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Slide 1 of 11
Changes in zooplankton
phenology at stn MC 1984-2010
Heather Anne Wright
LTER-MC MareChiara meeting
18. October.2012
Changes in zooplankton phenology
Heather.Wright@szn.it
Slide 2 of 11
Part I determine phenology
1. plankton taxa selection (20 zooplankton taxa)
2. exploratory data analysis (EDA)
3. identify trends in seasonal and long term abundance
4. determine phenology
5. significant change in phenology by seasons
Part II determine environmental drivers
1. Select environmental parameters/data
2. Calculate anomalies
3. Correlate phenological timing with anomalies (by year)
Changes in zooplankton phenology
Heather.Wright@szn.it
Introduction
Slide 3 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: plankton taxa selection
Mazzocchi et al., 2011. Zooplankton
associations in a Mediterranean long-
term time-series. JPR 23: 1163–1181.
Heat map analysis
L. Dubroca 1984:2006
C. Tortora 1984:2010
Discrimination using:
cluster analysis
heat map plots
EDA to explore:
abundance
frequency (omit rare)
season of occurrence
To select taxa:
dominant
ecological role
Slide 4 of 11
Part I: zooplankton taxa selection
Changes in zooplankton phenology
Heather.Wright@szn.it
Slide 5 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: EDA
Season of occurrence + peak
AMJ spring JAS JFM and OND
Slide 6 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: identify phenology
p=0.0172
Slide 7 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: changes in phenology SPRING taxa
Acartia clausi
∆ phenology 2°
End of season earlier when warmer
JAS_2m vs. 75% *p=0.0388
Centropages typicus
≠ phenology
Trend in 1° NS
End of season earlier when warmer
JAS_int vs. 75% *p=0.0281
Oithona similis
∆ phenology 1°
end of season earlier when warmer
OND_2m vs. 75% *p=0.0399
Slide 8 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: changes in phenology SUMMER taxa
Clausocalanus furcatus
∆ phenology 2°
Phenology delayed and shorter
Duration shorter when warmer
JAS_int vs. Duration **p=0.0014
Peak in September
Paracalanus parvus
≠ phenology
Trend in 1° NS
start of season earlier when warmer
MAM_2m vs. 25% *p=0.0174
Peak in peak in August
start of season driven by temp
Slide 9 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: changes in phenology AUTUMN taxa
Temora stylifera
∆ phenology
End of season earlier
Peak in October
Calocalanus spp.
∆ phenology 2°
Earlier in spring, later in autumn
Bimodal peak in April and Nov
Correlation with JAS_int Temp.
Chaetognaths
∆ phenology 2°
Peak in October
JAS_2m vs. 75%
End of season is later when
summer temp is higher
Slide 10 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Oncaeidae
≠ phenology
No trend in phenology
No correlations with timing vs. Temp
bimodal
appendicularia
≠ phenology
Slight trend in timing vs. Temp
[7:12] vs. OND_2m NS
Removed 1987 and 1998 outliers
bimodal
Cirripedia larvae
≠ phenology
Slight trend in timing vs. Temp
[7:12] vs. JAS_int NS
bimodal
Part I: changes in phenology WINTER taxa
Slide 11 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Summary of results (in progress)
Spring taxa:
End of season is significantly correlated with temperature anomalies in summer and
Autumn. Taxa with a June peak are correlated with JAS (summer) temperature and taxa
with a October peak are correlated with OND (autumn) temperature.
Summer taxa:
Start of season in earlier and duration is shorter when temperature anomalies are above
average. Taxa with an August peak are significantly correlated with spring MAM temp.
Autumn taxa:
End of season is earlier for T.stylifera when temp anomalies are higher, but the end of
season later when warmer for other species. Not a consistent trend in Autumn taxa
Winter taxa:
No significant changes in phenology. All selected winter zooplankton taxa are bimodal.
Slide 12 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Acknowledgements
LTER-MC and MECA – for sampling and data
Grazia Mazzocchi, SZN – director of studies
Adriana Zingone , SZN– internal advisor
Diana Sarno, SZN – phytoplankton taxonomy
Francesca Margiotta, SZN-MECA
Enzo Saggiomo, SZN-MECA
Laurent Dubroca , IFRMER– external collaborator
Cristina Tortora, SZN – post-doc, collaborator
Slide 13 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part I: example of methods
Part II (1995-2010)
Start *p=0.011
Middle **p=0.006
End *p=0.013
Cumulative percentile method:
start 25% middle 50% end 75%
Timing of central tendency [1:12] or [1:6, 7:12]
Slide 14 of 11
Changes in zooplankton phenology
Heather.Wright@szn.it
Part II: example of anomalies
What is an anomaly?
The term temperature anomaly means a departure from a reference value or long-
term average. A positive anomaly indicates that the observed temperature was
warmer than the reference value, while a negative anomaly indicates that the
observed temperature was cooler than the reference value.
Reference:
http://www.ncdc.noaa.gov/cmb-faq/anomalies.php

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LTER meeting 2012

  • 1. Slide 1 of 11 Changes in zooplankton phenology at stn MC 1984-2010 Heather Anne Wright LTER-MC MareChiara meeting 18. October.2012 Changes in zooplankton phenology Heather.Wright@szn.it
  • 2. Slide 2 of 11 Part I determine phenology 1. plankton taxa selection (20 zooplankton taxa) 2. exploratory data analysis (EDA) 3. identify trends in seasonal and long term abundance 4. determine phenology 5. significant change in phenology by seasons Part II determine environmental drivers 1. Select environmental parameters/data 2. Calculate anomalies 3. Correlate phenological timing with anomalies (by year) Changes in zooplankton phenology Heather.Wright@szn.it Introduction
  • 3. Slide 3 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: plankton taxa selection Mazzocchi et al., 2011. Zooplankton associations in a Mediterranean long- term time-series. JPR 23: 1163–1181. Heat map analysis L. Dubroca 1984:2006 C. Tortora 1984:2010 Discrimination using: cluster analysis heat map plots EDA to explore: abundance frequency (omit rare) season of occurrence To select taxa: dominant ecological role
  • 4. Slide 4 of 11 Part I: zooplankton taxa selection Changes in zooplankton phenology Heather.Wright@szn.it
  • 5. Slide 5 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: EDA Season of occurrence + peak AMJ spring JAS JFM and OND
  • 6. Slide 6 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: identify phenology p=0.0172
  • 7. Slide 7 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: changes in phenology SPRING taxa Acartia clausi ∆ phenology 2° End of season earlier when warmer JAS_2m vs. 75% *p=0.0388 Centropages typicus ≠ phenology Trend in 1° NS End of season earlier when warmer JAS_int vs. 75% *p=0.0281 Oithona similis ∆ phenology 1° end of season earlier when warmer OND_2m vs. 75% *p=0.0399
  • 8. Slide 8 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: changes in phenology SUMMER taxa Clausocalanus furcatus ∆ phenology 2° Phenology delayed and shorter Duration shorter when warmer JAS_int vs. Duration **p=0.0014 Peak in September Paracalanus parvus ≠ phenology Trend in 1° NS start of season earlier when warmer MAM_2m vs. 25% *p=0.0174 Peak in peak in August start of season driven by temp
  • 9. Slide 9 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: changes in phenology AUTUMN taxa Temora stylifera ∆ phenology End of season earlier Peak in October Calocalanus spp. ∆ phenology 2° Earlier in spring, later in autumn Bimodal peak in April and Nov Correlation with JAS_int Temp. Chaetognaths ∆ phenology 2° Peak in October JAS_2m vs. 75% End of season is later when summer temp is higher
  • 10. Slide 10 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Oncaeidae ≠ phenology No trend in phenology No correlations with timing vs. Temp bimodal appendicularia ≠ phenology Slight trend in timing vs. Temp [7:12] vs. OND_2m NS Removed 1987 and 1998 outliers bimodal Cirripedia larvae ≠ phenology Slight trend in timing vs. Temp [7:12] vs. JAS_int NS bimodal Part I: changes in phenology WINTER taxa
  • 11. Slide 11 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Summary of results (in progress) Spring taxa: End of season is significantly correlated with temperature anomalies in summer and Autumn. Taxa with a June peak are correlated with JAS (summer) temperature and taxa with a October peak are correlated with OND (autumn) temperature. Summer taxa: Start of season in earlier and duration is shorter when temperature anomalies are above average. Taxa with an August peak are significantly correlated with spring MAM temp. Autumn taxa: End of season is earlier for T.stylifera when temp anomalies are higher, but the end of season later when warmer for other species. Not a consistent trend in Autumn taxa Winter taxa: No significant changes in phenology. All selected winter zooplankton taxa are bimodal.
  • 12. Slide 12 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Acknowledgements LTER-MC and MECA – for sampling and data Grazia Mazzocchi, SZN – director of studies Adriana Zingone , SZN– internal advisor Diana Sarno, SZN – phytoplankton taxonomy Francesca Margiotta, SZN-MECA Enzo Saggiomo, SZN-MECA Laurent Dubroca , IFRMER– external collaborator Cristina Tortora, SZN – post-doc, collaborator
  • 13. Slide 13 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part I: example of methods Part II (1995-2010) Start *p=0.011 Middle **p=0.006 End *p=0.013 Cumulative percentile method: start 25% middle 50% end 75% Timing of central tendency [1:12] or [1:6, 7:12]
  • 14. Slide 14 of 11 Changes in zooplankton phenology Heather.Wright@szn.it Part II: example of anomalies What is an anomaly? The term temperature anomaly means a departure from a reference value or long- term average. A positive anomaly indicates that the observed temperature was warmer than the reference value, while a negative anomaly indicates that the observed temperature was cooler than the reference value. Reference: http://www.ncdc.noaa.gov/cmb-faq/anomalies.php