Acclimation to warmer temperatures can protect host populations from both further heat stress and the potential invasion of pathogens

Thermal acclimation can provide an essential buffer against heat stress for host populations, while acting simultaneously on various life‐history traits that determine population growth. In turn, the ability of a pathogen to invade a host population is intimately linked to these changes via the supply of new susceptible hosts, as well as the impact of warming on its immediate infection dynamics. Acclimation therefore has consequences for hosts and pathogens that extend beyond simply coping with heat stress—governing both population growth trajectories and, as a result, an inherent propensity for a disease outbreak to occur. The impact of thermal acclimation on heat tolerances, however, is rarely considered simultaneously with metrics of both host and pathogen population growth, and ultimately fitness. Using the host Daphnia magna and its bacterial pathogen, we investigated how thermal acclimation impacts host and pathogen performance at both the individual and population scales. We first tested the effect of maternal and direct thermal acclimation on the life‐history traits of infected and uninfected individuals, such as heat tolerance, fecundity, and lifespan, as well as pathogen infection success and spore production. We then predicted the effects of each acclimation treatment on rates of host and pathogen population increase by deriving a host's intrinsic growth rate (r m ) and a pathogen's basic reproductive number (R0). We found that direct acclimation to warming enhanced a host's heat tolerance and rate of population growth, despite a decline in life‐history traits such as lifetime fecundity and lifespan. In contrast, pathogen performance was consistently worse under warming, with within‐host pathogen success, and ultimately the potential for disease spread, severely hampered at higher temperatures. Our results suggest that hosts could benefit more from warming than their pathogens, but only by linking multiple individual traits to population processes can the full impact of higher temperatures on host and pathogen population dynamics be realised

Resources, key traits and the size of fungal epidemics in Daphnia populations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111939/1/jane12363.pd

Temperature Drives Epidemics in a Zooplankton-Fungus Disease System: A Trait-Driven Approach Points to Transmission via Host Foraging

Climatic warming will likely have idiosyncratic impacts on infectious diseases, causing some to increase while others decrease or shift geographically. A mechanistic framework could better predict these different temperature-disease outcomes. However, such a framework remains challenging to develop, due to the nonlinear and (sometimes) opposing thermal responses of different host and parasite traits and due to the difficulty of validating model predictions with observations and experiments. We address these challenges in a zooplanktonfungus (Daphnia dentifera–Metschnikowia bicuspidata) system. We test the hypothesis that warmer temperatures promote disease spread and produce larger epidemics. In lakes, epidemics that start earlier and warmer in autumn grow much larger. In a mesocosm experiment, warmer temperatures produced larger epidemics. A mechanistic model parameterized with trait assays revealed that this pattern arose primarily from the temperature dependence of transmission rate (b), governed by the increasing foraging (and, hence, parasite exposure) rate of hosts ( f ). In the trait assays, parasite production seemed sufficiently responsive to shape epidemics as well; however, this trait proved too thermally insensitive in the mesocosm experiment and lake survey to matter much. Thus, in warmer environments, increased foraging of hosts raised transmission rate, yielding bigger epidemics through a potentially general, exposure-based mechanism for ectotherms. This mechanistic approach highlights how a trait-based framework will enhance predictive insight into responses of infectious disease to a warmer world

Habitat, predators, and hosts regulate disease in Daphnia through direct and indirect pathways

Community ecology can link habitat to disease via interactions among habitat, focal hosts, other hosts, their parasites, and predators. However, complicated food web interactions (i.e., trophic interactions among predators and their impacts on host density and diversity) often obscure the important pathways regulating disease. Here, we disentangle community drivers in a case study of planktonic disease, using a two‐step approach. In step one, we tested univariate field patterns linking community interactions directly to two disease metrics. Density of focal hosts (Daphnia dentifera) was related to density but not prevalence of fungal (Metschnikowia bicuspidata) infections. Both disease metrics appeared to be driven by selective predators that cull infected hosts (fish, e.g., Lepomis macrochirus), sloppy predators that spread parasites while feeding (midges, Chaoborus punctipennis), and spore predators that reduce contact between focal hosts and parasites (other zooplankton, especially small‐bodied Ceriodaphnia sp.). Host diversity also negatively correlated with disease, suggesting a dilution effect. However, several of these univariate patterns were initially misleading, due to confounding ecological links among habitat, predators, host density, and host diversity. In step two, path models uncovered and explained these misleading patterns, and grounded them in habitat structure (refuge size). First, rather than directly reducing infection prevalence, fish predation drove disease indirectly through changes in density of midges and frequency of small spore predators (which became more frequent in lakes with small refuges). Second, small spore predators drove the two disease metrics through fundamentally different pathways: they directly reduced infection prevalence, but indirectly reduced density of infected hosts by lowering density of focal hosts (likely via competition). Third, the univariate diversity–disease pattern (signaling a dilution effect) merely reflected the confounding direct effects of these small spore predators. Diversity per se had no effect on disease, after accounting for the links between small spore predators, diversity, and infection prevalence. In turn, these small spore predators were regulated by both size‐selective fish predation and refuge size. Thus, path models not only explain each of these surprising results, but also trace their origins back to habitat structure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/1/ecm1222_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/2/ecm1222-sup-0001-AppendixS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134436/3/ecm1222.pd

Susceptible host availability modulates climate effects on dengue dynamics

Experiments and models suggest that climate affects mosquito-borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context-dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state-of-the-art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.R35GM133439 - NIH HHS; DBI-1667584 - National Science Foundation; DEB-1655203 - National Science Foundation; 00028335 - Lenfest Foundation; Stanford University: Bing Fellowship in Honor of Paul Ehrlich, Stanford Data Science Scholars program, Lindsay Family E-IPER Fellowship, Illich-Sadowsky Interdisciplinary Graduate Fellowship, Terman Fellowship, King Center for Global Development seed grant; SERDP 15 RC-2509 - U.S. Department of Defense; University of California San Diego: McQuown Chair in Natural Sciences; DBI-1611767 - National Science Foundation; RAPID DEB-1640780 - National Science Foundation; R35GM133439 - NIH HHS; Hellman Foundation: Hellman Faculty Fellowship; Stanford Woods Institute for the Environment: Environmental Ventures Program; DEB-1518681 - National Science Foundation; R35 GM133439 - NIGMS NIH HHS; DEB-2011147 - National Science Foundationhttps://www.biorxiv.org/content/biorxiv/early/2020/10/19/2019.12.20.883363.full.pdfAccepted manuscrip

Thermal biology of mosquito-borne disease

Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species – including globally important diseases like malaria, dengue, and Zika – synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23–29ºC and declining to zero below 9–23ºC and above 32–38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25–26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration

Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18–34°C with maximal transmission occurring in a range from 26–29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones

Fluctuating temperatures have a surprising effect on disease transmission

Theory predicts that temperature fluctuations should reduce performance near an organism's thermal optimum. A new study in PLOS Biology found fluctuations increased parasite transmission instead, highlighting questions about how climate change will impact infectious diseases. [Abstract copyright: Copyright: © 2023 Marta S. Shocket. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Temperature explains broad patterns of Ross River virus transmission across Australia

Thermal biology predicts that vector-borne disease transmission peaks at intermediate temperatures and declines at high and low temperatures. However, thermal optima and limits remain unknown for most vector-borne pathogens. We built a mechanistic model for the thermal response of Ross River virus, an important mosquito-borne pathogen in Australia, Pacific Islands, and potentially at risk of emerging worldwide. Transmission peaks at moderate temperatures (26.4˚C) and declines to zero at thermal limits (17.0 and 31.5˚C). The model accurately predicts that transmission is year-round endemic in the tropics but seasonal in temperate areas, resulting in the nationwide seasonal peak in human cases. Climate warming will likely increase transmission in temperate areas (where most Australians live) but decrease transmission in tropical areas where mean temperatures are already near the thermal optimum. These results illustrate the importance of nonlinear models for inferring the role of temperature in disease dynamics and predicting responses to climate change