Diversity-disease Relationship Research Articles

New insights into biodiversity-disease relationships: the importance of the host community network characterization

Camera-trapping-based social network analysis (SNA) is a valuable tool to characterize communities and identify species with an outstanding role in pathogen maintenance. This study provides new insights into the contentious debate on the effect of biodiversity on disease risk by combining SNA with the assessment of host diversity indicators and pathogen richness in Spain. The apparent species richness detected by camera traps at each study site ranged from 10 to 33 species (mean ± standard error (SE): 20.73 ± 1.94) and their apparent diversity rates (i.e., Shannon index) ranged from 0.57 to 2.55 (mean ± SE: 1.97 ± 0.16). At the community level, vertebrate host diversity had a marginal dilution effect on the disease risk and was negatively correlated to pathogen richness. The exposure to multiple pathogens, as a proxy of disease risk, was negatively associated with apparent host diversity. The disease risk was driven by the interaction of apparent biodiversity with the presence of livestock and with the centrality of the indicator species (i.e., the wild boar). The maximum risk of co-exposure to pathogens was reached when the lowest apparent biodiversity rates coincided with the highest wild boar centrality in the host community or with the presence of livestock, respectively. The highest confluence of pathogens occurred at lower apparent diversity indexes, higher wild boar relative abundances and predominance of agricultural lands. Our results suggest that the diversity-disease relationship is not linear and depends on the environment and host community characteristics, thereby opening avenues for designing new prevention strategies.

Impact of vector richness on the risk of vector-borne disease: The role of vector competence.

A central goal of disease ecology is to identify the factors that drive the spread of infectious diseases. Changes in vector richness can have complex effects on disease risk, but little is known about the role of vector competence in the relationship between vector richness and disease risk. In this study, we firstly investigated the combined effects of vector competence, interspecific competition, and feeding interference on disease risk through a two-vector, one-host SIR-SI model, and obtained threshold conditions for the occurrence of dilution and amplification effects. Secondly, we extended the above model to the case of N vectors and assumed that all vectors were homogeneous to obtain analytic expressions for disease risk. It was found that in the two-vector model, disease risk declined more rapidly as interspecific competition of the high-competence vector increased. When vector richness increases, the positive effects of adding a high-competence vector species on disease transmission may outweigh the negative effects of feeding interference due to increased vector richness, making an amplification effect more likely to occur. While the addition of a highly competitive vector species may exacerbate the negative effects of feeding interference, making a dilution effect more likely to occur. In the N-vector model, the effect of increased vector richness on disease risk was fully driven by the strength of feeding interference and interspecific competition, and changes in vector competence only quantitatively but not qualitatively altered the vector richness-disease risk relationship. This work clarifies the role of vector competence in the relationship between vector richness and disease risk and provides a new perspective for studying the diversity-disease relationship. It also provides theoretical guidance for vector management and disease prevention strategies.

A comprehensive diversity analysis on the gut microbiomes of ASD patients: from alpha, beta to gamma diversities.

Autism spectrum disorder (ASD) is estimated to influence as many as 1% children worldwide, but its etiology is still unclear. It has been suggested that gut microbiomes play an important role in regulating abnormal behaviors associated with ASD. A de facto standard analysis on the microbiome-associated diseases has been diversity analysis, and nevertheless, existing studies on ASD-microbiome relationship have not produced a consensus. Here, we perform a comprehensive analysis of the diversity changes associated with ASD involving alpha-, beta-, and gamma-diversity metrics, based on 8 published data sets consisting of 898 ASD samples and 467 healthy controls (HC) from 16S-rRNA sequencing. Our findings include: (i) In terms of alpha-diversity, in approximately 1/3 of the studies cases, ASD patients exhibited significantly higher alpha-diversity than the HC, which seems to be consistent with the "1/3 conjecture" of diversity-disease relationship (DDR). (ii) In terms of beta-diversity, the AKP (Anna Karenina principle) that predict all healthy microbiomes should be similar, and every diseased microbiome should be dissimilar in its own way seems to be true in approximately 1/2 to 3/4 studies cases. (iii) In terms of gamma-diversity, the DAR (diversity-area relationship) modeling suggests that ASD patients seem to have large diversity-area scaling parameter than the HC, which is consistent with the AKP results. However, the MAD (maximum accrual diversity) and RIP (ratio of individual to population diversity) parameters did not suggest significant differences between ASD patients and HC. Throughout the study, we adopted Hill numbers to measure diversity, which stratified the diversity measures in terms of the rarity-commonness-dominance spectrum. It appears that the differences between ASD patients and HC are more propounding on rare-species side than on dominant-species side. Finally, we discuss the apparent inconsistent diversity-ASD relationships among different case studies and postulate that the relationships are not monotonic.

Host exposure to a common pollutant can influence diversity-disease relationships.

Hosts and parasites are embedded in communities where species richness and composition can influence disease outcomes (diversity-disease relationships). The direction and magnitude of diversity-disease relationships are influenced by variation in competence (ability to support and transmit infections) of hosts in a community. However, host susceptibility to parasites, which mediates host competence, is not static and is influenced by environmental factors, including pollutants. Despite the role that pollutants can play in augmenting host susceptibility, how pollutants influence diversity-disease dynamics is not well understood. Using an amphibian-trematode model, we tested how NaCl influences diversity-disease dynamics. We predicted that NaCl exposure can alter relative susceptibility of host species to trematodes, leading to cascading effects on the diversity-disease relationship. To test these predictions, we exposed hosts to benign or NaCl environments and generated communities that differed in number and composition of host species. We exposed these communities to trematodes and measured disease outcomes at the community (total infections across all hosts within a community) and species levels (average number of infections per host species within a community). Host species differed in their relative susceptibility to trematodes when exposed to NaCl. Consequently, at the community level (total infections across all hosts within a community), we only detected diversity-disease relationships (dilution effects) in communities where hosts were exposed to NaCl. At the species level, disease outcomes (average number of infections/species) and whether multi-species communities supported lower number of infections relative to single-species communities depended on community composition. Notably, however, as with overall community infection, diversity-disease relationships only emerged when hosts were exposed to NaCl. Synthesis. Pollutants are ubiquitous in nature and can influence disease dynamics across a number of host-parasite systems. Here, we show that NaCl exposure can alter the relative susceptibility of host species to parasites, influencing the relationship between biodiversity and disease at both community and species levels. Collectively, our study contributes to the limited knowledge surrounding environmental mediators of host susceptibility and their influence on diversity-disease dynamics.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza.

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

Risk factors for Lyme disease: A scale-dependent effect of host species diversity and a consistent negative effect of host phylogenetic diversity

Biodiversity can influence disease risk. One example of a diversity-disease relationship is the dilution effect, which suggests higher host species diversity (often indexed by species richness) reduces disease risk. While numerous studies support the dilution effect, its generality remains controversial. Most studies of diversity-disease relationships have overlooked the potential importance of phylogenetic diversity. Furthermore, most studies have tested diversity-disease relationships at one spatial scale, even though such relationships are likely scale dependent. Using Lyme disease as a model system, we investigated the effects of host species richness and phylogenetic relatedness on the number of reported Lyme disease cases in humans in the U.S.A. at two spatial scales (the county level and the state level) using piecewise structural equation modelling. We also accounted for relevant climatic and habitat-related factors and tested their correlations with the number of Lyme disease cases. We found that species assemblages with more related species (i.e., host species in the order Rodentia) were associated with more Lyme disease cases in humans. Host species richness correlated negatively with the number of Lyme disease cases at the state level (i.e., a dilution effect), a pattern that might be explained by the higher number of reservoir-incompetent species at high levels of species richness at this larger spatial scale. In contrast, a positive correlation was found between species richness and the number of Lyme disease cases at the county level, where a higher proportion of rodent species was associated with higher levels of species richness, potentially amplifying the disease risk. Our results highlight that analyse at a single spatial scale can miss some impacts of biodiversity on human health. Thus, multi-scale analyses with consideration of host phylogenetic diversity are critical for improving our understanding of diversity-disease relationships.

Deciphering the interactions between plant species and their main fungal root pathogens in mixed grassland communities

Abstract Plant diversity can reduce the risk of plant disease, but positive, and neutral effects have also been reported. These contrasting relationships suggest that plant community composition, rather than diversity per se, affects disease risk. Here, we investigated how the diversity and composition of plant communities drive root‐associated pathogen accumulation belowground. In a temperate grassland biodiversity experiment, containing 16 plant species (forbs and grasses), we determined the abundance of root‐associated fungal pathogens in individual plant species growing in monocultures and in four‐species mixtures through Illumina MiSeq amplicon sequencing. In the plant monocultures, we identified three major fungal pathogens that differed in host range: Paraphoma chrysanthemicola, associated with roots of forb species of the Asteraceae family, Slopeiomyces cylindrosporus, associated with grass species, and Rhizoctonia solani, associated with multiple forb and grass species. In mixtures, there was no significant reduction in relative abundance of these pathogens in their host species as compared to monocultures. However, in mixtures, there was a significant increase in relative abundance of each pathogen in several non‐host and host plant species. Across mixtures, plant community composition affected pathogen relative abundance in individual plant species. This effect was driven by the presence of a particular neighbouring plant species (depending on the pathogen), rather than functional group composition (i.e. grass/forb ratio) or averaged pathogen pressure (based on monocultures) of all neighbours. Specifically, the presence of neighbour host species Achillea millefolium significantly increased P. chrysanthemicola, but decreased R. solani relative abundance in several host and non‐host plant species in mixtures. Synthesis. Our results indicate that interactions between different plant species—both host and non‐hosts—and fungal pathogens underlie the effects of plant diversity on root pathogen abundance. Non‐host species may act as pathogen reservoirs in diverse plant communities, as they harboured certain pathogens in mixtures, but not in monocultures. Additionally, particular host species can strongly affect pathogen abundance in other (host and non‐host) plant species in plant mixtures, suggesting clear effects of species identity in the diversity–disease relationship. Below‐ground disease risk thus depends on plant community composition rather than diversity per se, via specific interactions between plant species and their root‐associated pathogens.

Host community composition, community assembly pattern, and disease transmission mode jointly determine the direction and strength of the diversity-disease relationship

Rapid global biodiversity loss and increasing emerging infectious diseases underscore the significance of identifying the diversity-disease relationship. Although experimental evidence supports the existence of dilution effects in several natural ecosystems, we still know very little about the conditions under which a dilution effect will occur. Using a multi-host Susceptible-Infected-Recovered model, we found when disease transmission was density-dependent, the diversity-disease relationship could exhibit an increasing, decreasing, or non-monotonic trend, which mainly depended on the patterns of community assembly. However, the combined effects of the host competence-abundance relationship and species extinction order may reverse or weaken this trend. In contrast, when disease transmission was frequency-dependent, the diversity-disease relationship only showed a decreasing trend, the host competence-abundance relationship and species extinction order did not alter this decreasing trend, but it could reduce the detectability of the dilution effect and affect disease prevalence. Overall, a combination of disease transmission mode, community assembly pattern, and host community composition determines the direction or strength of the diversity-disease relationship. Our work helps explain why previous studies came to different conclusions about the diversity-disease relationship and provides a deeper understanding of the pathogen transmission dynamics in actual communities.

How Multiple Interaction Types Affect Disease Spread and Dilution in Ecological Networks

Ecological communities are composed of different functional guilds that are engaging in multiple types of biotic interactions. We explore how ecological networks fare when confronting infectious diseases according to density-dependent (DD) and frequency-dependent (FD) transmission modes. Our model shows that network compositions can dictate both disease spreading and the relationship between disease and community diversity (including species richness and Shannon’s diversity) as depicted in the dilution effect. The disease becomes more prevalent within communities harboring more mutualistic interactions, generating a positive relationship between disease prevalence and community diversity (i.e., an amplification effect). By contrast, in communities with a fixed proportion of mutualistic interactions, higher diversity from the balance of competition and predation can impede disease prevalence (i.e., the dilution effect). Within-species disease prevalence increases linearly with a species’ degree centrality. These patterns of disease transmission and the diversity-disease relationship hold for both transmission modes. Our analyses highlight the complex effects of interaction compositions in ecological networks on infectious disease dynamics and further advance the debate on the dilution effect of host diversity on disease prevalence.

Species densities, assembly order, and competence jointly determine the diversity-disease relationship.

Since species vary in abundance and host competence (i.e., ability to get infected and transmit a pathogen), changes in species composition caused by biodiversity loss impacts disease dynamics. Forecasting effects of species composition on disease depends on community (dis)assembly, processes determining how species are added to (or lost from) communities. We simulated community assembly by planting mesocosms, nested along a richness gradient, and tested how relationships between richness, species assembly order, and overall density affect disease risk. Mesocosms with up to six crop species of varying competence were inoculated with a soilborne fungal pathogen, Rhizoctonia solani. Disease was measured as species-level prevalence, community-level prevalence, and total number of diseased plants. Regardless of metric, richness limited disease when species assembly order negatively correlated with competence and total density remained unchanged with richness. When density increased with richness or species assembled randomly, richness primarily correlated positively or weakly with disease. Our results align with theoretical expectations and represent the first empirical study to test the influence of species densities, assembly order, and competence on diversity-disease relationships.

Links between biodiversity and human infectious and non-communicable diseases: a review.

Biodiversity has intrinsic value and a fundamental role in human health. The relationship between them is complex, and the specific sustaining processes are still not well understood. In view of the rapidly evolving landscape, this literature review investigated scientific evidence for specific links between biodiversity and human infectious and non-communicable diseases to characterise identifiable relationships. A search of the PubMed and Web of Science databases using keyword algorithms identified relevant manuscripts published between 1 January 2000 and 18 April 2019. Qualitative data were extracted from 155 studies investigating links between or mechanisms linking biodiversity and infectious disease, non-communicable disease, allergic/inflammatory disease and microbiomes. None of the reviewed studies documented causal evidence for a mechanism linking biodiversity and human health. The main mechanisms proposed to link biodiversity and transmission of infectious disease were dilution and amplification. The dilution hypothesis argues that an increase in species diversity leads to a decrease in pathogen prevalence. The amplification effect is the converse, that there is a positive correlation between species diversity and disease risk/infection prevalence. Several driving factors are postulated, including encounter reduction, interspecies competition and predation. In addition, it appears that scale, both spatial and temporal, highly impacts diversity-disease relationships. There is strong evidence that the early environment of a child, including maternally transferred prenatal signals, affects immune maturation, modifying later disease risk. Bi-directional axes communicate between the gut microbiome and the brain, as well as between the skin microbiome and the lung, leading to direct and indirect immune, humoral and neural mechanisms. The main challenges in assessing links between biodiversity and human health are the wide variation in definitions of health and biodiversity, and the heterogeneity in types of studies encountered, as well as the complexity of interactions in dynamic systems. Contextually adapted integrative approaches, which maintain dialogue across disciplines and amongst all stakeholders, are most likely to generate robust evidence. Because of the relevance of local scale, research engagement must occur across levels to generate legitimate practices and translate into sustainable, equitable policies. Recommendations for future action include: improve the knowledge base on contribution of biodiversity to health, increase awareness of health effects of natural and near-natural environments and biodiversity, and promote synergies by increasing policy coherence.

Population-level diversity-disease relationship (p-DDR) in the human microbiome associated diseases

Diversity-disease relationship (DDR) is a de facto standard analysis in the studies of human microbiome associated diseases (MADs). For example, the species richness or Shannon entropy are routinely compared between the healthy and diseased groups. Nevertheless, the basic scale of the standard diversity analysis is individual subject rather than a cohort or population because the diversity is computed for individual samples, not for the group. Here we aim to expand the current DDR study from individual focus to population level, which can offer important insights for understanding the epidemiology of MADs. We analyzed the diversity-disease relationship at cohort scale based on a collection of 23 datasets covering the major human MADs. Methodologically, we harness the power of a recent extension to the classic species-area relationship (SAR), i.e., the diversity-area relationship (DAR), to achieve the expansion from individual DDR to inter-subject diversity scaling analysis. Specifically, we apply the DAR analysis to estimate and compare the potentially maximal accrual diversities of the healthy and diseases groups, as well as the inter-subject diversity scaling parameters and the individual-to-population diversity ratios. It was shown that, except for the potential diversity (Dmax) at the cohort level in approximately 5.4% cases of MADs, DAR parameters displayed no significant differences between healthy and diseased treatments. That is, the DAR parameters are rather resilient against MADs, except for the potential diversity in some diseases. We compared our population-level DDR with the existing individual-level DDR patterns and proposed a hypothesis to interpret their differences.

Species distribution patterns and the scale of host interactions quantitatively but not qualitatively affect the diversity–disease relationship

Evidence is accumulating to show that changes in host diversity can affect disease risk, yet the relationship between them is still disputed. Understanding what factors influence this relationship will help to reconcile this debate. In this paper, through spatially-explicit simulations, we investigated the effects of host spatial distribution patterns, the scale of host interactions (i.e. local vs. global interactions), the presence or absence of life history trade-offs, and community assembly rules on the diversity–disease relationship when the pathogen was a generalist. The results showed that intraspecific aggregation enhanced disease risk, while increased global interactions between hosts reduced disease risk. For a given host species richness level, the effect of the scale of host interactions on disease risk increased with intraspecific aggregation. However, neither species distribution patterns nor the scale of host interactions could reverse the diversity-disease relationship. The direction and strength of diversity on disease risk depended on community assembly and life history trade-offs. These results suggest that species distribution patterns and the scale of host interactions do not contribute to the discrepancy in results that lead to the debate over dilution effect, highlighting the complexity of mechanisms underlying the diversity–disease relationship.

Towards a mechanistic understanding of competence: a missing link in diversity-disease research.

Biodiversity loss may increase the risk of infectious disease in a phenomenon known as the dilution effect. Circumstances that increase the likelihood of disease dilution are: (i) when hosts vary in their competence, and (ii) when communities disassemble predictably, such that the least competent hosts are the most likely to go extinct. Despite the central role of competence in diversity-disease theory, we lack a clear understanding of the factors underlying competence, as well as the drivers and extent of its variation. Our perspective piece encourages a mechanistic understanding of competence and a deeper consideration of its role in diversity-disease relationships. We outline current evidence, emerging questions and future directions regarding the basis of competence, its definition and measurement, the roots of its variation and its role in the community ecology of infectious disease.

Heterogeneity–disease relationship in the human microbiome-associated diseases

Space is a critical and also challenging frontier in human microbiome research. It has been found that lack of consideration of scales beyond individual and ignoring of microbe dispersal are two crucial roadblocks in preventing deep understanding of the spatial heterogeneity of human microbiome. Assessing and interpreting the heterogeneity and dispersal in microbiomes explicitly are particularly challenging, but implicit approaches such as Taylor's power law (TPL) can be rather effective. Based on TPL, which achieved a rare status of ecological laws, we introduce a general methodology for characterizing the spatial heterogeneity of microbiome (i.e. characterization of microbial spatial distribution) and further apply it for investigating the heterogeneity-disease relationship (HDR) via analyzing a big dataset of 26 MAD (microbiome-associated disease) studies covering nearly all high-profile MADs including obesity, diabetes and gout. It was found that in majority of the MAD cases, the microbiome was sufficiently resilient to endure the disease disturbances. Specifically, in ∼10-16% cases, disease effects were significant-the healthy and diseased cohorts exhibited statistically significant differences in the TPL heterogeneity parameters. We further compared HDR with classic diversity-disease relationship (DDR) and explained their mechanistic differences. Both HDR and DDR cross-verified remarkable resilience of the human microbiomes against MADs.

Community context for mechanisms of disease dilution: insights from linking epidemiology and plant-soil feedback theory.

In many natural systems, diverse host communities can reduce disease risk, though less is known about the mechanisms driving this “dilution effect.” We relate feedback theory, which focuses on pathogen‐mediated coexistence, to mechanisms of dilution derived from epidemiological models, with the central goal of gaining insights into host–pathogen interactions in a community context. We first compare the origin, structure, and application of epidemiological and feedback models. We then explore the mechanisms of dilution, which are grounded in single‐pathogen, single‐host epidemiological models, from the perspective of feedback theory. We also draw on feedback theory to examine how coinfecting pathogens, and pathogens that vary along a host specialist–generalist continuum, apply to dilution theory. By identifying synergies among the feedback and epidemiological approaches, we reveal ways in which organisms occupying different trophic levels contribute to diversity–disease relationships. Additionally, using feedbacks to distinguish dilution in disease incidence from dilution in the net effect of disease on host fitness allows us to articulate conditions under which definitions of dilution may not align. After ascribing dilution mechanisms to macro‐ or microorganisms, we propose ways in which each contributes to diversity–disease and productivity–diversity relationships. Our analyses lead to predictions that can guide future research efforts.

How intraguild predation affects the host diversity-disease relationship in a multihost community

Broad evidence has shown that host diversity can impede disease invasion and reduce the eventual prevalence, but little is known on how species interactions play in shaping this host diversity-disease relationship. Previous work has illustrated that intraguild predation (IGP), combined with parasite-mediated indirect effects, can have strong influences on parasitic infection. Following this line of thinking, we here examine the role of predatory interactions in the disease transmission within a multihost community. Through varying fractions of IGP in a competitive community, we show that, dependent on the fraction of predatory interactions, species richness can switch from enhancing to inhibiting disease establishment/prevalence. Without IGP interactions, high host species richness can likely weaken the ‘dilution effect’ and in some cases even enhance the disease establishment (and/or prevalence) due to the existence of alternative sources for infection, whereas IGP can generally heighten the negative diversity-disease relationship due to the reduction of encounter rate between prospective hosts and parasites. Although trait-mediated interactions (captured as the infection-induced changes in predation rate) only weakly affect disease prevalence, density-mediated interactions (captured as the additional infection-induced mortality) can pose a relatively strong influence on disease transmission. Our results thus underline the importance of considering species interactions when investigating the host diversity-disease relationship.

Effect of spatial scale and latitude on diversity-disease relationships.

Natural ecosystems provide humans with different types of ecosystem services, often linked to biodiversity. The dilution effect (DE) predicts a negative relationship between biodiversity and risk of infectious diseases of humans, other animals, and plants. We hypothesized that a stronger DE would be observed in studies conducted at smaller spatial scales, where biotic drivers may predominate, compared to studies at larger spatial scales where abiotic drivers may more strongly affect disease patterns. In addition, we hypothesized a stronger DE in studies from temperate regions at mid latitudes than in those from subtropical and tropical regions, due to more diffuse species interactions at low latitudes. To explore these hypotheses, we conducted a meta‐analysis of observational studies of diversity–disease relationships for animals across spatial scales and geographic regions. Negative diversity–disease relationships were significant at small (combined site and local), intermediate (combined landscape and regional), and large (combined continental and global) scales and the effect did not differ depending on size of the study areas. For the geographic region analysis, a strongly negative diversity–disease relationship was found in the temperate region while no effect was found in the subtropical and tropical regions. However, no overall effect of absolute latitude on the strength of the dilution effect was detected. Our results suggest that a negative diversity–disease relationship occurs across scales and latitudes and is especially strong in the temperate region. These findings may help guide future management efforts in lowering disease risk.

Invasive species reduces parasite prevalence and neutralizes negative environmental effects on parasitism in a native mosquito.

Invasive species research often focuses on direct effects of invasion on native ecosystems and less so on complex effects such as those influencing host-parasite interactions. However, invaders could have important effects on native host-parasite dynamics. Where infectious stages are ubiquitous and native host-pathogen specificity is strong, invasive less-competent hosts may reduce the pool of infectious stages, effectively reducing native host-parasite encounter rate. Alternatively, invasive species could alter transmission via changes in native species abundance. Biotic and abiotic environmental factors can also impact disease dynamics by altering host or parasite condition. However, little is known about potential interactive effects of invasion and environmental context on native species disease dynamics. Moreover, experimental examinations of the mechanisms driving dilution effects are limited, but serve to provide tests of predictions leading to diversity-disease relationships. Using field and laboratory experiments, we tested competing hypotheses that an invasive species reduces the prevalence of a native parasite in its host by removing infectious propagules from the environment or by reducing native host abundance. In addition, we evaluated the role of detritus quantity as a resource base in mediating effects of the invasive species. Native parasite prevalence was reduced when the invasive species was present. Prevalence was also higher in high detritus habitats, although this effect was lost when the invasive species was present. The invasive species significantly reduced infectious propagules from the aquatic habitats. Presence of the invasive species had no effect on the native species abundance; thus, the reduction in parasitism was not due to changes in host density but through a reduction in infectious propagule encounters. We conclude that an invasive species can facilitate a native species by reducing parasite prevalence via a dilution effect and that these effects can be modified by resource level. Reductions in parasitism may have ripple effects throughout the community, altering the strength of competitive interactions, predation rates or coinfection with other pathogens. We advocate considering potential positive effects of invasive species on recipient communities, in addition to effects of invasions on host-parasite interactions to gain a broader understanding of the complex consequences of invasion.

Contrasting effects of host species and phylogenetic diversity on the occurrence of HPAI H5N1 in European wild birds.

Studies on the highly pathogenic avian influenza (HPAI) H5N1 suggest that wild bird migration may facilitate its long-distance spread, yet the role of wild bird community composition in its transmission risk remains poorly understood. Furthermore, most studies on the diversity-disease relationship focused on host species diversity without considering hosts' phylogenetic relationships, which may lead to rejecting a species diversity effect when the community has host species that are only distantly related. Here, we explored the influence of waterbird community composition for determining HPAI H5N1 occurrence in wild birds in a continental-scale study across Europe. In particular, we tested the diversity-disease relationship using both host species diversity and host phylogenetic diversity. Our results provide the first demonstration that host community composition-compared with previously identified environmental risk factors-can also effectively explain the spatial pattern of H5N1 occurrence in wild birds. We further show that communities with more higher risk host species and more closely related species have a higher risk of H5N1 outbreaks. Thus, both host species diversity and community phylogenetic structure, in addition to environmental factors, jointly influence H5N1 occurrence. Our work not only extends the current theory on the diversity-disease relationship, but also has important implications for future monitoring of H5N1 and other HPAI subtypes.