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Soil microorganism studies are crucial in ecological and biological research. However, the lack of standardized analytical methods for sampling makes it challenging to compare studies and obtain consistent results. Therefore, it is essential to establish standardized sampling methods in the field. Our study used a stratification method to collect 120 soil samples from various altitudinal ranges on Cangshan Mountain in China, with an altitude of 4122 m, and incredible microorganism biodiversity. This site provides an ideal landscape for studying elevation patterns in microorganisms. We conducted analyses on the variations of depth and stratification used in the sampling process, as these factors have been found to impact microbial diversity, elevation patterns, and community assembly mechanisms. We found that increasing the sampling depth provided more valuable research results by revealing elevation patterns of soil microorganisms. We therefore recommend sampling to a depth of 35 cm with stratification to determine the overall soil microbial diversity. A depth of 25 cm is suitable for studying elevation patterns with stratification. For investigating community assembly mechanisms without stratification, a depth of 15 cm is recommended. When exploring a specific taxon, the sampling depth can be adjusted accordingly. For studying the elevation pattern of archaea, a depth of 20 cm is appropriate. In the case of fungi, a depth of 40 cm is recommended, while a depth of 20 cm is suitable for studying elevation patterns. This study emphasizes the importance of standardization in sampling methods, particularly along the soil profiles, when studying soil microbiomes in montane areas. These recommendations should be adopted in future research to achieve more consistent and reliable results in the field.

Black‐and‐white snub‐nosed monkeys (Rhinopithecus bieti) rely on behavioral and dietary flexibility to survive in temperate latitudes at high‐elevation habitats characterized by climate and resource seasonality. However, little is known about how elevation influences their behavioral and dietary flexibility at monthly or seasonal scales. We studied an isolated R. bieti population at Mt. Lasha in the Yunling Provincial Nature Reserve, Yunnan, China, between May 2008 and August 2016 to assess the impacts of elevation on feeding behavior and diet. Across our sample, R. bieti occupied elevations between 3031 and 3637 m above mean sea level (amsl), with a 315.1 m amsl range across months and a 247.3 m amsl range across seasons. Contrary to expectations, individuals spent less time feeding when ranging across higher elevations. Lichen consumption correlated with elevation use across months and seasons, with individuals spending more time feeding on this important resource at higher elevations. Leaf consumption only correlated with elevation use during the spring. Our results suggest that R. bieti do not maximize their food intake at higher elevations and that monthly and seasonal changes in lichen and leaf consumption largely explain variation in elevation use. These findings shed light on the responses of R. bieti to environmental change and offer insight into strategies for conserving their habitats in the face of anthropogenic disturbance. Research Highlights: Black‐and‐white snub‐nosed monkeys (Rhinopithecus bieti) spend less time feeding in months and seasons when occupying higher‐elevation habitats.Leaves only comprise a higher percentage of the R. bieti diet when occupying higher‐elevation habitats in the spring.Lichen comprise a higher percentage of the R. bieti diet in months and seasons when occupying higher‐elevation habitats. [ABSTRACT FROM AUTHOR]

Provisioning can significantly affect the ranging patterns, foraging strategies, and time budget of wild primates. In this study, we document for the first time, the effects of provisioning on the activity budget and foraging effort in an Asian colobine. Over 3‐years, we used an instantaneous scanning method at 10‐min intervals to collect data on the activity budget of a semiprovisioned breeding band (SPB) of black‐and‐white snub‐nosed monkeys (Rhinopithecus bieti) (42–70 individuals) at Xiangguqing (Tacheng), Yunnan, China. We then compared the effects of provisioning in our study band with published data on a sympatric wild nonprovisioned breeding band (NPB) of R. bieti (ca. 360 monkeys) at the same field site. The SPB spent 25.6% of their daytime feeding, 17.1% traveling, 46.9% resting, and 10.3% socializing. In comparison, the NPB devoted more time to feeding (34.9%) and socializing (14.1%), less time to resting (31.3%), and was characterized by a greater foraging effort (1.74 versus 0.96, foraging effort = (feeding + traveling)/resting; see Methods). There was no difference between bands in the proportion of their activity budget devoted to traveling (15.7% vs. 17.1%). In addition, the SPB exhibited a more consistent activity budget and foraging effort across all seasons of the year compared to the NPB. These findings suggest that the distribution, availability, and productivity of naturally occurring feeding sites is a major determinant of the behavioral strategies and activity budget of R. bieti. Finally, a comparison of our results with data on six nonprovisioned R. bieti bands indicates that caution must be raised in meta‐analyses or intraspecific comparisons of primate behavioral ecology that contain data generated from both provisioned and nonprovisioned groups. Research Highlights: We studied the activity budget of a semiprovisioned band of black‐and‐white snub‐nosed monkeys and compared the results with six wild nonprovisioned bands.The semiprovisioned band spent less time feeding, more time resting, and had a lower foraging effort than the nonprovisioned bands.Caution must be exercised in conducting meta‐analyses when using data from both provisioned and nonprovisioned primate bands. [ABSTRACT FROM AUTHOR]

Simple Summary: Sexual dimorphism widely exists in animals and is reflected in different forms; of these, body mass dimorphism is the most prominent. Studies on the development and adaptation mechanism of sexual dimorphism in body mass can help us to understand how animals adapt to their environment via sexual dimorphism. As this has not been widely reported in Rhinopithecus, this study explores the ontogenetic development pattern of sexual dimorphism in the body mass of R. bieti, and interprets the causes resulting in extreme sexual dimorphism. The results showed that a significant dimorphism appears when females enter the reproductive period, reaching the maximum when males are mature for reproduction. It was determined that a period of decline begins after 8 years of age, and that males had a longer growth period than females. The large sexual dimorphism in body mass in R. bieti can be explained by both Bergmann's and Rensch's rules; however, the females' choice for males may not be significantly related to it. Overall, environmental adaptation, a distinctive alimentary system, and complex social structure have allowed R. bieti to have remarkable sexual dimorphism in body mass compared to other colobines. This study will undoubtedly highlight the same issues on the other 26 primate species in China, particularly the colobines, which will enrich research designs and enlarge research focus on China's primatology. Sexual dimorphism exists widely in animals, manifesting in different forms, such as body size, color, shape, unique characteristics, behavior, and sound. Of these, body mass dimorphism is the most obvious. Studies of evolutionary and ontogenetic development and adaptation mechanisms of animals' sexual dimorphism in body mass (SDBM), allow us to understand how environment, social group size, diet, and other external factors have driven the selection of sexual dimorphism. There are fewer reports of the ontogenetic development of sexual dimorphism in body mass in Rhinopithecus. This study explores the ontogenetic development pattern of SDBM in wild black-and-white snub-nosed monkeys (R. bieti), and the causes resulting in extreme sexual dimorphism compared to other colobines. A significant dimorphism with a ratio of 1.27 (p < 0.001) appears when females enter the reproductive period around six years old, reaching a peak (1.85, p < 0.001) when males become sexually mature. After the age of eight, the SDBM falls to 1.78, but is still significant (p < 0.001). The results also indicate that males had a longer body mass growth period than females (8 years vs. 5 years); females in larger breeding units had a significantly higher SDBM than those in smaller ones (2.12 vs. 1.93, p < 0.01). A comparative analysis with other colobines further clarifies that Rhinopithecus and Nasalis, which both have multilevel social organization, have the highest degree of SDBM among all colobines. The large SDBM in R. bieti can be explained through Bergman's and Rensch's rules. Overall, environmental adaptation, a distinctive alimentary system, and a complex social structure contribute to R. bieti having such a remarkable SDBM compared to other colobines. In addition, we found that females' choice for males may not be significantly related to the development of SDBM. [ABSTRACT FROM AUTHOR]

Food availability and climate represent environmental factors that affect species' social behavior, ranging patterns, diet, and activity budget. From August 2012 to September 2013, we examined the effects of seasonal changes in food availability, temperature, and rainfall on the diet and behavioral ecology of Shortridge's langur (Trachypithecus shortridgei) an Endangered primate species inhabiting moist evergreen broadleaf forests in the Eastern Himalayas. Our field site represents the northernmost latitudinal distribution of this species. Data were collected using scan sampling at 10 min intervals, and analyzed based on generalized linear models. The results indicate that the langurs experienced two feeding peaks (9:00 and 17:00) and two traveling peaks (10:00 and 19:00) during each day. Periods of rest, mainly occurred between 10:00 and 13:00, and overnight. Feeding accounted for 38.5% of the daily activity budget, followed by resting (35%), traveling (24.5%), and socializing (2%). During periods when young leaves were most available, the langurs increased feeding time on young leaves (35% vs. 4%). During periods of maximum fruit availability, the langurs decreased total time spent feeding (36.6% vs. 40.4%), devoted more time to traveling (28.1% vs. 21%), and increased time spent consuming fruit (49.1% vs. 11.8%). During the winter, the langurs increased their consumption of mature leaves (44.5%) and reduced time spent traveling (20.2% vs. 25.4%). Overall, time spent resting was greatest in the spring (47.5%), time spent feeding was greatest during the summer (51.1%), and time spent in traveling was greatest in the autumn (33.2%). The frequency of social interactions remained relatively constant throughout the year. Foraging effort was greatest in the summer, when fruits dominated the diet. Like other species of temperate langurs, T. shortridgei devoted less time to resting, more time to feeding, and was characterized by a greater year‐round foraging effort than tropical/subtropical langurs. Research Highlights: This is the first study examining the activity budget and feeding effort of the Endangered Trachypithecus shortridgei.Food availability played a more critical role in the foraging effort and activity budget of Trachypithecus shortridgei than did rainfall or temperature.Similar to other temperate Trachypithecus species, T. shortridgei in the Gaoligong Mountains adopted a time minimizing behavioral strategy and had a greater annual foraging effort than tropical langur species. [ABSTRACT FROM AUTHOR]

Camera traps often produce massive images, and empty images that do not contain animals are usually overwhelming. Deep learning is a machine‐learning algorithm and widely used to identify empty camera trap images automatically. Existing methods with high accuracy are based on millions of training samples (images) and require a lot of time and personnel costs to label the training samples manually. Reducing the number of training samples can save the cost of manually labeling images. However, the deep learning models based on a small dataset produce a large omission error of animal images that many animal images tend to be identified as empty images, which may lead to loss of the opportunities of discovering and observing species. Therefore, it is still a challenge to build the DCNN model with small errors on a small dataset. Using deep convolutional neural networks and a small‐size dataset, we proposed an ensemble learning approach based on conservative strategies to identify and remove empty images automatically. Furthermore, we proposed three automatic identifying schemes of empty images for users who accept different omission errors of animal images. Our experimental results showed that these three schemes automatically identified and removed 50.78%, 58.48%, and 77.51% of the empty images in the dataset when the omission errors were 0.70%, 1.13%, and 2.54%, respectively. The analysis showed that using our scheme to automatically identify empty images did not omit species information. It only slightly changed the frequency of species occurrence. When only a small dataset was available, our approach provided an alternative to users to automatically identify and remove empty images, which can significantly reduce the time and personnel costs required to manually remove empty images. The cost savings were comparable to the percentage of empty images removed by models. [ABSTRACT FROM AUTHOR]

Abstract: Species distribution modeling (SDM) at fine spatial resolutions requires species occurrence data of high positional accuracy to achieve good model performance. However, wildlife occurrences recorded by patrols in ranger‐based monitoring programs suffer from positional errors, because recorded locations represent the positions of the ranger and differ from the actual occurrence locations of wildlife (hereinafter referred to as positional errors in patrol data). This study presented an evaluation of the impact of such positional errors in patrol data on SDM and developed a heuristic‐based approach to mitigating the positional errors. The approach derives probable wildlife occurrence locations from ranger positions, utilizing heuristics based on species preferred habitat and the observer's field of view. The evaluations were conducted through a case study of SDM using patrol records of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) in Yunnan, China. The performance of the approach was also compared against alternative sampling methods. The results showed that the positional errors in R. bieti patrol data had an adverse effect on SDM performance, and that the proposed approach can effectively mitigate the impact of the positional errors to greatly improve SDM performance. [ABSTRACT FROM AUTHOR]

Abstract: Studies on volunteered geographic information (VGI) have focused on examining its validity to reveal geographic phenomena in relatively recent periods. Empirical evaluation of the validity of VGI to reveal geographic phenomena in historical periods (e.g., decades ago) is lacking, although such evaluation is desirable for assessing the possibility of broadening the temporal scope of VGI applications. This article presents an evaluation of the validity of VGI to reveal historical geographic phenomena through a citizen data‐based habitat suitability mapping case study. Citizen data (i.e., sightings) of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) were elicited from local residents through three‐dimensional (3D) geovisualization interviews in Yunnan, China. The validity of the elicited sightings to reveal the historical R. bieti distribution was evaluated through habitat suitability mapping using the citizen data in historical periods. The results of controlled experiments demonstrated that suitability maps predicted using the historical citizen data had a consistent spatial pattern (correlation above 0.60) that reflects the R. bieti distribution (Boyce index around 0.90) in areas free of significant environmental change across historical periods. This in turn suggests that citizen data have validity for mapping historical geographic phenomena. It provides supporting empirical evidence for potentially broadening the temporal scope of VGI applications. [ABSTRACT FROM AUTHOR]

The vast accumulation of environmental data and the rapid development of geospatial visualization and analytical techniques make it possible for scientists to solicit information from local citizens to map spatial variation of geographic phenomena. However, data provided by citizens (referred to as citizen data in this article) suffer two limitations for mapping: bias in spatial coverage and imprecision in spatial location. This article presents an approach to minimizing the impacts of these two limitations of citizen data using geospatial analysis techniques. The approach reduces location imprecision by adopting a frequency-sampling strategy to identify representative presence locations from areas over which citizens observed the geographic phenomenon. The approach compensates for the spatial bias by weighting presence locations with cumulative visibility (the frequency at which a given location can be seen by local citizens). As a case study to demonstrate the principle, this approach was applied to map the habitat suitability of the black-and-white snub-nosed monkey (Rhinopithecus bieti) in Yunnan, China. Sightings ofR. bietiwere elicited from local citizens using a geovisualization platform and then processed with the proposed approach to predict a habitat suitability map. Presence locations ofR. bietirecorded by biologists through intensive field tracking were used to validate the predicted habitat suitability map. Validation showed that the continuous Boyce index (Bcont(0.1)) calculated on the suitability map was 0.873 (95% CI: [0.810, 0.917]), indicating that the map was highly consistent with the field-observed distribution ofR. bieti. Bcont(0.1) was much lower (0.173) for the suitability map predicted based on citizen data when location imprecision was not reduced and even lower (−0.048) when there was no compensation for spatial bias. This indicates that the proposed approach effectively minimized the impacts of location imprecision and spatial bias in citizen data and therefore effectively improved the quality of mapped spatial variation using citizen data. It further implies that, with the application of geospatial analysis techniques to properly account for limitations in citizen data, valuable information embedded in such data can be extracted and used for scientific mapping. [ABSTRACT FROM AUTHOR]

There exists very limited information on the set of scavengers that feed on the carcasses of wild primates. Here, we describe, based on information collected using a remote camera trap, carnivores consuming/scavenging the carcass of a wild golden snub-nosed monkey (Rhinopithecus roxellana) in the Laohegou Nature Reserve, Sichuan, China. During a 3 month behavioral and ecology study of a band of golden snub-nosed monkeys (March through May 2013), we encountered the carcass of an adult male (male golden snub-nosed monkeys weigh approximately 12–16 kg). After examining the dead monkey, we returned it to the death site and set out a camera trap to record the behavior and identity of scavengers. Over the course of 25 days, we collected 4145 photographs taken by the camera trap. Scavengers identified from these photographs include a masked civet (Paguma larvata), Asiatic black bear (Ursus thibetanus), large-billed crow (Corvus macrorhynchos) and the chestnut rat (Rattus fulvescens). No member of the golden snub-nosed monkey's social group, which was composed of approximately 120 individuals, was found to return to the general area of the death site. The masked civet fed principally on the face and intestines of the corpse at night, while the black bear consumed most of the body of the dead monkey during both the daytime and nighttime. These two taxa consumed virtually the entire carcass in one week. We suggest that the use of camera traps offers a powerful research tool to identify the scavenger community of a given ecosystem. [ABSTRACT FROM AUTHOR]

There exists very limited information on the set of scavengers that feed on the carcasses of wild primates. Here, we describe, based on information collected using a remote camera trap, carnivores consuming/scavenging the carcass of a wild golden snub-nosed monkey (Rhinopithecus roxellana) in the Laohegou Nature Reserve, Sichuan, China. During a 3 month behavioral and ecology study of a band of golden snub-nosed monkeys (March through May 2013), we encountered the carcass of an adult male (male golden snub-nosed monkeys weigh approximately 12–16 kg). After examining the dead monkey, we returned it to the death site and set out a camera trap to record the behavior and identity of scavengers. Over the course of 25 days, we collected 4145 photographs taken by the camera trap. Scavengers identified from these photographs include a masked civet (Paguma larvata), Asiatic black bear (Ursus thibetanus), large-billed crow (Corvus macrorhynchos) and the chestnut rat (Rattus fulvescens). No member of the golden snub-nosed monkey's social group, which was composed of approximately 120 individuals, was found to return to the general area of the death site. The masked civet fed principally on the face and intestines of the corpse at night, while the black bear consumed most of the body of the dead monkey during both the daytime and nighttime. These two taxa consumed virtually the entire carcass in one week. We suggest that the use of camera traps offers a powerful research tool to identify the scavenger community of a given ecosystem. [ABSTRACT FROM AUTHOR]

Golden snub-nosed monkey (Rhinopithecus roxellana) is one of the most endangered primate species found in China, exhibiting multilevel society consisting of several one-male-females together with their offspring units (OMU), and all-male units (AMU). Female dispersal patterns of the species within herd have been well documented, whereas those of the males within or between herds are still poorly understood. Our results based a long-term observation indicate that more than half of sub-adult males, and half of the deposed males that stayed a short period in OMU disperse between herds, three of them established their own OMU in new herd after the dispersal. Smaller number of the sub-adult and adult males, compared with adult females, stayed in natal herd, implying sub-adult males started dispersing and male-biased dispersal occurred between herds. High frequencies of resident males were wounded as their OUMs were taken over, and resident males co-operation defend bachelor males were found. Mating competition among males within the herd may have contributed to the scenarios of male-biased dispersal. The results also suggest that maintaining connection between isolated herds and establishing the corridors among the fragmented habitats for the species will greatly benefit increasing its gene flow and promoting conservation status. [ABSTRACT FROM AUTHOR]

• Here we provide a detailed description of male birth attendance during a diurnal birth event in nonhuman primate. • The 2nd observed diurnal birth event in Rhinopithecus bieti. • We suggest that infant attraction or 'Aunt behavior' offers the strongest explanation of cases of birth assistance and attendance in nonhuman primates. Birth attendance, or midwifery service, is an important characteristic in human evolution, and has been argued to separate our lineage from other taxa in the animal kingdom. Recent studies, however, indicate that similar or analogous behaviors also may occur in a small number of nonhuman primate species. Here, we report the first case of both male and female attendance and female birth assistance in a wild species of nonhuman primate, the black-and-white snub-nosed monkey (Rhinopithecus bieti). At our field site in Yunnan, China we observed a diurnal birth event in which the leader male of a one-male unit (OMU) remained in close- proximity (0–2 m) to the parturient, groomed her, and remained vigilant over a five hour pre- and postpartum period. In addition, a multiparous female member of the OMU also remained in close proximity to the soon-to-be mother, helped to pull the neonate from the birth canal, took the neonate from the new mother within 15 s of the birth, held the infant for 20 min, and then severed the umbilical cord. For the next several days the leader male traveled in close-proximity to the new mother and four days after the birth event, we observed him to share food with her. Given that diurnal births are extremely rare in this primate species; it remains unclear the degree to which the events we observed commonly occur during nighttime births. We argue that adult male and female black-and-white snub-nosed monkeys are highly attracted to young infants, and birth attendance and birth assistance in this, and certain other primate species, may play a critical role in maternal and infant survivorship. [ABSTRACT FROM AUTHOR]

The black snub-nosed monkey ( Rhinopithecus strykeri ) is an IUCN-Critically Endangered primate, recently discovered on the northern Sino-Myanmar border. In order to identify the most urgent gaps in the conservation of the black snub-nosed monkey, a hierarchical process was employed to predict the distribution and alterations in its habitat over the past 15 years. Our study showed that R. strykeri appeared to inhabit a range from E98°20′–98°50′, N25°40′–26°50′, including high quality habitat at 1420 km 2 , medium quality habitat at 750 km 2 , and low quality habitats at 1410 km 2 . Only 21.1% of the total habitat for R. strykeri is within protected areas in China. Approximately 2.6% of the entire habitat has been lost in the past 15 years, 96% of which has been in Myanmar. To save this species from extinction, it is urgent to establish trans-boundary conservation and management networks to address the loss of habitat, and to locate and preserve key wildlife corridors to link fragmented habitats between Myanmar and China. [ABSTRACT FROM AUTHOR]

• A framework for integrating multi-source wildlife data for habitat mapping. • A case study of Rhinopithecus bieti habitat mapping was conducted in Yunnan, China. • Sightings from volunteer villagers and official patrol records were integrated. • Data integration improved habitat mapping accuracy. • The integration framework can support biodiversity monitoring and conservation. Wildlife habitat mapping is a widely used tool for supporting decision making in conservation. It requires data indicating wildlife habitat use to model and map habitat suitability. Collecting wildlife data, however, requires much effort, especially for species in remote mountainous regions of limited accessibility. Such circumstances often necessitate the integration of limited amounts of data available from multiple sources for habitat mapping. To that end, this study presents a framework for integrating multi-source wildlife data for habitat mapping. For evaluating the integration framework, a case study of mapping habitat suitability of the black-and-white snub-nosed monkey (Rhinopithecus bieti) by integrating sightings elicited from local volunteer villagers and obtained from official patrol records was conducted in Yunnan, China. The integration was explored at three levels: data-, knowledge- and model-level following disparate principles. The predicted habitat suitability maps were validated against monkey occurrence data independently collected though field-tracking. Results show the suitability maps predicted based on data integration were more accurate compared to maps predicted based on individual data sources. Data- and model-level integration achieved higher accuracy compared to knowledge-level integration. Further, data- and model-level integration following a conservative principle, i.e., the 'minimum' operator, led to higher mapping accuracy. The integration framework is generally applicable for integrating data from multiple sources for habitat mapping. It is also easy to implement and thus can be conveniently adopted by practitioners. Habitat suitability maps generated based on integrated data from multiple sources could better supporting decision making in biodiversity monitoring and conservation. [ABSTRACT FROM AUTHOR]