RAQARMQFwETCg8PCv7tFwSaW5vW7NabW1ub1uzWm+jfDSYN3w0KFYkPCpYKD4kVCgAAAAIAFgAWBJoEmgAPACUAAAAyHgIUDgIiLgI0PgEBAyYiBwMGFjsBERQWOwEyNjURMzI2AeLs1ptbW5vW7NabW1ubAkvfDSYN3w0KFYkPCpYKD4kVCgSaW5vW7NabW1ub1uzWm/5AARMQEP7tEBf+7QoPDwoBExcAAAIAFgAWBJoEmgAPACUAAAAyHgIUDgIiLgI0PgEFIyIGFREjIgYXExYyNxM2JisBETQmAeLs1ptbW5vW7NabW1ubAZeWCg+JFQoN3w0mDd8NChWJDwSaW5vW7NabW1ub1uzWm7sPCv7tFxD+7RAQARMQFwETCg8AAAMAGAAYBJgEmAAPAJYApgAAADIeAhQOAiIuAjQ+ASUOAwcGJgcOAQcGFgcOAQcGFgcUFgcyHgEXHgIXHgI3Fg4BFx4CFxQGFBcWNz4CNy4BJy4BJyIOAgcGJyY2NS4BJzYuAQYHBicmNzY3HgIXHgMfAT4CJyY+ATc+AzcmNzIWMjY3LgMnND4CJiceAT8BNi4CJwYHFB4BFS4CJz4BNxYyPgEB5OjVm1xcm9Xo1ZtcXJsBZA8rHDoKDz0PFD8DAxMBAzEFCRwGIgEMFhkHECIvCxU/OR0HFBkDDRQjEwcFaHUeISQDDTAMD0UREi4oLBAzDwQBBikEAQMLGhIXExMLBhAGKBsGBxYVEwYFAgsFAwMNFwQGCQcYFgYQCCARFwkKKiFBCwQCAQMDHzcLDAUdLDgNEiEQEgg/KhADGgMKEgoRBJhcm9Xo1ZtcXJvV6NWbEQwRBwkCAwYFBycPCxcHInIWInYcCUcYChQECA4QBAkuHgQPJioRFRscBAcSCgwCch0kPiAIAQcHEAsBAgsLIxcBMQENCQIPHxkCFBkdHB4QBgEBBwoMGBENBAMMJSAQEhYXDQ4qFBkKEhIDCQsXJxQiBgEOCQwHAQ0DBAUcJAwSCwRnETIoAwEJCwsLJQcKDBEAAAAAAQAAAAIErwSFABYAAAE2FwUXNxYGBw4BJwEGIi8BJjQ3ASY2AvSkjv79kfsGUE08hjv9rA8rD28PDwJYIk8EhVxliuh+WYcrIgsW/awQEG4PKxACV2XJAAYAAABgBLAErAAPABMAIwAnADcAOwAAEyEyFh0BFAYjISImPQE0NgUjFTMFITIWHQEUBiMhIiY9ATQ2BSEVIQUhMhYdARQGIyEiJj0BNDYFIRUhZAPoKTs7KfwYKTs7BBHIyPwYA+gpOzsp/BgpOzsEEf4MAfT8GAPoKTs7KfwYKTs7BBH+1AEsBKw7KWQpOzspZCk7ZGTIOylkKTs7KWQpO2RkyDspZCk7OylkKTtkZAAAAAIAZAAABEwEsAALABEAABMhMhYUBiMhIiY0NgERBxEBIZYDhBUdHRX8fBUdHQI7yP6iA4QEsB0qHR0qHf1E/tTIAfQB9AAAAAMAAABkBLAEsAAXABsAJQAAATMyFh0BITIWFREhNSMVIRE0NjMhNTQ2FxUzNQEVFAYjISImPQEB9MgpOwEsKTv+DMj+DDspASw7KcgB9Dsp/BgpOwSwOylkOyn+cGRkAZApO2QpO2RkZP1EyCk7OynIAAAABAAAAAAEsASwABUAKwBBAFcAABMhMhYPARcWFA8BBiIvAQcGJjURNDYpATIWFREUBi8BBwYiLwEmND8BJyY2ARcWFA8BFxYGIyEiJjURNDYfATc2MgU3NhYVERQGIyEiJj8BJyY0PwE2MhcyASwVCA5exwcHaggUCMdeDhUdAzUBLBUdFQ5exwgUCGoHB8deDgj+L2oHB8deDggV/tQVHRUOXscIFALLXg4VHRX+1BUIDl7HBwdqCBQIBLAVDl7HCBQIagcHx14OCBUBLBUdHRX+1BUIDl7HBwdqCBQIx14OFf0maggUCMdeDhUdFQEsFQgOXscHzl4OCBX+1BUdFQ5exwgUCGoHBwAAAAYAAAAABKgEqAAPABsAIwA7AEMASwAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JiQyFhQGIiY0JDIWFAYjIicHFhUUBiImNTQ2PwImNTQEMhYUBiImNCQyFhQGIiY0Advy3Z9fX5/d8t2gXl6gAcbgv29vv+C/b2/+LS0gIC0gAUwtICAWDg83ETNIMykfegEJ/octICAtIAIdLSAgLSAEqF+f3fLdoF5eoN3y3Z9Xb7/gv29vv+C/BiAtISEtICAtIQqRFxwkMzMkIDEFfgEODhekIC0gIC0gIC0gIC0AAf/YAFoEuQS8AFsAACUBNjc2JicmIyIOAwcABw4EFx4BMzI3ATYnLgEjIgcGBwEOASY0NwA3PgEzMhceARcWBgcOBgcGIyImJyY2NwE2NzYzMhceARcWBgcBDgEnLgECIgHVWwgHdl8WGSJBMD8hIP6IDx4eLRMNBQlZN0ozAiQkEAcdEhoYDRr+qw8pHA4BRyIjQS4ODyw9DQ4YIwwod26La1YOOEBGdiIwGkQB/0coW2tQSE5nDxE4Qv4eDyoQEAOtAdZbZWKbEQQUGjIhH/6JDxsdNSg3HT5CMwIkJCcQFBcMGv6uDwEcKQ4BTSIjIQEINykvYyMLKnhuiWZMBxtAOU6+RAH/SBg3ISSGV121Qv4kDwIPDyYAAAACAGQAWASvBEQAGQBEAAABPgIeAhUUDgMHLgQ1ND4CHgEFIg4DIi4DIyIGFRQeAhcWFx4EMj4DNzY3PgQ1NCYCiTB7eHVYNkN5hKg+PqeFeEM4WnZ4eQEjIT8yLSohJyktPyJDbxtBMjMPBw86KzEhDSIzKUAMBAgrKT8dF2oDtURIBS1TdkA5eYB/slVVsn+AeTlAdlMtBUgtJjY1JiY1NiZvTRc4SjQxDwcOPCouGBgwKEALBAkpKkQqMhNPbQACADn/8gR3BL4AFwAuAAAAMh8BFhUUBg8BJi8BNycBFwcvASY0NwEDNxYfARYUBwEGIi8BJjQ/ARYfAQcXAQKru0KNQjgiHR8uEl/3/nvUaRONQkIBGxJpCgmNQkL+5UK6Qo1CQjcdLhJf9wGFBL5CjUJeKmsiHTUuEl/4/nvUahKNQrpCARv+RmkICY1CukL+5UJCjUK7Qjc3LxFf+AGFAAAAAAMAyAAAA+gEsAARABUAHQAAADIeAhURFAYjISImNRE0PgEHESERACIGFBYyNjQCBqqaZDo7Kf2oKTs8Zj4CWP7/Vj09Vj0EsB4uMhX8Ryk7OykDuRUzLar9RAK8/RY9Vj09VgABAAAAAASwBLAAFgAACQEWFAYiLwEBEScBBRMBJyEBJyY0NjIDhgEbDx0qDiT+6dT+zP7oywEz0gEsAQsjDx0qBKH+5g8qHQ8j/vX+1NL+zcsBGAE01AEXJA4qHQAAAAADAScAEQQJBOAAMgBAAEsAAAEVHgQXIy4DJxEXHgQVFAYHFSM1JicuASczHgEXEScuBDU0PgI3NRkBDgMVFB4DFxYXET4ENC4CArwmRVI8LAKfBA0dMydAIjxQNyiym2SWVygZA4sFV0obLkJOMCAyVWg6HSoqFQ4TJhkZCWgWKTEiGBkzNwTgTgUTLD9pQiQuLBsH/s0NBxMtPGQ+i6oMTU8QVyhrVk1iEAFPCA4ZLzlYNkZwSCoGTf4SARIEDh02Jh0rGRQIBgPQ/soCCRYgNEM0JRkAAAABAGQAZgOUBK0ASgAAATIeARUjNC4CIyIGBwYVFB4BFxYXMxUjFgYHBgc+ATM2FjMyNxcOAyMiLgEHDgEPASc+BTc+AScjNTMmJy4CPgE3NgIxVJlemSc8OxolVBQpGxoYBgPxxQgVFS02ImIWIIwiUzUyHzY4HCAXanQmJ1YYFzcEGAcTDBEJMAwk3aYXFQcKAg4tJGEErVCLTig/IhIdFSw5GkowKgkFZDKCHj4yCg8BIh6TExcIASIfBAMaDAuRAxAFDQsRCjePR2QvORQrREFMIVgAAAACABn//wSXBLAADwAfAAABMzIWDwEGIi8BJjY7AREzBRcWBisBESMRIyImPwE2MgGQlhUIDuYOKg7mDggVlsgCF+YOCBWWyJYVCA7mDioBLBYO+g8P+g4WA4QQ+Q4V/HwDhBUO+Q8AAAQAGf//A+gEsAAHABcAGwAlAAABIzUjFSMRIQEzMhYPAQYiLwEmNjsBETMFFTM1EwczFSE1NyM1IQPoZGRkASz9qJYVCA7mDioO5g4IFZbIAZFkY8jI/tTIyAEsArxkZAH0/HwWDvoPD/oOFgOEZMjI/RL6ZJb6ZAAAAAAEABn//wPoBLAADwAZACEAJQAAATMyFg8BBiIvASY2OwERMwUHMxUhNTcjNSERIzUjFSMRIQcVMzUBkJYVCA7mDioO5g4IFZbIAljIyP7UyMgBLGRkZAEsx2QBLBYO+g8P+g4WA4SW+mSW+mT7UGRkAfRkyMgAAAAEABn//wRMBLAADwAVABsAHwAAATMyFg8BBiIvASY2OwERMwEjESM1MxMjNSMRIQcVMzUBkJYVCA7mDioO5g4IFZbIAlhkZMhkZMgBLMdkASwWDvoPD/oOFgOE/gwBkGT7UGQBkGTIyAAAAAAEABn//wRMBLAADwAVABkAHwAAATMyFg8BBiIvASY2OwERMwEjNSMRIQcVMzUDIxEjNTMBkJYVCA7mDioO5g4IFZbIArxkyAEsx2QBZGTIASwWDvoPD/oOFgOE/gxkAZBkyMj7tAGQZAAAAAAFABn//wSwBLAADwATABcAGwAfAAABMzIWDwEGIi8BJjY7AREzBSM1MxMhNSETITUhEyE1IQGQlhUIDuYOKg7mDggVlsgB9MjIZP7UASxk/nABkGT+DAH0ASwWDvoPD/oOFgOEyMj+DMj+DMj+DMgABQAZ//8EsASwAA8AEwAXABsAHwAAATMyFg8BBiIvASY2OwERMwUhNSEDITUhAyE1IQMjNTMBkJYVCA7mDioO5g4IFZbIAyD+DAH0ZP5wAZBk/tQBLGTIyAEsFg76Dw/6DhYDhMjI/gzI/gzI/gzIAAIAAAAABEwETAAPAB8AAAEhMhYVERQGIyEiJjURNDYFISIGFREUFjMhMjY1ETQmAV4BkKK8u6P+cKW5uQJn/gwpOzspAfQpOzsETLuj/nClubmlAZClucg7Kf4MKTs7KQH0KTsAAAAAAwAAAAAETARMAA8AHwArAAABITIWFREUBiMhIiY1ETQ2BSEiBhURFBYzITI2NRE0JgUXFhQPAQYmNRE0NgFeAZClubml/nCju7wCZP4MKTs7KQH0KTs7/m/9ERH9EBgYBEy5pf5wpbm5pQGQo7vIOyn+DCk7OykB9Ck7gr4MJAy+DAsVAZAVCwAAAAADAAAAAARMBEwADwAfACsAAAEhMhYVERQGIyEiJjURNDYFISIGFREUFjMhMjY1ETQmBSEyFg8BBiIvASY2AV4BkKO7uaX+cKW5uQJn/gwpOzspAfQpOzv+FQGQFQsMvgwkDL4MCwRMvKL+cKW5uaUBkKO7yDsp/gwpOzspAfQpO8gYEP0REf0QGAAAAAMAAAAABEwETAAPAB8AKwAAASEyFhURFAYjISImNRE0NgUhIgYVERQWMyEyNjURNCYFFxYGIyEiJj8BNjIBXgGQpbm5pf5wo7u5Amf+DCk7OykB9Ck7O/77vgwLFf5wFQsMvgwkBEy5pf5wo7u8ogGQpbnIOyn+DCk7OykB9Ck7z/0QGBgQ/REAAAAAAgAAAAAFFARMAB8ANQAAASEyFhURFAYjISImPQE0NjMhMjY1ETQmIyEiJj0BNDYHARYUBwEGJj0BIyImPQE0NjsBNTQ2AiYBkKW5uaX+cBUdHRUBwik7Oyn+PhUdHb8BRBAQ/rwQFvoVHR0V+hYETLml/nCluR0VZBUdOykB9Ck7HRVkFR3p/uQOJg7+5A4KFZYdFcgVHZYVCgAAAQDZAAID1wSeACMAAAEXFgcGAgclMhYHIggBBwYrAScmNz4BPwEhIicmNzYANjc2MwMZCQgDA5gCASwYEQ4B/vf+8wQMDgkJCQUCUCcn/tIXCAoQSwENuwUJEASeCQoRC/5TBwEjEv7K/sUFDwgLFQnlbm4TFRRWAS/TBhAAAAACAAAAAAT+BEwAHwA1AAABITIWHQEUBiMhIgYVERQWMyEyFh0BFAYjISImNRE0NgUBFhQHAQYmPQEjIiY9ATQ2OwE1NDYBXgGQFR0dFf4+KTs7KQHCFR0dFf5wpbm5AvEBRBAQ/rwQFvoVHR0V+hYETB0VZBUdOyn+DCk7HRVkFR25pQGQpbnp/uQOJg7+5A4KFZYdFcgVHZYVCgACAAAAAASwBLAAFQAxAAABITIWFREUBi8BAQYiLwEmNDcBJyY2ASMiBhURFBYzITI2PQE3ERQGIyEiJjURNDYzIQLuAZAVHRUObf7IDykPjQ8PAThtDgj+75wpOzspAfQpO8i7o/5wpbm5pQEsBLAdFf5wFQgObf7IDw+NDykPAThtDhX+1Dsp/gwpOzsplMj+1qW5uaUBkKW5AAADAA4ADgSiBKIADwAbACMAAAAyHgIUDgIiLgI0PgEEIg4BFB4BMj4BNCYEMhYUBiImNAHh7tmdXV2d2e7ZnV1dnQHD5sJxccLmwnFx/nugcnKgcgSiXZ3Z7tmdXV2d2e7ZnUdxwubCcXHC5sJzcqBycqAAAAMAAAAABEwEsAAVAB8AIwAAATMyFhURMzIWBwEGIicBJjY7ARE0NgEhMhYdASE1NDYFFTM1AcLIFR31FAoO/oEOJw3+hQ0JFfod/oUD6BUd+7QdA2dkBLAdFf6iFg/+Vg8PAaoPFgFeFR38fB0V+voVHWQyMgAAAAMAAAAABEwErAAVAB8AIwAACQEWBisBFRQGKwEiJj0BIyImNwE+AQEhMhYdASE1NDYFFTM1AkcBeg4KFfQiFsgUGPoUCw4Bfw4n/fkD6BUd+7QdA2dkBJ7+TQ8g+hQeHRX6IQ8BrxAC/H8dFfr6FR1kMjIAAwAAAAAETARLABQAHgAiAAAJATYyHwEWFAcBBiInASY0PwE2MhcDITIWHQEhNTQ2BRUzNQGMAXEHFQeLBwf98wcVB/7cBweLCBUH1APoFR37tB0DZ2QC0wFxBweLCBUH/fMICAEjCBQIiwcH/dIdFfr6FR1kMjIABAAAAAAETASbAAkAGQAjACcAABM3NjIfAQcnJjQFNzYWFQMOASMFIiY/ASc3ASEyFh0BITU0NgUVMzWHjg4qDk3UTQ4CFtIOFQIBHRX9qxUIDtCa1P49A+gVHfu0HQNnZAP/jg4OTdRMDyqa0g4IFf2pFB4BFQ7Qm9T9Oh0V+voVHWQyMgAAAAQAAAAABEwEsAAPABkAIwAnAAABBR4BFRMUBi8BByc3JyY2EwcGIi8BJjQ/AQEhMhYdASE1NDYFFTM1AV4CVxQeARUO0JvUm9IOCMNMDyoOjg4OTf76A+gVHfu0HQNnZASwAgEdFf2rFQgO0JrUmtIOFf1QTQ4Ojg4qDk3+WB0V+voVHWQyMgACAAT/7ASwBK8ABQAIAAAlCQERIQkBFQEEsP4d/sb+cQSs/TMCq2cBFP5xAacDHPz55gO5AAAAAAIAAABkBEwEsAAVABkAAAERFAYrAREhESMiJjURNDY7AREhETMHIzUzBEwdFZb9RJYVHR0V+gH0ZMhkZAPo/K4VHQGQ/nAdFQPoFB7+1AEsyMgAAAMAAABFBN0EsAAWABoALwAAAQcBJyYiDwEhESMiJjURNDY7AREhETMHIzUzARcWFAcBBiIvASY0PwE2Mh8BATYyBEwC/tVfCRkJlf7IlhUdHRX6AfRkyGRkAbBqBwf+XAgUCMoICGoHFQdPASkHFQPolf7VXwkJk/5wHRUD6BQe/tQBLMjI/c5qBxUH/lsHB8sHFQdqCAhPASkHAAMAAAANBQcEsAAWABoAPgAAAREHJy4BBwEhESMiJjURNDY7AREhETMHIzUzARcWFA8BFxYUDwEGIi8BBwYiLwEmND8BJyY0PwE2Mh8BNzYyBExnhg8lEP72/reWFR0dFfoB9GTIZGQB9kYPD4ODDw9GDykPg4MPKQ9GDw+Dgw8PRg8pD4ODDykD6P7zZ4YPAw7+9v5wHRUD6BQe/tQBLMjI/YxGDykPg4MPKQ9GDw+Dgw8PRg8pD4ODDykPRg8Pg4MPAAADAAAAFQSXBLAAFQAZAC8AAAERISIGHQEhESMiJjURNDY7AREhETMHIzUzEzMyFh0BMzIWDwEGIi8BJjY7ATU0NgRM/qIVHf4MlhUdHRX6AfRkyGRklmQVHZYVCA7mDioO5g4IFZYdA+j+1B0Vlv5wHRUD6BQe/tQBLMjI/agdFfoVDuYODuYOFfoVHQAAAAADAAAAAASXBLAAFQAZAC8AAAERJyYiBwEhESMiJjURNDY7AREhETMHIzUzExcWBisBFRQGKwEiJj0BIyImPwE2MgRMpQ4qDv75/m6WFR0dFfoB9GTIZGTr5g4IFZYdFWQVHZYVCA7mDioD6P5wpQ8P/vf+cB0VA+gUHv7UASzIyP2F5Q8V+hQeHhT6FQ/lDwADAAAAyASwBEwACQATABcAABMhMhYdASE1NDYBERQGIyEiJjURExUhNTIETBUd+1AdBJMdFfu0FR1kAZAETB0VlpYVHf7U/doVHR0VAib+1MjIAAAGAAMAfQStBJcADwAZAB0ALQAxADsAAAEXFhQPAQYmPQEhNSE1NDYBIyImPQE0NjsBFyM1MwE3NhYdASEVIRUUBi8BJjQFIzU7AjIWHQEUBisBA6f4Dg74DhX+cAGQFf0vMhUdHRUyyGRk/oL3DhUBkP5wFQ73DwOBZGRkMxQdHRQzBI3mDioO5g4IFZbIlhUI/oUdFWQVHcjI/cvmDggVlsiWFQgO5g4qecgdFWQVHQAAAAACAGQAAASwBLAAFgBRAAABJTYWFREUBisBIiY1ES4ENRE0NiUyFh8BERQOAg8BERQGKwEiJjURLgQ1ETQ+AzMyFh8BETMRPAE+AjMyFh8BETMRND4DA14BFBklHRXIFR0EDiIaFiX+4RYZAgEVHR0LCh0VyBUdBA4iGhYBBwoTDRQZAgNkBQkVDxcZAQFkAQUJFQQxdBIUH/uuFR0dFQGNAQgbHzUeAWcfRJEZDA3+Phw/MSkLC/5BFR0dFQG/BA8uLkAcAcICBxENCxkMDf6iAV4CBxENCxkMDf6iAV4CBxENCwABAGQAAASwBEwAMwAAARUiDgMVERQWHwEVITUyNjURIREUFjMVITUyPgM1ETQmLwE1IRUiBhURIRE0JiM1BLAEDiIaFjIZGf5wSxn+DBlL/nAEDiIaFjIZGQGQSxkB9BlLBEw4AQUKFA78iBYZAQI4OA0lAYr+diUNODgBBQoUDgN4FhkBAjg4DSX+dgGKJQ04AAAABgAAAAAETARMAAwAHAAgACQAKAA0AAABITIWHQEjBTUnITchBSEyFhURFAYjISImNRE0NhcVITUBBTUlBRUhNQUVFAYjIQchJyE3MwKjAXcVHWn+2cj+cGQBd/4lASwpOzsp/tQpOzspASwCvP5wAZD8GAEsArwdFf6JZP6JZAGQyGkD6B0VlmJiyGTIOyn+DCk7OykB9Ck7ZMjI/veFo4XGyMhm+BUdZGTIAAEAEAAQBJ8EnwAmAAATNzYWHwEWBg8BHgEXNz4BHwEeAQ8BBiIuBicuBTcRohEuDosOBhF3ZvyNdxEzE8ATBxGjAw0uMUxPZWZ4O0p3RjITCwED76IRBhPCFDERdo78ZXYRBA6IDi8RogEECBUgNUNjO0qZfHNVQBAAAAACAAAAAASwBEwAIwBBAAAAMh4EHwEVFAYvAS4BPQEmIAcVFAYPAQYmPQE+BRIyHgIfARUBHgEdARQGIyEiJj0BNDY3ATU0PgIB/LimdWQ/LAkJHRTKFB2N/sKNHRTKFB0DDTE7ZnTKcFImFgEBAW0OFR0V+7QVHRUOAW0CFiYETBUhKCgiCgrIFRgDIgMiFZIYGJIVIgMiAxgVyAQNJyQrIP7kExwcCgoy/tEPMhTUFR0dFdQUMg8BLzIEDSEZAAADAAAAAASwBLAADQAdACcAAAEHIScRMxUzNTMVMzUzASEyFhQGKwEXITcjIiY0NgMhMhYdASE1NDYETMj9qMjIyMjIyPyuArwVHR0VDIn8SokMFR0dswRMFR37UB0CvMjIAfTIyMjI/OAdKh1kZB0qHf7UHRUyMhUdAAAAAwBkAAAEsARMAAkAEwAdAAABIyIGFREhETQmASMiBhURIRE0JgEhETQ2OwEyFhUCvGQpOwEsOwFnZCk7ASw7/Rv+1DspZCk7BEw7KfwYA+gpO/7UOyn9RAK8KTv84AGQKTs7KQAAAAAF/5wAAASwBEwADwATAB8AJQApAAATITIWFREUBiMhIiY1ETQ2FxEhEQUjFTMRITUzNSMRIQURByMRMwcRMxHIArx8sLB8/UR8sLAYA4T+DMjI/tTIyAEsAZBkyMhkZARMsHz+DHywsHwB9HywyP1EArzIZP7UZGQBLGT+1GQB9GT+1AEsAAAABf+cAAAEsARMAA8AEwAfACUAKQAAEyEyFhURFAYjISImNRE0NhcRIREBIzUjFSMRMxUzNTMFEQcjETMHETMRyAK8fLCwfP1EfLCwGAOE/gxkZGRkZGQBkGTIyGRkBEywfP4MfLCwfAH0fLDI/UQCvP2oyMgB9MjIZP7UZAH0ZP7UASwABP+cAAAEsARMAA8AEwAbACMAABMhMhYVERQGIyEiJjURNDYXESERBSMRMxUhESEFIxEzFSERIcgCvHywsHz9RHywsBgDhP4MyMj+1AEsAZDIyP7UASwETLB8/gx8sLB8AfR8sMj9RAK8yP7UZAH0ZP7UZAH0AAAABP+cAAAEsARMAA8AEwAWABkAABMhMhYVERQGIyEiJjURNDYXESERAS0BDQERyAK8fLCwfP1EfLCwGAOE/gz+1AEsAZD+1ARMsHz+DHywsHwB9HywyP1EArz+DJaWlpYBLAAAAAX/nAAABLAETAAPABMAFwAgACkAABMhMhYVERQGIyEiJjURNDYXESERAyERIQcjIgYVFBY7AQERMzI2NTQmI8gCvHywsHz9RHywsBgDhGT9RAK8ZIImOTYpgv4Mgik2OSYETLB8/gx8sLB8AfR8sMj9RAK8/agB9GRWQUFUASz+1FRBQVYAAAAF/5wAAASwBEwADwATAB8AJQApAAATITIWFREUBiMhIiY1ETQ2FxEhEQUjFTMRITUzNSMRIQEjESM1MwMjNTPIArx8sLB8/UR8sLAYA4T+DMjI/tTIyAEsAZBkZMjIZGQETLB8/gx8sLB8AfR8sMj9RAK8yGT+1GRkASz+DAGQZP4MZAAG/5wAAASwBEwADwATABkAHwAjACcAABMhMhYVERQGIyEiJjURNDYXESERBTMRIREzASMRIzUzBRUzNQEjNTPIArx8sLB8/UR8sLAYA4T9RMj+1GQCWGRkyP2oZAEsZGQETLB8/gx8sLB8AfR8sMj9RAK8yP5wAfT+DAGQZMjIyP7UZAAF/5wAAASwBEwADwATABwAIgAmAAATITIWFREUBiMhIiY1ETQ2FxEhEQEHIzU3NSM1IQEjESM1MwMjNTPIArx8sLB8/UR8sLAYA4T+DMdkx8gBLAGQZGTIx2RkBEywfP4MfLCwfAH0fLDI/UQCvP5wyDLIlmT+DAGQZP4MZAAAAAMACQAJBKcEpwAPABsAJQAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JgchFSEVISc1NyEB4PDbnl5entvw255eXp4BxeTCcXHC5MJxcWz+1AEs/tRkZAEsBKdentvw255eXp7b8NueTHHC5MJxccLkwtDIZGTIZAAAAAAEAAkACQSnBKcADwAbACcAKwAAADIeAhQOAiIuAjQ+AQQiDgEUHgEyPgE0JgcVBxcVIycjFSMRIQcVMzUB4PDbnl5entvw255eXp4BxeTCcXHC5MJxcWwyZGRklmQBLMjIBKdentvw255eXp7b8NueTHHC5MJxccLkwtBkMmQyZGQBkGRkZAAAAv/y/50EwgRBACAANgAAATIWFzYzMhYUBisBNTQmIyEiBh0BIyImNTQ2NyY1ND4BEzMyFhURMzIWDwEGIi8BJjY7ARE0NgH3brUsLC54qqp4gB0V/tQVHd5QcFZBAmKqepYKD4kVCg3fDSYN3w0KFYkPBEF3YQ6t8a36FR0dFfpzT0VrDhMSZKpi/bMPCv7tFxD0EBD0EBcBEwoPAAAAAAL/8v+cBMMEQQAcADMAAAEyFhc2MzIWFxQGBwEmIgcBIyImNTQ2NyY1ND4BExcWBisBERQGKwEiJjURIyImNzY3NjIB9m62LCsueaoBeFr+hg0lDf6DCU9xVkECYqnm3w0KFYkPCpYKD4kVCg3HGBMZBEF3YQ+teGOkHAFoEBD+k3NPRWsOExNkqWP9kuQQF/7tCg8PCgETFxDMGBMAAAABAGQAAARMBG0AGAAAJTUhATMBMwkBMwEzASEVIyIGHQEhNTQmIwK8AZD+8qr+8qr+1P7Uqv7yqv7yAZAyFR0BkB0VZGQBLAEsAU3+s/7U/tRkHRUyMhUdAAAAAAEAeQAABDcEmwAvAAABMhYXHgEVFAYHFhUUBiMiJxUyFh0BITU0NjM1BiMiJjU0Ny4BNTQ2MzIXNCY1NDYCWF6TGll7OzIJaUo3LRUd/tQdFS03SmkELzlpSgUSAqMEm3FZBoNaPWcfHRpKaR77HRUyMhUd+x5pShIUFVg1SmkCAhAFdKMAAAAGACcAFASJBJwAEQAqAEIASgBiAHsAAAEWEgIHDgEiJicmAhI3PgEyFgUiBw4BBwYWHwEWMzI3Njc2Nz4BLwEmJyYXIgcOAQcGFh8BFjMyNz4BNz4BLwEmJyYWJiIGFBYyNjciBw4BBw4BHwEWFxYzMjc+ATc2Ji8BJhciBwYHBgcOAR8BFhcWMzI3PgE3NiYvASYD8m9PT29T2dzZU29PT29T2dzZ/j0EBHmxIgQNDCQDBBcGG0dGYAsNAwkDCwccBAVQdRgEDA0iBAQWBhJROQwMAwkDCwf5Y4xjY4xjVhYGElE6CwwDCQMLBwgEBVB1GAQNDCIEjRcGG0dGYAsNAwkDCwcIBAR5sSIEDQwkAwPyb/7V/tVvU1dXU28BKwErb1NXVxwBIrF5DBYDCQEWYEZHGwMVDCMNBgSRAhh1UA0WAwkBFTpREgMVCyMMBwT6Y2OMY2MVFTpREQQVCyMMBwQCGHVQDRYDCQEkFmBGRxsDFQwjDQYEASKxeQwWAwkBAAAABQBkAAAD6ASwAAwADwAWABwAIgAAASERIzUhFSERNDYzIQEjNQMzByczNTMDISImNREFFRQGKwECvAEstP6s/oQPCgI/ASzIZKLU1KJktP51Cg8DhA8KwwMg/oTIyALzCg/+1Mj84NTUyP4MDwoBi8jDCg8AAAAABQBkAAAD6ASwAAkADAATABoAIQAAASERCQERNDYzIQEjNRMjFSM1IzcDISImPQEpARUUBisBNQK8ASz+ov3aDwoCPwEsyD6iZKLUqv6dCg8BfAIIDwqbAyD9+AFe/doERwoP/tTI/HzIyNT+ZA8KNzcKD1AAAAAAAwAAAAAEsAP0AAgAGQAfAAABIxUzFyERIzcFMzIeAhUhFSEDETM0PgIBMwMhASEEiqJkZP7UotT9EsgbGiEOASz9qMhkDiEaAnPw8PzgASwB9AMgyGQBLNTUBBErJGT+ogHCJCsRBP5w/nAB9AAAAAMAAAAABEwETAAZADIAOQAAATMyFh0BMzIWHQEUBiMhIiY9ATQ2OwE1NDYFNTIWFREUBiMhIic3ARE0NjMVFBYzITI2AQc1IzUzNQKKZBUdMhUdHRX+1BUdHRUyHQFzKTs7Kf2oARP2/ro7KVg+ASw+WP201MjIBEwdFTIdFWQVHR0VZBUdMhUd+pY7KfzgKTsE9gFGAUQpO5Y+WFj95tSiZKIAAwBkAAAEvARMABkANgA9AAABMzIWHQEzMhYdARQGIyEiJj0BNDY7ATU0NgU1MhYVESMRMxQOAiMhIiY1ETQ2MxUUFjMhMjYBBzUjNTM1AcJkFR0yFR0dFf7UFR0dFTIdAXMpO8jIDiEaG/2oKTs7KVg+ASw+WAGc1MjIBEwdFTIdFWQVHR0VZBUdMhUd+pY7Kf4M/tQkKxEEOykDICk7lj5YWP3m1KJkogAAAAP/ogAABRYE1AALABsAHwAACQEWBiMhIiY3ATYyEyMiBhcTHgE7ATI2NxM2JgMVMzUCkgJ9FyAs+wQsIBcCfRZARNAUGAQ6BCMUNhQjBDoEGODIBK37sCY3NyYEUCf+TB0U/tIUHR0UAS4UHf4MZGQAAAAACQAAAAAETARMAA8AHwAvAD8ATwBfAG8AfwCPAAABMzIWHQEUBisBIiY9ATQ2EzMyFh0BFAYrASImPQE0NiEzMhYdARQGKwEiJj0BNDYBMzIWHQEUBisBIiY9ATQ2ITMyFh0BFAYrASImPQE0NiEzMhYdARQGKwEiJj0BNDYBMzIWHQEUBisBIiY9ATQ2ITMyFh0BFAYrASImPQE0NiEzMhYdARQGKwEiJj0BNDYBqfoKDw8K+goPDwr6Cg8PCvoKDw8BmvoKDw8K+goPD/zq+goPDwr6Cg8PAZr6Cg8PCvoKDw8BmvoKDw8K+goPD/zq+goPDwr6Cg8PAZr6Cg8PCvoKDw8BmvoKDw8K+goPDwRMDwqWCg8PCpYKD/7UDwqWCg8PCpYKDw8KlgoPDwqWCg/+1A8KlgoPDwqWCg8PCpYKDw8KlgoPDwqWCg8PCpYKD/7UDwqWCg8PCpYKDw8KlgoPDwqWCg8PCpYKDw8KlgoPAAAAAwAAAAAEsAUUABkAKQAzAAABMxUjFSEyFg8BBgchJi8BJjYzITUjNTM1MwEhMhYUBisBFyE3IyImNDYDITIWHQEhNTQ2ArxkZAFePjEcQiko/PwoKUIcMT4BXmRkyP4+ArwVHR0VDIn8SooNFR0dswRMFR37UB0EsMhkTzeEUzMzU4Q3T2TIZPx8HSodZGQdKh3+1B0VMjIVHQAABAAAAAAEsAUUAAUAGQArADUAAAAyFhUjNAchFhUUByEyFg8BIScmNjMhJjU0AyEyFhQGKwEVBSElNSMiJjQ2AyEyFh0BITU0NgIwUDnCPAE6EgMBSCkHIq/9WrIiCikBSAOvArwVHR0VlgET/EoBE5YVHR2zBEwVHftQHQUUOykpjSUmCBEhFpGRFiERCCb+lR0qHcjIyMgdKh39qB0VMjIVHQAEAAAAAASwBJ0ABwAUACQALgAAADIWFAYiJjQTMzIWFRQXITY1NDYzASEyFhQGKwEXITcjIiY0NgMhMhYdASE1NDYCDZZqapZqty4iKyf+vCcrI/7NArwVHR0VDYr8SokMFR0dswRMFR37UB0EnWqWamqW/us5Okxra0w6Of5yHSodZGQdKh3+1B0VMjIVHQAEAAAAAASwBRQADwAcACwANgAAATIeARUUBiImNTQ3FzcnNhMzMhYVFBchNjU0NjMBITIWFAYrARchNyMiJjQ2AyEyFh0BITU0NgJYL1szb5xvIpBvoyIfLiIrJ/68Jysj/s0CvBUdHRUNivxKiQwVHR2zBEwVHftQHQUUa4s2Tm9vTj5Rj2+jGv4KOTpMa2tMOjn+ch0qHWRkHSod/tQdFTIyFR0AAAADAAAAAASwBRIAEgAiACwAAAEFFSEUHgMXIS4BNTQ+AjcBITIWFAYrARchNyMiJjQ2AyEyFh0BITU0NgJYASz+1CU/P00T/e48PUJtj0r+ogK8FR0dFQ2K/EqJDBUdHbMETBUd+1AdBLChizlmUT9IGVO9VFShdksE/H4dKh1kZB0qHf7UHRUyMhUdAAIAyAAAA+gFFAAPACkAAAAyFh0BHgEdASE1NDY3NTQDITIWFyMVMxUjFTMVIxUzFAYjISImNRE0NgIvUjsuNv5wNi5kAZA2XBqsyMjIyMh1U/5wU3V1BRQ7KU4aXDYyMjZcGk4p/kc2LmRkZGRkU3V1UwGQU3UAAAMAZP//BEwETAAPAC8AMwAAEyEyFhURFAYjISImNRE0NgMhMhYdARQGIyEXFhQGIi8BIQcGIiY0PwEhIiY9ATQ2BQchJ5YDhBUdHRX8fBUdHQQDtgoPDwr+5eANGiUNWP30Vw0mGg3g/t8KDw8BqmQBRGQETB0V/gwVHR0VAfQVHf1EDwoyCg/gDSUbDVhYDRslDeAPCjIKD2RkZAAAAAAEAAAAAASwBEwAGQAjAC0ANwAAEyEyFh0BIzQmKwEiBhUjNCYrASIGFSM1NDYDITIWFREhETQ2ExUUBisBIiY9ASEVFAYrASImPQHIAyBTdWQ7KfopO2Q7KfopO2R1EQPoKTv7UDvxHRVkFR0D6B0VZBUdBEx1U8gpOzspKTs7KchTdf4MOyn+1AEsKTv+DDIVHR0VMjIVHR0VMgADAAEAAASpBKwADQARABsAAAkBFhQPASEBJjQ3ATYyCQMDITIWHQEhNTQ2AeACqh8fg/4f/fsgIAEnH1n+rAFWAS/+q6IDIBUd/HwdBI39VR9ZH4MCBh9ZHwEoH/5u/qoBMAFV/BsdFTIyFR0AAAAAAgCPAAAEIQSwABcALwAAAQMuASMhIgYHAwYWMyEVFBYyNj0BMzI2AyE1NDY7ATU0NjsBETMRMzIWHQEzMhYVBCG9CCcV/nAVJwi9CBMVAnEdKh19FROo/a0dFTIdFTDILxUdMhUdAocB+hMcHBP+BhMclhUdHRWWHP2MMhUdMhUdASz+1B0VMh0VAAAEAAAAAASwBLAADQAQAB8AIgAAASERFAYjIREBNTQ2MyEBIzUBIREUBiMhIiY1ETQ2MyEBIzUDhAEsDwr+if7UDwoBdwEsyP2oASwPCv12Cg8PCgF3ASzIAyD9wQoPAk8BLFQKD/7UyP4M/cEKDw8KA7YKD/7UyAAC/5wAZAUUBEcARgBWAAABMzIeAhcWFxY2NzYnJjc+ARYXFgcOASsBDgEPAQ4BKwEiJj8BBisBIicHDgErASImPwEmLwEuAT0BNDY7ATY3JyY2OwE2BSMiBh0BFBY7ATI2PQE0JgHkw0uOakkMEhEfQwoKGRMKBQ8XDCkCA1Y9Pgc4HCcDIhVkFRgDDDEqwxgpCwMiFWQVGAMaVCyfExwdFXwLLW8QBxXLdAFF+goPDwr6Cg8PBEdBa4pJDgYKISAiJRsQCAYIDCw9P1c3fCbqFB0dFEYOCEAUHR0UnUplNQcmFTIVHVdPXw4TZV8PCjIKDw8KMgoPAAb/nP/mBRQEfgAJACQANAA8AFIAYgAAASU2Fh8BFgYPASUzMhYfASEyFh0BFAYHBQYmJyYjISImPQE0NhcjIgYdARQ7ATI2NTQmJyYEIgYUFjI2NAE3PgEeARceAT8BFxYGDwEGJi8BJjYlBwYfAR4BPwE2Jy4BJy4BAoEBpxMuDiAOAxCL/CtqQ0geZgM3FR0cE/0fFyIJKjr+1D5YWLlQExIqhhALIAsSAYBALS1ALf4PmBIgHhMQHC0aPzANITNQL3wpgigJASlmHyElDR0RPRMFAhQHCxADhPcICxAmDyoNeMgiNtQdFTIVJgeEBBQPQ1g+yD5YrBwVODMQEAtEERzJLUAtLUD+24ITChESEyMgAwWzPUkrRSgJL5cvfRxYGyYrDwkLNRAhFEgJDAQAAAAAAwBkAAAEOQSwAFEAYABvAAABMzIWHQEeARcWDgIPATIeBRUUDgUjFRQGKwEiJj0BIxUUBisBIiY9ASMiJj0BNDY7AREjIiY9ATQ2OwE1NDY7ATIWHQEzNTQ2AxUhMj4CNTc0LgMjARUhMj4CNTc0LgMjAnGWCg9PaAEBIC4uEBEGEjQwOiodFyI2LUAjGg8KlgoPZA8KlgoPrwoPDwpLSwoPDwqvDwqWCg9kD9cBBxwpEwsBAQsTKRz++QFrHCkTCwEBCxMpHASwDwptIW1KLk0tHwYGAw8UKDJOLTtdPCoVCwJLCg8PCktLCg8PCksPCpYKDwJYDwqWCg9LCg8PCktLCg/+1MgVHR0LCgQOIhoW/nDIFR0dCwoEDiIaFgAAAwAEAAIEsASuABcAKQAsAAATITIWFREUBg8BDgEjISImJy4CNRE0NgQiDgQPARchNy4FAyMT1AMMVnokEhIdgVL9xFKCHAgYKHoCIIx9VkcrHQYGnAIwnAIIIClJVSGdwwSuelb+YDO3QkJXd3ZYHFrFMwGgVnqZFyYtLSUMDPPzBQ8sKDEj/sIBBQACAMgAAAOEBRQADwAZAAABMzIWFREUBiMhIiY1ETQ2ARUUBisBIiY9AQHblmesVCn+PilUrAFINhWWFTYFFKxn/gwpVFQpAfRnrPwY4RU2NhXhAAACAMgAAAOEBRQADwAZAAABMxQWMxEUBiMhIiY1ETQ2ARUUBisBIiY9AQHbYLOWVCn+PilUrAFINhWWFTYFFJaz/kIpVFQpAfRnrPwY4RU2NhXhAAACAAAAFAUOBBoAFAAaAAAJASUHFRcVJwc1NzU0Jj4CPwEnCQEFJTUFJQUO/YL+hk5klpZkAQEBBQQvkwKCAVz+ov6iAV4BXgL//uWqPOCWx5SVyJb6BA0GCgYDKEEBG/1ipqaTpaUAAAMAZAH0BLADIAAHAA8AFwAAEjIWFAYiJjQkMhYUBiImNCQyFhQGIiY0vHxYWHxYAeh8WFh8WAHofFhYfFgDIFh8WFh8WFh8WFh8WFh8WFh8AAAAAAMBkAAAArwETAAHAA8AFwAAADIWFAYiJjQSMhYUBiImNBIyFhQGIiY0Aeh8WFh8WFh8WFh8WFh8WFh8WARMWHxYWHz+yFh8WFh8/shYfFhYfAAAAAMAZABkBEwETAAPAB8ALwAAEyEyFh0BFAYjISImPQE0NhMhMhYdARQGIyEiJj0BNDYTITIWHQEUBiMhIiY9ATQ2fQO2Cg8PCvxKCg8PCgO2Cg8PCvxKCg8PCgO2Cg8PCvxKCg8PBEwPCpYKDw8KlgoP/nAPCpYKDw8KlgoP/nAPCpYKDw8KlgoPAAAABAAAAAAEsASwAA8AHwAvADMAAAEhMhYVERQGIyEiJjURNDYFISIGFREUFjMhMjY1ETQmBSEyFhURFAYjISImNRE0NhcVITUBXgH0ory7o/4Mpbm5Asv9qCk7OykCWCk7O/2xAfQVHR0V/gwVHR1HAZAEsLuj/gylubmlAfSlucg7Kf2oKTs7KQJYKTtkHRX+1BUdHRUBLBUdZMjIAAAAAAEAZABkBLAETAA7AAATITIWFAYrARUzMhYUBisBFTMyFhQGKwEVMzIWFAYjISImNDY7ATUjIiY0NjsBNSMiJjQ2OwE1IyImNDaWA+gVHR0VMjIVHR0VMjIVHR0VMjIVHR0V/BgVHR0VMjIVHR0VMjIVHR0VMjIVHR0ETB0qHcgdKh3IHSodyB0qHR0qHcgdKh3IHSodyB0qHQAAAAYBLAAFA+gEowAHAA0AEwAZAB8AKgAAAR4BBgcuATYBMhYVIiYlFAYjNDYBMhYVIiYlFAYjNDYDFRQGIiY9ARYzMgKKVz8/V1c/P/75fLB8sAK8sHyw/cB8sHywArywfLCwHSodKAMRBKNDsrJCQrKy/sCwfLB8fLB8sP7UsHywfHywfLD+05AVHR0VjgQAAAH/tQDIBJQDgQBCAAABNzYXAR4BBw4BKwEyFRQOBCsBIhE0NyYiBxYVECsBIi4DNTQzIyImJyY2NwE2HwEeAQ4BLwEHIScHBi4BN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<h1 class="title toc-ignore">Rfishpop (Fourth tutorial)</h1>
<h4 class="author">Marta Cousido Rocha, Santiago Cerviño López, Maria Grazia Pennino</h4>
<h4 class="date">29/7/2020</h4>
</div>
<div id="population-dynamic-tools-in-support-of-fisheries-managment" class="section level2">
<h2>Population dynamic tools in support of fisheries managment</h2>
<p>As we mentioned in the previous tutorials the aim of the package is to implement a completed MSE (management strategy evaluation) cycle.</p>
<p>The firsts steps of this cycle have been explained in the previous tutorials:</p>
<ul>
<li><p>The operating model used to generate “true” ecosystem dynamics including the natural variations in the system.</p></li>
<li><p>The sampling procedure from the operating model to mimic collection of fishery dependent data and research surveys (and their inherent variability).</p></li>
</ul>
<p>After these steps the next point is to pass these data to the <strong>assessment model</strong>. Based on this assessment and the HCR (Haverst Control Rule), a management action is determined (e.g., a change in the TAC).</p>
<p><span style="color:red">NOTE: Our package does not implement any assessment models, the idea is to use available implementations of the assessment models. The package contains specific functions to change the format of the data into the required format of the assessment model function. Now, the package contains such functions for the data-poor methods, LBI (Length Based Indicators) and LB-SPR (Length Based Spawning Potential Ratio). The list of functions will be expanded when exploring the application of other assessment models to the data reported by our package. THE PACKAGE IS AN OPEN PROJECT AND NEW FUNCTIONS ARE INCLUDED CONSTANTLY. </span></p>
<p><span style="color:red">WARNING: Due to the open ISSUES than the user can see in the corresponding page we recommend to be careful with the interpretation of the results corresponding with the application of the assessment models.</span></p>
<p>In this tutorial we focus on explaining the use of the <span style="color:blue">functions for passsing the data to the LBI and LB-SPR methods.</span> Furthermore, the package also contains a <span style="color:blue">function to define and fill a FLStock object</span> using the information provided by the main function Population.Modeling in order to use any of the tools developed in the FLR project. Therefore the tutorial finishes explaining this function.</p>
<div id="data-for-length-based-indicators-lbi" class="section level3">
<h3><span style="color:blue"> Data for Length Based Indicators (LBI)</span></h3>
<p>The function provides required information for computing Length Based Indicators: Length distributions of catches and the corresponding average weight per length.</p>
<p>The arguments of this function are described above:</p>
<ul>
<li><p><em>Pop.Mod</em> A list containing the components returned by Population.Modeling function (main function).</p></li>
<li><p><em>CV</em> The coefficient of variation associated to the log-normal distribution used in Distribution.length function (see Details of such function).</p></li>
</ul>
<pre class="r"><code>??Distribution.length</code></pre>
<ul>
<li><em>RF.value</em> The number of values generated for each age (given a year and an iteration) from the log-normal distribution used in Distribution.length function (see Details of such function). By default RF.value=1000.</li>
</ul>
<p>The function <strong>reports</strong> the length distributions of catches for each year and iteration in our Pop.Mod object. Furthermore, the corresponding average weight per length (for each year and iteration) is also provided.</p>
<p>The first point to illustrate the use of this function is to create a population. In this case as we can see below logistic selectivity and Beverton-Holt recruitment model are used.</p>
<pre class="r"><code>library(Rfishpop)
ctrPop<-list(years=seq(1980,2020,1),niter=1,N0=15000,ages=0:15,minFage=2,
maxFage=5,tc=0.5,seed=NULL)
number_ages<-length(ctrPop$ages);number_years<-length(ctrPop$years)
Mvec=c(1,0.6,0.5,0.4,0.35,0.35,0.3,rep(0.3,9))
M<-matrix(rep(Mvec,number_years),ncol = number_years)
colnames(M)<-ctrPop$years
rownames(M)<-ctrPop$ages
ctrBio<-list(M=M,CV_M=0, L_inf=20, t0=0, k=0.3, CV_L=0, CV_LC=0, a=6*10^(-6), b=3,
a50_Mat=4, ad_Mat=-0.2,CV_Mat=0)
ctrSEL<-list(type="Logistic", par=list(a50_Sel=2.3, ad_Sel=-0.2),CV_SEL=0)
f=matrix(rep(0.5,number_years),ncol=number_years,nrow=1,byrow=TRUE)
ctrFish<-list(f=f,ctrSEL=ctrSEL)
a_BH=15000; b_BH=50; CV_REC_BH=0
SR<-list(type="BH",par=c(a_BH,b_BH,CV_REC_BH))
Pop.Mod<-Population.Modeling(ctrPop=ctrPop,ctrBio=ctrBio,ctrFish=ctrFish,SR=SR)</code></pre>
<p>Then <em>Data.to.LBI</em> function is used to obtain the length distributions and average weight per length. NOTE that in the next lines of code we access to the first element of the list which corresponds to the first iteration (in this case we only have one since niter=1, in other examples the next iterations are reported in the next elements of the list).</p>
<pre class="r"><code>resul=Data.to.LBI(Pop.Mod,CV=0.2)</code></pre>
<pre><code>## It is working, please give us a while :)</code></pre>
<pre class="r"><code>freq=resul$length[[1]];head(freq)</code></pre>
<pre><code>## MeanLength 1980 1981 1982 1983 1984
## 0 0.5 0.0000000000 0.0000000000 0.0000000000 0.000000000 0.0000000000
## 1 1.5 0.0007821501 0.0006742673 0.0007012268 0.000873915 0.0005982937
## 2 2.5 0.0085901661 0.0087250192 0.0087113939 0.008255136 0.0071343697
## 3 3.5 0.0068894617 0.0046767110 0.0037623513 0.005606329 0.0051177170
## 4 4.5 0.0906305041 0.2453732178 0.0343630730 0.038878719 0.0411166126
## 5 5.5 1.5276591078 1.3840296716 0.2742901352 0.391258906 0.3209590848
## 1985 1986 1987 1988 1989 1990
## 0 0.0000000000 0.0000000000 0.000000000 0.0000000000 0.0000000000 0.0000000000
## 1 0.0005632265 0.0003070498 0.000370640 0.0002598829 0.0002502123 0.0001853813
## 2 0.0052203530 0.0041585225 0.003489718 0.0030686169 0.0025487724 0.0022280729
## 3 0.0037915485 0.0019624488 0.002097565 0.0019138005 0.0019835817 0.0012891574
## 4 0.0288056214 0.0247530585 0.015736664 0.0156388005 0.0143469994 0.0121544731
## 5 0.2824763504 0.1812665904 0.219808076 0.1221960567 0.0739640204 0.1947055671
## 1991 1992 1993 1994 1995 1996
## 0 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.000000e+00 0.000000e+00
## 1 0.0001881399 0.0001390554 0.0001100531 0.0001002623 8.874757e-05 7.953683e-05
## 2 0.0018206155 0.0014808184 0.0012770312 0.0010747412 8.830383e-04 7.754841e-04
## 3 0.0017112717 0.0007391894 0.0007706425 0.0008108768 4.614874e-04 3.616440e-04
## 4 0.0080081092 0.0064550881 0.0059217386 0.0059608490 3.691779e-03 2.803163e-03
## 5 0.1286867721 0.1390133674 0.0720324489 0.0314380505 5.213021e-02 4.451086e-02
## 1997 1998 1999 2000 2001 2002
## 0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## 1 5.557572e-05 3.550448e-05 3.680132e-05 2.981536e-05 2.999053e-05 2.579508e-05
## 2 6.616657e-04 5.769478e-04 4.746619e-04 4.142432e-04 3.395356e-04 2.846509e-04
## 3 3.030450e-04 3.915295e-04 4.001177e-04 3.172821e-04 1.932016e-04 1.970238e-04
## 4 3.489021e-03 1.786192e-03 1.851803e-03 2.062430e-03 4.997152e-03 3.944728e-03
## 5 2.660268e-02 2.192325e-02 1.893162e-02 1.909276e-02 9.958221e-03 1.140292e-02
## 2003 2004 2005 2006 2007 2008
## 0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## 1 2.488095e-05 2.169572e-05 1.533443e-05 1.620620e-05 1.155130e-05 1.291799e-05
## 2 2.312015e-04 2.101570e-04 1.763459e-04 1.430776e-04 1.188413e-04 1.001972e-04
## 3 1.738673e-04 1.099680e-04 9.655997e-05 8.210575e-05 8.834821e-05 8.641986e-05
## 4 1.007757e-03 9.735160e-04 5.935523e-04 5.754473e-04 5.015331e-04 4.223060e-04
## 5 1.166066e-02 1.012988e-02 6.678104e-03 4.279142e-03 3.633536e-03 3.174015e-03
## 2009 2010 2011 2012 2013 2014
## 0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## 1 8.546600e-06 5.452013e-06 5.814901e-06 5.343079e-06 4.161529e-06 4.127880e-06
## 2 8.854839e-05 7.538001e-05 6.276083e-05 5.283712e-05 4.491581e-05 3.745444e-05
## 3 4.996207e-05 6.137115e-05 5.131294e-05 2.990437e-05 2.666209e-05 3.161308e-05
## 4 4.008586e-04 2.668448e-04 3.643764e-04 2.175256e-04 2.048474e-04 1.688351e-04
## 5 2.491076e-03 2.034716e-03 3.044086e-03 2.568630e-03 1.754431e-03 1.502795e-03
## 2015 2016 2017 2018 2019 2020
## 0 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
## 1 3.081493e-06 2.824305e-06 1.691025e-06 2.177186e-06 1.263141e-06 1.424969e-06
## 2 3.143123e-05 2.641811e-05 2.385816e-05 1.856829e-05 1.718398e-05 1.347041e-05
## 3 3.533223e-05 1.960432e-05 1.647580e-05 1.650826e-05 1.124130e-05 1.190655e-05
## 4 1.348207e-04 1.077556e-04 9.891330e-05 2.823123e-04 3.892485e-05 6.196704e-05
## 5 1.279374e-03 1.602208e-03 1.175025e-03 3.978452e-04 1.611127e-03 6.617532e-04</code></pre>
<pre class="r"><code>wal=resul$weight[[1]];head(wal)</code></pre>
<pre><code>## MeanLength 1980 1981 1982 1983 1984 1985
## 0 0.5 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 1.5 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 2.5 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 3.5 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 4.5 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 5.5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825
## 1986 1987 1988 1989 1990 1991 1992
## 0 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825
## 1993 1994 1995 1996 1997 1998 1999
## 0 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825
## 2000 2001 2002 2003 2004 2005 2006
## 0 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825
## 2007 2008 2009 2010 2011 2012 2013
## 0 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825
## 2014 2015 2016 2017 2018 2019 2020
## 0 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075 0.00000075
## 1 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025 0.00002025
## 2 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375 0.00009375
## 3 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725 0.00025725
## 4 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675 0.00054675
## 5 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825 0.00099825</code></pre>
<p>Furthermore than the data provided by Data.to.LBI function the LBI method also needs values for some life history parameters. Below, we explain how to access to some of them.</p>
<ul>
<li>Parameters of Von Bertalanffy Growth Model.</li>
</ul>
<pre class="r"><code>L_inf=Pop.Mod$Info$ctrBio$L_inf
k=Pop.Mod$Info$ctrBio$k
t0=Pop.Mod$Info$ctrBio$t0</code></pre>
<p>See details of the parameters using the following code.</p>
<pre class="r"><code>?Length_VB</code></pre>
<ul>
<li>Now, we can use the Von Bertalanffy Growth Model to obtain the length at 50% maturity (L50=<span class="math inline">\(L_{50}\)</span>).</li>
</ul>
<pre class="r"><code>x50=Pop.Mod$Info$ctrBio$a50_Mat
L50=Length_VB(L_inf, k, x50, t0) </code></pre>
<p>Since M is constant through the year but age dependent, the natural mortality divided by von Bertalanffy k coefficient is computed as follows, using the mean of the age vector.</p>
<pre class="r"><code>M.vec=Pop.Mod$Matrices$M[,1,1]
MK <-mean(M.vec)/k</code></pre>
<p>Finally, running the following line of code, after load the required code and libraries, LBI are computed.</p>
<pre class="r"><code>LBI=lb_ind(data=freq,binwidth=3,linf=L_inf,lmat=L50,mk_ratio=MK,weight=wal)
LBI</code></pre>
<pre><code>## Year L75 L25 Lmed L90 L95 Lmean Lc LFeM Lmaxy Lmat Lopt
## 1 1980 16.5 10.5 13.5 16.5 19.5 13.95330 10.5 13.15116 13.5 13.97612 13.98058
## 2 1981 16.5 10.5 13.5 16.5 19.5 13.97492 10.5 13.15116 16.5 13.97612 13.98058
## 3 1982 16.5 10.5 13.5 19.5 19.5 14.27187 10.5 13.15116 16.5 13.97612 13.98058
## 4 1983 16.5 10.5 13.5 19.5 19.5 14.74143 10.5 13.15116 16.5 13.97612 13.98058
## 5 1984 16.5 10.5 13.5 19.5 22.5 14.78277 10.5 13.15116 16.5 13.97612 13.98058
## 6 1985 16.5 10.5 13.5 19.5 19.5 14.53453 10.5 13.15116 16.5 13.97612 13.98058
## 7 1986 16.5 10.5 13.5 19.5 19.5 14.34528 10.5 13.15116 16.5 13.97612 13.98058
## 8 1987 16.5 10.5 13.5 19.5 19.5 14.37644 10.5 13.15116 16.5 13.97612 13.98058
## 9 1988 16.5 10.5 13.5 19.5 19.5 14.41213 10.5 13.15116 16.5 13.97612 13.98058
## 10 1989 16.5 10.5 13.5 19.5 19.5 14.42667 10.5 13.15116 16.5 13.97612 13.98058
## 11 1990 16.5 10.5 13.5 19.5 19.5 14.39976 10.5 13.15116 16.5 13.97612 13.98058
## 12 1991 16.5 10.5 13.5 19.5 19.5 14.37307 10.5 13.15116 16.5 13.97612 13.98058
## 13 1992 16.5 10.5 13.5 19.5 19.5 14.35111 10.5 13.15116 16.5 13.97612 13.98058
## 14 1993 16.5 10.5 13.5 19.5 19.5 14.32043 10.5 13.15116 16.5 13.97612 13.98058
## 15 1994 16.5 10.5 13.5 19.5 19.5 14.32474 10.5 13.15116 16.5 13.97612 13.98058
## 16 1995 16.5 10.5 13.5 19.5 19.5 14.26274 10.5 13.15116 16.5 13.97612 13.98058
## 17 1996 16.5 10.5 13.5 19.5 19.5 14.39352 10.5 13.15116 16.5 13.97612 13.98058
## 18 1997 16.5 10.5 13.5 19.5 19.5 14.30406 10.5 13.15116 16.5 13.97612 13.98058
## 19 1998 16.5 10.5 13.5 19.5 19.5 14.34084 10.5 13.15116 16.5 13.97612 13.98058
## 20 1999 16.5 10.5 13.5 19.5 19.5 14.42720 10.5 13.15116 16.5 13.97612 13.98058
## 21 2000 16.5 10.5 13.5 19.5 19.5 14.30572 10.5 13.15116 16.5 13.97612 13.98058
## 22 2001 16.5 10.5 13.5 19.5 19.5 14.28918 10.5 13.15116 16.5 13.97612 13.98058
## 23 2002 16.5 10.5 13.5 19.5 19.5 14.31631 10.5 13.15116 16.5 13.97612 13.98058
## 24 2003 16.5 10.5 13.5 19.5 19.5 14.33537 10.5 13.15116 16.5 13.97612 13.98058
## 25 2004 16.5 10.5 13.5 19.5 19.5 14.26832 10.5 13.15116 16.5 13.97612 13.98058
## 26 2005 16.5 10.5 13.5 19.5 19.5 14.30234 10.5 13.15116 16.5 13.97612 13.98058
## 27 2006 16.5 10.5 13.5 19.5 19.5 14.24663 10.5 13.15116 16.5 13.97612 13.98058
## 28 2007 16.5 10.5 13.5 19.5 19.5 14.31394 10.5 13.15116 16.5 13.97612 13.98058
## 29 2008 16.5 10.5 13.5 19.5 19.5 14.27866 10.5 13.15116 16.5 13.97612 13.98058
## 30 2009 16.5 10.5 13.5 19.5 19.5 14.27302 10.5 13.15116 16.5 13.97612 13.98058
## 31 2010 16.5 10.5 13.5 19.5 19.5 14.29466 10.5 13.15116 16.5 13.97612 13.98058
## 32 2011 16.5 10.5 13.5 19.5 19.5 14.32532 10.5 13.15116 16.5 13.97612 13.98058
## 33 2012 16.5 10.5 13.5 19.5 19.5 14.30493 10.5 13.15116 16.5 13.97612 13.98058
## 34 2013 16.5 10.5 13.5 19.5 19.5 14.28135 10.5 13.15116 16.5 13.97612 13.98058
## 35 2014 16.5 10.5 13.5 19.5 19.5 14.30448 10.5 13.15116 16.5 13.97612 13.98058
## 36 2015 16.5 10.5 13.5 19.5 19.5 14.33658 10.5 13.15116 16.5 13.97612 13.98058
## 37 2016 16.5 10.5 13.5 19.5 19.5 14.34940 10.5 13.15116 16.5 13.97612 13.98058
## 38 2017 16.5 10.5 13.5 19.5 19.5 14.30263 10.5 13.15116 16.5 13.97612 13.98058
## 39 2018 16.5 10.5 13.5 19.5 19.5 14.31148 10.5 13.15116 16.5 13.97612 13.98058
## 40 2019 16.5 10.5 13.5 19.5 19.5 14.34817 10.5 13.15116 16.5 13.97612 13.98058
## 41 2020 16.5 10.5 13.5 19.5 19.5 14.36501 10.5 13.15116 16.5 13.97612 13.98058
## Linf Lmax5 Lmean_LFeM Lc_Lmat L25_Lmat Lmean_Lmat Lmean_Lopt L95_Linf
## 1 20 21.78834 1.060994 0.7512817 0.7512817 0.9983677 0.9980487 0.975
## 2 20 21.99070 1.062637 0.7512817 0.7512817 0.9999141 0.9995947 0.975
## 3 20 21.80925 1.085217 0.7512817 0.7512817 1.0211612 1.0208350 0.975
## 4 20 23.15041 1.120922 0.7512817 0.7512817 1.0547587 1.0544217 0.975
## 5 20 23.44404 1.124066 0.7512817 0.7512817 1.0577165 1.0573786 1.125
## 6 20 23.56572 1.105190 0.7512817 0.7512817 1.0399547 1.0396224 0.975
## 7 20 22.92408 1.090799 0.7512817 0.7512817 1.0264138 1.0260859 0.975
## 8 20 22.87228 1.093169 0.7512817 0.7512817 1.0286436 1.0283149 0.975
## 9 20 22.67487 1.095883 0.7512817 0.7512817 1.0311971 1.0308676 0.975
## 10 20 22.99769 1.096988 0.7512817 0.7512817 1.0322376 1.0319078 0.975
## 11 20 23.00737 1.094942 0.7512817 0.7512817 1.0303118 1.0299827 0.975
## 12 20 22.75227 1.092912 0.7512817 0.7512817 1.0284020 1.0280734 0.975
## 13 20 22.73548 1.091242 0.7512817 0.7512817 1.0268309 1.0265028 0.975
## 14 20 22.80043 1.088910 0.7512817 0.7512817 1.0246357 1.0243083 0.975
## 15 20 22.72260 1.089238 0.7512817 0.7512817 1.0249444 1.0246170 0.975
## 16 20 22.51446 1.084523 0.7512817 0.7512817 1.0205081 1.0201820 0.975
## 17 20 22.81501 1.094467 0.7512817 0.7512817 1.0298653 1.0295362 0.975
## 18 20 22.61098 1.087665 0.7512817 0.7512817 1.0234647 1.0231377 0.975
## 19 20 22.73638 1.090462 0.7512817 0.7512817 1.0260965 1.0257687 0.975
## 20 20 23.09268 1.097029 0.7512817 0.7512817 1.0322757 1.0319459 0.975
## 21 20 22.38892 1.087791 0.7512817 0.7512817 1.0235832 1.0232562 0.975
## 22 20 22.48256 1.086534 0.7512817 0.7512817 1.0224000 1.0220733 0.975
## 23 20 22.71178 1.088596 0.7512817 0.7512817 1.0243408 1.0240135 0.975
## 24 20 22.55843 1.090046 0.7512817 0.7512817 1.0257052 1.0253775 0.975
## 25 20 22.61437 1.084947 0.7512817 0.7512817 1.0209074 1.0205813 0.975
## 26 20 22.43594 1.087534 0.7512817 0.7512817 1.0233418 1.0230148 0.975
## 27 20 22.39467 1.083298 0.7512817 0.7512817 1.0193556 1.0190299 0.975
## 28 20 22.47043 1.088416 0.7512817 0.7512817 1.0241716 1.0238444 0.975
## 29 20 22.51760 1.085734 0.7512817 0.7512817 1.0216475 1.0213211 0.975
## 30 20 22.96088 1.085304 0.7512817 0.7512817 1.0212433 1.0209170 0.975
## 31 20 22.75390 1.086950 0.7512817 0.7512817 1.0227921 1.0224654 0.975
## 32 20 22.60082 1.089282 0.7512817 0.7512817 1.0249860 1.0246585 0.975
## 33 20 22.47035 1.087731 0.7512817 0.7512817 1.0235266 1.0231996 0.975
## 34 20 22.53467 1.085938 0.7512817 0.7512817 1.0218397 1.0215132 0.975
## 35 20 22.57827 1.087697 0.7512817 0.7512817 1.0234944 1.0231674 0.975
## 36 20 22.62556 1.090138 0.7512817 0.7512817 1.0257917 1.0254640 0.975
## 37 20 22.86174 1.091112 0.7512817 0.7512817 1.0267085 1.0263805 0.975
## 38 20 22.74843 1.087557 0.7512817 0.7512817 1.0233626 1.0230357 0.975
## 39 20 22.58605 1.088229 0.7512817 0.7512817 1.0239955 1.0236684 0.975
## 40 20 22.57679 1.091019 0.7512817 0.7512817 1.0266208 1.0262928 0.975
## 41 20 22.73011 1.092300 0.7512817 0.7512817 1.0278257 1.0274973 0.975
## Lmaxy_Lopt Lmax5_Linf Pmega Pmegaref
## 1 0.965625 1.089417 0.2861911 0.3
## 2 1.180208 1.099535 0.2990168 0.3
## 3 1.180208 1.090463 0.3479604 0.3
## 4 1.180208 1.157520 0.4012854 0.3
## 5 1.180208 1.172202 0.4107362 0.3
## 6 1.180208 1.178286 0.3632892 0.3
## 7 1.180208 1.146204 0.3446012 0.3
## 8 1.180208 1.143614 0.3446462 0.3
## 9 1.180208 1.133743 0.3504072 0.3
## 10 1.180208 1.149884 0.3561220 0.3
## 11 1.180208 1.150369 0.3510683 0.3
## 12 1.180208 1.137613 0.3482172 0.3
## 13 1.180208 1.136774 0.3479302 0.3
## 14 1.180208 1.140022 0.3423647 0.3
## 15 1.180208 1.136130 0.3385102 0.3
## 16 1.180208 1.125723 0.3341333 0.3
## 17 1.180208 1.140750 0.3499254 0.3
## 18 1.180208 1.130549 0.3412195 0.3
## 19 1.180208 1.136819 0.3455299 0.3
## 20 1.180208 1.154634 0.3572259 0.3
## 21 1.180208 1.119446 0.3450845 0.3
## 22 1.180208 1.124128 0.3330269 0.3
## 23 1.180208 1.135589 0.3388170 0.3
## 24 1.180208 1.127921 0.3449620 0.3
## 25 1.180208 1.130718 0.3328816 0.3
## 26 1.180208 1.121797 0.3408938 0.3
## 27 1.180208 1.119733 0.3308046 0.3
## 28 1.180208 1.123522 0.3384218 0.3
## 29 1.180208 1.125880 0.3403805 0.3
## 30 1.180208 1.148044 0.3334355 0.3
## 31 1.180208 1.137695 0.3363604 0.3
## 32 1.180208 1.130041 0.3457045 0.3
## 33 1.180208 1.123518 0.3365962 0.3
## 34 1.180208 1.126734 0.3422300 0.3
## 35 1.180208 1.128913 0.3356211 0.3
## 36 1.180208 1.131278 0.3449992 0.3
## 37 1.180208 1.143087 0.3405842 0.3
## 38 1.180208 1.137422 0.3328874 0.3
## 39 1.180208 1.129303 0.3388395 0.3
## 40 1.180208 1.128840 0.3453181 0.3
## 41 1.180208 1.136506 0.3368642 0.3</code></pre>
<pre class="r"><code>lb_plot(data=freq,
binwidth=3,
linf=L_inf,
lmat=L50,
mk_ratio=MK,
weight=wal,l_units="cm")</code></pre>
<p><img 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" width="672" /></p>
</div>
<div id="length-based-spawning-potential-ratio-lb-spr" class="section level3">
<h3><span style="color:blue"> Length Based Spawning Potential Ratio (LB-SPR)</span></h3>
<p>The function provides required information for computing Length Based Spawning Potential Ratio (LB-SPR): Length distributions of catches.</p>
<p>The <strong>arguments</strong> of this function are described above:</p>
<ul>
<li><p><em>Pop.Mod</em> A list containing the components returned by Population.Modeling function (main function).</p></li>
<li><p><em>CV</em> The coefficient of variation associated to the log-normal distribution used in Distribution.length function (see Details of such function).</p></li>
</ul>
<p>Remember:</p>
<pre class="r"><code>??Distribution.length</code></pre>
<ul>
<li><em>RF.value</em> The number of values generated for each age (given a year and an iteration) from the log-normal distribution used in Distribution.length function (see Details of such function). By default RF.value=1000.</li>
</ul>
<p>The function <strong>reports</strong> the length distributions of catches for each year and iteration in our Pop.Mod object.</p>
<p><span style="color:red"> THE FUNCTION PROVIDES THE LENGTH DISTRIBUTION OF THE CATCHES AS THE PREVIOUS FUNCTION Data.to.LBI. THE DIFFERENCE IS THAT Data.to.LB.SPR DOES NOT PROVIDE THE AVERAGE WEIGHT PER LENGTH (not necessary here). ON THE OTHER HAND IN THE FOLLOWING EXAMPLE WE PROVIDE THE LINES OF CODE TO OBTAIN THE FORMAT REQUIRED BY THE LB-SPR IMPLEMENTATION. THESE LINES OF CODE ARE NOT INCLUDED IN THE FUNCTION BECAUSE TO CREATE THE REQUIRED OBJECT WE NEED TO FIX THE LIFE PARAMETERS AS WELL, AND THERE ARE A HUGE LIST OF PARAMETERS WHICH CAN BE FIXED AND INFINITY POSSIBILITIES OF DEFINITION. THEN IT IS EASIER AND MORE FLEXIBLE IF WE PROVIDE THE REQUIRED LINES OF CODE OUTSIDE THE FUNCTION. THE USER ONLY NEEDS TO FIX THE VALUES OF THE PARAMETERS AND RUN THE LINES.</span></p>
<p>To illustrate the practical use of the function we can use the population simulated previously.</p>
<pre class="r"><code>resul=Data.to.LB.SPR(Pop.Mod,CV=0.2)</code></pre>
<pre><code>## It is working, please give us a while :)</code></pre>
<p>Some life history parameters have been defined previously in the LBI section. The length at 95% maturity (L95=<span class="math inline">\(L_{95}\)</span>) is fixed below. Note that first we use the logistic equation to obtain the age at 95% maturity, and then <span class="math inline">\(L_{95}\)</span>.</p>
<pre class="r"><code>xd=Pop.Mod$Info$ctrBio$ad_Mat
x95=(-xd)*log(19)+x50
L95=Length_VB(L_inf, k, x95, t0)</code></pre>
<p>All the information collected above must be used through the following lines of code to apply the LB-SPR model.</p>
<p>First of all we create the object LB_pars.</p>
<pre class="r"><code>MyPars <- new("LB_pars")</code></pre>
<pre><code>## A blank LB_pars object created</code></pre>
<pre><code>## Default values have been set for some parameters</code></pre>
<pre class="r"><code>MyPars@Species <- "MySpecies"
MyPars@Linf <- L_inf # von Bertalanffy asymptotic length
MyPars@L50 <-L50 # Length at 50% maturity (L50)
MyPars@L95 <-L95 # Length at 95% maturity (L95)
MyPars@MK <-MK # The natural mortality divided by von Bertalanffy k #coefficient</code></pre>
<p>We need to add such information to the length distribution as follows.</p>
<pre class="r"><code>freq=resul[[1]]
write.csv(freq, file="len.csv")
Len <- new("LB_lengths", LB_pars=MyPars, file=paste0("len.csv"),
dataType="freq", header=TRUE)</code></pre>
<p>Now, the distribution length has the required format to be introduced in the LBSPRfit().</p>
<pre class="r"><code>myFit<- LBSPRfit(MyPars,Len)</code></pre>
<pre><code>## Fitting model</code></pre>
<pre><code>## Year:</code></pre>
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<pre class="r"><code>plotEsts(myFit)</code></pre>
<p><img 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" width="672" /></p>
</div>
<div id="a-flstock-class-object" class="section level3">
<h3><span style="color:blue"> A FLStock class object</span></h3>
<p>The function defines and fills a FLStock object using the information provided by the main function Population.Modeling.</p>
<p>The unique <strong>argument</strong> of this function is <em>Pop.Mod</em>.</p>
<p>The function <strong>returns</strong> the FLStock object (see R package FLCore) corresponding to the simulated population generated by Population.Modeling function.</p>
<p>If we use the population simulated before the next line allows us to apply the function.</p>
<pre class="r"><code>resul_FLStock=FLStock.from.Rfishpop(Pop.Mod)
resul_FLStock</code></pre>
<pre><code>## An object of class "FLStock"
##
## Name: My Rfishpop
## Description: A stock from Rfishpop simulator
## Quant: age
## Dims: age year unit season area iter
## 16 41 1 1 1 1
##
## Range: min max pgroup minyear maxyear minfbar maxfbar
## 0 15 15 1980 2020 2 5
##
## catch : [ 1 41 1 1 1 1 ], units = kg
## catch.n : [ 16 41 1 1 1 1 ], units = 1
## catch.wt : [ 16 41 1 1 1 1 ], units = kg
## discards : [ 1 41 1 1 1 1 ], units = kg
## discards.n : [ 16 41 1 1 1 1 ], units = 1
## discards.wt : [ 16 41 1 1 1 1 ], units = kg
## landings : [ 1 41 1 1 1 1 ], units = kg
## landings.n : [ 16 41 1 1 1 1 ], units = 1
## landings.wt : [ 16 41 1 1 1 1 ], units = kg
## stock : [ 1 41 1 1 1 1 ], units = kg
## stock.n : [ 16 41 1 1 1 1 ], units = 1
## stock.wt : [ 16 41 1 1 1 1 ], units = kg
## m : [ 16 41 1 1 1 1 ], units = m
## mat : [ 16 41 1 1 1 1 ], units =
## harvest : [ 16 41 1 1 1 1 ], units = f
## harvest.spwn : [ 16 41 1 1 1 1 ], units = f
## m.spwn : [ 16 41 1 1 1 1 ], units = f</code></pre>
<p><span style="color:red"> The advantage of being able to transfer the information from Pop.Mod object to a FLStock object is that now we can use tools developed in the FLR project.</span></p>
<p>For example, we can apply code/tools of the tutorial “Modelling stock recruitment with FLSR” of FLR project to our population created using Rfishpop package.</p>
<p>Initially, the libraries need to be called.</p>
<pre class="r"><code>library(FLCore)
library(ggplotFL)</code></pre>
<p>The user can load and visualize the results.</p>
<pre class="r"><code>plot(resul_FLStock)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<p>Given that recruitment and spawning stock biomass (SSB) are provided as an output of the assessment, their relationship can be visualized simply by ploting the recruits against the SSB.</p>
<pre class="r"><code>ggplot(aes(ssb, rec), data=model.frame(FLQuants(resul_FLStock, "ssb", "rec"))) +
geom_point() + geom_smooth(method="loess")</code></pre>
<p><img 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" width="672" /></p>
<p>An empty FLSR object can be directly created simply by:</p>
<pre class="r"><code>sr1 <- FLSR()</code></pre>
<p>An FLSR object can be also be created by directly converting an FLStock object:</p>
<pre class="r"><code>p4sr <- as.FLSR(resul_FLStock)</code></pre>
<p>The contents of the FLSR object are the following:</p>
<pre class="r"><code>summary(p4sr)</code></pre>
<pre><code>## An object of class "FLSR"
##
## Name: My Rfishpop
## Description: 'rec' and 'ssb' slots obtained from a 'FLStock' object
## Quant: age
## Dims: age year unit season area iter
## 1 41 1 1 1 1
##
## Range: min minyear max maxyear
## 0 1980 0 2020
##
## rec : [ 1 41 1 1 1 1 ], units = 1
## ssb : [ 1 41 1 1 1 1 ], units = kg
## residuals : [ 1 41 1 1 1 1 ], units = NA
## fitted : [ 1 41 1 1 1 1 ], units = 1
##
## Model: list()
## Parameters:
## params
## iter
## 1
## Log-likelihood: NA(NA)
## Variance-covariance: <0 x 0 matrix></code></pre>
<p>Fitting an SR model.</p>
<pre class="r"><code>model(p4sr) <-bevholt()
p4sr<-fmle(p4sr)</code></pre>
<pre><code>## Nelder-Mead direct search function minimizer
## function value for initial parameters = -6.323793
## Scaled convergence tolerance is 9.42319e-08
## Stepsize computed as 109.192993
## BUILD 3 61.335671 -10.003299
## HI-REDUCTION 5 52.486884 -10.003299
## HI-REDUCTION 7 42.336039 -10.003299
## HI-REDUCTION 9 30.897591 -10.003299
## LO-REDUCTION 11 0.802309 -10.003299
## SHRINK 15 26.895125 -10.003299
## LO-REDUCTION 17 6.873834 -10.003299
## HI-REDUCTION 19 -1.141723 -10.003299
## LO-REDUCTION 21 -8.244453 -10.003299
## REFLECTION 23 -9.533210 -10.229159
## EXTENSION 25 -10.003299 -11.740839
## REFLECTION 27 -10.229159 -12.839990
## REFLECTION 29 -11.740839 -13.330892
## EXTENSION 31 -12.839990 -15.188553
## EXTENSION 33 -13.330892 -18.179067
## EXTENSION 35 -15.188553 -21.098642
## EXTENSION 37 -18.179067 -30.881719
## REFLECTION 39 -21.098642 -33.090110
## EXTENSION 41 -30.881719 -45.372460
## EXTENSION 43 -33.090110 -60.169086
## EXTENSION 45 -45.372460 -72.480090
## EXTENSION 47 -60.169086 -121.808138
## LO-REDUCTION 49 -72.480090 -121.808138
## LO-REDUCTION 51 -112.290709 -146.568402
## HI-REDUCTION 53 -121.808138 -146.568402
## REFLECTION 55 -140.909016 -171.385428
## LO-REDUCTION 57 -146.568402 -180.291403
## LO-REDUCTION 59 -171.385428 -182.315168
## LO-REDUCTION 61 -180.291403 -204.407968
## HI-REDUCTION 63 -182.315168 -219.511671
## HI-REDUCTION 65 -204.407968 -237.381609
## LO-REDUCTION 67 -219.511671 -247.709894
## HI-REDUCTION 69 -237.381609 -278.232793
## LO-REDUCTION 71 -247.709894 -278.232793
## HI-REDUCTION 73 -268.092125 -278.293730
## REFLECTION 75 -278.232793 -329.993430
## HI-REDUCTION 77 -278.293730 -329.993430
## LO-REDUCTION 79 -307.121579 -331.613107
## LO-REDUCTION 81 -329.993430 -345.851423
## HI-REDUCTION 83 -331.613107 -374.713143
## HI-REDUCTION 85 -345.851423 -375.691052
## LO-REDUCTION 87 -374.713143 -387.340300
## HI-REDUCTION 89 -375.691052 -450.238254
## HI-REDUCTION 91 -387.340300 -450.238254
## LO-REDUCTION 93 -400.401835 -450.238254
## HI-REDUCTION 95 -426.646352 -450.238254
## LO-REDUCTION 97 -431.251092 -463.215428
## HI-REDUCTION 99 -450.238254 -472.754829
## HI-REDUCTION 101 -463.215428 -488.372094
## LO-REDUCTION 103 -472.754829 -522.334957
## HI-REDUCTION 105 -488.372094 -522.334957
## HI-REDUCTION 107 -508.031942 -536.111330
## LO-REDUCTION 109 -522.334957 -545.339316
## HI-REDUCTION 111 -536.111330 -569.331056
## HI-REDUCTION 113 -545.339316 -569.331056
## LO-REDUCTION 115 -567.556823 -613.163766
## HI-REDUCTION 117 -569.331056 -618.592291
## HI-REDUCTION 119 -599.964256 -618.592291
## HI-REDUCTION 121 -613.163766 -632.990457
## HI-REDUCTION 123 -618.592291 -658.535910
## HI-REDUCTION 125 -632.990457 -662.446648
## LO-REDUCTION 127 -658.535910 -670.817778
## HI-REDUCTION 129 -662.446648 -716.581260
## HI-REDUCTION 131 -670.817778 -716.581260
## LO-REDUCTION 133 -690.176199 -724.989675
## HI-REDUCTION 135 -716.581260 -727.285182
## HI-REDUCTION 137 -724.989675 -780.355686
## HI-REDUCTION 139 -727.285182 -780.355686
## HI-REDUCTION 141 -751.651534 -780.355686
## LO-REDUCTION 143 -755.045478 -780.355686
## HI-REDUCTION 145 -779.791100 -790.912464
## REFLECTION 147 -780.355686 -806.419246
## HI-REDUCTION 149 -790.912464 -817.656232
## HI-REDUCTION 151 -806.419246 -847.829741
## HI-REDUCTION 153 -817.656232 -847.829741
## LO-REDUCTION 155 -834.239284 -847.829741
## HI-REDUCTION 157 -846.986580 -878.939948
## LO-REDUCTION 159 -847.829741 -893.939989
## HI-REDUCTION 161 -876.964249 -893.939989
## HI-REDUCTION 163 -878.939948 -905.891838
## HI-REDUCTION 165 -893.939989 -926.065088
## HI-REDUCTION 167 -905.891838 -926.065088
## REFLECTION 169 -916.008854 -946.828723
## HI-REDUCTION 171 -926.065088 -956.087738
## LO-REDUCTION 173 -946.828723 -1007.409548
## HI-REDUCTION 175 -956.087738 -1007.409548
## HI-REDUCTION 177 -988.393110 -1007.409548
## HI-REDUCTION 179 -989.229992 -1024.747943
## HI-REDUCTION 181 -1007.409548 -1032.069865
## HI-REDUCTION 183 -1024.747943 -1053.658021
## HI-REDUCTION 185 -1032.069865 -1053.658021
## HI-REDUCTION 187 -1053.035008 -1068.999144
## LO-REDUCTION 189 -1053.658021 -1080.403194
## HI-REDUCTION 191 -1068.999144 -1087.944349
## HI-REDUCTION 193 -1080.403194 -1138.579239
## LO-REDUCTION 195 -1087.944349 -1138.579239
## HI-REDUCTION 197 -1120.962808 -1138.579239
## HI-REDUCTION 199 -1132.385570 -1154.628105
## LO-REDUCTION 201 -1138.579239 -1162.599824
## HI-REDUCTION 203 -1154.628105 -1169.897303
## HI-REDUCTION 205 -1162.599824 -1230.571662
## LO-REDUCTION 207 -1169.897303 -1230.571662
## HI-REDUCTION 209 -1195.944215 -1230.571662
## HI-REDUCTION 211 -1198.144014 -1230.571662
## REFLECTION 213 -1212.382522 -1281.447922
## HI-REDUCTION 215 -1230.571662 -1281.447922
## LO-REDUCTION 217 -1241.152573 -1281.447922
## HI-REDUCTION 219 -1263.403296 -1281.447922
## LO-REDUCTION 221 -1271.435079 -1300.333825
## HI-REDUCTION 223 -1281.447922 -1324.282498
## HI-REDUCTION 225 -1300.333825 -1324.282498
## REFLECTION 227 -1310.337412 -1327.329586
## HI-REDUCTION 229 -1324.282498 -1363.275847
## HI-REDUCTION 231 -1327.329586 -1363.275847
## HI-REDUCTION 233 -1356.801400 -1363.275847
## HI-REDUCTION 235 -1357.314613 -1382.587030
## HI-REDUCTION 237 -1363.275847 -1396.796547
## HI-REDUCTION 239 -1382.587030 -1403.483022
## LO-REDUCTION 241 -1396.796547 -1425.550010
## HI-REDUCTION 243 -1403.483022 -1432.555870
## HI-REDUCTION 245 -1424.498497 -1432.555870
## HI-REDUCTION 247 -1425.550010 -1440.726036
## LO-REDUCTION 249 -1431.357777 -1440.726036
## LO-REDUCTION 251 -1432.555870 -1440.726036
## HI-REDUCTION 253 -1438.201816 -1448.967503
## HI-REDUCTION 255 -1440.726036 -1461.358094
## HI-REDUCTION 257 -1448.967503 -1480.336368
## HI-REDUCTION 259 -1461.358094 -1497.705974
## LO-REDUCTION 261 -1476.762123 -1497.705974
## SHRINK 265 -1481.336566 -1497.705974
## SHRINK 269 10000000000000000159264882086242060268642480002022248888446080244060806448408406080884680842682004844.000000 -1497.705974
## LO-REDUCTION 271 -1476.762123 -1497.705974
## Exiting from Nelder Mead minimizer
## 273 function evaluations used</code></pre>
<p>Diagnostic plots can be produced by simply calling the plot function on the FLSR object.</p>
<pre class="r"><code>plot(p4sr)</code></pre>
<p><img src="data:image/png;base64,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" width="672" /></p>
<p>Of course this is only one example but any tools of FLR project can be used. Below we apply also some code of “Short Term Forecasting for advice using FLash” tutorial of FLR project.</p>
<p>Load the required packages.</p>
<pre class="r"><code>library(FLAssess)
library(FLash)
library(ggplotFL)
library(FLBRP)</code></pre>
<p>Extending the stock object for the projections. A simple 3-year forecast for the weights, natural mortality, etc., assuming these are equal to their averages over the last 3 years.</p>
<pre class="r"><code>maxyr_stk <- range(resul_FLStock)[["maxyear"]]
ple4_stf <- stf(resul_FLStock,nyears=3,wts.nyears=3, na.rm=TRUE)
maxyr_stf <- range(ple4_stf)[["maxyear"]]
range(ple4_stf)</code></pre>
<pre><code>## min max plusgroup minyear maxyear minfbar maxfbar
## 0 15 15 1980 2023 2 5</code></pre>
<pre class="r"><code>stock.wt(ple4_stf)[,ac((maxyr_stf-5):maxyr_stf)]</code></pre>
<pre><code>## An object of class "FLQuant"
## , , unit = unique, season = all, area = unique
##
## year
## age 2018 2019 2020 2021 2022 2023
## 0 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
## 1 0.00083571 0.00083571 0.00083571 0.00083571 0.00083571 0.00083571
## 2 0.00440874 0.00440874 0.00440874 0.00440874 0.00440874 0.00440874
## 3 0.01003114 0.01003114 0.01003114 0.01003114 0.01003114 0.01003114
## 4 0.01637988 0.01637988 0.01637988 0.01637988 0.01637988 0.01637988
## 5 0.02250536 0.02250536 0.02250536 0.02250536 0.02250536 0.02250536
## 6 0.02791478 0.02791478 0.02791478 0.02791478 0.02791478 0.02791478
## 7 0.03243749 0.03243749 0.03243749 0.03243749 0.03243749 0.03243749
## 8 0.03608586 0.03608586 0.03608586 0.03608586 0.03608586 0.03608586
## 9 0.03895822 0.03895822 0.03895822 0.03895822 0.03895822 0.03895822
## 10 0.04118168 0.04118168 0.04118168 0.04118168 0.04118168 0.04118168
## 11 0.04288231 0.04288231 0.04288231 0.04288231 0.04288231 0.04288231