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Changes in the woody vegetation of macro clearances in Vištytgiris Botanical-Zoological Reserve
2014
Panitauskaite, E., Aleksandras Stulginskis Univ., Akademija, Kauno reg. (Lithuania) | Abraitiene, J., Aleksandras Stulginskis Univ., Akademija, Kauno reg. (Lithuania)
An important factor in the development of forest ecosystem is the ability to regenerate. Natural intensity of self thinning of a forest depends on the tree species and environmental conditions. Due to abiotic and biotic factors in a continuous forest tract, there appears a clearing, which, depending on the size, forms new growth conditions. Over time, the resulting new space is occupied by herbaceous and woody vegetation. Most often regeneration of a new forest depends on the size of the plot. The study was conducted in 2013 during the growing season in a typical broadleaf forest stand. During the study woody vegetation and projection coverage of herbaceous vegetation was registered in large clearings. Light conditions in the plots and under tree canopies, as well as soil parameters were ascertained. Based on the collected data, the view of the structure of woody vegetation, projection coverage of herbaceous vegetation, light conditions, temperature, soil moisture content and pH changes were obtained. In order to clarify the influence of microclimatic conditions on natural forest regeneration, the data on light and soil characteristics were analyzed. The aim of the study - was to determine the changes of woody and herbaceous vegetation in spruce stand clearings and to assess the impact of microclimate. During the study it was found out that in large plots dominated species demanding higher amount of light, while herbaceous vegetation was attributed to the third, fourth groups of aggressiveness. Naturally regenerated seedlings condition was mostly influenced by light conditions and soil moisture content.
Mostrar más [+] Menos [-]Impact of the fields, fertilized with manure from big livestock companies on drainage water quality
2013
Miseviciene, S., Aleksandras Stulginskis Univ., Akademija, Kauno reg. (Lithuania)
The paper presents data on the water quality in drainage from manure-fertilized areas in a large livestock company (629 conditional livestock) from 2008 to 2012. The scheme of investigation consists of two field variants: manure fertilized and non-fertilized. Researches are carried out in drained areas, where the drainage water is drained away through outlets. The nitrogen rate 170 kg haE-1 is used annually to fertilize fields in spring. The aim of the research was to ascertain the impact of large livestock company fields fertilized annually with manure on the water quality in drainage. For the purpose of chemical investigations, water samples from drainage were taken once per month. Water analyses were carried out by the accredited Chemical Analytical Laboratory of the Water Management Engineering Institute of Aleksandras Stulginskis University according to specified methods. Investigation results have demonstrated that fields fertilized annually with manure raised the contents of Nmin and P2O5 in the soil by 1.5 and 2.2 times respectively in comparison to the non-fertilized ones. The increase in these contents was conditioned by the higher air temperature and the lower rainfall. The seasonality of Ntotal concentrations in drainage water was discovered: higher concentrations were identified in autumn and winter, lower concentrations – in spring and summer. Due to low dissolubility in the soil, low Ptotal concentrations were identified in drainage water. The highest concentrations were identified with the start of drainage operation.
Mostrar más [+] Menos [-]Detection and reduction of land degradation in Smarde Municipality rural territory [Latvia]
2017
Cintina, V., Latvia Univ. of Agriculture, Jelgava (Latvia) | Baumane, V., Latvia Univ. of Agriculture, Jelgava (Latvia)
The aim of the paper is to explore the possibilities of detection and reduction of land degradation in Smarde municipality rural territory (56°57′18″ N; 23°20′17″ E). To carry out land degradation prevention measures, initially the territories of degraded land should be determined. This paper highlights the field inspection method. For territory inspection a model was used that gave the opportunity to identify degradation types with their characteristic features and possibilities to reduce the land degradation. The territory of Smarde municipality rural territory was inspected in nature and degraded territories identified. The costs of land degradation elimination depend on the type of land degradation. In territories where the land degradation reduction or elimination has been done, its control has to continue in order to stop the development of land degradation.
Mostrar más [+] Menos [-]Identification of wet areas in agricultural lands using remote sensing data
2019
Stals, T., Latvian State Forest Research Inst. Silava, Salaspils (Latvia) | Ivanovs, J., Latvian State Forest Research Inst. Silava, Salaspils (Latvia)
Wet areas in agricultural lands are usually not fully or properly managed due to problematic accessibility by heavy machinery and are associated with lower crop yields. There are neither studies regarding spatial distribution of wet agricultural areas in Latvia nor large scale soil maps. Being aware of these wet areas, it would be possible to plan actions for effective management of these areas, starting with a scale of landscape. A geographic information system model could serve as an assistant for decision-making, such as, a direct support for the management of amelioration systems, change of land use and management patterns or granting support payments. Remote sensing data like Sentinel-2 satellite images and LiDAR (Light detecting and ranging) technology can be used to identify local wet areas. The focus of this article is to evaluate different remote sensing indices and methods that can be used to identify wet areas in agricultural lands using open access data and software. From 52 indices, which were analysed with soil moisture field measurements in 33 sample plots, only two of them showed statistical significance in linear regression model (p is less than 0.05): normalized height model in resolution of 25 meters (r2 =0.45) and visible blue spectral band in April (r2 =0.39). Results from this study help to focus on different aspects of remote sensing data usage and methodology for future improvements in order to fully implement LiDAR and Sentinel-2 data for identification of wet areas in agricultural lands.
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