[output published (also) in: http://rpubs.com/scotti/SPA_PinusPinea_Tortoli]

Recovering transects data

## Warning: package 'googlesheets' was built under R version 3.3.3
## Warning: package 'dplyr' was built under R version 3.3.3
## # A tibble: 2 x 10
##             sheet_title author  perm version             updated
##                   <chr>  <chr> <chr>   <chr>              <dttm>
## 1    TransectPinusPinea scotti    rw     old 2017-09-09 11:12:18
## 2 TransectPinusPinea_v2 scotti    rw     old 2016-12-09 10:33:58
## # ... with 5 more variables: sheet_key <chr>, ws_feed <chr>,
## #   alternate <chr>, self <chr>, alt_key <chr>
## Sheet successfully identified: "TransectPinusPinea"
## Sheet ' PointPatternWithMarks '  found.
## Accessing worksheet titled 'PointPatternWithMarks'.
## Parsed with column specification:
## cols(
##   Area = col_character(),
##   IdPoint = col_character(),
##   X = col_double(),
##   Y = col_double(),
##   `H [m]` = col_double(),
##   `N palchi` = col_integer(),
##   AreaInsid = col_double(),
##   Note = col_character(),
##   Note_cod = col_character(),
##   KEY = col_character(),
##   n_el_gruppo = col_integer(),
##   sum_d_coll_sq = col_integer(),
##   n_fusti = col_integer(),
##   sum_d130sq = col_integer()
## )
## Classes 'tbl_df', 'tbl' and 'data.frame':    102 obs. of  15 variables:
##  $ Area         : chr  "3" "3" "3" "3" ...
##  $ IdPoint      : chr  "C1" "C2" "C3" "C4" ...
##  $ X            : num  5.4 14.6 23 26.1 26.8 29.2 26.6 29.2 32.4 33.3 ...
##  $ Y            : num  9.3 4.8 5.5 9.9 4.3 4 4.4 4.4 0.7 4.3 ...
##  $ H [m]        : num  7.5 2.4 6 3.6 3.4 6.7 3.6 3.2 3.3 8 ...
##  $ N palchi     : int  13 8 10 8 7 11 8 9 6 13 ...
##  $ AreaInsid    : num  63.65 4.95 23.01 4.81 2.88 ...
##  $ Note         : chr  NA NA NA NA ...
##  $ Note_cod     : chr  "A" "A" "A" "A" ...
##  $ KEY          : chr  "3C1" "3C2" "3C3" "3C4" ...
##  $ n_el_gruppo  : int  1 1 1 1 1 1 2 1 1 1 ...
##  $ sum_d_coll_sq: int  7396 169 1600 100 49 1600 148 169 36 1444 ...
##  $ n_fusti      : int  3 1 3 1 1 2 2 1 1 2 ...
##  $ sum_d130sq   : int  1785 9 509 49 16 845 49 25 4 1025 ...
##  $ nPf          : Factor w/ 13 levels "2","3","4","5",..: 12 7 9 7 6 10 7 8 5 12 ...
##  - attr(*, "spec")=List of 2
##   ..$ cols   :List of 14
##   .. ..$ Area         : list()
##   .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
##   .. ..$ IdPoint      : list()
##   .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
##   .. ..$ X            : list()
##   .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
##   .. ..$ Y            : list()
##   .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
##   .. ..$ H [m]        : list()
##   .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
##   .. ..$ N palchi     : list()
##   .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
##   .. ..$ AreaInsid    : list()
##   .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
##   .. ..$ Note         : list()
##   .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
##   .. ..$ Note_cod     : list()
##   .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
##   .. ..$ KEY          : list()
##   .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
##   .. ..$ n_el_gruppo  : list()
##   .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
##   .. ..$ sum_d_coll_sq: list()
##   .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
##   .. ..$ n_fusti      : list()
##   .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
##   .. ..$ sum_d130sq   : list()
##   .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
##   ..$ default: list()
##   .. ..- attr(*, "class")= chr  "collector_guess" "collector"
##   ..- attr(*, "class")= chr "col_spec"

Initializing PPP and SO list

Spatial patterns windows are, partially, undefined. The width is fixed to 10m while the length is open and has to be estimated!!

library(spatstat)
## Warning: package 'spatstat' was built under R version 3.3.3
## Loading required package: nlme
## 
## Attaching package: 'nlme'
## The following object is masked from 'package:dplyr':
## 
##     collapse
## Loading required package: rpart
## 
## spatstat 1.52-1       (nickname: 'Apophenia') 
## For an introduction to spatstat, type 'beginner'
## 
## Note: R version 3.3.2 (2016-10-31) is more than 9 months old; we strongly recommend upgrading to the latest version
Areas <- unique(ppwm$Area)
t_windows <- list()
for(tid in Areas) t_windows[[tid]] <- ripras(ppwm$X[ppwm$Area==tid],ppwm$Y[ppwm$Area==tid], shape = "rectangle")
# ripras():  Estimate window from points alone
reduced <- c(1, 2, 3, 4, 6, 5, 7)
ppwm0 <- ppwm
ppwm <- ppwm[, reduced]
names(ppwm)[5:7] <- c("#whorls", "height [m]", "crown [m^2]")
trss <- solist()
# To display transects as seen from the see
#    exchange x and y
#    mirror on the negative side the y ==> K=-1
K <- -1
for(tid in Areas) {
  trs <- ppp(ppwm$Y[ppwm$Area==tid],K*c(ppwm$X[ppwm$Area==tid])
             , yrange = range(K*t_windows[[tid]]$xrange), xrange = c(-10, 10)
             , marks = ppwm[ppwm$Area==tid, c(5:7)])
  unitname(trs) <- "m"
#  print(paste(tid,class(trs)))
  trss[[length(trss)+1]] <- trs
}
names(trss)=paste("Trs-",Areas,sep="")

Transects density distribution analysis

plot(as.solist(lapply(trss, density)), nrows=1, equal.scales=T, valign=T, 
      main = "", hsep=2, cex.main=.7,
      equal.ribbon=TRUE, ribbon = T, ribside="left",
      panel.end=function(i,y,...){contour(y, ...)})
#      par(mar=c(0,0,2,0)), 
#  title(main="Density distribution", line =-1)
Axis(trss, side=4, cex.axis=.6, at=seq(100,20,-20), labels = seq(0,80,20), line = -3)
text(150,70,"distance [m]", srt = 90)

Correlations among marks

library("PerformanceAnalytics", lib.loc="~/R/win-library/3.3")
## Loading required package: xts
## Loading required package: zoo
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric
## 
## Attaching package: 'xts'
## The following objects are masked from 'package:dplyr':
## 
##     first, last
## 
## Attaching package: 'PerformanceAnalytics'
## The following object is masked from 'package:graphics':
## 
##     legend
ow <- options("warn")[[1]]
options(warn = -1)
for(i in 1:4) chart.Correlation(marks(trss[[i]])
                                , histogram=TRUE, pch=19
                                , main=names(trss)[i])

options(warn = ow)

Distribution of mark values

for(i in 1:length(trss)) {
  tid <- names(trss)[i]
  trs <- trss[[tid]]
  plot(trs, cex.main=1.1, main="", 
       hsep=0, par(mar=c(0,0.5,0,0), cex=.6), mar.panel=c(0,0,0,.9))
  title(main = paste("Marks in",tid), line = -2)
}
## Warning: Interpretation of arguments maxsize and markscale has changed (in
## spatstat version 1.37-0 and later). Size of a circle is now measured by its
## diameter.

#        which.marks = c(9, 1, 3), 
#        main.panel=c("#whorls", "height [m]", "crown [m^2]"),

Analysis of spatial characters

Kl <- as.anylist(lapply(trss, Kest))
for(i in 1:length(Kl)) {
  leg <- plot(Kl[[i]], legend = F, main=names(Kl)[[i]])
  legend("topleft",legend = leg$key, lty=leg$lty, col=leg$col)
}

Analysis of the spatial behaviour of each mark

pmkc <- function(x, m) plot(main=paste(names(trss)[x],":"
                                ,names(trss[[1]]$marks)[m])
                     ,markcorr(setmarks(unmark(trss[[x]])
                                       ,marks(trss[[x]])[[m]])))

for(m in 1:length(marks(trs))) {
  for(i in 1:length(trss)) pmkc(i, m)
}