Monitoring Groundwater Health Using Citizen Scientists in Semi-Arid Regional Australia.

Citizen science (CS) around the world is undergoing a resurgence, potentially due to the utilization of new technologies and methods to capture information, such as data and photo entry via mobile phone apps. CS has been used in aquatic ecology for several decades, however the use of volunteers to collect data in groundwaters has rarely occurred. Groundwater research, particularly groundwater ecosystems, is unevenly distributed across the world, limiting our knowledge of these ecosystems and their functions. Here, we engaged six volunteer farmers in semi-arid region of north-western New South Wales, Australia to participate in an assessment of groundwater health using privately owned wells. Volunteers were supplied with sampling kits and instructions on sampling methods. Data retrieved indicated the health of the groundwater ecosystems, simultaneously providing information on water quality and groundwater biota present within the farm aquifers. Diverse stygofauna were collected from the trial, which reflected historical records of stygofauna within the same catchment indicating the viability of using citizen scientist for data collection. The citizen science project not only aided the collection of data and assessment of groundwater health, but also provided a tool for education, attracting media attention which furthered the education to a national audience. The amount of data still required to understand groundwater ecosystems, combined with the urgency to manage these environments, suggests that citizen scientists may complement the efforts of scientists around the globe to establish the impacts and consequences of human activities on this resource.

Urbanisation of floodplain ecosystems: Weight-of-evidence and network meta-analysis elucidate multiple stressor pathways.

Freshwater floodplains are dynamic, diverse ecosystems that represent important transition zones between terrestrial, riparian, subsurface and aquatic habitats. Given their historic importance in human development, floodplains have been exposed to a variety of pressures, which in combination have been instrumental in driving changes within these ecosystems. Here, we present an evidence-based framework to explore direct and indirect effects of pressures and stressors on floodplain ecosystems and test this structure within the urban landscape. Evidence was obtained from peer-reviewed scientific literature, focusing on effects of key pressures and stressors on receptors, including species composition (e.g., species presence-absence, diversity) and ecosystem function (e.g., biomass, decomposition). The strength of direct and indirect effects of individual and multiple stressors on biological receptors was quantified using two separate analyses: an evidence-weighted analysis and a quantitative network meta-analysis using data extracted from 131 studies. Results demonstrate the power of adopting a systematic framework to advance quantitative assessment of floodplain ecosystems affected by multiple stressors. While direct pathways were generally stronger and provided the core network skeleton, there were many more significant indirect pathways indicating evidence gaps in our mechanistic understanding of these processes. Indeed, the importance of indirect pathways (e.g. increase in impervious surface → increase in the accumulation rate of sediment nutrients) suggests that embracing complexity in network meta-analysis is a necessary step in revealing a more complete snapshot of the network. Results from the weight-of-evidence approach generally mirrored the direct pathway structure and demonstrated the strength of incorporating study quality alongside data sufficiency. Networks illustrated novel disturbance pathways (e.g., decrease in habitat structure → decrease in structure and function of aquatic and riparian assemblages) that can be used for hypothesis generation for future scientific enquiries. Our results highlight the broader applicability of adopting the proposed framework for assessing complex environments, such as floodplains.