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. 2019 Nov 27;5(11):eaaz0414.
doi: 10.1126/sciadv.aaz0414. eCollection 2019 Nov.

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

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

Brian J Enquist et al. Sci Adv. .

Abstract

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.

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Figures

Fig. 1
Fig. 1. Computational workflow for creating gSADs.
TNRS, Taxonomic Name Resolution Service; GNRS, Geographic Name Resolution Service.
Fig. 2
Fig. 2. The gSAD for all plant species.
(A) Schematic illustration of the predicted gSAD based on expectations from theory (see main text) (28). In the inset, we list several differing predictions for the shape of the gSAD. (B) Two estimates of the gSAD for all land plant species. The first distribution (green) is the observed number of observations per species for all species found in ecological plots. Each data point represents the total number of individuals observed for a given species. The second distribution (red) is all botanical specimens collected within 100 km of each plot. The third distribution (light purple) is all botanical specimens per species. Each distribution is strongly modal at the lowest abundance, showing that most species have only been observed a very small number of times and only a few species are common. The distributions are shown on log10-transformed axes. Comparing the shape of the distributions of the competing fits of differing proposed gSAD distributions allows us to test differing hypotheses for the origin of the gSAD.
Fig. 3
Fig. 3. Does using the number of observations in botanical datasets provide a reliable measure of rarity?
Assessments of rarity by taxonomic specialists at the Missouri Botanical Garden and the New York Botanical Garden for a random sample of 300 species with three observations or fewer in the BIEN database. Most species (72.7%) identified as “rare” based on the number of unique occurrences within the BIEN database are also recognized as rare by experts. Approximately 7.3% of these species appear to be incorrectly characterized as rare, as they are recognized by experts as abundant or having large ranges. The apparent scarcity of approximately 7.5% of these taxa may reflect recent taxonomic splits or old names no longer used. Moreover, 10.3% are non-native species (which may or may not be rare). In sum, we estimate that between 72 and 90% of plant taxa (recognized as rare + recent name + unresolved + old name) identified by BIEN as being rare would be recognized as rare by other measures.
Fig. 4
Fig. 4. Where are rare species distributed geographically?
Plotting the geographic coordinates for all the observations for species with three observations or fewer at a coarse, 1° resolution reveals several patterns. The sampling background is shown (grey cells are areas with no georeferenced botanical sampling records, while yellow cells indicate regions with observation records but no rare species). Colored cells correspond to areas with rare species (species with three observations or fewer) rarified to the sampling intensity using the Margalef index (see the Supplementary Materials). Areas with a proportionally high number of rare species are dark brown (“hotspots of rarity”), while areas with relatively low numbers of rare species are yellow to orange. Areas with a high number of rare species tend to be clustered in a small number of locations including mountainous tropical and subtropical regions including New Guinea, Indonesia, southwestern China, Madagascar, the Andes (in Ecuador, Columbia, and Peru), Central America (Costa Rica and Panama), and southern Mexico. In addition, several notable temperate zone locations including the Fynbos in South Africa and southwest Australia, Northern Iran/Georgia/Turkey, and the Iberian Peninsula.
Fig. 5
Fig. 5. Regions that currently have high numbers of rare species are also characterized by higher human impact and will experience faster rates of future climate change.
(A) Density plot of human footprint index in areas with rare species (light gray) and the global map (dark gray). Areas with rare species have, on average, human footprint values of 8.5 ± 5.8, which is ~1.6 times higher (P < 0.001, Wilcoxon test) human impact than on the globe on average (5.2 ± 5.8). (B) Density plot of the ratio of future climate (temperature) velocity versus historical climate velocity. On average, areas with rare species will experience ~200 (±58) times greater rates of temperature velocity than those same areas experienced historically and will experience ~1.2 times greater (P < 0.001, Wilcoxon test) rates of temperature velocity change than the globe will experience on average (170 ± 77). (C) Global variation in the human footprint index. Areas with high human footprint are in brown. Areas with low human footprint are dark green. (D) Global map of the ratio between future (baseline climate to late century, 1960–1990 to 2060–2080, under RCP8.5) and historical rates of temperature change [LGM to baseline climate (~21 ka ago to 1960–1990)]. Future temperatures will increase across the globe. However, in comparison with historical rates of climate change, some areas will experience relatively faster (ratio values greater than 1; yellow to red values) or slower (ratio values less than 1; green to blue values) rates of change. Note that many of the regions of rarity hotspots are found in regions that will be experiencing relatively faster rates of climate change compared to historical rates of change.
Fig. 6
Fig. 6. What will happen to rare species diversity with climate change?
(A) The predicted change in Margalef SAR rarity index under climate change from the autoregressive models (SAR). The rarity indices are log-transformed. Large decreases in climate suitability for rare species are in red to orange, whereas smaller reductions in climate suitability are given in green to blue colors. Note the large decreases in climate suitability for rare species in the Andes and Mesoamerica, African highlands, New Guinea, southwestern China, Indonesia, Nepal, and New Zealand. (B) The diagonal 1:1 line (red) represents situations of no difference between the predicted current and future rarity index from SAR and OLS models. All points in the scatter plot are below the diagonal line, indicating a reduction of rare species diversity across all the areas where they currently occur.

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