Accepted Manuscript Succinctus Parasitic worms: how many really? Giovanni Strona, Simone Fattorini PII: DOI: Reference:

S0020-7519(14)00027-7 http://dx.doi.org/10.1016/j.ijpara.2014.01.002 PARA 3613

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International Journal for Parasitology

Received Date: Revised Date: Accepted Date:

1 October 2013 10 January 2014 13 January 2014

Please cite this article as: Strona, G., Fattorini, S., Parasitic worms: how many really?, International Journal for Parasitology (2014), doi: http://dx.doi.org/10.1016/j.ijpara.2014.01.002

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Succinctus

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Parasitic worms: how many really?

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Giovanni Stronaa,*, Simone Fattorinib

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a

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Fermi 2749, 21027 Ispra (VA), Italy

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b

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Sustainability (PEERS), Universidade dos Açores, Departamento de Ciências Agrárias, Pico da Urze,

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9700-04, Angra do Heroísmo, Terceira, Açores, Portugal

Institute for Environment and Sustainability, Joint Research Centre, European Commission, Via E.

Azorean Biodiversity Group (CITA-A) and Platform for Enhancing Ecological Research &

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*Corresponding author. Tel.: +39 0332 783047; fax: +39 0332 785230.

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E-mail address: [email protected] (G. Strona).

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ABSTRACT

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Accumulation curves are useful tools to estimate species diversity. Here we argue that they can also be

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used in the study of global parasite species richness. Although this basic idea is not completely new,

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our approach differs from the previous ones as it treats each host species as an independent sample. We

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show that randomly resampling host-parasite records from the existing databases makes it possible to

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empirically model the relationship between the number of investigated host species, and the

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corresponding number of parasite species retrieved from those hosts. This method was tested on 21

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inclusive lists of parasitic worms occurring on vertebrate hosts. All of the obtained models conform

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well to a power law curve. These curves were then used to estimate global parasite species richness.

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Results obtained with the new method suggest that current predictions are likely to severely

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overestimate parasite diversity.

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Keywords: Accumulation curve, Biodiversity, Helminth, Host range, Power law, Rarefaction curve

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Parasitism is the most common lifestyle on Earth (Poulin and Morand, 2004). Parasites can play

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fundamental roles in ecosystems by contributing much biomass and productivity (Kuris et al., 2008),

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by increasing connectance, nestedness (asymmetry of interactions), chain length and linkage density of

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food webs (Lafferty et al., 2006), and by performing several „„ecosystem services‟‟, such as regulating

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host abundance and, potentially, buffering pollution levels in natural communities (Dobson et al.,

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2008). All of these aspects give strong support to Windsor's claim for “equal rights for parasites”

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(1995), highlighting the importance of analytically extending our knowledge on parasite diversity.

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There is ample data available on parasite occurrence (Dobson et al., 2008), but perhaps it is not

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being capitalized on when trying to estimate global parasite diversity. According to Poulin and Morand

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(2004), the total number of parasite species (Sp) living on Earth can be estimated, for each parasite

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group, by using the simple linear relationship: Sp = Sh× (Pn/Hr), where Pn is the average number of

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parasite species per host species, Hr is the average parasite host range, and Sh is the total number of

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available host species. In spite of its appealing immediacy, the above formula may severely

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overestimate global parasite diversity. The estimate of Pn is very likely to be biased upwards due to the

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empirically documented, universal decelerating nature of species accumulation curves (Gotelli and

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Colwell, 2001, 2010) that makes the discovery of new parasite species less likely as more host species

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are investigated. To test this hypothesis, we propose here to randomly resample existing databases as a

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systematic way to model empirically the relationship between the number of examined host species and

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the number of parasite species retrieved.

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This approach was applied to to 21 different lists of parasitic worms associated with vertebrates.

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We used FishPEST (Strona and Lafferty, 2012a,b; Strona et al., 2013) to compile lists of the

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distribution of acanthocephalans, cestodes, monogeneans, nematodes and trematodes on fish, while we

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used all of the data available from the host-parasite database of the Natural History Museum of

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London, UK (http://www.nhm.ac.uk/) to compile lists of the distribution of acanthocephalans, cestodes, 3

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nematodes and trematodes on amphibians, birds, mammals and reptiles. Details of each list (i.e.

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number of host species, number of parasite species, number of host-parasite records) are provided in

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Table 1. The relationship between number of sampled hosts and number of retrieved parasites was

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modelled for each list by reiterating 1000 times a very simple two-step procedure that consisted of (i)

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selecting a random number of host species from the complete list, and (ii) comparing the number of

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randomly selected host species with the overall number of all the (different) parasite species found on

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those hosts (see Fig. 1). To empirically model the observed relationships, we used several models

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commonly used for species accumulation curves such as the Clench, exponential, logarithm and power

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functions (e.g. Thompson et al., 2003; Díaz-Francés and Soberón, 2005). For all lists, the relationship

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between the number of sampled host species and the corresponding number of retrieved parasite

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species was best modelled by a decelerating power function (R2 > 0.9 in all cases except two; see Table

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1 and Fig. 2 as an example). In addition, for each one of the 21 complete lists, we computed the

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average number of parasite per host (Pn), and the average number of hosts used by a parasite (Hr).

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The power function is not asymptotic but it is used here only for extrapolation within the known value

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of the independent variable (number of host species). From a purely theoretical point of view, the

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consistency of the power law relationship (with an exponent

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82,000). The consistency in the shape of the relationships modelled for the different host and parasite

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taxa suggests that the method proposed here is not much affected by unequal sampling, and that the

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obtained results may be representative of a very general pattern. However, we would like to emphasize

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that our purpose here is not to replace current estimates of parasite biodiversity, but to promote the

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debate on a fundamental issue that, in our opinion, is far from being closed.

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Acknowledgments We are very grateful to Kevin D. Lafferty for his suggestions on a very early version of the

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manuscript. We thank two anonymous referees for their comments on the paper. The views expressed

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are purely those of the writers and may not in any circumstances be regarded as stating an official

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position of the European Commission.

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References

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Brown, J.H., Gupta, V.K., Li, B.L., Milne, B.T., Restrepo, C., West, G.B. 2002. The fractal nature of

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nature: power laws, ecological complexity and biodiversity. Philos. Trans. R. Soc. B 357, 619–

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626.

153 154 155 156 157 158 159 160 161

Díaz-Francés, E., Soberón, J. 2005. Statistical estimation and model selection of species-accumulation functions. Conserv. Biol. 19, 569-573. Dobson, A., Lafferty, K.D., Kuris, A.M., Hechinger, R.F., Jetz, W. 2008. Homage to Linnaeus: How many parasites? How many hosts? Proc. Natl. Acad. Sci. USA 105, 11482–11489. Dove, A.D., Cribb, T.H. 2006. Species accumulation curves and their applications in parasite ecology. Trends Parasitol. 22, 568–574. Gotelli, N.J., Colwell, R.K. 2001. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391. Gotelli, N.J., Colwell, R.K. 2010. Estimating species richness. In: Magurran, A.E., McGill B.J. (Eds),

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Biological Diversity: Frontiers In Measurement And Assessment. Oxford University Press,

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Oxford, pp. 39-54.

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International Union for Conservation of Nature . 2012. The IUCN Red List of Threatened Species. www.iucnredlist.org Version 2012.2.

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Kuris, A.M., Hechinger, R.F., Shaw, J.C., Whitney, K.L., Aguirre-Macedo, L., Boch, C.A., Dobson,

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A.P., Dunham, E.J., Fredensborg, B.L., Huspeni, T.C., Lorda, J., Mababa, L., Mancini, F.T.,

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Mora, A.B., Pickering, M., Talhouk, N.L., Torchin, M.E., Lafferty, K.D. 2008. Ecosystem

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energetic implications of parasite and free-living biomass in three estuaries. Nature 454, 515–

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518.

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Lafferty, K.D., Dobson, A.P., Kuris, A.M. 2006. Parasites dominate food web links. Proc. Natl. Acad. Sci. USA 103, 11211–11216. 9

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Poulin, R., Morand, S. 2004. Parasite biodiversity. Smithsonian Institution Press, Washington, DC.

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Poulin, R. 2007. Evolutionary Ecology of Parasites (2nd Edition). Princeton University Press,

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Princeton, NJ. Rossiter, W. 2013. Current opinions: Zeros in host–parasite food webs: Are they real? Int. J. Parasitol. Parasites Wildl. 2, 228–234. Strona, G., Lafferty, K.D. 2012a. How to catch a parasite: Parasite Niche Modeler (PaNic) meets Fishbase. Ecography 35, 481–486. Strona, G., Lafferty, K.D. 2012b. FishPEST: an innovative software suite for fish parasitologists. Trends Parasitol. 28, 123. Strona, G., Lafferty, K.D. 2013. Predicting what helminth parasites a fish species should have using parasite co-occurrence modeler (PaCo). J. Parasitol. 99, 6–10. Strona, G., Palomares, M.L.D., Bailly, N., Galli, P., Lafferty, K.D. 2013. Host range, host ecology, and distribution of more than 11800 fish parasite species. Ecology 94, 544–544. Thompson, G.G., Withers, P.C., Pianka, E.R., Thompson, S.A. 2003. Assessing biodiversity with

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species accumulation curves; inventories of small reptiles by pit-trapping in Western Australia.

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Austral Ecol. 28, 361–383.

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Windsor, D.A. 1995. Equal rights for parasites. Conserv. Biol. 9, 1–2.

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Figure legends

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Fig. 1. Diagrammatic illustration of the procedure to model the relationship between the number of

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sampled host species and the number of retrieved parasite species. (A) represents a hypothetical

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complete host-parasite list, including five host species (i.e. the fish silhouettes) and six parasite species

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(P1-6). At each step (B-F) a host species is sampled for parasites and the overall numbers of sampled

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host species (Sh) and retrieved parasite species (Sp) are plotted on graph to build an accumulation

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curve.

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Fig. 2. Relationship between number of examined host species and the number of retrieved parasite

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species for fish acanthocephalans. Data were retrieved from FishPEST (Strona and Lafferty, 2012a,b;

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Strona et al., 2013). Circles indicate the values obtained by randomly extracting host species from the

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database. Continuous line indicates the power law regression line that best approximates these values (y

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= 10.709x 0.570; R2 = 0.992; non-linear least-squares regression with Levenberg-Marquardt algorithm).

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Dotted line indicates the linear relationship estimated using the Pn/Hr ratio (y = 0.519 x).

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Table 1. Details of each host-parasite list used in the analyses. Sp Parasite Taxon Host Taxon Acanthocephalans Amphibians Acanthocephalans Birds Acanthocephalans Fish Acanthocephalans Mammals Acanthocephalans Reptiles Cestodes Amphibians Cestodes Birds Cestodes Fish Cestodes Mammals Cestodes Reptiles Monogeneans Fish Nematodes Amphibians Nematodes Birds Nematodes Fish Nematodes Mammals Nematodes Reptiles Trematodes Amphibians Trematodes Birds Trematodes Fish Trematodes Mammals Trematodes Reptiles

Sh

27 43 194 427 581 1119 135 226 18 17 29 75 1820 1048 1519 1516 1208 1069 48 64 4351 2337 211 198 984 1011 1479 1557 2901 1404 296 152 235 130 1726 948 4259 3013 1197 879 359 80

Sh_IUCN 6771 10064 32400 5501 9547 6771 10064 32400 5501 9547 32400 6771 10064 32400 5501 9547 6771 10064 32400 5501 9547

R2 Pred1 Pred2 RN 0.94 4252 1000 78 0.98 4572 1079 1034 1.00 16823 4290 2764 0.98 3286 961 798 0.78 10109 4643 41 0.95 2618 570 132 0.99 17478 8596 6456 0.99 32464 13709 4705 0.98 6216 3444 7783 0.94 7160 2118 144 1.00 60322 34401 7926 0.97 7216 2578 672 0.99 9795 3778 5611 1.00 30777 12482 4699 0.99 11366 7228 15312 0.97 18592 8657 689 0.94 12240 4606 771 0.99 18323 7252 9286 1.00 45799 20892 13614 0.97 7491 3796 7367 0.88 42842 32936 828

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Sp, number of parasite species; Sh, number of host species; Sh_IUCN, estimated number of described

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species according to International Union for Conservation of Nature (2012); RN, number of host-

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parasite records; R2, goodness of fit of the power law function that best modeled the relationship

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between the number of sampled hosts and the number of retrieved parasites; Pred1, global number of

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parasite species predicted by the traditional approach; Pred2, global number of parasite species

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predicted by our resampling procedure.

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Figure 1

P1 P2

P3 P4 P2

P4

Sp

P6 P3 P6

P1 P5 P3

P1 P2 P3 P4

P1 P2 P3 P4 P5 P6

P1 P2

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Sh

6 5 4 Sp 3 2 1 1

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Sh

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4 Sp 3 2 1 1

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P1 P2 P3 P4 P5

P1 P2 P3 P4 P5 P6

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Sh

5 4 Sp 3 2 1 1

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Sh

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6 5 4 Sp 3 2 1 Sh

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Figure 2

Number of retrived parasite species

900 800 700 600 500 400 300 200 100 0 0

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Number of sampled host species

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Highlights 

We propose a new approach to estimate global parasite richness.



The new method is based on randomly resampling existing databases.



This method was applied to several large host-parasite lists.



Power law best models the relation between sampled hosts and retrieved parasites.



The new approach revealed that current predictions overestimate parasite diversity.

Parasite Species N

Host Species N

Parasitic worms: how many really?

Accumulation curves are useful tools to estimate species diversity. Here we argue that they can also be used in the study of global parasite species r...
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