Environmental DNA: The next chapter.

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

Spread and dynamics of the COVID-19 epidemic in Italy: Effects of emergency containment measures.

The spread of coronavirus disease 2019 (COVID-19) in Italy prompted drastic measures for transmission containment. We examine the effects of these interventions, based on modeling of the unfolding epidemic. We test modeling options of the spatially explicit type, suggested by the wave of infections spreading from the initial foci to the rest of Italy. We estimate parameters of a metacommunity Susceptible-Exposed-Infected-Recovered (SEIR)-like transmission model that includes a network of 107 provinces connected by mobility at high resolution, and the critical contribution of presymptomatic and asymptomatic transmission. We estimate a generalized reproduction number ([Formula: see text] = 3.60 [3.49 to 3.84]), the spectral radius of a suitable next-generation matrix that measures the potential spread in the absence of containment interventions. The model includes the implementation of progressive restrictions after the first case confirmed in Italy (February 21, 2020) and runs until March 25, 2020. We account for uncertainty in epidemiological reporting, and time dependence of human mobility matrices and awareness-dependent exposure probabilities. We draw scenarios of different containment measures and their impact. Results suggest that the sequence of restrictions posed to mobility and human-to-human interactions have reduced transmission by 45% (42 to 49%). Averted hospitalizations are measured by running scenarios obtained by selectively relaxing the imposed restrictions and total about 200,000 individuals (as of March 25, 2020). Although a number of assumptions need to be reexamined, like age structure in social mixing patterns and in the distribution of mobility, hospitalization, and fatality, we conclude that verifiable evidence exists to support the planning of emergency measures.

Estimating species distribution and abundance in river networks using environmental DNA.

All organisms leave traces of DNA in their environment. This environmental DNA (eDNA) is often used to track occurrence patterns of target species. Applications are especially promising in rivers, where eDNA can integrate information about populations upstream. The dispersion of eDNA in rivers is modulated by complex processes of transport and decay through the dendritic river network, and we currently lack a method to extract quantitative information about the location and density of populations contributing to the eDNA signal. Here, we present a general framework to reconstruct the upstream distribution and abundance of a target species across a river network, based on observed eDNA concentrations and hydro-geomorphological features of the network. The model captures well the catchment-wide spatial biomass distribution of two target species: a sessile invertebrate (the bryozoan Fredericella sultana) and its parasite (the myxozoan Tetracapsuloides bryosalmonae). Our method is designed to easily integrate general biological and hydrological data and to enable spatially explicit estimates of the distribution of sessile and mobile species in fluvial ecosystems based on eDNA sampling.

Integrated field, laboratory, and theoretical study of PKD spread in a Swiss prealpine river.

Proliferative kidney disease (PKD) is a major threat to wild and farmed salmonid populations because of its lethal effect at high water temperatures. Its causative agent, the myxozoan Tetracapsuloides bryosalmonae, has a complex lifecycle exploiting freshwater bryozoans as primary hosts and salmonids as secondary hosts. We carried out an integrated study of PKD in a prealpine Swiss river (the Wigger). During a 3-year period, data on fish abundance, disease prevalence, concentration of primary hosts' DNA in environmental samples [environmental DNA (eDNA)], hydrological variables, and water temperatures gathered at various locations within the catchment were integrated into a newly developed metacommunity model, which includes ecological and epidemiological dynamics of fish and bryozoans, connectivity effects, and hydrothermal drivers. Infection dynamics were captured well by the epidemiological model, especially with regard to the spatial prevalence patterns. PKD prevalence in the sampled sites for both young-of-the-year (YOY) and adult brown trout attained 100% at the end of summer, while seasonal population decay was higher in YOY than in adults. We introduce a method based on decay distance of eDNA signal predicting local species' density, accounting for variation in environmental drivers (such as morphology and geology). The model provides a whole-network overview of the disease prevalence. In this study, we show how spatial and environmental characteristics of river networks can be used to study epidemiology and disease dynamics of waterborne diseases.

Measuring the state of aquatic environments using eDNA-upscaling spatial resolution of biotic indices.

Aquatic macroinvertebrates, including many aquatic insect orders, are a diverse and ecologically relevant organismal group yet they are strongly affected by anthropogenic activities. As many of these taxa are highly sensitive to environmental change, they offer a particularly good early warning system for human-induced change, thus leading to their intense monitoring. In aquatic ecosystems there is a plethora of biotic monitoring or biomonitoring approaches, with more than 300 assessment methods reported for freshwater taxa alone. Ultimately, monitoring of aquatic macroinvertebrates is used to calculate ecological indices describing the state of aquatic systems. Many of the methods and indices used are not only hard to compare, but especially difficult to scale in time and space. Novel DNA-based approaches to measure the state and change of aquatic environments now offer unprecedented opportunities, also for possible integration towards commonly applicable indices. Here, we first give a perspective on DNA-based approaches in the monitoring of aquatic organisms, with a focus on aquatic insects, and how to move beyond traditional point-based biotic indices. Second, we demonstrate a proof-of-concept for spatially upscaling ecological indices based on environmental DNA, demonstrating how integration of these novel molecular approaches with hydrological models allows an accurate evaluation at the catchment scale. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Modelling environmental DNA transport in rivers reveals highly resolved spatio-temporal biodiversity patterns.

The ever-increasing threats to riverine ecosystems call for novel approaches for highly resolved biodiversity assessments across taxonomic groups and spatio-temporal scales. Recent advances in the joint use of environmental DNA (eDNA) data and eDNA transport models in rivers (e.g., eDITH) allow uncovering the full structure of riverine biodiversity, hence elucidating ecosystem processes and supporting conservation measures. We applied eDITH to a metabarcoding dataset covering three taxonomic groups (fish, invertebrates, bacteria) and three seasons for a catchment sampled for eDNA at 73 sites. We upscaled eDNA-based biodiversity predictions to approximately 1900 reaches, and assessed α- and ß-diversity patterns across seasons and taxonomic groups over the whole network. Genus richness predicted by eDITH was generally higher than values from direct eDNA analysis. Both predicted α- and ß-diversity varied depending on season and taxonomic group. Predicted fish α-diversity increased downstream in all seasons, while invertebrate and bacteria α-diversity either decreased downstream or were unrelated to network position. Spatial ß-diversity mostly decreased downstream, especially for bacteria. The eDITH model yielded a more refined assessment of freshwater biodiversity as compared to raw eDNA data, both in terms of spatial coverage, diversity patterns and effect of covariates, thus providing a more complete picture of freshwater biodiversity.

Freshwater fish diversity in the western Amazon basin shaped by Andean uplift since the Late Cretaceous.

South America is home to the highest freshwater fish biodiversity on Earth, and the hotspot of species richness is located in the western Amazon basin. The location of this hotspot is enigmatic, as it is inconsistent with the pattern observed in river systems across the world of increasing species richness towards a river's mouth. Here we investigate the role of river capture events caused by Andean mountain building and repeated episodes of flooding in western Amazonia in shaping the modern-day richness pattern of freshwater fishes in South America, and in Amazonia in particular. To this end, we combine a reconstruction of river networks since 80 Ma with a mechanistic model simulating dispersal, allopatric speciation and extinction over the dynamic landscape of rivers and lakes. We show that Andean mountain building and consequent numerous small river capture events in western Amazonia caused freshwater habitats to be highly dynamic, leading to high diversification rates and exceptional richness. The history of marine incursions and lakes, including the Miocene Pebas mega-wetland system in western Amazonia, played a secondary role.

Environmental DNA allows upscaling spatial patterns of biodiversity in freshwater ecosystems.

The alarming declines of freshwater biodiversity call for efficient biomonitoring at fine spatiotemporal scales, such that conservation measures be grounded upon accurate biodiversity data. Here, we show that combining environmental DNA (eDNA) extracted from stream water samples with models based on hydrological first principles allows upscaling biodiversity estimates for aquatic insects at very high spatial resolution. Our model decouples the diverse upstream contributions to the eDNA data, enabling the reconstruction of taxa distribution patterns. Across a 740-km2 basin, we obtain a space-filling biodiversity prediction at a grain size resolution of 1-km long stream sections. The model's accuracy in matching direct observations of aquatic insects' local occurrence ranges between 57-100%. Our results demonstrate how eDNA can be used for high-resolution biodiversity assessments in rivers with minimal prior knowledge of the system. Our approach allows identification of biodiversity hotspots that could be otherwise overlooked, enabling implementation of focused conservation strategies.

Generation and application of river network analogues for use in ecology and evolution.

Several key processes in freshwater ecology are governed by the connectivity inherent to dendritic river networks. These have extensively been analyzed from a geomorphological and hydrological viewpoint, yet structures classically used in ecological modeling have been poorly representative of the structure of real river basins, often failing to capture well-known scaling features of natural rivers. Pioneering work identified optimal channel networks (OCNs) as spanning trees reproducing all scaling features characteristic of natural stream networks worldwide. While OCNs have been used to create landscapes for studies on metapopulations, biodiversity, and epidemiology, their generation has not been generally accessible.Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we provide the R-package OCNet. Owing to the stochastic process generating OCNs, multiple network replicas spanning the same surface can be built; this allows performing computational experiments whose results are irrespective of the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the package provides functions that aggregate OCNs into an arbitrary number of nodes, calculate several descriptors of river networks, and draw relevant network features.We describe the main functionalities of the package and its integration with other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species.In conclusion, OCNet provides a powerful tool to generate realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems and enhances our knowledge on spatial processes in freshwater ecology in general.

Effects of feed allowance and indispensable amino acid reduction on feed intake, growth performance and carcass characteristics of growing pigs.

The hypothesis that pigs placed on diets with reduced indispensable amino acid (AA) content attempts to offset the reduction in the nutrient density with increased feed intake was tested. In the experiment, feeds with a high or a low AA content were administrated to pigs fed ad-libitum or restrictively according to a 2 × 2 factorial design. Ninety-six barrows were housed in 8 pens (12 pigs/pen) equipped with automatic feeders. Within pen, and from 47 body weight (BW) onwards, 6 pigs were fed ad libitum. The others pigs were allowed to consume, as a maximum, the feed amounts indicated by the breeding company feeding plane to optimize the feed efficiency. In early (86-118 kg BW) and late (118-145 kg BW) finishing, the pigs of 4 pens received feeds with high indispensable AA contents (8.1 and 7.5 g lysine/kg in the two periods, respectively). The other pigs received feeds with reduced indispensable AA contents (lysine, methionine, threonine and tryptophan) by 9 and 18% in early and late finishing, respectively. Body lipid and protein (Pr) retentions were estimated from BW and back-fat depth measures recorded at the beginning and the end of each period. Nitrogen excretion was estimated as actual intake minus estimated N-retention (Pr/6.25). Pigs were slaughtered at 144 kg BW. Restricted feeding decreased feed intake (-7%), daily gain (-5%), carcass weight (-2.6%) and back-fat depth (-8.0%) but increased gain:feed ratio (+2%). The AA restriction increased feed intake (+5.9%), carcass weight (+4.9%) and intramuscular fat (+17.6%), and reduced carcass weight variation (-36%), with no effects on the feed efficiency and the estimated Pr (142 g/d). N excreted was reduced by feed (-9%) and dietary AA (-15%) restrictions. Irrespectively of the feeding level, the pigs responded to a reduction of the dietary essential AA content by increasing their feed intake.

Effect of progressive reduction in crude protein and lysine of heavy pigs diets on some technological properties of green hams destined for PDO dry-cured ham production.

In order to investigate the effects of dietary crude protein (CP) and lysine (Lys) content on some technological properties of green hams destined for Protected Designation of Origin (PDO) dry-cured ham, green hams visual appraisal scores, thickness, iodine number and fatty acid composition of subcutaneous fat, and ham weight losses during seasoning (SL) were assessed. The green hams were obtained from 233 pigs fed four diets containing 140 to 110g/kg CP and 6.5 to 5.3g/kg total Lys from 90 to 165kg body weight. A reduction in dietary CP and Lys of up to 20% compared with conventional feeds led to a 15% increase in the thickness of the subcutaneous fat, a 5% decrease in linoleic and polyunsaturated fatty acids in subcutaneous fat and a 7% decrease in SL. A 20% reduction of CP and Lys in diets for finishing pigs has positive effects on the technological properties of green hams destined for PDO dry-cured ham production.

An epidemiological model for proliferative kidney disease in salmonid populations.

BACKGROUND: Proliferative kidney disease (PKD) affects salmonid populations in European and North-American rivers. It is caused by the endoparasitic myxozoan Tetracapsuloides bryosalmonae, which exploits freshwater bryozoans and salmonids as hosts. Incidence and severity of PKD in brown trout populations have recently increased rapidly, causing a decline in fish catches and local extinctions in many river systems. PKD incidence and fish mortality are known to be enhanced by warmer water temperatures. Therefore, environmental change is feared to increase the severity of PKD outbreaks and extend the disease range to higher latitude and altitude regions. We present the first mathematical model regarding the epidemiology of PKD, including the complex life-cycle of its causative agent across multiple hosts. METHODS: A dynamical model of PKD epidemiology in riverine host populations is developed. The model accounts for local demographic and epidemiological dynamics of bryozoans and fish, explicitly incorporates the role of temperature, and couples intra-seasonal and inter-seasonal dynamics. The former are described in a continuous-time domain, the latter in a discrete-time domain. Stability and sensitivity analyses are performed to investigate the key processes controlling parasite invasion and persistence. RESULTS: Stability analysis shows that, for realistic parameter ranges, a disease-free system is highly invasible, which implies that the introduction of the parasite in a susceptible community is very likely to trigger a disease outbreak. Sensitivity analysis shows that, when the disease is endemic, the impact of PKD outbreaks is mostly controlled by the rates of disease development in the fish population. CONCLUSIONS: The developed mathematical model helps further our understanding of the modes of transmission of PKD in wild salmonid populations, and provides the basis for the design of interventions or mitigation strategies. It can also be used to project changes in disease severity and prevalence because of temperature regime shifts, and to guide field and laboratory experiments.