Positive species richness effect on AGB manifested through niche
complementarity
Recent studies have provided evidence for the need to explore beyond
species richness, how stand biomass and carbon relates to functional
trait and structure-based diversity (Conti & Díaz, 2013; Dimobe, Kuyah,
Dabré, Ouédraogo, & Thiombiano, 2019; Finegan et al., 2015; Hao, Zhang,
Zhao, & von Gadow, 2018; Lin et al., 2016; Prado-junior et al., 2016;
Wang et al., 2011; Zhang & Chen, 2015). Others researchers also
documented the importance of phylogenetic diversity (Lasky et al., 2014;
Satdichanh et al., 2019; Wasof et al., 2018). In this study, we compared
the relative importance (and mediation) of functional trait, structure
and dominance metric in explaining species richness effects on biomass
stock. Interestingly, none of the single-trait functional diversity
(FDvar) and dominance (CWM) metrics explained AGB variation in our
stands. Contrary to some previous studies (Conti & Díaz, 2013; Finegan
et al., 2015; Fotis et al., 2018), our study showed that FDvar and CWM
of wood density and plant maximum height in these mixed species stands
did not influence AGB. Lin et al. (2016) showed that biomass carbon
responds most strongly to CWM values of wood density and maximum tree
height in subtropical evergreen broad-leaved forest in China. Similarly,
Wasof et al. (2018) showed that biomass of the forest understorey was
mainly related to CWM of plant traits (leaf area and plant height) in
temperate deciduous forests in Northern France. Some of our previous
studies also showed that CWM of traits correlate strongly with biomass
and carbon stock (S. Mensah, du Toit, et al., 2018; S. Mensah, Veldtman,
Assogbadjo, et al., 2016; Sylvanus Mensah, Salako, Glèlè Kakaï, &
Sinsin, 2020). Although not anticipated, the conflictual result is not
surprising and might be due the complexity of these stands ecosystem
structures, perhaps because of the low functional trait values (low
level of functional diversity) of the dominant species.
Nevertheless, our analyses showed that among the multi-trait functional
diversity indices, functional evenness had a significant and positive
relationship with biomass, partly corroborating reports of positive
relationship between multi-trait functional diversity metrics and AGB in
forest stands (Dimobe et al., 2019; Hao et al., 2018; S. Mensah,
Veldtman, Assogbadjo, et al., 2016; Rawat, Arunachalam, Arunachalam,
Alatalo, & Pandey, 2019). Our finding is also in line with the general
expectation that evenness should positively correlate with biomass
production (Kirwan et al., 2007; Nijs & Roy, 2000; Wilsey & Potvin,
2000). Functional evenness reflects the evenness of species contribution
to AGB (in this case) within the stand (Mason et al., 2005). As such,
our result suggests that there is homogeneity in the distribution of the
relative density (i.e., lower variance in the abundance of different
species) across the multivariate trait space, reducing interspecific
competition (Tilman, 1982). Because high values of functional evenness
indicate effective resource utilization and development of productive
communities (Kelemen et al., 2017) through niche complementarity and
facilitative effects (Polley, Wilsey, & Derner, 2003; Polley, Wilsey,
& Tischler, 2007), the positive functional evenness and AGB
relationship (Figure 2) as well as the significant mediation role of
functional evenness (Figure 4), as observed in this study are supportive
of the niche complementarity, as a mechanism driving positive species
richness effect on AGB in our mixed species stands.
Furthermore, the positive effects of structural diversity metrics on AGB
stress the importance of niche complementarity hypothesis, as the main
mechanism operating in these stands. Particularly, we found that CV DBH
and CV Npb were the most important predictors of AGB, after functional
evenness. These results indicate that structural diversity promotes AGB,
as also pointed out in previous studies (Wang et al., 2011; Yan, Zhang,
Wang, Zhao, & Gadow, 2015). The structural diversity metrics as
computed here (i.e. CV DBH, CV Ht and CV Npb) reflect the amount of both
intra and interspecific vertical and horizontal tree size and crown
variation within the plot, (Seidel et al., 2019; Wang et al., 2011), and
thus are somewhat indicative of resources capture and use by species
(Yachi & Loreau, 2007). For example, greater intra and interspecific
vertical and horizontal tree size and crown variations would translate
into forest vertical stratification and crown complementarity, which
allow for greater light infiltration and promote complementary use of
light by trees in the subcanopy, canopy and above canopy layer, leading
to higher performance at stand level, as previously shown in
multi-storey Afromontane natural forest in South Africa (S. Mensah, du
Toit, et al., 2018). We thus argue that the positive effects of both CV
DBH and CV Npb on AGB result from resource-use efficiency and
complementarity due to high structural (tree size and crown)
differentiation, supporting facilitation and niche differentiation or
complementarity, as also shown in spruce-dominated forest stands in
Canada (Wang et al., 2011).