Environmental Management Applications Research Articles

Signalling: Growth Promoters and Inhibitors

Plant growth and development are intricately regulated by a multitude of signaling pathways that respond to internal and external cues. Central to these regulatory mechanisms are the signaling pathways of growth promoters and inhibitors. Various growth-promoting hormones, including auxins, cytokinins, gibberellins, and brassinosteroids, stimulate cell division, elongation, and differentiation, playing vital roles in shaping plant architecture and influencing various developmental processes. The pathways of these growth promoters involve specific receptors and transcription factors that orchestrate growth in response to dynamic signals. In contrast, growth inhibitors, represented by hormones like abscisic acid, ethylene, jasmonic acid, and salicylic acid, act as crucial checkpoints that restrict growth during stress, pathogen attacks, or other adverse conditions. These signaling pathways trigger growth inhibition and activate defense mechanisms, enabling plants to adapt to challenging environments. Balancing the interplay between growth promoters and inhibitors allows plants to allocate resources efficiently and ensure their survival under changing circumstances. Understanding these signaling pathways is not only fundamental to plant biology but also essential for applications in agriculture, horticulture, and environmental management. This abstract provides a concise overview of these essential processes. This knowledge enables us to manipulate plant growth and development for improved crop yields, disease resistance, and stress tolerance. Ongoing research continues to unravel the complexities of these pathways, offering valuable insights into how plants delicately balance growth promotion and inhibition to thrive in an ever-evolving world.

Research on economic growth in smart cities based on wireless sensor networks

With the acceleration of urbanization, the concept of smart city is rising gradually. Wireless sensor network as an important technical support of smart city, its application in environmental monitoring and water resources management has a profound impact on economic growth. Water resource is one of the most dependent resources for human beings. With the growth of world population and the rapid development of economy, water resource crisis is constant, water pollution, water shortage and water waste coexist. How to build a perfect water resource economic policy is a worldwide problem at present. At present, the formulation of water resources policies is often based on experience or the knowledge system of decision makers. Due to the dynamic nature of water resources utilization and the incomplete information of decision makers, there are often policy failures, which affect economic growth. Based on this, this paper uses system dynamics model to study the mechanism of water resources management policies affecting economic growth by taking Gansu, Tianjin and Zhejiang as three qualitatively representative arid areas, transitional areas and water-rich areas. The research results show that under the same water resources policy coupling, different regions also have different eco-economic effects. The effect of coupled water resources policy is better than that of single water resources management policy.

Ground Tire Rubber as a Sustainable Additive: Transforming Desert Sand Behavior

Managing waste tires presents a significant challenge globally, particularly in regions experiencing high temperatures and shortage of landfill sites. This issue is affecting countries like Kuwait, where the abundance of waste tires is a major source of environmental and safety risks, particularly during the intensely hot summer months. This extreme heat has sparked numerous fires, leading to substantial air pollution due to thick black smoke. Given the limited disposal options, recycling waste tires and finding practical applications for ground tire rubber (GTR) is essential. To address the challenge, a comprehensive laboratory testing program was conducted, using locally produced rubber aggregates as an additive to Kuwait's local surface sands. Two new variables were examined namely the size and gradation of the GTR, and the density of the compacted mixes. For this purpose, two different sizes of rubber aggregates, fine and coarse produced locally, were utilized, and the impact of relative compaction on the strength and compressibility of the mixtures was investigated by testing samples compacted to the maximum density and to 95% of the maximum density. The results suggest that combining local surface sands with rubber tire additives results in a lighter, more permeable, and compressible material, contributing significantly to sustainable waste management. With 20% rubber additive the maximum dry density decreased by nearly 20%, and the permeability increased by 1.74–3.11 times and the compression index increased by 6.15 and 3.8 times with fine and coarse rubber respectively. The angle of friction remained unchanged at 36° with the addition of coarse rubber and decreased by 3°–4° with fine rubber. The change in behavior although not an increase in the strength and stiffness, offers a range of suitable practical applications in civil engineering and environmental management, including use as a drainage layer, embankment construction on soft ground, earth fill around retaining walls, an additive in asphalt mixes, and in manufacturing compressible tiles for sports facilities.

Green synthesis of silver nanoparticles by waste of Murcott Mandarin peel as a sustainable approach for efficient heavy metal removal from metal industrial wastewater

This study introduces a sustainable and environmentally friendly method for synthesizing silver nanoparticles (Ag-NPs) using waste from Murcott Mandarin peel (Citrus reticulata Blanco × C. sinensis (L.) Obs.). By repurposing agricultural waste as a precursor for nanoparticle synthesis, the research not only reduces waste but also aligns with green chemistry principles. The synthesis process involved extracting bioactive compounds from Murcott Mandarin peel, which acted as both reducing and stabilizing agents during nanoparticle formation. Characterization techniques, including UV–Vis spectroscopy and X-ray diffraction (XRD), confirmed the successful formation of silver nanoparticles. These nanoparticles demonstrated exceptional efficiency in removing heavy metals from metal industrial wastewater, particularly lead ions. Batch experiments revealed significant adsorption capabilities, with lead ions being uptake by silver nanoparticles at a rate of 42.7 mg/g under optimal conditions of pH 5.5 and 60 min of stirring. Additionally, Murcott Mandarin Solid Residue (MM-SR) obtained from the filtration process during Ag-NP synthesis exhibited promising lead ion uptake, reaching 6.6 mg/g under the same optimal conditions. The eco-friendly synthesis route and the efficient heavy metal removal capabilities of silver nanoparticles underscore the potential of utilizing agricultural waste in nanomaterial synthesis for wastewater treatment. This approach not only tackles waste disposal challenges but also generates value-added materials with practical applications in environmental management. Overall, the study emphasizes the importance of exploring innovative and sustainable pathways for nanoparticle synthesis, highlighting the promising role of silver nanoparticles synthesized from Murcott Mandarin peel waste in cost-effective and environmentally benign strategies for heavy metal removal in metal industrial wastewater treatment.

Recent Advances in Development of Biosensors for Monitoring of Airborne Microorganisms.

The early detection of infectious microorganisms is crucial for preventing and controlling the transmission of diseases. This article provides a comprehensive review of biosensors based on various diagnostic methods for measuring airborne pathogens. This article aims to explore recent advancements in the field of biosensors tailored for the detection and monitoring of airborne microorganisms, offering insights into emerging technologies and their potential applications in environmental surveillance and public health management. The study summarizes the research conducted on novel methods of detecting airborne microorganisms using different biological sensors, as well as the application of signal amplification technologies such as polymerase chain reaction (PCR), immunoassay reactions, molecular imprinted polymers (MIP) technique, lectin and cascade reactions, and nanomaterials. Antibody and PCR detection methods are effective for specific microbial strains, but they have limitations including limited stability, high cost, and the need for skilled operators with basic knowledge of the target structure. Biosensors based on MIP and lectin offer a low-cost, stable, sensitive, and selective alternative to antibodies and PCR. However, challenges remain, such as the detection of small gas molecules by MIP and the lower sensitivity of lectins compared to antibodies. Additionally, achieving high sensitivity in complex environments poses difficulties for both methods. The development of sensitive, reliable, accessible, portable, and inexpensive biosensors holds great potential for clinical and environmental applications, including disease diagnosis, treatment monitoring, and point-of-care testing, offering a promising future in this field. This review presents an overview of biosensor detection principles, covering component identification, energy conversion principles, and signal amplification. Additionally, it summarizes the research and applications of biosensors in the detection of airborne microorganisms. The latest advancements and future trends in biosensor detection of airborne microorganisms are also analyzed.

Response of soil erosion resistance to straw incorporation amount in the black soil region of Northeast China

Straw incorporation has been considered as an effective environmental management application to improve soil erosion resistance (SER) and organic carbon sequestration. SER is useful to evaluate soil erosion subjected to concentrated flow. Nevertheless, few studies have been performed to examine how SER varied with the amount of straw incorporation on sloping croplands in high latitude and cool regions. In the current study, the fixed bed scouring tests were conducted in a large hydraulic flume using undisturbed soil samples taken from Hebei small watershed in the black soil region of Northeast China. The response of SER to different straw incorporation amounts (0, 1.125, 2.25, 4.5, 6.75, 9.0 and 13.5 t ha−1) was quantified after three months of straw decomposition. The major influencing factors and the corresponding mechanisms were determined. The findings demonstrated that rill erodibility firstly decreased exponentially with straw incorporation amount (R2 = 0.93), while it slightly increased when straw incorporation amount was more than 9.0 t ha−1. Critical shear stress firstly increased logarithmically (R2 = 0.90) and then slightly decreased when the amount exceeded 9.0 t ha−1. Compared to the treatment of 0 t ha−1, rill erodibility reduced by 17.0%–92.8% and critical shear stress increased by 59.6%–127.2% across different treatments of straw incorporation. Rill erodibility had significant and negative correlations with soil organic matter content, aggregate stability, cohesion, root mass density, straw mass density and straw decomposition amount. The key mechanisms for promoting SER were derived by the direct and indirect effects of straw incorporation and its decomposition on soil physicochemical properties and crop roots. The amount of 9.0 t ha−1 was recommended as the optimum amount of straw incorporation in croplands in Northeast China. These findings are useful to understand how soil erosion resistance responds to the amount of straw incorporation and make rational environmental management policy for semi-humid and cool regions.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Comparative Analysis of Ground-Based Solar Irradiance Measurements and Copernicus Satellite Observations

Solar irradiance data provided by the Copernicus program are crucial for several scientific, environmental, and energy management applications, but their validation by means of ground-based measurements may be necessary, especially if daily and hourly data resolutions are required. The validation process not only ensures that reliable information is available for solar energy resource planning, power plant performance assessment, and grid integration, but also contributes to the improvement of the Copernicus system itself. Ground-based stations offer site-specific data, allowing for comprehensive assessments of the system’s performance. This work presents a comparative statistical analysis of solar irradiance data provided by the Copernicus system and ground-based measurements on a seasonal basis at three specific Italian reference sites, showing a maximum average relative error of less than 7% for hourly horizontal global irradiance in the irradiance range defined by the IEC 61724-2.

Implementation of a Wireless Sensor Network for Environmental Measurements

Nowadays, the need to monitor different physical variables is constantly increasing and can be used in different applications, from humidity monitoring to disease detection in living beings, using a local or wireless sensor network (WSN). The Internet of Things has become a valuable approach to climate monitoring, daily parcel monitoring, early disease detection, crop plant counting, and risk assessment. Herein, an autonomous energy wireless sensor network for monitoring environmental variables is proposed. The network’s tree topology configuration, which involves master and slave modules, is managed by microcontrollers embedded with sensors, constituting a key part of the WSN architecture. The system’s slave modules are equipped with sensors for temperature, humidity, gas, and light detection, along with a photovoltaic cell to energize the system, and a WiFi module for data transmission. The receiver incorporates a user interface and the necessary computing components for efficient data handling. In an open-field configuration, the transceiver range of the proposed system reaches up to 750 m per module. The advantages of this approach are its scalability, energy efficiency, and the system’s ability to provide real-time environmental monitoring over a large area, which is particularly beneficial for applications in precision agriculture and environmental management.

Backward and forward simulation of polycyclic aromatic hydrocarbons by the grid-scale model _validation and applications for environmental management

Polycyclic aromatic hydrocarbons (PAHs) associated with fine particulate matter (PM2.5) can cause serious health problems, but data are scarce. We have previously developed a grid-scale model (GSM) to simulate PM2.5-PAH levels on an hourly basis. This study aims to verify the applicability of the model to different years and to reasonably assess the long-term spatiotemporal effects on PAH variation in Kaohsiung. From the resulting database, the annual mean of PM2.5-PAH was found to have decreased from 3.18 in 2005 to 1.78 ng m−3 in 2018, representing an overall decrease of 44%. Thus, this study found that the progressive decrease in PAH levels was closely related to green transport and the gradual tightening of industrial operation regulations. Namely, in the urban area near the central public transport hubs, the estimated PAHs had significantly decreased by 16% (0.37 ng m−3) in 2009 with the operation of the high-speed railway in 2007 and the mass rapid transit in 2008. Near industrial areas, PAHs were reduced by environmental regulations, including air pollution control fees and cap-and-trade policies. By using GSM simulation, this study demonstrated a useful and feasible urban planning tool, and can serve as a reference for future studies related to epidemiology and environmental management.

Enhancing shallow water quality monitoring efficiency with deep learning and remote sensing: A case study in Mar Menor

Satellite remote sensing technology has proven effective in monitoring various environmental parameters, but its efficiency in assessing shallow lakes has been limited. This study applies state-of-the-art machine and deep learning algorithms supported by classical statistic methods to analyze remote sensing data to measure chlorophyll-a (Chl-a) concentration levels. Focused on a shallow coastal lagoon, Mar Menor, this work analyzes statistically daily Sentinel 3 information behaviour and compares Machine Learning and Deep Learning techniques to enhance efficiency and accuracy data of this satellite. Convolutional Neural Networks (CNNs) stand out as a robust choice, capable of delivering excellent results even in the presence of anomalous events. Our findings demonstrate that the CNN-based approach directly utilizing satellite data yields promising results in monitoring shallow lakes, offering enhanced efficiency and robustness. This research contributes to optimizing remote sensing data to and produce a continuous information flow addressed to monitoring shallow aquatic ecosystems with potential environmental management and conservation applications.

A Critical Review of the Effectiveness of Biochar Coupled with Arbuscular Mycorrhizal Fungi in Soil Cadmium Immobilization.

Cadmium-contaminated soil significantly threatens global food security and human health. This scenario gives rise to significant worries regarding widespread environmental pollution. Biochar and arbuscular mycorrhizal fungi (AMF) can effectively immobilize cadmium in the soil in an environmentally friendly way. Existing studies have separately focused on the feasibility of each in remediating polluted soil. However, their association during the remediation of cadmium-polluted soils remains unclear. This review paper aims to elucidate the potential of biochar, in conjunction with AMF, as a strategy to remediate soil contaminated with cadmium. This paper comprehensively analyzes the current understanding of the processes in cadmium immobilization in the soil environment by examining the synergistic interactions between biochar and AMF. Key factors influencing the efficacy of this approach, such as biochar properties, AMF species, and soil conditions, are discussed. The influences of biochar-AMF interactions on plant growth, nutrient uptake, and overall ecosystem health in cadmium-contaminated environments are highlighted. This review indicates that combining biochar and AMF can improve cadmium immobilization. The presence of AMF in the soil can create numerous binding sites on biochar for cadmium ions, effectively immobilizing them in the soil. Insights from this review contribute to a deeper understanding of sustainable and eco-friendly approaches to remediate cadmium-contaminated soils, offering potential applications in agriculture and environmental management.

The Clothes Matter—Exploiting Agronomical Functions of Trichogenic Selenium Nanoparticles Sharing Activities with Biological Systems Wherein (Were) Formed

The formation of biogenic selenium nanoparticles (SeNPs) through microbial activities is a promising technique that can contribute to the development of reliable, non-toxic and environmentally friendly synthesis methods. Among these, under optimal conditions, myconanotechnology confers particular characteristics due to the generation of bioactive fungal metabolites with various bioactivities. The formed SeNPs are known to be stabilized by the biomolecules of the microorganism, forming a so-called bio-corona or capping structure. The composition of this bio-corona greatly impacts the SeNPs activity, but investigations have been limited to date. The SeNPs produced by Trichoderma sp. have potential applications in crops and environmental management, as both selenium and Trichoderma are known to benefit cultivated plants and phytoremediation. This review summarizes the biosynthesis of SeNPs by Trichoderma sp. and contextualizes the possible correlations between SeNPs and biomolecules produced by Trichoderma; it also provides a missing analysis that could help understand and optimize this process. Biosynthesis methods and probable mechanisms are briefly discussed as well as the role and applications of trichogenic SeNPs as plant protectants, plant biostimulants, and safe biofortifying agents. The knowledge gaps related to mechanisms of trichogenic SeNPs biosynthesis, the control of the desired characteristics for a specific agricultural function, and technology scale-up are discussed in connection with the needed future research directions.

Fractal representations in image processing of remote sensing of the earth

This article explores the application of fractal representations in the image processing of remote sensing data for Earth observation. Fractals, with their self-similar properties and complex patterns, offer a powerful mathematical framework for analyzing the intricate structures found in natural landscapes. The study highlights the advantages of using fractal-based methods over traditional image processing techniques, particularly in capturing the multifaceted textures and irregularities of Earth’s surface features. By leveraging fractal geometry, enhanced accuracy in the classification and interpretation of remote sensing images is achieved. This approach facilitates better monitoring and understanding of environmental changes, land use patterns, and natural disasters. The findings underscore the potential of fractal representations to significantly improve the quality and efficacy of remote sensing image analysis, providing a robust tool for Earth science research and practical applications in environmental management.

Oxidation-alkaline-enhanced abiotic humification valorizes lignin-rich biogas digestate into artificial humic acids

This study introduces a cost-effective, mild thermal abiotic humification method for producing highly humified artificial humic acids (AHAs) from lignin-rich biogas digestate. Derived from the anaerobic digestion of cattle manure, the digestate slurry undergoes an MnO2-KOH-urea-enhanced humification reaction. Key process variables, such as MnO2 dose (0–15 mg/L), KOH dose (0–1 mol/L), urea dose (0–1.2 mol/L), reaction time (30–150 min), and temperature (25–85 °C), were systematically explored to optimize AHA yield, carboxylic acid content, and lignin removal. Optimal conditions, employing 7.69 mg/L of MnO2, 0.57 mol/L of KOH, and 0.63 mol/L of urea at 85 °C for 106 min, resulted in an impressive AHA yield of 32.15%, featuring a significant carboxylic acid content of 3.325 mmol/g. Under these conditions, up to 65% of lignin was effectively removed, accompanied by the release of orthophosphate up to 258 mg/L. The produced AHAs exhibited reduced toxicity, as demonstrated by substantial reductions of 54.13%, 57.14%, and 42.50% in phenols, furfural, and hydroxymethylfurfural, respectively. Notably, the AHAs displayed favorable characteristics, including a lower molecular weight (760.49 g/mol), diminished aromaticity (66.25% reduction), higher humification degree (lower C/N ratio of 8.79), increased oxidation degree (higher O/C ratio of 0.6), and elevated spectral index of humification (higher E4/E6 of 4.58). Analytical techniques, such as FT-IR, XPS, and TGA-MS, revealed chemical resemblance and enhanced functionality of AHAs compared to natural counterparts. Differentiation between AHA, lignin, and humification residues was confirmed through SEM-EDX, ICP-OES, and organic/inorganic carbon analyses. The obtained AHAs exhibit promising characteristics suitable for diverse applications in sustainable agriculture and environmental management.

4D structural changes and pore network model of biomass during pyrolysis

Biochar is an engineered carbon-rich substance used for soil improvement, environmental management, and other diverse applications. To date, the understanding of how biomass affects biochar microstructure has been limited due to the complexity of analysis involved in tracing the changes in the physical structure of biomass as it undergoes thermochemical conversion. In this study, we used synchrotron x-ray micro-tomography to visualize changes in the internal structure of biochar from diverse feedstock (miscanthus straw pellets, wheat straw pellets, oilseed rape straw pellets, and rice husk) during pyrolysis by collecting a sequence of 3D scans at 50 °C intervals during progressive heating from 50 °C to 800 °C. The results show a strong dependence of biochar porosity on feedstock as well as pyrolysis temperature, with observed porosity in the range of 7.41–60.56%. Our results show that the porosity, total surface area, pore volume, and equivalent diameter of the largest pore increases with increasing pyrolysis temperature up to about 550 °C. The most dramatic development of pore structure occurred in the temperature range of 350–450 °C. This understanding is pivotal for optimizing biochar’s properties for specific applications in soil improvement, environmental management, and beyond. By elucidating the nuanced variations in biochar’s physical characteristics across different production temperatures and feedstocks, this research advances the practical application of biochar, offering significant benefits in agricultural, environmental, and engineering contexts.

What is the Effect of a Magnetic Field on Dye Adsorption onto Graphite Carbon?

This research explores the impact of magnetic fields on dye adsorption onto graphite carbon, utilizing electric currents to generate varying magnetic field strengths, as determined by the Biot-Savart law. The study demonstrates that even with small current magnitudes typically used in physics laboratories, the generated magnetic fields significantly influence dye adsorption. Through experiments with currents ranging from 1.5 A to 7.5 A, resulting in magnetic fields from 1.54 µT to 4.63 µT, we observed enhanced adsorption for congo red, methylene blue, and methyl orange. In contrast, phenol red exhibited a unique desorption pattern due to electrostatic repulsion. Temperature variations were noted but were considered to have a negligible effect on the adsorption behavior. The findings highlight the crucial role of magnetic energy density and the charge of dye molecules in the adsorption process, leading to the conclusion that magnetic fields, indeed, play a significant role in influencing dye adsorption onto graphite carbon, with potential applications in environmental conservation and industrial waste management.

Spaceborne SAR Time-Series Images Change Detection Based on SAR-SIFT-Logarithm Background Subtraction

Synthetic Aperture Radar (SAR) image change detection aims to detect changes with images of the same area acquired at different times. It has wide applications in environmental monitoring, urban planning and resource management. Traditional change detection methods for spaceborne SAR time-series images typically adopt a pairwise comparison strategy to obtain multi-temporal change information. However, this kind of method has the problem of losing the overall change information, which is time consuming. To address this problem, this paper proposes a new change detection algorithm for spaceborne SAR time-series data based on SAR-SIFT-Logarithm Background Subtraction. This algorithm combines the SAR-SIFT image registration technology with Logarithm Background Subtraction. The method first preprocesses the input time-series data with steps like noise reducing and radiometric calibration. Then, the images will be coregistered by the SAR-SIFT step to avoid mismatches-induced detection performance degradation. Next, the parts that remained unchanged throughout the time period are modeled with a median filter to obtain the static background. The change information is then obtained via the subtraction of background and CFAR detection and clustering. The proposed algorithm is validated using the Sentinel-1 GRD and PAZ-1 time-series dataset. Experimental results demonstrate that the proposed method effectively detects the overall change information and reduces processing time compared to traditional pairwise comparison methods.

Sensitive fluorescent detection of o-aminophenol by hemicyanine boronic acid

O-Aminophenol (OAP) is widely used in various industries, but it can have severe negative impacts on both the environment and human health. Herein, we reported the development of hemicyanine boronic acid (HBA) for the fluorescent detection of OAP. The reaction of HBA with OAP produced a strong fluorescence emission at 675 nm because of the generation of tricyclic borate ester hemicyanine (TBEH). The detection was very rapid, sensitive and specific. The detection had a linear range 0.1 – 10.0 µM in ethanol with a detection limit of 60 nM in water and ethanol. The accuracy and precision of our results were successfully verified via HPLC analysis. Our study offers a valuable tool for the facile and efficient detection of OAP, with practical applications in environmental and health management.

Annual Review of Ecology, Evolution, and Systematics, Volume 53

About This Journal—The Annual Review of Ecology, Evolution, and Systematics, in publication since 1970, covers significant developments in the fields of ecology, evolutionary biology, and systematics, as they apply to all life on Earth. Essay reviews cover topics ranging from phylogeny, speciation, and molecular evolution through behavior and evolutionary physiology to population dynamics, ecosystems processes, and applications in invasion biology, conservation, and environmental management. 20 articles in Volume 53.