What causes greater deviations from predictions of metabolic scaling theory in earlier successional forests?

Sun, Han; Wang, Xiangping; Wu, Pengcheng; Wei, Han; Xu, Kai; Liang, Penghong; Liu, Chao; Yin, Weilun; Xia, Xinli

doi:10.1016/j.foreco.2017.09.007

Cited by 11 publications

(12 citation statements)

References 42 publications

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“…However, a further analysis showed that all the L-D, S-D and R-D exponents supported the MST predictions in primary forests, while the S-D and R-D exponents deviated more from MST predictions in secondary forests. This is consistent with some studies (Enquist et al 2009;Duncanson et al 2015;Sun et al 2017a) which found that the MST predictions may be only supported in late successional forests, while forests in earlier successional stages revealed greater deviations. Note that .…”

Section: Allometries Vary With Successional Stage In Natural Forestssupporting

confidence: 93%

“…For instance, Duncanson et al (2015) demonstrated that allometries of trees in younger forests may vary quite substantially, while tree allometries in mature forests taller than 35 m were consistent with MST predictions. Likewise, Sun et al (2017a) found that H-D allometric scaling exponents conformed to MST predictions in late-successional broadleaf and Korean pine mixed forests in northeast China, while forests in earlier successional stages revealed greater deviations. These deviations from the predictions of MST may be primarily caused by biotic factors such as light competition and recruitment limitation, while climate may indirectly affect allometric exponents through these biotic factors.…”

Section: Introductionmentioning

confidence: 61%

“…To determine the effects of climate, biotic factors, and phylogeny on allometric relationships, we explained the L-D, S-D, and R-D scaling exponents with variables as follows: (1) Climate. Previous studies have shown that energy and water availability, and winter coldness can affect allometric relationships (Wang et al 2006;Lines et al 2012;Sun et al 2017a), so we selected PET (energy), MTCM (coldness), and MI (water availability) for statistical analyses. Other climate indices are similar to PET, MTCM, and MI in biological meaning and thus were not used to avoid collinearity.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, studies have proposed an explanation for why observed scaling exponents deviated from the MST predictions in forests (Rüger and Condit 2012;Duncanson et al 2015;Sun et al 2017a). These authors found that measured allometric exponents only agreed with MST predictions in late successional forests, because earlier successional forests were more affected by biotic and abiotic factors.…”

Section: Introductionmentioning

confidence: 99%

“…More tests need to be conducted to determine whether it applies to other forest biomes (e.g. subtropical and warm-temperate forests), and is therefore applicable across a broad climatic scale (Duncanson et al 2015;Sun et al 2017a).…”

Section: Introductionmentioning

confidence: 99%

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Effects of climate, biotic factors, and phylogeny on allometric relationships: testing the metabolic scaling theory in plantations and natural forests across China

2020

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Background: Metabolic scaling theory (MST) is still in debate because observed allometric exponents often deviate from MST predictions, and can change significantly depending on environment, phylogeny, and disturbance. We assembled published scaling exponents from literatures for three allometric relationships linked to biomass allocation: leaf biomass-diameter (L-D), stem biomass-diameter (S-D), and root biomass-diameter (R-D). We used data from natural forests and plantations across China to test the following hypotheses: 1) the allometric relationships of trees support the predictions of MST on a broad scale; 2) the observed deviations from MST predictions are caused by climate, biotic factors, and/or phylogeny; 3) abiotic and biotic factors influence allometric relationships in plantations and natural forests differently, and different allometric relationships (i.e. L-D, S-D, and R-D) are affected differently. We related these scaling exponents to geographic climate gradient, successional stage, stand density, leaf form and phenology, and phylogeny. We used mixed-effect models to examine the major factors affecting tree allometries. Results: In natural forests, S-D and R-D scaling exponents were consistent with MST predictions in primary forests, but were significantly lower in secondary forests. Both S-D and R-D scaling exponents in plantations had a medium value that fell between those of the secondary and primary forests, despite plantations being similar in species characteristics and age to secondary forests. The S-D and R-D exponents were significantly affected by factors that are not yet considered in MST, including winter coldness which explained 2.76%-3.24% of variations, successional stage (7.91%-8.20% of variations), density (a surrogate for competition, 5.86%-8.54% of variations), and especially phylogeny (45.86%-56.64% of variations explained). However, the L-D scaling exponents conformed to MST predictions in primary, secondary, and plantation forests, and was not strongly explained by most factors. Conclusion: MST is only applicable to primary (steady-state) forests, and climate, biotic factors and phylogeny are causes of the observed deviations of allometric relationships from MST predictions. Forest management practices in plantations have a strong influence on tree allometries. L-D allometry is more strongly controlled by biophysical constraints than S-D and R-D allometries, however, the mechanisms behind this difference still need further examinations.

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Section: Allometries Vary With Successional Stage In Natural Forestssupporting

confidence: 93%

Section: Introductionmentioning

confidence: 61%