Transcript Bruce Chessman`s presentation on the use of traits to predict aquatic

Do traits of freshwater species
predict vulnerability to climate
change?
Bruce Chessman
Climate Change Science, NSW DECCW
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Climate change is likely to be the
greatest driver of ecological change in
rivers and wetlands of the MurrayDarling Basin
 Climate models generally project:
-
Increased temperatures
Increased evapotranspiration
Reduced runoff, especially in the south-east
Shift from winter/spring to summer/autumn
runoff
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Likely traits of vulnerable freshwater
species
 Intolerant of higher temperatures
 Intolerant of stagnant conditions
 Lacking mechanisms to survive drying
 Inflexible timing of life-cycle events
 Small geographic range
 Specialised habitat requirements
 Low mobility
 Low fecundity
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Management for vulnerable species
 Protect normal habitats
 Protect refuge habitats
 Maintain dispersal corridors
 Assist dispersal
 Control non-climatic threats
 Ex-situ conservation
4
Trends in NSW river invertebrates from
1994-2007 as a test of traits as
predictors
19
 Environmental
changes in NSW from
1994 to 2007 broadly
mirror those projected
by climate models
 Large quantity of
invertebrate data
available from river
bioassessment
projects
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Average air
temperature (C)
17
1994 1997 2000 2003 2006
700
600
500
Average
discharge at
254 gauges
(GL)
400
300
200
100
0
1994
1997 2000 2003 2006
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Invertebrate data
 6582 kick or sweep samples from various
habitats at 1818 river sites across NSW
 Identification only to family level, not species
 Data are essentially presence/absence per
sample (non-quantitative sampling)
-28
Latitude (°S)
-30
-32
Sydney
-34
-36
-38
140
142
144
146
148
Longitude (°E)
150
152
154
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Data analysis
 Logistic regression used to identify
invertebrate families with significantly
increasing or decreasing probability of
capture in samples taken over the whole
State in the period 1994-2007
 Trends of individual families tested for
correlation with their traits
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Trait 1: thermophily
(preference for higher temperatures)
 Thermophily of an invertebrate family =
average water temperature for samples in which
the family was recorded
divided by
average water temperature for all samples
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5
Trait 2: rheophily
waterfall or
cascade
(preference for flowing
water)
4
 Habitats sampled scored
from fast-flowing to still
rapid
3
riffle
 Rheophily of a family =
average score of samples
in which the family was
recorded
divided by
average score of all
samples
2
run
1
glide
0
still water
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Constraints on analysis
 Family level only
 In order to detect long-term Statewide trends
it was necessary to adjust for extraneous
variation associated with:
-
Shifting site locations (many sites but few
sampled often)
-
Different habitats sampled
Sampling at different times of the year
Changes in sampling methods
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Overall results
 33 families had significantly increasing
probability of capture
 37 families had significantly declining
probability of capture
 54 families had no significant trend (mostly
rare)
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Traits and trends
2
2
Increasers
Odds ratio
Odds ratio
Increasers
1
1
Decreasers
Decreasers
0
0
0
0.5
1
Thermophily
Heat-loving families
were significantly more
likely to have increased
1.5
0
1
2
3
4
Rheophily
Current-loving families
were significantly more
likely to have declined
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Conclusions
 Trends did reflect traits as expected
 BUT single traits were weak predictors of
trend
 Traits and trends are likely to vary among
species within a family and among life history
stages
 Trait combinations may predict trends better
than single traits
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Future directions
 Consider a wide range of traits
 Derive traits for each life-history stage of
each species (not families)
 Vulnerability estimates based on
combinations of traits rather than single traits
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Thank you
And thanks to all those who collected the
monitoring data for this analysis
Further reading
Chessman BC 2009. Climatic changes and 13-year trends in
stream macroinvertebrate assemblages in New South
Wales, Australia. Global Change Biology 15, 2791-2802.
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