The effects of consumer pressure and water availability on plant interactions

The stress gradient hypothesis original purposed the frequency of plant interactions along countervailing gradients of abiotic stress and consumer pressure. However, research to date has studied these two stressors in isolation rather than together, thereby potentially neglecting the interaction of these factors on plant composition. During an extreme drought and an above average rainfall year in the arid central valley of California, USA, we artificially manipulated a soil moisture gradient and erected animal exclosures to examine the interactions between dominant shrubs and the subordinate annual community. There was a high frequency of positive interactions between shrubs and the annual community at all levels of soil moisture and consumer pressure. Shrub facilitation and water addition displayed similar effect sizes on plant communities, however, the shrub facilitation effect was significantly stronger in watered plots. Shrubs and positive interactions maintain productivity of annual plant communities at environmental extremes despite reductions in droughts stress or consumer pressure and these positive effects are even more pronounced with water addition. The relationship between consumer pressure and abiotic stress on plant interactions is non-linear, particularly since shrubs can facilitate understorey plants through a series of different mechanisms.

Consumer pressure, soil moisture, and shrub interactions

## 
##  Shapiro-Wilk normality test
## 
## data:  data$Biomass
## W = 0.70532, p-value < 2.2e-16

## 
##  Shapiro-Wilk normality test
## 
## data:  m1$residuals
## W = 0.8549, p-value = 2.963e-14

## 
##  Shapiro-Wilk normality test
## 
## data:  m2$residuals
## W = 0.95084, p-value = 0.000249

Consumer pressure effects on plant interactions

Soil moisture effects on plant interactions

Species richness and plant abundance

## Analysis of Deviance Table
## 
## Model: Negative Binomial(6.504), link: log
## 
## Response: abundance
## 
## Terms added sequentially (first to last)
## 
## 
##                                 Df Deviance Resid. Df Resid. Dev  Pr(>Chi)
## NULL                                              239     269.19          
## Microsite                        1   5.6497       238     263.54 0.0174587
## Exclosure                        1   0.2436       237     263.30 0.6216254
## SWC.initial                      1  12.7782       236     250.52 0.0003507
## Microsite:Exclosure              1   0.3931       235     250.12 0.5306886
## Microsite:SWC.initial            1   2.6654       234     247.46 0.1025544
## Exclosure:SWC.initial            1   1.2390       233     246.22 0.2656646
## Microsite:Exclosure:SWC.initial  1   0.0584       232     246.16 0.8090474
##                                    
## NULL                               
## Microsite                       *  
## Exclosure                          
## SWC.initial                     ***
## Microsite:Exclosure                
## Microsite:SWC.initial              
## Exclosure:SWC.initial              
## Microsite:Exclosure:SWC.initial    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Deviance Table
## 
## Model: Negative Binomial(16.0757), link: log
## 
## Response: abundance
## 
## Terms added sequentially (first to last)
## 
## 
##                                 Df Deviance Resid. Df Resid. Dev Pr(>Chi)
## NULL                                              119     178.35         
## Microsite                        1  25.3505       118     153.00 4.78e-07
## Exclosure                        1   8.5440       117     144.46 0.003467
## SWC.initial                      1   4.1301       116     140.33 0.042128
## Microsite:Exclosure              1   2.3114       115     138.02 0.128425
## Microsite:SWC.initial            1   1.7496       114     136.27 0.185926
## Exclosure:SWC.initial            1   2.5548       113     133.71 0.109960
## Microsite:Exclosure:SWC.initial  1   5.4288       112     128.28 0.019807
##                                    
## NULL                               
## Microsite                       ***
## Exclosure                       ** 
## SWC.initial                     *  
## Microsite:Exclosure                
## Microsite:SWC.initial              
## Exclosure:SWC.initial              
## Microsite:Exclosure:SWC.initial *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Deviance Table
## 
## Model: Negative Binomial(121833.9), link: log
## 
## Response: richness
## 
## Terms added sequentially (first to last)
## 
## 
##                                 Df Deviance Resid. Df Resid. Dev Pr(>Chi)
## NULL                                              239     86.916         
## Microsite                        1   4.9236       238     81.993  0.02649
## Exclosure                        1   0.4141       237     81.578  0.51989
## SWC.initial                      1   0.5055       236     81.073  0.47711
## Microsite:Exclosure              1   0.5339       235     80.539  0.46498
## Microsite:SWC.initial            1   0.0019       234     80.537  0.96485
## Exclosure:SWC.initial            1   0.6888       233     79.848  0.40658
## Microsite:Exclosure:SWC.initial  1   0.1733       232     79.675  0.67716
##                                  
## NULL                             
## Microsite                       *
## Exclosure                        
## SWC.initial                      
## Microsite:Exclosure              
## Microsite:SWC.initial            
## Exclosure:SWC.initial            
## Microsite:Exclosure:SWC.initial  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Deviance Table
## 
## Model: Negative Binomial(141925.3), link: log
## 
## Response: richness
## 
## Terms added sequentially (first to last)
## 
## 
##                                 Df Deviance Resid. Df Resid. Dev Pr(>Chi)
## NULL                                              119     41.965         
## Microsite                        1  10.1880       118     31.777 0.001414
## Exclosure                        1   2.0611       117     29.716 0.151102
## SWC.initial                      1   0.0507       116     29.666 0.821876
## Microsite:Exclosure              1   0.2390       115     29.427 0.624939
## Microsite:SWC.initial            1   0.3236       114     29.103 0.569472
## Exclosure:SWC.initial            1   0.2680       113     28.835 0.604696
## Microsite:Exclosure:SWC.initial  1   0.0068       112     28.828 0.934093
##                                   
## NULL                              
## Microsite                       **
## Exclosure                         
## SWC.initial                       
## Microsite:Exclosure               
## Microsite:SWC.initial             
## Exclosure:SWC.initial             
## Microsite:Exclosure:SWC.initial   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Interactions among annuals with consumer pressure and soil moisture

## Analysis of Deviance Table
## 
## Model: Negative Binomial(0.8282), link: log
## 
## Response: abundance2
## 
## Terms added sequentially (first to last)
## 
## 
##                   Df Deviance Resid. Df Resid. Dev  Pr(>Chi)    
## NULL                                479     692.46              
## species            1   61.399       478     631.06 4.661e-15 ***
## Microsite          1    2.248       477     628.81    0.1338    
## species:Microsite  1   44.941       476     583.87 2.030e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Analysis of Deviance Table
## 
## Model: Negative Binomial(1.0411), link: log
## 
## Response: abundance2
## 
## Terms added sequentially (first to last)
## 
## 
##                   Df Deviance Resid. Df Resid. Dev  Pr(>Chi)    
## NULL                                239     441.89              
## species            1   31.310       238     410.58 2.199e-08 ***
## Microsite          1    2.489       237     408.09    0.1146    
## species:Microsite  1  109.682       236     298.41 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## $lsmeans
##  Microsite species   lsmean        SE df asymp.LCL asymp.UCL
##  Open      brome   3.837479 0.1012017 NA  3.639127  4.035831
##  Shrub     brome   4.356816 0.1008417 NA  4.159170  4.554462
##  Open      nbrome  3.664843 0.1013687 NA  3.466164  3.863522
##  Shrub     nbrome  2.810406 0.1027799 NA  2.608961  3.011851
## 
## Results are given on the log scale. 
## Confidence level used: 0.95 
## 
## $contrasts
##  contrast                     estimate        SE df   z.ratio p.value
##  Open,brome - Shrub,brome   -0.5193366 0.1428664 NA -3.635120  0.0016
##  Open,brome - Open,nbrome    0.1726362 0.1432389 NA  1.205232  0.6235
##  Open,brome - Shrub,nbrome   1.0270728 0.1442411 NA  7.120528  <.0001
##  Shrub,brome - Open,nbrome   0.6919728 0.1429848 NA  4.839485  <.0001
##  Shrub,brome - Shrub,nbrome  1.5464095 0.1439887 NA 10.739794  <.0001
##  Open,nbrome - Shrub,nbrome  0.8544367 0.1443583 NA  5.918859  <.0001
## 
## Results are given on the log scale. 
## P value adjustment: tukey method for comparing a family of 4 estimates