Структурно-грамматическое оформление лингвистических терминов в крымскотатарском языке

В статье предпринята попытка исследования структурных и частеречных особенностей лингвистических терминов крымскотатарского языка. Подробно анализируется соотношение однословных и многокомпонентных терминологических единиц. Рассматриваются типология структурных моделей двухсловных терминов-словосочетаний.У статті здійснена спроба дослідження структурних особливостей лінгвістичних термінів кримськотатарської мови та їх належність до частин мови. Докладно аналізується співвідношення однослівних і багатокомпонентних терінологічних одиниць. Розглядається типологія структурних моделей двослівних термінів-словосполучень.The author of the article makes an effort to research into structural and parts-of-speech peculiarities of Crimean Tatar linguistic terminology. The correlation of one-word and multi-componential terminological units is analyzed in detail. The article also deals with the structural types of the two-word term combinations

Grazing away the resilience of patterned ecosystems

Ecosystems’ responses to changing environmental conditions can be modulated by spatial self-organization. A prominent example of this can be found in drylands, where formation of vegetation patterns attenuates the magnitude of degradation events in response to decreasing rainfall. In model studies, the pattern wavelength responds to changing conditions, which is reflected by a rather gradual decline in biomass in response to decreasing rainfall. Although these models are spatially explicit, they have adopted a mean-field approach to grazing. By taking into account spatial variability when modeling grazing, we find that (over)grazing can lead to a dramatic shift in biomass, so that degradation occurs at rainfall rates that would otherwise still maintain a relatively productive ecosystem. Moreover, grazing increases the resilience of degraded ecosystem states. Consequently, restoration of degraded ecosystems could benefit from the introduction of temporary small-scale exclosures to escape from the basin of attraction of degraded states.</p

Stability and Fluctuations in Complex Ecological Systems

From 08-12 August, 2022, 32 individuals participated in a workshop, Stability and Fluctuations in Complex Ecological Systems, at the Lorentz Center, located in Leiden, The Netherlands. An interdisciplinary dialogue between ecologists, mathematicians, and physicists provided a foundation of important problems to consider over the next 5-10 years. This paper outlines eight areas including (1) improving our understanding of the effect of scale, both temporal and spatial, for both deterministic and stochastic problems; (2) clarifying the different terminologies and definitions used in different scientific fields; (3) developing a comprehensive set of data analysis techniques arising from different fields but which can be used together to improve our understanding of existing data sets; (4) having theoreticians/computational scientists collaborate closely with empirical ecologists to determine what new data should be collected; (5) improving our knowledge of how to protect and/or restore ecosystems; (6) incorporating socio-economic effects into models of ecosystems; (7) improving our understanding of the role of deterministic and stochastic fluctuations; (8) studying the current state of biodiversity at the functional level, taxa level and genome level.Comment: 22 page

Resolving soil and surface water flux as drivers of pattern formation in Turing models of dryland vegetation: A unified approach

Over the past two decades, multi-component dryland vegetation models have been successful in qualitatively reproducing the spatial vegetation patterns widely observed in nature. In the two-component (water, vegetation) Klausmeier model, water flow from bare to vegetated areas drives pattern formation. The more elaborate Rietkerk and Gilad three-component models make a distinction between soil and surface water. In this article the three models are approximated from within a unifying framework, with a focus on processes that drive pattern formation, in order to promote the understanding of similarities and differences between these models. Reduction from a model with a separate soil and surface water component, to a model with a single water component, preserves Turing instability in all but one of the cases studied

GNU Octave/MATLAB model implementation

This file can be used to compute model runs as in Figure 2 from the publication

GNU Octave/MATLAB model implementation

This file can be used to compute model runs as in Figure 2 from the publication

Resolving soil and surface water flux as drivers of pattern formation in Turing models of dryland vegetation: A unified approach

Over the past two decades, multi-component dryland vegetation models have been successful in qualitatively reproducing the spatial vegetation patterns widely observed in nature. In the two-component (water, vegetation) Klausmeier model, water flow from bare to vegetated areas drives pattern formation. The more elaborate Rietkerk and Gilad three-component models make a distinction between soil and surface water. In this article the three models are approximated from within a unifying framework, with a focus on processes that drive pattern formation, in order to promote the understanding of similarities and differences between these models. Reduction from a model with a separate soil and surface water component, to a model with a single water component, preserves Turing instability in all but one of the cases studied