Biology subjects

Tverskoi, D.

Publications and source records attributed to Tverskoi, D..

3 recordsLinked to original sources

bioRxiv2025

Signatures of adaptive self-organization detected in swidden societies worldwide

Quantitative signatures of adaptive self-organization and the spatial scale of human management can be detected in anthropogenic landscapes. Yet, while abundant evidence for self-organization in physical and natural systems exists, there are few adaptive self-organization models that can explain coupled dynamics of human subsistence systems that have also been rigorously validated. Here, we analyze over 18,000 forest patches extracted from 18 remotely-sensed swidden mosaics from tropical and subtropical regions across the planet. We discover a power law signature of adaptive self-organization in the size of the patches and correlation distances that indicate the spatial scale of socioecological adaptation. To explain this pattern, we propose a mathematical model of swidden labor reciprocity, normative reasoning, field placement, forest disturbance and regrowth dynamics that explains the emergent spatial structure of swidden mosaics. Social self-organization can promote sustainable levels of forest disturbance when ecological dynamics such as facilitation, seed-dispersal and competition are conditioned by social dynamics, giving rise to power-law land-use patterns. We use simulations to explore the emergent properties of the model and identify two regimes: deforestation and sustainable swidden. When we analyze the relationship between the simulation results in the remote sensing data, we find that 16/18 of the study areas exhibit power-law distributions and spatial correlation patterns that match the sustainable swidden regime in the model. These findings support the hypothesis that adaptive self-organization may be a general characteristic of coupled human and natural systems.

ecology↗

bioRxiv2024

A complex adaptive systems model of labor reciprocity and normative reasoning in swidden agriculture

Swidden (aka "slash-and-burn") agriculture is a prototypical coupled human and natural system and understanding the social, cultural, and environmental factors shaping the trajectories of swidden forests is essential to mitigate climate change and ensure equitable collaboration between scientists, planners, and Indigenous communities. Despite this, mathematical models integrating its social and ecological dynamics are rare. Here, we use complex adaptive systems theory to develop a model where individuals rely on labor exchange driven by reciprocity, and on normative reasoning that can lead to sanctions. Our results identify three emergent regimes: low-intensity swidden, sustainable high-intensity swidden that maximizes ecosystem services and harvest returns, and deforestation. We show that sustainable high-intensity swidden evolves if labor reciprocity and normative reasoning are balanced: helping behavior should be significantly conditioned by normative reasoning to prevent over-harvesting, while reciprocity is necessary to prevent excessive sanctioning. We find that the sustainable high-intensity swidden regime is robust to changes in group size, is resilient to environmental shocks, can evolve under various models of forest ecology, and is most productive for both forests and farmers when the balance of labor reciprocity and normative reasoning results in an intermediate scale of forest disturbance. Overall, we illuminate the importance of Indigenous social norms and customary practices related to swidden labor in maintaining sustainable and intensive swidden agriculture.

ecology↗

bioRxiv2021

The evolution of germ-soma specialization under different genetic and environmental effects

Division of labor exists at different levels of biological organization - from cell colonies to human societies. One of the simplest examples of the division of labor in multicellular organisms is germ-soma specialization, which plays a key role in the evolution of organismal complexity. Here we formulate and study a general mathematical model exploring the emergence of germ-soma specialization in colonies of cells. We consider a finite population of colonies competing for resources. Colonies are of the same size and are composed by asexually reproducing haploid cells. Each cell can contribute to activity and fecundity of the colony, these contributions are traded-off. We assume that all cells within a colony are genetically identical but gene expression is affected by variation in the microenvironment experienced by individual cells. Through analytical theory and evolutionary agent-based modeling we show that the shape of the trade-off relation between somatic and reproductive functions, the type and extent of variation in within-colony microenvironment, and, in some cases, the number of genes involved, are important predictors of the extent of germ-soma specialization. Specifically, increasing convexity of the trade-off relation, the number of different environmental gradients acting within a colony, and the number of genes (in the case of random microenvironmental effects) promote the emergence of germ-soma specialization. Overall our results contribute towards a better understanding of the role of genetic, environmental, and microenvironmental factors in the evolution of germ-soma specialization.

evolutionary biology↗