PROPORTIONAL VEGETATION COVER (= FRACTIONAL COVER): 'fractional_cover' function


The 'fractional_cover' function in the 'auscoverR' package calculates fractional cover from AusPlots point intercept (PI) data (as generated by 'get_ausplots'). Fractional cover refers to the proportions of green vegetation, dead vegetation and bare substrate cover. Cover fractions are assigned as follows: . ‘Green’ or ‘photosynthetic vegetation’: is living vascular plant cover. . ‘Brown’ or ‘non-photosynthetic vegetation’: is either vascular plant cover scored as ‘dead’, or substrate scored as litter, coarse woody debris or cryptogam (see below) that has no other veg cover. . ‘Bare’ or ‘bare ground’: is rock, outcrop, gravel or bare soil with no veg cover substrate.

Typically, 1010 intercept points are used to compute fractional cover in a plot. These 1010 intercept points correspond to 11 points at 1 meters intervals in each of 10 transects of 10 meters of length (5 transects oriented North to South and 5 oriented East to West; see ‘Ecosystem Surveillance Monitoring - AusPlots Methods’). The percentage scored for each fraction is computed as the number of hits assigned to each fraction times 100 divided by the total number of PIs taken (usually 1010, but this number can vary).

A height rule is applied, so that scoring the green/brown/bare fraction from point intercept hits of the uppermost vegetation/substrate stratum overrides the others. That is, a dead tree overrides a living shrub beneath and vice versa. Similarly, any vegetation cover overrides substrate coding, etc. This means for each of the intercepts, there is a single coding.

Arguments:

  • 'ground_fractional': When set to ‘TRUE’ it computes fractional cover exclusively for Ground Cover. That is, fractional cover is computed only for grasses (hummock, tussock, other); sedge; rush; forb; fern; and vine plant growth forms. Presently, cryptogam cover is excluded, and included in the non-photosynthetic fraction instead. The default for this argument is ‘FALSE’.
  • 'in_canopy_sky': With the default value ('in_canopy_sky = FALSE'), only the substrate is considered for those hits. This argument applies only to regular fractional cover (i.e. for 'ground_fractional = FALSE'), as trees are excluded in the green fraction for ground fractional cover by default.

Occasionally, substrate type was not collected (i.e. ‘NC’) or could not be assigned to one of the above categories (i.e. ‘Unknwn’). In these cases, if there was no vegetation cover above those points percent cover is scored as an ‘NA’ fraction.

The 'fractional_cover' function returns a data frame. In this data frame rows denote plots, columns denote fractions (i.e. bare, brown, green, and NA), and values are cover percentages.





EXAMPLES

Examples of the use of the 'fractional_cover' funtion are presented below. In the examples, different flavours of Fractional Cover are computed by varying the argument values (see above). Fractional cover is computed for the full set of vegetation point intersect data currently available at AusPlots, so running these examples might take a little bit of time (between 1.6 and 1.9 minutes per example in my machine). The list of data frames containing information for all currently available AusPlots sites (i.e. the 'AP.data' list) was previously created iusing the 'get_ausplots' function (see the 'Obtaining AusPlots data: 'get_ausplots' function' Step-by-Step Guide; we use the list created in Example 4). The resulting 'Fractional Cover' data frames can be eriched with addional information as seen in the 'Manipulating AusPlots data II: Merging data frames' Step-by-Step Guide.

Boxes with grey background contain code snippets, and boxes with white background containt code (text) outputs.



Example 1: 'Regular' Fractional Cover, only for Substrate

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# ===============================================================================
# PROPORTIONAL VEGETATION COVER (= FRACTIONAL COVER): 'fractional_cover' function
# ===============================================================================

# Fractional Cover: 'Regular' Fractional Cover, only for Substrate
# ================================================================
# I.e.: Function call with the default argument values
AP.data.FC.RFC.Substrate = fractional_cover(AP.data$veg.PI, ground_fractional="FALSE", in_canopy_sky="FALSE")
class(AP.data.FC.RFC.Substrate)

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## [1] "data.frame"

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dim(AP.data.FC.RFC.Substrate)

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## [1] 653   5

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head(AP.data.FC.RFC.Substrate)

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##                       site_unique  bare brown green  NA.
## NSABBS0005-58582 NSABBS0005-58582  1.09 39.60 59.31  0.0
## NSABBS0006-58557 NSABBS0006-58557  3.17 32.67 64.06  0.1
## NSABHC0001-53596 NSABHC0001-53596 31.26 42.24 26.51  0.0
## NSABHC0002-53597 NSABHC0002-53597  0.00  0.00 30.10 69.9
## NSABHC0003-53598 NSABHC0003-53598 46.57 28.14 25.29  0.0
## NSABHC0004-53599 NSABHC0004-53599 26.63 36.63 36.73  0.0

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summary(AP.data.FC.RFC.Substrate)

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##  site_unique             bare           brown           green      
##  Length:653         Min.   : 0.00   Min.   : 0.00   Min.   : 0.10  
##  Class :character   1st Qu.: 9.90   1st Qu.:20.69   1st Qu.:22.99  
##  Mode  :character   Median :22.48   Median :29.91   Median :38.51  
##                     Mean   :27.76   Mean   :30.86   Mean   :41.12  
##                     3rd Qu.:42.38   3rd Qu.:40.00   3rd Qu.:55.74  
##                     Max.   :98.71   Max.   :77.82   Max.   :97.92  
##       NA.         
##  Min.   : 0.0000  
##  1st Qu.: 0.0000  
##  Median : 0.0000  
##  Mean   : 0.2667  
##  3rd Qu.: 0.0000  
##  Max.   :69.9000

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Example 2: 'Regular' Fractional Cover, including Trees 

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# Fractional Cover: 'Regular' Fractional Cover, including Trees
# =============================================================
AP.data.FC.RFC.Trees = fractional_cover(AP.data$veg.PI, ground_fractional="FALSE", in_canopy_sky="TRUE")
#class(AP.data.FC.RFC.Trees)
#dim(AP.data.FC.RFC.Trees)
head(AP.data.FC.RFC.Trees)

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##                       site_unique  bare brown green  NA.
## NSABBS0005-58582 NSABBS0005-58582  1.09 36.53 62.38  0.0
## NSABBS0006-58557 NSABBS0006-58557  2.77 27.33 69.80  0.1
## NSABHC0001-53596 NSABHC0001-53596 31.26 42.24 26.51  0.0
## NSABHC0002-53597 NSABHC0002-53597  0.00  0.00 30.10 69.9
## NSABHC0003-53598 NSABHC0003-53598 46.57 28.14 25.29  0.0
## NSABHC0004-53599 NSABHC0004-53599 26.63 36.63 36.73  0.0

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summary(AP.data.FC.RFC.Trees)

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##  site_unique             bare           brown           green      
##  Length:653         Min.   : 0.00   Min.   : 0.00   Min.   : 0.10  
##  Class :character   1st Qu.: 9.31   1st Qu.:19.22   1st Qu.:25.05  
##  Mode  :character   Median :22.08   Median :28.22   Median :40.89  
##                     Mean   :27.41   Mean   :29.20   Mean   :43.13  
##                     3rd Qu.:41.78   3rd Qu.:38.12   3rd Qu.:59.80  
##                     Max.   :98.71   Max.   :72.67   Max.   :97.92  
##       NA.         
##  Min.   : 0.0000  
##  1st Qu.: 0.0000  
##  Median : 0.0000  
##  Mean   : 0.2634  
##  3rd Qu.: 0.0000  
##  Max.   :69.9000

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Example 3: Fractional Ground Cover

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# Fractional Cover: Fractional Ground Cover
# =========================================
AP.data.FC.RFC.Trees = fractional_cover(AP.data$veg.PI, ground_fractional="TRUE")
#class(AP.data.FC.RFC.Trees)
#dim(AP.data.FC.RFC.Trees)
head(AP.data.FC.RFC.Trees)

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##                       site_unique  bare brown green   NA.
## NSABBS0005-58582 NSABBS0005-58582  1.58 98.42  0.00  0.00
## NSABBS0006-58557 NSABBS0006-58557  5.35 94.36  0.20  0.10
## NSABHC0001-53596 NSABHC0001-53596 33.73 55.98 10.29  0.00
## NSABHC0002-53597 NSABHC0002-53597  0.00  0.00 17.92 82.08
## NSABHC0003-53598 NSABHC0003-53598 54.02 44.12  1.86  0.00
## NSABHC0004-53599 NSABHC0004-53599 28.42 48.81 22.77  0.00

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summary(AP.data.FC.RFC.Trees)

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##  site_unique             bare           brown           green      
##  Length:653         Min.   : 0.00   Min.   : 0.00   Min.   : 0.00  
##  Class :character   1st Qu.:13.86   1st Qu.:33.60   1st Qu.: 3.76  
##  Mode  :character   Median :26.83   Median :49.70   Median :12.18  
##                     Mean   :30.98   Mean   :51.37   Mean   :17.27  
##                     3rd Qu.:46.58   3rd Qu.:70.59   3rd Qu.:25.64  
##                     Max.   :99.60   Max.   :98.42   Max.   :97.92  
##       NA.         
##  Min.   : 0.0000  
##  1st Qu.: 0.0000  
##  Median : 0.0000  
##  Mean   : 0.3838  
##  3rd Qu.: 0.0000  
##  Max.   :82.0800

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