Application of a generalized additive model (GAM) to reveal relationships between environmental factors and distributions of pelagic fish and krill: a case study in Sendai Bay, Japan

被引:134
作者
Murase, Hiroto [1 ]
Nagashima, Hiroshi [2 ]
Yonezaki, Shiroh [3 ]
Matsukura, Ryuichi [4 ]
Kitakado, Toshihide [5 ]
机构
[1] Inst Cetacean Res, Chuo Ku, Tokyo 1040055, Japan
[2] Miyagi Prefecture Fisheries Technol Inst, Ishinomaki, Miyagi 9862135, Japan
[3] Natl Res Inst Far Seas Fisheries, Shimizu Ku, Shizuoka 4248633, Japan
[4] Hokkaido Univ, Grad Sch Environm Sci, Hakodate, Hokkaido 0418611, Japan
[5] Tokyo Univ Marine Sci & Technol, Minato Ku, Tokyo 1088477, Japan
关键词
abundance estimation; distribution model; echosounder; ecosystem; fish; GAM; habitat model; marine ecology; POLLOCK THERAGRA-CHALCOGRAMMA; BERING-SEA; CLUPEA-HARENGUS; SPECIES DISTRIBUTION; ECOLOGICAL THEORY; ACOUSTIC SURVEYS; NORTH-SEA; ZOOPLANKTON; ABUNDANCE; COPEPODS;
D O I
10.1093/icesjms/fsp105
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
A generalized additive model (GAM) was applied to fishery-survey data to reveal the influences of environmental factors on the distribution patterns of Japanese anchovy (Engraulis japonicus), sand lance (Ammodytes personatus), and krill (Euphausia pacifica). Echosounder and physical-oceanographic data were collected in Sendai Bay, Japan, in spring 2005. A hierarchical model was used with two spatial strata: (i) presence and absence of each species; and (ii) biomass density of each species, given its presence; and six environmental covariates (surface water temperature, salinity, and chlorophyll, and near-seabed water temperature, salinity, and depth). The results indicate non-linear responses of the two indices to the environmental covariates. In addition, the biomasses estimated by the GAMs were comparable with estimates based on conventional, stratified-random sampling for each species. GAMs are very useful for (i) investigating the effects of environmental factors on the distributions of biological organisms, and (ii) predicting the distributions of animal densities in unsurveyed areas.
引用
收藏
页码:1417 / 1424
页数:8
相关论文
共 35 条
[1]  
AGLEN A, 1989, 1989B30 ICES CM
[2]  
[Anonymous], 195 ICES
[3]  
[Anonymous], 2007, R LANG ENV STAT COMP
[4]   Species distribution models and ecological theory: A critical assessment and some possible new approaches [J].
Austin, Mike .
ECOLOGICAL MODELLING, 2007, 200 (1-2) :1-19
[5]   Spatial prediction of species distribution: an interface between ecological theory and statistical modelling [J].
Austin, MP .
ECOLOGICAL MODELLING, 2002, 157 (2-3) :101-118
[6]   Changes in the spatial distribution of autumn spawning herring (Clupea harengus L.) derived from annual acoustic surveys during the period 1984-1996 [J].
Bailey, MC ;
Maravelias, CD ;
Simmonds, EJ .
ICES JOURNAL OF MARINE SCIENCE, 1998, 55 (03) :545-555
[7]   Spatio-temporal patterns in herring (Clupea harengus L.) school abundance and size in the northwest North Sea:: modelling space-time dependencies to allow examination of the impact of local school abundance on school size [J].
Beare, DJ ;
Reid, DG ;
Petitgas, P .
ICES JOURNAL OF MARINE SCIENCE, 2002, 59 (03) :469-479
[8]   An estimate of error for the CCAMLR 2000 survey estimate of krill biomass [J].
Demer, DA .
DEEP-SEA RESEARCH PART II-TOPICAL STUDIES IN OCEANOGRAPHY, 2004, 51 (12-13) :1237-1251
[10]   Predictive habitat distribution models in ecology [J].
Guisan, A ;
Zimmermann, NE .
ECOLOGICAL MODELLING, 2000, 135 (2-3) :147-186