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Fig. 3 in The vascular plant diversity of Burkina Faso (West Africa) - a quantitative analysis and implications for conservation

Fig. 3. – Origin of introduced plant species in Burkina Faso. The majority of introduced species originates in the Americas.

Fig. 6 in The vascular plant diversity of Burkina Faso (West Africa) - a quantitative analysis and implications for conservation

Fig. 6. – Province species richness in relation to province characteristics. Species richness per province is shown dependent on 4 factors.

Fig. 1 in The vascular plant diversity of Burkina Faso (West Africa) - a quantitative analysis and implications for conservation

Fig. 1. – The provinces of Burkina Faso and their assignment to the phytogeographic zones used in this study. The classification of provinces to the PGZs is modified after WHITE (1983) and GUINKO (1984a). [1: Les Balé; 2: Bam; 3: Banwa; 4: Bazègua. 5: Bougouriba; 6: Boulgou; 7: Boulkiemdé; 8: Ganzourgou; 9: Gnagna; 10: Gourma; 11: Houet; 12: Ioba; 13: Kadiogo; 14: Kénédougou; 15: Comoé; 16: Komandjari; 17: Kompienga; 18: Kossi; 19: Koulpélogo; 20: Kouritenga; 21: Kourwéogo; 22: Léraba; 23: Loroum; 24: Mouhoun; 25: Nahouri; 26: Namentenga; 27: Nayala; 28: Oubritenga; 29: Oudalan; 30: Passoré; 31: Sanguié; 32: Sanmatenga; 33: Séno; 34: Sissili; 35: Soum; 36: Sourou; 37: Tapoa; 38: Tuy; 39: Yagha; 40: Yatenga; 41: Ziro; 42: Zondoma; 43: Zoundwéogo; 44: Poni; 45: Noumbiel]

opencc-by-4.0Mar 2022View details →

Supplementary data for article "Small hydropower – small ecological footprint? A multi-annual environmental impact analysis using aquatic macroinvertebrates as bioindicators. Part 2: effects on functional diversity" by Scotti A., et al.

Supplementary data for article "Small hydropower – small ecological footprint? A multi-annual environmental impact analysis using aquatic macroinvertebrates as bioindicators. Part 2: effects on functional diversity" by Scotti A., et al.: - Trait-based distances calculated for each pair of taxa; - CWM, CWM(LN) values, and their difference (CWMDIFF) Refer to the published articles for further details.

opencc-by-4.0Dec 2021View details →

Fig. 3 in Ecological Analysis Of Butterflies And Day-Flying Moths Diversity Of The Gouraya National Park (Algeria)

Fig. 3. Projection of the butterfly and day-flying moth species of the three stations studied on the first two axes of the correspondence factor analysis.

opencc-by-4.0Dec 2021View details →

Fig. 2 in Ecological Analysis Of Butterflies And Day-Flying Moths Diversity Of The Gouraya National Park (Algeria)

Fig. 2. Evolution of the species richness of butterflies and day-flying moths at the three stations of Gouraya National Park, mean temperature in Bejaia (DAAE, 2012).

opencc-by-4.0Jul 2018View details →

Fig. 5 in Helminths Of The Mallard, Anas Platyrhynchos (Aves, Anatidae) In Ukraine: Analysis Of The Diversity In Mixed Forest Zone And The Black Sea Region

Fig. 5. Configuration of 2-dimensional MDS for specimens of Mallard from the mixed forest zone (P) and from the steppe zone (B) with overlapping clusters at similarity level of 15 %.

opencc-by-4.0Jul 2018View details →

Fig. 3 in Helminths Of The Mallard, Anas Platyrhynchos (Aves, Anatidae) In Ukraine: Analysis Of The Diversity In Mixed Forest Zone And The Black Sea Region

Fig. 3. Prevalence (with lower and upper confidence intervals at significant level 95 %) and mean intensity (with range; in case when only one or two birds were infected by a certain type of helminth, then the actual intensity values are given) of Mallard´s infection with: A — trematodes from the mixed forest zone; B — trematodes from the steppe zone. * Logarithmic scale was used

opencc-by-4.0Jun 2022View details →

Spanish melon landraces: revealing useful diversity by genomic, morphologic, and metabolomic analysis. Supplementary data.

Original data linked to the publication Spanish melon landraces: revealing useful diversity by genomic, morphologic, and metabolomic analysis. It includes, Supp. Table 1: Genomic data; Supp. Table 2: Characterization data; Supp. Table 3: sugar and acids data; Supp Table Supp. Table 4: Voaltile organic compounds data; Supp Table 5: Germplasm details; Supp. table 6: Cromatographic parameters

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Data from: Worldwide impacts of landscape anthropization on mosquito abundance and diversity: a meta-analysis

In recent decades, the emergence and resurgence of vector-borne diseases have been well documented worldwide, especially in tropical regions where protection and defence tools for human populations are still very limited. In this context, the dynamics of pathogens are influenced by landscape anthropization (i.e., urbanization, deforestation, and agricultural development), and one of the mechanisms through which this occurs is a change in the abundance and/or diversity of the vectors. An increasing number of empirical studies have described heterogeneous effects of landscape anthropization on vector communities; therefore, it is difficult to have an overall picture of these effects on a global scale. Here, we performed a meta-analysis to quantify the impacts of landscape anthropization on a global scale on the presence/abundance and diversity of mosquitoes, the most important arthropods affecting human health. We obtained 338 effect sizes on 132 mosquito species, compiled from 107 studies in 52 countries that covered almost every part of the world. The results of the meta-analysis showed an overall decline of mosquito presence/abundance and diversity in response to urbanization, deforestation, and agricultural development, except for a few mosquito species that have been able to exploit landscape anthropization well. Our results highlighted that these few favoured mosquito species are those of global concern. They thus provide a better understanding of the overall effect of landscape anthropization on vector communities and, more importantly, suggest a greater risk of emergence and transmission of vector-borne diseases in human-modified landscapes.

opencc-zeroAug 2022View details →

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Analysis of nitrous oxide reductase diversity from wastewater: a SINTAX database

This study explores the genetic landscape of nitrous oxide (N2O) reduction in wastewater treatment plants (WWTPs) by profiling 1083 high-quality metagenome-assembled genomes (HQ MAGs) derived from 23 Danish full-scale WWTPs. The analysis focuses on the distribution and diversity of nitrous oxide reductase (nosZ) genes, key players in N2O reduction, and their connection to other nitrogen metabolism pathways. A custom pipeline for clade-specific nosZ gene identification outperformed existing methods, revealing the presence of 503 nosZ sequences in 489 MAGs. Notably, 48.7% of the MAGs harboured nosZ genes, with clade II dominating (92.3%). Taxonomic profiling reveals the distribution of nosZ clade I and clade II-containing MAGs, emphasizing the dominance of Bacteroidota and Pseudomonadota. Notably, Chloroflexota exhibits unexpected affiliations with nosZ clade I. The taxonomic diversity of non-denitrifying N2O-reducers is also explored, highlighting the presence of these organisms in Bacteroidota, Chloroflexota, and other phyla.

opencc-zeroApr 2024View details →

Fig. 2 in Factors Influencing Weed Species Diversity In Southeastern Part Of Latvia: Analysis Of A Two-Year Weed Survey Data

Fig. 2. Influence of field variables and crop groups on weed density, common and rare species richness in 2013 and 2014. Constrained analysis (RDA) with five constraining variables: Year (2013 or 2014), N_group (N1 0-50, N2 50- 100, N3 100-140, N4>140 kg ha–1 pure nitrogen per hectar), pH and crop group (c.s. – spring cereals, c.w. – winter cereals, S o.s.r. – spring oilseed rape, W o.s.r. – winter oilseed rape, Other – other crops, including maize, grassland, root crops and legumes). The proportion of constrained variation was 33%, the overall analysis and each of the factors were significant (p <0.05), significance tested with permutation tests.

Fig. 1 in Factors Influencing Weed Species Diversity In Southeastern Part Of Latvia: Analysis Of A Two-Year Weed Survey Data

Fig. 1. Generalized linear models (Poisson) of the total species richness against species density in 2014 and 2013. Model coefficients were 2.41 (p <0.0001) in 2014 and 2.40 (p <0.0001) in 2013. Residual deviance / residual d.f. ratio was used to estimate model overdispersion (1.62 in 2014 and 1.35 in 2013).

FIGURE 4 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 4. Linear regression of MAP on correspondence axis 1 (CA1) score; estimated MAP for each of fossil locality based on CA1 score is indicated. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.

FIGURE 3 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 3. Axes three and four of the correspondence analysis. A) Positions of the fossil localities and 179 modern ecoregions; B) Positions of the 22 variables. Note that the scale is not the same in the two graphs.

FIGURE 2 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 2. Axes one and two of the correspondence analysis. A) Positions of the fossil localities and 179 modern ecoregions; B) Positions of the 22 variables. Note that the scale is not the same in the two graphs.

FIGURE 1 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 1. Locations of the 179 modern ecoregions (colored areas) and the five fossil localities (stars) used in this study. Ecoregions are overlain on a grayscale global mean annual precipitation (MAP) map derived from Fick and Hijmans (2017), with lighter regions indicating areas of higher MAP and darker regions indicating areas of lower MAP. Abbreviations: LV, La Venta, Colombia; QH, Quebrada Honda, Bolivia; RU, Rümikon, Switzerland; SC, Santa Cruz, Argentina; TG, Tinguiririca, Chile.

FIGURE 7 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 7. Classification Tree results for CT3, biome. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.

FIGURE 5 in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 5. Composite hierarchical cluster analysis with the positions of the five fossil localities (dagger symbols) indicated. Solid black lines indicate the results when all five fossil localities are included in the analysis; dashed black lines indicate the results when each fossil locality is analyzed individually. The position of Rümikon did not vary in the two analysis. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.