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

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...

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Autores principales: Latella, M., Bertagni, M. B., Vezza, P., Camporeale, C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507785/
https://www.ncbi.nlm.nih.gov/pubmed/32999706
http://dx.doi.org/10.1029/2020MS002094
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author Latella, M.
Bertagni, M. B.
Vezza, P.
Camporeale, C.
author_facet Latella, M.
Bertagni, M. B.
Vezza, P.
Camporeale, C.
author_sort Latella, M.
collection PubMed
description 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.
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spelling pubmed-75077852020-09-28 An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling Latella, M. Bertagni, M. B. Vezza, P. Camporeale, C. J Adv Model Earth Syst Research Articles 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. John Wiley and Sons Inc. 2020-08-19 2020-08 /pmc/articles/PMC7507785/ /pubmed/32999706 http://dx.doi.org/10.1029/2020MS002094 Text en ©2020. The Authors. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Latella, M.
Bertagni, M. B.
Vezza, P.
Camporeale, C.
An Integrated Methodology to Study Riparian Vegetation Dynamics: From Field Data to Impact Modeling
title 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_short 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
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507785/
https://www.ncbi.nlm.nih.gov/pubmed/32999706
http://dx.doi.org/10.1029/2020MS002094
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