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 spatio-temporal 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 (TITAN2).  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.

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.

Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on difficult to define thresholds of distances, sequence similarity cutoffs, or monophyly. Most methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study is to use a naïve Bayesian classifier (Wang et al., 2007) to automate unsupervised taxonomic assignments for large batches of insect COI sequences such as data obtained from environmental barcoding using next generation sequencing platforms. This method provides rank-flexible taxonomic assignments with an associated bootstrap support value and it is faster than the BLAST-based methods commonly used in environmental sequence surveys. We have developed and rigorously tested the performance of three different training sets using leave-one-out cross-validation, two field datasets, and targeted testing of Lepidoptera, Diptera, and Mantodea sequences obtained from the Barcode of Life Data system. We found that type I error rates, incorrect taxonomic assignments with a high bootstrap support, were already relatively low but could be lowered further by ensuring that all query taxa are actually present in the reference database. Choosing bootstrap support cutoffs according to query length and summarizing taxonomic assignments to more inclusive ranks can also help to reduce error while retaining the maximum number of assignments. Additionally, we highlight gaps in the taxonomic and geographic representation of insects in public sequence databases that will require further work by taxonomists to improve the quality of assignments generated using any method.