How Strong Is the Relationship Between Rainfall Variability and Caatinga Productivity? A Case Study Under a Changing Climate

Salimon, Cleber Ibraim; Anderson, Liana O.

doi:10.1590/0001-3765201720170143

Cited by 18 publications

(7 citation statements)

References 20 publications

(9 reference statements)

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“…Also, even though seeds harvested from 2011-2013 exhibited similar ψ b (-0.8 to -0.9 MPa), the hydrotime (θ HPEG ) proved that 2012 seeds required more time to conclude their germination in water restriction. This response is in agreement with the low vigor of the lot, which, in its turn, might be linked to an unusually severe drought, with 65% less rainfall than the historical average (Souza et al, 2017;Salimon and Anderson, 2018), mainly during the flowering season (Figure 1).…”

Section: Effects Of the Environmental Stress On Germinationsupporting

confidence: 80%

Environmental stress, future climate, and germination of Myracrodruon urundeuva seeds 1

et al. 2019

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Myracrodruon urundeuva, a native species from the Brazilian Caatinga, is widely distributed across its endemic region, where it also plays an essential socioeconomic role. The objective of this study was to evaluate the influence of environmental stress on the germination of M. urundeuva seeds harvested in different years (2010 to 2013). Seeds were germinated at constant temperatures between 10 to 40 °C, osmotic potentials from 0 to -0.8 MPa (in polyethylene glycol 6000 solutions), and from 0 to -0.5 MPa (in NaCl solutions). The experiment was conducted according to a completely randomized design, with three replicates of 50 seeds, in a factorial scheme (harvest year x stress intensity) for each environmental stress. Germination data were then analysed using thermal, hydro and halo time models, and future germination responses projected according to climate change scenarios. The germination thermal thresholds ranged from 7.4 to 53.3 oC. The germination base osmotic threshold (using polyethylene glycol) was -0.6 MPa and the base osmotic threshold in NaCl was -0.43MPa. Seeds from different harvest years showed distinct tolerance to environmental stresses. The thermal, hydro and halo-time models were efficient to describe the germinative response of seeds, and the climate models allowed to identify the germination responses of M. urundeuva in future climate. According to the models for future climate (RCP 8.5), the reduction of rainfall by 2100 will directly affect seed germination and seedling recruitment of M. urundeuva.

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Section: Effects Of the Environmental Stress On Germinationsupporting

confidence: 80%

Environmental stress, future climate, and germination of Myracrodruon urundeuva seeds 1

et al. 2019

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“…The Brazilian estimates of soybean productivity essentially follow two axes: either by subjective methods (Gusso et al, 2017), which do not allow for a quantitative analysis of the errors involved (Rizzi & Rudorff, 2007); or by a drop in yield based on agrometeorological models (Meshesha & Abeje, 2018), which study the interaction between climate and productivity (Salimon & Anderson, 2017;Gajić et al 2018), seeking to quantify the effects of climate variations on plant behavior (Nascimento et al, 2018). In this context, there is a growing demand for methodologies that acquire productivity information and monitor large-scale soybean crops.…”

Section: Introductionmentioning

confidence: 99%

A Spectral Agrometeorological Model for Estimating Soybean Grain Productivity in Mato Grosso, Brazil

et al. 2020

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This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index -NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to estimate production and productivity in the study area. Willmott's agreement index was 0.99 and 0.96 and Pearson's correlation coefficient was 0.99 and 0.84 for production and productivity, respectively.

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“…Remote sensing methodologies provide an answer to the questions related to extensive tropical grassland management, allowing to estimate productivity in extensive pasture areas without in situ destructive sampling. Salimon et al [17] state that the use of remote sensing facilitates the measurement of forage biomass through a contrast between different wavelengths and the other targets, besides presenting a low cost and being able to cover large areas in a short space of time. Spectral reflectance of canopy covers can provide a fast and non-destructive method for the evaluation of biophysical parameters, such as LAI, biomass, height, or N content in the plant.…”

Section: Introductionmentioning

confidence: 99%

Mapping Productivity and Essential Biophysical Parameters of Cultivated Tropical Grasslands from Sentinel-2 Imagery

et al. 2020

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Nitrogen (N) is the main nutrient element that maintains productivity in forages; it is inextricably linked to dry matter increase and plant support capacity. In recent years, high spectral and spatial resolution remote sensors, e.g., the European Space Agency (ESA)’s Sentinel satellite missions, have become freely available for agricultural science, and have proven to be powerful monitoring tools. The use of vegetation indices has been essential for crop monitoring and biomass estimation models. The objective of this work is to test and demonstrate the applicability of different vegetation indices to estimate the biomass productivity, the foliar nitrogen content (FNC), the plant height and the leaf area index (LAI) of several tropical grasslands species submitted to different nitrogen (N) rates in an experimental area of São Paulo, Brazil. Field reflectance data of Panicum maximum and Urochloa brizantha species’ cultivars were taken and convoluted to the Sentinel-2 satellite bands. Subsequently, different vegetation indices (Normalized Difference Vegetation Index (NDI), Three Band Index (TBI), Difference light Height (DLH), Three Band Dall’Olmo (DO), and Normalized Area Over reflectance Curve (NAOC)) were tested for the experimental grassland areas, and composed of Urochloa decumbens and Urochloa brizantha grass species, which were sampled and destructively analyzed. Our results show the use of different relevant Sentinel-2 bands in the visible (VIS)–near infrared (NIR) regions for the estimation of the different biophysical parameters. The FNC obtained the best correlation for the TBI index combining blue, green and red bands with a determination coefficient (R2) of 0.38 and Root Mean Square Error (RMSE) of 3.4 g kg−1. The estimation of grassland productivity based on red-edge and NIR bands showed a R2 = 0.54 and a RMSE = 1800 kg ha−1. For the LAI, the best index was the NAOC (R2 = 0.57 and RMSE = 1.4 m2 m−2). High values of FNC, productivity and LAI based on different sets of Sentinel-2 bands were consistently obtained for areas under N fertilization.

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How Strong Is the Relationship Between Rainfall Variability and Caatinga Productivity? A Case Study Under a Changing Climate

Cited by 18 publications

References 20 publications

Environmental stress, future climate, and germination of Myracrodruon urundeuva seeds 1

Environmental stress, future climate, and germination of Myracrodruon urundeuva seeds 1

A Spectral Agrometeorological Model for Estimating Soybean Grain Productivity in Mato Grosso, Brazil

Mapping Productivity and Essential Biophysical Parameters of Cultivated Tropical Grasslands from Sentinel-2 Imagery

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