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Direct and cascading impacts of tropical land-use change on multi-trophic biodiversity

Nature Ecology & Evolution volume 1, pages 1511–1519 (2017)Cite this article

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Abstract

The conversion of tropical rainforest to agricultural systems such as oil palm alters biodiversity across a large range of interacting taxa and trophic levels. Yet, it remains unclear how direct and cascading effects of land-use change simultaneously drive ecological shifts. Combining data from a multi-taxon research initiative in Sumatra, Indonesia, we show that direct and cascading land-use effects alter biomass and species richness of taxa across trophic levels ranging from microorganisms to birds. Tropical land use resulted in increases in biomass and species richness via bottom-up cascading effects, but reductions via direct effects. When considering direct and cascading effects together, land use was found to reduce biomass and species richness, with increasing magnitude at higher trophic levels. Our analyses disentangle the multifaceted effects of land-use change on tropical ecosystems, revealing that biotic interactions on broad taxonomic scales influence the ecological outcome of anthropogenic perturbations to natural ecosystems.

In recent years, experimental research that manipulates plant diversity and composition has elucidated how primary producers influence the structure of food webs via bottom-up trophic cascades13,14,15. These findings lend credence to the theory that perturbations at particular trophic levels can have profound impacts on the structure of whole ecosystems as these effects ripple across functional groups of organisms that are linked by their trophic interactions16. This notion holds crucial implications for the way that land-use change will impact ecosystems, raising the question of how bottom-up cascades impact multi-trophic communities in combination with the direct impacts of management practices in intensified land-use systems. Experimental manipulations of trophic levels have been necessary to understand how trophic cascades operate in simple multi-trophic systems, but these experiments are restricted to systems of low trophic complexity due to strong logistical constraints. Multivariate analytical techniques such as structural equation modelling allow for the inference of cascading effects from observational data in more complex systems by analysing the covariance structure of multiple variables17, thus expanding our ability to explore cascading dynamics in complex systems. On one hand, direct land-use effects could dominate through factors such as pesticide application imposing direct toxic effects on invertebrates and microorganisms in intensively managed plantations (Fig. 1a). In contrast, cascading effects could prevail for consumers that may be more strongly impacted by the depletion of their resources (Fig. 1b), but these effects could also conjointly impact various trophic levels. Identifying and understanding these direct and cascading processes could improve the efficiency of conservation and management efforts in tropical land-use systems by allowing practitioners to target taxa whose manipulation might have especially broad impacts on many other important taxa, such as those that are of conservation concern or that provide important ecosystem services.

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Fig. 1: How land-use change may directly and indirectly alter whole ecosystems.
Fig. 2: Path model of direct and cascading land-use effects in a tropical multi-trophic system.
Fig. 3: Summary of land-use effects on diversity and biomass of interacting taxa.
Fig. 4: Example of the d-sep procedure used to construct the multilevel path models.

References

  1. Laurance, W. F., Sayer, J. & Cassman, K. G. Agricultural expansion and its impacts on tropical nature. Trends Ecol. Evol. 29, 107–116 (2014).

    Article  PubMed  Google Scholar 

  2. Foley, J. A. et al. Global consequences of land use. Science 309, 570–574 (2005).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  4. Basset, Y. et al. Arthropod diversity in a tropical forest. Science 338, 1481–1484 (2012).

    Article  CAS  PubMed  Google Scholar 

  5. Wilcove, D. S., Giam, X., Edwards, D. P., Fisher, B. & Koh, L. P. Navjot’s nightmare revisited: logging, agriculture, and biodiversity in Southeast Asia. Trends Ecol. Evol. 28, 531–540 (2013).

    Article  PubMed  Google Scholar 

  6. Fitzherbert, E. B. et al. How will oil palm expansion affect biodiversity? Trends Ecol. Evol. 23, 538–545 (2008).

    Article  PubMed  Google Scholar 

  7. Li, H., Aide, T. M., Ma, Y., Liu, W. & Cao, M. Demand for rubber is causing the loss of high diversity rain forest in SW China. Biodivers. Conserv. 16, 1731–1745 (2007).

    Article  Google Scholar 

  8. Barnes, A. D. et al. Consequences of tropical land use for multitrophic biodiversity and ecosystem functioning. Nat. Commun. 5, 5351 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Gibson, L. et al. Primary forests are irreplaceable for sustaining tropical biodiversity. Nature 478, 378–381 (2011).

    Article  CAS  PubMed  Google Scholar 

  10. Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363 (2008).

    Article  PubMed  Google Scholar 

  11. Tscharntke, T. et al. Landscape moderation of biodiversity patterns and processes - eight hypotheses. Biol. Rev. 87, 661–685 (2012).

    Article  PubMed  Google Scholar 

  12. Gardner, T. A. et al. Prospects for tropical forest biodiversity in a human-modified world. Ecol. Lett. 12, 561–582 (2009).

    Article  PubMed  Google Scholar 

  13. Denno, R. F. et al. Bottom-up forces mediate natural-enemy impact in a phytophagous insect community. Ecology 83, 1443–1458 (2002).

    Article  Google Scholar 

  14. Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556 (2010).

    Article  CAS  PubMed  Google Scholar 

  15. Borer, E. T., Seabloom, E. W., Tilman, D. & Novotny, V. Plant diversity controls arthropod biomass and temporal stability. Ecol. Lett. 15, 1457–1464 (2012).

    Article  PubMed  Google Scholar 

  16. Wootton, J. T. The nature and consequences of indirect effects in ecological communities. Annu. Rev. Ecol. Syst. 25, 443–466 (1994).

    Article  Google Scholar 

  17. Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge Univ. Press, New York, 2006).

  18. Shipley, B. Confirmatory path analysis in a generalized multilevel context. Ecology 90, 363–368 (2009).

    Article  PubMed  Google Scholar 

  19. Allen, K., Corre, M. D., Tjoa, A. & Veldkamp, E. Soil nitrogen-cycling responses to conversion of lowland forests to oil palm and rubber plantations in Sumatra, Indonesia. PLoS ONE 10, e0133325 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Hautier, Y., Niklaus, P. A. & Hector, A. Competition for light causes plant biodiversity loss after eutrophication. Science 324, 636–638 (2009).

    Article  CAS  PubMed  Google Scholar 

  21. Tripathi, B. M. et al. Tropical soil bacterial communities in Malaysia: pH dominates in the equatorial tropics too. Microb. Ecol. 64, 474–484 (2012).

    Article  PubMed  Google Scholar 

  22. Schneider, D. et al. Impact of lowland rainforest transformation on diversity and composition of soil prokaryotic communities in Sumatra (Indonesia). Front. Microbiol. 6, 1–12 (2015).

    Article  Google Scholar 

  23. Krashevska, V., Klarner, B., Widyastuti, R., Maraun, M. & Scheu, S. Impact of tropical lowland rainforest conversion into rubber and oil palm plantations on soil microbial communities. Biol. Fert. Soils 51, 697–705 (2015).

    Article  CAS  Google Scholar 

  24. Lange, M. et al. Plant diversity increases soil microbial activity and soil carbon storage. Nat. Commun. 6, 6707 (2015).

    Article  CAS  PubMed  Google Scholar 

  25. Zak, D. R., Holmes, W. E., White, D. C., Peacock, A. D. & Tilman, D. Plant diversity, soil microbial communities, and ecosystem function: are there any links? Ecology 84, 2042–2050 (2003).

    Article  Google Scholar 

  26. Ewers, R. M. & Didham, R. K. Confounding factors in the detection of species responses to habitat fragmentation. Biol. Rev. 81, 117–142 (2006).

    Article  PubMed  Google Scholar 

  27. Rand, T. A., Tylianakis, J. M. & Tscharntke, T. Spillover edge effects: the dispersal of agriculturally subsidized insect natural enemies into adjacent natural habitats. Ecol. Lett. 9, 603–614 (2006).

    Article  PubMed  Google Scholar 

  28. Degens, B. P., Schipper, L. A., Sparling, G. P. & Duncan, L. C. Is the microbial community in a soil with reduced catabolic diversity less resistant to stress or disturbance? Soil Biol. Biochem. 33, 1143–1153 (2001).

    Article  CAS  Google Scholar 

  29. Wilson, E. O. & Hölldobler, B. Eusociality: origin and consequences. Proc. Natl Acad. Sci. USA 102, 13367–13371 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Hill, J. K. & Hamer, K. C. Determining impacts of habitat modification on diversity of tropical forest fauna: the importance of spatial scale. J. Appl. Ecol. 41, 744–754 (2004).

    Article  Google Scholar 

  31. Mumme, S., Jochum, M., Brose, U., Haneda, N. F. & Barnes, A. D. Functional diversity and stability of litter-invertebrate communities following land-use change in Sumatra, Indonesia. Biol. Conserv. 191, 750–758 (2015).

    Article  Google Scholar 

  32. Digel, C., Curtsdotter, A., Riede, J. O., Klarner, B. & Brose, U. Unravelling the complex structure of forest soil food webs: higher omnivory and more trophic levels. Oikos 123, 1157–1172 (2014).

    Article  Google Scholar 

  33. Vijay, V., Pimm, S. L., Jenkins, C. N. & Smith, S. J. The impacts of oil palm on recent deforestation and biodiversity loss. PLoS ONE 11, e0159668 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Margono, B., Potapov, P., Turubanova, S., Stolle, F. & Hansen, M. C. Primary forest cover loss in Indonesia over 2000–2012. Nat. Clim. Change 4, 730–735 (2014).

    Article  Google Scholar 

  35. IUSS Working Group WRB World Reference Base for Soil Resources 2006 - A Framework for International Classification, Correlation and Communication (Food and Agriculture Organization of the United Nations, Rome, 2006).

  36. Soil Survey Staff. Keys to Soil Taxonomy, 12th ed. (USDA-Natural Resources Conservation Service, Washington DC, 2014). 

  37. Allen, K., Corre, M. D., Kurniawan, S., Utami, S. R. & Veldkamp, E. Spatial variability surpasses land-use change effects on soil biochemical properties of converted lowland landscapes in Sumatra, Indonesia. Geoderma 284, 42–50 (2016).

    Article  CAS  Google Scholar 

  38. Lewis, S. L. et al. Concerted changes in tropical forest structure and dynamics: evidence from 50 South American long-term plots. Phil. Trans. R. Soc. Lond. B 359, 421–436 (2004).

    Article  CAS  Google Scholar 

  39. Drescher, J. et al. Ecological and socio-economic functions across tropical land use systems after rainforest conversion. Phil. Trans. R. Soc. B 371, 20150275 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Gee, G. & Bauder, J. in Methods of Soil Analysis, Part 1 (ed. Klute, A.) 383–411 (Soil Science Society of America, Madison, WI, 1986).

  41. Blake, G. & Hartge, K. in Methods of Soil Analysis, Part 1 (ed. Klute, A.) 363–375 (Soil Science Society of America, Madison, WI, 1986).

  42. Chave, J. et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145, 87–99 (2005).

    Article  CAS  PubMed  Google Scholar 

  43. Wauters, J. B., Coudert, S., Grallien, E., Jonard, M. & Ponette, Q. Carbon stock in rubber tree plantations in western Ghana and Mato Grosso (Brazil). Forest Ecol. Manag. 255, 2347–2361 (2008).

    Article  Google Scholar 

  44. Asari, N., Suratman, M. N., Jaafar, J. & Khalid, M. M. Estimation of above ground biomass for oil palm plantations using allometric equations. Int. Proc. Chem. Biol. Environ. Eng. 58, 110–114 (2013).

    Google Scholar 

  45. Schnitzer, S. A., DeWalt, S. J. & Chave, J. Censusing and measuring lianas: a quantitative comparison of the common methods. Biotropica 38, 581–591 (2006).

    Article  Google Scholar 

  46. Niiyama, K. et al. Estimation of root biomass based on excavation of individual root systems in a primary dipterocarp forest in Pasoh Forest Reserve, Peninsular Malaysia. J. Trop. Ecol. 26, 271–284 (2010).

    Article  Google Scholar 

  47. Syahrinudin The Potential of Oil Palm and Forest Plantations for Carbon Sequestration on Degraded Land in Indonesia (ed. Vlek, P. L. G.) (Ecology and Development Series No. 28, Cuvillier Verlag, Goettingen, 2005).

  48. Grove, S. J. Extent and composition of dead wood in Australian lowland tropical rainforest with different management histories. Forest Ecol. Manag. 154, 35–53 (2001).

    Article  Google Scholar 

  49. Kauffman, J. B. & Donato, D. Protocols for the Measurement, Monitoring and Reporting of Structure, Biomass and Carbon Stocks in Mangrove Forests (Center for International Forestry Research (CIFOR), Bogor, 2012).

    Google Scholar 

  50. Brookes, P. C., Landman, A., Pruden, G. & Jenkinson, D. S. Chloroform fumigation and the release of soil nitrogen: a rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842 (1985).

    Article  CAS  Google Scholar 

  51. Davidson, E. A., Eckert, R. W., Hart, S. C. & Firestone, M. K. Direct extraction of microbial biomass nitrogen from forest and grassland soils of California. Soil Biol. Biochem. 21, 773–778 (1989).

    Article  Google Scholar 

  52. Schneider, D., Arp, G., Reimer, A., Reitner, J. & Daniel, R. Phylogenetic analysis of a microbialite-forming microbial mat from a hypersaline lake of the Kiritimati Atoll, central Pacific. PLoS ONE 8, e66662 (2013).

  53. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Bragg, L., Stone, G., Imelfort, M., Hugenholtz, P. & Tyson, G. W. Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat. Methods 9, 425–426 (2012).

    Article  CAS  PubMed  Google Scholar 

  55. Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Larsen, N. et al. The ribosomal database project. Nucleic Acids Res. 21, 3021–3023 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).

  58. Wielgoss, A., Tscharntke, T., Buchori, D., Fiala, B. & Clough, Y. Temperature and a dominant dolichoderine ant species affect ant diversity in Indonesian cacao plantations. Agr. Ecosyst. Environ. 135, 253–259 (2010).

    Article  Google Scholar 

  59. Fayle, T. M., Yusah, K. M. & Hashimoto, Y. Key to the Ant Genera of Borneo in English and Malay (2014); http://www.tomfayle.com/Key%20to%20the%20ant%20genera%20of%20Borneo%20v1%20(English-Malay).pdf

  60. Gowing, G. & Recher, H. F. Length–weight relationships for invertebrates from forests in south-eastern New South Wales. Aust. J. Ecol. 9, 5–8 (1984).

    Article  Google Scholar 

  61. Wilman, H. et al. EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals. Ecology 95, 2027 (2014).

    Article  Google Scholar 

  62. R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2015).

  63. Swaine, M. D. Rainfall and soil fertility as factors limiting forest species distributions in Ghana. J. Ecol. 84, 419–428 (1996).

    Article  Google Scholar 

  64. Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).

    Article  Google Scholar 

  65. Chapin, F. S. III et al. Consequences of changing biodiversity. Nature 405, 234–242 (2000).

    Article  CAS  PubMed  Google Scholar 

  66. Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R 2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).

    Article  Google Scholar 

  67. Olobatuyi, M. E. A User’s Guide to Path Analysis (University Press of America, Lanham, MD, 2006).

  68. Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).

    Article  Google Scholar 

  69. Byrne, B. M. Structural Equation Modeling with AMOS: Basic Concepts, Applications and Programming (Taylor and Francis, New York, 2012).

Download references

Acknowledgements

We thank R. K. Didham, J. S. Powers and C. Scherber for providing helpful comments and suggestions. We acknowledge the village leaders, local landowners, PT REKI and Bukit Duabelas National Park for granting us access and use of their properties, and thank our permit granting bodies, the Indonesian Institute of Sciences (LIPI) and the Ministry of Forestry (PHKA). We also thank our field and laboratory assistants, the rangers within the protected forest areas for assistance in the field, and D. Gunawan from the Meteorological, Climatological and Geophysical Agency of Indonesia for climate data. This study was financed by the German Research Foundation (DFG) in the framework of the collaborative German-Indonesian research project EFForTS, the Ministry of Science and Culture of Lower Saxony within the framework of the BEFmate project, an FCS Swiss Government Scholarship, an Indonesian Directorate General of Higher Education scholarship, and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig funded by the German Research Foundation (FZT 118).

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Author notes

  1. Andrew D. Barnes and Kara Allen contributed equally to this work.

Authors and Affiliations

  1. Systemic Conservation Biology, University of Goettingen, Berliner Str. 28, 37073, Goettingen, Germany

    Andrew D. Barnes, Malte Jochum & Ulrich Brose

  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103, Leipzig, Germany

    Andrew D. Barnes & Ulrich Brose

  3. Institute of Biology, Leipzig University, Johannisallee 21, 04103, Leipzig, Germany

    Andrew D. Barnes

  4. Soil Science of Tropical and Subtropical Ecosystems, University of Goettingen, Büsgen Institute, Büsgenweg 2, 37077, Goettingen, Germany

    Kara Allen, Marife D. Corre, Edzo Veldkamp & Syahrul Kurniawan

  5. Department of Ecology, Evolution, and Behavior, University of Minnesota, 306 Ecology, 1987 Upper Buford Circle, St. Paul, MN, 55108, USA

    Kara Allen

  6. Biodiversity, Macroecology & Biogeography, University of Goettingen, Büsgenweg 1, 37077, Goettingen, Germany

    Holger Kreft & Katja Rembold

  7. Institute of Plant Sciences, University of Bern, Altenbergrain 21, 3013, Bern, Switzerland

    Malte Jochum

  8. Department of Crop Sciences, Agroecology, University of Goettingen, Grisebachstr. 6, 37077, Goettingen, Germany

    Yann Clough, Kevin Darras, Lisa H. Denmead & Teja Tscharntke

  9. Centre for Environmental and Climate Research, Lund University, Sölvegatan 37, 22362, Lund, Sweden

    Yann Clough

  10. Department of Genomic and Applied Microbiology & Goettingen Genomics Laboratory, Institute of Microbiology and Genetics, University of Goettingen, Grisebachstr. 8, 37077, Goettingen, Germany

    Rolf Daniel & Dominik Schneider

  11. Marine and Environmental Management, School of Applied Sciences, Toi Ohomai Institute of Technology, 70 Windermere Drive, 3112, Tauranga, New Zealand

    Lisa H. Denmead

  12. Department of Silviculture, Faculty of Forestry, Bogor Agricultural University, Darmaga Campus, 16680, Bogor, Indonesia

    Noor Farikhah Haneda

  13. Department of Plant Ecology and Ecosystems Research, University of Goettingen, Untere Karspüle 2, 37073, Goettingen, Germany

    Dietrich Hertel & Martyna M. Kotowska

  14. Bioclimatology, University of Goettingen, Büsgenweg 2, 37077, Goettingen, Germany

    Alexander Knohl & Ana Meijide

  15. Department of Soil Science, Faculty of Agriculture, Brawijaya University, Malang, Indonesia

    Syahrul Kurniawan

  16. Conservation Biology Division, Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, CH-3012, Bern, Switzerland

    Walesa Edho Prabowo

  17. Institute of Ecology, Friedrich Schiller University Jena, Dornburger-Str. 159, 07743, Jena, Germany

    Ulrich Brose

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  1. Andrew D. Barnes
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Contributions

K.A., A.D.B. and U.B. designed the study; K.A., A.D.B., M.J., K.D., L.H.D., M.M.K., S.K., A.M., K.R., W.E.P. and D.S. collected the data; K.A. and A.D.B. analysed the data; all authors contributed to the writing of the manuscript.

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Correspondence to Andrew D. Barnes.

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Barnes, A.D., Allen, K., Kreft, H. et al. Direct and cascading impacts of tropical land-use change on multi-trophic biodiversity. Nat Ecol Evol 1, 1511–1519 (2017). https://doi.org/10.1038/s41559-017-0275-7

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