A global synthesis on land-cover changes in watersheds shaping freshwater detrital food webs

Anthropogenic land-cover changes are among the most pressing global threats to both aquatic and terrestrial ecosystems, jeopardising biodiversity and the critical connections between these systems. Resource flows and trophic interactions intricately link aquatic and terrestrial ecosystems, with terrestrial-derived detritus playing a foundational role in supporting aquatic food webs. These detrital inputs form essential cross-ecosystem linkages, underpinning key ecological processes and providing vital resources for aquatic communities. Yet, little research has focused on how land-cover changes cascade across this linkage. To better understand how land-cover changes in the watershed influence freshwater detrital food webs, we conducted a meta-analysis of field studies reporting the effects of vegetation changes on freshwater detrital consumers and organic matter decomposition. The results from 144 studies, reporting 1235 comparisons, showed that, overall, land-cover changes in the waters..., , , # A global synthesis on land-cover changes in watersheds shaping freshwater detrital food webs This READ ME file contains information on the R-scripts and variables in the datasets used for the analyses. ### Data files: dat_MA.txt: Main dataset with information on each observation of each study, with the following variables: * study_ID - Levels: several; unique identifier for each study (detailed infos can be found in the Supplementary material Table S5 and data sources) * ID - Levels: continuous: unique identifier for each comparison * year - Levels: continuous, publication year * lat - Levels: continuous; latitude in decimal degrees * lon - Levels: continuous; longitude in decimal degrees * climate - Levels: boreal, temperate; sub-tropical, tropical, climate zone * season - Levels: year, winter, spring, summer, autumn, dry, wet; timepoint of field study * scale - Levels: local, catchment, local+catchment; spatial scale of field study * temp_diff - Levels: continuous; temporal diff...,