DOI: 10.5061/dryad.bnzs7h4mj
title: Vertebrate diversity and biomass along a recovery gradient in a lowland tropical forest

description: Deforestation of tropical forests have resulted in extensive areas of
 secondary forests with the potential to restore biodiversity to former
 old-growth forest levels. The recovery of vertebrate communities is an
 essential component of biodiversity and ecosystem restoration, as
 vertebrates provide key ecosystem functions. However, little is known
 about the recovery trajectories and habitat preferences of vertebrates in
 tropical landscapes with differing land-use legacies. We used camera traps
 covering three weeks to study the activity of ground-based mammals and
 birds in the understory of 57 sites along a forest recovery gradient,
 ranging from active agriculture, such as pastures and cacao plantations,
 to naturally recovering forests and old-growth forests in the Chocó
 rainforest in north-western Ecuador. Our results show that diversity and
 biomass of wild vertebrates are highest in old-growth forests and late
 recovery stages, while for domestic vertebrates, these indices are highest
 in agricultural land. Additionally, while species-habitat networks showed
 low habitat specificity for vertebrate species, an indicator species
 analysis found no species to indicate old-growth forests, Dasyprocta
 punctata and Tayassu pecari to indicate all forest types, and Aramides
 wolfi and Pecari tajacu to indicate late regeneration forests. We suggest
 that these patterns are caused by a high habitat connectivity and large
 amounts of remaining old-growth forest in our study area. Our findings
 indicate that secondary forests have a high potential for the recovery of
 vertebrate species diversity and biomass to old-growth level in lowland
 tropical forests with short regeneration times.
description: # Vertebrate diversity and biomass along a recovery gradient in a
 **lowland tropical forest**
 [https://doi.org/10.5061/dryad.bnzs7h4mj](https://doi.org/10.5061/dryad.bnzs7h4mj) ## Description of the data and file structure These data set contain data derived by camera traps on 65 plots in the reserves Reserva Río Canandé and Reserva Tesoro Escondido in northwest Ecuador. ### Files and variables #### File: Grella\_et\_al.\_vertebrate\_assessment\_R-script.R **Description:** R code for data analysis * Includes the following analysis: * Analysis of species diversity and biomass using a generalized linear model * Network analysis * Indicator species analysis * Predictions of species diversity and biomass using a generalized additive model #### File: S4\_environment.ods **Description:** Environmental information of plot location, land-use legacy, surrounding forest cover and forest distance of each plot * Project3: Information about plot selection * Reassembly: Plots that are in the final plot selection of the REASSEMBLY Research Unit * Wuerzburg: Additional plots that were sampled for this study * Camera Year: Sampling year in which the camera traps were installed * Plot_ID: Plot name * PREX: Information if this plot was part of the perturbation-recruitment experiment of the REASSEMBLY Research Unit. For this experiment parts of the plots were either fenced for preventing vertebrates access or disturbed by removing vegetation and leaf litter. * 1 means that there was a PREX treatment on the plot * NA means that there was no PREX treatment on the plot * Latitude and Longitude: GPS coordinates of plot * Elevation: Altitude of plot (meters above sea level) * Treatment1, Treatment2, Category4, Category7: Different variations of the land-use categories depending on regeneration age and land-use legacy (pasture or cacao plantation) * Regeneration: Year in which the plot was abandoned for natural regeneration * Succession: Years since abandonment * Forest_1km: Forest cover in a 1 km radius. See methods in Escobar et al. (2024). * Distance_forest_m: Distance from plot to the next old-growth forest when plot was agricultural land. See methods in Escobar et al. (2024). * Distance_edge_m: Distance from plot to the next forest edge when plot was forested. See methods in Escobar et al. (2024). #### File: S5\_Observed\_for\_57\_plots\_and\_predicted\_values\_for\_all\_65\_plots.csv **Description:** Evironmental information (S4) and biomass and diversity information (S7) complemented with predictions of diversity and biomass on each plot. Predictions were calculated using a generalized additive model. * Bird_pred_bio: Prediction of bird biomass * Dom_all_pred_bio: Prediction of domestic vertebrate biomass * Mammal_pred_bio: Prediction of mammal biomass * Birdsq0_pred: Prediction of bird number of observed species (q0) * Domesticsq0_pred: Prediction of domestic vertebrate number of observed species (q0) * Mammalsq0_pred: Prediction of mammal number of observed species (q0) * Birdsq1_pred: Prediction of bird effective species number (q1) * Domesticsq1_pred: Prediction of domestic vertebrate effective species number (q1) * Mammalsq1_pred: Prediction of mammal effective species number (q1) #### File: S6\_community.csv **Description:** List of captured species on each plot * Latin Name: Latin species name * Group: Species were grouped into * Mammal * Bird * Domestic Bird (DomBird) * Domestic Mammal (Dom_Mammal) * Human #### File: S7\_biomass\_diversity.csv **Description:** Diversity and biomass on each plot * Plot: plot name * Category7: Land-use categories used for the analysis of species diversity and biomass * Bird_Bio: Bird biomass * Mammal_Bio: Mammal biomass * Dom_all_Bio: Domestic vertebrate biomass * Birdsq1: Bird effective species number (q1) * Birdsq0: Bird number of observed species (q0) * Domesticsq1: Domestic vertebrate effective species number (q1) * Domesticsq0: Domestic vertebrate number of observed species (q0) * Mammalsq1: Mammal effective species number (q1) * Mammalsq0: Mammal number of observed species (q0) #### File: S8\_community\_indicspecies.csv **Description:** List of captured species on each plot (S6) formated for indicator species analysis ## Code/software The provided code is written in the programming language R. For analysis we used R version 4.2 and the following R packages: ggplot2, ggpubr, stringr, bipartite, tidyr, indicspecies, mgcv, nlme, readODS, ncf, MASS. ## Literature Escobar, S., Newell, F. L., Endara, M.-J., Guevara-Andino, J. E., Landim, A. R., Neuschulz, E. L., Nußer, R., Müller, J., Pedersen, K. M., Schleuning, M., Tremlett, C. J., Villa-Galaviz, E., Schaefer, H. M., Donoso, D. A., & Blüthgen, N. (2024). *Reassembly of a tropical rainforest ecosystem: A new chronosequence in the Ecuadorian Chocó tested with the recovery of tree attributes*. bioRxiv [Preprint]. [https://doi.org/10.1101/2024.03.21.586145](https://doi.org/10.1101/2024.03.21.586145)