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Do traits of freshwater species predict vulnerability to climate change?. Bruce Chessman Climate Change Science, NSW DECCW. Climate change is likely to be the greatest driver of ecological change in rivers and wetlands of the Murray-Darling Basin. Climate models generally project:
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Do traits of freshwater species predict vulnerability to climate change? Bruce Chessman Climate Change Science, NSW DECCW
Climate change is likely to be the greatest driver of ecological change in rivers and wetlands of the Murray-Darling Basin • Climate models generally project: • Increased temperatures • Increased evapotranspiration • Reduced runoff, especially in the south-east • Shift from winter/spring to summer/autumn runoff
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
Management for vulnerable species • Protect normal habitats • Protect refuge habitats • Maintain dispersal corridors • Assist dispersal • Control non-climatic threats • Ex-situ conservation
Trends in NSW river invertebrates from 1994-2007 as a test of traits as predictors • 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
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)
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
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
5 waterfall or cascade Trait 2: rheophily(preference for flowing water) 4 rapid • Habitats sampled scored from fast-flowing to still • Rheophily of a family = average score of samples in which the family was recorded divided by average score of all samples 3 riffle 2 run 1 glide 0 still water
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
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)
Traits and trends Increasers Increasers Heat-loving families were significantly more likely to have increased Decreasers Decreasers Current-loving families were significantly more likely to have declined
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
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
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.