DivEst {entropart} | R Documentation |

Estimates diversity of a metacommunity.

```
DivEst(q = 0, MC, Biased = TRUE, Correction = "Best", Tree = NULL,
Normalize = TRUE, Z = NULL, Simulations = 100,
ShowProgressBar = TRUE, CheckArguments = TRUE)
is.DivEst(x)
## S3 method for class 'DivEst'
plot(x, ..., main = NULL, Which = "All",
Quantiles = c(0.025, 0.975), colValue = "red", lwdValue = 2, ltyValue = 2,
colQuantiles = "black", lwdQuantiles = 1, ltyQuantiles = 2)
## S3 method for class 'DivEst'
autoplot(object, ..., main = NULL, Which = "All",
labels = NULL, font.label = list(size=11, face="plain"),
Quantiles = c(0.025, 0.975), colValue = "red",
colQuantiles = "black", ltyQuantiles = 2)
## S3 method for class 'DivEst'
summary(object, ...)
```

`q` |
A number: the order of diversity. |

`MC` |
A |

`Biased` |
Logical; if |

`Correction` |
A string containing one of the possible corrections. The correction must be accepted by |

`Tree` |
An object of class |

`Normalize` |
If |

`Z` |
A relatedness matrix, |

`Simulations` |
The number of simulations to build confidence intervals. |

`ShowProgressBar` |
If |

`CheckArguments` |
Logical; if |

`x` |
An object to be tested or plotted. |

`main` |
The title of the plot. |

`Which` |
May be |

`labels` |
Vector of labels to be added to multiple plots. |

`font.label` |
A list of arguments to customize labels. See |

`object` |
A |

`Quantiles` |
A vector containing the quantiles of interest. |

`colValue` |
The color of the line representing the real value on the plot. |

`lwdValue` |
The width of the line representing the real value on the plot. |

`ltyValue` |
The line type of the line representing the real value on the plot. |

`colQuantiles` |
The color of the lines representing the quantiles on the plot. |

`lwdQuantiles` |
The width of the lines representing the quantiles on the plot. |

`ltyQuantiles` |
The line type of the lines representing the quantiles on the plot. |

`...` |
Additional arguments to be passed to the generic methods. |

`Divest`

estimates the diversity of the metacommunity and partitions it into alpha and beta components.

If `Tree`

is provided, the phylogenetic diversity is calculated else if `Z`

is not `NULL`

, then similarity-based entropy is calculated.

Bootstrap confidence intervals are calculated by drawing simulated communities from a multinomial distribution following the observed frequencies (Marcon et al, 2012; 2014).

A `Divest`

object which is a `DivPart`

object with an additional item in its list:

`SimulatedDiversity` |
A matrix containing the simulated values of alpha, beta and gamma diversity. |

`Divest`

objects can be summarized and plotted.

Eric Marcon <Eric.Marcon@agroparistech.fr>, Bruno Herault <Bruno.Herault@cirad.fr>

Marcon, E., Herault, B., Baraloto, C. and Lang, G. (2012). The Decomposition of Shannon's Entropy and a Confidence Interval for Beta Diversity. *Oikos* 121(4): 516-522.

Marcon, E., Scotti, I., Herault, B., Rossi, V. and Lang, G. (2014). Generalization of the partitioning of Shannon diversity. *PLOS One* 9(3): e90289.

Marcon, E., Herault, B. (2015). Decomposing Phylodiversity. *Methods in Ecology and Evolution* 6(3): 333-339.

```
# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
data(Paracou618)
# Estimate Shannon diversity.
Estimation <- DivEst(q = 1, Paracou618.MC, Biased = FALSE, Correction = "UnveilJ",
Simulations = 20)
plot(Estimation)
summary(Estimation)
```

[Package *entropart* version 1.6-10 Index]