Environmental changes, such as climate warming and higher herbivory pressure, are altering the carbon balance of Arctic ecosystems; yet, how these drivers modify the carbon balance among different habitats remains uncertain. This hampers our ability to predict changes in the carbon sink strength of tundra ecosystems. We investigated how spring goose grubbing and summer warming-two key environmental-change drivers in the Arctic-alter CO2 fluxes in three tundra habitats varying in soil moisture and plant-community composition. In a full-factorial experiment in high-Arctic Svalbard, we simulated grubbing and warming over two years and determined summer net ecosystem exchange (NEE) alongside its components: gross ecosystem productivity (GEP) and ecosystem respiration (ER). After two years, we found net CO2 uptake to be suppressed by both drivers depending on habitat. CO2 uptake was reduced by warming in mesic habitats, by warming and grubbing in moist habitats, and by grubbing in wet habitats. In mesic habitats, warming stimulated ER (+75%) more than GEP (+30%), leading to a 7.5-fold increase in their CO2 source strength. In moist habitats, grubbing decreased GEP and ER by similar to 55%, while warming increased them by similar to 35%, with no changes in summer-long NEE. Nevertheless, grubbing offset peak summer CO2 uptake and warming led to a twofold increase in late summer CO2 source strength. In wet habitats, grubbing reduced GEP (-40%) more than ER (-30%), weakening their CO2 sink strength by 70%. One-year CO2-flux responses were similar to two-year responses, and the effect of simulated grubbing was consistent with that of natural grubbing. CO2-flux rates were positively related to aboveground net primary productivity and temperature. Net ecosystem CO2 uptake started occurring above similar to 70% soil moisture content, primarily due to a decline in ER. Herein, we reveal that key environmental-change drivers-goose grubbing by decreasing GEP more than ER and warming by enhancing ER more than GEP-consistently suppress net tundra CO2 uptake, although their relative strength differs among habitats. By identifying how and where grubbing and higher temperatures alter CO2 fluxes across the heterogeneous Arctic landscape, our results have implications for predicting the tundra carbon balance under increasing numbers of geese in a warmer Arctic.

In potato breeding, maturity class (MC) is a crucial selection criterion because this is a critical aspect of commercial potato production. Currently, the classification of potato genotypes into MCs is done visually, which is time- and labor-consuming. The objective of this research was to use vegetation indices (VIs) derived from unmanned aerial vehicle (UAV) imagery to remotely assign MCs to potato plants grown in trials, representing three different early stages within a multi-year breeding program. The relationships between VIs (GOSAVI - Green Optimized Soil Adjusted Vegetation Index, MCARI2 - Modified Chlorophyll Absorption Index-Improved, NDRE - Normalized Difference Red Edge, NDVI - Normalized Difference Vegetation Index, and OSAVI - Optimized Soil Adjusted Vegetation Index and WDVI - Weighted Difference Vegetation Index) and visual potato canopy status were determined. Further, this study aimed to identify factors that could improve the accuracy (decrease Mean Absolute Error - MAE) of potato MC estimation remotely. Results show that VIs derived from UAV imagery can be effectively used to remotely assign MCs to potato breeding lines, with higher accuracy for the potato B-clones (20 plants per plot) than the A-clones (6 plants per plot). Among the tested VIs, the NDRE allowed for potato MC evaluation with the lowest MAE. Applying NDRE for remote MC estimation using a validation dataset of potato B-clones (100 plants per plot), resulted in an MC estimate with a 0.81 MAE. However, the accuracy of potato MC estimation using UAV image-based methods should be improved by reducing the potato canopy's variability (increasing uniformity) within the plot. This could be achieved by minimizing 1) potato vines bending over the neighboring row, causing vine overlap between plots, and 2) plants damaged by tractor wheels during field operations. En el mejoramiento de la papa, la clase de madurez (CM) es un criterio de selecci & oacute;n crucial porque este es un aspecto cr & iacute;tico de la producci & oacute;n comercial de papa. Actualmente, la clasificaci & oacute;n de los genotipos de papa en MC se realiza visualmente, lo que requiere mucho tiempo y trabajo. El objetivo de esta investigaci & oacute;n fue utilizar & iacute;ndices de vegetaci & oacute;n (VIs) derivados de im & aacute;genes de veh & iacute;culos a & eacute;reos no tripulados (UAV) para asignar de forma remota MCs a plantas de papa cultivadas en ensayos, representando tres etapas tempranas diferentes dentro de un programa de mejoramiento de varios a & ntilde;os. Se determinaron las relaciones entre los VIs (GOSAVI - & Iacute;ndice de Vegetaci & oacute;n Ajustado al Suelo Optimizado Verde, MCARI2 - & Iacute;ndice de Absorci & oacute;n de Clorofila Modificado-Mejorado, NDRE - Borde Rojo de Diferencia Normalizada, NDVI - & Iacute;ndice de Vegetaci & oacute;n de Diferencia Normalizada, y OSAVI - & Iacute;ndice de Vegetaci & oacute;n Ajustado al Suelo Optimizado y WDVI - & Iacute;ndice de Vegetaci & oacute;n de Diferencia Ponderada) y la visualizaci & oacute;n del dosel de la papa. Adem & aacute;s, este estudio tuvo como objetivo identificar factores que podr & iacute;an mejorar la precisi & oacute;n (disminuir el Error Absoluto Medio - MAE) de la estimaci & oacute;n de MC de papa de forma remota. Los resultados muestran que los VI derivados de las im & aacute;genes de UAV se pueden utilizar de manera efectiva para asignar MC de forma remota a las l & iacute;neas de mejoramiento de papa, con mayor precisi & oacute;n para los clones B de papa (20 plantas por parcela) que para los clones A (6 plantas por parcela). Entre los VI probados, el NDRE permiti & oacute; la evaluaci & oacute;n de la MC de papa con el MAE m & aacute;s bajo. La aplicaci & oacute;n de NDRE para la estimaci & oacute;n remota de MC utilizando un conjunto de datos de validaci & oacute;n de clones B de papa (100 plantas por parcela), result & oacute; en una estimaci & oacute;n de MC con un MAE de 0.81. Sin embargo, la precisi & oacute;n de la estimaci & oacute;n de la MC de la papa utilizando m & eacute;todos basados en im & aacute;genes UAV debe mejorarse reduciendo la variabilidad del dosel de la papa (aumentando la uniformidad) dentro de la parcela. Esto podr & iacute;a lograrse minimizando 1) los tallos de papa que se doblan sobre el surco vecino, lo que causa la superposici & oacute;n de follaje entre las parcelas, y 2) las plantas da & ntilde;adas por las ruedas de los tractores durante las operaciones de campo.

White lupine (Lupinus albus L.) is a well-known green manure crop in Hungary, but the production of seeds can be badly impacted by weeds. The sweet white lupine 'Nelly' was grown on acidic sandy soil, and experimental plots were treated with different herbicides. Flumioxazin (0.06 kg ha(-1)), pendimethalin (5 L ha(-1)), dimethenamid-P (1.4 L ha(-1)), pethoxamid (2 L ha(-1)), clomazone (0.2 L ha(-1)), metobromuron (3 L ha(-1)), and metribuzin (0.55 L ha(-1)) were applied pre-emergence (1-2 days after sowing). Imazamox was also tested and applied post-emergence (1 L ha(-1)) when some basal leaves were clearly distinct (BBCH 2.3). In this paper, the weed control efficiency and the phytotoxicity of herbicides applied to lupine are examined. Vegetation index datasets were collected 12 times using a manual device and 2 times using an unmanned aerial vehicle (UAV). The phytotoxicity caused by herbicides was visually assessed on several occasions throughout the breeding season. The frequency of weed occurrence per treatment was assessed. The harvested seed yields, in kg ha(-1), were analyzed after the seeds were cleaned. The herbicides metribuzin and imazamox caused extensive damage to white lupine. While pendimethalin, dimethenamid-P, pethoxamid, and clomazone were outstanding in several measured indicators, the final ranking which summarizes all the variables showed that only the pethoxamid and clomazone treatments performed better than the control. Metribuzin and imazamox were highly phytotoxic to white lupine. In the future, it would be appropriate to integrate more post-emergence active substances into trials, and the pre-emergence herbicides involved in this study should be further tested.

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought-vegetation interaction in this area under the influence of climate-permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter-Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the source area and provide reference for ecological protection in permafrost regions.

The 2011 off the Pacific coast of Tohoku Earthquake occurred, and coastal forests were severely damaged by a huge tsunami. Since the disaster, coastal forest restoration projects have been underway by the Forestry Agency and local governments. Detailed time-series monitoring of the regeneration process of coastal forests is important in order to proceed with regeneration appropriately. The Normalized Difference Vegetation Index (NDVI), which uses near-infrared and visible red images obtained from optical satellite observations, has been widely used to survey trees and vegetation. However, it has been reported that NDVI tends to be saturated depending on the observation period and vegetation type. In addition, there is a tendency for index values to be overestimated on the soil surface. In particular, in the case of coastal forest regeneration, the influence of the soil surface is even greater because the complex mixture of soil surface and afforestation is assessed from observation images. To date, many improvement vegetation indices have been proposed to reduce soil surface effects and more appropriately evaluate vegetation activity. However, the applicability of improvement indexes using higher-resolution satellite images for evaluating the regeneration of tsunami-affected coastal forests has not yet been sufficiently investigated.

For the period 2001-2020, the interannual variability of the normalized difference vegetation index (NDVI) is investigated in connection to Indian summer monsoon rainfall (ISMR). According to Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data, the ISMR and the vegetative activity of the Indo-Gangetic plain (IGP) in the month of January show a significant negative association. We hypothesized that the January vegetation state affects the ISMR via a delayed hydrological response, in which the wet soil moisture anomaly formed throughout the winter to accommodate the water needs of intensive farming influences the ISMR. The soil moisture anomalies developed in the winter, particularly in the root zone, persisted throughout the summer. Evaporative cooling triggered by increasing soil moisture lowers the summer surface temperature across the IGP. The weakening of monsoon circulation as a result of the reduced intensity of land-sea temperature contrast led in rainfall suppression. Further investigation shows that moisture transport has increased significantly over the past two decades as a result of increasing westerly over the Arabian Sea, promoting rainfall over India. Agriculture activities, on the other hand, have resulted in greater vegetation in India's northwest and IGP during the last two decades, which has a detrimental impact on rainfall processes. Rainfall appears to have been trendless during the last two decades as a result of these competing influences. With a lead time of 5 months, this association between January's vegetation and ISMR could be one of the potential predictors of seasonal rainfall variability.

Understanding vegetation changes and their driving forces in global alpine areas is critical in the context of climate change. We aimed to reveal the changing trend in global alpine vegetation from 1981 to 2015 using the least squares regression method and Mann-Kendall (MK) test. The area-of-influence dominated by anthropogenic activity and natural factors was determined in an area with significant vegetation change by residual analysis; the primary driving force of vegetation change in the area-of-influence dominated by natural factors was identified using the partial correlation method. The results showed that (1) the vegetation in the global alpine area exhibited a browning trend from 1981 to 2015 on the annual scale; however, a greening trend was observed from May to July on the month scale. (2) The influence of natural factors was greater than that of anthropogenic activities, and the positive impact of natural factors was greater than the negative impact. (3) Among the factors that were often considered as the main natural factors, the contribution of albedo to significant changes in vegetation were greater than that of temperature, precipitation, soil moisture, and sunshine duration. This study provides a scientific basis for the protection of vegetation and sustainable development in alpine regions.

Little is known about the mechanism of climate-vegetation coverage coupled changes in the Tibetan Plateau (TP) region, which is the most climatically sensitive and ecologically fragile region with the highest terrain in the world. This study, using multisource datasets (including satellite data and meteorological observations and reanalysis data) revealed the mutual feedback mechanisms between changes in climate (temperature and precipitation) and vegetation coverage in recent decades in the Hengduan Mountains Area (HMA) of the southeastern TP and their influences on climate in the downstream region, the Sichuan Basin (SCB). There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA, which is most significant during winter, and then during spring, but insignificant during summer and autumn. Rising temperature significantly enhances local vegetation coverage, and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the atmosphere. The atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air pressure. The high pressure anomaly disperses downstream via the westerly flow, expands across the SCB, and eventually increases the SCB temperature. This effect lasts from winter to the following spring, which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in spring. These results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios, as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.

With a typical alpine grassland ecosystem, the Tibetan Plateau (TP) is a highly representative region to observe the effects of climate change on ecosystems. Continued global warming has increased the drought risk of TP, yet the response of vegetation to drought remains unclear. To understand the spatial heterogeneity of the vegetation response to drought and identify the key control factors of vegetation response to drought in different elevation intervals on TP, we introduced three vegetation indexes (EVI, LAI, and GPP) and multi-scale drought indexes, including the Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI), to determine the spatial response of vegetation growth to drought from 2000 to 2015. Land surface temperature (LST), land cover, snow cover, population density, and soil texture were selected as potential control factors. The mean values of the maximum correlation coefficients for the six combinations indicated that 14.3%/12.0% (SPI/SPEI) of the vegetation growth on TP was significantly affected by water conditions (p < 0.05). The extent of vegetation growth responses to drought were mainly influenced by LST with the highest contribution rate of 65.8% at 3000-4500 m intervals. The response time is mainly dependent on the proportion of grassland, with the highest contribution rate of 81.7% at 4500-6000 m intervals. The results provide reasonable evidence for understanding the spatial heterogeneity of the elevation dependence of the alpine ecosystem response to drought.

The Mongolian Plateau is one of the regions most sensitive to climate change, the more obvious increase of temperature in 21st century here has been considered as one of the important causes of drought and desertification. It is very important to understand the multi-year variation and occurrence characteristics of drought in the Mongolian Plateau to explore the ecological environment and the response mechanism of surface materials to climate change. This study examines the spatio-temporal variations in drought and its frequency of occurrence in the Mongolian Plateau based on the Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) (1982-1999) and the Moderate-resolution Imaging Spectroradiometer (MODIS) (2000-2018) datasets; the Temperature Vegetation Dryness Index (TVDI) was used as a drought evaluation index. The results indicate that drought was widespread across the Mongolian Plateau between 1982 and 2018, and aridification incremented in the 21st century. Between 1982 and 2018, an area of 164.38 x 10(4) km(2)/yr suffered from drought, accounting for approximately 55.28% of the total study area. An area of approximately 150.06 x 10(4) km(2) (51.43%) was subject to more than 160 droughts during 259 months of the growing seasons between 1982 and 2018. We observed variable frequencies of drought occurrence depending on land cover/land use types. Drought predominantly occurred in bare land and grassland, both of which accounting for approximately 79.47% of the total study area. These terrains were characterized by low vegetation and scarce precipitation, which led to frequent and extreme drought events. We also noted significant differences between the areal distribution of drought, drought frequency, and degree of drought depending on the seasons. In spring, droughts were widespread, occurred with a high frequency, and were severe; in autumn, they were localized, frequent, and severe; whereas, in summer, droughts were the most widespread and frequent, but less severe. The increase in temperature, decrease in precipitation, continuous depletion of snow cover, and intensification of human activities have resulted in a water deficit. More severe droughts and aridification have affected the distribution and functioning of terrestrial ecosystems, causing changes in the composition and distribution of plants, animals, microorganisms, conversion between carbon sinks and carbon sources, and biodiversity. We conclude that regional drought events have to be accurately monitored, whereas their occurrence mechanisms need further exploration, taking into account nature, climate, society and other influencing factors.