Predicting Climate Change Impacts to the Canadian Boreal Forest
Climate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sens...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2014-03-01
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| Series: | Diversity |
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| Online Access: | http://www.mdpi.com/1424-2818/6/1/133 |
| _version_ | 1811307720113913856 |
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| author | Trisalyn A. Nelson Nicholas C. Coops Michael A. Wulder Liliana Perez Jessica Fitterer Ryan Powers Fabio Fontana |
| author_facet | Trisalyn A. Nelson Nicholas C. Coops Michael A. Wulder Liliana Perez Jessica Fitterer Ryan Powers Fabio Fontana |
| author_sort | Trisalyn A. Nelson |
| collection | DOAJ |
| description | Climate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sensing and based on vegetation productivity. Vegetation productivity indices, representing annual amounts and variability of greenness, have been shown to relate to tree and wildlife richness in Canada’s boreal. Relationships between historical satellite-derived productivity and climate data were applied to modelled scenarios of future climate to predict and map potential future vegetation productivity for 592 regions across Canada. Results indicated that the pattern of vegetation productivity will become more homogenous, particularly west of Hudson Bay. We expect climate change to impact biodiversity along north/south gradients and by 2080 vegetation distributions will be dominated by processes of seasonality in the north and a combination of cumulative greenness and minimum cover in the south. The Hudson Plains, which host the world’s largest and most contiguous wetland, are predicted to experience less seasonality and more greenness. The spatial distribution of predicted trends in vegetation productivity was emphasized over absolute values, in order to support regional biodiversity assessments and conservation planning. |
| first_indexed | 2024-04-13T09:10:25Z |
| format | Article |
| id | doaj.art-d365a3935161431f8d36ccfb57195276 |
| institution | Directory Open Access Journal |
| issn | 1424-2818 |
| language | English |
| last_indexed | 2024-04-13T09:10:25Z |
| publishDate | 2014-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diversity |
| spelling | doaj.art-d365a3935161431f8d36ccfb571952762022-12-22T02:52:54ZengMDPI AGDiversity1424-28182014-03-016113315710.3390/d6010133d6010133Predicting Climate Change Impacts to the Canadian Boreal ForestTrisalyn A. Nelson0Nicholas C. Coops1Michael A. Wulder2Liliana Perez3Jessica Fitterer4Ryan Powers5Fabio Fontana6Spatial Pattern Analysis & Research (SPAR) Lab, Department of Geography, University of Victoria, Victoria V8W 3R4, BC, CanadaDepartment of Forest Resources Management, University of British Columbia, Vancouver V6T 1Z4, BC, CanadaPacfic Forestry Centre, Canadian Forest Service, Natural Resources Canada, Victoria V8Z 1M5, BC, CanadaDepartment of Geography, University of Montreal, Montreal H2V 2B8, QC, CanadaSpatial Pattern Analysis & Research (SPAR) Lab, Department of Geography, University of Victoria, Victoria V8W 3R4, BC, CanadaDepartment of Forest Resources Management, University of British Columbia, Vancouver V6T 1Z4, BC, CanadaFederal Office of Meteorology and Climatology MeteoSwiss, Swiss GCOS Office, Zurich CH-8004, SwitzerlandClimate change is expected to alter temperature, precipitation, and seasonality with potentially acute impacts on Canada’s boreal. In this research we predicted future spatial distributions of biodiversity in Canada’s boreal for 2020, 2050, and 2080 using indirect indicators derived from remote sensing and based on vegetation productivity. Vegetation productivity indices, representing annual amounts and variability of greenness, have been shown to relate to tree and wildlife richness in Canada’s boreal. Relationships between historical satellite-derived productivity and climate data were applied to modelled scenarios of future climate to predict and map potential future vegetation productivity for 592 regions across Canada. Results indicated that the pattern of vegetation productivity will become more homogenous, particularly west of Hudson Bay. We expect climate change to impact biodiversity along north/south gradients and by 2080 vegetation distributions will be dominated by processes of seasonality in the north and a combination of cumulative greenness and minimum cover in the south. The Hudson Plains, which host the world’s largest and most contiguous wetland, are predicted to experience less seasonality and more greenness. The spatial distribution of predicted trends in vegetation productivity was emphasized over absolute values, in order to support regional biodiversity assessments and conservation planning.http://www.mdpi.com/1424-2818/6/1/133climate changebiodiversity, borealspace-time analysisfPARDHI |
| spellingShingle | Trisalyn A. Nelson Nicholas C. Coops Michael A. Wulder Liliana Perez Jessica Fitterer Ryan Powers Fabio Fontana Predicting Climate Change Impacts to the Canadian Boreal Forest Diversity climate change biodiversity, boreal space-time analysis fPAR DHI |
| title | Predicting Climate Change Impacts to the Canadian Boreal Forest |
| title_full | Predicting Climate Change Impacts to the Canadian Boreal Forest |
| title_fullStr | Predicting Climate Change Impacts to the Canadian Boreal Forest |
| title_full_unstemmed | Predicting Climate Change Impacts to the Canadian Boreal Forest |
| title_short | Predicting Climate Change Impacts to the Canadian Boreal Forest |
| title_sort | predicting climate change impacts to the canadian boreal forest |
| topic | climate change biodiversity, boreal space-time analysis fPAR DHI |
| url | http://www.mdpi.com/1424-2818/6/1/133 |
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