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Biology
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Adaptation of Living Species to Environmental Stress (2nd Edition)
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Adaptation of Living Species to Environmental Stress (2nd Edition)

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Ecology".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 805

Special Issue Editors

Dr. Mario Pagano

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Guest Editor
Institute of Research on Terrestrial Ecosystems (IRET), National Research Council (CNR), Via Madonna del Piano 10, 50019 Sesto Fiorentino, FI, Italy
Interests: plant biology; food security; THz imaging; enzyme; molecular biology
Special Issues, Collections and Topics in MDPI journals
Dr. Sonia Del Prete

E-Mail Website
Guest Editor
Institute of Biosciences and Bioresources (IBBR), CNR, Via Pietro Castellino 111, 80131 Napoli, Italy
Interests: biochemistry; molecular biology; enzyme; gene expression; plant sciences
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Environmental stress has played a crucial role in the evolution of living organisms, highlighting the critical interaction between organisms and their environments. Both abiotic and biotic stressors force species to continuously adapt and evolve. For instance, terrestrial ecosystems confront heightened frequencies and intensities of extreme events, such as droughts and wildfires. Climate change intensifies these challenges, aggravated by factors such as habitat fragmentation and invasive species, precipitating profound and irreversible ecological shifts at local and global levels, and jeopardizing environmental, socio-economic and cultural integrity. Recently, the surge in urbanization has introduced additional environmental stressors for living organisms, including sound waves emitted by industrial machinery or vehicles.

We warmly welcome researchers to contribute papers or reviews that explore various aspects of the adaptation of species to environmental stress.

In particular, this Special Issue aims to delve into, though not exclusively, the following inquiries:

  • How do elements such as silicon, carbon or nitrogen influence terrestrial ecosystems?
  • What are the global repercussions of climate change, and how do they impact worldwide ecosystems?
  • Can certain elements mitigate the effects of global change on our ecosystems?
  • Do the acoustic emissions occurring worldwide induce specific genetic or functional alterations in living organisms?

The objective of this Special Issue is to comprehensively understand how diverse changes, such as acoustic or climatic ones, influence living species within our ecosystems and the potential consequences on a global scale.

Manuscripts exploring theoretical frameworks, controlled field experiments and/or laboratory investigations are warmly encouraged.

Dr. Mario Pagano
Dr. Sonia Del Prete
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • adaptation
  • environmental stress
  • evolutionary response
  • physiological adaptation
  • behavioral adaptation
  • morphological adaptation
  • climate change
  • conservation biology
  • biodiversity
  • ecological resilience
  • sound waves

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Related Special Issue

Published Papers (1 paper)

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Research

23 pages, 2586 KB  
Article
Explainable AI-Based Hyperspectral Classification Reveals Differences in Spectral Response over Phenological Stages
by Rameez Ahsen, Pierpaolo Di Bitonto, Pierfrancesco Novielli, Michele Magarelli, Donato Romano, Martina Di Venosa, Anna Maria Stellacci, Nicola Amoroso, Alfonso Monaco, Bruno Basso, Roberto Bellotti and Sabina Tangaro
Biology 2026, 15(6), 454; https://doi.org/10.3390/biology15060454 - 11 Mar 2026
Viewed by 543
Abstract
Optimizing nitrogen (N) fertilization is essential for sustaining durum wheat yield and grain quality while reducing the environmental impacts associated with N over-application. Hyperspectral sensing provides a rapid and non-destructive approach for monitoring crop N status. However, high-dimensional data, phenology-dependent spectral responses, and [...] Read more.
Optimizing nitrogen (N) fertilization is essential for sustaining durum wheat yield and grain quality while reducing the environmental impacts associated with N over-application. Hyperspectral sensing provides a rapid and non-destructive approach for monitoring crop N status. However, high-dimensional data, phenology-dependent spectral responses, and spatial autocorrelation in field measurements limit robust nitrogen classification and interpretation. This study evaluated hyperspectral-based nitrogen status classification in durum wheat under Mediterranean field conditions and identified key spectral regions using explainable artificial intelligence. A field experiment was conducted in Southern Italy using ten N fertilization rates (0–180 kg N ha−1). Canopy reflectance was acquired at the booting and heading stages from georeferenced sampling locations. Three nitrogen stratification strategies (binary Low–High, Extreme, and three-level) were evaluated using Random Forest, SVM-RBF, and XGBoost classifiers. Model performance was assessed using spatially independent Leave-One-Plot-Out cross-validation at both the sample and plot levels, with plot-level predictions derived through majority voting. Classification robustness was strongly influenced by the stratification strategy and phenological stage. The binary Low–High stratification achieved the highest sample-level accuracy, with a maximum of 0.78 at booting (SVM-RBF) and 0.75 at heading (SVM-RBF), whereas the Extreme stratification produced intermediate performance, with maximum accuracies of 0.73 at booting (SVM-RBF) and 0.63 at heading (XGBoost). Plot-level aggregation improved performance, reaching up to 0.90 at booting and 1.00 at heading. SHAP analysis highlighted red, red-edge, and near-infrared wavelengths as the dominant contributors, with increased reliance on longer wavelengths at the heading. Overall, explainable machine learning provides a robust framework for hyperspectral nitrogen monitoring in durum wheat. Full article
(This article belongs to the Special Issue Adaptation of Living Species to Environmental Stress (2nd Edition))
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