Housekeeping. WF4133 Fisheries Science. Housekeeping. Housekeeping. Housekeeping 2/19/2018. Now is the time to be looking for summer jobs!

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F Fisheries Science Module : Fish and fish population dynamics Class Housekeeping Now is the time to e looking for summer jos! State wesites USA jos Fisheries.org Texas A&M Position: Seasonal Technician Agency: GDNR RD Fisheries Management Stream Survey Program Duration: Not more than 68 calendar days from start date. Responsiilities: Sampling fish in streams throughout Georgia using ackpack electrofishing and seining techniques, completing haitat and water quality assessments, repairing and maintaining sampling equipment, assisting with grounds work, data entry, life history and fish distriution research, and other duties as assigned. Daily and overnight ( nights per week) travel may e required. Field work days frequently extend eyond eight hours. Lodging, travel reimursement, sampling gear, and uniforms provided. Qualifications: Individuals with an interest in fisheries management, stream ecology, and/or ichthyology are encouraged to apply. Applicants should e capale of performing long days of strenuous work in adverse conditions. Compensation: $.9/hour, plus free housing To Apply: https://gadnr.org/sites/default/files/dnr/pdf/dnr_application_for_employment 6.pdf Complete the DNR Application of Employment You must specify which position(s) you are applying for on your application: Position ) Seasonal Tech., must e availale to start in early April Position ) Seasonal Tech., must e availale to start in mid May Position ) Seasonal Tech., must e availale to start in early June Please send the completed application and three references to luke.aker@dnr.ga.gov or to the address listed elow. Interviews will e held on April in Social Circle GA. Luke Baker Fisheries Technician III 76 557 Fisheries Management/Stream Survey Program 65 US Highway 78 SE Social Circle, GA 5 Housekeeping Larry Pugh will e joining our AFS su unit at 5: PM on Feruary th, in TH8 to participate in an agency jo preparation & interview workshop. He will cover an introduction to MDFP, discuss jos & qualifications for various hiring levels, and interview tips & tricks from the pre interview, conducting the interview, to handling the postinterview. Bring CV and Resumes Housekeeping La Monday Age and growth pm Group : Team Gar Aaron James Joshua Tipton Ivy Hice Laura Drake :pm Group : Team Paddlefish Sarah Yasko Jaco Moore Evangelin VonBoeckman James Hillhouse pm Group : Team Sturgeon Murry Burgess Brandon Gerhart Durham Norman Jackson Guenther :pm Group : Team Bass Chris Arnold Bayley ilmoth Alexander Binney Housekeeping Exam I is ednesday Feruary st.

A real datasheet You can do a pretty good jo predicting weight from length! EIGHT LENGTH RELATIONSHIP Length weight relationship Isometric scaling If = then fish growth is isometric all dimensions change similarly over time shape of fish does not change over time 6 7 al Allometric scaling if < then fish gets more fusiform with time Allometric scaling if > then fish gets more plump with time al al

Using length weight relationships Estimate weight from length Measure variation from the expected weight for length of individual fish or relevant group of individuals as indications of fatness, general well eing, gonad development, etc. Does a fish weigh more than another even though they are the same length? Estimating weight from length 6 7 Straightening the curve Law of logarithms a L log ( ) log ( a L ) log ( ) log ( a) log ( L) Estimating weight from length Non linear 6 8 Log log ( ) log ( a) log ( L) log ( ) a ' log ( L).5.5 Linearized.5.5 Log Can estimate weight from length! Length weight data eight eight eight 76.5 y =.59x 5.557 5.557.59 Length.5 5.557.59 8 g.5.5...6.8 Log (TL) Log (t) 768 g 6 7

Length weight eight for an age fish. eight.length. 5.9 cm eight (kg)... Total length (cm) 5 eight. Length eight. eight 8... 5 5 5 5 Total length (cm) 5 6 7 Age eight for an age 6 fish Age weight 8.6 cm Total length (cm) 5 5 eight. Length eight. 9 eight 67.. eight length (kg)....9 cm 8.6 cm 5. 5 6 7 Age 5 6 7 Age Condition Does a fish weigh more or less than expected. FISH CONDITION Similar length! 6 7

Condition Metrics Differ in how standard weight is computed Cuic of oserved length (L ) Fulton s condition factor (K) Predicted weight from oserved length using length weight relationship for studied stock LeCren s relative condition factor (Kn) Predicted 75 th percentile of mean weights from many populations given oserved length Relative weight (r) Standard weights How much does the fish weigh relative to some standard weight ased on its length? The standard fish Both the same length How do weights compare? Fulton s condition factor (K) hen metric hen english eight K Length eight C Length Relative Condition Factor (Kn) Relative condition factor (K n ) allows for allometric growth; that is, when shape changes as fish grow (Le Cren 95). K n eight a Length Assumes isometric growth! Can e difficult to interpret and compare, largely unused today. But good precursor! Relative weight Relative weight ( r ) represents refinement of the K n concept (ege and Anderson 978) Standardization among populations Facilitate comparison and interpretation Relative weight ( r ): a measure of condition here, eight = actual weight eight standard = length specific standard weight predicted y a length weight regression constructed to represent the species (75 th percentile) here, a = intercept = slope eight r eight standard Log ( eight ) a log ( Length) standard 5

Standard eight Standard weight equations are fit in several ways, ut generally speaking, you use linear regression on weight length data from the species range. However, we regress through the 75 th percentile to get an equation that represents the healthiest fish. The equation aove can e linearized: Log ( eight ) a log ( Length) standard Fitting Standard eight Log (t).5 y =.59x 5.557.5.5.5...6.8 Log (TL) Fitting Standard eight Standard eights Log (t).5.5 Fit line to the 75 th percentile y =.59x 5.557.5 Typical regression fits a.5 line to the 5 th percentile...6.8 Log (TL) Predicted as the 75 th percentile of mean weights from many populations given oserved length Largemouth Bass s equation s L 5.58.7 Relative eights (r) Generally accepted method of computing ody condition More accepted in N.A. than in Europe Computed as r s here is the length and s is the standard weight r Interpretation Thus, r= if fish is at 75 th percentile of mean weights for many stocks 75th r= 6

Intercept (a ) and slope () parameters If r < then a fish is less plump than an average fish of the same length from 75% of stocks. Species Intercept (a ) Slope () Minimum TL Source Largemouth ass -5.58.7 5 Henson (99) Bluegill -5.7.6 8 Hillman (98) Redear sunfish -.968.9 7 Pope et al. (995) 75th Channel catfish -5.8.9 7 Brown et al. (995) r< hite ass x striped ass -5..9 5 Brown and Murphy (99) Black crappie -5.68.5 Neumann and Murphy (99) hite crappie -5.6. Neumann and Murphy (99) Example: A largemouth ass is caught y electrofishing the is 56 mm and 6 g. Henson (99) determined a = 5.58 and =.7 for largemouth ass. r s 6 r 56 6 r 665 95 r 5.58.7 Interpretation If the mean r < then fish in stock are less plump, on average, Relative to an fish from the 75 th percentile less plump than an aove average standard. should not e surprised to see values < Some uses r values are well elow for an individual or a size group, prolems may exist in food or feeding conditions r values are well aove, fish may not e making the est use of a surplus of prey. Trends and patterns? Can e evaluated y plotting individual r values y fish length or mean r values for lengthgroups Calculation of mean r for an entire sample can mask important length related trends in fish condition The length groups defined y the five cell PSD model provide a convenient asis for determination of r values. Low r for a length group could e evidence of competition influencing growth. 7

r Interpretation Example r Interpretation Example From Daugherty and Sutton. 5. North American Journal of Fisheries Management 5:9. From Liao et al. 995. Transactions of the American Fisheries Society :87-. Body Condition Body Condition Factors affecting condition data Not a good idea to comine condition data from different seasons. Mature and immature fish are est analyzed separately. May need to analyze male and female fish separately. Factors affecting condition data Target r may need to e adjusted for region. Genetic differences may play a role. r provides a means for comparison and standardization across haitats. Integration of size structure and r Rules of thum Mean Relative eight (r) 5 95 9 85 8 7 6 9 8 Five fish per length interval (e.g., cm) Measure more fish if males and females have different weight length relationships Do not include small fish in weight length analyses if weights are inaccurate or precision is low. 75 6 8 PSD 8