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PNC

The PNC package is an open-source, all-in-one solution forempirically testing the key assumption of phylogenetic nicheconservatism (PNC) in ecological community studies. Designed foraccessibility and scientific rigor, PNC streamlines the entireworkflow—from integrating comprehensive, global trait databases(covering plants, birds, mammals, reptiles, amphibians, and fish) toassessing data quality, performing dimensionality reduction, and batchprocessing analyses.

By bridging a critical methodological gap, the PNC package enablesrobust, phylogenetically-informed ecology, biogeography, andconservation research—supporting more accurate predictions of speciesdistributions, better assessments of global change risks, and strongerfoundations for biodiversity conservation.

Get started with PNC to bring standardized, automated phylogeneticniche conservatism tests into your workflow!

Installation

From CRAN (recommended)

{r,class.source = 'fold-show'} # install.packages("PNC")

From GitHub (developmentversion)

{r,class.source = 'fold-show'} # if (!requireNamespace("devtools", quietly = TRUE)) {install.packages("devtools")} # devtools::install_github("biodiversity-monitoring/PNC")

Main functions ofPNC and their descriptions

Name	Type	Description
AmphiBIO	Database	A comprehensive global database of amphibian natural history traits.It provides 12 continuous traits related to ecology, morphology, andreproduction for over 6,500 species across all orders (Anura, Caudata,Gymnophiona), 61 families, and 531 genera (Oliveira et al., 2017).
AVONET	Database	A comprehensive trait database for extant avian species, providingdetailed morphological information through 11 continuous traits covering11,009 bird species worldwide (Tobias et al., 2022).
BCI	Database	A 50-hectare forest ecosystem dataset from Barro Colorado Island,comprising comprehensive species inventories, phylogenetic trees atspecies and genus levels, and community composition matrices (Condit etal., 2019).
COMBINE	Database	An integrated mammalian trait database consolidating 40 continuousmorphological and ecological traits for 6,234 extant and recentlyextinct mammal species (Soria et al., 2021).
Fishlife	Database	A comprehensive compilation of life-history traits for describedfish species (Chondrichthyes and Osteichthyes), featuring 17 continuoustraits with at least one measurement for 26,622 species (Thorson et al.,2023).
HimalayanBirds	Database	A dataset providing information on bird species in the Himalayas,including species names, phylogenetic relationships, and communitycomposition across elevation bands (Ding et al., 2021).
ReptTraits	Database	A comprehensive reptilian trait dataset comprising 8 continuousmorphological and ecological traits across 12,060 species spanning majorreptilian clades (Crocodylia, Testudines, Rhynchocephalia, Amphisbaenia,Sauria, and Serpentes) (Oskyrko et al., 2024).
TRY	Database	A global plant trait database providing species-level datasets with20 continuous traits widely utilized in ecological and evolutionaryresearch (Kattge et al., 2020).
`merge_dataset()`	function	Merges two data frames based on the “species” column, automaticallyhandling missing values and inconsistent columns.
`extract_traits()`	function	Extracts trait data at the species, genus, or family level fromglobal trait databases.
`coverage()`	function	Provides statistics on trait availability, including the number ofmissing values and coverage rates.
`pnc()`	function	Performs a phylogenetic niche conservatism analysis within a singlecommunity, quantifying the phylogenetic signal in trait data. OptionalPCA dimensionality reduction and multiple statistical approaches aresupported.
`compnc()`	function	Conducts a comprehensive phylogenetic niche conservatism analysisacross multiple communities, similar in function to`pnc()`.
`pnc_robustness()`	function	Evaluates the robustness of phylogenetic signal estimates bysimulating trait data and testing the consistency of statisticalsignificance conclusions.
`compnc_robustness()`	function	Extends`pnc_robustness()` to evaluate the robustness ofphylogenetic signal estimates across multiple communities.

PNC workflow

Study case 1

```{r,class.source = ‘fold-show’} library(PNC)

Load dataset

data(“BCI”) str(BCI) data(“TRY”) head(TRY)

species level

Extract species names

sp <- colnames(BCI$com) sp

Extracttrait data for the specified species from the TRY database

subtraits <- extract_traits(sp, TRY, rank = “species”, traits =c(“LA”, “LMA”, “LeafN”, “PlantHeight”, “SeedMass”, “SSD”))head(subtraits)

Calculateand display the coverage of the trait data

coverage(subtraits)

Performphylogenetic niche conservatism analysis using the pnc() function

pnc(subtraits, BCI$phy_species, methods = “lambda”, pca_axes =c(“PC1”, “PC2”))

Assessthe robustness of the phylogenetic signal estimates

set.seed(123) pnc_robustness(subtraits, BCI$phy_species, methods =“lambda”, n_simulations = 100)

genus level

Extract genus names

sp2 <- unique(BCI$splist$genus)

Extracttrait data for the specified genera from the TRY database

subtraits2 <- extract_traits(sp2, TRY, rank = “genus”, traits =c(“LA”, “LMA”, “LeafN”, “PlantHeight”, “SeedMass”, “SSD”))head(subtraits2)

Calculateand display the coverage of the trait data

coverage(subtraits2)

Performphylogenetic niche conservatism analysis

pnc(subtraits2, BCI$phy_genus, methods = “lambda”, pca_axes =c(“PC1”, “PC2”))

Assessthe robustness of the phylogenetic signal estimates at the genuslevel

set.seed(123) pnc_robustness(subtraits2, BCI$phy_genus, methods =“lambda”, n_simulations = 100)

### Study case 2```{r,class.source = 'fold-show'}# Load datasetdata("HimalayanBirds")str(HimalayanBirds)data("AVONET")head(AVONET)# Extract species namessp <- colnames(HimalayanBirds$com)sp# Extract trait data for the specified species from the AVONET databasesubtraits <- extract_traits(sp, AVONET, rank = "species")head(subtraits)# Calculate and display the coverage of the trait datacoverage(subtraits)# Perform phylogenetic niche conservatism analysispnc(subtraits, HimalayanBirds$phy_species, methods = "lambda", pca_axes = c("PC1", "PC2"))set.seed(123)# Assess the robustness of the phylogenetic signal estimates pnc_robustness(subtraits,               HimalayanBirds$phy_species,               methods = "lambda",               pca_axes = c("PC1", "PC2"),               n_simulations = 100)# Perform phylogenetic niche conservatism analysis across multiple communitiescompnc(com = HimalayanBirds$com, subtraits, HimalayanBirds$phy_species, methods = "lambda", pca_axes = NULL)# Assess the robustness of phylogenetic signal estimates across multiple communitiesset.seed(123)robust_results <- compnc_robustness(HimalayanBirds$com,                                    subtraits,                                    HimalayanBirds$phy_species,                                    methods = "lambda",                                    pca_axes = c("PC1", "PC2"),                                    n_simulations = 100)robust_results

Reference

Condit, R., Perez, R., Aguilar, S., Lao, S., Foster, R., Hubbell,S.P. (2019). Complete data from the Barro Colorado 50-ha plot: 423617trees, 35 years, 2019 version.https://doi.org/10.15146/5xcp-0d46

Ding, Z., Hu, H., Cadotte, M.W., Liang, J., Hu, Y., & Si, X.(2021). Elevational patterns of bird functional and phylogeneticstructure in the central Himalaya. Ecography, 44(9), 1403-1417.https://doi.org/10.1111/ecog.05660

Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I. C.,Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M.,Acosta, A. T. R., Adamidis, G. C., Adamson, K., Aiba, M., Albert, C. H.,Alcántara, J. M., Alcázar C, C., Aleixo, I., Ali, H., Amiaud, B., etal. (2020). TRY plant trait database – enhanced coverage and openaccess. Global Change Biology, 26(1), 43-60.https://doi.org/10.1111/gcb.14904

Oliveira, B. F., São-Pedro, V. A., Santos-Barrera, G., Penone, C.,& Costa, G. C. (2017). AmphiBIO, a global database for amphibianecological traits. Scientific data, 4(1), 1-7.https://doi.org/10.1038/sdata.2017.123

Oskyrko, O., Mi, C., Meiri, S., & Du, W. (2024). ReptTraits: acomprehensive dataset of ecological traits in reptiles. Scientific Data,11(1), 243.https://doi.org/10.1038/s41597-024-03079-5

Soria, C. D., Pacifici, M., Di Marco, M., Stephen, S. M., &Rondinini, C. (2021). COMBINE: a coalesced mammal database of intrinsicand extrinsic traits. Ecology, 102(6), e03344.https://doi.org/10.1002/ecy.3344

Thorson, J. T., Maureaud, A. A., Frelat, R., Mérigot, B., Bigman, J.S., Friedman, S. T., Palomares, M. L. D., Pinsky, M. L., Price, S. A.,& Wainwright, P. (2023). Identifying direct and indirectassociations among traits by merging phylogenetic comparative methodsand structural equation models. Methods in Ecology and Evolution, 14(5),1243-1255.https://doi.org/10.1111/2041-210X.14076

Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang,J., Sayol, F., Neate-Clegg, M. H. C., Alioravainen, N., Weeks, T. L.,Barber, R. A., Walkden, P. A., MacGregor, H. E. A., Jones, S. E. I.,Vincent, C., Phillips, A. G., Marples, N. M., Montaño-Centellas, F. A.,Leandro-Silva, V., Claramunt, S., Darski, B., et al. (2022). AVONET:morphological, ecological and geographical data for all birds. EcologyLetters, 25(3), 581-597.https://doi.org/10.1111/ele.13898

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