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2007 to July 2011. Temperature data are not available for Tony Sinks Cave from March 2009 to January 2010 due to instrument loss. Crayfish growth rates were estimated as the difference between OCL at initial marking and the OCL upon recapture divided by days elapsed. This rate was then multiplied by 365 to acquire an annual growth increment. Since growth increments are “episodic” due to the molting cycle, annual growth increments were only calculated for individuals recaptured over intervals of 350 days or longer. Negative annual growth-increments were attributed to measuring error and were excluded from analyses. For crayfish recaptured multiple times, the annual growth increment was calculated using the recapture date closest to the 350-day minimum. Annual growth increments were regressed against average OCL to estimate the size-specific annual growth rate. To estimate size-at-age, the size-specific annual growth rate was first seeded with a 3 mm OCL individual, the size of juveniles attached to the pleopods of a single female collected from Hering Cave. This process was then iterated at annual intervals and growth trajectories bounded by 95% confidence limits were then constructed using a bootstrap technique (Whitmore & Huryn, 1999). A significant difference in growth trajectories among caves was assumed when 95% confidence intervals did not overlap. Separate growth trajectories were produced for male and female crayfish to assess sexspecific patterns. Time-to-maturity was estimated by plotting the smallest reproductive (Form I) male and female (using presence of cement glands) onto the resulting growth trajectories. The largest male and female and the smallest female with ova or young were used to estimate minimum life span and age-at-first-reproduction, respectively. Ages constrained by 95% confidence limits represented the estimated range. Cumulative size-frequency distributions were constructed for each cave, including Shelta Cave (see below), and then compared to examine for 79
differences in size structure among populations using pairwise Kolmogorov-Smirnov (K-S) tests. K-S tests were performed in program R version 2.14.0 (R Development Core Team, 2008). Cooper’s (1975) growth models Growth rates reported by Cooper (1975) were estimated as the difference between TCL at initial marking and upon recapture divided by months elapsed. Cooper (1975) calculated monthly growth rates for a total of 56 individuals (Cooper, 1975, pp. 273-280, Tables 36 and 37) ranging in size from 10 to 47 mm TCL. Only 10 of these were less than 23 mm TCL, however. Cooper (1975) constructed his mean and maximum growth models by placing the 56 individuals for which he calculated monthly growth rates into six size-classes. The mean and maximum monthly growth rate for each size class was then used to estimate the number of months required for an individual to grow through each size-class. Essentially, Cooper (1975) constructed a series of linear growth models that approximated an exponential growth model (see results below). To compare the results of this study with those of Cooper (1975), first Cooper’s (1975) original growth models were reconstructed (Cooper, 1975, p. 312, Table 43). Annual growth rates were then calculated from the crayfish that Cooper (1975) had marked for at least 11 months (n = 26; Cooper, 1975, pp. 273-280, Tables 36 and 37), and growth models were constructed using the methods described in this study (see above). A subset of Cooper’ (1975) data was used because it better reflected the rationale (e.g. crayfish molt cycle) and methods (e.g. annual growth rates) used to construct growth models for the three study populations from this study. A sizefrequency histogram for the Shelta Cave population was also recreated (Cooper, 1975, p. 158, Fig. 26) by digitizing the original figure (DigitizeIt version 1.5.8b; Bormann, 2010). Cooper’s (1975) TCL was converted to OCL using a conversion factor that allowed size-classes and cumulative size-frequency distributions to be compared among studies. Crayfish from Hering 80
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THE INFLUENCE OF ENERGY AVAILABILIT
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ABSTRACT Detritus from surface envi
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LIST OF ABBREVIATIONS AND SYMBOLS m
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NC IL ON U.K. VIAT VIE Fig. North C
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AIC K-S Akaike information criterio
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laboratory work and was an excellen
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LIST OF TABLES TABLE 2.1 TABLE 2.2
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LIST OF FIGURES FIGURE 2.1 (a) Box
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FIGURE 4.3 Growth models for Orcone
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chemolithoautotrophy-based systems;
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ecology, 51, 31-53. Gibert J. & Cul
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CHAPTER 2 EFFECTS OF ORGANIC MATTER
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community structure in cave “pits
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communities and how variation in co
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the different source locations was
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of natural-log transformed data (%
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peak in organic matter in Big Mouth
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Figs. 5a, b). The breakdown rate of
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per litter bag. Similarly, Huntsman
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ags was the greater retention of li
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Historically, limited resource inpu
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Culver, D.C. & Pipan, T. (2009) The
Page 45 and 46: Merritt, R.W., Cummins, K.W. & Berg
Page 47 and 48: Table 1. Mean (1 S.D.) macroinverte
Page 49 and 50: Table 2. Mean (±1 S.D.) daily temp
Page 51 and 52: Figure 1. (a) Box and whisker plot
Page 53 and 54: Figure 3. Non-metric multidimension
Page 55 and 56: Figure 5. Box and whisker plot of l
Page 57 and 58: streams, while the obligate-cave sp
Page 59 and 60: More recent observational and exper
Page 61 and 62: of netting (mesh size 2.5×1.5-cm)
Page 63 and 64: the two end-members. This conservat
Page 65 and 66: crop organic matter significantly i
Page 67 and 68: macroinvertebrate biomass to levels
Page 69 and 70: and surface streams (20-35,000 g m
Page 71 and 72: these factors, the stable isotope a
Page 73 and 74: surface streams. Thus, it is likely
Page 75 and 76: subsides to ecosystem dynamics have
Page 77 and 78: populations. Journal of Applied Eco
Page 79 and 80: Poulson T.L. & Lavoie K.H. (2001) T
Page 81 and 82: Wood P., Gunn J. & Perkins J. (2002
Page 83 and 84: Table 2. Mean (±1 standard deviati
Page 85 and 86: Table 2. Continued Chironomini Para
Page 87 and 88: Figure 1. Mean (bars are standard e
Page 89 and 90: Figure 3. Non-metric multidimension
Page 91 and 92: CHAPTER 4 REXAMINING EXTREME LONGEI
Page 93 and 94: individuals, he predicted that it w
Page 95: A phylogeographic study by Buhay &
Page 99 and 100: and females in Tony Sinks Cave were
Page 101 and 102: Estimates of life span for O. austr
Page 103 and 104: available size-classes were well re
Page 105 and 106: References Anonymous (1999) Cave Sc
Page 107 and 108: Huryn A.D. & Wallace J.B. (1987) Pr
Page 109 and 110: Whitmore N. & Huryn A.D. (1999) Lif
Page 111 and 112: Table 2. Estimated life span (years
Page 113 and 114: Figure 1. Annual growth increment (
Page 115 and 116: Figure 3. Growth models for Orconec
Page 117 and 118: CHAPTER 5 CONSUMER-RESOURCE DYNAMIC
Page 119 and 120: following incidental inputs of orga
Page 121 and 122: Temperature data were not available
Page 123 and 124: minimum (Venarsky et al., 2012b). A
Page 125 and 126: 100% organic matter (i.e., maximum
Page 127 and 128: Macroinvertebrate biomass varied si
Page 129 and 130: Discussion The energy-limitation hy
Page 131 and 132: crayfish captured in most months we
Page 133 and 134: systems is likely high, especially
Page 135 and 136: function of microbial films in grou
Page 137 and 138: Crustacean Biology, 4, 35-54. Momot
Page 139 and 140: Whitmore N. & Huryn A. (1999) Life
Page 141 and 142: Table 2. Assimilation efficiencies
Page 143 and 144: Table 3. Continued Tanypodinae 0.03
Page 145 and 146: Table 5. Estimates of mean wood and
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Figure 1. (A) Box and whisker plot
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CHAPTER 6 OVERALL CONCLUSIONS Due t
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characteristics (e.g., higher growt
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characteristics, highly efficient p
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