DRIFT: incorporating an eco-social system network and time series approach into environmental flow assessments

IF 1.1 4区 环境科学与生态学 Q3 MARINE & FRESHWATER BIOLOGY
A. Joubert, C. Brown, J. King, H. Beuster, A. Greyling
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引用次数: 2

Abstract

DRIFT (Downstream Response to Imposed Flow Transformation) is an interactive, ecological-social process and software package to assist with environmental flow assessments and river management decision-making. It was originally developed in the 1990s and has subsequently evolved and been applied in over 50 studies in Africa, South America, Asia and Europe. Early versions provided predicted ecological responses over time to specific flow changes, while the latest version provides responses to flow and non-flow drivers as seasonal time series. Here, an ecosystem or eco-social network is built for the river, with links between driver and responder indicators, and relationships created for each link. The network and relationships are developed and entered into the software by specialists based on available data and their knowledge. A range of scenarios is explored through the predicted indicator time series, discipline and site level ecological integrity, and social well-being. While DRIFT models vary in complexity, they are all based on relatively simple fundamental principles and arithmetic. Sequential averaging and summation through the system network is used to calculate an indicator’s response to different drivers for successive seasons over time, while the discipline and site level summaries are found using weighted summation of indicator results and individual discipline results, respectively. Information from different specialist areas is therefore processed in the same way, thereby enabling coherent integration across disciplines.
DRIFT:将生态社会系统网络和时间序列方法纳入环境流量评估
DRIFT(下游对强制流量变化的响应)是一个互动的生态社会过程和软件包,用于协助环境流量评估和河流管理决策。它最初开发于20世纪90年代,后来在非洲、南美、亚洲和欧洲的50多项研究中得到了发展和应用。早期版本提供了对特定流量变化的预测生态响应,而最新版本则将流量和非流量驱动因素的响应作为季节性时间序列。在这里,为河流建立了一个生态系统或生态社会网络,在驾驶员和响应者指标之间建立了联系,并为每个联系建立了关系。网络和关系是由专家根据可用数据和他们的知识开发并输入软件的。通过预测的指标时间序列、学科和场地级别的生态完整性以及社会福祉,探索了一系列场景。虽然DRIFT模型的复杂性各不相同,但它们都基于相对简单的基本原理和算法。通过系统网络的顺序平均和求和用于计算指标在一段时间内对连续季节的不同驱动因素的响应,而学科和站点级总结分别使用指标结果和单个学科结果的加权求和来找到。因此,来自不同专业领域的信息以相同的方式处理,从而实现跨学科的连贯整合。
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来源期刊
African Journal of Aquatic Science
African Journal of Aquatic Science MARINE & FRESHWATER BIOLOGY-
CiteScore
3.90
自引率
7.10%
发文量
31
审稿时长
>12 weeks
期刊介绍: The African Journal of Aquatic Science is an international journal devoted to the study of the aquatic sciences, covering all African inland and estuarine waters. The Journal publishes peer-reviewed original scientific papers and short articles in all the aquatic science fields including limnology, hydrobiology, ecology, conservation, biomonitoring, management, water quality, ecotoxicology, biological interactions, physical properties and human impacts on African aquatic systems.
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