An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling

Abstract Riparian environments are highly dynamic ecosystems that support biodiversity and numerous services and that are conditioned by anthropogenic activities and climate change. In this work, we propose an integrated methodology that combines different research approaches—field studies and numer...

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Autores principales:	M. Latella, M. B. Bertagni, P. Vezza, C. Camporeale
Formato:	article
Lenguaje:	EN
Publicado:	American Geophysical Union (AGU) 2020
Materias:	flow‐vegetation interactions impact models model calibration riparian vegetation stochastic processes Physical geography GB3-5030 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/5168b992c5294d2190b8b2fe2d21c149
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spelling	oai:doaj.org-article:5168b992c5294d2190b8b2fe2d21c1492021-11-15T14:20:27ZAn Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling1942-246610.1029/2020MS002094https://doaj.org/article/5168b992c5294d2190b8b2fe2d21c1492020-08-01T00:00:00Zhttps://doi.org/10.1029/2020MS002094https://doaj.org/toc/1942-2466Abstract Riparian environments are highly dynamic ecosystems that support biodiversity and numerous services and that are conditioned by anthropogenic activities and climate change. In this work, we propose an integrated methodology that combines different research approaches—field studies and numerical and analytical modeling—in order to calibrate an ecohydrological stochastic model for riparian vegetation. The model yields vegetation biomass statistics and requires hydrological, topographical, and biological data as input. The biological parameters, namely, the carrying capacity and the flood‐related decay rate, are the target of the calibration as they are related to intrinsic features of vegetation and site‐specific environmental conditions. The calibration is here performed for two bars located within the riparian zone of the Cinca River (Spain). According to our results, the flood‐related decay rate has a spatial dependence that reflects the zonation of different plant species over the study site. The carrying capacity depends on the depth of the phreatic surface, and it is adequately described by a right‐skewed curve. The calibrated model well reproduces the actual biogeography of the Cinca riparian zone. The overall percentage absolute difference between the real and the computed biomass amounts to 9.3% and 3.3% for the two bars. The model is further used to predict the future evolution of riparian vegetation in a climate‐change scenario. The results show that the change of hydrological regime forecast by future climate projections may induce dramatic reduction of vegetation biomass and strongly modify the Cinca riparian biogeography.M. LatellaM. B. BertagniP. VezzaC. CamporealeAmerican Geophysical Union (AGU)articleflow‐vegetation interactionsimpact modelsmodel calibrationriparian vegetationstochastic processesPhysical geographyGB3-5030OceanographyGC1-1581ENJournal of Advances in Modeling Earth Systems, Vol 12, Iss 8, Pp n/a-n/a (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	flow‐vegetation interactions impact models model calibration riparian vegetation stochastic processes Physical geography GB3-5030 Oceanography GC1-1581
spellingShingle	flow‐vegetation interactions impact models model calibration riparian vegetation stochastic processes Physical geography GB3-5030 Oceanography GC1-1581 M. Latella M. B. Bertagni P. Vezza C. Camporeale An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
description	Abstract Riparian environments are highly dynamic ecosystems that support biodiversity and numerous services and that are conditioned by anthropogenic activities and climate change. In this work, we propose an integrated methodology that combines different research approaches—field studies and numerical and analytical modeling—in order to calibrate an ecohydrological stochastic model for riparian vegetation. The model yields vegetation biomass statistics and requires hydrological, topographical, and biological data as input. The biological parameters, namely, the carrying capacity and the flood‐related decay rate, are the target of the calibration as they are related to intrinsic features of vegetation and site‐specific environmental conditions. The calibration is here performed for two bars located within the riparian zone of the Cinca River (Spain). According to our results, the flood‐related decay rate has a spatial dependence that reflects the zonation of different plant species over the study site. The carrying capacity depends on the depth of the phreatic surface, and it is adequately described by a right‐skewed curve. The calibrated model well reproduces the actual biogeography of the Cinca riparian zone. The overall percentage absolute difference between the real and the computed biomass amounts to 9.3% and 3.3% for the two bars. The model is further used to predict the future evolution of riparian vegetation in a climate‐change scenario. The results show that the change of hydrological regime forecast by future climate projections may induce dramatic reduction of vegetation biomass and strongly modify the Cinca riparian biogeography.
format	article
author	M. Latella M. B. Bertagni P. Vezza C. Camporeale
author_facet	M. Latella M. B. Bertagni P. Vezza C. Camporeale
author_sort	M. Latella
title	An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title_short	An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title_full	An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title_fullStr	An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title_full_unstemmed	An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title_sort	integrated methodology to study riparian vegetation dynamics: from field data to impact modeling
publisher	American Geophysical Union (AGU)
publishDate	2020
url	https://doaj.org/article/5168b992c5294d2190b8b2fe2d21c149
work_keys_str_mv	AT mlatella anintegratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT mbbertagni anintegratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT pvezza anintegratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT ccamporeale anintegratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT mlatella integratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT mbbertagni integratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT pvezza integratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling AT ccamporeale integratedmethodologytostudyriparianvegetationdynamicsfromfielddatatoimpactmodeling
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An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling

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