GaudreauPerezHarati2018

Référence

Gaudreau, J., Perez, L., Harati, S. (2018) Towards modelling future trends of Quebec’s boreal birds’ species distribution under climate change. Canadian Historical Review, 7(9). (Scopus )

Résumé

Adaptation to climate change requires prediction of its impacts, especially on ecosystems. In this work we simulated the change in bird species richness in the boreal forest of Quebec, Canada, under climate change scenarios. To do so, we first analyzed which geographical and bioclimatic variables were the strongest predictors for the spatial distribution of the current resident bird species. Based on canonical redundancy analysis and analysis of variance, we found that annual temperature range, average temperature of the cold season, seasonality of precipitation, precipitation in the wettest season, elevation, and local percentage of wet area had the strongest influence on the species’ distributions. We used these variables with Random Forests, Multivariate Adaptive Regression Splines and Maximum Entropy models to explain spatial variations in species abundance. Future species distributions were calculated by replacing present climatic variables with projections under different climate change pathways. Subsequently, maps of species richness change were produced. The results showed a northward expansion of areas of highest species richness towards the center of the province. Species are also likely to appear near James Bay and Ungava Bay, where rapid climate change is expected. © 2018 by the authors.

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@ARTICLE { GaudreauPerezHarati2018,
    AUTHOR = { Gaudreau, J. and Perez, L. and Harati, S. },
    TITLE = { Towards modelling future trends of Quebec’s boreal birds’ species distribution under climate change },
    JOURNAL = { Canadian Historical Review },
    YEAR = { 2018 },
    VOLUME = { 7 },
    NUMBER = { 9 },
    NOTE = { cited By 0 },
    ABSTRACT = { Adaptation to climate change requires prediction of its impacts, especially on ecosystems. In this work we simulated the change in bird species richness in the boreal forest of Quebec, Canada, under climate change scenarios. To do so, we first analyzed which geographical and bioclimatic variables were the strongest predictors for the spatial distribution of the current resident bird species. Based on canonical redundancy analysis and analysis of variance, we found that annual temperature range, average temperature of the cold season, seasonality of precipitation, precipitation in the wettest season, elevation, and local percentage of wet area had the strongest influence on the species’ distributions. We used these variables with Random Forests, Multivariate Adaptive Regression Splines and Maximum Entropy models to explain spatial variations in species abundance. Future species distributions were calculated by replacing present climatic variables with projections under different climate change pathways. Subsequently, maps of species richness change were produced. The results showed a northward expansion of areas of highest species richness towards the center of the province. Species are also likely to appear near James Bay and Ungava Bay, where rapid climate change is expected. © 2018 by the authors. },
    AFFILIATION = { Laboratory of Environmental Geosimulation (LEDGE), Department of Geography, University of Montreal, Chemin de la Côte-Sainte-Catherine, Pavillon 520, Montreal, QC H2V 2B8, Canada },
    ART_NUMBER = { 335 },
    AUTHOR_KEYWORDS = { Bioclimatic modelling; Biogeography; Boreal Quebec; Climate change; Ecological change; Random forest (RF); Redundancy analysis (RDA); Species richness },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.3390/ijgi7090335 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053281631&doi=10.3390%2fijgi7090335&partnerID=40&md5=11b42a4ba1692e54eeb89d00d25dda0c },
}

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