Fishery Bulletin 113(2) 
Reese, D. C., and R. D. Brodeur. 
2006. Identifying and characterizing biological hotspots 
in the northern California Current. Deep Sea Res. (II 
Top. Stud. Oceanogr.) 53:291-314. Article 
Rose, G. A., B. A. Atkinson, J. Baird, C. A. Bishop, and D. W. 
Kulka. 
1994. Changes in distribution of Atlantic cod and 
thermal variations in Newfoundland waters, 1980- 
1992. ICES Mar. Sci. Symp. 198:542-552. 
Rose, G. A., and D. W. Kulka. 
1999. Hyperaggregation of fish and fisheries: how 
catch-per-unit-effort increased as the northern cod 
( Gadus morhua) declined. Can. J. Fish. Aquat. Sci. 
56:118-127. Article 
Rulifson, R. A., and T. M. Moore. 
2009. Population estimates of spiny dogfish aggregations 
overwintering south of Cape Hatteras, North Carolina, 
using an area density method. In Biology and manage- 
ment of dogfish sharks (V. F. Gallucci, G. A. McFarlane, 
and G. G. Bargmann, eds.) p. 133-138. Am. Fish. Soc., 
Bethesda, MD. 
Sagarese, S. R., M. G. Frisk, R. M. Cerrato, K. A. Sosebee, J. A. 
Musick, and P. J. Rago. 
2014a. Application of generalized additive models to ex- 
amine ontogenetic and seasonal distributions of spiny 
dogfish ( Squalus acanthias ) in the Northeast (US) 
shelf large marine ecosystem. Can. J. Fish. Aquat. Sci. 
71:847-877. Article 
Sagarese, S. R., M. G. Frisk, T. J. Miller, K. A. Sosebee, J. A. 
Musick, and P. J. Rago. 
2014b. Influence of environmental, spatial, and onto- 
genetic variables on habitat selection and manage- 
ment of spiny dogfish in the Northeast (US) shelf 
large marine ecosystem. Can. J. Fish. Aquat. Sci. 
71:567-580. Article 
Salthaug, A., and S. Aanes. 
2003. Catchability and the spatial distribution of fishing 
vessels. Can. J. Fish. Aquat. Sci. 60:259-268. Article 
Shepherd, T., F. Page, and B. Macdonald. 
2002. Length and sex-specific associations between spiny 
Appendix: Semivariograms 
Spatial analyses of spatiotemporal overlap between 
spiny dogfish ( Squalus acanthias) and commercial 
fisheries in the northeast U.S. shelf large marine eco- 
system included the use of semivariograms to inves- 
tigate the spatial dependence of sample points, en- 
abling geostatistical modeling. Semivariograms were 
used in conjunction with ordinary kriging to interpo- 
late survey and fishery catch of spiny dogfish outside 
of the sampled domain. This appendix provides de- 
tails on the semivariogram modeling used and mod- 
el selection process in this study of spatiotemporal 
interactions between spiny dogfish and commercial 
fisheries. 
Methods 
Empirical semivariograms (y[/z] ) were calculated with 
the following semivariance equation: 
dogfish (Squalus acanthias) and hydrographic variables 
in the Bay of Fundy and Scotian Shelf. Fish. Oceanogr. 
11:78-89. Article 
Smith, S. J., and F. H. Page. 
1996. Associations between Atlantic cod ( Gadus morhua) 
and hydrographic variables: implications for the man- 
agement of the 4VsW cod stock. ICES J. Mar. Sci. 
53:597-614. Article 
Swain, D. P., G. A. Poirier, and A. F. Sinclair. 
2000. Effect of water temperature on catchability of At- 
lantic cod ( Gadus morhua) to the bottom-trawl survey 
in the southern Gulf of St Lawrence. ICES J. Mar. Sci. 
57:56-68. Article 
Tallack, S. M. L., and J. W. Mandelman. 
2009. Do rare-earth metals deter spiny dogfish? A 
feasibility study on the use of electropositive “mis- 
chmetal” to reduce the bycatch of Squalus acanthias 
by hook gear in the Gulf of Maine. ICES J. Mar. Sci. 
66:315-322. Article 
Trenkel, V. M., R. I. C. C. Francis, P. Lorance, S. Mahevas, M.- 
J. Rochet, and D. M. Tracey. 
2004. Availability of deep-water fish to trawling and 
visual observation from a remotely operated vehicle 
(ROV). Mar. Ecol. Prog. Ser. 284:293-303. Article 
Wagenmakers, E. J., and S. Farrell. 
2004. AIC model selection using Akaike weights. Psy- 
chon. Bull. Rev. 11:192—196. Article 
Waring G. T., E. Josephson, K. Maze-Foley, and P. E. Rosel 
(eds.). 
2011. U.S. Atlantic and Gulf of Mexico marine mammal 
stock assessments — 2010, Appendix III. NOAA Tech. 
Memo. NMFS-NE-219, 595 p. 
Webster, R., and A. B. McBratney. 
1989. On the Akaike Information Criterion for choosing 
models for variograms of soil properties. J. Soil Sci. 
40:493-496. Article 
Wilberg, M. J., J. T. Thorson, B. C. Linton, and J. Berkson. 
2009. Incorporating time-varying catchability into popu- 
lation dynamic stock assessment models. Rev. Fish. 
Sci. 18:7-24. Article 
*h) = 2^h) nZ(Xi) ~ Z(Xi+h)]2 ’ (1) 
where ZOq) and Z(x j+h) = measured values of catch per 
unit of effort (CPUE) at sample points Xj 
and respectively; and 
n(h) = the total number of sample pairs for any 
separation distance h (Matheron, 1971). 
Each semivariogram was used to estimate 3 parame- 
ters: 1) the range (a), or the asymptotic distance beyond 
which samples were spatially independent; 2) the sill 
(Cg), or the value of the semivariance at any distance 
>a; and 3) the nugget (Co), the semivariance at the ori- 
gin (h= 0). In situations where autocorrelation between 
2 locations changed with both direction and distance (a 
condition known as anisotropy), 2 additional parame- 
ters were estimated: 1) the ratio of the minor to major 
axis lengths and 2) the angle of the principal direction 
of continuity (Pebesma et al., 2011). Anisotropic param- 
eters were estimated with the use of the intamap pack- 
age (Pebesma et al., 2011). Multiple theoretical models 
were tested, including the following ones: 
