We tested whether we could use knowledge of the proportions of shared parasitoids (diAjB values) between host species in our training metaweb (Fig. 1e), as well as initial attack rates from (pre-treatment) time at our validation sites (Fig. 1g), to predict t parasitism rates at (post-treatment) time 1 at the validation sites (Fig. 1h), given t + known changes in host abundances (Fig. 1g, h). Parasitism rate refers to the number of parasitism events divided by the number of hosts sampled. We first calculated the expected parasitism rate at time + 1 of host species in habitat using: t i A (3) where is host abundance, is a time step (before or after sampling dates), and all n t other variables are defined as in Equation 2. Here, when = 2, can take values of either q B habitat. When = 1, is limited to being either one habitat or the other (here plantation q B or native forest). That is, when = 2, this equation calculates the expected parasitism rate q of host in habitat based on potential apparent competition with hosts in the same and i A the adjacent habitat. When = 1 it calculates the expected parasitism rate of host in q i habitat based on potential apparent competition with hosts either in plantation or in A native forest. In both cases, can take values of either habitat. We calculated from A diAjB the metaweb (transect plus extra sampling data for maximum resolution on interactions) from our training sites (Fig. 1d, e), and (transect plus extra sampling data) and αiAl(t) (transect data only, for a standardized measure of abundance) from our validation njB(t) sites in the pre-herbivore-reduction (time samples (in both reduction and control sites; t) Fig. 1g). We calculated (transect data only) and (transect plus extra njB(t+1) niA(t+1) sampling data, since was calculated from transect plus extra sampling data) from αiAl(t) the post-herbivore-reduction samples (also in both reduction and control sites; Fig. 1h).
We tested whether we could use knowledge of the proportions of shared parasitoids (diAjB values) between host species in our training metaweb (Fig. 1e), as well as initial attack rates from (pre-treatment) time t at our validation sites (Fig. 1g), to predict parasitism rates at (post-treatment) time t + 1 at the validation sites (Fig. 1h), given known changes in host abundances (Fig. 1g, h). Parasitism rate refers to the number of parasitism events divided by the number of hosts sampled. We first calculated the expected parasitism rate at time t + 1 of host species i in habitat A using: (3) where n is host abundance, t is a time step (before or after sampling dates), and all other variables are defined as in Equation 2. Here, when q = 2, B can take values of either habitat. When q = 1, B is limited to being either one habitat or the other (here plantation or native forest). That is, when q = 2, this equation calculates the expected parasitism rate of host i in habitat A based on potential apparent competition with hosts in the same and the adjacent habitat. When q = 1 it calculates the expected parasitism rate of host i in habitat A based on potential apparent competition with hosts either in plantation or in native forest. In both cases, A can take values of either habitat. We calculated diAjB from the metaweb (transect plus extra sampling data for maximum resolution on interactions) from our training sites (Fig. 1d, e), and αiAl(t) (transect plus extra sampling data) and njB(t) (transect data only, for a standardized measure of abundance) from our validation sites in the pre-herbivore-reduction (time t) samples (in both reduction and control sites; Fig. 1g). We calculated njB(t+1) (transect data only) and niA(t+1) (transect plus extra sampling data, since αiAl(t) was calculated from transect plus extra sampling data) from the post-herbivore-reduction samples (also in both reduction and control sites; Fig. 1h).
NCOMMS-16-01466B_main%20text_AMK_CFFinal.docx