APPENDIX

Table A1. Example of how intrinsic rate of increase (r) is calculated using a life history table approach for a simulation including one dam. lx is calculated by multiplying the previous lx survival rate by the stage-specific survival (sx) and by the dam survival rate associated with that life stage (note that a return spawner will have encountered the same dam twice in its life time, thus the dam survival associated with this stage is the dam-passage rate multiplied by itself – e.g. 0.90 * 0.90=0.81).

Age (x) / sx / Dam / lx / mx / lx*mx / lx*mx*x
egg / 0 / 1 / 1 / 1 / 0 / 0 / 0
smolt / 2.5 / 0.0177 / 1 / 0.0177 / 0 / 0 / 0
2SW / 4 / 0.0083 / 0.9 / 0.00015 / 8500 / 1.12 / 4.50
kelt / 4.5 / 0.63 / 0.9 / 9.26E-05 / 0 / 0 / 0
2S / 5 / 0.8 / 0.81 / 7.40E-05 / 8500 / 0.51 / 2.55
SUM / 1.63 / 7.04
lx*mx*x / lx*mx / 4.31
r / 0.11

*2S = return spawner

Table A2. The per capita population growth rate (r) for Atlantic salmon (Salmo salar)inhabiting rivers having 0 to 4 dams for a range of dam-passage survival rates under a deterministic model.

Kelt stage included / Number of dams / Per capita population growth (r)
1.00 / 0.90 / 0.87 / 0.83
Yes / 0 / 0.14 / - / - / -
1 / - / 0.11 / 0.10 / 0.09
2 / - / 0.08 / 0.06 / 0.03
3 / - / 0.05 / 0.02 / -0.02
4 / - / 0.02 / -0.02 / -0.07
No / 0 / 0.06 / - / - / -
1 / - / 0.03 / 0.02 / 0.01
2 / - / 0.00 / -0.01 / -0.04
3 / - / -0.02 / -0.05 / -0.08
4 / - / -0.04 / -0.08 / -0.13

Influence of kelt survival

A study by Halttunen et al. (2009) measured a 92% survival rate for Atlantic salmon kelts in River Alta in Northern Norway. This estimate was a minimum as some fish may not have been recorded or the tags used may have malfunctioned. The study did not, however, measure the number of returning kelts, and thus some at-sea mortality may have been unaccounted for. Other studies have shown kelt survival to range extensively from <1% to 40-60% (Ducharme 1969; Niemela et al. 2006; Hubley et al 2008; USASAC 2011). It therefore seems reasonable for kelt survival in the present study to be 80%, although it is noted that this may be a slight over-estimate. To address the concern that 80% kelt survival may be unrealistic, a sensitivity analysis was conducted to determine the influence kelt survival may have on the model output. As expected, the probability of population decline increased when kelt survival was decreased (Table 4, in text). This increase was most apparent with each drop in kelt survival, however decrease in probability of decline slowed once kelt survival was ≤0.10. Interestingly, once kelt survival reached 1%, the results were very similar to the no-kelt scenarios presented in Table 2. This indicates that kelts can play a large role in population persistence, and increasing kelt survival is likely to help stabilize population decline. This is supported by the statistically significant difference (p-value = 0.002) between groups of kelt survival, which may indicate sensitivity of the model to kelt survival. Moreover, a linear model that included the number of dams, DPS, kelt survival, and their interaction as factors was created to determine which of these factors best describes the probabilities of decline found in Table 4. It was found that all three factors and their interactions were highly significant (p-value 2.2e-16; adjusted R-squared 0.9973). This is an indication that all three are important for population persistence of Atlantic salmon, and that their effects are not independent of one another. However, the magnitude of the changes in kelt survival may not be biologically significant because a 99% decrease in kelt survival only resulted in a 31% increase in probability of decline (Table 4), whereas one may expect a greater decline should the role of kelts be incredibly influential. Conversely, an increase from 1 to 4 dams resulted in a >30% increase in decline. Indeed, it appears that the number of dams (particularly when greater than two) and the DPS may have a greater influence on probability of decline for Atlantic salmon.

References

Ducharme, L. J. A. 1969. Atlantic salmon returning for their fifth and sixth consecutive spawning trips. J. Fish. Res. Board Can. 26: 1661–1664.

Halttunen, E., Rikardsen, A. H., Davidsen, J. G., Thorstad, E. B., and Dempson, J. B. 2009. Survival, migration speed and swimming depth of Atlantic salmon kelts during sea entry and fjord migration.In Tagging and Tracking of Marine Animals with Electronic Devices.Edited by J.L. Nielsen, H Arrizabalaga, N. Fragoso, A. Hobday, M. Lutcavage, and J. Sibert.Springer Netherlands. pp. 35-49.

Hubley, P. B., Amiro, P. G., Gibson, A. J. F., Lacroix, G. L., and Redden, A. M. 2008. Survival and behaviour of migrating Atlantic salmon (Salmo salar L.) kelts in river, estuarine, and coastal habitat. ICES J. Mar. Sci.65(9): 1626-1634.

Niemela, E., Erkinaro, J., Julkunen, M., Hassinen, E., Lansman, M.,and Brors, S. 2006. Temporal variation in abundance, return rateand life histories of previously spawned Atlantic salmon in a large Subarctic river. J. Fish Biol.68: 1222–1240.

USASAC. 2011. Annual report of the U.S. Atlantic Salmon Assessment Committee. Report no. 23 – Activities. Prepared for U.S. Section to NASCO (North Atlantic Salmon Conservation Organization). Available from [accessed 8 March 2016].