Modelling of land cover change in abandoned landscape using time series of aerial photography

4 Český abstrakt Práce se zabývá modelováním změny krajinného pokryvu způsobené opouštěním krajiny. Studijní plocha o rozměrech 2,5 km × 2 km se nachází ve vojenském újezdu Hradiště, v okolí bývalé obce Tocov. Vzhledem k nedostatku historických dat o vegetaci na krajinné úrovni byly jako zdroj dat použity historické letecké snímky. Ty byly ortorektifikovány, mozaikovány a automaticky objektově klasifikovány do kategorií dřeviny a bezlesí. Postupné zarůstání krajiny bylo modelováno pomocí zobecněných lineárních modelů se smíšenými efekty (lmer) s použitím proměnných odvozených z digitálního výškového modelu, údajů o původním land use a prostorových proměnných získaných pomocí algoritmů na bázi celulárních automatů. Za účelem ověření predikce modelů se skutečným stavem, interpretace a vizualizace výsledků byla vytvořena aplikace PEMZOK Prostorově Explicitní Model Zarůstání Opuštěné Krajiny, která je jedním z výsledků této práce. Byla zjištěna stále rostoucí rychlost zarůstání zbylých bezlesí. Největší zjištěný vliv na šíření dřeviny měla vzdálenost k nejbližší dřevině a hustoty dřevin v blízkém okolí (15 m × 15 m) a širším okolí (105 m × 105 m) ve výchozím roce. Modely s těmito proměnnými a původním land use byly nejúspěšnější skupinou modelů. Faktory odvozené z digitálního modelu terénu vedly k poněkud horší...Obsah 5 English abstract This thesis deals with modelling of land cover change in abandoned landscape. The study site is located in the military area Hradiště, around the former village Tocov, it is 2,5 km long and 2 km wide. Due to lack of historical vegetation data on landscape scale, historical aerial photographs were used as a primary source of data. They were orthorectified, mosaicked and automatically object oriented then classified in two categories woodland and grassland. Changes between two successive classified images were modelled with generalized linear models with mixed effects (lmer). Variables that were derived from digital elevation model, former land use and spatial variables computed with algorithms based on cellular automata were used. In order to verify the model predictions with the actual situation and for easier interpretation and visualization of results, a new application PEMZOK (Spatially explicit model of overgrowth of abandoned landscape) was developed and is one of the results of this work. Rapid rate of overgrowth of remaining grasslands was found. The largest observed effect on the spread of trees had the distance to the nearest tree or shrub and density of trees in the vicinity (15 m × 15 m) and the wider neighbourhood (105 m × 105 m). Models with these variables and land use...Department of BotanyKatedra botanikyFaculty of SciencePřírodovědecká fakult

Distributions of vascular plants in the Czech Republic. Part 2

The second part of the publication series on the istributions of vascular plants in the Czech Republic includes grid maps of 87 taxa of the genera Antennaria, Aposeris, Astragalus, Avenula, Bidens, Carex, Cenchrus, Centunculus, Convallaria, Crocus, Cryptogramma, Cyperus, Dryopteris, Gladiolus, Gratiola, Helictochloa, Hierochloë, Lindernia, Maianthemum, Myriophyllum, Notholaena, Nymphoides, Radiola, Schoenoplectus, Sisyrinchium, Spergularia, Tillaea, Veratrum and Veronica. The maps were produced by taxonomic experts based on all available herbarium, literature and field records. The plants studied include 56 taxa registered in the Red List of vascular plants of the Czech Republic, some of which showed remarkable declines. Spatial and temporal dynamics of individual species are shown in maps and documented by records included in the Pladias database and available in Electronic appendices. The maps are accompanied by comments, which include additional information on distribution, habitats, taxonomy and biology of the species

A laboratory for conceiving Essential Biodiversity Variables (EBVs)—The ‘Data pool initiative for the Bohemian Forest Ecosystem’

Effects of climate change-induced events on forest ecosystem dynamics of composition, function and structure call for increased long-term, interdisciplinary and integrated research on biodiversity indicators, in particular within strictly protected areas with extensive non-intervention zones. The long-established concept of forest supersites generally relies on long-term funds from national agencies and goes beyond the logistic and financial capabilities of state-or region-wide protected area administrations, universities and research institutes. We introduce the concept of data pools as a smaller-scale, user-driven and reasonable alternative to co-develop remote sensing and forest ecosystem science to validated products, biodiversity indicators and management plans. We demonstrate this concept with the Bohemian Forest Ecosystem Data Pool, which has been established as an interdisciplinary, international data pool within the strictly protected Bavarian Forest and Šumava National Parks and currently comprises 10 active partners. We demonstrate how the structure and impact of the data pool differs from comparable cases. We assessed the international influence and visibility of the data pool with the help of a systematic literature search and a brief analysis of the results. Results primarily suggest an increase in the impact and visibility of published material during the life span of the data pool, with highest visibilities achieved by research conducted on leaf traits, vegetation phenology and 3D-based forest inventory. We conclude that the data pool results in an efficient contribution to the concept of global biodiversity observatory by evolving towards a training platform, functioning as a pool of data and algorithms, directly communicating with management for implementation and providing test fields for feasibility studies on earth observation missions.publishedVersio

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Methodology of microclimate measurement with TMS microclimate stations

The methodology of microclimate measurement contains procedures for creating a representative network of stations on the examples of networks installed in the area of the Šumava National Park. It also deals with procedures for correct data acquisition and processing. The methodology will enable the NP Šumava Administration to continue data acquisitions from the newly created network after the end of the project, or to facilitate the creation of their own network for the study of other research questions

Use of remote sensing data for monitoring of long-term vegetation dynamics on the landscape scale

This thesis deals with the use of remote sensing data for studying and monitoring vegetation changes. Thanks to archival materials, we can now make extensive studies at the landscape and global level without the need for large-scale old field data. From the Middle Ages, we can rely on different types of maps, for vegetation studies, these are mainly forestry maps. Since the 1930's, aerial photographs have been available in Europe, and satellite imagery was available since the 1970's. Availability and quality of satellite imagery had increased rapidly during my study. The most recent data source are unmanned aerial systems and methods of processing their data, which allow inexpensive detailed mapping of large areas. The presented publications do not only solve ecological research questions, but also contribute to solving current environmental problems in the Czech Republic, from nature conservation in National Parks and protected areas to monitoring of plant invasions. I have used archival forest maps for the reconstruction and analysis of large disturbances (windthrow and subsequent gradations of bark beetle) in forests of Šumava and the Bavarian Forest in 1868-1870. Species composition, as well as environmental factors derived from digital elevation model, were analyzed. The same topic was also..

Methodology of processing hemispherical photographs

The methodology of processing hemispherialc photographs is a complex set of activities, starting with the creation of an image with a fish-eye lens, image editing in graphic editors and ending with analysis in specialized software. The obtained data indicate the amount of radiation falling into the undergrowth and the method of processing affects their quality. The procedure developed by the GIS and Remote Sensing Department of BU CAS integrates methods from various programmes into a script in R