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As a complement to the additive partitioning biodiversity effect equation, we used diversity�Cinteraction models (Kirwan et?al. 2009) to investigate species interaction patterns, contributing to biotic resistance in the mixtures from the first experiment. Comparing models based on the different ecological assumptions allowed us to test alternative hypotheses about the relative role of functional groups and functional redundancy in biotic resistance (Kirwan et?al. 2009). Model 1 describes species identity effect alone without http://www.selleck.cn/products/BEZ235.html species interaction: (eqn 2) The response variable (y) represents RCIavg as an indicator for biotic resistance to invasion by P.?australis. ��i is the estimated performance of species i in contribution to biotic resistance, and Pi is the initial proportion of species i in seed mixture. In the case of monoculture treatment of species i, Pi is equal to 1. Model 2 describes functional group identity effect alone without species interaction: (eqn 3) Model 3 describes functional group identity effect and average species interaction: (eqn 4) Model 4 describes functional group identity effect and species interaction within and between functional group: (eqn 5) Model 5 describes functional group identity effect and separate pairwise species interactions: (eqn 6) Model 6 describes functional group identity effect and species interactions between functional group without species http://www.selleckchem.com/products/PLX-4032.html interaction within each functional group: (eqn 7) Each model was tested using glm function in r software. Pairs of models were compared for significant difference in model predictions for RCIavg using anova.lm function in r software. Using Model 6, we estimated model prediction about the effect of functional group composition (both functional group identity and interaction) on RCIavg using predict function in stats package in r software. The model prediction on response surface was drawn in ternary plot using levelplot function in lattice package in r software. All anova tests and correlation http://www.selleckchem.com/products/AZD2281(Olaparib).html analyses were conducted using the jmp? software (? SAS Institute Inc.; Cary, NC, USA). Partitioning diversity effect was calculated using mathematical equations in the Excel software (? Microsoft). Cluster analysis and diversity�Cinteraction modelling, which is based on multiple regressions, were conducted using r (http://www.r-project.org). In monoculture treatments and for both experiments, relative competitive effect of wetland plants on P.?australis was mostly related to their functional group identity, while species identity effect remained redundant within each functional group (Figs?2 and 3). In 2009 experiment, relative competitive index (RCIavg) of 11 wetland plants on P.?australis was significantly different among three FGs (F2,20?=?46.62, P?