Efects of topographic variability and forest attributes on fne-scale soil fertility in late-secondary succession of Atlantic Forest

Background:Understanding how soil fertility changes due to topographical conditions and forest attributes is an essential premise for local-scale forest management practices.We evaluated the efects of topographic variables and forest attributes on soil fertility along a local topographical gradient in a Brazilian Atlantic Forest.We hypothesised that soil fertility is positively afected by topographic variability and forest attributes(structure and diversity).We used tree species richness,composition,abundance,and aboveground biomass as forest attributes.We analysed two 1-ha for‑est patches with contrasting topographical conditions.We used diferent linear mixed efects models(LMMs)to test the main efects of diferent forest attributes and topography variables on soil fertility.Results:The results showed that higher topographic variability determines soil fertility along a fne-scale gradient.The frst two axes of the PCA explained 66.8%of the variation in soil data,with the frst axis(PCA_(1))explaining 49.6%of the variation in soil data and positively correlating with fertility-related soil properties.The second axis(PCA_(2))explained 17.2%of the variation in topographical data and positively correlated with convexity(the elevation of a plot minus the average elevation of all immediate neighbour plots)and elevation.Our best models showed that topo‑graphic variables(elevation and convexity)are the main predictors that afect fne-scale soil fertility.Conclusions:Our study demonstrates that the topographic variability,mainly elevation and convexity,determines fne-scale soil fertility in an Atlantic Forest.These results advance our understanding that context-dependent condi‑tions based on topography and soil properties have a high variability at a fne scale,which can infuence variations in forest attributes(i.e.,species distribution,diversity and structure of tree communities).In addition,the information generated in this research may be important for planning forest restoration activities(passive and active)based on the high variability of environmental variables at a fne scale.