Toxic blooms phenology and abiotic controls in a changing ......Toxic blooms phenology and abiotic controls in a changing world. The case of Alexandrium minutum in Britany (French

Toxic blooms phenology and abiotic controls in a changing world. The case of Alexandrium minutum in Britany (French coast).

Annie Chapelle, Carles Guallar-Morillo, Cédric Bacher, Martin Plus, Marc Sourisseau, Guillaume Le Gland, Valérie le Guennec, Laure Guillou

• A. minutum blooms and toxicities, a 27 years survey on the French coast

• Environmental niche of A. minutum populations • Phenology of A. minutum blooms and its controls • Using 2 approachs, statistical and trait-based

modelling • In a changing world ?

A. minutum blooms and toxicities, a 27 years survey on the French coast

• First detection of A. minutum in 1988 (source Rephy) • Present on the English Channel, Atlantic and Mediterranean French coast

A. minutum blooms and toxicities, a 27 years survey on the French coast

High blooms leading to toxicity only in Breton Estuaries. Maximum 44 M cell L-1

(source Rephy and Final, Paralex, Daoulex projects).

• Penzé, Morlaix, Abers (since 88) • Rance (since 96) • Rade de Brest (since 2010)

A. minutum blooms and toxicities, a 27 years survey on the French coast

• Niche analysis Statistical studies : 1988 – 2014 •Phenology analysis 17 regions, 67 stations •Trait-based modelling Brest bay, 2012 - 2014

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Chlorophyll In situ, Satellite Temperature In situ, Satellite, Models

Salinity In situ, Models Turbidity In situ Oxygen In situ

Suspended Particulate Matter Satellite Nutrients (N, P, Si) In situ, Models

Irradiance Satellite Tide (coefficient and hight) In situ, Models

River flow In situ Atmospheric pressure In situ, Models

Wind (Direction, Speed) In situ, Models AMO, NAO Climate index

Environmental parameters Studied sites

Environmental niche of A. minutum populations

• ‘The ecological niche is the volume in the environmental space that permits a positive growth of the species’ (Hutchinson 1957)

• Potential niche versus realised niche

Principal Component Analysis (Trait-base modelling)

• Define environmental space

Principal Component Analysis

Environmental var. 1

Environmental var. 4

Environmental var. 2

Environmental var. 3

(Broennimann et al. 2012) Kernel density function

Environmental niche of A. minutum populations

• ‘The ecological niche is the volume in the environmental space that permits a positive growth of the species’ (Hutchinson 1957)

• Potential niche versus realised niche

(Dutkiewicz & Follows, 2009)

Traits Types of distributions Diatom or Dinoflagellate Random law (Binary reponse)

Size (1µm – 100µm) Random and uniform law

Optimal temperature (10°C – 20°C)

Random and uniform law

Maximum growth rate Eppley function ( dependence in Topt)

Minimum Quota in Nitrogen, Phosphate and Silicium

Allometric law (Trade off with size)

Maximum Quota in Nitrogen, Phosphate and Silicium

Allometric law (Trade off with size)

Maximum Uptake rate in Nitrogen, Phosphate and Silicium

Allometric law (Trade off with size and optimal temperature)

Saturation coefficient in Nitrogen, Phosphate and Silicium

Allometric law (Trade off with size)

Optimal irradiance Constant : 20 W.m-2

(Principal Component Analysis) Trait-base modelling • 50 species + A.minutum

1 25 50 75

Contour probability mass

Environmental niche of A. minutum populations

• Principal Component Analysis

Realised niche : Warm temperatures, high irradiance, low river flow Lower turbidity and higher salinities favourable

NAO and tides apparently no influence

Environmental variables Minimum Maximum

Salinity 3.20 38.10 psu

Temperature 4.40 25.90 °C

Turbidity 0.08 120.00 NTU

Sea Surface Irradiance 8.9 416.5 W · m-2

Tidal coefficient 38.6 103.9

North Atlantic Oscillation index -1.654 1.658

-0.06 -0.02 0.02 0.06

-0.0

6-0

.02

0.02

0.06

PC1 (31.3%)

PC

2 (1

7.7%

)

River flow

Salinity

Turbidity SSI

Temp.

Tidal coeff.

PC1 (34.5%)

PC2

(15.

6%)

PC3 = 14.1%

•NAO

n = 6798

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Environmental niche of A. minutum populations Trait-based numerical modelling

• A. minutum alone → Potential niche

Abun

danc

e (c

ell L

-1)

Abun

danc

e (c

ell L

-1)

A. minutum alone

A. minutum in competition

Potential niche : From May to October Realised niche : From May to August

• A. minutum in competition → Realised niche Model Data

A. minutum _____

Picoplancton _____

Nanoplancton _____

Microplancton _____

Environmental niche of A. minutum populations • Trait-based numerical modelling

Temperature control N, P control

Potential niche : Dilution, Temperature. Temperature treshold : 15°C Realised niche : Dilution, Temperature, Nutrients. Importance of competition for nutrients

T control

Bloom possible when : µ > d µ (T, I, Nut) d (tide, flow)

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

dilution - growth

15°C

temperature

‘Phenology’ characterise the life cycle phases or activities of plants and animals in their temporal occurrence throughout the year, especially in relation to climate and weather’ (Lieth 1957, Vliet & de Groot 2004)

Define Phytoplankton bloom events

1 Max. abundance day 2 Max. abundance 3 Bloom start day 4 Bloom end day 5 Bloom length

Phenology of A. minutum and its controls

0 100 200 300

0e+0

02e

+06

Al

exan

driu

m m

inut

um

0 100 200 300

0e+0

02e

+06

1. Raw data

0 100 200 300

01

23

45

6

Lo

g 10 A

lexa

ndriu

m m

inut

um

Day of the year

2. Log10 transformation

6 Increase length 7 Decrease length 8 Steepness increase 9 Steepness decrease

Day of the year

Abun

danc

e

1,2

3 4

5 6 7

8 9 Day of the year

3. Fit Weibull function

(Rolinski et al. 2007)

0 1 2 3 4 5 6 7

1length_bloom

0 100 200 300

4yday_start6yday_end

0 100 200 300

1steepness_

-2 -1 0 1 2

Log10(Alexandrium minutum)

Days

Day of the year

Day-1

Maximum abundance

Steepness increase

Decrease duration

Increase duration

Maximum abundance day

Bloom duration

Bloom end day

Bloom start day

Steepness decrease

Phenology of A. minutum and its controls

Weibull application to data (52 year-station time series)

Phenology of A. minutum and its controls

Temperature at the start of the bloom control growth rate (+), bloom length (-), bloom increase length (-), bloom lenght decrease (-).

Irradiance and Salinity also correlated but less.

Stepwise regressions with environmental parameters

8 10 12 14 16 18

020

4060

8010

012

0

df_Phen$Temp_start

df_P

hen$

raw

_len

gth_

incr

ease

Blo

om le

ngth

incr

ease

(Day

s) Bloom length increase

Linear model R2 = 0.77

Start Temperature (°C) 0.0 0.1 0.2 0.3 0.4 0.5 0.6

0.0

0.2

0.4

0.6

0.8

1.0

fitted(model_glm)

mod

el_g

lm$m

odel

$"df

_Phe

n$ Steepness increase

Obs

erve

d

Predicted

Logistic model R2 = 0.72

Temperature Temperature

Irradiance Salinity (River flow?)

Factors

Phenology of A. minutum and its controls 3 years modelling, Brest bay

2012 2013

2014

R² = 0.8995

100110120130140150

60 80 100 120

Mod

el d

ata

(d)

In situ data (d)

Start of the bloom

2012 2013

2014

R² = 0.9086

200220240260280300

285 290 295 300 305 310M

odel

dat

a (d

)

In situ data (d)

End of the bloom

2014

2013

2012

R² = 0.5986

175180185190195200205

185 190 195 200 205

Mod

el D

ata

(d)

In situ Data (d)

Day of the maximum

2012

2013

2014

R² = 0.9751

0

500000

1000000

1500000

0 20000000 40000000 60000000Mod

el d

ata

(Cel

l/L)

In situ data (Cell/L)

Max value of abondance

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Abundance max : 2012 > 2014 > 2013 Day of the maximum: 2014 > 2012 >2013 Start of the bloom : 2014 > 2013 > 2012 End of the bloom : model ≠ data

0 1 2 3 4 5 6 7

1length_bloom

0 100 200 300

4yday_start6yday_end

0 100 200 300

1steepness_

-2 -1 0 1 2

Log10(Alexandrium minutum)

Days

Day of the year

Day-1

Maximum abundance

Steepness increase

Decrease duration

Increase duration

Maximum abundance day

Bloom duration

Bloom end day

Bloom start day

Steepness decrease

Phenology of A. minutum and its controls Weibull application to data (52 year-station time series) + 3 years modelling

___ 2012

___ 2013

___ 2014

2012 is a very exceptional bloom in term of amplitude in the Brest bay Blooms in Brest bay lasted more

Phenology of A. minutum and its controls

3 years modelling, Brest bay

Temperature controls the bloom initiation Nutrients (P) control the bloom amplitude

Temperature limitation Phosphorus limitation

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

+ +

-

Alexandrium minutum phenology and controls, in a changing world ? Perspectives

Bust : Parasitic control Boom : Abitoic control Lag

Guillou et al 2015

A. minutum

Temperature

Tides

River flow

Nutrients

Climatic changes

Human changes

+

+ +

-

-

Abiotic controls

Predation Parasitism

Intra/Inter specific

competition

Life cycle

-

Biotic controls

Alexandrium minutum phenology and abiotic controls, in a changing world ? Perspectives - Scenarios

A. minutum

Temperature

Tides

River flow

Nutrients

Climatic changes

Human changes

+

+ +

-

-

Abiotic controls Biotic controls

Predation Parasitism

Intra/Inter specific

competition

Life cycle

Abiotic controls : need scenarios climatic and human changes Biotic controls : our studies and collaborations

-

Film Lann vraz (S. Daniellou)

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