Species-environment relationships and potential for distribution modelling in coastal waters

被引:35
作者
Snickars, M. [1 ]
Gullstrom, M. [2 ]
Sundblad, G. [3 ]
Bergstrom, U. [4 ]
Downie, A. -L. [5 ]
Lindegarth, M. [6 ]
Mattila, J. [1 ]
机构
[1] Abo Akad Univ, Dept Biosci, Huso Biol Stn, FI-20520 Turku, Finland
[2] Stockholm Univ, Dept Ecol Environm & Plant Sci, SE-10691 Stockholm, Sweden
[3] AquaBiota Water Res, SE-11550 Stockholm, Sweden
[4] Swedish Univ Agr Sci, Dept Aquat Resources, SE-74242 Oregrund, Sweden
[5] SYKE, Finnish Environm Inst, FI-00251 Helsinki, Finland
[6] Univ Gothenburg, Dept Marine Ecol, SE-45296 Stromstad, Sweden
基金
芬兰科学院; 瑞典研究理事会;
关键词
Baltic Sea; Environmental gradients; Predictions; Review; Benthos; Biophysical relationships; PIKEPERCH SANDER-LUCIOPERCA; PLATICHTHYS-FLESUS L; NORTHERN BALTIC SEA; FISH ASSEMBLAGES; DISTRIBUTION PATTERNS; SUBSTRATUM SELECTION; COMMUNITY STRUCTURE; SPATIAL-PATTERNS; HUMAN IMPACTS; HABITAT;
D O I
10.1016/j.seares.2013.04.008
中图分类号
Q17 [水生生物学];
学科分类号
071004 [水生生物学];
摘要
Due to increasing pressure on the marine environment there is a growing need to understand species-environment relationships. To provide background for prioritising among variables (predictors) for use in distribution models, the relevance of predictors for benthic species was reviewed using the coastal Baltic Sea as a case-study area. Significant relationships for three response groups (fish, macroinvertebrates, macrovegetation) and six predictor categories (bottom topography, biotic features, hydrography, wave exposure, substrate and spatiotemporal variability) were extracted from 145 queried peer-reviewed field-studies covering three decades and six subregions. In addition, the occurrence of interaction among predictors was analysed. Hydrography was most often found in significant relationships, had low level of interaction with other predictors, but also had the most non-significant relationships. Depth and wave exposure were important in all subregions and are readily available, increasing their applicability for cross-regional modelling efforts. Otherwise, effort to model species distributions may prove challenging at larger scale as the relevance of predictors differed among both response groups and regions. Fish and hard bottom macrovegetation have the largest modelling potential, as they are structured by a set of predictors that at the same time are accurately mapped. A general importance of biotic features implies that these need to be accounted for in distribution modelling, but the mapping of most biotic features is challenging, which currently lowers the applicability. The presence of interactions suggests that predictive methods allowing for interactive effects are preferable. Detailing these complexities is important for future distribution modelling. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:116 / 125
页数:10
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