Sensitivity analysis for time varying ecological networks

Gonzalo Robledo

Exploring the importance of aromatic plants' extrafloral volatiles for pollinator attraction

Kantsa et al., 2025

Aromatic plants occur in many plant lineages and have widespread ethnobiological significance. Yet, the ecological significance and evolutionary origins of aromatic volatile emissions remain uncertain. Aromatic emissions have been implicated in defensive interactions but may also have other important functions. In this Viewpoint article, we propose an ecologically relevant definition for the aromatic phenotype and evaluate available evidence relating to the ecological role of aromatic emissions, focusing specifically on their role in pollinator attraction. We synthesize available literature addressing the use of extrafloral volatiles by pollinators, including evidence that aromatic plant emissions are primary foraging cues for some species, and present new behavioral findings documenting bee attraction to the aromatic lemon thyme in the absence of flowers. We highlight recent ecological research showing that aromatic species are highly influential in Mediterranean plant–pollinator communities and their emissions predict key interactions, particularly with bees. Based on the available evidence, we hypothesize that aromatic plants represent a form of chemical aposematism, wherein high levels of constitutive defense enable signaling phenotypes that convey information to both potential antagonists and mutualists. Finally, we outline future research priorities to clarify the role of aromatic emissions in information ecology and explore their application in agricultural systems.

https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.70496

Threats to conservation from artificial-intelligence-generated wildlife images and videos 

Guerrero-Casado et al., 2025

Cada vez son más frecuentes los videos de animales generados por IA ¿Cuáles son las consecuencias de esto? Este es precisamente en tema que se trabaja en el artículo. 

Resumen generado por IA del artículo:

Vínculo al articulo: 

https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/cobi.70138

Vínculos a algunos videos de comportamientos animales generados por IA. Algunos claramente falsos, otros más engañosos:

https://www.instagram.com/reel/DQ8rZoGiLSo/?igsh=MXgwbWpjMTJzaHFxcg==

https://www.instagram.com/reel/DPo3oIIDsOn/?igsh=MWhvaXgyNms2N2dzbQ==

https://www.instagram.com/reel/DRIMz7xFhE0/?igsh=MTV1MGFnaTdueno4eA==

https://www.instagram.com/reel/DRHs-ulDRbD/?igsh=MXV3Mmw1d3JlanpqdA==

https://www.instagram.com/reel/DRC430-kQFH/?igsh=Z24yZ3kyMHl3bmd1

https://www.instagram.com/reel/DQjlez9inh0/?igsh=MWU4NHBlMGFhOGV3

https://www.instagram.com/reel/DPG8vQ1EpOx/?igsh=MXV6b2Y3OW1qeDR3bg==

https://www.instagram.com/reel/DP1lkC4DRiP/?igsh=MXg0NDVnNGRvcXNzdA==

https://www.instagram.com/reel/DQjv_pYE-lm/?igsh=MWFydnZ4cHBhYjQ0dg==

https://www.instagram.com/reel/DQgZ5V9CWMv/?igsh=MWNha2Q4cnhjd3pwNA==

https://www.instagram.com/reel/DQ6T20Wijpf/?igsh=MXZvZnU0bTkxejg0ZQ==

https://www.instagram.com/reel/DQGTBBhjE-J/?igsh=b2ZobjJzcHpxNmZ6

https://www.instagram.com/reel/DP-AxJICC6m/?igsh=Y2g5eTI2cGYxb2Jm

https://www.instagram.com/reel/DQw05CViMQE/?igsh=MTI1dGd6NmpsNDRqZg==

https://www.instagram.com/reel/DPyRrFCjMNH/?igsh=ZjFib3RjbHVma2Vh

https://www.instagram.com/reel/DQ94EFEDlPe/?igsh=MTgyMWY2dWo5ZWt4bA==

https://www.instagram.com/reel/DRChYI0lVrG/?igsh=MXZ4MHlmOTQwZjFjdQ==

https://www.instagram.com/reel/DP1UHr4k4aO/?igsh=MTlkN3B5bXp0NDR3dA==

https://www.instagram.com/reel/DQ7V2JTgSbi/?igsh=azU2aGpiN3k0aWJz

https://www.instagram.com/reel/DRF07uajRzI/?igsh=MTllZXVvdXh0eXFhaw==

https://www.instagram.com/reel/DRARE25EjIj/?igsh=bG0wd3B6bGVvZDd3

https://www.instagram.com/reel/DPbkwKoDJhx/?igsh=NTl0NXBwNWo4ajVi

Entanglements of art and ecology 

Ros Gray

 A diverse and distinct microbiome inside living trees

Arnold et al., preprint

Despite significant advances in microbiome research across various environments, the microbiome of Earth’s largest biomass reservoir– the wood of living trees– remains largely unexplored. This oversight neglects a critical aspect of global biodiversity and potentially key players in tree health and forest ecosystem functions. Here we illuminate the microbiome inhabiting and adapted to wood, and further specialized to individual host species. We demonstrate that a single tree can host approximately a trillion microbes in its aboveground internal tissues, with microbial communities partitioned between heartwood and sapwood, each maintaining a distinct microbiome with minimal similarity to other plant tissues or nearby ecosystem components. Notably, the heartwood microbiome emerges as a unique ecological niche, distinguished in part by endemic archaea and anaerobic bacteria that drive consequential biogeochemical processes. Our research supports the emerging idea of a plant as a “holobiont”—a single ecological unit comprising host and associated microorganisms—and parallels human microbiome research in its implications for host health, disease, and functionality. By mapping the structure, composition, and potential sources and functions of the tree internal microbiome, our findings pave the way for novel insights into tree physiology and forest ecology, and establish a new frontier in environmental microbiology.

Overview of the black oak (Quercus velutina) prokaryotic microbiome. a.) Relative abundance of the top 9 prokaryotic classes (all other classes grouped in beige) in the a) bark, b) sapwood, c) heartwood, d) fine roots, e) coarse roots, f) mineral soil, g) organic soil, h) leaf litter, i) heart-rot, j) branches, and k) leaves. Source-tracking percent estimations (out of 1 or 100%) for microbial contribution from neighboring sites to the b.) heartwood and c.) sapwood microbiomes, based on FEAST analyses (taxa agglomerated at the species level). Mean value represented by the colored dot; SE represented by the bar. d.) Principal coordinate analysis for black oak tissues and surrounding environments, based on weighted UniFrac distance, with dashed lines converging on the centroid for each sample type.

https://www.biorxiv.org/content/10.1101/2024.05.30.596553v1

Discover network dynamics with neural symbolic regression

Yu et al., 2025

Discovering network dynamics—automatically

Complex systems are everywhere: from ecosystems and gene networks to epidemics and social behavior. Each consists of many interacting components whose collective dynamics are notoriously difficult to model. Traditionally, scientists have relied on intuition and simplified equations—but for most real systems, the governing laws remain unknown.

Zihan Yu, Jingtao Ding & Yong Li  introduce ND2, a neural symbolic regression framework that discovers network dynamics directly from data. The key insight is to reduce the overwhelming search space of possible equations—normally exploding with the number of nodes—to an equivalent one-dimensional symbolic problem. ND2 combines graph neural networks and transformers (via a pretrained model called NDformer) with Monte Carlo tree search to automatically uncover concise, interpretable formulas that explain how networks evolve.

Applied to ten benchmark systems, ND2 correctly recovered the governing equations of classics such as Kuramoto oscillators, FitzHugh–Nagumo neurons, and Lotka–Volterra populations. More impressively, when tested on real data, it corrected existing biological models—reducing prediction errors by 60% in gene regulation and 56% in microbial communities—by revealing hidden higher-order interactions. In epidemic networks, ND2 uncovered transmission laws that explain cross-country differences in intervention effects and even captured the same power-law patterns across scales.

This study demonstrates how machine-driven discovery can bridge observational data and theoretical understanding, advancing complexity science from describing what we observe to deriving why it happens—directly from the data itself.

Abstract:

Network dynamics are fundamental to analyzing the properties of high-dimensional complex systems and understanding their behavior. Despite the accumulation of observational data across many domains, mathematical models exist in only a few areas with clear underlying principles. Here we show that a neural symbolic regression approach can bridge this gap by automatically deriving formulas from data. Our method reduces searches on high-dimensional networks to equivalent one-dimensional systems and uses pretrained neural networks to guide accurate formula discovery. Applied to ten benchmark systems, it recovers the correct forms and parameters of underlying dynamics. In two empirical natural systems, it corrects existing models of gene regulation and microbial communities, reducing prediction error by 59.98% and 55.94%, respectively. In epidemic transmission across human mobility networks of various scales, it discovers dynamics that exhibit the same power-law distribution of node correlations across scales and reveal country-level differences in intervention effects. These results demonstrate that machine-driven discovery of network dynamics can enhance understandings of complex systems and advance the development of complexity science.

https://www.nature.com/articles/s43588-025-00893-8

Rafael Araujo

GEOMETRY/Flight

http://rafael-araujo.com

AI is helping to decode animals’ speech. Will it also let us talk with them?

Rachel Fieldhouse

Deep in the rainforests of the Democratic Republic of the Congo, Mélissa Berthet found bonobos doing something thought to be uniquely human.

During the six months that Berthet observed the primates, they combined calls in several ways to make complex phrases1. In one example, bonobos (Pan paniscus) that were building nests together added a yelp, meaning ‘let’s do this’, to a grunt that says ‘look at me’. “It’s really a way to say: ‘Look at what I’m doing, and let’s do this all together’,” says Berthet, who studies primates and linguistics at the University of Rennes, France.

In another case, a peep that means ‘I would like to do this’ was followed by a whistle signalling ‘let’s stay together’. The bonobos combine the two calls in sensitive social contexts, says Berthet. “I think it’s to bring peace.”

The study, reported in April, is one of several examples from the past few years that highlight just how sophisticated vocal communication in non-human animals can be. In some species of primate, whale and bird, researchers have identified features and patterns of vocalization that have long been considered defining characteristics of human language. These results challenge ideas about what makes human language special — and even how ‘language’ should be defined.

Perhaps unsurprisingly, many scientists turn to artificial intelligence (AI) tools to speed up the detection and interpretation of animal sounds, and to probe aspects of communication that human listeners might miss. “It’s doing something that just wasn’t possible through traditional means,” says David Robinson, an AI researcher at the Earth Species Project, a non-profit organization based in Berkeley, California, that is developing AI systems to decode communication across the animal kingdom.

As the research advances, there is increasing interest in using AI tools not only to listen in on animal speech, but also to potentially talk back.

Continue reading:

https://www.nature.com/articles/d41586-025-02917-9

Common mycorrhizal networks facilitate plant disease resistance by altering rhizosphere microbiome assemblyAuthor links open overlay panel

Zhang et al., 2025

Arbuscular mycorrhizal fungi can interconnect the roots of individual plants by forming common mycorrhizal networks (CMNs). These symbiotic structures can act as conduits for interplant communication. Despite their importance, the mechanisms of signal transfer via CMNs and their implications for plant community performance remain unknown. Here, we demonstrate that CMNs act as a pathway to elicit defense responses in healthy receiver plants connected to pathogen-infected donors. Specifically, we show that donor plants infected by the phytopathogen Botrytis cinerea transfer jasmonic acid via CMNs, which then act as a chemical signal in receiver plants. This signal transfer to receiver plants induces shifts in root exudates, promoting the recruitment of specific microbial taxa (Streptomyces and Actinoplanes) that are directly linked to the suppression of B. cinerea infection. Collectively, our study reveals that CMNs act as interplant chemical communication conduits, transferring signals that contribute to plant disease resistance via modulation of the rhizosphere microbiota.

https://www.sciencedirect.com/science/article/pii/S1931312825003427

Meta-analysis shows that planting nitrogen-fixing species increases soil organic carbon stock

Sun et al., 2025

Nitrogen (N)-fixing species are widely used in forestation and agriculture. The effects of planting N-fixing species on soil organic carbon (SOC) stock, however, remain uncertain, limiting policy development and their application towards a possible climate change mitigation strategy. Here we conduct a global meta-analysis of 385 datapoints from 136 studies comparing SOC stock with planting N-fixing versus non-N-fixing species. Planting N-fixing species increases SOC stock by 16% compared with non-N-fixing species. This SOC increase is closely accompanied by soil N increases, with an average accumulation of 7.8 g of SOC per gram of soil N increase. Climate mediates SOC responses, with greater SOC sequestration observed in drier and warmer regions, particularly in the tropics. We estimate that an additional increase of 0.29–0.75 PgC yr−1 in global SOC stock could be achieved by adopting N-fixing species for forestation, agriculture and regeneration of marginal lands, highlighting their potential for climate change mitigation.

Global distribution of the selected studies testing the effects of planting N-fixing species on SOC stock in this meta-analysis. Green and orange dots represent the geographic locations of studies on tree and crop planting, respectively. The green and orange shaded areas show the distribution ranges of planted forests and croplands, respectively. Inset: the distribution of the sites in the global biomes based on climatic conditions: MAT and MAP. Black dots indicate study sites in this meta-analysis.

https://www.nature.com/articles/s41559-025-02861-x.epdf

Advances in microbial based bio-inoculum for amelioration of soil health and sustainable crop production

Samantaray et al., 2024

The adoption of sustainable agricultural practices is increasingly imperative in addressing global food security and environmental concerns, with microbial based bio-inoculums emerging as a promising approach for nurturing soil health and fostering sustainable crop production.This review article explores the potential of microbial based bio-inoculumsor biofertilizers as a transformative approach to enhance plant disease resistance and growth. It explores the commercial prospects of biofertilizers, highlighting their role in addressing environmental concerns associated with conventional fertilizers while meeting the growing demand for eco-friendly agricultural practices. Additionally, this review discusses the future prospects of biofertilizers, emphasizing the ongoing advancements in biotechnology and formulation techniques that are expected to enhance their efficacy and applicability. Furthermore, this article provides insights into strategies for the successful acceptance of biofertilizers among farmers, including the importance of quality control, assurance, and education initiatives to raise awareness about their benefits and overcome barriers to adoption. By synthesizing the current research findings and industrial developments, this review offers valuable guidance for stakeholders seeking to exploit the potential of biofertilizers or beneficial microbes to promote soil health, ensure sustainable crop production, and addressing the challenges of modern agriculture.

https://www.sciencedirect.com/science/article/pii/S2666517424000336

Mutualism provides a basis for biodiversity in eco-evolutionary community assembly

Gui Araujo,Miguel Lurgi

Ecological communities are considerably more complex than simple collections of species sharing the same environment. The large number of ecological interactions among species drives changes in populations through time that dictate the persistence of the entire community. Most research into the mechanisms of biodiversity considers different interaction types (mutualism, competition, consumer-resource) in isolation in either ecological or evolutionary contexts. In this study, we developed a community growth model that incorporates mutualism, competition, and consumer-resource interactions and considers both ecological and evolutionary mechanisms of assembly together. We found that communities formed via evolutionary speciation can reach higher species richness and exhibit greater proportions of mutualistic interactions than purely ecological models, resulting in more complex community structures. High levels of mutualism lead to communities more resilient to disturbances, such as the arrival of new species or sudden changes in abundances. Our research extends previous efforts by aiming to understand how evolutionary processes shape the diversity of ecological interactions and the role of these interactions in species persistence. Such knowledge is essential for preserving and restoring ecosystems in the face of growing environmental degradation.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013402

Natural selection

Paul Nurse

Application of microbial inoculants significantly  enhances crop productivity: A meta-analysis of studies from 2010 to 2020

Li et al, 2022

Abstract

Introduction

With the rapid development of microbial technology, microbial inoculant is considered as a promising tool in sustainable agricultural systems. Mechanisms by which microbial inoculants improve crop yield include improving plant nutrient availability and alleviating abiotic/biotic stresses (e.g., drought, salt and disease). However, the field efficacy of microbial inoculants remains inconsistent, which constrains large-scale adoptions. Identity of dominant mechanisms that underpin the positive impacts of different microbial inoculants is limited. Thus, a comprehensive quantitative assessment of known inoculants on crop performance is needed to provide guidance for the development of effective microbial tools from both research and commercial perspectives.

Materials and Methods

Based on 97 peer-reviewed publications, we conducted a meta-analysis to quantify the benefits of different microbial inoculants on crop yield, and to identify the key mechanisms that underpin enhanced crop yield.

Results

Result showed that (i) alleviation of stresses was the major mechanism (53.95%, n = 53) by which microbial inoculants enhance crop yield, while improving plant nutrient availability accounted for 22.25% (n = 58) of crop yield enhancement. (ii) Pseudomonas was the most effective microbial inoculant in enhancing crop yield through alleviating stresses (63.91%, n = 15), whereas Enterobacter was the most effective in improving plant nutrient availability (27.12%, n = 5). (iii) Considering both mechanisms together, Pseudomonas (49.94%, n = 21), Enterobacter (27.55%, n = 13) and Bacillus (25.66%, n = 32) were the largest sources of microbial inoculants to enhance crop yield, and the combination of diazotroph Burkholderia with its legume host had the highest effect on improving the yield (by 196.38%). Microbial inoculants also improve nutritional quality by enhancing mineral contents in the produce.

Conclusion

Our analysis provides evidence that microbial inoculants can enhance agricultural productivity and nutritional quality and can be used either alone or in combination with reduced amount of agrochemicals to promote sustainable agriculture.

https://onlinelibrary.wiley.com/doi/full/10.1002/sae2.12028

Revisiting the cry-for-help hypothesis in plant–microbe interactions

Tharp et al., 2025

The ‘cry-for-help hypothesis’ (CHH) is broadly used to study how root exudate modulation under stress influences recruitment of beneficial microbes in the rhizosphere. Here, we explored common misconceptions and limitations of the CHH and advocate for the reassessment of this prevalent hypothesis to unfold the ecological complexities of plant–microbe interactions.

https://www.cell.com/trends/plant-science/abstract/S1360-1385(25)00223-7

Linalool-triggered plant-soil feedback drives defense adaptation in dense maize plantings

Guo et al., 2025

Structured Abstract

INTRODUCTION

Planting crops more densely increases overall yields, but it also raises the risk of pest and pathogen outbreaks. Although plants can modify their architecture to adapt to crowded conditions, how they adjust their immune responses remains largely unknown. Understanding how plants manage these trade-offs is critical for sustainable agriculture, especially in the context of increasing global food demands.

RATIONALE

Plants release chemical cues, such as volatiles, that inform neighbors of environmental conditions. One such compound, linalool, is a constitutively emitted leaf volatile in maize and other grasses. We hypothesized that linalool could act as a signal in densely planted fields, triggering plant-soil feedback that prepares neighboring plants for potential biotic stress. We explored how linalool shapes root signaling, soil microbiota, and ultimately plant defense and growth.

RESULTS

Field surveys revealed that maize plants in the inner rows of densely planted fields suffered less herbivore damage than those at the edges but that they also had reduced growth. Laboratory soil–transplantation experiments confirmed that soils conditioned by high-density plantings decreased plant biomass while enhancing resistance to insects, nematodes, and pathogens. These effects extended across genotypes and species.

Volatile profiling identified linalool as a key compound increasing with planting density. Exposure of maize to synthetic linalool reproduced the feedback effects, which required the presence of a living plant. Mechanistically, linalool activated jasmonate signaling in roots and up-regulated genes that drive the biosynthesis and exudation of the specialized metabolite HDMBOA-Glc. This exudate reshaped the rhizosphere microbiome, selectively enriching bacteria that suppressed plant growth but increased resistance in subsequently grown plants. Soil sterilization and microbial inoculation confirmed that these microbes were essential for the feedback loop.

In plants grown in linalool-conditioned soil, defense-related signaling, particularly salicylic acid signaling, was up-regulated, whereas growth-promoting metabolic pathways were down-regulated. Plants lacking salicylic acid signaling did not show growth-defense trade-offs, confirming salicylic acid’s role in expressing the feedback-triggered defense.

CONCLUSION

This study uncovers a volatile-triggered feedback mechanism through which maize adapts its defense in crowded environments. The constitutive emission of linalool primes neighboring plants by activating root jasmonate signaling, promoting HDMBOA-Glc exudation, and altering the rhizosphere microbiome. This, in turn, leads to elevated defense and suppressed growth in subsequent plants through salicylic acid signaling. These findings shed light on how plants integrate aboveground cues and belowground processes to optimize defense in high-density settings. Harnessing this natural defense pathway through breeding, microbial inoculants, or synthetic biology could enable the development of crops that are more resilient and require fewer chemical inputs.

https://www.science.org/doi/10.1126/science.adv6675

The Bird and The Tree 

Cornell Lab of Ornithology

Law of complexity  

Robert Hazen and Michael Wong

Plant sap analysis

Joel Williams

Maximum Entropy is a Foundation for Complexity Science

John Harte

 CÓMO GENERAR CRÉDITOS DE CARBONO

 The Hive Architect | Saving Britain's Wild Bees

 Myth of the Machine: Lewis Mumford

Farmer-led Research on Europe’s Full Productivity

This report presents the results of the first phase of European Alliance for Regenerative Agriculture (EARA) ongoing farmer-led research program, introducing a groundbreaking way to measure real-world agricultural success through the Regenerating Full Productivity (RFP) index. Developed with and for farmers, the RFP captures both agronomic and ecological performance in a single, practical tool.

Tested across 14 countries from 2021 to 2023, this first phase reveals compelling results:

• +33% higher full productivity on average, with gains up to 52.

• Stronger ecosystem performance, with over 25% more photosynthesis, 24% more soil cover, and 16% greater plant diversity.

• Yield parity with major input reduction: Regenerating farms achieved, on average, only a 2% lower yield (in kilocalories and protein), while using 61% less synthetic nitrogen fertiliser and 75% less pesticides and making 20% higher gross margin per hectare.

• Regional food sovereignty: While average EU farms import over 30% of livestock feed from outside the EU, pioneering farmers achieved similar yields using feed exclusively from Europe.

Full Report:

https://eara.farm/wp-content/uploads/EARA_Farmer-led-Research-on-Europes-Full-Productivity_2025_06_03.pdf

Impacts of climate change on global agriculture accounting for adaptation

Hultgren et al., 2025

Climate change threatens global food systems, but the extent to which adaptation will reduce losses remains unknown and controversial. Even within the well-studied context of US agriculture, some analyses argue that adaptation will be widespread and climate damages small, whereas others conclude that adaptation will be limited and losses severe. Scenario-based analyses indicate that adaptation should have notable consequences on global agricultural productivity, but there has been no systematic study of how extensively real-world producers actually adapt at the global scale. Here we empirically estimate the impact of global producer adaptations using longitudinal data on six staple crops spanning 12,658 regions, capturing two-thirds of global crop calories. We estimate that global production declines 5.5 × 1014 kcal annually per 1 °C global mean surface temperature (GMST) rise (120 kcal per person per day or 4.4% of recommended consumption per 1 °C; P < 0.001). We project that adaptation and income growth alleviate 23% of global losses in 2050 and 34% at the end of the century (6% and 12%, respectively; moderate-emissions scenario), but substantial residual losses remain for all staples except rice. In contrast to analyses of other outcomes that project the greatest damages to the global poor, we find that global impacts are dominated by losses to modern-day breadbaskets with favourable climates and limited present adaptation, although losses in low-income regions losses are also substantial. These results indicate a scale of innovation, cropland expansion or further adaptation that might be necessary to ensure food security in a changing climate.

a–f, Colours indicate central estimate in a high-emissions scenario (RCP 8.5), net of adaptation costs and benefits, for maize (a), soybean (b), rice (c), wheat (d), cassava (e) and sorghum (f) for 2089–2098. Projections computed for 24,378 subnational units relative to counterfactual yields, uncropped regions are shaded in grey. Wheat shows winter wheat and spring wheat projections combined, weighted by their area share in each region. Estimates in each location are ensemble means across climate and statistical uncertainty. Incomes from SSP3.

https://www.nature.com/articles/s41586-025-09085-w