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Context Forest fragmentation, defined as the spatial configuration of habitat within landscapes, has been quantified using an expanding range of metrics and analytical workflows. Although methodological diversity has increased rapidly with advances in remote sensing and computational capacity, comparability and ecological interpretability remain uneven. Objectives This review advances forest fragmentation analysis by systematically tracking the evolution of methodological families from 1990 to 2025 and identifying structural constraints that limit transferability across regions and scales. Methods We synthesized 138 studies and quantitatively analyzed an operational subset of 127 methodological and hybrid papers. Studies were grouped into twelve methodological families, and their proportional representation was evaluated across four temporal periods. Study level classification and complete search details are provided in the supplementary materials to ensure transparency and reproducibility. Results Patch–mosaic metrics remain the analytical backbone of fragmentation research. Over time, analytical approaches have expanded from early patch-based measures toward connectivity-oriented, density-based, and emerging three-dimensional formulations. This trajectory reflects cumulative methodological expansion rather than paradigm replacement. Across methodological families, recurring constraints include sensitivity to spatial support, context-dependent parameterization, uneven validation of automated or global products, limited linkage to biological responses, and inconsistent reporting of methodological settings. Conclusions Progress in fragmentation analysis is likely to depend less on introducing new indices and more on strengthening comparability through explicit documentation of habitat definitions, spatial resolution, connectivity rules, edge settings, window supports, and change detection parameters. By clarifying methodological trajectories and emphasizing transparent reporting, this review provides a structured foundation for more transferable and ecologically grounded fragmentation research.

Using 12 104 publications from 2014 to 2023 in the DeepBone database, this study employs bibliometric methods, including full-text latent Dirichlet allocation (LDA) modelling, co-occurrence network analysis and geographic mapping with ArcGIS, to examine three key aspects of vertebrate palaeontology development: geographic distribution of newly established taxa, gender demographics among researchers and research trends. Gender data were analysed using automated tools with manual verification to ensure accuracy, while methodological evolution was investigated through systematic text mining and classification. Among 8336 newly established taxa, mammals (34.72%) and fishes (29.76%) dominate, followed by reptiles (25.34%), birds (7.39%) and amphibians (2.80%). Geographic analysis reveals significant regional disparities, with the USA (13.50%) and China (13.32%) contributing the most, while Africa and Oceania remain under-represented (less than 10%). Gender analysis indicates a gradual increase in female representation from 22.78 to 27.20% over the decade, highlighting the imperative to address gender disparities in vertebrate palaeontology, thereby advancing equity in alignment with UNESCO Sustainable Development Goal 5. LDA topic modelling identifies 15 distinct research topics, encompassing evolutionary biology, cranial and skeletal morphology, dinosaur–bird evolution and human evolution, while co-occurrence analysis highlights the evolution of research methodologies, revealing strong interconnections between phylogenetic analysis (15%), traditional morphological analysis (12%) and high-resolution imaging techniques (9%).

By analyzing content, this paper aims to map empirical quantitative research on International Human Resource Management. Our filters will be “when, where, what, and how.” “When” indicates the time span we use to analyze the evolution of International Human Resource Management, “where” refers to the influential journals chosen for publication; “what” covers the different topics dealt with in IHRM, and “how” is linked to the various methodologies and statistical techniques applied. Using the “when, where, what, and how” of empirical quantitative, International Human Resource Management studies allows us to identify how different topics have been investigated and so may lead us to suggest methodological refinements to improve the analysis and knowledge of topics in International Human Resource Management. It will allow us to detect trends and research gaps and point to the most prominent journals for publication and dissemination of results.

This chapter contains sections titled: Introduction Point of departure – divergent policy perspectives, difficulties in definition and temporal relevance International, national and local drug monitoring mechanisms Challenges in monitoring illicit drug use An overview of common information sources and some of their limitations Issues for the interpretation and analysis of data Mixed methods Triangulation Reliability and validity Reflections in a broken mirror: Pragmatic and imperfect solutions to an intractable problem

An extensive body of knowledge exists on network outcomes and on how network structures may contribute to the creation of outcomes at different levels of analysis, but less attention has been paid to understanding how and why organizational networks emerge, evolve, and change. Improved understanding of network dynamics is important for several reasons, perhaps the most critical being that the understanding of network outcomes is only partial without an appreciation of the genesis of the network structures that resulted in such outcomes. To provide a context for the papers in this special issue, and with the broader goal of furthering network dynamics research, we present a framework that begins by discussing the meaning and role of network dynamics and goes on to identify the drivers and key dimensions of network change as well as the role of time in this process. We conclude with theoretical and methodological issues that researchers need to address in this domain.

We present a comprehensive review of the evolutionary design of neural network architectures. This work is motivated by the fact that the success of an Artificial Neural Network (ANN) highly depends on its architecture and among many approaches Evolutionary Computation, which is a set of global-search methods inspired by biological evolution has been proved to be an efficient approach for optimizing neural network structures. Initial attempts for automating architecture design by applying evolutionary approaches start in the late 1980s and have attracted significant interest until today. In this context, we examined the historical progress and analyzed all relevant scientific papers with a special emphasis on how evolutionary computation techniques were adopted and various encoding strategies proposed. We summarized key aspects of methodology, discussed common challenges, and investigated the works in chronological order by dividing the entire timeframe into three periods. The first period covers early works focusing on the optimization of simple ANN architectures with a variety of solutions proposed on chromosome representation. In the second period, the rise of more powerful methods and hybrid approaches were surveyed. In parallel with the recent advances, the last period covers the Deep Learning Era, in which research direction is shifted towards configuring advanced models of deep neural networks. Finally, we propose open problems for future research in the field of neural architecture search and provide insights for fully automated machine learning. Our aim is to provide a complete reference of works in this subject and guide researchers towards promising directions.

Tandemly repeated non-coding sequences, widely known as satellite DNAs (satDNAs), are extremely diverse and highly variable components of eukaryotic genomes. In recent years, advances in high-throughput sequencing and new bioinformatics platforms have enabled in-depth studies of all (or nearly all) tandem repeats in any genome (the satellitome), while a growing number of telomere-to-telomere assemblies facilitates their detailed mapping. Research performed on a large number of non-model plant and animal species changed significantly the “classical” view on these sequences, both in an organizational and functional sense, from ballast compacted in the form of heterochromatin to elements that are important for structuring the entire genome, as well as for its functions and evolution. The diversity of repeat families, and the complexity of their intraspecies and interspecies distribution patterns, posed new questions, urging for species-by-species comparative analyses. Here we integrate some basic features of different forms of sequences repeated in tandem and rapidly growing data evidencing extensive dispersal of satDNA sequences in euchromatin, their putative roles and evolutionary significance. Importantly, we also present and discuss various issues brought on by the use of new methodological approaches and point out potential threats to the analysis of satDNAs and satellitomes.

The rise in the West of religious unbelief and its sometimes companions, relativism and nihilism, has been widely noted. Dostoyevsky’s famous dictum, “Without God, everything is permissible,” has in many quarters been taken as more recommendation than warning. The causes behind this trend are surely complex, but a key accelerant appears to have been the triumph of Darwin’s theory of evolution, in its original and now updated forms. Taken to its logical conclusions, the theory, together with part of its methodological apparatus (methodological naturalism), would seem to drain physical reality of meaning and humans of free will, significance, and higher purpose. Atheist philosopher Daniel Dennett called it a “universal acid.” The subject is one that could fill many books. One manageable way of rendering the subject manageable in a single paper is by considering key narratives that buttress Darwinian theory and by tracing the theory’s impact on the narrative arts of literature and film. How have Christians in the academy responded to modern evolutionary theory’s impact on the culture? One response has been to graft it onto Christianity in the hopes of neutralizing the theory’s more pernicious cultural implications. In practice, such attempts have tended to fundamentally alter either modern evolutionary theory or Christianity or both. Before attempting any such union, we would do well to revisit the foundations of the theory.

A fundamental problem in the field of the social studies of science is how to measure the patterns of international scientific collaboration to analyse the structure and evolution of scientific fields. This study here confronts the problem by developing an allometric model of morphological changes in order to measure and analyse the relative growth of international research collaboration in comparison with domestic collaboration only for fields of science. Statistical analysis, based on data of internationally co-authored papers from National Science Foundation (1997–2012 period), shows an acceleration (a disproportionate relative growth) of collaboration patterns in medical sciences, social sciences, geosciences, agricultural sciences, and psychology (predominantly applied fields). By contrast, some predominantly basic fields, including physics and mathematics, have lower levels of relative growth in international scientific collaboration. These characteristics of patterns of international research collaboration seem to be vital contributing factors for the evolution of the social dynamics and social construction of science. The main aim of this article is therefore to clarify the on-going evolution of scientific fields that might be driven by the plexus (interwoven combination of parts in a system) of research disciplines, which generates emerging research fields with high growth rates of international scientific collaboration.

Over the past decade, numerous studies have suggested that plant genomes have been substantially influenced by interkingdom horizontal gene transfer (iHGT). Although the prevalence of this process in eukaryotes—particularly in multicellular organisms—remains an active area of discussion, many reported plant iHGT candidates have not always been examined in light of alternative evolutionary explanations. This raises the possibility that the contribution of iHGT to plant genome evolution may be less pervasive than currently proposed. In this perspective article, we revisit the evidence commonly used to support iHGT in plants and consider plausible alternative scenarios that could generate similar phylogenetic patterns. We also outline key limitations of the methods currently used to detect iHGT and suggest directions for improving future analyses. Our goal is to encourage careful evaluation of the criteria applied to infer iHGT and to promote a balanced view of its potential impact on plant genome evolution.