4 DISCUSSION
4.1 The potential geographical distribution of
species
Habitat is a vital place for survival, reproduction and population
development of species. Its quality can directly influence the
distribution, quantity and survival rate of species (Hall et al., 1997;
Zhang et al., 2019). We utilized the MaxEnt model to predict the
potential geographical distribution of 25 rare, endangered and/or
national protected plant species in Northwest Yunnan. The results showed
that the potential distribution area (i.e., Region where HSI ≥ 0.4) of
each species was between 826.33 km2 and 44,963.53
km2, which indicated that these species had obvious
differences in their adaptability to environmental factors such as the
topography and climate in Northwest Yunnan. The potential distribution
area of these target species
were
mainly concentrated in the mid-western, mid-eastern and northern parts
of the study area, which was in good agreement with the prediction
results of the potential distribution area which studied by Zhuang et
al. (2018a). The prediction results of this study will provide possible
new areas for species distribution and field investigation. In addition,
the potential distribution area of species overlapped greatly in the
mid-western and northern parts of Northwest Yunnan. We roughly divided
them into two parts. One part was close to the Gaoligong Mountain and
Baima Snow Mountain NNRs, which were almost consistent with the hotspot
distribution of key higher plant species in Northwest Yunnan (Ye et al.,
2020a). Similarly, the other part was located in Shangri-La County,
which might be related to the fact that Shangri-La is situated at the
core area of the Three Parallel Rivers World Natural Heritage Site (Yang
et al., 2013), with abundant landscape types, vegetation types, and
ecosystem types. Consequently, the results reflected that these regions
mentioned above will play a crucial role in
biodiversity
conservation in the future.
4.2 A model used to predict the distribution of
species
The model prediction method can help to compensate for the difficulty in
field investigation.
The
vertical
peaks and horizontal valleys in Northwest Yunnan greatly limit the
accessibility of field surveys. Hence, by combining the model prediction
with field investigation, the field survey can be carried out in the
order of habitat suitability, with priority given to the field
investigation in the optimal suitability distribution area and the
potential distribution area that has not been studied. In addition, the
completeness, accuracy and reliability of species geographical
distribution data
are
important and key links of division of key biodiversity areas.
Meanwhile, the accuracy of the data and the precision of the model
prediction are also mutually promoted (Zhang et al., 2016; Wu et al.,
2016; Zhuang et al., 2018a). In this study, we tried our best to collect
a lot of species distribution data through multiple approaches, but
there are still some species with relatively less distribution data. For
example, Coptis teeta is also distributed in Myanmar and other
countries. Therefore, more species distribution data must be collected
to construct a more accurate species distribution model. In addition,
the distribution of species is not only determined by topography,
climate and edaphic factors, but also influenced by social and economic
structure, land use type, human disturbance and other social factors. In
some cases, due to the influence of the local microenvironment, the
areas predicted to be of lower suitability levels are actually the
distribution areas of species. Therefore, the results obtained in this
study are only advisory. A more precise and accurate potential
distribution prediction needs to be supported by more comprehensive
social and environmental factors and more precise and more reliable
species distribution information.
4.3 Environmental explanations for the potential
distribution of
species
From an ecological point of view, environmental factors can affect the
spatial distribution of species, as well as their habitat suitability
(Zhang et al., 2019). In this study, we found that the cumulative
contribution rate of Bio12 (25.92%), Bio19 (15.86%) and Pop (17.95%)
to the MaxEnt model prediction results reached 59.73%. Furthermore, the
contribution rate of Bio12 was the highest, which was consistent with
the results obtained by Zhuang et al.
(2018).
In addition, the R 2 values of the GWR model
were all above 0.80, indicated that the model has a reliable goodness of
fit for explaining the potential distribution of species. Moreover, the
water model (R 2 = 0.88, AIC = 7703.82) showed a
higher explanation rate compared to other single models, followed by the
temperature model (R 2 = 0.88, AIC = 7939.56)
and topographical model (R 2 = 0.88, AIC =
7900.40), which were second only to the water model in their
interpretation effect on the potential distribution of species.
Accordingly, this result suggested that climate (temperature and water
factor) and habitat heterogeneity (topographical factor) could play an
important role in the prediction of potential distribution areas of
species, which was coincide with the research results of Ștefănescu et
al. (2017). However, compared with all single models, the comprehensive
model (R 2 = 0.92, AIC = 6785.26) that combines
all environmental factors had a better goodness of fit, which indicated
that the potential distribution of species was the result of the
combined effects of various environmental factors (Wang et al., 2018).
The main thing worth mentioning is that, rare and endangered species are
usually restricted to specialized edaphic or topographic or other
environmental conditions which occupy a quite fraction of their
climatically suitable range. Therefore, on the basis of this study, it
is necessary to study the effects of other relevant environmental
factors on the potential distribution of species.
4.4 Suggestions for the protection of rare and endangered
plant
species
In recent decades, due to the disturbance of human activities and the
impacts of the external natural environment, especially climate change,
the population size and distribution area of some rare, endangered
and/or threatened species had been declining (Yu et al., 2014).
Therefore, understanding the habitat suitability of species and its
influencing factors is the basis of protecting rare and endangered plant
species (Zhang et al., 2019). Habitat suitability plays an important
role in the survival and development of species. Hence, habitat
suitability assessment is the first step of effective conservation and
scientific management of species, and can provide scientific basis for
relevant departments to formulate valid conservation strategies. It has
become a resultful method to protect rare and endangered species by
scientifically predicting the potential distribution areas and habitat
suitability levels of species and planning wild nature reserve in the
best suitable areas (Xiao et al., 2011; Xu et al., 2015). The results of
this study revealed that the habitat suitability of species near
Gaoligong Mountain and Baima Snow Mountain NNRs and Shangri-La Country
was relatively high, and these areas were also the core regions for the
distribution of rare, endangered and/or national protected species in
Northwest Yunnan. For this reason, it is suggested that to strengthen
the conservation of these areas. In addition, Shangri-La Country had
more habitat suitability distribution areas for species, but there were
only three PNRs with a small area, namely, Napahai, Bitahai and Haba
Snow Mountain PNRs (Ye et al., 2020a). It is recommended that
appropriate expansion of the nature reserve should be carried out, with
measures combining in-situ and ex-situ conservation to
strengthen the protection of species in a state of isolation and/or
fragmentation. In addition, the
species distribution model is an estimate of the potential distribution
of species, and its essence is prediction research. Therefore, the
results of the model simulation cannot be used as the only basis for
formulating strategies of species conservation, and corresponding field
surveys should be carried out according to the simulation prediction
results, so as to formulate more scientific and reasonable strategies
for species conservation (Renner & Warton, 2013; Wen et al., 2019).
Correspondingly, by simulating the potential distribution area of
species, it can also provide some basic and scientific evidence for
species reintroduction.