Impact of cost distance and habitat fragmentation on the daily path length of Rhinopithecus bieti

Ethical standards

All research methods adhered to Chinese legal requirements and complied with protocols approved by the State Forestry Administration of China and the American Society of Primatologists principles for the ethical treatment of primates.

Study site and data collection

The research site is the Baimaxueshan National Nature Reserve, in Weixi, Tacheng, Gehuaqing (27°34′N, 99°17′E), Yunnan Province, China (Fig. 1). The elevation of the study area is between 2,600-4,000 m.

The vegetation in the research area can be divided into six categories: (i) Yunnan pine (Pinus yunanensis) forest (2,500–3,200 m); (ii) Evergreen broad-leaved forest (2,500–3,000 m), (iii) Montane sclerophyllous oak forest (3,200–3,500 m); (iv) Coniferous and broad-leaved mixed forest (Armand pine, Pinus armandii and Chinese hemlock, Tsuga chinensis, 2,900–3,600 m); (v) Dark conifer forest (Spruce-fir forests, 3,500–4,000 m); (vi) Non-forest vegetation, farmland, and barren land. Among the six vegetation types, only two, Coniferous and broad-leaved mixed forest and Dark conifer forest are suitable habitats for the Yunnan snub-nosed monkey (Kirkpatrick et al., 1998; Li et al., 2008; Xiao et al., 2003). Ren et al. (2009b) adopted Zhang’s classification (i.e., daily mean temperatures (T) ≥ 22 °C was scored as summer, T ≤ 10 °C was scored as winter and 10 °C <T < 22 °C spring and autumn) to recognize three seasons in this area: spring (May to July), autumn (August to October) and winter (November to April). These seasons differ in rainfall and temperature. Highest temperatures and greatest rainfall occur in July and August (spring and autumn), whereas the lowest temperatures and rainfall occur in December and January (winter) (Li et al., 2013).

Our R. bieti breeding band, consisted of approximately 407 individuals, and is habituated to human observers. The social organization of R. bieti is best described as a multi-level society (MLS), which is principally composed of from 14–18 one-male units (OMUs) and at least one all-male unit, which are collectively referred to as a breeding band. OMUs contain one adult male, from three to five adult females and several immature offspring. Males emigrate the OMU as juveniles (around age 4) and enter an all-male unit (AMU) which is composed of juvenile, subadult, and adult bachelor males. The number of bachelor males in the AMU ranged from 10–20. Typically, when the band travels, it is followed by one or more AMUs across its range. From July 2013 to June 2014, we recorded the location of the geographic center of the breeding band using a handheld Garmin GPS Map 62 s Geographic Positioning System (GPS). We followed the monkeys from 6:00 until they entered their sleeping tree on 21 days. Day length varied from 10 h in December to 14 h in June. In December, the monkeys entered their sleeping tree at 16:00 and in June the monkeys entered their sleeping site at 20:00. In order to determine the geographic center of the band, we were positioned 30 to 50 m away from the center of the band and then moved to the center location to record the GPS point. Ninety-three percent of our GPS data points were recorded in this way. On 7% of occasions, because of inclement weather and difficult-to-navigate terrain characterized by steep mountain slopes, we collected the GPS point at a distance of more than 100 m from the center of the band. Each GPS record included the location, altitude, and vegetation type based on the six habitat categories listed above. On average we recorded 3–4 GPS points per observation day. Data collection was accomplished with the assistance of local guides and reserve staff. Our field assistants had extensive experience in field tracking monkeys and in data collection, however, we did not test for interobserver reliability. We acknowledge that in recording only 3-4 GPS points per day and in obtaining data for only 21 complete days, the results presented in our study are best considered preliminary.

Data analysis

To calculate the DPL of the group, we converted GPS points to Shape files in ArcGIS 10.3 (Esri, Redlands, CA, USA) (https://www.arcgis.com). We screened the data to remove erroneous points (those that were clearly outside our study area). Our sample included 70 GPS points of observational data. This included 16 points in spring, 25 points in autumn, and 29 points in winter. The land-use map of the study area was added into the point Shape file via ArcGIS.The DPL during different seasons was calculated using the spatial analysis feature in ArcGIS 10.3. During spring we calculated DPL on five days (May: one day; June: two days; July: two days), in autumn on seven days (August: three days; September: two days; October: two days) and in winter during nine days (November: three days; March: three days; April: three days). We use the measurement tools to calculate the average DPL per season.

Cost distance was calculated using the “cost-distance” tool in ArcGIS 10.3, which simulates the accumulative cost distance for each cell based on its resistance surface score, as the species travels across its range. The resistance surface is also known as the cost-raster. Each cell, which measures 20 × 20 m, of the cost-raster is given a “cost” based on the habitat present in the cell. The cost of land use is defined as the resistance of different landscape types to the movement of the species (Perović et al., 2010). In this study, based on the research of Wu et al. (2009) and Chardon, Adriaensen & Matthysen (2003), we set resistance surface cost to two fixed values, giving the most suitable landscape types and the most unsuitable landscape types a cost value of 1 and 100, respectively. In addition, based on the results of Li et al. (2014), we assigned a cost of 1 to optimal habitat for R. bieti (Spruce-fir forests, Coniferous and broad-leaved mixed forest), a cost of 50 (shrubbery, Sclerophyllous evergreen broad-leaved forests) and 60 (Broad-leaved forests) to suitable habitats, a cost of 70 to unsuitable habitats (barren land, Non-forest land and Yunnan pine forests), and a cost of 100 to habitats containing barriers to movement (farmland and rangeland). The land-use map (20 × 20 mresolution) we used is derived from an assemblage of 13 SPOT 5 satellite images (November 2004, 60 × 60 km) covering the study area. We verified our habitat classification accuracy using data from the Conservation Information Centre of The Nature Conservancy of China. We generated the cost distance distribution map with the GPS points in different seasons using ArcGIS 10.3. We assumed that if the band was located in a particular habitat type when a GPS point was taken, that the band remained in that habitat type until the next GPS point was taken. On average, successive GPS points were taken four to six hours apart. One-way ANOVA tests were performed using SPSS 25.0 (IBM, Armonk, NY, USA).

Fragmentation analysis was conducted using the software FRAGSTATS 4.2 (McGarigal, Sam & Ene, 2012). We defined patch density (PD) using the fragmentation index. The fragmentation index is defined as the number of patches (a relatively homogeneous area that differs from its surroundings) per unit area (standardized to 100 ha in FRAGSTATS). The patch density is given by: (1)${\displaystyle \mathrm{PD}=\mathrm{N∕A},}$

where N is the number of patches and A is the total area of habitats. PD varies from 0 to infinity. Larger PD values indicate that the habitat is more fragmented but does not take into account the size of each patch (McGarigal & Marks, 1995; Saura & Martinez-Millan, 2001).

Reasons for limited ranging behavior

A detailed understanding of primate movement ecology offers important information for developing effective policies of wildlife management and conservation (Allen & Singh, 2016). Ren et al. (2009b) studied the correlation between the the DPL of R. bieti and ambient temperature. They argued that the reduced DPL in winter was a response to thermoregulatory factors associated with reducing energy expenditure during cold temperatures. Similarly, Liu, Ding & Grueter (2004) suggested that the limited movements of R. bieti at Mt. Fuhe represented a compromise between reduced food availability and cold temperatures. In this study, we found that the cost distance for R. bieti was significantly greater in the winter than during other seasons of the year, and that DPL also was the shortest in winter, averaging 1,411 m. This is consistent with the contention that several ecological factors including landscape heterogeneity, which was greater in areas exploited during the winter, limited the ranging behavior of R. bieti (Deng et al., 2014). In addition, in winter, R. bieti occupied the smallest home range (Ren et al., 2009a), supporting the conclusion that increased cost distance and access to large and concentrated food patches affect the ranging behavior of this primate species. We note, however, that given our limited sample size (21 complete days), these conclusions must be viewed as tentative.

Impact of habitat fragmentation on movement of R. bieti

Our study suggests that habitat fragmentation also affected the movement of R. bieti. Specifically, they exploited the largest home range and had the greatest DPL in autumn. Autumn represents a time of the year when the mnonkeys utilized less fragmented areas. In contrast during the winter, they exploited highly fragmented habitats had a reduced DPL. This is consistent with a study by Irwin (2008) of the Diademed sifaka. In this lemur species, groups in forest fragments traveled less each day than groups in continuous forest. Habitat disturbance also was reported to have a significant effect on the ranging behavior of roe deer (Capreolus capreolus) in southwestern France. These deer were found to avoid disturbed habitats (Coulon et al., 2008).

Fragmented forests are characterized by reduced biodiversity and for some primate species this results in a reduction in food availability and an increase in feeding effort (Virgós, 2001; Zimbres, Peres & Machado, 2017). The strategies of different primates to habitat fragmentation are varied (Onderdonk & Chapman, 2000). In the face of human disturbance, the Sichuan snub-nosed monkey (Rhinopithecus roxellana) was found to travel long-distances per day (Li et al., 2005). In areas in which human disturbance was limited, R. roxellana traveled approximately 1100 m per day, however, the breeding band traveled 1600 m per day in more fragmented habitats. In contrast, studies have shown that in fragmented forests, primates such as the Diademed sifaka (Irwin, 2008) and the collared brown lemur (Eulemur collaris) (Campera et al., 2014) conserve energy and cope with the lower food availability by traveling shorter distance per day. Based on the results of the current study, we found that when exploiting more fragmented habitats in the winter, R. bieti was found to exploit a smaller home range and concentrate their ranging activities to lower altitude forests characterized by warmer temperatures. These forest zones contained an abundance of lichen (Grueter et al., 2012; Grueter et al., 2009). Lichens are generally widespread in primary forest and available year-round, making them a key dietary resource for R. bieti, who exploits lichen during all months of the year (Grueter et al., 2009; Huang et al., 2017; Xiang et al., 2007).

The suitability of Yunnan pine forest

Our results suggest that the monkeys alter their pattern of habitat utilization seasonally, likely in response to changes in the distribution and availability of currently available feeding sites. In winter, they spent inhabited Yunnan pine forest (needs more data to support). Yunnan pine forest contains several species of lichens, which can account for more than 80% of winter feeding time (from November to March) (Grueter et al., 2009). Yunnan pine forest has a lower lichen index (1.39) than does spruce-fir forest (which has a lichen index of 1.81), however, the former is found at an elevation of 2,500–3,200 m, which is lower and warmer than spruce-fir forest (3,500–4,000 m) (Grueter et al., 2009; Li et al., 2008). In addition, Yunnan pine forest is phototropic, tends to grow in warmer areas, and therefore may offer thermoregulatoy benefits during the winter (Chen et al., 2012).

In our study we considered Yunnan pine forest to be an unsustainable habitat for R. bieti because it contains Matsutake mushrooms, which have a high economic value to members of the local human communities and therefore is characterized by high human disturbance (Li et al., 2008; Xiao et al., 2003). However, Matsutake mushrooms are collected only during the summer and the monkeys were observed to exploit this habitat during the winter. Thus, it is critical to obtain data on seasonal patterns of habitat use for both the human and nonhuman primate communities in order to develop effective conservation solutions for a given species. Although in general, the snub-nosed monkeys avoided areas of high-intensity human disturbance, during the winter most of their activity time occurred in Yunnan pine forest. We hypothesize that due to its warmer microclimate, abundance of lichen, and decreased human activity, Yunnan pine forest represents a critical winter habitat for R. bieti. This hypothesis will be tested more rigorously in our future research.

Reduced DPL in winter

Our results reveal that the DPL of R. bieti in winter (1411 m) was shorter than in spring and autumn. These results are consistent with Ren et al. (2009b) who studied this Yunnan snub-nosed monkey breeding band 10 years earlier. In that study, DPL was shortest in the winter (874 m). Similarly, Grueter et al. (2013) studying the same breeding band found that DPL in the winter (985 m) was lower than during other seasons of the year. Our estimate of DPL, was approximately 30% larger than found in previous studies. This could reflect that fact Grueter et al.’s (2013) data were based on a four-season model, and data were collected for one month per season (January, April, July and September). In the case of Ren et al.’s (2009a) and Ren et al.’s (2009b) study, they divided the year into three seasons. In that study, data on breeding band location were collected using a single GPS collar that was affixed to a healthy adult male who was a leader male of a one-male unit (OMU) in the breeding band. Given that OMU females are pregnant during the winter, it is possible that a decrease in winter ranging behavior represents an attempt to reduce prenatal reproductive costs to breeding females. Finally, in our study we collected data for only three month in winter (November, March and April). However, our method of collecting GPS data by tracking the breeding band (similar to the method used by Grueter et al., 2013) was limited because we could only obtain 3-4 location points per day. Therefore, the actual distance traveled per day by wild R. bieti remains unclear. However, what was consistent among these three studies was that the monkeys traveled shorter distances per day in the winter than during other times of the year, which could reflect seasonal differences in day length, seasonal differences in resource distribution and availability, or seasonal differences in predation-risk and reproduction.

Implications for conservation and management

Long-term monitoring of R. bieti in both more and less fragmented landscapes contributes to our understanding of patterns of habitat utilization and feeding ecology (Irwin, 2008). Such data are essential for developing management plans for species conservation and habitat restoration. Recent genetic evidence indicates that human-induced habitat fragmentation has led to a decrease in the population size and genetic variability of R. bieti (Li et al., 2014). Based on our results, we recommend that improved habitat suitability for the Yunnan snub-nosed monkey requires protecting existing spruce-fir forests, regenerating new spruce-fir forests, constructing corridor between spruce-fir forests and Yunnan Pine Forest in order to promote movement, dispersal, and increased gene flow across breeding bands. These conservation actions represent important steps in protecting and restoring suitable habitat and in decreasing the extinction risk of isolated subpopulations of R. bieti.