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Niche measures and growth rate do not predict interspecific variation in spatial synchrony of phytoplankton

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Abstract

Spatial synchrony occurs when local populations exhibit correlated dynamics over time. Recent studies, both experimental and observational, have indicated that the magnitude of spatial synchrony, in cross-species analyses, is correlated with the level of specialization. In theory, specialist species would exhibit higher levels of synchrony than generalist species because they would be more sensitive to environmental variations. In addition, according to simulation studies, species with high growth rates should have more synchronized dynamics. In this study, we tested these hypotheses using datasets (phytoplankton populations and environmental variables) obtained in the Cana Brava Reservoir (State of Goiás, Brazil). We used a multiple regression model to test whether the average level of spatial synchrony was correlated with variables that indicate environmental specialization and population growth rate. In general, the average values of spatial synchrony were low, indicating the predominance of local factors in controlling population dynamics. We found no significant relationship between synchrony and our explanatory variables. To assess the generality of correlates of spatial synchrony, we suggest that future studies should focus on a common same set of explanatory variables.

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References

  • Anderson TL, Walter JA, Levine TD, Hendricks SP, Johnston KL, White DS et al (2018) Using geography to infer the importance of dispersal for the synchrony of freshwater plankton. Oikos 127:403–414

    Google Scholar 

  • Burrows MT, Moore JJ, James B (2002) Spatial synchrony of population changes in rocky shore communities in Shetland. Mar Ecol Prog Ser 240:39–48

    Google Scholar 

  • Carneiro FM, Nabout JC, Vieira LC, Roland F, Bini LM (2014) Determinants of chlorophyll-a concentration in tropical reservoirs. Hydrobiologia 740:89–99

    CAS  Google Scholar 

  • Chevalier M, Laffaille P, Grenouillet G (2014) Spatial synchrony in stream fish populations: influence of species traits. Ecography 37:960–968

    Google Scholar 

  • Cottingham KL, Carpenter SR (1998) Population, community, and ecosystem variates as ecological indicators: Phytoplankton responses to whole-lake enrichment. Ecol Appl 8:508–530

    Google Scholar 

  • Defriez EJ, Reuman DC (2017a) A global geography of synchrony for marine phytoplankton. Global Ecol Biogeogr 26:867–877

    Google Scholar 

  • Defriez EJ, Reuman DC (2017b) A global geography of synchrony for terrestrial vegetation. Global Ecol Biogeogr 26:878–888

    Google Scholar 

  • Defriez EJ, Sheppard LW, Reid PC, Reuman DC (2016) Climate change-related regime shifts have altered spatial synchrony of plankton dynamics in the North Sea. Glob Chang Biol 22:2069–2080

    PubMed  Google Scholar 

  • Dolédec S, Chessel D, Gimaret-Carpentier C (2000) Niche separation in community analysis: a new method. Ecology 81:2914–2927

    Google Scholar 

  • Dray S, Dufour A (2007) The ade4 Package: implementing the duality diagram for ecologists. J Stat Softw 22:1–20

    Google Scholar 

  • Eaton AD, Clesceri LS, Franson MAH, Rice EW, Greenberg AE (2005) Standard methods for the examination of water and Wastewater. American Public Health Association, Washington, DC

    Google Scholar 

  • Finlay BJ (2002) Global dispersal of free-Living microbial eukaryote species. Science 296:1061–1063

    CAS  PubMed  Google Scholar 

  • Gouhier TC, Guichard F (2014) Synchrony: quantifying variability in space and time. Methods Ecol Evol 5:524–533

    Google Scholar 

  • Hanski I, Woiwod IP (1993) Spatial synchrony in the dynamics of moth and aphid populations. J Anim Ecol 62:656–668

    Google Scholar 

  • Heino M, Kaitala V, Ranta E, Lindstrom J (1997) Synchronous dynamics and rates of extinction in spatially structured populations. Proc R Soc B Biol Sci 264:481–486

    Google Scholar 

  • Karasiewicz S, Dolédec S, Lefebvre S (2017) Within outlying mean indexes: refining the OMI analysis for the realized niche decomposition. PeerJ 5:e3364

    PubMed  PubMed Central  Google Scholar 

  • Koenig WD (2002) Global patterns of environmental synchrony and the Moran effect. Ecography 25:283–288

    Google Scholar 

  • Kruk C, Huszar VLM, Peeters ETHM, Bonilla S, Costa L, Lürling M et al (2010) A morphological classification capturing functional variation in phytoplankton. Freshw Biol 55:614–627

    Google Scholar 

  • Lansac-Tôha FA, Bini LM, Velho LFM, Bonecker CC, Takahashi EM, Vieira LCG (2008) Temporal coherence of zooplankton abundance in a tropical reservoir. Hydrobiologia 614:387–399

    Google Scholar 

  • Legendre P, Borcard D (2018) Box–Cox-chord transformations for community composition data prior to beta diversity analysis. Ecography 41:1820–1824

    Google Scholar 

  • Liebhold A, Koenig WD, Bjørnstad ON (2004) Spatial synchrony in population dynamics. Annu Rev Ecol Evol Syst 35:467–490

    Google Scholar 

  • Litchman E, Klausmeier CA (2008) Trait-based community ecology of phytoplankton. Annu Rev Ecol Evol Syst 39:615–639

    Google Scholar 

  • Lodi S, Velho LFM, Carvalho P, Bini LM (2014) Patterns of zooplankton population synchrony in a tropical reservoir. J Plankton Res 36:966–977

    Google Scholar 

  • Lodi S, Velho LFM, Carvalho P, Bini LM (2018) Effects of connectivity and watercourse distance on temporal coherence patterns in a tropical reservoir. Environ Monit Assess 190:566

    PubMed  Google Scholar 

  • Lopes VG, Castelo-Branco CW, Kozlowsky-Suzuki B, Sousa-Filho IF, Souza LC, Bini LM (2018) Environmental distances are more important than geographic distances when predicting spatial synchrony of zooplankton populations in a tropical reservoir. Freshw Biol 63:1592–1601

    CAS  Google Scholar 

  • Lund JWG, Kipling C, Le Cren ED (1958) The inverted microscope method of estimating algal numbers and the statistical basis of estimations by counting. Hydrobiologia 11:143–170

    Google Scholar 

  • Marquez JF, Lee AM, Aanes S, Engen S, Herfindal I, Salthaug A et al (2019) Spatial scaling of population synchrony in marine fish depends on their life history. Ecol Lett 22:1787–1796

    PubMed  Google Scholar 

  • Moran PAP (1953) The statistical analysis of the Canadian Lynx cycle. Aust J Zool 1:291–298

    Google Scholar 

  • Pandit SN, Kolasa J, Cottenie K (2009) Contrasts between habitat generalists and specialists: an empirical extension to the basic metacommunity framework. Ecology 90:2253–2262

    PubMed  Google Scholar 

  • Pandit SN, Kolasa J, Cottenie K (2013) Population synchrony decreases with richness and increases with environmental fluctuations in an experimental metacommunity. Oecologia 171:237–247

    PubMed  Google Scholar 

  • Pandit SN, Cottenie K, Enders EC, Kolasa J (2016) The role of local and regional processes on population synchrony along the gradients of habitat specialization. Ecosphere 7:1–11

    Google Scholar 

  • Paradis E, Baillie SR, Sutherland WJ, Gregory RD (1999) Dispersal and spatial scale affect synchrony in spatial population dynamics. Ecol Lett 2:114–120

    Google Scholar 

  • Paradis E, Baillie SR, Sutherland WJ, Gregory RD (2000) Spatial synchrony in populations of birds: effects of habitat, population trend, and spatial scale. Ecology 81:2112–2125

    Google Scholar 

  • Rangel LM, Silva LH, Rosa P, Roland F, Huszar VL (2012) Phytoplankton biomass is mainly controlled by hydrology and phosphorus concentrations in tropical hydroelectric reservoirs. Hydrobiologia 693:13–28

    CAS  Google Scholar 

  • Ranta E, Kaitala V, Lindström J, Helle E, Lindstrom J (1997) The moran effect and synchrony in population dynamics. Oikos 78:136–142

    Google Scholar 

  • R Core Team (2018) R: a language and environment for statistical computing, 3.6.0. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/

  • Reynolds CS (2006) The ecology of phytoplankton. Cambridge University Press, Cambridge

    Google Scholar 

  • Reynolds CS, Huszar VLM, Kruk C, Naselli-Flores L, Melo S (2002) Towards a functional classification of the freshwater phytoplankton. J Plankton Res 24:417–428

    Google Scholar 

  • Rhodes JR, Jonzén N (2011) Monitoring temporal trends in spatially structured populations: how should sampling effort be allocated between space and time? Ecography 34:1040–1048

    Google Scholar 

  • Sæther BE, Coulson T, Grøtan V, Engen S, Altwegg R, Armitage KB et al (2013) How life history influences population dynamics in fluctuating environments. Am Nat 182:743–759

    PubMed  Google Scholar 

  • Souza ACC (2008) Assessment and statistics of Brazilian hydroelectric power plants: dam areas versus installed and firm power. Renew Sustain Energy Rev 12:1843–1863

    Google Scholar 

  • Stenseth NC, Ehrich D, Rueness EK, Lingjærde OC, Chan KS, Boutin S et al (2004) The effect of climatic forcing on population synchrony and genetic structuring of the Canadian lynx. Proc Natl Acad Sci 101:6056–6061

    CAS  PubMed  Google Scholar 

  • Tedesco P, Hugueny B (2006) Life history strategies affect climate based spatial synchrony in population dynamics of West African freshwater fishes. Oikos 115:117–127

    Google Scholar 

  • Vieira MC, Roitman I, Barbosa HO, Velho LFM, Vieira LCG (2019) Spatial synchrony of zooplankton during the impoundment of amazonic reservoir. Ecol Indic 98:649–656

    Google Scholar 

  • Vogt RJ, Rusak JA, Patoine A, Leavitt PR (2011) Differential effects of energy and mass influx on the landscape synchrony of lake ecosystems. Ecology 92:1104–1114

    PubMed  Google Scholar 

  • Walter JA, Sheppard LW, Anderson TL, Kastens JH, Bjørnstad ON, Liebhold AM et al (2017) The geography of spatial synchrony. Ecol Lett 20:801–814

    PubMed  Google Scholar 

  • Xu Y, Cai Q, Shao M, Han X (2012) Patterns of asynchrony for phytoplankton fluctuations from reservoir mainstream to a tributary bay in a giant dendritic reservoir (Three Gorges Reservoir, China). Aquat Sci 74:287–300

    CAS  Google Scholar 

  • Zanon JE, Rodrigues L, Bini LM (2018) Hard to predict: Synchrony in epiphytic biomass in a floodplain is independent of spatial proximity, environmental distance, and environmental synchrony. Ecol Indic 93:379–386

    CAS  Google Scholar 

  • Zanon JE, Carvalho P, Rodrigues LC, Bini LM (2019) Potential mechanisms related to the spatial synchrony of phytoplankton is dependent on the type of data. Hydrobiologia 841:95–108

    Google Scholar 

Download references

Acknowledgements

This research was funded by Coordination for the Improvement of Higher Level Personnel (CAPES; scholarships to MNS and RVG) and Brazilian Council of Research (CNPq; grants to LMB and LCR). This work was also developed in the context of the National Institutes for Science and Technology (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG.

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Correspondence to Luis Mauricio Bini.

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da Silva, M.N., Granzotti, R.V., de Carvalho, P. et al. Niche measures and growth rate do not predict interspecific variation in spatial synchrony of phytoplankton. Limnology 22, 121–127 (2021). https://doi.org/10.1007/s10201-020-00640-0

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