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The 'species'_table function in the 'ausplotsR' is used to generate a species occurrence matrix from AusPlots raw data. The species occurence matrix can be then used in multiple applications that require species-level data. For example, it can be used to investigate patterns of presence/absence and/or abundance (note that vegetation 'cover' is used as a surrogate for vegetation 'abundace'), compute indices of species diversity, or elaborate rank-abundance plots.

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Examples of the different arguments combinations in the 'species_table' function are presented below. Species occurrence matrices are computed for the full set of vegetation point intersect data currently available at AusPlots. The list of data frames containing information for all currently available AusPlots sites (i.e. the 'AP.data' list) was previously created using 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 class and dimensions of the returned data frame are the same in all examples, so they are only displayed for the first example (the corresponding code is commented out in the other examples). The resulting species occurrence data frames can be enriched with additional information (see 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.

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Example 1. Scoring metric; Presence/Absence ('m_kind = "PA")

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# ===========================================================================
# SPECIES-LEVEL DATA: 'species_table' function and species occurence matrices
# ===========================================================================

# Scoring metric: Presence/Absence
# ================================
AP.data.SppbySites.PA = species_table(AP.data$veg.PI, m_kind="PA")
class(AP.data.SppbySites.PA)

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## [1] "data.frame"

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dim(AP.data.SppbySites.PA) # Number of rows and columns in the matrix: Sites x Species

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## [1]  653 3665

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AP.data.SppbySites.PA[1:5, 1:5]

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##                  Abutilon.fraseri Abutilon.halophilum Abutilon.hannii
## NSABBS0005-58582                0                   0               0
## NSABBS0006-58557                0                   0               0
## NSABHC0001-53596                0                   0               0
## NSABHC0002-53597                0                   0               0
## NSABHC0003-53598                0                   0               0
##                  Abutilon.hannii.subsp..prostrate..p.k.latz.427.
## NSABBS0005-58582                                               0
## NSABBS0006-58557                                               0
## NSABHC0001-53596                                               0
## NSABHC0002-53597                                               0
## NSABHC0003-53598                                               0
##                  Abutilon.leucopetalum
## NSABBS0005-58582                     0
## NSABBS0006-58557                     0
## NSABHC0001-53596                     0
## NSABHC0002-53597                     0
## NSABHC0003-53598                     0

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summary(AP.data.SppbySites.PA[,1:3])

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##  Abutilon.fraseri  Abutilon.halophilum Abutilon.hannii   
##  Min.   :0.00000   Min.   :0.000000    Min.   :0.000000  
##  1st Qu.:0.00000   1st Qu.:0.000000    1st Qu.:0.000000  
##  Median :0.00000   Median :0.000000    Median :0.000000  
##  Mean   :0.01072   Mean   :0.007657    Mean   :0.001531  
##  3rd Qu.:0.00000   3rd Qu.:0.000000    3rd Qu.:0.000000  
##  Max.   :1.00000   Max.   :1.000000    Max.   :1.000000

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Example 2A. Scoring metric; Percent Cover (m_kind = "percent_cover"), Cover Type: Prejected Foliage Cover (cover_type="PFC")

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# Scoring metric: Percent Cover
# =============================

# Cover Type: Projected foliage cover (PFC)
# -----------------------------------------
# Hits scoered as 'in canopy sky' are removed
AP.data.SppbySites.PcC.PFC = species_table(AP.data$veg.PI, m_kind="percent_cover", cover_type="PFC")
#class(AP.data.SppbySites.PcC.PFC)
#dim(AP.data.SppbySites.PcC.PFC) # Number of rows and columns in the matrix: Sites x Species
#AP.data.SppbySites.PcC.PFC[1:5, 1:5]
summary(AP.data.SppbySites.PcC.PFC[,1:3])

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##  Abutilon.fraseri   Abutilon.halophilum Abutilon.hannii    
##  Min.   :0.000000   Min.   :0.000000    Min.   :0.0000000  
##  1st Qu.:0.000000   1st Qu.:0.000000    1st Qu.:0.0000000  
##  Median :0.000000   Median :0.000000    Median :0.0000000  
##  Mean   :0.001516   Mean   :0.005307    Mean   :0.0003033  
##  3rd Qu.:0.000000   3rd Qu.:0.000000    3rd Qu.:0.0000000  
##  Max.   :0.297030   Max.   :1.980198    Max.   :0.1980198

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Example 2B. Scoring metric; Percent Cover (m_kind = "percent_cover"), Cover Type: Opaque Canopy Cover (cover_type="OCC")

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# Cover Type: Opaque Canopy Cover (OCC)
# -------------------------------------
# Hits scoered as 'in canopy sky' are retained
AP.data.SppbySites.PcC.OCC = species_table(AP.data$veg.PI, m_kind="percent_cover", cover_type="OCC")
#class(AP.data.SppbySites.PcC.OCC)
#dim(AP.data.SppbySites.PcC.OCC) # Number of rows and columns in the matrix: Sites x Species
#AP.data.SppbySites.PcC.OCC[1:5, 1:5]
summary(AP.data.SppbySites.PcC.OCC[,1:3])

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##  Abutilon.fraseri   Abutilon.halophilum Abutilon.hannii    
##  Min.   :0.000000   Min.   :0.000000    Min.   :0.0000000  
##  1st Qu.:0.000000   1st Qu.:0.000000    1st Qu.:0.0000000  
##  Median :0.000000   Median :0.000000    Median :0.0000000  
##  Mean   :0.001516   Mean   :0.005307    Mean   :0.0003033  
##  3rd Qu.:0.000000   3rd Qu.:0.000000    3rd Qu.:0.0000000  
##  Max.   :0.297030   Max.   :1.980198    Max.   :0.1980198

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Example 3. Scoring metric; Frequency ('m_kind = "freq")

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# Scoring metric: Frequency
# =========================
AP.data.SppbySites.Freq = species_table(AP.data$veg.PI, m_kind="freq")
#class(AP.data.SppbySites.Freq)
#dim(AP.data.SppbySites.Freq) # Number of rows and columns in the matrix: Sites x Species
#AP.data.SppbySites.Freq[1:5, 1:5]
summary(AP.data.SppbySites.Freq[,1:3])

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##  Abutilon.fraseri   Abutilon.halophilum Abutilon.hannii    
##  Min.   :0.000000   Min.   :0.00000     Min.   :0.0000000  
##  1st Qu.:0.000000   1st Qu.:0.00000     1st Qu.:0.0000000  
##  Median :0.000000   Median :0.00000     Median :0.0000000  
##  Mean   :0.001378   Mean   :0.00245     Mean   :0.0003063  
##  3rd Qu.:0.000000   3rd Qu.:0.00000     3rd Qu.:0.0000000  
##  Max.   :0.200000   Max.   :0.80000     Max.   :0.2000000

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Example 4A. Scoring metric; IVI (m_kind = "IVI"), Cover Type: Prejected Foliage Cover (cover_type="PFC")

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# Scoring metric: IVI
# ===================

# Cover Type: Projected foliage cover (PFC)
# -----------------------------------------
# Hits scoered as 'in canopy sky' are removed
AP.data.SppbySites.IVI.PFC = species_table(AP.data$veg.PI, m_kind="IVI", cover_type="PFC")
#class(AP.data.SppbySites.IVI.PFC)
#dim(AP.data.SppbySites.IVI.PFC) # Number of rows and columns in the matrix: Sites x Species
#AP.data.SppbySites.IVI.PFC[1:5, 1:5]
summary(AP.data.SppbySites.IVI.PFC[,1:3])

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##  Abutilon.fraseri   Abutilon.halophilum Abutilon.hannii    
##  Min.   :0.000000   Min.   :0.00000     Min.   :0.0000000  
##  1st Qu.:0.000000   1st Qu.:0.00000     1st Qu.:0.0000000  
##  Median :0.000000   Median :0.00000     Median :0.0000000  
##  Mean   :0.001378   Mean   :0.00245     Mean   :0.0003063  
##  3rd Qu.:0.000000   3rd Qu.:0.00000     3rd Qu.:0.0000000  
##  Max.   :0.200000   Max.   :0.80000     Max.   :0.2000000

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Example 4B. Scoring metric; IVI (m_kind = "IVI"), Cover Type: Opaque Canopy Cover (cover_type="OCC")

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# Cover Type: Opaque Canopy Cover (OCC)
# -------------------------------------
# Hits scoered as 'in canopy sky' are retained
AP.data.SppbySites.IVI.OCC = species_table(AP.data$veg.PI, m_kind="IVI", cover_type="OCC")
#class(AP.data.SppbySites.IVI.OCC)
#dim(AP.data.SppbySites.IVI.OCC) # Number of rows and columns in the matrix: Sites x Species
#AP.data.SppbySites.IVI.OCC[1:5, 1:5]
summary(AP.data.SppbySites.IVI.OCC[,1:3])

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##  Abutilon.fraseri   Abutilon.halophilum Abutilon.hannii    
##  Min.   :0.000000   Min.   :0.00000     Min.   :0.0000000  
##  1st Qu.:0.000000   1st Qu.:0.00000     1st Qu.:0.0000000  
##  Median :0.000000   Median :0.00000     Median :0.0000000  
##  Mean   :0.001378   Mean   :0.00245     Mean   :0.0003063  
##  3rd Qu.:0.000000   3rd Qu.:0.00000     3rd Qu.:0.0000000  
##  Max.   :0.200000   Max.   :0.80000     Max.   :0.2000000

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