Hydrology-oriented forest management trade-offs. A modeling framework coupling field data, simulation results and Bayesian Networks

Alberto Garcia-Prats; María González-Sanchis; Antonio D Del Campo; Cristina Lull

doi:10.1016/j.scitotenv.2018.05.134

Hydrology-oriented forest management trade-offs. A modeling framework coupling field data, simulation results and Bayesian Networks

Sci Total Environ. 2018 Oct 15:639:725-741. doi: 10.1016/j.scitotenv.2018.05.134. Epub 2018 May 26.

Authors

Alberto Garcia-Prats¹, María González-Sanchis², Antonio D Del Campo², Cristina Lull²

Affiliations

¹ Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de Vera s/n. 46022, Valencia, Spain. Electronic address: agprats@upvnet.upv.es.
² Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de Vera s/n. 46022, Valencia, Spain.

PMID: 29803044
DOI: 10.1016/j.scitotenv.2018.05.134

Abstract

Hydrology-oriented forest management sets water as key factor of the forest management for adaptation due to water is the most limiting factor in the Mediterranean forest ecosystems. The aim of this study was to apply Bayesian Network modeling to assess potential indirect effects and trade-offs when hydrology-oriented forest management is applied to a real Mediterranean forest ecosystem. Water, carbon and nitrogen cycles, and forest fire risk were included in the modeling framework. Field data from experimental plots were employed to calibrate and validate the mechanistic Biome-BGCMuSo model that simulates the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere. Many other 50-year long scenarios with different conditions to the ones measured in the field experiment were simulated and the outcomes employed to build the Bayesian Network in a linked chain of models. Hydrology-oriented forest management was very positive insofar as more water was made available to the stand because of an interception reduction. This resource was made available to the stand, which increased the evapotranspiration and its components, the soil water content and a slightly increase of deep percolation. Conversely, Stemflow was drastically reduced. No effect was observed on Runof due to the thinning treatment. The soil organic carbon content was also increased which in turn caused a greater respiration. The long-term effect of the thinning treatment on the LAI was very positive. This was undoubtedly due to the increased vigor generated by the greater availability of water and nutrients for the stand and the reduction of competence between trees. This greater activity resulted in an increase in GPP and vegetation carbon, and therefore, we would expect a higher carbon sequestration. It is worth emphasizing that this extra amount of water and nutrients was taken up by the stand and did not entail any loss of nutrients.

Keywords: Bayesian Network modeling; Biome-BGCMuSo model; Hydrology-oriented forest management.