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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ftjalces:oai:ojs.pkp.sfu.ca:article/41 2024-06-16T07:33:08+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: A Journal Devoted to the Biology and Management of Moose; 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 Peer-reviewed Article 2008 ftjalces 2024-05-22T03:01:08Z 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) |
institution |
Open Polar |
collection |
Alces (A Journal Devoted to the Biology and Management of Moose) |
op_collection_id |
ftjalces |
language |
English |
topic |
Alces alces British Columbia GIS moose stratified random block survey vegetation attributes |
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 |
topic_facet |
Alces alces British Columbia GIS moose stratified random block survey vegetation attributes |
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 |
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. |
title |
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_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_sort |
using gis to modify a stratified random block survey design for moose |
publisher |
Lakehead University |
publishDate |
2008 |
url |
http://alcesjournal.org/index.php/alces/article/view/41 |
genre |
Alces alces |
genre_facet |
Alces alces |
op_source |
Alces: A Journal Devoted to the Biology and Management of Moose; Vol. 44 (2008); 111-116 2293-6629 0835-5851 |
op_relation |
http://alcesjournal.org/index.php/alces/article/view/41/40 http://alcesjournal.org/index.php/alces/article/view/41 |
op_rights |
Copyright (c) 2021 Alces: A Journal Devoted to the Biology and Management of Moose |
_version_ |
1802012330325704704 |