10.5061/DRYAD.M905QFV0F
Yinghui, Jia
0000-0002-5384-4552
China Agricultural University
Fangfang, Li
China Agricultural University
Cang, Ma
Qinghai University
Guangqian, Wang
Tsinghua University
Jun, Qiu
Tsinghua University
Swarm behavior simulation of plateau pika
Dryad
dataset
2020
FOS: Animal and dairy science
National Natural Science Foundation of China
https://ror.org/01h0zpd94
91847302
National Natural Science Foundation of China
https://ror.org/01h0zpd94
51879137
National Natural Science Foundation of China
https://ror.org/01h0zpd94
51979276
2021-12-30T00:00:00Z
2021-12-30T00:00:00Z
en
3167229412 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
As an important species on the Qinghai-Tibet Plateau, the pika has great
controversy in grassland protection and ecological function service. The
population change of pika is related to the fragile and sensitive
ecological chain of Qinghai-Tibet Plateau. The traditional methods of
population density survey include sampling method, marker recapture
method, removal sampling method, etc., which are cumbersome to operate and
consume a lot of manpower and material resources. In recent years, more
and more scholars use camera capture method to characterize or calculate
population density. This method is simple to operate and widely
applicable, but how to establish the relationship between actual
population density and monitoring data under the condition that individual
identification cannot be carried out is a big challenge faced by this
method. In order to solve this problem, the density of pika was estimated
by two methods. First, random encounter model (SEM) was used to estimate
the density of pika based on actual field observation data. Secondly, a
Monte Carlo model is established to describe the behavior of pika and the
practical problems are simulated by using probability statistics. The
results obtained by the two methods are compared and mutually verified,
and it is found that the two model results are in good agreement, and the
probabilistic model can effectively establish the relationship between the
ecological physical parameters of the population and the monitoring
space.
The field observation is implemented in Dari County, which is located in
the southeast of the Qinghai-Tibet Plateau with the geographic coordinates
of 98°15' ~100°33' east longitude and 32°36' ~ 34°15'
north latitude. The average altitude of Dari County is over 4200 m, and it
has an alpine and semi-humid climate, belonging to “National Nature
Reserve of Three Rivers Source” in China. The cameras are installed at 6
different habitat location, which are the benchland of Jiqu River, 100 m
and 300m from the river bank of Jiqu River, beside the road, gentle sunny
slope, and steep sunny slope. A 7-day monitoring was conducted from Aug
12th to Aug 18th, 2019. The foresafe H885 field infrared cameras were
applied under the photo & video mode, and the recording time is
set to be 30s. The camera works 24 hours a day. If an animal enters the
monitoring range of the camera sensor, the camera is triggered and takes a
picture recording the shooting date and time, and then record a video of
30 seconds. After that, it returns to the standby mode. The simulation
model contains a cave system model and a pika behaviour model. First, n
control points are randomly generated in the simulation area to construct
a Delaunay triangulation. Thiessen polygons are divided according to the
given boundary conditions, each of which represents the area occupied by a
cave system. With the given maximum and minimum number of caves in a cave
system and , as well as the minimum distance between any two caves in
the cave system , caves in each cave system are randomly generated. Then,
a certain number of pikas are randomly generated for each cave system
given the maximum and minimum number of pikas for each cave system and
. The pika’s daily ground activity time is , and the fixed time length of
each step when the pika goes out is . Each pika has two alternative
states at each time step, i.e., outside and inside the cave. The behavior
of pikas when going out is classified into two categories: high-intensity
activities, such as running; and low-intensity activities, such as
foraging and playing. The moving direction of a pika in each step is
random with constrained maximize distance.
The full code for the swarm behaviour simulation model is provided. The
program is coded using matlab. Before running the code, one should
download a tool kit named mpt and add it to the path of matlab. Any
suggestions and advice to the code is welcomed. The original video data is
too large, so we only give the raw images instantly taken after the
cameras were triggered. Due to unexpected natural conditions and cameras
overturned, some of the pictures may have people, birds shown up, and some
may be blurry, resulting in varied normal operating days for each camera.
By checking the videos taken after, we determined whether this shoot was
effective or not. If the time interval between two images are less than
two minutes, we assumed that the camera tracked the same pika. Notably, we
are very sorry that we lost the images and videos taken from the benchland
of Jiqu River and some at the steep sunny slope due to computer crush.