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Fisheries and Oceans Canada. Pêches et Océans Canada. Canada. Ecosystem Variability in NAFO Waters Adjacent to the Newfoundland and Labrador Shelf during the Decade of 2000-2009. By E. Colbourne, P. Pepin and G. Maillet Fisheries and Oceans Canada. OUTLINE. Introduction

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By E. Colbourne, P. Pepin and G. Maillet Fisheries and Oceans Canada

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Fisheries and Oceans

Canada

Pêches et Océans

Canada

Canada

Ecosystem Variability in NAFO Waters Adjacent to the Newfoundland and Labrador Shelf during the Decade of 2000-2009

By

E. Colbourne, P. Pepin and G. Maillet

Fisheries and Oceans Canada


OUTLINE

  • Introduction

  • Decadal Scale Variability in Meteorological and Oceanographic Climate (1950-2009)

  • Intra-Decadal Variability in the Physical, Biological and Chemical Environment (2000-2009)

  • Summary


The Study Area/ Observations

  • ICNAF 1949-1979

  • NAFO 1979-Present

  • Focused on Physical Observations

  • Canadian Atlantic Zone Monitoring Program (AZMP)

  • 1999-Present


Groundfish surveys - Selected stations

Atlantic Zone Monitoring Program (AZMP)- a joint initiative of 5 DFO labs- Physical, Biological and Chemical Observations

Sections – Spring Summer and fall

Fixed stations – Every two weeks

Remote Sensing -

Bi-weekly composites

Continuous Plankton Recorder (CPR)


OUTLINE

  • Introduction

  • Decadal Scale Variability in Meteorological and Oceanographic Climate (1950-2009)

  • Intra-Decadal Variability in the Physical, Biological and Chemical Environment (2000-2009)

  • Summary


NWA AIR TEMPERATURES

NAO

AIR

TEMP

  • Highest on record during 2000s

  • Highest variability during the 1970-1990s

SST


NL SHELF SEA ICE EXTENT

Sea-Ice

Lowest Since 1960s

  • Sea-Ice Lowest Since 1960s

  • Highly variable during 1970-1990s


NL SHELF TEMPERATURES

STATION 27

  • Record High Temp in 2000s

  • Salinity Record Low in 1990s

Record High in 2000s


STANDARD SECTIONS CIL

Low Variability in 2000s, 1950S


LABRADOR CURRENT GEOSTROPHIC TRANSPORT

  • Geostrophic Transport of Labrador Current above average in 2000s.


1970s

1980s

1990s

1960s

2000s

1950s

COMPOSITE CLIMATE INDEX

  • Standardized Anomalies of 27 Meteorological, Sea Ice, Temperature, Salinity Time Series

(Xi-Xmean)/σ (1971-2000)


COMPOSITE CLIMATE INDEX

SALINITY


RECAP DECADAL TRENDS

  • The 1970s, 1980s and 1990s experienced extreme intra-decadal variability with cold/warm, fresh/saline conditions.

  • The 1990s experienced the most extreme variability and was the coldest and freshest in the 6 decades of observations.

  • The decade of 2000s was the warmest decade in over 60 years of ocean measurements but very similar to 1960s.

  • The 2000s showed among the least variability reflecting a continuing warming trend throughout the region.


OUTLINE

  • Introduction

  • Decadal Scale Variability in Meteorological and Oceanographic Climate (1950-2009)

  • Intra-Decadal Variability in the Physical, Biological and Chemical Environment (2000-2009)

  • Summary


STATION 27 – Zooplankton Biomass

  • Biomass highly variable, record low in 2008 to near-record high in 2009.

  • High levels of abundance of large and small copepods in 2009Microcalanus sp., Oithona sp., Pseudocalanus sp. and Oncaea sp.

  • Warm water species Acartia sp., Centropages sp., and Temora longicornis were at low levels of abundance.


Standard Sections (NL) Zooplankton Abundance

  • Both small and large copepods demonstrated similar patterns of variation.

  • Lowest abundances at the start of the time-series, with a gradual increase to a peak between 2004-2006.

  • After 2006, copepods were about average for the AZMP period.

  • Other groups carnivores, omnivores and non-copepod secondary producers (meroplankton) exhibited similar patterns.


SALINITY

Environmental Forcing and Biogeochemical State

  • During the 12 years of AZMP observations, the physical environment was characterized by warm saline conditions.

  • Low intra-decadal variability, reflecting the warming trend throughout the region.


PHYTOPLANKTON

NITRATE (0-50 M)

Environmental Forcing and Biogeochemical State

Standard Sections

Station 27

  • Most correlations were weak and not consistent across the region.

  • Phytoplankton at S27 demonstrated consistent negative correlations with most climate indices.

  • In general, nutrient and phytoplankton had a significantly greater proportion of negative correlations than expected by chance (85/130).

Correlation coefficients of environmental variables with biochemical indices


Environmental Forcing and Biogeochemical State

27 Zooplankton Taxa (Standard Sections)

  • No single environmental variable demonstrated a consistent pattern of correlations with the 27 zooplankton taxa.

  • And no single zooplankton taxa demonstrated a consistent pattern of correlation with any environmental index.

  • 59% of the 3080 correlations were positive, which is a significant departure from random.

Box-whisker plots of the distribution of Pearson’s correlation coefficient of each index of physical environmental variables (y-axis) with all indices of zooplankton abundance (27 taxonomic groups) from each of the four oceanographic sections.


NUTRIENTS

PHYTOPLANKTON

ZOOPLANKTON

AZMP BIOGEOCHEMICAL COMPOSITE (2000-2009)

(Xi-Xmean)/σ (Referenced 1999-2010)


Environmental Forcing and Biogeochemical State

  • The decade of 2000s was characterized by warm climate conditions.

  • The biochemical state exhibited a high degree of inter-annual variability during this period.


BIOCHEMICAL SUMMARY 2000s

  • Nutrient were weakly correlated (-ive) with the physical environment.

  • Phytoplankton at Station 27 was significantly correlated (-ive) with the physical environment.

  • Some zooplankton taxa varied by 2-orders of magnitude with a general tendency towards +ive correlations with the physical environment.

  • No single environmental index provides strong predictive capacity of the biochemical state.

  • Environmental conditions have not varied sufficiently during AZMP to allow an accurate assessment of the full response of ecosystem productivity to changes in physical drivers of the system.


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