all an ecologist wants to know, but never can find peter m.j. herman netherlands institute of...

All an ecologist wants to know, but never can find

Peter M.J. Herman

Netherlands Institute of Ecology

Yerseke

p.herman@nioo.knaw.nl

Total N vs. Total P

Anorganic N vs.Anorganic P

What makes us jealous ?

Large datasets

Reliably measured data

Covering most of the ocean

Far-reaching interpretations

System primary production (gC.m-2.y-1)

0 100 200 300 400 500 600 700

Sys

tem

-ave

rage

d m

acro

faun

a bi

omas

sg

AF

DW

m-2

0

10

20

30

40

50

60

70

B=-1.5 + 0.105 Pr2=0.77

GR

OS

VM

WS

B1

B2

ED

EW

CBSFBLIS

LY

COL

YT

BF

Cross-system comparisons of benthic biomass and primary production in estuaries

System-averaged benthic biomass relates to system-averaged primary production

Possible implications for effects eutrophication

Possible norm for biomass

But: system coverage poor!

Herman et al. 1999 Adv.Ecol.Res

0

2

4

6

8

10

12

14

0 2000 4000

Depth (m)

Re

sp

ira

tio

n (

gC

.m-2

.y-1

)

SCOC Macro Meio

Benthic data from shelf break

Heip et al. 2001 DSR IIOmex project: benthic fauna and sediment biogeochemisty

0.1

1

10

100

1 10 100 1000

(Estimated) SCOC (gC.m -2 .y-1)

Bio

mas

s m

acro

fau

na

(gA

FD

W.m

-2)

Shelf break data compared with shallow systems

Shallow systemsEstimated as 1/3 PP

Consistent pattern over orders of magnitude of organic loading

What could be mined further ?

More data sets on benthic biomass, PP and sediment oxygen consumption

Breakdown of datasets: regionally, with water depth, with physical conditions, with nature of primary production etc..

Breakdown of benthic biomass into different functional groups, even species.

Better resolution of variability behind the averages – what are determining factors for these

Sediment community oxygen consumption

0 2000 4000 6000Depth [m]

-6

-4

-2

0

2

4

6L

og

e (

SO

C [

mm

ol m

-2 d

-1]

)

Henrik Andersson et al. submitted

Refining with PP-depth gradients

0 2000 4000 6000

Depth [m]

0.05

0.50

5.00

50.00

500.00

Prim

ary

Pro

duct

ion

[ mm

ol C

m-2

d-1

]

Derived: rates of pelagic oxygen consumption with depth

0 100 200 300 400 500

Depth (m)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Oxy

gen

Upt

ake

Rat

e (m

mol

m-3

d-1

)

+ relative role of water column / sediment in mineralisation+ estimate of benthic denitrification

Corrected for lateral production gradient

Uniformly productive ocean

What could be mined further?

Relation with macro/meiobenthic biomass, species composition and diversity

Depth (m) Latitude

Oxygen (ml/l) % Org. Carbon

E.g. Levin & Gage (1998)

Macrobenthic diversity as a function of depth, oxygen, latitude, carbon content of sediment

Danish monitoring: relation mussels – chl a

Kaas et al. (1996)

Bloom

Decay

graz

prod

'mix

prodK

'

Koseff et al., 1993

?-> mixing rates?

1 2 3 40

5

10

15

20

25

30

35

biom

ass

(g A

FD

W/m

² ±

se)

salinity region

intertidal undeep subtidal deep subtidal channel

Macrobenthos Westerschelde: depth & salinity

Tom YsebaertPeter Herman

Biomass (g AFDW.m-2) of feeding groupsIntertidal stratum

salinity zones

zone 1 zone 2 zone 3 zone 4

Bio

mas

s (g

AF

DW

m-2

)

0

5

10

15

20

25

susp surf depo omni pred

Comparison other regional systems

0

20

40

60

80

100

120

140

bio

mas

s (g

AF

DW

.m-2)

intertidalshallow subtidaldeep subtidalchannel

WS OS GR VM

Tom YsebaertPeter Herman

GrevelingenOosterscheldeVeerse MeerWesterschelde

Distribution ~ * macro- vs. micro-

vs. non-tidal* wave vs. current* transparancy* oxygen conditions

Functional guilds and depth distribution : Oosterschelde

0 1 2 3 4

-1 - 2 m

2 - 5 m

5 - 8 m

> 8 m

0 20 40 60

-1 - 2 m

2 - 5 m

5 - 8 m

> 8 m

Biomass (g AFDW.m-2)Deposit feeders

Biomass (g AFDW.m-2)Suspension feeders

Model for suspension feeder occurrence

CPCzz

CK

zt

C

mixing sinking

production - consumption

P

P

P

Phytoplankton growth at depth z:

-> food depletion suspension feeders depends on production, mixing, pelagic losses-> suspension feeders deeper as water gets more transparant

Some common denominators

Data sets must come from both similar and dissimilar systems

Comparability of methods is prerequisiteNot valuable without physical and/or chemical

metadataTaxonomy problems when analysed at species

level ; autecology often lacking when analysed at functional group level

Models needed to make data meaningful

What would we want?

Easily accessible, highly resolved ecological dataGeoreferencedConsistent taxonomyAuto-ecological informationWell-documented methodsPhysical and chemical data (depth, light,

chlorophyll, nutrients, sediment composition, physical stress,…) linked

Spatiotemporal variation represented

What could we do with it?

Inter-system comparison of limiting factors on species / functional guilds / trophic groups

Deriving norms and indicators adapted to local circumstances

Detecting general temporal trends ~ global changeBetter exploitation of remotely sensed variables

Testing ecological hypothesesDetecting patterns that suggest experimental

approach or detailed research

What would we need for it ?

Linking of existing databases from national / regional monitoring programmes

Quality control on data setsExchange formatsResolution of the taxonomic messBetter linking between ecological, physical and

biogeochemical datasets