Daugiau, kaip 80 % hidrografinio tinklo Lietuvoje sudaro melioracijos kanalai. Daugiau kaip 30 % bebrų populiacijos gyvena šiuose kanaluose. Bebrų veikla neretai trikdo normalų melioracijos sistemų funkcionavimą. Tyrimui pasirinktos dviejuose skirtinguose kraštovaizdžiuose esančios bebravietės (Molėtų bei Panevėžio rajonuose). Šiame darbe buvo tiriama bebraviečių tankumas, pasiskirstymas, erdvinės charakteristikos bei statybinės veiklos intensyvumas melioracijos kanaluose. Nustatytas bebrų poveikio mastas bei šio masto pokyčiai. Ištirtose teritorijose bebrų veikiama pusė melioracijos kanalų linijinio ilgio. Per 10 metų (1995-2005) bebraviečių skaičius melioracijos kanaluose praktiškai nepakito, taigi nekito ir melioracijos sistemoms daromas poveikis. / More than 80 % of hydro-graphical network in Lithuania is composed of drainage channels. More than 30 % of beaver populations in Lithuania live in drainage channels. Beaver activity often dislocates irrigations systems. This research was taken in two different landscapes. Beaver sites were visited in Moletai and Panevezys districts. Density, spread, dimensions and constructional activity were recorded in drainage channels. Also this study shows influence over the environment of changing number in beaver populations. Half of linear lengths of irrigation systems are influenced by beaver activity. The number of beaver sites did not change in a ten year period (1995-2005) as well as did not change the damage caused by beaver activity.

Just as the carbon dioxide observations that form the Keeling curve revolutionized the study of the global carbon cycle, free and open access to all available Landsat imagery is fundamentally changing how the Landsat record is being used to study ecosystems and ecological dynamics. This dissertation advances the use of Landsat time series for visualization, classification, and detection of changes in terrestrial ecological processes. More specifically, it includes new examples of how complex ecological patterns manifest in time series of Landsat observations, as well as novel approaches for detecting and quantifying these patterns. Exploration of the complexity of spectral-temporal patterns in the Landsat record reveals both seasonal variability and longer-term trajectories difficult to characterize using conventional bi-temporal or even annual observations. These examples provide empirical evidence of hypothetical ecosystem response functions proposed by Kennedy et al. (2014). Quantifying observed seasonal and phenological differences in the spectral reflectance of Massachusetts’ forest communities by combining existing harmonic curve fitting and phenology detection algorithms produces stable feature sets that consistently out-performed more traditional approaches for detailed forest type classification. This study addresses the current lack of species-level forest data at Landsat resolutions, demonstrating the advantages of spectral-temporal features as classification inputs. Development of a targeted change detection method using transformations of time series data improves spatial and temporal information on the occurrence of flood events in landscapes actively modified by recovering North American beaver (Castor canadensis) populations. These results indicate the utility of the Landsat record for the study of species-habitat relationships, even in complex wetland environments. Overall, this dissertation confirms the value of the Landsat archive as a continuous record of terrestrial ecosystem state and dynamics. Given the global coverage of remote sensing datasets, the time series visualization and analysis approaches presented here can be extended to other areas. These approaches will also be improved by more frequent collection of moderate resolution imagery, as planned by the Landsat and Sentinel-2 programs. In the modern era of global environmental change, use of the Landsat spectral-temporal domain presents new and exciting opportunities for the long-term large-scale study of ecosystem extent, composition, condition, and change.