Ecosystem Behavior Research Articles

Software Engineering for Collective Cyber-Physical Ecosystems

Today's distributed and pervasive computing addresses large-scale cyber-physical ecosystems, characterised by dense and large networks of devices capable of computation, communication and interaction with the environment and people. While most research focuses on treating these systems as “composites” (i.e., heterogeneous functional complexes), recent developments in fields such as self-organising systems and swarm robotics have opened up a complementary perspective: treating systems as “collectives” (i.e., uniform, collaborative, and self-organising groups of entities). This article explores the motivations, state of the art, and implications of this “collective computing paradigm” in software engineering. In particular, it discusses its peculiar challenges, implied by characteristics like distribution, situatedness, large scale, and cooperative nature. These challenges outline significant directions for future research in software engineering, touching on aspects such as macro-programming, collective intelligence, self-adaptive middleware, learning/synthesis of collective behaviour, human involvement, safety and security in collective cyber-physical ecosystems.

Effect of temperature on circadian clock functioning of trees in the context of global warming.

Plant survival in a warmer world requires the timely adjustment of biological processes to cyclical changes in the new environment. Circadian oscillators have been proposed to contribute to thermal adaptation and plasticity. However, the influence of temperature on circadian clock performance and its impact on plant behaviour in natural ecosystems are not well-understood. We combined bioinformatics, molecular biology and ecophysiology to investigate the effects of increasing temperatures on the functioning of the circadian clock in two closely related tree species from Patagonian forests that constitute examples of adaptation to different thermal environments based on their altitudinal profiles. Nothofagus pumilio, the species from colder environments, showed a major rearrangement of its transcriptome and reduced ability to maintain rhythmicity at high temperatures compared with Nothofagus obliqua, which inhabits warmer zones. In altitude-swap experiments, N. pumilio, but not N. obliqua, showed limited oscillator function in warmer zones of the forest, and reduced survival and growth. Our findings show that interspecific differences in the influence of temperature on circadian clock performance are associated with preferred thermal niches, and to thermal plasticity of seedlings in natural environments, highlighting the potential role of a resonating oscillator in ecological adaptation to a warming environment.

Feeding behavior and prey characteristics of great egrets (Ardea alba) in eco-friendly and conventional rice fields in South Korea

Rice fields are important wildlife habitats; however, intensive agricultural practices have reduced the population of farmland birds. As a high-level consumer, the great egret (Ardea alba) serves as an indicator of the overall biodiversity of rice fields. However, little is known about the effects of farming methods on the feeding habitat selection of the great egret. Therefore, we examined the influence of eco-friendly and conventional farming methods on prey characteristics and great egret feeding behavior in rice field ecosystems. We employed focal observations and trap-based sampling to quantify prey characteristics and great egret feeding behaviors in eco-friendly and conventional rice fields. Great egrets showed more hunting attempts per minute and a higher intake rate in conventional fields, but feeding efficiency did not differ. Moreover, they consumed larger loaches in eco-friendly fields than in conventional fields. Great egrets exhibited slower feeding behaviors in eco-friendly fields due to the increased handling time of larger prey, such as loaches. Eco-friendly fields supported a higher abundance of larger-sized loaches than conventional fields, indicating their potential for supporting a higher abundance of great egrets. Our findings highlight the importance of sustainable farming practices for the conservation of the great egret.

The Use of Digital Twins to Address Smart Tourist Destinations’ Future Challenges

This research aims to conceptualise the use of the digital twins (DT) tool in tourism to address smart tourist destinations’ future challenges to enhance tourists’ experiences and residents’ quality of life through better services developed by DTs. This paper investigated the use of DT technology to tackle the new challenges facing smart tourist destinations (STDs) in terms of urban planning, sustainability, security, marketing, and tourism activities by using data on this topic from expert researchers and public and private organisations. Also, this research adopted a systematic review approach to analyse and illustrate the existing literature on the topic of DTs and their use for STDs, which helped us develop the DT concept in a STD context. The findings of this research reveal that DT technology is emerging as a disruptive technology tool that is being used to improve the management of STDs in terms of their efficiency, safety, sustainability, environmental protection, productivity, and energy consumption. Moreover, DT technology is a nascent tool in the tourism and marketing industries, but its versatility in relation to its capacity to analyse data and predict the behaviour of tourism and business ecosystems to address relevant issues at STDs gives it a key role in the tourism industry. Finally, a new definition of DT technology has been included in this study within a tourism and STDs context, filling the gap in this topic in the tourism industry according to some researchers’ suggestions. There are limited scientific publications about DT technology that jointly tackle the DT technology and STDs sphere. Accordingly, this manuscript defines DT technology and provides a new viewpoint of this technology that will help to initiate academic discussions on DT tourism within the context of STDs.

Differential Transform Method (DTM) and Physics-Informed Neural Networks (PINNs) in Solving Integral–Algebraic Equation Systems

Integral–algebraic equations and their systems are a common description of many technical and engineering problems. Often, such models also describe certain dependencies occurring in nature (e.g., ecosystem behaviors). The integral equations occurring in this problem may have two types of domains—symmetric or asymmetric. Depending on whether such symmetry exists in the system describing a given problem, we must choose the appropriate method to solve this system. In this task, the absence of symmetry is more advantageous, but the presented examples demonstrate how one can approach cases where symmetry is present. In this paper, we present the application of two methods for solving such tasks: the analytical Differential Transform Method (DTM) and Physics-informed Neural Networks (PINNs). We consider a wide class of these types of equation systems, including Volterra and Fredholm integrals (which are also in a single model). We demonstrate that despite the complex nature of the problem, both methods are capable of handling such tasks, and thus, they can be successfully applied to the issues discussed in this article.

Swimming kinematics of deep-sea fishes.

Although the deep oceans represent Earth's largest habitat, the challenges of studying deep-sea organisms in situ have limited our understanding of adaptation, ecology, and behaviour in these important ecosystems. One fundamental trait of fishes that remains largely unexplored in the deep ocean is swimming, a vital process for movement, migration, and dispersal in marine habitats. Deep-sea conditions such as temperature, pressure, and food availability could each impact the speed and efficiency of swimming in fishes. To investigate swimming kinematics of fishes with increasing depth, we analysed in situ video of bony fishes across a 6000-m depth gradient. We compared open-source videos of fishes from National Oceanic and Atmospheric Administration (NOAA)Ocean Exploration with tank-based recordings of shallow-water relatives from Puget Sound, Washington, USA to understand how both habitat depth and phylogeny influence swimming in fishes. We analysed kinematics in four dominant demersal fish groups, the orders Anguilliformes, Gadiformes, Ophidiiformes, and Perciformes. Deep-sea fishes swam consistently slowly. Swimming kinematics varied across temperature, oxygen, body elongation, and depth. These results suggest that swimming kinematics do not change linearly with increasing habitat depth in fishes and that the impacts of deep-sea conditions such as low temperatures, high pressures, and low nutrient availability on swimming behaviour need to be considered independently of one another. These findings provide insight into the evolution of fish form and function in the deep ocean.

Microfluidics for studying the deep underground biosphere: from applications to fundamentals.

In this review, selected examples are presented to demonstrate how microfluidic approaches can be utilized for investigating microbial life from deep geological environments, both from practical and fundamental perspectives. Beginning with the definition of the deep underground biosphere and the conventional experimental techniques employed for these studies, the use of microfluidic systems for accessing critical parameters of deep life in geological environments at the microscale is subsequently addressed (high pressure, high temperature, low volume). Microfluidics can simulate a range of environmental conditions on a chip, enabling rapid and comprehensive studies of microbial behavior and interactions in subsurface ecosystems, such as simulations of porous systems, interactions among microbes/microbes/minerals, and gradient cultivation. Transparent microreactors allow real-time, noninvasive analysis of microbial activities (microscopy, Raman spectroscopy, FTIR microspectroscopy, etc.), providing detailed insights into biogeochemical processes and facilitating pore-scale analysis. Finally, the current challenges and opportunities to expand the use of microfluidic methodologies for studying and monitoring the deep biosphere in real time under deep underground conditions are discussed.

Monitoring soil salinity in coastal wetlands with Sentinel-2 MSI data: Combining fractional-order derivatives and stacked machine learning models

Monitoring soil salinity is essential for understanding the behavior of coastal wetland ecosystems and implementing effective management strategies. Despite the advantages of the Multi-Spectral Instrument (MSI) data for large-scale, high-frequency soil salinity monitoring, challenges remain in data preprocessing and model construction. We combined fractional-order derivative (FOD) technology with stacked machine learning models to monitor and map soil salinity using Sentinel-2 MSI data. The base models included Elastic Net Regression, Support Vector Regression, Artificial Neural Network, Extreme Gradient Boosting, and Random Forest, with Non-Negative Least Squares as the meta-learner. The results showed that low-order FOD enhanced image gradients and maintained a high peak signal-to-noise ratio, thereby improving the correlation with soil salinity. Notably, the 0.25-order FOD showed the best performance, increasing the correlation coefficient with soil salinity by up to 13 %. The stacked machine learning models effectively combined the strengths of different base models, enhancing prediction accuracy by more than 8 % compared to single models. Furthermore, combining stacked models with FOD further improved prediction accuracy, with an increase in R² of up to 9 %. The combination of 0.25-order FOD and the stacked machine learning model achieved the best performance (R² = 0.82, RMSE = 10.19 ppt, RPD = 2.38, RPIQ = 4.69). This approach provides a reference for rapid and effective large-scale digital mapping of soil salinity in coastal wetlands.

Characterization of soil organic carbon at profile scale in two forest soils under pine and holm oak

Context It is essential to promote soil carbon sequestration as a means to mitigate climate change. Thus, it is fundamental to know the distribution of C in the soil at profile scale, the characteristics of humic substances as indicators of soil organic matter (SOM) turnover and their relationship with other soil properties. Aims Two forest ecosystems under pine and holm oak developed under a Meso-Mediterranean climate in Spain were used to characterize SOM through the complete sequence of layers of the soil profile. Methods General soil analysis, infrared spectroscopic analysis and soil color measurements were conducted for the characterization. Key results Humus form under oak was found to be Mull mesotrophic–Mull acid while humus under pine Moder oligotrophic. The infrared spectrum determined that oxidation of the humic acids was more complete in the deeper horizons. Relationships between intensities of the main spectral bands in both soils followed similar maximum and minimum sequence values. The total humic extract (THE) color measured by reflection was found inversely related to the THE color measured by transmission. In the same way, the color spectrum between 350 and 800 nm in the THE showed an inverse relation between hue/brightness and absorbance values. Conclusions Infrared analysis and color measurements provided evidence of a different level of stabilization of humic substances from each soil, and between the different horizons. Large spatial variability in soil organic carbon quantity and quality was observed. Implications Better understanding of carbon sequestration behavior in different soil ecosystems in its crucial role within the global carbon cycle

Wolves foraging on berries is likely a widespread behavior in southern boreal ecosystems

AbstractWolves are opportunistic generalists that can respond quickly to new and unique food sources. Wolves in some ecosystems will consume berries and other fruits when they are abundant and available; however, many aspects of this behavior remain unknown. In the Greater Voyageurs Ecosystem (GVE), Minnesota, USA, wolves consistently consume berries, particularly blueberries, when they are available. We deployed remote cameras in blueberry patches to record wolves foraging on berries over several years. We captured footage of wolves of all age classes, social statuses, and sex foraging on blueberries alone or with other wolves. Our observations indicate berry consumption by wolves is a widespread behavior in the GVE and likely in similar southern boreal ecosystems. We hope our work spurs researchers across wolf range to examine whether berry consumption by wolves is a widespread and ubiquitous behavior for wolves.

How combined pairwise and higher-order interactions shape transient dynamics.

Understanding how species interactions shape biodiversity is a core challenge in ecology. While much focus has been on long-term stability, there is rising interest in transient dynamics-the short-lived periods when ecosystems respond to disturbances and adjust toward stability. These transitions are crucial for predicting ecosystem reactions and guiding effective conservation. Our study introduces a model that uses convex combinations to blend pairwise and higher-order interactions (HOIs), offering a more realistic view of natural ecosystems. We find that pairwise interactions slow the journey to stability, while HOIs speed it up. Employing global stability analysis and numerical simulations, we establish that as the proportion of HOIs increases, mean transient times exhibit a significant reduction, thereby underscoring the essential role of HOIs in enhancing biodiversity stabilization. Our results reveal a robust correlation between the most negative real part of the eigenvalues of the Jacobian matrix associated with the linearized system at the coexistence equilibrium and the mean transient times. This indicates that a more negative leading eigenvalue correlates with accelerated convergence to stable coexistence abundances. This insight is vital for comprehending ecosystem resilience and recovery, emphasizing the key role of HOIs in promoting stabilization. Amid growing interest in transient dynamics and its implications for biodiversity and ecological stability, our study enhances the understanding of how species interactions affect both transient and long-term ecosystem behavior. By addressing a critical gap in ecological theory and offering a practical framework for ecosystem management, our work advances knowledge of transient dynamics, ultimately informing effective conservation strategies.

Neoichnology of Rhinella dorbignyi (Bufonidae) burrows: improving the recognition and interpretation of toad burrows

A neoichnological characterization of toad burrows from organic-rich soils is presented in order to establish key ichnological signatures for their recognition in the geological record. Dorbigny’s Toad (Rhinella dorbignyi) produces J-shaped burrows with a single elliptical opening resembling the ichnogenus Macanopsis. The burrow varies from 15 to 20 cm in length and has a constant diameter along the shaft, enlarged in the chamber. The shaft is elliptical with a diameter of 2.5-3.0 cm in the major axis and 1.0–1.5 cm in the minor axis. The chamber is semicircular, with a distinct floor, and an average diameter of 5 cm in the major axis. A thick (3–5 mm), compacted, smooth, and uniform inorganic lining made of soil covers the burrow throughout its length. Surficial features, such as horizontal and vertical millimeter-scale striations and ridges, occur in the burrow surface and are produced by keratinized granules and spikes on the skin of R. dorbignyi. Those surficial features are generated during the toad’s movements inside the burrow as well as anchoring during ambush predation behavior. The main distinct features observed on the burrow surface are well-developed circular pit impressions produced by the keratinized tubercles present in the toad’s ankles during climbing activity. These characteristics encompass useful ichnotaxobases for recognition and distinguishing toad burrows from J-shaped, Macanopsis-like burrows produced by other soil-dwelling animals. The burrow architecture of R. dorbignyi suggests that J-shaped burrows are efficient structures for ambush predatory behavior in terrestrial ecosystems, as observed in spiders and scorpions.

Microplastics and benthic animals reshape the geochemical characteristics of dissolved organic matter by inducing changes in keystone microbes in riparian sediments

Dissolved organic matter (DOM) in riparian sediments plays a vital role in regulating element cycling and pollutant behavior of river ecosystems. Microplastics (MPs) and benthic animals (BAs) have been frequently detected in riparian sediments, influencing the substance transformation in river ecosystems. However, there is still a lack of systematic investigation on the effects of MPs and BAs on sediment DOM. This study investigated the impact of MPs and BAs on the geochemical characteristics of DOM in riparian sediments and their microbial mechanisms. The results showed that MPs and BAs increased sediment DOC concentration by 34.24%∼232.97% and promoted the conversion of macromolecular components to small molecular components, thereby reducing the humification degree of DOM. Mathematical model verified that the changes of keystone microbes composition in sediments were direct factors affecting the characteristics of DOM in riparian sediment. Especially, MPs tolerant microbes, including Planctomicrobium, Rhodobacter, Hirschia and Lautropia, significantly increased DOC concentration and decreased humification degree (P < 0.05). In addition, MPs and BAs could also influence keystone microbes in sediments by altering the structure of microbial network, thereby indirectly affecting DOM characteristics. The study demonstrates the pollution behavior of MPs in river ecosystems and provides a basis for protecting the ecological function of riparian sediments from MPs pollution.

Additional data on the ongoing naturalization of the non-native woody plant Duranta erecta ( Verbenaceae) in Sicily, Italy

We recorded the occurrence of Duranta erecta L. in the Aeolian Islands (Sicily, Italy), where it currently behaves as a casual alien. At the global scale, however, this woody species has shown highly invasive behaviour in different island ecosystems. On the basis of this evidence, we have investigated which ecological and biological traits may have allowed its establishment and spread, and could trigger its further expansion in the Aeolian Islands in the near future. Several factors seem to have favoured its success on a global scale, such as the wide edaphic and climatic range, the tolerance to anthropogenic disturbance, and the production of toxic metabolites that protect it from herbivore browsing and from competition with other plants. The study of the organisms that perform pollination and seed dispersal is probably the key to understanding the local naturalization of this plant, introduced about three centuries ago in Europe and the Mediterranean, here discussed in detail for the first time.

Influence of the initial microbiota on eggplant shibazuke pickle and eggplant juice fermentation.

The findings shown in this study provide insight into the microbial succession during spontaneous pickle fermentation and the role of Lactiplantibacillus plantarum in eggplant pickle production. Moreover, the novel method of using filter-sterilized vegetable juice with an artificial microbiota to emulate spontaneous fermentation can be applied to other spontaneously fermented products. This approach allows for the evaluation of the effect of specific initial microbiota in the absence of plant-associated bacteria from raw materials potentially promoting a greater understanding of microbial behavior in complex microbial ecosystems during vegetable fermentation.

Release of Radioactive Particles to the Environment.

When environmental impact and risks associated with radioactive contamination of ecosystems are assessed, the source term and deposition must be linked to ecosystem transfer, biological uptake and effects in exposed organisms. Thus, a well-defined source term is the starting point for transport, dose, impact and risk models. After the Chornobyl accident, 3-4 tons of spent nuclear fuel were released and radioactive particles were important ingrediencies of the actual source term. As Chornobyl particles were observed in many European countries, some scientists suggested that radioactive particles were "a peculiarity of the Chornobyl accident." In contrast, research over the years has shown that a major fraction of refractory elements such as uranium (U) and plutonium (Pu) released to the environment has been released as particles following a series of past events such as nuclear weapons tests, non-criticality accidents involving nuclear weapons, military use of depleted uranium ammunition, and nuclear reactor accidents. Radioactive particles and colloids have also been observed in discharges from nuclear installations to rivers or to regional seas and are associated with nuclear waste dumped at sea. Furthermore, radioactive particles have been identified at uranium mining and tailing sites as well as at other NORM sites such as phosphate or oil and gas industrial facilities. Research has also demonstrated that particle characteristics such as elemental composition depend on the emitting source, while characteristics such as size distribution, structure, and oxidation state influencing ecosystem transfer will also depend on the release scenarios. Thus, access to advanced particle characteristic techniques is essential within radioecology. After deposition, localized heterogeneities such as particles will be unevenly distributed in the environment. Thus, inventories can be underestimated, and impact and risk assessments of particle contaminated areas may suffer from unacceptable large uncertainties if radioactive particles are ignored. The present paper will focus on key sources contributing to the release of radioactive particles to the environments, as well as linking particle characteristics to ecosystem behavior and potential biological effects.

Spatial analysis of olive fly on Samos island

Cultivation of olive-trees is one of the landmark land-uses and agroecosystems of the Mediterranean. The single most important factor of production-loss is infestation by the olive fruit fly (OLF, Bactrocera oleae). We examine the spatiotemporal dynamics of OLF populations on Samos Island by employing spatial-analysis methods for a focused estimation on olive plantations. The case study includes a variation of areas across altitude. We use data for three years (2017–2019) from 399 trap locations that are not associated with farms or other major anthropogenic installations and measure temperature and humidity in 24 locations across the island to: examine the temporal variation of OLF populations, to check the relationship of temperature, humidity, and geomorphological characteristics and calculate the estimated spatial distribution of OLF. Results show small differences of annual averages, but very important spatiotemporal differences and micro hot/cold spots of OLF populations. Findings suggest significant movement of OLF populations across landscape. This approach can help achieve a deeper understanding of OLF behavior in Mediterranean ecosystems and contribute toward new approaches in pest management of olive trees.

FinTech forecasting using an evolving connectionist system for lenders and borrowers: ecosystem behavior

&lt;span lang="EN-US"&gt;Financial Technology (FinTech) which is included in the development of digitalization in the financial sector in the industrial era 4.0. Fintech can make any transactions anywhere with the pillars of Peet-to-Peer (P2P) lending, merchants and crowdfunding. In the P2P Lending pillar, there are borrowers and lenders who are digitized in Fintech devices. Fintech in Indonesia is controlled by a state agency called the Otoritas Jasa Keuangan or Financial Services Authority (OJK). In the movement of P2P Lending, there are borrowers and lenders who can be said to be investors where these activities are reported to the OJK. This data can be forecasted using a neural network approach such as ECoS, which is a method capable of forecasting with learning that develops in the hidden layer. In this research article, we present results on forecasting borrowers with a Mean Absolute Percentage Error (MAPE) of 0.148% and forecasting lenders with an accuracy measurement with MAPE of 0.209% with a learning rate 1 = 0.6 and a learning rate 2 = 0.3. So, this forecasting model can be said as an optimization in FinTech activities on the behavior of borrowers and lenders.&lt;/span&gt;

The application of a low-cost microcomputer logger with pressure-temperature based sensor for coastal observations: A preliminary study

Abstract Nearshore hydrodynamics, such as water level fluctuations, field observations play a crucial role in understanding and monitoring the dynamics of the coastal region. The observed parameters provide insight into oceanographic processes, climate change impacts, and the behavior of marine ecosystems that could be valuable for coastal management and infrastructure development planning. Most of the available hydrodynamic loggers are provided by companies with relatively high prices. Due to limited budgets, many areas including Indonesia waters, have limited hydrodynamic observation data. In this paper, we presented a prototype of a simple (DIY-Do It Yourself) and low-cost water level logger with a microcomputer that could be applied in coastal regions. The system consists of a pressure-based sensor to detect water level fluctuations, a temperature sensor, a single-board microcomputer and data logger, and a power supply with different sampling frequencies for various coastal applications. The result showed the ability of the microcomputer system to measure high-resolution water levels and temperatures applicable for non-directional waves, tides and non-tides observations, and ecological monitoring. The microcomputer’s low power consumption makes it suitable for long-term coastal observations, even in remote or battery-powered applications. The body of the logger is designed from PVC-nylon with sensors made from waterproof and corrosion-free materials to ensure its applicability for coastal monitoring. Moreover, the flexibility of the microcomputer system allows for customization and adaptation to specific research requirements at relatively affordable prices.

Advances in Limnogeology: The lake‐basin‐type model revisited 25 years after…anomalies, conundrums and upgrades

AbstractThe lake‐basin‐type model classified the stratigraphic record of ancient lake systems according to rates of potential accommodation relative to sediment + water supply. The model convolved all modes and paths of water supply (direct fall, surficial, subsurface) with amounts and types of sediment supply (clastic, biogenic, chemical) into a single basin‐filling volume term (sediment + water); its major strength was its widespread applicability. This was supported by subsequent investigations confirming the utility of this approach, but it also revealed some important limitations due to simplifications in the original model. The model has been expanded here to address all inland waters (lakes, ponds, wetlands, playas) as well as adding two major subdivisions of the sediment + water term: (1) water supply paths and (2) the volume of water supply relative to sediment supply. Water supply flow paths in the subsurface are subdivided into ‘throughflow’, ‘recharge’ and ‘discharge’. Each of these groundwater hydrology states can be defined quite precisely by the ratio of net outflow to inflow, from persistently open to consistently closed. These paths can be deciphered using stable carbonate and oxygen isotope composition of primary lacustrine limestones, detailed sedimentology, stratigraphy, palaeontology and mineralogy. Distinguishing water supply paths provides additional insights into playa systems and the occurrence and character of evaporites and carbonates. The volume ratio of water to sediment supply most directly influences the water depths of lakes, ponds and wetlands, which affect water body hydrodynamics and ecosystem behaviour as well as the details of stratal stacking and depositional sequences. It helps fine‐tune estimates of the distribution of sediment texture, bedding, composition and organic matter content. The aim of this contribution is to address questions about the fundamental types of inland water bodies and to explain the new lake‐basin subtypes and provide examples that illustrate their potential to enable higher‐resolution, robust analysis of inland water systems and their stratigraphic records.