Cintia Moreno-Arias1 , Silvia López-Casas2, Carlos A. Rogeliz-Prada2 and Luz Jiménez-Segura1
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Abstract
Because dams block migratory routes of potamodromous fish to their spawning areas, and energy generation changes natural flow seasonality, it is necessary to identify spawning areas and their conditions. This information will help in management decisions in the Magdalena River basin regarding the future hydropower development. We identified which characteristics of the tributaries to the Magdalena River are important for determining potamodromous fish spawning grounds, and we estimated the percentage of future loss of spawning areas because of dam development. Ichthyoplankton density is directly related to the floodplain area, and inversely related with channel slope. Low channel slopes offer adult fish a longer distance for their upstream migration and a longer time for embryo development during their drift downstream from the spawning areas to nursery habitats (floodplain lakes). These features could increase the migration distance of the adults, the time for initial embryo development, and, because of its relationship with nursery habitats access, the offspring survival. The potential loss of the actual spawning grounds in the river network was estimated to be nearly 70% because of new dams. Our findings will help to reduce conflicts between hydropower and ecological interests.
Keywords: Basin geomorphology, Conservation, Freshwater fish, Magdalena River, Reproductive migrations
La construcción de hidroeléctricas puede afectar la reproducción de los peces migratorios potamódromos, ya sea porque las represas bloquean las rutas migratorias a sus áreas de desove, o porque la generación de energía cambia la estacionalidad del flujo natural. Esto hace necesario generar información sobre las áreas de desove y sus características, que permitan tomar decisiones de manejo, teniendo en cuenta el desarrollo hidroeléctrico propuesto a futuro en la cuenca del río Magdalena. Identificamos qué características de algunos afluentes del río Magdalena son importantes para los desoves y estimamos el porcentaje de pérdida futura de áreas de desoves debido al desarrollo hidroeléctrico. La densidad del ictioplancton se relacionó directamente con el área de la llanura aluvial e inversamente con la pendiente del canal. Estas características aumentan la distancia de migración de los adultos maduros, el tiempo para el desarrollo inicial del embrión y la supervivencia de la descendencia debido a la proximidad y/o conectividad con los hábitats de cría. La pérdida potencial de las zonas de desove en la red fluvial se estimó en casi el 70% debido a las nuevas presas. Nuestros hallazgos ayudarán a tomar decisiones sostenibles para reducir los conflictos entre intereses de desarrollo hidroeléctrico y ecológicos.
Palavras-chave: Conservación, Geomorfología de cuenca, Migraciones reproductivas, Peces dulceacuícolas, Río Magdalena.
Introduction
Reproduction is a biological process that increases the abundance of a population (Begon et al., 2006). Freshwater fish present an extraordinary diversity of strategies and tactics to reproduce (Wootton, Smith, 2014). The decision on where and when fertilization will occur, and how much to invest in the care of embryos are examples of reproductive traits in fish (Welcomme et al., 2006). Similarly, habitat conditions allow fish with a specific body conformation; the environment provides the conditions under which an individual spawns and its embryos survive (Matthews, 1998). Some fish species lay few eggs inside nests and care for them until the larvae feed independently. Others spawn hundreds of thousands of oocytes, fertilization occurs in open waters, and the embryos drift with the currents. Based on these and other traits in fish life strategies, Winnemiller, Rose (1992) proposed three reproductive strategies; one of them, is the periodic (or seasonal) strategy. This strategy involves fish spawning in open areas and without parental care.
Only those fish whose bodily features, food, and reproductive preferences can be satisfied by the conditions provided by a single habitat may be residents of that habitat. When not all the traits “work” within the same conditions, a fish can use different habitats that satisfy the requirements it has in each of its development periods (Matthews, 1998). Those are called periodic species and use different habitats during their life cycles (Winemiller, Rose, 1992). The movements carried out between these habitats are called migrations, and in freshwaters, they are associated with the environmental conditions imposed by the hydrological seasonality in the basins (Lucas, Baras, 2001).
The most striking migrations are those made to find places to reproduce. Several of these migrations have been described in freshwater around the world (Lucas, Baras, 2001). In tropical freshwaters, individuals travel long distances from their growth and feeding habitats in search of places within each basin that provide adequate conditions for spawning, fertilization of the oocytes, and the survival of the embryos (Carolsfeld et al., 2003).
The Magdalena River basin has 234 fish species (DoNascimiento et al., 2018); 23 of them are recognized as migratory fish species (Usma et al., 2009; Zapata, Usma 2013; López-Casas et al., 2016). Half of these migratory fish species are important for the country’s inland fisheries (Lasso et al., 2011). These species migrate upstream twice a year from the floodplain habitats in the lowlands of the basin to the parental river and its tributaries (Jiménez-Segura et al., 2016; López-Casas et al., 2016) at a maximum of 1200 m.a.s.l. and spawn with the beginning of the floods (Jiménez-Segura et al., 2010). Their embryos drift downstream from the spawning habitat; incubate during the drift, and lateral flooding transports larvae into floodplain lakes, which serve as their nursery habitats (Jiménez-Segura et al., 2016).
In Colombia, hydropower is by far the country’s largest source of energy. Colombia’s hydropower system generated 57341.9 GWh, representing 86% of the total generation in the country (66667 GWh; UPME, 2018). The Magdalena River basin has a high hydropower potential because of its proximity to transmission infrastructure, and it is one of the top ten rivers that produce the largest renewable water supply in the world (https://www.mapsofworld.com/world-top-ten/world-top-ten-fresh-water-supply-map.html; last consulted December 21, 2020; Ledec, Quintero, 2003). The basin currently has 35 hydropower dams (~70% of the country generation), and more than 100 new dams could be installed based on the Colombian energy sector plans (Opperman et al., 2017).
The most recent hydropower construction in the Magdalena River basin had been located in channels at elevations below 1000 m, breaking the migratory circuit of fish and disrupting reproduction (Jiménez-Segura et al., 2014a). To facilitate evidence-based decision making for the conservation of Colombian aquatic biodiversity, we used ichthyoplankton density to identify where the migratory freshwater fish spawn in the Magdalena River Basin, which environmental characteristics determine spawning sites, and how the hydropower planning may affect those spawning areas. Our analysis tests two hypotheses: a) if environmental characteristics of tributaries influence the habitat selection for fish spawning and b) if the hydropower planning development may affect some of those tributaries as spawning areas. Our results highlight the importance of variables at geomorphological basin scale in the spawning intensity of the potamodromous fish in a tropical Andean river system and provide relevant information for decision-making in energy development planning in the Magdalena River basin, aimed at reducing the impacts of the industry on the diversity of the ichthyofauna, on the dynamics of fish populations and artisanal fisheries production.
Material and methods
Study area. The Magdalena River basin is located in the north-western region of the South American continent and is the largest hydrological basin in the northern Andes. It is entirely located in Colombia and has an extension of 257,438 km2, about a quarter of the country’s land area. It flows from South to North between the central and eastern Andes ranges between 3º and 11º North latitude and between 74º and 76º West longitude (Nie et al., 2010). It is unique worldwide because the three Andean branches generate one of the most complex aquatic systems in South America (Restrepo et al., 2020). With a 1612 km length from its source in the Andes, it discharges 7100 m3.s-1 of water and 144 Mt of sediment per year to the Caribbean Sea (Kettner et al., 2010). There are two main drainage areas, the Magdalena and Cauca Rivers, which each have 151 sub-basins, 42 of which are tributaries that drain directly into the Magdalena mainstream (Restrepo, Kjerfve, 2000; López-Casas et al., 2016). The watershed is characterized by high tectonic activity, hillslopes commonly exceeding 45º, landslides, steep gradients, and high relief tributary basins (Restrepo et al., 2006).
This basin has moderate rainfall with 2050 mm yr−1 on average, and an annual bimodal hydrological cycle with two rainy and two dry seasons. Water temperature changes with the altitude and the climatic seasons (Ramírez González, Viña-Vizacaíno, 1998). At elevations between 3500 and 500 m, the temperature is within a range between eight and 26.7 °C (Herrera-Pérez et al., 2019); in the main river at 135 m of elevation, the annual mean temperature is 27 °C (Jiménez-Segura, 2007) and in the floodplain lakes it can reach 37 °C (Restrepo et al., 2020).
Eighty percent of the population of Colombia inhabit the Magdalena basin, which carries a high environmental impact (Galvis, Mojica, 2007). Current trends for the Magdalena drainage basin include an increase in population densities; accelerated upland erosion rates due to poor agricultural practices, widespread deforestation, and mining (Restrepo et al., 2006). In addition, the Magdalena River basin has been the focus of many hydropower plants, most with dams higher than 15 m, and 32% are located between 0 and 1000 m in altitude (Jiménez-Segura et al., 2014b).
Fish species. Because of the spawning characteristics of the potamodromous fish species in the Magdalena River, the density of drifting ichthyoplankton (eggs and/or larvae) can be used to measure spawning intensity (King et al., 2016). Ichthyoplankton data of thirteen species were included: bocachico Prochilodus magdalenae Steindachner 1879, bagre rayado Pseudoplatystoma magdaleniatum Buitrago-Suarez & Burr, 2007, blanquillo Sorubim cuspicaudus Littmann, Burr & Nass, 2000, picuda Salminus affinis Steindachner, 1880, dorada Brycon moorei Steindachner, 1878, vizcaína Curimata mivartii Steindachner, 1878, moino Megaleporinus muyscorum (Steindachner, 1900), bagre sapo Pseudopimelodus bufonius (Valenciennes, 1840), sardina Psalidodon cf. fasciatus (Cuvier, 1819), arenca Triportheus magdalenae (Steindachner, 1878), pacora Plagioscion magdalenae (Steindachner, 1878) and one genera with two very similar species, difficult to identify in their first stages of life, capaz Pimelodus grosskopfii Steindachner, 1879 and barbudo Pimelodus yuma Villa-Navarro & Acero P., 2017.
Sampling design. In order to test which environmental parameters are related to the intensity of fish spawning, we selected ten tributaries of the Magdalena River based on discharge magnitude (less than 200 m3.s-1, between 201 and 500 m3.s-1, and more than 501 m3.s-1) and accessibility. This pool of ten included five tributaries of less than 200 m3.s-1 (Opón, Cesar, Boque, Espíritu Santo and Nechí rivers), four between 201 and 500 m3.s-1 (Samaná, Nare, Carare and Sogamoso rivers), and one bigger than 501 m3.s-1 of discharge (San Jorge River) (Fig. 1).
FIGURE 1 | Location of the sampling tributaries (black circles) in the Magdalena River basin. T01: Samaná River; T02: Nare River; T03: Espíritu Santo River; T04: Carare River; T05: Opón River; T06: Sogamoso River; T07: Boque River; T08: Nechí River; T09: San Jorge River and T10: Cesar River. Magdalena River runs north.
Ichthyoplankton sampling. Because spawning of potamodromous fish in the Magdalena River is highly seasonal (Barletta et al., 2015), ichthyoplankton samples were taken at the beginning of the two-yearly floods of the basin. Each day before 09:00 h during twenty consecutive days in September of 2013 (spawning after the second migration of the year) and May of 2014 (spawning after the first migration). Ichthyoplankton was collected with a conical–cylindrical plankton net (1.5 m long, 0.5 m mouth diameter, 400 μm mesh net tapering to collection jar), placed horizontally to filter against the flow for one minute at the highest velocity section of the channel; longer filtering times were not possible because of clogging of the net due to the high concentration of suspended sediment. The sampled volume was measured using a General Oceanics Inc. (Florida, USA) flowmeter fixed into the net mouth. Three samples were taken each day. Ichthyoplankton density was estimated as the sum of all the individuals collected per sample by the water filtered volume and related to ten cubic meters (ind.10m-3) (Tab. 1).
Ichthyoplankton samples were separated and grouped according to their development period and stage following Nakatani et al. (2001) in eggs, embryos, yolk sac larvae, larvae-preflexion, larvae-flexion and larvae-postflexion. Eggs and embryos were fixed in 96% alcohol for subsequent genetic identification, and the other larvae stage in a solution of buffered 4% formalin for subsequent taxonomic identification. Larval taxonomic identification was carried out using the keys of Nakatani et al. (2001) for neotropical groups (Order, Family, and Genera), and the key of Jiménez-Segura (2007) for Magdalena species as well as descriptions for some genera and species (Contreras, Contreras, 1989; Aristizabal-Regino et al., 2004; Atencio-García, 2005; Novoa, Cataño, 2005; Arias-Gallo et al., 2010; Valbuena-Villarreal et al., 2012; AUNAP, 2012). Eggs were separated according to the characteristics associated with spawning eggs of migratory species (open waters) according to Godinho et al. (2010): eggs laid in open and current areas and synchronous total spawns during the rising waters. To identify the species of the embryos, the sequences of the COI gene of the potamodromous fish species of the basin were defined following standard protocols (Hebert et al., 2003), and a coincidence analysis was carried out between the COI gene sequence of embryos and that of adult individuals, using PCR multiplex tests.
Geomorphological and physicochemical characteristics of the tributary basins. Nine non-redundant geomorphological and physicochemical variables were measured at the reach and basin-wide scales (Tab. 1). Reach scale includes in situ variables such as transparency, conductivity and water temperature measured in the field. Basin-wide scale variables include basin area, channel sinuosity, elevation, floodplain area, average channel slope and average flow were calculated from 90-m digital elevation models (DEM) covering the Colombian Andes. Forty-two layers of the U.S. Geological Survey were downloaded from http://gdem.ersdac.jspacesystems.or.jp and merged for further processing. Average flow data was calculated from the serial data flow of the Colombian Hydrological Institute “Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM)”.
TABLE 1 | Basin-scale geomorphic variables and local physicochemical variables that were examined as a part of this study. The average median density of ichthyoplankton per tributary is also presented.
Geomorphologic basin scale variables | Physicochemical reach scale variables | |||||||||
Tributary | Density (ind.10m-3) | Basin area (ha) | Channel sinuosity index | Elevation (msnm) | Floodplain area (ha) | Slope (%) | Flow (m3.s-1) | Conduc (µS) | Temp (°C) | Trans (cm) |
Samaná River | 0.00 | 1,153 | 1.40 | 175 | 0 | 13.04 | 278.4 | 52.8 | 25.3 | 26.5 |
Nare River | 0.51 | 5,606 | 1.51 | 130 | 1 | 12.82 | 409.7 | 25.6 | 24. | 28.4 |
Espíritu Santo River | 0.00 | 572 | 1.72 | 253 | 0 | 43.55 | NA | 77.5 | 23.38 | 11.8 |
Carare River | 4.65 | 6,556 | 1.42 | 94 | 515 | 5.82 | 275.7 | 240.6 | 28.7 | 7.7 |
Opón River | 3.49 | 2,164 | 1.57 | 84 | 509 | 7.34 | 64.3 | 208.8 | 27.9 | 4.9 |
Sogamoso River | 3.42 | 22,398 | 1.80 | 71 | 324 | 6.92 | NA | 167.0 | 26.0 | 3.2 |
Boque River | 0.18 | 803 | 1.35 | 43 | 60 | 9.26 | 45.5 | 62.7 | 24.7 | 13.5 |
Nechí River | 11.07 | 14,411 | 1.36 | 40 | 1,304 | 5.49 | 692.6 | 23.8 | 27.0 | 8.9 |
San Jorge River | 13.02 | 4,155 | 1.53 | 36 | 960 | 6.37 | 309.7 | 46.3 | 26.9 | 5.2 |
Cesar River | 24.66 | 9,617 | 1.64 | 30 | 1,684 | 3.29 | 171.8 | 165.5 | 28.9 | 9.1 |
To calculate the basin-wide scale variables: basin area, channel sinuosity, floodplain area, and average channel slope, we first derive the drainage paths and directions within the drainage basin using the hydrological ArcGis software tools. For this, we created a digital flow network with two derived grids for each watershed from the modified elevation model: a flow direction grid and a flow accumulation grid. To ensure the proper direction of flow across each basin, we made a hydrological correction using the function TopoGrid (Fransen et al., 2006). This function modifies the DEM in areas under hydrology stream vectors to force downstream flow. It assures hydrologically conditioned digital elevation models, so they can better represent actual flow across the landscape. After that, we create vectors delineating streams from the accumulated flow grid, assuming a minimum basin area of 1.5 ha to generate a channel (Fransen et al., 2006). Finally, we create 3D points for each sample site from coordinates taken in sampled localities with a Global Positioning System (GPS) Garmin Etrex 20x.
Channel sinuosity was expressed as a sinuosity index calculated by dividing the total length of the river channel between the length of a straight line between the highest and the lowest points of the river (Fukushima, 2001). For the mean floodplain extension estimation, we follow Hall et al. (2007) procedure, which calculates it as a function of valley topography, projecting the river height at the lowest point of the reach in the DEM and then calculating the area corresponding to that height and surrounding surfaces with low vertical relief (< 1 m) above the stream channel. This approach cannot replace in situ methods for providing accurate representative geometries at a single reach but can permit one to obtain the spatial variability (Beighley, Gummadi, 2011). ArcView® software was used to calculate geomorphological basin characteristics.
Location of the spawning area. To locate the reaches of the rivers used by migratory fish to spawn, we use a Tier 1 tool. The model uses the time it takes an individual (post-fertilization hours) to reach a period and stage of development as the drifting time, and average speed of the water at each stretch of the river (López-Casas et al., 2018).
Reservoir locality and the change in the spawning area. The model used to predict spawning areas is sensitive to infrastructure associated with barriers in water bodies. For our analysis, we used the database incorporated in the mathematical model that identifies large dams in the Magdalena-Cauca basin under the categories of projects in operation, projects under construction and possible future projects (López-Casas et al., 2018). The database for possible future projects corresponds to the one identified in the study of the electric power sector: inventory of hydroelectric resources developed for Colombia (DNP et al., 1979).
Statistical Analysis. To realize further analyses, we checked first for significant differences in ichthyoplankton density among tributaries using an ANOVA test. After that, we tested for relationships between geomorphological and physicochemical variables and the ichthyoplankton density with a squared multiple correlation analysis (SMC). Then, a multiple regression analysis, and separated simple linear regressions for significantly correlated variables were performed to evaluate the magnitude of the effect of these variables on ichthyoplankton density. To find differences in ichthyoplankton density among tributaries, the [boxplot]{boxplot} (Becker et al., 1988; Murrell, 2005) and [stats]{kruskal.test} were used for the boxplot and ANOVA test (Gibbons, Chakraborti, 2011). The [ltm] {rcor.test} function (Rizopoulos, 2006) was used to calculate the correlations and probabilities between variables, and the [psych] {smc} function (Revelle, 2014) to calculate the multiple correlations. The [SciViews] {panel.hist}, [SciViews] {panel.cor} and [SciViews] {panel.reg} functions (Grosjean, 2014) and [graphics] {pairs} for the graphic. To evaluate the independent variables (selected from the SMC analysis) contribution to regression model and their effect on ichthyoplankton density, the hierarchical partitioning algorithm of Chevan, Sutherland (1991) was conducted, using the [hier.part] {hier.part} function (Walsh, Mac Nally, 2013). Simple regression analyses were made with the [stats] {lmtest} function (Hothorn et al., 2015). All analyses were made using R version 3.3.2, and all the tests were conducted at a significance level of 0.05.
To ensure the validity of statistical analysis results, all variables were tested for normality using the Kolmogorov–Smirnov test through the function [nortest]{lillie.test} (Gross, 2015); autocorrelation among all the variables was tested using the Durbin-Watson test by the function [lmtest]{dwtest} (Hothorn et al., 2015); and Breusch-Pagan test was used to prove variance homogeneity using the function [lmtest]{bptest} (Hothorn et al., 2015). When assumptions were not satisfied, variables were log-transformed with the eqnln(variable-(min(variable)-1)) equation.
Results
Ichthyoplankton density was different among tributaries (Kruskal-Wallis H = 208.29, df = 9, p<2.2e-16; Fig. 2). In the Cesar and San Jorge rivers we detected the highest densities of eggs and larvae.
Geomorphologic determinants of spawning migrations. Only two significant correlations were found between the measured variables and ichthyoplankton density (Multiple Correlation R2 = 0.92, F = 21.62, df = 6, p = 0.001). A direct relation (positive correlation) was found between ichthyoplankton density and floodplain area (R = 0.95, p < 0.001) and an inverse relation (negative correlation) with the average stream slope (R = 0.81, p = 0.016) (Tab. 2; Fig. 3).
Floodplain area and channel slope explains 92% of the variability in the ichthyoplankton density in the Magdalena basin (R2 = 0.92, F= 40.4, p = 0.0001, df = 7). However, just the floodplain area was significantly influential in the model (multiple regression, β = 0.001, p = 0.005). The assumptions of normality (Kolmogorov-Smirnov test D = 0.14, p = 0.79), autocorrelation (Durbin-Watson test DW = 1.63, p =0.23) and homoscedasticity in the residuals (Breusch-Pagan test BP = 1.13, p = 0.56) were fulfilled. Simple linear regression for floodplain area and channel slope versus ichthyoplankton density were significant with a probability of 99%. Of the variability of ichthyoplankton density, 79% was explained by floodplain area (R2 = 0.79, F = 29.86, df = 8, p = 0.0005) and 65% for the slope (R2 = 0.65, F = 14.82, df = 8, p = 0.004). All the assumptions were fulfilled for both models (slope: K-S test D = 0.16, p = 0.62; D-W test DW = 1.03, p = 0.06; B-P test BP = 1.03, p = 0.06) (floodplain: K-S test D = 0.23, p = 0.13; D-W test DW = 1.93, p = 0.42; B-P test BP = 0.50, p = 0.47).
Location of the spawning area. According to our sampling design and the model used, potential spawning grounds for the 13 fish species analyzed accounted for a total of 7,278.8 km of rivers (Fig. 4A), including Strahler orders from three to eight (7.2 % of the 101,110 km of the total network).
Reservoir locality and the change in the spawning area. The potential spawning areas for the same 13 fish species under a scenario of full hydroelectric development in the Magdalena basin allows us to predict a loss of migratory spawning grounds of 68.3%, with just 2.3% of the rivers of the basin (2304.7 km of rivers) remaining as viable and connected spawning habitat (Fig. 4B).
FIGURE 2 | Spatial variation in the median density of ichthyoplankton among tributaries. (Kruskal-Wallis H = 208.29, df = 9, p-value < 2.2e-16). T01: Samaná River; T02: Nare River; T03: Espíritu Santo River; T04: Carare River; T05: Opón River; T06: Sogamoso River; T07: Boque River; T08: Nechí River; T09: San Jorge River and T10: Cesar River.
TABLE 2 | Correlation and p-values of the Squared Multiple Correlation (SMC) analysis. Upper diagonal part contains correlation coefficient estimates and the lower diagonal part contains corresponding p-values. Significant correlated variables (listed in bold) with density were then used for the multiple regression analysis.
Density | Basin | Sinuos | Height | Slope | Flood | Flow | Cond | Transp | Temp | |
Density | **** | 0.61 | 0.58 | -0.66 | -0.81 | 0.95 | 0.12 | 0.17 | -0.51 | 0.69 |
Basin | 0.11 | **** | 0.02 | -0.43 | -0.58 | 0.75 | 0.74 | -0.06 | -0.26 | 0.45 |
Sinuos | 0.13 | 0.97 | **** | -0.19 | -0.34 | 0.43 | -0.35 | 0.38 | -0.23 | 0.44 |
Height | 0.07 | 0.28 | 0.65 | **** | 0.81 | -0.72 | 0.02 | -0.07 | 0.77 | -0.43 |
Slope | 0.02 | 0.13 | 0.41 | 0.01 | **** | -0.88 | -0.02 | -0.49 | 0.88 | -0.87 |
Flood | <0.01 | 0.03 | 0.28 | 0.04 | <0.01 | **** | 0.26 | 0.18 | -0.64 | 0.74 |
Flow | 0.78 | 0.03 | 0.40 | 0.96 | 0.96 | 0.51 | **** | -0.51 | 0.16 | -0.05 |
Cond | 0.69 | 0.88 | 0.35 | 0.87 | 0.22 | 0.68 | 0.19 | **** | -0.52 | 0.75 |
Transp | 0.19 | 0.59 | 0.58 | 0.02 | <0.01 | 0.09 | 0.71 | 0.19 | **** | -0.76 |
Temp | 0.06 | 0.26 | 0.28 | 0.29 | <0.01 | 0.03 | 0.91 | 0.03 | 0.03 | **** |
FIGURE 3 | Correlations between geomorphological and physicochemical variables, and ichthyoplankton density. Basin: basin area, Sinuous: channel sinuosity index, Flood: floodplain area, Cond: conductivity, Trans: transparency, Temp: temperature. α = 0.05.
FIGURE 4 | Potential spawning grounds for 13 sampled potamodromous fish species of the Magdalena basin. A. Baseline (current) scenario, and B. Full hydroelectric projects development scenario.
Discussion
Geomorphological variables were shown to be determinant for spawning site selection, while no significant relationship of ichthyoplankton density with each effluent water characteristics was found. Mature individuals of potamodromous fish lay their eggs into the open waters in the river channel without nests construction or any parental care (Winemiller, Rose, 1992). This means that the local conditions tested in this study are unimportant in the selection of tributaries for spawn. In contrast, broad-scale variables of each river basin, such as slope and nearest floodplain area, were important because they determine the drifting distance, which is mediated by water velocity and, with that, the developmental stage of the embryos when reach nursery habitats. Water direction and velocity increase connectivity between important environments for the different phases of the fish life cycle, being responsible for driving eggs and very recently hatched larvae from spawning to nursery grounds (Lopes, Zaniboni-Filho, 2019). In addition, the proximity of the floodplains in these drifting reaches, increase the chance that river floods take the larvae into the floodplain lakes.
This study aimed to develop a better understanding of the spawning ground selection and reproductive migratory behavior of potamodromous tropical fish through the relation of local physicochemical and geomorphological basin scale variables with ichthyoplankton density. Furthermore, using a complementary tool allows analyzing hydropower development to choose project configurations at macro basin scale, we assess possibilities for minimizing impacts related to potential spawning areas in a basin. Although several studies of migratory fish spawning habitats have been made in temperate zones (Garbe et al., 2016; King et al., 2016; Thurow, 2016; Naus et al., 2018; Zhang et al., 2018; Harding et al., 2019), as far as we know, this study is the first of this kind in tropics.
Floodplain ecosystems are the most productive aquatic ecosystems in the tropics and maintain a great diversity and abundance of organisms, including several species of fishes that depend on them for completion of the life cycle (Harvey, Carolsfeld, 2003; Granado-Lorencio et al., 2012; White et al., 2012; Górski et al., 2014; Zacardi et al., 2017; Ben-Hasan et al., 2018). For potamodromous species, for example, the extension of floodplains and the amount of resources within them determines abundance (Gomes, Agostinho, 1997) and growth (López-Casas, 2015) for mature reproductive adults and offspring (Godinho et al., 2010, Reynalte-Tataje et al., 2013). This could explain why the tributaries with the most extensive floodplain areas presented higher ichthyoplankton densities. As the migrant reproductive populations live in those habitats, it is expected that tributaries connected to more extensive floodplains maintain a greater number of mature spawners and then a higher reproductive activity than those with a small, more remote floodplain area.
The habitats fish select for reproduction must be aimed to increase the survival of the offspring (Lassala, Renesto, 2007), ensuring that larvae reach the most suitable rearing habitats. For potamodromous fishes, this means spawning upstream of the greatest areas of inundated floodplains with the greatest production and abundance of food and shelter (Hamilton, 2002; Hall et al., 2007). Potamodromous fish are pelagic spawners with very high fecundities, and total spawning (Godinho et al., 2010). They inhabit the floodplain lakes where they feed and grow (Reynalte-Tataje et al., 2013) and carry out seasonally reproductive migrations to the main river and tributaries where they spawn (Jiménez-Segura et al., 2010). After spawning, both offspring and parents go downstream with the current to return to floodplains, which provide critical rearing and growth habitats (Junk et al., 1989; Marmulla, 2001; Jiménez-Segura et al., 2010; Reynalte-Tataje et al., 2012; Barzotto et al., 2015; López-Casas et al., 2016).
Our results suggest that reproductive adults probably migrate to rivers closer and better connected to their growth areas, allowing their larvae to get into the closer and more connected floodplain systems. If this is true, some genetic structure and a homing signal could be expected in those species. However, still if this behavior has not been described for species in the Magdalena basin, it has been proposed for other potamodromous Neotropical species (Sivasundar et al., 2001; Castro, Vari, 2004; Hatanaka et al., 2006; Sanches, Galetti Jr., 2007, 2012; Pereira et al., 2009; Barroca et al., 2012, Aguirre-Pabón et al., 2013; Berdugo, Narváez Barandica, 2014; Landínez-García, Márquez, 2016; Márquez Fernández et al., 2020) and some studies in the Magdalena basin found genetic populational structure between the main river and its tributaries for the bocachico, P. magdalenae, the pataló, Ichthyoelephas longirostris (Steindachner, 1879), the capaz, Pimelodus grosskopfii and the barbudo, Pimelodus yuma (= Pimelodus clarias) (Márquez Fernández et al., 2020) suggesting some kind of homing behavior, and supporting the idea of migrations to closer and more connected rivers to the growth areas. It has been proposed, notwithstanding, that genetic structure can be explained by spatial or temporal reproductive isolation, given the broad geographic scales and extreme weather events. In the Magdalena basin, isolation by distance (IBD) can be caused because of natural or artificial barriers. However, in absence of geographic barriers, as happens in the medium and lower sections of the Magdalena basin, isolation by time (IBT) can explain genetic structure, because of the bimodal hydrological behavior of the basin and the presence of several reproductive peaks of the species (Márquez Fernández et al., 2020).
Some studies, on the contrary, suggest that neotropical migratory freshwater fishes are panmictic populations or with a high gene flow between sub-basins or different sections of the basin (Sivasundar et al., 2001; Castro, Vari, 2004; Aguirre-Pabón et al., 2013, Márquez Fernández et al., 2020). In this regard, López-Casas et al. (2016) suggest that even if potamodromous fishes can present homing behavior, some populations or at least a portion of individuals into populations can migrate long distances through the Magdalena basin for spawning in more distant rivers. This could be explicated by the IBT concept, since temporal variations in hydrological and weather events, can make or erase geographical barriers for potamodromous fishes. As could be occurring in the Momposina depression in the lower section of the Magdalena basin, which depending on the hydrological moment and the intensities of rains can join or separate Cauca and Magdalena sub-basins (Jiménez-Segura et al., 2020). Hence, depending on the timing of migrations and reproductive peaks of different species will present genetic structure or not (Márquez Fernández et al., 2020). There is not enough evidence to support any of these hypothesis, and further studies will need to be undertaken.
In agreement with our results, different studies show that fish in temperate zones have lower spawning activity in steeper rivers (Moir et al., 1998, 2002; Montgomery et al., 1999; Merz, Setka, 2004; Louhi et al., 2008). The slope can be determinant for fish reproduction at different scales. At the local scale, slope influences the availability of suitable and more oxygenated places for egg deposition and successful incubation (Dauble, Geist, 2000), especially in temperate migratory fish which are nest spawners and have high requirements of habitat for their nest location (Pandian, 2010). At the basin scale, slope restrictions could be imposed for migrations itself, as steeper rivers affect the capability of fishes to reach higher places (Kruse et al., 1997; Dauble, Geist, 2000; Walters et al., 2003; Fransen et al., 2006). As potamodromous tropical fishes are open substratum pelagic spawners and lay numerous buoyant eggs into the current (Godinho et al., 2010), requirements at the local scale for parental fish or spawners are not so important as in temperate zones. The challenge for them may be the energy budget to move upstream a sufficient distance to enhance the survival of their offspring, because the longer the embryos drift, the longer time they will have to develop themselves during the downstream drift from their spawning grounds to the rearing areas. Larvae must travel the river to their nursery habitats in the floodplain before their yolk sac reserves run out. To take advantage of the food in the floodplains, the digestive system of the larvae must be already functional, and it must be sufficiently mobile to engage in foraging of available plankton and invertebrates. If fish larvae can not access the floodplain lakes in this critical developmental window, they will starve.
Channel slope seems to be a barrier and determines the fish capability to access the tributaries (Hall et al., 2007). The point at which a gradient becomes a barrier depends on the fish species. Cramer (2001) found that segments of rivers in which the gradient is greater than or equal to 20% for at least 200 m imperil Atlantic Salmon migration, but a limit of 10% in the channel slope has been found in other species as limiting to fish migration (Edds, 1993; Kruse et al., 1997). There is no information related to this for migratory fishes in the Magdalena basin. However, this study shows that slopes greater than 14% limit the migratory fish upstream movements, and rivers with higher slopes are less used as spawning areas than those with gentler slopes.
Although variables such as elevation, temperature, basin area, sinuosity, and conductivity are correlated with spawning habitats and migrations in temperate rivers (Moir et al., 1998, 2002; Montgomery et al., 1999; Merz, Setka, 2004; Louhi et al., 2008) as well as local physicochemical variables as flow, temperature and conductivity, which can act as a trigger of spawning and as a cue for fish spawning in tropics (Jiménez-Segura, 2007, Jiménez-Segura et al., 2010; Baran, Guerin, 2012; Zacardi et al., 2017; Rosa et al., 2018; King et al., 2019), no significant effect of these variables seems to exist on spawning activity in this study. We conclude that those variables do not influence migration and selection of tributaries used for reproduction. However, a significant relationship was found between elevation and temperature with the floodplain area and channel slope, so it is probable that those two variables indirectly capture the effects of other landscape-scale factors influencing the likelihood of fish presence. Streams at higher elevations tend to be steeper and colder and therefore may contain more barriers to upstream fish movements (Bozek, Hubert, 1992; Jaramillo-Villa et al., 2010; Carvajal-Quintero et al., 2015), and streams in lower areas tend to be in wider valleys that support bigger floodplain extensions and warmer waters (Junk, 1989).
Unlike temperate migratory fishes, spawning ground selection in tropical migratory species is not determined by physicochemical and geomorphological habitat characteristics at the spawning sites, but by the strength of the migration, which depends on the size of the migratory adult population inhabiting the floodplain lake systems connected to those rivers and on the capability of fishes to reach the tributaries, or potential barriers preventing fishes from reaching those tributaries. The species reproductive strategy determines different environmental constraints on fish in temperate systems. Most temperate migratory fish are nest constructing and need precise physical and chemical variables to ensure the development and survival of the offspring. However, tropical migratory fishes are pelagic spawners, and offspring survival depends on the favorable conditions at the nursery habitats more than in spawning ones, so those fishes need conditions to allow their offspring to reach rearing habitats in the floodplains. Even though this study was made in one basin in the tropics, we believe that these findings can be extended to other mountains’ tropical floodplain-river systems; nonetheless, further studies are needed.
We applied the Tier 1 model (López-Casas et al., 2018) to map the distribution of spawning grounds in the Magdalena basin in two different scenarios of hydropower development: current scenario, and full hydroelectric project development scenario. Our results of both modeling show that if the more than 100 new dams proposed in the Magdalena Basin are installed, 68.3% of the potential 7278.8 km of rivers used for our 13 studied migratory species will be lost, and a similar proportion of the spawning areas of the 10 non-studied remaining migratory species in the basin will be lost as well. This would aggravate the already delicate situation of the fisheries resource in the Magdalena Basin, on which a large part of the riparian population depends for both, economic incomes and as a protein source (more than 157,000 people are directly associated with fishing in the basin) (Valderrama-Barco et al., 2020).
We analyzed the effects of dam construction on the spawning area extension. However, it is well known that the effect of different environmental alterations is synergistic. Other alterations, such as deforestation, mining, erosion, poor agricultural practice, climate change, overfishing, non-native species introductions and eutrophication, affect the aquatic environment and its biota (Bunn, Arthington, 2002; Barletta et al., 2010) and can reduce the quantity and quality of these remaining spawning areas. An assessment of hydroelectric development scenarios in the Magdalena basin is beyond the scope of this study, nevertheless, we recognize that hydroelectric development will continue in the basin. We believe the Tier 1 model could be a useful tool to evaluate project configurations at the basin scale to minimize impacts on potential spawning areas in a basin and conserve the fishing resource, which is of great ecological and social importance.
As the Tier 1 model did not consider the density of ichthyoplankton, it gives equal importance to spawning habitat lost in the entire basin. Our results indicate that spawning habitat importance varies widely between tributaries, primarily in response to flooded areas and slopes. Taking this into account, we consider that the model could be improved, including ichthyoplankton densities, slope and floodplain areas, to be more precise in the location of these critical areas for the conservation of potamodromous species.
Finally, we would like to highlight that, in addition to the findings of various authors who have found a relationship between the physical and chemical conditions of the water with spawning in Neotropical fish, we found that spawning site selection for potamodromous fish is influenced mainly by geomorphological variables that mediate the time of embryo drift and development and the entrance of larva into the floodplains (nursery habitats); information that had not been previously identified or quantified before in Neotropical systems. However, because of the particularity of the Magdalena basin hydrogeomorphology and a more homogeneous geology, compared to other neotropical hydrological systems, certain reproductive strategies linked to geomorphology but not to physicochemical characteristics are favored. This is of particular importance, since, due to the construction of dams, the geomorphology of the basins would be affected and with them the availability of spawning areas. A critical next step is the identification and conservation of the most important migratory fish habitats in the basin. Given the many pressures the fisheries resource in the Magdalena basin faces today, and the additional impacts to come from hydroelectric projects proposed in the spawning area extension, as well as the importance of this resource for a significant proportion of the population settled in the basin, we emphasize and propose to use our results for better planning of the basin, which would allow hydroelectric development without compromising the conservation of the fish resource, and the livelihoods of the communities that depend on it.
Acknowledgments
This research was supported by the U.S. Agency for International Development (USAID) through The Nature Conservancy Colombia. We thank to J. Delgado for financial achieved management. We also thank A. Bialetzki and R. Leite, whose experience and comments greatly improved the research. To Scott Winton for English revision and suggestions. Finally, we thank our colleagues from the Laboratorio de Ictiología Universidad de Antioquia (GIUA) for assistance with field and laboratory work.
References
Aguirre-Pabón J, Narváez Barandica J, García LC. Mitochondrial DNA variation of the bocachico Prochilodus magdalenae (Characiformes, Prochilodontidae) in the Magdalena River Basin, Colombia. Aquat Conserv. 2013; 23(4):594–605. https://doi.org/10.1002/aqc.2339
Arias-Gallo M, Jiménez-Segura LF, Dorado MP. Desarrollo larval de Prochilodus magdalenae (Steindachner, 1879) (Pisces: Prochilodontidae), río Magdalena, Colombia. Actual Biol. 2010; 32(93):199–208. Available from: http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0304-35842010000200007&lng=en&tlng=en
Aristizabal-Regino J, Arabia-Ricardo F, Atencio-García VJ. Desarrollo embrionario y periodos larvarios de la dorada Brycon moorei sinuensis. Informe técnico. Montería, Colombia: Programa de Acuicultura, Universidad de Córdoba. 2004.
Atencio-García VJ. Descripción del desarrollo ontogénico y aspectos del alevinaje de la dorada (Brycon sinuensis Dahl, 1955). [Titular professor application work]. Córdoba: Universidad de Córdoba; 2005.
Autoridad Nacional de Acuicultura y Pesca (AUNAP). Aspectos básicos sobre reproducción y larvicultura en pataló (Ichthyoelephas longirostris) y Doncella (Ageneiosus pardalis). Neiva: Ministerio de Agricultura y Desarrollo Rural, Universidad Surcolombiana; 2012.
Baran E, Guerin E. Fish bioecology in relation to sediments in the Mekong and in tropical rivers. Phnom Penh: Project “A Climate Resilient Mekong: Maintaining the Flows that Nourish Life” led by the Natural Heritage Institute [Internet]. Phnom Penh; 2012. Available from: http://aquaticcommons.org/8732/1/WF_3137.pdf
Barletta M, Jaureguizar AJ, Baigun C, Fontoura NF, Agostinho AA, Almeida-Val VMF et al. Fish and aquatic habitat conservation in South America: A continental overview with emphasis on neotropical systems. J Fish Biol. 2010; 76(9):2118–76. https://doi.org/10.1111/j.1095-8649.2010.02684.x
Barletta M, Cussac VE, Agostinho AA, Baigún C, Okada EK, Carlos Catella A et al. Fisheries ecology in South American river basins. In: Craig JF, editor. Freshwater fisheries ecology. Wiley-Blackwell; 2015. p.311–48. https://doi.org/10.1002/9781118394380.ch27
Barroca TM, Arantes FP, Magalhães BF, Siqueira FF, Horta CCR, Pena IF et al. Genetic diversity and population structure of Prochilodus costatus and Prochilodus argenteus preceding dam construction in the Paraopeba River, São Francisco River Basin, Minas Gerais, Brazil. Open J Genet. 2012; 2(2):121–30. https://doi.org/10.4236/ojgen.2012.22017
Barzotto E, Sanches PV, Bialetzki A, Orvati L, Gomes LC. Larvae of migratory fish (Teleostei: Ostariophysi) in the lotic remnant of the Paraná River in Brazil. Zoologia (Curitiba). 2015; 32(4):270–80. http://dx.doi.org/10.1590/S1984-46702015000400002
Begon M, Townsend CR, Harper JL. Ecology: From individuals to ecosystems. 4th ed. Wiley-Blackwell; 2006.
Becker RA, Chambers JM, Wilks AR. The new S language: A programming environment for data analysis and graphics. Pacific Grove: Wadsworth & Brooks/Cole; 1988.
Beighley RE, Gummadi V. Developing channel and floodplain dimensions with limited data: A case study in the Amazon Basin. Earth Surf Process Landf. 2011; 36(8):1059–71. https://doi.org/10.1002/esp.2132
Ben-Hasan A, Walters C, Christensen V, Al-Husaini M, Al-Foudari H. Is reduced freshwater flow in Tigris-Euphrates rivers driving fish recruitment changes in the Northwestern Arabian Gulf? Mar Pollut Bull. 2018; 129(1):1–07. https://doi.org/10.1016/j.marpolbul.2018.02.012
Berdugo GO, Narváez Barandica JC. Genetic diversity and population structure of bocachico Prochilodus magdalenae (Pisces, Prochilodontidae) in the Magdalena River basin and its tributaries, Colombia. Genet Mol Biol. 2014; 37(1):37–45. http://dx.doi.org/10.1590/S1415-47572014000100008
Bozek MA, Hubert WA. Segregation of resident trout in streams as predicted by three habitat dimensions. Can J Zool. 1992; 70(5):886–90. https://doi.org/10.1139/z92-126
Bunn SE, Arthington AH. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manage. 2002; 30(4):492–507. https://doi.org/10.1007/s00267-002-2737-0
Castro RMC, Vari RP. Detritivores of South American fish family Prochilodontidae (Teleostei, Ostariophysi, Characiformes): A phylogenetic and revisionary study. Smithson Contrib Zool. 2004; 622:1–189. https://doi.org/10.5479/si.00810282.622
Carolsfeld J, Harvey B, Ross C, Baer A, editors. Migratory fishes of South America: Biology, fisheries, and conservation status. Canada: World Fisheries Trust, The Word Bank, International Development Research Centre; 2003.
Carvajal-Quintero JD, Escobar F, Alvarado F, Villa-Navarro FA, Jaramillo-Villa Ú, Maldonado-Ocampo JA. Variation in freshwater fish assemblages along a regional elevation gradient in the northern Andes, Colombia. Ecol Evol. 2015; 5(13):2608–20. https://doi.org/10.1002/ece3.1539
Chevan A, Sutherland M. Hierarchical Partitioning. Am Stat. 1991; 45(2):90–96. https://doi.org/10.2307/2684366
Contreras P, Contreras J. Desarrollo embrionario y larval del bagre rayado Pseudoplatystoma magdaleniatum (Linnaeus, 1776) (Pisces: Pimelodidae): Informe interno. Barrancabermeja: Inderena, Estación Piscícola de San Silvestre; 1989.
Cramer SP. The relationship of stream habitat features to potential for production of four salmonid species. Gresham: Urban Buffers [Internet]. Gresham; 2001.
Dauble DD, Geist DR. Comparison of mainstem spawning habitats for two populations of fall Chinook salmon in the Columbia River Basin. River Res. 2000; 16(4):345–61. Departamento Nacional de Planeación (DNP), FONADE, Fondo Nacional de Proyectos de Desarrollo, GTZ, Interconexión Eléctrica S.A., ISA, Sociedad Alemana de Cooperación Técnica. Estudio del sector Energía Eléctrica: Inventario de los recursos hidroeléctricos. Bogotá: DNP. Bogotá; 1979.
DoNascimiento C, Herrera Collazos EE, Maldonado-Ocampo J. Lista de especies de peces de agua dulce de Colombia / Checklist of the freshwater fishes of Colombia. Asociación Colombiana de Ictiólogos. Dataset/Checklist v. 2.10. [Internet]. 2018. http://doi.org/10.15472/numrso
Edds DR. Fish Assemblage Structure and Environmental Correlates in Nepal’s Gandaki River. Copeia. 1993; 1993(1):48–60. https://doi.org/10.2307/1446294
Fransen BR, Duke SD, McWethy LG, Walter JK, Bilby RE. A logistic regression model for predicting the upstream extent of fish occurrence based on geographical information systems data. N Am J Fish Manag. 2006; 26(4):960–75. https://doi.org/10.1577/M04-187.1
Fukushima M. Salmonid habitat–geomorphology relationships in low-gradient streams. Ecology. 2001; 82(5):1238–46. https://doi.org/10.2307/2679985
Galvis G, Mojica JI. The Magdalena River freshwater fishes and fisheries. Aquat Ecosyst Health Manag. 2007; 10(2):127–39. http://dx.doi.org/10.1080/14634980701357640
Garbe J, Beevers L, Pender G. The interaction of low flow conditions and spawning brown trout (Salmo trutta) habitat availability. Ecol Eng. 2016; 88:53–63. https://doi.org/10.1016/j.ecoleng.2015.12.011
Gibbons JD, Chakraborti S. Nonparametric statistical inference. In: Lovric M, editors. International encyclopedia of statistical science: Volume 1. Berlin, Heidelberg: Springer-Verlag; 2011. p.977–79. https://doi.org/10.1007/978-3-642-04898-2_420
Godinho AL, Lamas IR, Godinho HP. Reproductive ecology of Brazilian freshwater fishes. Environ Biol Fishes. 2010; 87(2):143–62. https://doi.org/10.1007/s10641-009-9574-4
Gomes LC, Agostinho AA. Influence of the flooding regime on the nutritional state and juvenile recruitment of the curimba, Prochilodus scrofa, Steindachner, in upper Paraná River, Brazil. Fish Manag Ecol. 1997; 4(4):263–74. https://doi.org/10.1046/j.1365-2400.1997.00119.x
Górski K, Collier KJ, Hamilton DP, Hicks BJ. Effects of flow on lateral interactions of fish and shrimps with off-channel habitats in a large river-floodplain system. Hydrobiologia. 2014; 729(1):161–74. https://doi.org/10.1007/s10750-012-1352-1
Granado-Lorencio C, Gulfo A, Alvarez F, Jiménez-Segura LF, Carvajal-Quintero JD, Hernández-Serna A. Fish assemblages in floodplain lakes in a Neotropical river during the wet season (Magdalena River, Colombia). J Trop Ecol. 2012; 28(3):271–79. https://www.jstor.org/stable/41510848
Gross J. Package ‘nortest’. Version 1.0-4 [Internet]. 2015. Available from: https://cran.r-project.org/web/packages/nortest/nortest.pdf
Grosjean P. SciViews: SciViews – Main package. Version 0.9-5 [Internet]. 2014. Available from: https://mran.revolutionanalytics.com/snapshot/2015-07-13/web/packages/SciViews/index.html
Hall JE, Holzer DM, Beechie TJ. Predicting river floodplain and lateral channel migration for salmon habitat conservation. J Am Water Resour Assoc. 2007; 43(3):786–97. https://doi.org/10.1111/j.1752-1688.2007.00063.x
Hamilton SK. Hydrological controls of ecological structure and function in the Pantanal wetland (Brazil). In: McClain ME, editor. The ecohydrology of South American rivers and wetlands. IHAS Special Publication no. 6: International Association of Hydrological Sciences; 2002. p.133–58.
Hatanaka T, Henrique-Silva F, Galetti Jr. PM. Population substructuring in a migratory freshwater fish Prochilodus argenteus (Characiformes, Prochilodontidae) from the São Francisco River. Genetica. 2006; 126(1):153–59. https://doi.org/10.1007/s10709-005-1445-0
Harding DJ, Roberts DT, Sternberg D, Mullins TM, Kennard MJ, Dwyer RG. Flow-related migration, juvenile dispersal and gonad development in two co-occurring mullet species, Mugil cephalus and Trachystoma petardi, in a regulated river system. Mar Freshw Res. 2019; 70(8):1105–15. https://doi.org/10.1071/MF18365
Harvey B, Carolsfeld J. Introduction: Fishes of the floods. In: Carolsfeld J, Harvey B, Ross C, Baer A, editors. Migratory fishes of South America: Biology, fisheries and conservation status. Canada: World Fisheries Trust, The Word Bank, International Development Research Centre; 2003. p.1–18. Available from: http://hdl.handle.net/10986/14929
Hebert PDN, Cywinska A, Ball SL, deWaard JR. Biological identifications through DNA barcodes. Proc R Soc Lond B Biol Sci. 2003; 270(1512):313–21. https://doi.org/10.1098/rspb.2002.2218
Herrera-Pérez J, Parra JL, Restrepo-Santamaría D, Jiménez-Segura LF. The influence of abiotic environment and connectivity on the distribution of diversity in an Andean fish fluvial network. Front Environ Sci. 2019; 7:09. https://doi.org/10.3389/fenvs.2019.00009
Hothorn T, Zeileis A, Farebrother RW, Cummins C, Millo G, Mitchell D. Pacakge ‘lmtest’. Version 0.9-34. [Internet]. 2015. Available from: https://cran.r-project.org/web/packages/lmtest/lmtest.pdf
Jaramillo-Villa U, Maldonado-Ocampo JA, Escobar F. Altitudinal variation in fish assemblage diversity in streams of the central Andes of Colombia. J Fish Biol. 2010; 76(10):2401–17. https://doi.org/10.1111/j.1095-8649.2010.02629.x
Jiménez-Segura LF. Ictioplancton y reproducción de los peces en la cuenca media del Río Magdalena (Sector de Puerto Berrio, Antioquia). [PhD Thesis]. Medellín: Universidad de Antioquia; 2007.
Jiménez-Segura LF, Palacio J, Leite R. River flooding and reproduction of migratory fish species in the Magdalena River basin, Colombia. Ecol Freshw Fish. 2010; 19(2):178–86. https://doi.org/10.1111/j.1600-0633.2009.00402.x
Jiménez-Segura LF, Maldonado-Ocampo JA, Pérez-Gallego CM. Gradiente de recuperación longitudinal en la estructura de la ictiofauna en un río andino regulado. Biota Colomb. 2014a; 15(2):61–80. Available from: http://revistas.humboldt.org.co/index.php/biota/article/view/321
Jiménez-Segura LF, Restrepo-Santamaría D, López-Casas S, Delgado J, Valderrama M, Álvarez J et al. Ictiofauna y desarrollo del sector hidroeléctrico en la cuenca del río Magdalena-Cauca, Colombia. Biota Colomb. 2014b;15(2):3–25. Available from: http://hdl.handle.net/20.500.11761/9452
Jiménez-Segura LF, Galvis-Vergara G, Cala-Cala P, García-Alzate CA, López-Casas S, Ríos-Pulgarín MI et al. Freshwater fish faunas, habitats and conservation challenges in the Caribbean river basins of north-western South America. J Fish Biol. 2016; 89(1):65–101. http://dx.doi.org/10.1111/jfb.13018
Jiménez-Segura L, Herrera-Pérez J, Valencia-Rodríguez D, Castaño-Tenorio I, López-Casas S, Ríos MI et al. Ecología e historias de vida de los peces en la cuenca del río Magdalena, Colombia. In: Jiménez-Segura L, Lasso CA, editors. XIX. Peces de la cuenca del río Magdalena, Colombia: Diversidad, conservación y uso sostenible. Bogotá D.C.: Serie Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 2020. p.159–204.
Junk WJ, Bayley PB, Sparks RE. The flood pulse concept in river-floodplain systems. In: Dodge DP, editor. Proceedings of the International Large River Symposium (LARS). Ontario: Canadian Special Publication of Fisheries and Aquatic Sciences 106; 1989. p.110–27.
Kettner AJ, Restrepo JD, Syvitski JD. A spatial simulation experiment to replicate fluvial sediment fluxes within the Magdalena River basin, Colombia. J Geol. 2010; 118(4):363–79. https://doi.org/10.1086/652659
King AJ, Gwinn DC, Tonkin Z, Mahoney J, Raymond S, Beesley L. Using abiotic drivers of fish spawning to inform environmental flow management. J Appl Ecol. 2016; 53(1):34–43. https://doi.org/10.1111/1365-2664.12542
King AJ, Doidge C, Buckle D, Tyler KJ. Preliminary evidence of spawning phenologies of freshwater fish in a wet–dry tropical river: the importance of both wet and dry seasons. Mar Freshw Res. 2019; 71(2):202–12. https://doi.org/10.1071/MF18458
Kruse CG, Hubert WA, Rahel FJ. Geomorphic influences on the distribution of Yellowstone cutthroat trout in the Absaroka Mountains, Wyoming. Trans Am Fish Soc. 1997; 126(3):418–27. Landínez-García RM, Márquez EJ. Development and characterization of 24 polymorphic microsatellite loci for the freshwater fish Ichthyoelephas longirostris (Characiformes: Prochilodontidae). PeerJ. 2016; 4:e2419. https://doi.org/10.7717/peerj.2419
Lassala MDP, Renesto E. Reproductive strategies and genetic variability in tropical freshwater fish. Genet Mol Biol. 2007; 30(3):690–97. http://dx.doi.org/10.1590/S1415-47572007000400030
Lasso CA, Agudelo Córdoba E, Jiménez-Segura LF, Ramírez-Gil H, Morales-Betancourt M, Ajiaco-Martínez RE et al, editors. I. Catálogo de los recursos pesqueros continentales de Colombia. Bogotá D.C.: Serie Editorial Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt (IAvH); 2011.
Ledec G, Quintero JD. Good dams and bad dams: Environmental criteria for site selection of hydroelectric projects. The World Bank: Latin A\merica and Caribbean Region – Sustainable Development Working Paper 16 [Internet]. 2003. Available from: http://hdl.handle.net/10986/20226
Lopes CA, Zaniboni-Filho E. Mosaic environments shape the distribution of Neotropical freshwater ichthyoplankton. Ecol Freshw Fish. 2019; 28(4):544–53. https://doi.org/10.1111/eff.12473
López-Casas S. Magdalena potamodromous migrations: Effects of regulated and natural hydrological regimes. [PhD Thesis]. Medellín: Universidad de Antioquia; 2015. Available from: http://bibliotecadigital.udea.edu.co/dspace/bitstream/10495/5651/1/SilviaLopezCasas_2015_MagdalenaPotadromousMigrations.pdf
López-Casas S, Rogeliz-Prada CA, Angarita H, Jiménez-Segura LF, Moreno-Arias C. Modelling potential spawning grounds for Magdalena basin potamodromous fish: A tier 1 tool for environmental impact assessment of hydropower projects. Tokyo: 12th International Symposium on Ecohydraulics; 2018.
López-Casas S, Jiménez-Segura LF, Agostinho AA, Pérez CM. Potamodromous migrations in the Magdalena River basin: Bimodal reproductive patterns in neotropical rivers. J Fish Biol. 2016; 89(1):157–71. https://doi.org/10.1111/jfb.12941
Louhi P, Mäki-Petäys A, Erkinaro J. Spawning habitat of Atlantic salmon and brown trout: General criteria and intragravel factors. River Res Appl. 2008; 24(3):330–39. https://doi.org/10.1002/rra.1072
Lucas M, Baras E. Migration of freshwater fishes. Oxford: Blackwell Science; 2001.
Marmulla G, editor. Dams, fish and fisheries: Opportunities, challenges and conflict resolution. Rome: FAO Fisheries Technical Paper. No. 419 [Internet]. Rome: FAO; 2001. Available from: http://www.fao.org/docrep/004/Y2785E/y2785e01a.htm
Márquez Fernández EJ, Restrepo-Escobar N, Yepes-Acevedo AJ, Narváez-Barandica JC. Diversidad y estructura genética de los peces de la cuenca del río Magdalena, Colombia. In: Jiménez-Segura L, Lasso CA, editors. XIX. Peces de la cuenca del río Magdalena, Colombia: Diversidad, conservación y uso sostenible. Bogotá D.C.: Serie Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 2020. p.115–58.
Matthews WJ. Patterns in freshwater fish ecology. Boston: Springer; 1998. https://doi.org/10.1007/978-1-4615-4066-3
Merz JE, Setka JD. Evaluation of a spawning habitat enhancement site for Chinook salmon in a regulated California river. N Am J Fish Manag. 2004; 24(2):397–407. http://dx.doi.org/10.1577/M03-038.1
Moir HJ, Soulsby C, Youngson A. Hydraulic and sedimentary characteristics of habitat utilized by Atlantic salmon for spawning in the Girnock Burn, Scotland. Fish Manag Ecol. 1998; 5(3):241–54. https://doi.org/10.1046/j.1365-2400.1998.00105.x
Moir HJ, Soulsby C, Youngson AF. Hydraulic and sedimentary controls on the availability and use of Atlantic salmon (Salmo salar) spawning habitat in the River Dee system, north-east Scotland. Geomorphology. 2002; 45(3–4):291–308. https://doi.org/10.1016/S0169-555X(01)00160-X
Montgomery DR, Beamer EM, Pess GR, Quinn TP. Channel type and salmonid spawning distribution and abundance. Can J Fish Aquat Sci. 1999; 56(3):377–87. https://doi.org/10.1139/f98-181
Murrell P. R Graphics. Boca Raton: Chapman & Hall/CRC; 2005.
Nakatani K, Agostinho AA, Baumgartner G, Bialetzki A, Sanches PV, Makrakis MC et al. Ovos e larvas de peixes de água doce: Desenvolvimento e manual de identificação. Maringá: Eletrobrás, UEM; 2001.
Naus CJ, Reid Adams S. Fish nursery habitat function of the main channel, floodplain tributaries and oxbow lakes of a medium-sized river. Ecol Freshw Fish. 2018; 27(1):4–18. https://doi.org/10.1111/eff.12319
Nie J, Horton BK, Mora A, Saylor JE, Housh TB, Rubiano J, Naranjo J. Tracking exhumation of Andean ranges bounding the Middle Magdalena Valley basin, Colombia. Geology. 2010; 38(5):451–54. https://doi.org/10.1130/G30775.1
Novoa JD, Cataño Y. Descripción del desarrollo embrionario y larvario del blanquillo Sorubim cuspicaudus (Littman, Burr y Nass, 2000). [Undergraduate Dissertation]. Montería: Universidad de Córdoba; 2005.
Opperman J, Hartmann J, Raepple J. The power of rivers: A business case. The Nature Conservancy [Internet]. Washington (DC); 2017. Available from: http://seforall.org/sites/default/files/powerofriversreport_final1.pdf
Pandian TJ. Sexuality in fishes. Enfield: Science Publishers; 2010. https://doi.org/10.1201/EBK1578086856
Pereira LHG, Foresti F, Oliveira C. Genetic structure of the migratory catfish Pseudoplatystoma corruscans (Siluriformes, Pimelodidae) suggests homing behaviour. Ecol Freshw Fish. 2009; 18(2):215–25. https://doi.org/10.1111/j.1600-0633.2008.00338.x
Ramírez González A, Viña-Vizcaíno G. Limnología Colombiana: Aportes a su conocimiento y estadísticas de análisis. Colombia: Editorial Panamericana; 1998.
Restrepo JD, Kjerfve B. Magdalena River: Interannual variability (1975–1995) and revised water discharge and sediment load estimates. J Hydrol (Amst). 2000; 235(1–2):137–49. https://doi.org/10.1016/S0022-1694(00)00269-9
Restrepo JD, Kjerfve B, Hermelin M, Restrepo JC. Factors controlling sediment yield in a major South American drainage basin: The Magdalena River, Colombia. J Hydrol (Amst). 2006; 316(1–4):213–32. https://doi.org/10.1016/j.jhydrol.2005.05.002
Restrepo JD, Cárdenas-Rozo A, Paniagua-Arroyave JF, Jiménez-Segura L. Aspectos físicos de la cuenca del río Magdalena, Colombia: Geología, hidrología, sedimentos, conectividad, ecosistemas acuáticos e implicaciones para la biota. In: Jiménez-Segura L, Lasso CA, editors. XIX. Peces de la cuenca del río Magdalena, Colombia: Diversidad, conservación y uso sostenible. Bogotá D.C.: Serie Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 2020. p.41–84.
Revelle W. psych: Procedures for psychological, psychometric, and personality research. Version 1.4.5 [Internet]. 2014. Available from: http://CRAN.R-project.org/package=psych
Reynalte-Tataje DA, Agostinho AA, Bialetzki A, Hermes-Silva S, Fernandes R, Zaniboni-Filho E. Spatial and temporal variation of the ichthyoplankton in a subtropical river in Brazil. Environ Biol Fishes. 2012; 94(2):403–19. https://doi.org/10.1007/s10641-011-9955-3
Reynalte-Tataje DA, Agostinho AA, Bialetzki A. Temporal and spatial distributions of the fish larval assemblages of the Ivinheima River sub-basin (Brazil). Environ Biol Fishes. 2013; 96(7):811–22. https://doi.org/10.1007/s10641-012-0073-7
Rizopoulos D. ltm: An R package for latent variable modelling and item response analysis. J Stat Softw. 2006; 17(5):1–25. http://dx.doi.org/10.18637/jss.v017.i05
Rosa GR, Salvador GN, Bialetzki A, Santos GB. Spatial and temporal distribution of ichthyoplankton during an unusual period of low flow in a tributary of the São Francisco River, Brazil. River Res Appl. 2018; 34(1):69–82. https://doi.org/10.1002/rra.3225
Sanches A, Galetti Jr. PM. Genetic evidence of population substructuring in the neotropical freshwater fish Brycon hilarii (Valenciennes, 1850). Braz J Biol. 2007; 67(4 Suppl):889–95. https://doi.org/10.1590/S1519-69842007000500012
Sanches A, Galetti Jr. PM. Population genetic structure revealed by a school of the freshwater migratory fish, Brycon hilarii. Lat Am J Aquat Res. 2012; 40(2):408–17.
Sivasundar A, Bermingham E, Ortí G. Population structure and biogeography of migratory freshwater fishes (Prochilodus, Characiformes) in major South American rivers. Mol Ecol. 2001; 10(2):407–17. https://doi.org/10.1046/j.1365-294X.2001.01194.x
Thurow RF. Life history of potamodromous fishes. In: Morais P, Daverat F, editors. An introduction to fish migration. Boca Raton: CRC Press; 2016. p.29–54.
Unidad de Planeación Minero Energética (UPME). Boletín estadístico de minas y energía 2016–2018. Colombia: Ministerio de Minas y Energia [Internet]. Colombia; 2018. Available from: https://www1.upme.gov.co/PromocionSector/SeccionesInteres/Documents/Boletines/Boletin_Estadistico_2018.pdf
Usma JS, Valderrama M, Escobar MD, Ajiaco-Martínez RE, Villa-Navarro F, Castro F et al. Peces dulceacuícolas migratorios en Colombia. In: Naranjo LG, Amaya-Espinel JD, editors. Plan Nacional de las especies migratorias: Diagnóstico e identificación de acciones para la conservación y el manejo sostenible de las espécies migratórias de la biodiversidade em Colombia. Bogotá D.C.: Ministerio de Ambiente, Vivienda y Desarrollo Territorial, WWF Colombia; 2009. p.103–32. Available from: http://d2ouvy59p0dg6k.cloudfront.net/downloads/plan_migratorias_version_web.pdf
Valbuena-Villarreal RD, Zapata-Berruecos BE, David-Ruales C, Cruz-Casallas PE. Desarrollo embrionario del capaz Pimelodus grosskopfii (Steindachner, 1879). Int J Morphol. 2012; 30(1):150–56. http://dx.doi.org/10.4067/S0717-95022012000100027
Valderrama-Barco M, Escobar-Cardona JL, Pardo BR, Toro SM, Gutiérrez CJC, López-Casas S. Servicios ecosistémicos generados por los peces de la cuenca del río Magdalena, Colombia. In: Jiménez-Segura LF, Lasso CA, editors. XIX. Peces de la cuenca del río Magdalena, Colombia: Diversidad, conservación y uso sostenible. Bogotá D.C.: Serie Recursos Hidrobiológicos y Pesqueros Continentales de Colombia. Instituto de Investigación de Recursos Biológicos Alexander von Humboldt; 2020. p.205–36.
Walsh C, Mac Nally R. hier.part: Hierarchical Partitioning. Version 1.0-4. [Internet]. 2013. Available from: http://CRAN.R-project.org/package=hier.part
Walters DM, Leigh DS, Freeman MC, Freeman BJ, Pringle CM. Geomorphology and fish assemblages in a Piedmont River basin, U.S.A. Freshw Biol. 2003; 48(11):1950–70. https://doi.org/10.1046/j.1365-2427.2003.01137.x
Welcomme RL, Winemiller KO, Cowx IG. Fish environmental guilds as a tool for assessment of ecological condition of rivers. River Res Appl. 2006; 22(3):377–96. https://doi.org/10.1002/rra.914
White SM, Ondra-ková M, Reichard M. Hydrologic connectivity affects fish assemblage structure, diversity, and ecological traits in the unregulated Gambia River, West Africa. Biotropica. 2012; 44(4):521–30. https://doi.org/10.1111/j.1744-7429.2011.00840.x
Winemiller KO, Rose KA. Patterns of life history diversification in North American fishes: Implications for population regulation. Can J Fish Aquat Sci. 1992; 49 (10):2196–218. https://doi.org/10.1139/f92-242
Wootton R, Smith C. Reproductive biology of teleost fishes. Chichester: Wiley-Blackwell; 2014. Available from: https://doi.org/10.1002/9781118891360
Zacardi DM, Ponte SCS, Ferreira LC, Lima MAS, Silva AJS, Chaves CS. Diversity and spatio-temporal distribution of the ichthyoplankton in the lower Amazon River, Brazil. Biota Amazônia. 2017; 7(2):12–20.
Zapata LA, Usma JS, editors. Guía de las especies migratorias de la biodiversidad en Colombia: Volumen 2 – Peces. Bogotá, DC.: Ministerio de Ambiente y Desarrollo Sostenible, WWF-Colombia: Colombia; 2013. Available from: http://awsassets.panda.org/downloads/migratoriaspeces_42_web_final.pdf
Zhang P, Yang Z, Cai L, Qiao Y, Chen X, Chang J. Effects of upstream and downstream dam operation on the spawning habitat suitability of Coreius guichenoti in the middle reach of the Jinsha River. Ecol Eng. 2018; 120:198–208. https://doi.org/10.1016/j.ecoleng.2018.06.002
Authors
Cintia Moreno-Arias1 , Silvia López-Casas2, Carlos A. Rogeliz-Prada2 and Luz Jiménez-Segura1
[1] Grupo de ictiología, Universidad de Antioquia. Calle 67 #53-108, 050010 Medellín, ANT, Colombia. (CMA)
morenocintia@gmail.com (corresponding author), (LJS) luz.jimenez@udea.edu.co.
[2] The Nature Conservancy, Calle 67 No 7 – 94, piso 3, 110231 Bogotá D.C., Colombia. (SLC) silvilopezcasas@yahoo.com, (CRP) carlos.rogeliz@tnc.org.
Authors Contribution
Cintia Moreno-Arias: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing-original draft, Writing-review and editing.
Silvia López-Casas: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing-original draft, Writing-review and editing.
Carlos A. Rogeliz-Prada: Formal analysis, Investigation, Methodology, Visualization, Writing-original draft, Writing-review and editing.
Luz Jiménez-Segura: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing-original draft, Writing-review and editing.
Ethical Statement
The care and use of experimental animals complied with the Colombian Ministry of Environment and Sustainable Development (MinAmbiente) animal welfare laws, guidelines, and policies as approved by National Aquaculture and Fisheries Authority (AUNAP) through resolution 986 of 2013.
Competing Interests
The authors declare no competing interests.
How to cite this article
Moreno-Arias C, López-Casas S, Rogeliz-Prada CA, Jiménez-Segura L. Protection of spawning habitat for potamodromous fish, an urgent need for the hydropower planning in the Andes. Neotrop Ichthyol. 2021; 19(3):e210027. https://doi.org/10.1590/1982-0224-2021-0027
Copyright
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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© 2021 The Authors.
Diversity and Distributions Published by SBI
Accepted May 24, 2021 by Paulo Pompeu
Submitted January 22, 2021
EpubOctober 08, 2021