Species distribution model and
inspection
All
SDMs use the correlation between the species sample data and
environmental variables to estimate the ecological niche of the species
according to a specific method and show the correlation to the studied
area (Panda & Behera, 2019; Thorson, 2019; Wang et al., 2019; Yu et
al., 2019). We predicted the distribution of birds by using
the
MaxEnt model, which only uses existing events to study the principle of
balance and simulates the absent data from the background(Manish &
Pandit, 2019). It defines the correlation
between species and the environment
variables, and predict the distribution according the present sample
data
(Dudik et al., 2007; Dudik et al., 2004; Phillips et al., 2006; Phillips
& Dudik, 2008). The
distribution
which has the highest entropy is selected to be the optimal distribution
from all the eligible distribution.
We used the default settings and divided the data into two parts, 75%
for modeling and 25% for evaluating.
The jackknife test was done in MaxEnt to recognize the importance of
variables, and the benefit of the test is to give the approximate
confidence intervals for many parameters (Jacome et al., 2019;
Shcheglovitova & Anderson, 2013).
The
Area Under Curve (AUC), the proportion under the Receiver Operating
Characteristic Curve (ROC), was used to evaluate the performance of
model (Phillips et al., 2006). The
AUC
value is positively correlated with the model, so we picked the model
with AUC value over 0.8 seeing at Table S2 (Elith et al., 2011; Fourcade
et al., 2014).
Index of habitat change
2.4.1 The habitat loss
The
decrease of habitat area is the main threat to the decline in
biodiversity which is caused by climate change (Taubert et al.,
2018).
There
is a continuous distribution suitability map coming from the model. To
calculate the habitat loss, the “maximum training sensitivity plus
specificity logistic
threshold(MaxSSS)”
was used to classify the continuous distribution suitability into the
binary distribution map (Saupe et al., 2019; Vale et al., 2014).
We also calculated the mean
suitability of the map. The calculating of habitat loss is based on the
comparison between the suitable area in current and future scenarios. It
was described as habitat loss when the suitable area turns to the
unsuitable area and the opposite is habitat gain..
2.4.2 The population centroid
The
population
centroid is regarded as the represented indicator reflecting the
population movement process (Collins et al., 2017; Liu et al.,
2019).We
calculated
the
population centroid of the habitat
for migratory birds in
longitude
(X)
and
latitude (Y) to explain the bias in
future.
After
compared the population centroid of the species , we take the average
offset distance in two scenarios
X=\(\frac{\sum{X_{i}P_{i}}}{P}\)Y=\(\frac{\sum{Y_{i}P_{i}}}{P}\)
where\(X_{i}\)and\(Y_{i}\ \)is
the longitude and latitude of the site , and\(P_{i}\)is the sustainability at site, and P is the total sustainability .
Results
Spatial changes of habitat and the shift of
population
centroid
Based on the current and the two future scenarios, the models simulated
the distribution of 7 orders of migratory birds and the endangered birds
well by checking the AUC
value(Table
S1). The current and future potential geographical distribution of birds
in China is shown in Fig.S1.
Table
2. Result of models assessing how climate influence the habitat change.