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opencc-by-4.0Jun 2016View details →

Figure 4 in Comparison of trophic structure of the benthic macroinvertebrates in three Bulgarian riverine water bodies

Figure 4. Relative share of FFGs (%) in the plain stations of the studied river basins (see the abbreviations in Section 2).

opencc-by-4.0Jun 2016View details →

Figure 5 in Comparison of trophic structure of the benthic macroinvertebrates in three Bulgarian riverine water bodies

Figure 5. Similarity of species composition of the FFGs between studied sites (MDS plot) (the numbers correspond to the surveyed stations as described in Section 2).

opencc-by-4.0Jun 2016View details →

Figure 7 in Comparison of trophic structure of the benthic macroinvertebrates in three Bulgarian riverine water bodies

Figure 7. Dendrogram of cluster analysis of the species composition in DF (see the abbreviations in Section 2).

opencc-by-4.0Jan 2021View details →

Figure 2 in Diet composition, guild structure and trophic relationships of wintering birds of prey in an estuarine wetland (The Evros Delta National Park, Greece)

Figure 2. Cluster analysis (dendrogram) based on the biomass proportions of the diets of the seven species of birds of prey studied in Evros Delta.

opencc-by-4.0Jan 2021View details →

Figure 1 in Diet composition, guild structure and trophic relationships of wintering birds of prey in an estuarine wetland (The Evros Delta National Park, Greece)

Figure 1. Diet compiled for the most important prey taxa of the seven species of birds of prey studied in the Evros Delta, a) by biomass (upper graph) and b) by numbers (lower graph) (Shannon index/Evenness are shown below each species name).

opencc-by-4.0Aug 2020View details →

Fig. 1 in Stable isotope analysis spills the beans about spatial variance in trophic structure in a fish host - parasite system from the Vaal River System, South Africa

Fig. 1. Map of the Vaal River showing the position of sampling sites (I: below Grootdraai Dam; II: Vaal Dam; III: below Vaal River Barrage; IV: Bloemhof Dam; V: below Vaalharts Weir; VI: Douglas Weir) along the Vaal River. The block (B) indicates the position of the Vaal River within South Africa and insert A indicates the position of South Africa shaded on the African continent.

Fig. 2 in Can dams affect the trophic structure of ichthyofauna? A long-term effects in the Neotropical region

Fig. 2. Detrended Correspondence Analysis (DCA) (biplot) considering the fish species of each stretch and the different trophic categories in Jurumirim Reservoir, Upper Paranapanema River, state of São Paulo, Brazil. Acronym of the species in the Table III.

Fig. 3 in Can dams affect the trophic structure of ichthyofauna? A long-term effects in the Neotropical region

Fig. 3. Importance of trophic guilds (in numeric abundance and biomass) by stretch (lotic, transition, and lentic) of Jurumirim Reservoir, Upper Paranapanema River, state of São Paulo, Brazil.

Fig. 4 in Can dams affect the trophic structure of ichthyofauna? A long-term effects in the Neotropical region

Fig. 4. Proportion of the resources used by the species in the three studied zones in Jurumirim Reservoir, Upper Paranapanema River, state of São Paulo, Brazil: 1, Lotic; 2, Transition; 3, Lentic.

Figs 5-7 in Can dams affect the trophic structure of ichthyofauna? A long-term effects in the Neotropical region

Figs 5-7. Trophic interactions networks built with fish species (black) and resources consumed (gray): Fig. 5, Stretch 1 (lotic); Fig. 6, Stretch 2 (transition) and Fig. 7, Stretch 3 (lentic) in Jurumirim Reservoir, Upper Paranapanema River, state of São Paulo, Brazil.

Fig. 1 in Can dams affect the trophic structure of ichthyofauna? A long-term effects in the Neotropical region

Fig. 1. Map of Jurumirim Reservoir (Upper Paranapanema River, state of São Paulo, Brazil) indicating the three samplings zones.

FIGURE 4 in Hydropower affects fish trophic structure both downstream of the dam and upstream of the reservoir

FIGURE 4 | A. Non-metrical multidimensional scaling (NMDS) of trophic structure. B. NMDS of species composition. (BU= Before/ upstream, BD= Before/downstream, AU= After/upstream, AD= After/downstream).

FIGURE 3 in Hydropower affects fish trophic structure both downstream of the dam and upstream of the reservoir

FIGURE 3 | A. Trophic structure of the fish assemblage represented by relative biomass of the trophic guilds. Line inside the box = median; box = 25th and 75th percentiles; whiskers = 1.5 x IQR; dots = outliers. B. Non-metrical multidimensional scaling (NMDS) of the relative biomass for each trophic guild. (Detr= Detritivores, Herb= Herbivores, Inse= Insectivores, Omni= Omnivore, Pisc= Piscivore, BU= Before/upstream, BD= Before/downstream, AU= After /upstream, AD=After/downstream).

FIGURE 2 in Hydropower affects fish trophic structure both downstream of the dam and upstream of the reservoir

FIGURE 2 | Daily average flow for three fluviometric stations. S1 and S2 are located upstream of the reservoir, and S3 is located downstream of the dam. The gray dashed line represents the date in which the dam was closed. The Energy Company of Minas Gerais (CEMIG) provided historical flow data (1996 – 2016) of the fluviometric stations nº 1743023 (S1), 1642029 (S2), and 1642044 (S3).

FIGURE 1 in Hydropower affects fish trophic structure both downstream of the dam and upstream of the reservoir

FIGURE 1 | Map of Irapé Hydroelectric Power Plant showing the fish sampling points (1 through 4) and fluviometric stations (S1, S2, S3).

opencc-by-4.0Sep 2024View details →

Hydrology and trophic flexibility structure alpine stream food webs in the Teton Range, Wyoming, USA

Data and code necessary to replicate the findings from the manuscript titled "Hydrology and trophic flexibility structure alpine stream food webs in the Teton Range, Wyoming, USA". Abstract: Understanding biotic interactions and how they vary across habitats is important for assessing the vulnerability of communities to climate change. Receding glaciers in high mountain areas can lead to the hydrologic homogenization of streams and reduce habitat heterogeneity, which are predicted to drive declines in regional diversity and imperil endemic species. However, little is known about food web structure in alpine stream habitats, particularly among streams fed by different hydrologic sources (e.g., glaciers or snowfields). We used gut content and stable isotope analyses to characterize food web structure of alpine macroinvertebrate communities in streams fed by glaciers, subterranean ice, and seasonal snowpack in the Teton Range, Wyoming, USA. Specifically, we sought to: (1) assess community resource use among streams fed by different hydrologic sources; (2) explore how variability in resource use relates to feeding strategies; and (3) identify which environmental variables influenced resource use within communities. Average taxa diet differed among all hydrologic sources, and food webs in subterranean ice-fed streams were largely supported by the gold alga Hydrurus. This finding bolsters a hypothesis that streams fed by subterranean ice may provide key habitat for cold-water species under climate change by maintaining a longer growing season for this high-quality food resource. While a range of environmental variables associated with hydrologic source (e.g., stream temperature) were related to diet composition, hydrologic source categories explained the most variation in diet composition models. Less variable diets within versus among streams suggests high trophic flexibility, which was further supported by high levels of omnivory. This inherent trophic flexibility may bolster alpine stream communities against future changes in resource availability as the mountain cryosphere fades. Ultimately, our results expand understanding of the habitat requirements for imperiled alpine taxa while empowering predictions of their vulnerability under climate change.

Fig. 6 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF

Fig. 6. Proportion of autochthonous feeding items (black) and allochthonous (gray) with respect to the rainy (C) and dry (S) seasons for the fish species that presented this significant variation. Species abbreviations: Aspidoras fuscoguttatus (aspfus), Astyanax sp. (astsp), Characidium xanthopterum (chaxan), Hasemania sp. (hassp), Hyphessobrycon balbus (hypbal), Heptapterus sp. (hepsp), Knodus moenkhausii (knomoe), Kolpotocheirodon theloura (kolthe), Moenkhausia sp. (moesp), Phalloceros harpagos (phahar), Planaltina myersi (plamye), Rhamdia quelen (rhaque) and Rivulus pictus (rivpic)..

Fig. 1 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF

Fig. 1. Localization of the Brasília National Park in the Distrito Federal and distribution of sampling sites in the Bananal stream subbasin, Paranoá Lake basin, DF.

Fig. 5 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF

Fig. 5. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Moenkhausia sp., Phalloceros harpagos, Planaltina myersi, Rhamdia quelen and Rivulus pictus. The number of analyzed stomachs is shown in parentheses.

Fig. 4 in Trophic structure of a fish community in Bananal stream subbasin in Brasília National Park, Cerrado biome (Brazilian Savanna), DF

Fig. 4. Feeding items distributed according to the frequency of fish species occurrence (axis X) and relative abundance (axis Y), based upon the method proposed by Amundsen et al (1996): Aspidoras fuscoguttatus, Astyanax sp., Characidium xanthopterum, Hasemania sp., Hyphessobrycon balbus, Heptapterus sp., Knodus moenkhausii and Kolpotocheirodon theloura. The number of analyzed stomachs is shown in parentheses.