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Spatial patterns of herbaceous biodiversity in Mongolia steppe were examined and explained with biotic and abiotic factors including climate, livestock grazing, and fire disturbance. Vegetation data were collected from 63 sites across different steppe types (i.e., semi-desert, typical, and forb steppes) in 2012 and 2013. Three categorical (three st...
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... the latitudinal gradients from south to north, precipitation increases and air temperature decreases, and steppe type changes from semi-desert to forb-steppe types. Such distinct climatic gradients were identified across the weather stations in our study area (Table 1). Generally, distinct biome-specific climate gradient in our study region can be distinguished as: hot (mean annual temperature 2.6 °C) and dry (mean annual precipitation 132 mm y −1 ) semi-desert steppe, cool (0.40 °C) and wet (284 mm y −1 ) forbsteppe, and intermediate temperature (1.39 °C) and precipitation (201 mm y −1 ) of typical steppe (Table 1). ...Context 2
... distinct climatic gradients were identified across the weather stations in our study area (Table 1). Generally, distinct biome-specific climate gradient in our study region can be distinguished as: hot (mean annual temperature 2.6 °C) and dry (mean annual precipitation 132 mm y −1 ) semi-desert steppe, cool (0.40 °C) and wet (284 mm y −1 ) forbsteppe, and intermediate temperature (1.39 °C) and precipitation (201 mm y −1 ) of typical steppe (Table 1). ...Context 3
... biotic and abiotic factors were collected for explaining spatial biodiversity pattern. Monthly climatic data (year 2001 to 2010) from 10 meteorological stations (Table 1, triangles in Fig. 1a) were collected from the Mongolia Institute of Meteorology, Hydrology, and Environment for the study regions. We assumed that site weather could be represented by the climatic data from the nearest meteorological station if they were less than 50 km from each other. ...Similar publications
Accurate estimates of forest aboveground biomass (AGB) could reduce uncertainties in the characterization of terrestrial carbon fluxes. Light Detection and Ranging (LiDAR) provides an accurate measure of canopy height and vertical structure and information for the estimation of aboveground biomass of vegetation. Spaceborne large footprint LiDAR (IC...
Climate is one of the most important factors affecting the condition of vegetation. Plants are highly sensitive to climate change and display the most sensitive response to the effect of the climate change and environment, most particularly seen in the annual and seasonal alternations of vegetation productivity. Through the analysis of remotely sen...
Areas of grassland improvement and degradation were mapped and assessed to identify the driving forces of change in vegetation cover in the Three Rivers headwater region of Qinghai, China. Based on linear regression at the pixel level, we analyzed the vegetation dynamics of the grasslands of this region using MODIS NDVI data sets from 2000 to 2010....
Climate changes are having dramatic ecological impacts in mid- to high-latitude mountain ranges where growth conditions are limited by climatic variables such as duration of growing season, moisture, and ambient temperature. We document patterns of forest vegetative response for 5 major alpine forest communities to current climate variability in th...
South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the...
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... Major mountain ranges (e.g., the Altai and Sayan Range in the northwest, the Khangai Range in the central region, and the Great Hingan Range in the east) intercept moisture, resulting in rain shadow regions in the west, south, and southeast [21]. Precipitation decreases gradually from the northern to the southern territory, where forest steppe, typical steppe, desert steppe, and desert occur in turn; vegetation production and biodiversity are positively correlated with precipitation [3,27,28]. ...
In the present study, we tested the applicability of multi-sensor satellite data to account for key natural factors of annual livestock number changes in county-level soum districts of Mongolia. A schematic model of nomadic landscapes was developed and used to select potential drivers retrievable from multi-sensor satellite data. Three alternative methods (principal component analysis, PCA; stepwise multiple regression, SMR; and random forest machine learning model, RF) were used to determine the key drivers for livestock changes and Dzud outbreaks. The countrywide Dzud in 2010 was well-characterized by the PCA as cold with a snowy winter and low summer foraging biomass. The RF estimated the annual livestock change with high accuracy (R2 > 0.9 in most soums). The SMR was less accurate but provided better intuitive insights on the regionality of the key factors and its relationships with local climate and Dzud characteristics. Summer and winter variables appeared to be almost equally important in both models. The primary factors of livestock change and Dzud showed regional patterns: dryness in the south, temperature in the north, and foraging resource in the central and western regions. This study demonstrates a synergistic potential of models and satellite data to understand climate–vegetation–livestock interactions in Mongolian nomadic pastures.
... It is generally hypothesized that the increase of human activity intensity can reduce plant species diversity and therefore reduce grassland ANPP and stability [9][10][11] . Although the decrease of plant species diversity with the increase of human activity intensity has been widely reported by previous studies [12][13][14] , the observed diversityfunction relationships are inconsistent [ 2 , 15-19 ], leading to contradictory understandings on the effect of human activity intensity on grassland ecosystem functions [20] . Although ecological theories, e.g., the complementary effect and the insurance effect, have been successfully used to explain these inconsistent observations [ 2 , 16 , 19 ], we still lack a complete understanding on the exact processes leading to various anthropogenic-induced diversity-function relationships, limiting our capabilities to make appropriate management policies to enhance grassland ecosystem functionality. ...
Grasslands are one of the largest coupled human-nature terrestrial ecosystems on Earth, and severe anthropogenic-induced grassland ecosystem function declines have been reported recently. Understanding factors influencing grassland ecosystem functions is critical for making sustainable management policies. Canopy structure is an important factor influencing plant growth through mediating within-canopy microclimate (e.g., light, water, and wind), and it is found coordinating tightly with plant species diversity to influence forest ecosystem functions. However, the role of canopy structure in regulating grassland ecosystem functions along with plant species diversity has been rarely investigated. Here, we investigated this problem by collecting field data from 170 field plots distributed along an over 2000 km transect across the northern agro-pastoral ecotone of China. Aboveground net primary productivity (ANPP) and resilience, two indicators of grassland ecosystem functions, were measured from field data and satellite remote sensing data. Terrestrial laser scanning data were collected to measure canopy structure (represented by mean height and canopy cover). Our results showed that plant species diversity was positively correlated to canopy structural traits, and negatively correlated to human activity intensity. Canopy structure was a significant indicator for ANPP and resilience, but their correlations were inconsistent under different human activity intensity levels. Compared to plant species diversity, canopy structural traits were better indicators for grassland ecosystem functions, especially for ANPP. Through structure equation modeling analyses, we found that plant species diversity did not have a direct influence on ANPP under human disturbances. Instead, it had a strong indirect effect on ANPP by altering canopy structural traits. As to resilience, plant species diversity had both a direct positive contribution and an indirect contribution through mediating canopy cover. This study highlights that canopy structure is an important intermediate factor regulating grassland diversity-function relationships under human disturbances, which should be included in future grassland monitoring and management.
... Among various climate factors, precipitation is particularly important to control the vegetative composition of plant communities in semi-arid and arid rangelands (Fujita et al. 2013;Graetz et al. 1988). Along the precipitation gradient from arid to semi-arid, the vegetation becomes dense and diverse and steppe-type varies gradually from desert steppe to typical steppe and to forest steppe in the Mongolian rangelands, where aridity primarily controls the composition of plant life forms (Fernandez-Gimenez and Allen-Diaz 1999; Narantsetseg et al. 2015). ...
... For examples, above-ground standing biomass increases from arid to semi-arid steppes (Fernandez-Gimenez and Allen-Diaz 1999). Perennial herbaceous plant is the dominant life form in semi-arid steppes, but this changes to annual or biennial life form in arid steppe of Mongolia (Fujita et al. 2012;Narantsetseg et al. 2015). Climate also affects vegetation indirectly by regulating number and composition of local livestock. ...
... In fact, some studies aimed at comparing the relative importance of different drivers concluded that either climate (Liu et al., 2013) or grazing (Hilker et al., 2014) played a more prominent role, but this varied regionally and differed between ecological zones (Liu et al., 2013). For instance, Narantsetseg et al. (2015) concluded that rangeland health in Mongolia is controlled by regional variations in climate and vegetation productivity but is locally modified by intensive livestock grazing pressure with different grazing sensitivity for different steppe types. Other studies concluded that grazing might not be the leading driver of degradation in non-equilibrium systems like the desert steppe and desert, where precipitation has a more prominent role in causing vegetation change (Fernandez-Gimenez and Allen-Diaz, 1999;Wesche and Retzer, 2005). ...
... A more common approach to infer the effects of grazing was based on spatial gradients, where the distance to places where livestock concentrate, such as winter camps or wells, was used as a proxy for grazing intensity (Ahlborn et al., 2020;Narantsetseg et al., 2015). In some cases, the gradients in grazing intensity were confirmed using dung counts in the same areas (Sasaki et al., 2018), but dung counts may not work well for all species and may differ between ecological zones (Jamsranjav et al., 2018). ...
Rangeland degradation compromises the functioning of extensive natural ecosystems and threatens pastoral livelihoods worldwide. Yet, defining rangeland degradation and its underlying causes remains controversial. In this study we review rangeland studies to identify different approaches used to assess rangeland degradation in Mongolia, where the prevalence of degradation is frequently referenced in media and policy documents. We compiled studies addressing rangeland degradation, with a special emphasis on the grey literature, to assess: 1) how different studies defined and quantified rangeland degradation; 2) whether a theoretical background was explicitly mentioned; 3) which drivers of degradation were identified and whether their effects were quantified; and 4) the distribution of the studies across relevant environmental gradients. We found 114 studies published between 1950 and 2021. Degradation was frequently assessed as a change in vegetation or land cover, but there was no standard definition of rangeland degradation and only a few studies explicitly defined contrasting degradation levels (19 studies). Less than one third of studies (27) referred to a theoretical framework. Grazing and climate (precipitation and temperature), alone or in combination, were most frequently mentioned as drivers of degradation but the impact of different drivers differed across ecological zones. The majority of studies were conducted in the steppe, forest steppe and desert steppe zones of central Mongolia. Future studies should consider the differences in ecological potential of each rangeland and quantify the relative importance of different drivers in each ecological zone. Emerging initiatives for rangeland assessment and monitoring that use long-term data collection following standardized methodologies based on robust theoretical frameworks hold promise for the design of policies and strategies for sustainable land use in Mongolia.
... As a result, Reference [20] tested 168 metrics of spectral diversity. Among them, however, Normalized Difference Vegetation Index (NDVI) or its variances (NDVI Sill, NDVI Range, CVNDVI) are the most commonly applied, mainly in biodiversity analysis [21,22]. The third type of landscape metrics, which allow one to quantify, among others, the functioning and stability of ecosystems, their biodiversity and degree of fragmentation [23,24]. ...
Landscape quality (LQ) encompasses diverse characteristic of the natural and cultural environment. The most effective tool to analyze LQ is the use of indicators. The main problem in the assessment of LQ is not the lack of indicators, but its multitude. That is why, the indicators’ categorization is a problematic issue. The paper aims to introduce and test the methodology for selecting the suitable indicators based on the example of two national parks located in the south-east part of Poland. The method composed of the following stages: (1) Selection of spatial units being analyzed; (2) selection of indicators type(s); (3) selection of specific indicators; (4) calculation of indicator set no 1; (5) analysis of the correlation between indicators’ pairs; (6) selection of a final set of indicators; (7) analysis of effectiveness. The latter stage, refers to the statistical analysis of significance between results obtained dependently on the data sources, a spatial unit of analysis and analyzed regions. The results showed that the categorization composed of ten, mainly composite indicators, can be applied to conclude on different levels of LQ of protected areas. The differences between two analyzed data sources, different spatial units, as well as diverse regions, occurred to be statistically insignificant. Generally, the results of the effectiveness analysis showed that a final categorization of LQ indicators is adequate to conclude on the diverse dimensions of LQ of analyzed protected areas.
... The Mongolian steppe is one of the largest temperate grassland biomes in the world with diverse floral communities and environmental gradients covering an extensive region ( Narantsetseg et al. 2015). Recently, this steppe has suffered from increasing natural and anthropogenic hazards such as desertification and Dzud (i.e. ...
... applied for on-site FVC observations ( Narantsetseg et al. 2015) but, recently, FVC estimation based on nadir pointing digital camera images (DCI) was suggested as an alternative measure of field FVC using color classification algorithms. ( Li et al. 2005;Luscier et al. 2006;Laliberte et al. 2007;Jiapaer, Chen, and Bao 2011). ...
... Toward the south, forest gradually disappears and grassland coverage grades through the typical steppe grassland of central Mongolia to sparse or desert steppe or deserts in the Gobi regions. In the eastern part of Mongolia, tall herbaceous plants grow but, to the west, dryness increases and vegetation becomes a short-grassdominated grassland ( Narantsetseg et al. 2015). ...
Fractional green vegetation cover (FVC) is a useful indicator for monitoring grassland status. Satellite imagery with coarse spatial but high temporal resolutions has been preferred to monitor seasonal and inter-annual FVC dynamics in wide geographic area such as Mongolian steppe. However, the coarse spatial resolution can cause a certain uncertainty in the satellite-based FVC estimation, which calls attention to develop a robust statistical test for the relationship between field FVC and satellite-derived vegetation indices. In the arid and semi-arid Mongolian steppe, nadir pointing digital camera images (DCI) were collected and used to produce a FVC dataset to support the evaluation of satellite-based FVC retrievals. An optimal DCI processing method was determined with respect to three color spaces (RGB, HIS, L*a*b*) and six green pixel classification algorithms, from which a country-wide dataset of DCI-FVC was produced and used for evaluating the accuracy of satellite-based FVC estimates from MODIS vegetation indices. We applied three empirical and three semi-empirical MODIS-FVC retrieval models. DCI data were collected from 96 sites across the Mongolian steppe from 2012 to 2014. The histogram algorithm using the hue (H) value of the HIS color space was the optimal DCI method (r2 = 0.94, percent root-mean-square-error (RMSE) = 7.1%). For MODIS-FVC retrievals, semi-empirical Baret model was the best-performing model with the highest r2 (0.69) and the lowest RMSE (49.7%), while the lowest MB (+1.1%) was found for the regression model with normalized difference vegetation index (NDVI). The high RMSE (>50% or so) is an issue requiring further enhancement of satellite-based FVC retrievals accounting for key plant and soil parameters relevant to the Mongolian steppe and for scale mismatch between sampling and MODIS data.
... In arid grasslands, though climate-driven, inter-annual variations of plant biodiversity and biomass are strong (Fernandez-Gimenez and Allen-Diaz 1999; Stumpp et al. 2005), it is also clear that livestock have critical impacts on plant communities and locally participate in pasture land degradation . Because the daily feeding distance of livestock is generally constrained to a few kilometers in Mongolia (Cérénhand 2005), livestock impacts can produce finer-scale pasture heterogeneity of plant composition and standing biomass than that caused by regional climate gradients (Narantsetseg et al. 2014;Narantsetseg et al. 2015). ...
Backgrounds: In arid grasslands, wells are subject to heavy trampling and grazing pressure, which can increase vulnerability to local land degradation. To investigate trampling and grazing, we surveyed plant communities at three well sites in the desert steppe of Mongolia, using 1600-m line transects from the wells. The sites (Bshrub, Sshrub, and shrubL) differed by concomitant shrub type (big shrub, small shrub, and shrub-limited) and livestock pressure (light, medium, and heavy). A plant classification scheme based on edibility and morphology (rosette or creeping type) was used to separate grazing and trampling effects on plant communities. Results: Edible plants were dominant at all sites but a fraction of grazing- and trampling-tolerant plants increased in the order Bshrub, Sshrub, and shrubL, following livestock pressure. Clear transition zones from inedible to edible plant groups were recognized but at different locations and ranges among the sites. Trampling-tolerant plants explained 90% of inedible plants at Sshrub with camels and horses, but grazing-tolerant plants prevailed (60%) at shrubL with the largest livestock number. Plant coverage increased significantly along the transects at Bshrub and Sshrub but showed no meaningful change at shrubL. Herbaceous plant biomass showed significant positive and negative trends at Bshrub and shrubL, respectively. Conclusions: Both grazing and trampling can produce larger fractions of inedible plants; in this, camel and horses can have considerable effects on desert-steppe plant communities through trampling.
In the context of global climate change, changes in precipitation patterns will have profound effects on desert plants, particularly on shallow-rooted plants, such as ephemeral plants. Therefore, we conducted an experiment on artificial control of precipitation for four dominant ephemeral plants, Erodium oxyrhinchum, Alyssum linifolium, Malcolmia scorpioides, and Hyalea pulchella, in the southern edge of Gurbantunggut Desert. We measured the importance value and some growth parameters of the four species under increased or decreased precipitation and constructed trait correlation networks for each of the four species. We also compared the response of increased or decreased precipitation to vegetation coverage. The results show that drought significantly reduced the survival rate, seed production and weight, and aboveground biomass accumulation of ephemeral plants. The four ephemeral plants showed different tolerance and response strategies to precipitation changes. E. oxyrhinchum and M. scorpioides can avoid drought by accelerating life history, and E. oxyrhinchum, A. linifolium, and H. pulchella can alleviate the negative effects of drought by adjusting leaf traits. However, the response of different species to the wet treatment was not consistent. Based on the results of the trait correlation network, we consider A. linifolium belongs to the ruderal plant, E. oxyrhinchum and M. scorpioides belong to the competitive plants, and H. pulchella belongs to the stress-tolerant plant. The outstanding trait coordination ability of E. oxyrhinchum makes it show absolute dominance in the community. This indicate that ephemeral plants can adapt to precipitation changes to a certain extent, and that distinct competitive advantages in growth or reproduction enabled species coexistence in the same ecological niche. Nevertheless, drought significantly reduces their community cover and the ecological value of ephemeral plants. These findings established the basis to predict vegetation dynamics in arid areas under precipitation changes.
Landscape-based surrogate measures are commonly used to measure plant diversity, however, the difference between predicted diversity and field measures raises doubts about their effectiveness. A review of the literature was performed to address this (115 studies first evaluations, 61 second evaluations) to establish the types of surrogates used, their usefulness and factors affecting their prediction power. Three types of indicators were detected: landscape metrics, indicators based on the variability of spectral data and geomorphometric indices. The most effective indicators were slope, altitude, elevation, percentage of land cover (PLAND) and edge density (ED), as well as diverse distance metrics. Spectral data, shape index (SHAPE), patch area (PA) and the Shannon diversity index (SHDI) were less useful. Four possible explanatory variables for the effectiveness of surrogates were identified: landscape type analysed, species (taxa) examined, habitat quality and scale of research.
