National Electrofishing Programme for Scotland

References

NEPS Report (2021)

I A Malcolm, F L Jackson, K J Millidine, P J Bacon, A G McCartney and R J Fryer. 2023. The National Electrofishing Programme for Scotland (NEPS) 2021. Scottish Marine and Freshwater Science Reports Vol 14, No 2, pp. 63 doi: 10.7489/12435-1

NEPS Report (2019)

Malcolm I.A., Millidine K.J, Jackson F.L, Glover R.S Fryer R.J. 2020. The National Electrofishing Programme for Scotland (NEPS) 2019. Scottish Marine and Freshwater Science Vol 11 No 9, 56pp. DOI: 10.7489/12321-1

NEPS Report (2018)

Malcolm, I.A. Millidine, K.J. Jackson, F.L. Glover, R.S. and Fryer, R.J. (2019) Assessing the status of Atlantic salmon (Salmo salar) from juvenile electrofishing data collected under the National Electrofishing Programme for Scotland (NEPS). Scottish Marine and Freshwater Science Vol. 10 No. 2.

NEPS R Shiny Application

This interactive application allows you to explore data collected under the NEPS programme and accompanies the NEPS report (above). Functionality allows you to map data and analytical outputs at site, regional or national scales and to export maps and the underlying processed data.

Data from NEPS 2018, 2019 and 2021 (included within the NEPS 21 Report) can be explored within a new R Shiny application, which includes information on densities of juvenile salmon and trout, levels of genetic introgression in juvenile salmon and water quality.

National juvenile salmon density model for Scotland (the benchmark) 

Malcolm IA, Millidine KJ, Glover RS, Jackson FL, Millar CP, Fryer RJ. 2019. Development of a large-scale juvenile density model to inform the assessment and management of Atlantic salmon (Salmo salar) populations in Scotland. Ecological Indicators 96: 303–316 DOI: 10.1016/J.ECOLIND.2018.09.005

Generalised Random Tessellation Stratified Sample Design

Kincaid, T. M. and Olsen, A. R. 2017. spsurvey: Spatial Survey Design and Analysis. R package version 3.4.

Stevens, D.L., Olsen, A.R., 2004. Spatially balanced sampling of natural resources. J. Am. Stat. Assoc. 99, 262–278.

Modelling Capture Probability

Glover. R.S., Fryer. R.J., Soulsby. C., Malcolm. I.A. 2019. These are not the trends you are looking for: poorly calibrated single‐pass electrofishing data can bias estimates of trends in fish abundance. Journal of Fish Biology.

Millar, C.P., Fryer, R.J., Millidine, K.J., Malcolm, I.A., 2016. Modelling capture probability of Atlantic salmon (Salmo salar) from a diverse national electrofishing dataset: Implications for the estimation of abundance. Fish. Res. 177, 1–12.

Millar, C.P., Fryer, R.J., Malcolm, I.A., Glover, R.S., 2017. ef: Modelling Framework for the Estimation of Salmonid Abundance in Scottish Rivers.

Dauphin, G.J.R., Chaput, G.J., Breau, C., Cunjak, R.A., 2018. Hierarchical model detects decadal changes in calibration relationships of single pass electrofishing indices of abundance of Atlantic Salmon in two large Canadian catchments. Can. J. Fish. Aquat. Sci. cjfas-2017-0456.

Two Stage Models Incorporating Capture Probability and Density Predictions

Glover, R.S., Fryer, R.J., Soulsby, C., Bacon, P.J., Malcolm, I.A., 2018. Incorporating estimates of capture probability and river network covariance in novel habitat - abundance models: assessing the effects of conservation stocking on catchment-scale production of juvenile Atlantic salmon (Salmo salar) from a long-term electrofishing dataset. Ecol. Indic. 93, 302–315.

Millar, C.P., Millidine, K.J., Middlemas, S.J. & Malcolm, I.A. Development of a Model for Predicting Large Scale  Spatio-Temporal Variability in Juvenile Fish Abundance from Electrofishing Data. Scottish Marine and  Freshwater Science Report. Volume 6. Number 6.

Malcolm, I.A., Millidine, K., Glover, R.S., Hawkins, L., Millar, C., 2016. Assessing the status of Atlantic salmon in the Aberdeenshire River Dee from electrofishing data. Mar. Scotl. Sci. Rep. 7.