abundance and distribution of crayfish in two florida...
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Abundance and distribution of crayfish in two Florida spring-fed rivers managed for Hydrilla
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Tiffani Manteuffel PI: Dr. C. Ross Hinkle Co-PI: Dr. I. Jack Stout FWC Research Review University of Central Florida March 4, 2014
• Hydrilla in Wakulla River • Impact on crayfish? • Crayfish importance • Question • Study design
• N-mixture models for abundance • Crayfish collection • Batch marking • Spatial design • Temporal design • Habitat parameters
• Pilot study • Hypotheses • Conclusions & Broader Impacts
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Outline
Hydrilla in Wakulla River
• Known invasive • Herbicide is primary control 14 years
3 Savery 2000
www.aquaweed.com plants.ifas.ufl.edu
Impact of Hydrilla herbicide? • Die-off of native crayfish observed • No direct impact in experiment • Changes in dissolved oxygen, prey? • Need baseline data to clarify if losses can degrade
ecosystem function
4 FDEP study 2005
Crayfish
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Economically & Culturally
• Food source –specialty & subsistence • Centuries-long consumption • Commercial harvest & farming
worldwide Ecologically • Burrowing in, aerating sediments & grazing on detritus impacts nutrient cycling • Omnivores • Prey to birds, fish
Holdich 2002, Palmer et al. 1997, Covich et al. 1999
thedailywaster.wordpress.com
www.louisianaseafoodnews.com
www.gcsu.edu
Question
What are the habitat characteristics that affect crayfish abundance and distribution in the Wakulla and Silver Rivers?
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Study sites
Silver River
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Wakulla River
• Estimate abundance and detection probability from count data
• Instead of capture-mark-recapture
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Abundance analysis: N-mixture models
Royle 2004, Joseph et al. 2009
Crayfish ID and Collection • Minnow traps, baited with cat food • Species ID on adult males only
Keys: Hobbs 1989, Hobbs and Hobbs 1991, Coignet et al 2012 9
Batch Marking Nail polish (varnish) or oil-based permanent marker on carapace
10 (Coignet et al. 2012, Ramalho et al. 2010)
Spatial Design
Acosta and Perry 2000, Gherardi et al. 2000 11
Dominant Veg. 3 Dominant Veg. 1 Dominant Veg. 2
River
60 m
60 m
dow
nstr
eam
Triangles= traps Colors= 2 spatial sets
-3-6 surveys in year -Population closed within survey -Repeat 3-5 times in one survey
Temporal Design
Day 1 2 3 4 5 6 7 8 9 10
Place Set A
Place Set B
Check Set A
Check Set B
Check Set A
Check Set B
Check Set A
Check Set B
Check Set A
Check Set B
Rep 1 Rep 1 Rep 2 Rep 2 Rep 3 Rep 3 Rep 4 Rep 4
Batch Mark
Batch Mark
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Triangles= traps Colors= 2 spatial sets
Parameters Parameter Importance to crayfish Vegetation & bottom type Shelter, food, atm O2, defense
Percent cover of vegetation shelter, food
Aquatic vegetation height above water line
access to atm O2
Detritus composition Food source
Distance to springhead Human use
“left” or “right” bank Light availability Water depth Dissolved oxygen, vegetation, atm O2
Dissolved Oxygen (DO) Physiological tolerances
Temperature Physiological tolerances
Holdich 2002, Caine 1978 13
Pilot data
Total crayfish Vegetation 0 bare, near cypress 4 bullrush, shallow 4 bullrush, shallow 3 bullrush, shallow 2 log, shallow 2 Bullrush, shallow 2 eelgrass, shallow 1 eelgrass, deep, open 1 eelgrass, open 1 bullrush and eelgrass islands 7 bullrush and eelgrass islands 1 pickerel weed, shallow 1 Eelgrass, shallow
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11 females, 18 males, 4 days
Shallow and vegetated
Deep & somewhat vegetated
Pilot data
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0123456
0 1 2 3 4 5 6 7
Freq
uenc
y
Number of crayfish
Number of crayfish/traps after 4 days
• Most sites will be occupied, but abundance will vary based on abiotic and biotic characteristics
• Minimal differences throughout year
Hypotheses
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Conclusions What are the habitat characteristics that affect crayfish abundance and distribution in the Wakulla and Silver Rivers?
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Conclusions What are the habitat characteristics that affect crayfish abundance and distribution in the Wakulla and Silver Rivers? Provide overall & site-specific abundances with count data Collect general movement of crayfish between sites Understand important abiotic or biotic parameters
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Broader Impacts Understudied taxon in native range (Helms et al. 2013)
managers want crayfish research • Mitigate potential impacts (Florida Springs Task Force 2000)
Crayfish ecology relevant to nutrient cycling, ecosystem process important to these rivers
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www.saj.usace.army.mil
www.crustahunter.com
waterquality.ifas.ufl.edu
Broader Impacts Understudied taxon in native range (Helms et al. 2013)
managers want crayfish research • Mitigate potential impacts (Florida Springs Task Force 2000)
Crayfish ecology relevant to nutrient cycling, ecosystem process important to these rivers
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www.saj.usace.army.mil
www.crustahunter.com
waterquality.ifas.ufl.edu
Broader Impacts Understudied taxon in native range (Helms et al. 2013)
managers want crayfish research • Mitigate potential impacts (Florida Springs Task Force 2000)
Crayfish ecology relevant to nutrient cycling, ecosystem process important to these rivers
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www.saj.usace.army.mil
www.crustahunter.com
waterquality.ifas.ufl.edu
Acknowledgments Committee: Dr. C. Ross Hinkle, Dr. I. Jack Stout and Dr. Joshua King
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Special thanks: Dr. John Osborne, practical field advice @ Wakulla prelim sampling
Dr. Eric Stolen, N-mixture modeling EPaS Lab Department of Biology faculty & staff BGSA Funding: Florida Fish & Wildlife Conservation Commission
Questions?
23 voices.nationalgeographic.com
• Most sites will be occupied, but abundance will vary based on abiotic and biotic characteristics
• Minimal differences throughout year
Dominant Veg. 3
Dominant Veg. 1
Dominant Veg. 2
River
Hypotheses
24 Larger circle means more crayfish
dow
nstr
eam
Crayfish globally
• Society for Freshwater Science revealed holes in understanding basic biology and ecology of native crayfish
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http://iz.carnegiemnh.org/crayfish/NewAstacidea/infraorder.asp?io=Astacidea Families of crayfish globally
Helms et al. 2013, Nystrӧm 2002
Outline Development of project Hydrilla and management impact Why crayfish? Study sites Crayfish collection Sampling scheme site selection timeline parameters Abundance analysis with N-mixture models Implications
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EXTRA SLIDES
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28 Royle 2004, Joseph et al. 2009
Abundance analysis: N-mixture models • Covariates on spatial differences & detection probability • Counts nit (where i is site and t is time) are nit ~ Bin(Ni, p)
• independent realizations of binomial random variable • Parameters, N=population size and p=detection probability, from which we
get abundance • Assume probability distribution takes form of Poisson or negative binomial
to get likelihood
• Unmarked package in R
29 (Kéry et al. 2005, Royle 2004)
Crayfish roles
• Reduce particulate matter volume & leaf pack mass
• Single species leaf pack breakdown—33-54% slower without crayfish
• Regulate submerged vegetation, snails, periphyton (algae + cyanobacteria + microorganism + detritus)
• Reduce Potamogeton biomass 30 Creed and Reed 2004, Schofield and Pringle 2001, Lodge et al. 1994, Feminella and Resh 1989
Nutrients in, out, within an
ecosystem
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Sswm.info
abiotic
biotic
Chapin et. al. 2011
Predictions
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Crayfish ecology & biology
Aspects we may consider: • Abundance • Distribution • Biodiversity • Life history • Interactions
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Benthic invertebrates
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Recycle nutrients though consumption, burrowing, waste Process 20-73% of leaf litter in headwater streams
Covich et al. 1999
Highest species richness in freshwater sediments
Terrestrial food source connected to the aquatic food web
Palmer 1997, Covich et al. 1999, Swan and Palmer 2006
Animals influence the volume and availability of nutrients within ecosystems (Vanni 2002) 35
Freshwater Ecosystems
Primary productivity, nutrient cycling, terrestrial areas oceans Services: irrigation, power generation, food and potable water provisioning What are the “players” and interactions (biotic and abiotic) that contribute to or impact these processes and services?
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Moderntraveler.travelwebmarketing.com
www.conservationgateway.org
Carpenter et al. 1996, Palmer et al. 1997, Chapin et al. 2011, Postel and Carpenter 1997
Crayfish ecology & biology
Aspects we may consider: • Abundance • Distribution • Biodiversity • Life history • Interactions
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Decomposition Detritus: Dead, particulate organic matter greater than 0.5 µm, generally vascular plant material, and houses microorganisms
Decomposition: Process of the physical fragmentation, microorganismal colonization, and invertebrate action that leads to physical deconstruction and chemical changes in detritus
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-Reduces the mass of detritus -Fragment the material -Converts to other organics & inorganics
www.burakianphotography.com
Majority of nitrogen and phosphorus for plants is available through decomposition
Boulton and Boon 1991, Mann 1988, Chapin et al. 2011, Cummins and Klug 1979
Detritivore: Organism that gets food (energy) through detritus breakdown
Florida crayfish
39 http://iz.carnegiemnh.org
• 57 species (Global crayfish resources 2014) • Hobbs (1942) general life history characteristics,
methods, species distributions • Procambarus
Population structure compared to physiology (Breinholt et al. 2011)
Population dynamics after environmental stress (Acosta and Perry 2001)
General ecology & tolerance to certain abiotic & biotic factors (Caine 1978)
Shredder
• invertebrate functional group that prefer to eat coarse particulate organic matter (the largest leaf litter in detritus) generally inhabited by microorganisms
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(2) Two way random block ANOVA
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Source Df SS MS F
Blocks (b) b-1=3 3, 21 df= 3.07
First factor (f)-crayfish f-1=1 1, 21 df= 4.33
Second Factor (s)-time s-1=4 4, 21 df= 2.84
First * Second interaction (f-1)*(s-1)=4 4, 21 df= 2.84
Residual (f*s-1)*(b-1)=27
Total f*s*b-1= 39
1) Expected Results - Abundance
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Power analysis 1 crayfish density
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A B crayfish time
y 1 n 2
3 4 5
df A 1 B 4 A*B 4
Two way ANOVA with multiple crayfish densities
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Source Df SS MS F
Blocks 3 3, 33= 2.89
First-crayfish 2 2, 33= 3.29
Second-time 4 4, 33= 2.66
First*second interaction
8 8, 33 = 2.24
residual 42
total 59
Power analysis 2 crayfish density
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y1 1 y2 2 n 3 4 5
df A 2 B 4
A*B 8
N-mixture modeling example from literature
• Counts of six bird spps
• 10 days by same observer at 50 sites, 0.5 miles apart
• i= 1 to 50 and t= 1 to 10 is Binomial (Ni, p) is reasonable (assuming closed population because breeding birds have territories)
• Data are sparse: counts low, lots of zeros
• “sparse data from spatially replicate count surveys can be utilized to effectively estimate population sizes while properly accounting for the detection process when local (site-specific) abundance, Ni, can be modeled as exchangeable random variables”
• Counts are independently and identically distributed random variables (Each nit) same probability distribution as rest and are independent
• Random variable: value variance is due to chance
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Freshwater food web
47 www.freshwater-science.org
Lignin, Phenolics, Nitrogen sources • Lignin-2ndry cell wall of plants, some algae
(organic), complex polymer of aromatic alcohols Phenols-hydroxyl + aromatic hydrocarbon (organic), carbolic acid Nitrogen content, protein
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