Assessment of ecological vulnerability and decision-making application for prioritizing roadside ecological restoration: A method combining geographic information system, Delphi survey and Monte Carlo simulationby Guobao Song, Zhe Li, Yangang Yang, Henry Musoke Semakula, Shushen Zhang

Ecological Indicators

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Year
2015
DOI
10.1016/j.ecolind.2014.11.032
Subject
Decision Sciences (all) / Ecology, Evolution, Behavior and Systematics / Ecology

Text

Ecological Indicators 52 (2015) 57–65

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Ecological Indicators j o ur na l ho me page: www.elsev ier .com

Assessment of ecological vulnerability and decisi applica re combin lph

Carlo s

Guobao S em a Key Laborator l Scien

Technology, Da b Henan Zheng c Research Insti a r t i c l

Article history:

Received 11 November 2013

Received in revised form 24 November 2014

Accepted 25 November 2014

Keywords:

Ecological vuln

Monte Carlo

GIS

Uncertainty

Fund allocatio

Study experience of ecologist plays an important role in assessing the contribution of different influencing factors to ecological vulnerability, helping policy makers to target measures for ecological restoration.

However, uncertainty is unavoidable due to variation of study experience among experts. In this study, a new method that combines Delphi survey, geographic information system and Monte Carlo simulation 1. Introdu

The asse disturbance world, espe 2013; De La 2006). Und spective is e to conduct

McLeod, 20 quantified o tool to supp

Spatial a (GIS) can q ∗ Correspon

E-mail ad (Z. Li), yg.yan zhangss@dlut. http://dx.doi.o 1470-160X/© erability assessment n was proposed to assess regional ecological vulnerability and to quantify the uncertainty of assessing result. We illustrated the capacity of this method by using a case study in northeastern Inner Mongolia,

China. An index system for 13 spatial variables was established to calculate an ecological vulnerability index (EVI) from the three aspects of ecological sensitivity (ES), ecological resilience (ER) and naturalsocial pressure (NSP). The assessment shows that the southwestern region of the study area, especially in the counties of Sonid Left and Right, was seriously threatened by a high ES and a low ER. Onguiud county in the Greater Hinggan Mountains had a high EVI due to an intensive NSP. Based on the assessing result and regional road distribution, an EVI cost curve was created to facilitate the prioritization of allocating limited funds among the various counties for roadside ecological restoration. © 2014 Elsevier Ltd. All rights reserved. ction ssment of ecological vulnerability to continuous human has received much attention in many parts of the cially under the context of climate change (Cinner et al., nge et al., 2010; Fraser et al., 2011; Füssel and Klein, erstanding ecological vulnerability from a spatial perssential for policy makers to formulate priori strategies ecological restoration (Kelly and Adger, 2000; Villa and 02). An assessment of ecological vulnerability should be ver space and time (Jin and Meng, 2011) and serve as a ort appropriate ecological restorations. nalysis supported by a geographic information system uantify ecological vulnerability by overlaying various ding author. Tel.: +86 136 1092 5530; fax: +86 41184706151821. dresses: gb.song@dlut.edu.cn (G. Song), lz1989@mail.dlut.edu.cn g@rioh.cn (Y. Yang), semhm2000@yahoo.co.uk (H.M. Semakula), edu.cn (S. Zhang). spatial variables using weighting methods (Li and Fan, 2014; Lu et al., 2012; Rahman et al., 2009). The determination of the weights, however, produces a new challenge. Several methods of spatial principal component analysis (Li et al., 2006), the analytic hierarchy process (Li and Fan, 2014; Song et al., 2010) and fuzzy membership functions (Lu et al., 2012) have been proposed to facilitate weight assignment for the various factors. The expertise of ecologists cannot be neglected but can be assessed by the Delphi survey method.

High levels of uncertainty, though, are unavoidably introduced into the final assessment due to differences in personal experience in the study of ecology. Monte Carlo simulation (Cullen and Frey, 1999;

Lo et al., 2005) that repeatedly and randomly samples the available data based on a specific probability distribution is widely applied to quantify the accumulated uncertainties (Fahd et al., 2014; Ramírez et al., 2008; Wang et al., 2008).

The practical application of ecological assessments is a separate issue, especially in China. We selected and reviewed 76 studies of the assessment of ecological vulnerability from all openly published studies in the China National Knowledge Infrastructure (CNKI), the largest literature database in China. The majority rg/10.1016/j.ecolind.2014.11.032 2014 Elsevier Ltd. All rights reserved.tion for prioritizing roadside ecological ing geographic information system, De imulation onga,∗, Zhe Lia,b, Yangang Yangc, Henry Musoke S y of Industrial Ecology and Environmental Engineering (MOE), School of Environmenta lian 116024, China da Environmental Technology & Consulting Co., Ltd, Zhengzou 450002, China tute of Highway, Ministry of Transportation, Beijing 100088, China e i n f o a b s t r a c t/ locate /eco l ind on-making storation: A method i survey and Monte akulaa, Shushen Zhanga ce and Technology, Dalian University of 58 G. Song et al. / Ecological Indicators 52 (2015) 57–65

Fig. 1. Flowch cision index; ES: eco t. of these st cal restorat spatial over decision-m ical restora results of th and practic are thus urg

As an ex roads are u priately is assessment model (Cut and respon adaptive ca of “sensitiv (2003), cou assessing e

We first es ecological s social press to quantify logical vuln spatial over tested to de ties of roads is illustrate 2. Materia 2.1. Study a

The stu autonomou 111.2–126. 47 adminis and had a p

Mongolia A semiarid an the southea fall, sandsto occasional

Wu et al., 2 area north t and the we parts of th ecotone bet ecologically ocation of the northeastern part of the Inner Mongolia Autonomous Region. ance to various ecosystems. The region had approximatelyart for the assessment of ecological vulnerability and its application for making de logical sensitivity; ER: ecological resilience; NSP: natural-social pressure; W: weigh udies did not provide practical strategies of ecologiion but focused on assessments by similar methods of lay supported by a GIS. Only three studies addressed aking protocols for the practical engineering of ecologtion but did not recommend ways to implement the eir assessments. An integration of academic research al applications associated with ecological assessment ently needed for both researchers and policy makers. ample, funds for the ecological restoration of regional sually limited. Allocating insufficient resources approthus a challenge that needs to be addressed. Many frameworks are available, such as hazard of place ter, 1996), hazard exposure, preparedness, prevention se (Weichselgartner, 2001), exposure, sensitivity and pacity (Polsky et al., 2007) etc. In this study, the model ity, resilience and pressure” proposed by Turner et al. pling human and natural systems was employed for cological vulnerability in northeastern Inner Mongolia. tablished an assessment index system incorporating ensitivity (ES), ecological resilience (ER) and naturalure (NSP). A questionnaire survey was then conducted the contribution of each factor (weight), and an ecoerability index (EVI) was further calculated by repeated laying. Finally, a case of vulnerability assessment was termine how to prioritize fund allocation for the activiide ecological restoration. A flow chart of this procedure d in Fig. 1. l and methods rea dy area (Fig. 2) is the northeastern part of the s region of Inner Mongolia, China (41.3–53.3◦ N,