Explaining the excess of rare species in natural species abundance distributions

Nature ◽  
2003 ◽  
Vol 422 (6933) ◽  
pp. 714-716 ◽  
Author(s):  
Anne E. Magurran ◽  
Peter A. Henderson
Keyword(s):  
Rare Species ◽  
Species Abundance ◽  
Species Abundance Distributions

scholarly journals The commonness of rarity: Global and future distribution of rarity across land plants

2019 ◽  
Author(s):  
Brian Joseph Enquist ◽  
Xiao Feng ◽  
Bradley Boyle ◽  
Brian Maitner ◽  
Erica A. Newman ◽  
...  
Keyword(s):  
Plant Species ◽  
Rare Species ◽  
Large Fraction ◽  
Neutral Theory ◽  
Species Abundance ◽  
Land Plant ◽  
Observation Data ◽  
Heavy Tailed Distributions ◽  
Species Abundance Distributions ◽  
Heavy Tailed

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant species observation data in order to quantify the fraction of Earth’s extant land plant biodiversity that is common versus rare. Tests of different hypotheses for the origin of species commonness and rarity indicates that sampling biases and prominent models such as niche theory and neutral theory cannot account for the observed prevalence of rare species. Instead, the distribution of commonness is best approximated by heavy-tailed distributions like the Pareto or Poisson-lognormal distributions. As a result, a large fraction, ~36.5% of an estimated ~435k total plant species, are exceedingly rare. We also show that rare species tend to cluster in a small number of ‘hotspots’ mainly characterized by being in tropical and subtropical mountains and areas that have experienced greater climate stability. Our results indicate that (i) non-neutral processes, likely associated with reduced risk of extinction, have maintained a large fraction of Earth’s plant species but that (ii) climate change and human impact appear to now and will disproportionately impact rare species. Together, these results point to a large fraction of Earth’s plant species are faced with increased chances of extinction. Our results indicate that global species abundance distributions have important implications for conservation planning in this era of rapid global change.

scholarly journals The commonness of rarity: Global and future distribution of rarity across land plants

2019 ◽  
Vol 5 (11) ◽  
pp. eaaz0414 ◽  
Author(s):  
Brian J. Enquist ◽  
Xiao Feng ◽  
Brad Boyle ◽  
Brian Maitner ◽  
Erica A. Newman ◽  
...  
Keyword(s):  
Plant Species ◽  
Conservation Planning ◽  
Rare Species ◽  
Extinction Risk ◽  
Large Fraction ◽  
Neutral Theory ◽  
Species Abundance ◽  
Risk Assessments ◽  
Human Land Use ◽  
Species Abundance Distributions

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change.

scholarly journals Fuzzy Quantification of Common and Rare Species in Ecological Communities (FuzzyQ)

2020 ◽  
Author(s):  
Juan A. Balbuena ◽  
Clara Montlleó ◽  
Cristina Llopis-Belenguer ◽  
Isabel Blasco-Costa ◽  
Volodimir L. Sarabeev ◽  
...  
Keyword(s):  
Rare Species ◽  
Clustering Algorithm ◽  
Species Abundance ◽  
R Package ◽  
Ecological Communities ◽  
Wide Range ◽  
Species Abundance Distributions ◽  
The Common ◽  
Spatio Temporal ◽  
The Impact

Abstract1. Most species in ecological communities are rare whereas only a few are common. This distributional paradox has intrigued ecologists for decades but the interpretation of species abundance distributions remains elusive.2. We present Fuzzy Quantification of Common and Rare Species in Ecological Communities (FuzzyQ) as an R package. FuzzyQ shifts the focus from the prevailing species-categorization approach to develop a quantitative framework that seeks to place each species along a rare-commonness gradient. Given a community surveyed over a number of sites, quadrats, or any other convenient sampling unit, FuzzyQ uses a fuzzy clustering algorithm that estimates a probability for each species to be common or rare based on abundance-occupancy information. Such as probability can be interpreted as a commonness index ranging from 0 to 1. FuzzyQ also provides community-level metrics about the coherence of the allocation of species into the common and rare clusters that are informative of the nature of the community under study.3. The functionality of FuzzyQ is shown with two real datasets. We demonstrate how FuzzyQ can effectively be used to monitor and model spatio-temporal changes in species commonness, and assess the impact of species introductions on ecological communities. We also show that the approach works satisfactorily with a wide range of communities varying in species richness, dispersion and abundance currencies.4. FuzzyQ produces ecological indicators easy to measure and interpret that can give both clear, actionable insights into the nature of ecological communities and provides a powerful way to monitor environmental change on ecosystems. Comparison among communities is greatly facilitated by the fact that the method is relatively independent of the number of sites or sampling units considered. Thus, we consider FuzzyQ as a potentially valuable analytical tool in community ecology and conservation biology.

scholarly journals A lognormal distribution of the lengths of terminal twigs on self-similar branches of elm trees

2017 ◽  
Vol 284 (1846) ◽  
pp. 20162395 ◽  
Author(s):  
Kohei Koyama ◽  
Ken Yamamoto ◽  
Masayuki Ushio
Keyword(s):  
Lognormal Distribution ◽  
Species Abundance ◽  
Self Similarity ◽  
Lognormal Distributions ◽  
Multiplicative Effect ◽  
Wide Range ◽  
Error Distributions ◽  
Species Abundance Distributions ◽  
Self Similar ◽  
Ulmus Davidiana

Lognormal distributions and self-similarity are characteristics associated with a wide range of biological systems. The sequential breakage model has established a link between lognormal distributions and self-similarity and has been used to explain species abundance distributions. To date, however, there has been no similar evidence in studies of multicellular organismal forms. We tested the hypotheses that the distribution of the lengths of terminal stems of Japanese elm trees ( Ulmus davidiana ), the end products of a self-similar branching process, approaches a lognormal distribution. We measured the length of the stem segments of three elm branches and obtained the following results: (i) each occurrence of branching caused variations or errors in the lengths of the child stems relative to their parent stems; (ii) the branches showed statistical self-similarity; the observed error distributions were similar at all scales within each branch and (iii) the multiplicative effect of these errors generated variations of the lengths of terminal twigs that were well approximated by a lognormal distribution, although some statistically significant deviations from strict lognormality were observed for one branch. Our results provide the first empirical evidence that statistical self-similarity of an organismal form generates a lognormal distribution of organ sizes.

scholarly journals How, when, and where relic DNA biases estimates of microbial diversity

2017 ◽  
Author(s):  
JT Lennon ◽  
ME Muscarella ◽  
SA Muscarella ◽  
BK Lehmkuhl
Keyword(s):  
Microbial Diversity ◽  
Dna Sequences ◽  
Species Abundance ◽  
Rrna Gene ◽  
Bacterial Dna ◽  
Soil Sediment ◽  
Species Abundance Distributions ◽  
Abundance And Diversity ◽  
Dna Pool ◽  
Biased Estimates

Extracellular or “relic” DNA is one of the largest pools of nucleic acids in the mbiosphere1,2. Relic DNA can influence a number of important ecological and evolutionary processes, but it may also bias estimates of microbial abundance and diversity, which has implications for understanding environmental, engineered, and host-associated ecosystems. We developed models capturing the fundamental processes that regulate the size and composition of the relic DNA pools to identify scenarios leading to biased estimates of biodiversity. Our models predict that bias increases with relic DNA pool size, but only when the species abundance distributions (SAD) of relic and intact DNA are distinct from one another. We evaluated our model predictions by quantifying relic DNA and assessing its contribution to bacterial diversity using 16S rRNA gene sequences collected from different ecosystem types, including soil, sediment, water, and the mammalian gut. On average, relic DNA made up 33 % of the total bacterial DNA pool, but exceeded 80 % in some samples. Despite its abundance, relic DNA had no effect on estimates of taxonomic and phylogenetic diversity, even in ecosystems where processes such as the physical protection of relic DNA are common and predicted by our models to generate bias. Rather, our findings are consistent with the expectation that relic DNA sequences degrade in proportion to their abundance and therefore may contribute minimally to estimates of microbial diversity.

scholarly journals A new method to analyze species abundances in space using generalized dimensions

2015 ◽  
Author(s):  
Leonardo A Saravia
Keyword(s):  
Species Abundance ◽  
Abundance Distribution ◽  
Community Patterns ◽  
Information Dimension ◽  
Generalized Dimension ◽  
Species Abundances ◽  
Species Abundance Distributions ◽  
Species Area ◽  
Generalized Dimensions ◽  
Relationship Of

Species-area relationships (SAR) and species abundance distributions (SAD) are among the most studied patterns in ecology, due to their application to both theoretical and conservation issues. One problem with these general patterns is that different theories can generate the same predictions, and for this reason they cannot be used to detect different mechanisms of community assembly. A solution is to search for more sensitive patterns, for example by extending the SAR to the whole species abundance distribution. A generalized dimension ($D_q$) approach has been proposed to study the scaling of SAD, but to date there has been no evaluation of the ability of this pattern to detect different mechanisms. An equivalent way to express SAD is the rank abundance distribution (RAD). Here I introduce a new way to study SAD scaling using a spatial version of RAD: the species-rank surface (SRS), which can be analyzed using $D_q$. Thus there is an old $D_q$ based on SAR ($D_q^{SAD}$), and a new one based on SRS ($D_q^{SRS}$). I perform spatial simulations to examine the relationship of $D_q$ with SAD, spatial patterns and number of species. Finally I compare the power of both $D_q$, SAD, SAR exponent, and the fractal information dimension to detect different community patterns using a continuum of hierarchical and neutral spatially explicit models. The SAD, $D_q^{SAD}$ and $D_q^{SRS}$ all had good performance in detecting models with contrasting mechanisms. $D_q^{SRS}$, however, had a better fit to data and allowed comparisons between hierarchical communities where the other methods failed. The SAR exponent and information dimension had low power and should not be used. SRS and $D_q^{SRS}$ could be interesting methods to study community or macroecological patterns.

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