Developing drought stress index for monitoring Pinus densiflora diebacks in Korea

Background: The phenomenon of tree dieback in forest ecosystems around the world, which is known to be associated with high temperatures that occur simultaneously with drought, has received much attention. Korea is experiencing a rapid rise in temperature relative to other regions. Particularly in the growth of evergreen conifers, temperature increases in winter and spring can have great influence. In recent years, there have been reports of group dieback of Pinus densiflora trees in Korea, and many studies are being conducted to identify the causes. However, research on techniques to diagnose and monitor drought stress in forest ecosystems on local and regional scales has been lacking. Results: In this study, we developed and evaluated an index to identify drought and high-temperature vulnerability in Pinus densiflora forests. We found the Drought Stress Index (DSI) that we developed to be effective in generally assessing the drought-reactive physiology of trees. During 2001–2016, in Korea, we refined the index and produced DSI data from a 1 × 1-km unit grid spanning the entire country. We found that the DSI data correlated with the event data of Pinus densiflora mass dieback compiled in this study. The average DSI value at times of occurrence of Pinus densiflora group dieback was 0.6, which was notably higher than during times of nonoccurrence. Conclusions: Our combination of the Standard Precipitation Index and growing degree days evolved and short- and long-term effects into a new index by which we found meaningful results using dieback event data. Topographical and biological factors and climate data should be considered to improve the DSI. This study serves as the first step in developing an even more robust index to monitor the vulnerability of forest ecosystems in Korea

Local and regional steppe vegetation palatability at grazing hotspot areas in Mongolia

Background: Climate and livestock grazing are key agents in determining current Mongolian steppe vegetation communities. Together with plant coverage or biomass, palatability of steppe community is regarded as a useful indicator of grassland degradation, in particular, at grazing hotspots in arid and semi-arid grasslands. This study analyzed relationships between livestock grazing pressure and steppe vegetation palatability at three summer pastures with different aridity (dry, xeric, and mesic) and livestock numbers (1,100, 1,800, and 4,100 sheep units, respectively). At each site, it was surveyed coverage, biomass, and species composition of different palatability groups (i.e., palatable [P], impalatable [IP], and trampling-tolerant [TT]) along a 1-km transect from grazing hotspots (i.e., well) in every July from 2015 to 2018. Results: In results, total vegetation coverage increased with wetness, 7 times greater at mesic site than dry one in averages (33.1% vs. 4.5%); biomass was 3 times higher (47.1 g m-2 vs. 15.7 g m-2). Though P was the dominant palatability group, the importance of IP in total coverage increased with aridity from mesic (0.6%) to dry (40.2%) sites. Whereas, TT increased with livestock numbers across sites. Locally, IP was observed more frequently near the wells and its spatial range of occurrence becomes farther along the transects with aridity across sites from mesic (< 100 m) to dry (< 700 m from the well). Conclusions: Our results showed that the importance of IP and its spatial distribution are different at both local and regional scales, indicating that the palatability parameters are sensitive to discern balance between selective-grazing demand and climate-driven foraging supply in Mongolian rangelands

Retrievals of All-Weather Daily Air Temperature Using MODIS and AMSR-E Data

Satellite optical-infrared remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective air temperature (Ta) retrieval at a spatial resolution of 5 km. However, frequent cloud cover can result in substantial signal loss and remote sensing retrieval error in MODIS Ta. We presented a simple pixel-wise empirical regression method combining synergistic information from MODIS Ta and 37 GHz frequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for estimating surface level Ta under both clear and cloudy sky conditions in the United States for 2006. The instantaneous Ta retrievals showed favorable agreement with in situ air temperature records from 40 AmeriFlux tower sites; mean R2 correspondence was 86.5 and 82.7 percent, while root mean square errors (RMSE) for the Ta retrievals were 4.58 K and 4.99 K for clear and cloudy sky conditions, respectively. Daily mean Ta was estimated using the instantaneous Ta retrievals from day/night overpasses, and showed favorable agreement with local tower measurements (R2 = 0.88; RMSE = 3.48 K). The results of this study indicate that the combination of MODIS and AMSR-E sensor data can produce Ta retrievals with reasonable accuracy and relatively fine spatial resolution (~5 km) for clear and cloudy sky conditions

Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System

We applied an approach for daily estimation and monitoring of evapotranspiration (ET) over the Northeast Asia monsoon region using satellite remote sensing observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Frequent cloud cover results in a substantial loss of remote sensing information, limiting the capability of continuous ET monitoring for the monsoon region. Accordingly, we applied and evaluated a stand-alone MODIS ET algorithm for representative regional ecosystem types and an alternative algorithm to facilitate continuous regional ET estimates using surface meteorological inputs from the Korea Land Data Assimilation System (KLDAS) in addition to MODIS land products. The resulting ET calculations showed generally favorable agreement (root-mean-square error  \u3c 1.3 mm d−1) with respect to in situ measurements from eight regional flux tower sites. The estimated mean annual ET for 3 years (2006 to 2008) was approximately 362.0 ± 161.5 mm yr−1 over the Northeast Asia domain. In general, the MODIS and KLDAS-based ET (MODIS-KLDAS ET) results showed favorable performance when compared to tower observations, though the results were overestimated for a forest site by approximately 39.5% and underestimated for a cropland site in South Korea by 0.8%. The MODIS-KLDAS ET data were generally underestimated relative to the MODIS (MOD16) operational global terrestrial ET product for various biome types, excluding cropland; however, MODIS-KLDAS ET showed better agreement than MOD16 ET for forest and cropland sites in South Korea. Our results indicate that MODIS ET estimates are feasible but are limited by satellite optical-infrared remote sensing constraints over cloudy regions, whereas alternative ET estimates using continuous meteorological inputs from operational regional climate systems (e.g., KLDAS) provide accurate ET results and continuous monitoring capability under all-sky conditions

Satellite-based assessments on regional summer and winter conditions triggering massive livestock loss (Dzud) in Mongolia

Includes bibliographical references.Presented at the Building resilience of Mongolian rangelands: a trans-disciplinary research conference held on June 9-10, 2015 in Ulaanbaatar, Mongolia.Dzud is a term referring either to conditions when melting snow refreezes to form an icy layer covering the grass, or to unusually heavy snow falls in Eurasian arid and semi-arid regions. Under dzud condition, animals cannot obtain food under snow or ice layer, which sometimes results in a dzud disaster, i.e. massive livestock kills. It has been recognized that the dzud disaster is directly induced by the harsh winter conditions but often influenced by drought in the previous summer. In this study, a data-intensive reanalysis on regional determinants of dzud disaster was conducted for more than 300 soums (an administrative unit equivalent with county in US) in Mongolia. Various climatic, hydrological, and vegetation variables were developed from satellite remote sensing (RS) data, which includes daily mean air temperature, dew-point temperature, and evapotranspiration, monthly precipitation, and 16-day NDVI from 2003 to 2010. Annual livestock census data were collected for every soum in Mongolia. Each variable was standardized to z-score and utilized for stepwise multiple regression analysis to identify factors statistically significant for explaining soum-level livestock mortality. The regression models were successfully constructed for two-third of total soums. Considerable spatial variability in the determinants of livestock mortality were found across soums in Mongolia. As the primary determinants, summer NDVI and dryness equally explained 22% of the soum mortality, while 33% and 16% of the mortality were explained with winter temperature and precipitation, respectively. Spatial patterns were also identified with winter precipitation and temperature being primary determinants in mountain regions and northern cool and semi-arid regions, while summer NDVI and dryness were important in southern hot and arid regions. Our results indicate combined efforts of monitoring RS-based summer NDVI and dryness and forecasting winter temperature and precipitation can provide useful tools for dzud disaster early warning

Distance-to-well effects on plant community based on palatability and grazing tolerance in the desert-steppe of Mongolia

Includes bibliographical references.Presented at the Building resilience of Mongolian rangelands: a trans-disciplinary research conference held on June 9-10, 2015 in Ulaanbaatar, Mongolia.Wells in grasslands are usually accompanied with increased traffic by humans and livestock. The purpose of this study was to detect whether plant community structure differs in spatial arrangement with different grazing gradients in the desert steppe of Mongolia. We found poor correlation between total coverage and distance-to-well in big-shrub and shrub-limited sites but strong correlation in the small-shrub site. Dominance of palatable plants along the transect appeared in the big-shrub site but that of palatable, grazing avoider and grazing tolerant plants appeared in other two sites. The results show that these communities might respond differently to grazing pressure. Livestock trampling was limited to near the well and then grazing might be effective far from the well, because all sites showed dominance of palatable herbaceous plants. Sub-dominance of Eurotia ceratoides appeared nearest to the well and followed Caragana spp. sub-dominance. Ajania spp. sub-dominance appeared more away than E. ceratoides and Caragana spp. Dominance of palatable herbaceous plants appeared near the well, compared with that of shrubs. In all sites, palatable herbaceous plant community was replaced by grazing tolerant plant community near the well and shrubs disappeared. This indicates that succession after grazing might be faster in herbaceous plant community than shrub one

Lake area (km²) timeseries from 2000 to 2011.

<p>Filled squares and open circles indicate lake areas from Landsat TM/ETM+ and MODIS09GQ, respectively. Upper and lower keymaps show lake water pixels from Landsat and MODIS, respectively. Numbers at the top of each figure are the lake ID numbers shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151395#pone.0151395.g001" target="_blank">Fig 1</a>.</p

Seasonal (June-to-September) and inter-annual variations of total lake surface areas (km²) detected based on MODIS minimum composite NDVI from 2000 to 2011.

<p>(a) monthly lake surface area, (b) annual maximum (closed circle), minimum (open circle), and mean (triangle) lake areas with annual range (vertical bar) of seasonal lake area change. Lake areas are shown only for June to September. Closed circle in (a) indicate the lake area in June of each year.</p

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

<div><p>A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km²in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km². The lake area decreased by -9.3% at an annual rate of -53.7 km² yr^-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.</p></div

A sample MODIS 250m NDVI overlaid with a GIS lake data layer (red polygons) and Landsat images.

<p>Blue polygons are lakes with areas greater than 6.25 km² in Mongolia. Light blue polygons on Landsat images are the 28 evaluation lakes. Data sources are USGS LPDAAC for MODIS NDVI; USGS GLOVIS for Landsat images; Digital Chart of the World for lake polygons, respectively.</p