This work presented an FEM (finite element method) mathematical model that describes the temperature distribution in different parts of a 3D printer based on additive manufacturing process using filament extrusion during its operation. Variation in properties also originate from inconsistent choices of process parameters employed by individual manufacturers. Therefore, a mathematical model that calculates temperature changes in the filament (and the resulting print) during an FFF (fused filament fabrication) process was deemed useful, as it can estimate otherwise immeasurable properties (such as the internal temperature of the filament during the printing). Two variants of the model (both static and dynamic) were presented in this work. They can provide the user with the material's thermal history during the print. Such knowledge may be used in further analyses of the resulting prints. Thanks to the dynamic model, the cooling of the material on the printing bed can be traced for various printing speeds. Both variants simulate the printing of a PLA (Polylactic acid) filament with the nozzle temperature of 220 °C, bed temperature of 60 °C, and printing speed of 5, 10, and 15 m/s, respectively.

• Klíčová slova
• FFF, additive manufacturing, dynamic and static model, fused filament fabrication, temperature distribution modelling, thermal history,
• Publikační typ
• časopisecké články MeSH

Studying current and future geographic distribution is essential for conserving endangered species such as the Boreal Owl and Eurasian Pygmy Owl. The main aim of this study was to determine the potential distribution of both species in the Balkan Peninsula by using spatial distribution models (SDMs) in MaxEnt. We used data from field surveys, the scientific and grey literature, and an online database. We considered the current time and two future periods, 2041-2060 and 2061-2080. For future periods, we included different climate scenarios (SSP 126, 245, 370, and 585) in studying the potential geographic distribution of both species. We identified two types of potential future refugia for species: in situ and ex situ. Our study shows the highly suitable area for the Boreal Owl increased during the 2041-2060 period compared with the current area in all scenarios, except in SSP 585. However, during the 2061-2080 period, the highly suitable areas contracted. For the Eurasian Pygmy Owl, highly suitable areas decreased during 2041-2060, but during the 2061-2080 period, it was larger than the current area. Our study is of importance for conservation and preserving areas of potential distribution and refugia for Boreal and Eurasian Pygmy Owls in the face of climate change.

• Klíčová slova
• Aegolius funereus, Balkan Peninsula, Glaucidium passerinum, MaxEnt, climate change, refugia, species distribution modelling, suitability modelling,
• Publikační typ
• časopisecké články MeSH

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

• Klíčová slova
• bias, detectability, distribution change, methods, occupancy, rare species, sampling, spatial data, species distribution modelling, survey,
• MeSH
• biodiverzita * MeSH
• Publikační typ
• časopisecké články MeSH

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Variation of habitats and resources important for farmland birds seems to be only partly captured by ordinary statistics on land-use and agricultural production. For instance, densities of rodents being prey for owls and raptors or structures of rural architecture providing nesting sites for many species are central for bird diversity but are not reported in any official statistics. Thus, modelling species distributions, population abundance and trends of farmland birds may miss important predictive habitat elements. Here, we involve local socio-economy factors as a source of additional information on rural habitat to test whether it improves predictions of barn owl occurrence in 2768 churches across Poland. Barn owls occurred in 778 churches and seemed to prefer old churches made of brick located in regions with a milder climate, higher share of arable land and pastures, low road density and low levels of light pollution. Including data on local unemployment, the proportion of elder citizens, commune income per citizen, the share of citizens with high education and share of farmers among working population improved the model substantially and some of these variables predicted barn owl occurrence better than several land-use and climate data. Barn owls were more likely to occur in areas with high unemployment, a higher proportion of older citizens in a local population and higher share of farmers among working population. Importantly, the socio-economy variables were correlated with the barn owl occurrence despite all climatic, infrastructure and land-use data were present in the model. We conclude that the socio-economy of local societies may add important but overlooked information that links to spatial variation in farmland biodiversity.

• Klíčová slova
• Agriculture, Conservation, Modelling, Owls, Socioeconomy, Statistical analyses,
• MeSH
• biodiverzita MeSH
• ekosystém MeSH
• Stringiformes * MeSH
• zemědělství MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Polsko MeSH

The distribution of data presented in many electrophysiological studies is presumed to be normal without any convincing evidence. To test this presumption, the cell membrane capacitance and magnitude of inward rectifier potassium currents were recorded by the whole-cell patch clamp technique in rat atrial myocytes. Statistical analysis of the data showed that these variables were not distributed normally. Instead, a positively skewed distribution appeared to be a better approximation of the real data distribution. Consequently, the arithmetic mean, used inappropriately in such data, may substantially overestimate the true mean value characterizing the central tendency of the data. Moreover, a large standard deviation describing the variance of positively skewed data allowed 95% confidence interval to include unrealistic negative values. We therefore conclude that the normality of the electrophysiological data should be tested in every experiment and, if rejected, the positively skewed data should be more accurately characterized by the median and interpercentile range or, if justified (namely in the case of log-normal and gamma data distribution), by the geometric mean and the geometric standard deviation.

• Klíčová slova
• Cardiomyocyte, Gamma distribution, Geometric mean, Inward rectifier, Log-normal distribution, Median, Membrane capacitance, Normal distribution,
• MeSH
• algoritmy MeSH
• buněčná membrána patologie   fyziologie   MeSH
• elektrická kapacitance MeSH
• elektrody MeSH
• elektrofyziologie metody   MeSH
• interpretace statistických dat MeSH
• krysa rodu Rattus MeSH
• membránové potenciály MeSH
• normální rozdělení * MeSH
• potkani Wistar MeSH
• reprodukovatelnost výsledků MeSH
• srdeční síně patologie   MeSH
• svalové buňky fyziologie   MeSH
• teoretické modely MeSH
• zvířata MeSH
• Check Tag
• krysa rodu Rattus MeSH
• mužské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Efficient tick and tick-borne disease control is a major goal in the efforts to improve the livestock industry in developing countries. To gain a better understanding of the distribution and abundance of livestock ticks under changing environmental conditions, a country-wide field survey of tick infestations on indigenous cattle was recently carried out in Tanzania. This paper evaluates four models to generate tick predictive maps including areas between the localities that were surveyed. Four techniques were compared: (1) linear discriminant analysis, (2) quadratic discriminant analysis, (3) generalised regression analysis, and (4) the weights-of-evidence method. Inter-model comparison was accomplished with a data-set of adult Rhipicephalus appendiculatus ticks and a set of predictor variables covering monthly mean temperature, relative humidity, rainfall, and the normalised difference vegetation index (NDVI). The data-set of tick records was divided into two equal subsets one of which was utilised for model fitting and the other for evaluation, and vice versa, in two independent experiments. For each locality the probability of tick occurrence was predicted and compared with the proportion of infested animals observed in the field; overall predictive success was measured with mean squared difference (MSD). All models exhibited a relatively good performance in configurations with optimised sets of predictors. The linear discriminant model had the least predictive success (MSD>or=0.210), whereas the accuracy increased in the quadratic discriminant (MSD>or=0.197) and generalised regression models (MSD>or=0.173). The best predictions were gained with the weights-of-evidence model (MSD>or=0.141). Theoretical as well as practical aspects of all models were taken into account. In summary, the weights-of-evidence model was considered to be the best option for the purpose of predictive mapping of the risk of infestation of Tanzanian indigenous cattle. A detailed description of the implementation of this model is provided in an annex to this paper.

• MeSH
• biologické modely MeSH
• diskriminační analýza MeSH
• infestace klíšťaty veterinární   MeSH
• nemoci skotu parazitologie   MeSH
• regresní analýza MeSH
• Rhipicephalus * MeSH
• skot MeSH
• statistické modely * MeSH
• zvířata MeSH
• Check Tag
• skot MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH
• Geografické názvy
• Tanzanie MeSH

This article studies the effect of travel costs on population distribution in a patchy environment. The Ideal Free Distribution with travel costs is defined in the article as the distribution under which it is not profitable for individuals to move, i.e., the movement between patches ceases. It is shown that depending on the travel costs between patches, the Ideal Free Distribution may be unique, there may be infinitely many possible IFDs, or no Ideal Free Distribution exists. In the latter case, animal distribution can converge to an equilibrium of distributional dynamics at which individuals do disperse, but the net movement between patches ceases. Such distributional equilibrium corresponds to balanced dispersal.

• Klíčová slova
• Balanced dispersal, Evolutionary game theory, Habitat selection, Ideal Free Distribution, Travel cost,
• MeSH
• biologické modely MeSH
• ekosystém * MeSH
• lidé MeSH
• pohyb * MeSH
• populační dynamika MeSH
• rozšíření zvířat MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

A stepwise sequential assimilation algorithm is proposed based on an optimisation approach for recursive parameter estimation and tracking of radioactive plume propagation in the early stage of a radiation accident. Predictions of the radiological situation in each time step of the plume propagation are driven by an existing short-term meteorological forecast and the assimilation procedure manipulates the model parameters to match the observations incoming concurrently from the terrain. Mathematically, the task is a typical ill-posed inverse problem of estimating the parameters of the release. The proposed method is designated as a stepwise re-estimation of the source term release dynamics and an improvement of several input model parameters. It results in a more precise determination of the adversely affected areas in the terrain. The nonlinear least-squares regression methodology is applied for estimation of the unknowns. The fast and adequately accurate segmented Gaussian plume model (SGPM) is used in the first stage of direct (forward) modelling. The subsequent inverse procedure infers (re-estimates) the values of important model parameters from the actual observations. Accuracy and sensitivity of the proposed method for real-time forecasting of the accident propagation is studied. First, a twin experiment generating noiseless simulated "artificial" observations is studied to verify the minimisation algorithm. Second, the impact of the measurement noise on the re-estimated source release rate is examined. In addition, the presented method can be used as a proposal for more advanced statistical techniques using, e.g., importance sampling.

• Klíčová slova
• Assimilation of measurements, Ill-posed inversion problem, Measurement noise, Radioactivity release, Urgent emergency,
• MeSH
• algoritmy MeSH
• monitorování radiace metody   MeSH
• normální rozdělení MeSH
• počítačová simulace MeSH
• předpověď MeSH
• radioaktivita * MeSH
• teoretické modely * MeSH
• únik radioaktivních látek * MeSH
• Publikační typ
• časopisecké články MeSH

The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geographical and temporal variation in climate. Projections to future climatic conditions suggest a change in relative climatic suitability that would result in HbS being displaced by HbF in northern Britain. This would facilitate local adaptation to future climate-without Hb displacement, populations in northern Britain would likely be suboptimally adapted because their Hb would not match local climatic conditions. Our study shows how pre-existing physiological differences can influence the adaptive capacity of species to climate change.

• MeSH
• aklimatizace * MeSH
• Arvicolinae genetika   MeSH
• fyziologická adaptace MeSH
• hemoglobiny MeSH
• klimatické změny * MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• hemoglobiny MeSH