2012
DOI: 10.1139/f2011-179
|View full text |Cite
|
Sign up to set email alerts
|

Three-dimensional kernel utilization distributions improve estimates of space use in aquatic animals

Abstract: Tracking data have previously been used to define animal movement patterns through two-dimensional (2D) kernel utilization distributions and separate analysis of vertical locations. Here we describe the use of three-dimensional (3D) kernel utilization distributions to estimate the volumetric space use of individuals based on tracking data and to estimate the overlap in activity space between individuals. Data from European eels (Anguilla anguilla) from Norwegian coastal waters were used to compare the informat… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

3
76
0

Year Published

2012
2012
2022
2022

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 64 publications
(79 citation statements)
references
References 14 publications
3
76
0
Order By: Relevance
“…horizontal area) data, providing areal estimates of overlap. However, in aquatic ecosystems are three-dimensional, making estimates of habitat partitioning based on areal data of limited use (Simpfendorfer et al, 2012). Differences in the degree of habitat overlap among piscivores were dependent on the type of data (e.g., depth, space, or both) used to quantify overlap.…”
Section: Discussionmentioning
confidence: 99%
“…horizontal area) data, providing areal estimates of overlap. However, in aquatic ecosystems are three-dimensional, making estimates of habitat partitioning based on areal data of limited use (Simpfendorfer et al, 2012). Differences in the degree of habitat overlap among piscivores were dependent on the type of data (e.g., depth, space, or both) used to quantify overlap.…”
Section: Discussionmentioning
confidence: 99%
“…Following Simpfendorfer et al (2012), we accounted for the uncertainty in our positional data by multiplying our smoothing factor by a value >1. To determine this multiplier, we calculated the 50 and 95% UD and multiplied the smoothing factor by values from 1 to 10.…”
Section: -D Kernel Udmentioning
confidence: 99%
“…These factors influence the behaviour of fish in such a way that using traditional 2D KUD methods can be inappropriate to evaluate inter-specific habitat overlap (e.g. Simpfendorfer et al 2012). Overall we observed minimal habitat overlap (3D) between escaped rainbow trout and native lake trout throughout the study.…”
Section: Discussionmentioning
confidence: 99%
“…Previously it was common for kernel densities to be estimated in 2 dimensions (2D, i.e. areal); however, areal estimates of species distribution may greatly overestimate habitat overlap if the species in question occupy different depths (Simpfendorfer et al 2012, Guzzo et al 2016. To this end, we calculated 3D KUDs for individual fish (for examples, see the Supplement at www.int-res.com/articles/suppl/ q009 p415_ supp.…”
Section: Kernel Density Estimatormentioning
confidence: 99%
See 1 more Smart Citation