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Fig. 4 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 4. EZPAE down-weighted against homoplasy, using altitudinally zoned mountain ranges as OGU, 'characters' made non-additive. Strict consensus tree of four equally parsimonious trees (CI = 0.674, 0.580) produced by maximum parsimony analysis with weighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes. Alphabetic codes of termini correspond with mountain ranges as abbreviated in Fig. 3; the suffixes 'low' & 'high' refer to low (<1,250m) and high (>1,250m) sample data.

Fig. 2. PAE using 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 2. PAE using 1° grids as OGU. Strict consensus tree of 760 equally parsimonious trees (CI = 0.501, RI = 0.557) produced by maximum parsimony analysis with unweighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes (see Fig 1A for explanation of alphabetic codes).

Fig. 3 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 3. PAE using mountain ranges as OGU. Strict consensus tree of nine equally parsimonious trees (CI = 0.745, RI = 0.722) produced by maximum parsimony analysis with weighted 'characters' and implicit enumeration in TNT. Symmetrical resampling support is given under the nodes. Abbreviations. – CM, Cardamom Mountains; DK, Dong Paya Yen – Khao Yai Forest Complex; DL, Daen Lao Range; LP, Luang Prabang Range; NST, Nakhon Si Thammarat Range; PM, Petchabun Mountains; PR, Phuket Range; PPR, Phu Pan Range; TH, Tenasserim Hills; TT, Thanon Thongchai Range. Grid-B and Grid-L refer to 1° grids (B and L in Fig. 1A) that were not assigned to any mountain range.

Fig. 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 1. Maps of Thailand showing: A, Grid of 1° of latitude and longitude denoted by single-letters A–W. Mountain ranges are indicated by two- or three letter codes (CD, DK, DL, LP, NST, PM, PPR, PR, TH & TT) and the grids that comprise each range are colour-coded. Grids B and L were not assigned to any mountain range; B, Species richness (number of species) of Hybos present in 1° grids; C, reciprocal weighted endemicity of Hybos spp. calculated for 1° grids.

opencc-by-4.0Sep 2018View details →

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.

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.

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

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Data from: Successional shifts in tree demographic strategies in wet and dry Neotropical forests

This dataset summarizes demographic rates, abundances and basal area across a succession of ~800 (sub) tropical tree species to explore generalities in demographic trade-offs and successional shifts in demographic strategies across four Neotropical forests that cover a large rainfall gradient. We used repeated forest inventory data from chronosequences in two wet (Costa Rica, Panama) and two dry forests (Yucatán, Oaxaca, both Mexico) to quantify demographic rates of ~800 tree species. For each forest, we explored the main demographic trade-offs and assigned tree species to five demographic groups by performing a weighted Principal Component Analysis (PCA) that accounts for differences in sample size. We aggregated the basal area and abundance across demographic groups to identify successional shifts in demographic strategies over the entire successional gradient from very young (<5 years) to old-growth forests. This dataset provides raw and transformed demographic rates, their weights in the weighted PCA, assignments to demographic groups, and forest inventory data at the species level, as well as the code for performing the weighted PCA.

opencc-zeroDec 2022View details →

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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 →

FIG. 6 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 6. — Bryophytes species distributions along an elevational gradient in Catimbau National Park according to life history traits: A, light requirements; B, life-forms. TABLE 3. — Spearman (Rs) correlation table between life history traits showing that light demanding and life-forms are correlated with the species richness in base and top of elevational gradient, respectively. Italic font indicates Spearman value and normal font indicates Spearman coefficient (Rs). P-value in bold are significant (p <0.05).

FIG. 3 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 3. — The effects of altitude decomposed into three elevational belts on bryophyte richness. Model based on the Poisson distribution and log connection method for unprocessed data. Own illustration: Fabronia ciliaris (Brid.) Brid.

FIG. 5 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 5. — Principal Component Analysis (PCA) based on the substrates colonized along elevational gradient in Catimbau National Park.

FIG. 1 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 1. — Results of the clustering with weighted average between Caatinga areas (including rocky outcrops) based on the Sørensen similarity index showing that the bryophyte flora of Catimbau NP is singular: dotted arm indicates Rocky outcrop in Bahia state; brackets in light gray indicates areas in Paraíba state and the bold arms indicate the areas in Pernambuco state; site P29, highlighted in blue shows the isolation of Catimbau NP. Bahia state is approximately 370 km from Pernambuco state and 930 km from Paraíba, in a straight line. Coefficient of Cofenetic Correlation (CCC) = 0.80. Own illustration: Fabronia ciliaris (Brid.) Brid.

FIG. 4 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 4. — Venn diagram showing the low percentage of similarity between the belts levels based on the Sørensen-Dice index, total number of species per belt, and the amount of species shared between each belt.

FIG. 2 in A small elevational gradient shows negative bottom-to-top bryophyte richness in a seasonally dry forest in Brazil

FIG. 2. — Elevational distribution and representativeness of bryophyte families in the Catimbau National Park. The width of the bars denotes the number of species per family. The elevation is measured in meters.

opencc-zeroJun 2023View details →

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Seed dispersal syndrome predicts ethanol concentration of fruits in a tropical dry forest

Studying fruit traits and their interactions with seed dispersers can improve how we interpret patterns of biodiversity, ecosystem function, and evolution. Mounting evidence suggests that fruit ethanol is common, variable, and may exert selective pressures on seed dispersers. To test this, we comprehensively assess fruit ethanol content in a wild ecosystem and explore sources of variation. We hypothesise that both phylogeny and seed dispersal syndrome explain variation in ethanol levels, and we predict that fruits with mammalian dispersal traits will contain higher levels of ethanol than those with bird dispersal traits. We measured ripe fruit ethanol content in species with mammal- (n = 16), bird- (n = 14), or mixed-dispersal (n = 7) syndromes in a Costa Rican tropical dry forest. Seventy-eight percent of fruit species yielded measurable ethanol concentrations. We detected a phylogenetic signal in maximum ethanol levels (Pagel's λ = 0.82). Controlling for phylogeny, we observed greater ethanol concentrations in mammal-dispersed fruits, indicating that dispersal syndrome helps explain variation in ethanol content and that mammals may be more exposed to ethanol in their diets than birds. Our findings further our understanding of wild fruit ethanol and its potential role as a selective pressure on frugivore sensory systems and metabolism.

opencc-by-4.0Jul 2023View details →

Fig. 8. Peruvian vegetation types. A. Amazonian forest, Pasco Region. B. Northwest Peruvian montane forest, Piura Region. C. Dry forest, Piura Region. D in The genus Begonia (Begoniaceae) in Peru

Fig. 8. Peruvian vegetation types. A. Amazonian forest, Pasco Region. B. Northwest Peruvian montane forest, Piura Region. C. Dry forest, Piura Region. D. Lomas, Lima Region. All photographs taken by P.W. Moonlight.

opencc-zeroAug 2023View details →

FIG. 3 in New species of lichen for Colombia tropical dry forest

FIG. 3. — Pyrenula gigaspora Soto-Medina, Aptroot & Lücking, sp. nov.: A, habitus; B, ascospores. Scale bars: A, 10 mm; B, 20 μm.

opencc-zeroAug 2023View details →

FIG. 2 in New species of lichen for Colombia tropical dry forest

FIG. 2. — Ocellularia vallensis Soto-Medina & Lücking, sp. nov.: A, habitus; B, C, ascospores. Scale bars: A, 10 mm; B, C, 10 μm.