Estimating the degree to which distance and temperature differences drive changes in fish community composition over time in the upper Mississippi River
Autoři:
James H. Larson aff001; Jon M. Vallazza aff001; Brent C. Knights aff001
Působiště autorů:
U.S. Geological Survey, Upper Midwest Environmental Sciences Center, La Crosse, WI, United States of America
aff001
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225630
Souhrn
Similarity in community composition declines as distance between locations increases, a phenomenon that has been observed in a wide variety of freshwater, marine and terrestrial ecosystems. One driver of the distance-similarity relationship is the presence of environmental gradients that alter the suitability of sites for particular species. Although some environmental gradients, such as geology, do not change on a year-to-year basis, others, such as temperature, vary annually and over longer time periods. Here, we used a 21-year dataset of fish communities in the upper Mississippi River to examine the effect of distance on variation in community composition and to assess whether the effect of distance is primarily due to its effect on thermal regime. Because the Mississippi River is aligned mostly north-to-south, larger distances along the river roughly correspond to larger differences in latitude and therefore thermal regime. As expected, there was a moderate distance-similarity relationship, suggesting greater distance leads to less similarity. The effect of distance appeared to increase slightly over time. Using a subset of data for which air temperature was available, we compared models that incorporated both difference among sites in degree days (a surrogate for thermal regime) and physical distance (river km). Although physical distance presumably incorporates more environmental gradients than just temperature (and other potential mechanisms), temperature alone appears to be more strongly associated with differences in the Mississippi River fish community than distance.
Klíčová slova:
Carps – Fish biology – Freshwater fish – Marine ecosystems – Mathematical models – Rivers – Mississippi – Animal navigation
Zdroje
1. Soininen J, McDonald R, Hillebrand H. The distance decay of similarity in ecological communities. Ecography 2007;30: 3–12. doi: 10.1111/j.2006.0906–7590.04817.x
2. Perkin JS, Gido KB. Fragmentation alters stream fish community structure in dendritic ecological networks. Ecol Appl. 2012; doi: 10.1890/12-0318.1 23387118
3. Gehrke PC, Gilligan DM, Barwick M. Changes in fish communities of the Shoalhaven River 20 years after construction of Tallowa Dam, Australia. River Res Appl. 2002;18: 265–286. doi: 10.1002/rra.669
4. Lee HW, Bailey-Brock JH, McGurr MM. Temporal changes in the polychaete infaunal community surrounding a Hawaiian mariculture operation. Mar Ecol Prog Ser. 2006;307: 175–185. doi: 10.3354/meps307175
5. Brown J, Gillooly J, Allen A, Savage V, West G. Toward a metabolic theory of ecology. Ecology. 2004;85: 1771–1789. Available: http://www.esajournals.org/doi/abs/10.1890/03-9000
6. Enquist BJ, Economo EP, Huxman TE, Allen AP, Ignace DD, Gillooly JF. Scaling metabolism from organisms to ecosystems. Nature 2003;423: 639–642. doi: 10.1038/nature01671 12789338
7. O’Connor MI, Bruno JF, Gaines SD, Halpern BS, Lester SE, Kinlan BP, et al. Temperature control of larval dispersal and the implications for marine ecology, evolution, and conservation. Proc Natl Acad Sci U S A. National Academy of Sciences; 2007;104: 1266–71. doi: 10.1073/pnas.0603422104 17213327
8. Chezik KA, Lester NP, Venturelli PA, Tierney K. Fish growth and degree-days I: selecting a base temperature for a within-population study. Can J Fish Aquat Sci. 2014;71: 47–55. doi: 10.1139/cjfas-2013-0295
9. Burgmer T, Hillebrand H, Pfenninger M. Effects of climate-driven temperature changes on the diversity of freshwater macroinvertebrates. Oecologia. 2007;151: 93–103. doi: 10.1007/s00442-006-0542-9 16964502
10. Chick JH, Pegg MA, Koel TM. Spatial patterns of fish communities in the Upper Mississippi river system: Assessing fragmentation by low-head dams. River Res Appl. 2006;22: 413–427. doi: 10.1002/rra.912
11. Theiling CH, Nestler JM. River stage response to alteration of Upper Mississippi River channels, floodplains, and watersheds. Hydrobiologia. 2010;640: 17–47. doi: 10.1007/s10750-009-0066-5
12. Zigler S, Dewey M, Knights B, Runstrom A, Steingraeber M. Hydrologic and hydraulic factors affecting passage of paddlefish through dams in the upper Mississippi River. Trans Am Fish Soc. 2004;133: 160–172.
13. Knights BC, Vallazza JM, Zigler SJ, Dewey MR. Habitat and movement of lake sturgeon in the Upper Mississippi River system, USA. Trans Am Fish Soc. 2002;131: 507–522.
14. Tripp S, Brooks R, Herzog D, Garvey J. Patterns of fish passage in the upper Mississippi River. River Res Appl. 2014;30: 1056–1064. doi: 10.1002/rra.2696
15. Larson JH, Knights BC, McCalla SG, Monroe E, Tuttle-Lau M, Chapman DC, et al. Evidence of Asian carp spawning upstream of a key choke point in the Mississippi River. North Am J Fish Manag. 2017;37: 903–919. doi: 10.1080/02755947.2017.1327901
16. Gutreuter S, Burkhardt R, Lubinski K. Long Term Resource Monitoring Program Procedures: Fish Monitoring. Natl Biol Serv. 1995; LTRMP 95–P002–1. 42 pp.
17. Houser JN, Bierman DW, Burdis RM, Soeken-Gittinger LA. Longitudinal trends and discontinuities in nutrients, chlorophyll, and suspended solids in the Upper Mississippi River: Implications for transport, processing, and export by large rivers. Hydrobiologia. 2010;651: 127–144. doi: 10.1007/s10750-010-0282-z
18. R Development Core Team. R: A language and environment for statistical computing. [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2014. Available: http://www.r-project.org
19. Bray JR, Curtis JT. An ordination of the upland forest communities of southern Wisconsin. Ecol Monogr. Ecological Society of America; 1957;27: 325–349. doi: 10.2307/1942268
20. Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14: 927–930. doi: 10.1111/j.1654-1103.2003.tb02228.x
21. Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67: 1–48. doi: 10.18637/jss.v067.i01
22. Burnham KP, Anderson DR. Model Selection and Inference A Practical Information-Theoretic Approach. New York, New York, USA: Springer-Verlag; 1998.
23. Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol. 2013;4: 133–142. doi: 10.1111/j.2041-210x.2012.00261.x
24. Lubinski K, Burkhardt R, Sauer J, Soballe DM, Yin Y. Initial analyses of change detection capabilities and data redundancies in the Long Term Resource Monitoring program. Rock Island, IL; 2001.
25. Anderson RL, Anderson CA, Larson JH, Knights B, Vallazza J, Jenkins SE, et al. Influence of a high‐head dam as a dispersal barrier to fish community structure of the Upper Mississippi River. River Res Appl. 2019; 1–10. doi: 10.1002/rra.3534
26. Araújo ES, Marques EE, Freitas IS, Neuberger AL, Fernandes R, Pelicice FM. Changes in distance decay relationships after river regulation: similarity among fish assemblages in a large Amazonian river. Ecol Freshw Fish. Wiley/Blackwell (10.1111); 2013;22: 543–552. doi: 10.1111/eff.12054
27. Hansen GJA, Read JS, Hansen JF, Winslow LA. Projected shifts in fish species dominance in Wisconsin lakes under climate change. Glob Chang Biol. John Wiley & Sons, Ltd (10.1111); 2017;23: 1463–1476. doi: 10.1111/gcb.13462 27608297
28. Wilcox DB, Stefanik EL, Kelner DE, Cornish MA, Johnson DJ, Hodgins IJ, et al. Improving fish passage through navigation dams on the upper Mississippi River system. Interim Report For The Upper Mississippi River–Illinois Waterway System Navigation Study. 2004.
29. Becker GC. Fishes of Wisconsin. Madison, WI USA: University of Wisconsin Press; 1983.
30. Kolar CS, Chapman DC, Courtenay WR, Housel CM, Williams JD, Jennings DP. Bigheaded Carps: A Biological Synopsis and Environmental Risk Assessment. Special Publication 33. American Fisheries Society; 2007.
31. Wehrly KE, Wiley MJ, Seelbach PW. Classifying regional variation in thermal regime based on stream fish community patterns. Trans Am Fish Soc. Taylor & Francis Group; 2003;132: 18–38. doi: 10.1577/1548-8659(2003)132<0018:CRVITR>2.0.CO;2
Článek vyšel v časopise
PLOS One
2019 Číslo 12
- Tisícileté topoly, mokří psi, stárnoucí kočky a ospalé octomilky – „jednohubky“ z výzkumu 2024/41
- Jaké jsou aktuální trendy v léčbě karcinomu slinivky?
- Může hubnutí souviset s vyšším rizikem nádorových onemocnění?
- Menstruační krev má značný diagnostický potenciál, mimo jiné u diabetu
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
Nejčtenější v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy