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The biodiversity–ecosystem function hypothesis postulates that higher biodiversity is correlated with faster ecosystem process rates and increased ecosystem stability in fluctuating environments. Exhibiting high spatiotemporal habitat diversity, floodplains are highly productive ecosystems, supporting communities that are naturally resilient and highly diverse.We examined linkages among floodplain wetland habitats, invertebrate communities and their associated traits, and ecosystem function across 60 sites within the floodplain wetlands of the lower Wolastoq | Saint John River, New Brunswick, using structural equation modelling and Threshold Indicator Taxa ANalysis.We identified key environmental filters structuring invertebrate communities, by linking increased niche differentiation through shoreline change, flood pulse dynamics, and macrophyte bed complexity with increased taxa and functional diversity.Examination of traits linked to ecosystem functions revealed that more resilient wetlands with balance between primary productivity and decomposition as carbon sources were associated with greater functional evenness and richness, while habitat patches with elevated decomposition rates had lower functional richness, reflecting a simplified, more disturbed habitat.While our more complex overarching SEM model was ultimately compromised by an overspecified number of pathways, our results nevertheless are indicative of a divergence between wetland and riverine ecosystems in their relationships linking biodiversity and ecosystem function, illustrating how to define ecosystem health in wetland habitats, and demonstrating how critical functions support healthy wetland habitats by providing increased resilience to disturbance. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Preservation of DNA in bulk environmental samples is conventionally achieved using ethanol; however, transportation restrictions on ethanol, particularly from remote locations, are problematic, and ethanol requires a lengthy evaporation period to avoid polymerase chain reaction inhibition. We examined the efficacy of an easily accessible, non-toxic, propylene glycol-based antifreeze as an alternative to molecular-grade ethanol for preserving macroinvertebrate DNA from bulk-benthos DNA samples. We used 2 processing methods (no evaporation of preservative vs full evaporation) to test the differences in both cytochrome oxidase I (COI) exact sequence variants (ESVs) and COI taxonomic orders detected in both ethanol- and antifreeze-preserved samples. Our results suggest that antifreeze is a suitable alternative to ethanol for preservation of DNA in freshly collected samples (e.g., up to 3 d) because of the comparable ESV richness detected in antifreeze-preserved samples. We have demonstrated that by using antifreeze, it is possible to achieve sufficient taxonomic coverage and assess macroinvertebrate assemblages within bulk-benthos DNA samples. The application of this non-regulated preservative is particularly important for remote sampling (i.e., only air accessible) and sampling for community-based biomonitoring projects within Indigenous territories where alcohol is prohibited or not available. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Ecological networks are powerful tools for visualizing biodiversity data and assessing ecosystem health and function. Constructing these networks requires considerable empirical efforts, and this remains highly challenging due to sampling limitations and the laborious and notoriously limited, error-prone process of traditional taxonomic identification. Recent advancements in high-throughput gene sequencing and high-performance computing provide new ways to address these challenges. DNA metabarcoding, a method of bulk taxonomic identification from DNA extracted from environmental samples, can generate detailed biodiversity information through a standardizable analytical pipeline for species detection. When this biodiversity information is annotated with prior knowledge on taxon interactions, body size, and trophic position, it is possible to generate trait-based networks, which we call "heuristic food webs". Although curating trait matrices for constructing heuristic food webs is a laborious, often intractable process using manual literature surveys, it can be greatly accelerated via text mining, allowing knowledge of relevant traits to be gathered across large databases. To explore this possibility, we employed a General Architecture for Text Engineering (GATE) system to create a hybrid text-mining pipeline combining rule-based and machine-learning modules. This pipeline was then used to query online repositories of published papers for missing data on a key trait, body size, that could not be gathered from existing trophic link libraries of freshwater benthic macroinvertebrates. Combining text-mined body size information with feeding information from existing sources allowed us to generate a database of over 20,000 pairwise trophic interactions. Next, we developed a pipeline that uses taxa lists generated from DNA metabarcoding and annotates this matrix with trophic information from existing databases and text-mined body size data. In this way, we generated heuristic food webs for wetland sites within a large delta complex formed by the confluence of the Peace and Athabasca rivers in northern Alberta: the Peace-Athabasca delta. Finally, we used these putative food webs and their network properties to resolve spatial and temporal differences between the benthic subwebs of wetlands in the Peace and Athabasca sectors of the delta complex. Specifically, we asked two questions. (1) How do food web properties (e.g. number of links, linkage density, trophic height) differ between the wetlands of the Peace and Athabasca deltas? (2) How do food web properties change temporally in wetlands of the two deltas? We discuss using DNA-generated, trait-based food webs as a powerful tool for rapid bioassessment, assess the limitations of our current approach, and outline a path forward to make this powerful tool more widely available for land managers and conservation biologists. [ABSTRACT FROM AUTHOR]