Climate warming alters the relative importance of plant root and microbial community in regulating the accumulation of soil microbial necromass carbon in a Tibetan alpine meadow.

Climate warming is predicted to considerably affect variations in soil organic carbon (SOC), especially in alpine ecosystems. Microbial necromass carbon (MNC) is an important contributor to stable soil organic carbon pools. However, accumulation and persistence of soil MNC across a gradient of warming are still poorly understood. An 8-year field experiment with four levels of warming was conducted in a Tibetan meadow. We found that low-level (+0-1.5°C) warming mostly enhanced bacterial necromass carbon (BNC), fungal necromass carbon (FNC), and total MNC compared with control treatment across soil layers, while no significant effect was caused between high-level (+1.5-2.5°C) treatments and control treatments. The contributions of both MNC and BNC to soil organic carbon were not significantly affected by warming treatments across depths. Structural equation modeling analysis demonstrated that the effect of plant root traits on MNC persistence strengthened with warming intensity, while the influence of microbial community characteristics waned along strengthened warming. Overall, our study provides novel evidence that the major determinants of MNC production and stabilization may vary with warming magnitude in alpine meadows. This finding is critical for updating our knowledge on soil carbon storage in response to climate warming.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing RNDVI-T in spring (May-June) and autumn (September) and decreasing RNDVI-T in summer (July-August). Growing season RNDVI-T for alpine steppe increased slightly, mainly due to increasing RNDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (RNDVI-P) for alpine meadow increased slightly, mainly in spring and summer, and RNDVI-P for alpine steppe increased, mainly in spring. Moreover, RNDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. RNDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland.

Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau.

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land-atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin ) than with maximum temperature (Tmax ) before the growing season ('preseason' henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin , but negatively with Tmax . A 1-K increase in preseason Tmin advanced green-up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000-2004 (P < 0.01). In contrast, increases in preseason Tmax did not advance green-up date (P > 0.10) and higher summer Tmax even reduced greenness by 2.6% K(-1) (P < 0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax . Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.

Precipitation impacts on vegetation spring phenology on the Tibetan Plateau.

The ongoing changes in vegetation spring phenology in temperate/cold regions are widely attributed to temperature. However, in arid/semiarid ecosystems, the correlation between spring temperature and phenology is much less clear. We test the hypothesis that precipitation plays an important role in the temperature dependency of phenology in arid/semiarid regions. We therefore investigated the influence of preseason precipitation on satellite-derived estimates of starting date of vegetation growing season (SOS) across the Tibetan Plateau (TP). We observed two clear patterns linking precipitation to SOS. First, SOS is more sensitive to interannual variations in preseason precipitation in more arid than in wetter areas. Spatially, an increase in long-term averaged preseason precipitation of 10 mm corresponds to a decrease in the precipitation sensitivity of SOS by about 0.01 day mm(-1) . Second, SOS is more sensitive to variations in preseason temperature in wetter than in dryer areas of the plateau. A spatial increase in precipitation of 10 mm corresponds to an increase in temperature sensitivity of SOS of 0.25 day °C(-1) (0.25 day SOS advance per 1 °C temperature increase). Those two patterns indicate both direct and indirect impacts of precipitation on SOS on TP. This study suggests a balance between maximizing benefit from the limiting climatic resource and minimizing the risk imposed by other factors. In wetter areas, the lower risk of drought allows greater temperature sensitivity of SOS to maximize the thermal benefit, which is further supported by the weaker interannual partial correlation between growing degree days and preseason precipitation. In more arid areas, maximizing the benefit of water requires greater sensitivity of SOS to precipitation, with reduced sensitivity to temperature. This study highlights the impacts of precipitation on SOS in a large cold and arid/semiarid region and suggests that influences of water should be included in SOS module of terrestrial ecosystem models for drylands.

Siwu decoction exerts a phytoestrogenic osteoprotective effect on postmenopausal osteoporosis via the estrogen receptor/phosphatidylinositol 3-kinase/serine/threonine protein kinase pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Siwu decoction (SWD) is widely used in gynecological diseases, such as peripheral menopause syndrome, premature ovarian failure, and menstrual disorder. However, the mechanism of SWD on postmenopausal osteoporosis (PMOP) remains unclear. AIM OF THE STUDY: To discover the phytoestrogenic osteoprotective effect of SWD on PMOP. MATERIALS AND METHODS: The potential mechanism of SWD on PMOP was filtered through network pharmacology research. The potential mechanism was verified in MC3T3-E1 cell lines in vitro. CCK8 assay was conducted to assess cell proliferation and the expressions of ER/PI3K/AKT pathway were analyzed using Western blot. Female F-344 rats were chosen to set up the PMOP model. The osteoprotective effect of SWD in vivo was evaluated using Hematoxylin-eosin staining, TRAP staining, Goldner staining and DXA. The potential mechanism was verified in vivo through Western blot and immunohistochemistry. RT-qPCR was conducted to unveil the expressions of osteogenesis genes. RESULTS: Network pharmacology research showed that ER/PI3K/AKT pathway may be the potential mechanism of SWD on PMOP. SWD promoted the proliferation of osteoblasts and regulated the protein expressions of ER/PI3K/AKT pathway in vitro. SWD improved the morphological structure, bone mineralization and bone mineral density of femurs and suppressed osteoclastogenesis in PMOP rat model via ER/PI3K/AKT pathway in vivo. In addition, SWD regulated the mRNA expressions of osteogenesis-related genes. CONCLUSIONS: SWD exerts a phytoestrogenic osteoprotective on PMOP by regulating ER/PI3K/AKT pathway, which marks it as a valuable medicine or supplement of PMOP.

Impacts of the Three Gorges Dam on riparian vegetation in the Yangtze River Basin under climate change.

As the largest hydroelectric project in the world, the Three Gorges Dam (TGD) is expected to have significant environmental and ecological impacts on riparian vegetation in the Yangtze River Basin (YRB). However, existing studies have mainly focused on small segments of the YRB. In addition, few studies have quantified the responses of riparian vegetation to both climatic factors and dam construction. In this study, we investigated riparian vegetation dynamics over the entire YRB before, during, and after the construction of TGD from 1982 to 2015 using the normalized difference vegetation index (NDVI). Furthermore, the effects of climatic factors and dam construction on riparian vegetation were quantitatively analyzed using path analysis. The results demonstrate that the YRB has experienced a generally greening trend after TGD construction. The impacts of climate change on riparian vegetation have exhibited notable spatial heterogeneity and temperature is the main climatic factor that affects riparian vegetation growth. Moreover, TGD becomes the major contributor to riparian vegetation dynamics in the YRB after TGD construction. TGD has not only directly enhanced riparian vegetation but also indirectly affected riparian vegetation by regulating the microclimate. This study highlights the significance of anthropogenic interference when evaluating the relationships between riparian vegetation and climatic factors, providing useful insights for the effective management and conservation of large-scale riparian ecosystems.

Altitude explains insignificant autumn phenological changes across regions with large topography relief in the Tibetan Plateau.

The start of the growing season (SGS) and the end of the growing season (EGS) are widely employed in global change studies to represent the spring and autumn phenology, respectively. Despite the Tibetan Plateau (TP) experiencing significant warming in recent decades, EGS has exhibited only slight changes. Previous studies have concentrated on exploring the environmental regulation of phenology, ignoring the distinctive influences of elevation. Therefore, a more in-depth investigation into the underlying mechanism is warranted. In this study, we investigate the variability of EGS among alpine vegetation regions at different elevations and conduct an analysis based on satellite data. Phenology data of alpine vegetation are extracted from SPOT NDVI dataset spanning from 1999 to 2018, using a piecewise-logistic-maximum-ratio method. We analyze the factors influencing EGS trends at different elevations. The results show that the overall insignificant variation in EGS is mainly attributed to altitude. With the altitude increasing, the annual mean EGS experiences a delay of 0.28 days/100 m below 3500 m, while it advances by 0.2 days/100 m above 3500 m. The opposing shift in elevation below and above 3500 m leads to this counteraction. Elevation emerges as the predominant factor influencing EGS trends, explaining the highest variations (38 %), followed by SGS (22 %) and precipitation (22 %). The elevation effect is most pronounced in areas with substantial topography fluctuations. Moreover, the elevation lapse rate of EGS (ELR_EGS) exhibits an opposite trend with growing season (GS) temperature and a similar trend with GS precipitation between the regions below and above 3500 m, ultimately linking to this counteraction. This study underscores elevation is a critical regulator of vegetation EGS responses to climatic changes over the TP, revealing significant spatial heterogeneities in these responses.

Excessive climate warming exacerbates nitrogen limitation on microbial metabolism in an alpine meadow of the Tibetan Plateau: Evidence from soil ecoenzymatic stoichiometry.

Soil ecoenzymatic stoichiometry reflects the dynamic equilibrium between microorganism's nutrient requirements and resource availability. However, uncertainties persist regarding the key determinants of nutrient restriction in relation to microbial metabolism under varying degrees of warming. Our long-term and multi-level warming field experiment (control treatment, +0.42 °C, +1.50 °C, +2.55 °C) in a typical alpine meadow unveiled a decline in carbon (C)- and nitrogen (N)-acquired enzymes with escalating warming magnitudes, while phosphorus (P)-acquired enzymes displayed an opposite trend. Employing enzymatic stoichiometry modeling, we assessed the nutrient limitations of microbial metabolic activity and found that C and N co-limited microbial metabolic activities in the alpine meadow. Remarkably, high-level warming (+2.55 °C) exacerbated microbe N limitation, but alleviate C limitations. The structural equation modeling further indicated that alterations in soil extracellular enzyme characteristics (SES) were more effectively elucidated by microbial characteristics (microbial biomass C, N, P, and their ratios) rather than by soil nutrients (total nutrient contents and their ratios). However, the microbial control over SES diminished with higher levels of warming magnitude. Overall, our results provided novel evidence that the factors driving microbe metabolic limitation may vary with the degree of warming in Tibet alpine grasslands. Changes in nutrient demand for microorganism's metabolism in response to warming should be considered to improve nutrient management in adapting to different future warming scenarios.

Consistent time allocation fraction to vegetation green-up versus senescence across northern ecosystems despite recent climate change.

Extended growing season lengths under climatic warming suggest increased time for plant growth. However, research has focused on climatic impacts to the timing or duration of distinct phenological events. Comparatively little is known about impacts to the relative time allocation to distinct phenological events, for example, the proportion of time dedicated to leaf growth versus senescence. We use multiple satellite and ground-based observations to show that, despite recent climate change during 2001 to 2020, the ratio of time allocated to vegetation green-up over senescence has remained stable [1.27 (± 0.92)] across more than 83% of northern ecosystems. This stability is independent of changes in growing season lengths and is caused by widespread positive relationships among vegetation phenological events; longer vegetation green-up results in longer vegetation senescence. These empirical observations were also partly reproduced by 13 dynamic global vegetation models. Our work demonstrates an intrinsic biotic control to vegetation phenology that could explain the timing of vegetation senescence under climate change.

Concave Ni(OH)2 Nanocube Synthesis and Its Application in High-Performance Hybrid Capacitors.

The controlled synthesis of hollow structure transition metal compounds has long been a very interesting and significant research topic in the energy storage and conversion fields. Herein, an ultrasound-assisted chemical etching strategy is proposed for fabricating concave Ni(OH)2 nanocubes. The morphology and composition evolution of the concave Ni(OH)2 nanocubes suggest a possible formation mechanism. The as-synthesized Ni(OH)2 nanostructures used as supercapacitor electrode materials exhibit high specific capacitance (1624 F g-1 at 2 A g-1) and excellent cycling stability (77% retention after 4000 cycles) due to their large specific surface area and open pathway. In addition, the corresponding hybrid capacitor (Ni(OH)2//graphene) demonstrates high energy density (42.9 Wh kg-1 at a power density of 800 W kg-1) and long cycle life (78% retention after 4000 cycles at 5 A g-1). This work offers a simple and economic approach for obtaining concave Ni(OH)2 nanocubes for energy storage and conversion.

Life cycle assessment and carbon reduction potential prediction of electric vehicles batteries.

Electric vehicles (EVs) battery is a crucial component of energy storage components for electric vehicles. However, the environmental impact of EVs battery is still not clear. Therefore, this paper establishes a cradle-to-cradle life cycle assessment (LCA) frame and clarifies the environmental impacts on the entire lifespan of EVs battery in China. Specifically, the environmental impact of battery production, battery use, and recycling & disposal stages are analyzed and measured. In addition, the carbon reduction potential of recycling and secondary use under a future electricity mix is estimated. Results show that: (1) The production stage of EVs battery with the carbon emission of 105 kgCO2-eq/kWh, which has the most significant impact on the environment. (2) In the recycling process, cascade utilization can reduce 1.536 kgCO2-eq/kWh carbon emission. In terms of recycling methods, hydrometallurgy can reduce the most carbon emission (13.3 kgCO2-eq/kWh), followed by the combined hydro-pyrometallurgical process (8.11 kgCO2-eq/kWh) and pyrometallurgy (0.57 kgCO2-eq/kWh). (3) Under the estimated electricity mix in 2030, 2040, and 2050, the carbon emission in battery production can be approximately reduced by 31.9 %, 45 %, and 48.1 %, respectively.

Increased productivity of temperate vegetation in the preceding year drives early spring phenology in the subsequent year in northern China.

Under global warming, rising temperature have advanced spring phenology in recent decades. However, the internal physiological mechanisms driving changes in spring phenology still remain poorly understood. Here, we investigated the effects of temperate vegetation gross primary productivity (GPP) during the preceding year on spring phenology of the subsequent year based on the start of growing season (SOS) extracted from NDVI datasets between 1982 and 2015. We found that the preceding year's GPP had an effect on the subsequent year's SOS, equivalent to 33 %-50 % of effect of the preseason's mean temperature. Specifically, in the temperate and semi-humid or humid conditions, the preceding year's GPP had a stronger effect on SOS than in boreal or semi-arid conditions. In addition, the SOS of the dwarf vegetation, with less transport pressure and higher carbon concentrations, was more sensitive to the preceding year's GPP than that of tall forests. We found the effects of the preceding year's GPP on SOS varied with space and vegetation types. Therefore, the physiological mechanism should be considered in future spring phenology model separately according to space and vegetation types, to improve the accuracy of future phenology and then global carbon sequestration predictions.

Projecting future aboveground carbon sequestration rate of alpine forest on the eastern Tibetan Plateau in response to climate change.

The aboveground carbon sequestration rate (ACSR) of forests serves as an indicator of their carbon sequestration capacity over time, providing insights into the potential carbon sequestration capacity of forest ecosystems. To explore the long-term Spatiotemporal variation of ACSR in the transitional ecotone of the eastern Tibetan Plateau under climate change scenarios, we utilized a forest landscape model that was parameterized with forest inventory data from the eastern Tibetan Plateau to simulate this ecological function changes. The study found that climate warming had significant effect on forests ACSR in different types of forests. ACSR was significantly reduced (p<0.05) in cold temperate coniferous and temperate coniferous forests, whereas it was significantly increased in deciduous broad-leaved forests. However, the impact of climate warming on evergreen broad-leaved forests was found to be negligible. At the species level, climate warming has mostly suppressed the ACSR of coniferous trees, except for Chinese hemlock. The main dominant species, spruce and fir, have been particularly affected. Conversely, the ACSR of most broad-leaved trees has increased due to climate warming. In addition, at the landscape scale, the ACSR within this region is expected to experience a steady decline after 2031s-2036s. Despite the effects of climate warming, this trend is projected to persist. In conclusion, the forests ACSR in this region will be significantly affected by future climate warming. Our research indicates that climate warming will have a noticeable suppressive effect on conifers. It is imperative that this factor be taken into account when devising forest management plans for the future in this region.

Coarse spatial resolution remote sensing data with AVHRR and MODIS miss the greening area compared with the Landsat data in Chinese drylands.

The warming-wetting climates in Chinese drylands, together with a series of ecological engineering projects, had caused apparent changes to vegetation therein. Regarding the vegetation greening trend, different remote sensing data had yielded distinct findings. It was critical to evaluate vegetation dynamics in Chinese drylands using a series of remote sensing data. By comparing the three most commonly used remote sensing datasets [i.e., MODIS, Advanced Very High Resolution Radiometer (AVHRR), and Landsat], this study comprehensively investigated vegetation dynamics for Chinse drylands. All three remote sensing datasets exhibited evident vegetation greening trends from 2000 to 2020 in Chinese drylands, especially in the Loess Plateau and Northeast China. However, Landsat identified the largest greening areas (89.8%), while AVHRR identified the smallest greening area (58%). The vegetation greening areas identified by Landsat comprise more small patches than those identified by MODIS and AVHRR. The MODIS data exhibited a higher consistency with Landsat than with AVHRR in terms of detecting vegetation greening areas. The three datasets exhibited high consistency in identifying vegetation greening in Northeast China, Loess Plateau, and Xinjiang. The percentage of inconsistent areas among the three datasets was 39.56%. The vegetation greening areas identified by Landsat comprised more small patches. Sensors and the atmospheric effect are the two main reasons responsible for the different outputs from each NDVI product. Ecological engineering projects had a great promotion effect on vegetation greening, which can be detected by the three NDVI datasets in Chinese drylands, thereby combating desertification and reducing dust storms.

Elevational distribution and seasonal dynamics of alpine soil prokaryotic communities.

The alpine grassland ecosystem is a biodiversity hotspot of plants on the Qinghai-Tibetan Plateau, where rapid climate change is altering the patterns of plant biodiversity along elevational and seasonal gradients of environments. However, how belowground microbial biodiversity changes along elevational gradient during the growing season is not well understood yet. Here, we investigated the elevational distribution of soil prokaryotic communities by using 16S rRNA amplicon sequencing along an elevational gradient between 3,200 and 4,200 m, and a seasonal gradient between June and September in the Qinghai-Tibetan alpine grasslands. First, we found soil prokaryotic diversity and community composition significantly shifted along the elevational gradient, mainly driven by soil temperature and moisture. Species richness did not show consistent elevational trends, while those of evenness declined with elevation. Copiotrophs and symbiotic diazotrophs declined with elevation, while oligotrophs and AOB increased, affected by temperature. Anaerobic or facultatively anaerobic bacteria and AOA were hump-shaped, mainly influenced by moisture. Second, seasonal patterns of community composition were mainly driven by aboveground biomass, precipitation, and soil temperature. The seasonal dynamics of community composition indicated that soil prokaryotic community, particularly Actinobacteria, was sensitive to short-term climate change, such as the monthly precipitation variation. At last, dispersal limitation consistently dominated the assembly process of soil prokaryotic communities along both elevational and seasonal gradients, especially for those of rare species, while the deterministic process of abundant species was relatively higher at drier sites and in drier July. The balance between deterministic and stochastic processes in abundant subcommunities might be strongly influenced by water conditions (precipitation/moisture). Our findings suggest that both elevation and season can alter the patterns of soil prokaryotic biodiversity in alpine grassland ecosystem of Qinghai-Tibetan Plateau, which is a biodiversity hotspot and is experiencing rapid climate change. This work provides new insights into the response of soil prokaryotic communities to changes in elevation and season, and helps us understand the temporal and spatial variations in such climate change-sensitive regions.

Vehicle unpaved road response spectrum acquisition based on accelerometer and GPS data.

This paper describes a response acquisition system composed of some spindle accelerometers and a time synchronized on-board GPS receiver developed in order to collect the dynamic response of vehicle riding on an unpaved road. A method of time-space conversion for calculating the response spectrum is proposed to eliminate the adverse effect of time-varying speed, based on the transform from the equitime sampled spindle acceleration responses to equidistance sampling. By using two groups of independent distance histories acquired from GPS, a method called long-range error correction is proposed to improve the accuracy of the vehicle's distance information, which is critical for the time-space conversion. The accuracy and limitations of the system have been analyzed, and its validity has been verified by implementing the system on a wheel loader for road response spectrum measuring. This paper offers a practical approach to obtaining unpaved road response spectra for durability road simulation.

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Alpine grassland is threatened by the import of chemicals, fertilizers and other external resources with increasing human activities on the Qinghai-Tibet Plateau. It is unclear how carbon cycle of alpine grasslands is affected by the inputs of external resources such as nitrogen, phosphorus, and potassium (N, P, K) and their interactions. We conducted a 3 year experiment on the interactive addition of N, P and K with alpine grassland as the research object to clarify ecosystem carbon exchange process in response to resource addition by measuring community coverage and ecosystem carbon exchange. The results showed the alpine meadow was represented by carbon sequestration during the growing season. The mean value of net ecosystem CO2 exchange (NEE) was -13.0 µmol·m-2·s-1 under the control treatment. NEE, ecosystem respiration (ER), and gross ecosystem productivity (GEP) showed no significant responses when N, P and K were added separately. NEE was significantly increased by 95.3% and 63.9%, GEP was significantly increased by 45.5% and 33.0% under the combined addition of NP and NPK, but ER remained stable. The combined addition of NP or NPK mainly increased NEE and GEP by increasing the coverage of plant communities and affecting ecosystem water use efficiency. Plant community coverage was increased by 18.1% and 21.4%, respectively. The addition of NP increased productivity and autotrophic respiration in alpine meadow. It might cause soil acidification to inhibit heterotrophic respiration, thereby did not change ER due to the two aspects canceling each other out. The addition of N, P, K alone and NK and PK did not change ecosystem carbon exchange, while the combined addition of NP increased NEE and GEP on the nutrient-deficient alpine meadows, indicating that ecosystem carbon uptake was co-limited by N and P in alpine meadow.

Acoustic signal dominance in the multimodal communication of a nocturnal mammal.

Multimodal communication in animals is common, and is particularly well studied in signals that include both visual and auditory components. Multimodal signals that combine acoustic and olfactory components are less well known. Multimodal communication plays a crucial role in agonistic interactions in many mammals, but relatively little is known about this type of communication in nocturnal mammals. Here, we used male Great Himalayan leaf-nosed bats Hipposideros armiger to investigate multimodal signal function in acoustic and olfactory aggressive displays. We monitored the physiological responses (heart rate [HR]) when H. armiger was presented with 1 of 3 stimuli: territorial calls, forehead gland odors, and bimodal signals (calls + odors). Results showed that H. armiger rapidly increased their HR when exposed to any of the 3 stimuli. However, the duration of elevated HR and magnitude of change in HR increased significantly more when acoustic stimuli were presented alone compared with the presentation of olfactory stimuli alone. In contrast, the duration of elevated HR and magnitude of change in HR were significantly higher with bimodal stimuli than with olfactory stimuli alone, but no significant differences were found between the HR response to acoustic and bimodal stimuli. Our previous work showed that acoustic and chemical signals provided different types of information; here we describe experiments investigating the responses to those signals. These results suggest that olfactory and acoustic signals are non-redundant signal components, and that the acoustic component is the dominant modality in male H. armiger, at least as it related to HR. This study provides the first evidence that acoustic signals dominate over olfactory signals during agonistic interactions in a nocturnal mammal.

The confounding effect of snow cover on assessing spring phenology from space: A new look at trends on the Tibetan Plateau.

The Tibetan Plateau is the highest and largest plateau in the world, hosting unique alpine grassland and having a much higher snow cover than any other region at the same latitude, thus representing a "climate change hot-spot". Land surface phenology characterizes the timing of vegetation seasonality at the per-pixel level using remote sensing systems. The impact of seasonal snow cover variations on land surface phenology has drawn much attention; however, there is still no consensus on how the remote sensing estimated start of season (SOS) is biased by the presence of preseason snow cover. Here, we analyzed SOS assessments from time series of satellite derived vegetation indices and solar-induced chlorophyll fluorescence (SIF) during 2003-2016 for the Tibetan Plateau. We evaluated satellite-based SOS with field observations and gross primary production (GPP) from eddy covariance for both snow-free and snow covered sites. SOS derived from SIF was highly correlated with field data (R2 = 0.83) and also the normalized difference phenology index (NDPI) performed well for both snow free (R2 = 0.77) and snow covered sites (R2 = 0.73). On the contrary, normalized difference vegetation index (NDVI) correlates only weakly with field data (R2 = 0.35 for snow free and R2 = 0.15 for snow covered sites). We further found that an earlier end of the snow season caused an earlier estimate of SOS for the Tibetan Plateau from NDVI as compared to NDPI. Our research therefore adds new evidence to the ongoing debate supporting the view that the claimed advance in land surface SOS over the Tibetan Plateau is an artifact from snow cover changes. These findings improve our understanding of the impact of snow on land surface phenology in alpine ecosystems, which can further improve remote sensing based land surface phenology assessments in snow-influenced ecosystems.

Integrating satellite and unmanned aircraft system (UAS) imagery to model livestock population dynamics in the Longbao Wetland National Nature Reserve, China.

The collection of field-based animal data is laborious, risky and costly in some areas, such as various nature reserves. Although multiple studies have used satellite imagery, aerial imagery, and field data individually for some animal species surveys, several technical issues still need to be addressed before full standardization of remote sensing methods for modeling animal population dynamics over large areas. This study is the first to model the population dynamics of livestock in the Longbao Wetland National Nature Reserve, China by utilizing yak estimations from Worldview-2 satellite imagery (0.5 m) collected in 2010 and yaks counted in a ground-based survey conducted in 2011 in combination with the animal population structure precisely extracted from UAS imagery captured in 2016. As a consequence, 5501, 5357, and 5510 yaks were estimated to appear in the reserve in 2010, 2011 and 2016, respectively. In total, 1092, 1062 and 1092 sheep were estimated to appear in the reserve in 2010, 2011 and 2016, respectively. The uncertainty of the presented method is also discussed. Primary experiments show that both the satellite imagery and UAS imagery are promising for use in yak censuses, but no sheep were observed in the satellite imagery because of the low resolution. Compared to the ground-based survey conducted in 2011, the UAS image estimate and satellite imagery count deviated in yak quantity by 2.69% and 2.86%, respectively. UASs are a reliable and low-budget alternative to animal surveys. No discernable changes in animal behaviors and animal distributions were observed as the UAS passed at a height of 700 m, and the accuracy of UAS imagery counts were not significantly affected by the short-distance animal movement and image mosaicking errors. The experimental results illustrate the advantages of the combination of satellite and UAS imagery in modeling animal population dynamics.