The future of endangered crayfish in light of protected areas and habitat fragmentation


  • 1.

    Erős, T., O’Hanley, J. R. & Czeglédi, I. A unified model for optimizing riverscape conservation. J. Appl. Ecol. 55, 1871–1883 (2018).


    Google Scholar
     

  • 2.

    Ruggeri, P., Pasternak, E. & Okamura, B. To remain or leave: Dispersal variation and its genetic consequences in benthic freshwater invertebrates. Ecol. Evol. 9, 12069–12088 (2019).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • 3.

    Baguette, M., Blanchet, S., Legrand, D., Stevens, V. M. & Turlure, C. Individual dispersal, landscape connectivity and ecological networks. Biol. Rev. 88, 310–326 (2013).

    PubMed 

    Google Scholar
     

  • 4.

    Geist, J. Seven steps towards improving freshwater conservation. Aquat. Conserv. Mar. Freshw. Ecosyst. 25, 447–453 (2015).


    Google Scholar
     

  • 5.

    Kujala, H., Lahoz-Monfort, J. J., Elith, J. & Moilanen, A. Not all data are equal: Influence of data type and amount in spatial conservation prioritisation. Methods Ecol. Evol. 9, 2249–2261 (2018).


    Google Scholar
     

  • 6.

    Johnson, J. B., Peat, S. M. & Adams, B. J. Where’s the ecology in molecular ecology?. Oikos 118, 1601–1609 (2009).


    Google Scholar
     

  • 7.

    Janse, J. H. et al. GLOBIO-aquatic, a global model of human impact on the biodiversity of inland aquatic ecosystems. Environ. Sci. Policy 48, 99–114 (2015).


    Google Scholar
     

  • 8.

    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).

    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • 9.

    Moore, D., Cranston, G., Reed, A. & Galli, A. Projecting future human demand on the Earth’s regenerative capacity. Ecol. Indic. 16, 3–10 (2012).


    Google Scholar
     

  • 10.

    Yawson, D. O., Adu, M. O. & Armah, F. A. Impacts of climate change and mitigation policies on malt barley supplies and associated virtual water flows in the UK. Sci. Rep. 10, 1–12 (2020).


    Google Scholar
     

  • 11.

    Naidoo, R. et al. Global mapping of ecosystem services and conservation priorities. Proc. Natl. Acad. Sci. USA 105, 9495–9500 (2008).

    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • 12.

    Hermoso, V., Villero, D., Clavero, M. & Brotons, L. Spatial prioritisation of EU’s LIFE-Nature programme to strengthen the conservation impact of Natura 2000. J. Appl. Ecol. 55, 1575–1582 (2018).


    Google Scholar
     

  • 13.

    Hermoso, V., Morán-Ordóñez, A., Canessa, S. & Brotons, L. Realising the potential of Natura 2000 to achieve EU conservation goals as 2020 approaches. Sci. Rep. 9, 1–10 (2019).

    CAS 

    Google Scholar
     

  • 14.

    Lobera, G., Pardo, I., García, L. & García, C. Disentangling spatio-temporal drivers influencing benthic communities in temporary streams. Aquat. Sci. 81, 1–17 (2019).

    CAS 

    Google Scholar
     

  • 15.

    Richman, N. I. et al. Multiple drivers of decline in the global status of freshwater crayfish (Decapoda: Astacidea). Philos. Trans. R. Soc. B Biol. Sci. 370, 20140060 (2015).

  • 16.

    Manenti, R. et al. Causes and consequences of crayfish extinction: Stream connectivity, habitat changes, alien species and ecosystem services. Freshw. Biol. 64, 284–293 (2019).


    Google Scholar
     

  • 17.

    Kozák, P., Füreder, L., Kouba, A., Reynolds, J. & Souty-Grosset, C. Current conservation strategies for European crayfish. Knowl. Manag. Aquat. Ecosyst. 01, https://doi.org/10.1051/kmae/2011018 (2011).

  • 18.

    Pârvulescu, L. Introducing a new Austropotamobius crayfish species (Crustacea, Decapoda, Astacidae): A miocene endemism of the Apuseni Mountains, Romania. Zool. Anz. 279, 94–102 (2019).


    Google Scholar
     

  • 19.

    Kouba, A., Petrusek, A. & Kozák, P. Continental-wide distribution of crayfish species in Europe: Update and maps. Knowl. Manag. Aquat. Ecosyst. 413, 05–31 (2014).


    Google Scholar
     

  • 20.

    Pârvulescu, L. et al. A journey on plate tectonics sheds light on European crayfish phylogeography. Ecol. Evol. 9, 1957–1971 (2019).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • 21.

    Pârvulescu, L. & Zaharia, C. Current limitations of the stone crayfish distribution in Romania: Implications for its conservation status. Limnologica 43, 143–150 (2013).


    Google Scholar
     

  • 22.

    Klobučar, G. I. V. et al. Role of the Dinaric Karst (western Balkans) in shaping the phylogeographic structure of the threatened crayfish Austropotamobius torrentium. Freshw. Biol. 58, 1089–1105 (2013).


    Google Scholar
     

  • 23.

    Qian, S. S., Cuffney, T. F., Alameddine, I., McMahon, G. & Reckhow, K. H. On the application of multilevel modeling in environmental and ecological studies. Ecology 91, 355–361 (2010).

    PubMed 

    Google Scholar
     

  • 24.

    Manning, P. et al. Redefining ecosystem multifunctionality. Nat. Ecol. Evol. 2, 427–436 (2018).

    PubMed 

    Google Scholar
     

  • 25.

    Koizumi, I., Usio, N., Kawai, T., Azuma, N. & Masuda, R. Loss of genetic diversity means loss of geological information: The endangered Japanese crayfish exhibits remarkable historical footprints. PLoS ONE 7, e33986 (2012).

    ADS 
    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • 26.

    McNyset, K. M. Use of ecological niche modelling to predict distributions of freshwater fish species in Kansas. Ecol. Freshw. Fish 14, 243–255 (2005).


    Google Scholar
     

  • 27.

    Henrys, P. A. & Jarvis, S. G. Integration of ground survey and remote sensing derived data: Producing robust indicators of habitat extent and condition. Ecol. Evol. 9, 8104–8112 (2019).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • 28.

    Pârvulescu, L., Zaharia, C., Satmari, A. & Drăguţ, L. Is the distribution pattern of the stone crayfish in the Carpathians related to karstic refugia from Pleistocene glaciations?. Freshw. Sci. 32, 1410–1419 (2013).


    Google Scholar
     

  • 29.

    Longshaw, M. & Stebbing, P. Biology and Ecology of Crayfish. (CRC Press, 2015).

  • 30.

    Chucholl, C. The bad and the super-bad: Prioritising the threat of six invasive alien to three imperilled native crayfishes. Biol. Invasions 18, 1967–1988 (2016).


    Google Scholar
     

  • 31.

    Chucholl, C. & Schrimpf, A. The decline of endangered stone crayfish (Austropotamobius torrentium) in southern Germany is related to the spread of invasive alien species and land-use change. Aquat. Conserv. Mar. Freshw. Ecosyst. 26, 44–56 (2016).


    Google Scholar
     

  • 32.

    Pârvulescu, L. et al. Flash-flood potential: A proxy for crayfish habitat stability. Ecohydrology 9, 1507–1516 (2016).


    Google Scholar
     

  • 33.

    Farr, T. G. et al. The shuttle radar topography mission. Rev. Geophys. 45, RG2004 (2007).

  • 34.

    Şandric, I. et al. Integrating catchment land cover data to remotely assess freshwater quality: A step forward in heterogeneity analysis of river networks. Aquat. Sci. 81, 26 (2019).


    Google Scholar
     

  • 35.

    Burkhard, B., Kroll, F., Nedkov, S. & Müller, F. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 21, 17–29 (2012).


    Google Scholar
     

  • 36.

    Zeller, K. A., McGarigal, K. & Whiteley, A. R. Estimating landscape resistance to movement: A review. Landsc. Ecol. 27, 777–797 (2012).


    Google Scholar
     

  • 37.

    Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).


    Google Scholar
     

  • 38.

    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2017).

  • 39.

    Freeman, E. A. & Moisen, G. G. A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa. Ecol. Modell. 217, 48–58 (2008).


    Google Scholar
     

  • 40.

    Iorgu, E. I., Popa, O. P., Petrescu, A.-M. & Popa, L. O. Cross-amplification of microsatellite loci in the endangered stone-crayfish Austropotamobius torrentium (Crustacea: Decapoda). Knowl. Manag. Aquat. Ecosyst. 08, https://doi.org/10.1051/kmae/2011021 (2011).

  • 41.

    Peakall, R. & Smouse, P. E. genalex 6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295 (2006).

  • 42.

    Goudet, J. FSTAT (Version 1.2): A computer program to calculate F-statistics. J. Hered. 86, 485–486 (1995).

  • 43.

    Rousset, F. genepop’007: A complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).

    PubMed 

    Google Scholar
     

  • 44.

    Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. & Shipley, P. micro-checker: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).


    Google Scholar
     

  • 45.

    Dempster, A. P., Laird, N. M. & Rubin, D. B. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B 39, 1–22 (1977).

    MathSciNet 
    MATH 

    Google Scholar
     

  • 46.

    Chapuis, M. P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).

    PubMed 
    CAS 

    Google Scholar
     

  • 47.

    Weir, B. S. & Cockerham, C. C. Estimating F‐statistics for the analysis of population structure. Evolution (N. Y). 38, 1358–1370 (1984).

  • 48.

    Hammer, D. A. T., Ryan, P. D., Hammer, Ø. & Harper, D. A. T. Past: Paleontological Statistics Software Package for Education and Data Analysis. Palaeontologia Electronica vol. 4 https://palaeo-electronica.orghttp//palaeo-electronica.org/2001_1/past/issue1_01.htm. (2001).

  • 49.

    Nei, M., Tajima, F. & Tateno, Y. Accuracy of estimated phylogenetic trees from molecular data. J. Mol. Evol. 19, 153–170 (1983).

    ADS 
    PubMed 
    CAS 

    Google Scholar
     

  • 50.

    Langella, O. Populations, 1.2. 30. https://bioinformatics.org/~tryphon/populations (1999).

  • 51.

    Pritchard, J. K., Stephens, M., Rosenberg, N. A. & Donnelly, P. Association mapping in structured populations. Am. J. Hum. Genet. 67, 170–181 (2000).

    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • 52.

    Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).

    PubMed 
    CAS 

    Google Scholar
     

  • 53.

    Kopelman, N. M., Mayzel, J., Jakobsson, M., Rosenberg, N. A. & Mayrose, I. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191 (2015).

    PubMed 
    PubMed Central 
    CAS 

    Google Scholar
     

  • 54.

    Vähä, J. P. & Primmer, C. R. Efficiency of model-based Bayesian methods for detecting hybrid individuals under different hybridization scenarios and with different numbers of loci. Mol. Ecol. 15, 63–72 (2005).


    Google Scholar
     

  • 55.

    Bergl, R. A. & Viglant, L. Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli). Mol. Ecol. 16, 501–516 (2006).


    Google Scholar
     

  • 56.

    Jombart, T., Devillard, S. & Balloux, F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genet. 11, 1–15 (2010).


    Google Scholar
     

  • 57.

    Paetkau, D., Calvert, W., Stirling, I. & Strobeck, C. Microsatellite analysis of population structure in Canadian polar bears. Mol. Ecol. 4, 347–354 (1995).

    PubMed 
    CAS 

    Google Scholar
     

  • 58.

    Duchesne, P. & Turgeon, J. FLOCK Provides Reliable Solutions to the ‘“Number of Populations”’ Problem. https://doi.org/10.1093/jhered/ess038.

  • 59.

    Janes, J. K. et al. The K = 2 conundrum. Mol. Ecol. 26, 3594–3602 (2017).

    PubMed 

    Google Scholar
     

  • 60.

    Funk, S. M. et al. Major inconsistencies of inferred population genetic structure estimated in a large set of domestic horse breeds using microsatellites. Ecol. Evol. 10, 4261–4279 (2020).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • 61.

    Berger, C., Štambuk, A., Maguire, I., Weiss, S. & Füreder, L. Integrating genetics and morphometrics in species conservation—A case study on the stone crayfish, Austropotamobius torrentium. Limnologica 69, 28–38 (2018).


    Google Scholar
     

  • 62.

    Iojă, C. I. et al. The efficacy of Romania’s protected areas network in conserving biodiversity. Biol. Conserv. 143, 2468–2476 (2010).


    Google Scholar
     

  • 63.

    Rabăgia, T. & Maţenco, L. Tertiary tectonic and sedimentological evolution of the South Carpathians foredeep: Tectonic vs eustatic control. Mar. Pet. Geol. 16, 719–740 (1999).

  • 64.

    Rãdoane, M., Rãdoane, N. & Dumitriu, D. Geomorphological evolution of longitudinal river profiles in the Carpathians. Geomorphology 50, 293–306 (2003).

    ADS 

    Google Scholar
     

  • 65.

    Helms, B., Loughman, Z. J., Brown, B. L. & Stoeckel, J. Recent advances in crayfish biology, ecology, and conservation. Freshw. Sci. 32, 1273–1275 (2013).


    Google Scholar
     

  • 66.

    Svobodová, J. et al. The relationship between water quality and indigenous and alien crayfish distribution in the Czech Republic: Patterns and conservation implications. Aquat. Conserv. Mar. Freshw. Ecosyst. 22, 776–786 (2012).


    Google Scholar
     

  • 67.

    Pöckl, M. & Streissl, F. Austropotamobius torrentium as an indicator for habitat quality in running waters? Bull. Français la Pêche la Piscic. 743–758, https://doi.org/10.1051/kmae:2005030 (2005).

  • 68.

    Magyar, I. et al. Progradation of the paleo-Danube shelf margin across the Pannonian Basin during the Late Miocene and Early Pliocene. Glob. Planet. Change 103, 168–173 (2013).

    ADS 

    Google Scholar
     

  • 69.

    Zhang, Y., Luan, P., Ren, G., Hu, G. & Yin, J. Estimating the inbreeding level and genetic relatedness in an isolated population of critically endangered Sichuan taimen (Hucho Bleekeri) using genome-wide SNP markers. Ecol. Evol. 10, 1390–1400 (2020).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • 70.

    Hoarau, G. et al. Low effective population size and evidence for inbreeding in an overexploited flatfish, plaice (Pleuronectes platessa L.). Proc. Biol. Sci. 272, 497–503 (2005).

  • 71.

    Jourdan, J. et al. Reintroduction of freshwater macroinvertebrates: Challenges and opportunities. Biol. Rev. https://doi.org/10.1111/brv.12458 (2018).

    Article 
    PubMed 

    Google Scholar
     

  • 72.

    Oidtmann, B., Heitz, E., Rogers, D. & Hoffmann, R. Transmission of crayfish plague. Dis. Aquat. Organ. 52, 159–167 (2002).

    PubMed 

    Google Scholar
     

  • 73.

    Rusch, J. C. et al. Simultaneous detection of native and invasive crayfish and Aphanomyces astaci from environmental DNA samples in a wide range of habitats in Central Europe. NeoBiota (2020).

  • 74.

    Hall, Q. A., Curtis, J. M., Williams, J. & Stunz, G. W. The importance of newly-opened tidal inlets as spawning corridors for adult Red Drum (Sciaenops ocellatus). Fish. Res. 212, 48–55 (2019).


    Google Scholar
     

  • 75.

    Stewart, F. E. C., Darlington, S., Volpe, J. P., McAdie, M. & Fisher, J. T. Corridors best facilitate functional connectivity across a protected area network. Sci. Rep. 9, 10852 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • 76.

    Strauss, A., White, A. & Boots, M. Invading with biological weapons: The importance of disease-mediated invasions. Funct. Ecol. 26, 1249–1261 (2012).


    Google Scholar
     

  • 77.

    Clavero, M. & García-Berthou, E. Invasive species are a leading cause of animal extinctions. Trends Ecol. Evol. 20, 110 (2005).

    PubMed 

    Google Scholar
     

  • 78.

    Nunes, A. L., Tricarico, E., Panov, V. E., Cardoso, A. C. & Katsanevakis, S. Pathways and gateways of freshwater invasions in Europe. Aquat. Invasions 10, 359–370 (2015).


    Google Scholar
     

  • 79.

    Zeng, Y. & Yeo, D. C. J. Assessing the aggregated risk of invasive crayfish and climate change to freshwater crabs: A Southeast Asian case study. Biol. Conserv. 223, 58–67 (2018).


    Google Scholar
     

  • 80.

    Alonso, F., Temino, C. & Diéguez-Uribeondo, J. Status of the white-clawed crayfish, Austropotamobius pallipes (Lereboullet, 1858), in Spain: Distribution and legislation. 31–53 (2000).

  • 81.

    Van Dyck, H. & Baguette, M. Dispersal behaviour in fragmented landscapes: Routine or special movements?. Basic Appl. Ecol. 6, 535–545 (2005).


    Google Scholar
     

  • 82.

    Rodrigues, A. S. L., Pilgrim, J. D., Lamoreux, J. F., Hoffmann, M. & Brooks, T. M. The value of the IUCN Red List for conservation. Trends Ecol. Evol. 21, 71–76 (2006).

    PubMed 

    Google Scholar
     

  • 83.

    Füreder, L., Gherardi, F. & Souty-Grosset, C. Austropotamobius torrentium. The IUCN Red List of Threatened Species 2010 e.T2431A9439449 https://doi.org/10.2305/IUCN.UK.2010-3.RLTS.T2431A9439449.en (2010).



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