Plant ecological niche distribution along heavy metal gradients

(1)

Sylvain Boisson, Arnaud Monty,

Maxime Séleck , Mylor Ngoy Shutcha,

Michel-Pierre Faucon, Grégory Mahy

(2)

Ecological niche

• Place occupied by an organism in ecosystem (Grinnell, 1917)

• Sum of conditions that allow an organism to occur in environment

26/06/2013 56th IAVS Symposium | June 26-30 2013 | Tartu 2

(3)

Ecological niche

• Place occupied by an organism in ecosystem (Grinnell, 1917)

• Sum of conditions that allow an organism to occur in environment

• Role of an organism in ecosystem (Elton, 1927)

• Influence a an organism on his environment

(4)

Ecological niche

• Place occupied by an organism in ecosystem (Grinnell, 1917)

• Sum of conditions that allow an organism to occur in environment

• Role of an organism in ecosystem (Elton, 1927)

• Influence a an organism on his environment

• n-dimensional hypervolume (Hutchinson, 1957)

• Dimensions = conditions and resources

26/06/2013 56th IAVS Symposium | June 26-30 2013 | Tartu

V1

V2

V3

3-dimensions niche (V)

(5)

Ecological niche

• For one environmental factor

GRADIENT

A

B

U

N

D

A

N

C

E

5

(6)

Ecological niche

• For one environmental factor

GRADIENT

Favorable

Stress

No

tolerance

No

tolerance

A

B

U

N

D

A

N

C

E

6

(7)

Ecological niche

• For one environmental factor

GRADIENT

Optimum

Niche width

A

B

U

N

D

A

N

C

E

7

(8)

Species distribution

• Individualistic continuum concept (Gleason, 1926)

Species response assemblages are random in community

Abundance

Resource gradient

(9)

Species distribution

• Resource partitioned continuum (Austin, 1985)

Resource partitioning and competition lead to uniform distribution along gradient

Abundance

Resource gradient

(10)

Species distribution

• Competitive exclusion principle (Gause, 1934)

Two species competing for the same resources (niche) cannot coexist if other

ecological factors are constant

Abundance

Competition

Niche width

Resource gradient

(11)

Species distribution

• Competitive exclusion principle (Gause, 1934)

Two species competing for the same resources (niche) cannot coexist if other

ecological factors are constant

Abundance

Niche width

Resource gradient

(12)

Species distribution

• Competitive exclusion in herbaceous vegetation (Grime, 1973)

Species diversity is higher at intermediate intensity of stress

Species diversity

Intensity of stress

(13)

Species distribution

• Resource partitioned continuum (Austin, 1985)

• Competitive exclusion principle (Gause, 1934)

• Competitive exclusion in herbaceous vegetation (Grime, 1973)

(14)

Species distribution

• Resource partitioned continuum (Austin, 1985)

• Competitive exclusion principle (Gause, 1934)

• Competitive exclusion in herbaceous vegetation (Grime, 1973)

Abundance

Resource gradient

(15)

Species distribution

• Plant species are packed on mesic position of environmental gradient ;

• Niche widths are narrower when optima of species are packed (Lawesson &

Oksanen 2002)

Abundance

Resource gradient

De

nsi

ty

of op

tima

15

(16)

Species distribution

• Ecological response curves are often skewed …

• …with a ‘longer tail’ towards mesic position (Austin & Gaywood, 1994)

Abundance

Resource gradient

(17)

How coexist species in community along resource gradient ?

• Species optima are packed on mesic position

• Species tolerances are narrower in mesic conditions

• Response curves are more skewed at the extremities of gradients

Abundance

Resource gradient

(18)

How coexist species in community along resource gradient ?

• Species optima are packed on mesic position

• Species tolerances are narrower in mesic conditions

• Response curves are more skewed at the extremities of gradients

Abundance

Resource gradient

(19)

How coexist species in community along resource gradient ?

• Species optima are packed on mesic position

• Species tolerances are narrower in mesic conditions

• Response curves are more skewed at the extremities of gradients

Abundance

Resource gradient

(20)

How coexist species in community along resource gradient ?

• Species optima are packed on mesic position

• Species tolerances are narrower in mesic conditions

• Response curves are more skewed at the extremities of gradients

Abundance

Resource gradient

(21)

How coexist species in community along resource gradient ?

• Species optima are packed on mesic position

• Species tolerances are narrower in mesic conditions

• Response curves are more skewed on the extremities of gradients

Abundance

Resource gradient

In this study,

we tested these assumptions on response curves

along a metal toxicity gradient

(22)

Resource gradient vs metal toxicity gradient

(23)

Resource gradient

vs metal toxicity gradient

Most studies focus on macronutrients =

low toxicity

(24)

Resource gradient vs

metal toxicity gradient

Species distribution on Cu, Co, Pb, etc. ?

Metals are toxic at lower concentrations

(25)

Study site

• Katangan copperbelt, Katanga (D.R. Congo)

• Copper and cobalt outcrops  contaminated soils

(26)

Original flora

• More than 650 plant species, 9 % endemics

Cu

&

Co

(27)

Original flora

• More than 650 plant species, 9 % endemics

Cu

&

Co

Haumaniastrum robertii Gladiolus ledoctei Lopholaena deltombei Gladiolus ledoctei 27

(28)

Sampling

• Vegetation

• 184 taxa

• 172 quadrats (1m²) on 3 hills

• Presence/absence

• Soils

• 10-15 cm depth

• Cu and Co extracted by EDTA 4.65 (atomic absorption spectroscopy)

Example on one hill

(29)

Modeling & analysis

• Select taxa with occurrence ≥ 8 in dataset (=80 taxa)

(30)

Modeling & analysis

• Select taxa with occurrence ≥ 8 in dataset (=80 taxa)

• Generalized additive model (Cu and Co) (Hastie & Tibshirani, 1990)

• Non parametric method, robust

• Logistic approach (0/1)

(31)

Modeling & analysis

• Select taxa with occurrence ≥ 8 in dataset (=80 taxa)

• Generalized additive model (Cu and Co) (Hastie & Tibshirani, 1990)

• Non parametric method, robust

• Logistic approach (0/1)

(32)

Modeling & analysis

• Select taxa with occurrence ≥ 8 in dataset (=80 taxa)

• Generalized additive model (Cu and Co) (Hastie & Tibshirani, 1990)

• Non parametric method, robust

• Logistic approach (0/1)

• Niche optima and niche width calculation

• Optimum : X location for Y-max

• Width : extremities of AUC 80 %

Niche width

X

left

X

right

(33)

Modeling & analysis

• Skewness coefficient (Fisher, 1930)

µ

₃

/𝜎

3 • µ3, central moment of order 3

• 𝜎, standard deviation (µ2

1/2

₎

+

0 -

(34)

Modeling & analysis

• Skewness coefficient (Fisher, 1930)

µ

₃

/𝜎

3 • µ3, central moment of order 3

• 𝜎, standard deviation (µ2

1/2

₎

• Density curve

• Kernel density

-

+

0

34

(35)

Taxa distribution

Along copper gradient

(36)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

Along copper gradient

(37)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

Along copper gradient

(38)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

• Group 1 : 40 taxa

Along copper gradient

Group 1

40 taxa

Variable tolerance capacities

(39)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

• Group 1 : 40 taxa

• Group 2 : 31 taxa

Group 2

31 taxa

Well defined and uniformly

distributed optima

Along copper gradient

Group 1

(40)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

• Group 1 : 40 taxa

• Group 2 : 31 taxa

Group 2

31 taxa

Well defined and uniformly

distributed optima

• Variable tolerance

Along copper gradient

Group 1

(41)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

• Group 1 : 40 taxa

• Group 2 : 31 taxa

Group 2

31 taxa

Well defined and uniformly

distributed optima

• Variable tolerance

• Competition

Along copper gradient

Group 1

(42)

Taxa distribution

• Range : 29 – 10 000 mg Cu.kg soil

-1

• Group 1 : 40 taxa

• Group 2 : 31 taxa

• Group 3 : 9 taxa

_{Group 2}

Group 3

9 taxa

Optima ≥ 10 000 mg kg-1

Highly toxic conditions (Cu)

Large niche widths

Along copper gradient

Group 1

(43)

Along resource gradient

Along copper gradient

Optima are packed on mesic position

Density of

probability

Optima (mg Cu kg soil

-1

₎

All taxa

Group 2 taxa

max

(44)

Along resource gradient

Along copper gradient

Optima are packed on mesic position

Density of

probability

Optima (mg Cu kg soil

-1

₎

All taxa

Group 2 taxa

max

(45)

Niche width are narrower on mesic positions

Along resource gradient

0 1000

2000

3000

4000

5000

6000

7000

8000

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Niche

wid

th

(m

g

kg

-1

)

Optima (mg Cu kg

-1

₎

All taxa:

R

2 _{= 0.54}

p-value < 0.001

Group 2 only

R

2 _{= 0.50}

p-value < 0.001

Along copper gradient

(46)

Skewness is higher at the extremities of gradient

All taxa :

R

2 _{= 0.66}

p-value < 0.001

Group 2 only :

R

2 _{= 0.52}

p-value < 0.001

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000

Sk

ewness

co

ef

ficient

Optima (mg Cu kg

-1

₎

Along resource gradient

+

0 -

Along copper gradient

(47)

1 1

of theoritical niche distributions

Abundance

Resource gradient

Abundance

Metal toxicity gradient

(48)

Implication for conservation

Botanical garden

Phytostabilization strategies

(49)

for your attention

sylvain.boisson@ulg.ac.be

More informations : copperflora.org

(50)

(51)

Modeling & analysis

x 3

• Select taxa with occurrence ≥ 8 in dataset (=80 taxa)

• Generalized additive model (Cu and Co) (Hastie & Tibshirani, 1990)

• Non parametric method, robust

• Logistic approach (0/1)

• 3 degrees of smoothing by taxon

• Selection with Akkaike Information Criterion

(52)

Taxa distribution

Along cobalt gradient

• Range : 2 – 900 mg kg

-1

(53)

Taxa distribution

Along cobalt gradient

Group 1

45 taxa

• Range : 2 – 900 mg kg

-1

• Group 1 : 45 taxa

(54)

Taxa distribution

Along cobalt gradient

Group 1

Group 2

• Range : 2 – 900 mg kg

-1

• Group 1 : 45 taxa

• Group 2 : 28 taxa

28 taxa

54

(55)

Taxa distribution

Along cobalt gradient

Group 1

Group 2

Group 3

• Range : 2 – 900 mg kg

-1

• Group 1 : 45 taxa

• Group 2 : 28 taxa

• Group 3 : 7 taxa

55

(56)

Density of optima

Density of

probability

Optima (mg Cu kg soil

-1

₎

All taxa

Group 2 taxa

max

Along cobalt gradient

(57)

Niche width depends on niche optimum

Along cobalt gradient

0

100

200

300

400

500

600

700

800

900

0

100

200

300

400

500

600

700

800

900 Optima (mg Co kg

-1

₎

All taxa :

R

2 _{= 0.57}

p-value < 0.01

Group 2 only :

R

2 _{= 0.23}

p-value < 0.01

57

(58)

Skewness depends on niche optimum

Along cobalt gradient

All taxa :

R

2 _{= 0.48}

p-value < 0.001

Group 2 only :

R

2 _{= 0.29}

p-value < 0.001

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

0

100

200

300

400

500

600

700

800

900 Optima (mg Co kg

-1

₎

58

(59)

• Gradient : 0 – 10 000 mg kg

-1

• 11 % highly tolerant taxa

• For group 2, optima are uniformly

distributed along gradient

• Gradient : 0 – 1000 mg kg

-1

• 9 % highly tolerant taxa

• For group 2, optima are packed on

lowest concentrations

Niches distribution

Along copper gradient

Along cobalt gradient

Niche width and niche skewness depend on optimum location on the gradient

Assumptions assumed for resource gradient are verified on metal gradient

! Mesic conditions are found at low metal concentrations

! Copper is an essential element <> Cobalt is a beneficial element

(60)

Médiane 1er_Quartile ₃ème_Quartile _3Q-1Q

B. lobelioides

₁₁₃

₈₆

₂₄₃

₁₅₇

T. coerulea

₁₂₆

₇₇

₁₇₂

₉₅

L. deltombei

₂₉₄

₂₃₄

₅₆₀

₃₂₅

T. likasiensis

₂₁₁

₁₉₃

₃₆₄

₁₇₀

B. kisimbae

₂₂₃

₂₀₀

₂₂₃

₂₃

H. rosulatum

₂₀₉

₇₉

₄₆₄

₃₈₅

E. cupricola

₁₂₈₆

₃₃₂

₁₃₁₃

₉₈₁

S. neptunii

₅₃₂₅

₁₈₀₈

₇₁₇₀

₅₃₆₁

C. zigzag

₇₅₇₁

₅₃₂₀

₈₆₀₃

₃₂₈₃

Médiane 1er_Quartile ₃ème_Quartile _3Q-1Q

B. lobelioides

₅₃

₄₃

₆₅

₂₂

T. coerulea

₁₅

₁₀

₄₈

₃₈

L. deltombei

₁₅

₉

₂₈

₁₉

T. likasiensis

₁₅

₁₀

₄₄

₃₃

B. kisimbae

₅₁

₃₇

₅₁

₁₃

H. rosulatum

₂

₁₀

₄₉

₃₈

E. cupricola

₅₂

₄₅

₉₀

₄₅

S. neptunii

₃₃

₃₀

₂₀₇

₁₇₇

C. zigzag

₁₅₁

₁₂₃

₁₉₁

₆₇

Cu (mg kg-1)

Co (mg kg-1)

60