DOI: 10.6084/m9.figshare.29043689
title: Rebound from Restoration: Assessing the Diversity of Bird Assemblages in Revegetated and Remnant Patches of Critically Endangered Lowland Subtropical Rainforest. Datasets

description: Abstract:<br>With increased rates of biodiversity loss and deforestation, ecological restoration has become a common practice worldwide. Despite this, metrics that are often used to quantify the success of biodiversity recovery display highly variable patterns depending upon the ecosystem being restored. The aims of this study were to investigate four biodiversity metrics - Chao2 species richness, rainforest-dependent species richness, functional diversity and phylogenetic diversity - of bird assemblages occurring in connected remnant, fragmented remnant, old revegetation and young revegetation patches of critically endangered Australian lowland subtropical rainforest (LSR). The study also examined the influence of site-based vegetation and landscape attributes on bird assemblages in these patches. A combination of passive acoustic monitoring and bird surveys revealed 72 species across eight study sites. While no site-based vegetation attributes were significant predictors of avian diversity, high canopy cover had a strong positive relationship with rainforest-dependent species. The landscape context surrounding the patches had a significant relationship with three metrics, with vegetated vs cleared land within a 200m and 500m radius from the recording location being a significant positive predictor of species richness, rainforest-dependent species richness and functional diversity. A non-metric multidimensional scaling analysis showed that rainforest-dependent species were associated with sites connected to uncleared remnant vegetation in the broader landscape, while generalist species were associated with fragmented sites. The results of our study highlight the importance of ecological restoration for the recovery of bird assemblages in Australian LSR, as well as the variables that may influence fluctuations in species richness, rainforest-dependent species richness, functional diversity and phylogenetic diversity within these communities. Future ecological restoration initiatives should aim to re-establish canopy cover and restore the connectivity and extent of LSR to facilitate the recolonisation of diverse bird assemblages that depend on this critically endangered ecosystem.<br>This repository contains the data required to replicate the results in the associated publication. All analyses were undertaken in R. All companion coding is provided in R. The R project "Borrow_etal_2025_Rebound from Restoration.Rproj" will load in all data.<b>Borrow et al 2025 - site specific species data - </b>contains all species lists and presence absence data required for species richness and species richness estimator calculation.<b>Borrow et al 2025 Chao2 Species Richness Predictors Code</b> was used to calculate Chao2 species richness.<b>Borrow et al 2025 Functional Diversity Matrix</b> - contains the functional traits for the species detected in the study. These were derived from EltonTraits1.0 (Wilman et al., 2014). The companion script<b> </b><b>Borrow et al 2025 Functional Diversity Calculations</b> is provided. The functions in <b>FD_calculator</b> are required for this analysis and have been adapted from a now unavailable workshop by Dan Flynn (dff2101@columbia.edu). Please cite Petchey & Gaston (2002) for methods.<b>Borrow et al 2025 Phylogenetic_Distance_From_Presence_Absence_dataframes</b> - contains the methods to convert presence and absence datasets to phylogenetic trees so that phylogenetic distance can be calculated. The published tree used to produce this from Jetz et al., 2012. A shortened Newick file is provided to bypass the need to relabel the outdated genus and species names in the Jetz tree.<b>Borrow et al 2025 - spatial data </b>- contains the spatial data calculated at 100m, 200m, and 500m from the autonomous recording unit.<b>Borrow et al 2025 - MASTER FILE - Data Analysis Attributes </b>- contains the calculated diversity metrics and spatial data required to run GLMs. <b>Borrow et al 2025 Generalised Linear Model Code</b> is the companion code.<b>Borrow et al 2025 NMDS dataset</b> - provides presence and absence datasets in a layout ready for NMDS analysis. <b>Borrow et al 2025 NMDS Code</b> is the companion code to facilitate the replication of the results.<br><br>References for data sources and methods used in study:Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K., & Mooers, A. O. (2012). The global diversity of birds in space and time. Nature, 491(7424), 444–448. https://doi.org/10.1038/nature11631Petchey, O. L., & Gaston, K. J. (2002). Functional diversity (FD), species richness and community composition. <i>Ecology Letters, 5</i>(3), 402-411. https://doi.org/10.1046/j.1461-0248.2002.00339Wilman, H., Belmaker, J., Simpson, J., de la Rosa, C., Rivadeneira, M. M., & Jetz, W. (2014). EltonTraits 1.0: Species‐level foraging attributes of the world's birds and mammals: Ecological Archives E095‐178. <i>Ecology</i>, <i>95</i>(7), 2027-2027.