DOI QR코드

DOI QR Code

Characterizing Responses of Biological Trait and Functional Diversity of Benthic Macroinvertebrates to Environmental Variables to Develop Aquatic Ecosystem Health Assessment Index

환경변이에 대한 저서성 대형무척추동물의 생물학적 형질과 기능적 다양성 분석: 수생태계 건강성 평가 관점에서

  • Received : 2020.03.04
  • Accepted : 2020.03.19
  • Published : 2020.03.31

Abstract

The biological indices based on the community structure with species richness and/or abundance are commonly used to assess aquatic ecosystem health. Meanwhile, recently functional traits-based approach is considered in ecosystem health assessment to reflect ecosystem functioning. In this study, we developed a database of biological traits for 136 taxa consisting of major stream insects (Ephemeroptera, Plecoptera, Trichoptera, Coleoptera, and Odonata) collected at Korean streams on the nationwide scale. In addition, we obtained environmental variables in five categories (geography, climate, land use, hydrology and physicochemistry) measured at each sampling site. We evaluated the relationships between community indices based on taxonomic diversity and functional diversity estimated from biological traits. We classified sampling sites based on similarities of their environmental variables and evaluated relations between clusters of sampling sites and diversity indices and biological traits. Our results showed that functional diversity was highly correlated with Shannon diversity index and species richness. The six clusters of sampling sites defined by a hierarchical cluster analysis reflected differences of their environmental variables. Samples in cluster 1 were mostly from high altitude areas, whereas samples in cluster 6 were from lowland areas. Non-metric multidimensional scaling (NMDS) displayed similar patterns with cluster analysis and presented variation of taxonomic diversity and functional diversity. Based on NMDS and community-weighted mean trait value matrix, species in clusters 1-3 displayed the resistance strategy in the life history strategy to the environmental variables whereas species in clusters 4-6 presented the resilience strategy. These results suggest that functional diversity can complement the biological monitoring assessment based on taxonomic diversity and can be used as biological monitoring assessment tool reflecting changes of ecosystem functioning responding to environmental changes.

군집지수와 FD와의 상관분석 결과 FD는 군집지수 중 Shannon 다양도와 가장 높은 상관성을 보였다. 조사지점은 환경 특성에 따라 6개의 그룹으로 나누어졌으며, 고도에 따라서 뚜렷한 차이를 보였다. 이에 따라 고도가 높은 그룹 1은 산림의 비율이 많고 좋은 수질을 보였으나 고도가 낮은 그룹 6은 수질이 양호하지 않았다. 환경 구배에 따른 조사지역 그룹과 군집지수와 FD의 연관성 분석을 위해 NMDS를 시행하였으며 그룹 1~3에서 FEve를 제외한 모든 지수가 높았다. 그룹 간의 종구성은 그룹 1~3에는 하루살이목, 날도래목, 강도래목이 높았으며, 그룹 4, 5에는 잠자리목, 딱정벌레목이 주요하게 나타났다. 생물학적 형질은 그룹 1~3에서 생식기간이 길고, 이동성이 낮은 형질 특성을 보였으며 생물의 저항력 전략을 잘 보여주었다. 반대로 그룹 4~6은 생식기간이 짧고, 이동성이 높은 회복력의 전략을 뚜렷하게 반영해 주었다. 수질의 오염도가 낮은 상류는 교란의 빈도가 적고 공간적으로 높은 이질성을 가졌으며 생물이 주로 저항성 전략을 보였으며 생물이 서식지에 오래 머무를 수 있어 기능적, 구조적 생물다양성이 높게 나타났다. 반대로 수질의 오염도가 높은 하류는 교란의 빈도가 높고 공간적으로 균질성이 높으며 생물은 주로 회복력의 전력을 보여 교란에 의해 이동하거나 회피할 수 있는 휴면기, 고치, 세포, 알 등의 독특한 형태를 갖는 반면 생물다양성은 낮게 나타났다. 본 연구를 통해 저서성 대형 무척추동물의 기능적 다양성은 수서 생태계 환경과의 관계를 잘 설명해 주었다. 따라서 생물의 형질을 이용한 기능적 다양성은 잠재적으로 수생태계 건강성 평가에 효과적으로 이용될 수 있을 것이다.

Keywords

References

  1. Anderson, M.J., K.E. Ellingsen and B.H. McArdle. 2006. Multivariate dispersion as a measure of beta diversity. Ecology Letters 9: 683-693. https://doi.org/10.1111/j.1461-0248.2006.00926.x
  2. Authro. 2006. A Database of Lotic Invertebrate Traits for North America: U.S. Geological Survey Data Series 187, http://pubs.water.usgs.gov/ds187.
  3. Balvanera, P., A.B. Pfisterer, N. Buchmann, J.S. He, T. Nakashizuka, D. Raffaelli and B. Schmid. 2006. Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecology Letters 9: 1146-1156. https://doi.org/10.1111/j.1461-0248.2006.00963.x
  4. Bauernfeind, E. and T. Soldan. 2012. The Mayflies of Europe (Ephemeroptera). Brill, Leiden.
  5. Bonada, N., N. Prat, V.H. Resh and B. Statzner. 2006. Developments in aquatic insect biomonitoring: a comparative analysis of recent approaches. Annual Review of Entomology 51: 495-523. https://doi.org/10.1146/annurev.ento.51.110104.151124
  6. Botta-Dukat, Z. 2005. Raos quadratic entropy as a measure of functional diversity based on multiple traits. Journal of Vegetation Science 16: 533-540. https://doi.org/10.1111/j.1654-1103.2005.tb02393.x
  7. Bremner, J., S.I. Rogers and C.L.J. Frid. 2006. Methods for describing ecological functioning of marine benthic assemblages using biological traits analysis (BTA). Ecological Indicators 6: 609-622. https://doi.org/10.1016/j.ecolind.2005.08.026
  8. Briers, R. 2016. Biotic: Calculation of Freshwater Biotic Indices. R package version 0.1.2. https://github.com/robbriers/biotic.
  9. Brown, L.E., K. Khamis, M. Wilkes, P. Blaen, J.E. Brittain, J.L. Carrivick, S. Fell, N. Friberg, L. Fureder, G.M. Gislason, S. Hainie, D.M. Hannah, W.H.M. James, V. Lencioni, J.S. Olafsson, C.T. Robinson, S.J. Saltveit, C. Thompson and A.M. Milner. 2018. Functional diversity and community assembly of river invertebrates show globally consistent responses to decreasing glacier cover. Nature Ecology & Evolution 2: 325-333. https://doi.org/10.1038/s41559-017-0426-x
  10. Canessa, R., A. Saldaña, R.S. Rios and E. Gianoli. 2018. Functional trait variation predicts distribution of alien plant species across the light gradient in a temperate rainforest. Perspectives in Plant Ecology, Evolution and Systematics 32: 49-55. https://doi.org/10.1016/j.ppees.2018.04.002
  11. Chapin, F.S., E.S. Zavaleta, V.T. Eviner, R.L. Naylor, P.M. Vitousek, H.L. Reynolds, D.U. Hooper, S. Lavorel, O.E. Sala, S.E. BHobbie, M.C. Mack and S. Diaz. 2000. Consequences of changing biodiversity. Nature 405: 234-242. https://doi.org/10.1038/35012241
  12. Charvet, S., A. Kosmala and B. Statzner. 1998. Biomonitoring through biological traits of benthic macroinvertebrates: perspectives for a general tool in stream management. Archiv fur Hydrobiologie 142: 415-432. https://doi.org/10.1127/archiv-hydrobiol/142/1998/415
  13. Chevenet, F., S. Doledec and D. Chessel. 2006. A fuzzy coding approach for the analysis of long-term ecological data. Freshwater Biology 31: 295-309. https://doi.org/10.1111/j.1365-2427.1994.tb01742.x
  14. Cornwell, W.K., D.W. Schwilk and D.D. Ackerly. 2006. A traitbased test for habitat filtering: convex hull volume. Ecology 87: 1465-1471. https://doi.org/10.1890/0012-9658(2006)87[1465:ATTFHF]2.0.CO;2
  15. Covich, A., M. Austen, F. Baerlocher, E. Chauvet, B. Cardinale, C. Biles, P. Inchausti, O. Dangles, M. Solan, M. Gessner, B. Statzner and B. Moss. 2004. The role of biodiversity in the functioning of freshwater and marine benthic ecosystems. Bioscience 54: 767-775. https://doi.org/10.1641/0006-3568(2004)054[0767:TROBIT]2.0.CO;2
  16. Culp, J.M., D.G. Armanini, M.J. Dunbar, J.M. Orlofske, N.L. Poff, A.I. Pollard, A.G. Yates and G.C. Hose. 2011. Incorporating traits in aquatic biomonitoring to enhance causal diagnosis and prediction. Integrated Environmental Assessment and Management 7: 187-197. https://doi.org/10.1002/ieam.128
  17. Diaz, S. and M. Cabido. 2001. Vive la difference: plant functional diversity matters to ecosystem processes. Trends in Ecology & Evolution 16: 646-655. https://doi.org/10.1016/S0169-5347(01)02283-2
  18. Doledec, S., J.M. Olivier and B. Statzner. 2000. Accurate description of the abundance of taxa and their biological traits in stream invertebrate communities: effects of taxonomic and spatial resolution. Archiv fur Hydrobiologie 148: 25-43. https://doi.org/10.1127/archiv-hydrobiol/148/2000/25
  19. Doledec, S., N. Phillips, M. Scarsbrook, R.H. Riley and C.R. Townsend. 2006. Comparison of structural and functional approaches to determining landuse effects on grassland stream invertebrate communities. Journal of the North American Benthological Society 25: 44-60. https://doi.org/10.1899/0887-3593(2006)25[44:COSAFA]2.0.CO;2
  20. Doledec, S. and B. Statzner. 2008. Invertebrate traits for the biomonitoring of large European rivers: an assessment of specific types of human impact. Freshwater Biology 53: 617-634. https://doi.org/10.1111/j.1365-2427.2007.01924.x
  21. Dray, S. and P. Legendre. 2008. Testing the species traits-environment relationships: the fourth-corner problem revisited. Ecology 89: 3400-3412. https://doi.org/10.1890/08-0349.1
  22. Dudgeon, D. 1999. Tropical Asian Streams: Zoobenthos, Ecology and Conservation (Vol. 1). Hong Kong University Press.
  23. Dunn, O.J. 1964. Multiple comparisons using rank sums. Technometrics 6: 241-252. https://doi.org/10.1080/00401706.1964.10490181
  24. Edmunds, G.F., S.L. Jensen and L. Berner. 1976. The Mayflies of North and Central America. University of Minnesota Press.
  25. Feld, C.K. and D. Hering. 2007. Community structure or function:effects of environmental stress on benthic macroinvertebrates at different spatial scales. Freshwater Biology 52:1380-1399. https://doi.org/10.1111/j.1365-2427.2007.01749.x
  26. Feld, C.K., F. de Bello and S. Doledec. 2014. Biodiversity of traits and species both show weak responses to hydromorphological alteration in lowland river macroinvertebrates. Freshwater Biology 59: 233-248. https://doi.org/10.1111/fwb.12260
  27. Garnier, E., J. Cortez, G. Billes, M.-L. Navas, C. Roumet, M. Debussche, G. Laurent, A. Blanchard, D. Aubry, A. Bellmann, C. Neill and J.-P. Toussaint. 2004. Plant functional markers capture ecosystem properties during secondary succession. Ecology 85: 2630-2637. https://doi.org/10.1890/03-0799
  28. Garrido, J., J.C. Benetti and A.P. Bilbao. 2011. Identification Guide of Freshwater Macroinvertebrates of Spain. Springer Dordrecht.
  29. Gayraud, S., B. Statzner, P. Bady, A. Haybachp, F. Scholl, P. Ussegio-Polatera and M. Bacchi. 2003. Invertebrate traits for the biomonitoring of large European rivers: an initial assessment of alternative metrics. Freshwater Biology 48:2045-2064. https://doi.org/10.1046/j.1365-2427.2003.01139.x
  30. Giller, P.S., P. Giller and B. Malmqvist. 1998. The Biology of Streams and Rivers. Oxford University Press, Oxford.
  31. Giraudoux, P. 2013. Pgirmess: data analysis in ecology. R package version 1.5.
  32. Hooper, D.U., F.S. Chapin, J.J. Ewel, A. Hector, P. Inchausti, S. Lavorel, J.H. Lawton, D.M. Lodge, M. Loreau, S. Naeem, B. Schmid, H. Setala, A.J. Symstad, J. Vandermeer and D.A. Wardle. 2005. Effects of biodiversity on ecosystem fucntioning:a consequensus of current knowledge. Ecological Monographs 75: 3-35. https://doi.org/10.1890/04-0922
  33. Huryn, A.D., J.B. Wallace and N.H. Anderson. 2008. Habitat life history, secondary production, and behavioral adaptations of aquatic insects. 3nd edition, In: Merritt, R.W., K.W. Cummins and M.B. Berg (eds.), An Introduction to the Aquatic Insects of North America. 4th ed. Kendall/Hunt Publishing Company, Dubuque, lowa, pp. 55-103.
  34. Hynes, H.B.N. 1970. The Ecology of Running Waters. Liverpool University Press, Liverpool.
  35. IPCC. 2014. Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland.
  36. Jun, Y.-C., N.-Y. Kim, S.-H. Kim, Y.-S. Park, D.-S. Kong and S.-J. Hwang. 2016. Spatial distribution of benthic macroinvertebrate assemblages in relation to environmental variables in Korean nationwide streams. Water 8: 27. https://doi.org/10.3390/w8010027
  37. Jung, K. 2007. Odonata of Korea. 1064 Studio.
  38. Jung, K. 2011. Odonata larvae of Korea. Nature and Ecology, Seoul.
  39. Kim, M.C., S.P. Chon and J.K. Lee. 2013. Invertebrates in Korean Freshwater Ecosystems. Geobook, Seoul.
  40. Kruskal, J.B. 1964. Nonmetric multidimensional scaling: a numerical method. Psychometrika 29: 115-129. https://doi.org/10.1007/BF02289694
  41. Kwak, I.-S., D.-S. Lee, C. Hong and Y.-S. Park. 2018. Distribution patterns of benthic macroinvertebrates in streams of Korea. Korean Journal of Ecology and Environment 51:60-70. https://doi.org/10.11614/KSL.2018.51.1.060
  42. Kwon, S.J., Y.C. Chon and J.H. Park. 2013. Benthic Macroinvertebrates. Nature and Ecology, Seoul.
  43. Laliberte, E. and P. Legendre. 2010. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91: 299-305. https://doi.org/10.1890/08-2244.1
  44. Lavorel, S., J. Storkey, R.D. Bardgett, F. de Bello, M.P. Berg, X. Le Roux, M. Moretti, C. Mulder, R.J. Pakeman, S. Diaz and R. Harrington. 2013. A novel framework for linking functional diversity of plants with other trophic levels for the quantification of ecosystem services. Journal of Vegetation Science 24: 942-948. https://doi.org/10.1111/jvs.12083
  45. Lee, D.-Y., M.-J. Bae, Y.-S. Kwon, C.-W. Park, H.M. Yang, Y. Shin, T.-S. Kwon and Y.-S. Park. 2018a. Characteristics of spatiotemporal patterns in benthic macroinvertebrate communities in two adjacent headwater streams. Korean Journal of Ecology and Environment 51: 192-203. https://doi.org/10.11614/KSL.2018.51.2.192
  46. Lee, D.Y., D.S. Lee, M.J. Bae, S.J. Hwang, S.Y. Noh, J.S. Moon and Y.S. Park. 2018b. Distribution patterns of odonate assemblages in relation to environmental variables in streams of South Korea. Insects 9.
  47. Legendre, P. and L. Legendre. 2012. Numerical Ecology, 3rd ed. Elsevier, Amsterdam.
  48. Legras, G., N. Loiseau and J.C. Gaertner. 2018. Functional richness:Overview of indices and underlying concepts. Acta Oecologica 87: 34-44. https://doi.org/10.1016/j.actao.2018.02.007
  49. Lenat, D.R. 1988. Water quality assessment of streams using a qualitative collection method for benthic macroinvertebrates. Journal of the North American Benthological Society 7: 222-233. https://doi.org/10.2307/1467422
  50. Menezes, S., D.J. Baird and A.M.V.M. Soares. 2010. Beyond taxonomy: a review of macroinvertebrate trait-based community descriptors as tools for freshwater biomonitoring. Journal of Applied Ecology 47: 711-719. https://doi.org/10.1111/j.1365-2664.2010.01819.x
  51. Merritt, R.W., K.W. Cummins and M.B. Berg. 2008. An Introduction to the Aquatic Insects of North America, 4th ed. Kendall Hunt Publishing, Dubuque, Iowa.
  52. Ministry of Environment / National Institute of Environmental Research, 2008. The Survey and Evaluation of Aquatic Ecosystem Health in Korea. The Ministry of Environment/National Institute of Environmental Research, Incheon, Korea (in Korean with English summary).
  53. Mondy, C.P., I. Munoz and S. Doledec. 2016. Life-history strategies constrain invertebrate community tolerance to multiple stressors: A case study in the Ebro basin. Science of The Total Environment 572: 196-206. https://doi.org/10.1016/j.scitotenv.2016.07.227
  54. Oksanen, J., F.G. Blanchet, R. Kindt, P. Legendre, R.B. O'Hara, S. Gavin, P. Solymos, M.H.H. Stevens and H. Wagner. 2011. vegan: Community Ecology Package. R package version 1:17-10.
  55. Paisley, M.F., D.J. Trigg and W.J. Walley. 2014. Revision of the Biological Monitoring Working Party (BMWP) score system: derivation of present-only and abundance-related scores from field data. River Research and Applications 30:887-904. https://doi.org/10.1002/rra.2686
  56. Pease, A.A., J.M. Taylor, K.O. Winemiller and R.S. King. 2015. Ecoregional, catchment, and reach-scale environmental factors shape functional-trait structure of stream fish assemblages. Hydrobiologia 753: 265-283. https://doi.org/10.1007/s10750-015-2235-z
  57. Petchey, O.L. and K.J. Gaston. 2002. Functional diversity (FD), species richness and community composition. Ecology Letters 5: 10.
  58. Poff, N.L., J.D. Olden, N.K.M. Vieira, D.S. Finn, M.P. Simmons and B.C. Kondratieff. 2006. Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships. Journal of the North American Benthological Society 25: 730-755. https://doi.org/10.1899/0887-3593(2006)025[0730:FTNONA]2.0.CO;2
  59. Pohlert, T. 2014. The Pairwise Multiple Comparison of Mean Ranks Package (PMCMR). R package. http://CRAN. R-project.org/package=PMCMR.
  60. Pont, D., B. Hugueny, U. Beier, D. Goffaux, A. Melcher, R. Noble, C. Rogers, N. Roset and S. Schmutz. 2006. Assessing river biotic condition at a continental scale: a European approach using functional metrics and fish assemblages. Journal of Applied Ecology 43: 70-80. https://doi.org/10.1111/j.1365-2664.2005.01126.x
  61. R Core Team. 2017. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  62. Resh, V.H., A.G. Hildrew, B. Statzner and C.R. Townsend. 1994. Theoretical habitat templets, species traits, and species richness: a synthesis of long-term ecological research on the Upper RhOne River in the context of concurrently developed ecological theory. Freshwater Biology 31: 539-554. https://doi.org/10.1111/j.1365-2427.1994.tb01756.x
  63. Ricotta, C. and M. Moretti. 2011. CWM and Rao’s quadratic diversity:a unified framework for functional ecology. Oecologia 167: 181-188. https://doi.org/10.1007/s00442-011-1965-5
  64. Schmitz, O.J. 2010. Resolving Ecosystem Complexity (MPB-47). Princeton University Press, Princeton, New Jersey.
  65. Schmitz, O.J., R.W. Buchkowski, K.T. Burghardt and C.M. Donihue. 2015. Chapter Ten - Functional Traits and Trait-Mediated Interactions: Connecting Community-Level Interactions with Ecosystem Functioning, In: Pawar, S., Woodward, G., Dell, A.I. (eds.), Advances in Ecological Research, vol. 52. Academic Press, Oxford, pp. 319-343.
  66. Shannon, C.E. 1948. A mathematical theory of communication. Bell System Technical Journal 27: 379-423 and 623-656. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  67. Siegel, S. and N.J. Castellan. 1988. Nonparametric Statistics for the Behavioral Sciences. McGraw-Hill, New York.
  68. Sneath, P.H.A. and R.R. Sokal. 1973. Numerical Taxonomy: The Principles and Practice of Numerical Classification. W. H. Freeman and Co., London.
  69. Sponseller, R.A., E.F. Benfield and H.M. Valett. 2001. Relationships between land use, spatial scale and stream macroinvertebrate communities. Freshwater Biology 46: 1409-1424. https://doi.org/10.1046/j.1365-2427.2001.00758.x
  70. Statzner, B. and L.A. Beche. 2010. Can biological invertebrate traits resolve effects of multiple stressors on running water ecosystems? Freshwater Biology 55: 80-119. https://doi.org/10.1111/j.1365-2427.2009.02369.x
  71. Statzner, B., B. Bis, S. Doledec and P. Usseglio-Polatera. 2001. Perspectives for biomonitoring at large spatial scales: a unified measure for the functional composition of invertebrate communities in European running waters. Basic and Applied Ecology 2: 73-85. https://doi.org/10.1078/1439-1791-00039
  72. Statzner, B., K. Hoppenhaus, M.-F. Arens and P. Richoux. 1997. Reproductive traits, habitat use and templet theory: a synthesis of world-wide data on aquatic insects. Freshwater Biology 38: 109-135. https://doi.org/10.1046/j.1365-2427.1997.00195.x
  73. Statzner, B., S. Doledec and B. Hugueny. 2004. Biological trait composition of European stream invertebrate communities:assessing the effects of various trait filter types. Ecography 27: 470-488. https://doi.org/10.1111/j.0906-7590.2004.03836.x
  74. Swenson, N.G. 2014. Functional and Phylogenetic Ecology in R. Springer, New York.
  75. Thorp, J.H. and A.P. Covich. 2009. Ecology and Classification of North American Freshwater Invertebrates. Academic Press, San Diego.
  76. Tilman, D. 2001. Functional diversity, Encyclopedia of Biodiversity. Academic Press, pp. 109-121.
  77. Townsend, C.R. and A.G. Hildrew. 1994. Species traits in relation to a habitat templet for river systems. Freshwater Biology 31: 265-275. https://doi.org/10.1111/j.1365-2427.1994.tb01740.x
  78. Usseglio-Polatera, P., M. Bournaud, P. Richoux and H. Tachet. 2000a. Biological and ecological traits of benthic freshwater macroinvertebrates: relationships and definition of groups with similar traits. Freshwater Biology 43: 175-205. https://doi.org/10.1046/j.1365-2427.2000.00535.x
  79. Usseglio-Polatera, P., M. Bournaud, P. Richoux and H. Tachet. 2000b. Biomonitoring through biological traits of benthic macroinvertebrates: how to use species trait databases? Hydrobiologia 422/423: 153-162. https://doi.org/10.1023/A:1017042921298
  80. Vandewalle, M., F. de Bello, M.P. Berg, T. Bolger, S. Doledec, F. Dubs, C.K. Feld, R. Harrington, P.A. Harrison, S. Lavorel, P.M. da Silva, M. Moretti, J. Niemela, P. Santos, T. Sattler, J.P. Sousa, M.T. Sykes, A.J. Vanbergen and B.A. Woodcock. 2010. Functional traits as indicators of biodiversity response to land use changes across ecosystems and organisms. Biodiversity and Conservation 19: 2921-2947. https://doi.org/10.1007/s10531-010-9798-9
  81. Villeger, S., N.W.H. Mason and D. Mouillot. 2008. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89: 2290-2301. https://doi.org/10.1890/07-1206.1
  82. Vo$\ss$, K. and R.B. Schafer. 2017. Taxonomic and functional diversity of stream invertebrates along an environmental stress gradient. Ecological Indicators 81: 235-242. https://doi.org/10.1016/j.ecolind.2017.05.072
  83. Wang, W.J., H.S. He, F.R. Thompson, M.A. Spetich and J.S. Fraser. 2018. Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change. Science of The Total Environment 634: 1214-1221. https://doi.org/10.1016/j.scitotenv.2018.03.353
  84. Ward, J.H. 1963. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58: 236-244. https://doi.org/10.1080/01621459.1963.10500845
  85. Wichard, W., W. Arens and G. Eisenbeis. 2002. Biological Atlas of Aquatic Insects. Apollo Books, Stenstrup, Denmark.
  86. Wiggins, G.B. 2004. Caddisflies: the Underwater Architects. University of Toronto Press, Totonto.
  87. Woon, D.H., S.J. Kwon and Y.C. Chon. 2005. Aquatic Insects of Korea. Korea Ecosystem Service, Seoul.