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Oecologiafifth-lowest and fifth-highest values (i.e., extreme 0.5 %simulated cases at either end) as simulation envelopes.However, because the simulation tests are performed atdifferent scales concurrently, this simulation inferenceyields an underestimated Type I error rate (Loosmore andFord 2006). We therefore combined this simulation envelopemethod with a goodness-of-fit test (GOF) (Diggle2003). Further analysis were only performed for those datasets where the observed GOF’s P \ 0.005 (Loosmore andFord 2006; Wiegand et al. 2007).ResultsTest of habitat heterogeneityExcept for Ulmus laciniata, all focal species showed significantaggregation up to 30 m (i.e. P \ 0.005 for GOFtests). Adults of 12 of the 15 focal species showed increasingaggregation at scales r [ 10 m (Online Resource 4). Thisindicated that most of the focal species exhibited habitatpreference caused by large-scale habitat heterogeneity,suggesting that we should account for habitat heterogeneityin our analysis of density dependence.Early-stage density dependenceFor a total of 5,762 seedlings, mortality was 29.8 % from2005–2010, thus averaging *6 % per year. Among the 11abundant focal species, percent seedling mortality between2005 and 2010 ranged from 11.0 to 55.4 % (mean =38.8 %).Before controlling for habitat preference, for 5 of the 11focal species, the best-fit model was the density-independentmodel, indicating that neither seedling nor tree neighborsinfluenced seedling survival. For 4 species, the best-fit modelincluded overall seedling density or basal area of trees, withno difference between the effects of conspecifics and heterospecifics.For the remaining 2 species, the best-fit modelincluded separate terms for conspecific and heterospecificneighbors. For Philadelphus schrenkii, the best-fit model(model 5) included conspecific and heterospecific seedlingdensities, but not tree basal area, and the effect of conspecificseedling density was significantly negative. For Deutziaglabrata, the best-fit model was the full model (model 9),which included separate terms for conspecific and heterospecificseedling and tree neighbors. The effect of conspecificneighbors was significantly negative for both seedling densityand basal area of trees C1 cm dbh. In contrast, the effectof heterospecific basal area of trees C1 cmdbhwassignificantlypositive (Online Resource 5). Thus, of the 11 focalspecies, only 2 showed patterns of seedling survival consistentwith conspecific negative density dependence.Nonetheless, in the community-wide analysis, wedetected significant conspecific negative density dependence.With all species combined, the probability ofseedling survival was best described by model 6, whichincluded separate conspecific and heterospecific seedlingterms and overall basal area of trees. The effect of conspecificseedling density was significantly negative. Theeffect of overall basal area of trees C1 cm dbh was significantlypositive (Table 3).However, after removing the two species that showednegative density dependence in the species-level analysis(Deutzia glabrata and Philadelphus schrenkii), community-wideseedling survival was best fitted by model 4,indicating that there was an effect of overall basal area oftrees C1 cm dbh, but no effect of seedling neighbors. Theeffect of overall basal area of trees C1 cm dbh remainedsignificantly positive (Table 3).Controlling for habitat heterogeneity did not qualitativelyalter the observed patterns of conspecific negativedensity dependence at the seedling stage. Including canopyopenness and topographic position as covariates in themodels did change the best-fit models for 6 of the 11 focalspecies (Online Resource 6 vs. 5). However, for all 6 ofthose species, the best-fit models did not include separateterms for conspecific and heterospecific neighbors,regardless of whether the model controlled for habitatheterogeneity. For the community-level analyses, the bestfitmodels did not change when including canopy opennessand topographic position as covariates, and the coefficientvalues for neighbor effects were similar compared withmodels that did not include these habitat variables(Table 3).Later-stage conspecific density dependenceWe calculated the number of species showing aggregated,random and regular patterns at the sapling and juvenilestage at each (1 m) scale up to 10 m. For saplings, 11 of 15species exhibited additional aggregation relative to adults(i.e. saplings were more clustered than adults), 7 speciesshowed random patterns (i.e. not significantly differentfrom the adults), and 1 species showed more regular patterns(i.e. saplings were less aggregated than the adults) atscales up to 10 m (Fig. 1d). For juveniles, 8 of 15 speciesexhibited additional aggregation relative to adults, 13species showed random patterns, and no species showedmore regular patterns up to 10 m (Fig. 1e).The 11 species (73 %) that exhibited additional aggregationrelative to adults in the sapling stage were all foundto have a decline in the strength of additional clusteringfrom the sapling to juvenile stage at the scale of 0–10 m,indicating that the majority of abundant species showedconspecific density dependence across the study area1236