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76 results for “tropical rivers”
Does the River Continuum Concept apply on a tropical island? Longitudinal variation in a Puerto Rican stream
We examined whether a tropical stream in Puerto Rico matched predictions of the River Continuum Concept (RCC) for macroinvertebrate functional feeding groups (FFGs). Sampling sites for macroinvertebrates, basal resources, and fishes ranged from headwaters to within 2.5 km of the fourth-order estuary. In a comparison to a model temperate system where RCC predictions generally held, we used catchment area as a measure of stream size in order to examine truncated RCC predictions (i.e., cut off to correspond to the largest stream size sampled in Puerto Rico). Despite dominance of generalist freshwater shrimps, which use more than one feeding mode, RCC predictions held for scrapers, shredders, and predators. Collector-filterers showed a trend opposite that predicted by the RCC, but patterns in basal resources suggest that this is consistent with the central RCC theme: longitudinal distributions of FFGs follow longitudinal patterns in basal resources. Alternatively, the filterer pattern may be explained by fish predation affecting distributions of filter-feeding shrimp. Our results indicate that the RCC generally applies to running waters on tropical islands. However, additional theoretical and field studies across a broad array of stream types should examine whether the RCC needs to be refined to reflect the potential influence of top-down trophic controls on FFG distributions. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Fig. 4 in Physical habitat simulation for small-sized characid fish species from tropical rivers in Brazil
Fig. 4. The velocities and depth comparison between the field measurement and the numerical model for points in 50% cros- s-section width of the Velhas reach (a-b) and in 50% width of the Curimataí reach (c-d).
Fig. 5 in Habitat preferences of common native fishes in a tropical river in Southeastern Brazil
Fig. 5. Substrate preferences of seven dominant native fish species in the Guandu River. Type of Substrate: 1, clay; 2, mud; 3, sand; 4, boulder/cobble/gravel; 5, bedrock.
Fig. 2 in Habitat preferences of common native fishes in a tropical river in Southeastern Brazil
Fig. 2. Distribution of sampling by habitat availability (%) in terms of depth (m), velocity (m s-1), and type of substrate. (1, clay; 2, mud; 3, sand; 4, boulder/cobble/gravel; 5, bedrock).
Fig. 1 in Habitat preferences of common native fishes in a tropical river in Southeastern Brazil
Fig. 1. Study area, Guandu River, indicating the four sampled stretches. WTP, Water Treatment Plant.
Fig. 3 in How does diet influence the reproductive seasonality of tropical freshwater fish? A case study of a characin in a tropical mountain river
Fig. 3. Non-Metric Multi-Dimensional Scaling Ordination (NMDS) of monthly variations of the diet with respect to sex. Stress = 0.10. Filled symbols are the dry months.
Fig. 2 in How does diet influence the reproductive seasonality of tropical freshwater fish? A case study of a characin in a tropical mountain river
Fig. 2. Monthly variation of prey types-IRI values. Rainfall follows a bimodal seasonal pattern (shadow on background). The asterisks show the months in which reproduction occurs.
Fig. 1 in How does diet influence the reproductive seasonality of tropical freshwater fish? A case study of a characin in a tropical mountain river
Fig. 1. Ontogenetic and intersexual variation in the diet of Creagrutus guanes. Size classes correspond to standard length ranges: 3 = 21-30 mm; 4 = 31-40 mm; 5 = 41-50 mm; 6 = 51-60 mm; 7 = 61-70mm; 8 = 71-80mm.
Fig. 2 in Reproductive seasonality of Geophagus steindachneri Eigenmann & Hildebrand, 1922 (Perciformes: Cichlidae) in a tropical mountain river
Fig. 2. Monthly variation in adult females: (a) SL, standard length and WE, eviscerated weight, (b) liver and fat weight, and (c) ovary weight. Barplot behind the lines represents the rainfall pattern.
Fig. 5 in Reproductive seasonality of Geophagus steindachneri Eigenmann & Hildebrand, 1922 (Perciformes: Cichlidae) in a tropical mountain river
Fig. 5. Monthly variation in adult males: (a) SL, standard length and WE, eviscerated weight, (b) liver and fat weight, and (c) testis weight. Barplot behind the lines represents the rainfall pattern.
Fig. 3 in Reproductive seasonality of Geophagus steindachneri Eigenmann & Hildebrand, 1922 (Perciformes: Cichlidae) in a tropical mountain river
Fig. 3. Monthly variation in (a) the frequency of ovarian development stages and (b) the frequency of mouthbrooding females carrying embryos, larvae, or juveniles.
Fig. 1 in Reproductive seasonality of Geophagus steindachneri Eigenmann & Hildebrand, 1922 (Perciformes: Cichlidae) in a tropical mountain river
Fig. 1. Monthly variation of environmental variables: (a) rainfall pattern, (b) pH and temperature, and (c) conductivity and transparency.
Fig. 4 in Reproductive seasonality of Geophagus steindachneri Eigenmann & Hildebrand, 1922 (Perciformes: Cichlidae) in a tropical mountain river
Fig. 4. Differences between females that were not performing parental care and mouth-brooding females: (a) stage of ovary maturity, with circle size indicating number of females in each condition; (b) liver and ovary weight.
Figure 7 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 7. NMDS diagram of macroinvertebrates in the sampled periods. (A) NMDS: structure; (B) NMDS: composition.
Figure 1 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 1. Study site and sampling stations (P1, P2, and P2) in Barbosa Lake (the circle shows the connection site between the lake and the river).
Figure 4 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 4. Means and standard deviations of root biomass of E. azurea (g.DW–1) in Barbosa Lake during the study period.
Figure 2 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 2. Scheme of an adult E. azurea individual showing the sampled root mass in sequential direction from the apical to the basal parts of the plant.
FIGURE 4 in Fish biodiversity of a tropical estuary under severe anthropic pressure (Doce River, Brazil)
FIGURE 4 | Main human-driven impacts after the 19th century and their consequences on the Doce River basin. Photos by A. Villela (Exotic species) and E. Nascimento (Mining dam collapse); the other pictures belong to the public domain (Tab. S2).
FIGURE 2 in Fish biodiversity of a tropical estuary under severe anthropic pressure (Doce River, Brazil)
FIGURE 2 | Number of species, genera and families for fish orders in the Doce River estuary. The following orders were represented by a single species and were omitted in the figure: Anguilliformes, Atheriniformes, Aulopiformes, Beloniformes, Blenniiformes, Centrarchiformes, Cyprinodontiformes, Elopiformes, Scombriformes, Spariformes, Symbranchiformes and Syngnathiformes (illustrative taxa images from Phylopic.org).
FIGURE 1 in Fish biodiversity of a tropical estuary under severe anthropic pressure (Doce River, Brazil)
FIGURE 1 | Location of the study area in Eastern Brazil with some features detailed: A. Sandy banks; B. Marginal creek; and C. Main channel of the Doce River estuary (DRE). Photos: Helder C. Guabiroba (A; C), Alexandre Villela (B). Aerial image source: (GEOBASES, 2015).
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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