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Sensitivity of Spring Phenology to Warming Across Temporal and Spatial Climate Gradients in Two Independent Databases
Authors:Benjamin I Cook  Elizabeth M Wolkovich  T Jonathan Davies  Toby R Ault  Julio L Betancourt  Jenica M Allen  Kjell Bolmgren  Elsa E Cleland  Theresa M Crimmins  Nathan J B Kraft  Lesley T Lancaster  Susan J Mazer  Gregory J McCabe  Brian J McGill  Camille Parmesan  Stephanie Pau  James Regetz  Nicolas Salamin  Mark D Schwartz  Steven E Travers
Institution:1. NASA Goddard Institute for Space Studies, New York, New York, USA
2. Ocean and Climate Physics, Lamont-Doherty Earth Observatory, Palisades, New York, USA
3. Division of Biological Sciences, University of California-San Diego, La Jolla, California, USA
4. Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
5. Department of Biology, McGill University, Montreal, Quebec, Canada
6. National Center for Atmospheric Research, Boulder, Colorado, USA
7. U.S. Geological Survey, Tucson, Arizona, USA
8. Department of Ecology & Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA
20. Swedish National Phenology Network, Swedish University of Agricultural Sciences, Asa, Sweden
9. Department of Biology, Theoretical Population Ecology and Evolution Group, Lund University, Lund, Sweden
10. USA National Phenology Network, Tucson, Arizona, USA
11. National Center for Ecological Analysis and Synthesis, Santa Barbara, California, USA
12. Department of Ecology, Evolution and Marine Biology, University of California-Santa Barbara, Santa Barbara, California, USA
13. U.S. Geological Survey, Denver Federal Center, Denver, Colorado, USA
14. Ecology and Environmental Science, University of Maine, Orono, Maine, USA
15. Integrative Biology, University of Texas, Austin, Texas, USA
16. Marine Sciences Institute Portland Square, University of Plymouth, Plymouth, UK
17. Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
18. Department of Geography, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
19. Department of Biological Sciences, North Dakota State University, Fargo, North Dakota, USA
Abstract:Disparate ecological datasets are often organized into databases post hoc and then analyzed and interpreted in ways that may diverge from the purposes of the original data collections. Few studies, however, have attempted to quantify how biases inherent in these data (for example, species richness, replication, climate) affect their suitability for addressing broad scientific questions, especially in under-represented systems (for example, deserts, tropical forests) and wild communities. Here, we quantitatively compare the sensitivity of species first flowering and leafing dates to spring warmth in two phenological databases from the Northern Hemisphere. One??PEP725??has high replication within and across sites, but has low species diversity and spans a limited climate gradient. The other??NECTAR??includes many more species and a wider range of climates, but has fewer sites and low replication of species across sites. PEP725, despite low species diversity and relatively low seasonality, accurately captures the magnitude and seasonality of warming responses at climatically similar NECTAR sites, with most species showing earlier phenological events in response to warming. In NECTAR, the prevalence of temperature responders significantly declines with increasing mean annual temperature, a pattern that cannot be detected across the limited climate gradient spanned by the PEP725 flowering and leafing data. Our results showcase broad areas of agreement between the two databases, despite significant differences in species richness and geographic coverage, while also noting areas where including data across broader climate gradients may provide added value. Such comparisons help to identify gaps in our observations and knowledge base that can be addressed by ongoing monitoring and research efforts. Resolving these issues will be critical for improving predictions in understudied and under-sampled systems outside of the temperature seasonal mid-latitudes.
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