Predicting green: really radical (plant) predictive processing

In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly

Swarming Behavior in Plant Roots

Interactions between individuals that are guided by simple rules can generate swarming behavior. Swarming behavior has been observed in many groups of organisms, including humans, and recent research has revealed that plants also demonstrate social behavior based on mutual interaction with other individuals. However, this behavior has not previously been analyzed in the context of swarming. Here, we show that roots can be influenced by their neighbors to induce a tendency to align the directions of their growth. In the apparently noisy patterns formed by growing roots, episodic alignments are observed as the roots grow close to each other. These events are incompatible with the statistics of purely random growth. We present experimental results and a theoretical model that describes the growth of maize roots in terms of swarming

Composição florística e estrutura da comunidade de plantas do estrato herbáceo em áreas de cultivo de árvores frutíferas

O objetivo do presente trabalho foi caracterizar, em três épocas, a comunidade de plantas presentes em áreas de cultivo de abacateiro e de nogueira pecan, localizadas na Fazenda Experimental Lageado, da FCA-UNESP, município de Botucatu-SP. Em decorrência da arquitetura da copa e do caráter decíduo das nogueiras, esta área apresenta-se mais ensolarada, o que produz condições ambientais diferentes entre as duas áreas estudadas. Foi estabelecida uma grade retangular composta de 55 parcelas quadradas, contíguas, com 5 m de lado, havendo 40 parcelas sob os abacateiros e 15 sob as nogueiras. As coletas foram realizadas em março, maio e agosto de 1993, quando foram sorteados quadrados de 1x 1 m em cada parcela, de forma a não haver coincidência entre as amostragens realizadas em cada época. Foram levantadas as espécies ocorrentes, sua porcentagem de cobertura e freqüência. Os dados foram analisados através de métodos multivariados, utilizando-se a Análise de Agrupamento para as seis situações (3 épocas x 2 ambientes). Foram coletadas, no total, 54 espécies, distribuídas em 38 gêneros e 19 famílias, sendo Asteraceae e Poaceae as que contribuíram com o maior número de espécies. A riqueza em espécies foi maior na área sob as nogueiras; em ambas as áreas, a riqueza foi maior na estação úmida. Sob os abacateiros, a porcentagem de cobertura total da comunidade apresentou pouca variação temporal, diferindo da área sob as nogueiras onde se observou flutuação deste parâmetro. O padrão de distribuição espacial, para quase todas as populações, foi do tipo agrupado. A similaridade florística foi maior entre as duas áreas dentro de cada época de coleta. A presença constante de espécies como Commelina nudiflora que contribuiu com valores elevados de cobertura nas três épocas de coleta, mostra a necessidade de utilizar métodos de controle permanentes na área do pomar estudado.The main goal of this study was to describe the floristic composition and the community structure of the vegetation under avocado and pecan trees growing at Fazenda Experimental Lageado, FCA -UNESP, Botucatu -SP, Brazil. The studied areas differ in relation to light exposure conditioned by canopy architecture and pecan leaf deciduousness. A rectangular frame measuring 25 x 55 m was divided in 55 quadrats of 5 x 5 m. Forty quadrats were located under avocado trees and 15 under pecan trees. Frequency and percentage weed cover were estimated in both conditions at March, May and August 1993. Quadrats of 1 x 1 m were randomly assigned to a new area within each plot, each month. A Cluster Analysis was performed with six experimental groups (3 sampling dates x environmental conditions). Fifty four species, 38 genera and 19 families were recorded in total. Asteraceae and Poaceae had greater number of species. Species richness was greater at pecan tree community. In both areas, the richness was greater at the wet season. Total percentage of weed cover showed small variation only under the avocado trees during the study period. Most populations showed an aggregate distribution pattern. Floristic similarity was greater among the two areas at each sampling period. Commelina nudiflora and some other weed species had high cover values during all the study period. Therefore, a continuous weed control is indicated to the studied orchard

Signal processing and transduction in plant cells: the end of the beginning?

Plants have a very different lifestyle to animals, and one might expect that unique molecules and processes would underpin plant-cell signal transduction. But, with a few notable exceptions, the list is remarkably familiar and could have been constructed from animal studies. Wherein, then, does lifestyle specificity emerge

Exploring the complex information processes underlying plant behavior

Newly discovered plant behaviors, linked to historical observations, contemporary technologies, and emerging knowledge of signaling mechanisms, argue that plants utilize complex information processing systems. Plants are goal-oriented in an evolutionary and physiological sense; they demonstrate agency and learning. While most studies on plant plasticity, learning, and memory deal with the responsiveness of individual plants to resource availability and biotic stresses, adaptive information is often perceived from and coordinated with neighboring plants, while competition occurs for limited resources. Based on existing knowledge, technologies, and sustainability principles, climate-smart agricultural practices are now being adopted to enhance crop resilience and productivity. A deeper understanding of the dynamics of plant behavior offers a rich palette of potential amelioration strategies for improving the productivity and health of natural and agricultural ecosystems

Physiologically mediated self/non-self discrimination in roots

Recent evidence suggests that self/non-self discrimination exists among roots; its mechanisms, however, are still unclear. We compared the growth of Buchloe dactyloides cuttings that were grown in the presence of neighbors that belonged to the same physiological individual, were separated from each other for variable periods, or originated from adjacent or remote tillers on the same clone. The results demonstrate that B. dactyloides plants are able to differentiate between self and non-self neighbors and develop fewer and shorter roots in the presence of other roots of the same individual. Furthermore, once cuttings that originate from the very same node are separated, they become progressively alienated from each other and eventually relate to each other as genetically alien plants. The results suggest that the observed self/non-self discrimination is mediated by physiological coordination among roots that developed on the same plant rather than allogenetic recognition. The observed physiological coordination is based on an as yet unknown mechanism and has important ecological implications, because it allows the avoidance of competition with self and the allocation of greater resources to alternative functions