is largely due to its prediction of within-habitat effects. For this analysis we included only cases in which parasitism was observed at because zero-values (no parasitism) could t+1, not be attributed to either within- or cross-habitat hosts. We separated the expected parasitism rates into the expected attacks based on cross-habitat versus within-habitat host abundances. To calculate cross-habitat vs. within-habitat expected parasitism rates, we set equal to 1 in Equation 3, and first set (the habitat of host to be plantation q B j) forest. These settings allowed us to calculate expected parasitism rates for host in both i plantation and native forest based on apparent competition with hosts in plantation forest. For host in plantation forest, this would produce within-habitat expected parasitism i rates, and for host in native forest, this would produce cross-habitat expected parasitism i rates. We then set to be native forest, and again calculated for host For host B EiA(t+1) i. in plantation forest, this produced cross-habitat expected parasitism rates, and for host i i in native forest, this produced within-habitat expected parasitism rates. This process produced both within- and cross-habitat expected parasitism rates for each host species i in plantation forest, and each host species in native forest. To test whether cross-habitat i expected parasitism rates predicted observed parasitism rate, and whether they predicted a component of the variation in observed parasitism rate beyond that predicted by expected parasitism rate, we used a GLMM with a binomial distribution and as the response variable. Within-habitat and cross-habitat expected parasitism OiA(t+1) rates were included as separate fixed predictors, and forest within site within block were included as nested random factors in the full model, before selection of the best random and then fixed effect structure. Expected parasitism rates were log-transformed to achieve a more even distribution of values and improve linear model fit (but results were not
is largely due to its prediction of within-habitat effects. For this analysis we included only cases in which parasitism was observed at t+1, because zero-values (no parasitism) could not be attributed to either within- or cross-habitat hosts. We separated the expected parasitism rates into the expected attacks based on cross-habitat versus within-habitat host abundances. To calculate cross-habitat vs. within-habitat expected parasitism rates, we set q equal to 1 in Equation 3, and first set B (the habitat of host j) to be plantation forest. These settings allowed us to calculate expected parasitism rates for host i in both plantation and native forest based on apparent competition with hosts in plantation forest. For host i in plantation forest, this would produce within-habitat expected parasitism rates, and for host i in native forest, this would produce cross-habitat expected parasitism rates. We then set B to be native forest, and again calculated EiA(t+1) for host i. For host i in plantation forest, this produced cross-habitat expected parasitism rates, and for host i in native forest, this produced within-habitat expected parasitism rates. This process produced both within- and cross-habitat expected parasitism rates for each host species i in plantation forest, and each host species i in native forest. To test whether cross-habitat expected parasitism rates predicted observed parasitism rate, and whether they predicted a component of the variation in observed parasitism rate beyond that predicted by expected parasitism rate, we used a GLMM with a binomial distribution and OiA(t+1) as the response variable. Within-habitat and cross-habitat expected parasitism rates were included as separate fixed predictors, and forest within site within block were included as nested random factors in the full model, before selection of the best random and then fixed effect structure. Expected parasitism rates were log-transformed to achieve a more even distribution of values and improve linear model fit (but results were not
NCOMMS-16-01466B_main%20text_AMK_CFFinal.docx