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Implementing and optimizing biodiversity monitoring is crucial given the current, worldwide biodiversity decline. Compared to other ecosystems, monitoring of biodiversity is lagging behind in groundwater ecosystems, both because of sparse taxonomic knowledge and methodological constraints. We here assessed temporal variation in the occurrence and abundance of macroinvertebrates collected systematically from shallow groundwater aquifers of Switzerland to establish general principles on seasonality and repeatability of assessment outcomes. We found no seasonal abundance pattern for obligate groundwater amphipods and isopods, indicating temporal consistency. In contrast, other macroinvertebrates (predominantly stygophiles and stygoxenes) showed pronounced seasonality in their detection rate. However, we found variability in detection rates across groundwater amphipod species and especially across sampling sites. For groundwater communities, characterized by narrowly-distributed and rare species, our results highlight the need for tailored and extensive sampling strategies. When setting up monitoring programs on groundwater fauna, detection probability, temporal autocorrelation, and standardization of sampling effort should be carefully considered. Applying novel, systematic approaches, can offer promising methodologies for understanding and conserving groundwater ecosystems.

Abstract More than half of the world’s rivers dry up periodically, but our understanding of the biological communities in dry riverbeds remains limited. Specifically, the roles of dispersal, environmental filtering and biotic interactions in driving biodiversity in dry rivers are poorly understood. Here, we conduct a large-scale coordinated survey of patterns and drivers of biodiversity in dry riverbeds. We focus on eight major taxa, including microorganisms, invertebrates and plants: Algae, Archaea, Bacteria, Fungi, Protozoa, Arthropods, Nematodes and Streptophyta. We use environmental DNA metabarcoding to assess biodiversity in dry sediments collected over a 1-year period from 84 non-perennial rivers across 19 countries on four continents. Both direct factors, such as nutrient and carbon availability, and indirect factors such as climate influence the local biodiversity of most taxa. Limited resource availability and prolonged dry phases favor oligotrophic microbial taxa. Co-variation among taxa, particularly Bacteria, Fungi, Algae and Protozoa, explain more spatial variation in community composition than dispersal or environmental gradients. This finding suggests that biotic interactions or unmeasured ecological and evolutionary factors may strongly influence communities during dry phases, altering biodiversity responses to global changes.

Abstract Freshwater macroinvertebrates are a diverse group and play key ecological roles, including accelerating nutrient cycling, filtering water, controlling primary producers, and providing food for predators. Their differences in tolerances and short generation times manifest in rapid community responses to change. Macroinvertebrate community composition is an indicator of water quality. In Europe, efforts to improve water quality following environmental legislation, primarily starting in the 1980s, may have driven a recovery of macroinvertebrate communities. Towards understanding temporal and spatial variation of these organisms, we compiled the TREAM dataset (Time seRies of European freshwAter Macroinvertebrates), consisting of macroinvertebrate community time series from 1,816 river and stream sites (mean length of 19.2 years and 14.9 sampling years) of 22 European countries sampled between 1968 and 2020. In total, the data include >93 million sampled individuals of 2,648 taxa from 959 genera and 212 families. These data can be used to test questions ranging from identifying drivers of the population dynamics of specific taxa to assessing the success of legislative and management restoration efforts.

Abstract Plant–insect trophic systems should be particularly sensitive to processes altering species spatial co‐occurrences, as impacts on one level can cascade effectively through the strong trophic reliance to the other level. Here, we predicted the biogeography of Lepidoptera–plant communities under global‐change scenarios, exploiting spatially resolved data on 423 Lepidoptera species and their 848 food plants across the German state of Baden‐Württemberg (ca. 36,000 km2). We performed simulations of plant extinction and Lepidoptera expansion, and respectively assessed their cascading consequences—namely secondary extinction of Lepidoptera and change in functional distance of plants—on the interaction networks. Importantly, the simulations were spatially explicit, as we accounted for realistic landscape contexts of both processes: Plant extinctions were simulated as “regional” (a species goes extinct in the whole region at once) vs. “isolation‐driven” (a species gradually goes extinct from the peripheral or isolated localities according to its real regional distribution); Lepidoptera expansions were simulated with random, northward, and upward directions according to real topography. The consequences were assessed based on empirical community composition and trophic relationships. When evaluated by regional richness, the robustness of Lepidoptera assemblages against secondary extinctions was higher under isolation‐driven plant extinctions than regional plant extinction; however, this relationship was reversed when evaluated by averaged local richness. Also, with isolation‐driven plant extinctions, Lepidoptera at the central sub‐region of Baden‐Württemberg appeared to be especially vulnerable. With Lepidoptera expansions, plants' functional distances in local communities dropped, indicating a possible increase of competition among plants, yet to a lesser extent particularly with upward movements. Together, our results suggested that the communities' composition context at the landscape scale (i.e., how communities, with respective species composition, are arranged within the landscape) matters when assessing global‐change influences on interaction systems; spatially explicit consideration of such context can reveal localised consequences that are not necessarily captured via a spatially implicit, regional perspective.

Rivers are biodiverse ecosystems that play an essential role in the processing of organic matter from headwaters to the lower reaches. The biodiversity within these spatially complex ecosystems is often subject to huge seasonal variation, particularly in temperate regions, for example seasonal peaks in emergence of aquatic insects or migration of fish through the river network. However, these ecosystems are also subject to strong anthropogenic pressures that affect not only the biodiversity within this system, but the functions this biodiversity provides to key ecosystem processes. Therefore, spatial and temporally dynamics must be considered to effectively assess and understand the biodiversity and functioning within an ecosystem. Here, we assessed ecosystem function at a high spatial and temporal resolution across a large river network, specifically focussing on standardised organic–matter decomposition. Our results show—even when correcting for temperature—significant effects of both season and water chemistry parameters on microbial decomposition. However, we found no effect of space (i.e., site location within the network) on ecosystem function, contrary to expectations. We also found no imprint of the microbial community richness assessed in the water column (α–diversity and Shannon Index) on the patterns of organic–matter decomposition, however, this may be due to our focus on potential colonising microbes rather than benthic communities. Our study highlights the need to include functional indicators for the assessment of ecosystems.

The monitoring and management of aquatic ecosystems depend on precise estimates of biodiversity. Metabarcoding analyses of environmental nucleic acids (eNAs), including environmental DNA (eDNA) and environmental RNA (eRNA), have garnered attention for their cost-effective and non-invasive biomonitoring capabilities. However, the accuracy of biodiversity estimates obtained through eNAs can vary among different organismal groups. Here we evaluate the performance of eDNA and eRNA metabarcoding across nine organismal groups, ranging from bacteria to terrestrial vertebrates, in three cross-sections of the Yangtze River, China. We observe robust complementarity between eDNA and eRNA data. The relative detectability of eNAs was notably influenced by major taxonomic groups and organismal sizes, with eDNA providing more robust signals for larger organisms. Both eDNA and eRNA exhibited similar cross-sectional and longitudinal patterns. However, the detectability of larger organisms declined in eRNA metabarcoding, possibly due to differential RNA release and decay among different organismal groups or sizes. While underscoring the potential of eDNA and eRNA in large river biomonitoring, we emphasize the need for differential interpretation of eDNA versus eRNA data. This highlights the importance of careful method selection and interpretation in biomonitoring studies.

Abstract Anthropogenically forced changes in global freshwater biodiversity demand more efficient monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the appropriate spatio-temporal resolution of robust biodiversity assessment remains ambiguous. Here, using intensive, spatio-temporal eDNA sampling across space (five rivers in Europe and North America, with an upper range of 20–35 km between samples), time (19 timepoints between 2017 and 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers using eDNA. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of environmental conditions were taxon-specific, reflecting habitat filtering of communities rather than effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatio-temporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river community ecology during a time of environmental change.

Abstract Ecological and ecosystem monitoring is rapidly shifting towards using environmental DNA (eDNA) data, particularly in aquatic systems. This approach enables a combined coverage of biodiversity across all major organismal groups and the assessment of ecological indices. Yet, most current approaches are not exploiting the full potential of eDNA data, largely interpreting results in a localized perspective. In riverine networks, by explicitly modelling hydrological transport and associated DNA decay, hydrology‐based models enable upscaling eDNA‐based diversity information, providing spatially integrated inference. To capitalize on these unprecedented biodiversity data and translate it into space‐filling biodiversity projections, a streamlined implementation is needed. Here, we introduce the eDITH R‐package, implementing the eDITH model to project biodiversity across riverine networks with minimal prior information. eDITH couples a species distribution model relating a local taxon's eDNA shedding rate in streamwater to environmental covariates, a mass balance expressing the eDNA concentration at a river's cross‐section as a weighted sum of upstream contributions, and an observational model accounting for uncertainties in eDNA measurements. By leveraging on spatially replicated eDNA measurements and minimal hydro‐morphological data, eDITH enables disentangling the various upstream eDNA sources, and produces space‐filling maps of a taxon's spatial distribution at any chosen resolution. eDITH is applicable to both eDNA concentration and metabarcoding data, and to any taxon whose DNA can be retrieved in streamwater. The eDITH package provides user‐friendly functions for single‐run execution and fitting of eDITH to eDNA data with both Bayesian methods (via the BayesianTools package) and non‐linear optimization. An interface to the DHARMa package allows model validation via posterior predictive checks. Necessary preliminary steps such as watershed delineation and hydrological characterization are implemented via the rivnet package. We illustrate eDITH's workflow and functionalities with two case studies from published fish eDNA data. The eDITH package provides a user‐friendly implementation of eDITH, specifically intended for ecologists and conservation biologists. It can be used without previous modelling knowledge but also allows customization for experienced users. Ultimately, eDITH allows upscaling eDNA biodiversity data for any river globally, transforming how state and change in biodiversity in riverine systems can be tracked at high resolution in a highly versatile manner.

Abstract Biodiversity loss in river ecosystems is much faster and more severe than in terrestrial systems, and spatial conservation and restoration plans are needed to halt this erosion. Reliable and highly resolved data on the state of and change in biodiversity and species distributions are critical for effective measures. However, high‐resolution maps of fish distribution remain limited for large riverine systems. Coupling data from global satellite sensors with broad‐scale environmental DNA (eDNA) and machine learning could enable rapid and precise mapping of the distribution of river organisms. Here, we investigated the potential for combining these methods using a fish eDNA dataset from 110 sites sampled along the full length of the Rhone River in Switzerland and France. Using Sentinel 2 and Landsat 8 images, we generated a set of ecological variables describing both the aquatic and the terrestrial habitats surrounding the river corridor. We combined these variables with eDNA‐based presence and absence data on 29 fish species and used three machine‐learning models to assess environmental suitability for these species. Most models showed good performance, indicating that ecological variables derived from remote sensing can approximate the ecological determinants of fish species distributions, but water‐derived variables had stronger associations than the terrestrial variables surrounding the river. The species range mapping indicated a significant transition in the species occupancy along the Rhone, from its source in the Swiss Alps to outlet into the Mediterranean Sea in southern France. Our study demonstrates the feasibility of combining remote sensing and eDNA to map species distributions in a large river. This method can be expanded to any large river to support conservation schemes.

Abstract Blue-green infrastructure (BGI), combining semi-natural and engineered elements, offers multifaceted benefits like stormwater management, water purification, heat mitigation, and habitat provision. However, current BGI designs prioritize engineering goals, overlooking its ecological potential. Here we advocate for integrating engineering and ecological objectives into BGI design to enhance performance and biodiversity. Through an interdisciplinary literature review, we emphasize the importance of species diversity, abundance, and ecological processes, to improve engineering performance and resilience, and lower management costs. We emphasize the importance of interdisciplinary collaboration to navigate trade-offs between engineering and ecological objectives, ultimately enabling us to engineer both for and with biodiversity.

Abstract Rivers are an important component of the global carbon cycle and contribute to atmospheric carbon exchange disproportionately to their total surface area. Largely, this is because rivers efficiently mobilize, transport and metabolize terrigenous organic matter (OM). Notably, our knowledge about the magnitude of globally relevant carbon fluxes strongly contrasts with our lack of understanding of the underlying processes that transform OM. Ultimately, OM processing en route to the oceans results from a diverse assemblage of consumers interacting with an equally diverse pool of resources in a spatially complex network of heterogeneous riverine habitats. To understand this interaction between consumers and OM, we must therefore account for spatial configuration, connectivity, and landscape context at scales ranging from local ecosystems to entire networks. Building such a spatially explicit framework of fluvial OM processing across scales may also help us to better predict poorly understood anthropogenic impacts on fluvial carbon cycling, for instance human-induced fragmentation and changes to flow regimes, including intermittence. Moreover, this framework must also account for the current unprecedented human-driven loss of biodiversity. This loss is at least partly due to mechanisms operating across spatial scales, such as interference with migration and habitat homogenization, and comes with largely unknown functional consequences. We advocate here for a comprehensive framework for fluvial networks connecting two spatially aware but disparate lines of research on (i) riverine metacommunities and biodiversity, and (ii) the biogeochemistry of rivers and their contribution to the global carbon cycle. We argue for a research agenda focusing on the regional scale—that is, of the entire river network—to enable a deeper mechanistic understanding of naturally arising biodiversity–ecosystem functioning coupling as a major driver of biogeochemically relevant riverine carbon fluxes.

Abstract Standard and easily accessible cross-thematic spatial databases are key resources in ecological research. In Switzerland, as in many other countries, available data are scattered across computer servers of research institutions and are rarely provided in standard formats (e.g., different extents or projections systems, inconsistent naming conventions). Consequently, their joint use can require heavy data management and geomatic operations. Here, we introduce SWECO25, a Swiss-wide raster database at 25-meter resolution gathering 5,265 layers. The 10 environmental categories included in SWECO25 are: geologic, topographic, bioclimatic, hydrologic, edaphic, land use and cover, population, transportation, vegetation, and remote sensing. SWECO25 layers were standardized to a common grid sharing the same resolution, extent, and geographic coordinate system. SWECO25 includes the standardized source data and newly calculated layers, such as those obtained by computing focal or distance statistics. SWECO25 layers were validated by a data integrity check, and we verified that the standardization procedure had a negligible effect on the output values. SWECO25 is available on Zenodo and is intended to be updated and extended regularly.

Abstract Subterranean ecosystems (comprising terrestrial, semi-aquatic, and aquatic components) are increasingly threatened by human activities; however, the current network of surface-protected areas is inadequate to safeguard subterranean biodiversity. Establishing protected areas for subterranean ecosystems is challenging. First, there are technical obstacles in mapping three-dimensional ecosystems with uncertain boundaries. Second, the rarity and endemism of subterranean organisms, combined with a scarcity of taxonomists, delays the accumulation of essential biodiversity knowledge. Third, establishing agreements to preserve subterranean ecosystems requires collaboration among multiple actors with often competing interests. This perspective addresses the challenges of preserving subterranean biodiversity through protected areas. Even in the face of uncertainties, we suggest it is both timely and critical to assess general criteria for subterranean biodiversity protection and implement them based on precautionary principles. To this end, we examine the current status of European protected areas and discuss solutions to improve their coverage of subterranean ecosystems.

Abstract The collection of environmental DNA (eDNA) and subsequent metabarcoding are useful tools for assessing marine fish biodiversity noninvasively. It is of particular importance to evaluate biodiversity in regions that are hard to access and thus less well studied. Sampling and preservation methods tailored to the specific circumstances are required. Aquatic eDNA is often captured on filters made of different materials and pore sizes, and subsequently stored under divergent conditions for varying periods of time. Previous studies on multispecies detection in marine systems have primarily focused on capture and extraction effects. Our study, in contrast, examined the effects of filter type, storage method, and storage time on DNA yield, alpha (i.e., ZOTU richness) and beta diversity (i.e., ZOTU composition) recovered from a marine ecosystem in Shark Bay, Western Australia. We compared two different filter types (cellulose‐nitrate filters with pore sizes of 0.45 μm; glass‐fiber filters with pore sizes of 0.1 μm), two storage methods (preservation in Longmire's solution and drying, respectively), various storage times (30–68 days) on two metabarcoding assays using different fish‐specific primers. Our results showed that storage time decreased DNA yield and affected alpha and beta diversity estimates. Cellulose‐nitrate filters stored in Longmire's solution proved to be the best combination with the smallest decrease in DNA yield, no effect on alpha diversity and consistent community compositions. Storing glass‐fiber filters in Longmire's solution led to a decrease in eDNA yield and alpha diversity estimates with increasing storage time. Furthermore, the largest change in beta diversity for each metabarcode was found for glass‐fiber filters regardless of storage method. Our results highlight the importance of considering storage time and interactions between storage method and filter when analyzing eDNA results, especially when storing samples for an extended time period or comparison of samples stored for different durations.

Eutrophication due to nutrient addition can result in major alterations in aquatic ecosystem productivity. Foundation species, individually and interactively, whether present as invasive species or as instruments of ecosystem management and restoration, can have unwanted effects like stabilizing turbid eutrophic states. In this study, we used whole-pond experimental manipulations to investigate the impacts of disturbance by nutrient additions in the presence and absence of two foundation species: Dreissena polymorpha (a freshwater mussel) and Myriophyllum spicatum (a macrophyte). We tracked how nutrient additions to ponds changed the prokaryotic and eukaryotic communities, using 16S, 18S, and COI amplicon sequencing. The nutrient disturbance and foundation species imposed strong selection on the prokaryotic communities, but not on the microbial eukaryotic communities. The prokaryotic communities changed increasingly over time as the nutrient disturbance intensified. Post-disturbance, the foundation species stabilized the prokaryotic communities as observed by the reduced rate of change in community composition. Our analysis suggests that prokaryotic community change contributed both directly and indirectly to major changes in ecosystem properties, including pH and dissolved oxygen. Our work shows that nutrient disturbance and foundation species strongly affect the prokaryotic community composition and stability, and that the presence of foundation species can, in some cases, promote the emergence and persistence of a turbid eutrophic ecosystem state.

Groundwater is a vast ecosystem harboring a high diversity of specialized taxa. Despite its diversity, groundwater is a still relatively unexplored and threatened ecosystem. Especially the linkage of groundwater with other ecosystems remains largely unknown from the perspective of groundwater fauna. Here, we used citizen science data to get a first baseline knowledge of the occurrence, diversity, and biomass of major macroinvertebrate groups found in shallow groundwater systems of Switzerland. We investigated all organisms collected from the groundwater in 346 spring catchment boxes of municipal drinking water providers. We morphologically identified the organisms on a broad taxonomic level and estimated their biomass and pigmentation using automated image processing. Crustaceans, particularly Niphargus and groundwater isopods, were the most common taxa of obligate groundwater organisms. We also found a surprisingly high number of macroinvertebrates associated with surface and subsurface ecosystems. These taxa might be accidentally entering the groundwater or use it as temporary habitat. In both cases they possibly contribute essential allochthonous energy imports from the surface. We found a positive relationship between the estimated biomass of macroinvertebrates in the samples and the occurrence and abundance of Niphargus. Owing to the widespread occurrences of surface and subsurface macroinvertebrates in our groundwater samples, our study provides evidence for common interactions between groundwater, soil, and surface ecosystems.

Abstract Groundwater is the physically largest freshwater ecosystem, yet one of the least explored habitats on earth, both because of accessing difficulties and the scarcity of the organisms inhabiting it. Here, we demonstrate how a two-fold approach provides complementary information on the occurrence and diversity of groundwater amphipods. Firstly, we used a citizen science approach in collaboration with municipal water providers who sampled groundwater organisms in their spring catchment boxes over multiple weeks, followed by DNA barcoding. Secondly, we collected four 10 L water samples at each site, in one sampling event, for environmental DNA (eDNA) metabarcoding. We found that citizen science was very effective in describing the distribution and abundance of groundwater amphipods. Although the single time-point of eDNA sampling did not detect as many amphipods, it allowed the assessment of the entire groundwater community, including microorganisms. By combining both methods, we found different amphipod species co-occurring with distinct sequences from the eDNA-metabarcoding dataset, representing mainly micro-eukaryotic species. We also found a distinct correlation between the diversity of amphipods and the overall biodiversity of groundwater organisms detected by eDNA at each site. We thus suggest that these approaches can be used to get a better understanding of subterranean biodiversity.

Abstract Molecular techniques using DNA retrieved from community or environmental samples, in particular environmental DNA (eDNA), are becoming increasingly popular for detecting individual species, assessing biodiversity, and quantifying ecological indices. More recently, eDNA has also been proposed as a template for population genetics, and several studies have already tested the feasibility of this approach, mostly looking at vertebrate species. Their results along with general opportunities offered by these types of “community‐based” samples, such as the possibility to target multiple species at the same time, have generated great enthusiasm and expectations for using eDNA in population genetics. However, not every aspect of population genetics can be addressed by eDNA‐based data and some inherent limitations may challenge its conclusions. Here, we firstly review the state of current knowledge of DNA retrieved from environmental and community samples for population genetics. Then, focusing on eDNA, we summarize the opportunities but also detail four main limitations of its use for population‐level inferences, namely, (1) the difficulty to retrieve a species‐specific dataset, (2) the potential lack of correlation between observed and true allelic frequencies, (3) the loss of individual information in multi‐locus genotyping and linkage between loci, and (4) the uncertainty about the individuals contributing to the sampled DNA pool (e.g., number, life‐stage, or sex). Some of these limitations might be overcome with the development of new technologies or models that account for the specificities of eDNA. Others, however, are inherent, and their effect on the inferences must be thoroughly evaluated. The possibility of gaining insights into genetic diversity and population structure from DNA retrieved from community and environmental samples is appealing for scientists, conservation managers, and other practitioners. Yet, to avoid false expectations and incorrect inferences, it is imperative that these limitations are known and considered alongside the opportunities and advantages.

Abstract Reliable and comparable estimates of biodiversity are the foundation for understanding ecological systems and informing policy and decision‐making, especially in an era of massive anthropogenic impacts on biodiversity. Environmental DNA (eDNA) metabarcoding is at the forefront of technological advances in biodiversity monitoring, and the last few years have seen major progress and solutions to technical challenges from the laboratory to bioinformatics. Water eDNA has been shown to allow the fast and efficient recovery of biodiversity signals, but the rapid pace of technological development has meant that some important principles regarding sampling design, which are well established in traditional biodiversity inventories, have been neglected. Using a spatially explicit river flow model, we illustrate how sampling must be adjusted to the size of the watercourse to increase the quality of the biodiversity signal recovered. We additionally investigate the effect of sampling parameters (volume, number of sites, sequencing depth) on detection probability in an empirical data set. Based on traditional sampling principles, we propose that aquatic eDNA sampling replication and volume must be scaled to match the organisms' and ecosystems' properties to provide reliable biodiversity estimates. We present a generalizable conceptual equation describing sampling features as a function of the size of the ecosystem monitored, the abundance of target organisms, and the properties of the sequencing procedure. The aim of this formalization is to enhance the standardization of critical steps in the design of biodiversity inventory studies using eDNA. More robust sampling standards will generate more comparable biodiversity data from eDNA, which is necessary for the method's long‐term plausibility and comparability.

Abstract 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 β-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 β-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 β-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.

Abstract Metabarcoding of environmental DNA (eDNA) is a powerful tool for describing biodiversity, such as finding keystone species or detecting invasive species in environmental samples. Continuous improvements in the method and the advances in sequencing platforms over the last decade have meant this approach is now widely used in biodiversity sciences and biomonitoring. For its general use, the method hinges on a correct identification of taxa. However, past studies have shown how this crucially depends on important decisions during sampling, sample processing, and subsequent handling of sequencing data. With no clear consensus as to the best practice, particularly the latter has led to varied bioinformatic approaches and recommendations for data preparation and taxonomic identification. In this study, using a large freshwater fish eDNA sequence dataset, we compared the frequently used zero‐radius Operational Taxonomic Unit (zOTU) approach of our raw reads and assigned it taxonomically (i) in combination with publicly available reference sequences (open databases) or (ii) with an OSU (Operational Sequence Units) database approach, using a curated database of reference sequences generated from specimen barcoding (closed database). We show both approaches gave comparable results for common species. However, the commonalities between the approaches decreased with read abundance and were thus less reliable and not comparable for rare species. The success of the zOTU approach depended on the suitability, rather than the size, of a reference database. Contrastingly, the OSU approach used reliable DNA sequences and thus often enabled species‐level identifications, yet this resolution decreased with the recent phylogenetic age of the species. We show the need to include target group coverage, outgroups and full taxonomic annotation in reference databases to avoid misleading annotations that can occur when using short amplicon sizes as commonly used in eDNA metabarcoding studies. Finally, we make general suggestions to improve the construction and use of reference databases for metabarcoding studies in the future.

Abstract Macroinvertebrates serve as key indicators in ecological assessments of aquatic ecosystems, where the composition and richness of their communities are indicative of environmental and anthropogenic change. Established monitoring of macroinvertebrates is expensive and time‐consuming, and relies on expert taxonomic knowledge. In contrast, biomonitoring based on molecular tools can support faster characterization of aquatic communities but needs validation for the target taxonomic groups and the study region. Here, we used data from a biomonitoring program covering a large biogeographic gradient to compare the routine kick‐net method with eDNA metabarcoding. We used two primer pairs targeting COI, one targeting a broad metazoan spectrum (mICOIintF/jgHCO2198) and another more recently developed primer pair optimized for the detection of freshwater invertebrates (fwhF2/EPTDr2n). We used the data of the macroinvertebrate monitoring with a focus on the orders of Ephemeroptera, Plecoptera, and Trichoptera across 92 rivers in Switzerland, covering four continental drainage basins and an elevational range from 198 to 1650 m a.s.l. Across all sample sites, the kick‐net detected more distinct taxa than either of the metabarcoding approaches. At a site level, however, both primer pairs detected on average more species. Comparing both primer pairs, the fwhF2/EPTDr2n primer pair captured more species assigned to the indicator groups Ephemeroptera, Plecoptera, and Trichoptera, and showed a significantly larger overlap with the kick‐net method. However, the community composition still varied significantly among the different metabarcoding approaches. Fewer Trichoptera species were recovered by eDNA, whereas the fwhF2/EPTDr2n primer pair detected more Plecopterans than the other two approaches. This study highlights the importance of the optimization and validation of novel molecular approaches under consideration of the target organismal group and the study area.

Aquatic (blue) and terrestrial (green) food webs are part of the same landscape, but it remains unclear whether they respond similarly to shared environmental gradients. Using long-term monitoring data from Switzerland and a metaweb approach, this study reveals how inferred blue and green food webs exhibit different properties along an elevation gradient and among land-use types.

IntroductionUnderstanding how species are distributed in space and how they interact with each other is central for scientific and conservation purposes. Species' distributions and interactions result from a complex interplay of local trophic dynamics, dispersal processes, resource availability, and abiotic factors governed by the landscape matrix, which also determines the spatial connectivity for organisms' dispersal and resource fluxes. River networks not only exhibit universal spatial structures, but their dendritic landscape structure is tightly linked to species and metacommunity processes therein.MethodsHere, using a mechanistic model of spatially connected food webs integrating both essential biological and hydrological aspects, we investigate how food-web properties vary in space, and how these patterns are influenced by key model parameters. We then contrast our predictions with a suite of null models, where different aspects (such as spatial structure or trophic interactions) of the spatial food-web model are alternatively relaxed.ResultsWe find that species richness is highest in areas where local nutrient load is maximal (lowland headwaters, according to our default assumption). Overall, species richness is positively associated with link density, modularity and omnivory, and negatively related to connectance, nestedness, and niche overlap. However, for metrics such as connectance and omnivory, stochasticity of trophic interactions is a much stronger predictor than spatial variables such as distance to outlet and drainage area. Remarkably, relationships between species richness and food-web metrics do not generally hold in null models, and are hence the outcome of coupled biological and physical (i.e., hydrological) processes characteristic to river networks.DiscussionOur model generates realistic patterns of species richness and food-web properties, shows that no universal food-web patterns emerge as a result of the riverine landscape structure, and paves the way for future applications aimed at disentangling metacommunity dynamics in river networks.

Abstract Biological assemblages are the result of dynamic processes that have explicit temporal and spatial dimensions. Although biodiversity patterns can be directly inferred from the structure of these assemblages, an assessment of changes through time and space is needed to understand how organisms initially assembled and how they are responding to local environmental and biotic factors. Small freshwater streams are particularly affected by contemporary anthropogenic activities and biological invasions, yet they are commonly less studied, as studies often focus on lakes and large streams. Here, we conducted a spatially explicit analysis of keystone shredder assemblages across eight years in 12 replicated small tributary streams. In each stream, we monitored multiple sites per kilometer of stream length. By assessing temporal beta diversity dynamics, defined by the gain or loss of species or abundance per species at individual sites, we show that changes in amphipod assemblages occur within the context of the surrounding terrestrial matrix and reflect recent amphipod colonization history. While amphipod composition was mostly constant in streams located in forested catchments, streams embedded in catchments with more extensive agricultural land use displayed more pronounced temporal changes, either driven by colonization of unoccupied upstream locations or by more pronounced but undirected fluctuations in gains and losses of species or abundance per species. Our study thus suggests that agricultural landscapes might destabilize aquatic amphipod assemblages, causing higher temporal changes in community structures and highlighting the vulnerability of aquatic ecosystems to terrestrial land use drivers.

Abstract River networks’ universal fractal structure not only defines their hydrology and connectivity, but has also profound biological consequences, especially regarding stability and persistence of organismal populations. While rivers’ scaling features are captured by Optimal Channel Networks, knowledge on adequate network topologies has hitherto been only partially transferred across geo- and biosciences. Consequently, ecologists have often studied riverine populations via random networks not respecting real rivers’ scaling character. Here we show that branching probability of random networks is a scale-dependent quantity in that it varies with the length scale or spatial resolution of observations. Therefore, our findings suggest that this property is not a robust driver of ecological dynamics. Moreover, we show that random networks lead to biased estimates of population stability and persistence, while only Optimal Channel Networks yield estimates comparable to real rivers. We hence advocate Optimal Channel Networks as model landscapes for realistic and generalizable projections of ecohydrological dynamics in riverine networks.

Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared three different approaches in order to better understand assessments of aquatic macroinvertebrate diversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species richness model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species richness model, that is, a generalized linear model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the kicknet and eDNA approaches, particularly at a local scale. We found the EPT-specific primer set fwhF2/EPTDr2n, detected a greater number of targeted EPT species compared to the more general primer set mlCOIintF/HCO2198. Moreover, we found that the species richness measured by eDNA from either primer set was poorly correlated to the richness measured by kicknet sampling (Pearson correlation = 0.27) and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the species richness model (Pearson correlation = 0.30 and 0.44, respectively). The weak relationships between the traditional kicknet sampling and eDNA with this model indicates inherent limitations in upscaling species richness estimates, and possibly a limited ability of the model to meet real world expectations. It is also possible that the number of replicates was not sufficient to detect ambiguous correlations. Future challenges include improving the accuracy and sensitivity of each approach individually, yet also acknowledging their respective limitations, in order to best meet stakeholder demands and address the biodiversity crisis we are facing.

By sampling environmental DNA across a large riverine network over multiple seasons, the varied dynamics between biodiversity and food-web dynamics are revealed.

Abstract Species react to environmental change via plastic and evolutionary responses. While both of them determine species’ survival, most studies quantify these responses individually. As species occur in communities, competing species may further influence their respective response to environmental change. Yet, how environmental change and competing species combined shape plastic and genetic responses to environmental change remains unclear. Quantifying how competition alters plastic and genetic responses of species to environmental change requires a trait-based, community and evolutionary ecological approach. We exposed unicellular aquatic organisms to long-term selection of increasing salinity—representing a common and relevant environmental change. We assessed plastic and genetic contributions to phenotypic change in biomass, cell shape, and dispersal ability along increasing levels of salinity in the presence and absence of competition. Trait changes in response to salinity were mainly due to mean trait evolution, and differed whether species evolved in the presence or absence of competition. Our results show that species’ evolutionary and plastic responses to environmental change depended both on competition and the magnitude of environmental change, ultimately determining species persistence. Our results suggest that understanding plastic and genetic responses to environmental change within a community will improve predictions of species’ persistence to environmental change.

Abstract Through the development of environmental DNA (eDNA) metabarcoding, in situ monitoring of organisms is becoming easier and promises a revolution in our approaches to detect changes in biodiversity over space and time. A cornerstone of eDNA approach is the development of primer pairs that allow amplifying the DNA of specific taxonomic groups, which is then used to link the DNA sequence to taxonomic identification. Here, we propose a framework for comparing primer pairs regarding (a) their capacity to bind and amplify a broad coverage of species within the target clade using in silico PCR, (b) their capacity to not only discriminate between species but also genera or families, and (c) their in situ specificity and efficiency across a variety of environments. As a case study, we focus on two mitochondrial 12S primer pairs, MiFish‐U and teleo, which were designed to amplify fishes. We found that the performance of in silico PCRs were high for both primer pairs, but teleo amplified more genera across Actinopterygii, Chondrichthyes, and Petromyzontomorphi than MiFish‐U. In contrast, the discriminatory power for species, genera, and families were higher for MiFish‐U than teleo, likely associated with the greater length of the amplified DNA fragments. The evaluation of their in situ efficiency showed a higher recovered species richness of teleo compared to MiFish‐U in tropical and temperate freshwater environments, but that generally both teleo and MiFish‐U primers pairs perform well to monitor fish species. Since more species were detected when used together, those primer pairs are best used in combination to increase the ability of species detection.

DNA-based taxon identification is improving the assessment and management of biodiversity in rivers. However, the lack of comprehensive DNA barcode reference libraries and globally highly unequal coverage are still hindering the application prospects of this method worldwide. Here, we analyzed the COI barcode gap in two reference libraries, Barcode of Life Data Systems (BOLD) and NCBI GenBank, with a focus on three aquatic animal groups (freshwater fish, aquatic insects and molluscs) in Chinese rivers. Our data show gaps in barcode coverage (e.g., organisms without barcodes) of ca. 40–70% of taxa in these groups in the BOLD or NCBI GenBank database, respectively. These gaps can rise even further if the barcode thresholds are set to contain at least five reference sequences per taxon. Furthermore, most barcodes are from non-local samples, and only 14.4% (BOLD) and 28.8% (NCBI GenBank) of reference sequences were from organisms sampled in China, respectively. The pairwise genetic distance of local barcodes is 3 to 5 times lower than non-local barcodes, indicating that the latter may not be a good substitute. When looking at individual catchments, ca. 60% of the potentially occurring aquatic species have one or more barcodes, yet the barcode coverage varies slightly across ten major river catchments, ranging from 54.3% (Liao River basin) to 68.2% (Huai River basin). The taxa Salmoniformes and Perciformes in freshwater fish, Odonata and Diptera in aquatic insects, and Bivalvia in molluscs have the best barcode coverage in most catchments (mean coverage >70%). This study gives the first overview and current status of barcode reference libraries of three major aquatic animal groups in Chinese rivers. Our results will help to better interpret current metabarcoding studies from China, and also provide a basis to develop a strategy of filling the gaps in the reference libraries of aquatic species in China.

Abstract Freshwater is vital to much life on Earth and is an essential resource for humans. Climate change, however, dramatically changes freshwater systems and reduces water quality, poses a risk to drinking water availability and has severe impacts on aquatic ecosystems and their biodiversity. The direct effects of climate change, such as increased temperatures and higher frequency of extreme meteorological events, interact with human responses to climate change, which we refer to here as ‘indirect effects’. The latter possibly have even greater impact than the direct effects of climate change. Specifically, changes in land‐use practices as responses to climate change, such as adjusted cropping regimes or a shift to renewable hydroelectricity to mitigate climate change, can very strongly affect freshwater ecosystems. Hitherto, these indirect effects and the possibility of idiosyncratic outcomes are under‐recognized. Here, we synthesize knowledge and identify threats to freshwater environments in alpine and pre‐alpine regions, which are particularly affected by climate change. We focus on the effects of adapted agriculture and hydropower production on freshwater quality and ecological status, as these examples have strong indirect effects that interact with direct effects of climate change (e.g., water temperature, droughts, isolation of populations). We outline how failure to effectively account for indirect effects associated with human responses to climate change may exacerbate direct climate change impacts on aquatic ecosystems. If managed properly, however, human responses to indirect effects offer potential for rapid and implementable leverage to mitigate some of the direct climate change effects on aquatic ecosystems. To better address looming risks, policy‐ and decisionmakers must account for indirect effects and incorporate them into restoration planning and the respective sectorial policies.