The drivers of avian‐haemosporidian prevalence in tropical lowland forests of New Guinea in three dimensions

Abstract

Haemosporidians are among the most common parasites of birds and often negatively impact host fitness. A multitude of biotic and abiotic factors influence these associations, but the magnitude of these factors can differ by spatial scales (i.e., local, regional and global). Consequently, to better understand global and regional drivers of avian-haemosporidian associations, it is key to investigate these associations at smaller (local) spatial scales. Thus, here, we explore the effect of abiotic variables (e.g., temperature, forest structure, and anthropogenic disturbances) on haemosporidian prevalence and host-parasite networks on a horizontal spatial scale, comparing four fragmented forests and five localities within a continuous forest in Papua New Guinea. Additionally, we investigate if prevalence and host-parasite networks differ between the canopy and the understory (vertical stratification) in one forest patch. We found that the majority of Haemosporidian infections were caused by the genus Haemoproteus and that avian-haemosporidian networks were more specialized in continuous forests. At the community level, only forest greenness was negatively associated with Haemoproteus infections, while the effects of abiotic variables on parasite prevalence differed between bird species. Haemoproteus prevalence levels were significantly higher in the canopy, and an opposite trend was observed for Plasmodium. This implies that birds experience distinct parasite pressures depending on the stratum they inhabit, likely driven by vector community differences. These three-dimensional spatial analyses of avian-haemosporidians at horizontal and vertical scales suggest that the effect of abiotic variables on haemosporidian infections are species specific, so that factors influencing community-level infections are primarily driven by host community composition.

Host phylogeny and elevation predict infection by avian haemosporidians in a diverse New Guinean bird community

“…79% in Malawi; Lutz et al, 2015). The dominance of Haemoproteus and near absence of Plasmodium and Leucocytozoon are unusual in comparison to other tropical avian haemosporidian communities (Fecchio et al, 2021), but consistent with other recent studies examining avian haemosporidian communities in New Guinea (Amaya‐Mejia et al, 2022; Bodawatta et al, 2020; Vinagre‐Izquierdo et al, 2022). Thus, accumulating evidence documents that the avian haemosporidian communities of New Guinea are—like the avian communities of the island—quite different from those of other regions, including other diverse tropical regions.…”

“…., 2020;Vinagre-Izquierdo et al, 2022). Thus, accumulating evidence documents that the avian haemosporidian communities of New Guinea are-like the avian communities of the island-quite different from those of other regions, including other diverse tropical regions.…”

Remotely sensed localised primary production anomalies predict the burden and community structure of infection in long‐term rodent datasets

“…Many previous studies have found that environmental variables, including those measured through remote sensing, may predict infectious agent populations or communities (Blersch et al, 2021; Carlson et al, 2022; Clark et al, 2020; Fecchio et al, 2020; Froeschke et al, 2010; King'ori et al, 2020; Kosoy & Biggins, 2022; Krasnov et al, 2010, 2021; Pauling et al, 2021; Shearer & Ezenwa, 2020; Vinagre‐Izquierdo et al, 2022) or zoonotic infection risk (Carlson et al, 2022; Glass et al, 2000, 2002; Parmenter et al, 1999; Pauling et al, 2021; Redding et al, 2021). However, where these have focussed on vegetation predictors, or their correlates, in most cases between‐locality variation or within‐year variation has been studied, which may have limitations.…”

“…EVI, enhanced vegetation index; TAI, total abundance index. Shearer & Ezenwa, 2020;Vinagre-Izquierdo et al, 2022) or zoonotic infection risk (Carlson et al, 2022;Glass et al, 2000Glass et al, , 2002Parmenter et al, 1999;Pauling et al, 2021;Redding et al, 2021).…”

Examining paleobotanical databases: Revisiting trends in angiosperm folivory and unlocking the paleoecological promise of propensity score matching and specification curve analysis

“…A recent study that examined ten bipartite network metrics included a separate biological justification for each (Valido et al, 2019). H 2 ′ is typically the only bipartite network metric used to evaluate specialization (Bucharova et al, 2022;da Silva Goldas et al, 2022;Vinagre-Izquierdo et al, 2022;Virgo et al, 2022). Whereas it is indeed the case that most bipartite network metrics are related to the concept of specialization (Fründ et al, 2016), the decision in the original study to calculate a plethora of metrics for the sake of quantifying the very same phenomenon (specialization) is far from accepted practice in ecology.…”