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Analysing the distance decay of community similarity in river networks using Bayesian methods

  • 1.

    Nekola, J. C. & White, P. S. The distance decay of similarity in biogeography and ecology. J. Biogeogr. 26, 867–878 (1999).

    Article 

    Google Scholar 

  • 2.

    Soininen, J., McDonald, R. & Hillebrand, H. The distance decay of similarity in ecological communities. Ecography 30, 3–12 (2007).

    Article 

    Google Scholar 

  • 3.

    Whittaker, R. H. Communities and Ecosystems (MacMillan Publishing, 1975).

    Google Scholar 

  • 4.

    Pulliam, H. R. On the relationship between niche and distribution. Ecol. Lett. 3, 349–361 (2000).

    Article 

    Google Scholar 

  • 5.

    Pulliam, H. Sources, sinks, and population regulation. Am. Nat. 132, 652–661 (1988).

    Article 

    Google Scholar 

  • 6.

    Hanski, I. & Gilpin, M. Metapopulation dynamics: Brief history and conceptual domain. Biol. J. Linn. Soc. 42, 3–16 (1991).

    Article 

    Google Scholar 

  • 7.

    MacArthur, R. H. & Wilson, E. O. The Theory of Island Biogeography (Princeton University Press, 2001).

    Book 

    Google Scholar 

  • 8.

    Tuomisto, H. & Ruokolainen, K. Analyzing or explaining beta diversity? Understanding the targets of different methods of analysis. Ecology 87, 2697–2708 (2006).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 9.

    Astorga, A. et al. Distance decay of similarity in freshwater communities: Do macro- and microorganisms follow the same rules?: Decay of similarity in freshwater communities. Glob. Ecol. Biogeogr. 21, 365–375 (2012).

    Article 

    Google Scholar 

  • 10.

    Leibold, M. A. et al. The metacommunity concept: A framework for multi-scale community ecology. Ecol. Lett. 7, 601–613 (2004).

    Article 

    Google Scholar 

  • 11.

    Nekola, J. C. & Brown, J. H. The wealth of species: Ecological communities, complex systems and the legacy of Frank Preston. Ecol. Lett. 10, 188–196 (2007).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 12.

    Hubbell, S. The Unified Neutral Theory of Biodiversity and Biogeography (MPB-32) (Princeton University Press, 2001).

    Google Scholar 

  • 13.

    Fodelianakis, S., Valenzuela-Cuevas, A., Barozzi, A. & Daffonchio, D. Direct quantification of ecological drift at the population level in synthetic bacterial communities. ISME J. https://doi.org/10.1038/s41396-020-00754-4 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 14.

    Gravel, D., Canham, C. D., Beaudet, M. & Messier, C. Reconciling niche and neutrality: The continuum hypothesis: Reconciling niche and neutrality. Ecol. Lett. 9, 399–409 (2006).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 15.

    Legendre, P., Borcard, D. & Peres-Neto, P. R. Analyzing beta diversity: Partitioning the spatial variation of community composition data. Ecol. Monogr. 75, 435–450 (2005).

    Article 

    Google Scholar 

  • 16.

    Wilson, K. A., Cabeza, M. & Klein, C. J. Fundamental concepts of spatial conservation prioritization. In Spatial Conservation Prioritization: Quantitative Methods & Computational Tools (eds Moilanen, A. et al.) 16–27 (Oxford University Press, 2009).

    Google Scholar 

  • 17.

    Morlon, H. et al. A general framework for the distance-decay of similarity in ecological communities. Ecol. Lett. 11, 904–917 (2008).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 18.

    Tuomisto, H. Dispersal, environment, and floristic variation of western Amazonian forests. Science 299, 241–244 (2003).

    ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 19.

    Gómez-Rodríguez, C. & Baselga, A. Variation among European beetle taxa in patterns of distance decay of similarity suggests a major role of dispersal processes. Ecography 41, 1825–1834 (2018).

    Article 

    Google Scholar 

  • 20.

    Stella, J. C., Rodríguez-González, P. M., Dufour, S. & Bendix, J. Riparian vegetation research in Mediterranean-climate regions: Common patterns, ecological processes, and considerations for management. Hydrobiologia 719(1), 291–315 (2013).

    Article 

    Google Scholar 

  • 21.

    Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R. & Cushing, C. E. The river continuum concept. Can. J. Fish. Aquat. Sci. 37, 130–137 (1980).

    Article 

    Google Scholar 

  • 22.

    Rouquette, J. R. et al. Species turnover and geographic distance in an urban river network. Divers. Distrib. 19, 1429–1439 (2013).

    Article 

    Google Scholar 

  • 23.

    Kuglerová, L., Jansson, R., Sponseller, R. A., Laudon, H. & Malm-Renöfält, B. Local and regional processes determine plant species richness in a river-network metacommunity. Ecology 96, 381–391 (2015).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 24.

    Zhang, Z., Gao, J. & Cai, Y. The effects of environmental factors and geographic distance on species turnover in an agriculturally dominated river network. Environ. Monit. Assess. 191, 201 (2019).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 25.

    Jost, L., Chao, A. & Chazdon, R. Compositional similarity and beta diversity. In Biological Diversity: Frontiers in Measurement and Assessment (eds Magurran, A. & McGill, B.) 66–84 (Oxford University Press, 2011).

    Google Scholar 

  • 26.

    Olson, D. M. et al. Terrestrial ecoregions of the world: A new map of life on earth. Bioscience 51, 933 (2001).

    Article 

    Google Scholar 

  • 27.

    Miranda, P., Coelho, F., Tomé, A. & Valente, M. Climate Change in Portugal. Scenarios, Impacts and Adaptation Measures—SIAM Project (Gradiva, 2002).

    Google Scholar 

  • 28.

    CIS-WFD. River and lakes—Typology, reference conditions and classification systems, Common Implementation Strategy for the Water Framework Directive (2000/60/EC), Guidance document no 10. 94 (2003).

  • 29.

    INAG. Manual para a avaliação biológica da qualidade da água em sistemas fluviais segundo a DQA—Protocolo de amostragem e análise para os macrófitos (2008).

  • 30.

    Agência Portuguesa do Ambiente. Plano de Gestão da Região Hidrográfica do Tejo, Relatório técnico, Versão Extensa Parte 2—Caracterização e Diagnóstico da Região Hidrográfica. (2012).

  • 31.

    Oksanen, J. et al. vegan: Community Ecology Package—Version 2.7-7. https://CRAN.R-project.org/package=vegan (2021).

  • 32.

    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).

  • 33.

    Peterson, E. E., Theobald, D. M. & Ver Hoef, J. M. Geostatistical modelling on stream networks: Developing valid covariance matrices based on hydrologic distance and stream flow. Freshw. Biol. 52, 267–279 (2007).

    Article 

    Google Scholar 

  • 34.

    Csardi, G. & Nepusz, T. The Igraph software package for complex network research. InterJournal Complex Syst. 1695, 1–9 (2005).

    Google Scholar 

  • 35.

    Lu, B., Sun, H., Harris, P., Xu, M. & Charlton, M. Shp2graph: Tools to convert a spatial network into an Igraph graph in R. ISPRS Int. J. Geo-Inf. 7, 293 (2018).

    Article 

    Google Scholar 

  • 36.

    Vogt, J. & Foisneau, S. CCM River and Catchment Database—Version 2.0 Analysis Tools. (2007).

  • 37.

    Monteiro-Henriques, T. et al. Bioclimatological mapping tackling uncertainty propagation: Application to mainland Portugal. Int. J. Climatol. 36, 400–411 (2016).

    Article 

    Google Scholar 

  • 38.

    Ward, J. V. & Stanford, J. A. The serial discontinuity concept: Extending the model to floodplain rivers. Regul. Rivers Res. Manag. 10, 159–168 (1995).

    Article 

    Google Scholar 

  • 39.

    Dias, F. S., Betancourt, M., Rodríguez-González, P. M. & Borda-de-Água, L. A Bayesian Approach for Analysing Pairwise Comparisons: A Case Study Using Species Composition Similarity (2021) https://doi.org/10.32942/osf.io/sn5jr.

  • 40.

    Stan Development Team. Stan Functions Reference Version 2.25. (2020).

  • 41.

    McElreath, R. Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman and Hall/CRC, 2020).

    Book 

    Google Scholar 

  • 42.

    Rodríguez-González, P. M., Ferreira, M. T., Albuquerque, A., Santo, D. E. & Rego, P. R. Spatial variation of wetland woods in the latitudinal transition to arid regions: A multiscale approach. J. Biogeogr. 35, 1498–1511 (2008).

    Article 

    Google Scholar 

  • 43.

    Stan Development Team. RStan: the R interface to Stan Version 2.21. https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started (2020).

  • 44.

    Betancourt, M. Hierarchical Modeling (2020).

  • 45.

    Muneepeerakul, R., Weitz, J. S., Levin, S. A., Rinaldo, A. & Rodriguez-Iturbe, I. A neutral metapopulation model of biodiversity in river networks. J. Theor. Biol. 245, 351–363 (2007).

    ADS 
    MathSciNet 
    PubMed 
    MATH 
    Article 
    PubMed Central 

    Google Scholar 

  • 46.

    Thompson, R. & Townsend, C. A truce with neutral theory: Local deterministic factors, species traits and dispersal limitation together determine patterns of diversity in stream invertebrates: Neutral theory and local determinism. J. Anim. Ecol. 75, 476–484 (2006).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 47.

    Steinitz, O., Heller, J., Tsoar, A., Rotem, D. & Kadmon, R. Environment, dispersal and patterns of species similarity. J. Biogeogr. 33, 1044–1054 (2006).

    Article 

    Google Scholar 

  • 48.

    Nilsson, C., Brown, R. L., Jansson, R. & Merritt, D. M. The role of hydrochory in structuring riparian and wetland vegetation. Biol. Rev. Camb. Philos. Soc. 85, 837–858 (2010).

    PubMed 
    PubMed Central 

    Google Scholar 

  • 49.

    Gelmi-Candusso, T. A. et al. Estimating seed dispersal distance: A comparison of methods using animal movement and plant genetic data on two primate-dispersed Neotropical plant species. Ecol. Evol. 9, 8965–8977 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 50.

    Rodríguez-González, P. M. et al. A spatial stream-network approach assists in managing the remnant genetic diversity of riparian forests. Sci. Rep. 9, 6741 (2019).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 51.

    Ward, J. V., Tockner, K., Arscott, D. B. & Claret, C. Riverine landscape diversity. Freshw. Biol. 47, 517–539 (2002).

    Article 

    Google Scholar 

  • 52.

    Fraaije, R. G. A. et al. Spatial patterns of water-dispersed seed deposition along stream riparian gradients. PLoS ONE 12, e0185247 (2017).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 53.

    Bendix, J. Flood disturbance and the distribution of riparian species diversity. Geogr. Rev. 87, 468–483 (1997).

    Article 

    Google Scholar 

  • 54.

    Kuglerová, L., Dynesius, M., Laudon, H. & Jansson, R. Relationships between plant assemblages and water flow across a boreal forest landscape: A comparison of liverworts, mosses, and vascular plants. Ecosystems 19, 170–184 (2016).

    Article 
    CAS 

    Google Scholar 

  • 55.

    Wubs, E. R. J. et al. Going against the flow: A case for upstream dispersal and detection of uncommon dispersal events. Freshw. Biol. 61, 580–595 (2016).

    CAS 
    Article 

    Google Scholar 

  • 56.

    Carrera, M., Gyakum, J. & Lin, C. Observational study of wind channeling within the St. Lawrence river valley. J. Appl. Meteorol. Climatol. 48, 2341–2361 (2009).

    ADS 
    Article 

    Google Scholar 

  • 57.

    Kuparinen, A., Katul, G., Nathan, R. & Schurr, F. M. Increases in air temperature can promote wind-driven dispersal and spread of plants. Proc. R. Soc. B Biol. Sci. 276, 3081–3087 (2009).

    Article 

    Google Scholar 

  • 58.

    Soomers, H. et al. Wind and water dispersal of wetland plants across fragmented landscapes. Ecosystems 16, 434–451 (2013).

    Article 

    Google Scholar 

  • 59.

    Jones, K. N. Analysis of pollinator foraging: Tests for non-random behaviour. Funct. Ecol. 11, 255–259 (1997).

    Article 

    Google Scholar 

  • 60.

    Ferreira, M. T. & Aguiar, F. Riparian and aquatic vegetation in Mediterranean-type streams (western Iberia). Limnetica 25, 411–424 (2005).

    Google Scholar 

  • 61.

    Petts, G. E. & Amoros, C. Fluvial hydrosystems: a management perspective. In The Fluvial Hydrosystems (eds Petts, G. E. & Amoros, C.) 263–278 (Springer Netherlands, 1996) https://doi.org/10.1007/978-94-009-1491-9_12.

    Chapter 

    Google Scholar 

  • 62.

    Benda, L. et al. The network dynamics hypothesis: How channel networks structure riverine habitats. Bioscience 54, 413–427 (2004).

    Article 

    Google Scholar 

  • 63.

    QGIS Development Team. QGIS Geographic Information System-Version 3.20.3. (2021).


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