A Likelihood Framework for Modeling Pairwise Beta Diversity Patterns Based on the Tradeoff Between Colonization and Extinction

Abstract

Ecological communities are assembled by various mechanisms, including a tradeoff between colonization and extinction processes. However, it is still unclear how this tradeoff influences pairwise beta diversity patterns. Herein, we propose a novel likelihood framework to disentangle the compound impacts of species' colonization and extinction rates on community-level compositional dissimilarity, which are ignored by traditional indices. The framework infers two parameters of colonization and extinction rates, allowing ecologists to study their latitudinal or broad-scale spatial variation patterns and test the relative influences of associated environmental factors. More importantly, the likelihood-based model showed that multi-site beta diversity is essentially identical to the local colonization failure or extinction rate of species in newly colonized sites but is not related to species' colonization rates. Profoundly, the present likelihood model allows ecologists to explicitly infer the independent species' colonization rate parameter and test its underpinning mechanisms, as it can be proven that this parameter would be only implicitly measured if used to compute multi-site beta diversity indices.

Floral composition and diversity of the lagos coastal environment, South‐Western, Nigeria

“…Although our study failed to examine the factors that underpin the general distribution pattern of the species nevertheless, they are inextricably related to the sufficiency of seed dispersal by water, close proximity of the locations, similar elevation range, and largely uniform environments suitable for species establishment. In addition, the pair‐wise β‐diversity inferred that species occupying similar or equivalent habitats may not necessarily be the same (Carvalho et al, 2013; Villéger et al, 2012; Wu et al, 2020). This uneven occurrence may be partly related to the prevailing flood regimes, microclimate, and the extent of anthropogenic activities in those areas.…”

Effects of different indices and pairwise methods on the longitudinal pattern of β diversity of stream fish assemblages

“…The three indices consider three components: the matching component a is the number of species shared by the two assemblages, and b and c represent the number of unique species in the two assemblages respectively. In comparison with β Jac , the denominator of which is the total number of species ( a + b + c ) found in a pair of assemblages, and β Sor gives more weight to a (Wu et al, 2020). Nevertheless, all of the indices are limited to a according to their calculation formulae and show a stronger relationship with variation in a (Jaccard, 1912; Koleff et al, 2003; Simpson, 1943; Sørensen, 1948) (Table 1).…”

Editorial: Modeling large-scale ecological and evolutionary dynamics

“…At the community level, understanding of spatial variation in species composition, i.e., beta-diversity patterns, has primarily relied on empirical studies using non-parametric indices of differences in taxonomic composition (e.g., Baselga, 2010) or evolutionary relatedness, in the case of phylogenetic beta-diversity (Swenson, 2011). For understanding the spatial patterns, there have been recent attempts to incorporate biogeographical and macroevolutionary processes such as dispersal and diversification (e.g., Wu et al, 2020), but species differences in dispersal capabilities along contrasting environmental gradients are difficult to quantify. Jang et al fill this gap with an eco-evolutionary model that accounts for species-specific population growth, dispersal, niche evolution, and species diversification along an environmental gradient.…”