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opencc-by-4.0Sep 2018View details →

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.

Fig. 6 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 6. Variation in Equitability (J) and Berger-Parker dominance (DBP) of Diptera (A) and Auchenorrhyncha (B) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Values of J (bars) and DBP (lines) were computed in PAST and 95% confidence intervals obtained by bootstrapping using 9999 random samples. In Kruskal-Wallis H-tests there was a significant difference between the medians for Berger-Parker dominance in Diptera (H = 26.7, p <0.01) and Auchenorrhyncha (H = 14.9, p <0.01). Equitability was significantly different for Diptera (H = 36.5, p <0.01) but not for Auchenorrhyncha (H = 10.7, p = 0.0582).

Fig. 10 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 10. Variation in Mean Monthly Turnover (βwM) of Diptera (A) and Auchenorrhyncha (B) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. The mean value of βwM in each elevation zone ± standard error is indicated. Note that the vertical axis does not extend to zero. In Kruskal-Wallis H-tests there was a significant difference between the medians for Diptera (H = 29.0, p <0.01) and Auchenorrhyncha (H = 22.1, p <0.01).

Fig. 2 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 2. Observed species richness (Sobs) of Diptera and Auchenorrhyncha trapped in six elevation zones over 12 months sampling at Doi Inthanon in 2014. Diptera, open circles; Auchenorrhyncha, closed circles.). In Kruskal-Wallis H-tests there was a significant difference between the medians for Diptera (H = 22.1, p <0.01) and Auchenorrhyncha (H = 14.3, p <0.05).

Fig. 1. Relative abundance, A in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 1. Relative abundance, A* (number of individuals caught. trap-1. month-1) of Diptera and Auchenorrhyncha trapped in six elevation zones over 12 months sampling at Doi Inthanon in 2014. Standard errors indicated. Note log10 scale. Data were fitted to a linear regression model in PAST; Diptera, open circles (r2 = 0.8567, p = 0.0081); Auchenorrhyncha, closed circles (r2 = 0.3182, p = 0.2434). In Kruskal-Wallis H-tests of untransformed data there was a significant difference between the medians for Diptera (H = 29.3, p <0.01) but not for Auchenorrhyncha (H = 3.3, p = 0.657).

Fig. 8 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 8. Variation in species turnover measured as βw of Diptera (a) and Auchenorrhyncha (b) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Pairwise calculations of βw between each quadrat of a grid of elevation and month with the quadrat with maximum species richness (April/1,500–2,000 m quadrat for Diptera and June/500–1,000 m quadrat for Auchenorrhyncha) were mapped using the multiquadric gridding algorithm in the gridding module of PAST. Values of βw (indicated by colour scale bar) vary between 0 (complete identity) and 1.0 (complete non-identity). Data are not available for January and February at <500 m and 500–1,000 m.

Fig. 3. Relative abundance, A in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 3. Relative abundance, A* (number of individuals caught. trap-1. month-1) of Diptera and Auchenorrhyncha over 12 months sampling at Doi Inthanon in 2014. Standard errors indicated. Note log10 scale. In Kruskal-Wallis H-tests of untransformed data there was a significant difference between the medians for Diptera (H = 24.5, p <0.05) and Auchenorrhyncha (H = 34.3, p <0.01).

Fig. 9 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 9. Spatiotemporal variation in species turnover measured as Mean Local Turnover βwL of Diptera (A) and Auchenorrhyncha (B) trapped during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Data were plotted on a grid of elevation zone (vertical axis) and months (horizontal axis) and mapped using the multiquadric gridding algorithm in the gridding module of PAST. Values of βwL (indicated by colour scale bar) vary between 0 (complete identity) and 1.0 (complete non-identity). Data are not available for January and February at <500 m and 500–1,000 m.

Fig. 7 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 7. Monthly variation in Equitability (J) of Diptera assemblages during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Only points linking data from elevation zones 2,000–2,500 m and>2,500 m are connected by lines. Equitability declines profoundly at higher elevations between September and November indicating a decline in evenness of Diptera assemblages with corresponding prevalence of a number of relatively abundant species compared with other times of year and other elevations.

Fig. 5 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand

Fig. 5. Spatiotemporal variation in abundance and species richness of Diptera and Auchenorrhyncha trapped over 12 months sampling over six 500 m elevation zones at Doi Inthanon in 2014. The left panel shows Relative Abundance, A* (number of individuals caught. trap-1. month-1) as log (1+A*) for Diptera (A) and Auchenorryncha (C). The right panel shows observed species richness, S, for Diptera (B) 10 obs and Auchenorryncha (D). Data were plotted on a grid of elevation zone (vertical axis) and months (horizontal axis) and mapped using the multiquadric gridding algorithm in the gridding module of PAST. Values of log10(1+A*) and Sobs are indicated by the colour scale bars. Data are not available for January and February at <500 m and 500–1,000 m.

opencc-by-4.0Dec 2014View details →

Fig. 31. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 700 m in A Systematic Review Of Sulawesi Bunomys (Muridae, Murinae) With The Description Of Two New Species

Fig. 31. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 700 m (in 1976). Examples of Bunomys chrysocomus were caught amid the rocks in the foreground, deep within the forest, and occasionally on trunks and branches spanning the stream. Similar dense streamside forest and bridging trunks and limbs from old treefalls characterize much of the habitat along the Sungai Sadaunta where B. chrysocomus as well as B. karokophilus, n. sp., were encountered (see Natural History in account of B. chrysocomus).

opencc-by-4.0Dec 2014View details →

Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m in A Systematic Review Of Sulawesi Bunomys (Muridae, Murinae) With The Description Of Two New Species

Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m (in 1974). Typical forest composition on terraces just above the stream: dense undergrowth of shrubs and tree saplings, woody vines looping through the understory. Beneath the dense cover, the ground is wet, the air cool. Most Bunomys chrysocomus were trapped in this kind of stream terrace habitat, either on the ground beneath the shrubs, alongside decomposing, moss-covered trunks and limbs lying on the terrace, or among moss-covered rocks. Bunomys karokophilus, n. sp., was encountered in similar habitat.

opencc-zeroSep 2021View details →

Active restoration fosters better recovery of tropical rainforest birds than natural regeneration in degraded forest fragments

<ol> <li>Ecological restoration has emerged as a key strategy for conserving tropical forests and habitat specialists, and monitoring faunal recovery using indicator taxa like birds can help assess restoration success. Few studies have examined, however, whether active restoration achieves better recovery of bird communities than natural regeneration, or how bird recovery relates to habitat affiliations of species in the community.</li> <li>In rainforests restored over the past two decades in a fragmented landscape (Western Ghats, India), we examined whether bird species richness and community composition recovery in 23 actively restored (AR) sites was significantly better than recovery in paired naturally regenerating (NR) sites, relative to 23 undisturbed benchmark (BM) rainforests. We measured 8 habitat variables and tested whether bird recovery tracked habitat recovery, whether rainforest and open-country birds showed contrasting patterns, and assessed species-level responses to restoration.</li> <li>We recorded 92 bird species in 460 point-count surveys. Rainforest bird species richness was highest in BM, intermediate in AR, and lowest in NR. Contrastingly, open-country bird species richness was least in BM, intermediate in AR, and highest in NR.</li> <li>Bird community composition varied significantly across treatment types with composition in AR in transition from NR to BM. Bird community dissimilarity between sites was positively related to dissimilarity in habitat structure and floristics, and geographic distance between sites. Variance partitioning indicated that structural and floristic dissimilarity explained 90% of the variation in community composition.</li> <li>Indicator species analysis revealed significant associations of 34 species with one or more treatment types. Species associated with BM and AR treatment types were all rainforest species, while only 38% of species associated with AR and NR treatment types were rainforest species.</li> <li> Synthesis and applications: We show that active restoration of degraded fragments benefits rainforest birds and reduces the infiltration of open-country birds, and highlight the importance of considering rainforest and open-country species separately. In human-modified tropical rainforest landscapes, active restoration of degraded fragments fosters partial recovery and complements protection of mature forests for bird conservation.</li> </ol>

opencc-by-4.0Dec 2022View details →

Data from: Plant Community Structure in Tropical Rain Forest Fragments of the Western Ghats, India

DESCRIPTIONThis dataset includes vegetation plot data on trees, lianas, understorey plants, and regeneration, and related data and species name matching files in five rainforest sites collected in 2003 as part of the following study:MUTHURAMKUMAR, S., AYYAPPAN, N., PARTHASARATHY, N., MUDAPPA, D., RAMAN, T. R. S., SELWYN, M. A. & PRAGASAN, L. A. 2006. <a href="http://doi.org/10.1111/j.1744-7429.2006.00118.x">Plant community structure in tropical rain forest fragments of the Western Ghats, India</a>. Biotropica 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.xThe regeneration data were analysed and presented in the following publication and related dataset:OSURI, A. M., CHAKRAVARTHY, D., MUDAPPA, D., RAMAN, T. R. S., AYYAPPAN, N., MUTHURAMKUMAR, S. & PARTHASARATHY, N. 2017. Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India. Journal of Tropical Ecology 33(4): 270-284. DOI: <a href="http://doi.org/10.1017/S0266467417000219">10.1017/S0266467417000219</a>OSURI, A. M., CHAKRAVARTHY, D., MUDAPPA, D., RAMAN, T. R. S., AYYAPPAN, N., MUTHURAMKUMAR, S. & PARTHASARATHY, N. 2017. <a href="http://doi.org/10.5061/dryad.vd0nn">Data from: Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India</a>, Dryad, Dataset, https://doi.org/10.5061/dryad.vd0nn CONTACTSCONTACT #1 1. Name: <a href="https://orcid.org/0000-0002-1347-3953">T. R. Shankar Raman</a> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Work Phone: +91 821 2515601 4. Email address: trsr@ncf-india.org 5. ORCID: https://orcid.org/0000-0002-1347-3953CONTACT #2 1. Name: <a href="https://orcid.org/0000-0001-9708-4826">Divya Mudappa</a> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Work Phone: +91 821 2515601 4. Email address: divya@ncf-india.org 5. ORCID: https://orcid.org/0000-0001-9708-4826CONTACT #3 1. Name: <a href="https://orcid.org/0000-0001-9909-5633">Anand M. Osuri</a> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India 3. Work Phone: +91 821 2515601 4. Email address: aosuri@ncf-india.org 5. ORCID: https://orcid.org/0000-0001-9909-5633CONTACT #4 1. Name:  <a href="https://orcid.org/0000-0003-4383-557X">N. Ayyappan</a> 2. Work Address: French Institute of Pondicherry, No. 11, Post Box No. 33, Saint Louis Street, Pondicherry – 605 001, India. 3. Work Phone: + 91- 413-2231616 4. Email address: ayyappan.n@ifpindia.org 5. ORCID: https://orcid.org/0000-0003-4383-557XCONTACT #5 1. Name:  <a href="https://orcid.org/0000-0002-7791-8499">S. Muthuramkumar</a> 2. Work Address: V.H.N.S.N. College, 3/151-1, College Road, Virudhunagar - 626001, Tamil Nadu, India. 3. Work Phone: + 91-4562-280154 4. Email address: muthuramkumar@vhnsnc.edu.in 5. ORCID: https://orcid.org/0000-0002-7791-8499CONTACT #6 1. Name:  <a href="https://orcid.org/0000-0002-4172-5441">N. Parthasarathy</a> 2. Work Address: Department of Ecology and Environmental Sciences, Pondicherry University, R Venkat Raman Nagar, Kalapet, Pondicherry 605014, India 3. Work Phone: + 91-413-2654326 4. Email address: parthapu@yahoo.com 5. ORCID: https://orcid.org/0000-0002-4172-5441 KEYWORDSAnamalai hills; biodiversity hotspot; disturbance; endemics; fragmentation; lianas; plant conservation; tree diversity; tropical rain forest; understory plants. GEOGRAPHIC COVERAGE1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E) TEMPORAL COVERAGE1. Begins: 2003-03-01 (Year, Month, Day) 2. Ends: 2003-04-30 (Year, Month, Day) METHODSMethods involved systematic vegetation plots for trees, lianans and understorey plants as described in Muthuramkumar et al. 2006 (Biotropica 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.x) and for tree and woody regeneration as described in Osuri et al. 2017 (Journal of Tropical Ecology 33(4): 270-284. DOI: 10.1017/S0266467417000219). The vegetation sampling methods are briefly described below.The present study was conducted in five tropical wet evergreen forest fragments located on the Valparai plateau (Fig. 1): Akkamalai (AK, 2600 ha), Upper Manamboli (UM, 100 ha), Lower Manamboli (LM, 100 ha), Tata Finlay (TF, 32 ha), and Injipara (IP, 18 ha).In each site, vegetation was sampled in randomly placed noncontiguous plots of 20 × 20 m located at least 50 m apart and at least 20 m into the fragment interior from the edges, major trails, or roads. We sampled 20 plots each in IP, TF, and LM, and 25 plots each in UM and AK. Within each plot, all trees ≥30cm girth at breast height (gbh, at 1.3 m; corresponding to DBH of 9.55 cm) and lianas ≥1 cm diameter at breast height (DBH) were identified to species, counted, and their girth/diameter measured. For multi-stemmed trees bole girths were measured separately, basal area calculated and summed. Each 20 x 20 m plot was divided into four 10 × 10 m quarters.For understory plants, 2 × 2 m quadrats were laid at the four corners of the 20 × 20 m plot (one in each of the corresponding four quarters) and all shrubs, undershrubs, herbs, ferns, and small twiners found within the quadrats were enumerated and identified. The regeneration sampling was done in a 5 × 5-m plot (0.0025 ha) placed at the outer corner of the first (south-west) quarter of the 20 x 20 m plot. Within each regeneration plot, we identified, counted and measured all tree saplings >1 cm diameter at breast height (dbh, at 1.3 m) and <9.55 cm dbh (equivalent to <30 cm girth at breast height, gbh). Woody shrubs of 1–9.55 cm dbh were alsorecorded in the regeneration plots (but these were excluded in the Osuri et al. 2017 analysis).For vegetatively propagating plants a clump of stems that is basally connected was considered as one individual. Canopy height was measured with a range finder and canopy closure was measured using a spherical densiometer. Vouchers were identified with regional flora and confirmed with the Western Ghats collections available in the herbarium of Salim Ali School of Ecology, Pondicherry University, from our previous works in the region. ACKNOLWEDGEMENTSFunders and other supporters of the research are acknowledged in the original publications. The compilation and publication of this dataset was carried out as part of an NCF project supported by Fondation Franklinia. FILES INCLUDEDBesides the 00_README.txt file that contains this metadata, the dataset includes the following 11 files, whose details and contents are explained below. 01_all_sites.csvDescription: The file contains details of the five study sites (three continuous forest and two forest fragment sites).   Note: Current Name of TF (Tata Finlay) site is Old Valparai, current name of Akkamalai (AK) is Iyerpadi-Akkamalai complex. Sites and codes correspond to the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x).Column names and descriptions: eventDate: Date range when sampling was carried out in the sites old_sitename: Name of the site as used in the Muthuramkumar et al. (2006) paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x) sitecode: Site code as used in the Muthuramkumar et al. (2006) paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x) site: Site name as at present and used in this dataset decimalLatitude: latitude in decimal degrees North decimalLongitude: longitude in decimal degrees East geodeticDatum: Geodetic Datum WGS 84 coordinateUncertaintyInMeters: Uncertainty in metres of the GPS location (as only one location available for entire site where points were distributed) type: Indicates whether site was continuous rainforest or rainforest fragment Area_ha: Area in hectares Altitude_min_m: Minimum altitude in metres of sampled plots Altitude_max_m: Maximum altitude in metres of sampled plots Ownership: Whether site is in privately owned land or within state-protected reserve Average_canopy_height_m: average canopy height in metres Canopy_closure_%: estimated canopy closure in percentage Nearby_plantations: Adjoining plantations 02_all_trees_adult_data.csvDescription: The file contains records of all adult trees >= 30 cm girth at breast height of 1.3 m (gbh) recorded within 20 m x 20 m plots across three continuous forests and two forest fragments.Note: Same as in the Osuri et al. (2017) dataset (https://doi.org/10.5061/dryad.vd0nn), with Tithonia diversifolia added back in Injipara and data from one additional site (Manamboli Lower) added back from the original dataset corresponding to the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x).   Column names and descriptions: x: Row index site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site q_no: An unique number assigned to each of four 10m x 10m quarters within each adult plot t_no: An unique number assigned to each individual tree within each site. old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset) osuri_code: Revised species codes used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) current_code: Species codes used at present gbh_1 to gbh_16: Girth at breast height of single- (gbh_1) and multi-stemmed (gbh_2 – gbh_16) individuals, measured in centimetres (cm) P_ID: Unique plot ID created by combining columns site and plot_no 03_all_liana_data.csvDescription: The file contains records of all lianas >= 1 cm diameter at breast height of 1.3 m (dbh) recorded within 20 m x 20 m plots across three continuous forests and two forest fragments.Note: Lianas were not included in the Osuri et al. (2017) dataset (https://doi.org/10.5061/dryad.vd0nn).Column names and descriptions: x: Row index site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site q_no: An unique number assigned to each of four 10m x 10m quarters within each adult plot t_no: An unique number assigned to each individual tree within each site. old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset) osuri_code: Indicated as NA since these data were not used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) current_code: Species codes used at present dbh_1 to dbh_11: Diameter at breast height of single- (dbh_1) and multi-stemmed (dbh_2 – dbh_11) individuals, measured in centimetres (cm)     P_ID: Unique plot ID created by combining columns site and plot_no 04_all_herbs_data.csvDescription: The file contains records of all understorey plants (shrubs, undershrubs, herbs, ferns, and small twiners) recorded in 2 m × 2 m quadrats laid at the four corners of each 20 m × 20 m plot in three continuous forests and two forest fragments.Note: Understorey plants were not included in the Osuri et al. (2017) dataset (https: //doi.org/10.5061/dryad.vd0nn).Column names and descriptions: x: Row index site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m plot within each site corner_no: An unique number assigned to each of four 2 m x 2 m quadrat laid at the four corners of the 20 m x 20 m plot t_no: A number assigned to each individual species recorded within the corner plot. old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset) osuri_code: Indicated as NA since these data were not used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) current_code: Species codes used at present count: Number of individuals counted (for vegetatively propagating plants a clump of stems that was basally connected was considered as one individual) P_ID: Unique plot ID created by combining columns site and plot_no 05_all_regeneration_data.csvDescription: The file contains records of woody seedlings and saplings (1-5 cm diameter at breast height at 1.3 m, dbh) and larger-stemmed trees (>5 cm dbh) recorded within single 5 m x 5 m regeneration plots nested within 20 m x 20 m plots. Plots were located in three continuous forests and two forest fragments. Data were filtered during analysis in Osuri et al. (2017, Journal of Tropical Ecology) to retain only seedling and saplings, defined as individuals with effective diameter <=5 cm.Note: Same as in the Osuri et al. (2017) dataset, with Tithonia diversifolia added back in Injipara from original dataset; and data from one additional site (Manamboli Lower) added back from the Muthuramkumar et al. 2006 dataset.   Column names and descriptions: x: Row index site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site q_no: The 5 m x 5 m plot was placed in the SW corner of the 20 m x 20 m plot in this q_no which indicates one of the four 10 m x 10 m quarters of the 20 m x 20 m plot, where each quarter was given a unique number in each site t_no: An unique number assigned to each individual seedling, sapling or tree within each site. old_code: Species codes used at the time of data collection (for full species names refer to 06_all_species_names.csv file with this dataset) osuri_code: Revised species codes used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) current_code: Species codes used at present dbh_1 to dbh_12: Diameter at breast height of single- (dbh_1) and multi-stemmed (dbh_2 – dbh_12) individuals, measured in centimetres (cm)     eff_dbh: Effective diameter at breast height (cm)- calculated as ((dbh)^2 +(dbh_1)^2 +...+(dbh_12)^2)^(1/2), P_ID: Unique plot ID created by combining columns site and plot_no 06_all_canopy_readings.csvDescription: The file contains canopy-related measurements taken in each 20 m × 20 m plot in three continuous forests and two forest fragments.Note: Units of light meter reading were not recordedColumn names and descriptions: site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site reading: A number assigned to the 1 to 4 readings taken in each plot light: Light measurement taken with a light meter in the plot canopy_openness: Canopy openness (scored from 0-100%) using a spherical densiometer (Canopy cover = 100 - canopy openness) P_ID: Unique plot ID created by combining columns site and plot_no 07_all_extracanopy_trees_data.csvDescription: The file contains records of additional trees outside the 5 x 5 m plot whose canopy was overhead of the plot.Note: Species codes are used to denote presence (not count of stems) of that species in the overhead canopy.Column names and descriptions: site: Name of forest site plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site q_no: The 5 m x 5 m plot was placed in the SW corner of the 20 m x 20 m plot in this q_no which indicates one of the four 10 m x 10 m quarters of the 20 m x 20 m plot, where each quarter was given a unique number in each site old_code: Species codes used at the time of data collection (for full species names refer to 06_all_species_names.csv file with this dataset) osuri_code: Revised species codes used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) current_code: Species codes used at present P_ID: Unique plot ID created by combining columns site and plot_no 08_all_species_names.csvDescription: This file provides species codes and species scientific names as originally used in the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x), and as matched with the Global Biodiversity Information Facility (GBIF) species name matching toolNote: For plots that had no species occurrences (old_code = No herbs, Noliana), NA has been used for other columnsColumn names and descriptions: group: Code indicating main dataset group where species occurs (tree and regeneration data, liana data, understorey plants data) old_code: Species codes used at the time of data collection (refer to traits data file for full species names) osuri_code: Revised species codes if used in the Osuri et al. 2017 paper in Journal of Tropical Ecology 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) or else indicated as NA current_code: Species codes used at present original_name: Scientific name of plant species as used at the time of the original publication (Muthuramkumar et al. 2006) original_fullname: Scientific name and authorship of plant species as used at the time of the original publication (Muthuramkumar et al. 2006) original_family: Family of the plant species as used at the time of original publication GBIFname: Scientific name as matched by GBIF species name matching tool key: GBIF name matching tool key number matchType: Type of match confidence: Confidence returned by name matching tool status: Whether accepted name or synonym rank: Taxanomic rank (level) to which identified kingdom: Taxonomic Kingdom phylum: Taxonomic Phylum class: Taxonomic Class order: Taxonomic Order family: Taxonomic Family genus: Taxonomic Genus species: Taxonomic Species canonicalName: Canonical part of scientific name matched by GBIF authorship: Authorship of scientific name matched by GBIF scientificName: Current scientific name (from species, genus, or family columns) 09_tabula_Biotropica_appendix1.csvDescription: This file contains tabled values extracted from Appendix 1 of Muthuramkumar et al. 2006 paper in Biotropica (DOI: 10.1111/j.1744-7429.2006.00118.x); extraction from PDF carried out using Tabula software (https://tabula.technology/)Note: Last 5 columns contain total abundance (count of individuals/stems) in the corresponding site.Column names and descriptions: slno: serial number habit: Plant habit indicating trees, lianas, or understorey plants species: species name as used in Appendix 1 of Muthuramkumar et al. 2006 asterisk: species endemic to Western Ghats are indicated by an asterisk (∗ ), and invasive species by double asterisk (∗∗ ). voucher_number: voucher number of herbarium specimen deposited in the herbarium of Salim Ali School of Ecology, Pondicherry University, India. family: plant family as in Appendix 1 Iyerpadi-Akkamalai: abundance (total number of individuals counted) in this site Manamboli_Upper: abundance (total number of individuals counted) in this site Manamboli_Lower: abundance (total number of individuals counted) in this site Old_Valparai: abundance (total number of individuals counted) in this site Injipara: abundance (total number of individuals counted) in this site 10_Muthuramkumar et al 2006_Abstract and Appendix 1_extract_Biotropica.pdfExtracted PDF of first page with Abstract and Appendix 1 of Muthuramkumar et al. 2006 (DOI: 10.1111/j.1744-7429.2006.00118.x). 11_figure_1_Biotropica_paper.jpgJPEG image of Figure 1 (map of study area) from the following publication: MUTHURAMKUMAR, S., AYYAPPAN, N., PARTHASARATHY, N., MUDAPPA, D., RAMAN, T. R. S., SELWYN, M. A. & PRAGASAN, L. A. 2006. Plant community structure in tropical rain forest fragments of the Western Ghats, India. Biotropica 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.x

opencc-zeroJan 2023View details →

High-resolution tropical rain-forest canopy climate data

Canopy habitats challenge researchers with their intrinsically difficult access. The current scarcity of climatic data from forest canopies limits our understanding of the conditions and environmental variability of these diverse and dynamic habitats. We present 307 days of climate records collected between 2019 and 2020 in the tropical rainforest canopy of the Yasuní National Park, Ecuador. We monitored climate with a 10-minute temporal resolution in the middle crowns of eight canopy trees. The distance between canopy climate stations ranged from 700 m to 10 km. Apart from air temperature, relative humidity, leaf wetness, and photosynthetically active radiation (PAR), measured in each canopy climate station, global radiation, rainfall, and wind speed were measured in different subsets of them. We processed the eight data series to omit erroneous records resulting from sensor failures or lack of the solar-based power supply. In addition to the eight original data series, we present three derived data series, two aggregating canopy climate for valleys or for ridges (from four stations each), and one overall average (from the eight stations). This last derived data series contains 306 days, while the shortest of the original data series covers 22 days and the longest 296 days. In addition to the data, two open-source tools, developed in RStudio, are presented that facilitate data visualization (a dashboard) and data exploration (a filtering app) of the original and aggregated records.

opencc-by-4.0Jan 2023View details →

Tropical cyclones facilitate recovery of forest leaf area from dry spells in East Asia

This online repository copies the source code and the download link of the input data for the research work of analyzing forest leaf area change due to the TC activities in the west pacific ocean basin.  TC Track data, mask, climate reanalysis, leaf area, ERA5 (wind speed, surface pressure data), and SPEI dataset:  <a href="http://YYCdb.synology.me:5833/sharing/YizTR8HPR">http://YYCdb.synology.me:5833/sharing/YizTR8HPR</a> password:bg-2022-115 File size: 373G The path for downloading the source code/script for analyzing the LAI changes: <a href="http://YYCdb.synology.me:5833/sharing/JC2AGt9Kh">http://YYCdb.synology.me:5833/sharing/JC2AGt9Kh</a> password:bg-2022-115 File size: 880M Data table for all events used in this study: <a href="http://YYCdb.synology.me:5833/sharing/MqA4YFBHk">http://YYCdb.synology.me:5833/sharing/MqA4YFBHk</a> password:bg-2022-115 Filesize:824K

opencc-by-4.0Nov 2022View details →

Data and code from paper: The carbon sink of secondary and degraded humid tropical forests

This repository contains the data and code produced for the following paper: Title: The carbon sink of recovering secondary and degraded humid tropical forests Contact: Viola Heinrich (viola.heinrich@bristol.ac.uk) Please note: <ul> <li> throughout repository where files include reference to: <...congo_basin...> this refers to the Central Africa region as it is termed in the main paper.</li> <li>the code has not been amended 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> 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 R (v3.6) for which the code and output datasets are available here. To access the code used in Google Earth Engine 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  This repository contains the following zipped folders: <ul> <li>data_folder: 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 "regrowthModel_..RDS. 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 "regrowthModel_..RDS) 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>code_folder.zip: 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> Data and Code usage: 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.  Further source data in .xlsx format were also submitted with the main manuscript. If you need anything else, please contact the corresponding author: Viola Heinrich (viola.heinrich@bristol.ac.uk)

opencc-zeroFeb 2023View details →

The relationship between plant diversity and facilitation during tropical dry forest restoration

Restoration programs that promote the functioning of restored ecosystems are in urgent demand. Although several biodiversity and ecosystem functioning (BEF) experiments have demonstrated the importance of functional complementarity enhancing plant community performance, no BEF study has yet experimentally manipulated facilitation testing its contribution to how the complementarity effect modulates community performance. We built a restoration experiment manipulating diversity and facilitation in a tropical semiarid forest. We planted 4704 seedlings of 16 native tree species to assemble 147 experimental communities with 45 different compositions comprising 1, 2, 4, 8 or 16 species. Facilitation was included in the experimental design by creating a gradient of communities from low to high facilitation potential (based on prior research). We measured functional diversity and functional identity using species above and below-ground traits to investigate how they modulate the effects of species diversity and facilitation on leaf biomass production, and its additive partition biodiversity effects (NE, CE & SE). The joint influence of diversity and facilitation was tested separately for leaf biomass production and Net Biodiversity Effect using Linear Mixed Models (LMMs). We subsequently ran LMMs including functional diversity and functional identity. We hypothesised that facilitation would increase community productivity and functioning and that functional dispersion and functional identity related to above and below-ground traits would explain facilitation performance. Facilitation positively influenced leaf biomass production as predicted, but unexpectedly, neither of the functional traits were important for modulating the facilitation process. Positive values for Complementarity Effect (CE) showed that plants performed better in mixtures in comparison to monocultures. Selection Effect (SE) negative values, showed that species with below-average performance in monocultures, performed better in mixtures. Unexpectedly, CE did not increase as species diversity or facilitation increased. SE was influenced negatively by facilitation leading to a more equal distribution of biomass production between species in mixtures. Synthesis: Facilitation improves biomass production in restored communities and increases biomass equitability among plant species and thus ecosystem reliability. To improve restoration success, plant communities should be built using facilitating plants.

opencc-zeroFeb 2023View details →

Nutrient-based species selection is a prevalent driver of community assembly and functional trait space in tropical forests

1. Soil nutrient availability and functional traits interact in complex ways during the assembly of tree communities hindering our understanding of the implications that this may have for their phylogenetic and functional diversity. 2. We combined abundance, taxonomic, phylogenetic and functional trait data of 222 tree species distributed along nutrient concentration gradients at twenty-four plots in two tropical forest study sites. We analysed micro and macronutrient concentration in organic and topsoil horizons and tested for: (1) nutrient-based species sorting due to contrasting trait-environment relationships; (2) whether nutrient filtering has consequences for phylogenetic and functional diversity, and functional space size and occupancy; and (3) we mapped trait distributions across the phylogeny of tree species to track the evolutionary signature of nutrient availability. 3. We found that total nitrogen (N), available phosphorus and total potassium in soil accounted for 68% of the variation in tropical tree species community composition, with strong associations with nutrient concentration for 89% of the tree species included in the analysis. This nutrient-based species selection was mediated by interactions between the three soil nutrient concentrations with leaf nitrogen, leaf thickness and wood density. Soil N concentration was positively associated with the functional space at the site level. At a plot level soil N concentration positively correlated with functional evenness and it was negatively associated with the functional space not occupied by any species in the tree community. Despite the phylogenetic conservatism of leaf N across tree lineages even when not considering legumes, many sister-species pairs show contrasting values which match with their habitat preferences thus indicating the evolutionary lability of this trait, particularly within recently diversified clades. 4. Synthesis. Our results demonstrate that soil nutrient-based species selection is a prevalent driver of community assembly in tropical forests, a process mediated by key functional traits within the leaf and wood economics spectrum. Functional space size and its filling increase with soil nutrient concentration, whereas niche vacancy decreases. This selection process has likely influenced tropical tree species diversification patterns via habitat specialization.