Swimmers itch drivers in northern MI lakes. Thomas R. Raffel, Ph.D. Department of Biological Sciences Oakland University Rochester, MI

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1 Swimmers itch drivers in northern MI lakes Thomas R. Raffel, Ph.D. Department of Biological Sciences Oakland University Rochester, MI

2 Schistosomiasis: 2-host life cycle (SNAILS) Exposure in water Human schistosomes (3 spp) 2 nd most important tropical disease worldwide million people infected/yr; 800,000 deaths Avian schistosomes (12-15 spp) Trying to infect birds Itchy bumps 1-2 days post-exposure Gradually fade over ~1 week Adult worms (in blood vessel) Trichobilharzia cercaria penetrating skin

3 Michigan: home of swimmer s itch! Trichobilharzia spp. First described by Cort in Douglas Lake (1928 ) Stagnicola catescopium* (= Stagnicola emarginata) Physa integra

4 Research Goals 1. Temporal dynamics Generate daily field data for cercaria abundance Test predictions for potential warning systems 2. Spatial distribution Identify landscape-level predictors of snail and parasite abundance Inform management decisions

5 I. Temporal dynamics: Gaps in Knowledge Temperature, Celsius High day to day variation reported, but no daily field data available for cercaria abundance Trematode biology is temperature-dependent - Snail growth & reproductive rates - Cercaria production rate Most studies ignore temperature fluctuations /1 6/8 6/15 6/22 6/29 7/6 7/13 7/20 7/27 Date

6 I. Temporal dynamics: Thermal Stress Hypothesis (Paull et al 2015) Proposed that high temperatures are energetically stressful to snails, depleting energy stores (e.g., fat reserves) during long warm periods. Depleted host energy limits cercaria production by trematode parasites

7 I. Temporal dynamics: Thermal Stress Hypothesis Immediate Effect Warm Temperatures Metabolism (reaction rates) Energy budget of snail (fat reserve) Delayed Effect Cercaria

8 I. Temporal dynamics: Thermal Stress Hypothesis Predictions: Higher levels when current water temperature is high Lower levels following multiple days of warm temperatures

9 Summer 2015 Madelyn Messner Needed a large number of daily cercaria samples from natural sites during peak swimmer s itch season

10 Citizen scientists! Volunteer recruitment & training Daily samples: July 6 August 2

11 Temporal dynamics: July 6 August 2, 2015 Daily samples- filter 50L water Hourly temperature & light

12 Sample Processing Collect filter sample Extract DNA qpcr to estimate cercaria abundance

13 Temporal dynamics: sample processing 378 individual sample tubes DNA extraction from dried sample 1 ml lysis buffer + 10 ul proteinase K qpcr DNA quantification TaqMan Assay (Jothikumar et al 2015) Target itch-causing schistosomes Singlicate reactions w/reruns for inhibited reactions IPC measures reaction inhibition (reduces measurement bias) Singlicate reactions (low precision for individual measurements)

14 Temporal dynamics: statistical analysis Response variable: Cercaria/ 50L Substantial day to day variation Random effects: - Location - Snail population - Snail infection levels - Bird visitation - Water currents Log cercaria/ 50L Min Daily Temp

15 Temporal dynamics: temporal confoundment Pirate attacks EXAMPLE: (Hypothetical) Pirate attacks correlate with ocean wind speed Can we conclude increased wind speed caused the increase in pirate attacks through time? Ocean wind speed Problem: YEAR THOUSANDS of possibly relevant variables increased or decreased during this time period, making this a potentially CONFOUNDED predictor variable Poor evidence for causality (temporally confounded analysis) 1790

16 Temporal dynamics: temporal confoundment Standard method account for long-term trend first, before testing for relationships Method 1: Detrend cercaria data using deviations from a spline curve fit to data *Method 2: Use past cercaria levels (over 3, 5, or 7 days) as a covariate in the analysis. Past levels predict current levels. AFTER accounting for the long-term trend, we tested for effects of current & past daily temperatures on cercaria abundance Better evidence for a meaningful relationship

17 Temporal dynamics: Results Random variation. (singlicate analyses) Best model according to AIC: 3 predictors 1. Higher cercaria levels in past 5 days higher cercaria levels today 2. Current temps positive trend 3. Past temps significant negative effect Predictor variable Coefficient χ 2 p-value Log cercaria prev 5 days <0.001 Min daily water temp Previous 5 day water temp <0.001

18 Temporal dynamics: Conclusions Field evidence for Thermal Stress Hypothesis Positive effect of current temps - Widely cited in literature - Weaker (non-significant) effect in our analysis Negative effect of past temps - Novel finding; highly significant and predictive - Higher-precision assays might help improve predictions in the future

19 Research Goals 1. Temporal dynamics Generate daily field data for cercaria abundance Test predictions for potential warning systems 2. Spatial distribution Identify landscape-level predictors of snail and parasite abundance Inform management decisions

20 II. Large-Scale Spatial Survey (16 lakes; 38 sites) What determines patterns of schistosome cercariae abundance across a broad landscape? >50 volunteers trained >1040 cercaria samples collected >3000 miles driven >2500 qpcr assays run Jason & Ryan Maddie & Jenna Aleena & Alex

21 What determines swimmer s itch at a particular SITE? SWIMMER S ITCH! Wind/Waves? Cercariae in water Snail population density Percent snails infected Cercariae produced per snail Algal growth? Bird infection? Temperature? Possible environmental drivers..

22 Hypothesized drivers: Land Use Urbanization Agriculture Vegetation Development Physical charateristics Wave action Lake size/depth Substrate type Temperature Insecticide runoff Zebra mussels Herbicide runoff Nutrient pollution (N, P) Bird visitation Temperature Arthropod predators (crayfish) Water clarity Attached algae Snail density Infected snails Water clarity hypotheses*: 1. Clear water lets light penetrate to bottom of lake 2. Algal periphyton is often light-limited, especially in deeper water 3. Snail populations are often limited by periphyton (food) abundance 4. Trematode abundance often limited by abundance of host snails Cercariae in water

23 2016 survey parameters (>60 possible predictors.): Continuous/Daily monitoring: Cercaria density - daily filtered-water samples (volunteers + qpcr) Wind speed & direction (volunteers) Water temperature & light penetration (HOBO loggers) Bird visitation Weekly surveys: Snail quadrat sampling & collection (identification, size distribution) Turbidity & zebra mussel densities (quadrats) Crayfish trapping Zooplankton sampling (density, composition) Site-level measurements: Attached algae (periphyton) growth & composition Zebra mussel settling rates Water chemistry (nitrates+nitrites+ammonia, organophosphate) Pesticides (2,4-D; glyphosate) Sediment cores (Phosphorus, Organic carbon) Substrate & shoreline characteristics; fetch; slope Lake-level characteristics: Land use in watershed & near shore Lake size & depth

24 Results Part 1: Snails responded to water clarity Supported a core prediction of our water clarity hypotheses.

25 HOWEVER: Snails were dominated by Pleurocera

26 Pleurocera drove the Turbidity pattern

27 and Pleurocera are NON-HOST snails. Characteristics: Thick-walled shells Operculate Common in larger rivers MI is northern edge of known distribution Not known to host Trichobilharzia sp. parasites Encyclopedia of Life: Pleurocera collection records

28 Results 2: Cercariae responded to Stagnicola No added predictive power by adding other snail species to the analysis

29 Cercaria levels versus Stagnicola density:

30 Comparing 2015 & 2016 datasets:

31 Stagnicola snails: Stagnicola catascopium/emarginata/elodes Characteristics: Known hosts for Trichobilharzia spp. parasites Non-Operculate ARCTIC taxon rare south of MI Eat algal periphyton & macrophytes Lives in deep water (up to 30 feet for L. catascopium) Prefer solid substrates Regulation by fish predators? Encyclopedia of Life: Stagnicola collection records

32 Stagnicola snails: Stagnicola catascopium/emarginata/elodes

33 Some sites had cercariae despite no Stagnicola. Might indicate influx of cercariae from offsite via water currents Can we account for any of this variation in our analysis?

34 Results 3: Submerged vegetation reduced cercariae (after accounting for snail density) F 1,35 = 7.0; P = Sites with few or no Stagnicola snails How could submerged vegetation reduce the influx of cercariae from other sites?

35 How could submerged vegetation reduce the influx of cercariae from other sites? Plants as physical barriers? Plants as accidental hosts? Floating water plants (Christensen 1979) Hedychia coronarium (mariposa) (Warren & Peters 1968)

36 Bladderwort (Utricularia spp.) Carnivorous water plant Known to eat cercariae! Widespread in MI Sometimes mistaken for milfoil Cercariae Gibson & Warren 1970 Bladderwort Eurasian milfoil

37 Summary Swimmer s itch apparent risk factors Maximum Lake Depth Deciduous trees Submerged vegetation Stagnicola Cercariae

38 Summary Swimmer s itch apparent risk factors Shallow Lake: LOW Risk Medium Risk Deep Lake: Medium Risk HIGH Risk

39 THANK YOU!!! Collaborators: Pieter Johnson, Sara Paull, Bryan LaFonte, Curt Blankespoor, Ronald Reimink, David Szlag Oakland University Support: Doug Wendell (chair), Arik Dvir, Cathy Starnes, Sheryl Hugger, Jan Bills, Kathy Lesich, Shawn Rasanen Oakland Undergraduate researchers: Fieldwork: R. McWhinnie, J. McBride, A. Hajek, A. Bageris; qpcr: J. McBride, S. Trotter, G. Everett, J. Willis; Invertebrate counts: Melissa Ostrowski, James Willis, Rima Stepanian, Aman Singh Funds & Lodging (still compiling names for 2016 ): Oakland University Startup Al Flory & Monika Schultz Chimney Corners Resort Platte Lake Improvement Assn Glen Lake Association Lake Leelanau Lake Assn Leelanau Clean Water Walloon Lake Association Lime Lake Association Higgins Lake Property Owners Assn SICON LLC Twin Lakes Property Owners Assn Elk-Skegemog Lake Assn Crystal Lake & Watershed Org. Lake Margrethe Foundation Fund Hamlin Lake Preservation Society Portage Lake Watershed Forever Intermediate Lake Association RAFFEL LAB: Madelyn Messner* Jason Sckrabulis* Ryan McWhinnie* Jenna McBride* Alex Bageris Aleena Hajek Karie Altman ALL OUR CITIZEN SCIENTIST VOLUNTEERS! (NEXT SLIDE)

40 2015 survey volunteers (8 lakes) (Crystal Lake) Al Flory & Monica Schultz; Ted & Barb Fischer; Pat & Sherry Grant (Glen Lake) Mike & Sara Litch; Rob Karner; John DePuy; John Kassarjian (Lake Leelanau) John Lutchko; Dave Hunter; John Popa; Wayne Swallow (Platte Lake) Bob & Mason Blank; Wilfred Swieki (Little Traverse Lake) Len Allgaier (Lime Lake) Dean Manikas (Walloon Lake) Russ Kittleson (Higgins Lake) Ron Reimink; Curt Blankespoor 2016 survey volunteers (16 lakes) (Crystal Lake) Al Flory & Monica Schultz; Ted Fischer; Jana Way; Joel Buzzell; Shary Grant (Deer Lake) Todd Sorenson; Alec Sherman (Douglas Lake) Curt Blankespoor; Kira Surber (Elk Lake) Bob & Bryce Kingon; Dean Ginther; Ruth Bay (Glen Lake) John Kassarjian; Mike Litch; Denny Becker; Bill Meserve; Jack Laitala; Chris Dorsey Shugart (Hamlin Lake) Ginny Hluchan; Linda & Ted Leibole; Judi Cartier & Ed Franckowiak; Paula & Mike Veronie; Denny Lavis; Joe Muzzo; Mara DeChene; Gail Hanna; Kathy Grossenbacher; Jim Gallie (Higgins Lake) Jim Vondale; Charlene Cornell; Richard Weadock; John & Susan Osler; Anne Grein; Ken Dennings; Greg Douglas; Rebekah Gibson; Sue Gederbloom (Intermediate Lake) Steve & Kathy Young; Jim & Karen Gilleylen; Scott Zimmerman; Marcia Collins; Claude & Joyce Gilkerson; Sheridan & Bob Haack (Lake Leelanau) David Hunter; John Popa; John Lutchko; Nick Fleezanis; Page Sikes (Lime Lake) Dean Manikas (Little Traverse Lake) Len Allgaier and Kristin Race (Lake Margrethe) Sandra & Ken Michalik; Mike Ravesi; Lisa Jaenicke; Nancy Atchison (Platte Lake) Wilfred J. Swiecki; Bob Blank; Tom & Christian Inman; Jackie & John Randall (Portage Lake) Al Taylor; Mary Reed; Tammy Messner; Ted Lawrence (Lake Skegemog) Dave Hauser; Kathi Gober (Walloon Lake) Christine Wedge; Russ & Kathy Kittleson; John Markewitz; Megan Muller-Girard

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42 What does thermal stress predict through time? Paull et al 2015 Cold to Warm: initial increase in parasite production followed by steady decline Constant Warm: parasite production declines longer it is held at warm temps

43 I. Large-Scale Survey (16 lakes; 38 sites)

44 Primary drivers of Pleurocera:

45 Effective Fetch (L f ) Distance wind can blow over water more wave action (in theory) Correlates with lake size & depth Effective Fetch = σ D i cos γ i σ cos γ i D 45R D 90 D 45L Modified Effective Fetch = D 45Lcos 45 + D 90 cos 90 + D 45R cos 45 cos 45 + cos 90 + cos 45 But why are Pleurocerid snails more abundant at high-fetch sites? Possible hypothesis: Adapted for shallow water & high wave action

46 Drivers of water clarity:

47 Drivers of mussel abundance:

48 Conifers effects on turbidity, snails, & mussels?

49 Conifers effects on turbidity, snails, & mussels? Conifers release terpenes ( turpentine ) Toxic to algae? (few studies) Less algae lower turbidity Less food for mussels More food for snails

50 Summary factors affecting snail (Pleurocera) abundance Gravel Alkalinity Temperature Conifers Mussels Water clarity Fetch D 45R D 45L D 90 Pleurocera (Dominant snail)