134844 20260217205451.0 doi 10.3390/agronomy14040830 sideral 138323 ART-2024-138323 eng Jarne, Adrián Universidad de Zaragoza Predictive Production Models for Mountain Meadows: A Review 2024 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA/GCP-2021-000100 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 3.4 2024 AGRONOMY 21 / 129 = 0.163 2024 Q1 T1 PLANT SCIENCES 69 / 273 = 0.253 2024 Q2 T1 0.744 2024 Agronomy and Crop Science 2024 Q1 6.7 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Usón, Asunción Universidad de Zaragoza (orcid)0000-0002-0139-0843 Reiné, Ramón Universidad de Zaragoza (orcid)0000-0002-9990-571X 5011 705 Universidad de Zaragoza Dpto. CC.Agrar.y Medio Natural Área Producción Vegetal 14, 4 (2024), 830 [14 pp.] Agronomy (Basel) Agronomy (Basel) 2073-4395 260403 http://zaguan.unizar.es/record/134844/files/texto_completo.pdf Versión publicada 2672166 http://zaguan.unizar.es/record/134844/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:134844 articulos driver 2026-02-17-20:19:00 ARTICLE