Transcript Document 7343104

A long-term study of a small
rocky reef
Bill Ballantine
Leigh Marine Laboratory
New Zealand
This study aims to determine the variations
over TIME in a NATURAL marine benthic
community
i.e. where there is no exploitation, no serious
disturbance and no driving force for change.
To make this valid, practical and generally meaningful
requires a large number of decisions, choices,
stratifications, etc. including -
Theoretical points:
1. For spatial comparisons the observations need to be made
at the same time.
Similarly, comparisons over time need observations at the
same place.
The study needs a fixed site.
2. Comparisons in space need to be separated by sufficient
distance to avoid auto-correlation (pseudo-replication).
Similarly, replicates in time need sufficient separation in time.
The study must extend over multiple generations.
Practical considerations:
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No human interference : in a marine reserve
No major natural disturbances (e.g. erosion)
Easily accessible for frequent observations
Simple topography – uniform, gentle, bedrock slope
Reduced secondary factors (e.g. rock type)
Low diversity – only ~15 significant species
Short generation times – < 1 - 5 years
Comprehensive – all significant species monitored
Small enough to allow census of most species
Large enough to provide multiple patch dynamics
The locality: Goat Island Bay, Leigh
Standard Reef
Standard Reef: total area 5m x 4m
Standard Reef: 1–20 @ 1m2, A-L @ 0.1 m2
Most data that will be shown comes from 1-10 m2
Square 2 : open rock and crevices
The Standard Reef biological community
Trophic level
Carnivorous whelk
3
2
Barnacles
Mussels
Grazing molluscs
4 species
1
Phytoplankton
Benthic microflora
Cellana radians
Sypharochiton pelliserpentis
Melagraphia aethiops
Turbo smaragda
Ralfsia
Good data: regular census
Some data: infrequent sampling
Grazing molluscs:
• RESIDENTS
• A chiton
• Sypharochiton pelliserpentis
A patellid limpet
• Cellana radians
• VISITORS
– A turbinid snail
• Turbo smaragda
– A trochid snail
• Melagraphia aethiops
Sypharochiton
pelliserpentis
Homing to crevices (< 30 cm)
Slow growing and long-lived (>3 years)
Small changes (<10% per month and <50% per year)
No seasonality
Range of biomass over time ~
4x
Sypharochiton pelliserpentis biomass*in 1-10 m2 (all data)
Standard Reef, Echinoderm Reef
500
Biomass (g)
400
300
Mean
200
100
0
1997
1998
1999
2000
2001
2002
2003
2004
Graph: Sigmaplot Sypharo biom 1-1- 1997 on Graph page 1
Data: Excel SigplotSy1-1097on Sheet 1
*
Total wet weight
2005
2006
2007
2008
2009
Cellana radians
Home-ranging (< 1 m)
Fast growing and short-lived (< 2 years)
Rapid changes (up to 50% per month)
Strong seasonality (summer peaks)
Range of biomass over time
>20x
Cellana radians biomass (g) 1-10 m2 (all data)
Standard
Reef,
Echinoderm
Reefm2
Cellana
radians
biomass
(g) 1-10
500
Cellana radians biomass (g)
400
300
200
100
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Turbo smaragdus
Wide-ranging (up and back to lower zone)
Moderate growth rate and longevity
Very rapid short term changes (>50% per month) and
rapid changes per year >70%)
Weak seasonality
Range of biomass over time
>20x
Turbo biomass (g) 1-10 m2 (all data)
Standard
Reef, Echinoderm
Turbo biomass
(g) 1-10Reef
m2
500
Turbo biomass (g)
400
300
200
100
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Melagraphia
aethiops
Very wide-ranging (at this level)
Moderate growth rate and longevity
Long periods of low (< 30) or high (> 50) abundance
No seasonality
Range of biomass over time
>20x
Melagraphia aethiops biomass in 1-10 sq m (all data)
Standard Reef, Echinoderm Reef
500
Melagraphia biomass (g)
400
300
200
100
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Conclusions for grazing molluscs:
1. The variations of biomass over time are LARGE and important.
2. The variations are NOT PREDICTABLE (beyond very short time
frames).
3. The variations are NOT RANDOM and the patterns are distinctive for
each species.
4. The variations show no persistent patterns of competition.
None of these conclusions were expected, and they do not match well
with existing theory on food web models.
Comparison of 4 grazing molluscs
Cellana
Sypharochiton
500
400
400
Cellana radians biomas (g)
500
Biomass (g)
300
200
300
200
100
100
0
0
1997
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
1998
1999
2000
2001
2002
2003
2004
2006
2007
2008
2
Melagraphia
Melagraphia biomass in 10 m
Turbo
500
500
400
400
300
300
200
200
Melagraphia biomass (g)
Turbo smaragdus biomass (g)
2005
2008
100
(standard months)
100
0
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Sessile species:
• A small sheet-forming barnacle
– Chamaesipho columna
• A black encrusting alga
– Ralfsia (cf confusa)
• A small mussel
– Xenostrobus pulex
– Despite only 3 species, the patch dynamics are complex
Barnacles: Chamaesipho columna
Clean barnacle % cover 1-10 m2
Standard Reef, Echinoderm Reef
Clean barnacle % cover (no Ralfsia or mussels)
100
80
60
40
20
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Ralfsia covered barnacles
months)
Ralfsia % cover 1-10 m2 (std motnhs)
Standard Reef, Echinoderm Reef
100
Ralfsia % cover
80
60
40
20
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Mussels % cover in photonodes A-E (std motnhs)
Standard Reef, Echinoderm Reef
100
Mussel % cover
80
60
40
20
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Conclusions for sessile species are the same as for the
grazing molluscs –
(a) large variations over time
(b) unpredictable
(c) different patterns for each species
(d) low correlations between species
Sessile species dynamics
• Barnacles settle only on bare rock
• Ralfsia only grows well on or between barnacles
• Mussels settle on Ralfsia, barnacles or themselves, but not on
bare rock
Settlement (all species) occurs as strong pulses, but is only
weakly seasonal.
Ralfsia grows over barnacles but does not harm them
Mussels grow over and smother barnacles and Ralfsia
Ralfsia dies back after ~ 12 months
There is no equilibrium state.
Barnacles
100
90
Clean barnacle % cover (no Ralfsia or Mussels)
80
70
60
50
40
Variations with time
30
20
10
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Ralfsia
100
1999
90
80
Barnacles
Ralfsia
Bare
Barnacles
Ralfsia
Mussels
Barnacles
Bare
Mussels
70
2001
Ralfsia % cover
60
50
40
2003
30
20
10
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Mussels
100
90
80
Mussels % cover
70
60
50
40
30
20
10
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Correlation coefficients (r)
for 1-10 m2 on Standard Reef 1997 onwards
CHITON
CHITON
CELLANA
TURBO
TROCHID
BARNACLES
RALFSIA
MUSSELS
CELLANA
TURBO
TROCHID
BARNACLES
RALFSIA
MUSSELS
0.60
0.41
0.59
0.19
-0.09
-0.32
0.25
0.57
0.22
-0.12
-0.25
0.48
0.23
-0.16
-0.09
0.31
-0.08
-0.46
-0.61
-0.33
-0.18
Extra time
A further 9 years of data is available but includes a 2 year gap.
Conclusions from extra time confirm and
reinforce previous conclusions especially:
(a) The range of variation
(b) The specifically distinct patterns
Sypharochiton biomass (g) 1-10 m2
600
Sypharochiton biomass (g)
500
400
300
200
100
0
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Cellana radians biomass (g) 1-10 m2
1200
1000
800
Cellana radians biomass (g)
500
400
300
200
*
100
0
1987
1989
1991
1993
1995
1997
1999
2001
* Three lines of evidence indicate a similar event occurred in 1981
2003
2005
2007
2009
2 m2
Turbo
smaragdus
biomass
(g)m
1-10
Turbo
smaragdus
(g) 1-10
500
Turbo biomass (g)
400
300
200
100
0
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Melagraphia aethiops biomass (g) 1-10 m2
300
Melagraphia biomass (g)
250
200
150
100
50
0
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
Discussion:
1. All species in this natural and undisturbed community show
variations over time which are:
(a) Large and ‘ecologically important’
(b) Unpredictable (except for very short periods)
(c) Non-random and distinctive in their patterns
(d) Largely independent
Given (a) and (d), it follows that the interactions between species
are varying over time.
2. There is little or no comparable data because
(a) these are very difficult to obtain even if time is
available and undisturbed sites exist
(b) the topic does not seem interesting to most
workers
(c) career paths and grant agency policies tend to
prevent their collection.
3. Existing knowledge is mainly from studies that are:
(a) short-term
(b) detailed and precise
(c) focused on active processes and limiting factors
Such studies are necessary and important, but are effectively
just short clips from a movie.
500
Cellana radians biomass 10m2
Cellana radians biomas (g)
400
300
200
100
0
1997
1998
1999
2000
2001
2002
2003
2004
2005
The conclusions from the 3 periods would be quite different.
2006
2007
2008
4.
Existing theory on temporal variation in biological
communities consists mainly of implicit and untested
assumptions that such variation is
(a) small, except when disturbed from outside
(b) and /or periodic (e.g. seasonal)
(c) and /or random
(d) and /or unimportant
5. Existing models of biological community dynamics
implicitly assume that
(a)
(b)
(c)
(d)
the community is maintained by active processes
these processes can be recognized and estimated
the estimates can be used to make a useful model
it is not necessary to include any temporal variation
(other than that produced by external factors)
e.g. Branch (2008) Trophic interactions in sub-tidal rocky reefs on the west
coast of South Africa
6. Such models are useful as descriptions, but they cannot be made
predictive in any precise way because they are equilibrium
models and are unable to cope with continuous or complex
temporal changes.
Conclusions
1.
In a simple undisturbed rocky shore community the main
species showed large changes in abundance over timescales that included multiple generations.
2.
These changes were not predictable, except over very short
time frames but were not random. Each species had a
distinctive pattern but the details never repeated precisely.
3.
4.
Despite all the changes and the absence of any
equilibrium state, the community persisted through
time as frequently recurring similar structures and
patterns.
There is little comparable data (spatially-explicit,
multi-generational), and no clear theory on what
temporal changes should be expected in an undisturbed
community.
5.
It is not known if the kind of changes found in this study
would occur in other communities, but it seems likely.
6.
It is well-known that even simple physical systems can show
complex intrinsic dynamics, if the system is externally
forced and governed by non-linear processes.
7.
Biological communities are such systems and
consequently are likely to show similar intrinsic
dynamics.
8.
Furthermore, although these intrinsic dynamics will be
overlaid by ‘external’ disturbances (such as exploitation,
severe storms, pollution, etc.) they are
likely to continue to operate.
A useful analogy ?
In the 1960s, weather forecasters were confident that with
better data and analysis, their forecasts would improve
indefinitely.
Edward Lorentz proved that this is not true.
“Complex systems” are completely deterministic and show
recognizable types of order, but do not reach equilibrium
and never repeat exactly the same state.
Consequently, detailed predictions are not possible (except
for short periods), no matter how much is known about
the present situation or the governing processes.
Biological communities are likely to be “complex systems” of
this type.
If ecologists considered the component species of a
community analogous to the weather at a locality and the
entire community analogous to the climate, I believe
considerable practical and theoretical advances could be
made with existing data.
Community predictability will become a matter of pattern and
probability not precision.
The climate of an area is composed entirely of ‘weather events’
none of which can be precisely predicted, but we know that
the climate of an area has real and useful levels of
predictability, indeed most of our activities depend on this
(e.g. successful farming is possible).
Three problems with this study
1. No spatial replication
2. Very small area
3. Simple community (low biodiversity)
I could only manage a single, small, simple area for a long period.
Better data would not only require large amounts of work and
finance, it would also require a long time. Consequently it seems
sensible to extract as much information as possible from the
present study.
A recent relevant paper
Beninca et al (2008) Chaos in a long-term experiment with a
plankton community. Nature: 451, 822-826.
They maintained a closed mesocosm under constant
conditions for 8 years and showed:
1. A complex biological community can persist despite large,
unpredictable changes in all its component trophic groups.
Stability is not required.
2. These changes were due to intrinsic dynamics and longterm prediction can be fundamentally impossible.
Help!
Some of this team (expert mathematicians with highpowered computers) have offered to analyse the Standard
Reef and associated climate data and these are being sent
to them by John Atkins and Agnès Le Port.
(i)
(ii)
I would very much appreciate:
Any suggestions for forms of analysis (e.g. correlation with
SOI, lag times, etc.
References to any comparable data sets (i.e. long-term,
fixed site(s), undisturbed, and multi-species).
My email is [email protected]
Acknowledgements
Over the years, many people assisted with the very tedious
task of recording the data in this study.
Many others helped with studies of particular species, with
analysis and with discussion.
Although they are too numerous to list, I am very grateful to
them all.
Neil Barr and Agnès Le Port helped prepare this presentation.