In this overview (introductory article to a special issue including 14 papers), we consider all main types of natural and artificial inland freshwater habitas (fwh). For each type, we identify the main biodiversity patterns and ecological features, human impacts on the system and environmental issues, and discuss ways to use this information to improve stewardship. Examples of selected key biodiversity/ecological features (habitat type): narrow endemics, sensitive (groundwater and GDEs); crenobionts, LIHRes (springs); unidirectional flow, nutrient spiraling (streams); naturally turbid, floodplains, large-bodied species (large rivers); depth-variation in benthic communities (lakes); endemism and diversity (ancient lakes); threatened, sensitive species (oxbow lakes, SWE); diverse, reduced littoral (reservoirs); cold-adapted species (Boreal and Arctic fwh); endemism, depauperate (Antarctic fwh); flood pulse, intermittent wetlands, biggest river basins (tropical fwh); variable hydrologic regime—periods of drying, flash floods (arid-climate fwh). Selected impacts: eutrophication and other pollution, hydrologic modifications, overexploitation, habitat destruction, invasive species, salinization. Climate change is a threat multiplier, and it is important to quantify resistance, resilience, and recovery to assess the strategic role of the different types of freshwater ecosystems and their value for biodiversity conservation. Effective conservation solutions are dependent on an understanding of connectivity between different freshwater ecosystems (including related terrestrial, coastal and marine systems).

Groundwater is a vital ecosystem of the global water cycle, hosting unique biodiversity and providing essential services to societies. Despite being the largest unfrozen freshwater resource, in a period of depletion by extraction and pollution, groundwater environments have been repeatedly overlooked in global biodiversity conservation agendas. Disregarding the importance of groundwater as an ecosystem ignores its critical role in preserving surface biomes. To foster timely global conservation of groundwater, we propose elevating the concept of keystone species into the realm of ecosystems, claiming groundwater as a keystone ecosystem that influences the integrity of many dependent ecosystems. Our global analysis shows that over half of land surface areas (52.6%) has a medium‐to‐high interaction with groundwater, reaching up to 74.9% when deserts and high mountains are excluded. We postulate that the intrinsic transboundary features of groundwater are critical for shifting perspectives towards more holistic approaches in aquatic ecology and beyond. Furthermore, we propose eight key themes to develop a science‐policy integrated groundwater conservation agenda. Given ecosystems above and below the ground intersect at many levels, considering groundwater as an essential component of planetary health is pivotal to reduce biodiversity loss and buffer against climate change.

Macrophytes are important components of freshwater ecosystems, playing a relevant role in carbon and nutrient cycles. Notwithstanding their widespread diffusion in temperate to subtropical shallow lakes, little effort has been performed so far in extensively mapping macrophyte communities at regional to continental scale. A rule-based classification scheme was implemented for mapping four macrophyte community types (helophyte, emergent rhizophyte, floating, and submerged-floating association). Input features were selected among multispectral reflectance and multi-temporal vegetation indices, based on Landsat data acquired over four test sites: Lake Taihu (China), Kis-Balaton wetland (Hungary), Lake Trasimeno and Mantua Lakes system (Italy). The best performing features were derived from Water Adjusted Vegetation Index (WAVI) computed at: early spring, maximum growth, and late autumn conditions. Overall accuracy (OA) and Kappa coefficient (k) of macrophyte maps produced with our approach over the ensemble of four sites were 90.1% and 0.865, respectively, with best performance in European temperate areas (OA = 93.6–94.2%, k = 0.887–0.916), and lower scores for subtropical Lake Taihu (OA=82.8%, k=0.762). Per-class accuracies were higher than 80% for all target classes, except for the submerged-floating association, with misclassifications concentrated in Taihu site. The robustness of the approach was tested over two independent validation cases: a different site (i.e. Lake Varese, Italy), and a different input dataset (i.e. AVNIR-2 data, for Mantua Lakes system). Consistent accuracy results were achieved: OA = 94.3% (k = 0.922) and OA= 85.6% (k = 0.766), with some misclassification due to spatial resolution of AVNIR-2 data