Biology subjects

Klimes, A.

Publications and source records attributed to Klimes, A..

3 recordsLinked to original sources

bioRxiv2026

Data-driven identification of the ecologically relevant climatic windows and climate summaries with StatClim model

Climate affects biological processes and organisms. It is extensively recorded, and its effects are frequently studied. Climatic variables are recorded as time series of measurements, but these are often summarized as long-term averages, throwing away biologically relevant information. Subsequent analyses can therefore miss important climate effects or suffer from low predictive power. Here, we propose a new method, StatClim, inferring the most informative climatic summary from the data. Instead of taking a fixed arbitrary summary of a time series, StatClim automatically estimates the beginning and width of a climatic window and simultaneously calculates data aggregation, which best predicts a response variable. We implemented the proposed approach as a Bayesian hierarchical model in Stan. We illustrated the potential of StatClim on published data on mast seeding of Fagus sylvatica. StatClim correctly identified known climatic windows relevant for this tree species, but also uncovered that mast seeding is triggered by high temperatures within these windows. We demonstrated flexibility of the model to account for complex data structures, we ran power analysis showing the ability of the model to identify climatic effects even with modest datasets, and we evaluated its false positive rate, which is lower than 0.01. We discuss the advantages and limitations of StatClim. Compared to existing alternatives, it is suitable for hypothesis testing and offers important advances, such as estimation of the type of aggregation. In combination with existing methods, StatClim will facilitate data-driven use of climatic and microclimatic data and therefore discovering so far unknown climatic effects on biological processes and ecosystem functioning.

ecology↗

bioRxiv2024

: A tool for modelling ecosystem resilience

AimsA number of modelling frameworks exist to aid in the identification and exploration of stable states and the assessment of resilience from ecological datasets. However, because such models are complex to implement there is a substantial barrier for the application in ecological research. Here we develop a flexible model of ecological resilience based on Bayesian approximation of the "stability landscape". We illustrate its usage on a tropical area where variation in tree cover has been previously interpreted as alternative stable states. MethodsThe stability landscape, from which stable states and resilience parameters are computed, is modelled using a mixture of multiple distributions, each representing a regression between the system state variable and the environmental covariates. Our "mixglm" model allows the mean, precision, and probability parameters of these distributions in the landscape to be dependent on multiple external covariates. "Mixglm" is implemented as a function in R package with the same name, internally using Bayesian inference via NIMBLE. We also conducted a power analysis to provide guidance regarding required sample size. ResultsWe illustrate the use of the "mixglm" on a published case of tree cover in South America which reports a stability landscape with three distinct stable states. Using "mixglm", we were able to replicate the identification of these states. Moreover, we quantified uncertainty of our estimates, and computed resilience of South Americas forests. Conclusions"Mixglm" can be readily used for description of stability landscapes and identification of stable states in most spatial datasets of system state variables, and it is accompanied by tools for calculation of resilience metrics. It can also be further expanded using regression framework to account for more complex data structures such as spatio-temporal data.

ecology↗

bioRxiv2021

Comparative anatomy of leaf petioles in temperate trees and shrubs

Petioles are important plant organs connecting stems with leaf blades and affecting light-harvesting leaf ability as well as transport of water, nutrient and biochemical signals. Despite petioles high diversity in size, shape and anatomical settings, little information is available about their structural adaptations across evolutionary lineages and environmental conditions. To fill our knowledge gap, we investigated the variation of petiole morphology and anatomy in 95 European woody plant species using phylogenetic comparative models. Two major axes of variation were related to leaf area (from large and soft to small and tough leaves), and plant size (from cold-adapted shrubs to warm-adapted tall trees). Larger and softer leaves are found in taller trees of more productive habitats. Their petioles are longer, with a circular outline, thin cuticles without trichomes, and are anatomically characterised by the predominance of sclerenchyma, larger vessels, interfascicular areas with fibers, indistinct phloem rays, and the occurrence of prismatic crystals and druses. In contrast, smaller and tougher leaves are found in shorter trees and shrubs of colder or drier habitats. Their petioles are characterized by teret outline, thick cuticle, simple and non-glandular trichomes, epidermal cells smaller than cortex cells, phloem composed of small cells and radially arranged vessels, fiberless xylem, lamellar collenchyma, acicular crystals and secretory elements. Individual anatomical traits were linked to different internal and external drivers. The petiole length and vessel conduit size increase, while cuticle thickness decreases, with increasing leaf blade area. Epidermis cell walls are thicker in leaves with higher specific leaf area. Collenchyma becomes absent with increasing temperature, epidermis cell size increases with plant height and temperature, and petiole outline becomes polygonal with increasing precipitation. We conclude that species temperature and precipitation optima, plant height, leaf area and thickness exerted a significant control on petiole anatomical and morphological structures not confounded by phylogenetic inertia. Unrelated species with different evolutionary histories but similar thermal and hydrological requirements have converged to similar petiole anatomical structures. Our findings contribute to improving current knowledge about the functional morphoanatomy of the petiole as the key organ that plays a crucial role in the hydraulic pathways in plants.

ecology↗