Influence of model selection on the predicted distribution of the seagrass Zostera marina

被引:48
作者
Downie, Anna-Leena [1 ,3 ]
von Numers, Mikael [2 ]
Bostrom, Christoffer [2 ]
机构
[1] Finnish Environm Inst, Ctr Marine Res, Helsinki 00251, Finland
[2] Abo Akad Univ, FIN-20520 Turku, Finland
[3] Ctr Environm Fisheries & Aquaculture Sci, Lowestoft NR33 0HT, Suffolk, England
关键词
Zostera marina; habitat suitability; GAM; Maxent; spatial predictions; ecological niche; Baltic Sea; GENERALIZED ADDITIVE-MODELS; FAVORABILITY FUNCTIONS; SPECIES DISTRIBUTIONS; HABITAT SUITABILITY; THRESHOLD CRITERIA; AQUATIC VEGETATION; ECOSYSTEM; PROBABILITY; EELGRASS; SEA;
D O I
10.1016/j.ecss.2012.12.020
中图分类号
Q17 [水生生物学];
学科分类号
071004 ;
摘要
There is an increasing need to model the distribution of species and habitats for effective conservation planning, but there is a paucity of models for the marine environment. We used presence (131) and absence (219) records of the marine angiosperm Zostera marina L from the archipelago of SW Finland, northern Baltic Sea, to model its distribution in a 5400 km(2) area. We used depth, slope, turbidity, wave exposure and distance to sandy shores as environmental predictors, and compared a presence-absence method: generalised additive model (GAM), with a presence only method: maximum entropy (Maxent). Models were validated using semi-independent data sets. Both models performed well and described the niche of Z marina fairly consistently, although there were differences in the way the models weighted the environmental variables, and consequently the spatial predictions differed somewhat. A notable outcome from the process was that with relatively equal model performance, the area actually predicted in geographical space can vary by twofold. The area predicted as suitable for Z marina by the ensemble was almost half of that predicted by the GAM model by itself. The ensemble of model predictions increased the model predictive capability marginally and clearly shifted the model towards a more conservative prediction, increasing specificity, but at the same time sacrificing sensitivity. The environmental predictors selected into the final models described the potential distribution of Z. marina well and showed that in the northern Baltic the species occupies a narrow niche, typically thriving in shallow and moderately exposed to exposed locations near sandy shores. We conclude that a prediction based on a combination of model results provides a more realistic estimate of the core area suitable for Z. marina and should be the modelling approach implemented in conservation planning and management. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:8 / 19
页数:12
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