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Biodiversity and Conservation

, Volume 27, Issue 2, pp 273–285 | Cite as

A review of ecological gradient research in the Tropics: identifying research gaps, future directions, and conservation priorities

  • Jannes Muenchow
  • Petra Dieker
  • Jürgen Kluge
  • Michael Kessler
  • Henrik von Wehrden
Review Paper
  • 581 Downloads

Abstract

The Tropics are global centers of biodiversity. Ecological and land use gradients play a major role in the origin and maintenance of this diversity, yet a comprehensive synthesis of the corresponding large body of literature is still missing. We searched all ISI-listed journals for tropical gradient studies. From the resulting 1023 studies, we extracted study-specific information, and analyzed it using descriptive analytical tools and GLMs. Our results reveal that dry tropical areas are vastly understudied compared to their humid counterparts. The same holds true for large parts of Africa, but also the Philippines and the South Asian region. However, we also found that (applied) research output of developing tropical countries is nowadays on par with the output of developed countries. Vegetation and elevation were the most studied response variable and gradient, respectively. By contrast, inconspicous organisms such as oribatid mites and edaphic gradients were largely missing in the literature. Regarding biodiversity, tropical gradient studies dealt extensively with species richness and ecosystem diversity, but much less with genetic diversity. We encourage a wider use of modern statistical learning tools such as non-linear (spatio-temporal) regression and classification techniques, and simulations. Finally, we would embrace an even further development of synergies between applied and basic research and between researchers based in developed and in tropical countries.

Keywords

Synthesis Tropical ecology Environmental gradient relationships Biodiversity 

Notes

Acknowledgements

We would like to thank all tropical gradient reseachers whose work provided the basis of the present work. Furthermore, we are most grateful to the Deutsche Forschungsgemeinschaft (Project Ri 370/19-1) for partly funding this work.

Supplementary material

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Supplementary material 1 (DOCX 119 kb)
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Supplementary material 2 (DOCX 35 kb)
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Supplementary material 3 (DOCX 150 kb)

References

  1. Baddeley A, Turner R (2005) Spatstat: an R package for analyzing spatial point patterns. J Stat Softw 12:1–42CrossRefGoogle Scholar
  2. Blangiardo M, Cameletti M (2015) Spatial and spatio-temporal Bayesian models with R-INLA. Wiley, ChichesterCrossRefGoogle Scholar
  3. Brown JH (2014) Why are there so many species in the tropics? J Biogeogr 41:8–22.  https://doi.org/10.1111/jbi.12228 CrossRefPubMedGoogle Scholar
  4. CIA (2016) Central Intelligence Unit. https://www.cia.gov/library/publications/the-world-factbook/geos/ve.html. Accessed 17 Sep 2016
  5. Colwell RK (1997) EstimateS: statistical estimation of species richness and shared species from samples. http://viceroy.eeb.uconn.edu/estimates/. Accessed 31 July 2013
  6. de la Harpe M, Paris M, Karger D, Rolland J, Kessler M, Salamin N, Lexer C (2017) Molecular ecology studies of species radiations: current research gaps, opportunities, and challenges. Mol Ecol 26:2608–2622CrossRefPubMedGoogle Scholar
  7. Diggle P (1985) A Kernel-method for smoothing point process data. Appl Stat 34:138–147.  https://doi.org/10.2307/2347366 CrossRefGoogle Scholar
  8. Dirzo R, Raven PH (2003) Global state of biodiversity and loss. Annu Rev Environ Resour 28:137–167.  https://doi.org/10.1146/annurev.energy.28.050302.105532 CrossRefGoogle Scholar
  9. Dormann CF (2011) How to be a specialist? Quantifying specialisation in pollination networks. Netw Biol 1:1–20Google Scholar
  10. Feeley KJ, Malhi Y, Zelazowski P, Silman MR (2012) The relative importance of deforestation, precipitation change, and temperature sensitivity in determining the future distributions and diversity of Amazonian plant species. Glob Change Biol 18:2636–2647.  https://doi.org/10.1111/j.1365-2486.2012.02719.x CrossRefGoogle Scholar
  11. Feilhauer H, Faude U, Schmidtlein S (2011) Combining Isomap ordination and imaging spectroscopy to map continuous floristic gradients in a heterogeneous landscape. Remote Sens Environ 115:2513–2524CrossRefGoogle Scholar
  12. Groombridge B (1992) Global biodiversity: status of the Earth’s living resources. Chapman & Hall, LondonCrossRefGoogle Scholar
  13. Harding S, McComiskie R, Wolff M, Trewin D, Hunter S (2014) State of the tropics 2014 report. James Cook University, CairnsGoogle Scholar
  14. Holmgren M, Schnitzer SA (2004) Science on the rise in developing countries. PLoS Biol 2:10–13.  https://doi.org/10.1371/journal.pbio.0020001 CrossRefGoogle Scholar
  15. Illig J, Norton RA, Scheu S, Maraun M (2010) Density and community structure of soil- and bark-dwelling microarthropods along an altitudinal gradient in a tropical montane rainforest. Exp Appl Acarol 52:49–62.  https://doi.org/10.1007/s10493-010-9348-x CrossRefPubMedPubMedCentralGoogle Scholar
  16. IUCN (2016) International Union for Conservation of Nature and Natural Resources (IUCN) Red List of Threatened Species. Summary statistics for globally threatened species. Table 1: numbers of threatened species by major groups of organisms (1996–2016). http://www.iucnredlist.org/about. Accessed 17 Sep 2016
  17. James G, Witten D, Hastie T, Tibshirani R (2013) An introduction to statistical learning, vol 6. Springer, New YorkCrossRefGoogle Scholar
  18. Janzen DH (1988) Tropical dry forest: the most endangered tropical ecosystem. In: Wilson EO (ed) Biodiversity. National Academy Press, Washington, DC, pp 130–137Google Scholar
  19. Kreft H, Jetz W (2013) Comment on “an update of wallace’s zoogeographic regions of the world”. Science.  https://doi.org/10.1126/science.1237471 PubMedGoogle Scholar
  20. Krupnick GA (2013) Conservation of tropical plant biodiversity: what have we done, where are we going? Biotropica 45:693–708.  https://doi.org/10.1111/Btp.12064 CrossRefGoogle Scholar
  21. Lewis SL, Edwards DP, Galbraith D (2015) Increasing human dominance of tropical forests. Science 349:827–832.  https://doi.org/10.1126/science.aaa9932 CrossRefPubMedGoogle Scholar
  22. MacArthur RH (1984) Geographical ecology: patterns in the distribution of species. Princeton University Press, PrincetonGoogle Scholar
  23. Malhado ACM et al (2014) Geographic and temporal trends in Amazonian knowledge production. Biotropica 46:6–13.  https://doi.org/10.1111/Btp.12079 CrossRefGoogle Scholar
  24. Meyer D, Zeileis A, Hornik K (2006) The strucplot framework: visualizing multi-way contingency tables with vcd. J Stat Softw 17:1–48CrossRefGoogle Scholar
  25. Miles L et al (2006) A global overview of the conservation status of tropical dry forests. J Biogeogr 33:491–505.  https://doi.org/10.1111/j.1365-2699.2005.01424.x CrossRefGoogle Scholar
  26. Muenchow J, Feilhauer H, Bräuning A, Rodríguez EF, Bayer F, Rodríguez RA, von Wehrden H (2013a) Coupling ordination techniques and GAM to spatially predict vegetation assemblages along a climatic gradient in an ENSO-affected region of extremely high climate variability. J Veg Sci 24:1154–1166.  https://doi.org/10.1111/jvs.12038 CrossRefGoogle Scholar
  27. Muenchow J, Hauenstein S, Bräuning A, Bäumler R, Rodríguez EF, von Wehrden H (2013b) Soil texture and altitude, respectively, widely determine the floristic gradient of the most diverse fog oasis in the Peruvian desert. J Trop Ecol 29:427–438.  https://doi.org/10.1017/S0266467413000436 CrossRefGoogle Scholar
  28. Muenchow J, von Wehrden H, Rodríguez EF, Rodríguez RA, Bayer F, Richter M (2013c) Woody vegetation of a Peruvian tropical dry forest along a climatic gradient depends more on soil than annual precipitation. Erdkunde 64:241–248.  https://doi.org/10.3112/erdkunde.2013.03.03 CrossRefGoogle Scholar
  29. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858CrossRefPubMedGoogle Scholar
  30. Pitman NCA, Widmer J, Jenkins CN, Stocks G, Seales L, Paniagua F, Bruna EM (2011) Volume and geographical distribution of ecological research in the Andes and the Amazon, 1995-2008. Trop Conserv Sci 4:64–81CrossRefGoogle Scholar
  31. PPG I (2016) A community-derived classification for extant lycophytes and ferns. J Syst Evol 54(6):563–603Google Scholar
  32. R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  33. Rahbek C (2005) The role of spatial scale and the perception of large-scale species-richness patterns. Ecol Lett 8:224–239CrossRefGoogle Scholar
  34. Richter M, Diertl KH, Emck P, Peters T, Beck E (2009) Reasons for an outstanding plant diversity in the tropical Andes of Southern Ecuador. Landsc Online 12:1–35Google Scholar
  35. Rubel F, Kottek M (2010) Observed and projected climate shifts 1901–2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorol Z 19:135–141CrossRefGoogle Scholar
  36. Sánchez-Azofeifa GA et al (2005) Research priorities for neotropical dry forests. Biotropica 37:477–485.  https://doi.org/10.1111/j.1744-7429.2005.00066.x Google Scholar
  37. Scheller RM, Mladenoff DJ (2007) An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems. Landsc Ecol 22:491–505.  https://doi.org/10.1007/s10980-006-9048-4 CrossRefGoogle Scholar
  38. Stocks G, Seales L, Paniagua F, Maehr E, Bruna EM (2008) The geographical and institutional distribution of ecological research in the tropics. Biotropica 40:397–404.  https://doi.org/10.1111/j.1744-7429.2007.00393.x CrossRefGoogle Scholar
  39. The Plant List (2013) A working list of all plant species. http://www.theplantlist.org/. Accessed 17 Sep 2016
  40. Tonkin JD, Arimoro FO, Haase P (2016) Exploring stream communities in a tropical biodiversity hotspot: biodiversity, regional occupancy, niche characteristics and environmental correlates. Biodivers Conserv 25:975–993.  https://doi.org/10.1007/s10531-016-1101-2 CrossRefGoogle Scholar
  41. UNDP (2016) United Nations Development Programme. Human development reports. http://hdr.undp.org/en/countries/. Accessed 17 Sep 2016
  42. von Humboldt A (1807) Idee zu einer Geographie der Pflanzen. Wissenschaftliche Buchgesellschaft, DarmstadtGoogle Scholar
  43. von Wehrden H, Hanspach J, Bruelheide H, Wesche K (2009) Pluralism and diversity: trends in the use and application of ordination methods 1990-2007. J Veg Sci 20:695–705CrossRefGoogle Scholar
  44. Whittaker RH (1967) Gradient analysis of vegetation. Biol Rev 42:207–264CrossRefPubMedGoogle Scholar
  45. Willig MR, Presley SJ (2016) Biodiversity and metacommunity structure of animals along altitudinal gradients in tropical montane forests. J Trop Ecol 32:421–436.  https://doi.org/10.1017/s0266467415000589 CrossRefGoogle Scholar
  46. Worldbank (2016) The Worldbank. Working for a world free of poverty. http://www.worldbank.org/. Accessed 17 Sep 2016
  47. Yang J, Weisberg PJ, Bristow NA (2012) Landsat remote sensing approaches for monitoring long-term tree cover dynamics in semi-arid woodlands: comparison of vegetation indices and spectral mixture analysis. Remote Sens Environ 119:62–71.  https://doi.org/10.1016/j.rse.2011.12.004 CrossRefGoogle Scholar
  48. Zuur AF, Ieno EN, Walker N, Saveliev AA, Smith GM (2009) Mixed effects models and extensions in ecology with R. Statistics for biology and health. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Institute of Geography, Friedrich Schiller University JenaJenaGermany
  2. 2.Institute of Ecology, Friedrich Schiller University JenaJenaGermany
  3. 3.Institute of GeographyPhilipps-Universität MarburgMarburgGermany
  4. 4.Institute of Systematic and Evolutionary BotanyUniversity of ZurichZurichSwitzerland
  5. 5.Institute of Ecology, Faculty of Sustainability and Center for MethodsLeuphana UniversityLüneburgGermany

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