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due to high water velocities (Webster & Benfield, 1986; Simon & Benfield, 2001). Despite differences among caves in organic matter abundance and total macroinvertebrate biomass per litter bag, breakdown rates within each litter type and mesh size were similar except for red maple in coarse-mesh bags in Salt River and Tony Sinks caves. An absence of shredders can affect litter breakdown rates in surface systems (Wallace et al., 1986; Hieber & Gessner, 2002; Eggert & Wallace, 2003) and previous studies in cave systems have attributed slow leaf litter breakdown rates to the absence of large shredding taxa (Brussock et al., 1988; Galas et al., 1996; Simon & Benfield, 2001). The generally low shredder biomass found in the present study was likely to be a significant factor driving similarities in breakdown rates among cave streams. Breakdown rates of corn and red maple litter spanned a wide range of values (k = 0.001 to 0.012 d -1 ). Mesh size significantly affected breakdown rate, which was generally faster and more variable in coarse- than in fine-mesh litter bags. The difference in breakdown rate among mesh sizes was unlikely to have been due to shredder exclusion because: i) shredder biomass was universally low (2 -17% of total biomass per litter bag) among all cave stream communities, ii) large-bodied shredders (e.g. crayfish, plecopterans, trichopterans, amphipods) were not well represented in the coarse-mesh litter bags, and iii) the dominant potential shredder was a smallbodied dipteran (Polypedilum) capable of colonizing both coarse and fine mesh litter bags (Table 1). Slower litter breakdown in fine mesh bags have been attributed to anaerobic conditions due to reduced gas exchange (Cummins et al., 1980, Webster & Benfield, 1986). Compaction of leaf litter occurred within the litter bags from this study, which potentially generated anaerobic conditions in the centre of fine-mesh bags. However, macroinvertebrate biomass in fine mesh bags was similar to or higher than in coarse-mesh bags and there was no evidence of anaerobic conditions (e.g. blackened litter). A more probable cause of the slower breakdown in fine-mesh 21
ags was the greater retention of litter fragments from physical and invertebrate processing. The relatively high breakdown rates of litter in coarse-mesh bags in Tony Sinks and Salt River were probably due to the effects of flooding. The large coefficient of variation (CV) for discharge in these systems indicates that floods occurred frequently, potentially accelerating coarse-mesh breakdown rates via fragmentation and abrasion due to high water velocities (Canton & Martinson, 1990). Mean corn litter breakdown rates estimated in this study were two to 20× lower than past estimates for surface streams (Table 3). Not surprisingly, the available surface studies of corn litter breakdown have been in agricultural streams (Rosi-Marshall et al., 2007; Griffiths et al., 2009; Swan et al., 2009), with higher nutrient concentrations (e.g. N and P) and shredder abundances than the cave streams used in this study. The oligotrophic state of the cave streams in this study, coupled with low shredder biomass, probably contributed to the relatively low breakdown rates of corn litter measured in this study. Mean breakdown rates for maple litter in the study streams in this study were either similar to or lower than estimates made using similar methods in surface systems (Table 3) with comparable nutrient concentrations. Shredder abundances were higher in the surface stream studies, which is likely to have contributed to faster litter breakdown. Litter breakdown estimates from this studies fine-mesh bags were two to five times slower than estimates reported in a study by Gulis & Suberkropp (2003) that used 1-mm mesh bags to minimize macroinvertebrate colonization. While the smaller mesh size used in this study may have contributed to slower breakdown via increased fragment retention, limited microbial colonization may have also played a role. Microbial abundance and diversity have been reported to be lower in both hyporheic habitats and aquifers than in surface streams (Ellis, Stanford & Ward, 1998; 22
Page 1 and 2: THE INFLUENCE OF ENERGY AVAILABILIT
Page 3 and 4: ABSTRACT Detritus from surface envi
Page 5 and 6: LIST OF ABBREVIATIONS AND SYMBOLS m
Page 7 and 8: NC IL ON U.K. VIAT VIE Fig. North C
Page 9 and 10: AIC K-S Akaike information criterio
Page 11 and 12: laboratory work and was an excellen
Page 13 and 14: LIST OF TABLES TABLE 2.1 TABLE 2.2
Page 15 and 16: LIST OF FIGURES FIGURE 2.1 (a) Box
Page 17 and 18: FIGURE 4.3 Growth models for Orcone
Page 19 and 20: chemolithoautotrophy-based systems;
Page 21 and 22: ecology, 51, 31-53. Gibert J. & Cul
Page 23 and 24: CHAPTER 2 EFFECTS OF ORGANIC MATTER
Page 25 and 26: community structure in cave “pits
Page 27 and 28: communities and how variation in co
Page 29 and 30: the different source locations was
Page 31 and 32: of natural-log transformed data (%
Page 33 and 34: peak in organic matter in Big Mouth
Page 35 and 36: Figs. 5a, b). The breakdown rate of
Page 37: per litter bag. Similarly, Huntsman
Page 41 and 42: Historically, limited resource inpu
Page 43 and 44: 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 and 96:
A phylogeographic study by Buhay &
Page 97 and 98:
differences in size structure among
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
Page 147 and 148:
Figure 1. (A) Box and whisker plot
Page 149 and 150:
CHAPTER 6 OVERALL CONCLUSIONS Due t
Page 151 and 152:
characteristics (e.g., higher growt
Page 153 and 154:
characteristics, highly efficient p
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