MAXENT MODELING FOR PREDICTING THE POTENTIAL HABITAT AND FUTURE DISTRIBUTION OF A RARE SPECIES OPHRYS APIFERA HUDS. IN THE GREATER CAUCASUS (AZERBAIJAN) Текст научной статьи по специальности «Биологические науки»

ОРИГИНАЛЬНЫЕ СТАТЬИ RESEARCH ARTICLES

MAXENT MODELING FOR PREDICTING THE POTENTIAL HABITAT

AND FUTURE DISTRIBUTION OF A RARE SPECIES OPHRYS APIFERA HUDS. IN THE GREATER CAUCASUS (AZERBAIJAN)

Nigar Mursal, Naiba P. Mehdiyeva

Institute of Botany, Azerbaijan National Academy of Science, Azerbaijan e-mail:nigarbiology1292@mail.ru

As a result of the negative impact of various natural and anthropogenic factors, nowadays the vegetation of our planet is facing serious threats and degradation in large areas, many numbers of plant species have completely disappeared from the Earth, and ten thousands of species are in danger of extinction. Similar processes are taking place in Azerbaijan, so that 266 plant species of the local flora are included in the second edition of the Red Book. The purpose of the present study is determination of the status of populations of a rare species of Ophrys apifera Huds., in the north-eastern part of the Greater Caucasus (within Azerbaijan) and a prognostic assessment of the status of this species under a changing climate scenario. 8 populations of Ophrys apifera were investigated during 2017-2020 in Khizi, Shabran, Guba and Shamakhi regions. The study of the ontogenetic structure of populations shows that they are normal, but Pop 1-2, Pop 5-7 are incomplete due to the absence of subsenil and senile individuals. Analysis of the basic ontogenetic spectrum shows that Pop 2 is left-sided, Pop 3, Pop 5-6 - central, Pop 1, Pop 4 and Pop 7-8 bimodal. Based on the spatial and demographic values of the population of Ophrys apifera, the highest value of the recovery and replacement index was recorded in Pop 2. According to age and efficiency indices, Pop 5 and Pop 7 are mature, while other populations are young. As a result of the analysis of phytocenological features of Ophrys apifera, it was determined that this plant grows in forests, dry grassy slopes and meadows at altitudes of 603-1326 m a.s.l. The small population of this plant (in Pop 8 - 16 individuals) is found in the forest near Tazakend village of Khizi region, the largest population (in Pop 4 - 124 individuals) is found on the grassy mountain slopes around Gizmeydan village of Shamakhi region and in the meadow near the mud volcano (at a distance of 200 m). Orchis purpurea Huds., Anacamptis pyramidalis (L.) Rich., Ornithogalum ponticum Zahar. are often found in plant communities along with Ophrys apifera. For the first time, we applied the MaxEnt algorithm of the Species Distribution Modeling to predict the potential habitat and future distribution of Ophrys apifera. According to the present and future models of this species established that Ophrys apifera will be affected by strong climate change in the future and there will be a loss of suitable areas. Key words: MaxEnt, rare species, prediction, population status, species distributing modeling

Introduction

One of the problems actively discussed at all levels in modern times is the study of the negative impact of global warming on biodiversity, the identification of potential risks in this area, and the identification of ways to prevent and eliminate them.

Predicting the response of biodiversity to climate change is an active part of research (Dillon et al., 2010; Gilman et al., 2010; Pereira et al., 2010; Salamin et al., 2010; Beaumont et al., 2011; Dawson et al.., 2011; McMahon et al., 2011). Different predictions are important in informing scientists about the potential for future risks and can support the development of proactive strategies to reduce the impact of climate

change on biodiversity (Pereira et al., 2010; Parmesan et al., 2011). Although there is relatively limited evidence for the extinction of plant species caused by climate change, research shows that climate change will even outpace habitat destruction, the greatest global threat to biodiversity in the next few decades (Leadley et al., 2010). Thus, according to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the average global surface temperature has increased by 0.85 degrees over the last 130 years (1880 - 2012) (Stocker, 2014; Zomer et al., 2015).

Ecological niche or Species Distribution Modeling (SDM) are aimed at forecasting key areas for target species according to the environmental conditions in which the species currently exists (Guisan & Zimmermann, 2000). In addition, SDM can provide a way to protect nature by predicting the effects of global warming and unsystematic land use, by researching inappropriate areas, as well as more investigated areas, reintroduction, or areas of high availability for the natural conservation of such endangered species (Fois et al., 2018; Safaei et al., 2018). The main task of SDM is to understand how the environment shapes the distribution of a species in a local area (Mohamed Abdelaal et al., 2019).

The Maxent entropy (Maxent) model (Phillips et al., 2004) is one of the algorithms of SDM derived from statistical mechanics (Jaynes, 1957). The MaxEnt program is the most appropriate tool for predicting the potential distribution of species, especially rare and endangered species. There are several advantages to this method, the basis of which is data of the location of the species and environmental information (Elith et al., 2011).

The current study is dedicated to the determination current status of populations of the rare species Ophrys apifera in the north-eastern part of the Greater Caucasus, the current potential distribution of the species and the prediction of suitable areas under the climatic scenario using the MaxEnt model. The following goals have been set for this purpose:

1. to study population status of the studied species;

2. compile a GIS map of the potential distribution of Ophrys apifera and identify critical environmental factors affecting suitable areas;

3. to assess the future suitable dynamic spatial-temporal areas of Ophrys apifera under the climate scenario;

4. To determine the relationships of climate change variables to the Ophrys apifera.

Material and Methods

The object of research. The object of research is Ophrys apifera Huds. (Orchidaceae Juss.) included in the second edition of the Red Book of Azerbaijan (2013). This plant is a perennial herb, 20-40 cm tall. The tuberoid is spherical or elliptical. The leaves are oblong-lanceolate, 5-10 cm long, 2-3 cm wide. Bracts are linear-lanceolate, longer than the ovary. The flowers are 5-6, sparsely. The outer leaves of the inflorescence are light purple with 3 green veins; inner oval-lanceolate, purple with 1-veined, lip velvety, the edges of the lip bent downwards (Fig. 1).

Fig. 1. Ophrys apifera Huds. in nature.

In Azerbijan, the distribution of Ophrys apifera covers Guba part of the Greater Caucasus, Kur-Araz lowland, Kur plain, Nakhchivan plain, Lankaran lowland, grows from the lowland to the middle mountain zone, in forest and in bushes (Rzazade, 1952).

The methods of research. The geobotanical description of the plant communities was conducted using generally accepted geobotanical methods (Mirkin et al., 2001; Pedrotti, 2013). Ontogenetic and demographic structure of populations was investigated according methods to T.A. Rabotnov, A.A. Uranov (Uranov, 1975).

The Euro + Med Plantbase (2006-) was used to determine the taxonomic status of species in the plant communities. Distribution maps of studied species were implemented in ArcGIS 10.5.1.

Compiling of prognostic models. 19 bioclimate layers were obtained (Table 1) from the WorldClim database (http://www.worldclim.org/, Hijmans et al., 2005). All environmental variables were re-selected using a second network of 30 arc-seconds to provide a spatial resolution of approximately 1 km (Fick & Hijmans, 2017). The geographical coordinates of the distribution place (longitude and latitude) were obtained through the Global Positioning System (Garmin GPS-12) receiver.

During the study, all models were performed using the MaxEnt algorithm with standard parameters (version 3.3.3 k; Phillips et al., 2006). This algorithm is especially useful because it is possible to get good results even if a small sample-area is included. This is also very important for researchers working with rare species (Bosso et al., 2013; Fois et al., 2015, 2018; Vasconcelos et al., 2012). We calculated the Area Under the Curve (AUC) of the Receiver Operating characteristic Curve (ROC) for determining the accuracy of the resulting models. The AUC rate is an indicator for measuring model performance (Bosso et al., 2013; Fois et al., 2018; Yi et al., 2016). A score of about 1 of this rate is considered the best model performance (Fielding & Bell, 1997; Phillips et al., 2006). 0.5 AUC indicates that the model predictions are not better than random

Table 1. Bioclimate variables

Variables and description Unit

Biol = Annual Mean Temperature °C

Bio2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) °C

Bio3 = Isothermality %

Bio4 = Temperature Seasonality °C

Bio5 = Max Temperature of Warmest Month °C

Bio6 = Min Temperature of Coldest Month °C

Bio7 = Temperature Annual Range °C

Bio8 = Mean Temperature of Wettest Quarter °C

Bio9 = Mean Temperature of Driest Quarter °C

Bio10 = Mean Temperature of Warmest Quarter °C

Bioll = Mean Temperature of Coldest Quarter mm

Bio12 = Annual Precipitation mm

Bio13 = Precipitation of Wettest Month mm

Bio14 = Precipitation of Driest Month mm

Bio15 = Precipitation Seasonality %

Bio16 = Precipitation of Wettest Quarter mm

Bio17 = Precipitation of Driest Quarter mm

Bio18 = Precipitation of Warmest Quarter mm

Bio19 = Precipitation of Coldest Quarter mm

expectations, 0.5-0.7 degrees of poor performance, 0.7-0.9 acceptable or average performance, >0.9 indicates high performance (Peterson et al., 2011).

MaxEnt results are included in ArcGIS 10.5.1 for further analysis and visualization, and potential areas are grouped into five classes as follows: unsuitable (0-0.2), less suitable (0.2-0.4), relatively suitable (0.4-0.6), suitable (0.6-0.7), most suitable (0.7-1.0) (Choudhury et al., 2016; Qin et al., 2017; Yang et al., 2013). Under the CSIRO (Commonwealth Scientific and Industrial Research Organization) climate scenario, has been developed a model for predicting the future distribution of species.

Result and discussion

During the study, populations of Ophrys apifera were found in Khizi, Shabran, Guba and Shamakhi regions in the north-eastern part of the Greater Caucasus (Azerbaijan). Totally, 8 populations of this plant in those regions were studied and was studied their condition (Mursal, 2020) (Fig. 2).

Pop 1 - was investigated in the forest around Zeyva village of Shabran region, a.s.l. 603 m, Pop 2 - in the forest of Ispik village of Guba region, a.s.l. 775 m, Pop 3-5 around Gizmeydan village of Shamakhi region: respectively; in the territory of mud volcano, a.s.l. 1326 m; in the meadow, a.s.l. 1020 m; among the bushes, a.s.l. 1276 m, Pop 6-7 - around Altiagach settlement in Khizi region: respectively; on dry slopes, a.s.l. 762 m; in the forest, a.s.l. 1280 m, Pop 8 - in the forest around Tazakend village of Khizi region, a.s.l. 805 m (Fig. 3.).

Fig. 2. Distribution map of populations of Ophrys apifera Huds.

Fig. 3. Distribution of populations of the species Ophrys apifera Huds. in different altitude zones

Pop 1 and Pop 2 is studied in mainly oak-hornbeam (Quercuseto-Carpinusetum) forests. The slope exposure is 30 degrees. The projective cover of herbs is 60-70%. The number of plant individuals in 1 m area is 1-3. In the plant community, Ophrys apifera co-exists with trees Acer campestre L., Quercus pubescens subsp. crispata (Steven) Greuter & Burdet, Quercus petraea subsp. iberica (Steven ex M. Bieb.) Crassiln., Carpinus betulus L.; shrubs Crataegus rhipidophylla Gand,; herbs Sanguisorba officinalis L., Primula acaulis (L.) L., Fragaria vesca L., Pimpinella peregrina L., Orchis simia Lam,. Lathyrus sylvestris L., Arum elongatum Steven, Leontodon hisbidus L., Onobrichis bobrovii Grossh., Orchis purpurea Huds.

Pop 3, Pop 4, Pop 5 are found in the meadows where the projective cover of herbs is 80-100%. The height of the herbs is 50-60 cm. The slope exposure is 30 degrees. The number of plant individuals per 1 m2 is 2-3. In the plant community O.apifera co-exists with such herbs as Plantago lanceolata L., Anthemis altissima L., Bromus lanceolatus Roth., Xeranthemum cylindraceum Sm., Euphorbia boissieriana (Woronow) Prokh., Lolium rigidum Gaudin, Filago arvensis L., Galium verum L., Origanum vulgare L., Teucrium polium L., Linum orientale Boiss., Potentilla recta L., Ornithogalum ponticum Zahar., Lythrum salicaria L., Filipendula vulgaris Moench, Pimpinella rhodantha Boiss., Anacamptispyramidalis (L.) Rich.

Where Pop 6, Pop 7 and Pop 8 is studied the total projective cover of herbs is 80-100%. The slope exposure is 30 degrees. The number of plant individuals in 1 m area is 1-3. In the plant community, O.apifera co-exists with trees Quercus anatolica (Schwarz) D. Sosn., Carpinus betulus, Pyrus salicifolia Pall.; shrubs Juniperus communis L. subsp. oblonga (Bieb.) Galushko, Ligustrum vulgare L., Viburnum lantana L., Cotinus coggygria Scop. and shrub-lian Lonicera caprifolium L.; herbs Dianthus ruprechtii Schischk, Bellardia trixago (L.) All., Orchis picta Lois., Galium verum L., Ornithogalum ponticum, Anacamptis pyramidalis (L.) Rich., Echium rubrum Jacq., Trifolium pratense L., Xeranthemum squarrosum Boiss., Rumex crispus L., Melissa officinalis L., Tragopogon graminifollus DC.

The small population of this plant (Pop 8 - 16 individuals) is found in the forest near Tazakend village of Khizi region, and the largest population (Pop 4-124 individuals) is in the meadows near the mud volcano (200 m) on the grassy mountain slopes around Gizmeydan village of Shamakhi region.

The ontogenetic structure of 8 populations of Ophrys apifera was studied and it was determined that all populations are normal. However, Pop 1, Pop 2, Pop 5-7 are incomplete due to the absence of subsenile and senile individuals. The basic ontogenetic spectrum is Pop 2 left-sided, Pop 3, Pop 5-6 central, Pop 1, Pop 4 and Pop 7-8 bimodal type (Fig. 4).

°/o 40

Pop 1 Pop 2 Pop 3 Pop 4 Pop 5 Pop 6 Pop 7 Pop S

Fig. 4. Ontogenetic spectrum of populations of Ophrys apifera Huds.

According to the demographic structure of the Ophrys apifera it was determined that the number and average density of individuals is highest in Pop 4 and lowest in Pop 2. The highest average density of pregenerative individuals is observed in Pop 6, generative individuals - Pop 7, and postgenerative individuals - Pop 6. The recovery (Ir) and replacement (Irep) indices show the highest values in Pop 2. According to the age (A) and efficiency (œ) indices, Pop 5 and Pop 7 are mature, other populations are young type (Table 2).

Table 2. Spatial and demographic indicators of populations of Ophrys apifera Huds.

Pop n Xa Xpre Xg Xpost Ir Ia Irep A œ Type of Pop

Pop 1 44 2.93 1.8 1.13 0 1.59 0 1.59 0.26 0.49 Young

Pop 2 29 1.93 1.2 0.73 0 1.64 0 1.64 0.205 0.455 Young

Pop 3 70 4.67 2.53 1.93 0.2 1.310 0.043 1.187 0.284 0.512 Young

Pop 4 124 8.27 3.8 4.2 0.27 0.904 0.03 0.850 0.291 0.543 Young

Pop 5 28 3.5 3.5 2.25 0.125 0.5 0.036 0.474 0.335 0.639 Mature

Pop 6 52 6.5 6.375 3.5 0.375 0.625 0 0.625 0.324 0.579 Young

Pop 7 34 4.25 4.25 2.625 0 0.619 0 0.619 0.304 0.623 Mature

Pop 8 16 2 2 1 0 1 0 1 0.272 0.534 Young

Note: n - number of individuals; Xa - total average density of plants (individuals / m2); Xpre - density o: the pregenerative individuals (individuals / m2); Xg - density of generative individuals (individuals / m2); Xpost -density of postgenerative individuals (individuals / m2); Ir - recovery index; Ia - aging index; Irep - replacement index; A - age index; © - efficiency index.

Prognostic model. We have developed a prognostic model of the Species Distribution Model using the MaxEnt algorithm for determining the suitable areas of Ophrys apifera. The AUC indicators of this model showed a highly predicative performance. Thus, these indicators were 0.993 in the model conducted for the current period, and 0.987 in the model under the climate scenario. The results of the Jacknife test of this model under the current period and climate scenario are shown in Figure 5. This test mainly measures the extent to which climate variables affect the potential distribution of a species (Fig. 5).

A

B

Fig. 5. Bioclimate variables involved in prediction suitable areas for Ophrys apifera Huds. at the present time (A), under the climate scenario (B).

As can be seen from the Figure 5, the most favorable bioclimate variables currently affecting the potential distribution of the species were mean temperature of wettest quarter (Bio 8), mean diurnal range (Bio 2), and precipitation of wettest month (Bio 13). According to the results of the Jacknife test of the model presented under the climate scenario, it can be said that along with Bio 8, Bio 2 bioclimate variables, precipitation of driest month (Bio 14), precipitation seasonality (Bio 15), mean temperature of driest quarter (Bio 9) climate variables were also recorded.

As a result of the research, we have compiled a map of the potential habitat of the species Ophrys apifera in the current period (A) and under the climatic scenario (B) (Fig. 6). According to these maps, currently the most suitable areas for this species are Samur-Davachi lowland, Guba part of the Greater Caucasus, Kur-Araz lowland, Diabar (especially Baku city, Beylagan and Imishli districts - green and dark green areas). Other areas (western Greater Caucasus, Kur plain, northern, central and southern Lesser Caucasus, Nakhchivan mountainous part, Lankaran lowland and mountainous part -dark purple areas) are considered unsuitable and less suitable.

Fig. 6. Potential distribution of Ophrys apifera Huds. in the current period (A) and under the climate scenario (B).

Looking at the model of this species presented for 2030 under the climatic scenario, we can see that there will be a decrease in the areas of suitable and relatively suitable areas of Ophrys apifera. Thus, Samur-Davachi lowland, Guba part of the Greater Caucasus will be transformed from suitable areas into relatively suitable areas. There is a difference in the size of unsuitable and less suitable areas too. It is clear from the present and future modelling of this species that there will be strong climate change effects and loss of suitable areas for Ophrys apifera in the future.

Conclusion

Reducing number of species one of the main criteria for creating a list of species in need of protection (Vakhrameeva, 2006). Demographic indicators, such as the number, density and age structure of individuals, reflect the recovery and survival

strategies of individuals are key characteristics for assessing population (Krivosheev et al., 2009). Substantial research has been conducted in Azerbaijan since 2016 till now to identify and protect populations of rare species (Alizade et al., 2016; Osmanova et al., 2018; Mursal & Mehdiyeva, 2019; Mursal et al., 2020). The assessment of populations of the rare species Ophrys apifera in the north-eastern part of the Greater Caucasus, is a continuation of this research. As a result of research, populations of this species were found in forests, dry grassy slopes and meadows at the altitudes of 603-1326 m a.s.l. The study of the demographic structure revealed that only two of these populations (Pop 5 and Pop 7) are mature, and other populations are young type. For the first time, the MaxEnt algorithm of the Species Distribution Modeling was applied to predict the potential distribution and future status of the species Ophrys apifera. As a result of the prediction, it became clear that this plant will be affected by strong climate change in the future and there will be a reduction in the size of suitable areas.

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MAXENT МОДЕЛИРОВАНИЕ ДЛЯ ПРОГНОЗИРОВАНИЯ ПОТЕНЦИАЛЬНОГО ОБИТАНИЯ И БУДУЩЕГО РАСПРОСТРАНЕНИЯ РЕДКОГО ВИДА OPHRYS APIFERA HUDS. НА БОЛЬШОМ КАВКАЗЕ (АЗЕРБАЙДЖАН)

Нигяр Мурсал, Наиба П. Мехтиева

Институт ботаники Национальной Академии Наук Азербайджана, Aзербайджан

е-mail: nigarbiology1292@mail. ru

В результате негативного воздействия различных природных и антропогенных факторов растительный мир нашей планеты в настоящее время сталкивается с серьезными угрозами и деградацией растительного покрова на значительных территориях. Многие виды растений уже полностью исчезли с лица Земли, а десятки тысяч видов находятся на грани исчезновения. Аналогичные процессы происходят и в Азербайджане, где 266 видов высших растений местной флоры включены во второе издание республиканской Красной книги. Целью настоящего исследования является определение статуса популяций редкого вида Ophrys apifera Huds. в северо-восточной части

Большого Кавказа (в пределах Азербайджана) и прогностическая оценка статуса этого вида в условиях изменения климата. В течение 2017-2020 гг. исследовано 8 популяций Ophrys apifera в Хызынском, Шабранском, Губинском и Шамахинском районах. Изучение онтогенетической структуры популяций (Поп) свидетельствует, что все они нормальные, но из-за отсутствия субсе-нильных и сенильных особей. Поп 1-2, Поп 5-7 - неполночленные. Анализ основного онтогенетического спектра показывает, что в Поп 2 спектр левосторонний, Поп 3, Поп 5-6 - центральный, Поп 1, Поп 4, Поп 7-8 - бимодальный. Исходя из пространственных и демографических значений популяций Ophrys apifera, наибольшее значение индекса восстановления и замещения было зарегистрировано в Поп 2. Согласно показателям возраста и эффективности, Поп 5 и Поп 7 являются зрелыми, а другие популяции - молодыми. В результате анализа фитоценологических особенностей Ophrys apifera установлено, что это растение произрастает в лесах, на сухих травянистых склонах и лугах на высоте 603-1326 м над ур. м. Небольшая популяция этого растения (8-16 особей) встречается в лесном массиве в окрестностях селения Тазакенд Хызынского района, самая большая популяция (4-124 особи) - на травянистых горных склонах в окрестностях сел. Гызмей-дан и грязевого вулкана (на расстоянии 200 м) Шамахинского района. В составе ценозов вместе с Ophrys apifera часто встречаются Orchis purpurea Huds., Anacamptis pyramidalis (L.) Rich., Ornithogalum ponticum Zahar. Нами впервые применен алгоритм MaxEnt моделирования распределения для вида Ophrys apifera с целью прогнозирования его потенциального развития. Согласно прогнозным моделям этого вида установлено, что в будущем под воздействием климатических изменений будет происходить деградация и уменьшение благоприятных территорий для произрастания Ophrys apifera и, как следствие, сужение его ареала.

Ключевые слова: MaxEnt, редкий виды, прогноз, статус популяции, моделирование распространения видов