Intersecting Ecosystem Services Across the Aquatic Continuum: From Global Change Impacts to Local, and Biologically Driven, Synergies and Trade-Offs

Abstract

The study of ecosystem services requires the integration of different observational points. This is particularly true in Water, as this element continuously cycles, increasing chances of interaction among services originating in different ecosystems. However, aquatic scientists historically approached the study of inland/freshwater and open/marine waters in different ways and this cultural division potentially hampers integrative approaches. Herein, we explored the literature pertaining to ecosystem services across the last 23 years, analysing 4,590 aquatic papers. By aggregating and intersecting topics included in this papers’ collection using text-mining and topical network approaches, we saw that the study of local environmental conditions (e.g., river estuary management) and synergies and trade-offs between services (e.g., carbon sequestration and water purification) can display several potential conceptual links between freshwater and marine sciences. Our analyses suggest that to intersect ecosystem services across the aquatic continuum, the conceptual integration between marine and freshwater science must be reinforced, especially at the interface between different “salinity realms.” Such integration should adopt a “system thinking” perspective, in which the focus is on multiple socio-ecological processes giving rise to interactions that are (i) biologically mediated, (ii) potentially conflicting, and (iii) entangled within networks.

Plant growth promoting rhizobacteria (PGPR) application for coping with salinity and drought: a bibliometric network multi‐analysis

“…(2019) and D'Alelio et al . (2021) to obtain a clean dataframe to generate a tidy Document Term Matrix (DTM), eliminating non‐accessible, unreadable or uninformative publications, based on PRISMA guidelines (Moher et al . 2009).…”

“…We limited our approach to keywords to exclude biases in the information-flow network, possibly caused by less-strictly related words, repetitions, word similarity due to ending, conjugations and declensions. The here outlined approach is based on previous text mining analyses reported in Hay-Mele et al (2019) andD'Alelio et al (2021).…”