Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma
Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host popu...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Blanchet, Simon [verfasserIn] Méjean, Lionel [verfasserIn] Bourque, Jean-François [verfasserIn] Lek, Sovan [verfasserIn] Thomas, Frédéric [verfasserIn] Marcogliese, David J. [verfasserIn] Dodson, Julian J. [verfasserIn] Loot, Géraldine [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2009 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Oecologia - Berlin : Springer, 1968, 160(2009), 1 vom: 03. Feb. |
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| Übergeordnetes Werk: |
volume:160 ; year:2009 ; number:1 ; day:03 ; month:02 |
| Links: |
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| DOI / URN: |
10.1007/s00442-008-1272-y |
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| Katalog-ID: |
SPR006075134 |
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| 100 | 1 | |a Blanchet, Simon |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma |
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| 520 | |a Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. | ||
| 650 | 4 | |a Causal links |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Pathogenic effects |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Reciprocal effects |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Growth rate |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Parasite |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Behavior |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Path analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Model selection |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Susceptibility |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Méjean, Lionel |e verfasserin |4 aut | |
| 700 | 1 | |a Bourque, Jean-François |e verfasserin |4 aut | |
| 700 | 1 | |a Lek, Sovan |e verfasserin |4 aut | |
| 700 | 1 | |a Thomas, Frédéric |e verfasserin |4 aut | |
| 700 | 1 | |a Marcogliese, David J. |e verfasserin |4 aut | |
| 700 | 1 | |a Dodson, Julian J. |e verfasserin |4 aut | |
| 700 | 1 | |a Loot, Géraldine |e verfasserin |4 aut | |
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10.1007/s00442-008-1272-y doi (DE-627)SPR006075134 (SPR)s00442-008-1272-y-e DE-627 ger DE-627 rakwb eng 590 333.7 ASE 42.90 bkl Blanchet, Simon verfasserin aut Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 Méjean, Lionel verfasserin aut Bourque, Jean-François verfasserin aut Lek, Sovan verfasserin aut Thomas, Frédéric verfasserin aut Marcogliese, David J. verfasserin aut Dodson, Julian J. verfasserin aut Loot, Géraldine verfasserin aut Enthalten in Oecologia Berlin : Springer, 1968 160(2009), 1 vom: 03. Feb. (DE-627)25462975X (DE-600)1462019-4 1432-1939 nnns volume:160 year:2009 number:1 day:03 month:02 https://dx.doi.org/10.1007/s00442-008-1272-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 42.90 ASE AR 160 2009 1 03 02 |
| spelling |
10.1007/s00442-008-1272-y doi (DE-627)SPR006075134 (SPR)s00442-008-1272-y-e DE-627 ger DE-627 rakwb eng 590 333.7 ASE 42.90 bkl Blanchet, Simon verfasserin aut Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 Méjean, Lionel verfasserin aut Bourque, Jean-François verfasserin aut Lek, Sovan verfasserin aut Thomas, Frédéric verfasserin aut Marcogliese, David J. verfasserin aut Dodson, Julian J. verfasserin aut Loot, Géraldine verfasserin aut Enthalten in Oecologia Berlin : Springer, 1968 160(2009), 1 vom: 03. Feb. (DE-627)25462975X (DE-600)1462019-4 1432-1939 nnns volume:160 year:2009 number:1 day:03 month:02 https://dx.doi.org/10.1007/s00442-008-1272-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 42.90 ASE AR 160 2009 1 03 02 |
| allfields_unstemmed |
10.1007/s00442-008-1272-y doi (DE-627)SPR006075134 (SPR)s00442-008-1272-y-e DE-627 ger DE-627 rakwb eng 590 333.7 ASE 42.90 bkl Blanchet, Simon verfasserin aut Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 Méjean, Lionel verfasserin aut Bourque, Jean-François verfasserin aut Lek, Sovan verfasserin aut Thomas, Frédéric verfasserin aut Marcogliese, David J. verfasserin aut Dodson, Julian J. verfasserin aut Loot, Géraldine verfasserin aut Enthalten in Oecologia Berlin : Springer, 1968 160(2009), 1 vom: 03. Feb. (DE-627)25462975X (DE-600)1462019-4 1432-1939 nnns volume:160 year:2009 number:1 day:03 month:02 https://dx.doi.org/10.1007/s00442-008-1272-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 42.90 ASE AR 160 2009 1 03 02 |
| allfieldsGer |
10.1007/s00442-008-1272-y doi (DE-627)SPR006075134 (SPR)s00442-008-1272-y-e DE-627 ger DE-627 rakwb eng 590 333.7 ASE 42.90 bkl Blanchet, Simon verfasserin aut Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 Méjean, Lionel verfasserin aut Bourque, Jean-François verfasserin aut Lek, Sovan verfasserin aut Thomas, Frédéric verfasserin aut Marcogliese, David J. verfasserin aut Dodson, Julian J. verfasserin aut Loot, Géraldine verfasserin aut Enthalten in Oecologia Berlin : Springer, 1968 160(2009), 1 vom: 03. Feb. (DE-627)25462975X (DE-600)1462019-4 1432-1939 nnns volume:160 year:2009 number:1 day:03 month:02 https://dx.doi.org/10.1007/s00442-008-1272-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 42.90 ASE AR 160 2009 1 03 02 |
| allfieldsSound |
10.1007/s00442-008-1272-y doi (DE-627)SPR006075134 (SPR)s00442-008-1272-y-e DE-627 ger DE-627 rakwb eng 590 333.7 ASE 42.90 bkl Blanchet, Simon verfasserin aut Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma 2009 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 Méjean, Lionel verfasserin aut Bourque, Jean-François verfasserin aut Lek, Sovan verfasserin aut Thomas, Frédéric verfasserin aut Marcogliese, David J. verfasserin aut Dodson, Julian J. verfasserin aut Loot, Géraldine verfasserin aut Enthalten in Oecologia Berlin : Springer, 1968 160(2009), 1 vom: 03. Feb. (DE-627)25462975X (DE-600)1462019-4 1432-1939 nnns volume:160 year:2009 number:1 day:03 month:02 https://dx.doi.org/10.1007/s00442-008-1272-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_374 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_2939 GBV_ILN_2946 GBV_ILN_2949 GBV_ILN_2951 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4346 GBV_ILN_4393 GBV_ILN_4700 42.90 ASE AR 160 2009 1 03 02 |
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Enthalten in Oecologia 160(2009), 1 vom: 03. Feb. volume:160 year:2009 number:1 day:03 month:02 |
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Causal links Pathogenic effects Reciprocal effects Growth rate Parasite Behavior Path analysis Model selection Susceptibility |
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Blanchet, Simon @@aut@@ Méjean, Lionel @@aut@@ Bourque, Jean-François @@aut@@ Lek, Sovan @@aut@@ Thomas, Frédéric @@aut@@ Marcogliese, David J. @@aut@@ Dodson, Julian J. @@aut@@ Loot, Géraldine @@aut@@ |
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Blanchet, Simon |
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590 333.7 ASE 42.90 bkl Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma Causal links (dpeaa)DE-He213 Pathogenic effects (dpeaa)DE-He213 Reciprocal effects (dpeaa)DE-He213 Growth rate (dpeaa)DE-He213 Parasite (dpeaa)DE-He213 Behavior (dpeaa)DE-He213 Path analysis (dpeaa)DE-He213 Model selection (dpeaa)DE-He213 Susceptibility (dpeaa)DE-He213 |
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Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma |
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Blanchet, Simon Méjean, Lionel Bourque, Jean-François Lek, Sovan Thomas, Frédéric Marcogliese, David J. Dodson, Julian J. Loot, Géraldine |
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why do parasitized hosts look different? resolving the “chicken-egg” dilemma |
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Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma |
| abstract |
Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. |
| abstractGer |
Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. |
| abstract_unstemmed |
Abstract Phenotypic differences between infected and non-infected hosts are often assumed to be the consequence of parasite infection. However, pre-existing differences in hosts’ phenotypes may promote differential susceptibility to infection. The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. Disentangling the causality of host–parasite interactions should contribute substantially to evaluating the role of parasites in ecological and evolutionary processes. |
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Why do parasitized hosts look different? Resolving the “chicken-egg” dilemma |
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Méjean, Lionel Bourque, Jean-François Lek, Sovan Thomas, Frédéric Marcogliese, David J. Dodson, Julian J. Loot, Géraldine |
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Méjean, Lionel Bourque, Jean-François Lek, Sovan Thomas, Frédéric Marcogliese, David J. Dodson, Julian J. Loot, Géraldine |
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25462975X |
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| doi_str |
10.1007/s00442-008-1272-y |
| up_date |
2024-07-03T20:40:23.648Z |
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1803591848978022400 |
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The phenotypic variability observed within the host population may therefore be a cause rather than a consequence of infection. In this study, we aimed at disentangling the causes and the consequences of parasite infection by calculating the value of a phenotypic trait (i.e., the growth rate) of the hosts both before and after infection occurred. That procedure was applied to two natural systems of host–parasite interactions. In the first system, the infection level of an ectoparasite (Tracheliastes polycolpus) decreases the growth rate of its fish host (the rostrum dace, Leuciscus leuciscus). Reciprocally, this same phenotypic trait before infection modulated the future level of host sensitivity to the direct pathogenic effect of the parasite, namely the level of fin degradation. In the second model, causes and consequences linked the growth rate of the fish host (the rainbow smelt, Osmerus mordax) and the level of endoparasite infection (Proteocephalus tetrastomus). Indeed, the host’s growth rate before infection determined the number of parasites later in life, and the parasite biovolume then decreased the host’s growth rate of heavily infected hosts. We demonstrated that reciprocal effects between host phenotypes and parasite infection can occur simultaneously in the wild, and that the observed variation in the host phenotype population was not necessarily a consequence of parasite infection. 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