CardouAubinBergeronEtAl2020

Référence

Cardou, F., Aubin, I., Bergeron, A., Shipley, B. (2020) Functional markers to predict forest ecosystem properties along a rural-to-urban gradient. Journal of Vegetation Science, 31(3):416-428. (Scopus )

Résumé

Questions: With increasing focus on urban sustainability, new tools are needed to manage urban woodlands for resilience and ecosystem service provision. Functional traits can provide quantitative and testable links between urban plant communities and specific ecosystem properties (functional markers). We ask whether commonly described multivariate patterns of trait association with urbanization (trait syndromes) capture changes in ecosystem properties associated with urbanization. Given that environmental heterogeneity can generate weak or non-linear trait–ecosystem property relationships, we ask whether linear methods can yield functional markers with significant power for different ecosystem properties. Location: Montreal metropolitan area (Canada). Methods: We documented the functional composition of 43 woodlands along an urbanization gradient and measured proxies of three ecosystem properties: plant colonization, soil water infiltration and organic matter decomposition. We use redundancy analysis to identify traits associated with urbanization, and multiple linear regression and model selection to identify response and effect traits that best predict actual differences in ecosystem properties. We compare the resulting linear model with a non-linear equivalent. Results: Traits associated with urbanization (urban syndrome) were inconsistently selected as best predictors of ecosystems properties (functional markers). Although predictive power varied between ecosystem properties, all three could be significantly predicted from community-weighted traits (functional markers), with both response and effect traits contributing to the final model. When we fitted equivalent non-linear models, we found that traits had largely non-linear relationships with ecosystem properties. Conclusions: Our results demonstrate that community-weighted traits of urban woodlands can yield functional markers that capture ecosystem properties, but these are inconsistently identified by “trait syndrome” approaches. In linear combinations, such functional markers provide a testable and generalizable way to quantify ecosystem properties in urban woodlands. Capturing such properties is one important step toward management of woodlands for their continued ability to provide ecosystem services into the future. © 2020 International Association for Vegetation Science

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@ARTICLE { CardouAubinBergeronEtAl2020,
    AUTHOR = { Cardou, F. and Aubin, I. and Bergeron, A. and Shipley, B. },
    JOURNAL = { Journal of Vegetation Science },
    TITLE = { Functional markers to predict forest ecosystem properties along a rural-to-urban gradient },
    YEAR = { 2020 },
    NOTE = { cited By 0 },
    NUMBER = { 3 },
    PAGES = { 416-428 },
    VOLUME = { 31 },
    ABSTRACT = { Questions: With increasing focus on urban sustainability, new tools are needed to manage urban woodlands for resilience and ecosystem service provision. Functional traits can provide quantitative and testable links between urban plant communities and specific ecosystem properties (functional markers). We ask whether commonly described multivariate patterns of trait association with urbanization (trait syndromes) capture changes in ecosystem properties associated with urbanization. Given that environmental heterogeneity can generate weak or non-linear trait–ecosystem property relationships, we ask whether linear methods can yield functional markers with significant power for different ecosystem properties. Location: Montreal metropolitan area (Canada). Methods: We documented the functional composition of 43 woodlands along an urbanization gradient and measured proxies of three ecosystem properties: plant colonization, soil water infiltration and organic matter decomposition. We use redundancy analysis to identify traits associated with urbanization, and multiple linear regression and model selection to identify response and effect traits that best predict actual differences in ecosystem properties. We compare the resulting linear model with a non-linear equivalent. Results: Traits associated with urbanization (urban syndrome) were inconsistently selected as best predictors of ecosystems properties (functional markers). Although predictive power varied between ecosystem properties, all three could be significantly predicted from community-weighted traits (functional markers), with both response and effect traits contributing to the final model. When we fitted equivalent non-linear models, we found that traits had largely non-linear relationships with ecosystem properties. Conclusions: Our results demonstrate that community-weighted traits of urban woodlands can yield functional markers that capture ecosystem properties, but these are inconsistently identified by “trait syndrome” approaches. In linear combinations, such functional markers provide a testable and generalizable way to quantify ecosystem properties in urban woodlands. Capturing such properties is one important step toward management of woodlands for their continued ability to provide ecosystem services into the future. © 2020 International Association for Vegetation Science },
    AFFILIATION = { Département de Biologie, Université de Sherbrooke, Sherbrooke, QC, Canada; Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie, ON, Canada; Institut de Recherche en Biologie Végétale, Université de Montréal, Montréal, QC, Canada },
    AUTHOR_KEYWORDS = { colonization; compaction; connectivity; decomposition; ecosystem functioning; functional indicators; functional markers; urban forest; urban-to-rural gradient; water infiltration },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1111/jvs.12855 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082136249&doi=10.1111%2fjvs.12855&partnerID=40&md5=6ea533c541bce58c4001a861690248b9 },
}

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