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Spatial distribution pattern of mustelids in the eastern edge of the Qinghai-Tibet plateau

Cite this dataset

Liu, Zhoutao; Su, Tengwei; Li, Qian; Li, Zhaoyuan (2024). Spatial distribution pattern of mustelids in the eastern edge of the Qinghai-Tibet plateau [Dataset]. Dryad. https://doi.org/10.5061/dryad.7m0cfxq2w

Abstract

Evolutionary theory predicts that the species of an evolutionarily successful taxon would not overlap in spatial distribution. To test the prediction, we document our research on the spatial associations of mustelids, an evolutionarily successful group of Order Carnivore, using infrared camera trap data on species distribution collected from the national nature reserves of Liancheng, Wolong, Tangjiahe, and Heizhugou in China in 2017-2021. Data showed seven mustelid species occurring in the study area, including Arctonyx collarisMele leucurus, Martes foinaMartes flavigula, Mustela altaica, Mustela nivalis, and Mustela sibirica. Following Ricklefs’ definition of biological community, we identified five networks of species associations. The mustelids occurred in the networks. Species from the same genus, such as M. foina and M. flavigula, stayed in different networks to avoid competition due to similar feeding habits or habitat preferences. Species with different feeding habits or habitat preferences either occurred in different networks, such as M. altaica and M. flavigula, or coexist in the same networks but avoided direct spatial associations, such as M. foina and A. collaris. Asymmetrical associations were found between different genera, such as M. foina and M. altaica; or between different subfamilies, such as M. flavigula and A. collaris. These associations may be attributed to interspecific killing or seed dispersal. However, these associations accounted for only a small proportion and would not impact the species diversity of Mustelidae. It is thus concluded that the prediction is supported by our research findings and that spatial avoidance may be the biogeographic strategy of maintaining the species diversity of the family. We also found that the well protection of the mustelids may benefit to the overall biodiversity conservation in Heizhugou, an NNR that has experienced severe deforestation.

README: Spatial distribution pattern of mustelids in the eastern edge of the Qinghai-Tibet plateau

Description of the data

This dataset includes the occurrence of different species at each camera site ("null" means this species didn't appear in this site ) and the Species List of Terrestrial Animal in four national nature reserves (“√” means this species has been recorded in the reserve; “×” means this species hasn't been recorded in the reserve): Dryad (https://doi.org/10.5061/dryad.7m0cfxq2w)

 

Methods

ArcGIS was used to generate a system of 1 km×1 km grids to cover the map of the four NNRs. NNRs are mountainous environments with many areas that are inaccessible to humans. Thus, a total of ≥5% of accessible grids were randomly selected, and each grid was installed with an infrared camera (models: Yianws L710 and Ltl Acorn 6210), although the large altitude differences and inaccessibility deformed the pattern of camera distribution, which appears unevenly distributed on 2-D maps. An ovital map was used to navigate our field workers to get into the grids to install cameras. The distance between neighboring cameras was maintained at ≥300 m. Cameras were placed in the major habitat types of the grids and fixed on tree trunks or other objects 50-80 cm above the ground, facing parallel to the ground. The angle of the lens allowed the cameras to trap images of animals on the ground in the front scenery and the animals on scrubs and middle canopy in the middle and distant sceneries; therefore, we obtained information on terrestrial and semi-arboreal species. Batteries and memory cards were replaced once every three months. Infrared cameras are triggered by the movement of infrared rays; thus, ectothermic animals do not trigger cameras. Therefore, we obtained thermostatic animals including birds and mammals. The coordinates and altitudes were measured using a compass on the mobile phones. The slopes and aspects were measured using the Ovital Map app on the phones. The height of the vegetation and the canopy coverage were estimated visually.

Because of the different habits of the species, all cameras worked for 12 months to obtain complete data on the distribution of the species. There were 128 sites randomly selected in Liancheng NNR, with cameras continuously working from July 2018 to June 2020; 103 sites in Tangjiahe NNR, with cameras working from September 2019 to December 2020; and 60 sites in Wolong NNR, with cameras working from February 2017 to April 2018. The northern part of Heizhugou NNR was inaccessible, so data were collected in the central and southern parts with 24 cameras working from September 2019 to December 2020. We checked the images and videos and identified the species with reference to Smith and Xie and Mackinnon et al. Murids were identified based on the dental morphological features. Accordingly, our technique did not support the identification, and thus the murids were not identified and we put all murids into a single form “murids”.

Considering that solitary animals and social animals have different ranging behaviors, resulting in different correlations between population density and occurrence frequency at a given site, and that some images with poor definition, especially taken at night, were not good enough to identify individuals, we only recorded information about the presence or absence of a species at a site, ignoring its occurrence frequency. Therefore, the data type is dichotomous. We then counted the number of cameras in which (a) both species in question were present, (b) only one species was present, (c) only the other species were present, and (d) both species were absent. According to Siegel and Castellan, we used the data to calculate the Phi coefficients rø and the Lambda statistics.

Funding

National Forestry and Grassland Administration of China, Award: 2017115