DOI: 10.5061/dryad.rfj6q57cc
title: Spatial variation in human disturbances and their effects on forest structure and biodiversity across an Afromontane forest

description: Context Human disturbances can have large impacts on forest structure and
 biodiversity, and thereby result in forest degradation, a property
 difficult to detect by remote sensing. Objectives To investigate spatial
 variation in anthropogenicdisturbances and their effects on forest
 structure and biodiversity. Methods In 144 plots of 20 x 20 m distributed
 across a forest area of 750 km2 in Southwest Ethiopia, we recorded:
 landscape variables (e.g., distance to forest edge), different human
 disturbances, forest structure variables, and species composition of trees
 and epiphyllous bryophytes. We then first assessed if landscape variables
 could explain the spatial distribution of disturbances. Second, we
 analysed how forest structure and biodiversity were influenced by
 disturbances. Results Human disturbances, such as coffee management and
 grazing declined with distance to forest edges and penetrated at least a
 kilometer into the forest. The slope was not related to disturbance
 levels, but several types of disturbances were less common at higher
 elevations. Among human disturbance types, coffee management reduced liana
 cover and was associated with altered species composition of trees. The
 presence of large trees and basal areas was not related to any of the
 disturbance gradients. Conclusions Although most anthropogenic
 disturbances displayed clear edge effects, surprisingly the variation in
 the chosen forest degradation indices was only weakly related to these
 disturbances. We suggest that the intersection between edge effects and
 forest degradation is very context-specific and relies much on how
 particular societies use the forests. For example, in this landscape
 coffee management seems to be a key driver.
description: For method of data collection and how it is processed ( see the
 method section of article)
description: <strong>Explanations to the archived files</strong> <strong>Title: Spatial variation in human disturbances and their effects on forest structure and biodiversity across an Afromontane Forest</strong> See methods section in the paper for complementary descriptions and explanations of column names. <strong>R-code for analyses and some figures:</strong> <strong>Enviromental1.R:</strong> Tests for Appendix S1, (based on GeramodelA _Appendex 2_dfs.csv) <strong>Enviromental2.R:</strong> Tests for Appendix S3, (based on humands.csv) <strong>Landscape1.R: </strong> Test for Appendix S2, (based on GeramodelA _Appendex 2_l.csv) <strong>Landscape on human disturbance.R:</strong> Statistical code for results presented in Table 2 and Figure 3, (based on HDLgradients.csv) <strong>Forest structure and biodiveristy.R:</strong> Statistical code for results presented in Table 3 and Figure 4, (based on HDLgradients.csv) <strong>Tree species compostion and disturbances.R: </strong>Statistical code for results presented in Figure 5, (based on richness3_coded.csv and threeACx_new.csv) <strong>Tree species compostion.R</strong>: Statistical code for results presented in main text and Figure 5, (based on richness3+.csv and threeACx_new.csv) <strong> </strong> <strong>Data files used in the R-script:</strong> <strong>GeramodelA _Appendex 2_dfs.csv:</strong> (used in Enviromental1.R, data for result presented in Appendix S1) column names: SiteID=Site ID, Coffeemanagement= Coffee management, Coffeedominance= Coffee dominance, Stumps= Stumps (presence absence, see main paper, Burnings= Burnings, Signsofhumanpresence= Signs of human presence, Grazing= Grazing, Spices= Spices, Canopycover= Canopy cover,  Treecircumference=Tree circumference, Largestcircumference= Largest circumference,  Treebasalarea= Tree basal area,  Circumference’sshannon= Circumference’s Shannon, Naturaldeadtrees= Natural dead trees, Decomposingtrees= Decomposing trees, Walkability= Walkability, Thickets= Thickets, Longestmoss= Longest moss, Non-coffeewoodyplants= Non-coffee woody plants, Treeabundance= Tree abundance <strong>GeramodelA _Appendex 2_l.csv:</strong> (used in Landscape1.R, data for result presented in Appendix S2) column names: SiteID=Site ID, Distancetohome= Distance to home, Distancetostream= Distance to stream, Closest footpathdistance= Closest footpath distance, Distancetoagricultural edge= Distance to agricultural edge, Distancetoroad= Distance to road, Slope, Forestcover= Forest cover, Elevation, Heatload, Costdistance= Cost distance <strong>humands.csv: </strong>(used in Enviromental2.R, data for result presented in Appendix S3) column names: SiteID=Site ID, Coffeemanagement= Coffee management, Coffeeoccurrence= Coffee occurrence, Signsofhumanpresence= Signs of human presence, Burnings, Stumps, Grazing, Spices, Coffeedominance= Coffee dominance <strong>HDLgradients.csv: (</strong>used in Landscape on human disturbance.R and <strong>Forest structure and biodiveristy.R</strong> , data for result presented in Table 2, Table 3, Figure 3, Figure 4) Column names: Coffeemanagement= Coffee management,Grazing, Signsofhumanpresence= Signs of human presence, Stumps, Spices, Distancetostream= Distance to stream, Closestfootpathdistance= Closest footpath distance, Distancetoagriculturaledge= Distance to agricultural edge, Distancetoroad= Distance to road,            Slope, Forestcover= Forest cover, Elevation, Heatload,Canopycovergradient= Canopy cover gradient, Largesttreegradient= Largesttreegradient, Deadwoodgradient= Dead wood gradient, Lianacover= Liana cover, Treespeciesrichness= Tree species richness, EpiphyllousBryophyteRichness= Epiphyllous Bryophyte Richness <strong>richness3_coded.csv:</strong> ( used in Tree species compostion and disturbances.R, data for result presented in Figure 5) column names: Row Labels=Site ID, algr=Albizia grandibracteata, algu=Albizia gummifera, alsc=Albizia schimperiana, alab=Allophylus abyssinicus, apdi=Apodytes dimidiata, beab=Bersama abyssinica, bran=Brucea antidysenterica, ceaf=Celtis africana, chmi=Chionanthus mildbraedii, coaf=Cordia africana, crma=Croton macrostachyus, culu=Cupressus lusitanica, cuho=Cussonia holstii, diab=Diospyros abyssinica, drst=Dracaena steudneri, ehcy=Ehretia cymosa, ekca=Ekebergia capensis, elbu=Elaeodendron buchananii, eura=Euclea  racemosa, euab=Euphorbia abyssinica, faan=Fagaropsis angolensis, fisu=Ficus sur, fith=Ficus thonningii,  fiva=Ficus vasta, gasa=Gallineria saxifraga, maca=Macaranga capensis, mala=Maesa lanceolata, maun=Maytenus undata, mife=Millettia ferruginea, olwe=Olea welwitschii, oxsp=Oxyanthus speciosus, pofu=Polyscias fulva, poad=Pouteria adolfi-friederici, praf=Prunus africana, ryne=Rytigynia neglecta, sael=Sapium ellipticum, scab=Schefflera abyssinica, sygu=Syzygium guineense, teno=Teclea nobilis, veam=Vernonia amygdalina, veau=Vernonia auriculifera, veda=Verpis dainellii <strong>threeACx_new.csv:</strong> ( used in Tree species compostion and disturbances.R, and Tree species compostion.R,  data for result presented in main text and Figure 5) column names: SiteID=Site ID, Coffeemanagement= Coffee management, Signsofhumanpresence= Signs of human presence, Stumps, Grazing, Spices <strong>richness3+.csv:</strong> ( used in Tree species composition.R,  data for result presented in main text and Figure 5) column names: Row Labels=Site ID, Albizia grandibracteata, Albizia gummifera, Albizia schimperiana, Allophylus abyssinicus, Apodytes dimidiata, Bersama abyssinica, Brucea antidysenterica, Celtis africana, Chionanthus mildbraedii,  Cordia africana,  Croton macrostachyus,  Cupressus lusitanica, Cussonia holstii,  Diospyros abyssinica,  Dracaena steudneri,  Ehretia cymosa, Ekebergia capensis, Elaeodendron buchananii, Euclea  racemosa, Euphorbia abyssinica, Fagaropsis angolensis, Ficus sur, Ficus thonningii, Ficus vasta, Gallineria saxifraga, Macaranga capensis, Maesa lanceolata, Maytenus undata, Millettia ferruginea, Olea welwitschii, Oxyanthus speciosus, Polyscias fulva, Pouteria adolfi-friederici, Prunus africana, Rytigynia neglecta, Sapium ellipticum, Schefflera abyssinica, Syzygium guineense, Teclea nobilis, Vernonia amygdalina, Vernonia auriculifera, Verpis dainellii