scholarly journals Soil Mycobiome Is Shaped by Vegetation and Microhabitats: A Regional-Scale Study in Southeastern Brazil

2021 ◽  
Vol 7 (8) ◽  
pp. 587
Author(s):  
Danielle Hamae Yamauchi ◽  
Hans Garcia Garces ◽  
Marcus de Melo Teixeira ◽  
Gabriel Fellipe Barros Rodrigues ◽  
Leila Sabrina Ullmann ◽  
...  

Soil is the principal habitat and reservoir of fungi that act on ecological processes vital for life on Earth. Understanding soil fungal community structures and the patterns of species distribution is crucial, considering climatic change and the increasing anthropic impacts affecting nature. We evaluated the soil fungal diversity in southeastern Brazil, in a transitional region that harbors patches of distinct biomes and ecoregions. The samples originated from eight habitats, namely: semi-deciduous forest, Brazilian savanna, pasture, coffee and sugarcane plantation, abandoned buildings, owls’ and armadillos’ burrows. Forty-four soil samples collected in two periods were evaluated by metagenomic approaches, focusing on the high-throughput DNA sequencing of the ITS2 rDNA region in the Illumina platform. Normalized difference vegetation index (NDVI) was used for vegetation cover analysis. NDVI values showed a linear relationship with both diversity and richness, reinforcing the importance of a healthy vegetation for the establishment of a diverse and complex fungal community. The owls’ burrows presented a peculiar fungal composition, including high rates of Onygenales, commonly associated with keratinous animal wastes, and Trichosporonales, a group of basidiomycetous yeasts. Levels of organic matter and copper influenced all guild communities analyzed, supporting them as important drivers in shaping the fungal communities’ structures.

2018 ◽  
Vol 42 (4) ◽  
pp. 415-430 ◽  
Author(s):  
Biao Zeng ◽  
Fuguang Zhang ◽  
Taibao Yang ◽  
Jiaguo Qi ◽  
Mihretab G Ghebrezgabher

Alpine sparsely vegetated areas (ASVAs) in mountains are sensitive to climate change and rarely studied. In this study, we focused on the response of ASVA distribution to climate change in the eastern Qilian Mountains (EQLM) from the 1990s to the 2010s. The ASVA distribution ranges in the EQLM during the past three decades were obtained from the Thematic Mapper remote sensing digital images by using the threshold of normalized difference vegetation index (NDVI) and artificial visual interpretation. Results indicated that the ASVA shrank gradually in the EQLM and lost its area by approximately 11.4% from the 1990s to the 2010s. The shrunken ASVA with markedly more area than the expanded one was mainly located at altitudes from 3700 m to 4300 m, which were comparatively lower than the average altitude of the ASVA distribution ranges. This condition led to the low ASVA boundaries in the EQLM moving upwards at a significant velocity of 22 m/decade at the regional scale. This vertical zonal process was modulated by topography-induced differences in local hydrothermal conditions. Thus, the ASVA shrank mainly in its lower parts with mild and sunny slopes. Annual maximum NDVI in the transition zone increased significantly and showed a stronger positive correlation with significantly increasing temperature than insignificant precipitation variations during 1990–2015. The ASVA shrinkage and up-shifting of its boundary were attributed to climate warming, which facilitated the upper part of alpine meadow in the EQLM by releasing the low temperature limitation on vegetation growth.


2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.


2020 ◽  
Vol 12 (10) ◽  
pp. 1546 ◽  
Author(s):  
Christopher Potter ◽  
Olivia Alexander

Understanding trends in vegetation phenology and growing season productivity at a regional scale is important for global change studies, particularly as linkages can be made between climate shifts and the vegetation’s potential to sequester or release carbon into the atmosphere. Trends and geographic patterns of change in vegetation growth and phenology from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets were analyzed for the state of Alaska over the period 2000 to 2018. Phenology metrics derived from the MODIS Normalized Difference Vegetation Index (NDVI) time-series at 250 m resolution tracked changes in the total integrated greenness cover (TIN), maximum annual NDVI (MAXN), and start of the season timing (SOST) date over the past two decades. SOST trends showed significantly earlier seasonal vegetation greening (at more than one day per year) across the northeastern Brooks Range Mountains, on the Yukon-Kuskokwim coastal plain, and in the southern coastal areas of Alaska. TIN and MAXN have increased significantly across the western Arctic Coastal Plain and within the perimeters of most large wildfires of the Interior boreal region that burned since the year 2000, whereas TIN and MAXN have decreased notably in watersheds of Bristol Bay and in the Cook Inlet lowlands of southwestern Alaska, in the same regions where earlier-trending SOST was also detected. Mapping results from this MODIS time-series analysis have identified a new database of localized study locations across Alaska where vegetation phenology has recently shifted notably, and where land cover types and ecosystem processes could be changing rapidly.


2013 ◽  
Vol 30 (7) ◽  
pp. 1266-1294 ◽  
Author(s):  
Rommel C. Zulueta ◽  
Walter C. Oechel ◽  
Joseph G. Verfaillie ◽  
Steven J. Hastings ◽  
Beniamino Gioli ◽  
...  

Abstract Natural ecosystems are rarely structurally simple or functionally homogeneous. This is true for the complex coastal region of Magdalena Bay, Baja California Sur, Mexico, where the spatial variability in ecosystem fluxes from the Pacific coastal ocean, eutrophic lagoon, mangroves, and desert were studied. The Sky Arrow 650TCN environmental research aircraft proved to be an effective tool in characterizing land–atmosphere fluxes of energy, CO2, and water vapor across a heterogeneous landscape at the scale of 1 km. The aircraft was capable of discriminating fluxes from all ecosystem types, as well as between nearshore and coastal areas a few kilometers distant. Aircraft-derived average midday CO2 fluxes from the desert showed a slight uptake of −1.32 μmol CO2 m−2 s−1, the coastal ocean also showed an uptake of −3.48 μmol CO2 m−2 s−1, and the lagoon mangroves showed the highest uptake of −8.11 μmol CO2 m−2 s−1. Additional simultaneous measurements of the normalized difference vegetation index (NDVI) allowed simple linear modeling of CO2 flux as a function of NDVI for the mangroves of the Magdalena Bay region. Aircraft approaches can, therefore, be instrumental in determining regional CO2 fluxes and can be pivotal in calculating and verifying ecosystem carbon sequestration regionally when coupled with satellite-derived products and ecosystem models.


2011 ◽  
Vol 3 (3) ◽  
pp. 157
Author(s):  
Daniel Rodrigues Lira ◽  
Maria do Socorro Bezerra de Araújo ◽  
Everardo Valadares De Sá Barretto Sampaio ◽  
Hewerton Alves da Silva

O mapeamento e monitoramento da cobertura vegetal receberam consideráveis impulsos nas últimas décadas, com o advento do sensoriamento remoto, processamento digital de imagens e políticas de combate ao desmatamento, além dos avanços nas pesquisas e gerações de novos sensores orbitais e sua distribuição de forma mais acessível aos usuários, tornam as imagens de satélite um dos produtos do sensoriamento remoto mais utilizado para análises da cobertura vegetal das terras. Os índices de cobertura vegetal deste trabalho foram obtidos usando o NDVI - Normalized Difference Vegetation Index para o Agreste central de Pernambuco indicou 39,7% de vegetação densa, 13,6% de vegetação esparsa, 14,3% de vegetação rala e 10,5% de solo exposto. O NDVI apresentou uma caracterização satisfatória para a classificação do estado da vegetação do ano de 2007 para o Agreste Central pernambucano, porém ocorreu uma confusão com os índices de nuvens, sombras e solos exposto, necessitando de uma adaptação na técnica para um melhor aprimoramento da diferenciação desses elementos, constituindo numa recombinação de bandas após a elaboração e calculo do NDVI.Palavras-chave: Geoprocessamento; sensoriamento remoto; índice de vegetação. Mapping and Quantification of Vegetation Cover from Central Agreste Region of Pernambuco State Using NDVI Technique ABSTRACTIn recent decades, advanced techniques for mapping and monitoring vegetation cover have been developed with the advent of remote sensing. New tools for digital processing, the generation of new sensors and their orbital distribution more accessible have facilitated the acquisition and use of satellite images, making them one of the products of remote sensing more used for analysis of the vegetation cover. The aim of this study was to assess the vegetation cover from Central Agreste region of Pernambuco State, using satellite images TM / LANDSAT-5. The images were processed using the NDVI (Normalized Difference Vegetation Index) technique, generating indexes used for classification of vegetation in dense, sparse and scattered. There was a proportion of 39.7% of dense vegetation, 13.6% of sparse vegetation, 14.3% of scattered vegetation and 10.5% of exposed soil. NDVI technique has been used as a useful tool in the classification of vegetation on a regional scale, however, needs improvement to a more precise differentiation among levels of clouds, shadow, exposed soils and vegetation. Keywords: Geoprocessing, remote sensing, vegetation index


2018 ◽  
Author(s):  
Anne J. Hoek van Dijke ◽  
Kaniska Mallick ◽  
Adriaan J. Teuling ◽  
Martin Schlerf ◽  
Miriam Machwitz ◽  
...  

Abstract. There is a need for a better understanding of the link between vegetation characteristics and tree transpiration to facilitate satellite derived transpiration estimation. Many studies use the normalized difference vegetation index (NDVI), a proxy for tree biophysical characteristics, to estimate evapotranspiration. In this study we investigated the link between sap velocity and 30 m resolution Landsat derived NDVI for twenty days during two contrasting precipitation years in a temperate deciduous forest catchment. Sap velocity was measured in the Attert catchment in Luxembourg in 25 plots of 20 × 20 m covering three geologies with sensors installed in 2–4 trees per plot. The results show that sap velocity and NDVI were significantly positively correlated in April, i.e., NDVI successfully captured the pattern of sap velocity during the phase of green-up. After green-up, a significant negative correlation was found during half of the studied days. During a dry period, sap velocity was uncorrelated to NDVI, but influenced by geology and aspect. In summary, in our study area, the correlation between sap velocity and NDVI was not constant, but varied with phenology and water availability. The same behaviour was found for the Enhanced Vegetation Index (EVI). This suggests that methods using NDVI or EVI to predict small-scale variability in (evapo)transpiration should be carefully applied and that NDVI and EVI cannot be used to scale sap velocity to stand level transpiration in temperate forest ecosystems.


2020 ◽  
Vol 12 (24) ◽  
pp. 4177
Author(s):  
Yonghua Zhu ◽  
Pingping Luo ◽  
Sheng Zhang ◽  
Biao Sun

Understanding the spatiotemporal characteristics of hydrological components and their impacts on vegetation are critical for comprehending hydrological, climatological, and ecological processes under environmental change and solving future water management challenges. Innovative methods need to be developed in semiarid areas to analyze the special hydrological factors in the water resource systems of these areas. Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) were applied with the normalized difference vegetation index (NDVI) data in this paper to analyze spatiotemporal changes of hydrological factors in the Xiliaohe River Basin (XRB). The results showed that precipitation (P), evapotranspiration (ET) and temperature (T) had similar seasonal change patterns at rates of 0.05 cm/yr., 0.01 cm/yr. and −0.05 °C/yr., respectively. Total water storage change (TWSC) was consistent with the change trend of soil moisture change (SMC) and showed a fluctuating trend. Groundwater change (GWC) showed a decreasing trend at a rate of −0.43 cm/yr. P and ET had a greater impact on GLDAS data (R = 0.634, P < 0.05 and R = 0.686, P < 0.01, respectively) than on other factors. GWC was more sensitive to changes in T (R = 0.570, P < 0.05). Furthermore, a lag period of 0 to 1 months was observed for the effects of P and ET on TWSC and GLDAS. NDVI showed an upward trend at a rate of 0.001 yr−1 between 2002 and 2014. A spatial distribution of NDVI was heterogeneous in the study area. ET, GLDAS and GWC in growing season limited vegetation growth and were more important than other factors in XRB. The results may contribute to an understanding of the relationships between the hydrological cycle and climate change and provide scientific support for local environmental management.


2021 ◽  
Vol 87 (9) ◽  
pp. 649-660
Author(s):  
Majid Rahimzadegan ◽  
Arash Davari ◽  
Ali Sayadi

Soil moisture content (SMC), product of Advanced Microwave Scanning Radiometer 2 (AMSR2), is not at an adequate level of accuracy on a regional scale. The aim of this study is to introduce a simple method to estimate SMC while synergistically using AMSR2 and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements with a higher accuracy on a regional scale. Two MODIS products, including daily reflectance (MYD021) and nighttime land surface temperature (LST) products were used. In 2015, 1442 in situ SMC measurements from six stations in Iran were used as ground-truth data. Twenty models were evaluated using combinations of polarization index (PI), index of soil wetness (ISW), normalized difference vegetation index (NDVI), and LST. The model revealed the best results using a quadratic combination of PI and ISW, a linear form of LST, and a constant value. The overall correlation coefficient, root-mean-square error, and mean absolute error were 0.59, 4.62%, and 3.01%, respectively.


2018 ◽  
Vol 10 (11) ◽  
pp. 1818 ◽  
Author(s):  
Zhengjia Liu ◽  
Yansui Liu

Human transformation of landscapes is pervasive and accelerating across the Earth. However, existing studies have not provided a comprehensive picture of how precipitation frequency and intensity respond to vegetation cover change. Therefore, this study took the Loess Plateau as a typical example, and used satellite-based Normalized Difference Vegetation Index (NDVI) data and daily gridded climatic variables to assess the responses of precipitation dynamics to human-induced vegetation cover change. Results showed that the total precipitation amount exhibited little change at the regional scale, showing an upward but statistically insignificant (p > 0.05) trend of 7.6 mm/decade in the period 1982–2015. However, the frequency of precipitation with different intensities showed large variations over most of the Loess Plateau. The number of rainy days (light, moderate, heavy, very heavy and severe precipitation) increased in response to increased vegetation cover, especially in the central-eastern Loess Plateau. Anthropogenic land cover change is largely responsible for precipitation intensity changes. Additionally, this study also observed high spatially explicit heterogeneity in different precipitation intensities in response to vegetation cover change across the Loess Plateau. These findings provide some reference information for our understanding of precipitation frequency and intensity changes in response to regional vegetation cover change in the Loess Plateau.


Sign in / Sign up

Export Citation Format

Share Document