Abstract
AbstractClimate‐driven alterations of hydro‐meteorological conditions can change river flow regimes and potentially affect the migration behaviour of fishes and the productivity of important fisheries in the Amazon basin, such as those for the continental‐scale migratory goliath catfishes (Brachyplatystoma, Pimelodidae). In this study, we investigated hydrologic responses to climate change using a hydrologic model forced with climate inputs, which integrate historical (2001–2010) observations and general circulation model (GCM) projections under the emission scenario Representative Concentration Pathway 8.5. We developed an empirical model to characterize future (2090–2099) climate‐change impacts on goliath catfish spawning migrations as a function of river flow depth dynamics at the upstream elevational limit of spawning (250 m) in headwater basins of the Amazon. The model results revealed spatially variable impacts of climate change on the catfish spawning migrations. The Marañón, Ucayali, Juruá, Purus, and Madeira basins had a predicted increase in the annual mean (3–8%) and maximum (1.1–4.9%) spawning migration rate (i.e., the fraction of fish that migrate to the spawning grounds in a day), mainly due to the lengthened rising phase of flow‐driven migratory events during wet seasons. The Caquetá‐Japurá, Putumayo‐Içá, Napo, and Blanco rivers had predicted decreases (3–7%) in the mean migration rate because of decreases in the length of the rising season of flow depth and the frequency of migratory events. The predicted timing of fish spawning migrations (quantified by the temporal centroid of migration rates) was delayed by 7–10 days in the west‐central and southwest regions and was 8 days earlier in the northwest and northcentral areas, due to changes in the onset of the rising season. We established a river depth baseline that controls the onset of goliath catfish spawning migration. This depth varies between 0.9–5.6 m across study sites. We found that the estimated depth baseline was most sensitive to uncertainties in river width and cross‐sectional channel shape. These results may help inform sustainable adaptation strategies for ecosystem conservation and local fisheries management in the Amazon basin.
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