دورية أكاديمية
أعرض في EDS

Human pressure drives biodiversity-multifunctionality relationships in large Neotropical wetlands.

التفاصيل البيبلوغرافية
العنوان: Human pressure drives biodiversity-multifunctionality relationships in large Neotropical wetlands.
المؤلفون: Moi DA; Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil. dieisonandrebv@outlook.com., Lansac-Tôha FM; Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil., Romero GQ; Laboratory of Multitrophic Interactions and Biodiversity, Department of Animal Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil., Sobral-Souza T; Department of Botany and Ecology, Institute of Bioscience, Federal University of Mato Grosso, Cuiabá, Brazil., Cardinale BJ; Department of Ecosystem Science and Management, Penn State University, University Park, PA, USA., Kratina P; School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK., Perkins DM; School of Life and Health Sciences, University of Roehampton, Whitelands College, London, UK., Teixeira de Mello F; Departamento de Ecología y Gestión Ambiental CURE, Universidad de la República, Maldonado, Uruguay., Jeppesen E; Department of Ecoscience and WATEC, Aarhus University, Aarhus C, Denmark.; Sino-Danish Centre for Education and Research, Beijing, China.; Limnology Laboratory, Department of Biological Sciences and Centre for Ecosystem Research and Implementation, Middle East Technical University, Ankara, Turkey.; Institute of Marine Sciences, Middle East Technical University, Erdemli-Mersin, Turkey., Heino J; Freshwater Centre, Finnish Environment Institute, Oulu, Finland., Lansac-Tôha FA; Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil.; Research Centre in Limnology, Ichthyology and Aquaculture (NUPÉLIA), Centre of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil., Velho LFM; Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil.; Research Centre in Limnology, Ichthyology and Aquaculture (NUPÉLIA), Centre of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil.; UniCesumar/ICETI, Maringá, Brazil., Mormul RP; Department of Biology (DBI), Center of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil.; Research Centre in Limnology, Ichthyology and Aquaculture (NUPÉLIA), Centre of Biological Sciences (CCB), State University of Maringá (UEM), Maringá, Brazil.
المصدر: Nature ecology & evolution [Nat Ecol Evol] 2022 Sep; Vol. 6 (9), pp. 1279-1289. Date of Electronic Publication: 2022 Aug 04.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Springer Nature Country of Publication: England NLM ID: 101698577 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2397-334X (Electronic) Linking ISSN: 2397334X NLM ISO Abbreviation: Nat Ecol Evol Subsets: MEDLINE
أسماء مطبوعة: Original Publication: [London] : Springer Nature
مواضيع طبية MeSH: Ecosystem* , Wetlands*, Animals ; Aquatic Organisms ; Biodiversity ; Brazil ; Humans
مستخلص: Many studies have shown that biodiversity regulates multiple ecological functions that are needed to maintain the productivity of a variety of ecosystem types. What is unknown is how human activities may alter the 'multifunctionality' of ecosystems through both direct impacts on ecosystems and indirect effects mediated by the loss of multifaceted biodiversity. Using an extensive database of 72 lakes spanning four large Neotropical wetlands in Brazil, we demonstrate that species richness and functional diversity across multiple larger (fish and macrophytes) and smaller (microcrustaceans, rotifers, protists and phytoplankton) groups of aquatic organisms are positively associated with ecosystem multifunctionality. Whereas the positive association between smaller organisms and multifunctionality broke down with increasing human pressure, this positive relationship was maintained for larger organisms despite the increase in human pressure. Human pressure impacted multifunctionality both directly and indirectly through reducing species richness and functional diversity of multiple organismal groups. These findings provide further empirical evidence about the importance of aquatic biodiversity for maintaining wetland multifunctionality. Despite the key role of biodiversity, human pressure reduces the diversity of multiple groups of aquatic organisms, eroding their positive impacts on a suite of ecological functions that sustain wetlands.
(© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)
التعليقات: Comment in: Nat Ecol Evol. 2022 Sep;6(9):1250-1251. (PMID: 35927314)
References: Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015). (PMID: 10.1038/nature1432425832402)
Di Marco, M., Venter, O., Possingham, H. P. & Watson, J. E. M. Changes in human footprint drive changes in species extinctions risk. Nat. Commun. 9, 4621 (2018). (PMID: 30397204621847410.1038/s41467-018-07049-5)
Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012). (PMID: 2267828010.1038/nature11148)
Hooper, D. U. et al. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75, 3–35 (2005). (PMID: 10.1890/04-0922)
Lefcheck, J. S. et al. Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats. Nat. Commun. 6, 6936 (2015). (PMID: 2590711510.1038/ncomms7936)
Soliveres, S. et al. Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality. Nature 536, 456–459 (2016). (PMID: 2753303810.1038/nature19092)
Schuldt, A. et al. Biodiversity across trophic levels drive multifunctionality in highly diverse forests. Nat. Commun. 9, 2989 (2018). (PMID: 30065285606810410.1038/s41467-018-05421-z)
Delgado-Baquerizo, M. et al. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, 211–220 (2020). (PMID: 10.1038/s41559-019-1084-y)
Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012). (PMID: 2267828910.1038/nature11118)
Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18, 834–843 (2015). (PMID: 26096863474497610.1111/ele.12469)
Jing, X. et al. The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate. Nat. Commun. 6, 8159 (2015). (PMID: 2632890610.1038/ncomms9159)
Fanin, N. et al. Consistent effects of biodiversity loss on multifunctionality across contrasting ecosystems. Nat. Ecol. Evol. 2, 269–278 (2018). (PMID: 2925529910.1038/s41559-017-0415-0)
Hautier, Y. et al. Local loss and spatial homogenization of plant diversity reduce ecosystem multifunctionality. Nat. Ecol. Evol. 2, 50–56 (2018). (PMID: 2920392210.1038/s41559-017-0395-0)
Venter, O. et al. Global terrestrial human footprint maps for 1993 and 2009. Sci. Data 3, 160067 (2016). (PMID: 27552448512748610.1038/sdata.2016.67)
Allan, E. et al. Interannual variation in land-use intensity enhances grassland multidiversity. Proc. Natl Acad. Sci. USA 111, 308–313 (2014). (PMID: 2436885210.1073/pnas.1312213111)
Moi, D. A. et al. Regime shifts in a shallow lake over 12 years: consequences for taxonomic and functional diversities, and ecosystem multifunctionality. J. Anim. Ecol. 91, 551–565 (2022). (PMID: 3495482710.1111/1365-2656.13658)
Moi, D. A. et al. Multitrophic richness enhances ecosystem multifunctionality of tropical shallow lakes. Funct. Ecol. 35, 942–954 (2021). (PMID: 10.1111/1365-2435.13758)
Byrnes, J. E. K. et al. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods Ecol. Evol. 5, 111–124 (2014). (PMID: 10.1111/2041-210X.12143)
Li, F. et al. Human activitiesʼ fingerprint on multitrophic biodiversity and ecosystem functions across a major river catchment in China. Glob. Change Biol. 26, 6867–6879 (2020). (PMID: 10.1111/gcb.15357)
Enquist, B. J. et al. The megabiota are disproportionately importante for biosphere functioning. Nat. Commun. 11, 699 (2020). (PMID: 32019918700071310.1038/s41467-020-14369-y)
Eisenhauer, N. et al. A multitrophic perspective on biodiversity–ecosystem functioning research. Adv. Ecol. Res. 61, 1–54 (2019). (PMID: 31908360694450410.1016/bs.aecr.2019.06.001)
Agostinho, A. A., Thomaz, S. M. & Gomes, L. C. Threats for biodiversity in the floodplain of the Upper Paraná River: effects of hydrological regulation by dams. Ecohydrol. Hydrobiol. 4, 255–268 (2004).
Chiaravalloti, R. M., Homewood, K. & Erikson, K. Sustainability and land tenure: who owns the floodplain in the Pantanal, Brazil? Land Use Policy 64, 511–524 (2017). (PMID: 10.1016/j.landusepol.2017.03.005)
Pelicice, F. M. et al. Large-scale degradation of the Tocantins–Araguaia River Basin. Environ. Manag. 68, 445–452 (2021). (PMID: 10.1007/s00267-021-01513-7)
Malekmohammadi, B. & Jahanishakib, F. Vulnerability assessment of wetland landscape ecosystem services using driver-pressure-state-impact-response (DPSIR) model. Ecol. Indic. 82, 293–303 (2017). (PMID: 10.1016/j.ecolind.2017.06.060)
McIntyre, P. B. et al. Fish extinctions alter nutrient recycling in tropical freshwaters. Proc. Natl Acad. Sci. USA 104, 4461–4466 (2006). (PMID: 10.1073/pnas.0608148104)
Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014). (PMID: 2506120210.1126/science.1251817)
Tilman, D., Isbell, F. & Cowles, J. M. Biodiversity and ecosystem functioning. Annu. Rev. Ecol. Evol. Syst. 45, 471–493 (2014). (PMID: 10.1146/annurev-ecolsys-120213-091917)
Heino, J. et al. Lakes in the era of global change: moving beyond single-lake thinking in maintaining biodiversity and ecosystem services. Biol. Rev. 96, 89–106 (2020). (PMID: 3286944810.1111/brv.12647)
Bridgewater, P. & Kim, R. E. The Ramsar conservation on wetlands at 50. Nat. Ecol. Evol. 5, 268–270 (2020). (PMID: 10.1038/s41559-021-01392-5)
Romero, G. Q. et al. Pervasive decline of subtropical aquatic insects over 20 years driven by water transparency, non-native fish and stoichiometric imbalance. Biol. Lett. 17, 20210137 (2021). (PMID: 34102072818701010.1098/rsbl.2021.0137)
Lansac-Tôha, F. M. et al. Scale-depedent patterns of metacommunity structuring in aquatic organisms across floodplain systems. J. Biogeogr. 48, 872–885 (2021). (PMID: 10.1111/jbi.14044)
Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016). (PMID: 10.1111/2041-210X.12613)
Weiss, K. C. B. & Ray, C. A. Unifying functional trait approaches to understand the assemblage of ecological communities: synthesizing taxonomic divides. Ecography 42, 2012–2020 (2019). (PMID: 10.1111/ecog.04387)
Laliberté, E. & Legendre, R. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91, 299–305 (2010). (PMID: 2038021910.1890/08-2244.1)
Mackereth, F. J. H, Heron, J & Talling, J. F. Water Analysis: Some Revised Methods for Limnologists. Publication No. 36 (Freshwater Biological Association, 1978).
Golterman, H. L., Clymo, R. S. & Ohnstad, M. A. M. Methods for Physical and Chemical Analysis of Freshwaters (Blackwell Scientific Publications, 1978).
Bernhardt, E. S. et al. The metabolic regimes of flowing waters. Limnol. Oceanogr. 63, S99–S118 (2018). (PMID: 10.1002/lno.10726)
Sun, J. & Liu, D. Geometric models for calculating cell biovolume and surface area for phytoplankton. J. Plankt. Res. 25, 1331–1346 (2003). (PMID: 10.1093/plankt/fbg096)
Froese, R. & Pauly, D. FishBase (2018); www.fishbase.org.
Porter, K. G. & Feig, Y. S. The use of DAPI for identifying and counting aquatic microflora1. Limnol. Oceanogr. 25, 943–948 (1980). (PMID: 10.4319/lo.1980.25.5.0943)
Manning, P. et al. Redifining ecosystem multifunctionality. Nat. Ecol. Evol. 2, 427–436 (2018). (PMID: 2945335210.1038/s41559-017-0461-7)
Hijmans, R. J. & van Etten, J. raster: Geographic analysis and modeling with raster data. R version 2.0–12 https://rspatial.org/raster (2012).
World Urbanization Prospects: The 2020 Revision: Highlights (United Nations, 2020).
Junk, W. J. et al. Brazilian wetlands: their definition, delineation, and classification for research, sustainable management, and protection. Aquat. Conserv. Mar. Freshwater Ecosyst. 24, 5–22 (2013). (PMID: 10.1002/aqc.2386)
Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and nonlinear mixed effects models. R version 3.1.137 https://CRAN.Rproject.org/package=nlme (2018).
K. Barton, MuMIn: Model selection and model averaging based on information criteria (AICc and alike). R version 1–1 https://CRAN.R-project.org/package=MuMIn (2014).
Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer, 2002).
Schielzeth, H. Simple means to improve the interpretability ofregression coefficients. Meth. Ecol. Evol. 1, 103–113 (2010). (PMID: 10.1111/j.2041-210X.2010.00012.x)
Aiken, L. S. & West, S. G. Multiple Regression: Testing and Interpreting Interactions (Sage Publications, 1991).
Rosseel, Y. lavaan: an R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2015).
Grace, J. B. & Bollen, K. A. Representing general theoretical concepts in structural equation models: the role of composite variables. Environ. Ecol. Stat. 15, 191–213 (2008). (PMID: 10.1007/s10651-007-0047-7)
R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
تواريخ الأحداث: Date Created: 20220804 Date Completed: 20220908 Latest Revision: 20221114
رمز التحديث: 20231215
DOI: 10.1038/s41559-022-01827-7
PMID: 35927315
قاعدة البيانات: MEDLINE
الوصف
تدمد:2397-334X
DOI:10.1038/s41559-022-01827-7