undefined

Mapping natural and artificial migration hindrances for fish using LiDAR remote sensing

Year of publication

2020

Authors

Hedger, Richard; Bergan, Morten A.; Blumentrath, Stefan; Eloranta, Antti P.

Abstract

We developed a new method to map and evaluate the impact of potential natural and artificial migration hindrances on the spatial distribution of sea trout (Salmo trutta) within stream networks. A stream network was derived from a 1 m2 spatial resolution LiDAR-based Digital Terrain Model (DTM), using part of Trondheim Region as a test case. Algorithms were developed to identify potential artificial migration hindrances (stream crossings and culverts) from the DTM, and to correct the DTM to enable generation of a terrain-derived stream network that followed the topography better than manually-digitized stream networks. Stream slope was computed at multiple-spatial scales throughout the terrain-derived network because steep slopes can be a potential natural migration hindrance. Potential migration hindrances were then quantified across the network from (1) the positions of crossings and culverts (using information generated from the DTM alongside GIS databases) and (2) stream slope metrics. The impact of potential migration hindrances on the spatial distribution of sea trout was determined by analysing the relationship between these stream network properties and the prevalence of sea trout across Trondheim Region, as determined by electro-fishing surveys conducted by Trondheim Kommune, NINA and NIVA. Models showed that prevalence was negatively related to the number of crossings and culverts downstream of the electrofishing site. However, no effect of slope was identified, and the predictive power of models was low. The terrain derivation-based approach developed here offered high local accuracy, but was computationally intensive, and suffered from potential confounding effects, and investigation of the effect of stream network properties on sea trout prevalence was limited by the quantity and quality of available data. This study has shown that a GIS-based approach, reliant on semi-automated processing of high-resolution DTM data, and integrated with GIS data, can be used to construct a stream network showing potential migration hindrances for fish populations. Further, there is potential for applying this approach over a wider geographical area and in different freshwater applications.
Show more

Organizations and authors

Publication type

Publication format

Monograph

Audience

Professional

MINEDU's publication type classification code

D4 Published development or research report or study

Publication channel information

Journal

NINA Report

Publisher

Norwegian Institute for Nature Research

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

Self-archived

No

Other information

Fields of science

Ecology, evolutionary biology

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Publication country

Norway

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes