Ecological uniqueness of species assemblages and their determinants in forest communities

Abstract

Aim Beta diversity can be partitioned into the contributions of individual sampling units to overall beta diversity, which are comparative indicators of the ecological uniqueness of species assemblages in the sampling units. Yet, what determines ecological uniqueness has rarely been examined. Here, we investigated the determinants of ecological uniqueness in species assemblages in forest communities. Location China. Methods We used tree census data, combined with spatially explicit environmental variables collected from forest dynamics plots across tropical, subtropical and temperate forests in China. We computed beta diversity as the total variation of the community data, and a site‐based approach was used to determine whether ecological uniqueness is related to local environmental conditions and/or community characteristics. Results Ecological uniqueness was explained by both local environment and community characteristics, but their relative importance varied across the four forest types. We provide direct evidence that the relationship between ecological uniqueness and species richness (EUSRR) is related to the percentage of rare species in the community. Local environmental factors affecting ecological uniqueness and beta diversity were inconsistent, indicating that focusing simultaneously on beta diversity and ecological uniqueness with regard to local environmental conditions is likely to be the appropriate approach to study forest community assembly. Main conclusions Although the EUSRR was negative in some cases, indicating high species richness, this does not necessarily imply high ecological uniqueness. Thus, for biological conservation, species‐rich sites and unique low‐richness sites should be valued more. The higher degree of ecological uniqueness indicates unique species compositions, which provides insight into finding such quadrats and taking measures for protection, restoration or management. We propose that focusing simultaneously on the beta diversity, species richness and ecological uniqueness of individual quadrats is likely to be a valuable approach for biodiversity conservation programmes.

Evaluating ecological uniqueness over broad spatial extents using species distribution modelling

“…Both these procedures should reduce the richness deviation we observed, and it would be interesting to verify if this can also be the case with LCBD values. Overall, our distribution results have implications for conservation, as they confirm that species richness and ecological uniqueness measured from LCBD values may conflict and highlight different potential hotspots (Dubois, Proulx, and Pellerin 2020;Yao et al 2021), thus reinstating the need to protect both with complementary strategies.…”

“…da Silva, Hernández, and Heino (2018) suggested that the proportion of rare and common species in the communities seems to determine if the relationship will be negative, non-significant, or positive. Yao et al (2021) supported this idea and showed that the relationship was negative when the proportion of rare species was lower and positive when the relationship was high. Our results further show that sites associated with a positive relationship within a curvilinear one tended to have a higher rare species proportion (Fig.…”

“…Both the original study and many of the later empirical ones have shown a negative relationship between LCBD scores and species richness (Legendre and De Cáceres 2013;da Silva and Hernández 2014;Heino and Grönroos 2017), although other studies observed both negative and positive relationships at different sites (Kong et al 2017) or quadrats (Yao et al 2021). Some studies showed that the direction of the relationship is related to the percentage of rare species in the community (da Silva, Hernández, and Heino 2018;Yao et al 2021). The LCBD-richness relationship and the effect of the proportion of rare species should therefore be investigated over broad spatial extents, as beta diversity and species rarity are both concepts that depend on scale.…”

“…We used a negative binomial regression with a log link function using the package MASS (Venables and Ripley 2002) in R for the richness estimates as our values shown overdispersion (Fletcher and Fortin 2018). We used a beta regression with a logit link function using the package betareg (Cribari-Neto and Zeileis 2010) for the LCBD values as they vary between 0 and 1, similar to Heino and Grönroos (2017) and Yao et al (2021).…”

Divergent Abiotic Stressors Drive Grassland Community Assembly of Tibet and Mongolia Plateau

“…Elucidating the mechanisms and drivers of plant community assembly is a key challenge in ecology ( Keddy, 1992 ; Vellend, 2010 ; Yao et al, 2021 ). However, many studies suggest that the traditional taxon-based approach is unable to adequately describe the influence of climate on plant community assembly processes ( McGill et al, 2006 ; Götzenberger et al, 2012 ; Purschke et al, 2013 ; Cadotte and Tucker, 2017 ).…”