Introduction
Phenology, the seasonal timing of life history events, is increasingly
relevant in the framework of global change studies (Cohen et al., 2018;
Staudinger et al., 2019; Horton et al., 2020). In general, species are
predicted to exhibit phenological shifts across wide geographical scales
in response to climate change. Phenological responses are predicted to
be particularly important for high elevation communities (Hodkinson,
2005; Stewart et al., 2019), wildlife at northern latitudes (Berger et
al., 2018) and cold-adapted species (Sarmento et al., 2019) prone to
seasonal mismatches, for example in coat colour (e.g., white snowshoe
hares on a brown background; Mills et al., 2013, Zimova et al., 2014,
Pedersen et al., 2017; Zimova et al., 2018) or arrival at calving
grounds (e.g., caribou arriving after spring vegetation flush; Post &
Forchhammer, 2008).
Many mammals of temperate zones experience high seasonal variance in
exposure to ambient temperature; pelage that offers heat retention in
winter is shed in summer, but for most species little is known about
rates of shedding or the extent it varies by sex or across broad
latitudinal or altitudinal gradients. Among these species are mountain
goats (Oreamnos americanus ), inhabitants of mountainous terrain
in northwestern North America (White et al., 2018). Mountain goats use
high, windy slopes above the treeline during summer (Chadwick, 2002) and
make use of snow patches for cooling (Sarmento et al., 2019). If they
did not shed their thick, two layered winter coats, which can grow over
ten centimeters long (Foresman, 2012), these would likely pose a
liability in summer. Across the late Holocene, their ranges diminished
in accordance with warming temperatures from northern Mexico to Idaho
(Festa-Bianchet & Cote, 2008).
Much remains to be learned about the triggers of shedding and
differences between the sexes in mammals, despite the noted high
visibility of massive chunks of hair hanging from species like bison
(Bison bison ) and muskoxen (Ovibos moschatus ) (Wilkinson,
1974; Berger and Cunningham, 1994). Most mammals moult to replace worn
out hairs and provide different summer and winter coats (Ryder, 1965),
including moose (Alces alces ), bison, elk (Cervus
canadensis ), and thinhorn sheep (Ovis dalli ). While moult is a
relatively understudied life history event (Beltran et al., 2018), it is
well-established that photoperiod and, to a lesser extent temperature,
control moult onset (Murray, 1965; Lincoln and Ebling, 1985; Mo et al.,
2006; Zimova et al., 2018). Moult is known to occur latest in lactating
mountain goat females (Déry et al., 2019) likely because, as documented
in red deer (Cervus elaphus ), the costs of milk production affect
female body condition even though food may be most abundant in summer
(Clutton-Brock et al., 1982).
Mountain goats offer an unusual opportunity to examine ecological
predictions about moult because they occur along latitudinal gradients
that vary in ambient condition including elevation. Because of their
stature as an iconic mammal of the mountains, there is likely to be high
interest from community scientists. Further, they occur in captive
settings including at the far northern extent of their range providing
opportunity for individual-level and repeated observation and comparison
with southern, better-photographed populations.
Community generated datasets offer a promising way to test hypotheses
about moult across broad geographical ranges in part because some
historical data are available and because volunteer monitoring is
growing in popularity (Taylor et al., 2019). This community-based
approach is intended to complement rather than replace long-term
research. For instance, community science data have been combined with
satellite data to examine how bird migration (arrival time at breeding
grounds) responds to advancing vegetation green-up dates (Mayor et al.,
2017). Community science data have also been explored across multiple
projects to assess climate change effects on American pika
(Ochotona princeps ) with reasonably reliable results
(Moyer-Horner et al., 2012). In addition to mammals and birds,
community-contributed photographs have been used to document glacial
retreat, and show promise to shift climate change conversations and
enhance public education and engagement (Mullen et al., 2013).
Here, we assess the utility of community photography, un underutilized
resource, to detect phenological patterns of moult in mountain goats
within and between a geographical gradient and between the sexes. We
employed a comparative study design involving detailed fieldwork of our
own that concentrated on captive and adjacent wild populations, with
decades of community scientist photos of moulting goats along gradients
of latitude and elevation (Figures 1-2). If the community science data
are commensurate with those from our own focal research, then it seems
plausible to explore long-term phenological patterns of moult across the
entire geographical range of a species using photographs. Collation of a
more complete photographic data base, and then using it to quantify
long-term and spatially extant patterns of shedding, provides a
barometer for detecting patterns and developing inferences regarding
impacts of climate change (Hetem et al., 2014; Vieira et al., 2017). We
might also expect greater community engagement with climate science
outcomes when communities are actively in involved in data collection.
However, there are issues to consider when relying on community sourcing
of data that may be influenced by variation in identification skills,
sampling effort and efficiency (Dickinson et al., 2010). Large data sets
and applying appropriate statistical models may help account for
potential bias (e.g., including observer error in assigning sex to an
animal and variation in sampling effort). Data are also often missing
from community science datasets (e.g., sampling some locations but not
others). The best way to deal with missing data often associated with
community science projects has received relatively little attention, and
the most common approach is to simply filter out such data (Dickinson et
al., 2010), despite it being well known that non-random filtering of
data can lead to bias and poor inference (Nakagawa, 2015). However, we
might expect that patterns in observed data provide information about
likely values of missing data (i.e., information is shared across
observations) (see Nakagawa, 2015).
Missing data is an issue for our study because animal sex is not always
clearly distinguishable in community sourced photographs nor is whether
or not a female is associated with a kid. Here, we develop a statistical
model of coat shedding that infers the most likely state of an animal
when unknown, and so, even the photographs with incomplete information
are still included in the model fit. This general approach could be
applied to other community science data sets, reducing the need to
remove seemingly uninformative data. Using this approach, we show how
community science data can help identify important environmental
predictors of shedding rates (e.g., elevation and latitude), the role of
the state of the animal (e.g., sex, whether caring for young), and
quantify the extent of geographical variation.