Table 1 Review of studies that used step selection functions to model landscape effects on movement probability

Elk (Cervus elaphus)

5-hour

200

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression

No

[11]

Cougar (Puma concolor)

15-min

35

Step length equal to the mean of all movement segments recorded during the same period of time. Turning angles generated at 10° increments around the starting point.

Compositional analysis

No

[22]

Roe deer (Capreolus capreolus)

2-hour and 6-hour

10

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression

No

[46]

Elk (Cervus elaphus)

5-hour

20

Pairs of step-lengths and turning angles jointly sampled with replacement from empirical distributions.

Conditional logistic regression

No

[20]

Moose (Alces alces)

2- hour

10

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression

Yes (sensu Boyce et al. [59])

[24]

Grizzly bear (Ursus Arctos)

4-hour

20

Drawn from 2 distributions established from observations of monitored individuals considering different period of the day.

Conditional logistic regression

No

[17]

Snowshoe Hares (Lepus americanus)

10-bound segment along hare trails left on snow

2

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression

No

[28]

North Island robin (Petroica longipes)

1-day

10

Single dispersal step (obtained with several 1-day locations) was matched with a random walk of the same length.

Conditional logistic regression

No

[23]

Wolf (Canis lupus)

2-hour

25

Drawn from 2 distributions established from observations of monitored individuals at the seasonal scale.

Conditional logistic regression

No

[25]

Barred Antshrike (Thammophilus doliatus); Rufous-naped Wren (Campylorhynchus rufinucha)

15-min

20

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression

No

[47]

Moose (Alces alces)

2-hour

2

Random turning angle (circular distribution). Random step length lower than the 99% quantile of the observed step lengths.

Conditional logistic regression

No

[64]

Moose (Alces alces)

1-hour

5

Drawn from 2 distributions established from observations of monitored individuals at the seasonal scale.

Conditional logistic regression

Yes (sensu Boyce et al. [59])

[26]

Grizzly bear (Ursus arctos)

1 hour

20

Drawn from 2 distributions established from observations of monitored individuals.

Conditional logistic regression (individual modelling)

No

[27]

Lynx (Lynx canadensis)

30-min

5

Step length and turning angle data drawn from movement paths to distinguish activity bouts from resting bouts (i.e. clusters of GPS locations).

Conditional logistic regression (individual modelling)

Yes (sensu Boyce et al. [59])

[16]