Modelling aboveground net primary production (ANPP) of an Atlantic mountain grassland based on time series approach

  1. A. Salaberria 1
  2. G. García-Baquero 1
  3. I. Odriozola 1
  4. A. Aldezabal 1
  1. 1 Universidad del País Vasco/Euskal Herriko Unibertsitatea
    info

    Universidad del País Vasco/Euskal Herriko Unibertsitatea

    Lejona, España

    ROR https://ror.org/000xsnr85

Revista:
Cuadernos de investigación geográfica: Geographical Research Letters
  1. Lasanta Martínez, Teodoro (ed. lit.)

ISSN: 0211-6820,  1697-9540

Año de publicación: 2019

Volumen: 45

Número: 2

Páginas: 551-569

Tipo: Artículo

DOI: 10.18172/CIG.3561 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Cuadernos de investigación geográfica: Geographical Research Letters

Resumen

Debido a que la producción primaria está relacionada tanto con la energía que sustenta las redes tróficas como con la diversidad de especies, generalmente se considera una propiedad clave del ecosistema y un indicador fiable del forraje disponible. En este trabajo se modeló la producción primaria neta aérea (ANPP) de un sistema de pastizales atlánticos de montaña con el fin de intentar pronosticarla a corto plazo. Como el pastoreo influye en la productividad, se aplicaron experimentalmente dos niveles de tratamiento (pastoreo y exclusión) en cada uno de los tres sitios de estudio. Los datos mensuales de ANPP se recolectaron a lo largo de tres períodos vegetativos consecutivos (2006-2008), obteniendo así seis series temporales (una por parcela). Dado que no se encontraron diferencias significativas entre los sitios (dentro de los tratamientos), estas seis series fueron promediadas y reducidas a dos (una por nivel de tratamiento). Posteriormente, se utilizaron dos tipos de modelos estadísticos para pronosticar la ANPP mensual: métodos de suavizado exponencial y modelos ARIMA. Ambas metodologías arrojaron pronósticos inadecuados debido a la presencia de características locales marcadas (valores atípicos innovadores) en nuestros datos de series temporales relativamente cortas. No obstante, se reveló información útil para un diseño de manejo del pastoreo más adecuado (por ejemplo, la presencia de variación dentro de un año en la ANPP y diferencias entre los tratamientos de pastoreo y exclusión). Es probable que se necesiten series de datos más largas, lo que requeriría un esfuerzo más exigente en la inversión de muestreo, para obtener predicciones adecuadas utilizando estas metodologías de series temporales.

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Información de financiación

This study received financial support from ETORTEK10/34 (Basque Government), UNESCO07/07 (University of the Basque Country) and AGL2013-48361-C2-1-R (Ministry of Economy and Competitiveness of the Spanish Government).

Financiadores

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