Metabarcoding a Metacommunity: detecting change in a wetland wilderness

AbstractThe 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. Using multi-species 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 for the first time, quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were near 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.</jats:p

Network-Based Biomonitoring:Exploring Freshwater Food Webs With Stable Isotope Analysis and DNA Metabarcoding

Threatened freshwater ecosystems urgently require improved tools for effective management. Food web analysis is currently under-utilized, yet can be used to generate metrics to support biomonitoring assessments by measuring the stability and robustness of ecosystems. Using a previously developed analysis pipeline, we combined taxonomic outputs from DNA metabarcoding with a text-mining routine to extract trait information directly from the literature. This pipeline allowed us to generate heuristic food webs for sites within the lower Saint John/Wolastoq River and the Grand Lake Meadows (hereafter called the “GLM complex”), Atlantic Canada's largest freshwater wetland. While these food webs are derived from empirical traits and their structure has been shown to discriminate sites both spatially and temporally, the accuracy of their properties have not been assessed against other methods of trophic analysis. We explored two approaches to validate the utility of heuristic food webs. First, we qualitatively compared how well-trophic position derived from heuristic food webs recovered spatial and temporal differences across the GLM complex in comparison to traditional stable isotope approaches. Second, we explored how the trophic position of invertebrates, derived from heuristic food webs, predicted trophic position measured from δ 15N values. In general, both heuristic food webs and stable isotopes were able to detect seasonal changes in maximum trophic position in the GLM complex. Samples from the entire GLM complex demonstrated that prey-averaged trophic position measured from heuristic food webs strongly predicted trophic position inferred from stable isotopes (R 2 = 0.60), and even stronger relationships were observed for some individual models (R 2 = 0.78 for best model). Beyond their areas of congruence, heuristic food web and stable isotope analyses also appear to complement one another, suggesting a surprising degree of independence between community trophic niche width (assessed from stable isotopes) and food web size and complexity (assessed from heuristic food webs). Collectively, these analyses indicate that trait-based networks have properties that correspond to those of actual food webs, supporting the routine adoption of food web metrics for ecosystem biomonitoring

Flight movement and spatial distribution of immunomarked thrips in onion, potato, and tomato

The objective of this work was to evaluate the spatial distribution of thrips in different crops, and the correlation between meterological parameters and the flight movements of this pest, using immunomarking. The experiment was conducted in cultivated areas, with tomato (Solanum lycopersicum), potato (Solanum tuberosum), and onion (Allium cepa); and non-cultivated areas, with weedy plants. The areas with tomato (100 days), potato (20 days), and weeds were sprayed with casein, albumin, and soy milk, respectively, to mark adult thrips; however, the areas with onion (50 days) and tomato (10 days) were not sprayed. Thrips were captured with georeferenced blue sticky traps, transferred into tubes, and identified by treatment area with the Elisa test. The dependence between the samples and the capture distance was determined using geostatistics. Meteorlogical parameters were correlated with thrips density in each area. The three protein types used for immunomarking were detected in different proportions in the thrips. There was a correlation between casein-marked thrips and wind speed. The thrips flew a maximum distance of 3.5 km and dispersed from the older (tomato) to the younger crops (potato). The immunomarking method is efficient to mark large quantities of thrips