All an ecologist wants to know, but never
can find
Peter M.J. Herman
Netherlands Institute of Ecology
Yerseke
[email protected]
What makes us jealous ?
Large datasets
Total N vs. Total P
Reliably measured data
Covering most of the
ocean
Far-reaching
interpretations
Anorganic N vs.
Anorganic P
Cross-system comparisons of benthic biomass
and primary production in estuaries
System-averaged macrofauna biomass
g AFDW m-2
Herman et al. 1999 Adv.Ecol.Res
70
System-averaged benthic
biomass relates to systemaveraged primary production
YT
60
GR
50
OS
Possible implications for
effects eutrophication
40
B2
30
Possible norm for biomass
EW VM
20
CB
B1 SFB
LIS
BF
LY
WS
10
But: system coverage poor!
B=-1.5
+ 0.105 P
2
r =0.77
ED
COL
0
0
100
200
300
400
500
600
700
System primary production (gC.m-2.y-1)
Benthic data from shelf break
Omex project: benthic fauna and sediment
biogeochemisty
Respiration (gC.m
-2
.y-1)
SCOC
Macro
Meio
14
12
10
8
6
4
2
0
0
2000
Depth (m)
4000
Heip et al. 2001 DSR II
Shelf break data compared with shallow
systems
-2
(gAFDW.m )
Biomass macrofauna
100
Shallow systems
Estimated as 1/3 PP
10
Consistent
pattern over
orders of
magnitude of
organic loading
1
0.1
1
10
100
1000
-1
(Estimated) SCOC (gC.m -2 .y )
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
Loge ( SOC [mmol m-2 d-1 ] )
6
4
2
0
-2
-4
-6
0
2000
4000
6000
Depth [m]
Henrik Andersson et al. submitted
Primary Production [ mmol C m-2 d-1]
Refining with PP-depth gradients
500.00
50.00
5.00
0.50
0.05
0
2000
4000
Depth [m]
6000
Derived: rates of pelagic oxygen consumption
with depth
Oxygen Uptake Rate (mmol m-3 d-1)
0.6
0.5
Uniformly productive ocean
0.4
0.3
0.2
Corrected for lateral
production gradient
0.1
0.0
0
100
200
300
400
500
Depth (m)
+ relative role of water column / sediment in mineralisation
+ estimate of benthic denitrification
What could be mined further?
 Relation with macro/meiobenthic biomass, species
composition and diversity
E.g. Levin &
Gage (1998)
Macrobenthic
diversity as a
function of
depth, oxygen,
latitude, carbon
content of
sediment
Depth (m)
Oxygen (ml/l)
Latitude
% Org. Carbon
Danish monitoring: relation mussels – chl a
Decay
Bloom
K '
 prod
 mix
 '
 prod
 graz
Koseff et al., 1993
Kaas et al. (1996)
?
-> mixing rates?
Macrobenthos Westerschelde: depth & salinity
intertidal
undeep subtidal
deep subtidal
channel
30
25
Biomass (g AFDW m-2)
biomass (g AFDW/m² ± se)
35
20
15
10
5
0
-2
Biomass (g AFDW.m ) of feeding groups
Intertidal stratum
25
susp
surf
depo
omni
pred
20
15
10
5
0
1
2
3
salinity region
4
zone 1
zone 2
zone 3
zone 4
salinity zones
Tom Ysebaert
Peter Herman
biomass (g AFDW.m-2)
Comparison other regional systems
140
120
100
80
60
40
20
0
WS
OS
GR
VM
intertidal
shallow subtidal
deep subtidal
channel
Distribution ~
* macro- vs. microvs. non-tidal
* wave vs. current
Grevelingen
* transparancy
Oosterschelde * oxygen conditions
Veerse Meer
Westerschelde
Tom Ysebaert
Peter Herman
Functional guilds and depth distribution :
Oosterschelde
Biomass (g AFDW.m-2)
Deposit feeders
0
1
2
3
Biomass (g AFDW.m-2)
Suspension feeders
4
0
-1 - 2 m
-1 - 2 m
2-5m
2-5m
5-8m
5-8m
>8m
>8m
20
40
60
Model for suspension feeder occurrence
Phytoplankton growth at depth z:
P
production consumption
C
  C 
 K
 (wC )+ P - C

t  z  z   z
mixing
P
P
sinking
-> 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 prerequisite
 Not valuable without physical and/or chemical
metadata
 Taxonomy 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 data
Georeferenced
Consistent taxonomy
Auto-ecological information
Well-documented methods
Physical 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 change
 Better exploitation of remotely sensed variables
 Testing ecological hypotheses
 Detecting 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 sets
 Exchange formats
 Resolution of the taxonomic mess
 Better linking between ecological, physical and
biogeochemical datasets