Skip to main content

Advertisement

Log in

Linking Landscape Ecology and Macroecology by Scaling Biodiversity in Space and Time

  • Spatial Scale-Measurement, Influence, and Integration (A Martin and J Holland, Section Editors)
  • Published:
Current Landscape Ecology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Despite the decades-long recognition of the importance of scaling in ecology, our knowledge about many ecological patterns and processes is still largely restricted to particular spatial and temporal scale domains with relatively narrow ranges. There is no exception when it comes to the study of biodiversity, one of the most important and active research fields in ecology. Increasing work suggests that such narrow ranges of scales are in most cases inadequate for addressing conservation challenges associated with biodiversity change. The need for understanding how biodiversity is shaped and will change across different scales is stronger than ever.

Recent Findings

Here, we review recent progresses of up-scaling and down-scaling biodiversity in the context of global environmental change, with focus on two relatively large spatial scale domains, i.e., the landscape and macroecological scales. Landscape ecology and macroecology are both active, but so-far poorly connected research fields. They share a common central motivation of unraveling spatial patterning of biodiversity and the underlying mechanisms. Our literature review suggests that landscape-scale processes may exert unexpected up-scaling effects to shape biodiversity patterns at macroecological scales, while macroecological processes may generate a range of down-scaling effects on landscape biodiversity. Specifically, although there is a lack of consensus on the underlying mechanisms, it is likely that landscape processes scale up through connectivity and feedback loops within and across landscapes to affect macroecological biodiversity responses. On the other hand, the down-scaling effects of macroecological processes on biodiversity is often confounded with small-scale processes, leading to various responses inconsistent with direct down-scaling extrapolations. In addition, the temporal dimension is indispensable to investigating effects and mechanisms of cross-scale processes. Specifically, long-term (decades and beyond) perspectives are necessary for re-evaluating ecological knowledge obtained from biodiversity responses to short-term environmental changes and recognizing historical legacies of both landscape and macroecological processes on biodiversity at the two spatial scales.

Summary

Overall, scaling analyses of ecological processes across spatial extents ranging from small habitats to the globe have revealed biodiversity responses to anthropogenic environmental changes as inconsistent with assumptions and extrapolations based on extant ecological knowledge at a few fixed scales. Such analyses are needed to better inform conservation actions and planning practiced mainly at local to macroecological scales. We suggest that elucidating cross-scaling mechanisms and accumulating long-term time series at multiple spatial scales are key to linking landscape ecology and macroecology in terms of biodiversity dynamics. Such efforts would be an important contribution to the ecological basis for managing biodiversity change in the Anthropocene, as these dynamics involve multiple up-scaling and down-scaling processes over time.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Tilman D, Isbell F, Cowles JM. Biodiversity and ecosystem functioning. Annu Rev Ecol Evol Syst. 2014;45:471–93.

    Google Scholar 

  2. Cardinale BJ, et al. Biodiversity loss and its impact on humanity. Nature. 2012;486(7401):59–67.

    CAS  PubMed  Google Scholar 

  3. Ceballos G, et al. Accelerated modern human-induced species losses: entering the sixth mass extinction. Sci Adv. 2015;1(5):e1400253.

    PubMed  PubMed Central  Google Scholar 

  4. Hulme PE. Trade, transport and trouble: managing invasive species pathways in an era of globalization. J Appl Ecol. 2009;46(1):10–8.

    Google Scholar 

  5. Seebens H, et al. No saturation in the accumulation of alien species worldwide. Nat Commun. 2017;8:14435.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Chapin FS, et al. Consequences of changing biodiversity. Nature. 2001;405(6783):234–42.

    Google Scholar 

  7. Martin J-L, Maris V, Simberloff DS. The need to respect nature and its limits challenges society and conservation science. Proceedings of the National Academy of Sciences USA. 2016;113(22):6105–12.

    CAS  Google Scholar 

  8. •• Isbell F, et al. Linking the influence and dependence of people on biodiversity across scales. Nature. 2017;546(7656):65–72. The authors present a review of recent progress in terms of multiscale relationships between human activities, biodiversity, ecosystem functioning, and ecosystem services. They show that small-scale human-driven biodiversity loss can produce cascading impacts on ecosystem functioning and services at larger scales through temporal and spatial insurance effects. They propose four complementary approaches that integrate small-scale experimental and large-scale observational studies to inform both landscape management and biosphere sustainability.

  9. Cardinale BJ, et al. The functional role of producer diversity in ecosystems. Am J Bot. 2011;98(3):572–92.

    PubMed  Google Scholar 

  10. Wang S, Loreau M. Biodiversity and ecosystem stability across scales in metacommunities. Ecol Lett. 2016;19(5):510–8.

    PubMed  PubMed Central  Google Scholar 

  11. O’Connor MI, et al. A general biodiversity-function relationship is mediated by trophic level. Oikos. 2017;126(1):18–31.

    Google Scholar 

  12. Nelson E, et al. Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales. Front Ecol Environ. 2009;7(1):4–11.

    Google Scholar 

  13. Greve M, et al. Spatial optimization of carbon-stocking projects across Africa integrating stocking potential with co-benefits and feasibility. Nat Commun. 2013;4:2975.

    PubMed  Google Scholar 

  14. Girardello M, et al. Global synergies and trade-offs between multiple dimensions of biodiversity and ecosystem services. Sci Rep. 2019;9(1):5636.

    PubMed  PubMed Central  Google Scholar 

  15. Newbold T, et al. Global effects of land use on local terrestrial biodiversity. Nature. 2015;520(7545):45–50.

    CAS  PubMed  Google Scholar 

  16. Haddad NM, et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci Adv. 2015;1(2):e1500052.

    PubMed  PubMed Central  Google Scholar 

  17. Wiens JA. Spatial scaling in ecology. Funct Ecol. 1989;3(4):385–97.

    Google Scholar 

  18. Levin SA. The problem of pattern and scale in ecology. Ecology. 1992;73(6):1943–67.

    Google Scholar 

  19. Connolly SR, et al. Process, mechanism, and modeling in macroecology. Trends in Ecology and Evolution. 2017;32(11):835–44.

    PubMed  Google Scholar 

  20. O’Neill RV. Transmutations across hierarchical levels. In: Innis GS, O’Neill RV, editors. Systems Analysis of Ecosystems. Elsevier; 1979. p. 59–78.

  21. Rastetter EB, et al. Aggregating fine-scale ecological knowledge to model coarser-scale attributes of ecosystems. Ecol Appl. 1992;2(1):55–70.

    PubMed  Google Scholar 

  22. Englund G, Cooper SD. Scale effects and extrapolation in ecological experiments. Adv Ecol Res. 2003;22:161–213.

    Google Scholar 

  23. • McGill BJ. The what, how and why of doing macroecology. Glob Ecol Biogeogr 2019;28(1):6–17. By discussing two main competing definitions of macroecology, the author identified their common ground as the need for an emergent approach. The author proposes an alternative definition as the study of what the emergent properties of large numbers of ecological entities are and how such properties arise from small-scale processes.

  24. Gaston KJ, Blackburn TM. A critique for macroecology. Oikos. 1999;84(3):353–68.

    Google Scholar 

  25. Estes L, et al. The spatial and temporal domains of modern ecology. Nature Ecology and Evolution. 2018;2(5):819–26.

    PubMed  Google Scholar 

  26. Fahrig L. Effects of habitat fragmentation on biodiversity. Annu Rev Ecol Evol Syst. 2003;34:487–515.

    Google Scholar 

  27. Fahrig L. Ecological responses to habitat fragmentation per se. Annu Rev Ecol Evol Syst. 2017;48:1–23.

    Google Scholar 

  28. Haddad NM, et al. Experimental evidence does not support the habitat amount hypothesis. Ecography. 2017;40(1):48–55.

    Google Scholar 

  29. Fahrig L. Rethinking patch size and isolation effects: the habitat amount hypothesis. J Biogeogr. 2013;40(9):1649–63.

    Google Scholar 

  30. Fletcher RJ, et al. Is habitat fragmentation good for biodiversity? Biol Conserv. 2018;226:9–15.

    Google Scholar 

  31. Hadly AS, Betts MG. Refocusing habitat fragmentation research using lessons from the last decade. Current Landscape Ecology Reports. 2016;1(2):55–66.

    Google Scholar 

  32. Fahrig L. Habitat fragmentation: a long and tangled tale. Glob Ecol Biogeogr. 2019;28(1):33–41.

    Google Scholar 

  33. Turner MG. Landscape ecology: what is the state of the science? Annu Rev Ecol Evol Syst. 2005;36:319–44.

    Google Scholar 

  34. Wu J. Landscape ecology, cross-disciplinarity, and sustainability science. Landsc Ecol. 2006;21(1):1–4.

    CAS  Google Scholar 

  35. Peters DPC, et al. Cross-scale interactions, nonlinearities, and forecasting catastrophic events. Proceedings of the National Academy of Sciences USA. 2004;101(42):15130–5.

    CAS  Google Scholar 

  36. Peters DPC, et al. Cross-scale interactions and changing pattern-process relationships: consequences for system dynamics. Ecosystems. 2007;10(5):790–6.

    Google Scholar 

  37. Heffernan JB, et al. Macrosystems ecology: understanding ecological patterns and processes at continental scales. Front Ecol Environ. 2014;12(1):65–73.

    Google Scholar 

  38. McGill BJ. Matters of scale. Science. 2010;328(5978):575–6.

    CAS  PubMed  Google Scholar 

  39. Sax DF, Gaines SD. Species diversity: from global decreases to local increases. Trends in Ecology and Evolution. 2003;18(11):561–6.

    Google Scholar 

  40. Veech JA. A probability-based analysis of temporal and spatial co-occurrence in grassland birds. J Biogeogr. 2006;33(12):2145–53.

    Google Scholar 

  41. Russell R, et al. Scale, environment, and trophic status: the context dependency of community saturation in rocky intertidal communities. Am Nat. 2006;167(6):e158–70.

    PubMed  Google Scholar 

  42. Whittaker RJ, Willis KJ, Field R. Scale and species richness: towards a general, hierarchical theory of species diversity. J Biogeogr. 2001;28(4):453–70.

    Google Scholar 

  43. Prinzing A, et al. Geographic variability of ecological niches of plant species: are competition and stress relevant? Ecography. 2002;25(6):721–9.

    Google Scholar 

  44. Pearson RG, Dawson TP. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Glob Ecol Biogeogr. 2003;12(5):361–71.

    Google Scholar 

  45. Bullock JM, et al. Geographical separation of two Ulex species at three spatial scales: does competition limit species’ ranges? Ecography. 2000;23(2):257–71.

    Google Scholar 

  46. Bond WJ. Large parts of the world are brown or black: a different view on the “Green World” hypothesis. J Veg Sci. 2005;16(3):261–6.

    Google Scholar 

  47. Heikkinen RK, et al. Biotic interactions improve prediction of boreal bird distributions at macro-scales. Glob Ecol Biogeogr. 2007;16(6):754–63.

    Google Scholar 

  48. Gotelli NJ, Graves GR, Rahbek C. Macroecological signals of species interactions in the Danish avifauna. Proceedings of the National Academy of Sciences USA. 2010;107(11):5030–5.

    CAS  Google Scholar 

  49. Ilsøe SK, et al. Global variation in woodpecker species richness shaped by tree availability. J Biogeogr. 2017;44(8):1824–35.

    Google Scholar 

  50. Araújo MB, Rozenfeld A. The geographical scaling of biotic interactions. Ecography. 2014;37(5):406–15.

    Google Scholar 

  51. Wise MS, et al. The role of biotic interactions in shaping distributions and realized assemblages of species: implications for species distribution modelling. Biol Rev. 2013;88(1):15–30.

    Google Scholar 

  52. Araújo MB, Peterson AT. Uses and misuses of bioclimatic envelope modeling. Ecology. 2012;93(7):1527–39.

    PubMed  Google Scholar 

  53. Hoffmann WA, et al. Ecological thresholds at the savanna-forest boundary: how plant traits, resources and fire govern the distribution of tropical biomes. Ecol Lett. 2012;15(7):759–68.

    PubMed  Google Scholar 

  54. Van Nes EH, et al. Fire forbids fifty-fifty forest. PLoS One. 2018;13(1):e0191027.

    PubMed  PubMed Central  Google Scholar 

  55. Staal A, et al. Resilience of tropical tree cover: the roles of climate, fire, and herbivory. Glob Chang Biol. 2018;24(11):5096–109.

    PubMed  Google Scholar 

  56. Hanski I. Habitat connectivity, habitat continuity, and meta-populations in dynamic landscapes. Oikos. 1999;87(2):209–19.

    Google Scholar 

  57. Wiens JA, Crawford CS. Gosz JR boundary dynamics: a conceptual framework for studying landscape ecosystems. Oikos. 1985;45(3):421–7.

    Google Scholar 

  58. Saunders DA, Hobbs RJ, Margules CR. Biological consequences of ecosystem fragmentation: a review. Conserv Biol. 1991;5(1):18–32.

    Google Scholar 

  59. Murcia C. Edge effects in fragmented forests: implications for conservation. Trends in Ecology and Evolution. 1995;10(2):58–62.

    CAS  PubMed  Google Scholar 

  60. Luoto M, Virkkala R, Heikkinen RK. The role of land cover in bioclimatic models depends on spatial resolution. Glob Ecol Biogeogr. 2007;16(1):34–42.

    Google Scholar 

  61. Reino L, et al. Does local habitat fragmentation affect large-scale distributions? The case of a specialist grassland bird. Divers Distrib. 2013;19(4):423–32.

    Google Scholar 

  62. Martins IS, Proença V, Pereira HM. The unusual suspect: land use is a key predictor of biodiversity patterns in the Iberian Peninsula. Acta Oecol. 2014;61:41–50.

    Google Scholar 

  63. Morelli F, Benedetti Y, Šímová P. Landscape metrics as indicators of avian diversity and community measures. Ecol Indic. 2018;90:132–41.

    Google Scholar 

  64. Thuiller W, Araújo MB, Lavorel S. Do we need land-cover data to model species distributions in Europe? J Biogeogr. 2004;31(3):353–61.

    Google Scholar 

  65. Xu C, et al. Can local landscape attributes explain species richness patterns at macroecological scales? Glob Ecol Biogeogr. 2014;23(4):436–45.

    Google Scholar 

  66. • Qiu Y, et al. The resolution-dependent role of landscape attributes in shaping macro-scale biodiversity patterns. Global Ecology and Biogeography. 2019. https://doi.org/10.1111/geb.12889. This study shows that the power of landscape attributes for explaining species richness patterns can be comparable with that of climatic variables, decreasing with thematic and spatial resolution. This confirmed significant role of landscape processes in shaping broad-scale biodiversity patterns complements the schematic in ref. 38 by extending the bar for habitat beyond the spatial scale of 1000 km.

  67. • Boivin NL, et al. Ecological consequences of human niche construction: examining long-term anthropogenic shaping of global species distributions. Proceedings of the National Academy of Sciences USA. 2016;113(23):6388–6396. The authors provide for the community of ecologists a timely review of accumulating archaeological and paleoecological evidence that human activities at the landscape scale since the Late Pleistocene have caused profound and lasting ecological consequences across spatial scales ranging from local to global. Recognizing the long-term role of anthropogenic landscape processes in shaping the biosphere necessitates further integration of deep time data on landscape changes across broad geographical extents to inform policies that account for the spatiotemporal scaling effects of landscape transformation.

  68. Wu J, et al. The three gorges dam: an ecological perspective. Front Ecol Environ. 2004;2(5):241–8.

    Google Scholar 

  69. Pfaff A, Robalino J. Spillovers from conservation programs. Ann Rev Resour Econ. 2017;9:299–315.

    Google Scholar 

  70. Lambin EF, Meyfroidt P. Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences USA. 2011;108(9):3465–72.

    CAS  Google Scholar 

  71. Johnson CN. Ecological consequences of Late Quaternary extinctions of megafauna. Proc R Soc B. 2009;276(1667):2509–19.

    CAS  PubMed  Google Scholar 

  72. Opdam P, Luque S, Jones KB. Changing landscapes to accommodate for climate change impacts: a call for landscape ecology. Landsc Ecol. 2009;24(6):715–21.

    Google Scholar 

  73. Burnside WR, et al. Human macroecology: linking pattern and process in big-picture human ecology. Biol Rev. 2012;87(1):194–208.

    PubMed  Google Scholar 

  74. Xu C, et al. Macroecological factors explain large-scale spatial population patterns of ancient agriculturalists. Glob Ecol Biogeogr. 2015;24(9):1030–9.

    Google Scholar 

  75. Tao T, et al. Macroecological factors shape local-scale spatial patterns in agriculturalist settlements. Proc R Soc B. 2017;284(1866):20172003.

    PubMed  Google Scholar 

  76. Scheffers, B.R. The broad footprint of climate change from genes to biomes to people. Science. 2015;354(6313):aaf7671.

  77. Lenoir J, et al. Going against the flow: potential mechanisms for unexpected downslope range shifts in a warming climate. Ecography. 2010;33(2):295–303.

    Google Scholar 

  78. Gilman SE, et al. A framework for community interactions under climate change. Trends in Ecology and Evolution. 2010;25(6):325–31.

    PubMed  Google Scholar 

  79. Opdam P, Wascher D. Climate change meets habitat fragmentation: linking landscape and biogeographical scale levels in research and conservation. Biol Conserv. 2004;117(3):285–97.

    Google Scholar 

  80. Bertrand R, et al. Changes in plant community composition lag behind climate warming in lowland forests. Nature. 2011;479(7374):517–20.

    CAS  PubMed  Google Scholar 

  81. Svenning J-C, Sandel B. Disequilibrium vegetation dynamics under future climate change. Am J Bot. 2013;100(7):1266–86.

    PubMed  Google Scholar 

  82. Pausas JG, Fernández-Muñoz S. Fire regime changes in the Western Mediterranean Basin: from fuel-limited to drought-driven fire regime. Clim Chang. 2012;110(1–2):215–26.

    Google Scholar 

  83. Rehm EM, Feeley KJ. The inability of tropical cloud forest species to invade grasslands above treeline during climate change: potential explanations and consequences. Ecography. 2015;38(12):1167–75.

    Google Scholar 

  84. Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003;421(6918):37–42.

    CAS  PubMed  Google Scholar 

  85. Moeslund JE, et al. Topographically controlled soil moisture is the primary driver of local vegetation patterns across a lowland region. Ecosphere. 2013;4(7):1–26.

    Google Scholar 

  86. Tabor K, Williams JW. Globally downscaled climate projections for assessing the conservation impacts of climate change. Ecol Appl. 2010;20(2):554–65.

    PubMed  Google Scholar 

  87. Gillingham PK, et al. The effect of spatial resolution on projected responses to climate warming. Divers Distrib. 2012;18(10):990–1000.

    Google Scholar 

  88. Potter KA, et al. Microclimatic challenges in global change biology. Glob Chang Biol. 2013;19(10):2932–9.

    PubMed  Google Scholar 

  89. Randin CF, et al. Climate change and plant distribution: local models predict high-elevation persistence. Glob Chang Biol. 2009;15(6):1557–69.

    Google Scholar 

  90. Hannah L, et al. Fine-grain modeling of species’ response to climate change: holdouts, stepping-stones, and microrefugia. Trends in Ecology and Evolution. 2014;29(7):390–7.

    PubMed  Google Scholar 

  91. Zellweger F, et al. Advances in microclimate ecology arising from remote sensing. Trends in Ecology and Evolution. 2019;34(4):327–41.

    PubMed  Google Scholar 

  92. Lenoir J, et al. Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe. Glob Chang Biol. 2013;19(5):1470–81.

    PubMed  Google Scholar 

  93. •• McGill BJ, et al. Fifteen forms of biodiversity trend in the Anthropocene. Trends in Ecology and Evolution. 2015;30(2):104–113. This review investigated 15 forms of biodiversity change over time across local to global scales, with many of them underexplored including spatial and temporal beta diversity at the landscape and macroecological scales. Importantly, despite of global biodiversity loss, alpha diversity, a seemingly well-studied metric, surprisingly remain constant across local sites. The authors conclude that addressing our current knowledge gap of biodiversity change at multiple spatiotemporal scales is necessary for better understanding and management of biodiversity change in the Anthropocene.

  94. Hobbs RJ, Higgs E, Harris JA. Novel ecosystems: implications for conservation and restoration. Trends in Ecology and Evolution. 2009;24(11):599–605.

    PubMed  Google Scholar 

  95. Hector A, et al. Conservation implications of the link between biodiversity and ecosystem functioning. Oecologia. 2001;129(4):624–8.

    CAS  PubMed  Google Scholar 

  96. Hector A, Bagchi R. Biodiversity and ecosystem multifunctionality. Nature. 2007;448(7150):188–90.

    CAS  PubMed  Google Scholar 

  97. Hooper DU, et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature. 2012;486(7401):105–8.

    CAS  PubMed  Google Scholar 

  98. Srivastava DS, Vellend M. Biodivresity-ecosystem function research: is it relevant to conservation? Annu Rev Ecol Evol Syst. 2005;36:267–94.

    Google Scholar 

  99. •• Vellend M, et al. Global meta-analysis reveals no net change in local-scale plant biodiversity over time. Proceedings of the National Academy of Sciences USA. 2013;110(48):19456–19459. The study analyzed changes in local plant diversity by compiling a database of vegetation monitoring sites across the globe and found that the local diversity of plants has not declined in recent history, inconsistent with the intuitive assumption that local sites are suffering biodiversity loss as in the case at the global scale. This contrast has stimulated both empirical and theoretical studies on the relationships between biodiversity changes at small and large scales.

  100. Supp SR, Ernest SKM. Species-level and community-level responses to disturbance: a cross-community analysis. Ecology. 2014;95(7):1717–23.

    PubMed  Google Scholar 

  101. Dornelas M, et al. Assemblage time series reveal biodiversity change but not systematic loss. Science. 2014;344(6181):296–9.

    CAS  PubMed  Google Scholar 

  102. Keil P, et al. Spatial scaling of extinction rates: theory and data reveal nonlinearity and a major upscaling and dowscaling challenge. Glob Ecol Biogeogr. 2018;27(1):2–13.

    Google Scholar 

  103. Jarzyna MA, Jetz W. Taxonomical and functional diversity change is scale dependent. Nat Commun. 2018;9:2565.

    PubMed  PubMed Central  Google Scholar 

  104. Graumlich LJ, et al. Paleoperspective in ecology. Ecology. 2005;86(7):1667–8.

    Google Scholar 

  105. Jackson ST. Looking forward from the past: history, ecology, and conservation. Front Ecol Environ. 2007;5(9):455.

    Google Scholar 

  106. Gill JL, et al. Pleistocene megafaunal collapse, novel plant communities, and enhanced fire regimes in North America. Science. 2009;326(5956):1100–3.

    CAS  PubMed  Google Scholar 

  107. Willis KJ, et al. Biodiversity baselines, thresholds, and resilience: testing predictions and assumptions using palaeoecological data. Trends in Ecology and Evolution. 2010;25(10):583–91.

    CAS  PubMed  Google Scholar 

  108. Barnosky AD, et al. Approaching a state shift in Earth’s biosphere. Nature. 2012;486(7401):52–8.

    CAS  PubMed  Google Scholar 

  109. Wolkovich EM, et al. Temporal ecology in the Anthropocene. Ecol Lett. 2014;17(11):1365–79.

    CAS  PubMed  Google Scholar 

  110. Peters DPC, et al. Living in an increasingly connected world: a framework for continental-scale environmental science. Front Ecol Environ. 2008;6(5):229–37.

    Google Scholar 

  111. Birks HJB, Felde VA, Seddon AWR. Biodiversity trends within the Holocene. The Holocene. 2016;26(6):994–1001. The authors present a rare example of using pollen records indicative of vegetation landscapes to reconstruct millennia-long biodiversity trends across biogeographical regions. They provide the first empirical assessment of temporal beta diversity trend at the biogeographical scale, with other forms of biodiversity across the Holocene and the Anthropocene also examined. The study highlights the shifting baselines for evaluating biodiversity change over different temporal scales.

  112. Willis KJ, Birks HJB. What is natural? The need for a long-term perspective in biodiversity conservation. Science. 2006;24(5803):1261–5.

    Google Scholar 

  113. Svenning J-C, et al. The influence of paleoclimate on present-day patterns in biodiversity and ecosystems. Annu Rev Ecol Evol Syst. 2015;46:551–72.

    Google Scholar 

  114. Bartlett LJ, et al. Robustness despite uncertainty: regional climate data reveal the dominant role of humans in explaining global extinctions of Late Quaternary megafauna. Ecography. 2016;39(2):152–61.

    Google Scholar 

  115. Sandom CJ, et al. High herbivore density associated with vegetation diversity in interglacial ecosystems. Proceedings of the National Academy of Sciences USA. 2014;111(11):4162–7.

    CAS  Google Scholar 

  116. Svenning J-C, Skov F. Limited filling of the potential range in European tree species. Ecol Lett. 2004;7(7):565–73.

    Google Scholar 

  117. Svenning J-C, Skov F. Ice age legacies in the geographical distribution of tree species richness in Europe. Glob Ecol Biogeogr. 2007;16(2):234–45.

    Google Scholar 

  118. Hoag C, Svenning J-C. African environmental change from the Pleistocene to the Anthropocene. Annu Rev Environ Resour. 2017;42:27–54.

    Google Scholar 

  119. Normand S, et al. Legacies of historical human activities in Arctic woody plant dynamics. Annu Rev Environ Resour. 2017;42:541–67.

    Google Scholar 

  120. Herrero C, et al. Impact of anthropogenic CO2 on the next glacial cycle. Clim Chang. 2014;122(1–2):283–98.

    CAS  Google Scholar 

  121. Faurby S, Svenning J-C. Historic and prehistoric human-driven extinctions have reshaped global mammal diversity patterns. Divers Distrib. 2015;21(10):1155–66.

    Google Scholar 

  122. Bowman DMJS, et al. The human dimension of fire regimes on Earth. Journal of Beogeography. 2011;38(12):2223–36.

    Google Scholar 

  123. Fuller DQ, et al. The contribution of rice agriculture and livestock to prehistoric methane levels: an archaeological assessment. The Holocene. 2011;21(5):743–59.

    Google Scholar 

  124. Turvey ST, et al. Long-term archives reveal shifting extinction selectivity in China’s postglacial mammal fauna. Proceedings the Royal Society B. 2017;284(1867):20171979.

    Google Scholar 

  125. Dornelas M, et al. BioTIME: a database of biodiversity time series for the Anthropocene. Glob Ecol Biogeogr. 2018;27(7):760–86.

    PubMed  PubMed Central  Google Scholar 

  126. Faith JT, Rowan J, Du A. (2019) Early hominins evolved within non-analog ecosystems. Proceedings of the National Academy of Sciences USA, 116, 21478-21483.

  127. Vellend M, et al. Plant biodiversity change across scales during the Anthropocene. Annual Review of Plant Biology. 2017;68:563–586. The authors present a comprehensive review of the scale dependence of plant biodiversity change across local to global scales and the underlying ecological processes that are responsible for these cross-scale differences. They conclude that both understanding multiscale biodiversity change over the long term and developing models that account for and predict biodiversity responses are important for addressing challenges for future conservation.

  128. Isbell F, et al. Quantifying effects of biodiversity on ecosystem functioning across times and places. Ecol Lett. 2018;21(6):763–78.

    PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work is supported by the National Key R&D Program of China (2017YFC0506200). CX acknowledges the support of National Natural Science Foundation of China (31770512), the CTF Foundation and the Fundamental Research Funds for the Central Universities (020814380112). SNT acknowledges the financial support of Postdoctoral International Exchange Program by China Postdoctoral Council and China Postdoctoral Science Foundation Grant 2019 M660110. JCS considers this work a contribution to his VILLUM Investigator project “Biodiversity Dynamics in a Changing World” funded by VILLUM FONDEN (grant 16549). JS is financed by the FEDER Funds through the Operational Competitiveness Factors Program-COMPETE and by National Funds through FCT-Foundation for Science and Technology within the scope of the project “PTDC/BIA-EVL/30931/2017-POCI-01-0145-FEDER-030931”. Luís Reino was funded by Portuguese National Funds through FCT, I.P., under the program of ‘Stimulus of Scientific Employment–Individual Support under the contract CEECIND/00445/2017. SA and CX are funded by CONICYT-FONDECYT grant 1170995.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Shuqing N. Teng or Chi Xu.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of the Topical Collection on Spatial Scale-Measurement, Influence, and Integration

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Teng, S.N., Svenning, JC., Santana, J. et al. Linking Landscape Ecology and Macroecology by Scaling Biodiversity in Space and Time. Curr Landscape Ecol Rep 5, 25–34 (2020). https://doi.org/10.1007/s40823-020-00050-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40823-020-00050-z

Keywords

Navigation