Phenological metrics of the grassland vegetation of Rio Grande do Sul, Brazil

Abstract

Considering that plant phenology studies allow establishing relationships between phenological patterns of vegetation and changes caused by climate variability, the aim of this study was to obtain phenological metrics for the predominant grassland typologies in Rio Grande do Sul State, Brazil (latitudes 27º 05’ and 33º 45’ S and longitudes 49° 43’ and 57º 39’ W) and to evaluate the spatial-temporal distribution pattern of these metrics under the influence of the subtropical climate variability. The phenological metrics were obtained based on the time series of the EVI (Enhanced Vegetation Index), of the sensor MODIS (Moderate Resolution Imaging Spectroradiometer), for the period from 2001 to 2014, through the Timesat program. Eleven phenological metrics were extracted, identifying the presence of two spatial distribution patterns of grass-dominated typologies in the Rio Grande do Sul state, Brazil, one located in the south-central region and the other located in the northeast, along the coast and in the western portion of the state. In addition, it was also observed that the phenological pattern of the grassland vegetation of the state of Rio Grande do Sul, Brazil, is controlled by the seasonality of vegetation, mainly associated with the variations in air temperature.

Climate change: vegetation and phenological phase dynamics

“…At the level of empirical research, Baniya et al (2019) used the Sen’s slope and Mann Kendall test statistics to investigate changes in vegetation at the national and provincial scales in Nepal from 2000 to 2017 and found a significant increase of the NDVI. Moreira et al (2019) evaluated the dynamic of phenological metrics based on enhanced vegetation index (EVI) for the period from 2001 to 2014 through the TIMESAT program and reported that the phenological pattern of Brazil was controlled by variations of air temperature. Deka et al (2019) adopted the threshold method to extract phenological parameters of vegetation and showed that the correlation of temperature and vegetation NDVI was stronger than that of precipitation in India.…”

Paleodiet of Lamini camelids (Mammalia: Artiodactyla) from the Pleistocene of southern Brazil: insights from stable isotope analysis (δ13C, δ18O)

“…Variations in camelid diet are mainly linked to climate (Gil et al 2016). Climatic conditions are responsible for the distribution of grass species and characterize their spatialization at a regional scale (Moreira et al 2019; Preston and Fjellheim 2020). Due to the greater consumption of C 3 grasses compared with C 4 grasses, the former likely occurred in higher abundance in southern Brazil during the Pleistocene.…”

“…Due to the greater consumption of C 3 grasses compared with C 4 grasses, the former likely occurred in higher abundance in southern Brazil during the Pleistocene. Grasses that use the C 4 photosynthetic pathway require warm growing-season temperatures, and their growth is therefore limited by low temperatures and the occurrence of frost during winter, whereas C 3 photosynthesis occurs in cool-season grasses (Boldrini et al 2015; Moreira et al 2019). So, the low temperatures of glacial periods may have favored the development of cool-season grasses over tropical grasses.…”

Modelling the Pastureland Productivity in Areas of Savanna in Northern Minas Gerais – Brazil

“…Garcia, Ferreira e Sano (2013) analyzed the quality of pastures in the Cerrado of Goiás State, using MODIS for providing vegetation indexes to obtain data about net primary productivity; these authors observed the relationship between environmental factors (soils) in the pasture productivity behavior. Moreira et al (2019), analyzing the pastures' phenological metrics of Brazil's southern, observed that the pastures' physical conditions are controlled by climatic seasonality, especially air temperature variation. However, the analyzes are growing to understand the Gross Primary Productivity (GPP) in pasture areas, which includes the ability of this land use to fix atmospheric carbon, indicating its state of vigor, through dry matter, because the greater the absorption carbon values of larger pastures are the biomass values (Veloso et al, 2020).…”