Potential of Unmanned Aerial Vehicle Red-Green-Blue Images for Detecting Needle Pests: A Case Study with Erannis jacobsoni Djak (Lepidoptera, Geometridae).

Erannis jacobsoni Djak (Lepidoptera, Geometridae) is a leaf-feeding pest unique to Mongolia. Outbreaks of this pest can cause larch needles to shed slowly from the top until they die, leading to a serious imbalance in the forest ecosystem. In this work, to address the need for the low-cost, fast, and effective identification of this pest, we used field survey indicators and UAV images of larch forests in Binder, Khentii, Mongolia, a typical site of Erannis jacobsoni Djak pest outbreaks, as the base data, calculated relevant multispectral and red-green-blue (RGB) features, used a successive projections algorithm (SPA) to extract features that are sensitive to the level of pest damage, and constructed a recognition model of Erannis jacobsoni Djak pest damage by combining patterns in the RGB vegetation indices and texture features (RGBVI&TF) with the help of random forest (RF) and convolutional neural network (CNN) algorithms. The results were compared and evaluated with multispectral vegetation indices (MSVI) to explore the potential of UAV RGB images in identifying needle pests. The results show that the sensitive features extracted based on SPA can adequately capture the changes in the forest appearance parameters such as the leaf loss rate and the colour of the larch canopy under pest damage conditions and can be used as effective input variables for the model. The RGBVI&TF-RF440 and RGBVI&TF-CNN740 models have the best performance, with their overall accuracy reaching more than 85%, which is a significant improvement compared with that of the RGBVI model, and their accuracy is similar to that of the MSVI model. This low-cost and high-efficiency method can excel in the identification of Erannis jacobsoni Djak-infested regions in small areas and can provide an important experimental theoretical basis for subsequent large-scale forest pest monitoring with a high spatiotemporal resolution.

Lagged feedback of peak season photosynthetic activities on local surface temperature in Inner Mongolia, China.

Increased vegetation peak growth and phenological shifts toward spring have been observed in response to climate warming in the temperate regions. Such changes have the potential to modify warming by perturbing land‒atmosphere energy exchanges; however, the signs and magnitudes of biophysical feedback on surface temperature in different biomes are largely unknown. Here, we synthesized information from vegetation growth proxies, land surface temperature (LST), and surface energy balance factors (surface evapotranspiration (ET), albedo, and broadband emissivity (BBE)) to investigate the variations in timing (PPT) and productivity (PPmax) of seasonal peak photosynthesis and their time-lagged biophysical feedbacks to the post-season LST in Inner Mongolia (IM) during 2001-2020. We found that increased PPmax, rather than advanced PPT, exhibited a significant impact on LST, with divergent signs and magnitudes across diurnal periods and among different biomes. In the grassland biome, increased PPmax cooled both LST during daytime (LSTday) and nighttime (LSTnight) throughout the post-season period, with a more pronounced response during daytime and diminishing gradually from July to September. This cooling effect on LST was primarily attributed to enhanced ET, as evidenced by the greater effect of ET cooling than that of albedo warming and BBE cooling based on a structural equation model (SEM). In the forest biome, increased PPmax led to a symmetrical warming effect on LSTday and LSTnight, and none of the surface energy balance factors were identified as significant intermediate explanatory factors for the observed warming effect. Moreover, the responses of average LST (LSTmean) and diurnal temperature range of LST (LSTDTR) to variations in PPmax were consistent with those of LSTday at two biomes. The observations above elucidate the divergent feedback mechanisms of vegetation peak growth on LST among different biomes and diurnal cycles, which could facilitate the improvement of the realistic parameterization of surface processes in global climate models.

Spatiotemporal variation of autumn phenology responses to preseason drought and temperature in alpine and temperate grasslands in China.

We investigate the spatiotemporal patterns and environmental controls of the end of the vegetation growing season (EOS) in autumn across the alpine and temperate grasslands of China from 2001 through 2020, focusing on whether the EOS is likely a "dryness effect" due to drought or a "coolness effect" caused by cold temperature in autumn. The results show that the EOS date is earlier (∼6 days earlier on average) in alpine grasslands than in temperate grasslands. During 2001-2020, a slight non-significant delay of 1.0 day/decade is observed for the regional averaged EOS, which is mostly induced by the delayed EOS in 64.4 % of the study region. Preseason temperature (1-2 months before the EOS) exerts a positive control on the EOS in most of the alpine grasslands and some regions of the eastern part of the temperate grasslands, while drought with a mean length of 3.2 months before the EOS exerts positive effects on the EOS in the central, southwestern, and western parts of the temperate grasslands and in the northeastern part of the alpine grasslands. The positive effects of temperature and drought are very likely phenomena reflecting that the EOS is the "coolness effect" associated with lower temperatures in autumn and the "dryness effect" due to drought, especially meteorological drought without consideration of soil moisture, in late summer and/or early autumn, respectively. Our findings are supported by an analysis of the spatial patterns of the cold degree days (CDD) and EOS sensitivity to the CDD. However, the negative effects of drought are also found in eastern temperate grasslands, likely caused by decreased temperature accompanied by increased moisture. The results presented here highlight the importance of incorporating the impacts of droughts on EOS variability, as well as their interactive effects with temperature, into current vegetation autumn phenology models for grasslands.

Change of Rice Paddy and Its Impact on Human Well-Being from the Perspective of Land Surface Temperature in the Northeastern Sanjiang Plain of China.

Large-scale and high-speed paddy land expansion has appeared in Northeast China since the 21st century, causing the change in land surface temperature. The lack of continuous investigation limits the exploration of discoveries in this region. To address this limitation, a collaborative approach that combined human-computer interaction technology, gravity center model and spatial analysis was established. It provided some new findings in spatiotemporal evolution, migration trajectory and surface cooling effect of the paddy field in Northeastern Sanjiang Plain, a center of paddy field planting in China. The results show that: (1) A sustained paddy expansion was monitored, with a total area ranging from 2564.58 km2 to 11430.94 km2, along with a rate of growth of 345.72% from 2000 to 2020. Correspondingly, its reclamation rate changed to 47.53% from 10.66%, showing the improved planting level of the paddy field. (2) Gravity center of paddy field continued to be revealed northward with a 5-year interval from 2000 to 2020. Migration distance of the straight line reached 23.94 km2, with the direction offset of 27.20° from east to north. (3) Throughout the growing season of crops, the land surface temperature of paddy field was 27.73°, 29.38°, 27.01°, 25.62° and 22.97° from May to October; and the cooling temperature effect of paddy field was investigated, with the reduced values of 0.61°, 0.79° and 1.10° in the low-, medium- and high-paddy field density regions from 2000 to 2020, respectively. Overall, these new findings in the cold temperate zone, high latitude region of the Northern Hemisphere, provided the reference for the investigation of paddy field monitoring and its environmental effects in China and other regions.

Spatial and temporal variability in extreme temperature and precipitation events in Inner Mongolia (China) during 1960-2017.

Due to global warming, extreme climate events have become an important issue, and different geographical regions have different sensitivities to climate change. Therefore, temporal and spatial variations in extreme temperature and precipitation events in Inner Mongolia were analyzed based on the daily maximum temperature, minimum temperature, and precipitation data during the period of 1960-2017. The results showed that warm extreme indices, such as SU25, TX90p, TN90p, and WSDI, significantly increased, whereas the cold extreme indices, such as FD0, TX10p, TN10p, and CSDI, significantly decreased; all indices have obvious abrupt changes based on the Mann-Kendall test; nighttime warming was higher than daytime warming. Extreme precipitation indices slightly decreased overall. All of the extreme temperature and precipitation indices had long-range correlations based on detrended fluctuation analysis (a > 0.5), thereby indicating that the extreme climate indices will maintain their current trend directions in the future. ENSO, AO, and IOD had a strong positive influence on warm extremes and a strong negative influence on cold extremes in Inner Mongolia. NCEP/NCAR and ERA-20CM reanalysis showed that strengthening anticyclone circulation, increasing geopotential height, decreasing daytime cloudiness and increasing nightime cloudiness contributed to changes in climate extremes in Inner Mongolia.

Himawari-8 Satellite Based Dynamic Monitoring of Grassland Fire in China-Mongolia Border Regions.

In this study, we used bands 7, 4, and 3 of the Advance Himawari Imager (AHI) data, combined with a Threshold Algorithm and a visual interpretation method to monitor the entire process of grassland fires that occurred on the China-Mongolia border regions, between 05:40 (UTC) on April 19th to 13:50 (UTC) on April 21st 2016. The results of the AHI data monitoring are evaluated by the fire point product data, the wind field data, and the environmental information data of the area in which the fire took place. The monitoring result shows that, the grassland fire burned for two days and eight hours with a total burned area of about 2708.29 km². It mainly spread from the northwest to the southeast, with a maximum burning speed of 20.9 m/s, a minimum speed of 2.52 m/s, and an average speed of about 12.07 m/s. Thus, using AHI data can not only quickly and accurately track the dynamic development of a grassland fire, but also estimate the spread speed and direction. The evaluation of fire monitoring results reveals that AHI data with high precision and timeliness can be highly consistent with the actual situation.

Spatiotemporal drought variability on the Mongolian Plateau from 1980-2014 based on the SPEI-PM, intensity analysis and Hurst exponent.

Knowledge about variations of drought can provide a scientific basis for water resource planning and drought mitigation. In this study, the variations and patterns of drought identified by the Standardized Precipitation Evapotranspiration Index (SPEI) were investigated on the Mongolian Plateau for the period 1980-2014, based on intensity analysis, linear regression, the Mann-Kendall test, wavelet analysis, and Hurst exponent. The results show that: 1) the annual SPEI decreased at a rate of -0.0133/yr over the past 35years, and a major abrupt change occurred in 1999; 2) drought on the Mongolian Plateau intensified from 1980 to 2014, and the drought in Mongolia has been more serious than in Inner Mongolia since the beginning of the 21st century; 3) the rate of drought/wet changes in 1980s-1990s and 1990s-2000s were faster than in 2000s-2010s. In 1980s-1990s, the different drought levels were transformed into various wet levels. In 1990s-2000s, the wet levels were transformed into drought, and in 2000s-2010s, the losses of drought levels were larger than the gains in wet levels; 4) the Hurst exponent is a reliable way to predict drought tendency, with a predictive accuracy as high as 91.7%; 5) the mean H value of the SPEI time series during 1980-2014 was 0.533, indicating that the future drought trend is generally consistent with the current state. In the future, the proportion of area with increasingly severe drought (72.2%) will be larger than that with increasingly wetter conditions (27.8%) on the Mongolian Plateau.

[Outcomes and correlated factors in patients with impaired fasting glucose: a ten-year follow-up analysis].

OBJECTIVE: To investigate the outcomes and relative risk factors in subjects with impaired fasting glucose in Inner Mongolia, China. METHOD: A total number of 32 villages in Kezuohou Banner and Naiman areas in Inner Mongolia were selected as the baseline surveys study fields from 2002 to 2003. Patients with IFG (5.6 mmol/L≤FPG<7.0 mmol/L) but without history of diabetes were selected as the study subjects. A follow-up study was conducted in 2013. Multinomial logistic regression analysis was used to evaluate the correlated factors. RESULTS: There were 384 patients with IFG recruited in the study. Out of them, 150 (39.1%) progressed to normoglycaemia, 174 (45.3%) remained as IFG, and 60 (15.6%) developed into type 2 diabetes mellitus. Through adjustment multivariately, patients that returning to the status of normoglycaemia were significantly associated under the function of TG (OR = 0.692, 95%CI:0.502-0.952, P < 0.05)and those developed to diabetes were significantly associated with factors as age(OR = 1.052, 95%CI:1.014-1.090, P < 0.05) or obesity (OR = 2.924, 95% CI:1.353-6.320, P < 0.05). CONCLUSION: 15.6% of the IFG patients developed diabetes mellitus among the Inner Mongolian population. Elevated TG was an inhibition factor for patients returning to normoglycaemia while both age and abdominal obesity were risk factors for the development of diabetes in the Inner Mongolian population.