Biology subjects

Piggott, J. J.

Publications and source records attributed to Piggott, J. J..

5 recordsLinked to original sources

bioRxiv2026

Beyond Environmental Matching: Maternal Effects Depend on Offspring Environmental Complexity and Fitness Traits

The consequences of maternal effects for offspring fitness can depend on the environmental conditions offspring encounter and the fitness traits considered. We used a transgenerational experiment in Daphnia magna to test how maternal exposure to warming and elevated salinity influenced offspring survival, reproduction and body size across matching, mismatching and multiple-stressor environments. Maternal exposure to salinity enhanced offspring survival under matching salinity, and benefits extended to mismatching environments. In contrast, maternal exposure to warming provided no survival benefit under matching warming and reduced survival in mismatching environments, while accelerating reproduction across contexts. Multiple-stressor conditions revealed pronounced maternal effects, while contrasting responses across survival, reproduction and body size showed that benefits to one fitness trait did not extend to others. Our findings demonstrate that environmental matching alone is insufficient to predict maternal effects, whose consequences depend on offspring environmental complexity and the fitness trait considered.

ecology↗

bioRxiv2026

Feeding the host reshapes virulence: nonlinear scaling in a microsporidian pathogen.

Resource availability is a central driver of ecological and evolutionary processes, yet its effects on infectious disease and virulence are not fully understood. A key limitation is that many studies consider only a narrow range of resource conditions or a limited subset of host and pathogen traits, potentially obscuring non-linear relationships. Here, we quantify how a gradient of six food levels simultaneously shapes host fitness and pathogen performance in the Daphnia magna- Ordospora colligata system. Across two laboratory experiments, we measured infection rates, pathogen burden, host fecundity, survival, and filtration rates. Increased food availability enhanced pathogen fitness, with both infection rates and spore burden increasing with provisioning. In contrast, host responses were trait-specific: while fecundity increased with food availability, pathogen-induced reductions in fecundity (i.e., virulence) peaked at intermediate resource levels, despite continued increases in pathogen load. This pattern indicates that resource availability alters host tolerance as well as pathogen growth, generating non-linear disease outcomes. Host survival was unaffected by either food provisioning or infection, further demonstrating that resource availability can simultaneously influence host and pathogen traits in different directions. Our results highlight the importance of integrating multiple fitness components across provisioning levels to understand disease dynamics and suggest that ongoing anthropogenic changes in resource availability may alter host-pathogen interactions.

zoology↗

bioRxiv2026

The duration and predictability of heatwaves shape host-parasite interactions under thermal stress

Anthropogenic climate change is expected to increase not only mean temperatures but also the magnitude and pattern of thermal variability, including the frequency, duration, and predictability of extreme events. While the effects of elevated mean temperatures on disease dynamics are well studied, far less is known about how different patterns of temperature variability shape host-parasite interactions, despite clear theoretical predictions from the climate variability hypothesis. Here, we used a controlled experimental system (Daphnia magna and two microsporidian parasites, Ordospora colligata and Hamiltosporidium tvaerminnensis) to disentangle the effects of thermal variability structure from mean temperature. Across two experiments, we exposed hosts to cyclic (predictable) and random (unpredictable) heatwaves under both non-stressful and stressful mean temperature regimes. Contrary to predictions from the climate variability hypothesis, temperature variability did not uniformly increase infection risk. Instead, infection outcomes depended on the interaction between mean temperature, duration of the heatwaves, the pattern of thermal variation, and parasite identity. Under non-stressful mean temperatures, thermal variability had negligible effects on infection. In contrast, under stressful mean temperatures, parasites responded in distinct ways: H. tvaerminnensis infection was sensitive to the predictability of heat events, whereas O. colligata responded primarily to heatwave duration. These results demonstrate that climatic variability can differentially alter host-parasite interactions rather than exerting consistent directional effects on disease. By showing that parasite-specific sensitivities to the pattern of thermal variation emerge under thermal stress, our study highlights a mechanism by which increasing climatic variability may reshape parasite communities and disease outcomes in a warming world.

ecology↗

bioRxiv2022

Stressor interactions at the community level: explaining qualitative mismatches between observations

Perturbations such as climate change, invasive species and pollution, impact the functioning and diversity of ecosystems. But because there is no unique way to measure functioning and diversity, this leads to a ubiquitous and overwhelming variability in community-level responses, that is often seen as a barrier to prediction in ecology. Here, we show that this variability can instead provide insights into hidden features of a communitys functions and responses to perturbations. By first analysing a dataset of global change experiments in microbial soil systems we show that variability of functional and diversity responses to a given perturbation is not random: aggregate properties that are thought to be mechanistically similar tend to respond similarly. We then formalise this intuitive observation to demonstrate that the variability of community-level responses to perturbations is not only predictable, but that it can also be used to access hidden and useful information about population-level responses to perturbations (i.e., response diversity and scaling by species biomass). Our theory offers a baseline expectation for the variability of community-level responses to perturbations and helps to explain the complexity of ecological responses to global change. Significance StatementMeasures of biodiversity and ecosystem functioning show highly variable responses to a given perturbation. This variability is traditionally thought of as reflecting our inability to predict ecological responses to global change. Our work, however, finds that variability of community-level responses is itself predictable and can even be used to gain insights about how species respond to perturbations and collectively contribute to ecosystem functions.

ecology↗

bioRxiv2020

Why scaling up uncertain predictions to higher levels of organisation will underestimate change

AO_SCPLOWBSTRACTC_SCPLOWUncertainty is an irreducible part of predictive science, causing us to over- or underestimate the magnitude of change that a system of interest will face. In a reductionist approach, we may use predictions at the level of individual system components (e.g. species biomass), and combine them to generate predictions for system-level properties (e.g. ecosystem function). Here we show that this process of scaling up uncertain predictions to higher levels of organization has a surprising consequence: it will systematically underestimate the magnitude of system-level change, an effect whose significance grows with the systems dimensionality. This stems from a geometrical observation: in high dimensions there are more ways to be more different, than ways to be more similar. This general remark applies to any complex system. Here we will focus on ecosystems thus, on ecosystem-level predictions generated from the combination of predictions at the species-level. In this setting, the ecosystems dimensionality is a measure of its diversity. We explain why dimensional effects do not play out when predicting change of a single linear aggregate property (e.g. total biomass), yet are revealed when predicting change of non-linear properties (e.g. absolute biomass change, stability or diversity), and when several properties are considered at once to describe the ecosystem, as in multi-functional ecology. Our findings highlight and describe the counter-intuitive effects of scaling up uncertain predictions, effects that will occur in any field of science where a reductionist approach is used to generate predictions.

ecology↗