Introduction
Climate change has caused widespread shifts in the reproductive periods
of populations across species, which may result in profound consequences
across levels of ecological organization. To date, the majority of
phenological studies has focused on magnitudes of phenological responses
in mean flowering time to climate conditions. However, many of the
ecological effects of phenological changes are caused by changes in the
duration of a plant species’ synchrony with pests or pollinators, or the
duration over which a species is exposed to adverse conditions during
vulnerable phenophases such as flowering or fruit production (Inouye
2008, Park et al. 2020). Mean flowering dates are not necessarily useful
in evaluating these processes, as changes in climate affect not only the
mean timing of flowering, but also flowering duration (CaraDonna et al.
2014). In such cases, phenological shifts in flowering duration may
alter the synchrony between interacting taxa, affecting plant-pollinator
interactions (Bodley et al. 2016), interspecific competition for
pollinators (Harris 1977, Waser 1978, Anderson and Schelfhout 1980,
Rathcke 1988, Forrest et al. 2010), and susceptibility to herbivory
(Asch and Visser 2007, Singer and Parmesan 2010) in ways that are not
apparent when considering only shifts in their mean timing. Therefore,
more fully determining the ecological consequences of phenological
shifts attributable to climate change requires that we develop the
ability to forecast changes in the duration of each phenophase (e.g.,
flowering) within local populations by modeling changes in the dates of
population-level onsets and terminations for that phenophase. However,
field-based phenological records documenting the onset and termination
of phenophases across multiple species are limited in geographic or
taxonomic scope (Sherry et al. 2011, Bock et al. 2014), and frequently
focus on repeated observation of specific individuals rather than local
populations. To date, this has limited our ability to assess
climate-driven shifts in phenological synchrony across regions and taxa,
highlighting the need for taxonomically and spatially extensive data
sources that offer the capacity to estimate the duration of targeted
phenophases.
Herbarium records and other specimen-based data represent the most
taxonomically, geographically, and temporally extensive source of
phenological information for wild and naturalized species (Davis et al.
2015, Willis et al. 2017). Moreover, herbarium specimens have been
widely used to estimate phenological responses to climate in temperate
regions (Davis et al. 2015, Rawal et al. 2015, Jones and Daehler 2018,
Park and Mazer 2018, Park et al. 2019, Taylor 2019, Ramirez-Parada et
al. 2022) and have captured patterns of phenological variation that are
similar to those observed in the field (Miller-Rushing et al. 2006,
Ramirez-Parada et al. 2022).
Despite their growing use, the utility of herbarium specimens for
estimating phenological onset and termination dates is unclear due to
several limitations. Crucially, herbarium records are sampled
opportunistically, providing single snapshots of the phenological status
(e.g., flowering) of an individual at a given place and time. As such,
it is rarely possible to discern whether a specimen was collected
immediately after the onset of a given phenophase, at its peak, or
shortly before its termination. Similarly, it is typically not possible
to determine whether the sampled individual represents a collection from
an early- or late-flowering individual within its local population. Due
to these sources of uncertainty, the phenological dates of individual
specimens may not reflect the date on which any specific individual- or
population-level phenological event occurred. This limitation has the
potential to restrict their utility for measuring the precise timing of
a given phenophase at the individual level or for estimating the
responses to climate of the extremes of a population’s temporal
phenological distribution (i.e., the onset and termination of a
phenophase at the population level).
Additionally, while validation studies have shown that herbarium-based
estimates of the temperature sensitivity of mean flowering dates
typically match those derived from field observations (Robbirt et al.
2011, Ramirez-Parada et al. 2022), estimates of the first (and last)
occurrence of a phenophase are more subject to the effects of outliers
and to variation in sampling intensity, population size, and other
confounding effects than estimates of mean flowering (Tryjanowski et al.
2005, Miller-Rushing and Primack 2008). These qualitative limitations of
specimen data may intrinsically limit the accuracy with which
population-level flowering onset and termination can be predicted even
when plant phenology responds strongly to well documented aspects of
climate. Similarly, it is possible that the number of specimens required
to overcome these limitations and produce accurate phenological
estimates from these data are prohibitive.
Finally, relative to living plants that are intensively monitored for
their phenological transitions, herbarium records may be subject to
several forms of bias when used to estimate the timing of phenological
events. First, some species may be preferentially collected during the
early or late portion of their local population-level flowering
displays. This is most likely among the earliest and latest-flowering
species, which flower partially outside of the typical growing season.
If specimen collection efforts in general are highest when most species
are in flower at a given location, then collection effort is likely to
be relatively high in the later portions of early-flowering species’
flowering period (i.e., when most other species are flowering) and inearly portions of late-flowering species’ flowering period.
Similarly, species are likely to be less frequently collected during
portions of their flowering period that frequently overlap with
inclement weather or storm events, as poor weather is associated with
reduced collector activity (Daru et al. 2017).
Alternatively, collectors may preferentially collect specimens from
individuals within certain portions of their individual flowering
period. Evaluations of collections across multiple species have found
that collectors often preferentially collect specimens from individuals
that are close to their peak flowering date, when the largest numbers of
flowers are present (Primack et al. 2004, Davis et al. 2015, Panchen et
al. 2019). Conversely, species with fragile flowers or that are
subjected to high rates of herbivory may be preferentially collected
shortly after the onset of flowering, when petals and other delicate
structures are most likely to be intact. Additionally, collectors who
prefer specimens bearing both flowers and fruits may collect specimens
shortly before flowering termination, when both structures are likely to
be present.
Despite such biases (Daru et al. 2017, Panchen et al. 2019), recent work
by Ramirez-Parada et al. (Ramirez-Parada et al. 2022) found that
herbarium- and field-based estimates of flowering sensitivity to
temperature closely agreed in magnitude and direction despite
substantial differences in the timing, location, and associated climate
conditions captured by both types of data. However, as this work
examined mean flowering time, the implications of these forms of bias
for predictions of the timing and duration of the local flowering period
for each species remain unknown.
Nevertheless, forecasting changes to the entire distribution of
phenological events within a population—rather than simple changes in
mean timing—is essential to understanding the effects of climate
change on seasonal floral resource availability as well as on a host of
ecological processes from pollinator activity to floral vulnerability to
frost damage. Determining whether predictions of population-level
flowering onset and termination are less accurate than predictions of
median flowering, or require larger sample sizes is therefore necessary
to confidently leverage the unparalleled taxonomic and spatiotemporal
scope of natural-history collections. Despite this, no studies to date
have sought to validate herbarium-based estimates of phenological onsets
and terminations, likely because such assessments require a suitable
reference dataset of population-level phenological timings against which
the accuracy of phenological predictions derived from specimen data can
be tested. Unfortunately, extensive field datasets of population-level
phenological events across several locations throughout the range of a
species are exceedingly rare, limiting our ability to empirically
validate such herbarium-based estimates.
In this study, we used simulated phenological data to robustly and
systematically assess the accuracy of models of population-level
flowering onset and termination derived from opportunistically sampled
data (henceforth, “phenoclimate” models). These data incorporated
uncertainty or bias in the timing of specimen collection relative to the
start and end of the flowering period of the sampled individual, and in
the relative timing of flowering of the individual relative to its
source population. By assessing the accuracy of estimated
population-level flowering onsets and terminations of simulated plant
taxa exhibiting different flowering characteristics and sampling biases,
we then assessed the effects individual plant flowering duration,
intrapopulation variation in flowering time among individual plants. We
then determined the relationship between data availability and model
performance, from which we inferred the number of specimens required to
produce reliable phenoclimate models of population-level flowering onset
and termination. Finally, we evaluated the effects of A) biases towards
collection of early or late individuals within local populations and B)
biases towards collection of individuals proximate to their flowering
onset or termination dates.