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Fishery Bulletin 92(2). 1994 



tively, vary spatially at random. The observed as- 

 sociation between sets of character differences and 

 geographic distances was tested relative to its per- 

 mutational variance, and the resulting statistic com- 

 pared against a Student's /-distribution with infinite 

 degrees of freedom. We performed analyses using 

 GEOVAR, a computer-program library for geo- 

 graphic variation analysis (written by David M. 

 Mallis and provided by Robert R. Sokal, State Uni- 

 versity of New York at Stony Brook). 



Character differences were compared first with 

 actual geographic distances (in nautical miles) be- 

 tween centers of blocks and then with reciprocals of 

 distances. In evaluations of reciprocals, where dis- 

 tances are scaled in a nonlinear manner, longer dis- 

 tances are considered effectively to be equal, and the 

 portion of the scale involving smaller distances is 

 expanded. Thus, use of reciprocals of distances in- 

 creases the power of analyses to reveal geographic 

 patterns that are "local" in nature (i.e. involving 

 closely placed blocks), whereas tests involving nau- 

 tical-mile distances evaluate "regional" trends. Posi- 

 tive associations of character differences and nau- 

 tical-mile distances are indicated by positive /-val- 

 ues, while negative /-values denote such associations 

 when using distance reciprocals. Douglas et al. 

 ( 1992) provided a simplified example to demonstrate 

 use of the Mantel procedure. 



We also computed matrix correlations (Sneath and 

 Sokal, 1973) between character differences and the 

 associated geographic distances or reciprocals of 

 distances between localities. The statistical signifi- 



cance of these coefficients cannot be tested in the 

 conventional way, because all pairs of localities were 

 used and these are not statistically independent. 

 However, the resulting values can be used as de- 

 scriptive statistics indicating the degree of associa- 

 tion of difference values. 



Morphological-environmental covariation 



We calculated product-moment correlations of block 

 means for morphological characters with environ- 

 mental variables. Data were available for 13 envi- 

 ronmental variables for the eastern tropical Pacific 

 Ocean (Table 2; data sources summarized in Dou- 

 glas et al., 1992). The list of environmental variables 

 used is somewhat different than that employed by 

 Schnell et al. (1986), because data for some of the 

 variables were not available for all blocks in the 

 broader geographic range being considered in the 

 current study. We also used UPGMA to summarize 

 associations among these environmental variables 

 for 51 blocks; since these two dolphin species have 

 broadly overlapping distributions in the eastern 

 tropical Pacific, the blocks used are representative 

 of areas inhabited by S. attenuata. 



In order to obtain summary variables reflecting 

 overall environmental trends, we conducted a prin- 

 cipal-components analysis of the 13 environmental 

 variables for 51 blocks with specimens of S. 

 longirostris (Douglas et al., 1992) or S. attenuata or 

 both. Individual blocks were projected onto the re- 

 sulting environmental principal components based 



Table 2 



Environmental measurements compiled for each 5° latitude-longitude block.' 



1 Sea Current (N., Winter) — Average northern component (in knots) of surface water current in winter. 



2 Sea Current (W., Winter) — Average western component (in knots) of surface water current in winter. 



3 Water Depth — Average sea depth (in m). 



4 Solar Insolation (Jan.) — Average incoming solar radiation for January (in gmcal/cnr). 



5 Solar Insolation (Annual) — Average annual incoming solar radiation in gmcal/cm 2 ). 



6 Sea Surface Temp. (Jan.) — Average January sea surface temperature (in°C). 



7 Sea Surface Temp. (July) — Average July sea surface temperature (in°C). 



8 Sea Surface Temp. (Ann. Var. ) — Average annual sea surface temperature variation (in°C). 



9 Oxygen Min. Layer (Depth) — Annual mean depth (in m) of absolute oxygen minimum surface with respect to the vertical. 



10 Surface Salinity — Average salinity (%<■) of surface sea water. 



11 Thermocline Depth (Winter) — Mean depths (in m) to top of thermocline for January, February, and March. 



12 Thermocline Depth (Summer) — Mean depths lin m) to top of thermocline for July, August, and September. 



13 Surface Dissolved Oxygen — Annual mean dissolved oxygen (mL/L) of surface sea water. 



' Data sources listed in Douglas et al (1992: table 2). Abbreviations: Ann. Var. = annual variation; Jan. = January. Min. = minimum; 

 N. = north; Temp. - temperature; W. = west. 



