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111 results for “Secondary Forest”
Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas, Hay meadow restoration experiment
Local and regional-scale processes interact to govern the assembly, diversity and functioning of ecological communities. Evaluating the interplay of these differently-scaled processes in the regulation of ecological systems is a challenging problem, but is crucial towards understanding and predicting the potential effects of accelerated human activity on biological diversity and ecosystem sustainability. Since 2000, two long-term field experiments have been underway in grasslands of eastern Kansas to investigate the interplay of soil resource availability, species interactions and regional processes governing plant secondary succession, community assembly, biodiversity, and ecosystem functioning. Both experiments involve manipulations of soil nutrients in permanent grassland study plots and employ multi-species seed addition treatments to evaluate the contribution of dispersal limitation and regional constraints on local species pools to the regulation of plant community dynamics. Hay meadow restoration experiment, previously funded by USDA, was established in 2000 in a section of the field that was left unplowed at the start of the experiment. Thus Experiment 2 was initiated in the context of secondary succession on recently abandoned cool-season hayfield where hay grass species were dominant at the start of the study. In this experiment we have been monitoring plant community change annually since 2001 in response to two aspects of hay management important in our area: annual fertilization and annual haying. The experimental design involves factorial manipulations of nutrient supply (two levels of NPK fertilization), annual haying (two levels: hayed; not hayed) and propagule input achieved by adding seeds of 41 native prairie species to half of the plots. Experiment 2 parallels Experiment 1 with manipulations of soil resources and species pools, but does so in the contexts of hay management and native prairie hay meadow restoration.
Earthworms in tropical tree plantations and secondary forests
We compared patterns of earthworm abundance and species composition in tree plantations and secondary forests of Puerto Rico. Tree plantations included pine (Pinus caribaea Morelet) and mahogany (Swietenia macrophylla King) established in the 1930s, 1960s, and 1970s; secondary forests were naturally regenerated in areas adjacent to these plantations. We found that (1) earthworm density and fresh weight in the secondary forests were twice those in either of the tree plantations, and did not differ between the plantations, and (2) the exotic earthworm species, Pontoscolex corethrurus M ller, dominated both plantations and the secondary forests, but native earthworm species, Pontoscolex spiralis Borges & Moreno, Estherella montana Gates, and E. gatesi Borges & Moreno, occurred only in the secondary forests. Our results suggest that naturally-regenerated secondary forests are preferable to pine and mahogany plantations for maintaining a high level of earthworm density, fresh weight, and native species. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Soil organic matter dynamics in the tabonuco forest, a plantation and a secondary forest in Guzman
In this project we try to find out the relationship between the primary production and the soil organic carbon fractions. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Stand Dynamics and Radial Growth Measurements from Old-Growth and Secondary-Growth Forests at the Coweeta Hydrologic Laboratory and Joyce Kilmer Wilderness Area
Our objectives were to define disturbance causes, rates (percent disturbance per decade), magnitudes and frequency (time since last disturbance) for both secondary and old-growth mixed-oak stands, and to determine if all mixed oak stands experience similar disturbance history.
Data from paper: Large carbon sink potential of Secondary Forests in Brazilian Amazon to mitigate climate change (public)
<p><strong>Title</strong>: Large carbon sink potential of Secondary Forests in the Brazilian Amazon to mitigate climate change</p> <p><strong>Contact:</strong> Viola Heinrich (viola.heinrich@bristol.ac.uk)</p> <p><strong>This repository contains</strong>:</p> <ol> <li>Zipped folder:<strong> Fig1_data_input.zip</strong> - all the files needed to produce Figure 1a-e of the main paper. Set the working directory to folder containing the file and use the script "Fig1a_f_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 1 - these files are in the format "<strong><driver>_assessment_v2.csv</strong>". The columns in the files are: A: age of secondary forest; B: 50th percentile (median) of the modal Aboveground Biomass (AGB) value for the given age (note, units are in biomass not carbon: Mg/ha/yr); C: The bias-corrected AGB value, calculated by subtracting the lowest AGB value in column B such that the AGB data starts at or near 0Mg/ha/yr at age 1. D: the number of secondary forest pixels observed to have the given age, E: "Threshold" : the threshold limits of the given driver e.g. 0 Fires in fire_assessmentv2.csv implies the corresponding secondary forest pixels experienced 0 fires throughout the analysis period. The folder also contains the output regrowth models seen in Figure 1 in the format "<strong>regrowth_model_<driver_threshold>.RData" </strong>where driver_threshold refers to the driving variable name and the associated threshold limit for the given driver.</li> <li>Zipped folder:<strong> Fig2_regions_outline.zip</strong> - contains the boundaries of the 4 regions identified in Figure 2a of the main paper in a shapefile (.shp) format and the corresponding file formats needed to produce and load a shapefile. </li> <li>Zipped folder: <strong>Fig1g_2b_e_variable_importance.zip</strong> - contains the output files of the random forest analysis assessing the variable importance for the whole Amazon ("whole_Amazon" subfolder) and for the different regions identified in Figure2a. Files are given as .RDS files that can be loaded in R and the corresponding figures produced using the script "Fig1g_2b_e_plot.R". Files start with the region of interest e.g. "whole_Amazon" or "NE_sector". Middle part of the filename - importance_conditionalTrue/False - this determines whether the importance was calculated using the conditional permutation (True) or not (False). The end of the file name - seed<NUM> - denotes the number of the random seed that was set to extract the sample data. e.g. whole_Amazon_2500_cforest_important_conditionalTrue_seed200.RDS - shows the conditional permutation importance assessment using a sample size of 2500 when the setseed parameter was set to 200 to extract a random sample representing the whole Amazon. The remaining files are the random forest output - as .RDS file. Please note the code to produce the random forest model and the importance assessment has not been included here - this code takes multiple days to run, so only the input and outputs have been included here. Please contact the corresponding author (see end) for more information on this. </li> <li>Zipped folder: <strong>Fig3_data_input.zip</strong> - all the files needed to produce Figure 3a-d of the main paper. Set the working directory to folder containing the file and use the script "Fig3_plot.R" to run (see below). The folder contains the input files of the 6 driving variables used to build regrowth models seen in Figure 3 - these files are in the format "<strong><REGION>-Group.csv</strong>". See bullet point 1 for explanations for the columns in the file. Again column E -"threshold" denotes the code used to identify the the 4 subclasses of regrowth seen in the Figure. Where 11 = No disturbance; 12 = Only burning; 21 = Only (multiple) deforestations; 22 = Both burning and multiple deforestations as disturbance. The code takes data in AGB and converts to AGC. The folder also contains the output regrowth models seen in Figure 3 in the format <strong>"regrowth_model_<region_disturbance_type>.RData" </strong>where region_disturbance refers to the region and the type of disturbance experienced. </li> <li> Zipped folder: <strong>Fig4_5_carbon_sink_2017.zip </strong>- Contains two subfolders: a) <strong>Map_aggre_0.1deg</strong> -this folder contains .tiff files (and associated files) of the losses, gains and net change in AGC between 2016 - 2017 in secondary forests in Amazonia - this has been aggregated to 0.1 degree grid cells so each cell contains the total sum of the losses/gains experienced by secondary forests in that 0.1degree grid cell. b) <strong>secondary_forest_by_region_and_disturbance </strong>- this folder contains .tiff files (and associated files) of the secondary forest data at the original resolution (30m) for 2016 and 2017 split up according to the regions identified in Figure 2, and the type of disturbance (if any). The associated files include a .dbf file which includes additional data [read "README.txt" file in folder] - upon loading the data in a GIS software - the age of the secondary forest pixel will be displayed - open the attribute table to see more data associated with that given pixel e.g. modelled associated AGB for a given pixel. Files in this folder can be used to make Figure 4d and Figure 5 - see script "Fig4_Fig5_plot.R" in the code repository (see below). </li> </ol> <p><strong>Code: </strong>The corresponding code mentioned here can be access here: <a href="https://github.com/heinrichTrees/secondary-forest-regrowth-amazon-public">heinrichTrees/secondary-forest-regrowth-amazon-public (github.com)</a></p> <p><strong>Data usage: </strong>When using any code or data in this repository or another related to this study please cite Heinrich et al.2021 and the original paper as well as the DOI of this repository. </p> <p>If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)</p>
Riparian buffers provide refugia during secondary forest succession
<p>Aim Secondary forests regenerating from human disturbance are increasingly becoming a predominant forest type in many regions, and they play a significant role in forest community dynamics. Understanding the factors that underlie the variation in species responses during secondary succession is important for understanding community assembly and biodiversity monitoring and management. Because species vary in ecology and behavior, responses to ecosystem change should vary among species. Here, we show that habitat type (riparian, upland), phylogeny, and species traits mediate anuran and lizard probability of occurrence and species richness in pasture and secondary forest. Location Sarapiquí and Osa Peninsula, Costa Rica. Methods We used phylogenetic occupancy models to estimate assemblage-level and species-specific responses to forest succession in 30 chronosequence sites that include pasture, secondary forest regenerating from pasture, and mature forest sites. Results For the majority of species, we found increasing probability of occurrence in upland habitats as forest regenerated from pasture to secondary forest and similar probability of occurrence in riparian habitats across pasture, secondary forest, and mature forest sites. Species' responses to forest stage were phylogenetically correlated, and the trend was especially strong for anuran response to pasture sites. Anurans with lotic larval habitat had a positive occupancy response to pasture upland habitat and anurans with lentic larval habitat had a variable response to different forest stages compared to mature forest.</p>
Figure 3 in Ant (Hymenoptera: Formicidae) species diversity in secondary forest and three agricultural land uses of the Colombian Pacific Coast
Figure 3. Number of shared ant species and total number of specimens caught (pitfall and Winkler sack) between four areas of different land use. Two oil palm plots of three and seven years of age were pooled. El Mira Research Center, Tumaco, Pacific Coast of Colombia. / Número de especies de hormigas compartidas y número total de individuos capturados (Pitfall y sacos Winkler) entre cuatro áreas con diferente uso de tierra. Las dos parcelas de palma de aceite de tres y siete años fueron agrupadas. Centro de Investigación El Mira, Tumaco, Nariño, costa pacÍfica de Colombia.
Figure 1 in Ant (Hymenoptera: Formicidae) species diversity in secondary forest and three agricultural land uses of the Colombian Pacific Coast
Figure 1. Map of El Mira Research Center of the Corporación Colombiana de Investigación Agropecuaria, Tumaco, Nariño, Pacific Coast of Colombia, with the location (arrows) of the pitfall trap transects. Yellow hybrid oil palm 7 years old; red hybrid oil palm 3 years old; black peach palm; white secondary forest. / Mapa del Centro de Investigación El Mira de la Corporación Colombiana de Investigación Agropecuaria, Tumaco, Nariño, costa pacÍfica de Colombia con la ubicación (flechas) de las trampas pitfall en los transectos. Amarillo palma de aceite hÍbrido 7 años; rojo palma de aceite hÍbrido 3 años; negro palma de chontaduro; blanco bosque secundario.
Figure 2 in Ant (Hymenoptera: Formicidae) species diversity in secondary forest and three agricultural land uses of the Colombian Pacific Coast
Figure 2. Variation in 0D diversity (species number) of Formicidae between four areas of different land use: El Mira Research Center, Tumaco, Pacific Coast of Colombia. SF: secondary forest, PP: Peach palm, OP7: Oil palm 7 years old, OP3: Oil palm 3 years old. / Variación en la diversidad 0D (número de especies) de Formicidae entre cuatro áreas con diferente uso de tierra. Centro de Investigación El Mira de la Corporación Colombiana de Investigación Agropecuaria, Tumaco, Nariño, costa pacÍfica de Colombia.
Fig. 2 in Camera Trapping The Indochinese Tiger, Panthera Tigris Corbetti, In A Secondary Forest In Peninsular Malaysia
Fig. 2. Cumulative number of individual tiger captured per month around FELDA Jerangau Barat, Terengganu between April 2000 to September 2000.
Fig. 3 in Camera Trapping The Indochinese Tiger, Panthera Tigris Corbetti, In A Secondary Forest In Peninsular Malaysia
Fig. 3. Identification of tiger individuals from infra-red sensor camera traps. Example of individual identification of tiger cubs (a, b) and adults (c, d) based on stripe patterns.
Linked collectors and determiners for: Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Otonga.
Natural history specimen data linked to collectors and determiners held within, "Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Otonga". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/08a79618-374c-4014-9e71-3194ef3cf69a">https://bionomia.net/dataset/08a79618-374c-4014-9e71-3194ef3cf69a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/08a79618-374c-4014-9e71-3194ef3cf69a">https://gbif.org/dataset/08a79618-374c-4014-9e71-3194ef3cf69a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Bilsa.
Natural history specimen data linked to collectors and determiners held within, "Tropical epiphyte diversity under human impact ? Comparing primary forests, secondary forests, and forest fragments in Ecuador - Bilsa". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0">https://bionomia.net/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0">https://gbif.org/dataset/42962fd5-34ee-4666-abdb-04e8ba4d23b0</a>. Formatted as a Frictionless Data package.
Fig. 1 in Secondary removal of seeds dispersed by gibbons (Hylobates lar) in a tropical dry forest in Thailand
Fig. 1. Distribution of experimental sites where seeds were dispersed by 4 groups of white-handed gibbons (Hylobates lar). Home range maps of the gibbons are based on Light (2016) and Phiphatsuwannachai et al. (2018), plus newly-discovered areas (extended home ranges) by the author. Fruiting trees and gibbon defecation locations were recorded in a GPS. Each site when active contained a camera trap and a paired control/treatment.
Fig 2 in Secondary removal of seeds dispersed by gibbons (Hylobates lar) in a tropical dry forest in Thailand
Fig 2. Estimates of beta-coefficients from binomial regressions with parameter estimates derived from model averaging with 95% confidence intervals. A variable is considered significant if the confidence interval does not overlap zero.
Data and code from paper: The carbon sink of secondary and degraded humid tropical forests
<p>This repository contains the data and code produced for the following paper:</p> <p><strong>Title: </strong>The carbon sink of recovering secondary and degraded humid tropical forests</p> <p><strong>Contact:</strong> Viola Heinrich (viola.heinrich@bristol.ac.uk)</p> <p><strong>Please note:</strong></p> <ul> <li> throughout repository where files include reference to: <...<strong>congo_basin</strong>...> this refers to the <strong>Central Africa </strong>region as it is termed in the main paper.</li> <li>the <strong>code</strong> <strong>has not been amended</strong> for wider use and still contains set working directories for use with University of Bristol systems, you will need to change these for the scripts to run. </li> </ul> <p>The data produced in this project were produced using a combination of programming languages due to differences in the author's preferences and expertise. Overall, the initial data analysis was carried out in (i) Google Earth Engine, and (ii) Arcpy (Python3.6.10). Most of the post-processing of the initial data was then carried out in <strong>R (v3.6) for which the code and output datasets are available here.</strong></p> <p>To access the code used in <strong>Google Earth Engine</strong> that was used to produce and export data from the Tropical Moist Forest dataset (e.g. Years Since Last Disturbance of secondary/degraded forest), please follow the link: https://code.earthengine.google.com/d303fc21e7b57a8fc259e0ee2b58bfb4 </p> <p>This repository contains the following zipped folders:</p> <ul> <li><strong>data_folder</strong>: this folder contains further folders with all the data produced for this paper.</li> </ul> <ol> <li>Fig1_data_models: All data needed to produce Figure 1 of the main paper, including an .RDS version of the 6 main regrowth models produced for this paper (secondary and degraded forests in the three regions). These are the files beginning with "<strong>regrowthModel_..RDS</strong>. Additionally, the folder includes the dataframe files originally from GeoTiff files that were used to extract the Aboveground Biomass in old-growth (undisturbed forests) > e.g. the subfolder "amazon_basin_oldG_AGB" contains the .dbf files representing the AGB in old-growth forest pixels. There are 4 files as the Amazon was split up into 4 sections for computational reasons. Similarly, the Central Africa region (here referred to as congo_basin) was split up into 2 regions.</li> <li>Fig2_data_models_plus_exFig3_to_5: The data needed to produce Figure 2 in the main paper as well as the Extended Data Figures 3 to 5. This includes .RDS versions of the regrowth models for secondary and degraded forests in the three regions for the different variables considered (files beginning with "<strong>regrowthModel_..RDS</strong>) e.g. "regrowtModel_borneo_deg_MaxTemo_low.rds", refers to the regrowth model shown in Figure 2c - the regrowth model for Bornean degraded forests for the variable "Maximum Temperature", where "low" refers to the lowest temperature range considered in the study. As before, files are provided giving information on the AGB in old-growth forests for each region within different conditions of each driving variable. </li> <li>Fig4: All the data needed to produce Figure 4 (and Supplementary Figure 18) of the main paper. This includes the file "regrowth_in_all_basins_by_country_input_data.csv", which contains data on the total number of cells for each forest type for each Years Since Last Disturbance (YSLD) in each region.</li> <li>Extended_dataFig1_input: The input for Extended Data Figure 1, including the values derived from other studies used in this comparison as well as additional notes/comments on how the data were assessed.</li> <li>Extended_dataFig2_input: the input data used to determine the standardised coefficients seen in the Extended Data Figure 2.</li> <li>Extended_data_table_inputs: The inputs for the Extended Data Tables 1 and 2. Inputs include the dataframe files (.dbf), of key variables that were extracted from the GeoTiff files. Only the .dbf files have been included here to limit excessively large data being uploaded. </li> </ol> <ul> <li><strong>code_folder.zip</strong>: The code in this folder was used to produce the main figures and results for the extended data tables shown in the paper. <ul> <li>this folder also contains a file "example_code_read_in_models.R" which provides an example of how best to read in the regrowth models for each region and forest type to extract important information such as the: (i) average growth rate in the first 20 years of analysis, (ii) all AGCs as a function of YSLD, and (iii) the estimated time it takes to reach the asymptote. </li> </ul> </li> </ul> <p><strong>Data and Code usage:</strong> When using any code or data in this repository or another related to this study please cite Heinrich et al. and the original paper as well as the DOI of this repository. </p> <p>Further source data in .xlsx format were also submitted with the main manuscript.</p> <p>If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)</p>
APPENDIX 12 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands
APPENDIX 12. — Relationships of accumulative species number with accumulative sampling efforts for eight largest islands.
FIG. 2 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands
FIG. 2. — Relationships of species richness with number of habitat types, area, elevation, shape irregularity, vegetative cover, and ISW for five bryophyte categories in 168 forest fragments of the Thousand Island Lake, China. The regression equations are derived from GLMMs. Note: ISW, the relative proportion of water within a circle of a diameter of 1000 m centered on a given island.
Riparian buffers provide refugia during secondary forest succession
Open the record for dataset details and reuse information.
Long-term studies of secondary succession and community assembly in the prairie-forest ecotone of eastern Kansas, Old-field succession experiment
Local and regional-scale processes interact to govern the assembly, diversity and functioning of ecological communities. Evaluating the interplay of these differently-scaled processes in the regulation of ecological systems is a challenging problem, but is crucial towards understanding and predicting the potential effects of accelerated human activity on biological diversity and ecosystem sustainability. Since 2000, two long-term field experiments have been underway in grasslands of eastern Kansas to investigate the interplay of soil resource availability, species interactions and regional processes governing plant secondary succession, community assembly, biodiversity, and ecosystem functioning. Both experiments involve manipulations of soil nutrients in permanent grassland study plots and employ multi-species seed addition treatments to evaluate the contribution of dispersal limitation and regional constraints on local species pools to the regulation of plant community dynamics. Old-field succession experiment, previously funded by the National Science Foundation, was initiated in 2001 in a section of the abandoned hay field that was sprayed with herbicide, plowed and disked prior to the start of the study to investigate plant community dynamics in the context of old-field succession initiated on bare soil. The experimental design involves factorial experimental gradients of nitrogen (N) supply (four levels of N fertilization), phosphorus (P) supply (two levels of P fertilization) and plant propagule input achieved by adding seeds of 50+ native and naturalized species to half of the study plots. With annual sampling this experiment allows us to examine old-field succession and community assembly unfolding along gradients of N and P fertilization and under conditions of ambient and experimentally-enriched species pools.
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