Updated models with new current map and 900 m buffer for dragons

Author: icrichmond

graphics/modeldiagnostics/normalmodels_ani.pdf

@@ -1,3 +1,3 @@
 "","term","estimate","std.error","statistic","p.value"
-"1","(Intercept)",254.813134260157,24.2945317864074,10.4884974322791,6.71767318802026e-14
-"2","mean.two",305.795863175109,38.2007397348525,8.0049722936678,2.50409228190112e-10
+"1","(Intercept)",209.396674141217,18.7479245067347,11.1690589572193,8.01830235334951e-15
+"2","mean.nine",231.65739955979,28.6637279895412,8.08190056939965,1.92283726013335e-10

graphics/modeldiagnostics/normalmodels_zyg.pdf

@@ -0,0 +1,3 @@
+"","term","estimate","std.error","statistic","p.value"
+"1","(Intercept)",25.8139141096835,7.03684717622861,3.66839203171645,0.000621188993085252
+"2","n.nine",1.71804649183252,0.16396643720788,10.4780375855477,6.94395375602082e-14

output/models/AnisopteraAbundanceCurrent_Summary.csv

@@ -0,0 +1,3 @@
+"","term","estimate","std.error","statistic","p.value"
+"1","(Intercept)",10.7839702541991,0.902384490165893,11.9505270444271,7.51648937810001e-16
+"2","mean.nine",4.96952227772855,1.37965690862497,3.60199861767183,0.000759191347658556

output/models/AnisopteraAbundanceHabitat_Summary.csv

@@ -1,3 +1,3 @@
 "","term","estimate","std.error","statistic","p.value"
-"1","(Intercept)",6.80586700241236,0.429057934791738,15.8623496981029,1.69174211432341e-20
-"2","n.two",0.0084216036360301,0.00243140044355351,3.46368433811826,0.00114682359453729
+"1","(Intercept)",7.0016182967857,0.409637476166867,17.0922308239532,8.41049614106333e-22
+"2","n.nine",0.0305382162593058,0.00954501296273808,3.19938971047197,0.00246772297558032

output/models/AnisopteraAbundanceHabitat_summary.csv

@@ -1,3 +1,3 @@
 "","term","estimate","std.error","statistic","p.value"
-"1","(Intercept)",0.934561788127682,0.129489014029536,7.2173056157066,3.82998910661173e-09
-"2","mean.threeh",-0.335944241204735,0.196841852783562,-1.7066707941127,0.0944831730440966
+"1","(Intercept)",0.94025559670646,0.118235263648641,7.95241256872919,3.00011515273737e-10
+"2","mean.three",-0.320401643063373,0.173671726998356,-1.84486933251033,0.0713630793374195

output/models/AnisopteraRichnessCurrent_summary.csv

@@ -0,0 +1,3 @@
+"","term","estimate","std.error","statistic","p.value"
+"1","(Intercept)",5.01701073330726,0.660974023197496,7.59032966081967,1.04755527700569e-09
+"2","mean.three",-2.39609904160638,0.970882091918778,-2.46796090024785,0.0172842405291333

output/models/AnisopteraSpeciesRichnessCurrent_Summary.csv

@@ -13,29 +13,29 @@ source("script/function - diagnosticplots.R")
 
 #### Correlations ####
 # check correlations between mean/sd and mean/hab 
-ggplot(ani, aes(x = n.two, y = mean.two)) + 
+ggplot(ani, aes(x = n.nine, y = mean.nine)) + 
   geom_point() + 
   geom_smooth(method = "lm", se = FALSE) + 
   stat_cor()
 # highly correlated
 
-ggplot(ani, aes(x = n.threeh, y = mean.threeh)) + 
+ggplot(ani, aes(x = n.three, y = mean.three)) + 
   geom_point() + 
   geom_smooth(method = "lm", se = FALSE) + 
   stat_cor()
-# correlation of 0.63, fairly correlated 
+# correlation of 0.54, fairly correlated 
 
-ggplot(ani, aes(x = mean.two, y = sd.two)) + 
+ggplot(ani, aes(x = mean.nine, y = sd.nine)) + 
   geom_point() + 
   geom_smooth(method = "lm", se = FALSE) + 
   stat_cor()
-# correlation of 0.5, OK
+# correlation of -0.21, OK
 
-ggplot(zyg, aes(x = mean.threeh, y = sd.threeh)) + 
+ggplot(zyg, aes(x = mean.three, y = sd.three)) + 
   geom_point() + 
   geom_smooth(method = "lm", se = FALSE) + 
   stat_cor()
-# correlation of 0.38, fairly correlated 
+# correlation of 0.23, OK
 
 # number of surrounding habitats and mean conductance are 
 # highly correlated
@@ -46,27 +46,29 @@ ggplot(zyg, aes(x = mean.threeh, y = sd.threeh)) +
 
 ## Anisoptera ##
 # Abundance
-ani_abun <- lm(abundance ~  mean.two,  data = ani)
+ani_abun <- lm(abundance ~  mean.nine,  data = ani)
 summary(ani_abun)
 # significant
 
-ani_abun_hab <- lm(abundance ~ n.two, data = ani)
+ani_abun_hab <- lm(abundance ~ n.nine, data = ani)
 summary(ani_abun_hab)
 # significant
 
 # Shannon Diversity 
-ani_shann <- lm(shannon ~ mean.two, data = ani)
+ani_shann <- lm(shannon ~ mean.nine, data = ani)
 summary(ani_shann)
-# almost significant
-ani_shann_hab <- lm(shannon ~ n.two, data = ani)
+# not significant
+
+ani_shann_hab <- lm(shannon ~ n.nine, data = ani)
 summary(ani_shann_hab)
 # not significant 
 
 # Species Richness
-ani_sr <- lm(speciescount ~ mean.two, data = ani)
+ani_sr <- lm(speciescount ~ mean.nine, data = ani)
 summary(ani_sr)
 # mean significant
-ani_sr_hab <- lm(speciescount ~ n.two, data = ani)
+
+ani_sr_hab <- lm(speciescount ~ n.nine, data = ani)
 summary(ani_sr_hab)
 # significant
 
@@ -87,40 +89,40 @@ dev.off()
 summ1 <- broom::tidy(ani_abun)
 write.csv(summ1, "output/models/AnisopteraAbundanceCurrent_Summary.csv")
 
-summ2 <- broom::tidy(ani_sr)
-write.csv(summ2, "output/models/AnisopteraRichnessCurrent_summary.csv")
+summ2 <- broom::tidy(ani_abun_hab)
+write.csv(summ2, "output/models/AnisopteraAbundanceHabitat_summary.csv")
 
-summ3 <- broom::tidy(ani_abun_hab)
-write.csv(summ3, "output/models/AnisopteraAbundanceHabitat_Summary.csv")
+summ3 <- broom::tidy(ani_sr)
+write.csv(summ3, "output/models/AnisopteraSpeciesRichnessCurrent_Summary.csv")
 
 summ4 <- broom::tidy(ani_sr_hab)
 write.csv(summ4, "output/models/AnisopteraSpeciesRichnessHabitat_Summary.csv")
 
 ## Zygoptera ##
 # Abundance
-zyg_abun <- lm(abundance ~ mean.threeh, data = zyg)
+zyg_abun <- lm(abundance ~ mean.three, data = zyg)
 summary(zyg_abun)
 # not significant
 
-zyg_abun_hab <- lm(abundance ~ n.threeh, data = zyg)
+zyg_abun_hab <- lm(abundance ~ n.three, data = zyg)
 summary(zyg_abun_hab)
 # not significant
 
 # Shannon Diversity 
-zyg_shann <- lm(shannon ~ mean.threeh, data = zyg)
+zyg_shann <- lm(shannon ~ mean.three, data = zyg)
 summary(zyg_shann)
-# almost significant (0.08)
+# almost significant (0.07)
 
-zyg_shann_hab <- lm(shannon ~ n.threeh, data = zyg)
+zyg_shann_hab <- lm(shannon ~ n.three, data = zyg)
 summary(zyg_shann_hab)
 # not significant
 
 # Species Richness
-zyg_sr <- lm(speciescount ~ mean.threeh, data = zyg)
+zyg_sr <- lm(speciescount ~ mean.three, data = zyg)
 summary(zyg_sr)
 # mean significant
 
-zyg_sr_hab <- lm(speciescount ~ n.threeh, data = zyg)
+zyg_sr_hab <- lm(speciescount ~ n.three, data = zyg)
 summary(zyg_sr_hab)
 # not significant
 
@@ -137,11 +139,11 @@ dev.off()
 
 # model diagnostic plots look ok
 
-summ6 <- broom::tidy(zyg_sr)
-write.csv(summ6, "output/models/ZygopteraRichnessCurrent_Summary.csv")
+summ6 <- broom::tidy(zyg_shann)
+write.csv(summ6, "output/models/ZygopteraShannonCurrent_Summary.csv")
 
-summ7 <- broom::tidy(zyg_shann)
-write.csv(summ7, "output/models/ZygopteraShannonCurrent_Summary.csv")
+summ7 <- broom::tidy(zyg_sr)
+write.csv(summ7, "output/models/ZygopteraSpeciesRichnessCurrent_Summary.csv")
 
 # IMPORTANT: sd seems to be a dummy variable - switches direction and magnitude 
 # of effect depending on what else is in the model, do not include in models. Can't