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Biodiversity and Conservation

, Volume 27, Issue 6, pp 1487–1501 | Cite as

Using herbarium specimens to select indicator species for climate change monitoring

  • Rebecca A. Hufft
  • Michelle E. DePrenger-Levin
  • Richard A. Levy
  • Melissa B. Islam
Original Paper

Abstract

Phenology is one of the best indicators to observe plant responses to climate change and predict future changes in plant communities. Choosing indicator species to monitor biological responses to climate change may be improved if herbarium specimens are combined with ongoing monitoring efforts to understand phenological responses over longer periods. We analyzed herbarium specimen data from Colorado’s alpine region, as alpine areas are predicted to be especially sensitive to climate change. We assessed phenological patterns in relation to temperature and precipitation for 287 species and growing degree days (GDD) for 235 species. Average low temperature, maximum GDD, and average precipitation increased over the study period. As temperature and GDD increased, phenology advanced, but as precipitation increased, phenology was delayed. Even with this variability of environmental responses, a significant trend of earlier flowering appeared when all species were analyzed together. Of the species that showed significantly earlier flowering dates, they advanced on average more than 39 days over the 61 years of the study. When assessing only specimens of species monitored in a national program (USA National Phenology Network), we found that these species showed similar trends to the entire dataset. When selecting species for ongoing monitoring efforts, herbarium specimens are an important resource to incorporate historical patterns into assessments of climate change and phenological drivers.

Keywords

Phenology Southern Rocky Mountains Flowering times Temperature Precipitation Growing degree days 

Notes

Acknowledgements

We are grateful to our long-time volunteer, Mo Ewing, for helping to pull together the data used in these analyses and reviewer comments that improved the manuscript.

Supplementary material

10531_2018_1505_MOESM1_ESM.pdf (91 kb)
Online Resource 1. Methods used to refine taxonomy of specimens used in analyses. Supplementary material 1 (PDF 91 kb)
10531_2018_1505_MOESM2_ESM.xlsx (87 kb)
Online Resource 2. Species used in the study including authority, family, life history, NPN status, and whether the species was included in analyses of GDD. Results of all regression analyses per species by year, TAmax, TAmin, PA, and GDD. Supplementary material 2 (XLSX 86 kb)
10531_2018_1505_MOESM3_ESM.xlsx (12 kb)
Online Resource 3. Breakpoint analysis for climate variables over time and first and mean reproductive date by year and climate variables. Supplementary material 3 (XLSX 11 kb)

References

  1. Ackerfield J (2015) Flora of Colorado. Botanical Research Institute of Texas, Fort WorthGoogle Scholar
  2. Bertin RI (2015) Climate change and flowering phenology in Worcester County, Massachusetts. Int J Plant Sci 176:107–119.  https://doi.org/10.1086/679619 CrossRefGoogle Scholar
  3. Bjorkman AD, Elmendorf SC, Beamish AL, Vellend M, Henry GHR (2015) Contrasting effects of warming and increased snowfall on Arctic tundra plant phenology over the past two decades. Glob Change Biol 21:4651–4661.  https://doi.org/10.1111/gcb.13051 CrossRefGoogle Scholar
  4. Brommer J, Lehikoinen A, Valkama J (2012) The breeding ranges of European and Arctic bird species move poleward. PLoS ONE 7:e43648.  https://doi.org/10.1371/journal.pone.0043648 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Cabin RJ, Mitchell RJ (2000) To Bonferroni or not to Bonferroni: when and how are the questions. Bull Ecol Soc Am 81(3):246–248Google Scholar
  6. Calinger KM, Queenborough S, Curtis PS (2013) Herbarium specimens reveal the footprint of climate change on flowering trends across north-central North America. Ecol Lett 16:1037–1044.  https://doi.org/10.1111/ele.12135 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Cao YS, Xiao Y, Huang HQ, Xu JC, Hu WH, Wang N (2016) Simulated warming shifts the flowering phenology and sexual reproduction of Cardamine hirsuta under different planting densities. Sci Rep 6:9.  https://doi.org/10.1038/srep27835 CrossRefGoogle Scholar
  8. CaraDonna PJ, Iler AM, Inouye DW (2014) Shifts in flowering phenology reshape a subalpine plant community. Proc Natl Acad Sci USA 111(13):4916–4921CrossRefPubMedPubMedCentralGoogle Scholar
  9. Cayuela L, Granzow-de la Cerda I, Albuquerque FS, Golicher JD (2012) Taxonstand: an R package for species names standardization in vegetation databases. Methods Ecol Evol 3(6):1078–1083CrossRefGoogle Scholar
  10. Cook BI, Wolkovich EM, Parmesan C (2012) Divergent responses to spring and winter warming drive community level flowering trends. Proc Natl Acad Sci USA 109:9000–9005.  https://doi.org/10.1073/pnas.1118364109 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Davis CC, Willis CG, Connolly B, Kelly C, Ellison AM (2015) Herbarium records are reliable sources of phenological change driven by climate and provide novel insights into species’ phenological cueing mechanisms. Am J Bot 102:1599–1609.  https://doi.org/10.3732/ajb.1500237 CrossRefPubMedGoogle Scholar
  12. Dawson TP (2011) Beyond predictions: biodiversity conservation in a changing climate. Science 332:664CrossRefGoogle Scholar
  13. de Reaumur RAF (1735) Observation du thérmomètre, faites à Paris pendant l’année 1735, compar-ées avec celles qui ont été faites sous la ligne, à l’Isle de France, à Alger et en quelquesunes de nos isles de l’Amérique. Mémoires de l’Académie Royale des Sciences de Paris 1735:545–576Google Scholar
  14. Duputie A, Rutschmann A, Ronce O, Chuine I (2015) Phenological plasticity will not help all species adapt to climate change. Glob Change Biol 21:3062–3073.  https://doi.org/10.1111/gcb.12914 CrossRefGoogle Scholar
  15. Feeley KJ, Silman MR (2011) Keep collecting: accurate species distribution modeling requires more collections than previously thought. Divers Distrib 17:1–9CrossRefGoogle Scholar
  16. Fitchett JM, Grab SW, Thompson DI (2015) Plant phenology and climate change: progress in methodological approaches and application. Prog Phys Geogr 39:460–482.  https://doi.org/10.1177/0309133315578940 CrossRefGoogle Scholar
  17. Fowler J, Nelson BE, Hartman RL (2014) Vascular plant flora of the alpine zone in the Southern Rocky Mountains, USA. J Bot Res Inst Texas 8:611–636Google Scholar
  18. Gallinat AS, Primack RB, Wagner DL (2015) Autumn, the neglected season in climate change research. Trends Ecol Evol 30:169–176.  https://doi.org/10.1016/j.tree.2015.01.004 CrossRefPubMedGoogle Scholar
  19. Ganjurjav H et al (2016) Differential response of alpine steppe and alpine meadow to climate warming in the central Qinghai-Tibetan Plateau. Agric For Meteorol 223:233–240.  https://doi.org/10.1016/j.agrformet.2016.03.017 CrossRefGoogle Scholar
  20. Gezon ZJ, Inouye DW, Irwin RE (2016) Phenological change in a spring ephemeral: implications for pollination and plant reproduction. Glob Change Biol 22:1779–1793.  https://doi.org/10.1111/gcb.13209 CrossRefGoogle Scholar
  21. Hart R, Salick J, Ranjitkar S, Xu JC (2014) Herbarium specimens show contrasting phenological responses to Himalayan climate. Proc Natl Acad Sci USA 111:10615–10619.  https://doi.org/10.1073/pnas.1403376111 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Hufft R, Zelikova TJ (2016) Ecological genetics, local adaptation, and phenotypic plasticity in Bromus tectorum in the context of a changing climate. In: Germino MJ, Chambers JC, Brown C (eds) Exotic brome grasses in rangeland ecosystems of the Western US. Springer, New YorkGoogle Scholar
  23. Inouye DW, Wielgolaski FE (2003) High altitude climates. In: Schwartz MD (ed) Phenology: an integrative environmental science for vegetation science, vol 39. Kluwer Academic Publishers, Dordrecht, pp 195–214CrossRefGoogle Scholar
  24. Kenney M, Janetos A, Lough G (2016) Building and integrated U.S. National Climate Indicators System. Clim Change 135:85–96CrossRefGoogle Scholar
  25. McMaster GS, Wilhelm WW (1997) Growing degree-days: one equation, two interpretations. Agric For Meteorol 87:291–300.  https://doi.org/10.1016/s0168-1923(97)00027-0 CrossRefGoogle Scholar
  26. Meng F et al (2016) Changes in phenological sequences of alpine communities across a natural elevation gradient. Agric For Meteorol 224:11–16.  https://doi.org/10.1016/j.agrformet.2016.04.013 CrossRefGoogle Scholar
  27. Meyer C, Weigelt P, Kreft H (2016) Multidimensional biases, gaps and uncertainties in global plant occurrence information. Ecol Lett 19:992–1006CrossRefPubMedGoogle Scholar
  28. Miller-Rushing AJ, Primack RB, Primack D, Mukunda S (2006) Photographs and herbarium specimens as tools to document phenological changes in response to global warming. Am J Bot 93:1667–1674CrossRefPubMedGoogle Scholar
  29. Mohandass D (2015) Increasing temperature causes flowering onset time changes of alpine ginger Roscoea in the Central Himalayas. J Asia-Pacific Biodiv 8:191–198CrossRefGoogle Scholar
  30. Morellato LPC et al (2016) Linking plant phenology to conservation biology. Biol Conserv 195:60–72.  https://doi.org/10.1016/j.biocon.2015.12.033 CrossRefGoogle Scholar
  31. Morris RA, Dou L, Hanken J, Kelly M, Lowery DB et al (2013) Semantic annotation of mutable data. PLoS ONE 8(11):e76093CrossRefPubMedPubMedCentralGoogle Scholar
  32. Muggeo VMR (2003) Estimating regression models with unknown break-points. Stat Med 22(19):3055–3071CrossRefPubMedGoogle Scholar
  33. Munson SM, Sher AA (2015) Long-term shifts in the phenology of rare and endemic Rocky Mountain plants. Am J Bot 102:1268–1276.  https://doi.org/10.3732/ajb.1500156 CrossRefPubMedGoogle Scholar
  34. Park IW (2012) Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery. Int J Biometeorol 56:1179–1182CrossRefPubMedGoogle Scholar
  35. Park DS, Davis CC (2017) Implications and alternatives of assigning climate data to geographical centroids. J Biogeogr 44(10):2188–2198CrossRefGoogle Scholar
  36. Park IW, Schwartz MD (2015) Long-term herbarium records reveal temperature-dependent changes in flowering phenology in the southeastern USA. Int J Biometeorol 59:347–355.  https://doi.org/10.1007/s00484-014-0846-0 CrossRefPubMedGoogle Scholar
  37. Parmesan C (2006) Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol Syst 37:637–669.  https://doi.org/10.1146/annurev.ecolsys.37.091305.110100 CrossRefGoogle Scholar
  38. Parmesan C, Hanley ME (2015) Plants and climate change: complexities and surprises. Ann Bot 116:849–864.  https://doi.org/10.1093/aob/mcv169 CrossRefPubMedPubMedCentralGoogle Scholar
  39. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  40. Rawal DS, Kasel S, Keatley MR, Nitschke CR (2015) Herbarium records identify sensitivity of flowering phenology of eucalypts to climate: implications for species response to climate change. Austral Ecol 40:117–125.  https://doi.org/10.1111/aec.12183 CrossRefGoogle Scholar
  41. Robbirt KM, Davy AJ, Hutchings MJ, Roberts DL (2011) Validation of biological collections as a source of phenological data for use in climate change studies: a case study with the orchid Ophrys sphegodes. J Ecol 99:235–241.  https://doi.org/10.1111/j.1365-2745.2010.01727.x CrossRefGoogle Scholar
  42. Russelle MP, Wilhelm WW, Olson RA, Power JF (1984) Growth analysis based on degree days. Crop Sci 24:28–32.  https://doi.org/10.2135/cropsci1984.0011183X002400010007x CrossRefGoogle Scholar
  43. Schmidt-Lebuhn AN, Knerr NJ, Kessler M (2013) Non-geographic collecting biases in herbarium specimens of Australian daisies (Asteraceae). Biodivers Conserv 22:905–919.  https://doi.org/10.1007/s10531-013-0457-9 CrossRefGoogle Scholar
  44. Suhrbier L, Kusber WH, Tschöpe O, Güntsch A, Berendsohn WG (2017) AnnoSys—implementation of a generic annotation system for schema-based data using the example of biodiversity collection data. Database (Oxford)(1):bax018.  https://doi.org/10.1093/database/bax018
  45. Thiers B (2017) Index herbariorum: a global directory of public herbaria and associated staff. New York Botanical Garden’s Virtual Herbarium, New YorkGoogle Scholar
  46. Urban MC (2015) Accelerating extinction risk from climate change. Science 348:571–573.  https://doi.org/10.1126/science.aaa4984 CrossRefPubMedGoogle Scholar
  47. U.S. Environmental Protection Agency (2016) Climate change indicators in the United States, 2016, 4th edn. EPA 430-R-16-004. www.epa.gov/climate-indicators
  48. USDA, NRCS (2017) The plants database. National Plant Data Team, Greensboro. http://plants.usda.gov
  49. Walther GR et al (2002) Ecological responses to recent climate change. Nature 416:389–395.  https://doi.org/10.1038/416389a CrossRefPubMedGoogle Scholar
  50. Wheeler JA et al (2016) The snow and the willows: earlier spring snowmelt reduces performance in the low-lying alpine shrub Salix herbacea. J Ecol 104:1041–1050.  https://doi.org/10.1111/1365-2745.12579 CrossRefGoogle Scholar
  51. White SN, Boyd NS, Van Acker RC (2015) Temperature thresholds and growing-degree-day models for red sorrel (Rumex acetosella) ramet sprouting, emergence, and flowering in wild blueberry. Weed Sci 63:254–263.  https://doi.org/10.1614/ws-d-14-00048.1 CrossRefGoogle Scholar
  52. Wieczorek J et al (2012) Darwin core: an evolving community-developed biodiversity data standard. PLoS ONE 7:e29715.  https://doi.org/10.1371/journal.pone.0029715 CrossRefPubMedPubMedCentralGoogle Scholar
  53. Willis CG, Ellwood ER, Primack RB et al (2017a) Old plants, new tricks: phenological research using herbarium specimens trends. Ecol Evol.  https://doi.org/10.1016/j.tree.2017.03.015 Google Scholar
  54. Willis CG, Law E, Williams AC et al (2017b) CrowdCurio: an online crowdsourcing platform to facilitate climate change studies using herbarium specimens. New Phytol 215(1):479–488CrossRefPubMedGoogle Scholar
  55. Wolf AA, Zavaleta ES, Selmants PC (2017) Flowering phenology shifts in response to biodiversity loss. Proc Natl Acad Sci USA 114:3463–3468CrossRefPubMedPubMedCentralGoogle Scholar
  56. Zhang Y, Dong S, Gao Q, Liu S, Zhou H, Ganjurjav H, Wang X (2016) Climate change and human activities altered the diversity and composition of soil microbial community in alpine grasslands of the Qinghai-Tibetan Plateau. Sci Total Environ 562:353–363.  https://doi.org/10.1016/j.scitotenv.2016.03.221 CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Denver Botanic GardensDenverUSA

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