Assessing biological dissimilarities between five forest communities

Abstract

Background: Dissimilarity in community composition is one of the most fundamental and conspicuous features by which different forest ecosystems may be distinguished. Traditional estimates of community dissimilarity are based on differences in species incidence or abundance (e.g. the Jaccard, Sørensen, and Bray-Curtis dissimilarity indices). However, community dissimilarity is not only affected by differences in species incidence or abundance, but also by biological heterogeneities among species.Methods: The objective of this study is to present a new measure of dissimilarity involving the biological heterogeneity among species. The "discriminating Avalanche" introduced in this study, is based on the taxonomic dissimilarity between tree species. The application is demonstrated using observations from five stem-mapped forest plots in China and Mexico. We compared three traditional community dissimilarity indices (Jaccard, Sørensen, and Bray-Curtis) with the "discriminating Avalanche" index, which incorporates information, not only about species frequencies, but also about their taxonomic hierarchies.Results: Different patterns emerged for different measures of community dissimilarity. Compared with the traditional approaches, the discriminating Avalanche values showed a more realistic estimate of community dissimilarities, indicating a greater similarity among communities when species were closely related.Conclusions: Traditional approaches for assessing community dissimilarity disregard the taxonomic hierarchy. In the traditional analysis, the dissimilarity between Pinus cooperi and Pinus durangensis would be the same as the dissimilarity between P. cooperi and Arbutus arizonica. The dissimilarity Avalanche dissimilarity between P. cooperi and P. durangensis is considerably lower than the dissimilarity between P. cooperi and A. arizonica, because the taxonomic hierarchies are incorporated. Therefore, the discriminating Avalanche is a more realistic measure of community dissimilarity. This main result of our study may contribute to improved characterization of community dissimilarities.

Latitudinal gradients and ecological drivers of β‐diversity vary across spatial scales in a temperate forest region

“…They documented seven negative, two positive and six non‐significant relationships. The variety of relationships may be caused by differences in the taxa (Hao et al, 2019), the latitudinal span, the size of sampling units, the specific geographical region of each study and the use of different β‐diversity metrics. In addition to the effect of the geographical region from which local communities are sampled, β‐diversity in a local site is also subjected to the effect of local niche‐ and dispersal‐based processes (Myers et al, 2013).…”

A classification of woody communities based on biological dissimilarity

“…Consequently, these systems are not entirely dissimilar, and may thus have similar ecosystem functions. The Discriminating Avalanche (DA), which represents an alternative metric by incorporating essential information about the biological heterogeneity among species (Ganeshaiah et al, 1997;Hao et al, 2019a), is defined as follows:…”

“…If there are no shared species among several samples, how can we discriminate among these forests and develop classifications using the species compositional attributes? Forest vegetation varies not only by species compositional attributes, but also by structural (i.e., the distribution of tree diameters, heights, or biomass stock; De Cáceres et al, 2018, 2019) and biological attributes (i.e., the heterogeneity of taxonomy, phylogeny, or morphology among species; Clarke & Warwick, 1998, 2001Petchey & Gaston, 2002;Webb et al, 2002;Hao et al, 2019aHao et al, , 2019b. These A second group includes temperate deciduous broad-leaved forests dominated by oak (Quercus) and beech (Fagus) from Europe and China.…”

“…It is reasonable, therefore, to use the biological heterogeneity among species as an essential basis for forest classification (Pavoine et al, 2004;Capelo, 2020;Lengyel et al, 2020). Hao et al (2019a) used the "Discriminating Avalanche," a measure for assessing the dissimilarity between forests that incorporates species abundance and any quantifiable biological heterogeneity among species, including taxonomic, phylogenetic, and functional distance. Compared with the traditional species abundance or incidence-based approaches, the Discriminating Avalanche provides more refined estimates of forest heterogeneity, and thus contributes to improve characterization of community dissimilarity (Hao et al, 2019a(Hao et al, , 2019b.…”

“…Hao et al (2019a) used the "Discriminating Avalanche," a measure for assessing the dissimilarity between forests that incorporates species abundance and any quantifiable biological heterogeneity among species, including taxonomic, phylogenetic, and functional distance. Compared with the traditional species abundance or incidence-based approaches, the Discriminating Avalanche provides more refined estimates of forest heterogeneity, and thus contributes to improve characterization of community dissimilarity (Hao et al, 2019a(Hao et al, , 2019b. Accordingly, the objective of this study is to evaluate the potential of the Discriminating Avalanche measure as a new basis for forest classification.…”