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THE AMERICAN JOURNAL OF AGRICULTURE AND BIOMEDICAL ENGINEERING (ISSN
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VOLUME 06 ISSUE10
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PUBLISHED DATE: - 30-10-2024
DOI: -
https://doi.org/10.37547/tajabe/Volume06Issue10-04
PAGE NO.: - 15-21
BIOCLIMATIC MODELING OF THE SPECIES
JURINEA SCHACHIMORDANICA
(ASTERACEAE)
Rustam Gulomov
Department of Biology, Namangan State University, Namangan, Uzbekistan
Shahnoza Alisherova
Student of Namangan State University, Namangan, Uzbekistan
Shodiyona Umaraliyeva
Student of Namangan State University, Namangan, Uzbekistan
INTRODUCTION
Central Asia is a particularly vulnerable region due
to its physical geography with temperate deserts
and semi-deserts (Lioubimtseva and Henebry
2009). The environment is very sensitive to global
climate change, and it is particularly vulnerable to
changing weather patterns (Brooke 2014).
Especially, water resources in this area are the
main factors for the sustainable development of
biodiversity. There is a low concentration of water
vapor over this area and the distribution of water
resources in Central Asia is very uneven.
Meteorological data have shown that air
temperatures are increasing across Central Asia,
and regional climate change scenarios show that
temperatures will rise by 1°C
–
3°C in the next 20
–
40 years. If global greenhouse gas emissions are
not reduced, temperatures are projected to rise by
3°C to 6°C above today’s levels by the end of the
century (Novikov et al., 2012).
In recent years, the growing demand for natural
medicinal plant and climate change has led to a
reduction in plant stocks. For this reason, much
attention is paid in the world to determine the
species composition of medicinal plants, study
RESEARCH ARTICLE
Open Access
Abstract
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their biological properties, identify natural
resources and bioclimatic modeling, scientifically
substantiating changes in populations as a result of
external.
For the first time, bioclimatic modeling of the
future potential distribution areas of this plant
species is being done using Maxent and ArcGIS
programs. The obtained results allow to sobtain
enough biomass for the creation and production of
plantations of the species in the areas of potential
distribution.
In recent years, the number of studies on
bioclimatic modeling has been increasing
(Gulomov, 2023; Abdullayev, 2024; Nuridinov,
2023; Najmiddinov, 2023).
The following tasks were defined as the research
objective: (1) identify the hot spots of J.
schachimordanica plant in Pamir-Alay under past
climatic conditions. (2) Explore the relationship
between the distribution of hot spots and
environmental factors, and explore the important
environmental factors that limit the distribution of
hot spots. (3) The hot spots of J. schachimordanica
plant in Pamir-Alay were predicted according to
the global climate change scenarios of the future
(2070s).
METHODS
In total 11 species presence records of J.
schachimordanica were incorporated in this
investigation. By searching the Global Biodiversity
Information
Facility
(GBIF;
https://www.gbif.org/), National Herbarium of
Uzbekistan (TASH), Kyrgyz National Herbarium
(FRU) and the results of field research conducted in
the Pamir-Alay regions in 2023-2024 were used.
The point’s record from each herbarium specimens
was
transformed
into
GPS
geographical
coordinates using Google Earth Pro 7.1 and ArcGIS
(version 10.6.1) software.
The current climate data used in this study (1970-
2000) come from the WorldClim database
(http://www.worldclim.org/). The model contains
four emission scenarios proposed by the sixth
International Coupled Models Comparison
Program (CMIP6). This scenarios are developed on
the basis of the typical concentration path (RCPs)
scenario, with a spatial resolution of 2.5 arc
minutes (~4.64 km2 at the equator). The data
contain 19 bioclimatic variables, which are obvious
biologically significant and are usually used in
species distribution and related ecological
modeling. The topographic data contain elevation
variables.
We used MaxEnt software (version 3.4.4) to model
the habitat suitability of J. schachimordanica plant
in Pamir-Alay. This software is considered to build
some of the best performing models for forecasting
species distribution with a limited number of
records. Initially, 11 coordinates in *CSV format
were stored and 19 bioclimatic variables and
altitude values obtained from the WorldClim
database were imported into the MaxEnt model.
From the MaxEnt model, the output map values
range from 0 to 1 (0 least and 1 most suitable
species probability pixels) (Phillips et al., 2006;
Min-Su Park, 2024; Gulomov and Batoshov, 2022;
Gulomov, 2022). In our models, 75% of the
occurrence records were used for training whereas
25% of the records were used for testing the model.
The background points and the number of
iterations were set at no more than 10,000 and
1000, respectively.
When receiving research results the scenarios
RCP2.6_2070s (SSP1-2.6 (ssp126) minimum
greenhouse gases) and RCP8.5_2070s (SSP5-8.5
(ssp585) maximum greenhouse gases) based on
IPCC proposed greenhouse gas concentrations
(RCP) were used. According to the IPCC (2019)
sixth report (AR5), the annual average
temperature is 0.4-1.6 °C under the RCP 2.6 (2061-
2080) scenario, and 1.4-2.6 °C under the RCP 8.5
(2061
–
2080) scenario.
The default output of Maxent is in the logistic form,
indicating the environmental suitability for J.
schachimordanica in Pamir-Alay with values
ranging from 0 to 1. For further analyses, the
results of MaxEnt were imported into ArcGIS
program potential habitats were reclassified as
follows: In this appendix, the high range of the
species is described in “Red”, the areas with low
distribution are described in “Orange”, the areas
with low probability of distribution and almost no
chanc
e of occurrence are described in “Green and
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White”. The resulting model was validated on the
basis of the area under the curve (AUC) calculated
from the receptor operating characteristic and
whose growth factor is set from 0 to 1. AUC values
> 09 indicate high accuracy, values of 07
–
08
indicate good accuracy, < 07 indicate poor
accuracy, and <05 indicate poor accuracy (Guo et
al., 2017). The contribution of variable
environmental factors is evaluated according to the
results of the Jackknife test.
RESULTS
For more than 60 years, herbarium specimens of
this species have not been re-collected and
targeted field research has not been conducted. In
2023-2024, as a result of targeted field research
conducted in Shakhimardan region of Fergana
Valley, it was possible to redefine the population of
J. schachimordanica, and samples of its leaves were
taken for the purpose of herbarium and DNA
barcoding (Gulomov et al., 2023).
By applying the MaxEnt model, the model
predicted the potential distribution of J.
schachimordanica plant in Pamir-Alay, with a
training AUC value of 0.991 and a test AUC value of
0.985, (under both climate scenarios) which
indicates its high level of predictive performance
(Fig.1).
Figure 1. Receiver operating characteristic curve; A) RCP2.6_2070s; B)
RCP8.5_2070s
It is endemic to the Fergana Valley. In the period of
Industry development (1970
–
2000), despite the
limiting effect of late anthropogenic climate change
on the range of the species, the ecological niche of
the species showed that it can be distributed in the
Badakhshan regions of the Central Asia, Pamir-
Alay, southwestern Tiyonshan, Tukmaniston.
However, the distribution of the species in these
areas has not been recorded (Fig.1).
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Figure 2. Hot spots of species under past climate change scenarios.
The RCP 2.6 2070 climate scenario associated with
an increase in minimum greenhouse gas
concentrations showed that the species' high and
medium suitable habitat will expand in the future.
In particular, during the period of industrial
development, the areas with a low brightness index
and unsuitable for the growth of the species will
become highly suitable areas under the RCP 2.6
2070 climate scenario. According to the RCP 2.6
(2061-2080) climate scenario, an increase in
temperature of 0.4-1.6 °C will create many
potentially suitable areas in the form of fragments
in the regions of Kazakhstan and Tajikistan. It is
directly related to precipitation (Bio19) and
elevation (Elv.) in the coldest quarter. Under the
RCP8.5_2070s climate scenario, an increase in
temperature of 1.4-2.6 °C has replaced scattered
high-level suitable areas with medium-level
suitable areas. Under both climate scenarios,
temperature increases of 0.4
–
1.6 °C and 1.4
–
2.6 °C
did not adversely affect the species main hotspots
(Fig.3).
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Figure 3.
Hot spots of species under future climate change scenarios.
Based on the predictions of the MaxEnt model, our
study showed that the species high habitats were
gradually differentiated but not drastically
reduced. Further research on its biological and
ecological adaptation should be done in the future
depending on different habitats and the response
of the plant to climate change. This makes it
possible to determine the ecological optimality of
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the species and its successful introduction in the
near future.
CONCLUSION
According to the RCP 2.6 (2061-2080) climate
scenario, an increase in temperature of 0.4-1.6 °C
will create many potentially suitable areas in the
form of the regions of Kazakhstan and Tajikistan. It
is directly related to precipitation (Bio19) and
elevation (Elv.) in the coldest quarter. Under the
RCP8.5_2070s climate scenario, an increase in
temperature of 1.4-2.6 °C has replaced scattered
high-level suitable areas with medium-level
suitable areas. Under both climate scenarios,
temperature increases of 0.4
–
1.6 °C and 1.4
–
2.6 °C
did not adversely affect the species' main hotspots.
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