USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE

We modified the standard, stratified random block design used typically in aerial surveys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based upon veget...

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Main Authors: Heard, Douglas C., Walker, Andrew B D, Ayotte, Jeremy B, Watts, Glen S
Format: Article in Journal/Newspaper
Language:English
Published: Lakehead University 2008
Subjects:
Online Access:http://alcesjournal.org/index.php/alces/article/view/41
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author Heard, Douglas C.
Walker, Andrew B D
Ayotte, Jeremy B
Watts, Glen S
author_facet Heard, Douglas C.
Walker, Andrew B D
Ayotte, Jeremy B
Watts, Glen S
author_sort Heard, Douglas C.
collection Alces (A Journal Devoted to the Biology and Management of Moose)
description We modified the standard, stratified random block design used typically in aerial surveys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based upon vegetation attributes that were predicted to have either high or low moose density from previous research. We assumed that polygons of early seral forest stands (<40 yr), shrubs, and meadows would have high moose density relative to other vegetation attributes. Vegetation polygons were often <1 km2, consequently, single grid cells usually included >1 high and low density polygons. Adjacent cells were amalgamated to produce sample units with >4 km2 of high density stratum area. Real-time navigation was used and the flight track was recorded over a map of sample units, strata boundaries, and topographic features to accurately identify polygon boundaries and assign each sighted moose to the appropriate strata. We concluded that our approach was efficient and effective in fine-grained environments where the relative selection by moose for vegetation patches is well understood, and those patches are mapped in digital databases.
format Article in Journal/Newspaper
genre Alces alces
genre_facet Alces alces
id ftjalces:oai:ojs.pkp.sfu.ca:article/41
institution Open Polar
language English
op_collection_id ftjalces
op_relation http://alcesjournal.org/index.php/alces/article/view/41/40
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op_rights Copyright (c) 2021 Alces: A Journal Devoted to the Biology and Management of Moose
op_source Alces; Vol. 44 (2008); 111-116
2293-6629
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publishDate 2008
publisher Lakehead University
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spelling ftjalces:oai:ojs.pkp.sfu.ca:article/41 2025-04-20T14:19:05+00:00 USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE Heard, Douglas C. Walker, Andrew B D Ayotte, Jeremy B Watts, Glen S 2008-01-01 application/pdf http://alcesjournal.org/index.php/alces/article/view/41 eng eng Lakehead University http://alcesjournal.org/index.php/alces/article/view/41/40 http://alcesjournal.org/index.php/alces/article/view/41 Copyright (c) 2021 Alces: A Journal Devoted to the Biology and Management of Moose Alces; Vol. 44 (2008); 111-116 2293-6629 0835-5851 Alces alces British Columbia GIS moose stratified random block survey vegetation attributes info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2008 ftjalces 2025-03-25T04:06:23Z We modified the standard, stratified random block design used typically in aerial surveys of moose (Alces alces). We laid a grid of approximately 9 km2 cells over our study area, and GIS was then used to allocate polygons into one of 2 strata within each grid cell. The 2 strata were based upon vegetation attributes that were predicted to have either high or low moose density from previous research. We assumed that polygons of early seral forest stands (<40 yr), shrubs, and meadows would have high moose density relative to other vegetation attributes. Vegetation polygons were often <1 km2, consequently, single grid cells usually included >1 high and low density polygons. Adjacent cells were amalgamated to produce sample units with >4 km2 of high density stratum area. Real-time navigation was used and the flight track was recorded over a map of sample units, strata boundaries, and topographic features to accurately identify polygon boundaries and assign each sighted moose to the appropriate strata. We concluded that our approach was efficient and effective in fine-grained environments where the relative selection by moose for vegetation patches is well understood, and those patches are mapped in digital databases. Article in Journal/Newspaper Alces alces Alces (A Journal Devoted to the Biology and Management of Moose)
spellingShingle Alces alces
British Columbia
GIS
moose
stratified random block survey
vegetation attributes
Heard, Douglas C.
Walker, Andrew B D
Ayotte, Jeremy B
Watts, Glen S
USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title_full USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title_fullStr USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title_full_unstemmed USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title_short USING GIS TO MODIFY A STRATIFIED RANDOM BLOCK SURVEY DESIGN FOR MOOSE
title_sort using gis to modify a stratified random block survey design for moose
topic Alces alces
British Columbia
GIS
moose
stratified random block survey
vegetation attributes
topic_facet Alces alces
British Columbia
GIS
moose
stratified random block survey
vegetation attributes
url http://alcesjournal.org/index.php/alces/article/view/41