Restoration opportunities beyond highly degraded tropical forests: insights from India’s Western Ghats
Data files
Mar 06, 2024 version files 678.58 KB
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Osuri_plotInfo.csv
8.63 KB
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Osuri_regen_data.csv
205.92 KB
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Osuri_tree_data.csv
459.25 KB
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README.md
4.79 KB
Abstract
Tropical rainforest remnants in human-modified landscapes exhibit varying levels of degradation, from highly degraded open-canopied and invasive plant-invaded habitats to closed-canopy forests that appear structurally intact. The former are frequently identified as being in a state of arrested recovery, and targeted for restoration, but restoration needs and opportunities in the latter remain underexplored. Using tree and seedling data from 105 plots spanning a canopy cover gradient in rainforest fragments and 19 plots in relatively intact “reference” rainforests in India’s Western Ghats mountains, we show that the floristic composition, conservation significance, and carbon stocks of closed-canopy fragments (CC) more closely resemble open-canopy fragments (OC) than reference rainforests (RR). For example, densities of old-growth forest species, endemic/threatened species, and carbon stocks, increased from 15%, 28%, and 22% of reference values in OC to 32%, 46%, and 35% in CC, respectively, while tree community similarity to RR showed no increase from OC to CC (15%). Seedlings mirrored this pattern, offering little indication of natural recovery in closed-canopy fragments. Further, we show using simulations that seedling enrichment in closed-canopy fragments can initiate varying levels of floristic and functional recovery towards reference targets. Our findings illustrate that seemingly structurally intact tropical rainforest fragments can remain arrested in a floristically degraded condition, and represent worthwhile targets for ecological restoration. Such forests expand opportunities for restoring conservation-priority and high carbon-storing species using relatively low-cost methods (e.g., enrichment planting), which can complement intensive restoration of highly degraded forests and minimally-assisted natural recovery of less-fragmented forests.
https://doi.org/10.5061/dryad.8kprr4xvb
This document describes the data and scripts associated with Osuri et al. 2024: Restoration opportunities beyond highly degraded tropical forests: insights from India’s Western Ghats
The upload contains three data files and four R scripts.
Description of the data and file structure
1. Osuri_tree_data.csv contains data from 132 tree (GBH >=30 cm) inventory plots (20m x 20m) in rainforest fragments and reference rainforests. 124 plots were analyzed, while 8 plots lacking canopy cover data were excluded. The data columns are:
DateTime: Date/timestamp
Treatment: Forest fragmentation status -- Fragment OR Benchmark (reference)
Site_ID: Unique site code for each plot
Species_name: Species name as recorded
Height: Tree height (m)
GBH1: Girth at breast height (cm) of single-stemmed trees
GBH1 - GBH12: Girth at breast height (cm) of multi-stemmed trees
Remarks: Remarks
Accept_name_WFO: World Flora Online accepted species names
Habit: Growth form -- Tree OR Shrub
Distribution: Distributional range and origin -- Endemic OR Native OR Introduced
IUCN_status: IUCN redlist category -- CR or EN or VU or NT or LC or DD, or NA (unknown)
wden_sps: Species-level wood density (g cm-3)
Wden_final: Wood density (g cm-3) used in biomass estimation, species level is available, else genus level
seed_size: Categorical -- S (Small; length <1 cm), M (Medium; length 1-3 cm), L (Large; length >3 cm), or NA (Unknown)
disperser: Seed dispersal mechanism -- Bird, Mammal, Mammal_bird (mammal and bird), Gravity, Wind, or Unknown
habt_new: Habitat affinity category: Mature (mature forest), Secondary (secondary or disturbed forest), NA (unknown/Introduced species)
ad_ht: Species maximum adult height (m)
DBH: Effective diameter (cm). Calculated as (d12 + d22 +...dn^2)^0.5, where d1 = GBH1/pi, and so on
Basal: Tree basal area (m2)
Carbon: Tree aboveground carbon stock (Mg)
2. Osuri_regen_data.csv contains data from 132 seedling (height >= 10 cm and GBH < 10 cm) plots (20m x 20m) in rainforest fragments and reference rainforests. 124 plots were analyzed, while 8 plots lacking canopy cover data were excluded. The data columns are:
Date: Date/timestamp
Site_ID: Unique site code for each plot
Treatment: Forest fragmentation status -- Fragment OR Benchmark (reference)
Species_name: Species name as recorded
Abun: No. of individuals counted
Accept_name_WFO: World Flora Online accepted species names
Habit: Growth form -- Tree OR Shrub
Distribution: Distributional range and origin -- Endemic OR Native OR Introduced
IUCN_status: IUCN redlist category -- CR or EN or VU or NT or LC or DD, or NA (unknown)
wden_sps: Species-level wood density (g cm-3)
Wden_final: Wood density (g cm-3) used in biomass estimation, species level is available, else genus level
seed_size: Categorical -- S (Small; length <1 cm), M (Medium; length 1-3 cm), L (Large; length >3 cm), or NA (Unknown)
disperser: Seed dispersal mechanism -- Bird, Mammal, Mammal_bird (mammal and bird), Gravity, Wind, or Unknown
habt_new: Habitat affinity category: Mature (mature forest), Secondary (secondary or disturbed forest), NA (unknown/Introduced species)
ad_ht: Species maximum adult height (m)
3. Osuri_plotInfo.csv contains site details of 132 plots, 124 of which were included in the analysis. The data columns are:
S_No.: Serial number
Site_name: Site name
Site_ID: Unique site code for each plot
Treatment: Forest fragmentation status -- Fragment OR Benchmark (reference)
Lat_final: Latitude of plot centroid (degree-decimal)
Long_final: Longitude of plot centroid (degree-decimal)
dist_PA: Distance from protected area (m)
CanCover: Canopy cover (%)
Sharing/Access information
For tree functional trait data and sources, see Osuri et. al. (2024) Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India
Code/Software
1. Osuri_tree_script.R contains R scripts for computing summaries, performing regression models, and creating graphs from the adult tree dataset (outputs: Fig. 2, Fig. S3, Fig. S5, Table S2)
2. Osuri_regen_script.R contains R scripts for computing summaries, performing regression models, and creating graphs from the regeneration dataset (outputs: Fig. 2, Fig. S4, Fig. S5, Table S3)
3. Osuri_simulation_script.R contains R scripts for performing the restoration simulations using the tree and regeneration datasets, and generating Fig. 3
4. Osuri_figure_composites.R contains R scripts for formatting Figs. 2, 3, S3, S4, and S5 as depicted in the manuscript