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While we have hydrothermally surveyed, to some degree, about 20% of the global ridge system (Figure 1b), only 13 ridge sections totaling half that distance (Figure 5) are suitable for examining the magmatic budget hypothesis described in the Introduction. These sections span the entire global spectrum of the ridge magmatic budget (as calculated from spreading rates), however, and describe a consistent and robust relationship. The first-order trend in plots of *V _{m}* vs. both

*p _{h}* = 0.043 + 0.00055

with *r ^{2}* = 0.93. This result agrees with earlier predictions [

Considerably more scatter exists in the *F _{s}* plot (Figure 5a). We interpret this scatter as a function of three overlapping uncertainties: increasing difficulty in defining the boundaries of discrete vent fields as spreading rate increases, wide variability in the effort expended in finding discrete vent sites on different ridge sections, and pronounced differences in the length of surveyed ridge sections (Table 1). After binning these data to mitigate these uncertainties as far as presently possible, the resultant least-squares regression is

*F _{s} *= 1.0 + 0.0023

with *r ^{2}* = 0.97.

These robust linear relations offer sturdy support for the hypothesis that crustal magmatic budget is the primary influence on the large-scale (multisegment) distribution of hydrothermal activity. The fact that the activity on ultraslow ridges is appreciably greater than zero, especially considering that we may have conservatively overestimated the true melt supply at the sampled ridges, suggests that ultraslow ridges may in fact be more efficient producers of vent fields than other ridges. We can test this idea by normalizing *F _{s}* to the time-averaged delivery of magma [

*F _{m}* = 10

where for each bin *N* is the number of vent fields observed, *L* is the total ridge length (km), *u _{s}* is the weighted average full spreading rate (mm/yr), and

**Figure 7. Site frequency Fs normalized to the magma delivery rate vs. spreading rate for the binned data in Figure 5a. Solid circles indicate mean values, open circles the uncertainty range (see Figure 5a). Approximately same trend would result using the ph data in Figure 5b (excluding the biased Gakkel Ridge result and the hotspot-affected ridge sections). **

Additional work on slow and ultraslow ridges will be required to establish whether the apparent trend between *F _{m}* and

Despite the robust trends in Figure 5, it is important to remember that these results do not demand that the fluxes of hydrothermal heat or chemicals are also similarly related to the magmatic budget. Many additional quantitative flux measurements, at a variety of spreading rates, will be needed to confirm that inference.

The global trend established in Figure 5a can also be used to estimate the total number of vent fields presently active on the ridge system. If we recast the binned data in Figure 5a as a plot of *F _{s}* vs.

*F _{s}* = 0.88 + 0.015

Applying this relation to the global distribution of ridge spreading rates binned at 20 mm/yr intervals yields a histogram of predicted vent sites with a total population of 1060 (with 95% confidence limits of 992–1153) (Figure 8). In contrast to the dominance of slow-spreading ridges in the global distribution of spreading rates (Figure 2c), vent field populations differ by only about a factor of 2 across spreading rate categories, except in the 100–140 mm/yr bins where total ridge length is <2% of the global sum.

**Figure 8. (a) Histogram of predicted vent site population as a function of spreading rate in 20 mm/yr bins (e.g., 0–20, 20–40, etc.). Total population on ridges is estimated as 1060. (b) and (c) show 95% confidence limits for high and low estimates, respectively.**

A recurring concern in attempting to relate hydrothermal activity to geological variability is that hydrothermal data are unavoidably time aliased. Mean hydrothermal activity over a much longer period might be distributed quite differently than at present, especially at slow spreading rates. This problem can be partially addressed by comparing the vent field distribution with the oceanic distribution of He, an unequivocal and conservative tracer of magmatic degassing along ridge crests [*Craig and Lupton*, 1981]. Overlaying the global ridge system with the deep-water (2000–3000 m) (He%) pattern [*Geosecs Atlantic, Pacific, and Indian Ocean Expeditions, *1987; *Jamous et al.*, 1992; *Lupton*, 1995, 1998; *Rüth et al.*, 2000] reveals a strong, but not perfect, correlation between *u _{s}* and (He%) (Figure 9). The most intense (He%) plume in the ocean spreads westward from the fastest spreading ridge segments in the ocean, and other intense plumes originate on the fast-spreading northern EPR and the intermediate-rate JDFR. The Atlantic has lower (He%) than either the Pacific or Indian Oceans [

Past this basic distinction between fast and slow ridges in Figure 9, the distribution of (He%) becomes more complex. Values of (He%) along fast-spreading ridges in the eastern Pacific show discrete highs rather than a uniform distribution corresponding to the spreading rate trend. Unexpectedly low (He%) values occur all along the ridge from the Indian Ocean triple junction to the EPR-Chile Rise triple junction. These features are not solely the result of long-wavelength fluctuations in the distribution of vent fields, but instead may be generated by patterns of oceanographic advection and ventilation. Deep currents in the eastern Pacific and vigorous vertical and circumpolar mixing around Antarctica are two primary controls on the (He%) distribution [*Farley et al.*, 1995; *Lupton*, 1998]. These complications, in fact, emphasize the value of more complete knowledge about the global distribution of vent fields. Without accurate knowledge of He sources along the global ridge system, the utility of (He%) distributions as a tracer of ocean advection and mixing will remain limited.

**Figure 9. Deep-water (~2000–3000 m) distribution of (He)% values [ Geosecs Atlantic, Pacific, and Indian Ocean Expeditions, 1987; Lupton, 1995, 1998; Jamous et al., 1992; Rüth et al., 2000] compared to ridge full spreading rates ((He)% = 100(R/R – 1); R = He/He). Areas with (He)% values >30 are shaded. The MOR is divided into four rate categories corresponding to increasing line thickness: 1, <20 mm/yr; 2, 20–<50 mm/yr; 3, 50–100 mm/yr; 4, >100 mm/yr. **

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