Predictive Production Models for Mountain Meadows: A Review

Author:

Jarne Adrián1,Usón Asunción1,Reiné Ramón1ORCID

Affiliation:

1. Departamento de Ciencias Agrarias y del Medio Natural, Escuela Politécnica Superior, Universidad de Zaragoza, Ctra Cuarte s/n, 22071 Huesca, Spain

Abstract

Meadows are the most important source of feed for extensive livestock farming in mountainous conditions, as well as providing many environmental services. The actual socioeconomic situation and climate change risk its conservation. That is why finding its optimal management is important. To do so, predictive models are a useful tool to determine the impact of different practices and estimate the consequences of future scenarios. Empirical models are a good analytical tool, but their applications in the future are limited. Dynamic models can better estimate the consequences of newer scenarios, but even if there are many dynamic models, their adaptation into grassland production estimation is scarce. This article reviews the most suitable predictive models for grass production in mountain meadows when data on agricultural management (mowing, grazing, fertilization) and forage value are available, considering the conservation of plant biodiversity.

Funder

Gobierno de Aragón

the European Agricultural Fund for Rural Development, European Union

Publisher

MDPI AG

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