DOI: 10.5061/dryad.73n5tb2tz
title: Data from: Cold and hungry: combined effects of low temperature and resource scarcity on an edge-of-range temperate primate, the golden snub-nose monkey

description: Both biotic and abiotic factors play important roles in influencing
 ecological distributions and niche limits. Where biotic and abiotic
 stressors co-occur in space and time, homeostatic systems face a different
 category of challenge in which stressors compound to impose a challenge
 that is greater than the sum of the separate factors. We studied the
 homeostatic strategies of the golden snub-nosed monkey (Rhinopithecus
 roxellana), a species living in temperate deciduous forests at the edge of
 the global distribution range for folivorous primates, to cope with the
 co-occurrence of cold temperatures and resource scarcity during winter. We
 discovered that in winter the monkeys experience a dietary energy deficit
 of 101 kJ/mbm·day-1 compared with calculated needs, despite increased
 feeding. This is partly offset by behavioral changes (reduced locomotion
 and increased resting) and reducing skin temperature by an average of 3.2
 oC through a cutaneous vasoconstriction to decrease heat loss. However,
 their major strategy is ingesting surplus energy and accumulating fat
 reserves when food was not limiting during summer and autumn. Their 14% of
 body mass lost over the winter represented an energy yield of 102
 kJ/mbm·day-1, which closely matched the calculated winter energy deficit
 of 101 kJ/mbm·day-1. However, the latter value assumes that all the
 75.41kJ/mbm·day-1 of protein ingested in winter was available for energy
 metabolism. This is almost certainly an over-estimate, suggesting that the
 study population was in negative energy balance over the study period. Our
 study therefore suggests that despite its suit of integrated homeostatic
 responses, the confluence of low temperatures and resource limitation
 during winter places this edge-of-range primate close the threshold of
 what is energetically viable. It also provides a framework for
 quantitative models predicting the vulnerability of temperate primates to
 global change.
description: Study Site Our study was conducted in
 Zhouzhi National Nature Reserve on the northern slope of the Qinling
 Mountains, which is the northernmost edge of <i>R.
 roxellana</i>’s range (107°45´-108°18´E, 33°42´-33°54´N, 56.39
 km<sup>2</sup>). The area is 90.5% forest, primarily deciduous
 broadleaf, mixed deciduous broadleaf, and conifer forests (Li and He
 2007). Our focal group (GNG group) has been studied since the 1999 and
 uses 2,250 ha that covers an elevational gradient from 1,380–2,974 m (Li
 et al. 2000). There were 12-14 one male with multi-female units and an
 all-male band (24-36 individuals), totaling 146-159 individuals.
 Even though our aim was to examine the nutritional budget of
 <i>R. roxellana</i> in a situation where resource scarcity
 coincided with high energy demand, we nonetheless provided a low level of
 supplementary foods (30g freshly sliced radish and 60g dry corn per
 individual per day) in April and May and between October and December (Hou
 et al. 2018). This maintained a provisioning cycle they had experienced
 since 2001, albeit at a reduced level, avoiding a situation where an
 abrupt change affected the behavior and observability of the monkeys. So
 doing helped ensure that our results are comparable to the earlier study
 Guo et al. (2018), which were similarly provisioned but to a higher
 level. We used a meteorological monitoring system
 (CR200X, USA) located at 1,600 m to record the temperature in the group’s
 core area. The China Meteorological Administration (C.M.A. 2012) views the
 winter as starting when the daily average temperature (DAT) is below
 10<sup> </sup><sup>o</sup>C for 5 days and ends on
 the first day the DAT exceed or equal 10<sup> o</sup>C for 5
 days. Similarly, the summer is defined as starting when the DAT exceeds
 22<sup> o</sup>C for 5 days and ends on the first day the DAT
 is equal to or less 22<sup>o</sup>C for 5 days. The in between
 periods are spring and autumn. Over the last seven years (May 2011 to
 April 2018) winter lasted 163.8 ± 6.8 days (M<i> ± </i>SD,
 mainly from middle October to March). The average daily temperature in
 winter was 2.4 ± 0.6<sup> o</sup>C (range from -15.8 to
 13.6<sup> o</sup>C). The monthly average minimum temperature
 was below 0<sup>o</sup>C from late November to early March
 (totally 113 days, Fig. 1). We selected 25 food species
 that previous research indicated were frequently eaten (constituting 88.7%
 of the overall diet (Hou et al. 2018)) and recorded the abundance of
 leaves, fruits, seeds, and buds on a scale of 0-4. We calculated a
 seasonal Food Availability Index (FAI) by multiplying this phenology score
 (mean score of three months) by the density of each species (number of
 stem/ha; Fig. 1) and summed this score across species.
 Behavioural Data We collected feeding data
 for one year (September 2014 to August 2015) for adult males, lactating
 females, non-lactating females, and juveniles. Golden snub-nosed monkeys
 are strictly seasonal breeders that reproduce every second year. Females
 conceive in autumn (1-2 months after the peak of food availability),
 gestating during winter and giving birth from mid-March to May (2-4 months
 before the peak of the food availability) (Xiang et al. 2017). Each day
 one individual was followed from dawn to dark. We collected 80 full-day
 follows (10.14 ± 0.04 hr per day, M<i> ± </i>SE), including 20
 days per season, and 5 days for each of the four categories of individuals
 per season. For each feeding bout, we recorded plant species, part (e.g.,
 leaf with petiole or not, bark with periderm or not), and start-stop time.
 In general, we defined a feeding patch as a single tree or liana (woody
 vines that twine the trees); however, when animals fed on fallen oak
 seeds, an important food items from late autumn to early spring, the area
 below the canopy was regarded as a food patch. We used
 Shannon-Wiener diversity index (<i>H’</i>) to characterize the
 diversity of food items eaten each season (Krebs 1989) using the top 20
 food species each season, based on the proportion of consumption time. We
 quantified the time allocation of individuals to different activities to
 determine activity budgets. The activities considered were feeding,
 moving, resting, and other activities. We determine daily path length
 (DPL) only of adults, as juveniles were not identified individually. We
 are able to be within 3 to 10 m of focal adults when they were feeding,
 resting, and moving, which facilitated individual recognition and
 permitted accurate estimation of location with the GPS (Garmin, GPSMAP
 63SC, Garmin Ltd., USA). Body Mass and
 Temperature All the monkeys are fully habituated,
 which enabled us to take thermal images from a distance of 3 to 5m. To
 determine if animals lost body mass over the winter, we weighed
 individually recognizable animals with a platform scale (accuracy, 0.02kg;
 EM-60KAL, A&D, Japan, Fig. 2a) over two weeks shortly after the
 start of winter (early December; Fig. 1) and in two weeks shortly after
 the start of spring (in early April). We lured the monkeys onto the
 platform of the scale using a small amount of corn, enabling us to record
 their body mass. We were unable to individually recognize juveniles, so
 the same juvenile may have been weighed more than once. We collected 188
 body weights (adult males, n = 40; adult females, n = 80; juveniles, n =
 68) with the two sampling periods having equal sample sizes. We estimated
 the energy value of decreased fatty tissues by multiplying the body mass
 loss by 37 kJ/g (energetic conversion factor for fat). It is difficult to
 measure animal’s internal temperature in the wild, so we used a thermal
 infrared imager (FLIR T640, USA) to assess monkeys’ facial skin
 temperature (<i>T</i><sub>fs</sub>) (Fig. 2b). We
 measured <i>T</i><sub>fs</sub> from recognizable
 adults from a distance of about 2 m in mid-December (winter) and mid-April
 (spring), respectively. To avoid any potential bias of
 <i>T</i><sub>fs </sub>due to the time of day and
 differences in activity levels, we measured the monkeys’
 <i>T</i><sub>fs</sub> from 10:00 a.m. to 12:00
 p.m. when monkeys were resting and inactive. Samples were taken once a day
 for a two-week period per season. Temperature data were assessed using
 FLIR R&D analysis software using only high-quality images (front
 view and near-distance). Diet We
 used the standard techniques to collect the food samples (Rothman et al.
 2012), and analyze the foods nutrients and calculate the energy values
 (van Soest 1994), as used in our previous studies (Guo et al. 2018, Hou et
 al. 2018). Total non-structural carbohydrates (TNC) was
 calculated by subtracting protein, lipids, NDF and ash from total dry mass
 (Rothman et al. 2012). Non-protein energy (NPE) was calculated using the
 summation of TNC, NDF, and lipids. Daily energy intake (DEI) was
 calculated through summation of all foods eaten during a day. To
 standardise the difference among different age-sex classes, we divided our
 calculated results by the individual’s metabolic body mass (mbm =
 M<sup>0.762</sup>, where M is body mass in kg (Nagy 1994)).
 Body mass for age/sex classes was based on average measurement for adult
 individuals and juveniles in winter and spring and we used the averaged
 body mass in spring and winter to represent the body mass in summer and
 autumn. Energy expenditure We
 evaluated energy budgets using two different indices: average daily
 metabolic need (ADMN) and daily energy expenditure (DEE). ADMN had been
 used by DaSilva (1992) to estimate the energy budget of <i>Colobus
 polykomos</i> (see also (Wasserman and Chapman 2003)). DEE was
 evaluated following the regression equation recommended by Pontzer et al.
 (2014) , who formulated the relationship between DEE (using the doubly
 labelled water technique) and body mass for 17 primate species and derived
 the following equation: y=0.69x+2.09, r<sup>2</sup> = 0.97 where y indicates log<sub>10</sub>DEE (kcal/day), x indicates log<sub>10</sub> body mass (kg). We did not distinguish body weight difference between lactating and non-lactating female. The primates used by Pontzer et al. (2014) occupy tropical and subtropical regions, so we calculated the DEE only for warm seasons (spring, summer, and autumn). For temperature-living primates, the DEE in winter (DEEW) should take into account the additional daily energetic costs of thermoregulation (ADECT) and baseline DEE (calculated from the above equation). The difference value of the ADECT between winter and spring was measured as 329kJ/mbm (Guo et al. 2018). Average daily metabolic need (ADMN) was estimated using the follow equation: ADMN=130*W<sup>0.762</sup>24*S+BMR*0.23884624*24-S+T*d*W*4.1868 where W = body mass (kg), S = number of active hours each day, T = travel costs (kcal/kg*km) = <i>0.1 (10)</i><sup><i>1.67*W</i><sup><i>-0.126</i></sup></sup>, d = daily path length, DPL (km), we used seasonal average DPL to represent d, Basal Metabolic Rate (BMR) was estimated by the following equation: BMR = 70 * 4.1868kJ/ kcal* body mass<sup>0.762</sup>. The ADMN values calculated through the above equation are used in warm seasons (spring, summer and autumn), while the ADMN in winter (ADMNW) should take the additional daily energetic costs of thermoregulation (329 kJ/mbm) and baseline ADMN in winter (calculated from above equation) into account. We considered the energetic costs of pregnancy and lactation for females when calculating ADMN and DEE. The costs of pregnancy and lactation individuals have been considered to increase energy expenditure, so, we multiply 1.25 and 1.5 in calculating the ADMN and DEE, respectively (Vogel, et al. 2017).
description: no missing values in the upload dataset.