Дэлгэрэнгүй мэдээлэл

Within the framework of this research, a new algorithm was designed to determine the plant’s red edge slope and the Leaf Area Index (LAI) based on their spectral characteristics using a hyperspectral LCTF (Liquid Crystal Tunable Filter) camera. In the first week of July 2022, we took pictures of field vegetation in several fields in the Khar Yamaat Nature Reserve with the LCTF camera. From the collected data, the light reflectance spectrum of many species of growing plants was distinguished with the help of image processing, and with that, we created a spectrum dataset of 21 different species. From the generated dataset, we designed an algorithm to determine plant species or dry grass based on the red edge slope, which works with approximately 95% accuracy. The algorithm also calculates the leaf area index, and healthy plants are distinguished from damaged grass and non-plant species. The results of this work demonstrate that vegetation can be classified by vegetation’s red edge slope using hyperspectral cameras. In the future, it will be possible to determine the location and number of growing plants using the algorithm we developed on the images taken by modern satellites and drones.

While traditional Earth observation satellites primarily capture images directly from overhead, advancements in technology now allow modern satellites to adjust their observation angles. The Gobi grasslands, characterized by limited plant diversity, sparse vegetation, or a low leaf area index, often appear as barren deserts in conventional satellite imagery. Despite this, the Gobi is renowned as one of the world's most iconic deserts, hosting a complete ecosystem with unique natural formations that support a range of biodiversity, including rare and endangered species. The landscape reveals a stark contrast: from particular perspectives, the valley radiates lush greenery, while from others, it unveils a predominantly sandy facade. This study aims to explore how the spectral reflectance of the Gobi Desert with observation angles and sunlight illumination, utilizing ground-level measurements and satellite data. Fieldwork was conducted on August 27, 2023, in the Shiveegov sum region of Govsumber province, at coordinates 46.05836N, 108.66189E, between 10:00 and 13:00, at hourly intervals. Measurements were taken using a Liquid Crystal Tunable Filter (LCTF) camera and a Handheld spectroradiometer at 20°, 40°, and 60° relative to the vertical axis, totaling 47 observations. The findings indicate that as the observation angle (zenith) increased, reflectance values decreased in the red light wavelength but increased in the infrared spectrum. Each pixel captured by the LCTF camera contains spectral data for the imaged area, offering a comprehensive two-dimensional correlation and streamlining the data analysis process. Images captured at nadir angles predominantly reflected the spectral characteristics of sand, while those taken at oblique angles more closely resembled vegetation spectra. Notably, the Normalized Difference Vegetation Index (NDVI) values varied significantly, showing a 65.9% increase at a 60° angle compared to a nadir perspective. The results suggest that oblique imaging in the Gobi steppe can yield richer biological surface data. Incorporating satellite observations, ground-level measurements, and joint analyses of the Gobi's grassland vegetation enhances precision and provides vital, timely insights for ecosystem evaluations.

Уламжлалт дэлхийг ажиглах хиймэл дагуулууд эгц доош чиглэн зураг авдаг бол нэн орчин үеийн хиймэл дагуулууд ажиглалтын өнцгийг өөрчлөн зураг авах техникийн чадамжтай болсон. Монгол орны нийт газар нутгийн 66% бэлчээр, 27% элсэрхэг бэлчээр буюу говийн бэлчээр эзэлж байна. Говийн бэлчээрийн бүс ургамлын төрөл зүйл цөөн, хөрсөн дээрх ногоон ургамлын бүрхэц сийрэг ургадаг буюу навчны талбайн индекс бага тул уламжлалт хиймэл дагуулаар авсан зурганд Говь амьгүй элсэн цөл мэт харагддаг. Дэлхийд алдартай элсэн цөлүүдийн нэг болох Говь нь биологийн олон янз байдал, тэр дундаа ховор, нэн ховор амьтдыг дэмждэг гайхалтай байгалийн тогтоц бүхий эрүүл, бүтэн экосистем юм. Говиор явахад тал хөндий хажуугаас харахад бүтнээр ногоон харагддаг бол эгц доош харахад элсэрхэг гадарга харагдана. Иймд энэ судалгаагаар говийн ургамлууд болон элсэрхэг хөрсөн дээрх гэрлийн ойлт ажиглалтын болон нарны тусгалын өнцгөөс хэрхэн хамаарч буйг газрын хэмжилт болон хиймэл дагуулын мэдээллээр судлахыг зорьсон болно. Судалгааг 2023 оны 08 дугаар сарын 27-ний өдөр Говьсүмбэр аймгийн Шивээговь сумын нутагт 46.05836N, 108.66189E байрлалд 10 цагаас 13 цагийн хороонд нэг цагийн давтамжтай, босоо тэнхлэгийн дагуу 20°, 40°, 60° өнцөг тус бүрд хэт олон сувагт шингэн кристалл филтер (LCTF) камер болон зөөврийн гар спектрометр (HandHeld Spectroradiometer) гэсэн хоёр төрлийн багажаар нийт 47 удаа хэмжилт хийж судалсан. Хэмжилтийн үр дүнд хэмжилтийн өнцгийн хэмжээ ихсэхэд ойлтын утга улаан гэрлийн долгионы мужид багасаж, хэт улаан долгионы мужид нэмэгдэж байгаа бөгөөд энэ нь говийн бэлчээрт ургамлын ойлт нь өнцгөөс хамаарсан төсөөллийг Зураг 1-т үзүүлэв. LCTF камерын пиксель тус бүр нь тухайн зурагт өртсөн хэсгийг спектр мэдээлэл харуулж байгаа нь 2 хэмжээст дэлгэрэнгүй хамаарлыг үзүүлж байна. Уг давуу тал нь судалгааны үр дүнг тооцоолоход арга зүйг энгийн болгож байна. Мөн ойлтын утга нь 12 цагт хамгийн өндөр байснаас нарны гэрлийн тусгалын өнцгөөс хамааралтай болох нь харагдсан. Гэхдээ нарны тусгалын өнцөг нь спектрийн хэлбэрт төдийлөн нөлөө үгүй байв. Харин ажиглалтын өнгийн эгц дээрээс авсан зураг илүү элсний спектрийг харуулж байгаа бол ажиглалтын өнцөг налуу болох тусам ургамлын спектрийн шинж чанартай төстэй байна. Дүгнэж хэлбэл Говь хээрийн бүст хажуу өнцгөөр зураг авах нь гадаргын биологийн шинж чанарыг судлахад илүү мэдээлэл өгнө. Хиймэл дагуулын өгөгдөл болон газар дээр нь очиж хэмжиж говийн бэлчээрийн ургамлыг хоршуулан судлах нь нарийвчлалыг нэмэгдүүлэх, экосистемийг үнэлэхэд бодит мэдээллийг өгөх чухал ач холбогдолтой.

Энэ судалгааны хүрээнд хэт олон сувагт LCTF (Liquid Crystal Tunable Filter) буюу шингэн кристалл шүүлтүүртэй камерын тусламжтай ургамлын зүйлийг түүний спектр шинж чанарт тулгуурлан ялгаж, навчны талбайн индекс LAI (Leaf Area Index) тооцож гаргах шинэ алгоритмыг туршин үзэв. 2022 оны 7-р сарын эхний долоо хоногт Хар Ямаат байгалийн нөөц газарт хэд хэдэн бодит талбарт LCTF камераар хээрийн ургамлуудын зургийг авч, цуглуулсан зурган мэдээллээс ургаж буй олон зүйлийн ургамлуудын гэрлийн ойлтын спектрийг дүрс боловсруулах аргаар ялгаж, түүгээр спектр сан үүсгэв. Үүсгэсэн сангийн мэдээллээс бид улаан хилийн зурваст тулгуурлан өвслөг ургамлын зүйлийн бүрдлийг тодорхойлох алгоритм туршиж үзсэн. Тухайн алгоритмаар навчны талбайн индексийг мөн тооцож гаргахад эрүүл ургамлыг хагдарсан өвс болон ургамал бус зүйлээс 95% дээш нийлэмжтэй ялгаж байна. Энэ ажлын үр дүнд ургамлын төрөл зүйлийг машинаар олон сувагт камерын тусламжтай өндөр нарийвчлалтай ялгах боломжтойг харуулж байна. Цаашид орчин үеийн хиймэл дагуул, дроноор авсан зургаас уг бидний хөгжүүлсэн алгоритмыг ашиглан хаана ямар төрөл зүйлийн ургамал хэр хэмжээгээр ургаж буйг ялгах боломж бүрдэх юм.

Mongolia's vast grasslands, crucial for both environmental and economic stability, are currently facing challenges due to overgrazing, climate change, and land-use changes. Understanding and effectively managing their Carrying Capacity (CC) and Relative Stocking Density (RSD) is essential for maintaining ecological balance. This study rigorously evaluates the CC and RSD of Mongolia's grasslands through an innovative approach that integrates ecological models with socio-economic data, aimed at improving grazing management practices. Data from the National Agency for Meteorology and Environmental Monitoring validates the model, providing precise CC and RSD estimates at the Soum level from 2000 to 2019. The study reveals significant regional variations in CC: northern grasslands exhibit a high CC of 2.8 Sheep Units (SU) per hectare, contrasting with the fragile CC in some southern regions, like the Gobi Desert, where it is as low as 0.3 SU per hectare. Approximately 38.8 % of Mongolia's territory maintains a CC exceeding 1.0 SU per hectare, indicative of sustainable grasslands. In contrast, 41.7 % of the land, primarily in southern regions, shows CCs below 0.5 SU per hectare, highlighting ecosystem vulnerability. The RSD, reflecting livestock numbers relative to CC, averages 1.07, suggesting a high livestock concentration near Ulaanbaatar but a more sustainable density across 43.2 % of the country. The research also explores adaptation scenarios against desertification and degradation, as well as improving pasture accessibility, providing insights for future grassland management strategies. In conclusion, this study emphasizes the need for sustainable land management practices to balance carrying capacity and stocking rates, offering a vital tool for policymakers and stakeholders in grassland conservation.

Land cover change is one of the major problems facing the world, and as human needs increase, so does the inappropriate use of land (Geist et al., 2008), and climate change, precipitation variability, temperature rise, and the frequency of extreme natural disasters are the primary factors influencing land cover change (Bordi et al., 2004; Nandintsetseg & Shinoda, 2013). Therefore, we will investigate how the land cover in the Khar Yamaat Nature Reserve changes between 2014 and 2019. Using Landsat satellite images from September 2014 and September 2019, the land cover change was classified in three ways using the pixel-based supervised classification method: Maximum likelihood classification, K-Nearest neighbor, and Minimum distance classifier. Based on common plant species and environmental factors, land cover categories were divided into nine categories: mountain steppe, dry steppe, shrubland, degraded area, agriculture, sand, lake, river, and meadow. To detect land cover changes, the" Maximum likelihood classification" that accurately depicts the spatial distribution of each land cover class and has a high statistical significance was chosen. During the six-year period from 2014 to 2019, the area of dry steppes decreased by-42,232 hectares or 42.8%, mountain steppes decreased by-3,797 hectares (3.84%), rivers decreased by-1,000 hectares (1.1%), meadows decreased by-1,581 hectares (1.6%), and agriculture decreased by-723 hectares (0.7%), while degraded area increased by 39480. For 2014 and 2019, the overall accuracy was 95.96 (k= 0.94) and 93.39 (k= 0.93).

Cysticercosis caused by the larval form of the Taenia hydatigena tapeworm poses a global challenge to the livestock industry. A total of 56 goats slaughtered in Khishig-Undur, Mongolia were evaluated for the presence of cystic lesions. Collected cysts were assessed using the mitochondrial 12S rRNA gene. In total, 46.4% (26/56) of evaluated goats were positive for T. hydatigena infection, with most cysts attached to the omentum, mesentery, liver, or spleen. Partial 12S rRNA gene sequences were obtained from all evaluated cysts and aligned with known sequences for T. hydatigena. Infection prevalence was higher in goats three years of age and older (50.0%; 17/34) compared to goats less than three years of age (40.0%; 9/22) (p=0.035). Infection with T. hydatigena appears to be highly prevalent in goats in Khishig-Undur. Additional studies are needed to evaluate local parasite transmission dynamics and the impact of this parasite on local livestock production.

Habitat degradation and heavy grazing by livestock are common conservation challenges across the steppes of Mongolia and Central Asia. Livestock grazing patterns are generally not uniform and are typically greater near campsites and watering holes. In this study, we examined how plant composition in a mountain steppe in southern Mongolia varied along a gradient of increasing distance from wells. We found that the cover and average height of Ephedera prezewalskii increased with increasing distance from the wells whereas soil chemistry and the other variables of plant composition that we examined were similar along the gradient of increasing distance from the wells. These results suggest relatively limited impact of livestock grazing on plant composition in our study. However, our study was limited in space and time and further studies are needed to understand the impact of livestock grazing in this mountain steppe in southern Mongolia.

Borrelia burgdorferi sensu lato and Rickettsia spp. are worldwide causes of tick-borne infections. We aimed to estimate the seroprevalence of immunoglobulin G (IgG) antibodies against different tick-borne diseases (TBDs) and determine risk factors among Mongolians from 2016 to 2020. Blood samples were obtained from voluntary participants with a history of suspected tick bite who visited our hospital, and IgG antibodies against Rickettsia and Borrelia were detected using enzyme-linked immunosorbent assay (ELISA). The IgG antibody seropositivity rate against Rickettsia was 21.8% (1032/4724), while 3.4% (162/4724) of participants tested positive for serum IgG antibodies against Borrelia by ELISA.Binary logistic regression analysis was performed to evaluate risk factors for tick-borne rickettsiosis (TBR) and tick-borne borreliosis (TBB) using IgG serum sample. Age, occupation, and residence were significantly associated with these diseases; however, sex did not show any significant association. Seroprevalence was significantly higher among herders (40.6%, 95% confidence interval [CI]: 35.5–45.8; odds ratio [OR] 0.61; P < 0.001) and students (32.8%, 95% CI: 30.2–35.4; OR 0.75; P < 0.001) than among individuals with other occupations. The 25–29 age group had a slightly higher seroprevalence (35.1%, 95% CI: 28.1–42.6; OR 0.61; P < 0.006) than those in other age groups. Province was a stronger predictor of TBR than occupation and age group. In univariate subgroup analysis by age group, occupation, and residence were significantly associated with TBR seroprevalence, whereas age and province were associated with TBB seroprevalence. Thus, risk factors for TBD include residence, occupation, and age group. This study was conducted using samples from all Mongolian provinces and the capital city, and the risk factors and prevalence of Rickettsia and Borreliaare highlighted.

We investigate the spatiotemporal variability of near-surface CO2 concentrations in Mongolia from 2010 to 2019 and the factors affecting it over four climate zones of Mongolia based on the Köppen-Geiger climate classification system, including arid desert climate (BWh), arid steppe climate (BSk), dry climate (Dw), and polar frost climate (ET). Initially, we validate the near-surface CO2 datasets obtained from the Greenhouse Gases Observing Satellite (GOSAT) using ground-based CO2 observations obtained from the World Data Center for Greenhouse Gases (WDCGG) and found good agreement. The results showed that CO2 concentrations over Mongolia steadily increased from 389.48 ppmv in 2010 to 409.72 ppmv in 2019, with an annual growth rate of 2.24 ppmv/year. Spatially, the southeastern Gobi desert region has the highest annual average CO2 concentration, while the northwestern Alpine and Meadow steppe region exhibits the most significant growth rate. Additionally, significant monthly and seasonal variations were observed in each climate zone, with CO2 levels decreasing to a minimum in summer and reaching a maximum in spring. Furthermore, our findings revealed a negative correlation between CO2 concentrations and vegetation parameters (NDVI, GPP, and LAI) during summer when photosynthesis is at its peak, while a positive correlation was observed during spring and autumn when the capacity for carbon sequestration is lower. Understanding CO2 concentrations in different climate zones and the uptake capacity of vegetation may help improve estimates of carbon sequestration in ecosystems such as deserts, steppes and forests.

Ковид-19 цар тахал нь байгаль орчин, хүний сайн сайхан байдал болон ЭРҮҮЛ мэндийн хоорондын харилцаа холбоог улам бүр тодруулсан. Засгийн газрууд, олон улсын байгууллага болон иргэдийн байгаль хамгааллыг харах өнцгийг өөрчилсөн. Ковид-19, түүнтэй төстэй цар тахал болох боломжтой халдварт өвчнүүд ирээдүйд гарах нь зайлшгүй үзэгдэл юм гэдгийг ойлгуулсан. SARS-Cov-2 нь амьтнаас хүнд халдсан байж болох ч цорын ганц халдварт өвчин үүсгэгч биш юм. Лайм өвчин, Ebola вирус, тарваган тахал зэрэг амьтнаас хүнд халддаг олон өвчин байна. Ихэнх халдварт өвчний тохиолдолууд нь хүний үйл ажиллагаатай холбоотой байна. Хүний үйл ажиллагааны улмаас биологийн олон янз байдал хомсдох нь улам бүр эрчимжиж байна. Өнгөрсөн зуунтай харьцуулахад зүйлийн мөхөж устах эрчим 100-1000 дахин өссөн. Тухайн амьдрах орчин экосистемээс амьтны зүйл устаж алга болохд тухайн амьдрах орчинд халдварт өвчний тархалт нэмэгддэг байна. Нэг ЭРҮҮЛ МЭНД гэсэн нэгдсэн хэтийн төлөв үгүй бол биологийн олон янз байдлын хувь нэмрийг олон хүн дутуу дүгнэх явдал байсаар байна. ДЭМБ, 2019 оны тоо баримтаас үзэхэд дэлхий даяар амьтнаар дамжин (халуун хумхаа, чичрэг г.м) халдах халдварт өвчний тохиолдол 200 сая илүү бүртгэгдсэн. Биологийн олон янз байдлын доройтол нь экосистемийн эрүүл мэндийг бууруулах гол хүчин зүйл болдог. Экосистемийн эрүүл мэнд буурах нь тухайн амьдрах орчинд байгаа өвчин үүсгэгчдийг шинэ эзэн, шинэ амьдрах орчин хайхад хүргэдэг байна. Амьтны нэг зүйл устаж алга болох нь тухайн амьдрах орчинд зооноз өвчин нэмэгдэх шалтгаан нь болдог байна.

Fritillaria dagana Turcz. has a restricted global distribution, occurring only in southern Siberia and northern Mongolia. Concerning its restricted distribution and endangered conservation status, we aimed to forecast its current and future suitable habitats as well as distribution shifts for 2050 and 2080. The Maxent model with different scenarios (RCP 4.5 and RCP 8.5) was used to analyze 113 georeferenced records of F. dagana using 19 bioclimatic factors from the WorldClim database. As a result, the amount and variance of precipitation and temperature, together with elevation, were shown to be the most significant factors affecting the species’ distribution. In particular, precipitation during the plant growing season had the greatest impact (55.2% variability) on the species distribution. Climate change was expected to cause a minor shift in the distribution of suitable habitats toward the north and an increase in habitat continuity, indicating that the climate will become more favorable for the growth of species and in the future. The species' highly suitable area will remain primarily concentrated in its current potential distribution area in central Siberia (around Lake Baikal). The species’ conservation status was determined to be near threatened, emphasizing the great relevance of facilitating proper conservation measures for F. dagana.

Fritillaria dagana Turcz. has a restricted distribution, occurring only in south Siberia and northern Mongolia, and is listed as endangered in both Russia and Mongolia at the regional level. Yet its global assessment has not yet been conducted. In this study, conservation status of the species has been assessed and evaluated to be vulnerable at the global level based on the IUCN criteria. In addition, species future potential distribution was modelled for the years of 2050 and 2080, using 19 bioclimatic variables of WorldClim database. A total of 113 georeferenced records of F. dagana were analysed using the MaxEnt model for distribution prediction. As a result, amount and variance of precipitation and temperature, together with elevation, were shown to be the most signifi cant factors impacting the species distribution. The predicted distribution maps, photo illustration in typical habitat and taxonomic note of the species are provided here.

The Ulz River in north-eastern Mongolia is an important habitat for breeding white-naped cranes Antigone vipio (WNCs) in the western population of the species. The destruction and degradation of wetlands, the main breeding habitat of the WNCs, are the main factors affecting the population. The breeding population census of 2019-2021 in the Ulz River basin was analyzed and compared to previous surveys conducted in 2001 and 2011. The surveys showed that along the Ulz River, crane pairs declined from 42 territorial pairs (TPs) in 2001 to 17 TPs in 2011 during the summer drought period, and then increased to 30 TPs in 2021 due to summer rainfalls. Along the Ulz River, six breeding pairs (BPs) of WNC in 2019, 11 BPs in 2020, and 18 BPs in 2021 were recorded. Estimates of detection probability using distance sampling yielded consistent results with 17–23% detectability. This indicated that changes in the BPs and TPs of the WNC along the Ulz River were affected by the rainy season. The number of TPs decreased in 2010 and 2011 during the periods of drought and, increased during the rainy season in 2021. This clearly indicated that breeding populations in the Ulz River are vulnerable to cyclical climate changes. Based on these studies, the western population of WNCs increased in the last three years and will decrease during future dry periods. A proper management of the Ulz River wetlands, is more important during the dry periods.

Энэ судалгаагаар Чух нуур орчмын ус, намгархаг газрын малын бэлчээрлэлтийг “харууц цэг”-ийн арга ашиглан VI-IX сарын хооронд сар тус бүрээр тооцон гаргасан үр дүнг сансрын дамжуулагч бүхий цэн тогорууны байршлын мэдээлэлтэй давхцуулан нягтшилын анализаар (KDE) боловсрууллаа. Үүний дараа сараар өөрчлөгдөх малын бэлчээр газар болон цэн тогорууны амьдрах орчны сонголтын орон зайн тархалт, давхцлыг тодорхойлов. Судалгааны үр дүнд VI сард нуурын бүрд хэсэгт түлхүү төвлөрж байгаа мал бэлчээрлэлт нь цэн тогорууны өндөг дарах үеийн байршил газартай давхцаж байгааг илрүүллээ. Харин VII сараас эхлэн хур бороо нэмэгдэж, уст цэгийн тоо олширч, харьцангуй чийглэг болж ирэх үед цэн тогоруу эзэмшил нутагаа тэлсэн бол гэрийн мал нь нуур орчмыг ашиглах нь багассан байна. Цэн тогорууны хувьд үржлийн хамгийн эмзэг үе болох VI сард гэрийн мал нуурын бүрдийг түлхүү ашиглаж байгаа нь ус намгархаг газар, түүний орчмыг малын нөлөөллөөс хамгаалах асуудлыг сараар харгалзан боловсруулсан хамгааллын бодлогыг цаашид нэвтрүүлэх хэрэгтэйг харуулж байна.

Чух нуурт 2019-2021 оны хугацаанд хавар болон намрын нүүдлийн үед нуураар дайран өнгөрч буй Нугасны (Anatidae) овгийн бүлгэмдлийн бүтэц, зүйлийн бүрдэл, тоо толгой тэдгээрийн өөрчлөлт болон доминант зүйлүүдийг илрүүлсэн. Судалгааны явцад 25 зүйлийн 142388 бодгаль шувуу бүртгэсэн бөгөөд хавар 24 зүйлийн 31819 бодгалийг, намар 20 зүйлийн 110569 бодгалийг нүүдлийн хугацаанд бүртгэсэн. Намрын нүүдлийн хувьд наймдугаар сараас есдүгээр сар хүртэлх хугацаанд идэвхжил өндөр бол хаврын нүүдлийн идэвхжил тавдугаар сарын дундуур болон зургаадугаар сарын эхээр нэмэгддэг болох нь гурван жилийн тооллогын явцад ажиглагдсан. Улаанхүзүүт шумбуур(Aythya erina), Гангар хун(Cygnus cygnus), Анхидал ангир(Tadorna tadorna), Хошуу галуу(Anser cygnoides), Алаг шунгаач(Bucephala clangula), Хондон ангир(Tadorna ferrugeniea) зэрэг зүйлүүд давамгайлагч зүйл болно. Эдгээр зүйлүүд олон тоогоор бүртгэгдэж байгаа нь Чух нуур дээрх зүйлүүдийн хувьд нүүдлийн үедээ дайран өнгөрөх таатай орчин болох нь харагдаж байна.

The Global Change Observation Mission-Climate (GCOM-C), launched in 2017, has suitable bands matching the photochemical reflectance index (PRI) definition. It also has the bands for the normalized difference vegetation index (NDVI). The PRI has a unique capability to detect plant stress caused by excessive light and drought. However, no moderate-resolution satellites had suitable bands for the PRI, requiring two narrow bands in green light in the definition. In this study, we conducted the early validation study of PRI and NDVI derived from the GCOM-C satellite and demonstrated those accuracies and characteristics in Mongolian grassland. The Mongolian Steppes (dry grasslands) are widely distributed on the plateau and therefore suitable for satellite validation. It is particularly suitable for the PRI validation because Mongolian grasslands have water stress due to the small amount of precipitation in summer. Therefore, we carried out field campaigns at three study sites in Mongolia. In this study, we found the seasonal pattern of PRI suggesting the potential to detect the water stress of vegetation, which is essential information for informed management of the grasslands. However, the correlation between the satellite-derived PRI and the in-situ PRI was negative because of the dependence of GCOM-C PRI on the soil moisture at sparse vegetation. For the accuracy assessment of PRI, which depends on rapidly changing light and soil moisture in a day, more exact synchronization of in-situ and satellite observation is required. On the other hand, we found that the NDVI derived from GCOM-C was highly accurate: The correlation coefficient (R) between the satellite-derived NDVI and the in-situ NDVI was 0.988 (RMSE=0.052). GCOM-C NDVI has enough similarities with MODIS NDVI in terms of accuracy, spatial resolution, and frequency. For example, we demonstrated that GCOM-C NDVI could detect the phenology with the same or better accuracy than MODIS NDVI. We also demonstrated their difference: the soil moisture dependence in sparse vegetation. The less dependency of GCOM-C NDVI on the soil moisture leads to a better classification of vegetation and non-vegetation in the sparse grassland than MODIS NDVI.

Mongolia has experienced several extreme climate events during the past decades, including severe extreme droughts. The issue of drought is of paramount signifi cance in our country of nomadic culture and nomadic pastoralism. The eighteen years (2001- 2018) MODIS satellite indices, Normalized Diff erence Vegetation Index (NDVI), and Normalized Diff erence Water Index (NDWI) data were analyzed for Khar Yamaat Nature Reserve. The Normalized Diff erence Drought Index (NDDI), combines information from both the NDVI and NDWI. During the summer, the average values of NDVI and NDWI were consistently lower under drought conditions (NDVI <0.2 and NDWI<-0.2) than under non-drought conditions (NDVI>0.6 and NDWI>0.4). NDVI values exhibited a quicker response to drought conditions than NDWI.

Gastrointestinal parasite infections in livestock and companion animals in Mongolia have not been investigated sufficiently. This study aimed to determine the prevalence of cyclophyllid cestodes (Taeniidae and Mesocestoididae) in Mongolian sheepdogs using copro-DNA analysis. Sheepdog fecal samples (n = 1242) were collected from five ecological zones (mountain taiga, forest-steppe, steppe, desert-steppe, and desert) and four geographical regions (Western, Khangai, Central, and Eastern) within 20 of the country's 21 provinces. Among the 1242 samples, 201 (16.2%) tested positive for mitochondrial cytochrome c oxidase subunit 1 (cox1) and ribosomal 12S rRNA encoding genes of cyclophyllid cestodes. Prevalence in the mountain taiga, forest-steppe, steppe, desert-steppe, and desert zones was 29.2%, 15.4%, 15.1%, 20.1%, and 9.1%, respectively. Prevalence in the Western, Khangai, Central, and Eastern regions was 19.9%, 18.6%, 12.1%, and 12.8%, respectively. Taenia hydatigena, Taenia multiceps, and two Mesocestoides species (Mesocestoides sp.1 and Mesocestoides sp.2) were identified. T. hydatigena was found in the samples from all 20 provinces (all five zones and four regions), while T. multiceps was detected in the samples from 19 provinces (all five zones and four regions). Mesocestoides sp.1 infection was detected in the samples from all zones (except desert) and regions; it was detected in 14 provinces. Mesocestoides sp.2 infection was detected in the samples from all zones (except mountain taiga) and regions and found in seven provinces. Cyclophyllidea infection in sheepdogs is highly prevalent across Mongolia, representing a zoonotic risk. Implementation of a surveillance program for sheepdogs and their owners, and the wild animals in all ecological zones should be considered. In addition, control measures, including public awareness campaigns, especially for sheepdog owners, and periodic deworming of sheepdogs are warranted.

Aim: Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection. Location: We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km2 of Mongolia's potential snow leopard range. Methods: Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country. Results: Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses. Main conclusions: This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that <12% of its entire land mass, and 42% of the potential snow leopard

This study aims to assess the impacts of both climate change and anthropogenic disturbances such as mining development and urbanization on pasture grazing capacity and its vulnerability in arid and semi-arid regions. To achieve the purpose, we have developed an integrated model to evaluate the pasture grazing capacity (GC), grazing pressure (GP) and vulnerability (VI). The model was applied to four target areas: an urban area (Ulaanbaatar) and steppe area (Altanbulag) in semi-arid regions and a mining area (Khanbogd) and desert (Manlai) in arid regions. The results revealed that GP greatly exceeded GC in the urban and mining areas, where presented higher vulnerability than other areas. The order of GC, GP and VI was: (1) GC: steppe area > urban area > desert area > mining area, (2) GP: urban area > steppe area > mining area > desert area, and (3) VI: urban area > mining area > desert area > steppe area. Finally, the change rate of GC, GP and VI in last two decades implied that comparing with climate change; anthropogenic disturbances had more significant impacts on pasture vulnerability.

Forest distribution in the forest-steppe of Mongolia depends on relief, permafrost, and climate, and is highly sensitive to climate change and anthropogenic disturbance. Forest fires and logging decreased the forest area in the forest-steppe of Mongolia. The intention of this study was to identify the geoecological parameters that control forest distribution and living-tree biomass in this semi-arid environment. Based on these parameters, we aimed to delineate the area that forest might potentially occupy and to analyse the spatial patterns of actual and potential tree biomass.

Abstract In semi-arid central Asia, relief has a strong impact on the distribution of vegetation and discontinuous permafrost. Our aim was to analyse causal chains and inter-relationships that control the spatial patterns of forest and permafrost in the forest-steppe of the northern Khangai Mountains in Mongolia. For this purpose, we conducted soil-profile descriptions, ground-penetrating radar sounding, and vegetation mapping to gain information about forest and permafrost distribution. We integrated remote-sensing analysis and field-mapping data, including soil properties, vegetation cover, forest fires and anthropogenic forest use. We developed and applied a technique for spatial delineation of permafrost distribution, based on the parameters Topographic Wetness Index (TWI), incoming solar radiation and Normalized Difference Vegetation Index (NDVI). Key outcomes of this study are that the occurrence of discontinuous permafrost within 1 m depth is limited to forest stands larger than 100 ha on north-facing slopes. Dense ground vegetation supports permafrost, whereas sandy soil texture leads to greater depth of the permafrost table. As the seasonal ice in the active layer progressively melts down during summer, meltwater interflow above the permafrost table provides additional soil moisture downslope. This process is reflected in enhanced vitality of the steppe vegetation on toe slopes below forests with permafrost. This effect can in turn be used to indirectly detect permafrost in forest stands by remote sensing. Permafrost mostly disappears after forest fires and other severe disturbances, but it may re-establish during forest regrowth. However, climate warming is presently leading to a loss of permafrost regeneration potential after disturbance, and to a shift from climate-induced and ecosystem-driven permafrost to entirely ecosystem-protected permafrost. These trends will result in a further decrease of permafrost area after forest disturbance.

Summary Research results suggest that some 86% of the species on Earth, and 91% in the ocean, still await description. Protecting biodiversity is vital for avoiding the next pandemic. It is estimated that 75 percent of all emerging infectious diseases in humans are zoonotic (those transferred from animals to humans). Land-use change and wildlife exploitation increase infectious disease risk by bringing people and domestic animals in close proximity to pathogen-carrying wildlife, and by disrupting the ecological processes that keep diseases in check. The economy and human well-being also depend on biodiversity for food, clean water, flood protection, erosion control, inspiration for innovation and much more. Over half the world’s global domestic product is moderately or highly dependent on biodiversity. The ongoing decline of biodiversity therefore poses important risks to society. Investing in biodiversity as part of the COVID-19 policy response can help to minimize these risks, while providing immediate jobs and economic stimulus (Biodiversity and the economic response to COVID-19: Ensuring a green and resilient recovery).

This paper addresses the ecosystem characteristics, biodiversity, conservation priorities, current threats and sustainable management of Khar Yamaat Nature Reserve, which lies in northeastern Mongolia. The formation of Khar Yamaat’s ecosystem and its biological diversity are unique in eastern Mongolia. Biogeographically, this nature reserve is located at the intersection between diff erent phytogeographical regions, specifi cally the Central-Khalkh dry steppe, Mongol-Dahurian forest-steppe, and Eastern-Mongolian tall-grass steppe. As such, this nature reserve is home to a diverse complement of plants and animals representing the various ecoregions, was established in 1998 to protect 50,691 hectares of rocky-mountains surrounded by vast steppes. Khar Yamaat’s unique geological formation and assemblage of ecosystems have, since then, become an area of focus for environmental restoration and a center for research and monitoring. In general, the habitats of the nature reserve were found to be largely intact, if stressed to varying degrees, but wildlife populations appeared to be low. Anthropogenic infl uences, particularly heavy grazing by livestock, have threatened some species of vascular plants with extinction and reduced the abundance and distributions of a few other species. Serious threats included excessive or illegal take of plants and animals, overgrazing by livestock, human caused wildfi res, climate change and associated drought, and mining in the buff er zone. In this paper, we discuss issues of conservation and sustainable management of Khar Yamaat Nature Reserve.

This paper addresses the ecosystem characteristics, biodiversity, conservation priorities, current threats and sustainable management of Khar Yamaat Nature Reserve, which lies in northeastern Mongolia. The formation of Khar Yamaat’s ecosystem and its biological diversity are unique in eastern Mongolia. Biogeographically, this nature reserve is located at the intersection between diff erent phytogeographical regions, specifi cally the Central-Khalkh dry steppe, Mongol-Dahurian forest-steppe, and Eastern-Mongolian tall-grass steppe. As such, this nature reserve is home to a diverse complement of plants and animals representing the various ecoregions, was established in 1998 to protect 50,691 hectares of rocky-mountains surrounded by vast steppes. Khar Yamaat’s unique geological formation and assemblage of ecosystems have, since then, become an area of focus for environmental restoration and a center for research and monitoring. In general, the habitats of the nature reserve were found to be largely intact, if stressed to varying degrees, but wildlife populations appeared to be low. Anthropogenic infl uences, particularly heavy grazing by livestock, have threatened some species of vascular plants with extinction and reduced the abundance and distributions of a few other species. Serious threats included excessive or illegal take of plants and animals, overgrazing by livestock, human caused wildfi res, climate change and associated drought, and mining in the buff er zone. In this paper, we discuss issues of conservation and sustainable management of Khar Yamaat Nature Reserve.

Shrub expansion has been widely documented in Northern Hemisphere due to the climate change and land use impacts. The findings of some studies show that shrub expansion greatly corresponds with changes in temperature and precipitation in Arctic, whereas studies in Tibetan Plateau show that shrub expansion is more dependent on soil moisture. However, there has not been sufficient studies of shrub expansion in Central Asia, including our country. We carried out studies on 12 shrub species present in Khar Yamaat Natural Reserve Area (N47.645727, E112.043829) to determine the response of several shrub species to climate factors and disturbances. We were able to distinguish diverse pore arrangements, various growth patterns, climate-growth relationships and finally, pointer years were recorded as well. That being the case, shrubs in Mongolia have successfully been proven to have a high dendrochronological potential and it is practicable to apply it for rangeland and ecological assessments.

The present study gives an overview of the flora of Hustai National Park, which hosts southern outposts of boreal forests embedded in a matrix of typical steppes. We address floristic composition, life forms, ecological groups and geographical elements, and compare our data against studies from broadly similar regions. A total of 493 vascular plant species belonging to 246 genera and 65 families were recorded. The biggest plant families are Asteraceae (67 species) followed by Poaceae (56 species), Fabaceae (51 species), and Rosaceae (33 species), while 21 families were represented by only one species each. Mesophytes (32.5%) and xerophytes (25.4%) were the most frequent ecological groups, indicating a typical mountain steppe environment. Most species were hemicryptophytes (56.8%), followed by therophytes (18.7%) and cryptophytes (geophytes 10.5%), while the least frequent life form classes were chamaephytes (5.1%) and helophytes (0.2%). Asian chorological elements constituted 52.3% of the total flora, while Eurasian account for 30%, Holarctic for 14.8%, Asian‐American for 1.4% and Cosmopolitan for 1.4%. The Hustai mountain range thus represents a key example of the transition zone between the relatively moist Taiga forests and the drier steppe grasslands. These climate transitional zones are very sensitive to changing climate and land use.