Characterizing and predicting Aquatic Invasive Species ...
Transcript of Characterizing and predicting Aquatic Invasive Species ...
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Characterizing and predicting Aquatic Invasive Species distributions: Reconciling large-scale
model predictions with small-scale observations and incorporating climate change scenarios
Thomas W. Therriault1, Claudio DiBacco2, Ben Lowen2 and Devin Lyons2
1 Fisheries and Oceans Canada, Pacific Biological Station 2 Fisheries and Oceans Canada, Bedford Institute of Oceanography
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European Green Crab (Carcinus maenas)
• Ranked on IUCN “100 Worst Invaders” list
• Globally many introductions
• Often negative ecosystem impacts including fisheries and aquaculture
Successful establishment
Failed introduction
Native range
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West Coast of North America GC • Arrived in San Francisco Bay in 1989 (packing material) • Slowly expanded northward into Pacific Northwest • Arrived in BC through
larval transport during 1998/99 El Nino
• Relatively few public reports after 1999
• No surveys until 2006
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Current Green Crab Distribution in BC • Continue to spread
north (larval dispersal) • Only recently reported
from Salish Sea (late fall 2016)
• Managers need to know the potential distribution both now and in the future
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It Is Not Just About Distribution • Simply knowing an AIS is present in a specific
location is of limited utility
• Managers really want to know where invasion “hotspots” are most likely in order to best utilize limited resources
• Especially true if these “hotspots” are unique (i.e., Salish Sea)
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So Where Were We in 2006?
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Potential Distribution - 1 • GARP model
based on west coast distribution in 2006-07
Therriault et al. 2008
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Potential Distribution - 2 • GARP model
based on Canadian distribution (both east coast and west coast locations)
Therriault et al. 2008
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Potential Distribution - 3 • GARP model
based on native range of European green crab
Therriault et al. 2008
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Challenges with Initial Predictions • Not overly informative for AIS Managers (most of BC suitable
in all scenarios)
• Differences in abundance (and hence potential impacts) among sites not captured (i.e., hotspots NOT identified)
• So how to move forward? – Different variables? – Different scales? – How to identify the right variables and the right scales?
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Factors Constraining AIS Distributions • For coastal temperate marine species, including AIS,
“reproductive success” is constrained primarily by temperature and salinity thresholds for growth, survival, and reproduction
• Additional factors can further constrain AIS invasion success including environmental and biotic (i.e., prey, competition) variables
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Predictions Using “Enhanced” Data
Lowen et al. 2016
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But What is the “Best” Scale for Predictions?
~ 64 km ~ 16 km ~ 1 km
~100’s m?
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Environmental Topography
• Summer SST – at 25 km (squares) – at 100’s m (circles)
• Complexity of BC’s sounds
and fijords with very limited data complicate predictions
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So Our “BIG” Question How does spatial resolution of ecological factors that constrain AIS distributions (e.g. temperature and salinity) influence the probability of accurately identifying suitable coastal habitats for AIS like GC? Really this represents a trade-off between relatively fine spatial resolution data that may be required (and unavailable) for predictions and coarser spatial resolution data that may be available but is masking important variation ultimately reducing the utility of predictions
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TSS
(sen
sitiv
ity +
spec
ifici
ty –
1)
Spatial scale (km)0 20 40 60 80 100
0.5
0.6
0.7
0.8
0.9
1.0
Resolving Observed GC Distributions in BC • Used MaxEnt
– which minimizes relative entropy between environmental and distribution probability densities
• Predictive Power (TSS)
decreased with increasing spatial scale
insitu loggers (100s m)
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Predictions with Increasing Resolution Predictive utility
1km
32km
100’s m insitu
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Spatial Resolution of Predictors (km)
Sensitivity, Specificity and Reliability
Lowen et al. 2016
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An “Optimal” Resolution for ENMs?
• “Best” predictions at 100s of m but resolution < 4 km was acceptable
Lowen et al. 2016
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But What about the Salish Sea?
• In fall 2016 GC were detected on US side of Salish Sea
• Additional modeling may help refine predictions
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“Updated” MaxEnt Models
Lyons et al. in prep
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Climate Projection MaxEnt Models
Lyons et al. in prep
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Conclusions • Probability of accurately identifying suitable habitat
for GC increased with spatial resolution of limiting environmental variables but “optimal” scale is likely to differ among AIS
• Suitable habitat for GC exists throughout coastal BC however, in the Salish Sea it is patchy
• Climate change likely to increase amount of suitable habitat for GC in BC
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Conclusions (and Caveats) • Invasion vectors not modeled here (but work is
underway on this) • Climate change is likely to change AIS vectors and
pathways in the future • Technological advancements should allow much
higher resolution environmental monitoring data collection in the future
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Next Steps
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Acknowledgements
• All the Green Crab trapping teams
• Funding provided by Fisheries and Oceans Canada’s Aquatic Invasive Species Program and the Second Canadian Aquatic Invasive Species Network (CAISN II)