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控制大型植物过度生长的水流管理——基于栖息地适宜性模型的评估

Flow Management to Control Excessive Growth of Macrophytes - An Assessment Based on Habitat Suitability Modeling.

作者信息

Ochs Konstantin, Rivaes Rui P, Ferreira Teresa, Egger Gregory

机构信息

Forest Research Centre, Instituto Superior de Agronomia, University of Lisbon, Lisbon, Portugal.

Department of Wetland Ecology, Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Rastatt, Germany.

出版信息

Front Plant Sci. 2018 Mar 19;9:356. doi: 10.3389/fpls.2018.00356. eCollection 2018.

DOI:10.3389/fpls.2018.00356
PMID:29616067
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5868135/
Abstract

Mediterranean rivers in intensive agricultural watersheds usually display outgrowths of macrophytes - notably alien species - due to a combination of high concentrations of nutrients in the water runoff and low flows resulting from water abstraction for irrigation. Standard mechanical and chemical control is used to mitigate the problems associated with excessive growth of plant biomass: mainly less drainage capacity and higher flood risk. However, such control measures are cost and labor-intensive and do not present long-term efficiency. Although the high sensitivity of aquatic vegetation to instream hydraulic conditions is well known, management approaches based on flow management remain relatively unexplored. The aim of our study was therefore to apply physical habitat simulation techniques promoted by the Instream Flow Incremental Method (IFIM) to aquatic macrophytes - the first time it has been applied in this context - in order to model shifts in habitat suitability under different flow scenarios in the Sorraia river in central Portugal. We used this approach to test whether the risk of invasion and channel encroachment by nuisance species can be controlled by setting minimum annual flows. We used 960 randomly distributed survey points to analyze the habitat suitability for the most important aquatic species (including the invasive Brazilian milfoil , , and ) in regard to the physical parameters 'flow velocity,' 'water depth,' and 'substrate size'. We chose the lowest discharge period of the year in order to assess the hydraulic conditions while disturbances were at a low-point, thus allowing aquatic vegetation establishment and subsistence. We then used the two-dimensional hydraulic River2D software to model the potential habitat availability for different flow conditions based on the site-specific habitat suitability index for each physical parameter and species. Our results show that the growth and distribution of macrophytes in the hydrologically stable vegetation period is primarily a function of the local physical instream condition. Using site-specific preference curves and a two-dimensional hydraulic model, it was possible to determine minimum annual flows that might prevent the excessive growth and channel encroachment caused by .

摘要

在集约化农业流域的地中海河流,由于径流中养分浓度高以及灌溉取水导致流量低,通常会出现大型植物生长过剩的情况,尤其是外来物种。标准的机械和化学控制方法用于减轻与植物生物量过度增长相关的问题,主要是排水能力下降和洪水风险增加。然而,这些控制措施成本高且劳动强度大,而且没有长期效果。尽管水生植被对河道内水力条件的高敏感性是众所周知的,但基于流量管理的管理方法仍相对未被探索。因此,我们研究的目的是将由河道内流量增量法(IFIM)推广的物理栖息地模拟技术应用于水生大型植物,这是该技术首次在这种情况下应用,以便对葡萄牙中部索拉亚河不同流量情景下栖息地适宜性的变化进行建模。我们使用这种方法来测试是否可以通过设定年度最小流量来控制有害物种入侵和河道侵占的风险。我们使用960个随机分布的调查点,分析了最重要的水生物种(包括入侵性的巴西龟草等)在“流速”“水深”和“基质大小”等物理参数方面的栖息地适宜性。我们选择一年中流量最低的时期,以便在干扰处于最低点时评估水力条件,从而使水生植被得以建立和生存。然后,我们使用二维水力模型River2D软件,根据每个物理参数和物种的特定地点栖息地适宜性指数,对不同流量条件下的潜在栖息地可用性进行建模。我们的结果表明,在水文稳定的植被期,大型植物的生长和分布主要取决于当地河道内的物理条件。利用特定地点的偏好曲线和二维水力模型,可以确定可能防止由……导致的过度生长和河道侵占的年度最小流量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/ccaa011e7820/fpls-09-00356-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/cf848cdf35da/fpls-09-00356-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/f88179d467a9/fpls-09-00356-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/17d22127332a/fpls-09-00356-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/ccaa011e7820/fpls-09-00356-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/cf848cdf35da/fpls-09-00356-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/f88179d467a9/fpls-09-00356-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/17d22127332a/fpls-09-00356-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79da/5868135/ccaa011e7820/fpls-09-00356-g004.jpg

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