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Parasite responses to large mammal loss in an African savanna
Author(s) -
Weinstein Sara,
Titcomb Georgia,
Agwanda Bernard,
Riginos Corinna,
Young Hillary
Publication year - 2017
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1002/ecy.1858
Subject(s) - wildlife , biology , mammal , abiotic component , biodiversity , ecology , rodent , herbivore , competition (biology) , population , sociology , demography
Abstract Biodiversity loss can alter disease transmission; however, the magnitude and direction of these effects vary widely across ecosystems, scales, and pathogens. Here we experimentally examine the effects of one of the most globally pervasive patterns of biodiversity decline, the selective loss of large wildlife, on infection probability, intensity and population size of a group of common rodent‐borne parasites – macroparasitic helminths. Consistent with previous work on vector‐borne pathogens, we found that large wildlife removal causes strong and systematic increases of rodent‐borne parasites, largely due to increases in rodent density, as rodents are released from competition with larger herbivores. Although we predicted that increased host density would also increase per capita infection among all directly transmitted parasites, this additional amplification occurred for only two of three examined parasites. Furthermore, the actual effects of large mammal loss on per capita infection were mediated by the complex suite of abiotic and biotic factors that regulate parasite transmission. Thus, while these results strongly suggest that large wildlife loss will cause systematic increases in rodent parasite populations, they also underscore the difficulty of making more specific predictions for a given parasite based on simple attributes such as transmission mode or life history strategy. Instead, detailed information on the ecology of each parasite species would be necessary to make more accurate predictions of how biodiversity loss will affect infection.

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