Age‐specific impacts of vegetation functional traits on gastrointestinal nematode parasite burdens in a large herbivore

Gastrointestinal nematode (GIN) parasites play an important role in the ecological dynamics of many animal populations. Recent studies suggest that fine-scale spatial variation in GIN infection dynamics is important in wildlife systems, but the environmental drivers underlying this variation remain poorly understood. We used data from over two decades of GIN parasite egg counts, host space use, and spatial vegetation data from a long-term study of Soay sheep on St Kilda to test how spatial autocorrelation and vegetation in an individual's home range predict parasite burden across three age groups. We developed a novel approach to quantify the plant functional traits present in a home range to describe the quality of vegetation present. Effects of vegetation and space varied between age classes. In immature lambs, strongyle parasite faecal egg counts (FEC) were spatially structured, being highest in the north and south of our study area. Independent of host body weight and spatial autocorrelation, plant functional traits predicted parasite egg counts. Higher egg counts were associated with more digestible and preferred plant functional traits, suggesting the association could be driven by host density and habitat preference. In contrast, we found no evidence that parasite FEC were related to plant functional traits in the host home range in yearlings or adult sheep. Adult FEC were spatially structured, with highest burdens in the north-east of our study area, while yearling FEC showed no evidence of spatial structuring. Parasite burdens in immature individuals appear more readily influenced by fine-scale spatial variation in the environment, highlighting the importance of such heterogeneity for our understanding of wildlife epidemiology and health. Our findings support the importance of fine-scale environmental variation for wildlife disease ecology and provides new evidence that such effects may vary across demographic groups within a population

A minimum data standard for vector competence experiments

The growing threat of vector-borne diseases, highlighted by recent epidemics, has prompted increased focus on the fundamental biology of vector-virus interactions. To this end, experiments are often the most reliable way to measure vector competence (the potential for arthropod vectors to transmit certain pathogens). Data from these experiments are critical to understand outbreak risk, but – despite having been collected and reported for a large range of vector-pathogen combinations – terminology is inconsistent, records are scattered across studies, and the accompanying publications often share data with insufficient detail for reuse or synthesis. Here, we present a minimum data and metadata standard for reporting the results of vector competence experiments. Our reporting checklist strikes a balance between completeness and labor-intensiveness, with the goal of making these important experimental data easier to find and reuse in the future, without much added effort for the scientists generating the data. To illustrate the standard, we provide an example that reproduces results from a study of Aedes aegypti vector competence for Zika virus

Host resources and parasite traits interact to determine the optimal combination of host parasite‐mitigation strategies

Organisms have evolved diverse strategies to manage parasite infections. Broadly, hosts may avoid infection by altering behaviour, resist infection by targeting parasites or tolerate infection by repairing associated damage. The effectiveness of a strategy depends on interactions between, for example, resource availability, parasite traits (virulence, life‐history) and the host itself (nutritional status, immunopathology). To understand how these factors shape host parasite‐mitigation strategies, we developed a mathematical model of within‐host, parasite‐immune dynamics in the context of helminth infections. The model incorporated host nutrition and resource allocation to different mechanisms of immune response: larval parasite prevention; adult parasite clearance; damage repair (tolerance). We also considered a non‐immune strategy: avoidance via anorexia, reducing intake of infective stages. Resources not allocated to immune processes promoted host condition, whereas harm due to parasites and immunopathology diminished it. Maximising condition (a proxy for fitness), we determined optimal host investment for each parasite‐mitigation strategy, singly and combined, across different environmental resource levels and parasite trait values. Which strategy was optimal varied with scenario. Tolerance generally performed well, especially with high resources. Success of the different resistance strategies (larval prevention or adult clearance) tracked relative virulence of larval and adult parasites: slowly maturing, highly damaging larvae favoured prevention; rapidly maturing, less harmful larvae favoured clearance. Anorexia was viable only in the short term, due to reduced host nutrition. Combined strategies always outperformed any lone strategy: these were dominated by tolerance, with some investment in resistance.Choice of parasite mitigation strategy has profound consequences for hosts, impacting their condition, survival and reproductive success. We show that the efficacy of different strategies is highly dependent on timescale, parasite traits and resource availability. Models that integrate such factors can inform the collection and interpretation of empirical data, to understand how those drivers interact to shape host immune responses in natural systems

Long-term temporal trends in gastrointestinal parasite infection in wild Soay sheep

Monitoring the prevalence and abundance of parasites over time is important for addressing their potential impact on host life histories, immunological profiles and their influence as a selective force. Only long-term ecological studies have the potential to shed light on both the temporal trends in infection prevalence and abundance and the drivers of such trends, because of their ability to dissect drivers that may be confounded over shorter time scales. Despite this, only a relatively small number of such studies exist. Here, we analysed changes in the prevalence and abundance of gastrointestinal parasites in the wild Soay sheep population of St. Kilda across 31 years. The host population density (PD) has increased across the study, and PD is known to increase parasite transmission, but we found that PD and year explained temporal variation in parasite prevalence and abundance independently. Prevalence of both strongyle nematodes and coccidian microparasites increased during the study, and this effect varied between lambs, yearlings and adults. Meanwhile, abundance of strongyles was more strongly linked to host PD than to temporal (yearly) dynamics, while abundance of coccidia showed a strong temporal trend without any influence of PD. Strikingly, coccidian abundance increased 3-fold across the course of the study in lambs, while increases in yearlings and adults were negligible. Our decades-long, intensive, individual-based study will enable the role of environmental change and selection pressures in driving these dynamics to be determined, potentially providing unparalleled insight into the drivers of temporal variation in parasite dynamics in the wild

Pressure to publish introduces large‐language model risks

Large-language models (LLMs) have the potential to accelerate research in ecology and evolution, cultivating new insights and innovation. However, whilst revelling in the plethora of opportunities, researchers need to consider that LLM use could also introduce risks. An important piece of context underpinning this perspective is the pressure to publish, where research careers are defined, at least partly, by publication metrics like number of papers, impact factor, citations etc. Coupled with academic employment insecurity, especially during early career, researchers may reason that LLMs are a low-risk and high-reward tool for publication. However, this pressure to publish can introduce risks if LLMs are used as a shortcut to game publication metrics instead of a tool to support true innovation. These risks may ultimately reduce research quality, stifle researcher development and incur reputational damage for researchers and the entire scientific record. We conclude with a series of recommendations to mitigate the magnitude of these risks and encourage researchers to apply caution whilst maximising LLM potential. Innovation invites excitement over novel uses, concern over misuses and fears about detrimental impacts on individuals and society. Large-language models (LLMs) represent a significant innovation that could impact how science is conducted, for better and for worse. Cooper et al. (2024) provide a timely overview of LLM use for research and teaching in ecology and evolution and suggest approaches to maximise LLM utility, especially in coding exercises. We agree with the points made by Cooper et al. (2024), but in this complementary extension, we highlight that the potential of LLMs extends beyond coding and could transform the entire research process from writing to reviewing and introduces new risks to scientific progress if applied incautiously. We term these risks: paper hacking, stunted researcher development and reputational risk. To frame our perspective, an important piece of context is the pressure to publish and the use of publication metrics as markers of researcher accomplishment. Scientists are typically judged through academic publishing and are incentivised to publish to progress in their career, that is ‘publish or perish’ (van Dalen & Henkens, 2012). Indeed, over a 10-year period, researchers beginning their careers in 2000 published 2.6 times more papers than researchers beginning their careers in 1950 (Fire & Guestrin, 2019), with the number of publications rising exponentially across an expanding number of journals (McGill, 2024). Combined with the current global socio-economic climate and academic job rarity, pressure on researchers (especially early career), is high. Against this backdrop of incentivised output and employment insecurity, researchers may reason that LLMs are a valuable tool for increasing publication rates