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opencc-by-4.0Apr 2013View details →

Supplementary material 2 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190

Supplementary material 2 from: Spafford R, Lortie C, Butterfield B (2013) A systematic review of arthropod community diversity in association with invasive plants. NeoBiota 16: 81-102. https://doi.org/10.3897/neobiota.16.4190

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Data from: Mycorrhizal symbiosis increases plant phylogenetic diversity and regulate community assembly

The intricate mechanisms shaping plant diversity and community composition are the cornerstone of ecological understanding. Yet, the role of mycorrhizal symbiosis, the fundamental partnership between fungi and plant roots, in influencing community composition has often been underestimated. Here, we use extensive species survey data from 1,315 terrestrial ecosystem sites to elucidate the influence of mycorrhizal symbiosis on plant phylogenetic diversity and its implications for community assembly processes. Our findings demonstrate that increasing mycorrhizal symbiotic potential leads to greater phylogenetic dispersion within plant communities. Furthermore, we unveil a distinct dichotomy in the assembly processes governed by mycorrhizal status. Mycorrhizal species predominantly influence deterministic processes, suggesting a role in niche-based community assembly. Conversely, non-mycorrhizal species exert a stronger influence on stochastic processes, highlighting the importance of random events in shaping community structure. These results underscore the crucial but often hidden role of mycorrhizal symbiosis in driving plant community diversity and assembly. This study provides valuable insights into the complex mechanisms shaping ecological communities and the way for more informed conservation and management practices that acknowledge the complex interplay between symbiosis and ecological community dynamics.

opencc-zeroJun 2024View details →

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Supplementary data from: Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic

The Arctic ecosystems and their species are exposed to amplified climate warming and, in some regions, to rapidly developing economic activities. We used macroecological modeling to estimate the community-level species richness across the Western Siberian tundra, with climate variables and anthropogenic influence identified as main explanatory factors. Our results reveal complex spatial patterns of community-level species richness in the Western Siberian Arctic. We show that climatic factors such as temperature (including paleotemperature) and precipitation are the main drivers of plant species richness in this area, and the role of relief is clearly secondary. Here we present a supplementing dataset to the analysis of our paper "Current and past climate co-shape community-level plant species richness in the Western Siberian Arctic" (<a href="https://doi.org/10.1002/ece3.11140">https://doi.org/10.1002/ece3.11140</a>). Our research is based on the Western Siberian part of the Russian Arctic Vegetation Archive (AVA-RUS, <a href="http://avarus.space">http://avarus.space</a>), with 1483 Braun-Blanquet plots observed from 2005-2018. The dataset contains geolocated species richness data along with sampled raster data on environmental and anthropogenic predictors used for modeling. The scripts are used for paleoclimatic data sampling; testing univariate predictive performance and limited collinearity for all predictors; fitting four different modes: random forest, gradient boosting machine, generalized linear model, and generalized additive model; their validation and projection. Detailed information regarding the data structure and the applied methods could be found in the paper.

opencc-zeroJul 2024View details →

Figure 3 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 3. Alfa rarefaction curve observed based on observed species (OTUs) value. The curve has shown flatter to the right, which indicates the comparatively high species richness of the senna italica samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 1 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 1. (A) Results of clustering: Assembling a group of organisms (The organisms in the same group are similar). (B) The number of OTUs generated for each sample. The Root.1 sample had the most OTUs of 24, while the Leave.1 sample had the fewest of 13. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 5 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan

Figure 5. CCA plot Analysis of illustrating the influence of elevation on spreading pattern of plant communities in Lalkoo valley Swat.

Figure 6. A in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 6. A. The phylum level in Bacteria (bar chart), the bacterial composition of the different samples was similar, while the distribution of each phylum varied in all samples. Based on the V3-V4 region of the 16S rRNA region. Bacterial communities at the phylum classification among the samples (pie chart), as a percentage of the total bacteria isolated from roots and leaves endophyte region. Based on the full-length 16S rRNA sequences. (B) The number of Actinobacteria among the samples. (C) The number of Proteobacteria among the samples. (D) The number of unclassified phyla among the samples. (E) The number of Firmicutes phyla among the samples. (F) The number of Cyanobacteria/Chloroplast among the samples. Roots samples: Roots.1, Roots.2, and Roots.3. Leaves samples: Leaves.1, Leaves.2, and Leaves.3 are associated with Senna italica.

Figure 4 in Composition and structure of plant communities in the Moist Temperate Forest Ecosystem of the Hindukush Mountains, Pakistan

Figure 4. Results of CCA joint biplot showing results for eleven plant communities' correlation with environmental variable. BAB-I: Berberis- Abies- Bergenia; PIP-II: Picea-Indigofera- Poa; APP-III: Abies- Parrotiopsis- Poa,QVP-IV:Quercus-Viburnum-Poa,PSP-V:PiceaSalix-Primula,AVP-VI:Abies-Viburnum -Poa; VTP-VII: ViburnumTaxus-Poa; PVL-VIII: Pinus-Viburnum-Lithospermum; ABC-IX: Abies-Berberis-Carex; PVP-X: Pinus-Viburnum-Poa; and PPP-XI: Parrotiopsis-Picea-Poa represents community types.

Figure 5 in Metagenomic study of the communities of bacterial endophytes in the desert plant Senna Italica and their role in abiotic stress resistance in the plant

Figure 5. Phylogenetic tree based on 16S rRNA gene sequences representing the diversity of endophytic bacterial communities associated with the leaves and roots from the desert medicinal plant Senna italica "at the Phylum level". The tree was constructed using the "one-click" mode in Phylogeny.fr.(Dereeper et al., 2008).

opencc-by-4.0Jul 2018View details →

Data from: Rhizosphere bacterial community composition depends on plant species identity and soil legacy effects

This record contains supplementary information for the article "Rhizosphere bacterial community composition depends on plant diversity legacy in soil and plant species identity". Supplemental Table S1. The table contains the annotation for all the samples sequenced and analyzed. Supplemental Table S2. The table contains all primer sequences used in the study. Supplemental Table S3. The zip-file contains a table with the taxonomic annotation of the operational taxonomic units (OTUs) identified in the study. Supplemental Table S4.  The zip-file contains a table with sequence counts of the operational taxonomic units (OTUs) identified in the study. Supplemental Table S5. The workbook contains a sheet with the number of operational taxonomic units (OTUs) exhibiting differential abundance in any of the contrasts tested in this study. Note that “down/up” indicates whether the OTU was less (“down”) or more (“up”) abundant in the first group of the contrast. For example, given the contrast “PH_mix_vs_mon_”, “down” corresponds to higher abundance in the pots from the monoculture plant history. Conversely, “up” refers to higher abundance in the pots from the mixed culture plant history. In addition, the workbook contains one sheet per contrast with the logBaseMean (log2 of the average normalized abundance across all samples), the logFC (log2 of the fold-change), the P-value, and the adjusted P-value (FDR). Only OTUs with a P-value <= 0.05 or an adjusted P-value (FDR) <= 0.1 are given. Supplemental Table S6. The table contains the number of bacterial OTUs annotated with a given bacterial phylum. Supplemental Table S7. The table contains all phyla tested for enrichment/depletion in the set of OTUs with an increased abundance in monoculture and mixed culture soils respectively. “Total counts (all OTUs)” corresponds to the total number of all OTUs annotated with a given phyla (reference set). “Observed” corresponds to the number of OTUs annotated with a given phyla in the set OTUs with increased abundance in monoculture/mixed culture soils (test set). "Expected" gives the number of OTUs which would be expected to be annotated with a given phyla if the test set were randomly sampled from the reference set. Supplemental File S1. The zip-file contains a fasta file with the 10'205 OTU sequences identified in the study.

opencc-by-4.0Dec 2017View details →

Fig. 3 in Insect visitors to the annual plant community in a xeric environment in Central Mexico

Fig. 3. Canonical correspondence analyses of the abundance of floral visitors in response to environmental variables (disturbance index, temperature, and humidity). (a) Effect of environmental variables on the abundance of each insect order of floral visitors. (b) Effect of environmental variables on the abundance of insect species displaying abundance that was significantly different between sites.

opencc-by-4.0Dec 2017View details →

Fig. 2 in Insect visitors to the annual plant community in a xeric environment in Central Mexico

Fig. 2. Dendrogram showing similarity indexes obtained from species composition of floral visitors shared by the annual plants distributed at the low (LPD) and high (HPD) plant density sites.

opencc-by-4.0Dec 2017View details →

Fig. 1 in Insect visitors to the annual plant community in a xeric environment in Central Mexico

Fig. 1. Abundance-rank curves of the insect species collected visiting the flowers of annual plants in sites with contrasting plant density. Relative abundance is plotted on a log10 scale, and the abscissa is the rank from the most to the least common species (James & Rathbun 1981). Closed triangles and diamonds indicate the abundance of Dasytinae species 1 (Coleoptera) and Miridae species 1 (Hemiptera), in the low and high plant density sites, respectively.

Figure 2 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 2. Typical examples of the plant communities in Majete Wildlife Reserve; A, riparian woodland (Rw); B, grassland (Gr); C–D, shrublands and woodlands (SW); E, transitional woodland (Tw); and F, miombo (M). Photo credits: W.A. Nieman.

Figure 1 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 1. Dendrogram of species composition for different woody plant communities based on the Jaccard similarity index.

Figure 4 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 4. The comparative performance of six incidence-based species richness estimators (Chao 2, Chao 2-bc, iChao 2, Jack 1, Jack 2 and ICE) for all woody plant species recorded in Majete Wildlife Reserve (n = 118). The observed species accumulation curve (Sobs) with 95% confidence intervals, as well as the cumulative number of singletons (the number of species recorded only once during the survey) and doubletons (the number of species recorded only twice during the survey), were also plotted. Estimated woody species richness values are indicated in brackets.

Figure 3 in The structure and composition of the woody plant communities of Majete Wildlife Reserve, Malawi

Figure 3. Distribution of woody plant communities in Majete Wildlife Reserve (MWR). The inset shows the location of the MWR in Malawi.

opencc-zeroAug 2021View details →

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Plant community data for European ecoregions

Patterns in macroecology are related to species occurrence across meaningful spatial and temporal scales. The dataset provided here reports species distribution data (presence-absence) for herbaceous plants across a number of European habitats (ecoregions). Species occurrence is accompanied by the corresponding plant's maximun stem height values. This dataset has been used to unveil patterns of herbaceous plant height clustering in mid-latitude European ecoregions. Presence-absence data for herbaceous plants were drawn from Atlas Florae Europaeae (Jalas & Suominen, 1964-1999). Associated to each species, a dominant habitat (ecoregion) was assigned according to the WWF Biomes of the World classification. Each herbaceous species in an ecoregion was characterized by its maximum stem height. Mean height values were obtained for different sources. In order to correlate clustering patterns with productivity measures, actual evapotranspiration (AET) data is also provided. AET maps were obtained from data estimated through remote sensing (Mu et al., 2011), which are publicly available in the MODIS project website (http://www.ntsg.umt.edu/project/modis/mod17.php). Plant distribution and trait data across Europe unveils a relation between plant height clustering and actual evapotranspiration. This clustering is most evident in mid-latitude ecoregions, where conditions for growth (reflected in actual evapotranspiration rates) are optimal. Away from this optimum, climate severity leads to non-significant height clustering in actual communities.

opencc-by-4.0Sep 2017View details →

Fig. 2 in The role of fruit bats in plant community changes in an urban forest in Indonesia

Fig. 2. Total number of fruit bats captured in this study from the UI urban forest. Species are abbreviated as follows: Cbr = C. brachyotis; Cho = C. horsfieldii; Cmi = C. minutus; Csp = C. sphinx; Cti = C. titthaecheilus; Mmi = M. minimus; Mso = M. sobrinus; Ram = R. amplexicaudatus.