Research Region and Sampling
The present investigation involved the collection of 20 water and 20 soil samples from the provinces of Afyon and Kütahya (Fig. 1) during the period spanning March 2011 to March 2013. The province of Afyon, located in the western region of Turkey, is characterized by a continental climate. This climate is marked by cold and snowy winters, as well as hot and dry summers. The locality serves as the focal point of an agrarian region and boasts contemporary, adequately furnished lodgings and wellness facilities. The presence of mineral-rich waters, thermal springs, and indoor swimming pools draws a significant number of visitors during the winter season. Kütahya, located in the western region of Turkey, exhibits a climatic pattern akin to that of Afyon. Kütahya is renowned for its Turkish baths situated within the region. The provinces exhibit distinct variations in their climate and environmental attributes.
Culture Methods
The Acanthamoeba culture methods utilized have been previously detailed by Lorenzo-Morales et al. [20]. The methodology involved dissolving 2 grams of soil samples in 20 milliliters of distilled sterile water, followed by inoculating 150 microliters of each sample onto 2% non-nutrient agar plates that were previously seeded with heat-killed E. coli. Following the inoculation of the samples, the plates were subjected to incubation at a temperature of 27 oC and were subsequently examined on a daily basis for a maximum duration of 14 days to detect the presence of Acanthamoeba, utilizing an inverted microscope.
Environmental Data
The study utilized a set of 19 bioclimatic (bioclim) variables and three variables derived from remotely sensed data to analyze the environmental data (Table 1). The present investigation employed the ASTER Global Digital Elevation Model (DEM) version 3, which features a spatial resolution of 30 meters, as the primary source of DEM data. The derivation of slope and aspect data from DEM data is accomplished through the utilization of geographic information system (GIS) tools.
The third iteration of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) is procured from the Land Processes Distributed Active Archive Center, which is operated by NASA. The third iteration of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM Version 3) retains the GeoTIFF format and the identical gridding and tile structure of its predecessors. It boasts a spatial resolution of 30 meters and 1°x1° tiles.
Table 1 Environmental data.
Name of Data Description
|
DEM
|
Digital Elevation Model (m)
|
Slope
|
Slope in degrees obtained from altitude (%)
|
Aspect
|
Aspect in degrees obtained from altitude (Direction)
|
BIO1
|
Annual mean temperature (°C)
|
BIO2
|
Mean diurnal range (mean of monthly (max temp - min temp)) (°C)
|
BIO3
|
Isothermality (BIO2/BIO7) (x100)
|
BIO4
|
Temperature seasonality (standard deviation x100)
|
BIO5
|
Max temperature of warmest month (°C)
|
BIO6
|
Min temperature of coldest month (°C)
|
BIO7
|
Temperature annual range (BIO5-BIO6) (°C)
|
BIO8
|
Mean temperature of wettest quarter (°C)
|
BIO9
|
Mean temperature of driest quarter (°C)
|
BIO10
|
Mean temperature of warmest quarter (°C)
|
BIO11
|
Mean temperature of coldest quarter (°C)
|
BIO12
|
Annual precipitation (mm)
|
BIO13
|
Precipitation of wettest month (mm)
|
BIO14
|
Precipitation of driest month (mm)
|
BIO15
|
Precipitation seasonality (coefficient of variation)
|
BIO16
|
Precipitation of wettest quarter (mm)
|
BIO17
|
Precipitation of driest quarter (mm)
|
BIO18
|
Precipitation of warmest quarter (mm)
|
BIO19
|
Precipitation of coldest quarter (mm)
|
The ASTER GDEM was generated through a methodology that relied on automated processing of a vast archive of 2.3 million scenes from the ASTER database. This involved a series of steps, including stereo-correlation to produce individual scene-based ASTER DEMs, masking to eliminate cloudy pixels, stacking of all cloud-screened DEMs, removal of residual bad values and outliers, averaging of selected data to generate final pixel values and correction of residual anomalies. The final output was partitioned into 1° by 1° tiles. The ASTER GDEM provides coverage of terrestrial surfaces within the latitudinal range of 83°N to 83°S, consisting of a total of 22,912 tiles measuring 1° by 1° each. The tiles that are incorporated in the analysis are those that possess a minimum of 0.01% of land area. Also, it is disseminated in the GeoTIFF file format, featuring geographic latitude and longitude coordinates, as well as a 1 arc-second (30 m) grid of elevation postings. The geoid reference utilized is WGS84/EGM96. Research conducted to authenticate and define the ASTER GDEM has substantiated that the precision of this worldwide product is 20 meters at a 95% level of confidence for vertical data and 30 meters at a 95% level of confidence for horizontal data.
In contrast to Version 2, Version 3 exhibits a reduction in the void area of elevation as a result of the utilization of enhanced processing techniques and an increase in ASTER stereo image data. Additionally, there is a decrease in the anomaly data of water area, which can be attributed to the incorporation of novel global water body data that will be expounded upon at a later point [21].
The bioclimatic variables for both present and projected 2070 conditions were obtained from the WorldClim website, specifically version 1.4 [22]. The bioclimatic variables were recorded at a nominal resolution of approximately 1 km2.
The extant bioclimatic information was derived from observed monthly climate data spanning the period from 1950 to 2000, based on average values. The 2070 forecast was based on downscaled and calibrated General Circulation Model (GCM) data, specifically the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), using the Representative Concentration Pathway 6.0 (rcp60).
The bioclimatic variables, both present and anticipated for the year 2070, serve to characterize the prevailing climatic circumstances, encompassing factors such as temperature, isothermality, and annual precipitation.
The maximum entropy models were executed using the MaxEnt v3.3.3 software, which is accessible to the public at “https://biodiversityinformatics.amnh.org/open_source/maxent/”. An ASCII file containing numerous environmental variables pertaining to Acanthamoeba species was generated and subsequently inputted into the MaxEnt software for the purpose of ENM analysis.
In line with Sofizadeh's research, the modeling framework utilized 74.46% of the presence points of Acanthamoeba species across 47 distinct locations, while the remaining 25% of the data was reserved for model evaluation [23].
The software was executed with the default settings, which included 10,000 background absences, 0.00001 convergent thresholds, 15 replicates, and 5,000 iterations. The output was in the form of a logistic function that displayed a continuous probability of presence between 0 and 1. A jackknife approach was employed to determine the individual contribution of each variable in the modeling process. Phillips et al. [24] measured the receiver operating characteristic curve (ROC) and the area under the curve (AUC) for the model.
In addition, a probability threshold was chosen to represent the training presence points at the 10th percentile, which was utilized as a cutoff probability for the conversion of continuous probability maps for both the present day and 2070 into binary maps.
The cartographic representations generated for the present day and the year 2070 have depicted the likelihood of the occurrence of Acanthamoeba species in their respective endemic regions, both in the contemporary era and in the anticipated future.