In silico identification of multiple conserved motifs within the control region of Culicidae mitogenomes.

Mosquitoes are important vectors for human and animal diseases. Genetic markers, like the mitochondrial COI gene, can facilitate the taxonomic classification of disease vectors, vector-borne disease surveillance, and prevention. Within the control region (CR) of the mitochondrial genome, there exists a highly variable and poorly studied non-coding AT-rich area that contains the origin of replication. Although the CR hypervariable region has been used for species differentiation of some animals, few studies have investigated the mosquito CR. In this study, we analyze the mosquito mitogenome CR sequences from 125 species and 17 genera. We discovered four conserved motifs located 80 to 230 bp upstream of the 12S rRNA gene. Two of these motifs were found within all 392 Anopheles (An.) CR sequences while the other two motifs were identified in all 37 Culex (Cx.) CR sequences. However, only 3 of the 304 non-Culicidae Dipteran mitogenome CR sequences contained these motifs. Interestingly, the short motif found in all 37 Culex sequences had poly-A and poly-T stretch of similar length that is predicted to form a stable hairpin. We show that supervised learning using the frequency chaos game representation of the CR can be used to differentiate mosquito genera from their dipteran relatives.

The rheology of ultra-high molecular weight poly(ethylene oxide) dispersed in a low molecular weight carrier.

Gel spinning is the industrial method of choice for combining hydrophilic ultra-high molecular weight (UHMW) polymer resins with a hydrophobic support polymer to produce composite filaments for cytapheresis. Cytapheresis is a medical technique for removal of leukocytes from blood. Gel spinning is used to avoid high melt viscosity and thermal sensitivity of UHMW resins and the high melt temperature of the substrate resin but requires the recovery of toxic solvents. The UHMW resin is used because it forms a stable gel phase in the presence of water; a lower molecular weight resin (LMW) simply dissolves. UHMW and LMW resins were both poly(ethylene oxide) (PEO) and the substrate was polyarylsulfone (PAS). The literature indicated PEO undergoes non-oxidative thermal degradation above 200 °C and PAS is processed up to 350 °C. Dynamic oscillatory shear rheometry was used to study 0, 25, 40, 50, 60, and 75 wt. % UHMW PEO in LMW PEO to take advantage of the sensitivity of viscosity to changes in molecular weight and material configuration, indicating degradation. Samples were exposed to 220 °C, 230 °C, 240 °C, 250 °C, 275 °C, and 300 °C temperatures for 5 min to explore conditions that could result in sample degradation. The viscosity decreased less with increasing UHMW PEO content for samples exposed to the same temperature and the viscosity decreased more with increasing exposure temperature for samples with the same UHMW PEO content. Parameters were regressed from observed data to predict the change in molecular weight via empiricisms relating the viscosity to molecular weight, shear rate, temperature, and time.

A global agenda for advancing freshwater biodiversity research.

Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.

Riparian and in-channel habitat properties linked to dragonfly emergence.

In freshwater ecosystems, habitat alteration contributes directly to biodiversity loss. Dragonflies are sentinel species that are key invertebrate predators in both aquatic (as larvae) and terrestrial ecosystems (as adults). Understanding the habitat factors affecting dragonfly emergence can inform management practices to conserve habitats supporting these species and the functions they perform. Transitioning from larvae to adults, dragonflies leave behind larval exoskeletons (exuviae), which reveal information about the emergent population without the need for sacrificing living organisms. Capitalizing on Atlantic Canada's largest freshwater wetland, the Grand Lake Meadows (GLM) and the associated Saint John/Wolastoq River (SJWR), we studied the spatial (i.e., across the mainstem, tributary, and wetland sites) and temporal (across 3 years) variation in assemblages of emergent dragonflies (Anisoptera) and assessed the relative contribution of aquatic and terrestrial factors structuring these assemblages. The GLM complex, including the lotic SJWR and its tributaries and associated lentic wetlands, provided a range of riparian and aquatic habitat variability ideal for studying dragonfly emergence patterns across a relatively homogenous climatic region. Emergent dragonfly responses were associated with spatial, but not temporal, variation. Additionally, dragonfly communities were associated with both aquatic and terrestrial factors, while diversity was primarily associated with terrestrial factors. Specific terrestrial factors associated with the emergence of the dragonfly community included canopy cover and slope, while aquatic factors included water temperature, dissolved oxygen, and baseflow. Our results indicate that management of river habitats for dragonfly conservation should incorporate riparian habitat protection while maintaining aquatic habitat and habitat quality.

DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness.

The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large scales. The Peace-Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification and DNA metabarcoding. By using multispecies occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera and quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were nearly random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

The Ecobiomics project: Advancing metagenomics assessment of soil health and freshwater quality in Canada.

Transformative advances in metagenomics are providing an unprecedented ability to characterize the enormous diversity of microorganisms and invertebrates sustaining soil health and water quality. These advances are enabling a better recognition of the ecological linkages between soil and water, and the biodiversity exchanges between these two reservoirs. They are also providing new perspectives for understanding microorganisms and invertebrates as part of interacting communities (i.e. microbiomes and zoobiomes), and considering plants, animals, and humans as holobionts comprised of their own cells as well as diverse microorganisms and invertebrates often acquired from soil and water. The Government of Canada's Genomics Research and Development Initiative (GRDI) launched the Ecobiomics Project to coordinate metagenomics capacity building across federal departments, and to apply metagenomics to better characterize microbial and invertebrate biodiversity for advancing environmental assessment, monitoring, and remediation activities. The Project has adopted standard methods for soil, water, and invertebrate sampling, collection and provenance of metadata, and nucleic acid extraction. High-throughput sequencing is located at a centralized sequencing facility. A centralized Bioinformatics Platform was established to enable a novel government-wide approach to harmonize metagenomics data collection, storage and bioinformatics analyses. Sixteen research projects were initiated under Soil Microbiome, Aquatic Microbiome, and Invertebrate Zoobiome Themes. Genomic observatories were established at long-term environmental monitoring sites for providing more comprehensive biodiversity reference points to assess environmental change.

Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples.

Biomonitoring programs have evolved beyond the sole use of morphological identification to determine the composition of invertebrate species assemblages in an array of ecosystems. The application of DNA metabarcoding in freshwater systems for assessing benthic invertebrate communities is now being employed to generate biological information for environmental monitoring and assessment. A possible shift from the extraction of DNA from net-collected bulk benthic samples to its extraction directly from water samples for metabarcoding has generated considerable interest based on the assumption that taxon detectability is comparable when using either method. To test this, we studied paired water and benthos samples from a taxon-rich wetland complex, to investigate differences in the detection of arthropod taxa from each sample type. We demonstrate that metabarcoding of DNA extracted directly from water samples is a poor surrogate for DNA extracted from bulk benthic samples, focusing on key bioindicator groups. Our results continue to support the use of bulk benthic samples as a basis for metabarcoding-based biomonitoring, with nearly three times greater total richness in benthic samples compared to water samples. We also demonstrated that few arthropod taxa are shared between collection methods, with a notable lack of key bioindicator EPTO taxa in the water samples. Although species coverage in water could likely be improved through increased sample replication and/or increased sequencing depth, benthic samples remain the most representative, cost-effective method of generating aquatic compositional information via metabarcoding.

Urbanisation of floodplain ecosystems: Weight-of-evidence and network meta-analysis elucidate multiple stressor pathways.

Freshwater floodplains are dynamic, diverse ecosystems that represent important transition zones between terrestrial, riparian, subsurface and aquatic habitats. Given their historic importance in human development, floodplains have been exposed to a variety of pressures, which in combination have been instrumental in driving changes within these ecosystems. Here, we present an evidence-based framework to explore direct and indirect effects of pressures and stressors on floodplain ecosystems and test this structure within the urban landscape. Evidence was obtained from peer-reviewed scientific literature, focusing on effects of key pressures and stressors on receptors, including species composition (e.g., species presence-absence, diversity) and ecosystem function (e.g., biomass, decomposition). The strength of direct and indirect effects of individual and multiple stressors on biological receptors was quantified using two separate analyses: an evidence-weighted analysis and a quantitative network meta-analysis using data extracted from 131 studies. Results demonstrate the power of adopting a systematic framework to advance quantitative assessment of floodplain ecosystems affected by multiple stressors. While direct pathways were generally stronger and provided the core network skeleton, there were many more significant indirect pathways indicating evidence gaps in our mechanistic understanding of these processes. Indeed, the importance of indirect pathways (e.g. increase in impervious surface → increase in the accumulation rate of sediment nutrients) suggests that embracing complexity in network meta-analysis is a necessary step in revealing a more complete snapshot of the network. Results from the weight-of-evidence approach generally mirrored the direct pathway structure and demonstrated the strength of incorporating study quality alongside data sufficiency. Networks illustrated novel disturbance pathways (e.g., decrease in habitat structure → decrease in structure and function of aquatic and riparian assemblages) that can be used for hypothesis generation for future scientific enquiries. Our results highlight the broader applicability of adopting the proposed framework for assessing complex environments, such as floodplains.

Towards a general framework for the assessment of interactive effects of multiple stressors on aquatic ecosystems: Results from the Making Aquatic Ecosystems Great Again (MAEGA) workshop.

A workshop was held in Wageningen, The Netherlands, in September 2017 to collate data and literature on three aquatic ecosystem types (agricultural drainage ditches, urban floodplains, and urban estuaries), and develop a general framework for the assessment of multiple stressors on the structure and functioning of these systems. An assessment framework considering multiple stressors is crucial for our understanding of ecosystem responses within a multiply stressed environment, and to inform appropriate environmental management strategies. The framework consists of two components: (i) problem identification and (ii) impact assessment. Both assessments together proceed through the following steps: 1) ecosystem selection; 2) identification of stressors and quantification of their intensity; 3) identification of receptors or sensitive groups for each stressor; 4) identification of stressor-response relationships and their potential interactions; 5) construction of an ecological model that includes relevant functional groups and endpoints; 6) prediction of impacts of multiple stressors, 7) confirmation of these predictions with experimental and monitoring data, and 8) potential adjustment of the ecological model. Steps 7 and 8 allow the assessment to be adaptive and can be repeated until a satisfactory match between model predictions and experimental and monitoring data has been obtained. This paper is the preface of the MAEGA (Making Aquatic Ecosystems Great Again) special section that includes three associated papers which are also published in this volume, which present applications of the framework for each of the three aquatic systems.

Vulnerability of diatom communities in the Peace-Athabasca Delta to environmental change.

Habitat degradation associated with resource development is a major ecological concern, particularly in Canada's boreal zone where limited information on biodiversity is available. Habitat degradation can lead to reductions in biodiversity and ecosystem function, especially when drivers of variability and diversity patterns have not been identified for a region of interest. In this study, the distribution of diatom genera in the Peace-Athabasca Delta in northeastern Alberta was examined in relation to seasonal, geographic, and alkalinity gradients. Grab samples of six abiotic variables (total dissolved nitrogen, total dissolved phosphorus, dissolved iron, turbidity, pH, and specific conductance (SPC)) were taken from 12 remote wetlands over three sampling periods, and regressed against an ordination of diatom community composition to identify key environmental drivers of diatom community variation. Indirect gradient analysis identified two major gradients among sites. First, separation of sites among sampling periods showed successional seasonal changes in diatom community composition. Second, separation of sites from the Peace sub-delta and Birch sub-delta showed a gradient of geographic separation. Direct gradient analysis failed to explain the underlying drivers of these two gradients, but did show that alkalinity is a key driver of diatom community composition in the Embarras sub-delta, and that these sites could be particularly vulnerable to community changes associated with acidification.

Omics Advances in Ecotoxicology.

Toxic substances in the environment generate adverse effects at all levels of biological organization from the molecular level to community and ecosystem. Given this complexity, it is not surprising that ecotoxicologists have struggled to address the full consequences of toxic substance release at ecosystem level, due to the limits of observational and experimental tools to reveal the changes in deep structure at different levels of organization. -Omics technologies, consisting of genomics and ecogenomics, have the power to reveal, in unprecedented detail, the cellular processes of an individual or biodiversity of a community in response to environmental change with high sample/observation throughput. This represents a historic opportunity to transform the way we study toxic substances in ecosystems, through direct linkage of ecological effects with the systems biology of organisms. Three recent examples of -omics advance in the assessment of toxic substances are explored here: (1) the use of functional genomics in the discovery of novel molecular mechanisms of toxicity of chemicals in the environment; (2) the development of laboratory pipelines of dose-dependent, reduced transcriptomics to support high-throughput chemical testing at the biological pathway level; and (3) the use of eDNA metabarcoding approaches for assessing chemical effects on biological communities in mesocosm experiments and through direct observation in field monitoring. -Omics advances in ecotoxicological studies not only generate new knowledge regarding mechanisms of toxicity and environmental effect, improving the relevance and immediacy of laboratory toxicological assessment, but can provide a wholly new paradigm for ecotoxicology by linking ecological models to mechanism-based, systems biology approaches.

Shifts of community composition and population density substantially affect ecosystem function despite invariant richness.

There has been considerable focus on the impacts of environmental change on ecosystem function arising from changes in species richness. However, environmental change may affect ecosystem function without affecting richness, most notably by affecting population densities and community composition. Using a theoretical model, we find that, despite invariant richness, (1) small environmental effects may already lead to a collapse of function; (2) competitive strength may be a less important determinant of ecosystem function change than the selectivity of the environmental change driver and (3) effects on ecosystem function increase when effects on composition are larger. We also present a complementary statistical analysis of 13 data sets of phytoplankton and periphyton communities exposed to chemical stressors and show that effects on primary production under invariant richness ranged from -75% to +10%. We conclude that environmental protection goals relying on measures of richness could underestimate ecological impacts of environmental change.

Reintroducing Environmental Change Drivers in Biodiversity-Ecosystem Functioning Research.

For the past 20 years, research on biodiversity and ecosystem functioning (B-EF) has only implicitly considered the underlying role of environmental change. We illustrate that explicitly reintroducing environmental change drivers in B-EF research is needed to predict the functioning of ecosystems facing changes in biodiversity. Next we show how this reintroduction improves experimental control over community composition and structure, which helps to provide mechanistic insight on how multiple aspects of biodiversity relate to function and how biodiversity and function relate in food webs. We also highlight challenges for the proposed reintroduction and suggest analyses and experiments to better understand how random biodiversity changes, as studied by classic approaches in B-EF research, contribute to the shifts in function that follow environmental change.

A new way to contemplate Darwin's tangled bank: how DNA barcodes are reconnecting biodiversity science and biomonitoring.

Encompassing the breadth of biodiversity in biomonitoring programmes has been frustrated by an inability to simultaneously identify large numbers of species accurately and in a timely fashion. Biomonitoring infers the state of an ecosystem from samples collected and identified using the best available taxonomic knowledge. The advent of DNA barcoding has now given way to the extraction of bulk DNA from mixed samples of organisms in environmental samples through the development of high-throughput sequencing (HTS). This DNA metabarcoding approach allows an unprecedented view of the true breadth and depth of biodiversity, but its adoption poses two important challenges. First, bioinformatics techniques must simultaneously perform complex analyses of large datasets and translate the results of these analyses to a range of users. Second, the insights gained from HTS need to be amalgamated with concepts such as Linnaean taxonomy and indicator species, which are less comprehensive but more intuitive. It is clear that we are moving beyond proof-of-concept studies to address the challenge of implementation of this new approach for environmental monitoring and regulation. Interpreting Darwin's 'tangled bank' through a DNA lens is now a reality, but the question remains: how can this information be generated and used reliably, and how does it relate to accepted norms in ecosystem study?This article is part of the themed issue 'From DNA barcodes to biomes'.

Large-Scale Monitoring of Plants through Environmental DNA Metabarcoding of Soil: Recovery, Resolution, and Annotation of Four DNA Markers.

In a rapidly changing world we need methods to efficiently assess biodiversity in order to monitor ecosystem trends. Ecological monitoring often uses plant community composition to infer quality of sites but conventional aboveground surveys only capture a snapshot of the actively growing plant diversity. Environmental DNA (eDNA) extracted from soil samples, however, can include taxa represented by both active and dormant tissues, seeds, pollen, and detritus. Analysis of this eDNA through DNA metabarcoding provides a more comprehensive view of plant diversity at a site from a single assessment but it is not clear which DNA markers are best used to capture this diversity. Sequence recovery, annotation, and sequence resolution among taxa were evaluated for four established DNA markers (matK, rbcL, ITS2, and the trnL P6 loop) in silico using database sequences and in situ using high throughput sequencing of 35 soil samples from a remote boreal wetland. Overall, ITS2 and rbcL are recommended for DNA metabarcoding of vascular plants from eDNA when not using customized or geographically restricted reference databases. We describe a new framework for evaluating DNA metabarcodes and, contrary to existing assumptions, we found that full length DNA barcode regions could outperform shorter markers for surveying plant diversity from soil samples. By using current DNA barcoding markers rbcL and ITS2 for plant metabarcoding, we can take advantage of existing resources such as the growing DNA barcode database. Our work establishes the value of standard DNA barcodes for soil plant eDNA analysis in ecological investigations and biomonitoring programs and supports the collaborative development of DNA barcoding and metabarcoding.

Ribosomal DNA and Plastid Markers Used to Sample Fungal and Plant Communities from Wetland Soils Reveals Complementary Biotas.

Though the use of metagenomic methods to sample below-ground fungal communities is common, the use of similar methods to sample plants from their underground structures is not. In this study we use high throughput sequencing of the ribulose-bisphosphate carboxylase large subunit (rbcL) plastid marker to study the plant community as well as the internal transcribed spacer and large subunit ribosomal DNA (rDNA) markers to investigate the fungal community from two wetland sites. Observed community richness and composition varied by marker. The two rDNA markers detected complementary sets of fungal taxa and total fungal composition clustered according to primer rather than by site. The composition of the most abundant plants, however, clustered according to sites as expected. We suggest that future studies consider using multiple genetic markers, ideally generated from different primer sets, to detect a more taxonomically diverse suite of taxa compared with what can be detected by any single marker alone. Conclusions drawn from the presence of even the most frequently observed taxa should be made with caution without corroborating lines of evidence.

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing.

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users.

FORUM: Ecological networks: the missing links in biomonitoring science.

Monitoring anthropogenic impacts is essential for managing and conserving ecosystems, yet current biomonitoring approaches lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems.Ecological networks (trophic or mutualistic) can offer new insights into ecosystem degradation, adding value to current taxonomically constrained schemes. We highlight some examples to show how new network approaches can be used to interpret ecological responses.Synthesis and applications. Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground-truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network-based perspective.

GenGIS 2: geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework.

GenGIS is free and open source software designed to integrate biodiversity data with a digital map and information about geography and habitat. While originally developed with microbial community analyses and phylogeography in mind, GenGIS has been applied to a wide range of datasets. A key feature of GenGIS is the ability to test geographic axes that can correspond to routes of migration or gradients that influence community similarity. Here we introduce GenGIS version 2, which extends the linear gradient tests introduced in the first version to allow comprehensive testing of all possible linear geographic axes. GenGIS v2 also includes a new plugin framework that supports the development and use of graphically driven analysis packages: initial plugins include implementations of linear regression and the Mantel test, calculations of alpha-diversity (e.g., Shannon Index) for all samples, and geographic visualizations of dissimilarity matrices. We have also implemented a recently published method for biomonitoring reference condition analysis (RCA), which compares observed species richness and diversity to predicted values to determine whether a given site has been impacted. The newest version of GenGIS supports vector data in addition to raster files. We demonstrate the new features of GenGIS by performing a full gradient analysis of an Australian kangaroo apple data set, by using plugins and embedded statistical commands to analyze human microbiome sample data, and by applying RCA to a set of samples from Atlantic Canada. GenGIS release versions, tutorials and documentation are freely available at http://kiwi.cs.dal.ca/GenGIS, and source code is available at https://github.com/beiko-lab/gengis.