130 research outputs found

    Microhabitat competition between Iberian fish species and the endangered Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866)

    Full text link
    "This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Ecohydraulics on 24-01-2017, available online: https://www.tandfonline.com/doi/full/10.1080/24705357.2016.1276417"[EN] Competition with invasive species is recognized as having a major impact on biodiversity conservation. The upper part of the Cabriel River (Eastern Iberian Peninsula) harbours the most important population of the Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866), a fish species in imminent danger of extinction. Currently, this species cohabits with several non-native species, such as the Iberian nase (Pseudochondrostoma polylepis; Steindachner, 1864) and the bermejuela (Achondrostoma arcasii; Steindachner, 1866). The potential habitat competition with these species was studied by analysing the spatial and temporal overlapping of suitable microhabitats. Generalized Additive Mixed Models (GAMMs) were developed to model microhabitat selection and these GAMMs were used to assess the habitat suitability (i.e. probability of presence) under several flows simulated with River2D. The Júcar nase will compete, spatially and temporally, for the few suitable microhabitats with bermejuela and, to a lesser extent, with small Iberian nase; conversely, large Iberian nase was of minor concern, due to increased differences in habitat preferences. This study represents an important assessment of potential competition and, therefore, these results might assist to better define future management practices in the upper part of the Cabriel River.This study was funded by the Spanish Ministry of Economy and Competitiveness through the SCARCE project (Consolider Ingenio 2010 CSD2009 00065); the Universitat Politècnica de València, through the project UPPTE/2012/294 [PAID 06 12]; it was also partially funded by the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economía y Competitividad) and FEDER funds. The authors would like to thank the help of the Conselleria de Territori i Vivenda (Generalitat Valenciana) and the Confederación Hidrográfica del Júcar (Spanish government), which provided environmental data to Alfredo Ollero, and the two anonymous reviewers who first suggested the submission of the paper to a regular journal. Finally, we would like to thank TECNOMA S.A. for the development of the hydraulic model.Muñoz Mas, R.; Soares Costa, RM.; Alcaraz-Hernández, JD.; Martinez-Capel, F. (2017). Microhabitat competition between Iberian fish species and the endangered Júcar nase (Parachondrostoma arrigonis; Steindachner, 1866). Journal of Ecohydraulics. 2(1):3-15. https://doi.org/10.1080/24705357.2016.1276417S31521Alcaraz, C., Carmona-Catot, G., Risueño, P., Perea, S., Pérez, C., Doadrio, I., & Aparicio, E. (2014). Assessing population status of Parachondrostoma arrigonis (Steindachner, 1866), threats and conservation perspectives. Environmental Biology of Fishes, 98(1), 443-455. doi:10.1007/s10641-014-0274-3ALMEIDA, D., & GROSSMAN, G. D. (2012). Utility of direct observational methods for assessing competitive interactions between non-native and native freshwater fishes. Fisheries Management and Ecology, 19(2), 157-166. doi:10.1111/j.1365-2400.2012.00847.xAlmeida, D., Merino-Aguirre, R., Vilizzi, L., & Copp, G. H. (2014). Interspecific Aggressive Behaviour of Invasive Pumpkinseed Lepomis gibbosus in Iberian Fresh Waters. PLoS ONE, 9(2), e88038. doi:10.1371/journal.pone.0088038Anderson, D. R., Burnham, K. P., & Thompson, W. L. (2000). Null Hypothesis Testing: Problems, Prevalence, and an Alternative. The Journal of Wildlife Management, 64(4), 912. doi:10.2307/3803199Aparicio, E., Vargas, M. J., Olmo, J. M., & de Sostoa, A. (2000). Environmental Biology of Fishes, 59(1), 11-19. doi:10.1023/a:1007618517557Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys, 4(0), 40-79. doi:10.1214/09-ss054Austin, M. (2007). Species distribution models and ecological theory: A critical assessment and some possible new approaches. Ecological Modelling, 200(1-2), 1-19. doi:10.1016/j.ecolmodel.2006.07.005Baltz, D. M., Vondracek, B., Brown, L. R., & Moyle, P. B. (1991). Seasonal Changes in Microhabitat Selection by Rainbow Trout in a Small Stream. Transactions of the American Fisheries Society, 120(2), 166-176. doi:10.1577/1548-8659(1991)1202.3.co;2Barbet-Massin, M., Jiguet, F., Albert, C. H., & Thuiller, W. (2012). Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution, 3(2), 327-338. doi:10.1111/j.2041-210x.2011.00172.xBeakes, M. P., Moore, J. W., Retford, N., Brown, R., Merz, J. E., & Sogard, S. M. (2012). EVALUATING STATISTICAL APPROACHES TO QUANTIFYING JUVENILE CHINOOK SALMON HABITAT IN A REGULATED CALIFORNIA RIVER. River Research and Applications, 30(2), 180-191. doi:10.1002/rra.2632BROOK, B., SODHI, N., & BRADSHAW, C. (2008). Synergies among extinction drivers under global change. Trends in Ecology & Evolution, 23(8), 453-460. doi:10.1016/j.tree.2008.03.011Brosse, S., Laffaille, P., Gabas, S., & Lek, S. (2001). Is scuba sampling a relevant method to study fish microhabitat in lakes? Examples and comparisons for three European species. Ecology of Freshwater Fish, 10(3), 138-146. doi:10.1034/j.1600-0633.2001.100303.xCLAVERO, M. (2011). Assessing the risk of freshwater fish introductions into the Iberian Peninsula. Freshwater Biology, 56(10), 2145-2155. doi:10.1111/j.1365-2427.2011.02642.xCollares-Pereira, M. J., & Coelho, M. M. (1983). Biometrical analysis of Chondrostoma polylepis x Rutilus arcasi natural hybrids (Osteichthyes-Cypriniformes-Cyprinidae). Journal of Fish Biology, 23(5), 495-509. doi:10.1111/j.1095-8649.1983.tb02930.xCosta, R. M. S., Martínez-Capel, F., Muñoz-Mas, R., Alcaraz-Hernández, J. D., & Garófano-Gómez, V. (2011). HABITAT SUITABILITY MODELLING AT MESOHABITAT SCALE AND EFFECTS OF DAM OPERATION ON THE ENDANGERED JúCAR NASE, PARACHONDROSTOMA ARRIGONIS (RIVER CABRIEL, SPAIN). River Research and Applications, 28(6), 740-752. doi:10.1002/rra.1598Dal Pozzolo A, Caelen O, Bontempi G. 2015. unbalanced: Racing for unbalanced methods selection. R package version 2.0.Elith, J., & Leathwick, J. R. (2009). Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics, 40(1), 677-697. doi:10.1146/annurev.ecolsys.110308.120159Elvira, B., & Almodovar, A. (2001). Freshwater fish introductions in Spain: facts and figures at the beginning of the 21st century. Journal of Fish Biology, 59(sa), 323-331. doi:10.1111/j.1095-8649.2001.tb01393.xElvira, B., & Almodóvar, A. (2006). Threatened fishes of the world: Chondrostoma arrigonis (Steindachner, 1866) (Cyprinidae). Environmental Biology of Fishes, 81(1), 27-28. doi:10.1007/s10641-006-9172-7Friedman, J. H. (2001). machine. The Annals of Statistics, 29(5), 1189-1232. doi:10.1214/aos/1013203451Fukuda, S., De Baets, B., Waegeman, W., Verwaeren, J., & Mouton, A. M. (2013). Habitat prediction and knowledge extraction for spawning European grayling (Thymallus thymallus L.) using a broad range of species distribution models. Environmental Modelling & Software, 47, 1-6. doi:10.1016/j.envsoft.2013.04.005Girard, V., Monti, D., Valade, P., Lamouroux, N., Mallet, J.-P., & Grondin, H. (2013). HYDRAULIC PREFERENCES OF SHRIMPS AND FISHES IN TROPICAL INSULAR RIVERS. River Research and Applications, 30(6), 766-779. doi:10.1002/rra.2675Gozlan, R. E., Britton, J. R., Cowx, I., & Copp, G. H. (2010). Current knowledge on non-native freshwater fish introductions. Journal of Fish Biology, 76(4), 751-786. doi:10.1111/j.1095-8649.2010.02566.xGuay, J. C., Boisclair, D., Rioux, D., Leclerc, M., Lapointe, M., & Legendre, P. (2000). Development and validation of numerical habitat models for juveniles of Atlantic salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences, 57(10), 2065-2075. doi:10.1139/f00-162Guisan, A., Graham, C. H., Elith, J., & Huettmann, F. (2007). Sensitivity of predictive species distribution models to change in grain size. Diversity and Distributions, 13(3), 332-340. doi:10.1111/j.1472-4642.2007.00342.xHeggenes, J., Brabrand, Åg., & Saltveit, S. (1990). Comparison of Three Methods for Studies of Stream Habitat Use by Young Brown Trout and Atlantic Salmon. Transactions of the American Fisheries Society, 119(1), 101-111. doi:10.1577/1548-8659(1990)1192.3.co;2Jowett, I. G., & Davey, A. J. H. (2007). A Comparison of Composite Habitat Suitability Indices and Generalized Additive Models of Invertebrate Abundance and Fish Presence–Habitat Availability. Transactions of the American Fisheries Society, 136(2), 428-444. doi:10.1577/t06-104.1Jowett, I. G., & Duncan, M. J. (2012). Effectiveness of 1D and 2D hydraulic models for instream habitat analysis in a braided river. Ecological Engineering, 48, 92-100. doi:10.1016/j.ecoleng.2011.06.036Laurikkala, J. (2001). Improving Identification of Difficult Small Classes by Balancing Class Distribution. Lecture Notes in Computer Science, 63-66. doi:10.1007/3-540-48229-6_9Leunda, P. (2010). Impacts of non-native fishes on Iberian freshwater ichthyofauna: current knowledge and gaps. Aquatic Invasions, 5(3), 239-262. doi:10.3391/ai.2010.5.3.03Lin, X., & Zhang, D. (1999). Inference in generalized additive mixed modelsby using smoothing splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 61(2), 381-400. doi:10.1111/1467-9868.00183Liu, C., Berry, P. M., Dawson, T. P., & Pearson, R. G. (2005). Selecting thresholds of occurrence in the prediction of species distributions. Ecography, 28(3), 385-393. doi:10.1111/j.0906-7590.2005.03957.xMaceda-Veiga, A. (2012). Towards the conservation of freshwater fish: Iberian Rivers as an example of threats and management practices. Reviews in Fish Biology and Fisheries, 23(1), 1-22. doi:10.1007/s11160-012-9275-5Maggini, R., Lehmann, A., Zimmermann, N. E., & Guisan, A. (2006). Improving generalized regression analysis for the spatial prediction of forest communities. Journal of Biogeography, 33(10), 1729-1749. doi:10.1111/j.1365-2699.2006.01465.xMarr, S. M., Olden, J. D., Leprieur, F., Arismendi, I., Ćaleta, M., Morgan, D. L., … García-Berthou, E. (2013). A global assessment of freshwater fish introductions in mediterranean-climate regions. Hydrobiologia, 719(1), 317-329. doi:10.1007/s10750-013-1486-9MARTÍNEZ-CAPEL, F., GARCÍA DE JALÓN, D., WERENITZKY, D., BAEZA, D., & RODILLA-ALAMÁ, M. (2009). Microhabitat use by three endemic Iberian cyprinids in Mediterranean rivers (Tagus River Basin, Spain). Fisheries Management and Ecology, 16(1), 52-60. doi:10.1111/j.1365-2400.2008.00645.xMouton, A. M., Alcaraz-Hernández, J. D., De Baets, B., Goethals, P. L. M., & Martínez-Capel, F. (2011). Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers. Environmental Modelling & Software, 26(5), 615-622. doi:10.1016/j.envsoft.2010.12.001Mouton, A. M., De Baets, B., & Goethals, P. L. M. (2010). Ecological relevance of performance criteria for species distribution models. Ecological Modelling, 221(16), 1995-2002. doi:10.1016/j.ecolmodel.2010.04.017Muñoz-Mas, R., Fukuda, S., Vezza, P., & Martínez-Capel, F. (2016). Comparing four methods for decision-tree induction: A case study on the invasive Iberian gudgeon ( Gobio lozanoi ; Doadrio and Madeira, 2004). Ecological Informatics, 34, 22-34. doi:10.1016/j.ecoinf.2016.04.011Muñoz-Mas, R., Lopez-Nicolas, A., Martínez-Capel, F., & Pulido-Velazquez, M. (2016). Shifts in the suitable habitat available for brown trout (Salmo trutta L.) under short-term climate change scenarios. Science of The Total Environment, 544, 686-700. doi:10.1016/j.scitotenv.2015.11.147Muñoz-Mas, R., Martínez-Capel, F., Garófano-Gómez, V., & Mouton, A. M. (2014). Application of Probabilistic Neural Networks to microhabitat suitability modelling for adult brown trout (Salmo trutta L.) in Iberian rivers. Environmental Modelling & Software, 59, 30-43. doi:10.1016/j.envsoft.2014.05.003Muñoz-Mas, R., Martínez-Capel, F., Schneider, M., & Mouton, A. M. (2012). Assessment of brown trout habitat suitability in the Jucar River Basin (SPAIN): Comparison of data-driven approaches with fuzzy-logic models and univariate suitability curves. Science of The Total Environment, 440, 123-131. doi:10.1016/j.scitotenv.2012.07.074Muñoz-Mas, R., Papadaki, C., Martínez-Capel, F., Zogaris, S., Ntoanidis, L., & Dimitriou, E. (2016). Generalized additive and fuzzy models in environmental flow assessment: A comparison employing the West Balkan trout (Salmo farioides; Karaman, 1938). Ecological Engineering, 91, 365-377. doi:10.1016/j.ecoleng.2016.03.009Olaya-Marín, E. J., Martínez-Capel, F., Soares Costa, R. M., & Alcaraz-Hernández, J. D. (2012). Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain). Science of The Total Environment, 440, 95-105. doi:10.1016/j.scitotenv.2012.07.093Paredes-Arquiola, J., Solera, A., Martinez-Capel, F., Momblanch, A., & Andreu, J. (2014). Integrating water management, habitat modelling and water quality at the basin scale and environmental flow assessment: case study of the Tormes River, Spain. Hydrological Sciences Journal, 59(3-4), 878-889. doi:10.1080/02626667.2013.821573Platts, P. J., McClean, C. J., Lovett, J. C., & Marchant, R. (2008). Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty. Ecological Modelling, 218(1-2), 121-134. doi:10.1016/j.ecolmodel.2008.06.028Reyjol, Y., Hugueny, B., Pont, D., Bianco, P. G., Beier, U., Caiola, N., … Virbickas, T. (2007). Patterns in species richness and endemism of European freshwater fish. Global Ecology and Biogeography, 16(1), 65-75. doi:10.1111/j.1466-8238.2006.00264.xRibeiro, F., Elvira, B., Collares-Pereira, M. J., & Moyle, P. B. (2007). Life-history traits of non-native fishes in Iberian watersheds across several invasion stages: a first approach. Biological Invasions, 10(1), 89-102. doi:10.1007/s10530-007-9112-2RIBEIRO, F., & LEUNDA, P. M. (2012). Non-native fish impacts on Mediterranean freshwater ecosystems: current knowledge and research needs. Fisheries Management and Ecology, 19(2), 142-156. doi:10.1111/j.1365-2400.2011.00842.xRincon, P. A., Correas, A. M., Morcillo, F., Risueno, P., & Lobon-Cervia, J. (2002). Interaction between the introduced eastern mosquitofish and two autochthonous Spanish toothcarps. Journal of Fish Biology, 61(6), 1560-1585. doi:10.1111/j.1095-8649.2002.tb02498.xRobalo, J. I., Almada, V. C., Levy, A., & Doadrio, I. (2007). Re-examination and phylogeny of the genus Chondrostoma based on mitochondrial and nuclear data and the definition of 5 new genera. Molecular Phylogenetics and Evolution, 42(2), 362-372. doi:10.1016/j.ympev.2006.07.003Romão, F., Quintella, B. R., Pereira, T. J., & Almeida, P. R. (2011). Swimming performance of two Iberian cyprinids: the Tagus nase Pseudochondrostoma polylepis (Steindachner, 1864) and the bordallo Squalius carolitertii (Doadrio, 1988). Journal of Applied Ichthyology, 28(1), 26-30. doi:10.1111/j.1439-0426.2011.01882.xShiroyama, R., & Yoshimura, C. (2016). Assessing bluegill (Lepomis macrochirus) habitat suitability using partial dependence function combined with classification approaches. Ecological Informatics, 35, 9-18. doi:10.1016/j.ecoinf.2016.06.005Thomas, J. A., & Bovee, K. D. (1993). Application and testing of a procedure to evaluate transferability of habitat suitability criteria. Regulated Rivers: Research & Management, 8(3), 285-294. doi:10.1002/rrr.3450080307Vezza, P., Muñoz-Mas, R., Martinez-Capel, F., & Mouton, A. (2015). Random forests to evaluate biotic interactions in fish distribution models. Environmental Modelling & Software, 67, 173-183. doi:10.1016/j.envsoft.2015.01.005Vilizzi, L., Copp, G. H., & Roussel, J.-M. (2004). Assessing variation in suitability curves and electivity profiles in temporal studies of fish habitat use. River Research and Applications, 20(5), 605-618. doi:10.1002/rra.767Wood, S. N. (2004). Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models. Journal of the American Statistical Association, 99(467), 673-686. doi:10.1198/016214504000000980Wood, S. N. (2006). Generalized Additive Models. doi:10.1201/9781420010404Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A., & Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. Statistics for Biology and Health. doi:10.1007/978-0-387-87458-

    Factors Related to Stocking Success of 178-mm Channel Catfish in Medium Size Oklahoma Reservoirs

    Get PDF
    The channel catfish Ictalurus punctatus is a commonly stocked freshwater fish species. Prior studies indicate that stocking advanced size (> 150 mm total length (TL)) fingerlings increases post-release survival but few studies have identified factors that influence stocking success. The present study was conducted to determine stocking contribution and growth of advanced size channel catfish (~178 mm TL), evaluate the impact of stocking and cessation of stocking, quantify habitat relationships, and evaluate trophic relationships of wild and stocked fish in medium size Oklahoma reservoirs: lakes McMurty and Ponca (control lakes), Okemah and Okmulgee (cease-stock lakes), and Greenleaf and Lone Chimney (stocked lakes). Channel catfish were immersed in a buffered solution of oxytetracycline (OTC) and stocked in October 2010 at lakes Greenleaf and Lone Chimney. The higher relative abundance of resident channel catfish in Lake Lone Chimney may have affected survival and growth of stocked fish. Stocking contribution at Lake Lone Chimney was low (~30%) compared to Lake Greenleaf (~98%). Fish stocked in Greenleaf reached an average length of 348 mm two years post-stock, whereas fish stocked in Lone Chimney grew to 240 mm, an increase by only 62 mm since stocking. To evaluate the full impact of stocking, two reservoirs were no longer stocked as part of an experimental manipulation. Relative abundance, growth, and size structure responded as expected. Cessation of stocking resulted in lower relative abundance, increased growth rates, and larger size structure. Whereas relative abundance increased for one stocked lake (Greenleaf), mean length at age and growth decreased, and size structure shifted to smaller size fish. Results from the multi-scale models indicate significant associations with both near-shore and land-use habitat types. Channel catfish were found at higher abundances in turbid areas with rock and coarse-woody debris, and a negative relationship was evident with aquatic vegetation, residential development and agriculture land-use. Trophic relationships indicated that intra-specific competitive interactions were evident. These results provide further evidence that density-dependent mechanisms likely reduced both survival and growth of stocked fish in Lake Lone Chimney. It also suggests that both habitat and relative stock size should be considered before stocking advanced size fingerlings.Wildlife Ecolog

    Habitat Analysis by Hierarchical Scheme and Stream Geomorphology

    Get PDF
    A study was undertaken to classify eight stream reaches in the North Branch of the Potomac River watershed and determine if geomorphologic differences influenced the availability of fish habitat structure and fish density. Stream reaches were classified using Rosgen Level II (1996) methods, and fish habitat was determined using Hydraulic Channel Unit (HCU) classification based on a method modified from Bisson et al. (1982). Other habitat variables were also studied such as stream shading and physical habitat based on the Rapid Bioassessment Protocol (Barbour et al. 1999). Despite the differences in HCU density between sites, HCU density did not influence fish density in the study streams. HCU density appeared to be mainly controlled by slope. Fish densities were highest in the relatively unimpacted streams, as expected. However, the impacted streams also appeared to have sufficient physical fish habitat structure to support fishes historically found in these streams. Other confounding variables, such as acid mine drainage, may be controlling factors in inhibiting fish populations in the impacted streams

    The Contribution of Missouri River Reservoir Side-Channel and Floodplain Habitats to Mainstem Fish Populations: The Effects of Losing Connectivity Between Hipple Lake and Lake Sharpe

    Get PDF
    Catastrophic flooding of the Missouri River in 2011 has had lasting effects on floodplain habitats (i.e. floodplain lakes) and side-channel habitats (e.g. canals, side-channel embayments, stilling basins, and tributaries) in Lake Sharpe, SD. Floodplain and side-channel habitats are rare habitat in Lake Sharpe, a mainstem Missouri River reservoir, and are thought to be crucial habitat for prey and sport fish. Hipple Lake, the only warm-water floodplain embayment in Lake Sharpe, is in danger of losing connectivity to the reservoir because of sedimentation resulting from the 2011 flood. To evaluate Hipple Lake’s natal and adult contribution to Lake Sharpe’s fishery, otolith microchemistry was used to quantify fish movement and natal origins. This data will be used to inform management decisions regarding restoring Hipple Lake’s connectivity to the main channel. Water trace element chemistry (e.g., Sr:Ca, Ba:Ca) among a cold-water side-channel embayment, warm-water floodplain embayment, canal complex, tributary, and the main channel of Lake Sharpe were spatially variable. Significant positive linear relationships existed between otolith trace element concentrations and water trace element concentrations for many species, but not for all species. Natal Sr:Ca and Ba:Ca ratios of adults varied spatially, which allowed for identification of natal origins of fish hatched in a warm-water floodplain embayment, a cold-water side-channel embayment, a tributary, a stilling basin, a canal complex, or the main channel. K-nearest neighbor discriminant analysis reclassified age-0 fish with sufficient accuracy for habitat-type scale classification (\u3e75% accuracy). Canals were important only for Gizzard Shad (Dorosoma cepedianum), whereas a tributary was important only for White Bass (Morone chrysops). A warm-water floodplain embayment, Hipple Lake, was important for natal recruitment of Bluegill (Lepomis macrochirus), Crappies (Pomoxis spp.), Largemouth Bass (Micropterus dolomieu), and Gizzard Shad. A cold-water side-channel embayment, La Framboise, was important for White Bass, Sauger (Sander canadensis), and Walleye (Sander vitreus) natal recruitment and adult use, as well as adult use for Bluegill, Yellow Perch (Perca flavescens), and Largemouth Bass. A stilling basin was important for Yellow Perch and Gizzard Shad. The main channel was equal or more important than side-channel and floodplain habitats for Bluegill, Crappie, Yellow Perch, Smallmouth Bass, Largemouth Bass and Sauger natal recruitment, and more important than side-channel and floodplain habitats for Crappie, Yellow Perch and Smallmouth Bass adult movement. Gizzard Shad collected at all sites moved frequently throughout the entire reservoir. At least 6% of adult Gizzard Shad in Lake Sharpe (~25,000 ha) originated in Hipple Lake (178 ha), and at least 17% of adult Gizzard Shad in Hipple Lake originated in Hipple Lake. Considering that Hipple Lake makes up only 0.77% of Lake Sharpe’s surface area, 6-17% of Lake Sharpe’s natal recruitment occurring in the floodplain lake is substantial. Nearly two-thirds (65.57%) of all Gizzard Shad recruitment in Lake Sharpe occurred in side-channel and floodplain habitats. This research shows the disproportional importance of warm-water floodplain embayments, canals, stilling basins and tributaries to Gizzard Shad recruitment in large reservoirs. Sport fish were found to utilize different habitats, with the floodplain and side-channel contribution to natal recruitment and adult movement varying from negligible to significant, dependent on species. Natal recruitment and movement patterns varied to a small extent on an annual scale for some species, and movements have changed to a small extent for some species since the 2011 flood

    Using population ecology to advance stream community assembly

    Get PDF
    2019 Summer.Includes bibliographical references.To view the abstract, please see the full text of the document

    Revisiting probabilistic neural networks: a comparative study with support vector machines and the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus)

    Full text link
    [EN] Probabilistic Neural Networks (PNNs) and Support Vector Machines (SVMs) are flexible classification techniques suited to render trustworthy species distribution and habitat suitability models. Although several alternatives to improve PNNs¿ reliability and performance and/or to reduce computational costs exist, PNNs are currently not well recognised as SVMs because the SVMs were compared with standard PNNs. To rule out this idea, the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus Doadrio & Carmona, 2006) was modelled with SVMs and four types of PNNs (homoscedastic, heteroscedastic, cluster and enhanced PNNs); all of them optimised with differential evolution. The fitness function and several performance criteria (correctly classified instances, true skill statistic, specificity and sensitivity) and partial dependence plots were used to assess respectively the performance and reliability of each habitat suitability model. Heteroscedastic and enhanced PNNs achieved the highest performance in every index but specificity. However, these two PNNs rendered ecologically unreliable partial dependence plots. Conversely, homoscedastic and cluster PNNs rendered ecologically reliable partial dependence plots. Thus, Eastern Iberian chub proved to be a eurytopic species, presenting the highest suitability in microhabitats with cover present, low flow velocity (approx. 0.3 m/s), intermediate depth (approx. 0.6 m) and fine gravel (64¿256 mm). PNNs outperformed SVMs; thus, based on the results of the cluster PNN, which also showed high values of the performance criteria, we would advocate a combination of approaches (e.g., cluster & heteroscedastic or cluster & enhanced PNNs) to balance the trade-off between accuracy and reliability of habitat suitability models.The study has been partially funded by the national Research project IMPADAPT (CGL2013-48424-C2-1-R) with MINECO (Spanish Ministry of Economy) and Feder funds and by the Confederacion Hidrografica del Near (Spanish Ministry of Agriculture and Fisheries, Food and Environment). This study was also supported in part by the University Research Administration Center of the Tokyo University of Agriculture and Technology. Thanks to Maria Jose Felipe for reviewing the mathematical notation and to the two anonymous reviewers who helped to improve the manuscript.Muñoz Mas, R.; Fukuda, S.; Portolés, J.; Martinez-Capel, F. (2018). Revisiting probabilistic neural networks: a comparative study with support vector machines and the microhabitat suitability for the Eastern Iberian chub (Squalius valentinus). Ecological Informatics. 43:24-37. https://doi.org/10.1016/J.ECOINF.2017.10.008S24374

    The roles of spatial scale and landscape change in mediating predator effects on stream fish communities

    Get PDF
    Doctor of PhilosophyDivision of BiologyKeith B. GidoThe role of predators in ecosystems has not only intrigued and puzzled ecologists over time, but predators are charismatic icons of conservation whose status indicates threats of global change. Through habitat alteration and fragmentation, climate change, and species introductions, predation pressure has been altered globally through the loss of apex predators, introduction of predators, and changes in predator distributions and abundance. While we know predators can influence ecosystems through top-down processes, managing changes in predation pressure requires quantifying effects of predators at scales relevant to management and conservation. In lotic systems, scales relevant to management often span across drainage basins, so predator effects must be quantified across stream networks. Because lotic communities also respond to landscape change, understanding the role of predators across stream networks requires careful consideration of local and broad scale abiotic factors influencing both predators and prey. I combined simulated, experimental, and observational data to 1) assess sampling strategies to determine effects of landscape change on stream fish communities, 2) measure changes in predator consumption rates across spatial scales and the role of prey behavior in driving scaling relationships, and 3) quantify the relationship between the presence of predators and stream fish community structure while controlling for abiotic variability across stream networks. In chapter 2, I compared how the distribution of sample sites (completely random, highly skewed, or uniform distributions) across landscape gradients influenced variability in measured responses of stream fish community metrics. Strong responses (species richness) to environmental gradients were robust to sample distributions, but large sample size and uniform distributions of samples across gradients were necessary to quantify more complex ecological responses (community composition). In chapter 3, I conducted a mesocosm study to quantify differences in per capita consumption across different arena sizes and measured three aspects of prey behavior hypothesized to be important in driving consumption rates: aggregation, movement, and spatial overlap with predators. Per capita consumption was highest in the largest arena relative to the smallest. I hypothesize the positive relationship between consumption and spatial scale was driven by lower group vigilance because prey aggregated less in large arenas. In chapter 4, I compared fish community structure, including richness and abundance of species, at sites in which a predatory fish, largemouth bass (Micropterus salmoides), were present or absent. I first identified which abiotic factors, including both natural stream attributes and anthropogenic landscape changes, drove the presence of largemouth bass and stream fish community structure. I then controlled for important abiotic factors to determine relationships between largemouth bass and stream fish community structure. Richness was higher than predicted based on abiotic factors at sites where bass were present. Several species associated with small impoundments exhibited significant co-occurrence patterns with largemouth bass, likely driving the heightened richness at sites with bass. Complex ecological phenomena such as community responses to predators are difficult to measures, especially in the context of landscape change. These studies highlight the importance of thoughtful study design, the scale-dependence of biotic interactions, and challenges of quantifying responses to predators at scales relevant to conservation and management

    Bioenergetics modeling to assess aquatic invasive species trophic impact

    Get PDF
    Energy requirements of aquatic invasive species (AIS) relative to native species may help explain differences in trophic impact, as species requiring more energy must consume more food, depleting resources more quickly. Variables relating to energy use were compared between co-existing invasive and native fish species in invaded habitats. Most comparisons (8/12) demonstrated higher rates in invasive species (1-46% greater), suggesting high trophic impact is a characteristic of AIS and should be of consideration in management. Bioenergetic mass-balance principles indicate energy consumed by a fish is offset by metabolic (~40%), waste (~30%), and growth (~30%) demands. Since routine metabolic rate data are copious, this rate was used as a surrogate for trophic impact. Non-parametric analyses were used to find relationships between RMR and traits, creating models to predict trophic impact. The models performed poorly, yet age-at-maturity, maximum total length, and eye diameter-to-head length ratio were consistently important in describing RMR

    Predictive modeling of freshwater mussels (Unionidae) in the Appalachians

    Get PDF
    Freshwater mussels are in decline, particularly in the Appalachian region of North America. This region contains the world\u27s greatest diversity of freshwater mussels, but many species are now threatened or endangered. Little is known of the basic ecology and distributions of species of freshwater mussels relative to other freshwater organisms. The goal of this study was to use predictive modeling to predict distributions of freshwater mussels in the Appalachians and identify correlated factors using a watershed framework. Models were developed in the upper Mid-Atlantic and Ohio drainage regions using subwatersheds and separately in the Tennessee region using catchments. Models developed at this scale had low predictive ability because few surveys of freshwater mussels are available at the subwatershed scale and a regional extent. Independent data were unavailable to evaluate catchment-based models. Additional mussel surveys are necessary to expand the potential for developing robust predictive models of most freshwater mussel species
    corecore