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Phenological and intrinsic predictors of mite and haemacoccidian infection dynamics in a Mediterranean community of lizards

Published online by Cambridge University Press:  03 June 2021

Robby M. Drechsler*
Affiliation:
Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, c/ Catedrático José Beltrán Martínez 2, E-46980 Paterna, Valencia, Spain
Josabel Belliure
Affiliation:
Department of Life Sciences, Global Change Ecology and Evolution Group (GLOCEE), Universidad de Alcalá (UAH), E-28805, Alcalá de Henares, Madrid, Spain
Rodrigo Megía-Palma
Affiliation:
Department of Biomedicine and Biotechnology, Universidad de Alcalá (UAH), Parasitology Area, Campus Universitario, E-28805, Alcalá de Henares, Madrid, Spain CIBIO-InBIO: Research Center in Biodiversity and Genetic Resources, University of Porto, P-4485-661, Vairão, Portugal
*
Author for correspondence: Robby M. Drechsler, E-mail: robbymar@uv.es

Abstract

Ectotherms are vulnerable to environmental changes and their parasites are biological health indicators. Thus, parasite load in ectotherms is expected to show a marked phenology. This study investigates temporal host–parasite dynamics in a lizard community in Eastern Spain during an entire annual activity period. The hosts investigated were Acanthodactylus erythrurus, Psammodromus algirus and Psammodromus edwardsianus, three lizard species coexisting in a mixed habitat of forests and dunes, providing a range of body sizes, ecological requirements and life history traits. Habitat and climate were considered as potential environmental predictors of parasite abundance, while size, body condition and sex as intrinsic predictors. Linear models based on robust estimates were fitted to analyse parasite abundance and prevalence. Ectoparasitic mites and blood parasites from two haemococcidian genera were found: Lankesterella spp. and Schellackia spp. Habitat type was the only predictor explaining the abundance of all parasites, being mostly higher in the forest than in the dunes. The results suggest that particularities in each host–parasite relationship should be accounted even when parasites infect close-related hosts under the same environmental pressures. They also support that lizard parasites can be biomarkers of environmental perturbation, but the relationships need to be carefully interpreted for each host–parasite assemblage.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press
Figure 0

Table 1. Mean ± s.e. of lizard body condition (×100) of each species in both considered habitat types, with the corresponding sample size (n, in lizards) and the results of the statistical analysis in each case

Figure 1

Fig. 1. Representation of the seasonal variation of infection parameters of each parasite (A: mites, B: Lankesterella spp. and C: Schellackia spp.) and each host species: A. erythrurus (solid line), P. algirus (dotted line) and P. edwardsianus (dashed line). From left to right: the prevalence, expressed as a percentage of infected individuals; the comparison between species of mean ± s.e. of infection abundance and the comparison between males (black) and females (gray) of mean ± s.e. infection abundance.

Figure 2

Fig. 2. Distribution of infected individuals among the snout-vent length (SVL) range of each host species: mites (A), Lankesterella spp. (B), and Schellackia spp. (C).

Figure 3

Table 2. Mean ± s.e. infection abundance of each parasite and prevalence (in brackets) for each host species

Figure 4

Table 3. Results of the general linear models for the parasite prevalence of the different parasites: residual deviance (Dev), residual degrees of freedom (d.f.) and F and P statistics

Figure 5

Fig. 3. Mean ± SE of the abundance of mites (A), Lankesterella spp. (B) and Schellackia spp. (C) in both habitats for each host species: A. erythrurus (black), P. algirus (dark grey) and P. edwardsianus (light grey). Significant differences between habitats are indicated by asteriscs.

Figure 6

Table 4. Robust estimates of parasite abundance for the different parasites: estimate (Est), standard error (s.e.) and z and P statistics

Figure 7

Fig. 4. Correlation of parasite abundance (A: mites, B: Lankesterella spp. and C: Schellackia spp.) with snout-vent length (SVL) for each host species: A. erythrurus (black), P. algirus (dark grey) and P. edwardsianus (light grey). Line of best fit included to show relationship.

Figure 8

Table 5. Robust estimates and general linear models showing the effect of host gravidity status on parasite abundance and prevalence: estimate (Est), standard error (s.e.), residual deviance (Dev), residual degrees of freedom (d.f.) and z, F and P statistics

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