首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Assessing and predicting biodiversity in a floodplain ecosystem: Assimilation of net primary production derived from imaging spectrometer data into a dynamic vegetation model
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Assessing and predicting biodiversity in a floodplain ecosystem: Assimilation of net primary production derived from imaging spectrometer data into a dynamic vegetation model

机译:评估和预测洪泛区生态系统中的生物多样性:将来自成像光谱仪数据的净初级生产同化为动态植被模型

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New concepts for river management in northwestern Europe are being developed which aim at both flood protection and nature conservation. As a result, methods are required that assess the effect of management activities on the biodiversity of floodplain ecosystems. In this paper, we show that dynamic vegetation models (DVMs) in combination with regional scale derived remote sensing products can be adopted to assess both current and future ecosystem development and biodiversity status of a complex floodplain ecosystem in the Netherlands. The dynamic vegetation model SMART2-SUMO2 in combination with the nature valuation model NTM3 predicting potential floristic diversity was applied to simulate the biodiversity status of the Millingerwaard floodplain along the river Rhine in the Netherlands. Estimates of net primary production (NPP) derived from airborne HyMap imaging spectrometer data were used for validation of the simulated NPP by the DVM at the time of data acquisition in 2004. Imaging spectrometer derived NPP was in good agreement with the SMART2-SUMO2 modeled results. The NTM3 derived nature valuation in 2004 expressed as plant diversity for the floodplain was high and well in agreement with field observations. In a next step, the DVM was re-initialized using imaging spectrometer derived NPP in 2004 and a forecast of plant diversity and biomass development in 2050 was made. A comparison was performed for three pre-defined floodplain management scenarios using a data-assimilation based approach as well as one without. Significant differences in biomass development can be observed between the scenarios. Predicted plant diversity for individual ecosystems in 2050 shows increased variability for forest ecosystems compared to grass ecosystems. This shows that floodplain management should take advantage of spatiotemporal dynamics of the floodplain as a basis for fostering the development of increased biodiversity. The results of this study demonstrate that imaging spectrometer derived products can be used for validation and initialization of DVMs. (C) 2008 Elsevier Inc. All rights reserved.
机译:正在开发西北欧河流管理的新概念,其目的是同时进行防洪和自然保护。结果,需要采取方法来评估管理活动对洪泛区生态系统生物多样性的影响。在本文中,我们表明,可以采用动态植被模型(DVM)结合区域尺度衍生的遥感产品来评估荷兰当前和未来的生态系统发展以及复杂的洪泛区生态系统的生物多样性状况。将动态植被模型SMART2-SUMO2与预测潜在植物区系的自然价值评估模型NTM3结合,用于模拟荷兰莱茵河沿岸的Millingerwaard漫滩的生物多样性状况。从机载HyMap成像光谱仪数据得出的净初级生产(NPP)估计值用于在2004年数据采集时通过DVM验证模拟的NPP。成像光谱仪得出的NPP与SMART2-SUMO2建模结果非常吻合。 NTM3在2004年得出的自然估值表示为洪泛区的植物多样性很高,并且与实地观测非常吻合。下一步,DVM在2004年使用成像光谱仪得出的NPP重新初始化,并预测了2050年植物的多样性和生物量的发展。使用基于数据同化的方法对三种预定义的洪泛区管理方案进行了比较,对于没有预定义的方案,则进行了比较。场景之间可以观察到生物量发展的显着差异。预测的2050年单个生态系统的植物多样性显示,与草类生态系统相比,森林生态系统的变异性增加。这表明,洪泛区管理应充分利用洪泛区的时空动态,以此作为促进发展生物多样性的基础。这项研究的结果表明,成像光谱仪衍生的产品可用于DVM的验证和初始化。 (C)2008 Elsevier Inc.保留所有权利。

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