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
To appear in:
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
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Succinctus
2
Parasitic worms: how many really?
3
Giovanni Stronaa,*, Simone Fattorinib
4 5
a
6
Fermi 2749, 21027 Ispra (VA), Italy
7
b
8
Sustainability (PEERS), Universidade dos Açores, Departamento de Ciências Agrárias, Pico da Urze,
9
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 &
10 11
*Corresponding author. Tel.: +39 0332 783047; fax: +39 0332 785230.
12
E-mail address: [email protected] (G. Strona).
1
13
ABSTRACT
14
Accumulation curves are useful tools to estimate species diversity. Here we argue that they can also be
15
used in the study of global parasite species richness. Although this basic idea is not completely new,
16
our approach differs from the previous ones as it treats each host species as an independent sample. We
17
show that randomly resampling host-parasite records from the existing databases makes it possible to
18
empirically model the relationship between the number of investigated host species, and the
19
corresponding number of parasite species retrieved from those hosts. This method was tested on 21
20
inclusive lists of parasitic worms occurring on vertebrate hosts. All of the obtained models conform
21
well to a power law curve. These curves were then used to estimate global parasite species richness.
22
Results obtained with the new method suggest that current predictions are likely to severely
23
overestimate parasite diversity.
24 25
Keywords: Accumulation curve, Biodiversity, Helminth, Host range, Power law, Rarefaction curve
26 27
2
28
Parasitism is the most common lifestyle on Earth (Poulin and Morand, 2004). Parasites can play
29
fundamental roles in ecosystems by contributing much biomass and productivity (Kuris et al., 2008),
30
by increasing connectance, nestedness (asymmetry of interactions), chain length and linkage density of
31
food webs (Lafferty et al., 2006), and by performing several „„ecosystem services‟‟, such as regulating
32
host abundance and, potentially, buffering pollution levels in natural communities (Dobson et al.,
33
2008). All of these aspects give strong support to Windsor's claim for “equal rights for parasites”
34
(1995), highlighting the importance of analytically extending our knowledge on parasite diversity.
35
There is ample data available on parasite occurrence (Dobson et al., 2008), but perhaps it is not
36
being capitalized on when trying to estimate global parasite diversity. According to Poulin and Morand
37
(2004), the total number of parasite species (Sp) living on Earth can be estimated, for each parasite
38
group, by using the simple linear relationship: Sp = Sh× (Pn/Hr), where Pn is the average number of
39
parasite species per host species, Hr is the average parasite host range, and Sh is the total number of
40
available host species. In spite of its appealing immediacy, the above formula may severely
41
overestimate global parasite diversity. The estimate of Pn is very likely to be biased upwards due to the
42
empirically documented, universal decelerating nature of species accumulation curves (Gotelli and
43
Colwell, 2001, 2010) that makes the discovery of new parasite species less likely as more host species
44
are investigated. To test this hypothesis, we propose here to randomly resample existing databases as a
45
systematic way to model empirically the relationship between the number of examined host species and
46
the number of parasite species retrieved.
47
This approach was applied to to 21 different lists of parasitic worms associated with vertebrates.
48
We used FishPEST (Strona and Lafferty, 2012a,b; Strona et al., 2013) to compile lists of the
49
distribution of acanthocephalans, cestodes, monogeneans, nematodes and trematodes on fish, while we
50
used all of the data available from the host-parasite database of the Natural History Museum of
51
London, UK (http://www.nhm.ac.uk/) to compile lists of the distribution of acanthocephalans, cestodes, 3
52
nematodes and trematodes on amphibians, birds, mammals and reptiles. Details of each list (i.e.
53
number of host species, number of parasite species, number of host-parasite records) are provided in
54
Table 1. The relationship between number of sampled hosts and number of retrieved parasites was
55
modelled for each list by reiterating 1000 times a very simple two-step procedure that consisted of (i)
56
selecting a random number of host species from the complete list, and (ii) comparing the number of
57
randomly selected host species with the overall number of all the (different) parasite species found on
58
those hosts (see Fig. 1). To empirically model the observed relationships, we used several models
59
commonly used for species accumulation curves such as the Clench, exponential, logarithm and power
60
functions (e.g. Thompson et al., 2003; Díaz-Francés and Soberón, 2005). For all lists, the relationship
61
between the number of sampled host species and the corresponding number of retrieved parasite
62
species was best modelled by a decelerating power function (R2 > 0.9 in all cases except two; see Table
63
1 and Fig. 2 as an example). In addition, for each one of the 21 complete lists, we computed the
64
average number of parasite per host (Pn), and the average number of hosts used by a parasite (Hr).
65
The power function is not asymptotic but it is used here only for extrapolation within the known value
66
of the independent variable (number of host species). From a purely theoretical point of view, the
67
consistency of the power law relationship (with an exponent
136
82,000). The consistency in the shape of the relationships modelled for the different host and parasite
137
taxa suggests that the method proposed here is not much affected by unequal sampling, and that the
138
obtained results may be representative of a very general pattern. However, we would like to emphasize
139
that our purpose here is not to replace current estimates of parasite biodiversity, but to promote the
140
debate on a fundamental issue that, in our opinion, is far from being closed.
7
141 142
Acknowledgments We are very grateful to Kevin D. Lafferty for his suggestions on a very early version of the
143
manuscript. We thank two anonymous referees for their comments on the paper. The views expressed
144
are purely those of the writers and may not in any circumstances be regarded as stating an official
145
position of the European Commission.
146 147 148
8
149
References
150
Brown, J.H., Gupta, V.K., Li, B.L., Milne, B.T., Restrepo, C., West, G.B. 2002. The fractal nature of
151
nature: power laws, ecological complexity and biodiversity. Philos. Trans. R. Soc. B 357, 619–
152
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),
162
Biological Diversity: Frontiers In Measurement And Assessment. Oxford University Press,
163
Oxford, pp. 39-54.
164 165
International Union for Conservation of Nature . 2012. The IUCN Red List of Threatened Species. www.iucnredlist.org Version 2012.2.
166
Kuris, A.M., Hechinger, R.F., Shaw, J.C., Whitney, K.L., Aguirre-Macedo, L., Boch, C.A., Dobson,
167
A.P., Dunham, E.J., Fredensborg, B.L., Huspeni, T.C., Lorda, J., Mababa, L., Mancini, F.T.,
168
Mora, A.B., Pickering, M., Talhouk, N.L., Torchin, M.E., Lafferty, K.D. 2008. Ecosystem
169
energetic implications of parasite and free-living biomass in three estuaries. Nature 454, 515–
170
518.
171 172
Lafferty, K.D., Dobson, A.P., Kuris, A.M. 2006. Parasites dominate food web links. Proc. Natl. Acad. Sci. USA 103, 11211–11216. 9
173
Poulin, R., Morand, S. 2004. Parasite biodiversity. Smithsonian Institution Press, Washington, DC.
174
Poulin, R. 2007. Evolutionary Ecology of Parasites (2nd Edition). Princeton University Press,
175 176 177 178 179 180 181 182 183 184 185 186
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
187
species accumulation curves; inventories of small reptiles by pit-trapping in Western Australia.
188
Austral Ecol. 28, 361–383.
189
Windsor, D.A. 1995. Equal rights for parasites. Conserv. Biol. 9, 1–2.
190
10
191 192
Figure legends
193 194
Fig. 1. Diagrammatic illustration of the procedure to model the relationship between the number of
195
sampled host species and the number of retrieved parasite species. (A) represents a hypothetical
196
complete host-parasite list, including five host species (i.e. the fish silhouettes) and six parasite species
197
(P1-6). At each step (B-F) a host species is sampled for parasites and the overall numbers of sampled
198
host species (Sh) and retrieved parasite species (Sp) are plotted on graph to build an accumulation
199
curve.
200 201
Fig. 2. Relationship between number of examined host species and the number of retrieved parasite
202
species for fish acanthocephalans. Data were retrieved from FishPEST (Strona and Lafferty, 2012a,b;
203
Strona et al., 2013). Circles indicate the values obtained by randomly extracting host species from the
204
database. Continuous line indicates the power law regression line that best approximates these values (y
205
= 10.709x 0.570; R2 = 0.992; non-linear least-squares regression with Levenberg-Marquardt algorithm).
206
Dotted line indicates the linear relationship estimated using the Pn/Hr ratio (y = 0.519 x).
11
207
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
12
208
Sp, number of parasite species; Sh, number of host species; Sh_IUCN, estimated number of described
209
species according to International Union for Conservation of Nature (2012); RN, number of host-
210
parasite records; R2, goodness of fit of the power law function that best modeled the relationship
211
between the number of sampled hosts and the number of retrieved parasites; Pred1, global number of
212
parasite species predicted by the traditional approach; Pred2, global number of parasite species
213
predicted by our resampling procedure.
13
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
2
C
Sh
6 5 4 Sp 3 2 1 1
2
Sh
3
4
1
A
4 Sp 3 2 1 1
2 1
E
P1 P2 P3 P4 P5
P1 P2 P3 P4 P5 P6
B
Sh
5 4 Sp 3 2 1 1
2
1
2
Sh
3
D
6 5 4 Sp 3 2 1 Sh
3
4
5
F
Figure 2
Number of retrived parasite species
900 800 700 600 500 400 300 200 100 0 0
500
1000
1500
Number of sampled host species
2000
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
S0020-7519(14)00027-7 http://dx.doi.org/10.1016/j.ijpara.2014.01.002 PARA 3613
To appear in:
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
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Succinctus
2
Parasitic worms: how many really?
3
Giovanni Stronaa,*, Simone Fattorinib
4 5
a
6
Fermi 2749, 21027 Ispra (VA), Italy
7
b
8
Sustainability (PEERS), Universidade dos Açores, Departamento de Ciências Agrárias, Pico da Urze,
9
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 &
10 11
*Corresponding author. Tel.: +39 0332 783047; fax: +39 0332 785230.
12
E-mail address: [email protected] (G. Strona).
1
13
ABSTRACT
14
Accumulation curves are useful tools to estimate species diversity. Here we argue that they can also be
15
used in the study of global parasite species richness. Although this basic idea is not completely new,
16
our approach differs from the previous ones as it treats each host species as an independent sample. We
17
show that randomly resampling host-parasite records from the existing databases makes it possible to
18
empirically model the relationship between the number of investigated host species, and the
19
corresponding number of parasite species retrieved from those hosts. This method was tested on 21
20
inclusive lists of parasitic worms occurring on vertebrate hosts. All of the obtained models conform
21
well to a power law curve. These curves were then used to estimate global parasite species richness.
22
Results obtained with the new method suggest that current predictions are likely to severely
23
overestimate parasite diversity.
24 25
Keywords: Accumulation curve, Biodiversity, Helminth, Host range, Power law, Rarefaction curve
26 27
2
28
Parasitism is the most common lifestyle on Earth (Poulin and Morand, 2004). Parasites can play
29
fundamental roles in ecosystems by contributing much biomass and productivity (Kuris et al., 2008),
30
by increasing connectance, nestedness (asymmetry of interactions), chain length and linkage density of
31
food webs (Lafferty et al., 2006), and by performing several „„ecosystem services‟‟, such as regulating
32
host abundance and, potentially, buffering pollution levels in natural communities (Dobson et al.,
33
2008). All of these aspects give strong support to Windsor's claim for “equal rights for parasites”
34
(1995), highlighting the importance of analytically extending our knowledge on parasite diversity.
35
There is ample data available on parasite occurrence (Dobson et al., 2008), but perhaps it is not
36
being capitalized on when trying to estimate global parasite diversity. According to Poulin and Morand
37
(2004), the total number of parasite species (Sp) living on Earth can be estimated, for each parasite
38
group, by using the simple linear relationship: Sp = Sh× (Pn/Hr), where Pn is the average number of
39
parasite species per host species, Hr is the average parasite host range, and Sh is the total number of
40
available host species. In spite of its appealing immediacy, the above formula may severely
41
overestimate global parasite diversity. The estimate of Pn is very likely to be biased upwards due to the
42
empirically documented, universal decelerating nature of species accumulation curves (Gotelli and
43
Colwell, 2001, 2010) that makes the discovery of new parasite species less likely as more host species
44
are investigated. To test this hypothesis, we propose here to randomly resample existing databases as a
45
systematic way to model empirically the relationship between the number of examined host species and
46
the number of parasite species retrieved.
47
This approach was applied to to 21 different lists of parasitic worms associated with vertebrates.
48
We used FishPEST (Strona and Lafferty, 2012a,b; Strona et al., 2013) to compile lists of the
49
distribution of acanthocephalans, cestodes, monogeneans, nematodes and trematodes on fish, while we
50
used all of the data available from the host-parasite database of the Natural History Museum of
51
London, UK (http://www.nhm.ac.uk/) to compile lists of the distribution of acanthocephalans, cestodes, 3
52
nematodes and trematodes on amphibians, birds, mammals and reptiles. Details of each list (i.e.
53
number of host species, number of parasite species, number of host-parasite records) are provided in
54
Table 1. The relationship between number of sampled hosts and number of retrieved parasites was
55
modelled for each list by reiterating 1000 times a very simple two-step procedure that consisted of (i)
56
selecting a random number of host species from the complete list, and (ii) comparing the number of
57
randomly selected host species with the overall number of all the (different) parasite species found on
58
those hosts (see Fig. 1). To empirically model the observed relationships, we used several models
59
commonly used for species accumulation curves such as the Clench, exponential, logarithm and power
60
functions (e.g. Thompson et al., 2003; Díaz-Francés and Soberón, 2005). For all lists, the relationship
61
between the number of sampled host species and the corresponding number of retrieved parasite
62
species was best modelled by a decelerating power function (R2 > 0.9 in all cases except two; see Table
63
1 and Fig. 2 as an example). In addition, for each one of the 21 complete lists, we computed the
64
average number of parasite per host (Pn), and the average number of hosts used by a parasite (Hr).
65
The power function is not asymptotic but it is used here only for extrapolation within the known value
66
of the independent variable (number of host species). From a purely theoretical point of view, the
67
consistency of the power law relationship (with an exponent
136
82,000). The consistency in the shape of the relationships modelled for the different host and parasite
137
taxa suggests that the method proposed here is not much affected by unequal sampling, and that the
138
obtained results may be representative of a very general pattern. However, we would like to emphasize
139
that our purpose here is not to replace current estimates of parasite biodiversity, but to promote the
140
debate on a fundamental issue that, in our opinion, is far from being closed.
7
141 142
Acknowledgments We are very grateful to Kevin D. Lafferty for his suggestions on a very early version of the
143
manuscript. We thank two anonymous referees for their comments on the paper. The views expressed
144
are purely those of the writers and may not in any circumstances be regarded as stating an official
145
position of the European Commission.
146 147 148
8
149
References
150
Brown, J.H., Gupta, V.K., Li, B.L., Milne, B.T., Restrepo, C., West, G.B. 2002. The fractal nature of
151
nature: power laws, ecological complexity and biodiversity. Philos. Trans. R. Soc. B 357, 619–
152
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),
162
Biological Diversity: Frontiers In Measurement And Assessment. Oxford University Press,
163
Oxford, pp. 39-54.
164 165
International Union for Conservation of Nature . 2012. The IUCN Red List of Threatened Species. www.iucnredlist.org Version 2012.2.
166
Kuris, A.M., Hechinger, R.F., Shaw, J.C., Whitney, K.L., Aguirre-Macedo, L., Boch, C.A., Dobson,
167
A.P., Dunham, E.J., Fredensborg, B.L., Huspeni, T.C., Lorda, J., Mababa, L., Mancini, F.T.,
168
Mora, A.B., Pickering, M., Talhouk, N.L., Torchin, M.E., Lafferty, K.D. 2008. Ecosystem
169
energetic implications of parasite and free-living biomass in three estuaries. Nature 454, 515–
170
518.
171 172
Lafferty, K.D., Dobson, A.P., Kuris, A.M. 2006. Parasites dominate food web links. Proc. Natl. Acad. Sci. USA 103, 11211–11216. 9
173
Poulin, R., Morand, S. 2004. Parasite biodiversity. Smithsonian Institution Press, Washington, DC.
174
Poulin, R. 2007. Evolutionary Ecology of Parasites (2nd Edition). Princeton University Press,
175 176 177 178 179 180 181 182 183 184 185 186
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
187
species accumulation curves; inventories of small reptiles by pit-trapping in Western Australia.
188
Austral Ecol. 28, 361–383.
189
Windsor, D.A. 1995. Equal rights for parasites. Conserv. Biol. 9, 1–2.
190
10
191 192
Figure legends
193 194
Fig. 1. Diagrammatic illustration of the procedure to model the relationship between the number of
195
sampled host species and the number of retrieved parasite species. (A) represents a hypothetical
196
complete host-parasite list, including five host species (i.e. the fish silhouettes) and six parasite species
197
(P1-6). At each step (B-F) a host species is sampled for parasites and the overall numbers of sampled
198
host species (Sh) and retrieved parasite species (Sp) are plotted on graph to build an accumulation
199
curve.
200 201
Fig. 2. Relationship between number of examined host species and the number of retrieved parasite
202
species for fish acanthocephalans. Data were retrieved from FishPEST (Strona and Lafferty, 2012a,b;
203
Strona et al., 2013). Circles indicate the values obtained by randomly extracting host species from the
204
database. Continuous line indicates the power law regression line that best approximates these values (y
205
= 10.709x 0.570; R2 = 0.992; non-linear least-squares regression with Levenberg-Marquardt algorithm).
206
Dotted line indicates the linear relationship estimated using the Pn/Hr ratio (y = 0.519 x).
11
207
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
12
208
Sp, number of parasite species; Sh, number of host species; Sh_IUCN, estimated number of described
209
species according to International Union for Conservation of Nature (2012); RN, number of host-
210
parasite records; R2, goodness of fit of the power law function that best modeled the relationship
211
between the number of sampled hosts and the number of retrieved parasites; Pred1, global number of
212
parasite species predicted by the traditional approach; Pred2, global number of parasite species
213
predicted by our resampling procedure.
13
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
2
C
Sh
6 5 4 Sp 3 2 1 1
2
Sh
3
4
1
A
4 Sp 3 2 1 1
2 1
E
P1 P2 P3 P4 P5
P1 P2 P3 P4 P5 P6
B
Sh
5 4 Sp 3 2 1 1
2
1
2
Sh
3
D
6 5 4 Sp 3 2 1 Sh
3
4
5
F
Figure 2
Number of retrived parasite species
900 800 700 600 500 400 300 200 100 0 0
500
1000
1500
Number of sampled host species
2000
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
