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<br />1.0 <br /> <br />LITTLE COLORADO RIVER HUMPBACK CHUB <br /> <br />237 <br /> <br />~ 0.8 <br />~ 0.6 <br />= <br />o <br />';: 0.4 <br />o <br />c. <br />e 0.2 <br />0.. <br /> <br />Cl:!. ...fb.. .:.. <br />c I;l~ . <br />.:p 0$ .. <br />.... 0'. <br />aD [J. .. <br />~.\; . <br />oJ 0 <br /> <br />,"" <br /> <br />. " <br /> <br />.. <br /> <br />" . <br />. . <br /> " . <br />" , <br /> , <br /> <br />0.0 <br /> <br />,of ,~' ,~'" ,0,0,"> ,~... ,0,0,<-' ~o,'" ,~" ,0,0,0" ,o,~ ",#' -f'''' ",<S>'" <br /> <br />Year <br /> <br />FIGURE L-Observed monthly mark rates of adult (age-4 <br />and older) humpback chub captured in the Little Colorado <br />River (diamonds) and the Little Colorado River inflow reach <br />of the Colorado River (squares). <br /> <br />on the model parameter of interest. We again evaluated <br />model fit using AlCc (Table 2). <br />The annual ASMR model.-We used the ASMR <br />model (Coggins et al. 2006) to estimate the age-specific <br />mortality rate, the age- and time-specific capture <br />probabilities, adult abundance, and recruit (age-2) <br />abundance. Like the traditional Jolly-Seber type <br />models, the annual ASMR model uses data aggregated <br />within years and ignores multiple within-year recapture <br />information. Three formulations (ASMR 1-3) of the <br />overall model structure were used to explore alter- <br />natives in estimating time- and age-specific capture <br />probabilities. We used a Markov chain-Monte Carlo <br />algorithm to assess parameter uncertainty for each <br />model formulation (Coggins et al. 2006). <br />Multistate movement models.-The ASMR and <br />traditional Jolly-Seber models do not explicitly <br />represent seasonal spawning movements between the <br />LCR and the LCR inflow reach. Because sampling has <br />historically been concentrated in the LCR (there were <br />over 12,500 recapture events in the LCR versus about <br />1,100 in the LCR inflow reach), it is possible that the <br />capture probabilities calCulated from spatially aggre- <br />gated data could lead to misleading population <br />estimates (e.g., underestimates of the numbers of adult <br />fish that are seasonally resident in the LCR inflow <br />reach). To evaluate this possibility, we developed <br />a spatially explicit model for individual recapture <br />histories (Appendix), treating fish as being in two <br />possible location states (the LCR or the LCR inflow <br />reach) in each sampling month. The binomial likeli- <br />hood function for this model was combined with the <br />Poisson likelihood function for unmarked fish from the <br />ASMR model (Coggins et al. 2006) to provide an <br />overall model for the dynamics of both marked and <br />unmarked fish. Our goal was to estimate age-specific <br />mortality rates, monthly movement rates to and from <br />the LCR, monthly capture probabilities in both <br />locations, and the abundance of llIIl11aIked fish over <br />time by maximizing this combined likelihood function. <br /> <br />", <br /> <br />We also evaluated multistate movement models <br />(Brownie et al. 1993; Hestbeck et al. 1991) in MARK <br />that allow animals to move between strata and provide <br />a probability of transitioning between strata. <br /> <br />Results <br />High mark rates (>80%) were achieved in the mid- <br />1990s (Figure 1). Examination of the monthly mark <br />rates among recapture locations (LCR versus LCR <br />inflow reach) indicates that fish mix and move between <br />the two areas, as there are similar patterns in overall <br />mark rate with large changes in sampling intensity. <br /> <br />Index-Based Assessments <br /> <br />Long-term catch rate indices from the standardized <br />hoop and trammel net sampling show 2-3-fold declines <br />in catch rate from the late 1980s to the present (Figure <br />2). Although all monthly trammel net samples from the <br />LCR inflow reach for 1990-2003 are presented, only <br />samples from 1990-1993 and 200 1 represent robust <br /> <br />0.3 <br /> <br />2 <br />~ 0.25 <br />~ 0.2 <br />~ 0.15 <br />2: 0.1 <br />a. <br />~ 0.05 <br />o <br /> <br />~~#~~#~~~~~~~~~#\$ <br /> <br />~ J51-I99mmTL <br /> <br /> <br />--$->200mmTL <br /> <br />Year <br /> <br />: 1.2 <br />~ \ <br />B <br />Ll 0.8 <br />Z 0.6 <br />~ 0.4 <br />E <br />E <br />f- <br /> <br />. . <br /> <br />" " <br /> <br />~.:~. -.".. ._~~. - _. h <br /> <br />. . . <br />'. . <br />. . <br /> <br />0.2 <br />o <br /> <br />~rf,> ~o,' ~o,'" ~o," ,~... ~o,<-' ,~'" ~o," ,~o" ~~ ",#' ",<S>' ",<S>'" -f''''' ",# <br /> <br />. . <br />" . <br /> <br />Year <br /> <br />FIGURE 2.-AnnuaI mean humpback chub caleh rate using <br />hoop nets (top panel; caleh}h, with 95% confidence intervals) <br />in the lower 1,200 m of the Little Colorado River (LCR) and <br />mean monthly humpback chub (1L >200 rom) catch rate <br />using trammel nets (bonom panel; catch .h-1.1oo m-I) in the <br />Little Colorado River inflow reach (LCR inflow reach) of the <br />Colorado River. In the bottom panel, diamonds represent the <br />extensive sampling that took place in 1990--1993 and 200t <br />and that was well distributed throughout the LCR inflow <br />reach. Squares represent the limited sampling that took place <br />in 1994-2000 and 2002-2003 and that, in some years, was <br />concentrated near the confluence of the LCR. Though both <br />regression lines (dashed, 1990--2003; solid, 1990--1993 and <br />2001) suggest a declining trend in abundance, the slope of <br />neither regression is significantly different from zero (P = 0.14 <br />for both regressions). <br />