@article{SoaresPereiraGomesCostaFoersteretal.2019,
  author    = {Soares Pereira, Francisco Jairo and Gomes Costa, Carlos Alexandre and F{\"o}rster, Saskia and Brosinsky, Arlena and de Araujo, Jose Carlos},
  title     = {Estimation of suspended sediment concentration in an intermittent river using multi-temporal high-resolution satellite imagery},
  series = {International journal of applied earth observation and geoinformation},
  volume    = {79},
  journal   = {International journal of applied earth observation and geoinformation},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0303-2434},
  doi       = {10.1016/j.jag.2019.02.009},
  pages     = {153 -- 161},
  year      = {2019},
  abstract  = {There is a shortage of sediment-routing monitoring worldwide, despite its relevance to environmental processes. In drylands, where water resources are more vulnerable to the sediment dynamics, this flaw is even more harmful. In the semi-arid Caatinga biome in the North-east of Brazil, rivers are almost all intermittent and hydro-sedimentological monitoring is scarce. In the biome, water supply derives from thousands of surface reservoirs, whose water availability is liable to be reduced by siltation and sediment-related pollution. The goal of this research was to evaluate the potential of multi-temporal high-resolution satellite imagery (RapidEye) to assess the suspended sediment concentration (SSC) in the medium-sized intermittent Jaguaribe River, Brazil, during a 5-year period. We validated 15 one-, two- and three-band indices for SSC estimation based on RapidEye spectral bands deduced in the context of the present investigation and nine indices proposed in the literature for other optical sensors, by comparing them with in-situ concentration data. The in-situ SSC data ranged from 67 mg.L-1 to 230 mg.L-1. We concluded that RapidEye images can assess moderate SSC of intermittent rivers, even when their discharge is low. The RapidEye indices performed better than those from literature. The spectral band that best represented SSC was the near infrared, whose performance improved when associated with the green band. This conclusion agrees with literature findings for diverse sedimentological contexts. The three-band spectral indices performed worse than those with only one or two spectral bands, showing that the use of a third band did not enhance the model ability. Besides, we show that the hydrological characteristics of semi-arid intermittent rivers generate difficulties to monitor SSC using optical satellite remote sensing, such as time-concentrated sediment yield; and its association with recent rainfall events and, therefore, with cloudy sky.},
  language  = {en}
}
@article{LohmannGuoTietjen2018,
  author    = {Lohmann, Dirk and Guo, Tong and Tietjen, Britta},
  title     = {Zooming in on coarse plant functional types-simulated response of savanna vegetation composition in response to aridity and grazing},
  series = {Theoretical ecology},
  volume    = {11},
  journal   = {Theoretical ecology},
  number    = {2},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1874-1738},
  doi       = {10.1007/s12080-017-0356-x},
  pages     = {161 -- 173},
  year      = {2018},
  abstract  = {Precipitation and land use in terms of livestock grazing have been identified as two of the most important drivers structuring the vegetation composition of semi-arid and arid savannas. Savanna research on the impact of these drivers has widely applied the so-called plant functional type (PFT) approach, grouping the vegetation into two or three broad types (here called meta-PFTs): woody plants and grasses, which are sometimes divided into perennial and annual grasses. However, little is known about the response of functional traits within these coarse types towards water availability or livestock grazing. In this study, we extended an existing eco-hydrological savanna vegetation model to capture trait diversity within the three broad meta-PFTs to assess the effects of both grazing and mean annual precipitation (MAP) on trait composition along a gradient of both drivers. Our results show a complex pattern of trait responses to grazing and aridity. The response differs for the three meta-PFTs. From our findings, we derive that trait responses to grazing and aridity for perennial grasses are similar, as suggested by the convergence model for grazing and aridity. However, we also see that this only holds for simulations below a MAP of 500 mm. This combined with the finding that trait response differs between the three meta-PFTs leads to the conclusion that there is no single, universal trait or set of traits determining the response to grazing and aridity. We finally discuss how simulation models including trait variability within meta-PFTs are necessary to understand ecosystem responses to environmental drivers, both locally and globally and how this perspective will help to extend conceptual frameworks of other ecosystems to savanna research.},
  language  = {en}
}