Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing
The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ...
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2024
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Online Access: | https://digitalcommons.mtu.edu/michigantech-p2/684 https://doi.org/10.3390/rs16071175 |
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ftmichigantuniv:oai:digitalcommons.mtu.edu:michigantech-p2-1684 2024-06-09T07:43:21+00:00 Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing Merchant, Michael Allan Battaglia, Michael J. French, Nancy Smith, Kevin Singer, Howard V. Armstrong, Llwellyn Harriman, Vanessa B. Slattery, Stuart 2024-04-01T07:00:00Z https://digitalcommons.mtu.edu/michigantech-p2/684 https://doi.org/10.3390/rs16071175 unknown Digital Commons @ Michigan Tech https://digitalcommons.mtu.edu/michigantech-p2/684 doi:10.3390/rs16071175 https://doi.org/10.3390/rs16071175 Michigan Tech Publications, Part 2 arctic boreal ducks Google Earth Engine NASA AboVE remote sensing wetlands text 2024 ftmichigantuniv https://doi.org/10.3390/rs16071175 2024-05-14T23:39:13Z The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ commonly use static (time invariant) habitat covariates to inform predictions, such as wetland type and extent maps. For the first time in this region, we developed species abundance models using high-resolution, time-varying wetland inundation data produced using satellite remote sensing methods. This data captured metrics of surface water extent and inundated vegetation in the Peace Athabasca Delta, Canada, which is within the NASA Arctic Boreal Vulnerability Experiment core domain. We used generalized additive mixed models to demonstrate the improved predictive value of this novel data set over time-invariant data. Our findings highlight both the potential complementarity and efficacy of dynamic wetland inundation information for improving estimation of duck abundance and distribution at high latitudes. Further, these data can be an asset to spatial targeting of biodiversity conservation efforts and developing model-based metrics of their success under rapidly changing climatic conditions. Text Arctic Michigan Technological University: Digital Commons @ Michigan Tech Arctic Canada Peace-Athabasca Delta ENVELOPE(-111.502,-111.502,58.667,58.667) Remote Sensing 16 7 1175 |
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Open Polar |
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Michigan Technological University: Digital Commons @ Michigan Tech |
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ftmichigantuniv |
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unknown |
topic |
arctic boreal ducks Google Earth Engine NASA AboVE remote sensing wetlands |
spellingShingle |
arctic boreal ducks Google Earth Engine NASA AboVE remote sensing wetlands Merchant, Michael Allan Battaglia, Michael J. French, Nancy Smith, Kevin Singer, Howard V. Armstrong, Llwellyn Harriman, Vanessa B. Slattery, Stuart Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
topic_facet |
arctic boreal ducks Google Earth Engine NASA AboVE remote sensing wetlands |
description |
The Arctic-Boreal zone (ABZ) covers over 26 million km2 and is home to numerous duck species; however, understanding the spatiotemporal distribution of their populations across this vast landscape is challenging, in part due to extent and data scarcity. Species abundance models for ducks in the ABZ commonly use static (time invariant) habitat covariates to inform predictions, such as wetland type and extent maps. For the first time in this region, we developed species abundance models using high-resolution, time-varying wetland inundation data produced using satellite remote sensing methods. This data captured metrics of surface water extent and inundated vegetation in the Peace Athabasca Delta, Canada, which is within the NASA Arctic Boreal Vulnerability Experiment core domain. We used generalized additive mixed models to demonstrate the improved predictive value of this novel data set over time-invariant data. Our findings highlight both the potential complementarity and efficacy of dynamic wetland inundation information for improving estimation of duck abundance and distribution at high latitudes. Further, these data can be an asset to spatial targeting of biodiversity conservation efforts and developing model-based metrics of their success under rapidly changing climatic conditions. |
format |
Text |
author |
Merchant, Michael Allan Battaglia, Michael J. French, Nancy Smith, Kevin Singer, Howard V. Armstrong, Llwellyn Harriman, Vanessa B. Slattery, Stuart |
author_facet |
Merchant, Michael Allan Battaglia, Michael J. French, Nancy Smith, Kevin Singer, Howard V. Armstrong, Llwellyn Harriman, Vanessa B. Slattery, Stuart |
author_sort |
Merchant, Michael Allan |
title |
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
title_short |
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
title_full |
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
title_fullStr |
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
title_full_unstemmed |
Species Abundance Modelling of Arctic-Boreal Zone Ducks Informed by Satellite Remote Sensing |
title_sort |
species abundance modelling of arctic-boreal zone ducks informed by satellite remote sensing |
publisher |
Digital Commons @ Michigan Tech |
publishDate |
2024 |
url |
https://digitalcommons.mtu.edu/michigantech-p2/684 https://doi.org/10.3390/rs16071175 |
long_lat |
ENVELOPE(-111.502,-111.502,58.667,58.667) |
geographic |
Arctic Canada Peace-Athabasca Delta |
geographic_facet |
Arctic Canada Peace-Athabasca Delta |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Michigan Tech Publications, Part 2 |
op_relation |
https://digitalcommons.mtu.edu/michigantech-p2/684 doi:10.3390/rs16071175 https://doi.org/10.3390/rs16071175 |
op_doi |
https://doi.org/10.3390/rs16071175 |
container_title |
Remote Sensing |
container_volume |
16 |
container_issue |
7 |
container_start_page |
1175 |
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1801372121202425856 |