TICI: a taxon-independent community index for eDNA-based ecological health assessment.

Global biodiversity is declining at an ever-increasing rate. Yet effective policies to mitigate or reverse these declines require ecosystem condition data that are rarely available. Morphology-based bioassessment methods are difficult to scale, limited in scope, suffer prohibitive costs, require skilled taxonomists, and can be applied inconsistently between practitioners. Environmental DNA (eDNA) metabarcoding offers a powerful, reproducible and scalable solution that can survey across the tree-of-life with relatively low cost and minimal expertise for sample collection. However, there remains a need to condense the complex, multidimensional community information into simple, interpretable metrics of ecological health for environmental management purposes. We developed a riverine taxon-independent community index (TICI) that objectively assigns indicator values to amplicon sequence variants (ASVs), and significantly improves the statistical power and utility of eDNA-based bioassessments. The TICI model training step uses the Chessman iterative learning algorithm to assign health indicator scores to a large number of ASVs that are commonly encountered across a wide geographic range. New sites can then be evaluated for ecological health by averaging the indicator value of the ASVs present at the site. We trained a TICI model on an eDNA dataset from 53 well-studied riverine monitoring sites across New Zealand, each sampled with a high level of biological replication (n = 16). Eight short-amplicon metabarcoding assays were used to generate data from a broad taxonomic range, including bacteria, microeukaryotes, fungi, plants, and animals. Site-specific TICI scores were strongly correlated with historical stream condition scores from macroinvertebrate assessments (macroinvertebrate community index or MCI; R2 = 0.82), and TICI variation between sample replicates was minimal (CV = 0.013). Taken together, this demonstrates the potential for taxon-independent eDNA analysis to provide a reliable, robust and low-cost assessment of ecological health that is accessible to environmental managers, decision makers, and the wider community.

Lake morphological characteristics and climatic factors affect long-term trends of phytoplankton community in the Rotorua Te Arawa lakes, New Zealand during 23 years observation.

Monitoring the long-term dynamics of lake phytoplankton can help understand their natural temporal variability, as well as assess potential impacts of interventions aimed at improving lake ecological condition. However, investigating long-term changes in lake ecosystems has received scant attention. In the present study, we analyzed a long-term dataset of phytoplankton communities collected from 1990 to 2013 from eleven of the 12 Rotorua Te Arawa lakes in New Zealand, to explore their responses to changing abiotic conditions. We used a sequential algorithm to examine the likelihood of regime shifts in abiotic and biotic factors during the study period that could be attributable to lake interventions. Our analysis suggests that lake interventions have improved the abiotic factors, whereas the response of biotic factors was less clear. Total phosphorus levels were implicated in the decline in lake condition, including in two lakes subject to lake interventions, and in four control lakes. Both abiotic and biotic factors showed diverse trends (e.g., increase, decrease or no change), and abiotic factors had more regime shifts than biotic factors. Shifts in biotic indices also displayed time lags to shifts in abiotic factors. Long-term responses of abiotic and biotic factors were also influenced by lake morphological characteristics and climatic variables. This latter finding underscores the importance of considering lake morphological characteristics and climate changes when planning management practices. A sound understanding of resilience and threshold of phytoplankton shifts to environmental changes are needed to assess the effectiveness of previous management strategies and prioritize the future conservation efforts toward water quality goals.

Dam design can impede adaptive management of environmental flows: a case study from the Opuha Dam, New Zealand.

The Opuha Dam was designed for water storage, hydropower, and to augment summer low flows. Following its commissioning in 1999, algal blooms (dominated first by Phormidium and later Didymosphenia geminata) downstream of the dam were attributed to the reduced frequency and magnitude of high-flow events. In this study, we used a 20-year monitoring dataset to quantify changes associated with the dam. We also studied the effectiveness of flushing flows to remove periphyton from the river bed. Following the completion of the dam, daily maximum flows downstream have exceeded 100 m(3) s(-1) only three times; two of these floods exceeded the pre-dam mean annual flood of 203 m(3) s(-1) (compared to 19 times >100 m(3) s(-1) and 6 times >203 m(3) s(-1) in the 8 years of record before the dam). Other changes downstream included increases in water temperature, bed armoring, frequency of algal blooms, and changes to the aquatic invertebrate community. Seven experimental flushing flows resulted in limited periphyton reductions. Flood wave attenuation, bed armoring, and a shortage of surface sand and gravel, likely limited the effectiveness of these moderate floods. Floods similar to pre-dam levels may be effective for control of periphyton downstream; however, flushing flows of that magnitude are not possible with the existing dam infrastructure. These results highlight the need for dams to be planned and built with the capacity to provide the natural range of flows for adaptive management, particularly high flows.