Birds_Maquis_analysis_by_plot_with_subunit_interactions
Ron Chen
2024-04-09
## Loading required package: readxl## Loading required package: lubridate##
## Attaching package: 'lubridate'## The following objects are masked from 'package:data.table':
##
## hour, isoweek, mday, minute, month, quarter, second, wday, week,
## yday, year## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union## Loading required package: solartime## - Winter data excluded.
## - The counts of all passing / wintering species (not breeding in the sampled unit) were set to zero. Abreed_and_non_breed contains the non-breeders as well.
## - Species less likely to be interacting with sampling location were EXCLUDED
## - observations with counts greater than or equal to 10 standard deviations AND greater than or equal to 60 individuals were set to 1,
## under the assumption that these are migrating or local wandering phenomena.
## No outliers found in unit Arid South.
## 2 outliers set equal to 1 in Herbaceous and Dwarf-Shrub Vegetation unit.
## unit point_name year
## 1: Herbaceous and Dwarf-Shrub Vegetation Gamla Near 3 2014
## 2: Herbaceous and Dwarf-Shrub Vegetation Yavneel Far 2 2018
## SciName count_under_250 Z_score
## 1: Passer domesticus 62 11.90316
## 2: Passer hispaniolensis 60 11.35733
## No outliers found in unit Inland Sands.
## No outliers found in unit Loess Covered Areas in the Northern Negev.
## No outliers found in unit Mediterranean-Desert Transition Zone.
## 5 outliers set equal to 1 in Mediterranean Maquis unit.
## unit point_name year SciName
## 1: Mediterranean Maquis Beit Oren Near 1 2019 Curruca curruca
## 2: Mediterranean Maquis Beit Oren Near 3 2019 Curruca curruca
## 3: Mediterranean Maquis Kerem Maharal Near 3 2021 Chloris chloris
## 4: Mediterranean Maquis Kerem Maharal Near 3 2021 Garrulus glandarius
## 5: Mediterranean Maquis Nir Etzion Far 11 2021 Columba livia
## count_under_250 Z_score
## 1: 99 11.94535
## 2: 142 17.16927
## 3: 80 19.19266
## 4: 150 20.50138
## 5: 100 14.85118
## 2 outliers set equal to 1 in Negev Highlands unit.
## unit point_name year SciName
## 1: Negev Highlands Yeruham Far Slope 5 2018 Carpospiza brachydactyla
## 2: Negev Highlands Bislach Near Slope 6 2020 Passer hispaniolensis
## count_under_250 Z_score
## 1: 70 14.34802
## 2: 100 10.61343
## No outliers found in unit Planted Conifer Forest.Mediterranean Maquis
Unit is divided into 3 subunits: Judea, Carmel and Galilee. Factors are proximity to settlements and time. Sampling started in spring 2012 (pilot year), but during T0 sampling was performed only in winter of 2014, and the next spring sampling was done in T1 (2015). Therefore 2012 will not be considered as pilot here but as T0. Total 5 campaigns, 3subunits per campaign, 5 sites per subunit, with 6 plots per site (total of 450 plot-campaign combinations).
Raw data Total abundance: 21855 Number of observations: 5795 Total richness: 108
Filtered data Total abundance: 13230 Number of observations: 3576 Total richness: 49
Model gma, abundance and richness
Richness done with rare species. Abundance and mean abundance done without rare species. Full models include cosine and sine of the time difference from June 21st (in radians).
richness
Explore data and plot mean-variance plot. There is a strong relationship, indicating that employing GLMs is the proper way to analyze, rather than OLS (assumption of homogeneity is violated).
## [1] "RICHNESS WITH RARE SPECIES"
| richness | year_ct | site | settlements | subunit | td_sc | cos_td_rad | sin_td_rad | h_from_sunrise | cos_hsun | sin_hsun | monitors_name | wind | precipitation | temperature | clouds | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min. : 0.000 | Min. :0.0 | Nir Etzion : 31 | Far :224 | Judean Highlands:150 | Min. :-1.9882 | Min. :-0.1671 | Min. :-1.0000 | Length:444 | Min. :-0.3289 | Min. :-0.1253 | Sassi Haham : 53 | 0 : 33 | 0 :119 | 0 : 4 | 0 : 32 | |
| 1st Qu.: 6.000 | 1st Qu.:3.0 | Aderet : 30 | Near:220 | Carmel :149 | 1st Qu.:-0.2713 | 1st Qu.: 0.5702 | 1st Qu.:-0.8215 | Class :difftime | 1st Qu.: 0.6855 | 1st Qu.: 0.2563 | Eyal Shochat: 47 | 1 : 42 | 3 : 2 | 1 : 38 | 1 : 0 | |
| Median : 8.000 | Median :5.0 | Ein Yaakov : 30 | NA | Galilee :145 | Median : 0.4918 | Median : 0.8140 | Median :-0.5808 | Mode :numeric | Median : 0.8738 | Median : 0.4863 | Eran Banker : 30 | 2 : 12 | NA’s:323 | 2 : 37 | 2 : 5 | |
| Mean : 8.054 | Mean :4.8 | Givat Yearim : 30 | NA | NA | Mean : 0.3205 | Mean : 0.7098 | Mean :-0.5864 | NA | Mean : 0.7997 | Mean : 0.4836 | Asaf Mayrose: 18 | 3 : 2 | NA | 3 : 18 | 3 : 13 | |
| 3rd Qu.:10.000 | 3rd Qu.:7.0 | Givat Yeshayahu: 30 | NA | NA | 3rd Qu.: 1.1023 | 3rd Qu.: 0.9413 | 3rd Qu.:-0.3375 | NA | 3rd Qu.: 0.9666 | 3rd Qu.: 0.7281 | Ohad Sharir : 18 | NA’s:355 | NA | NA’s:347 | NA’s:394 | |
| Max. :18.000 | Max. :9.0 | Goren : 30 | NA | NA | Max. : 1.7127 | Max. : 0.9976 | Max. :-0.0688 | NA | Max. : 1.0000 | Max. : 0.9998 | (Other) : 58 | NA | NA | NA | NA | |
| NA | NA | (Other) :263 | NA | NA | NA | NA | NA | NA | NA’s :89 | NA’s :89 | NA’s :220 | NA | NA | NA | NA |
no observation for all 4 weather variables. many NAs for sampling time of day variables.exclude from model. An extreme observation of richness>20 in Judean highlands near settlements.
| richness | year_ct | site | settlements | subunit | td_sc | cos_td_rad | sin_td_rad | h_from_sunrise | cos_hsun | sin_hsun | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| richness | 1.0000000 | -0.0647635 | 0.0921563 | 0.4762118 | -0.1958868 | 0.0617968 | 0.0751315 | 0.0460403 | -0.0582024 | 0.0933868 | -0.0342460 |
| year_ct | -0.0647635 | 1.0000000 | -0.0464072 | -0.0041782 | 0.0026486 | -0.6240340 | -0.5599811 | -0.6642968 | 0.0244310 | -0.0070326 | 0.0341395 |
| site | 0.0921563 | -0.0464072 | 1.0000000 | 0.0043400 | -0.1430283 | 0.0100854 | 0.0014078 | 0.0293999 | -0.0104260 | -0.0094853 | -0.0240013 |
| settlements | 0.4762118 | -0.0041782 | 0.0043400 | 1.0000000 | -0.0139419 | 0.0029695 | 0.0016285 | 0.0037459 | 0.0341209 | -0.0071595 | 0.0507160 |
| subunit | -0.1958868 | 0.0026486 | -0.1430283 | -0.0139419 | 1.0000000 | -0.0072106 | -0.0147569 | -0.0150797 | 0.1195292 | -0.1176660 | 0.1172271 |
| td_sc | 0.0617968 | -0.6240340 | 0.0100854 | 0.0029695 | -0.0072106 | 1.0000000 | 0.9788766 | 0.9693667 | -0.1975082 | 0.1811635 | -0.2043768 |
| cos_td_rad | 0.0751315 | -0.5599811 | 0.0014078 | 0.0016285 | -0.0147569 | 0.9788766 | 1.0000000 | 0.9008724 | -0.1878186 | 0.1700185 | -0.1970275 |
| sin_td_rad | 0.0460403 | -0.6642968 | 0.0293999 | 0.0037459 | -0.0150797 | 0.9693667 | 0.9008724 | 1.0000000 | -0.2005880 | 0.1868900 | -0.2040813 |
| h_from_sunrise | -0.0582024 | 0.0244310 | -0.0104260 | 0.0341209 | 0.1195292 | -0.1975082 | -0.1878186 | -0.2005880 | 1.0000000 | -0.9598144 | 0.9818950 |
| cos_hsun | 0.0933868 | -0.0070326 | -0.0094853 | -0.0071595 | -0.1176660 | 0.1811635 | 0.1700185 | 0.1868900 | -0.9598144 | 1.0000000 | -0.8930078 |
| sin_hsun | -0.0342460 | 0.0341395 | -0.0240013 | 0.0507160 | 0.1172271 | -0.2043768 | -0.1970275 | -0.2040813 | 0.9818950 | -0.8930078 | 1.0000000 |
Fit Poisson glm, check for existence of overdispersion
## [1] "Estimating overdispersion parameter phi: (Res. Dev.)/(n-p) where n=number of observations; p=number of parameters in the model."## [1] "od = 0.884489032364373"Overdispersion parameter is < 1. Choose Poisson.
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00702325 (tol = 0.002, component 1)## GVIF Df GVIF^(1/(2*Df))
## settlements 5.275980 1 2.296950
## year_ct 4.733290 1 2.175612
## subunit 5.403996 2 1.524680
## cos_td_rad 5.681629 1 2.383617
## sin_td_rad 7.442357 1 2.728068
## settlements:year_ct 4.715161 1 2.171442
## year_ct:subunit 7.180804 2 1.636980
## settlements:subunit 4.938103 2 1.490699go with mixed model, attempt model selection yet.
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: poisson ( log )
## Formula: richness ~ settlements * year_ct + subunit * year_ct + settlements *
## subunit + cos_td_rad + sin_td_rad + (1 | site)
## Data: P.anal
##
## AIC BIC logLik deviance df.resid
## 2106.5 2159.8 -1040.3 2080.5 431
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.04010 -0.54716 -0.09468 0.55937 2.67846
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.00841 0.09171
## Number of obs: 444, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.389901 0.219967 6.319 2.64e-10 ***
## settlementsNear 0.507954 0.078264 6.490 8.57e-11 ***
## year_ct 0.003986 0.011666 0.342 0.732595
## subunitCarmel 0.151911 0.105900 1.434 0.151434
## subunitGalilee 0.092777 0.110285 0.841 0.400211
## cos_td_rad 0.347864 0.151374 2.298 0.021559 *
## sin_td_rad -0.314705 0.178286 -1.765 0.077535 .
## settlementsNear:year_ct -0.003295 0.010890 -0.303 0.762194
## year_ct:subunitCarmel -0.007766 0.012996 -0.598 0.550153
## year_ct:subunitGalilee -0.026028 0.014597 -1.783 0.074574 .
## settlementsNear:subunitCarmel -0.062413 0.080739 -0.773 0.439506
## settlementsNear:subunitGalilee -0.302456 0.086496 -3.497 0.000471 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) sttlmN yer_ct sbntCr sbntGl cs_td_ sn_td_ sttN:_ yr_c:C
## settlmntsNr -0.228
## year_ct -0.232 0.390
## subunitCrml -0.356 0.261 0.297
## subunitGall -0.395 0.280 0.299 0.517
## cos_td_rad -0.911 0.006 0.043 0.102 0.139
## sin_td_rad 0.871 -0.007 0.096 -0.143 -0.199 -0.857
## sttlmntsN:_ 0.158 -0.668 -0.578 -0.009 -0.053 -0.009 0.012
## yr_ct:sbntC 0.322 -0.010 -0.490 -0.584 -0.330 -0.160 0.252 0.011
## yr_ct:sbntG 0.358 -0.047 -0.461 -0.300 -0.620 -0.203 0.298 0.068 0.514
## sttlmntsN:C 0.113 -0.541 -0.010 -0.471 -0.236 0.006 -0.011 0.007 0.003
## sttlmntsN:G 0.119 -0.518 -0.016 -0.232 -0.458 -0.003 0.006 0.026 0.005
## yr_c:G sttN:C
## settlmntsNr
## year_ct
## subunitCrml
## subunitGall
## cos_td_rad
## sin_td_rad
## sttlmntsN:_
## yr_ct:sbntC
## yr_ct:sbntG
## sttlmntsN:C -0.001
## sttlmntsN:G 0.016 0.485
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.00702325 (tol = 0.002, component 1)perform stepwise model selection of poisson mixed model.
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.0061038 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00642696 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00457295 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## richness ~ settlements * year_ct + subunit * year_ct + settlements *
## subunit + cos_td_rad + sin_td_rad + (1 | site)
## npar AIC
## <none> 2106.5
## cos_td_rad 1 2109.9
## sin_td_rad 1 2107.6
## settlements:year_ct 1 2104.6
## year_ct:subunit 2 2105.8
## settlements:subunit 2 2115.8remove settlements X year.
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00710827 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.0020179 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00289438 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00509036 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00266073 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## richness ~ subunit * year_ct + settlements * subunit + cos_td_rad +
## sin_td_rad + (1 | site)
## npar AIC
## <none> 2104.6
## cos_td_rad 1 2107.9
## sin_td_rad 1 2105.7
## subunit:year_ct 2 2103.9
## subunit:settlements 2 2113.9drop subunit X year
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00506164 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00234523 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## richness ~ year_ct + settlements * subunit + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 2103.9
## year_ct 1 2102.4
## cos_td_rad 1 2105.9
## sin_td_rad 1 2103.7
## settlements:subunit 2 2113.0drop year
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00234523 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## richness ~ settlements * subunit + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 2102.4
## cos_td_rad 1 2104.2
## sin_td_rad 1 2101.7
## settlements:subunit 2 2111.5## Single term deletions
##
## Model:
## richness ~ settlements * subunit + cos_td_rad + (1 | site)
## npar AIC
## <none> 2101.7
## cos_td_rad 1 2104.3
## settlements:subunit 2 2110.7interaction between settlements and subunit and cosin time of year remain. Final model:
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: poisson ( log )
## Formula: richness ~ settlements * subunit + cos_td_rad + (1 | site)
## Data: P.anal
##
## AIC BIC logLik deviance df.resid
## 2101.7 2134.5 -1042.8 2085.7 436
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1155 -0.5630 -0.1001 0.5738 2.8331
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.009577 0.09786
## Number of obs: 444, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.74469 0.07847 22.235 < 2e-16 ***
## settlementsNear 0.49234 0.05821 8.457 < 2e-16 ***
## subunitCarmel 0.11583 0.08860 1.307 0.191087
## subunitGalilee -0.03090 0.08899 -0.347 0.728371
## cos_td_rad 0.13438 0.06304 2.132 0.033044 *
## settlementsNear:subunitCarmel -0.06394 0.08073 -0.792 0.428348
## settlementsNear:subunitGalilee -0.29965 0.08646 -3.466 0.000529 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) sttlmN sbntCr sbntGl cs_td_ sttN:C
## settlmntsNr -0.461
## subunitCrml -0.592 0.408
## subunitGall -0.574 0.406 0.510
## cos_td_rad -0.589 0.002 0.023 -0.003
## sttlmntsN:C 0.336 -0.721 -0.560 -0.293 -0.007
## sttlmntsN:G 0.309 -0.673 -0.275 -0.556 0.001 0.486## $site
## (Intercept)
## Abirim -0.0712010618
## Aderet 0.0692034068
## Beit Oren -0.0306912904
## Ein Yaakov -0.0275697924
## Givat Yearim -0.0780986284
## Givat Yeshayahu 0.0913882764
## Goren -0.0094058403
## Iftach 0.1721905729
## Kerem Maharal 0.0989051815
## Kfar Shamai -0.0568288787
## Margaliot -0.0007220954
## Nehusha -0.0449114084
## Nir Etzion -0.1502032886
## Ofer 0.0846473912
## Ramat Raziel -0.0326109561
## Yagur 0.0021714675
##
## with conditional variances for "site"## $site
attempt to add year, see if significant:
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: poisson ( log )
## Formula: richness ~ year_ct + settlements * subunit + cos_td_rad + (1 |
## site)
## Data: P.anal
##
## AIC BIC logLik deviance df.resid
## 2103.7 2140.5 -1042.8 2085.7 435
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.12097 -0.56506 -0.09097 0.56724 2.83015
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.009533 0.09763
## Number of obs: 444, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.754542 0.100773 17.411 < 2e-16 ***
## year_ct -0.001018 0.006546 -0.156 0.876403
## settlementsNear 0.492325 0.058214 8.457 < 2e-16 ***
## subunitCarmel 0.115576 0.088509 1.306 0.191619
## subunitGalilee -0.031028 0.088896 -0.349 0.727059
## cos_td_rad 0.127539 0.076860 1.659 0.097042 .
## settlementsNear:subunitCarmel -0.063902 0.080727 -0.792 0.428603
## settlementsNear:subunitGalilee -0.299741 0.086459 -3.467 0.000527 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) yer_ct sttlmN sbntCr sbntGl cs_td_ sttN:C
## year_ct -0.628
## settlmntsNr -0.360 0.001
## subunitCrml -0.471 0.018 0.408
## subunitGall -0.452 0.009 0.406 0.510
## cos_td_rad -0.735 0.573 0.002 0.028 0.003
## sttlmntsN:C 0.263 -0.002 -0.721 -0.561 -0.293 -0.007
## sttlmntsN:G 0.237 0.007 -0.673 -0.275 -0.556 0.005 0.486year not significant, rightfully dropped. center time of year variable, highly correlated with intercept.
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: poisson ( log )
## Formula: richness ~ settlements * subunit + cos_td_rad_c + (1 | site)
## Data: P.anal
##
## AIC BIC logLik deviance df.resid
## 2101.7 2134.5 -1042.8 2085.7 436
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1155 -0.5630 -0.1001 0.5738 2.8331
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.009577 0.09786
## Number of obs: 444, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.84006 0.06344 29.005 < 2e-16 ***
## settlementsNear 0.49234 0.05821 8.457 < 2e-16 ***
## subunitCarmel 0.11583 0.08860 1.307 0.191096
## subunitGalilee -0.03090 0.08899 -0.347 0.728431
## cos_td_rad_c 0.13438 0.06304 2.132 0.033036 *
## settlementsNear:subunitCarmel -0.06393 0.08073 -0.792 0.428392
## settlementsNear:subunitGalilee -0.29966 0.08646 -3.466 0.000528 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) sttlmN sbntCr sbntGl cs_t__ sttN:C
## settlmntsNr -0.570
## subunitCrml -0.716 0.408
## subunitGall -0.712 0.406 0.510
## cos_td_rd_c -0.023 0.002 0.023 -0.003
## sttlmntsN:C 0.411 -0.721 -0.560 -0.293 -0.007
## sttlmntsN:G 0.383 -0.673 -0.275 -0.556 0.001 0.486## Registered S3 methods overwritten by 'broom':
## method from
## tidy.glht jtools
## tidy.summary.glht jtools| Observations | 444 |
| Dependent variable | richness |
| Type | Mixed effects generalized linear model |
| Family | poisson |
| Link | log |
| AIC | 2101.699 |
| BIC | 2134.465 |
| Pseudo-R² (fixed effects) | 0.291 |
| Pseudo-R² (total) | 0.344 |
| exp(Est.) | S.E. | z val. | p | |
|---|---|---|---|---|
| (Intercept) | 6.297 | 0.063 | 29.005 | 0.000 |
| settlementsNear | 1.636 | 0.058 | 8.457 | 0.000 |
| subunitCarmel | 1.123 | 0.089 | 1.307 | 0.191 |
| subunitGalilee | 0.970 | 0.089 | -0.347 | 0.728 |
| cos_td_rad_c | 1.144 | 0.063 | 2.132 | 0.033 |
| settlementsNear:subunitCarmel | 0.938 | 0.081 | -0.792 | 0.428 |
| settlementsNear:subunitGalilee | 0.741 | 0.086 | -3.466 | 0.001 |
| Group | Parameter | Std. Dev. |
|---|---|---|
| site | (Intercept) | 0.098 |
| Group | # groups | ICC |
|---|---|---|
| site | 16 | 0.009 |
## Loading required package: Cairo## Loading required package: extrafont## Registering fonts with R## Scale for x is already present.
## Adding another scale for x, which will replace the existing scale.
Test for average differences among levels (average across levels of interaction)
## subunit settlements emmean SE df asymp.LCL asymp.UCL
## Judean Highlands Far 1.84 0.0634 Inf 1.72 1.96
## Carmel Far 1.96 0.0619 Inf 1.83 2.08
## Galilee Far 1.81 0.0625 Inf 1.69 1.93
## Judean Highlands Near 2.33 0.0566 Inf 2.22 2.44
## Carmel Near 2.38 0.0561 Inf 2.27 2.49
## Galilee Near 2.00 0.0604 Inf 1.88 2.12
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95## contrast estimate SE df z.ratio p.value
## far_minus_near -0.3711 0.0343 Inf -10.813 <.0001
## carmel_minus_galilee 0.2646 0.0738 Inf 3.583 0.0003
## carmel_minus_judea 0.0839 0.0740 Inf 1.134 0.2569
## judea_minus_galilee 0.1807 0.0743 Inf 2.434 0.0149
##
## Results are given on the log (not the response) scale.## subunit settlements c.1 c.2 c.3 c.4
## 1 Judean Highlands Far 0.3333333 0.0 -0.5 0.5
## 2 Carmel Far 0.3333333 0.5 0.5 0.0
## 3 Galilee Far 0.3333333 -0.5 0.0 -0.5
## 4 Judean Highlands Near -0.3333333 0.0 -0.5 0.5
## 5 Carmel Near -0.3333333 0.5 0.5 0.0
## 6 Galilee Near -0.3333333 -0.5 0.0 -0.5Test for differences among levels of interaction
## contrast subunit estimate SE df z.ratio p.value
## Far - Near Judean Highlands -0.492 0.0582 Inf -8.457 <.0001
## Far - Near Carmel -0.428 0.0559 Inf -7.660 <.0001
## Far - Near Galilee -0.193 0.0639 Inf -3.014 0.0026
##
## Results are given on the log (not the response) scale.
## P value adjustment: fdr method for 3 tests## contrast settlements estimate SE df z.ratio p.value
## Judean Highlands - Carmel Far -0.1158 0.0886 Inf -1.307 0.2866
## Judean Highlands - Galilee Far 0.0309 0.0890 Inf 0.347 0.7284
## Carmel - Galilee Far 0.1467 0.0879 Inf 1.669 0.1901
## Judean Highlands - Carmel Near -0.0519 0.0797 Inf -0.651 0.6179
## Judean Highlands - Galilee Near 0.3306 0.0827 Inf 3.995 0.0002
## Carmel - Galilee Near 0.3824 0.0824 Inf 4.642 <.0001
##
## Results are given on the log (not the response) scale.
## P value adjustment: fdr method for 6 tests## [1] "% difference in near plots compared to far plots"## [1] "Judea"## [1] 63.61434## [1] "Galilee"## [1] 21.25019## [1] "Carmel"## [1] 53.48161## [1] "% difference between pairs of subunits NEAR settlements"## [1] "How high is Judea compared to Galilee?"## [1] 39.17383## [1] "How high is Carmel compared to Galilee?"## [1] 46.58696statistically significant lower richness in Galilee (but only far from settlements, near there is no significant difference) and far from settlements. No significant change in richness over time.
geometric mean of abundance
Explore data. Exclude time of day because of high number of NAs.
## [1] "GEOMETRIC MEAN ABUNDANCE WITHOUT RARE SPECIES"## Warning: Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Warning: Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
## Removed 1 row containing non-finite outside the scale range (`stat_boxplot()`).
| gma | year_ct | site | settlements | subunit | td_sc | cos_td_rad | sin_td_rad | |
|---|---|---|---|---|---|---|---|---|
| Min. : 1.000 | Min. :0.0 | Nir Etzion : 31 | Far :224 | Judean Highlands:150 | Min. :-1.9882 | Min. :-0.1671 | Min. :-1.0000 | |
| 1st Qu.: 2.074 | 1st Qu.:3.0 | Aderet : 30 | Near:220 | Carmel :149 | 1st Qu.:-0.2713 | 1st Qu.: 0.5702 | 1st Qu.:-0.8215 | |
| Median : 2.551 | Median :5.0 | Ein Yaakov : 30 | NA | Galilee :145 | Median : 0.4918 | Median : 0.8140 | Median :-0.5808 | |
| Mean : 2.784 | Mean :4.8 | Givat Yearim : 30 | NA | NA | Mean : 0.3205 | Mean : 0.7098 | Mean :-0.5864 | |
| 3rd Qu.: 3.248 | 3rd Qu.:7.0 | Givat Yeshayahu: 30 | NA | NA | 3rd Qu.: 1.1023 | 3rd Qu.: 0.9413 | 3rd Qu.:-0.3375 | |
| Max. :10.198 | Max. :9.0 | Goren : 30 | NA | NA | Max. : 1.7127 | Max. : 0.9976 | Max. :-0.0688 | |
| NA’s :1 | NA | (Other) :263 | NA | NA | NA | NA | NA |
Fit glm, compare gamma, gaussian (poisson inappropriate because response is not discrete)
Remove rows 211, 376, 408. Fit fixed and mixed models.
Mixed model converged
## Linear mixed model fit by REML ['lmerMod']
## Formula:
## gma ~ settlements * year_ct + subunit * year_ct + subunit * settlements +
## cos_td_rad + sin_td_rad + (1 | site)
## Data: P.anal
##
## REML criterion at convergence: 1257.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.2020 -0.6098 -0.1523 0.4633 6.1670
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.07522 0.2743
## Residual 0.93017 0.9645
## Number of obs: 440, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 0.80790 0.60095 1.344
## settlementsNear 0.31145 0.21210 1.468
## year_ct 0.02351 0.03046 0.772
## subunitCarmel 0.47934 0.29453 1.627
## subunitGalilee -0.03374 0.29511 -0.114
## cos_td_rad 1.22687 0.41128 2.983
## sin_td_rad -1.51981 0.49821 -3.051
## settlementsNear:year_ct -0.03415 0.02948 -1.159
## year_ct:subunitCarmel -0.07813 0.03726 -2.097
## year_ct:subunitGalilee -0.02821 0.03884 -0.726
## settlementsNear:subunitCarmel -0.09468 0.22426 -0.422
## settlementsNear:subunitGalilee 0.16530 0.22558 0.733
##
## Correlation of Fixed Effects:
## (Intr) sttlmN yer_ct sbntCr sbntGl cs_td_ sn_td_ sttN:_ yr_c:C
## settlmntsNr -0.182
## year_ct -0.212 0.322
## subunitCrml -0.362 0.202 0.315
## subunitGall -0.399 0.202 0.303 0.518
## cos_td_rad -0.916 0.006 0.040 0.114 0.147
## sin_td_rad 0.878 -0.007 0.108 -0.155 -0.205 -0.862
## sttlmntsN:_ 0.123 -0.667 -0.484 -0.005 -0.004 -0.006 0.006
## yr_ct:sbntC 0.336 -0.006 -0.509 -0.604 -0.337 -0.176 0.262 0.007
## yr_ct:sbntG 0.371 -0.005 -0.479 -0.318 -0.621 -0.215 0.309 0.005 0.530
## sttlmntsN:C 0.091 -0.527 -0.003 -0.379 -0.186 0.000 -0.004 0.002 0.001
## sttlmntsN:G 0.099 -0.523 0.001 -0.188 -0.378 -0.007 0.010 0.001 0.003
## yr_c:G sttN:C
## settlmntsNr
## year_ct
## subunitCrml
## subunitGall
## cos_td_rad
## sin_td_rad
## sttlmntsN:_
## yr_ct:sbntC
## yr_ct:sbntG
## sttlmntsN:C -0.002
## sttlmntsN:G 0.003 0.494perform stepwise model selection of gaussian model.
## Single term deletions
##
## Model:
## gma ~ settlements * year_ct + subunit * year_ct + subunit * settlements +
## cos_td_rad + sin_td_rad + (1 | site)
## npar AIC
## <none> 1250.8
## cos_td_rad 1 1257.8
## sin_td_rad 1 1258.4
## settlements:year_ct 1 1250.2
## year_ct:subunit 2 1251.6
## settlements:subunit 2 1248.2drop subunit X year
## Single term deletions
##
## Model:
## gma ~ settlements * year_ct + subunit * settlements + cos_td_rad +
## sin_td_rad + (1 | site)
## npar AIC
## <none> 1251.6
## cos_td_rad 1 1257.2
## sin_td_rad 1 1257.3
## settlements:year_ct 1 1250.9
## settlements:subunit 2 1248.9drop subunit X settlements
## Single term deletions
##
## Model:
## gma ~ settlements * year_ct + subunit + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 1248.9
## subunit 2 1245.6
## cos_td_rad 1 1254.5
## sin_td_rad 1 1254.8
## settlements:year_ct 1 1248.2drop subunit
## Single term deletions
##
## Model:
## gma ~ settlements * year_ct + cos_td_rad + sin_td_rad + (1 |
## site)
## npar AIC
## <none> 1245.6
## cos_td_rad 1 1251.2
## sin_td_rad 1 1251.4
## settlements:year_ct 1 1244.9drop settlements X year
## Single term deletions
##
## Model:
## gma ~ settlements + year_ct + cos_td_rad + sin_td_rad + (1 |
## site)
## npar AIC
## <none> 1244.9
## settlements 1 1246.3
## year_ct 1 1244.2
## cos_td_rad 1 1250.5
## sin_td_rad 1 1250.7drop year
## Single term deletions
##
## Model:
## gma ~ settlements + sin_td_rad + cos_td_rad + (1 | site)
## npar AIC
## <none> 1244.2
## settlements 1 1245.6
## sin_td_rad 1 1248.7
## cos_td_rad 1 1249.1drop settlements
## Single term deletions
##
## Model:
## gma ~ sin_td_rad + cos_td_rad + (1 | site)
## npar AIC
## <none> 1245.6
## sin_td_rad 1 1250.1
## cos_td_rad 1 1250.5only time of year remains in the model.
This is the final model:
## Linear mixed model fit by REML ['lmerMod']
## Formula: gma ~ sin_td_rad + cos_td_rad + (1 | site)
## Data: P.anal
##
## REML criterion at convergence: 1240.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.0507 -0.6108 -0.1965 0.4386 6.3048
##
## Random effects:
## Groups Name Variance Std.Dev.
## site (Intercept) 0.06728 0.2594
## Residual 0.94009 0.9696
## Number of obs: 440, groups: site, 16
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 1.3783 0.5200 2.650
## sin_td_rad -1.0643 0.4181 -2.545
## cos_td_rad 1.0433 0.3981 2.621
##
## Correlation of Fixed Effects:
## (Intr) sn_td_
## sin_td_rad 0.960
## cos_td_rad -0.968 -0.904
abundance
Explore data
## [1] "ABUNDANCE WITHOUT RARE SPECIES"
| abundance | year_ct | site | settlements | subunit | td_sc | cos_td_rad | sin_td_rad | |
|---|---|---|---|---|---|---|---|---|
| Min. : 0.00 | Min. :0.0 | Nir Etzion : 31 | Far :224 | Judean Highlands:150 | Min. :-1.9882 | Min. :-0.1671 | Min. :-1.0000 | |
| 1st Qu.: 15.75 | 1st Qu.:3.0 | Aderet : 30 | Near:220 | Carmel :149 | 1st Qu.:-0.2713 | 1st Qu.: 0.5702 | 1st Qu.:-0.8215 | |
| Median : 24.00 | Median :5.0 | Ein Yaakov : 30 | NA | Galilee :145 | Median : 0.4918 | Median : 0.8140 | Median :-0.5808 | |
| Mean : 29.17 | Mean :4.8 | Givat Yearim : 30 | NA | NA | Mean : 0.3205 | Mean : 0.7098 | Mean :-0.5864 | |
| 3rd Qu.: 36.00 | 3rd Qu.:7.0 | Givat Yeshayahu: 30 | NA | NA | 3rd Qu.: 1.1023 | 3rd Qu.: 0.9413 | 3rd Qu.:-0.3375 | |
| Max. :221.00 | Max. :9.0 | Goren : 30 | NA | NA | Max. : 1.7127 | Max. : 0.9976 | Max. :-0.0688 | |
| NA | NA | (Other) :263 | NA | NA | NA | NA | NA |
Some outliers with total abundance >100. Examine:
## subunit point_name datetime monitors_name
## 1: Judean Highlands Givat Yeshayahu Far 2 2017-04-20 10:20:00 Eran Banker
## 2: Judean Highlands Givat Yeshayahu Near 1 2017-04-20 06:25:00 Eran Banker
## 3: Judean Highlands Givat Yeshayahu Near 2 2017-04-20 06:50:00 Eran Banker
## 4: Judean Highlands Givat Yeshayahu Near 3 2017-04-20 07:15:00 Eran Banker
## 5: Judean Highlands Aderet Near 2 2019-05-26 06:52:00 Eran Banker
## 6: Carmel Beit Oren Near 3 2019-04-19 07:35:00 Other
## 7: Carmel Kerem Maharal Near 3 2021-04-17 07:41:00 Eliraz Dvir
## richness gma abundance
## 1: 11 5.356635 115
## 2: 13 9.170560 140
## 3: 14 7.652753 138
## 4: 16 9.098580 221
## 5: 15 5.408017 106
## 6: 10 4.471017 113
## 7: 11 4.385841 117Exclude 3 plots with high abundance (>150) to improve model fit.
PHI>1, hence choose negative binomial. Fit fixed and mixed models. Choose mixed model if possible, otherwise choose a model with fixed-effects only.
## [1] 3624.382## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00203414 (tol = 0.002, component 1)## [1] 3613.598mixed model converged, slightly better AIC. Perform stepwise model selection of mixed model.
## Single term deletions
##
## Model:
## abundance ~ settlements * year_ct + subunit * year_ct + subunit *
## settlements + cos_td_rad + sin_td_rad + (1 | site)
## npar AIC
## <none> 3613.6
## cos_td_rad 1 3631.7
## sin_td_rad 1 3630.9
## settlements:year_ct 1 3612.0
## year_ct:subunit 2 3613.5
## settlements:subunit 2 3613.0drop subunit X year
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.0033134 (tol = 0.002, component 1)## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.00417349 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## abundance ~ settlements * year_ct + subunit * settlements + cos_td_rad +
## sin_td_rad + (1 | site)
## npar AIC
## <none> 3613.5
## cos_td_rad 1 3628.7
## sin_td_rad 1 3627.3
## settlements:year_ct 1 3612.0
## settlements:subunit 2 3612.7drop settlements X year
## Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
## Model failed to converge with max|grad| = 0.0036899 (tol = 0.002, component 1)## Single term deletions
##
## Model:
## abundance ~ year_ct + subunit * settlements + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 3612.0
## year_ct 1 3611.3
## cos_td_rad 1 3627.2
## sin_td_rad 1 3625.8
## subunit:settlements 2 3611.1drop year
## Single term deletions
##
## Model:
## abundance ~ subunit * settlements + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 3611.3
## cos_td_rad 1 3625.5
## sin_td_rad 1 3624.5
## subunit:settlements 2 3610.5drop settlements X subunit
## Single term deletions
##
## Model:
## abundance ~ subunit + settlements + cos_td_rad + sin_td_rad +
## (1 | site)
## npar AIC
## <none> 3610.5
## subunit 2 3613.4
## settlements 1 3707.3
## cos_td_rad 1 3624.8
## sin_td_rad 1 3623.8Subunit, settlement and time of year remain, same as no interaction analysis.
community analysis using package MVabund
## Overlapping points were shifted along the y-axis to make them visible.##
## PIPING TO 2nd MVFACTOR## Only the variables Curruca.melanocephala, Turdus.merula, Streptopelia.decaocto, Passer.domesticus, Pycnonotus.xanthopygos, Parus.major, Columba.livia, Cinnyris.osea, Spilopelia.senegalensis, Garrulus.glandarius, Cecropis.daurica, Prinia.gracilis were included in the plot
## (the variables with highest total abundance).
## Overlapping points were shifted along the y-axis to make them visible.##
## PIPING TO 2nd MVFACTOR## Only the variables Curruca.melanocephala, Turdus.merula, Streptopelia.decaocto, Passer.domesticus, Pycnonotus.xanthopygos, Parus.major, Columba.livia, Cinnyris.osea, Spilopelia.senegalensis, Garrulus.glandarius, Cecropis.daurica, Prinia.gracilis were included in the plot
## (the variables with highest total abundance).
There are few observations with counts of >60. Examine these:
## point_name datetime SciName monitors_name
## 1: Givat Yeshayahu Near 3 2017-04-20 07:15:00 Passer domesticus Eran Banker
## 2: Ein Yaakov Near 31 2019-04-05 10:27:00 Passer domesticus Sassi Hahamstart model specification:
## nb po
## 974.5374 1331.7987## [1] "POISSON"
## [1] "NEGATIVE BINOMIAL"
negative binomial model is better than poisson according to residuals and AIC comparison.
## nb po nb1
## 974.5374 1331.7987 961.7814The addition of the explanatory variable ‘site’ is somewhat improving the AIC of the model. Prefer to exclude site, for simplification. stepwise selection of model:
## Single term deletions
##
## Model:
## spp_no_rare ~ settlements * year_ct + subunit * year_ct + subunit *
## settlements + cos_td_rad + sin_td_rad
## Df AIC
## <none> 23389
## cos_td_rad 24 23450
## sin_td_rad 24 23466
## settlements:year_ct 24 23361
## year_ct:subunit 48 23407
## settlements:subunit 48 23407drop settlements X year.
## Single term deletions
##
## Model:
## spp_no_rare ~ subunit * year_ct + subunit * settlements + cos_td_rad +
## sin_td_rad
## Df AIC
## <none> 23361
## cos_td_rad 24 23424
## sin_td_rad 24 23441
## subunit:year_ct 48 23386
## subunit:settlements 48 23381final model includes subunit x settlements, subunit x year_ct and sampling time of year.
##
## Test statistics:
## wald value Pr(>wald)
## (Intercept) 12.235 0.001 ***
## subunitCarmel 8.583 0.001 ***
## subunitGalilee 6.824 0.009 **
## year_ct 6.652 0.031 *
## settlementsNear 18.506 0.001 ***
## cos_td_rad 10.732 0.001 ***
## sin_td_rad 11.647 0.001 ***
## subunitCarmel:year_ct 7.692 0.002 **
## subunitGalilee:year_ct 7.597 0.006 **
## subunitCarmel:settlementsNear 4.319 0.662
## subunitGalilee:settlementsNear 7.458 0.001 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Test statistic: 39.56, p-value: 0.001
## Arguments:
## Test statistics calculated assuming response assumed to be uncorrelated
## P-value calculated using 999 resampling iterations via pit.trap resampling (to account for correlation in testing).## Analysis of Deviance Table
##
## Model: spp_no_rare ~ subunit * year_ct + subunit * settlements + cos_td_rad + sin_td_rad
##
## Multivariate test:
## Res.Df Df.diff Dev Pr(>Dev)
## (Intercept) 443
## subunit 441 2 401.0 0.01 **
## year_ct 440 1 117.0 0.01 **
## settlements 439 1 824.6 0.01 **
## cos_td_rad 438 1 47.5 0.04 *
## sin_td_rad 437 1 110.6 0.01 **
## subunit:year_ct 435 2 128.5 0.01 **
## subunit:settlements 433 2 104.7 0.02 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Univariate Tests:
## Acridotheres.tristis Alectoris.chukar
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 44.029 0.01 9.54 0.09
## year_ct 24.181 0.01 12.413 0.01
## settlements 80.478 0.01 36.319 0.01
## cos_td_rad 3.002 0.83 2.276 0.94
## sin_td_rad 5.64 0.30 0.596 1.00
## subunit:year_ct 8.217 0.41 2.436 0.98
## subunit:settlements 12.215 0.12 0.135 1.00
## Cinnyris.osea Columba.livia
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 18.184 0.01 9.081 0.10
## year_ct 4.452 0.41 4.349 0.41
## settlements 41.118 0.01 34.481 0.01
## cos_td_rad 1.651 0.97 0.274 1.00
## sin_td_rad 2.01 0.90 11.357 0.04
## subunit:year_ct 12.677 0.18 7.643 0.48
## subunit:settlements 0.91 1.00 7.796 0.48
## Curruca.curruca Falco.tinnunculus
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 27.998 0.01 8.726 0.11
## year_ct 14.071 0.01 0.424 0.98
## settlements 2.443 0.66 2.364 0.66
## cos_td_rad 7.887 0.16 0.078 1.00
## sin_td_rad 5.831 0.30 0.641 1.00
## subunit:year_ct 0.009 0.99 5.248 0.73
## subunit:settlements 0.463 1.00 0.526 1.00
## Passer.domesticus Prinia.gracilis
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 18.116 0.01 1.649 0.67
## year_ct 0.957 0.96 10.434 0.03
## settlements 170.553 0.01 54.604 0.01
## cos_td_rad 0.485 1.00 0.633 1.00
## sin_td_rad 2.962 0.71 1.004 0.98
## subunit:year_ct 2.283 0.98 13.996 0.11
## subunit:settlements 4.667 0.81 7.053 0.53
## Pycnonotus.xanthopygos Spilopelia.senegalensis
## Dev Pr(>Dev) Dev
## (Intercept)
## subunit 22.998 0.01 20.899
## year_ct 4.112 0.44 2.986
## settlements 46.389 0.01 162.398
## cos_td_rad 11.394 0.01 0.333
## sin_td_rad 0.499 1.00 0.603
## subunit:year_ct 3.75 0.82 4.692
## subunit:settlements 2.425 1.00 0.038
## Streptopelia.decaocto Streptopelia.turtur
## Pr(>Dev) Dev Pr(>Dev) Dev
## (Intercept)
## subunit 0.01 12.15 0.06 6.199
## year_ct 0.67 0.079 0.98 18.03
## settlements 0.01 1.962 0.66 1.6
## cos_td_rad 1.00 6.672 0.30 3.045
## sin_td_rad 1.00 14.008 0.04 1.847
## subunit:year_ct 0.73 1.683 0.98 1.887
## subunit:settlements 1.00 7.741 0.48 2.078
## Carduelis.carduelis Cecropis.daurica
## Pr(>Dev) Dev Pr(>Dev) Dev
## (Intercept)
## subunit 0.22 18.526 0.01 0.804
## year_ct 0.01 7.364 0.09 0.498
## settlements 0.66 9.786 0.03 34.435
## cos_td_rad 0.83 0.389 1.00 0.127
## sin_td_rad 0.92 1.61 0.92 3.044
## subunit:year_ct 0.98 12.307 0.20 0.41
## subunit:settlements 1.00 0.982 1.00 0.481
## Chloris.chloris Corvus.cornix
## Pr(>Dev) Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 0.68 9.599 0.09 34.187 0.01
## year_ct 0.98 1.13 0.96 0.269 0.98
## settlements 0.01 24.155 0.01 36.648 0.01
## cos_td_rad 1.00 0.224 1.00 1.013 1.00
## sin_td_rad 0.71 0.465 1.00 0.157 1.00
## subunit:year_ct 0.99 6.6 0.59 7.109 0.52
## subunit:settlements 1.00 0.45 1.00 21.928 0.01
## Corvus.monedula Curruca.melanocephala
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 23.137 0.01 38.349 0.01
## year_ct 0.306 0.98 0.745 0.97
## settlements 0.001 0.98 23.96 0.01
## cos_td_rad 0.184 1.00 0.3 1.00
## sin_td_rad 0.053 1.00 0.429 1.00
## subunit:year_ct 5.316 0.73 9.877 0.31
## subunit:settlements 9.568 0.27 0.509 1.00
## Dendrocopos.syriacus Garrulus.glandarius
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 3.624 0.51 26.547 0.01
## year_ct 0.002 0.98 4.65 0.41
## settlements 9.308 0.04 2.277 0.66
## cos_td_rad 1.417 1.00 1.146 1.00
## sin_td_rad 3.35 0.68 1.103 0.98
## subunit:year_ct 0.232 0.99 5.025 0.73
## subunit:settlements 5.453 0.71 8.802 0.35
## Parus.major Psittacula.krameri
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 26.708 0.01 12.826 0.04
## year_ct 0.357 0.98 1.303 0.96
## settlements 2.626 0.63 16.939 0.01
## cos_td_rad 3.376 0.81 0.793 1.00
## sin_td_rad 7.701 0.14 1.724 0.92
## subunit:year_ct 6.652 0.59 3.863 0.82
## subunit:settlements 4.806 0.80 0.813 1.00
## Troglodytes.troglodytes Turdus.merula
## Dev Pr(>Dev) Dev Pr(>Dev)
## (Intercept)
## subunit 4.791 0.42 2.302 0.67
## year_ct 0.88 0.96 2.975 0.67
## settlements 25.789 0.01 3.928 0.43
## cos_td_rad 0.48 1.00 0.347 1.00
## sin_td_rad 10.786 0.04 33.19 0.01
## subunit:year_ct 5.003 0.73 1.539 0.98
## subunit:settlements 2.959 0.98 1.928 1.00
## Arguments:
## Test statistics calculated assuming uncorrelated response (for faster computation)
## P-value calculated using 99 iterations via PIT-trap resampling.Interactions are significant only for one species: subunit X settlements: corvus cornix Therefore present only the analysis EXCLUDING subunit interactions with time / settlements
Chloris chloris
## (Intercept) subunitCarmel
## -0.98854683 -2.84322186
## subunitGalilee year_ct
## 0.25112325 0.05961992
## settlementsNear cos_td_rad
## 1.12688435 0.06354635
## sin_td_rad subunitCarmel:year_ct
## 0.17488417 0.14192611
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.10230269 1.19071202
## subunitGalilee:settlementsNear
## -0.01474921## (Intercept) subunitCarmel
## -0.98857852 -2.84323774
## subunitGalilee year_ct
## 0.25112269 0.05962000
## settlementsNear cos_td_rad
## 1.12688407 0.06357472
## sin_td_rad subunitCarmel:year_ct
## 0.17486723 0.14192861
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.10230239 1.19072193
## subunitGalilee:settlementsNear
## -0.01474811
## subunit year_ct.trend SE df asymp.LCL asymp.UCL
## Judean Highlands 0.0596 0.0621 Inf -0.0621 0.181
## Carmel 0.2015 0.0939 Inf 0.0176 0.386
## Galilee -0.0427 0.0784 Inf -0.1963 0.111
##
## Results are averaged over the levels of: settlements
## Confidence level used: 0.95## subunit year_ct.trend SE df z.ratio p.value
## Judean Highlands 0.0596 0.0621 Inf 0.960 0.5056
## Carmel 0.2015 0.0939 Inf 2.147 0.0953
## Galilee -0.0427 0.0784 Inf -0.544 0.5862
##
## Results are averaged over the levels of: settlements
## P value adjustment: fdr method for 3 testsPrinia gracilis
## (Intercept) subunitCarmel
## -2.27638999 1.39999441
## subunitGalilee year_ct
## 1.94591752 0.01456515
## settlementsNear cos_td_rad
## 2.39729256 0.26879856
## sin_td_rad subunitCarmel:year_ct
## 0.01699282 -0.07065450
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.25340672 -1.02832055
## subunitGalilee:settlementsNear
## -1.32949290## (Intercept) subunitCarmel
## -2.27639017 1.39999457
## subunitGalilee year_ct
## 1.94592061 0.01456519
## settlementsNear cos_td_rad
## 2.39729278 0.26879854
## sin_td_rad subunitCarmel:year_ct
## 0.01699292 -0.07065456
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.25340722 -1.02832035
## subunitGalilee:settlementsNear
## -1.32949444
## [1] 0.4987867 0.4962499 0.4937259 0.4912148 0.4887165 0.4862308 0.4837578
## [8] 0.4812974 0.4788495 0.4764141 0.4739910 0.4715802 0.4691818 0.4667955
## [15] 0.4644213 0.4620593 0.4597092 0.4573711 0.4550449 0.4527305 0.4504279
## [22] 0.4481370 0.4458577 0.4435901 0.4413339 0.4390893 0.4368561 0.4346342
## [29] 0.4324236 0.4302243 0.4280361 0.4258591 0.4236932 0.4215383 0.4193943
## [36] 0.4172612 0.4151390 0.4130276 0.4109269 0.4088369 0.4067575 0.4046888
## [43] 0.4026305 0.4005827 0.3985453 0.3965183 0.3945016 0.3924951 0.3904989
## [50] 0.3885128 0.3865368 0.3845708 0.3826149 0.3806689 0.3787328 0.3768065
## [57] 0.3748900 0.3729833 0.3710863 0.3691990 0.3673212 0.3654530 0.3635943
## [64] 0.3617450 0.3599051 0.3580746 0.3562535 0.3544415 0.3526388 0.3508453
## [71] 0.3490609 0.3472855 0.3455192 0.3437619 0.3420135 0.3402740 0.3385433
## [78] 0.3368215 0.3351084 0.3334040 0.3317083 0.3300212 0.3283427 0.3266727
## [85] 0.3250113 0.3233582 0.3217136 0.3200774 0.3184494 0.3168298 0.3152184
## [92] 0.3136151 0.3120201 0.3104331 0.3088543 0.3072834 0.3057205 0.3041656
## [99] 0.3026186 0.3010795## [1] 0.4063373## [1] 0.3963763## [1] 0.8834667## [1] 0.1400667## subunit year_ct.trend SE df asymp.LCL asymp.UCL
## Judean Highlands 0.0146 0.0537 Inf -0.0907 0.1198
## Carmel -0.0561 0.0554 Inf -0.1647 0.0525
## Galilee -0.2388 0.0667 Inf -0.3696 -0.1080
##
## Results are averaged over the levels of: settlements
## Confidence level used: 0.95## subunit year_ct.trend SE df z.ratio p.value
## Judean Highlands 0.0146 0.0537 Inf 0.271 0.7863
## Carmel -0.0561 0.0554 Inf -1.012 0.4672
## Galilee -0.2388 0.0667 Inf -3.579 0.0010
##
## Results are averaged over the levels of: settlements
## P value adjustment: fdr method for 3 testsCorvus cornix
## (Intercept) subunitCarmel
## -15.42600623 15.70257517
## subunitGalilee year_ct
## 13.87192863 0.12704637
## settlementsNear cos_td_rad
## 14.23600431 0.18428677
## sin_td_rad subunitCarmel:year_ct
## 0.22966983 -0.22029987
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.07066912 -13.55160365
## subunitGalilee:settlementsNear
## -13.01377130## (Intercept) subunitCarmel
## -33.96111315 34.23769072
## subunitGalilee year_ct
## 32.40704273 0.12705061
## settlementsNear cos_td_rad
## 32.77109998 0.18428119
## sin_td_rad subunitCarmel:year_ct
## 0.22967872 -0.22030413
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.07067299 -32.08669848
## subunitGalilee:settlementsNear
## -31.54886653## [1] 0
## subunit settlements emmean SE df asymp.LCL asymp.UCL
## Judean Highlands Far -33.3552 1.18e+06 Inf -2.32e+06 2320223.5
## Carmel Far -0.1749 2.00e-01 Inf -6.00e-01 0.2
## Galilee Far -1.2874 3.00e-01 Inf -1.80e+00 -0.8
## Judean Highlands Near -0.5841 2.00e-01 Inf -1.00e+00 -0.1
## Carmel Near 0.5095 2.00e-01 Inf 1.00e-01 0.9
## Galilee Near -0.0651 2.00e-01 Inf -5.00e-01 0.3
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95## [1] 1.698947e+16## [1] 100.8524## [1] 239.0577## contrast subunit estimate SE df z.ratio p.value
## Far - Near Judean Highlands -32.771 1.18e+06 Inf 0.000 1.0000
## Far - Near Carmel -0.684 3.00e-01 Inf -2.472 0.0202
## Far - Near Galilee -1.222 3.00e-01 Inf -3.574 0.0011
##
## Results are given on the log (not the response) scale.
## P value adjustment: fdr method for 3 testsSpelopelia senegalensis
## (Intercept) subunitCarmel
## -2.936826311 -0.668286496
## subunitGalilee year_ct
## -0.643406494 -0.015075605
## settlementsNear cos_td_rad
## 2.666033228 0.947865033
## sin_td_rad subunitCarmel:year_ct
## -1.109485319 -0.001706187
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.142228699 0.537009352
## subunitGalilee:settlementsNear
## 0.101942940## (Intercept) subunitCarmel
## -2.936826202 -0.668286790
## subunitGalilee year_ct
## -0.643406357 -0.015075609
## settlementsNear cos_td_rad
## 2.666033250 0.947864791
## sin_td_rad subunitCarmel:year_ct
## -1.109485396 -0.001706132
## subunitGalilee:year_ct subunitCarmel:settlementsNear
## -0.142228723 0.537009592
## subunitGalilee:settlementsNear
## 0.101942904
## subunit settlements emmean SE df asymp.LCL asymp.UCL
## Judean Highlands Far -1.686 0.295 Inf -2.265 -1.107
## Carmel Far -2.362 0.398 Inf -3.143 -1.582
## Galilee Far -3.012 0.522 Inf -4.034 -1.989
## Judean Highlands Near 0.980 0.144 Inf 0.699 1.262
## Carmel Near 0.841 0.146 Inf 0.554 1.127
## Galilee Near -0.244 0.190 Inf -0.617 0.129
##
## Results are given on the log (not the response) scale.
## Confidence level used: 0.95## [1] 1710.159## [1] 1658.419## [1] 1492.675## contrast subunit estimate SE df z.ratio p.value
## Far - Near Judean Highlands -2.67 0.328 Inf -8.125 <.0001
## Far - Near Carmel -3.20 0.424 Inf -7.551 <.0001
## Far - Near Galilee -2.77 0.551 Inf -5.023 <.0001
##
## Results are given on the log (not the response) scale.
## P value adjustment: fdr method for 3 testsSession information
## ─ Session info ───────────────────────────────────────────────────────────────
## setting value
## version R version 4.2.3 (2023-03-15 ucrt)
## os Windows 10 x64 (build 22631)
## system x86_64, mingw32
## ui RTerm
## language (EN)
## collate Hebrew_Israel.utf8
## ctype Hebrew_Israel.utf8
## tz Asia/Jerusalem
## date 2024-04-09
## pandoc 3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
##
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##
## [1] C:/Users/Ron Chen/AppData/Local/R/win-library/4.2.3
## [2] C:/Program Files/R/R-4.2.3/library
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