The completeness of taxonomic inventories for describing the global diversity and distribution of marine fishes

Abstract

Taxonomic inventories (or species censuses) are the most elementary data in biogeography, macroecology and conservation biology. They play fundamental roles in the construction of species richness patterns, delineation of species ranges, quantification of extinction risk and prioritization of conservation efforts in hot spot areas. Given their importance, any issue related to the completeness of taxonomic inventories can have far-reaching consequences. Here, we used the largest publicly available database of georeferenced marine fish records to determine its usefulness in depicting the diversity and distribution of this taxonomic group. All records were grouped at multiple spatial resolutions to generate accumulation curves, from which the expected number of species were extrapolated using a variety of nonlinear models. Comparison of the inventoried number of species with that expected from the models was used to calculate the completeness of the taxonomic inventory at each resolution. In terms of the global number of fish species, we found that approximately 21% of the species remain to be described. In terms of spatial distribution, we found that the completeness of taxonomic data was highly scale dependent, with completeness being lower at finer spatial resolutions. At a 3 degrees (approx. 350km2) spatial resolution, less than 1.8% of the world's oceans have above 80% of their fish fauna currently described. Censuses of species were particularly incomplete in tropical areas and across the entire range of countries' gross domestic product (GDP), although the few censuses nearing completion were all along the coasts of a few developed countries or territories. Our findings highlight that failure to quantify the completeness of taxonomic inventories can introduce substantial flaws in the description of diversity patterns, and raise concerns over the effectiveness of conservation strategies based upon data that remain largely precarious.

Figure 1

(a–c) Effects of the RSA distribution and (d–f) variable sampling on the rarefaction curves and (g–i) on the asymptotic number of species predicted by the models. Here, we created three hypothetical communities each with 500 species and 10 000 individuals. (a–c) The number of individuals per species in each community ranged from being equal to very unequal, to generate RSAs with different skews. For each of these communities, we created rarefaction curves (d–f) by sampling a variable number of individuals for each time period (simulating the sampling occurred at any given year). Sampling effort varied by a factor of five: from 200 to 1000 individuals each time period, from 400 to 1000, from 600 to 1000, from 800 to 1000 and exactly 1000 individuals each time. We also created another set of curves (not shown) using 10, 20, 30, 40 and 50 years of sampling. Thus, for each community, we created a total of 25 curves, combining all five sampling efforts and five groups of years. For each of these of curves, we fitted all nonlinear models and applied the approach mentioned in §2 to calculate the predicted asymptotic number of species in the community (g–i).

Figure 2

Temporal description of marine fish species worldwide. (a) The species accumulation curve, the smoothed rarefaction curve and the fit of the nonlinear models to the global data. Results for the different models are shown in table 2. (b) The accumulation of records with date stamps in OBIS.

Figure 3

Area of the world's oceans with taxonomic censuses over 80% complete at various spatial resolutions.

Figure 4

Taxonomic sampling of the marine fishes of the world. (a) The positions of the approximately 2.1 million georeferenced records used in this study. (b) The completeness of the taxonomic inventories within the high seas and EEZs of the world. (c–f) Resolutions of 36°×36°, 18°×18°, 9°×9°, and 3°×3°, respectively. White areas in the maps indicate locations whose curves have less than 10 years sampled. Congruence between the number of species observed and expected was R²=0.0098, n=1318, p<0.3 (at 3°×3°); R²=0.00002, n=409, p<0.9 (at 9°×9°); R²=0.0001, n=151, p<0.87 (at 18°×18°); and R²=0.85, n=48, p<0.001 (at 36°×36°).

Figure 5

Completeness of taxonomic inventories by marine habitat. Completeness of taxonomic inventories was determined at a 3° resolution for species residing in different marine habitats. Species-specific habitat associations were obtained from Froese & Pauly (2006). They were as follows: (a) pelagic, (b) demersal, (c) reef associated, (d) benthopelagic, (e) bathypelagic and (f) bathydemersal (details of each of the habitats can be found in Froese & Pauly (2006)). For a spatial reference of where the different habitats may occur (i.e. all delimited cells), we selected all the cells where at least one species with a particular habitat association has been described.