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    Beneficial metabolic transformations and prebiotic potential of hemp bran and its alcalase hydrolysate, after colonic fermentation in a gut model

    Quality controls for the validation of MICODE protocolTo validate the MICODE experimental approach in the version of fecal batch of the human proximal colon, we chose to monitor and check some parameters as quality controls (QC) related to metabolites and microbes at the end of fermentations, and in comparison, to the baseline. QCs adopted were; (i) the Firmicutes/Bacteroidetes ratio (F/B), which is related to health and disease11, was maintained at a low level, confirming the capacity to simulate a healthy in vivo condition for 24 h. (ii) The presence of Archea (e.g., Methanobrevibacter smithii and Methanosphaera stadtmanae), which are pretty sensible to oxygen content12, was retained from the baseline to the end point in each vessel and repetition, indicating that the environmental conditions were strictly maintained. (iii) Good’s rarity index of alpha biodiversity remained similar during time of fermentation (p  > 0.05), indicating enough support to the growth of rare species. (iv) Observed OTUs richness index scored approximately 400 OTUs at the end point. (v) The paradigm of prebiotics was confirmed when the positive control (FOS) was applied on MICODE; high probiotic and SCFAs increases and limitation of enteropathogens. (vi) Each GC/MS analysis had quantified some stool-related compounds (urea, 1-propanol, and butylated hydroxy toluene), that ranged across the complete chromatogram and were adsorbed at the same retention times.Changes in bacterial alpha and beta diversitiesThe microbiota diversity indices were analyzed to study the impact of HPBA on microbial population, to assess population’s stability during fermentation, and to compare its microbiota to that of other bioreactors (Figure S1). The baseline of value was compared to the endpoints of fermentation of different treatments. It is undisputable that a part of the effect of reduction in richness (Observed OTUs) was derived by the passage from in vivo to in vitro condition, but the focus must be set on the different trend that other alpha diversity indices had. For example, abundance (Chao 1) for HBPA was significantly higher at the end of fermentation (p  0.05) and HPBA (p  0.05), while oppositely, FOS decreased in evenness (p  > 0.05) and raised in dominance (p  0.05). Among these, 31 variables were significant and their Log2 fold changes in respect to the baseline were compared by post-hoc test (Table 1). The 41 OTUs selected were those that recorded shifts after fermentation and that from literature are susceptible to the effect of prebiotic or fiber substrates. We have included even three OTUs of Archea relative to QC of the experiments (previously discussed).Table 1 Abundances (% ± S.D.) and changes in phylum taxa (Log2 F/C) after 24 h in vitro fecal batch culture fermentations from healthy donors and administrated with HBPA, HB, and FOS as the substrates, and also including a blank control.Full size tableThe first group of OTUs included beneficial or commensal bacteria that usually respond to prebiotics. In this group, three Bifidobacterium were picked showing increases on the substrates and reduction on the blank control. HB and HBPA fostered Bif. bifidum, but just the latter did it significantly, making this taxon grew up to the 3.30% of relative abundance (p  More

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    Green roofs and pollinators, useful green spots for some wild bee species (Hymenoptera: Anthophila), but not so much for hoverflies (Diptera: Syrphidae)

    Seto, K. C., Güneralp, B. & Hutyra, L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl. Acad. Sci. USA 109, 16083–16088. https://doi.org/10.1073/pnas.1211658109 (2012).Article 
    ADS 

    Google Scholar 
    Faeth, S. H., Bang, C. & Saari, S. Urban biodiversity: Patterns and mechanisms. Ann. N. Y. Acad. Sci. 1223, 69–81. https://doi.org/10.1111/j.1749-6632.2010.05925.x (2011).Article 
    ADS 

    Google Scholar 
    Elmqvist, T., Zipperer, W. & Güneralp, B. Urbanisation, habitat loss, biodiversity decline: Solution pathways to break the cycle. In Routledge Handbook of Urbanisation and Global Environmental Change (eds Seta, K. et al.) 139–151 (Routledge, 2016).
    Google Scholar 
    Dirzo, R. et al. Defaunation in the Anthropocene. Science 345, 401–406 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS One 12, e0185809. https://doi.org/10.1371/journal.pone.0185809 (2017).Article 
    CAS 

    Google Scholar 
    Wagner, D., Grames, E. M., Forister, M. L., Berenbaum, M. R. & Stopak, D. Insect decline in the Anthropocene: Death by a thousand cuts. Biological sciences 118, e2023989118. https://doi.org/10.1073/pnas.2023989118 (2021).Article 
    CAS 

    Google Scholar 
    Goulson, D., Nicholls, E., Botias, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347, 6229. https://doi.org/10.1126/science.1255957 (2015).Article 
    CAS 

    Google Scholar 
    Ollerton, J. (2021) Pollinators & pollination: nature and society. Pelagic publishing.IPBES (2016). The assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services on pollinators, pollination and food production. potts, S.G., Imperatriz-Fonseca, V.L and Ngo, H.T. (eds). Secretariat of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, Bonn, Germany. 552 pages.Mallinger, R. E. & Gratton, C. Species richness of wild bees, but not the use of managed honeybees, increases fruit set of a pollinator dependent crop. J. Appl. Ecol. 52, 323–330 (2015).Article 

    Google Scholar 
    Kremen, C., Williams, N. M. & Thorp, R. W. Crop pollination from native bees at risk from agricultural intensification. Proc. Natl. Acad. Sci. U.S.A. 99, 16812–16816 (2002).Article 
    ADS 
    CAS 

    Google Scholar 
    Winfree, R., Fox, J. W., Williams, N. M., Reilly, J. R. & Cariveau, D. P. Abundance of common species, not species richness, drives delivery of a real-world ecosystem service. Ecol. Lett. 18, 626–635 (2015).Article 

    Google Scholar 
    Soroye, P., Newbold, T. & Kerr, J. Climate change contributes to widespread declines among bumble bees across continents. Science 367, 685–688 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Matteson, K. C., Ascher, J. S. & Langellotto, G. A. Bee richness and abundance in New York City urban gardens. Ann. Entomol. Soc. Am. 101(1), 140–150. https://doi.org/10.1603/0013-8746(2008)101[140:BRAAIN]2.0.CO;2 (2008).Article 

    Google Scholar 
    Carré, G. et al. Landscape context and habitat type as drivers of bee diversity in European annual crops. Agr. Ecosyst. Environ. 133(1–2), 40–47. https://doi.org/10.1016/j.agee.2009.05.001 (2009).Article 

    Google Scholar 
    Goulson, D., Lye, G. C. & Darvill, B. Decline and conservation of bumble bees. Ann. Rev. Entomol. 53, 191–208. https://doi.org/10.1146/annurev.ento.53.103106.093454 (2008).Article 
    CAS 

    Google Scholar 
    Bates, A. J. et al. Changing bee and hoverfly pollinator assemblages along an urban-rural gradient. PLoS One 6(8), e23459. https://doi.org/10.1371/journal.pone.0023459 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Deguines, N., Julliard, R., De Flores, M. & Fontaine, C. Functional homogenization of flower visitor communities with urbanisation. Ecol. Evol. 6(7), 1967–1976. https://doi.org/10.1002/ece3.2009 (2016).Article 

    Google Scholar 
    Larsson, M. Higher pollinator effectiveness by specialist than generalist flower-visitors of unspecialized Knautia arvensis (Dipsacaceae). Oecologia 146(3), 394–403. https://doi.org/10.1007/s00442-005-0217-y (2005).Article 
    ADS 

    Google Scholar 
    Pataki, D. E. et al. Coupling biogeochemical cycles in urban environments: Ecosystem services, green solutions, and misconceptions. Front. Ecol. Environ. 9, 27–36. https://doi.org/10.1890/090220 (2011).Article 

    Google Scholar 
    Mentens, J., Raes, D. & Hermy, M. Green roofs as a tool for solving rainwater runoff problems in the urbanized 21st century?. Landscape Urban Plann. 77, 217–226. https://doi.org/10.1016/j.landurbplan.2005.02.010 (2006).Article 

    Google Scholar 
    Oberndorfer, E. et al. Green roofs as urban ecosystems: Ecological structures, functions and services. Bioscience 57, 823–834. https://doi.org/10.1641/B571005 (2007).Article 

    Google Scholar 
    Braaker, S., Ghazoul, J., Obrist, M. K. & Moretti, M. Habitat connectivity shapes urban arthropod communities: The key role of green roofs. Ecology 95, 1010–1021. https://doi.org/10.1890/13-0705.1 (2014).Article 
    CAS 

    Google Scholar 
    Colla, S. R., Willis, E. & Packer, I. Can green roofs provide habitat for urban bees (Hymenoptera: Apidae)?. Cities and the Environment 2(1), 1–12 (2009).Article 

    Google Scholar 
    Tonietto, R., Fant, J., Ascher, J., Ellis, K. & Larkin, D. A comparison of bee communities of Chicago green roofs, parks and prairies. Landsc. Urban Plan. 103, 102–108 (2011).Article 

    Google Scholar 
    Ksiazek, K., Fant, J. & Skogen, K. An asssement of pollen limitation on Chicago green roofs. Landsc. Urban Plan. 107, 401–408 (2012).Article 

    Google Scholar 
    MacIvor, J. S. Building height matters: Nesting activity of bees and wasps on vegetated roofs. Israel J. Ecol. Evol. 62, 88–96. https://doi.org/10.1080/15659801.2015.1052635 (2015).Article 

    Google Scholar 
    Kratschmer, S., Kriechbaum, M. & Pachinger, B. Buzzing on top: Linking wild bee diversity, abundance and traits with green roof qualities. Urban Ecosyst. 21, 429–441 (2018).Article 

    Google Scholar 
    MacIvor, J. S., Ruttan, R. & Salehi, B. Exotics on exotics: Pollen analysis of urban bees visiting Sedum on a green roof. Urban Ecosyst. 18, 419–430 (2014).Article 

    Google Scholar 
    Matteson, K. C. & Langellotto, G. A. Determinates of inner city butterfly and bee species richness. Urban Ecosyst. 13, 333–347. https://doi.org/10.1007/s11252-010-0122-y (2010).Article 

    Google Scholar 
    Geslin, B., Gauzens, B., Thébault, E. & Dajoz, I. Plant pollinator networks along a gradient of urbanisation. PLoS One 8, e63421. https://doi.org/10.1371/journal.pone.0063421 (2013).Article 
    ADS 

    Google Scholar 
    Baldock, K.C.R, et al. (2015) Where is the UK’s pollinator biodiversity? The importance of urban areas for flower-visiting insects. Proc. R. Soc. B. https://doi.org/10.1098/rspb.2014.2849Theodorou, P. et al. Urban fragmentation leads to lower floral diversity, with knock-on impacts on bee biodiversity. Sci. Rep. 10, 21756. https://doi.org/10.1038/s41598-020-78736-x (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Lowenstein, D.M., Matteson, K.C., Xiao, I., Silva, A.M. and Minor, E.S (2014) Humans, bees, and pollination services in the city: The case of Chicago, IL (USA). Biodiversity Conservation 1–18. https://doi.org/10.1007/s10531-014-0752-0Winfree, R., Bartomeus, I. & Cariveau, D. Native pollinators in anthropogenic habitats. Annu. Rev. Ecol. Evol. Syst. 42, 1–22 (2011).Article 

    Google Scholar 
    Cariveau, D. P. & Winfree, R. Causes of variation in wild bee responses to anthropogenic drivers. Curr. Opin. Insect. Sci. 10, 104–109. https://doi.org/10.1016/j.cois.2015.05.004 (2015).Article 

    Google Scholar 
    Baldock, K. C. R. et al. A systems approach reveals urban pollinator hotspots and conservation opportunities. Nat. Ecol. Evol. 3, 363–373. https://doi.org/10.1038/s41559-018-0769-y (2019).Article 

    Google Scholar 
    Li, W. C. & Yeung, K. K. A. A comprehensive study of green roof performance from environmental perspective. Int. J. Sustain. Built Environ. 3, 127–134 (2021).Article 

    Google Scholar 
    Turner, M., Baker, W. L., Peterson, C. J. & Peet, R. K. Factors influencing succession: Lessons from large, infrequent natural disturbances. Ecosystems 1, 511–523. https://doi.org/10.1007/s100219900047 (1998).Article 

    Google Scholar 
    Molineux, C. J., Connop, S. P. & Gange, A. C. Manipulating soil microbial communities in extensive green roof substrates. Sci. Total Environ. 493, 632–638. https://doi.org/10.1016/j.scitotenv.2014.06.045 (2014).Article 
    ADS 
    CAS 

    Google Scholar 
    Macivor, S. & Ksiazek, K. Invertebrates on green roofs. Ecol. Stud. Anal. Synthes. 223, 333–355. https://doi.org/10.1007/978-3-319-14983-7_14 (2015).Article 

    Google Scholar 
    Madre, F., Vergnes, A., Machon, N. & Clergeau, P. A comparison of 3 types of green roof as habitats for arthropods. Ecol. Eng. 57, 109–117. https://doi.org/10.1016/j.ecoleng.2013.04.029 (2013).Article 

    Google Scholar 
    Lee, L. H. & Lin, J. C. Green roof performance towards good habitat for butterflies in the compact city. Int. J. Biol. 7, 103. https://doi.org/10.5539/ijb.v7n2p103 (2015).Article 
    CAS 

    Google Scholar 
    Preston, F. W. The canonical distribution of commonness and rarity: Part I. Ecology 43(2), 185–215. https://doi.org/10.2307/1931976 (1962).Article 

    Google Scholar 
    Orford, K. A., Murray, P. J., Vaughan, I. P. & Memmott, J. Modest enhancements to conventional grassland diversity improve the provision of pollination services. J. Appl. Ecol. 53, 906–915. https://doi.org/10.1111/1365-2664.12608 (2016).Article 

    Google Scholar 
    Brenneisen, S. The Natural Roof (NADA): Research Project Report on the Use of Extensive Green Roofs by Wild Bees (University of Wädenswil, 2005).
    Google Scholar 
    Jacobs, J., Berg, M., Beenaerts, N. & Artois, T. Biodiversity of Collembola on green roofs: A case study of three cities in Belgium. Ecol. Eng. 177, 106572. https://doi.org/10.1016/j.ecoleng.2022.106572 (2022).Article 

    Google Scholar 
    McKinney, M.L., Sisco, N.D. (2018) Systematic variation in roof spontaneous vegetation: residential “low rise” versus commercial “high rise” buildings. Urban Nature SI, 73–88.Rotheray, G.E., & Gilbert, S.F. (2011) The natural history of hoverflies. Tresaith, UK: Forrest TextBenvenuti, S. Wildflower green roofs for urban landscaping, ecological sustainability and biodiversity. Landsc. Urban Plan. 124, 151–161. https://doi.org/10.1016/j.landurbplan.2014.01.004 (2014).Article 

    Google Scholar 
    Schneider, F. Beitrag zur Kenntnis der Generationsverhaltnisse und Diapause rauberischer Schwebfliegen (Syrphldae, Dipt.). Mittl. Schweiz Ent Ges 21, 249–285 (1948).
    Google Scholar 
    Rader, R., Edwards, W., Westcott, D. A., Cunningham, S. A. & Howlett, B. G. Pollen transport differs among bees and flies in a human-modified landscape. Divers. Distrib. 17, 519–529. https://doi.org/10.1111/j.1472-4642.2011.00757.x (2011).Article 

    Google Scholar 
    Burgio, G. & Sommaggio, D. Syrphids as landscape bioindicators in Italian agroecosystems. Agr. Ecosyst. Environ. 120, 416–422 (2007).Article 

    Google Scholar 
    Doyle, T. et al. Pollination by hoverflies in the Anthropocene. Proc. R. Soc. B 287, 20200508. https://doi.org/10.1098/rspb.2020.0508 (2020).Article 

    Google Scholar 
    Persson, A. S., Ekroos, J., Olssona, P. & Smith, H. G. Wild bees and hoverflies respond differently to urbanisation, human population density and urban form. Landsc. Urban Plann. 204, 103901. https://doi.org/10.1016/j.landurbplan.2020.103901 (2020).Article 

    Google Scholar 
    Verboven, H., Uyttenbroeck, R., Brys, R. & Hermy, M. Different responses of bees and hoverflies to land use in an urban–rural gradient show the importance of the nature of the rural land use. Landsc. Urban Plan. 126, 31–41. https://doi.org/10.1016/j.landurbplan.2014.02.017 (2014).Article 

    Google Scholar 
    Schönrogge, K. et al. Host propagation permits extreme local adaptation in a social parasite of ants. Ecol. Lett. 9, 1032–1040 (2006).Article 

    Google Scholar 
    Schweiger, O. et al. Functional richness of local hoverfly communities (Diptera, Syrphidae) in response to land use across temperate Europe. Oikos 116, 461–472 (2007).Article 

    Google Scholar 
    KMI: Koninklijk Meteorologisch Instituut (2022) Analyse van het jaar 2020 en 2021. Available from https://www.meteobelgie.be/klimatologie/waarnemingen-en-analyses/jaar-2020/2274-jaa-2020 (2020) https://www.meteobelgie.be/klimatologie/waarnemingen-en-analyses/jaar-2021/2291-analyse-van-het-jaar-2021 (2021). Accessed on 12/05/2022.Shrestha, M. et al. Fluorescent pan traps affect the capture rate of insect orders in different ways. Insects 10(2), 40. https://doi.org/10.3390/insects10020040 (2019).Article 

    Google Scholar 
    Cooper, R., & Whitmore, R.C. (1990) Arthropod sampling methods in ornithology, Avian Foraging: theory, methodology, and applications. Studies in Avian Biology 13, Cooper Ornithological Society, California.Oberprieler, S. K., Andersen, A. & Braby, M. F. Invertebrate by-catch from vertebrate pitfall rraps can be useful for documenting patterns of invertebrate diversity. J. Insect. Conserv. 23(3), 547–554. https://doi.org/10.1007/s10841-019-00143-z (2019).Article 

    Google Scholar 
    Skvarla, M. J., Larson, J. L. & Dowling, A. P. G. Pitfalls and preservatives: A review. J. Entomol. Soc. Ontario 145, 15–43 (2014).
    Google Scholar 
    Michez, D., Rasmont, P., Terzo, M. and Vereecken, N.J. (2019) Bees of Europe. Hymenoptera of Europe 1. N.A.P Editions.Williams, P.H., et al. (2012): Unveiling cryptic species of the bumblebee subgenus Bombus s. str. worldwide with COI barcodes (Hymenoptera: Apidae). Syste. Biodiversity. https://doi.org/10.1080/14772000.2012.66457Falck, S., & Lewington, R (2020) Bijen veldgids voor Nederland en Vlaanderen. Tirion.Koster, A. (2022) De Nederlandse wilde bijen en hun planten. http://www.denederlandsebijen.nl/. Accessed on 21/4/2022.Speight, M.C.D. & Sarthou, J.P. (2013) StN keys for the identification of adult European Syrphidae (Diptera) 2013/Clés StN pour la détermination des adultes des Syrphidae Européens (Diptères) 2013. Syrph the Net, the database of European Syrphidae, Vol. 74, 133pp, Syrph the Net publications, Dublin.Roback, P., Legler, J. (2021) Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R. Taylor & Francis Group, LLC.R Core Team (2020) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.Oksanen, J., et al. (2014) Vegan: community ecology package. R Package 280.Bengtsson, H. (2017). matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors). R Package Version 0.52.2.Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01.Wickham, H., François, R., Henry, L. and Müller, K. (2022). dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr.Venables, W.N., & Ripley, B.D. (2002) Modern Applied Statistics with S, 4th ed. Springer, New York. ISBN 0–387–95457–0. https://www.stats.ox.ac.uk/pub/MASS4/.Ricotta, C. & Moretti, M. CWM and Rao’s quadratic diversity: A unified framework for functional ecology. Oecologia 167(1), 181–188 (2011).Article 
    ADS 

    Google Scholar 
    Leclère, D. et al. Bending the curve of terrestrial biodiversity needs an integrated strategy. Nature 585(7826), 551–556. https://doi.org/10.1038/s41586-020-2705-y (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Drossart, M., et al. (2019) Belgian red list of Bees. Belgian Science Policy (BRAIN-be – (Belgian Research Action through Interdisciplinary Networks). Mons: Presse universitaire de l’Université de Mons.Fahrig, L. Why do several small patches hold more species than few large patches?. Glob. Ecol. Biogeogr. 29, 615–628. https://doi.org/10.1111/geb.13059 (2020).Article 

    Google Scholar 
    Ayers, A. C. & Rehan, S. M. Supporting bees in cities: how bees are influenced by local and landscape features. Insects 12, 128. https://doi.org/10.3390/insects12020128 (2021).Article 

    Google Scholar 
    Domínguez, M. V. S., González, E., Fabián, D., Salvo, A. & Fenoglio, M. S. Arthropod diversity and ecological processes on green roofs in a semi-rural area of Argentina: Similarity to neighbor ground habitats and landscape effects. Landscape and Urban Planning 199, (2020).Castagneyrol, B. & Jactel, H. Unravelling plant- animal diversity relationships: A meta-regression analysis. Ecology 93(9), 2115–2124 (2012).Article 

    Google Scholar 
    Harrison, T., Gibbs, J. & Winfree, R. Phylogenetic homogenization of bee communities across ecoregions. Glob. Ecol. Biogeogr. 27, 1457–1466. https://doi.org/10.1111/geb.12822 (2018).Article 

    Google Scholar 
    Wenzel, A., Grass, I., Belavadi, V. V. & Tscharntke, T. How urbanisation is driving pollinator diversity and pollination, a systematic review. Biol. Conserv. 241, 108321. https://doi.org/10.1016/j.biocon.2019.108321 (2020).Article 

    Google Scholar 
    Martins, K. T., Gonzalez, A. & Lechowicz, M. J. Patterns of pollinator turnover and increasing diversity associated with urban habitats. Urban Ecosyst. 20, 1359–1371 (2017).Article 

    Google Scholar 
    Bucholz, S. & Egerer, M. Functional ecology of wild bees in cities: Towards a better understanding of trait-urbanisation relationships. Biodiver. Conserv. 29, 2779–2801 (2020).Article 

    Google Scholar 
    Hernandez, J. L., Frankie, G. W. & Thorp, R. W. Ecology of urban bees : A review of current knowledge and directions for future study. Cities Environ. 2, 1–15 (2009).Article 

    Google Scholar 
    Cane, J. H. Bees, pollination, and the challenges of sprawl. In Nature in fragments: The legacy of sprawl (eds Johnson, E. A. & Klemens, M. W.) 109–124 (Columbia University Press, 2005).Chapter 

    Google Scholar 
    Koch, K. Wilde bijensoorten in een stedelijke omgeving: Stad Antwerpen. Antenna 4, 8–12 (2014).
    Google Scholar 
    Soper, J. & Beggs, J. Assessing the impact of an introduced bee, Anthidium manicatum, on pollinator communities in New Zealand. NZ J. Bot. 51(3), 213–228. https://doi.org/10.1080/0028825X.2013.793202 (2013).Article 

    Google Scholar 
    Bennet, D.G., Kelly, D., & Clemens, J. (2018). Food plants and foraging distances for the native bee Lasioglossum sordidum in Christchurch Botanic Gardens. New Zealand J. Ecol. 42(1), 40–47. https://doi.org/10.20417/nzjecol.42.1Vanormelingen, P., Remer, M., & D’Haeseleer, J. (2021) Wilde bijen en bebouwing: meer verliezers dan winnaars? Themanummer bijen in de stad en dorp, Hymenovaria, maart 2021.Rader, R. et al. Alternative pollinator taxa are equally efficient but not as effective as the honey-bee in a mass flowering crop. J. Appl. Ecol. 46(5), 1080–1087. https://doi.org/10.1111/j.1365-2664.2009.01700.x (2009).Article 

    Google Scholar 
    Garantonakis, N. et al. Comparing the pollination services of honey bees and wild bees in a watermelon field. Sci. Hortic. 204, 138–144. https://doi.org/10.1016/j.scienta.2016.04.006 (2016).Article 

    Google Scholar 
    Foldesi, R., Howlett, B. G., Grass, I. & Batary, P. Larger pollinators deposit more pollen on stigmas across multiple plant species – A meta-analysis. J. Appl. Ecol. 58(4), 699–707. https://doi.org/10.1111/1365-2664.13798 (2021).Article 

    Google Scholar 
    Howlett, et al. (2011). Can insect body pollen counts be used to estimate pollen deposition on pak choi stigmas? New Zealand Plant Protection 64, 25–31. https://doi.org/10.30843/nzpp.2011.64.5951Nelson, W., Barry Donovan, L. E. & Howlett, B. Lasioglossum bees – the forgotten pollinators. J. Apic. Res. https://doi.org/10.1080/00218839.2022.2028966 (2022).Article 

    Google Scholar 
    Passaseo, A., Pétremand, G., Rochefort, S. & Castella, E. Pollinators emerging from extensive green roofs: Wild bees (Hymenoptera: Antophila) and hoverflies (Diptera: Syrphidae) in Geneva (Switzerland). Urban Ecosyst. 23, 1079–1086. https://doi.org/10.1007/s11252-020-00973-9 (2020).Article 

    Google Scholar 
    Odanaka, K. A. & Rehan, S. M. Impact indicators: Effects of land use management on functional trait and phylogenetic diversity of wild bees. Agric. Ecosyst. Environ. 286, 106663 (2019).Article 

    Google Scholar 
    Wilson, C. J. & Jamieson, M. A. The effects of urbanisation on bee communities depends on floral resource availability and bee functional traits. PLoS ONE 14(12), e0225852. https://doi.org/10.1371/journal.pone.0225852 (2019).Article 
    CAS 

    Google Scholar 
    Osborne, J. L. et al. Quantifying and comparing bumblebee nest densities in gardens and countryside habitats. J. Appl. Ecol. 45, 784–792. https://doi.org/10.1111/j.1365-2664.2007.01359.x (2007).Article 

    Google Scholar 
    Glaum, P., Simao, M. C., Vaidya, C., Fitch, G. & Lulinao, B. Big city Bombus: Using natural history and land-use history to find significant environmental drivers in bumble-bee declines in urban development. R Soc Open Sci. 4, 170156. https://doi.org/10.1098/rsos.170156 (2017) (PMID: 28573023).Article 
    ADS 

    Google Scholar 
    Rasmont, P. et al. Climatic risk and distribution atlas of European bumblebees. Biorisk 10, 1–246 (2015).Article 

    Google Scholar 
    Roger, N. et al. Impact of pollen resources drift on common bumblebees in NW Europe. Glob. Change Biol. 23, 68–76 (2017).Article 
    ADS 

    Google Scholar 
    Frankie, G. W. et al. Ecological patterns of bees and their host ornamental flowers in two northern California cities. J. Kansas Entomol. Soc. 78, 227–246 (2005).Article 

    Google Scholar 
    Lerman, S. B. & Milam, J. Bee fauna and floral abundance within lawn-dominated suburban yards in Springfield, MA. Ann. Entomol. Soc. Am. 109, 713–723 (2016).Article 
    CAS 

    Google Scholar 
    Braaker, S., Obrist, M. K., Ghazoul, J. & Moretti, M. Habitat connectivity and local conditions shape taxonomic and functional diversity of arthropods on green roofs. J. Anim. Ecol. 86, 521–531. https://doi.org/10.1111/1365-2656.12648 (2017).Article 

    Google Scholar 
    Passaseo, A., Rochefort, S., Pétremand, G., & Castella, E. (2021) Pollinators on green roofs: Diversity and trait analysis of wild bees (Hymenoptera: Anthophila) and Hoverflies (Diptera: Syrphidae) in an urban area (Geneva, Switzerland). Cities and the Environment (CATE) https://doi.org/10.15365/cate.2021.140201Hennig, E. & Ghazoul, J. Pollinating animals in the urban environment. Urban Ecosyst. 15, 149–166. https://doi.org/10.1007/s11252-011-0202-7 (2012).Article 

    Google Scholar 
    Mecke R. (1996) Die fauna begrünter dächer: Ökologische untersuchung verschiedener dachflächer im Hamburger stadtgebiet. University of Hamburg, Diploma dissertation.Bevk, D. The diversity of pollinators on green roofs. Acta Entomol. Slovenica 29(1), 5–14 (2021).
    Google Scholar 
    Speight, M.C.D. (2011) Species accounts of European Syrphidae (Diptera), Glasgow 2011. Syrph the Net, the database of European Syrphidae, vol. 65, 285 pp., Syrph the Net publications, Dublin.Wotton, K. R. et al. Mass seasonal migrations of hoverflies provide extensive pollination and crop protection services. Curr. Biol. 29, 2167–2173 (2019).Article 
    CAS 

    Google Scholar 
    Boyer, K. J., Fragoso, F. P., Mabin, M. E. D. & Brunet, J. Netting and pan traps fail to identify the pollinator guild of an agricultural crop. Nat. Res. Sci. Rep. 10, 13819. https://doi.org/10.1038/s41598-020-70518-9 (2020).Article 
    CAS 

    Google Scholar  More

  • in

    A comparative analysis of urban forests for storm-water management

    Rahman, M. A. et al. Comparing the infiltration potentials of soils beneath the canopies of two contrasting urban tree species. Urban For. Urban Green. 38, 22–32. https://doi.org/10.1016/j.ufug.2018.11.002 (2019).Article 

    Google Scholar 
    Zölch, T., Henze, L., Keilholz, P. & Pauleit, S. Regulating urban surface runoff through nature-based solutions – An assessment at the micro-scale. Environ. Res. 157, 135–144. https://doi.org/10.1016/j.envres.2017.05.023 (2017).Article 
    CAS 

    Google Scholar 
    Barron, O. V., Barr, A. D. & Donn, M. J. Effect of urbanisation on the water balance of a catchment with shallow groundwater. J. Hydrol. 485, 162–176. https://doi.org/10.1016/j.jhydrol.2012.04.027 (2013).Article 
    ADS 

    Google Scholar 
    Rosenzweig, B. R. et al. The value of urban flood modeling. Earth’s Future 9, e2020EF001739. https://doi.org/10.1029/2020EF001739 (2021).Article 
    ADS 

    Google Scholar 
    Pauleit, S., Fryd, O., Backhaus, A. & Jensen, M. B. In Encyclopedia of Sustainability Science and Technology (ed. Meyers, R. A.) 1–29 (Springer, 2020).
    Google Scholar 
    Rahman, M. A. et al. Traits of trees for cooling urban heat islands: A meta-analysis. Build. Environ. 170, 106606. https://doi.org/10.1016/j.buildenv.2019.106606 (2020).Article 

    Google Scholar 
    Ziter, C. D., Pedersen, E. J., Kucharik, C. J. & Turner, M. G. Scale-dependent interactions between tree canopy cover and impervious surfaces reduce daytime urban heat during summer. Proc. Natl. Acad. Sci. USA 116, 7575–7580. https://doi.org/10.1073/pnas.1817561116 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Waldrop, M. M. News feature: The quest for the sustainable city. Proc. Natl. Acad. Sci. 116, 17134–17138. https://doi.org/10.1073/pnas.1912802116 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Cleugh, H. A., Bui, E., Simon, D., Xu, J. & Mitchell, V. G. The Impact of Suburban Design on Water Use and Microclimate (2005).Chan, F. K. S. et al. “Sponge City” in China—A breakthrough of planning and flood risk management in the urban context. Land Use Policy 76, 772–778. https://doi.org/10.1016/j.landusepol.2018.03.005 (2018).Article 

    Google Scholar 
    Morgan, R. P. C. Soil Erosion and Conservation (Wiley, 2005).
    Google Scholar 
    Xu, C. et al. Surface runoff in urban areas: The role of residential cover and urban growth form. J. Clean. Prod. 262, 121421. https://doi.org/10.1016/j.jclepro.2020.121421 (2020).Article 

    Google Scholar 
    Ostoić, S. K. & van den Bosch, C. C. K. Exploring global scientific discourses on urban forestry. Urban For. Urban Green. 14, 129–138. https://doi.org/10.1016/j.ufug.2015.01.001 (2015).Article 

    Google Scholar 
    Rahman, M. A. et al. Tree cooling effects and human thermal comfort under contrasting species and sites. Agric. For. Meteorol. 287, 107947. https://doi.org/10.1016/j.agrformet.2020.107947 (2020).Article 
    ADS 

    Google Scholar 
    Rötzer, T., Rahman, M. A., Moser-Reischl, A., Pauleit, S. & Pretzsch, H. Process based simulation of tree growth and ecosystem services of urban trees under present and future climate conditions. Sci. Total Environ. 676, 651–664. https://doi.org/10.1016/j.scitotenv.2019.04.235 (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Grote, R. et al. Functional traits of urban trees: Air pollution mitigation potential. Front. Ecol. Environ. 14, 543–550. https://doi.org/10.1002/fee.1426 (2016).Article 

    Google Scholar 
    Pace, R. et al. A single tree model to consistently simulate cooling, shading, and pollution uptake of urban trees. Int. J. Biometeorol. 65, 277–289. https://doi.org/10.1007/s00484-020-02030-8 (2021).Article 
    ADS 

    Google Scholar 
    Kuehler, E., Hathaway, J. & Tirpak, A. Quantifying the benefits of urban forest systems as a component of the green infrastructure stormwater treatment network. Ecohydrology https://doi.org/10.1002/eco.1813 (2017).Article 

    Google Scholar 
    Rahman, M. A., Moser, A., Gold, A., Rötzer, T. & Pauleit, S. Vertical air temperature gradients under the shade of two contrasting urban tree species during different types of summer days. Sci. Total Environ. 633, 100–111. https://doi.org/10.1016/j.scitotenv.2018.03.168 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Rahman, M. A., Smith, J. G., Stringer, P. & Ennos, A. R. Effect of rooting conditions on the growth and cooling ability of Pyrus calleryana. Urban For. Urban Green. 10, 185–192. https://doi.org/10.1016/j.ufug.2011.05.003 (2011).Article 

    Google Scholar 
    Schellekens, J., Scatena, F. N., Bruijnzeel, L. A. & Wickel, A. J. Modelling rainfall interception by a lowland tropical rain forest in northeastern Puerto Rico. J. Hydrol. 225, 168–184. https://doi.org/10.1016/S0022-1694(99)00157-2 (1999).Article 
    ADS 

    Google Scholar 
    Guevara-Escobar, A., González-Sosa, E., Véliz-Chávez, C., Ventura-Ramos, E. & Ramos-Salinas, M. Rainfall interception and distribution patterns of gross precipitation around an isolated Ficus benjamina tree in an urban area. J. Hydrol. 333, 532–541. https://doi.org/10.1016/j.jhydrol.2006.09.017 (2007).Article 
    ADS 

    Google Scholar 
    Xiao, Q. F. & McPherson, E. G. Surface water storage capacity of twenty tree species in Davis, California. J. Environ. Qual. 45, 188–198. https://doi.org/10.2134/jeq2015.02.0092 (2016).Article 
    CAS 

    Google Scholar 
    Xiao, Q. F., McPherson, E. G., Ustin, S. L. & Grismer, M. E. A new approach to modeling tree rainfall interception. J. Geophys. Res. Atmos. 105, 29173–29188. https://doi.org/10.1029/2000jd900343 (2000).Article 
    ADS 

    Google Scholar 
    Carlyle-Moses, D. E. & Gash, J. H. C. In Forest Hydrology and Biogeochemistry: Synthesis of Past Research and Future Directions (eds Levia, D. F. et al.) 407–423 (Springer, 2011).Chapter 

    Google Scholar 
    Hirano, T. et al. The difference in the short-term runoff characteristic between the coniferous catchment and the deciduous catchment: The effects of storm size on storm generation processes of small forested catchment. J. Jpn. Soc. Hydrol. Water Resour. 22, 24–39. https://doi.org/10.3178/jjshwr.22.24 (2009).Article 

    Google Scholar 
    Chandler, K. R. & Chappell, N. A. Influence of individual oak (Quercus robur) trees on saturated hydraulic conductivity. For. Ecol. Manage. 256, 1222–1229. https://doi.org/10.1016/j.foreco.2008.06.033 (2008).Article 

    Google Scholar 
    Stewart, I. D. A systematic review and scientific critique of methodology in modern urban heat island literature. Int. J. Climatol. 31, 200–217. https://doi.org/10.1002/joc.2141 (2011).Article 

    Google Scholar 
    Beck, H. E. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5, 180214. https://doi.org/10.1038/sdata.2018.214 (2018).Article 

    Google Scholar 
    Moreno-de las Heras, M., Nicolau, J. M., Merino-Martín, L. & Wilcox, B. P. Plot-scale effects on runoff and erosion along a slope degradation gradient. Water Resour. Res. 46, W04503. https://doi.org/10.1029/2009WR007875 (2010).Article 
    ADS 

    Google Scholar 
    Wu, L., Peng, M., Qiao, S. & Ma, X.-Y. Effects of rainfall intensity and slope gradient on runoff and sediment yield characteristics of bare loess soil. Environ. Sci. Pollut. Res. 25, 3480–3487. https://doi.org/10.1007/s11356-017-0713-8 (2018).Article 

    Google Scholar 
    Rutter, A. J., Kershaw, K. A., Robins, P. C. & Morton, A. J. A predictive model of rainfall interception in forests, 1. Derivation of the model from observations in a plantation of Corsican pine. Agric. Meteorol. 9, 367–384. https://doi.org/10.1016/0002-1571(71)90034-3 (1971).Article 

    Google Scholar 
    Gash, J. H. C. An analytical model of rainfall interception by forests. Q. J. R. Meteorol. Soc. 105, 43–55. https://doi.org/10.1002/qj.49710544304 (1979).Article 
    ADS 

    Google Scholar 
    Véliz-Chávez, C., Mastachi-Loza, C. A., Gonzalez-Sosa, E., Becerril-Pia, R. & Ramos-Salinas, N. M. Canopy storage implications on interception loss modeling. Am. J. Plant Sci. 05, 3032–3048. https://doi.org/10.4236/ajps.2014.520320 (2014).Article 

    Google Scholar 
    Fan, J., Oestergaard, K. T., Guyot, A. & Lockington, D. A. Measuring and modeling rainfall interception losses by a native Banksia woodland and an exotic pine plantation in subtropical coastal Australia. J. Hydrol. 515, 156–165. https://doi.org/10.1016/j.jhydrol.2014.04.066 (2014).Article 
    ADS 

    Google Scholar 
    Ghimire, C. P., Bruijnzeel, L. A., Lubczynski, M. W. & Bonell, M. Rainfall interception by natural and planted forests in the Middle Mountains of Central Nepal. J. Hydrol. 475, 270–280. https://doi.org/10.1016/j.jhydrol.2012.09.051 (2012).Article 
    ADS 

    Google Scholar 
    Pereira, F. L. et al. Modelling interception loss from evergreen oak Mediterranean savannas: Application of a tree-based modelling approach. Agric. For. Meteorol. 149, 680–688. https://doi.org/10.1016/j.agrformet.2008.10.014 (2009).Article 
    ADS 

    Google Scholar 
    Pypker, T. G., Bond, B. J., Link, T. E., Marks, D. & Unsworth, M. H. The importance of canopy structure in controlling the interception loss of rainfall: Examples from a young and an old-growth Douglas-fir forest. Agric. For. Meteorol. 130, 113–129. https://doi.org/10.1016/j.agrformet.2005.03.003 (2005).Article 
    ADS 

    Google Scholar 
    Ringgaard, R., Herbst, M. & Friborg, T. Partitioning forest evapotranspiration: Interception evaporation and the impact of canopy structure, local and regional advection. J. Hydrol. 517, 677–690. https://doi.org/10.1016/j.jhydrol.2014.06.007 (2014).Article 
    ADS 

    Google Scholar 
    Price, A. G. & Carlyle-Moses, D. E. Measurement and modelling of growing-season canopy water fluxes in a mature mixed deciduous forest stand, southern Ontario, Canada. Agric. For. Meteorol. 119, 69–85. https://doi.org/10.1016/S0168-1923(03)00117-5 (2003).Article 
    ADS 

    Google Scholar 
    Fathizadeh, O., Hosseini, S. M., Zimmermann, A., Keim, R. F. & Darvishi Boloorani, A. Estimating linkages between forest structural variables and rainfall interception parameters in semi-arid deciduous oak forest stands. Sci. Total Environ. 601–602, 1824–1837. https://doi.org/10.1016/j.scitotenv.2017.05.233 (2017).Article 
    ADS 
    CAS 

    Google Scholar 
    Livesley, S. J., Baudinette, B. & Glover, D. Rainfall interception and stem flow by eucalypt street trees—the impacts of canopy density and bark type. Urban For. Urban Green. 13, 192–197. https://doi.org/10.1016/j.ufug.2013.09.001 (2014).Article 

    Google Scholar 
    Xiao, Q. & McPherson, E. G. Rainfall interception by Santa Monica’s municipal urban forest. Urban Ecosyst. 6, 291–302. https://doi.org/10.1023/B:UECO.0000004828.05143.67 (2002).Article 

    Google Scholar 
    Rohatgi, A. WebPlotDigitizer (4.4), 2020).Team, R. C. (R Foundation for Statistical Computing, 2020).García-Palacios, P., Gross, N., Gaitán, J. & Maestre, F. T. Climate mediates the biodiversity–ecosystem stability relationship globally. PNAS 115, 8400–8405. https://doi.org/10.1073/pnas.1800425115 (2018).Article 
    ADS 
    CAS 

    Google Scholar 
    Le Provost, G. et al. Land-use history impacts functional diversity across multiple trophic groups. PNAS 117, 1573–1579. https://doi.org/10.1073/pnas.1910023117 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    El Kateb, H., Zhang, H., Zhang, P. & Mosandl, R. Soil erosion and surface runoff on different vegetation covers and slope gradients: A field experiment in Southern Shaanxi Province, China. CATENA 105, 1–10. https://doi.org/10.1016/j.catena.2012.12.012 (2013).Article 

    Google Scholar 
    Oliveira, P. T. S. et al. The water balance components of undisturbed tropical woodlands in the Brazilian cerrado. Hydrol. Earth Syst. Sci. 19, 2899–2910. https://doi.org/10.5194/hess-19-2899-2015 (2014).Article 
    ADS 

    Google Scholar 
    Hümann, M. et al. Identification of runoff processes – The impact of different forest types and soil properties on runoff formation and floods. J. Hydrol. 409, 637–649. https://doi.org/10.1016/j.jhydrol.2011.08.067 (2011).Article 
    ADS 

    Google Scholar 
    Sun, D. et al. Soil erosion and water retention varies with plantation type and age. For. Ecol. Manage. 422, 1–10. https://doi.org/10.1016/j.foreco.2018.03.048 (2018).Article 

    Google Scholar 
    Jost, G., Schume, H., Hager, H., Markart, G. & Kohl, B. A hillslope scale comparison of tree species influence on soil moisture dynamics and runoff processes during intense rainfall. J. Hydrol. 420–421, 112–124. https://doi.org/10.1016/j.jhydrol.2011.11.057 (2012).Article 

    Google Scholar 
    Sadeghi, S. M. M., Attarod, P., Van Stan, J. T. & Pypker, T. G. The importance of considering rainfall partitioning in afforestation initiatives in semiarid climates: A comparison of common planted tree species in Tehran, Iran. Sci. Total Environ. 568, 845–855. https://doi.org/10.1016/j.scitotenv.2016.06.048 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Pretzsch, H. et al. Climate change accelerates growth of urban trees in metropolises worldwide. Sci. Rep. https://doi.org/10.1038/s41598-017-14831-w (2017).Article 

    Google Scholar 
    Rahman, M. A., Moser, A., Rötzer, T. & Pauleit, S. Microclimatic differences and their influence on transpirational cooling of Tilia cordata in two contrasting street canyons in Munich, Germany. Agric. For. Meteorol. 232, 443–456. https://doi.org/10.1016/j.agrformet.2016.10.006 (2017).Article 
    ADS 

    Google Scholar 
    Nytch, C. J., Meléndez-Ackerman, E. J., Pérez, M. E. & Ortiz-Zayas, J. R. Rainfall interception by six urban trees in San Juan, Puerto Rico. Urban Ecosyst. 22, 103–115. https://doi.org/10.1007/s11252-018-0768-4 (2018).Article 

    Google Scholar 
    Rahman, M. A. et al. Comparative analysis of shade and underlying surfaces on cooling effect. Urban For. Urban Green. 63, 127223. https://doi.org/10.1016/j.ufug.2021.127223 (2021).Article 

    Google Scholar 
    Chen, L., Zhang, Z. & Ewers, B. E. Urban tree species show the same hydraulic response to vapor pressure deficit across varying tree size and environmental conditions. PLoS One https://doi.org/10.1371/journal.pone.0047882 (2012).Article 

    Google Scholar 
    Moser-Reischl, A., Rahman, M. A., Pauleit, S., Pretzsch, H. & Rötzer, T. Growth patterns and effects of urban micro-climate on two physiologically contrasting urban tree species. Landsc. Urban Plan. 183, 88–99. https://doi.org/10.1016/j.landurbplan.2018.11.004 (2019).Article 

    Google Scholar 
    Hao, M. et al. Impacts of changes in vegetation on saturated hydraulic conductivity of soil in subtropical forests. Sci. Rep. 9, 8372. https://doi.org/10.1038/s41598-019-44921-w (2019).Article 
    ADS 
    CAS 

    Google Scholar 
    Peters, E. B., McFadden, J. P. & Montgomery, R. A. Biological and environmental controls on tree transpiration in a suburban landscape. J. Geophys. Res. Biogeosci. https://doi.org/10.1029/2009jg001266 (2010).Article 

    Google Scholar 
    Komatsu, H., Kume, T. & Otsuki, K. Increasing annual runoff—broadleaf or coniferous forests?. Hydrol. Process. 25, 302–318. https://doi.org/10.1002/hyp.7898 (2011).Article 
    ADS 

    Google Scholar 
    Li, X. et al. Process-based rainfall interception by small trees in Northern China: The effect of rainfall traits and crown structure characteristics. Agric. For. Meteorol. 218–219, 65–73. https://doi.org/10.1016/j.agrformet.2015.11.017 (2016).Article 
    ADS 

    Google Scholar 
    Lukaszkiewicz, J. & Kosmala, M. Determining the age of streetside trees with diameter at breast height-based multifactorial model. Arboricult. Urban For. 34, 137–143. https://doi.org/10.48044/jauf.2008.018 (2008).Article 

    Google Scholar 
    Buttle, J. M. & Farnsworth, A. G. Measurement and modeling of canopy water partitioning in a reforested landscape: The Ganaraska Forest, southern Ontario, Canada. J. Hydrol. 466–467, 103–114. https://doi.org/10.1016/j.jhydrol.2012.08.021 (2012).Article 

    Google Scholar 
    Yang, B., Lee, D. K., Heo, H. K. & Biging, G. The effects of tree characteristics on rainfall interception in urban areas. Landsc. Ecol. Eng. 15, 289–296. https://doi.org/10.1007/s11355-019-00383-w (2019).Article 
    CAS 

    Google Scholar 
    Klamerus-Iwan, A. & Witek, W. Variability in the Wettability and Water Storage Capacity of Common Oak Leaves (Quercus robur L). Water 10, 695. https://doi.org/10.3390/w10060695 (2018).Article 
    CAS 

    Google Scholar 
    Van Stan, J. T., Siegert, C. M., Levia, D. F. & Scheick, C. E. Effects of wind-driven rainfall on stemflow generation between codominant tree species with differing crown characteristics. Agric. For. Meteorol. 151, 1277–1286. https://doi.org/10.1016/j.agrformet.2011.05.008 (2011).Article 
    ADS 

    Google Scholar 
    Selbig, W. R. et al. Quantifying the stormwater runoff volume reduction benefits of urban street tree canopy. Sci. Total Environ. 806, 151296. https://doi.org/10.1016/j.scitotenv.2021.151296 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Centre for Watershed Protection. Review of the Available Literature and Data on the Runoff and Pollutant Removal Capabilities of Urban Trees (Center for Watershed Protection, 2017).
    Google Scholar 
    Berland, A. et al. The role of trees in urban stormwater management. Landsc. Urban Plan. 162, 167–177. https://doi.org/10.1016/j.landurbplan.2017.02.017 (2017).Article 

    Google Scholar 
    Pauleit, S. Urban street tree plantings: Indentifying the key requirements. Proc. Inst. Civ. Eng. Municipal Eng. 156, 43–50. https://doi.org/10.1680/muen.2003.156.1.43 (2003).Article 

    Google Scholar 
    Weller, M. Tree Inventory Data of Central European Cities—Studies on the Composition and Structure of Urban Tree Populations and Derivation of Ecosystem Services. MSC thesis, Technical University of Munich, Germany (2021). More

  • in

    Rapid upwards spread of non-native plants in mountains across continents

    Essl, F. et al. A conceptual framework for range-expanding species that track human-induced environmental change. BioScience 69, 908–919 (2019).Article 

    Google Scholar 
    Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. 4, 1044–1059 (2020).Article 

    Google Scholar 
    Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).Article 

    Google Scholar 
    Freeman, B. G., Lee-Yaw, J. A., Sunday, J. M. & Hargreaves, A. L. Expanding, shifting and shrinking: the impact of global warming on species’ elevational distributions. Glob. Ecol. Biogeogr. 27, 1268–1276 (2018).Article 

    Google Scholar 
    van Kleunen, M. et al. Global exchange and accumulation of non-native plants. Nature 525, 100–103 (2015).Article 

    Google Scholar 
    Alexander, J. M. et al. Lags in the response of mountain plant communities to climate change. Glob. Change Biol. 24, 563–579 (2018).Article 

    Google Scholar 
    Graae, B. J. et al. Stay or go—how topographic complexity influences alpine plant population and community responses to climate change. Perspect. Plant Ecol. Evol. Syst. 30, 41–50 (2018).Article 

    Google Scholar 
    Rumpf, S. B., Hülber, K., Zimmermann, N. E. & Dullinger, S. Elevational rear edges shifted at least as much as leading edges over the last century. Glob. Ecol. Biogeogr. 28, 533–543 (2019).Article 

    Google Scholar 
    Steinbauer, M. J. et al. Accelerated increase in plant species richness on mountain summits is linked to warming. Nature 556, 231–234 (2018).Article 
    CAS 

    Google Scholar 
    Mamantov, M. A., Gibson-Reinemer, D. K., Linck, E. B. & Sheldon, K. S. Climate-driven range shifts of montane species vary with elevation. Glob. Ecol. Biogeogr. 30, 784–794 (2021).Article 

    Google Scholar 
    Alexander, J. M. et al. Plant invasions into mountains and alpine ecosystems: current status and future challenges. Alp. Bot. 126, 89–103 (2016).Article 

    Google Scholar 
    Pauchard, A. et al. Ain’t no mountain high enough: plant invasions reaching new elevations. Front. Ecol. Environ. 7, 479–486 (2009).Article 

    Google Scholar 
    Alexander, J. M., MIREN Consortium et al. Assembly of nonnative floras along elevational gradients explained by directional ecological filtering. Proc. Natl Acad. Sci. USA 108, 656–661 (2011).Article 
    CAS 

    Google Scholar 
    Seipel, T. et al. Processes at multiple spatial scales determine non-native plant species richness and similarity in mountain regions around the world. Glob. Ecol. Biogeogr. 21, 236–246 (2012).Article 

    Google Scholar 
    Dainese, M. et al. Human disturbance and upward expansion of plants in a warming climate. Nat. Clim. Change 7, 577–580 (2017).Article 

    Google Scholar 
    McDougall, K. L. et al. Running off the road: roadside non-native plants invading mountain vegetation. Biol. Invasions 20, 3461–3473 (2018).Article 

    Google Scholar 
    Petitpierre, B. et al. Will climate change increase the risk of plant invasions into mountains? Ecol. Appl. 26, 530–544 (2016).Article 

    Google Scholar 
    Lembrechts, J. J. et al. Microclimate variability in alpine ecosystems as stepping stones for non‐native plant establishment above their current elevational limit. Ecography 41, 900–909 (2017).Article 

    Google Scholar 
    Haider, S. et al. Mountain roads and non-native species modify elevational patterns of plant diversity. Glob. Ecol. Biogeogr. 27, 667–678 (2018).Article 

    Google Scholar 
    Wolf, A., Zimmerman, N. B., Anderegg, W. R. L., Busby, P. E. & Christensen, J. Altitudinal shifts of the native and introduced flora of California in the context of 20th-century warming. Glob. Ecol. Biogeogr. 25, 418–429 (2016).Article 

    Google Scholar 
    Seipel, T., Alexander, J. M., Edwards, P. J. & Kueffer, C. Range limits and population dynamics of non-native plants spreading along elevation gradients. Perspect. Plant Ecol. Evol. Syst. 20, 46–55 (2016).Article 

    Google Scholar 
    Koide, D., Yoshida, K., Daehler, C. C. & Mueller-Dombois, D. An upward elevation shift of native and non-native vascular plants over 40 years on the island of Hawai’i. J. Vegetation Sci. 28, 939–950 (2017).Article 

    Google Scholar 
    Becker, T., Dietz, H., Billeter, R., Buschmann, H. & Edwards, P. J. Altitudinal distribution of alien plant species in the Swiss Alps. Perspect. Plant Ecol. Evol. Syst. 7, 173–183 (2005).Article 

    Google Scholar 
    Haider, S. et al. The role of bioclimatic origin, residence time and habitat context in shaping non-native plant distributions along an altitudinal gradient. Biol. Invasions 12, 4003–4018 (2010).Article 

    Google Scholar 
    Pyšek, P., Jarošík, V., Pergl, J. & Wild, J. Colonization of high altitudes by alien plants over the last two centuries. Proc. Natl Acad. Sci. USA 108, 439–440 (2011).Article 

    Google Scholar 
    Gottfried, M. et al. Continent-wide response of mountain vegetation to climate change. Nat. Clim. Change 2, 111–115 (2012).Article 

    Google Scholar 
    Lenoir, J. et al. Going against the flow: potential mechanisms for unexpected downslope range shifts in a warming climate. Ecography 33, 295–303 (2010).
    Google Scholar 
    Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T. & Mynsberge, A. R. Changes in climatic water balance drive downhill shifts in plant species’ optimum elevations. Science 331, 324–327 (2011).Article 
    CAS 

    Google Scholar 
    Rumpf, S. B. et al. Range dynamics of mountain plants decrease with elevation. Proc. Natl Acad. Sci. USA 115, 1848–1853 (2018).Article 
    CAS 

    Google Scholar 
    Scherrer, D. & Körner, C. Topographically controlled thermal-habitat differentiation buffers alpine plant diversity against climate warming. J. Biogeogr. 38, 406–416 (2011).Article 

    Google Scholar 
    Kelly, C. & Price, T. D. Correcting for regression to the mean in behavior and ecology. Am. Nat. 166, 700–707 (2005).Article 

    Google Scholar 
    Mazalla, L. & Diekmann, M. Regression to the mean in vegetation science. J. Vegetation Sci. 33, e13117 (2022).Article 

    Google Scholar 
    Colwell, R. K. & Lees, D. C. The mid-domain effect: geometric constraints on the geography of species richness. Trends Ecol. Evol. 15, 70–76 (2000).Article 
    CAS 

    Google Scholar 
    Colwell, R. K., Brehm, G., Cardelús, C. L., Gilman, A. C. & Longino, J. T. Global warming, elevational range shifts, and lowland biotic attrition in the wet tropics. Science 322, 258–261 (2008).Article 
    CAS 

    Google Scholar 
    Taheri, S., Naimi, B., Rahbek, C. & Araújo, M. B. Improvements in reports of species redistribution under climate change are required. Sci. Adv. 7, eabe1110 (2021).Article 

    Google Scholar 
    Haider, S. et al. Think globally, measure locally: the MIREN standardized protocol for monitoring plant species distributions along elevation gradients. Ecol. Evol. 12, e8590 (2022).Article 

    Google Scholar 
    Jacobsen, D. The dilemma of altitudinal shifts: caught between high temperature and low oxygen. Front. Ecol. Environ. 18, 211–218 (2020).Article 

    Google Scholar 
    Kueffer, C. et al. in Plant Invasions in Protected Areas Vol. 7 (eds Foxcroft, L. C. et al.) 89–113 (Springer, 2013).Halbritter, A. H., Alexander, J. M., Edwards, P. J. & Billeter, R. How comparable are species distributions along elevational and latitudinal climate gradients? Glob. Ecol. Biogeogr. 22, 1228–1237 (2013).Article 

    Google Scholar 
    Vitasse, Y. et al. Phenological and elevational shifts of plants, animals and fungi under climate change in the European Alps. Biol. Rev. 96, 1816–1835 (2021).Article 

    Google Scholar 
    Angert, A. L. et al. Do species’ traits predict recent shifts at expanding range edges? Ecol. Lett. 14, 677–689 (2011).Article 

    Google Scholar 
    Matteodo, M., Wipf, S., Stöckli, V., Rixen, C. & Vittoz, P. Elevation gradient of successful plant traits for colonizing alpine summits under climate change. Environ. Res. Lett. 8, 024043 (2013).Article 

    Google Scholar 
    Lembrechts, J. et al. Disturbance is the key to plant invasions in cold environments. Proc. Natl Acad. Sci. USA 113, 14061–14066 (2016).Article 
    CAS 

    Google Scholar 
    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Pebesma, E. Simple features for R: standardized support for spatial vector data. R J. 10, 439–446 (2018).Article 

    Google Scholar 
    Kahle, D. & Wickham, H. ggmap: spatial visualization with ggplot2. R J. 5, 144–161 (2013). http://journal.r-project.org/archive/2013-1/kahle-wickham.pdfSeipel, T., Haider, S. & MIREN consortium. MIREN survey of plant species in mountains (v2.0). Zenodo https://doi.org/10.5281/zenodo.5529072 (2022). More

  • in

    Ecologically unequal exchanges driven by EU consumption

    Rockström, J. et al. A safe operation space for humanity. Nature 461, 472–475 (2009).Article 

    Google Scholar 
    Chancel, L., Piketty, T., Saez, E. & Zucman, G. World Inequality Report 2022 (Belknap Press, 2022).Ivanova, D. et al. Environmental impact assessment of household consumption. J. Ind. Ecol. 20, 526–536 (2016).Article 
    CAS 

    Google Scholar 
    Steen-Olsen, K., Weinzettel, J., Cranston, G., Ercin, A. E. & Hertwich, E. G. Carbon, land, and water footprint accounts for the European Union: consumption, production, and displacements through international trade. Environ. Sci. Technol. 46, 10883–10891 (2012).Article 
    CAS 

    Google Scholar 
    Tukker, A. et al. Environmental and resource footprints in a global context: Europe’s structural deficit in resource endowments. Glob. Environ. Change 40, 171–181 (2016).Article 

    Google Scholar 
    Bruckner, B., Hubacek, K., Shan, Y., Zhong, H. & Feng, K. Impacts of poverty alleviation on national and global carbon emissions. Nat. Sustain. 5, 311–320 (2022).Article 

    Google Scholar 
    Hubacek, K. et al. Global carbon inequality. Energy, Ecol. Environ. 2, 361–369 (2017).Article 

    Google Scholar 
    Yu, Y., Feng, K. & Hubacek, K. Tele-connecting local consumption to global land use. Glob. Environ. Change 23, 1178–1186 (2013).Article 

    Google Scholar 
    Wilting, H. C., Schipper, A. M., Bakkenes, M., Meijer, J. R. & Huijbregts, M. A. J. Quantifying biodiversity losses due to human consumption: a global-scale footprint analysis. Environ. Sci. Technol. 51, 3298–3306 (2017).Article 
    CAS 

    Google Scholar 
    Lucas, P. L., Wilting, H. C., Hof, A. F. & Van Vuuren, D. P. Allocating planetary boundaries to large economies: distributional consequences of alternative perspectives on distributive fairness. Glob. Environ. Change 60, 102017 (2020).Article 

    Google Scholar 
    Beylot, A. et al. Assessing the environmental impacts of EU consumption at macro-scale. J. Clean. Prod. 216, 382–393 (2019).Article 

    Google Scholar 
    Koslowski, M., Moran, D. D., Tisserant, A., Verones, F. & Wood, R. Quantifying Europe’s biodiversity footprints and the role of urbanization and income. Glob. Sustain. 3, e1 (2020).Lutter, S., Pfister, S., Giljum, S., Wieland, H. & Mutel, C. Spatially explicit assessment of water embodied in European trade: a product-level multi-regional input-output analysis. Glob. Environ. Change 38, 171–182 (2016).Article 

    Google Scholar 
    Stadler, K. et al. EXIOBASE 3 (3.8.1) [Data set]. Zenodo https://doi.org/10.5281/ZENODO.4588235 (2021).Roadmap to a Resource Efficient Europe (European Commission, 2011).Steinmann, Z. J. N. et al. Headline environmental indicators revisited with the global multi-regional input–output database EXIOBASE. J. Ind. Ecol. 22, 565–573 (2018).Article 

    Google Scholar 
    Ivanova, D. et al. Mapping the carbon footprint of EU regions. Environ. Res. Lett. 12, 054013 (2017).Wiedmann, T. O. et al. The material footprint of nations. Proc. Natl Acad. Sci. USA 112, 6271–6276 (2015).Article 
    CAS 

    Google Scholar 
    Lenzen, M. et al. Implementing the material footprint to measure progress towards Sustainable Development Goals 8 and 12. Nat. Sustain. 5, 157–166 (2022).Dorninger, C. et al. The effect of industrialization and globalization on domestic land-use: a global resource footprint perspective. Glob. Environ. Change 69, 102311 (2021).Article 

    Google Scholar 
    Mekonnen, M. M. & Gerbens-Leenes, W. The water footprint of food. Water 12, 12 (2020).Article 

    Google Scholar 
    Prell, C. & Feng, K. Unequal carbon exchanges: the environmental and economic impacts of iconic U.S. consumption items. J. Ind. Ecol. 20, 537–546 (2016).Article 

    Google Scholar 
    Prell, C., Feng, K., Sun, L., Geores, M. & Hubacek, K. The economic gains and environmental losses of US consumption: a world-systems and input-output approach. Soc. Forces 93, 405–428 (2014).Article 

    Google Scholar 
    Prell, C. Wealth and pollution inequalities of global trade: a network and input-output approach. Soc. Sci. J. 53, 111–121 (2016).Article 

    Google Scholar 
    World Economic Outlook (October 2022) (International Monetary Fund, 2022); https://www.imf.org/external/datamapper/datasets/WEOWilting, H. C., Schipper, A. M., Ivanova, O., Ivanova, D. & Huijbregts, M. A. J. Subnational greenhouse gas and land-based biodiversity footprints in the European Union. J. Ind. Ecol. 25, 79–94 (2021). https://doi.org/10.1111/jiec.13042Cabernard, L. & Pfister, S. A highly resolved MRIO database for analyzing environmental footprints and Green Economy Progress. Sci. Total Environ. 755, 142587 (2021).Jakob, M., Ward, H. & Steckel, J. C. Sharing responsibility for trade-related emissions based on economic benefits. Glob. Environ. Chang. 66, 102207 (2021).Article 

    Google Scholar 
    Wood, R. et al. The structure, drivers and policy implications of the European carbon footprint. Clim. Policy 20, S39–S57 (2020).Article 

    Google Scholar 
    Wood, R. et al. Growth in environmental footprints and environmental impacts embodied in trade: resource efficiency indicators from EXIOBASE3. J. Ind. Ecol. 22, 553–564 (2018).Article 

    Google Scholar 
    Hubacek, K., Chen, X., Feng, K., Wiedmann, T. & Shan, Y. Evidence of decoupling consumption-based CO2 emissions from economic growth. Adv. Appl. Energy 4, 100074 (2021).Article 

    Google Scholar 
    Wiedmann, T. & Lenzen, M. Environmental and social footprints of international trade. Nat. Geosci. 11, 314–321 (2018).Article 
    CAS 

    Google Scholar 
    Dorninger, C. et al. Global patterns of ecologically unequal exchange: Implications for sustainability in the 21st century. Ecol. Econ. 179, 106824 (2021).Article 

    Google Scholar 
    Hickel, J., Dorninger, C., Wieland, H. & Suwandi, I. Imperialist appropriation in the world economy: drain from the global South through unequal exchange, 1990–2015. Glob. Environ. Change 73, 102467 (2022).Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).Article 
    CAS 

    Google Scholar 
    Ivanova, D. et al. Quantifying the potential for climate change mitigation of consumption options. Environ. Res. Lett. 15, 093001 (2020).Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).Article 
    CAS 

    Google Scholar 
    Ivanova, D. & Wood, R. The unequal distribution of household carbon footprints in Europe and its link to sustainability. Glob. Sustain. 3, e18 (2020).Hickel, J., O’Neill, D. W., Fanning, A. L. & Zoomkawala, H. National responsibility for ecological breakdown: a fair-shares assessment of resource use, 1970–2017. Lancet Planet. Heal. 6, e342–e349 (2022).Article 

    Google Scholar 
    Otto, I. M., Kim, K. M., Dubrovsky, N. & Lucht, W. Shift the focus from the super-poor to the super-rich. Nat. Clim. Change 9, 82–84 (2019).Article 

    Google Scholar 
    Wiedmann, T., Lenzen, M., Keyßer, L. T. & Steinberger, J. K. Scientists’ warning on affluence. Nat. Commun. 11, 3107 (2020).Nielsen, K. S., Nicholas, K. A., Creutzig, F., Dietz, T. & Stern, P. C. The role of high-socioeconomic-status people in locking in or rapidly reducing energy-driven greenhouse gas emissions. Nat. Energy 6, 1011–1016 (2021).Article 

    Google Scholar 
    Jakob, M. Why carbon leakage matters and what can be done against it. One Earth 4, 609–614 (2021).Article 

    Google Scholar 
    Lave, L. B. Using input–output analysis to estimate economy-wide discharges. Environ. Sci. Technol. 29, 420A–426A (1995).Article 
    CAS 

    Google Scholar 
    Wiedmann, T. A review of recent multi-region input–output models used for consumption-based emission and resource accounting. Ecol. Econ. 69, 211–222 (2009).Article 

    Google Scholar 
    Ewing, B. R. et al. Integrating ecological and water footprint accounting in a multi-regional input–output framework. Ecol. Indic. 23, 1–8 (2012).Article 

    Google Scholar 
    Brizga, J., Feng, K. & Hubacek, K. Household carbon footprints in the Baltic States: a global multi-regional input–output analysis from 1995 to 2011. Appl. Energy 189, 780–788 (2017).Hertwich, E. G. & Peters, G. P. Carbon footprint of nations: a global, trade-linked analysis. Environ. Sci. Technol. 43, 6414–6420 (2009).Article 
    CAS 

    Google Scholar 
    Zhong, H., Feng, K., Sun, L., Cheng, L. & Hubacek, K. Household carbon and energy inequality in Latin American and Caribbean countries. J. Environ. Manag. 273, 110979 (2020).Article 

    Google Scholar 
    Stadler, K. et al. EXIOBASE 3: developing a time series of detailed environmentally extended multi-regional input–output tables. J. Ind. Ecol. 22, 502–515 (2018).Article 

    Google Scholar 
    Hardadi, G., Buchholz, A. & Pauliuk, S. Implications of the distribution of German household environmental footprints across income groups for integrating environmental and social policy design. J. Ind. Ecol. 25, 95–113 (2021).Zhang, Q. et al. Transboundary health impacts of transported global air pollution and international trade. Nature 543, 705–709 (2017).Article 
    CAS 

    Google Scholar 
    Hoekstra, A. Y., Mekonnen, M. M., Chapagain, A. K., Mathews, R. E. & Richter, B. D. Global monthly water scarcity: blue water footprints versus blue water availability. PLoS ONE 7, e32688 (2012).Article 
    CAS 

    Google Scholar 
    IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).Schmidt, S. et al. Understanding GHG emissions from Swedish consumption—current challenges in reaching the generational goal. J. Clean. Prod. 212, 428–437 (2019).Article 

    Google Scholar 
    Huijbregts, M. A. J. Priority Assessment of Toxic Substances in the Frame of LCA. Development and Application of the Multi-Media Fate, Exposure and Effect Model USES-LCA (Interfaculty Department of Envrionmental Science, 1999).Huijbregts, M. A. J. Priority Assessment of Toxic Substances in the Frame of LCA. Time Horizon Dependency in Toxicity Potentials Calculated with the Multi-Media Fate, Exposure and Effects Model USES-LCA (Institute for Biodiversity and Ecosystem Dynamics, 2000).International Reference Life Cycle Data System (ILCD) Handbook (Publications Office EU, 2011).Verones, F., Moran, D., Stadler, K., Kanemoto, K. & Wood, R. Resource footprints an d their ecosystem consequences. Sci. Rep. 7, 40743 (2017).Chaudhary, A., Pfister, S. & Hellweg, S. Spatially explicit analysis of biodiversity loss due to global agriculture, pasture and forest land use from a producer and consumer perspective. Environ. Sci. Technol. 50, 3928–3936 (2016).Article 
    CAS 

    Google Scholar 
    Chaudhary, A., Verones, F., De Baan, L. & Hellweg, S. Quantifying land use impacts on biodiversity: combining species-area models and vulnerability indicators. Environ. Sci. Technol. 49, 9987–9995 (2015).Article 
    CAS 

    Google Scholar 
    Marquardt, S. G. et al. Consumption-based biodiversity footprints—do different indicators yield different results? Ecol. Indic. 103, 461–470 (2019).Article 

    Google Scholar 
    World Development Indicators DataBank (World Bank, 2022); https://databank.worldbank.org/source/world-development-indicatorsWorld Population Prospects 2022 (United Nations, 2022); https://population.un.org/wpp/Natural Earth Vector (Natural Earth, 2022); https://www.naturalearthdata.com/Lahti, L., Huovari, J., Kainu, M. & Biecek, P. Retrieval and analysis of eurostat open data with the Eurostat package. R J. 9, 385–392 (2017).Castellani, V., Beylot, A. & Sala, S. Environmental impacts of household consumption in Europe: comparing process-based LCA and environmentally extended input-output analysis. J. Clean. Prod. 240, 117966 (2019).Article 

    Google Scholar  More

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    Using size-weight relationships to estimate biomass of heavily targeted aquarium corals by Australia’s coral harvest fisheries

    Establishing size-weight relationships for heavily targeted coral species is an important first step towards informing sustainable harvest limits19. Placing coral harvests into an ecological context is a core requirement for implementing a defensible stock assessment strategy, and this need is particularly critical given escalating disturbances and widespread reports of coral loss7,17,25. Using these relationships, managers can now easily sample and calculate biomass per unit area. It is important to point out that all sites sampled in our study represent fished locations, and there is no information available to test whether standing biomass has declined due to sustained coral harvesting at these locations. While these data may now provide a critical baseline for assessing the future effects of ongoing fishing, it is also important to sample at comparable locations where fishing is not permitted or has not occurred (where possible), to test for potential effects of recent and historical harvesting.Biomass per unit area data presented herein highlights the highly patchy abundance and biomass of targeted coral species14, which is evident based on the often vastly different mean and median values (Table 2). Examining biomass per unit area estimates for C. jardinei for example, which returned some of the highest biomass estimates, the 33.75 kg·m−2 maximum estimate from a transect stands as an extreme outlier, with 12 of the 16 other transects being below 0.2 kg·m−2. This indicates the challenges of managing species that occur in patchily distributed concentrations, particularly in a management area the size of the QCF. It is also important to note, these estimates are generated only on transects where the target species occurred, and therefore, should technically not be considered as an overall estimate of standing biomass. While the estimation of size-weight relationships is a step towards a standing biomass estimate, many challenges remain in terms of sampling or reliably predicting the occurrence of these patchily distributed species. Bruckner et al.14 attempted to overcome this management challenge in a major coral fishery region of Indonesia by categorising and sampling corals (in terms of coral numbers) in defined habitat types, and then extrapolating to estimated habitat area based on visual surveys and available data. This approach, utilising size-weight relationship derived biomass per unit area estimates (instead of coral numbers), may be a viable method for the QCF, however much more information is needed to understand the habitat associations (e.g., nearshore to offshore), and environmental gradients that influence the size and abundance of individual corals. Fundamentally, it is also clear that much more data is required to effectively assess the standing biomass of aquarium corals in the very large area of operation available to Australian coral fisheries.These corals are found in a range of environments, and it is important to consider available information on life history if attempting to use coral size-weight relationships to inform management strategies via standing biomass estimation. All corals in this study can be found as free living corals (at least post-settlement) in soft-sediment, inter-reefal habitats, from which they are typically harvested by commercial collectors19. However, only four of the 6 species are colonial (C. jardinei, D. axifuga, E. glabrescens, M. lordhowensis) while the remaining two species (H. cf. australis and T. geoffroyi) are more typically monostomatous or solitary. As indicated in previous work24, if larger colonial corals were to be fragmented during harvesting instead of removed entirely, fishery impacts would likely be lessened24. Given the power relationship between coral maximum diameter and weight, larger corals contribute disproportionately to the total available biomass of each species in a given area. The potential environmental benefit of leaving larger colonies (at least partially) intact is not limited to impacts on standing biomass, as this practice would likely be demographically beneficial given the greater reproductive potential (i.e., fecundity) of larger colonies, which also do not need to overcome barriers to replenishment of populations associated with new recruits (i.e., high mortality during and post-settlement26). This conclusion was drawn largely from data on branching taxa (e.g., Acropora), which are relatively resilient to fragmentation and commonly undergo fragmentation as a result of natural processes27,28,29. D. axifuga can be considered to exhibit a relatively similar branching growth form, however, the growth form of E. glabrescens and C. jardinei changes with size, moving from small discrete polyps to large phaceloid and flabello-meandroid colonies, respectively19. While larger colonies of E. glabrescens and C. jardinei may be relatively resilient to harvesting via fragmentation, the same may not be true for smaller colonies, or species with massive growth forms such as M. lordhowensis. Typically, for each species, the average reported weight was quite low, coinciding with the lower end of the sampled maximum diameter range. For colonial species, the harvested smaller maximum diameters (if fragments) are ideal from an ecological perspective as this will have the least impact possible on standing biomass, and may also leave a potentially mature breeding colony intact. Ultimately, in light of these considerations, the development of uniform and standardised industry-wide harvest guidelines to balance economic and ecological outcomes may be necessary. The development of these guidelines would require consultation with commercial harvesters, as well as considerable additional work in measuring ecological impacts and better understanding the cost of these impacts from an economic perspective. Conversely, if whole colonies are collected, which is necessarily the case for solitary species such as H. cf. australis and T. geoffroyi (and potentially smaller colonies of other species such as E. glabrescens and C. jardinei); smaller colonies may be collected before they reach sexual maturity, hindering their ability to contribute to population replenishment. Therefore, collection of small fragments should be encouraged for colonial species; while for monostomatous species where this is not possible, introduction of a minimum harvest size based on sexual maturity should be considered.Additionally, the need for further consideration of the selectivity of ornamental coral harvest fisheries3,4,30 when assessing standing biomass is evident. Due to various desirable traits, the majority of available biomass may not be targeted by collectors. As emphasised in this study, the focus on smaller corals is indicative of the trend towards collection of most of these species at the lower portion of their size range, at least compared to some of the maximum sizes recorded on transects (e.g., see Tables 1 and 2, section b). However, it is also important to consider that transects were conducted in areas subject to commercial collection and are likely to skew results and prevent clear conclusions relating to size selectivity. Sampling of unfished populations (i.e., any residing outside of permitted fishing zones) and/or spatial and temporal matching of catch data and transect data across a larger sample of operators will be required to properly address industry size selectivity trends. For instance, only 17.5% of C. jardinei corals measured on transects fell within the diameter range represented by data obtained from collectors, with 81.9% of corals measured on transects exceeding this range. If it is viable to collect fragments from larger colonies (which does appear to be the case for some corals such as C. jardinei), then a larger proportion of standing biomass outside of this size range could be targeted by fishers. As an additional consideration, only desirable colour morphs of these corals will be harvested, and due to lack of appropriate data, the prevalence of these morphs remains unclear. H. cf. australis and M. lordhowensis for example often occur in brown colour morphs, which are far less popular in markets where certain aesthetic qualities (e.g., specific, eye-catching colours or combinations of colours) are desired, such as the ornamental aquarium industry. Even without delving into further considerations such as heritability of phenotypic traits, management conclusions drawn from standing biomass estimates may be ineffective in the absence of efforts to account for selectivity in this fishery.The relationship between size and weight was found to differ between all corals, with the exception of C. jardinei and E. glabrescens. There can be some moderate similarity in skeletal structure between these two species, particularly between small colonies, reflecting the similar maximum diameter range of sampling in the current study. Subsequently, inherent physiological constraints may be imposed on corals that prevent the maintenance of growth rates between corals of smaller and larger sizes, for example, as the surface area to volume ratio declines with growth31. In the current study, all corals, with the exception of C. jardinei, showed evidence of allometric growth, as exhibited by an estimated exponent value different to 3. Sample size for C. jardinei was greatly limited, as this species typically forms extensive beds, and are rarely brought to facilities as whole colonies. Therefore, the lack of evidence for allometric growth may reflect higher error for the species coefficient parameter due to the comparatively small sample size for this species. This suggests that mass would not increase consistently with changes in colony size in 3 dimensions31, which seems likely considering the change in exhibited form described for E. glabrescens and C. jardinei previously. In the current context, this indicates that the estimated ‘a’ and ‘b’ constants are likely to vary as the sample range increases, reflecting the changes in the size-weight relationship between smaller and larger samples of these species. Therefore, ideally, these models should incorporate data that reflect the maximum diameter range of the species in the region of application to allow increased accuracy of biomass estimation. To achieve this will require additional fishery-independent sampling, as large colonies are rarely collected whole, though may be collected as fragments depending on the species. Sampling may be challenging for some species given the difficulty of physically collecting and replacing large whole colonies, particularly for inter-reefal species such as M. lordhowensis, which can occur in deep, soft sediment habitat, subject to strong currents. Importantly, obtaining ex situ or in situ growth rate data should be considered a priority for the management of heavily targeted species. This data is likely to be another necessary component (in conjunction with size-weight relationships) of any stock assessment model developed for LPS corals, and may also eliminate the need to collect large sample colonies to improve estimated size-weight relationships.The disproportionate focus on smaller corals (i.e., corals in the current study averaged between 4.28 and 11.48 cm in maximum diameter) is likely to lead to an underestimation of weight in corals at greater diameters when used as inputs for size-weight models. This may explain the apparent minor underestimation observed in some species (e.g., M. micromussa, T. geoffroyi). In the current context, this represents an added level of conservatism with estimates obtained from these equations. While the relationship between size and weight was particularly strong for some species, (mainly D. axifuga and T. geoffroyi), for other species, such as M. lordhowensis, growth curves tended towards underestimation at larger diameter values. As the mass of a coral is reflective of the amount of carbonate skeleton that has been deposited32, the coral skeleton may increase disproportionately to coral diameter if or when corals start growing vertically. For example, in massive corals such as M. lordhowensis, vertical growth (i.e., skeletal thickening) is often very negligible among smaller colonies, with thickening of the coral skeleton only becoming apparent once the coral has reached a threshold size in terms of horizontal planar area. Additional fisheries-independent sampling outside of the relatively narrow size range of harvested colonies will be required to address this source of error in future applications. Ecological context in the form of fishery independent data on stock size and structure is essential for effective management, especially in ensuring that exploitation levels are sustainable and appropriate limits are in place. Coral harvest fisheries offer managers an ecologically and biologically unique challenge, as the implementation of standard fisheries management techniques and frameworks is hampered by their coloniality and unique biology, as well as a general lack of relevant data for assessing standing biomass and population turnover, not to mention the evolving taxonomy of scleractinian corals33. Similarly, fishery-related management challenges such as the extreme selectivity in terms of targeted size-ranges and colour-morphs, plus the potentially vast difference in the impact of various collection strategies (i.e., whole colony collection vs fragmentation during collection) also complicates the application of typical fisheries stock assessment frameworks. The relationships and equations established in the current work offer an important first step for coral fisheries globally by laying the groundwork for a defensible, ecologically sound management strategy through estimation of standing biomass, thus bridging the gap between weight-based quotas and potential environmental impacts of ongoing harvesting. It is important to note that the species selected for the current work do not represent the extent of heavily targeted LPS corals. For example, Fimbriaphyllia ancora (Veron & Pichon, 1980), Fimbriaphyllia paraancora (Veron, 1990), Cycloseris cyclolites (Lamark, 1815), and Acanthophyllia deshayesiana (Michelin, 1850) are examples of other heavily targeted corals of potential environmental concern19, and management would also benefit from the estimation of size-weight relationships for these species. Moving forward, the next challenge for the coral harvest fisheries will be to comprehensively document and track the standing biomass of heavily targeted and highly vulnerable coral stocks, explicitly accounting for fisheries effects and also non-fisheries threats, especially global climate change. More

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    Anthropogenic interventions on land neutrality in a critically vulnerable estuarine island ecosystem: a case of Munro Island (India)

    Land vulnerability of an area is directly related to the natural as well as anthropogenic activities involved in the geomorphological unit. Being one of the most vulnerable ecosystems, the estuaries and estuarine islands are delicately affected by both ecological processes of the sea and land and have pressures from multiple anthropogenic stressors and global climate change42,43,44. Ecological vulnerability and ecological sensitivity are similar and both originated from the concept of ecotone10,45. The geomorphologic concept of landscape sensitivity was first proposed by Brunsden and Thornes, who argued that the sensitivity indicated the propensity to change and the capacity to absorb the effects of disturbances10,46,47. Landscape sensitivity is studied by many researchers such as Allison and Thomas, Miles et al., Harvey, Knox, Usher, Haara et al., Thomas, Jennings and Yuan Chi8,47,48,49,50,51,52,53,54, through different case studies. Based on their findings Yuan Chi summarized the important characteristics of the landscape sensitivity are: a, the change of the landscape ecosystem; it involves the change likelihood, ratio, and component, as well as the resistance and susceptibility to the change, b, the temporal and spatial scales; which determine the occurrence, degree, and distribution of the change, c, the external disturbances that cause the change; the disturbances included natural and anthropogenic origins with different categories and intensities, and d, the threshold of the landscape sensitivity; it refers to the point of transition for the landscape ecosystem8. The environmental vulnerability of the Munroe Island has been studied based on the characterization of the geomorphological and sociocultural dynamics of the region based on the above characteristics.Bathymetric surveys in Ashtamudi lake and the Kallada riverThe present study shows that the geomorphic processes occurring on the Munroe Island are affected by anthropogenic disturbances in the morpho-dynamics of the Kallada river, Ashtamudi backwaters and associated fluvio-tidal interactions. A detailed bathymetric survey of both water bodies up to the tidal-influenced upper limit of the Kallada river27 was conducted with 200 m spaced grid references (Fig. 5). Bathymetry shows that the deepest point of the Ashtamudi backwater system is in Vellimon lake (13.45 m), the SE extension of Ashtamudi lake. The eastern side of Ashtamudi lake is deeper than the western side of this backwater system. The depth of the backwater decreases towards the estuary, and most parts of the lakebed are exposed here at the mouth of the inlet during the low tide. Compared to Ashtamudi lake, the Kallada river is deeper, and the riverbed area is recorded as the average depth is greater than 13 m. The deepest part of 14.9 m is recorded near Kunnathoor bridge, which is 12 km upstream from Munroe Island. Except for a few spots of hard (resistant) rocks, the river fairly and consistently follows a higher depth throughout its course.Figure 5Bathymetric profile of Ashtamudi lake and adjoining Kallada river (Figure was generated by Arc GIS 10.6).Full size imageOnce the Kallada river supplied very fertile alluvium during its flooding seasons (monsoon/rainy season), and most of this alluvium is deposited in the floodplains of the Munroe Island and the Ashtamudi lake. With a vast river catchment area from elevated lands of Western Ghats and a shorter course of 121 km33,55 and a higher elevation gradient of 12.6 m/km56, the Kallada river has a higher transporting capacity. The eroded surface and mined river/lakebeds at lower courses were replaced by the sediment load supplied by the Kallada river during each flood season until dam construction. During the focus group discussions with residents of the Island, they had described that they were crossing the Kallada river on foot in the 1990s or even earlier during the dry seasons. The construction of the Thenmala reservoir dam in 1980s across the river drastically choked the sediment supply of the Kallada river. In addition, excessive commercial sand mining without any regulation from the riverbeds of Kallada and Ashtamudi waterbodies accelerated the deepening of waterbodies. It increased the erosion of surface and subsurface soils through fluvial and hydraulic action. This, in turn, drastically reduced the deposition of fertile alluvium over the low-lying Munroe Island. The current bathymetry shows that the river channel has deepened its course to 14 m compared to 5–6 m of 1980s. When comparing the bathymetric data of 200127, it is interesting to note that no considerable changes occurred in the bathymetry of Ashtamudi lake over the last two decades.Dams indeed alter aquatic ecology and river hydrology, upstream and downstream, affecting water quality, quantity, breeding grounds and habitation22. The other significant impact of the damming of the Kallada river is the saline water intrusion towards upstream of Ashtamudi lake and the Kallada river. The freshwater discharge is regulated after the construction of the Thenmala reservoir, and the water is being diverted to the reservoir and associated canals. There is a decline in sedimentation over the floodplains and catchment area as a result of the increased tidal effects and associated running water dynamics, which may accelerate the erosion trend of the nearby places.Lithological characterization of the Munroe IslandThe Munroe Island is a riverine delta formation by the Kallada river at the conjunction of river and backwater systems. To understand the micro-geomorphological processes of the study area, the near-surface geology of the Munroe Island had been studied in detail with the help of resistivity meter surveys and borehole datalogs from different locations. As per the current resistivity survey, it is evident that the Munroe Island is formed by recent unconsolidated loose sediments more than 120 m thick succession below ground level (Figs. 6 and 7). The electrical resistivity tomography of identified locations within the deltaic region shows a meagre resistance value to its maximum penetration (Fig. 6), which proves that the sedimentary column with intercalations of sand and carbonaceous clays of varying thickness extends to a depth of 120 m, in turn indicating the process of enormous sedimentation happened during the recent geological period. Loose wet soils of saline nature records a lower resistance value for an electric circuit. The layers formed in the diagram (Fig. 6) represent the seasonal deposition of unconsolidated soils as thin sequence. The Mulachanthara station of the resistivity meter tomography, which is situated at a more stable location of the Island, has a higher resistivity value than the West Pattamthuruth location, which is located at the exact alluvial flood plain.Figure 6Electrical resistivity profiles of Munroe Island.Full size imageFigure 7Geomorphological map showing litho-log of north (Kannamkadu); middle (Konnayil Kadavu); and south (Perumon bridge) locations of Munroe Island (borehole data source: PWD, Govt of Kerala) (Software used: Arc GIS 10.6).Full size imageThe Public Works Department (PWD), Kerala State carried out soil profile studies through Soil Penetrating Test (SPT) borehole drilling method as part of constructing bridges at three different locations up to a depth of 62 m, i.e., one across the Kallada river (north side)57, one across Ashtamudi lake in southern Munroe Island58 and one at the central part of Munroe Island (across a canal)59 (Fig. 7). The hard rock is found only on the southern side of the lake at a depth of 45 m. The litho-log shows that unconsolidated loose sediments of significantly higher thickness occur in the entire Munroe Island (Fig. 7). Anidas Khan et al.60 studied the shear strength and compressibility characteristics of Munroe Island’s soil for two different locations with disturbed and undisturbed samples. They classified the soil of Mundrothuruth into medium compressibility clay (CI) and high compressibility clay (CH) with natural moisture contents of 44.5% and 74%, respectively. The unconfined compressive strengths of the undisturbed and remolded samples for the first location are 34.5 kN/m2 and 22.1 kN/m2, respectively, while they are 13 kN/m2 and 9 kN/m2 respectively for the second location60. Such compressive strength indicates that the soils of Munroe Island are soft or very soft in nature.Land degradation: a morphological analysisTo decrease the impact of the monsoon floods and to distribute the alluvium to the southern part of the island, Canol Munroe, the then Diwan of the Thiruvithamkoor Dynasty, made an artificial man-made canal during the 1820s connecting the Kallada river with the eastern extension of Ashtamudi lake, and this river is known as “Puthanar” (meaning a new river). During the last few decades, (after 1980s) the estuarine island ecosystem of Munroe Island has faced several structural deformities. The natural sedimentation and flooding happening in the Islands were very limited and hence, the normal events happened over the past several decades disturbed and significantly affected the land neutrality. These islands, once known as the region’s rice bowl, now devoid of any paddy cultivation mainly because of the increased soil salinity. According to the Cadastral map prepared by the revenue department (1960s) there were many paddy fields, locally named as Mathirampalli Vayal (Vayal is the local name for paddy field), Thekke Kothapppalam Vayal, Mattil Vayal, Kottuvayal, pallaykattu Vayal, Konnayil Vayal, Vadakke Kundara Vayal, Thachan Vayal, Thekke Kundara Vayal, Kizhakke Oveli Vayal, Thekke Oveli Vayal, Odiyil Vettukattu Vayal, Nedumala Vayal, Madathil Vayal, Karichal Vayal, Moonumukkil Vayal, Arupara Vayal, Kaniyampalli Vayal, Manakkadavu Vayal, Panampu Vayal, Pattamthuruth Vayal etc. The recent satellite images shows that no paddy cultivation exist now, which is further confirmed by the field observations conducted through our study. The annual report published by Gramapanchayat39 indicate that the paddy field of region was reduced from 227 to 8 acres (from 1950 to 1995) and now about in 2 acres only (2018). Most of the paddy fields of northern and northwestern regions are severely affected by land degradation due to erosion, saline water intrusion and flooding and are entirely or partially buried under the backwater system. Figure 8 depicts the morphological degradation of the severely affected areas of Munroe Island from 1989 to 2021 through different satellite images. Some paddy fields are converted into filtration ponds to take the benefit of frequent tidal flooding. The coconut plantations were later introduced in place of paddy fields, and they eventually replaced the paddy fields. However, during the last decades, it has been observed that these coconut plantations are also under threat mainly because of degradation of the soil fertility, which directly bears the quality and quantity of production (Fig. 9).Figure 8Morphological changes in the study area from the satellite images (a) 1989 (aerial photograph); (b) 2000 (Landsat); (c) 2011 (World View—II); (d) 2021 (Sentinel) (the modified maps of (a) is obtained from National remote Sensing Centre (NRSC), Hyderabad, (b) is downloaded from https://earthexplorer.usgs.gov/ (c) is obtained from Digital Globe through NRSC and (d) is downloaded from https://scihub.copernicus.eu/. Figures were generated using Arc GIS 10.6).Full size imageFigure 9Threatened coconut plantations indicating the low productive regime. Photographs taken by Rafeeque MK.Full size imageOver the study area the most affected alluvial plain of the Peringalam and Cheriyakadavu island are taken separately to study the morphological changes over the decades. This area is named Puthan Yekkalpuram (which means new alluvium land), and the north side of the Kallada river (the northward extension in the Mundrothuruth GP) is demarcated as old alluvium land (Pazhaya Yekkalpuram) as per the revenue department’s cadastral map. The study shows that total 38.73 acres of land has lost from the Peringalam and Cheriyakadavu Islands during the last 32 years, which is equivalent to 11.78% and 46.95% of the total geographical area of the Peringalam and Cheriyakadavu Islands, respectively. The land degradation details over the last three decades are given in the Table 2. Many other locations, such as Nenmeni and West Pattamthuruth, are also severely affected by land degradation. However, these areas are landlocked and less affected by running water or floods. Hence, the land degradation experienced is the settling of the topsoil and subsidence of structures such as houses and bridges. The sinking of basements of many houses and even the subsidence of railway platforms are well observed during field visits, indicating the alarming land degradation issues (Figs. 1 and 10) to be addressed its deserving importance. There are also clear indications of the gradual formation of new waterlogged areas in the islands, which may further deteriorate and forms the part of the backwater system which eventually affects total land area of the Munroe Island.Table 2 Land degradation of Peringalam and Cheriyakadavu region for the past 32 years.Full size tableFigure 10Various environmental degradations in Munroe Island. Photographs taken by Rafeeque MK.Full size imageThe island population also shows a negative growth over the years. According to the census report of 201138, the total population of Gramapanchayat has decreased to 9440 person/km2 in 2011 from 10,013 person/km2 of 2001 and 10,010 person/km2 of 1991 census reports. Frequent flooding (especially tidal flooding), the lack of drinking water, and migration in search of a better livelihood are the main reasons for the observed population reduction as revealed through the survey. The high intrusion of saline water into the cultivated land through tidal flooding and the lack of flushing of surface saline soils by monsoon floods (freshwater) decreased agricultural productivity of the area, and hence, now people are more dependent on fishing and backwater activities for their livelihood. Lack of proper transportation to the nearby markets limits their fishing activities to a daily subsistence level. Due to the flooding caused by subsidence/tidal surges and land degradation during the last few decades, more than 500 households have vacated their houses38,39.Tidal Flooding and Estuarine ProcessesIn Mundrothuruth, the major environmental degradation problems where occurring due to tidal flooding and saline water intrusion into the freshwater ecosystem. Mathew et al. studied the tidal and current mechanisms of the Ashtamudi backwater in 200161. They reported that the Kallada river plays a vital role in determining the eastern lake’s circulation pattern. In addition, the increased discharge from the north Chavara canal and the south Kollam canal also influences the local circulation of the Ashtamudi backwater. The current velocity reaches up to 100 cm/s at the estuary entrance, but it rapidly diminishes in the eastern parts, where the speed is generally less than 30 cm/s. One of the critical observations made during the field study, which corroborates with the acquaintance of local people as well, is that the flooding on Munroe Island is not related to the spring tide of the open ocean. The disappearance of the semidiurnal tide in the central lakes occurs due to frictional resistance and the time lags for the tide to travel across the estuary61. At the shorter semidiurnal period of approximately 12 h, the tide is more dissipated than the more extended constituents of 24-h duration. The survey conducted with the island inhabitants also reiterates these views.As per the experience of local inhabitants, tidal flooding in Munroe Island was not frequent in earlier times. The comparison of the bathymetry data collected during 200058 and 2017 (Fig. 5) in and around the regions of Munro Islands shows that there is not much change in bathymetry during the period. Hence, changes in basin geometry are not having a significant role in tidal dynamics in imparting the variations as observed. In addition to the bathymetric survey, the data on tide measurements at four locations corresponding to three seasons were also collected. The tide data measured during the pre-monsoon period is shown in Fig. 11a. The figure shows that the tidal range in the inland area is almost the same even during the spring and neap tides. As discussed earlier, the tidal flooding in Munro Island is not related to spring tide in the ocean, and there may be the influence of specific complicated dynamics in the basin for this flooding that needs to be studied more profoundly. Further the data pertaining to tidal dynamics were inadequate; we established three tide gauges in selected locations in and around Munro Island. From the analysis of tide gauge data, it is found that the signature of anomalous variability in water column height, which is not at all linked to the tidal dynamics.Figure 11(a) Salinity variation of bottom water at selected locations in Kallada river during monsoon and post monsoon. (b) Observed tide during pre-monsoon months.Full size imageThe water quality analysis for three time periods, during the year of the cyclonic storm, Okhi (2017), was conducted to understand river run-up impact on salinity in and around Munroe Island (Fig. 11). The riverbed is lowered below the baseline of erosion, and dense saline water is trapped in the deeps during high tide. This has been confirmed during the bathymetric survey of the Kallada river and Ashtamudi backwaters, which showed a significant increase in water depth, particularly within the river channel. The high-density saline water is trapped in the basins and trenches created in the river channel due to uncontrolled sand mining, which leads to the degradation of the quality of sediments and groundwater in the region. Nevertheless, the samples collected immediately after Okhi (when the dam’s shutter was opened due to heavy rainfall in the catchment area) show that the high runoff replaced the trapped saline water with fresh water. After ten days of the first sampling, the water became saline nature after the closure of the dam’s shutter. This proves that because of dam construction, the river runoff in the Kallada river was reduced significantly, and extensive human interactions especially sand mining activities increased the riverbed deepening and formation of pools beyond the base level of running water.Conservations and management strategiesConsidering the facts discussed above, the Munroe Island may continue to be badly affected unless suitable sustainable management strategies are not evolved. Construction and associated activities, such as the damming of reservoirs, sand mining and landfilling, are indispensable for any nation’s economic and social development. United Nations’s member states have formulated 17-point Sustainable Developmental Goals (SDGs) to better the world sustainably. Local and national governments pertaining to the Munroe Island need to develop a sustainable management plan to protect this Ramsar-listed wetland. The environmental issues of Mundrothuruth can be controlled, and land degradation may be monitored through a well-drafted working plan. All aspects of earth and social sciences may be integrated to draft such a management plan of reverse landscaping. The reverse landscaping (i.e., recalling the degrading landscape to its geomorphic isostatic state) method is a must-considered sustainable solution for land degradation and other environmental issues.The deep courses of Kallada river must be upwarped through a well-planned artificial sedimentation to eradicate the saline banks of deep basins. The sediments deposited in the Thenmala reservoir and the sediments removed through the digging of boat channels may be utilized in a periodic monitoring method. Sand mining from Ashtamudi lake and the Kallada river may be strictly controlled, and the minimum freshwater flow should be ensured. The construction methods practiced in Mundrothuruth are outdated and technically nonexistent. Well-studied engineering methods suitable for an environmentally fragile area must be implemented with a proper understanding of the soil characteristics, such as shear strength and compressibility rate, and hydrodynamics, such as tidal and fluvial actions. Soil fertility must be increased by supplying additional fertile soil and freshwater, at least for a minimum period. The inhabitants’ socioeconomic well-being is strengthened by advancing technology and providing easy access to the market and other social amenities. More