See new HierarchicalPartitioning results
All ANOVAs conducted using log+1 transforms. All charts show mean abundance. Error bars show 1 SE
Site effect was only significant for one species, Lerista edwardsae. Does this mean that sites can be pooled in subsequent analyses?
Generated using lmemultifactor()
numDF denDF F-value p-value
(Intercept) 1 22 133.98304 <.0001
Site 1 4 0.61518 0.4767
Conn 1 22 1.71652 0.2037
Site:Conn 1 22 10.58785 0.0036 ***

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.2058 0.2058 1.2226 0.281978 epdata$Treat 4 4.0046 1.0011 5.9467 0.002542 ** epdata$Site:epdata$Treat 4 1.0892 0.2723 1.6174 0.208885 Residuals 20 3.3670 0.1684 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 16 7.772721 0.0132 * Site 1 4 0.744309 0.4369 Setting 1 16 22.816299 0.0002 ** Dune 1 16 2.366991 0.1435 Conn 1 16 0.394499 0.5388 Site:Setting 1 16 2.184868 0.1588 Site:Dune 1 16 2.366991 0.1435 Site:Conn 1 16 0.394499 0.5388 Setting:Dune 1 16 2.761490 0.1160 Site:Setting:Dune 1 16 2.761490 0.1160 Removing three-way interaction makes AIC worse

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.4004 0.4004 1.7916 0.19574 epdata$Treat 4 3.4706 0.8677 3.8826 0.01715 * epdata$Site:epdata$Treat 4 0.8008 0.2002 0.8958 0.48479 Residuals 20 4.4694 0.2235 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
species ~ Site + Setting + Dune + Conn + Site:Setting + Setting:Dune
numDF denDF F-value p-value
(Intercept) 1 19 21.033257 0.0002 ***
Site 1 4 1.748863 0.2566
Setting 1 19 13.923258 0.0014 **
Dune 1 19 0.009700 0.9226
Conn 1 19 0.058201 0.8119
Site:Setting 1 19 3.055575 0.0966 .
Setting:Dune 1 19 3.666690 0.0707 .

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.1917 0.1917 0.5949 0.44956 epdata$Treat 4 3.4298 0.8574 2.6613 0.06271 . epdata$Site:epdata$Treat 4 0.7667 0.1917 0.5949 0.67042 Residuals 20 6.4438 0.3222 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
Linear mixed-effects model fit by maximum likelihood
Data: epdata
Log-likelihood: -59.71518
Fixed: species ~ Setting
(Intercept) SettingPark
3.353951e-16 1.833333e+00
Random effects:
Formula: ~1 | Block
(Intercept) Residual
StdDev: 0.7051382 1.660824
Number of Observations: 30
Number of Groups: 6
numDF denDF F-value p-value
(Intercept) 1 23 5.942308 0.0229 *
Setting 1 23 13.909066 0.0011 **

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.5134 0.5134 1.3197 0.26420 epdata$Treat 4 4.6909 1.1727 3.0147 0.04252 * epdata$Site:epdata$Treat 4 1.3626 0.3407 0.8757 0.49586 Residuals 20 7.7802 0.3890 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 19 16.435473 0.0007 ** Site 1 4 0.671926 0.4584 Setting 1 19 19.147975 0.0003 ** Dune 1 19 0.032842 0.8581 Conn 1 19 0.313499 0.5821 Site:Setting 1 19 2.656279 0.1196 Site:Conn 1 19 2.337651 0.1428

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 2.3719 2.3719 6.3785 0.02010 * epdata$Treat 4 2.4738 0.6184 1.6631 0.19793 epdata$Site:epdata$Treat 4 2.7390 0.6847 1.8414 0.16050 Residuals 20 7.4374 0.3719 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 18 28.629172 <.0001 ** Site 1 4 6.886502 0.0585 . Setting 1 18 2.985413 0.1011 Dune 1 18 1.384252 0.2547 Conn 1 18 0.784562 0.3874 Site:Setting 1 18 4.591002 0.0461 * Site:Dune 1 18 2.954090 0.1028 Setting:Dune 1 18 2.027920 0.1715

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.6237 0.6237 3.6014 0.072260 . epdata$Treat 4 3.7961 0.9490 5.4804 0.003805 ** epdata$Site:epdata$Treat 4 0.9689 0.2422 1.3988 0.270383 Residuals 20 3.4633 0.1732 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 19 22.520103 0.0001 ** Site 1 4 3.958531 0.1175 Setting 1 19 6.620797 0.0186 * Dune 1 19 9.552353 0.0060 ** Conn 1 19 3.382333 0.0816 . Site:Dune 1 19 5.132824 0.0354 * Setting:Dune 1 19 4.539817 0.0464 *

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.1882 0.1882 0.2312 0.63586 epdata$Treat 4 10.7005 2.6751 3.2855 0.03180 * epdata$Site:epdata$Treat 4 0.9806 0.2452 0.3011 0.87375 Residuals 20 16.2847 0.8142 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 22 52.37777 <.0001 Setting 1 22 1.92294 0.1794 Dune 1 22 13.54367 0.0013 **

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.3122 0.3122 1.1805 0.2902 epdata$Treat 4 0.7078 0.1770 0.6692 0.6209 epdata$Site:epdata$Treat 4 0.4359 0.1090 0.4121 0.7978 Residuals 20 5.2889 0.2644
Using lme
numDF denDF F-value p-value (Intercept) 1 24 9.24163 0.0056 *

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.02720 0.02720 0.1972 0.66176 epdata$Treat 4 1.57177 0.39294 2.8485 0.05098 . epdata$Site:epdata$Treat 4 1.08766 0.27191 1.9711 0.13791 Residuals 20 2.75896 0.13795 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using lme
numDF denDF F-value p-value (Intercept) 1 20 755.0215 <.0001 *** Site 1 4 0.2017 0.6766 Setting 1 20 12.0955 0.0024 ** Dune 1 20 0.0005 0.9830 Conn 1 20 0.0005 0.9828 Site:Conn 1 20 7.0582 0.0151 *

Df Sum Sq Mean Sq F value Pr(>F) epdata$Site 1 0.5967 0.5967 1.7515 0.20062 epdata$Treat 4 3.2982 0.8245 2.4204 0.08223 . epdata$Site:epdata$Treat 4 1.6047 0.4012 1.1776 0.35060 Residuals 20 6.8133 0.3407 --- Signif. codes: 0 ***, 0.001 **, 0.01 *, 0.05 ., 0.1 , 1
Using LME
numDF denDF F-value p-value (Intercept) 1 18 634.9432 <.0001 *** Site 1 4 1.8815 0.2421 Setting 1 18 9.7700 0.0058 * Dune 1 18 0.2075 0.6542 Conn 1 18 0.2610 0.6157 Site:Setting 1 18 1.0573 0.3175 Site:Dune 1 18 0.6200 0.4413 Site:Conn 1 18 3.0297 0.0988 .
Hypothesis: The agricultural or conservation park setting has an interaction with swale and dune-top settings in explaining differences in reptile communities. Also fit the dune interaction to check Hypothesis 3.

numDF denDF F-value p-value
(Intercept) 1 21 8.519283 0.0082
farmfactor 1 21 20.017807 0.0002 ***
Dune 1 21 2.076672 0.1643
farmfactor:Dune 1 21 2.768897 0.1110

numDF denDF F-value p-value
(Intercept) 1 21 17.227168 0.0005
farmfactor 1 21 13.003980 0.0017 **
Dune 1 21 0.009060 0.9251
farmfactor:Dune 1 21 2.717935 0.1141

numDF denDF F-value p-value
(Intercept) 1 21 5.517858 0.0287
farmfactor 1 21 13.123339 0.0016 **
Dune 1 21 0.143408 0.7087
farmfactor:Dune 1 21 0.191210 0.6664

numDF denDF F-value p-value
(Intercept) 1 21 16.211080 0.0006
farmfactor 1 21 16.817223 0.0005 ***
Dune 1 21 0.028845 0.8668
farmfactor:Dune 1 21 0.021633 0.8845

numDF denDF F-value p-value
(Intercept) 1 21 14.771562 0.0009
farmfactor 1 21 2.207673 0.1522
Dune 1 21 1.023636 0.3232
farmfactor:Dune 1 21 0.767727 0.3908

numDF denDF F-value p-value
(Intercept) 1 21 15.323702 0.0008
farmfactor 1 21 4.505092 0.0459 *
Dune 1 21 6.499855 0.0187 *
farmfactor:Dune 1 21 1.227008 0.2805

numDF denDF F-value p-value
(Intercept) 1 21 50.43785 <.0001
farmfactor 1 21 1.85529 0.1876
Dune 1 21 13.06717 0.0016 **
farmfactor:Dune 1 21 0.04005 0.8433

numDF denDF F-value p-value
(Intercept) 1 21 9.135788 0.0065
farmfactor 1 21 0.757254 0.3940
Dune 1 21 0.118875 0.7337
farmfactor:Dune 1 21 1.791742 0.1950

numDF denDF F-value p-value
(Intercept) 1 21 660.0790 <.0001
farmfactor 1 21 8.6397 0.0078 **
Dune 1 21 0.0529 0.8203
farmfactor:Dune 1 21 0.5355 0.4724

numDF denDF F-value p-value
(Intercept) 1 21 579.5905 <.0001
farmfactor 1 21 7.9368 0.0103 *
Dune 1 21 0.3625 0.5536
farmfactor:Dune 1 21 0.0205 0.8875

numDF denDF F-value p-value
(Intercept) 1 21 96.06453 <.0001
farmfactor 1 21 1.78720 0.1956
Dune 1 21 0.01485 0.9042
farmfactor:Dune 1 21 0.10288 0.7516
The composition of reptile communities inhabiting paddock dune-tops that are connected to vegetated roadside swales is different to that of the reptile communities inhabiting paddock dune-tops isolated from roadside vegetation.
Uses lme(log(species+1) ~ Treat, random = ~1|Block, data=farms, method="ML")
Ctenophorus fordi, Ctenotus schomburgkii not found in farms.





Reptile communities inhabiting dune-tops 10 km from a conservation park are different to those living on dune-tops within conservation parks





2D MDS (stress = 19.23265) with envfit vectors (p < 0.1). Vectors are probably dangerous as the MDS is unconstrained by them. Treatments within a replicate blocks share colour. ordisurf shows Condition.

Using ANOSIM, based on 1000 permutations, against presence-absence vegdist (29 sites)
"Pspinifex" R = 0.2136 P = 0.007 * "Pmelaleuca" R = 0.2939 P = 0.014 * "Peucalyptus" R = -0.1302 P = 0.717 "Spinifex" R = -0.1582 P = 0.893 "Melaleuca" R = -0.07018 P = 0.675 "Eucalyptus" R = 0.2642 P = 0.085 . "Bare" R = 0.009395 P = 0.471 "Leaf" R = -0.1341 P = 0.732 "Other" R = 0.1476 P = 0.108 "Clay" R = 0.1759 P = 0.078 . "Canopy" R = 0.3745 P = 0.003 * "Condition" R = 0.4032 P = 0.001 *
Using ANOSIM, based on 1000 permutations, against abundance vegdist (30 sites)
"Pspinifex" R = 0.2238 P = 0.002 * "Pmelaleuca" R = 0.266 P = 0.011 * "Peucalyptus" R = -0.1101 P = 0.646 "Spinifex" R = -0.09845 P = 0.818 "Melaleuca" R = -0.0745 P = 0.689 "Eucalyptus" R = 0.2404 P = 0.072 . "Bare" R = -0.02545 P = 0.536 "Leaf" R = -0.1698 P = 0.801 "Other" R = 0.1448 P = 0.105 "Clay" R = 0.1603 P = 0.066 . "Canopy" R = 0.3686 P = 0.002 * "Condition" R = 0.3928 P = 0.001 *
Using envfit, 1000 permutations, against presence-absence MDS (29 sites)
NMDS1 NMDS2 r2 Pr(>r) Pspinifex -0.992446 -0.122679 0.2067 0.049 * Pmelaleuca -0.635672 -0.771960 0.2523 0.024 * Peucalyptus 0.955749 -0.294184 0.0168 0.811 Spinifex -0.973562 -0.228422 0.1372 0.154 Melaleuca -0.891114 -0.453780 0.1363 0.140 Eucalyptus 0.428748 0.903424 0.1110 0.192 Bare 0.338175 -0.941083 0.4062 0.001 *** Leaf 0.276493 0.961016 0.1482 0.117 Other 0.031735 0.999496 0.1082 0.237 Clay 0.574420 0.818561 0.2167 0.029 * Canopy 0.816723 0.577029 0.0994 0.251 Condition -0.915488 0.402345 0.6122 <0.001 ***
Using adonis
adonis(formula = ahr ~ Pspinifex + Pmelaleuca + Peucalyptus + Spinifex + Melaleuca + Eucalyptus + Bare + Leaf + Other + Clay + Canopy + Condition, data = vegdata, permutations = 1000)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Pspinifex 1.00000 0.91484 0.91484 3.92451 0.0953 <0.001 ***
Pmelaleuca 1.00000 0.46948 0.46948 2.01399 0.0489 0.059 .
Peucalyptus 1.00000 0.20934 0.20934 0.89802 0.0218 0.996
Spinifex 1.00000 0.29480 0.29480 1.26464 0.0307 1.000
Melaleuca 1.00000 0.30302 0.30302 1.29991 0.0316 1.000
Eucalyptus 1.00000 0.32787 0.32787 1.40652 0.0342 1.000
Bare 1.00000 0.71195 0.71195 3.05414 0.0742 0.996
Leaf 1.00000 0.26100 0.26100 1.11964 0.0272 1.000
Other 1.00000 0.26978 0.26978 1.15732 0.0281 1.000
Clay 1.00000 0.42419 0.42419 1.81969 0.0442 1.000
Canopy 1.00000 0.29266 0.29266 1.25545 0.0305 1.000
Condition 1.00000 1.15915 1.15915 4.97254 0.1207 1.000
Residuals 17.00000 3.96286 0.23311 0.4128
Total 29.00000 9.60094 1.0000
adonis with each parameter fitted one-by-one:
Pspinifex 1.00000 0.91484 0.91484 2.94903 0.0953 0.008 ** Pmelaleuca 1.00000 0.70146 0.70146 2.20698 0.0731 0.023 * Peucalyptus 1.00000 0.22738 0.22738 0.67921 0.0237 0.786 Spinifex 1.00000 0.71905 0.71905 2.26678 0.0749 0.017 * Melaleuca 1.00000 0.69733 0.69733 2.19295 0.0726 0.016 * Eucalyptus 1.00000 0.30853 0.30853 0.92968 0.0321 0.516 Bare 1.00000 0.74689 0.74689 2.36198 0.0778 0.017 * Leaf 1.00000 0.50450 0.50450 1.55290 0.0525 0.118 Other 1.00000 0.33578 0.33578 1.01477 0.035 0.42 Clay 1.00000 0.74817 0.74817 2.36636 0.0779 0.015 * Canopy 1.00000 0.53242 0.53242 1.64390 0.0555 0.092 . Condition 1.00000 1.79674 1.79674 6.44637 0.1871 < 0.001 ***