Steelhead natal source inferences using otolith microchemistry
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1 Steelhead natal source inferences using otolith microchemistry Carson G. Prichard 1, Nicole M. Watson 1, Kevin L. Pangle 1, Jory L. Jonas 2, James J. Student 3 1 Central Michigan University, Department of Biology 2 Michigan DNR 3 Central Michigan University, Department of Earth and Atmospheric Sciences
2 Background Many sources of steelhead production 1. Five hatchery strains: Arlee, Chambers Creek, Ganaraska, Little Manistee, and Skamania Raised among six different hatcheries
3 Background Many sources of steelhead production 1. Five hatchery strains: Arlee, Chambers Creek, Ganaraska, Little Manistee, and Skamania Raised among six different hatcheries 2. Wild steelhead from natural reproduction Northwest Lower Peninsula of Michigan and elsewhere
4 Research questions To what extent can juvenile steelhead be discriminated by natal source using otolith microchemistry? Can the following be distinguished? 1. Juvenile steelhead from different hatcheries 2. Wild vs. hatchery juvenile steelhead among stocked streams 3. Wild juvenile steelhead among >30 different Lake MI tribs
5 Otoliths: fish ear bones Hard calcium carbonate structures located behind the brain Help fish hearing, balance, orientation Metabolically inert Concentric growth around core Reconstruct the environmental history of fish Act as a natural marker Journal of fish habitat occupancy
6 Geology influences otolith microchemistry Otolith chemical analysis has the potential to determine natal origins in the Great Lakes Unique geology Surficial Geology of Great Lakes Region Bedrock Geology of Great Lakes Region
7 Geology influences otolith microchemistry Otolith chemical analysis has the potential to determine natal origins in the Great Lakes Unique geology Surficial & Bedrock Geology Water Chemistry Strontium (Sr) and Barium (Ba) Others of importance: magnesium (Mg), manganese (Mn), iron (Fe), lead (Pb), copper (Cu) Otolith Chemistry
8 Elements analyzed with LA-ICPMS 1. Similar charge and/or size to Ca Detectable abundance Mg Ca Mn Cu Zn Sr Ba Pb
9 How LA-ICPMS measures elements Data (ppm of elements)
10 Objective 1: Hatchery analysis To what extent can juvenile steelhead from different hatcheries be discriminated using otolith microchemistry? Lake Michigan steelhead stocking, 2015 Fingerlings Yearlings Proportion Clipped 64, , Unclipped 373,929 1,087, Total 438,021 1,252,133 1
11 Objective 1: Hatchery analysis Hatchery steelhead samples Hatchery description Sample date Year class n Bodine State Fish Hatchery, IN 10 Apr Nov Jake Wolf Memorial Fish Hatchery, IL 20 Oct Kettle Moraine Springs Hatchery, WI 1 Nov Thompson State Fish Hatchery, MI 25 Apr Apr Wolf Lake State Fish Hatchery, MI 28 Aug
12 Results: Model performance Misclassification (%) Model m try = 0.5p 0.5 m try = p 0.5 m try = 2p 0.5 Hatchery ~ Mg, Mn, Cu, Zn, Sr, Ba, Pb Hatchery ~ Mg, Mn, Zn, Sr, Ba Hatchery ~ Mn, Sr, Ba Hatchery ~ Zn, Sr, Ba Hatchery ~ Sr, Ba Hatchery ~ Sr Hatchery ~ Ba
13 Results: Classifications among hatchery fish Predicted origin Known origin BSFH ILFH KMFH TSFH WLFH BSFH ILFH KMFH TSFH WLFH % Misclassified
14 Results: Classifications among hatchery fish Predicted origin Known origin BSFH ILFH KMFH TSFH WLFH % Misclassified BSFH ILFH KMFH TSFH WLFH
15 Objective 1: Implications Each hatchery imparts a unique microchemical signature on juvenile steelhead otoliths If all stocked steelhead were fin-clipped, we could reliably assign to correct natal origin
16 Objective 2: Hatchery vs. wild analysis To what extent can wild vs. hatchery juvenile steelhead be discriminated among stocked streams? Methods: Streams sampled for age-0 wild juvenile steelhead Classification models (n = 25) built using otolith chemistry inputs from: 1. Known wild-origin juvenile steelhead 2. Hatchery steelhead from hatchery(s) that source stockings of each respective watershed
17 Objective 2: Hatchery vs. wild analysis KMFH TSFH WLFH TSFH & WLFH BSFH, TSFH & WLFH Assignment W W W H H H H W Misclassification (%) Fischer Creek Hibbard Creek Sauk Creek Days River Eighteen Mile Creek Haymeadow Creek Horton Creek Jordan River Bigelow Creek Egypt Creek Honey Creek Little S Br Pere Marquette River Middle Br Pere Marquette River Prairie Creek Sanborn Creek Silver Creek Muskegon R trib Weldon Creek Kids Creek Platte River Bear Creek Lemon Creek Pine Creek Townsend Creek Dowagiac River trib.
18 Objective 2: Hatchery vs. wild analysis KMFH TSFH WLFH TSFH & WLFH BSFH, TSFH & WLFH Fischer Creek Hibbard Creek Sauk Creek Days River Eighteen Mile Creek Haymeadow Creek Horton Creek Jordan River Bigelow Creek Egypt Creek Assignment W W W H H H H W Misclassification (%) Honey Creek Little S Br Pere Marquette River Middle Br Pere Marquette River Prairie Creek Sanborn Creek Silver Creek Muskegon River trib Weldon Creek Kids Creek Platte River Bear Creek Lemon Creek Pine Creek Townsend Creek Dowagiac River trib
19 Objective 2: Hatchery vs. wild analysis Eighteen Mile Creek Bigelow Creek Sr (ppm) Sr (ppm) Origin Wild Hatchery Mn (ppm) Mg (ppm) Core Edge Core Edge
20 Unknown-origin assignment: Proof of concept Unknown-origin age-1+ Known-wild age-0 Age-1 assignment (n) Site Sample date wild KMFH WLFH Fischer Creek, WI 2-Sep Apr-15 Prairie Creek, MI 24-Jun Sep May-15 9-Oct-15 Sanborn Creek, MI 30-Jun Oct Jul Oct-15
21 Unknown-origin assignment: Proof of concept Unknown-origin age-1+ Known-wild age-0 Age-1 assignment (n) Site Sample date wild KMFH WLFH Fischer Creek, WI 2-Sep NA 28-Apr NA Prairie Creek, MI 24-Jun-14 3 NA 0 18-Sep-14 3 NA 0 11-May-15 1 NA 2 9-Oct-15 5 NA 0 Sanborn Creek, MI 30-Jun-14 5 NA 0 25-Oct-14 2 NA 0 14-Jul-15 7 NA 0 16-Oct-15 3 NA 0
22 Objective 2: Implications Among streams analyzed, hatchery- and wild-origin otolith signatures tend to differ Likely can discriminate wild- from hatchery-origin unmarked adults Stream-collected adults could be correctly classified for streams analyzed (assuming negligible straying)
23 Objective 3: Wild juvenile assignment To what extent can wild juvenile steelhead from different Lake Michigan tributaries be discriminated using otolith microchemistry? How does assignment accuracy vary with spatial scale?
24 Broader spatial scale improves accuracy 13 Regions 6 Regions WUP EUP Region NMI Region MDS NMI Year-class (fine) MDS Year-class (coarse) WIM WID TVC BMN LMN PMQ PMQ MSK 2014 (n = 179) 88% 2015 (n = 325) 89% Combined years 89% WIS MPM MSK SMI 2014 (n = 179) 91% 2015 (n = 325) 92% Combined Years 92% GRD KZO SJO
25 Summary 1. Can discriminate between hatcheries with >95% accuracy 2. Stream-specific known wild- and hatchery-origin assignment models range in accuracy from 90%-100% 3. Broader spatial scales improve assignment accuracy >90% at coarse geographic scale (6 regions)
26 Ongoing research 1. Comparison of otolith chemistries between resident sculpin and juvenile steelhead and coho salmon Can resident sculpin serve as surrogates for anadromous spp.? Does inter-year-class chemistry variation in coho and steelhead correlate with inter-annulus variation in sculpin? 2. Origin assignments of adult, unmarked steelhead from 2016 open-water fishery Coordinated with USFWS to obtain otoliths of >600 steelhead
27 Questions Acknowledgements:
28
29 Evidence of inter-annual variation Year-class t1 ~ year-class t2 (y predicted by x) Site Region (fine) Region (coarse) 2014 ~ % 49% 57% 2015 ~ % 63% 66%
30 Objective 2: Hatchery vs. wild analysis Origin Wild Hatchery
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