Fuzzy set theory for predicting the potential distribution and cost-effective monitoring of invasive species

被引:13
作者
Costa, Hugo [1 ]
Ponte, Nuno B. [2 ]
Azevedo, Eduardo B. [3 ,4 ]
Gil, Artur [5 ,6 ]
机构
[1] Univ Nottingham, Sch Geog, Nottingham NG7 2RD, England
[2] AZORINA SA, Soc Gestao Ambiental & Conservacao Nat, P-9500160 Ponta Delgada, Portugal
[3] Univ Azores CCMMG, Ctr Climate Meteorol & Global Change, Oporto, Portugal
[4] Res Ctr Agr & Environm Sci & Technol Azores CITA, P-9701851 Angra Do Heroismo, Portugal
[5] Ctr Ecol Evolut & Environm Changes CE3C, Oporto, Portugal
[6] Univ Azores, Dept Biol, Azorean Biodivers Grp, P-9501801 Ponta Delgada, Portugal
关键词
Uncertainty; MaxEnt; Invasive alien species; Management; INCORPORATING UNCERTAINTY; DISTRIBUTION MODELS; ALIEN PLANTS; MAXENT;
D O I
10.1016/j.ecolmodel.2015.07.034
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The presence of invasive species has been predicted using species distribution models (SDMs) and presence-only data to assist environmental management. However, SDMs include substantial uncertainty and the lack of absence data hampers the use of probabilistic predictions. A non-statistical theoretical basis able to deal with uncertainty on which to model invasive species distributions with presence-only data is thus needed. Fuzzy set theory satisfies these two requirements but has been little used. This paper proposes a fuzzy modelling approach for predicting invasive species potential distributions using presence-only data and SDMs to support the design of cost-effective monitoring schemes. The invasion of Gunnera tinctoria (Molina) Mirbel (Giant rhubarb) in the island of Sao Miguel (the Azores, Portugal) is used as case study. The latter involved the prediction of the potential distribution of the invader using MaxEnt and the selection of priority areas for monitoring the spread of the invader in case of scarcity of resources. In addition, MaxEnt was used within a traditional (non-fuzzy) approach, unable to quantity and report on uncertainty. The results of the fuzzy and non-fuzzy approaches are compared and their differences discussed, thus highlighting the potential benefits of using fuzzy set theory for species distribution modelling and management. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:122 / 132
页数:11
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