Latella M, Bertagni M B, Vezza P, Camporeale C
Department of Environmental, Land and Infrastructure Engineering Politecnico di Torino Turin Italy.
J Adv Model Earth Syst. 2020 Aug;12(8):e2020MS002094. doi: 10.1029/2020MS002094. Epub 2020 Aug 19.
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.
河岸环境是高度动态的生态系统,支持生物多样性和众多生态系统服务,且受到人为活动和气候变化的影响。在这项工作中,我们提出了一种综合方法,该方法结合了不同的研究方法——实地研究以及数值和分析建模——以便校准河岸植被的生态水文随机模型。该模型可得出植被生物量统计数据,并需要水文、地形和生物数据作为输入。生物参数,即承载能力和与洪水相关的衰减率,是校准的目标,因为它们与植被的内在特征和特定地点的环境条件相关。这里针对位于西班牙辛卡河河岸带内的两个河漫滩进行校准。根据我们的结果,与洪水相关的衰减率具有空间依赖性,这反映了研究区域内不同植物物种的带状分布。承载能力取决于潜水面的深度,并且可以用右偏曲线进行充分描述。校准后的模型很好地再现了辛卡河河岸带的实际生物地理学。两个河漫滩实际生物量与计算生物量之间的总体绝对差异百分比分别为9.3%和3.3%。该模型还用于预测气候变化情景下河岸植被的未来演变。结果表明,未来气候预测所预测的水文状况变化可能会导致植被生物量急剧减少,并强烈改变辛卡河河岸生物地理学。