Biodiversity increases and decreases ecosystem stability.

Losses and gains in species diversity affect ecological stability1-7 and the sustainability of ecosystem functions and services8-13. Experiments and models have revealed positive, negative and no effects of diversity on individual components of stability, such as temporal variability, resistance and resilience2,3,6,11,12,14. How these stability components covary remains poorly understood15. Similarly, the effects of diversity on overall ecosystem stability16, which is conceptually akin to ecosystem multifunctionality17,18, remain unknown. Here we studied communities of aquatic ciliates to understand how temporal variability, resistance and overall ecosystem stability responded to diversity (that is, species richness) in a large experiment involving 690 micro-ecosystems sampled 19 times over 40 days, resulting in 12,939 samplings. Species richness increased temporal stability but decreased resistance to warming. Thus, two stability components covaried negatively along the diversity gradient. Previous biodiversity manipulation studies rarely reported such negative covariation despite general predictions of the negative effects of diversity on individual stability components3. Integrating our findings with the ecosystem multifunctionality concept revealed hump- and U-shaped effects of diversity on overall ecosystem stability. That is, biodiversity can increase overall ecosystem stability when biodiversity is low, and decrease it when biodiversity is high, or the opposite with a U-shaped relationship. The effects of diversity on ecosystem multifunctionality would also be hump- or U-shaped if diversity had positive effects on some functions and negative effects on others. Linking the ecosystem multifunctionality concept and ecosystem stability can transform the perceived effects of diversity on ecological stability and may help to translate this science into policy-relevant information.

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021.

BackgroundThroughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches.AimHere, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater.MethodsWe developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69-70 and ORF1a Δ3675-3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC.ResultsBased on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69-70 was 0.34 (95% confidence interval (CI): 0.30-0.39) and based on ORF1a Δ3675-3677 was 0.53 (95% CI: 0.49-0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38-0.61).ConclusionDigital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.

Spatially cascading effect of perturbations in experimental meta-ecosystems.

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows.

Wastewater Reveals the Spatiotemporal Spread of SARS-CoV-2 in the Canton of Ticino (Switzerland) during the Onset of the COVID-19 Pandemic.

Wastewater-based epidemiology (WBE) has emerged as an effective tool for monitoring SARS-CoV-2 dynamics during the COVID-19 pandemic. Here, we add a spatial component to WBE and use it to investigate SARS-CoV-2 spread in the canton of Ticino during the onset of the pandemic in Switzerland (end of February 2020 to beginning of March 2020). Ticino is located at the border to Northern Italy, where a large COVID-19 outbreak occurred in February 2020. Not surprisingly, Ticino was the site of the first clinically confirmed COVID-19 case in Switzerland. We retrospectively analyzed daily influent samples from nine wastewater treatment plants in Ticino that jointly cover an area of 20 km × 60 km and 351,000 people (>99% of the population). Our result is a fine-grained view of the spatiotemporal evolution of the COVID-19 pandemic in this canton. The wastewater analysis revealed that by February 29, 2020, SARS-CoV-2 had already spread to all catchments. At the same time, only four individual cases had been clinically confirmed across the region served by the treatment plants investigated. Our results demonstrate that WBE could serve as a versatile tool to monitor the introduction and spread of an infectious agent on a regional scale. To fully exploit its utility, WBE should be implemented in real time and become an integral part of future disease surveillance efforts.

Wastewater-Based Estimation of the Effective Reproductive Number of SARS-CoV-2.

BACKGROUND: The effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. OBJECTIVES: We show that the dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater can be used to estimate Re in near real time, independent of clinical data and without the associated biases. METHODS: We collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, Switzerland, and San Jose, California, USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. RESULTS: The method to estimate Re from wastewater worked robustly on data from two different countries and two wastewater matrices. The resulting estimates were as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. DISCUSSION: To our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low-cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens. https://doi.org/10.1289/EHP10050.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC.

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Wastewater monitoring outperforms case numbers as a tool to track COVID-19 incidence dynamics when test positivity rates are high.

Wastewater-based epidemiology (WBE) has been shown to coincide with, or anticipate, confirmed COVID-19 case numbers. During periods with high test positivity rates, however, case numbers may be underreported, whereas wastewater does not suffer from this limitation. Here we investigated how the dynamics of new COVID-19 infections estimated based on wastewater monitoring or confirmed cases compare to true COVID-19 incidence dynamics. We focused on the first pandemic wave in Switzerland (February to April, 2020), when test positivity ranged up to 26%. SARS-CoV-2 RNA loads were determined 2-4 times per week in three Swiss wastewater treatment plants (Lugano, Lausanne and Zurich). Wastewater and case data were combined with a shedding load distribution and an infection-to-case confirmation delay distribution, respectively, to estimate infection incidence dynamics. Finally, the estimates were compared to reference incidence dynamics determined by a validated compartmental model. Incidence dynamics estimated based on wastewater data were found to better track the timing and shape of the reference infection peak compared to estimates based on confirmed cases. In contrast, case confirmations provided a better estimate of the subsequent decline in infections. Under a regime of high-test positivity rates, WBE thus provides critical information that is complementary to clinical data to monitor the pandemic trajectory.

Evolutionary costs and benefits of infection with diverse strains of Spiroplasma in pea aphids.

The heritable endosymbiont Spiroplasma infects many insects and has repeatedly evolved the ability to protect its hosts against different parasites. Defenses do not come for free to the host, and theory predicts that more costly symbionts need to provide stronger benefits to persist in host populations. We investigated the costs and benefits of Spiroplasma infections in pea aphids (Acyrthosiphon pisum), testing 12 bacterial strains from three different clades. Virtually all strains decreased aphid lifespan and reproduction, but only two had a (weak) protective effect against the parasitoid Aphidius ervi, an important natural enemy of pea aphids. Spiroplasma-induced fitness costs were variable, with strains from the most slowly evolving clade reaching higher titers and curtailing aphid lifespan more strongly than other strains. Some Spiroplasma strains shared their host with a second endosymbiont, Regiella insecticola. Although the result of an unfortunate handling error, these co-infections proved instructive, because they showed that the cost of infection with Spiroplasma may be attenuated in the presence of Regiella. These results suggest that mechanisms other than protection against A. ervi maintain pea aphid infections with diverse strains of Spiroplasma, and that studying them in isolation will not provide a complete picture of their effects on host fitness.

Comparing constitutive and induced costs of symbiont-conferred resistance to parasitoids in aphids.

Host defenses against parasites do not come for free. The evolution of increased resistance can be constrained by constitutive costs associated with possessing defense mechanisms, and by induced costs of deploying them. These two types of costs are typically considered with respect to resistance as a genetically determined trait, but they may also apply to resistance provided by 'helpers' such as bacterial endosymbionts. We investigated the costs of symbiont-conferred resistance in the black bean aphid, Aphis fabae (Scopoli), which receives strong protection against the parasitoid Lysiphlebus fabarum from the defensive endosymbiont Hamiltonella defensa. Aphids infected with H. defensa were almost ten times more resistant to L. fabarum than genetically identical aphids without this symbiont, but in the absence of parasitoids, they had strongly reduced lifespans, resulting in lower lifetime reproduction. This is evidence for a substantial constitutive cost of harboring H. defensa. We did not observe any induced cost of symbiont-conferred resistance. On the contrary, symbiont-protected aphids that resisted a parasitoid attack enjoyed increased longevity and lifetime reproduction compared with unattacked controls, whereas unprotected aphids suffered a reduction of longevity and reproduction after resisting an attack. This surprising result suggests that by focusing exclusively on the protection, we might underestimate the selective advantage of infection with H. defensa in the presence of parasitoids.