Nicolas Rothbacher, Kit T. Rodolfa, Mihir Bhaskar
et al.
Advances in Artificial Intelligence (AI) have generated widespread enthusiasm for the potential of AI to support our understanding and protection of the environment. As such tools move from basic research to more consequential settings, such as regulatory enforcement, the human context of how AI is utilized, interpreted, and deployed becomes increasingly critical. Yet little work has systematically examined the role of such organizational goals and incentives in deploying AI systems. We report results from a unique case study of a satellite imagery-based AI tool to detect dumping of agricultural waste, with concurrent field trials with the Wisconsin Department of Natural Resources (WDNR) and a non-governmental environmental interest group in which the tool was utilized for field investigations when dumping was presumptively illegal in February-March 2023. Our results are threefold: First, both organizations confirmed a similar level of ground-truth accuracy for the model's detections. Second, they differed, however, in their overall assessment of its usefulness, as WDNR was interested in clear violations of existing law, while the interest group sought to document environmental risk beyond the scope of existing regulation. Dumping by an unpermitted entity or just before February 1, for instance, were deemed irrelevant by WDNR. Third, while AI tools promise to prioritize allocation of environmental protection resources, they may expose important gaps of existing law.
Sara Si-moussi, Wilfried Thuiller, Esther Galbrun
et al.
Earthworms are key drivers of soil function, influencing organic matter turnover, nutrient cycling, and soil structure. Understanding the environmental controls on their distribution is essential for predicting the impacts of land use and climate change on soil ecosystems. While local studies have identified abiotic drivers of earthworm communities, broad-scale spatial patterns remain underexplored. We developed a multi-species, multi-task deep learning model to jointly predict the distribution of 77 earthworm species across metropolitan France, using historical (1960-1970) and contemporary (1990-2020) records. The model integrates climate, soil, and land cover variables to estimate habitat suitability. We applied SHapley Additive exPlanations (SHAP) to identify key environmental drivers and used species clustering to reveal ecological response groups. The joint model achieved high predictive performance (TSS >= 0.7) and improved predictions for rare species compared to traditional species distribution models. Shared feature extraction across species allowed for more robust identification of common and contrasting environmental responses. Precipitation variability, temperature seasonality, and land cover emerged as dominant predictors of earthworm distribution. Species clustering revealed distinct ecological strategies tied to climatic and land use gradients. Our study advances both the methodological and ecological understanding of soil biodiversity. We demonstrate the utility of interpretable deep learning approaches for large-scale soil fauna modeling and provide new insights into earthworm habitat specialization. These findings support improved soil biodiversity monitoring and conservation planning in the face of global environmental change.
Diana Wallison, Jessica Wert, Farnaz Safdarian
et al.
This study develops an integrated approach that includes EV charging and power generation to assess the complex cross-sector interactions of vehicle electrification and its environmental impact. The charging load from on-road EV operation is developed based on a regional-level transportation simulation and charging behavior simulation, considering different EV penetration levels, congestion levels, and charging strategies. The emissions from EGUs are estimated from a dispatch study in a power grid simulation using the charging load as a major input. A case study of Austin, Texas is performed to quantify the environmental impact of EV adoption on both on-road and EGU emission sources at the regional level. The results demonstrate the range of emission impact under a combination of factors.
Blessing Emerenini, Edward Beck, Kathryn Cantrel
et al.
As antibiotic resistance continues to pose a significant threat to public health, alternative treatments are urgently needed. Phage therapy, which utilizes bacteriophages to specifically target bacterial pathogens, has emerged as a promising solution. Given that bacteria often exist in biofilms -complex micro-communities that complicate treatment strategies, there is a clear need for models that account for spatial dynamics. This study aims to employ mathematical and statistical methodologies to identify optimal treatment strategies involving phage-antibiotic combinations. We developed an agent-based model to analyze how environmental factors (e.g. temperature, pH, and resource availability) influence bacteria-phage interactions during therapy, focusing on both healthy and immunocompromised patients. Utilizing \textit{Escherichia coli} as a case study, we observed that bacterial cells exhibit mutations that enhance their adaptability to varying environmental conditions and treatment approaches. Our findings suggest that the effectiveness of therapies targeting pathogenic and mutated bacterial cells can be significantly improved through strategic control of application timing and dosing. Additionally, we investigated the impact of biofilm structure on the efficacy of phage therapy, underscoring its importance in developing targeted treatment strategies.
Riccardo Gianluigi Serio, Maria Michela Dickson, Giuseppe Espa
et al.
Tourism has emerged as a significant driver of the global economy. As its economic impact grows, concerns regarding environmental sustainability have intensified. This paper explores the dual dimensions of sustainable tourism: the relationship between tourism supply and sustainability, and tourist demand characteristics. It highlights the critical role of young tourists, who exhibit a heightened awareness of environmental issues and advocate for sustainable practices. By conducting a survey among young Italian university students, the study identifies distinct segments based on family background, political orientation, and travel habits. Utilizing latent class cluster analysis, the findings aim to enhance understanding of pro-environmental behaviors among youth, offering insights for policymakers to foster sustainable tourism practices.
Amanda Sengeløv, Giacomo Capuzzo, Sarah Dalle
et al.
Understanding the spatial distribution of strontium isotopes in plants or other archives within a region is crucial for various fields, including archaeology, environmental studies, food sciences and forensic science. This study aims to create a detailed dynamic strontium isoscape for Belgium through high-density plant sampling, presented in a web application (IsoBel) that serves the mentioned research fields. A total of 540 plant samples (199 locations), representing various species of grass, shrubs, and trees across Belgium were collected and were analysed for their strontium isotope ratios (87Sr/86Sr) to create a first biologically available strontium map. Sampling sites were selected to cover diverse lithological formations and soil types, ensuring representative coverage of the region’s geological heterogeneity, by using a novel high density grid mapping method. Sixty-four previously published plants from 21 locations are also included in this study, bringing the total amount of plant samples used to 604 from 220 locations. The results reveal significant variations in 87Sr/86Sr across Belgium (ranging from 0.7054 to 0.7259), which reflect the underlying lithology and geological processes (tectonics, weathering,…) which shaped the landscape. Although overlapping 87Sr/86Sr is seen across the majority of lithologies, there is a statistically significant difference between the distribution of 87Sr/86Sr values across all different lithological units in Belgium (Kruskal-Wallis test; p < 0.0001). Distinct regional patterns were observed, with higher 87Sr/86Sr in the older geological south-eastern part of Belgium, compared to the younger north-western parts. The high-density plant sampling approach employed in this study allowed for enhanced spatial resolution and improved accuracy in the predictive surfaces for bioavailable 87Sr/86Sr created by Empirical Bayesian Kriging (EBK). These findings provide valuable insights into the geographic distribution of strontium isotopes within Belgium and offer a foundation for future studies in archaeology, ecology, environmental studies, food sciences and forensics. Furthermore, the extensive coverage of various plant species provided a robust representation of the local ecosystems and their strontium sources. Overall, this study contributes to the growing body of knowledge on regional strontium isoscapes, enhancing our understanding of the complex interplay between litho- and biosphere in shaping the strontium isotope compositions of ecosystems.
Climate change, overfishing, marine pollution and other anthropogenic drivers threaten our global oceans. More effective efforts are urgently required to improve the capacity of marine conservation action worldwide, as highlighted by the United Nations Decade of Ocean Science for Sustainable Development 2021–2030. Marine citizen science presents a promising avenue to enhance engagement in marine conservation around the globe. Building on an expanding field of citizen science research and practice, we present a global overview of the current extent and potential of marine citizen science and its contribution to marine conservation. Employing an online global survey, we explore the geographical distribution, type and format of 74 marine citizen science projects. By assessing how the projects adhere to the Ten Principles of Citizen Science (as defined by the European Citizen Science Association), we investigate project development, identify challenges and outline future opportunities to contribute to marine science and conservation. Synthesizing the survey results and drawing on evidence from case studies of diverse projects, we assess whether and how citizen science can lead to new scientific knowledge and enhanced environmental stewardship. Overall, we explore how marine citizen science can inform current understanding of marine biodiversity and support the development and implementation of marine conservation initiatives worldwide. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.
Modan Tailleur, Junwon Lee, Mathieu Lagrange
et al.
This paper explores whether considering alternative domain-specific embeddings to calculate the Fréchet Audio Distance (FAD) metric can help the FAD to correlate better with perceptual ratings of environmental sounds. We used embeddings from VGGish, PANNs, MS-CLAP, L-CLAP, and MERT, which are tailored for either music or environmental sound evaluation. The FAD scores were calculated for sounds from the DCASE 2023 Task 7 dataset. Using perceptual data from the same task, we find that PANNs-WGM-LogMel produces the best correlation between FAD scores and perceptual ratings of both audio quality and perceived fit with a Spearman correlation higher than 0.5. We also find that music-specific embeddings resulted in significantly lower results. Interestingly, VGGish, the embedding used for the original Fréchet calculation, yielded a correlation below 0.1. These results underscore the critical importance of the choice of embedding for the FAD metric design.
Pierre Monmarché, Sebastian J. Schreiber, Édouard Strickler
We examine to what extent the tempo and mode of environmental fluctuations matter for the growth of structured populations. The models are switching, linear ordinary differential equations $x'(t)=A(σ(ωt))x(t)$ where $x(t)=(x_1(t),\dots,x_d(t))$ corresponds to the population densities in the $d$ individual states, $σ(t)$ is a piece-wise constant function representing the fluctuations in the environmental states $1,\dots,N$, $ω$ is the frequency of the environmental fluctuations, and $A(1),\dots,A(n)$ are Metzler matrices. $σ(t)$ can either be a periodic function or correspond to a continuous-time Markov chain. Under suitable conditions, there is a Lyapunov exponent $Λ(ω)$ such that $\lim_{t\to\infty} \frac{1}{t}\log\sum_i x_i(t)=Λ(ω)$ for all non-negative, non-zero initial conditions $x(0)$ (with probability one in the random case). For both forms of switching, we derive analytical first-order and second-order approximations of $Λ(ω)$ in the limits of slow ($ω\to 0$) and fast ($ω\to\infty$) environmental fluctuations. When the order of switching and the average switching times are equal, we show that the first-order approximations of $Λ(ω)$ are equivalent in the slow-switching limit, but not in the fast-switching limit. We illustrate our results with applications to stage-structured and spatially-structured models. When dispersal rates are symmetric, the first order approximations suggest that population growth rates increase with the frequency of switching -- consistent with earlier work on periodic switching. In the absence of dispersal symmetry, we demonstrate that $Λ(ω)$ can be non-monotonic in $ω$. In conclusion, our results show how population growth rates depend on the tempo ($ω$) and mode (random versus deterministic) of the environmental fluctuations.
At present, the threat of technogenesis is not weakening despite the measures taken to reduce the levels of negative impact on the environment. In this regard, the authors analyze the standardization of risk management as an effective tool for monitoring the safety of not only design decisions in housing construction, but also any economic activity. The article discusses the safety aspects set out in Russian standards (GOSTs) and international guidelines. The analyzed regulatory documentation answers the question of how to achieve an acceptable level of risk. The basic concepts of risk assessment are given. There are positive changes in state standards in the safety area. Federal Law N7 regulates the leadership of the employer, and not his responsibility. As part of the improvement of environmental management for housing construction, the use of certain penalties, interest fines and forfeits looks quite natural. The main goal of the international standard ISO 14001 is not to point out the need for managers to have leadership qualities as the main factor in ensuring environmental safety for the construction industry, but to form a responsible attitude towards the environment and natural resources as the most important asset of economic activity. The article raises the issue that risk analysts cannot be fully guided by domestic standards due to their lack of development and inconsistency with the universal international documents ISO 31000:2018 "Risk management - Guidelines" and ISO 14001:2016 "Environmental management systems". A special risk assessment approach should be developed that describes the interaction of various scenarios, which will provide an increased environmental and economic effect in the field of housing construction safety.
Fossil fuel and conventional lubricant are not environmentally friendly, non-biodegradable, toxic, and non-renewable. Therefore, the objective of this paper is to evaluate the thermal and fluidity of the biolubricant synthesized from Mango (Mangifera indica L.) kernel oil (MKO) blended with cold flow property improvers using standard techniques. A twostep process of esterification and transesterification was employed to produce fatty acid methyl ester (FAME) from MKO mentioned as Mango kernel methyl ester (MKME). Double transesterification of the MKME with trimethylolpropane (TMP) in the presence of sodium methoxide yielded 95 % Mango oil based trimethylolpropane ester (MOTE). Anotherof the MKME was used to synthesize biolubricant using the conventional epoxidation which yielded 70 % Mango oil based epoxidised biolubricant (MEB-L). A simultaneous SDT 2960 TG/DTA from TA instrument analysis reveals MOTE to present higher thermal stability (302 °C) with 5 % weight loss compared to MEB-L (250.5 °C) with similar 5 % weight loss. Degradation was endothermic for both MOTE and MEB-L and predominantly followed a single step of weight lost. Degradation becomes rapid at temperature above 300 °C for MOTE while for MEB-L degradation started at temperature above 250 °C. At about the temperature range of 850 - 900 °C, 95 % of MEB-L and 77 % of MOTE were lost respectively. The relative thermal stability of MOTE would be attributed to the alcohol substitution of the branch chain Trimethylolpropane (TMP) resulting into a more thermally stable Triester (MOTE). The results of the analysis of the cold flow properties reveal that various blend of MEB-L with n-BE portrays better pour and cloud point as they are lower than their counterpart (blends of MOTE with n-BE) and (blends of even MOTE & MEB-L with EAA for both cloud/pour points).
Abstract Background Streptococcus iniae is an important fish pathogen that cause significant economic losses to the global aquaculture industry every year. Although there have some reports on the genotype of S.iniae and its relationship with virulence, no genome-scale comparative analysis has been performed so far. In our previous work, we characterized 17 isolates of S.iniae from Trachinotus ovatus and divided them into two genotypes using RAPD and rep-PCR methods. Among them, BH15-2 was classified as designated genotype A (in RAPD) and genotype 1 (in rep-PCR), while BH16-24 was classified as genotype B and genotype 2. Herein, we compared the differences in growth, drug resistance, virulence, and genome between BH15-2 and BH16-24. Results The results showed that the growth ability of BH16-24 was significantly faster than that of BH15-2 at the exponential stage. Antimicrobial tests revealed that BH15-2 was susceptible to most of the tested antibiotics except neomycin and gentamycin. In contrast, BH16-24 was resistant to 7 antibiotics including penicillin, sulfasomizole, compound sulfamethoxazole tablets, polymyxin B, spectinomycin, rifampin and ceftazidime. Intraperitoneal challenge of T.ovatus, showed that the LD50 value of BH15-2 was 4.0 × 102 CFU/g, while that of BH16-24 was 1.2 × 105 CFU/g. The genome of S.iniae BH15-2 was 2,175,659 bp with a GC content of 36.80%. Meanwhile, the genome of BH16-24 was 2,153,918 bp with a GC content of 36.83%. Comparative genome analysis indicated that compared with BH15-2, BH16-24 genome had a large-scale genomic inversion fragment, at the location from 502,513 bp to 1,788,813 bp, resulting in many of virulence and resistance genes differentially expression. In addition, there was a 46 kb length, intact phage sequence in BH15-2 genome, which was absent in BH16-24. Conclusion Comparative genomic studies of BH15-2 and BH16-24 showed that the main difference is a 1.28 Mbp inversion fragment. The inversion fragment may lead to abnormal expression of drug resistant and virulence genes, which is believed to be the main reason for the multiple resistance and weakened virulence of BH16-24. Our study revealed the potential mechanisms in underlying the differences of multidrug resistance and virulence among different genotypes of S.iniae.
Rhizosphere is a crucial area in comprehending the interaction between plants and microorganisms in constructed wetlands (CWs). However, influence of photoperiod, a key factor that regulates photosynthesis and rhizosphere microbial activity, remains largely unknown. This study investigated the effect of photoperiod (9, 12, 15 h/day) on pollutant removal and underlying mechanisms. Results showed that 15-hour photoperiod treatment exhibited the highest removal efficiencies for COD (87.26%), TN (63.32%), and NO3–-N (97.79%). This treatment enhanced photosynthetic pigmentation and root activity, which increased transport of oxygen and soluble organic carbon to rhizosphere, thus promoting microbial nitrification and denitrification. Microbial community analysis revealed a more stable co-occurrence network due to increased complexity and aggregation in the 15-hour photoperiod treatment. Phaselicystis was identified as a key connector, which was responsible for transferring necessary carbon sources, ATP, and electron donors that supported and optimized nitrogen metabolism in the CWs. Structural equation model analysis emphasized the importance of plant–microbe interactions in pollutant removal through increased substance, information, and energy exchange. These findings offer valuable insights for CWs design and operation in various latitudes and rural areas for small-scale decentralized systems.