New light in the dark - a proposed multidisciplinary framework for studying functional ecology of groundwater fauna

Groundwaters provide the vast majority of unfrozen freshwater resources on the planet, but our knowledge of subsurface ecosystems is surprisingly limited. Stygofauna, or stygobionts -subterranean obligate aquatic animals - provide ecosystem services such as grazing biofilms and maintaining water quality, but we know little about how their ecosystems function. The cryptic nature of groundwaters, together with the high degree of local endemism and stygofaunal site-specific adaptations, represent major obstacles for the field. To overcome these challenges, and integrate biodiversity and ecosystem function, requires a holistic design drawing on classical ecology, taxonomy, molecular ecology and geochemistry. This study presents an approach based on the integration of existing concepts in groundwater ecology with three more novel scientific techniques: compound specific stable isotope analysis (CSIA) of amino acids, radiocarbon analysis ( ¹⁴ C) and DNA analyses of environmental samples, stygofauna and gut contents. The combination of these techniques allows elucidation of aspects of ecosystem function that are often obscured in small invertebrates and cryptic systems. Carbon (δ ¹³ C) and nitrogen (δ ¹⁵ N) CSIA provides a linkage between biogeochemical patterns and ecological dynamics. It allows the identification of stygofaunal food web structures and energy flows based on the metabolic pathway of specific amino groups. Concurrently, ¹⁴ C provides complementary data on the carbon recycling and incorporation within the stygobiotic trophic webs. Changes in groundwater environmental conditions (e.g. aquifer recharge), and subsequent community adaptations, can be pinpointed via the measurementof the radiocarbon fingerprint of water, sediment and specimens. DNA analyses are a rapidly expanding approach in ecology. eDNA is mainly employed as a biomonitoring tool, while metabarcoding of individuals and/or gut contents provides insight into diet regimes. In all cases, the application of the approaches in combination provides more powerful data than any one alone. By combining quantitative (CSIA and ¹⁴ C) and qualitative (eDNA and DNA metabarcoding) approaches via Bayesian Mixing Models (BMM), linkages can be made between community composition, energy and nutrient sources in the system, and trophic function. This suggested multidisciplinary design will contribute to a more thorough comprehension of the biogeochemical and ecological patterns within these undervalued but essential ecosystems.