Dynamic biogeochemical provinces in the global ocean

被引:160
作者
Reygondeau, Gabriel [1 ,2 ,3 ]
Longhurst, Alan
Martinez, Elodie [2 ,4 ]
Beaugrand, Gregory [5 ]
Antoine, David [2 ,6 ]
Maury, Olivier [1 ]
机构
[1] Ins Rec Dev, Ctr Rech Halieut Mediterraneennes & Trop, UMR EME 212, FR-34203 Sete, France
[2] Univ Paris 06, CNRS, Lab Oceanog Villefranche, Villefranche Sur Mer, France
[3] Univ Oslo, Ctr Ecol & Evolutionary Synth, Dept Biosci, Oslo, Norway
[4] Univ Aix Marseille, CNRS INSU UMR 7294, Mediterranean Inst Oceanog, IRD UMR 235, Marseille, France
[5] Univ Sci & Technol Lille, CNRS, UMR LOG CNRS 8187, Lab Oceanol & Geosci,Stn Marine, Wimereux, France
[6] Curtin Univ, Dept Imaging & Appl Phys, Remote Sensing & Satellite Res Grp, Perth, WA 6845, Australia
关键词
Biogeography; Biogeochemical province; Biome; Seasonality; Meteo-oceanic oscillations; TIME-SERIES ANALYSIS; CLIMATE; VARIABILITY; COASTAL; SEA; OSCILLATION; MODEL; ZONE; TUNA;
D O I
10.1002/gbc.20089
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In recent decades, it has been found useful to partition the pelagic environment using the concept of biogeochemical provinces, or BGCPs, within each of which it is assumed that environmental conditions are distinguishable and unique at global scale. The boundaries between provinces respond to features of physical oceanography and, ideally, should follow seasonal and interannual changes in ocean dynamics. But this ideal has not been fulfilled except for small regions of the oceans. Moreover, BGCPs have been used only as static entities having boundaries that were originally established to compute global primary production. In the present study, a new statistical methodology based on non-parametric procedures is implemented to capture the environmental characteristics within 56 BGCPs. Four main environmental parameters (bathymetry, chlorophyll a concentration, surface temperature, and salinity) are used to infer the spatial distribution of each BGCP over 1997-2007. The resulting dynamic partition allows us to integrate changes in the distribution of BGCPs at seasonal and interannual timescales, and so introduces the possibility of detecting spatial shifts in environmental conditions.
引用
收藏
页码:1046 / 1058
页数:13
相关论文
共 66 条
[1]  
[Anonymous], 1936, P NATL I SCI INDIA, DOI DOI 10.1007/S13171-019-00164-5
[2]  
[Anonymous], P WORLD SCI M BIOL S
[3]  
Antonov J.I., 2006, WORLD OCEAN ATLAS 20, V2
[4]   A new model to assess the probability of occurrence of a species, based on presence-only data [J].
Beaugrand, G. ;
Lenoir, S. ;
Ibanez, F. ;
Mante, C. .
MARINE ECOLOGY PROGRESS SERIES, 2011, 424 :175-190
[5]   Differences in performance among four indices used to evaluate diversity in planktonic ecosystems [J].
Beaugrand, G ;
Edwards, M .
OCEANOLOGICA ACTA, 2001, 24 (05) :467-477
[6]   Simple procedures to assess and compare the ecological niche of species [J].
Beaugrand, Gregory ;
Helaouet, Pierre .
MARINE ECOLOGY PROGRESS SERIES, 2008, 363 :29-37
[7]  
Brander Keith, 2009, Journal of the Marine Biological Association of India, V51, P1
[8]   THE LOGNORMAL-DISTRIBUTION AS A MODEL FOR BIOOPTICAL VARIABILITY IN THE SEA [J].
CAMPBELL, JW .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 1995, 100 (C7) :13237-13254
[9]   Satellite remote sensing for an ecosystem approach to fisheries management [J].
Chassot, Emmanuel ;
Bonhommeau, Sylvain ;
Reygondeau, Gabriel ;
Nieto, Karen ;
Polovina, Jeffrey J. ;
Huret, Martin ;
Dulvy, Nicholas K. ;
Demarcq, Herve .
ICES JOURNAL OF MARINE SCIENCE, 2011, 68 (04) :651-666
[10]   El Nino/Southern Oscillation and tropical Pacific climate during the last millennium [J].
Cobb, KM ;
Charles, CD ;
Cheng, H ;
Edwards, RL .
NATURE, 2003, 424 (6946) :271-276