DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness

Bush, Alex and Monk, Wendy A. and Compson, Zacchaeus G. and Peters, Daniel L. and Porter, Teresita M. and Shokralla, Shadi and Wright, Michael T. G. and Hajibabaei, Mehrdad and Baird, Donald J. (2020) DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness. Proceedings of the National Academy of Sciences of the United States of America, 117 (15). pp. 8539-8545. ISSN 0027-8424

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Abstract

Too often, ecological monitoring studies are designed without understanding whether they have sufficient statistical power to detect changes beyond natural variability. The Peace–Athabasca Delta is North America’s largest inland delta, within a World Heritage area, and is currently threatened by human development. Using multispecies occupancy models we show that the wetland macroinvertebrate community is highly diverse, and spatial and temporal turnover are so high that composition is nearly random, emphasizing stochastic processes of assembly. Using DNA metabarcoding, our study detected more taxa, both overall and per sample, than traditional morphology-based sample processing, increasing our power to detect ecosystem change. Improving data quality and quantifying error are key to delivering effective monitoring and understanding the dynamic structure of the metacommunity.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.