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opencc-by-sa-4.0Nov 2017View details →

Data archive: Trophic structure of cold-water coral communities revealed from the analysis of tissue isotopes and fatty acid composition

Data belonging to the paper:  Dick van Oevelen, Gerard C. A. Duineveld, Marc S. S. Lavaleye, Tina Kutti and Karline Soetaert (2017) Trophic structure of cold-water coral communities revealed from the analysis of 55 tissue isotopes and fatty acid composition. Marine Biology Research, DOI: https://doi.org/10.1080/17451000.2017.1398404 Abstract: The trophic structure of cold-water coral reef communities at two contrasting locations, the 800- m deep Belgica Mounds (Irish margin) and 300-m deep Træna reefs (Norwegian Shelf), was investigated using stable isotope (δ13C and δ15N) and fatty-acid composition analysis. A broad range of specimens, with emphasis on (commercial) fish species, and organic matter sources were sampled using a variety of tools. Irrespective of the environmental and geographical setting, the δ15N values indicated that the food web encompasses roughly 1.5 to 3 trophic levels. Mobile echinoderms, i.e. sea urchins and sea stars, had highest δ15N values, indicative of a high trophic position in the food web. The fraction of bacterial fatty acids in reef fauna was generally low (<5%), indicating that enhanced bacterial production in the water column through seafloor seepage of nutrients (‘hydraulic theory’) does not form a significant energy pathway into the food web. The high fraction of algal and essential fatty acids in reef fauna and fish at both locations indicates a close coupling with surface productivity, but the transport mechanism depends on the hydrographic setting. At Træna, Calanus copepods and euphausiids form an additional link between primary production and fish, which is largely absent at Belgica Mounds. At Belgica Mounds, the reef community is primarily supported by phytodetritus, as evidenced by the high contribution of algal fatty acids in faunal tissue and seasonal chlorophyll a deposition and marine snow at the reef. The environmental setting of cold-water coral reefs influences the structure of the associated food web.

opencc-by-4.0Jan 2018View details →

Dataset for 'Different in the dark: The effect of habitat characteristics on community composition and beta diversity in bromeliad microfauna'

The file contains counting data for bromeliad-inhabiting microfauna (including, heterotrophic nanoflagellates, ciliates, amoeba and rotifers) from samples taken on Ilha do Cardoso, Brazil. Also included are additional Information on abiotic and biotic factors measured (e.g. pH, dissolved oxygen concentration etc.).

dryad40/100

Data from: Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition

Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured the effect of ARGs on host fitness in the absence of direct selection or determined if any costs are fixed or depend on the host strain, perhaps marking some ARG-host combinations as reservoirs that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse Escherichia spp. strains. Three ARGs (blaTEM-116, cat, and dfrA5, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions cause the success of ARGs to depend on available host strains, and, to a lesser extent, for successful host strains to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects over different host strains, especially the potential of reservoir strains that allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.

opencc-zeroMay 2024View details →

openmit-licenseMay 2024View details →

Source Data for main text and supplemental figures for manuscript "Community assessment of methods to deconvolve cellular composition from bulk gene expression"

Source Data for main text and supplemental figures for manuscript "Community assessment of methods to deconvolve cellular composition from bulk gene expression"

Figure 1 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest

Figure 1. Map of the RPPN Foz do Rio Aguapeí and location of the six studied areas in the RPPN Foz do Rio Aguapeí. Legend: (1) Lagoa São Gabriel; (2) Lagoa das Piranhas; (3) Lagoa dos Porcos; (4) Constructed wetland; (5) Aguapei river –; and (6) Lagoa da sede. Sources: CESP (2013) and Google Earth (2021).

Figure 2 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest

Figure 2. Cumulative curve of the 52 waterfowl bird species in the RPPN Foz do Rio Aguapeí showing stability from sample 27 to 31.

Figure 3 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest

Figure 3. NMDS (stress of 0.097) of the spatial distribution of the aquatic bird community recorded by the transect method in the lagoons of the RPPN Foz do Aguapeí, during the dry (rounded symbols) and rainy seasons (square symbols). Legend: LS = Lagoa da Sede; LSG = Lagoa São Gabriel; LP = Lagoa da Piranha and LPO = Lagoa dos Porcos.

SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment

SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream.

SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment

SI Figure 2: Compositional differences among bacterial microinvertebrate external and internal microbiomes as well as mats they were isolated from using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars show centroids of microbiome types for each animal host. All host microbiomes (internal and external) are distinct from mat communities (P<0.05), but external microbiomes are more similar to mats than internal microbiomes are to mats.

Figure 4 in Composition and spatio-temporal dynamics of aquatic bird community in humid areas of Alto Parana Atlantic Forest

Figure 4. NMDS (stress of 0.001) of the spatial distribution of the aquatic bird community recorded by the transect method in the lotic environments of the RPPN Foz do Aguapeí, during the dry (rounded symbols) and rainy seasons (square symbols). Legend: AR = Aguapeí River and CW = Constructed wetland.

opencc-by-4.0Mar 2018View details →

Figure 3 in Preliminary assessment of community composition and phylogeographic relationships of the birds of the Meratus Mountains, south-east Borneo, Indonesia

Figure 3. Lemon-bellied White-eyes Zosterops chloris from: (A) the Meratus Mountains (J. C. Eaton); (B) Tukangbesi Islands, south-east Sulawesi, Z. c. flavissimus (J. C. Eaton); and (C) Lore Lindu National Park, central Sulawesi, Z. c. mentalis (D. Beadle)

opencc-by-4.0Mar 2018View details →

Figure 4 in Preliminary assessment of community composition and phylogeographic relationships of the birds of the Meratus Mountains, south-east Borneo, Indonesia

Figure 4. Male Hill Blue Flycatchers (Cyornis banyumas) from: (A) the Meratus Mountains (J. C. Eaton) and (B) Poring, Sabah, C. b. montanus (J. C. Eaton)

opencc-by-4.0Mar 2018View details →

Figure 2 in Preliminary assessment of community composition and phylogeographic relationships of the birds of the Meratus Mountains, south-east Borneo, Indonesia

Figure 2. Rooted maximum likelihood trees indicating mtDNA-ND2 relationships between Meratus and other populations (in some cases species) for 12 species exhibiting marked genetic patterns. Bootstrap values are reported next to respective nodes.

opencc-by-4.0Dec 2022View details →

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.

opencc-by-4.0Dec 2022View details →

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.

opencc-by-4.0Dec 2022View details →

Рис. 2. UPGMA-ΑенΑрограмма схоΑства виΑового состава (А) и фаунистическая структура (B) сообществ земΛероек в пяти ΛокаΛитетах Амурской обΛасти: ЗЗ — Зейский заповеΑник; НЗ — Норский заповеΑник; ХЗ — Хинганский заповеΑник; ЧФЗ — ХинганоАрхаринский заказник; НБС — территория зоны вΛияния Нижнебурейской ГЭС. ΔТФ — Αревнетаежная фауна; БФ — бореаΛьная фауна; НФ — немораΛьная фауна; Αр. — преΑставитеΛи Αругих фауногенетических группировок (пояснения в тексте) Fig. 2. UPGMA dendrogram of species composition similarity (A) and fauna structure (B) of shrew communities in five Amur region localities: ZZ — Zeya nature reserve; NZ — Norsky nature reserve; KhZ — Khingansky nature reserve; ChFZ — KhinganoArkharinsky nature reserve; NBS — the area influenced by the Nizhnebureyskaya hydroelectric power station. DTP — ancient taiga fauna; BF — boreal fauna; NF — nemoral fauna; others — representatives of other faunagenetic groups (explained in the text) in Shrew species composition and fauna structure in the Norsky reserve

Рис. 2. UPGMA-ΑенΑрограмма схоΑства виΑового состава (А) и фаунистическая структура (B) сообществ земΛероек в пяти ΛокаΛитетах Амурской обΛасти: ЗЗ — Зейский заповеΑник; НЗ — Норский заповеΑник; ХЗ — Хинганский заповеΑник; ЧФЗ — ХинганоАрхаринский заказник; НБС — территория зоны вΛияния Нижнебурейской ГЭС. ΔТФ — Αревнетаежная фауна; БФ — бореаΛьная фауна; НФ — немораΛьная фауна; Αр. — преΑставитеΛи Αругих фауногенетических группировок (пояснения в тексте) Fig. 2. UPGMA dendrogram of species composition similarity (A) and fauna structure (B) of shrew communities in five Amur region localities: ZZ — Zeya nature reserve; NZ — Norsky nature reserve; KhZ — Khingansky nature reserve; ChFZ — KhinganoArkharinsky nature reserve; NBS — the area influenced by the Nizhnebureyskaya hydroelectric power station. DTP — ancient taiga fauna; BF — boreal fauna; NF — nemoral fauna; others — representatives of other faunagenetic groups (explained in the text)

Fig. 7 in Composition and Dynamics of Hexapod Communities on Yushan Bamboo () in the Subtropical Montane Areas of Taiwan.

Fig. 7. Redundancy analysis (RDA) of hexapod families identified in bimonthly surveys during 2009–2012. (A) RDA revealed that the explained variance derived on the first (X) and second (Y) axes for the first 19 families in the two principal components (i.e., PC1 and PC2) were 0.773 and 0.227, respectively. Triplot revealed the association between hexapod compositions at the family level and monthly average temperature (MAT) and monthly cumulative precipitation (MCP). Families are indicated by red arrows, and climatic factors are indicated by blue arrows. Samples collected in spring (April), summer (June and August), fall (October), and winter (December and February) are indicated by red triangles, empty triangles, diamonds, and circles, respectively. The eigenvalues on the first and second axes were 0.262 and 0.194, respectively. The arrow lengths and directions correspond to the variance explained by the climatic factors. The directions of the arrows indicate whether the magnitude of the variance explained by the climatic factors increased. The perpendicular distances between the family and climatic variable axes (or arrows) in the plot reflect their correlations; the smaller the distance is, the stronger the correlation is. (B) Spearman's Pearson correlation coefficients between the individuals of 19 hexapod families and two climate factors. The values for each family are presented in a gradient of blue to red to represent the families' expected correlations with the climatic factors. The values in the blue bars indicate the explained variance by the climatic factors for each family. The first three capital letters of family name in panel B were used in place of the full name of each family.

Fig. 6 in Composition and Dynamics of Hexapod Communities on Yushan Bamboo () in the Subtropical Montane Areas of Taiwan.

Fig. 6. Spatial ordination of hexapod compositions—determined through principal component analysis—identified in bimonthly surveys during 2009–2012. The dominant families with extremely low PC2 values (lower than -0.2) are listed (details provided in Table S4). The right and left areas present hexapods in the winter and summer groups, respectively.

Fig. 5 in Composition and Dynamics of Hexapod Communities on Yushan Bamboo () in the Subtropical Montane Areas of Taiwan.

Fig. 5. Transformed numbers (logN values) of adult (solid circle) and nymphal (empty circle) individuals belonging to the dominant family Cicadellidae identified in bimonthly surveys during 2009–2012.

Fig. 3 in Composition and Dynamics of Hexapod Communities on Yushan Bamboo () in the Subtropical Montane Areas of Taiwan.

Fig. 3. Variations of hexapod biodiversity indices in bimonthly surveys. Variations of Evenness (circle), Shannon (square), and Simpson (triangle) indices during 2009–2012. Temperature is indicated by gray bars.