2020
DOI: 10.1111/geb.13060
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Spatial variation in climate modifies effects of functional diversity on biomass dynamics in natural forests across Canada

Abstract: Aim Forest net biomass change (ΔAGB; the difference between biomass gain from growth and loss through mortality) determines how forests contribute to the global carbon cycle. Understanding how plant diversity affects ΔAGB in diverse abiotic conditions is crucial in the face of anthropogenic environmental change. Recent studies have advanced our understanding of the effects of plant diversity on growth dependent on the abiotic context, either supporting or rejecting the stress gradient hypothesis. However, we k… Show more

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Cited by 28 publications
(25 citation statements)
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References 55 publications
(132 reference statements)
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“…Plant maximum height was derived from our dataset for each species. We computed the functional dispersion (F dis ), which accounts for the distance of species to the centre of multi-trait functional space (Laliberté and Legendre, 2010;Mouchet et al, 2010) and has been often used as a relevant indicator of functional diversity in many BEF studies (e.g., Aponte et al, 2020;Hisano and Chen, 2020). As functional composition metrics, we computed the plot-level CWM of wood density (CWM WD ) and maximum tree height (CWM MAXH ).…”
Section: Diversity-related Biotic Attributesmentioning
confidence: 99%
“…Plant maximum height was derived from our dataset for each species. We computed the functional dispersion (F dis ), which accounts for the distance of species to the centre of multi-trait functional space (Laliberté and Legendre, 2010;Mouchet et al, 2010) and has been often used as a relevant indicator of functional diversity in many BEF studies (e.g., Aponte et al, 2020;Hisano and Chen, 2020). As functional composition metrics, we computed the plot-level CWM of wood density (CWM WD ) and maximum tree height (CWM MAXH ).…”
Section: Diversity-related Biotic Attributesmentioning
confidence: 99%
“…Plant–plant interactions can become more positive in water‐ or temperature‐limiting environments because the strength of abiotic facilitation is expected to increase under environmental stress, that is, the stress gradient hypothesis (Maestre et al., 2009; Wright et al., 2017). However, the positive relationship between tree diversity and forest productivity is stronger in resource‐rich than resource‐poor environments (Hisano & Chen, 2020). Moreover, the effects of plant diversity and their temporal trends between forests and grasslands are hypothesized to be different primarily due to variable species or individual recruitment rates (Forrester & Bauhus, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Communities characterized by a high CWM of WD reflect the coincidental dominance of slow‐growing species for maintaining ecosystem productivity. In such cases, the interactive processes should be weak in mixtures that are dominated by slow‐growing plants, which consequently cannot enhance the effects of mixtures on productivity (Hisano & Chen, 2020). However, the significant negative effect of the CWM of wood density in three‐species mixtures using the site‐specific dataset suggests that the responses of plant wood traits to environmental conditions might modify the plant functional diversity effects on productivity.…”
Section: Discussionmentioning
confidence: 99%
“…Our results also indicate that climate mediates tree mixture effects on productivity, and the relationships between the diversity of economics traits and tree mixture effects on productivity increase with higher precipitation (Figure ). When water availability increases, the competitive interactions involving light or nutrients will become more intense; thus, the complementarity effect will be enhanced to improve the uptake or use efficiency of light and/or nutrients (Ammer, 2019; Hisano & Chen, 2020; Jactel et al., 2018). However, some other studies have demonstrated the unimodal diversity–productivity relationship (the so‐called ‘hump‐or bell‐shaped’ curve) across climatic gradients (Fei et al., 2018; Grime, 1973; Loreau et al., 2001).…”
Section: Discussionmentioning
confidence: 99%