Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state

Pumas as a case study

Katherine A. Zeller, Kevin McGarigal, Paul Beier, Samuel A. Cushman, T. Winston Vickers, Walter M. Boyce

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.

Original languageEnglish (US)
Pages (from-to)541-557
Number of pages17
JournalLandscape Ecology
Volume29
Issue number3
DOIs
StatePublished - Mar 2014

Fingerprint

resource use
habitat
resource selection
animal
resources
connectivity
logistics
land cover
GPS
regression
modeling
performance
parameter
effect
analysis

Keywords

  • Conditional logistic regression
  • Connectivity
  • Cost-surface
  • Puma concolor
  • Resistance surface
  • Resource selection function

ASJC Scopus subject areas

  • Nature and Landscape Conservation
  • Ecology
  • Geography, Planning and Development

Cite this

Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state : Pumas as a case study. / Zeller, Katherine A.; McGarigal, Kevin; Beier, Paul; Cushman, Samuel A.; Vickers, T. Winston; Boyce, Walter M.

In: Landscape Ecology, Vol. 29, No. 3, 03.2014, p. 541-557.

Research output: Contribution to journalArticle

Zeller, Katherine A. ; McGarigal, Kevin ; Beier, Paul ; Cushman, Samuel A. ; Vickers, T. Winston ; Boyce, Walter M. / Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state : Pumas as a case study. In: Landscape Ecology. 2014 ; Vol. 29, No. 3. pp. 541-557.
@article{4d65aa3b6e454135b5115764feeeba4d,
title = "Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state: Pumas as a case study",
abstract = "Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.",
keywords = "Conditional logistic regression, Connectivity, Cost-surface, Puma concolor, Resistance surface, Resource selection function",
author = "Zeller, {Katherine A.} and Kevin McGarigal and Paul Beier and Cushman, {Samuel A.} and Vickers, {T. Winston} and Boyce, {Walter M.}",
year = "2014",
month = "3",
doi = "10.1007/s10980-014-9991-4",
language = "English (US)",
volume = "29",
pages = "541--557",
journal = "Landscape Ecology",
issn = "0921-2973",
publisher = "Springer Netherlands",
number = "3",

}

TY - JOUR

T1 - Sensitivity of landscape resistance estimates based on point selection functions to scale and behavioral state

T2 - Pumas as a case study

AU - Zeller, Katherine A.

AU - McGarigal, Kevin

AU - Beier, Paul

AU - Cushman, Samuel A.

AU - Vickers, T. Winston

AU - Boyce, Walter M.

PY - 2014/3

Y1 - 2014/3

N2 - Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.

AB - Estimating landscape resistance to animal movement is the foundation for connectivity modeling, and resource selection functions based on point data are commonly used to empirically estimate resistance. In this study, we used GPS data points acquired at 5-min intervals from radiocollared pumas in southern California to model context-dependent point selection functions. We used mixed-effects conditional logistic regression models that incorporate a paired used/available design to examine the sensitivity of point selection functions to the scale of available habitat and to the behavioral state of individual animals. We compared parameter estimates, model performance, and resistance estimates across 37 scales of available habitat, from 250 to 10,000 m, and two behavioral states, resource use and movement. Point selection functions and resistance estimates were sensitive to the chosen scale of the analysis. Multiple characteristic scales were found across our predictor variables, indicating that pumas in the study area are responding at different scales to different landscape features and that multi-scale models may be more appropriate. Additionally, point selection functions and resistance estimates were sensitive to behavioral state; specifically, pumas engaged in resource use behavior had an opposite selection response to some land cover types than pumas engaged in movement behavior. We recommend examining a continuum of scales and behavioral states when using point selection functions to estimate resistance.

KW - Conditional logistic regression

KW - Connectivity

KW - Cost-surface

KW - Puma concolor

KW - Resistance surface

KW - Resource selection function

UR - http://www.scopus.com/inward/record.url?scp=84897633759&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897633759&partnerID=8YFLogxK

U2 - 10.1007/s10980-014-9991-4

DO - 10.1007/s10980-014-9991-4

M3 - Article

VL - 29

SP - 541

EP - 557

JO - Landscape Ecology

JF - Landscape Ecology

SN - 0921-2973

IS - 3

ER -