Using long-term data to predict fish abundance: the case of Prochilodus lineatus (Characiformes, Prochilodontidae) in the intensely regulated upper Paraná River
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Abstract
Populations show spatial-temporal fluctuations in abundance, partly due to random processes and partly due to self-regulatory processes. We evaluated the effects of various external factors on the population numerical abundance of curimba Prochilodus lineatus in the upper Paraná River floodplain, Brazil, over a 19-year period. Panel data analysis was applied to examine the structure of temporal and spatial abundance while controlling auto-regressive processes and spatial non-homogeneity variances that often obscure relationships. As sources of population variation, we considered predation, competition, selected abiotic variables, construction of a dam upstream of the study area, water level and flood intensity during the spawning period. We found that biological interactions (predation and competition) were not significantly related to variations in curimba abundance; specific conductance was a space indicator of abundance, apparently linked to the biology of the species; intensity of floods determined inter-annual variation in abundances; Porto Primavera Dam negatively impacted the abundances at sites in the floodplain directly affected by discharges from the dam. Panel data analysis was a powerful tool that identified the need for intense flooding to maintain high abundances of curimba in the upper Paraná River. We believe our results apply to other species with similar life strategy.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Using long-term data to predict fish abundance: the case of Prochilodus lineatus (Characiformes, Prochilodontidae) in the intensely regulated upper Paraná River |
| Series title | Neotropical Ichthyology |
| DOI | 10.1590/1982-0224-20160029 |
| Volume | 15 |
| Issue | 3 |
| Year Published | 2017 |
| Language | English |
| Publisher | SciELO |
| Contributing office(s) | Coop Res Unit Atlanta |
| Description | e160029; 12 p. |
| First page | 1 |
| Last page | 12 |
| Country | Brazil |
| Other Geospatial | Paraná River |
| Google Analytic Metrics | Metrics page |