DOI: 10.5061/dryad.msbcc2g09
title: Southern hemisphere plants show more delays than advances in flowering phenology

description: This dataset is from the manuscript 'Southern hemisphere plants show
 more delays than advances in flowering phenology' whereby historic
 field data, modern field data and herbarium specimen data were used to
 determine if plants in Sydney, Australia were
 flowering earlier in the year through time. This dataset also contains
 meteorological data used to analyse the relationship between temperature
 or precipitation and flowering time shifts to work out if these long-term
 changes in flowering phenology were impacted by seasonal climate. Finally,
 this data also includes a data compilation from previous studies to
 determine whether species were advancing or regressing their flowering
 through time.
description: We collected flowering phenology data from the northern Sydney
 region, NSW, Australia. This region was selected as detailed flowering
 time data from the early 1960s were available for over 400 species in the
 dataset - Price, 1963: Contributions to the NSW Herbarium.
 Price (1963) recorded flowering at weekly intervals giving a high
 degree of sensitivity in assessing flowering time shifts. We set Price’s
 data to 1961, the most likely median sample date for species from her
 study. Price’s data indicated the timing of “abundant
 flowering” or the “main flush of flowering” (Price, 1963 p. 171) and we
 interpreted and used these data as “full flowering” from this period. Only
 full flowering data are presented throughout this paper. However, we also
 recorded the initiation of flowering and end of flowering. Analyses of
 these variables yields results that are quantitatively very similar to
 those for full flowering (Supporting Information S3: Tables
 S3a,b,c). We collected modern field data in sites
 selected to try to match the localities and ecosystems that would have
 been monitored by Price (1963). Fieldwork occurred from August-February
 (end of southern hemisphere winter, through to spring and summer) in 2010,
 2011, 2018 and 2019 for a subset of 37 species, in the northern Sydney
 region from the Price (1963) dataset. These species were selected from a
 range of families and growth forms and chosen based on their presence in
 the northern Sydney region and abundance at the locations sampled
 (typically we monitored &gt; 30 individuals, however, for some species
 there were lower numbers of individuals). For each species, we monitored
 flowering at weekly intervals to match sampling methods in Price (1963).
 Each species was determined to be in full flower if at least 50% of
 individual plants were in flower. We supplemented the
 historic data and field data with flowering phenology data collected from
 herbarium specimens from the John T. Waterhouse Herbarium (UNSW, Sydney,
 Australia), The Downing Herbarium (Macquarie University, Australia), the
 John Ray Herbarium (The University of Sydney, Australia) and the National
 Herbarium of New South Wales (Royal Botanic Gardens, Sydney, Australia).
 Herbarium specimens have been shown to yield similar results to field data
 and can be used in conjunction to increase sample sizes and time frames
 (Jones & Daehler, 2018). Herbarium specimens were only included if
 they had sufficient geo-location information for us to be certain that
 they were collected from the sample region. We scored each specimen for
 flowering status in accordance with field data scoring and species were in
 full flower when &gt;75% of the specimen’s reproductive organs/buds
 had turned to flowers. Although previous studies have used 50% as the
 threshold for full flowering, we believe that 75% more accurately captured
 full flowering in our species: as each specimen was only one section of a
 plant, a higher threshold for full flowering was necessary for comparison
 with our field data. Most specimens had date data resolved to the exact
 day of observation. We also included specimens with dates resolved to at
 least the month of flowering and for these specimens we arbitrarily
 appointed the 15<sup>th</sup> day of the month (the median of
 the month) as the specimen observation date. We
 conducted a literature search in December 2020 using Web of Science and
 Google Scholar with keywords ‘phenology’, ‘plants’ in combination with
 ‘climate change’, ‘temperature’ or ‘global warming’. This yielded
 flowering phenology shift data (days per decade) from studies worldwide,
 including reviews, meta-analyses and other literature. We only included
 studies that explicitly quantified shifts in phenology through time, had
 at least 10 years of data, quantified shifts in full flowering or first
 flowering date and were samples of native, non-agricultural species (i.e.
 no crop species). Species were classified as advancing or delaying in
 their flowering time independent of the significance of this relationship.
 We also included flowering shift data from the 27 native species in our
 current study. Our search yielded data for 830 species from seven studies
 in the northern hemisphere (562 of which originated from a recent
 meta-analysis) and 118 species across four studies (including the present
 study) from the southern hemisphere.
description: To use these data sets, see the cleaning and manipulation of the
 data, or run the same analyses all code is freely available at: https://github.com/SEveringham/flowering-phenology-changes-in-Sydney.