Métodos Cuantitativos Computarizados Para Biología Pesquera Métodos

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Métodos Cuantitativos Computarizados Para Biología Pesquera Métodos Métodos cuantcuantitativos computaaririzadooss parara biologbiología pesquera Isaías Hazarmabeth Salgado Ugarte Verónica Mitsui Saito Quezada UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO FACULTAD DE ESTUDIOS SUPERIORES ZARAGOZA Métodos cuantitativos computarizados para biología pesquera Isaías Hazarmabeth Salgado Ugarte Verónica Mitsui Saito Quezada Universidad Nacional Autónoma de México Facultad de Estudios Superiores Zaragoza Datos para catalogación bibliográfica Autores: Isaías Hazarmabeth Salgado Ugarte, Verónica Mitsui Saito Quezada. Métodos cuantitativos computarizados para biología pesquera. UNAM, FES Zaragoza, noviembre de 2020. Peso: 25.9 MB ISBN: 978-607-30-3715-0. Diseño de portada: Carlos Raziel Leaños. Diseño y formación de interiores: Claudia Ahumada Ballesteros. Esta obra se realizó con apoyo de la UNAM a través de la DGAPA, PAPIME, clave PE207417 y la FES Zaragoza. ______________________________________________________________________________ DERECHOS RESERVADOS Queda prohibida la reproducción o transmisión total o parcial del texto o las ilustraciones de la presente obra bajo cualesquiera formas, electrónicas o mecánicas, incluyendo fotocopiado, almacenamiento en algún sistema de recuperación de información, dispositivo de memoria digital o grabado sin el consentimiento previo y por escrito del editor. Métodos cuantitativos computarizados para biología pesquera. D.R. © Universidad Nacional Autónoma de México Av. Universidad # 3000, Col. Universidad Nacional Autónoma de México, C.U., Alcaldía de Coyoacán, C.P. 04510, Ciudad de México, México. Facultad de Estudios Superiores Zaragoza Av. Guelatao # 66, Col. Ejército de Oriente, Alcaldía de Iztapalapa, C.P. 09230, Ciudad de México, México. Índice Prólogo 9 Prefacio 13 Agradecimientos 17 Capítulo 1. Análisis de frecuencia de tallas 21 1.1 Histogramas 21 1.2 Polígonos de frecuencia 29 1.3 Estimadores de densidad por kernel (EDKs) 33 1.4 Estimadores de densidad por kernel de amplitud variable 38 1.5 Elección de amplitud de banda 41 1.6 Cálculo efciente de EDKs (discretizado y ASH-WARP) 42 1.7 Algunas consideraciones 45 1.8 Reglas prácticas para selección de intervalo/banda 48 1.8.1. Introducción 48 1.8.2. Reglas para elección de número de intervalos en histogramas 48 1.8.3. Reglas para elección de amplitud de intervalo en histogramas 49 1.8.4. Reglas sobresuavizadas 51 1.8.5. Reglas para elección de número y amplitud de intervalo en polígonos de 52 frecuencia 1.8.6. Reglas para elección de amplitud de banda en EDKs 54 1.8.7. Reglas sobresuavizadas para EDKs 55 1.9 Métodos de Cómputo Intensivo: 56 1.9.1. Validación cruzada por mínimos cuadrados 56 1.9.2. Validación cruzada sesgada 58 1.9.3. Ejemplos de Aplicación 59 Métodos cuantitativos computarizados para biología pesquera 1.9.4. Algunos comentarios sobre la elección del parámetro de suavización 76 1.9.5 Evaluación no paramétrica de la multimodalidad 76 1.9.6 Prueba de Multimodalidad de Silverman 77 1.10 Ejemplos de aplicación 81 1.10.1. Uso de reglas de amplitud de banda 81 1.10.2. Aplicación de la prueba de multimodalidad de Silverman 85 1.10.3. Algunos comentarios adicionales 92 1.11. Caracterización de componentes gaussianos en distribuciones multimodales 100 1.11.1. Introducción 100 1.11.2. Método de Bhatacharya 102 1.12. Análisis de las frecuencias de longitud del “kidai” (Dentex tumifrons) 110 1.13. Análisis de frecuencia de tallas de Cathorops melanopus por EDKs 120 1.14. Notas acerca de los cálculos 125 1.15. Mezcla fnita de distribuciones 126 1.16. Comparación de Dos Distribuciones de Frecuencia (Kolmogorov-Smirnov) 141 Capítulo 2. Alometría 149 2.1 Introducción 149 2.2 Relaciones entre dimensiones lineales 156 2.2.1. Otros ejemplos: Equinoideos 159 2.2.2. Gasterópodo Leucozonia cerata 164 2.2.3. Pelecípodo Pinctada mazatlanica 169 2.3 Relaciones en Dimensiones mixtas 172 2.3.1. Otros ejemplos de relaciones P-L 179 2.3.2. Gasterópodo Hexaplex princeps 180 2.3.3. Pelecípodo Hyotissa hiotis 183 2.4. Relaciones entre dimensiones de volumen 184 Capítulo 3 Estimación de la edad 189 3.1. Introducción 189 3.2. Escamas. Relación Cuerpo-Estructura 191 3.3. Otolitos 197 4 Índice 3.4. Relación Cuerpo-Otolito 201 3.5. Validación de la periodicidad de las marcas 202 3.6. Opérculos del gasterópodo Astraea undosa 203 3.7 Otolitos de la tilapia Oreochromis niloticus. Validación de periodicidad 214 3.7.1 Análisis de bordes 216 3.7.2. Análisis del incremento marginal 218 3.7.3. Razón del incremento marginal 220 Capítulo 4 Modelación del crecimiento individual 223 4.1 Introducción 223 4.2 Estimación de la edad 224 4.3 Estimación de los parámetros de la función de crecimiento de von Bertalanfy 226 (FCvB) 4.3.1 Gráfco de Ford-Walford 227 4.3.2 Gráfco de Gulland 228 4.3.3 Gráfco de Gulland-Holt 229 4.3.4 Método de Beverton y Holt 230 4.3.5 Regresión no lineal 230 4.4 Caso 1. Análisis de frecuencia de tallas 231 4.5 Caso 2. Longitud-edad a partir de lectura de estructuras duras 245 4.6 Algunas notas adicionales 251 4.7 Otras funciones de crecimiento 251 4.8 Caso 3. Crecimiento del caracol Hexaplex princeps 253 4.9 Caso 4. Crecimiento del holoturoideo (pepino de mar) Holothuria inornata 262 4.10 Ajuste de otras funciones con R 266 4.11 Crecimiento estacional. Ajuste para la FCvB 267 4.12 Ajuste de la FCvB por maxima verosimilitud 277 Capítulo 5 Comparación de funciones de crecimiento 285 5.1 Introducción 285 5.2 Prueba de la T2 de Hotelling 285 5 Métodos cuantitativos computarizados para biología pesquera 5.3 Suposiciones de la prueba T2 288 5.4 Pruebas de razón de verosimilitud 289 5.5 Prueba global de curvas de crecimiento 291 5.6 Pruebas de máxima verosimilitud 291 5.7 Programas 293 5.8 Consideraciones sobre comparación de curvas de crecimiento 302 5.9 Aplicación a funciones Logística y Gompert 303 Capítulo 6 Índices Morfofisiológicos 313 6.1 Introducción 313 6.2 El caso del pez “Suzuki” (Lateolabrax japonicus) 316 6.2.1 Material y métodos 318 6.2.2. Análisis multivariado de covarianza (ANMUCOVA) 321 6.3 El caso del gasterópodo marino Hexaplex princeps 333 6.3.1. Material y método 334 6.3.2. Índices morfofsiológicos 337 6.3.3. Análisis multivariado de covarianza (ANMUCOVA) 343 6.3.4. Valores suavizados 347 6.3.5. Comparación de índices con Temperatura y Clorofla 350 6.3.6. Consideraciones acerca de los resultados 352 6.4 Comandos en Stata 354 Capítulo 7 Estadios de Madurez Gonádica 363 7.1 Introducción 363 7.2 Escalas macroscópicas de madurez 363 7.3 Relación madurez talla 365 7.4 Escalas histológicas de madurez 372 7.5 Ciclo reproductivo del gasterópodo Hexaplex princeps 373 7.5.1. Gráfcos de Área 377 7.5.2. Suavización no lineal resistente 383 7.5.3. Correlación cruzada 386 6 Índice 7.6 Talla de primera madurez 392 7.7 Comparación con curva logística de dos parámetros 396 Bibliografía 401 Apéndices 419 Apéndice 1: Uso del programa AED2020 421 Apéndice 2: Listado de Programas para Stata 448 Apéndice 3: Listado de Archivos de Datos 451 Apéndice 4: Listado de Objetos para R 454 Apéndice 5: Comandos de Stata para Análisis Multivariado de Covarianza 460 Apéndice 6: Hojas de Datos en Excel 468 Apéndice 7: Programa PAC (Programas para el Análisis del Crecimiento) 469 Apéndice 8: Ajuste de distribuciones Gaussianas por Máxima Verosimilitud de la 472 distribución Multinomial Índice Temático 477 7 Prólogo l estudio de los recursos bióticos que permita una mejor comprensión de sus ciclos de Evida, así como una mejor administración para su aprovechamiento es sin duda una tarea permanente y continua, debido a las diversas condiciones y necesidades que la humanidad impone y enfrenta. Para el caso particular de recursos pesqueros el reto es grande dada las difcultades que el ambiente establece, así como las características de movilidad de la mayoría de las especies y el marco de acceso abierto para múltiples usuarios. La sociedad humana se benefcia de muchas maneras de los servicios a los ecosistemas generados por los recursos pesqueros, además de los benefcios económicos directos. Sin embargo, el incremento en la presión de pesca, contaminación, destrucción del hábitat, introducción de especies exóticas y otros factores de estrés continúan ejerciendo una fuerte presión sobre dichos recursos y sus hábitats. La captura pesquera se apropia de una parte sustancial (8%) de la producción primaria global en el mar y requiere entre 24 y 35% de la producción de surgencias y plataforma continental. Además, el objetivo de manejadores pesqueros por altos rendimientos de unas pocas especies de los límites superiores de las cadenas trófcas ha movido a las comunidades bióticas hacia una composición dominada por niveles trófcos inferiores los cuales, obligadamente son capturados por las pesquerías. Todavía es necesario desarrollar criterios y métodos de valoración de los distintos bienes y servicios que los diversos recursos pesqueros nos proporcionan además de su uso directo. Los peces constituyen más de la mitad de las 54,711 especies de vertebrados existentes con aproximadamente 29,400 especies vivientes, constituidas en 515 familias y 62 órdenes. Dentro de los invertebrados, grupos importantes por su explotación desde tiempos remotos son los moluscos (con más de 100,000 especies vivientes) que incluyen principalmente a los gasterópodos, pelecípodos y cefalópodos; en ciertas regiones del mundo son apreciados otros grupos como los equinodermos (equinoideos y holoturoideos). Los aspectos básicos importantes para la sobrevivencia de estos organismos están relacionados con la hidrología (niveles de oxígeno disuelto, nutrientes, salinidad, penetración de la luz, temperatura y contaminantes), así como los parámetros bióticos y ecología del sistema (recursos alimenticios, depredación, heterogeneidad de hábitat), todo lo cual solo se menciona como ejemplo de la magnitud del reto en investigación que se requiere y más cuando se considera que en ambientes tropicales se desarrollan las pesquerías multiespecífcas.
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