TY - JOUR
T1 - EcoAnthromes of Alberta
T2 - An example of disturbance-informed ecological regionalization using remote sensing
AU - Kearney, S. P.
AU - Coops, N. C.
AU - Stenhouse, G. B.
AU - Nelson, T. A.
N1 - Funding Information:
This research was supported by the Grizzly-PAW project ( NSERC File: CRDPJ 486175–15 , Grantee: N.C. Coops, FRM, UBC), in collaboration with fRI Research and FRIAA, Alberta Newsprint Company, Canfor, Cenovus, Repsol, Seven Generations Energy, Shell Canada, TransCanada Pipelines, Teck Resources, West Fraser, Westmoreland Coal, and Weyerhauser. More information can be found at http://paw.forestry.ubc.ca/ .
Publisher Copyright:
© 2019 Elsevier Ltd
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/3/15
Y1 - 2019/3/15
N2 - Humans influence ecosystems on magnitudes that often exceed that of natural forces such as climate and geology; however, frameworks rarely include anthropogenic disturbance when delineating unique ecological regions. A critical step toward understanding, managing and monitoring human-altered ecosystems is to incorporate disturbance into ecological regionalizations. Furthermore, quantitative regionalization approaches are desirable to provide cost-effective, repeatable and statistically sound stratification for environmental monitoring. We applied a two-stage multivariate clustering technique to identify ‘EcoAnthromes’ across a large area – the province of Alberta, Canada – at 30 m spatial resolution, and using primarily remotely sensed inputs. The EcoAnthrome clusters represent regions with unique ecological characteristics based on a combination of natural ecological potential (e.g., climatic and edaphic factors) and disturbance, both natural and anthropogenic. Compared to existing expert-derived Natural Subregions in Alberta, the model-based EcoAnthromes showed greater class separation and explained more variance for an assortment of variables related to land cover, disturbance and species intactness. The EcoAnthromes successfully separated important ecological regions that are defined by complex assemblages of topography, climate and disturbance, such as gravel-bed river valleys, boreal forests, grasslands, post-fire recovery areas and highly disturbed agricultural, industrial and urban landscapes. In addition to presenting a flexible method for EcoAnthrome regionalization, we group and describe the EcoAnthromes created for Alberta and discuss how they can complement expert-derived regionalizations to aid in environmental management efforts, such as species recovery planning and monitoring for threatened species.
AB - Humans influence ecosystems on magnitudes that often exceed that of natural forces such as climate and geology; however, frameworks rarely include anthropogenic disturbance when delineating unique ecological regions. A critical step toward understanding, managing and monitoring human-altered ecosystems is to incorporate disturbance into ecological regionalizations. Furthermore, quantitative regionalization approaches are desirable to provide cost-effective, repeatable and statistically sound stratification for environmental monitoring. We applied a two-stage multivariate clustering technique to identify ‘EcoAnthromes’ across a large area – the province of Alberta, Canada – at 30 m spatial resolution, and using primarily remotely sensed inputs. The EcoAnthrome clusters represent regions with unique ecological characteristics based on a combination of natural ecological potential (e.g., climatic and edaphic factors) and disturbance, both natural and anthropogenic. Compared to existing expert-derived Natural Subregions in Alberta, the model-based EcoAnthromes showed greater class separation and explained more variance for an assortment of variables related to land cover, disturbance and species intactness. The EcoAnthromes successfully separated important ecological regions that are defined by complex assemblages of topography, climate and disturbance, such as gravel-bed river valleys, boreal forests, grasslands, post-fire recovery areas and highly disturbed agricultural, industrial and urban landscapes. In addition to presenting a flexible method for EcoAnthrome regionalization, we group and describe the EcoAnthromes created for Alberta and discuss how they can complement expert-derived regionalizations to aid in environmental management efforts, such as species recovery planning and monitoring for threatened species.
KW - Anthropogenic disturbance
KW - EcoAnthrome
KW - Ecological classification
KW - Ecological regionalization
KW - Habitat
KW - Multivariate clustering
UR - http://www.scopus.com/inward/record.url?scp=85060013795&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060013795&partnerID=8YFLogxK
U2 - 10.1016/j.jenvman.2018.12.076
DO - 10.1016/j.jenvman.2018.12.076
M3 - Article
C2 - 30634122
AN - SCOPUS:85060013795
SN - 0301-4797
VL - 234
SP - 297
EP - 310
JO - Journal of Environmental Management
JF - Journal of Environmental Management
ER -