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University of Padova LASA – Environmental Systems Analysis Lab Light extinction Photosynthesis Algal growth

Light extinction Photosynthesis Algal growth - unipd.itlasa.dii.unipd.it/mces//LEX/14_mces.pdf · Light extinction Photosynthesis Algal growth . ... incident photons in the visible

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University of Padova LASA – Environmental Systems Analysis Lab

Light extinction

Photosynthesis

Algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction Light is the main energy source for ecosystems and has a key role in ecological

processes: photosynthesis, transpiration, evapotranspiration, …

Hence, the quantification of the energy reaching the Earth’s surface and living

organisms is important.

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Physical processes – light extinction

Lambert-Beer’s (Bouguer’s) law: most famous model

I: intensity or irradiance W m-2

dI = - k ∙ I ∙ dx

HP:

Homogeneous

medium

Iout (z) = Iin (0) ∙ e – k ∙ z

works well for low concentration

media.

K depends on medium, direction,

wavelength

Modello: I(z) = I(0)e-kz

PAR(prof) = 370.52*e-(4.50*prof)

R2 = 0.97 D

epth

(m

)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Lambert-Beer’s law (or Bouguer’s law)

Iout (z) = Iin (0) ∙ e – k ∙ z

Iout / Iin : trasmittance

Several applications (e.g. spectrophotometers)

k*z = optical depth (a measure of the ability of the layer to block light)

Hetereogeneous medium: apply relationship separately to layers using different k’s

Physical processes – light extinction

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction in the atmosphere

Not all solar radiation approaching earth’s surface actually reaches the ground.

Exctinction = scattering + absorption

Absorption → photons hit atmospheric gases (O2, O3,N2, H2O, CO2) and

aerosols (natural and anthropogenic): energy transformed into heat or radiated.

Scattering → photons are deviated by gases / aerosol without energy loss,

diffusion

•Rayleigh: particles with d<1/10 wavelength (N2 e O2 for visible radiation)

•Mie: particles with d up to 10*wavelength

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction in the atmosphere

Iout = Iin ∙ e – k ∙ m ∙ L

m = 1 / cosφ optical air mass (relative length…)

to take into account the sun is not at zenith (φ=0)

k = kscat gas+kscat aerosol+kabs gas+kabs aerosol

In inhabited regions, usually ksuspended particles >> kgas

Empirical relationships for φ >60° (refraction, non-uniform T, clouds and

other substances, Earth’s curvature, air density)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction in water

• Too few (or too much) light can limit primary

production (phytoplankton, macroalgae, etc.)

• Scattering and absorption due to water, suspended

and dissolved substances

• Also the other way: primary producers can

influence extinction (phytoplankton shading and

self shading). Feedback!

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

• Light used in photosynthesis mainly in the visible

range (400-700 nm) - PAR measured as:

– W m-2

– PPDF (photosynthetic photon flux density, number of

incident photons in the visible range per unit time per unit

area, i.e. μmol∙m-2∙s-1)

• Euphotic (photic) zone: RPP = photosynthesis (1%

PAR; zone where photosynthesis takes place, etc.),

from few cm to hundreds of meters

Light extinction in water

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction in water

k depends on wavelength; can be determined using

photometers at several z, Iin=56% (or less, depends on

wavelength) of I incident on the water surface

After few meters, light becomes monochromatic (green)

k can be computed in several ways

k = kw & diss + kpart

kpart =a*[Cpart]

When phyto has the biggest influence (i.e. eutrophic lakes, shading, self shading):

k = b + c*[A]

k = b + c*[A] + d*[A]e

In oligotrophic ecosystems b (background turbidity) dominates

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light exctintion in water

SDk

cost

Aakk 10

bAaAakk 210

TSSbk

TSSbAak 1

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Estinzione della luce in un mezzo secodo la

legge di Lambert-Beer

-25

-20

-15

-10

-5

0

0 0,2 0,4 0,6 0,8 1

Transmittance

Depth

[m

]

k = 0,2

k = 0,4

The role of K

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Physical processes – light extinction

February 2002

January 2002 Worst, but predictive

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light extinction in terrestrial ecosystems

• The canopy of trees can attenuate light (i.e.

tropical forests)

• Influence underlying vegetation / undergrowth

/ animals / nutrient cycling etc.

• Agriculture, crop spacing, water balance for

irrigation

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light exctinction in terrestrial ecosystems

Reflected light

Incoming light

Transmitted light

Absorbed light

Through gaps

(direct or diffuse)

Modified from Barausse, A. Light extinction. Chapter to be included in S.E.Jorgensen (ed.), Encyclopedia of Ecology, Elsevier, Amsterdam. Accepted.

Complex, multi-scale problem: few general models

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Light exctinction in terrestrial ecosystems

• Effects of vegetation

Iz (LAI) = Iin ∙ e – k ∙ LAI(z)

LAI(z) is the cumulated Leaf Area Index from the top of the canopy to depth z. The leaf area index is the ratio of the total one sided green leaf surface to the surface of the ground underneath the canopy (or the projected needle area per unit of ground surface).

Iin: incoming PPDF on the top of the canopy (where z=0)

k connected to the average leaf orientation, tree species, …

Often, hypotheses of Lambert Beer’s law are not realistic (homogeneous and isotropic medium?)

Other models, even complex (3D vegetation models) and field measurements (e.g. hemispherical photography)

Image from http://www.ext.vt.edu/pubs/entomology/444-203/444-203.html

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis

6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis 6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Phosynthesis

6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

1. Light (optimum irradiance: energy is needed but not too

much; Chlorophyll absorbance spectrum 400-700 nm and

depending on species, bacteria – bacteriochlorophyll also

longer wavelength)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis 6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

1. Light

2. Inorganic carbon

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis 6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

1. Light

2. Inorganic carbon

3. Water

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis 6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

1. Light

2. Inorganic carbon

3. Water

4. Temperature (optimum)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis 6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

Limiting factors:

Empirical model

PHOTO = k ∙ f (max demand for limiting factors)

1. Light

2. Inorganic carbon

3. Water

4. Temperature (optimum)

5. Other: plant characteristics and state (e.g. LAI,

reproductive state), nutrients (N in chlorophyll)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Acclimation: environmental fluctuations (light, T, humidity, nutrients (P, N, Si) )

0

Net

ph

oto

syn

thes

is

irradiance

shade acclimated

light acclimated

Photosynthesis at saturation level depends on species, T, pH, etc.

Photosynthesis

6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis

Not only chlorophyll photosynthesis: some autotroph bacteria with bacteriochlorophyll pigments

6 CO2 + 12 H2S → C6H12O6 + 12 S + 6 H2O

Electron donor: hydrogen sulfide instead of water. Reaction takes place only without oxygen (toxic), no oxygen production

Also some cyanobacteria (chlorophyll) can perform this reaction

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Chlorophyll photosynthesis - cyanobacteria

(blue-green algae, Cyanophyta, etc)

Unicellular prokaryote, can form colonies. They can:

• reduce N (fix N2 into NH3, often symbionts)

• reduce S (only some)

• reduce C (chlorophyll photosynthesis)

Atmospheric O2 and cyanobacteria

Photosynthesis in cytoplasm, not in specialized organs (chloroplasts, probably derived from cyanobacteria “embedded” as endosymbionts)

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Photosynthesis (respiration) vs net photosynthesis

In chlorophyll photosynthesis there are two separate reactions

– Light dependent: light energy to create high energy molecules, O2 released

– Light independent: CO2 transformed into organic compounds using such molecule energy

Photosynthesis

6 CO2 + 6 H20 + hν → C6H12O6 + 6 O2

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

PAR is about 56% of total incident radiation.

In water, Lambert Beer’s law:

heII 0

dove I0: light intensity on surface [W/m2] =0,56

: light exctinction coefficient [1/m]

h: depth [m]

Biological processes – photosynthesis

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

2

1

k

kMAX

I

I

I

I

PPwhere P: photosynthesis rate [mgO2/g/h]

Ik: light adaptation parameter

Saturation

P also depends on T (enzyme kinetics) and on pH (carbonate equilibrium)

2)5.6(

)20(

5.6

1

120

pH

MAX

TMAX

ePpHP

ePTP

Biological processes – photosynthesis

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab

Image source:

http://caliban.mpiz-koeln.mpg.de/haeckel/kunstformen/natur.html

Plankton

University of Padova LASA – Environmental Systems Analysis Lab

Image source:

http://biophysics.sbg.ac.at/rovigno/rovigno1.htm

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

GAsmesrdt

dA

where A: weight concentration of algae [mgX/l]

: growth rate [1/d]

r: respiration rate [1/d]

es: exudation rate [1/d]

m: non-predatory mortality rate [1/d]

s: sedimentation rate [1/d]

G: grazing [mgX/l/d]

GAsmdt

dA

where A: abundance (i.e. number) concentration [cell/l]

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

TfTrr ref

Respiration and exudation:

can also depend on the physiological state of the cell:

,...,,,,min SiCPNLfTkTrTr refrrefref

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Settling:

h

vs s

Non-predatory mortality:

TfTmm ref

Some authors point out to a carrying capacity-like effect:

ATkTm refmref

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

,...,,, SiCPNfLfTfTrefMAX

...,...,,, SifCfPfNfSiCPNf

,...,,,min,...,,, SifCfPfNfSiCPNf

...

1111,...,,,

SifCfPfNf

nSiCPNf

n

SifCfPfNfSiCPNf

...,...,,,

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Temperature limitation

Linear: min

min

TT

TTTf

ref

Exponential: refTTTf

Optimum:

2

3.2optx

opt

TT

TT

eTf

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Temperature °C

m

ax (

1/d

ay)

Biological processes – algal growth

University of Padova LASA – Environmental Systems Analysis Lab Modelling and Control of Environmental Systems

Biological processes – algal growth