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Table 3 Results of the logistic regression (presence or absence = p/a) and negative binomial (count) models of post-fire juvenile establishment. Coefficients and their levels of significance (if P < 0.05) are reported for all covariates retained in the final models. Covariates were centered and scaled prior to model construction to facilitate comparison. Performance statistics are given in Table 4 Asterisks indicate levels of significance for parameter coefficients: *** = P < 0.001, ** = P < 0.01, * = P < 0.05. Models were for field data collected in 2016 on the Tripod Complex fires in the Okanogan-Wenatchee National Forest, Washington, USA

From: Topography and post-fire climatic conditions shape spatio-temporal patterns of conifer establishment and growth

  All species Western larch Lodgepole pine Engelmann spruce Ponderosa pine Douglas-fir
Covariates p/a1 count p/a count p/a1 count p/a count p/a count p/a count
Elevation (m) --   0.010* 2.159** -- 0.555* 0.006** 1.442** –0.005* –2.603***   –0.457*
Slope (degrees) -- –0.234    --   0.118 0.907 –0.176*    0.433*
Heat load index --     -- –0.479*     –0.680*   
Topographic position index --     -- –0.610* –0.026* –1.655* 0.020* 1.157**   –0.292
Topographic wetness index --     --        
Shrub cover (percentage) -- –0.421*** 0.052   -- –0.427*      0.046*  
Distance to live seed source (m), binned2 -- –0.399** –0.999** –2.152*** -- 0.3282* –0.417 –0.596 –0.212   –0.566** –1.070***
Extant cones on snags -- -- -- -- -- 1.132* -- -- -- -- -- --
  1. 1Occurrence (presence or absence) models were not constructed for all species combined because juveniles were present on every site sampled. Neither an occurrence model nor a count model for subalpine fir was constructed because subalpine fir juveniles occurred on only four sites, so the models did not converge. Similarly, the occurrence model for lodgepole pine did not converge, as it occurred on all but seven sites. Models that were not run or variables that were not included are indicated by dashes (--)
  2. 2For the all species count model, I used minimum distance to live seed source of any species; for the species-specific models, I used bins of minimum distance to live conspecific seed source. Distance to seed source was not captured for every species at every site (e.g., due to true absence or no clear sightline) and so I generated an ordinal variable to account for these unknown distances: I binned known distances by 25 m intervals and set unknown distances equal to the largest bin value plus one