Efficient Restoration Strategy Research Articles

Natural and agricultural disturbances differentially impact seedling emergence from soil seed banks in hyperarid ecosystems

Saudi Arabia has implemented ambitious environmental protection programs by creating numerous nature reserves throughout the country. Establishment of the latter nature reserves has led to farm abandonment and the initiation of ecosystem recovery processes. Agricultural practices are known to impact the structure and physicochemical properties of soils while also often markedly affecting natural ecosystem restoration processes. Moreover, weed proliferation in crop fields may modify soil seed banks (SSB), thereby impacting subsequent vegetation recovery. Therefore, it is essential to assess SSB compositions in degraded sites, such as abandoned farms (AF), so as to identify weed species and design efficient restoration strategies in hyperarid ecosystems. In this study, SSB compositions in upper and deep soil layers, standing vegetation compositions, and soil chemical properties were analyzed and compared for two natural ecosystems (NE), two abandoned orchards (AO), two AF, and two natural evaporite basins (EB). NE, AO, AF, and EB all exhibited similar chemical properties, suggesting that former agricultural activities have been guided by a fine understanding of the local environments. Agriculture had impacted the species composition of the observed standing vegetation and germinable SSBs, which could be partly explained by soil property modifications. The findings highlighted that SSBs would warrant detailed study prior to designing ecological restoration strategies, and that the drivers of horizontal and vertical weed dissemination in hyperarid ecosystems should also be explored to gain further insight into weed proliferation patterns and to adapt restoration strategies accordingly.

Agglomerative Hierarchical Clustering Methodology to Restore Power System considering Reactive Power Balance and Stability Factor Analysis

Despite there are significant advancements in modern power systems, blackouts remain a potential risk, necessitating efficient restoration strategies. This paper introduces an innovative concept for power system restoration, focusing on balancing active and reactive power while ensuring voltage stability. For instance, this paper employs an agglomerative clustering technique, which partitions the power system into segments with balanced reactive power, facilitating swift restoration postblackout. Central to this methodology is the use of the line stability factor, which assesses the voltage stability of individual lines, identifying the system’s stronger and weaker sections based on voltage stability levels. This paper demonstrates the effectiveness of the proposed methodology through case study analysis, comparing voltage stability levels across agglomerative clusters and their geographical locations. The power system is divided into two stable partitions, considering the number of black-start generators, available reactive power, and voltage stability levels. This partitioning reveals that the clusters formed by the agglomerative method are inherently stable, suggesting enhanced system stability, dependability, and availability during the restoration phase following a blackout. In addition, this paper discusses the potential causes of blackouts, offering insights into their prevention, and finishes with a novel clustering methodology for power systems, considering reactive power and voltage stability. This method facilitates the parallel restoration of the system’s independent partitions, significantly reducing restoration time; it addresses critical challenges and outcomes, underscoring the methodology’s potential to revolutionize blackout recovery processes in modern power systems.

Deep Learning Based Effective Technique for Smart Grid Contingency Analysis Using RNN with LSTM

Smart grids play a crucial role in modernizing power systems, yet their susceptibility to disruptions necessitates effective contingency analysis for reliable operation. Traditional algorithms lack prediction accuracy for mitigation. To address this, a proposed method employs LSTM networks within a DL RNN framework, utilizing a logical collection of pertinent data—historical smart grid operation data, sensor measurements, weather conditions, and contingency events. This data undergoes preprocessing to train an LSTM-based DL RNN model capable of capturing temporal dependencies and complex dynamics within the smart grid system. The trained model yields a substantial improvement in prediction accuracy, increasing from 88% to 93%, while decreasing false positive and false negative rates from 3.2% to 1.25% with optimal time detection. Leveraging deep learning and recurrent neural networks, this approach offers accurate predictions, proactive decision support, and efficient restoration strategies, ultimately elevating the resilience and reliability of smart grid systems. The solution’s dataset encompasses a comprehensive array of relevant information. The neural network architecture integrates DL RNN with LSTM networks, showcasing its efficacy in enhancing prediction accuracy for smart grid contingency analysis. Evaluation metrics such as RMSE and MAPE providing a reliable foundation for proactive decision-making and fortifying the smart grid’s resilience against various contingencies.

Trichocoleus desertorum isolated from Negev desert petroglyphs: Characterization, adaptation and bioerosion potential

The Negev petroglyphs are considered valuable cultural heritage sites, but unfortunately, they are exposed to deterioration processes caused by anthropogenic and natural forces. Despite the many studies that have already pointed to the role of cyanobacteria in biogenic rock weathering, the knowledge involved in the process is still lacking. In this study, a cyanobacterial strain was isolated from the Negev Desert petroglyphs aiming to reveal its involvement in geochemical cycles and in the weathering processes of the rock substrate. The strain was characterized using morphological, molecular, and microscopic studies. The morphological research revealed a green-bluish, bundle-forming filamentous strain characterized by trichomes embedded in a common sheath. A combination of Nanopore and Illumina sequencing technologies facilitated the assembly of a near-complete genome containing 5,458,034 base pairs. A total of 5027 coding sequences were revealed by implementing PROKKA software. Annotation of five replicas of the 16S ribosomal RNA genes revealed that the Negev cyanobacteria isolate is closely (99.73 %) related to Trichocoleus desertorum LSB90_MW403957 isolated from the Sahara Desert, Algeria. The local strain was thus named Trichocoleus desertorum NBK24 CP116619. Several gene sequences that code for possible environmental adaptation mechanisms were found. Our study also identified genes for membrane transporters involved in the exchange of chemical elements, suggesting a possible interaction with rock minerals. Microscopic observations of T. desertorum NBK24 CP116619 infected onto calcareous stone slabs under laboratory conditions demonstrated the effect of the isolated cyanobacteria on stone surface degradation. In conclusion, the findings of this study further our understanding of terrestrial cyanobacterial genomes and functions and highlight the role of T. desertorum NBK24 CP116619 in stone weathering processes. This information may contribute to the creation of efficient restoration strategies for stone monuments affected by cyanobacteria.

Predicting cascading extinctions and efficient restoration strategies in plant–pollinator networks via generalized positive feedback loops

The extinction of a species in a plant–pollinator mutualistic community can cause cascading effects and lead to major biodiversity loss. The ecologically important task of predicting the severity of the cascading effects is made challenging by the complex network of interactions among the species. In this work, we analyze an ensemble of models of communities of plant and pollinator species. These models describe the mutualistic inter-species interactions by Boolean threshold functions. We show that identifying generalized positive feedback loops can help pinpoint the species whose extinction leads to catastrophic and substantial damage to the whole community. We compare these results with the damage percentage caused by the loss of species identified as important by previously studied structural measures and show that positive feedback loops and the information gained from them can identify certain crucial species that the other measures fail to find. We also suggest mitigation measures for two specific purposes: (1) prevent the damage to the community by protecting a subset of the species, and (2) restore the community after the damage by restoring a subset of species. Our analyses indicate that the generalized positive feedback loops predict the most efficient strategies to achieve these purposes. The correct identification of species in each category has important implications for conservation efforts and developing community management strategies.

Spatiotemporal seed transfer zones as an efficient restoration strategy in response to climate change

AbstractRestoration of wild plant populations in a changing environment is not a simple task, and it becomes increasingly complex and challenging in the context of climate change. In the present study, a spatiotemporal approach was used to delimit provisional seed transfer zones (STZs), for restoration activities involving two wild perennial grasses in Argentina. Ecogeographical land characterization maps were built specifically for the two species of Trichloris genus for the present bioclimatic conditions to define the different STZs; then, they were projected for two future climate scenarios (2050 and 2070). This allowed us to identify populations occurring in cells that underwent changes in ecogeographical categories, potential future beneficiaries of germplasm, and populations that could be used as corresponding source populations under the present conditions. Finally, the conservation status of populations was surveyed and a germplasm collection for future restoration activities was proposed. For the 2050 scenario, for Trichloris crinita, 32 potential beneficiary populations belonging to nine changing categories were identified, whereas for Trichloris pluriflora, four changing categories determined seven beneficiary populations. The number of changing categories and, consequently, the beneficiary populations increased in the 2070 scenario in both species. Several potential seed source populations are already stored in Argentine germplasm banks, but there is little representation of potential beneficiary populations. Spatial locations of still non‐conserved populations, both seed sources and beneficiaries, were prioritized for future germplasm collecting missions. This novel approach used for Trichloris spp. can also be adopted for other species for collection and/or restoration purposes in the light of climate change.

Applications of resilience engineering principles in different fields with a focus on industrial systems: A literature review

This paper reviews literature that addresses applications of resilience engineering principles to various fields. Recently the concept has attracted great attention from a technical and industrial perspective. The primary focus of this paper is to review the resilience engineering applications to industrial systems with the purpose of applying them to the chemical industry. A systematic review is performed to classify peer-reviewed journal papers that are associated with resilience engineering applications into three categories: industrial systems, ecological systems, and interlinked systems. The literature in the category of industrial systems is further divided based on the type of approaches such as field studies, case studies, methodologies, and mathematical modeling. After thoroughly analyzing the literature, four key research areas are identified: Considering socio-technical factors for resilience assessment efficiently; Inculcating the possibility of multiple disasters in resilience assessment; Design optimization for resilience enhancement; Efficient restoration strategies. All these research areas have not been explored exclusively for chemical facilities to a great extent. It is concluded that if these research areas are addressed appropriately, it would help in triggering the research pertaining to the application of resilience engineering principles in chemical facilities.

Bottom-Up Resource and Cost Estimation for Restoration of Supply Chain Interdependent Critical Infrastructure

Extreme events can damage or destroy multiple supply chain interdependent critical infrastructures elements. Although much research has focused on developing efficient restoration strategies, and/or making critical infrastructures more resilient, practitioners need tools to determine resources necessary to restore such damage. The methodology developed in this research estimates both the resources required to support the repair personnel, and restore different infrastructure elements. This method uses a dynamic mathematical model that establishes a framework to estimate post-disaster restoration costs from a whole system perspective. The model is validated with a case study of the resources required to restore multiple infrastructures that were damaged by the EF-5 tornado that struck Joplin, Missouri on May 22, 2011. Engineering managers, city planners, and policy makers can use the methodologies developed in this research to develop effective disaster planning schemas and to prioritize post-disaster restoration operations.

The effects of land degradation on plant community assembly: Implications for the restoration of the Tibetan Plateau

AbstractUnderstanding how biotic and abiotic filters drive plant distributions is critical for informing restoration efforts of degraded lands. However, it remains unclear whether or not it is possible to develop efficient restoration strategies that are based on field investigations? Here, we conducted a field‐based investigation along a land degradation gradient on the Tibetan Plateau. Along this gradient, we compared species composition, Pianka's niche overlap, and total aboveground biomass among grasses, sedges, legumes, and forbs. We also used Faith's (1992) phylogenetic diversity index (PD) and the net relatedness index (NRI) to measure community phylogenetic patterns. To understand the effects of abiotic filtering, we measured soil pH, moisture, electrical conductivity, total soil organic carbon, microbial biomass carbon, and microbial biomass nitrogen. Our results show that grasses replaced sedges and mesoxerophytes replaced mesohydrophytes with increasing land degradation. We also found that niche overlap declined with increasing degradation intensity. Furthermore, grass biomass increased, while sedges and legumes decreased, and forb biomass showed a hump‐shaped relationship with degradation intensity. In addition, the communities transitioned from a clustered to a more random phylogenetic pattern. Soil conditions changed from acidic to alkaline and from fertile to harsh (p < .05). High niche overlap indicates a high biotic filtering at lightly degraded land where abiotic filtering is less stressful. However, when degradation is intense, abiotic filtering is apparent, as indicated by low levels of niche overlap. Overall, we suggest that distantly related, arid tolerant and hardy plants, and soil reclamation should be considered in degraded alpine lands restoration.

Monitoring soil biological properties during the restoration of a phosphate mine under different tree species and plantation types

Open-pit mining activities for minerals and metals have left an international legacy of highly polluted soils and degraded landscapes. Reforestation is usually supposed to restore soil fertility and ecosystem services, and therefore to remediate and recover polluted sites. However, our understanding of the effects of tree species and recovery time on the restoration of abiotic and biotic soil properties remains scarce. In this study, the effects of a series of restoration chronosequence (unrestored control, 10-year, 20-year, and natural forest) and plantation types (nitrogen-fixing broad-leaved Alnus nepalensis and coniferous Cupressus torulosa monocultures, as well as their mixed plantation) on soil physicochemical and biological properties were explored in a phosphate mine. Our results showed that soil quality index (SQI), which integrates important soil physical, chemical, and biological parameters including bulk density, soil organic carbon and microbial biomass, could provide valuable information about soil health. The average SQI values of 20-year plantations were 1.55 times of 10-year plantations, and the mixed plantation was 1.13 and 1.27 times of A. nepalensis and C. torulosa monoculture, respectively. Thus, recovery time, as well as plantation type, were the main determinants of the alterations in key soil conditions during the phosphate mining restoration. At the beginning restoration (10 years), A. nepalensis monoculture performed better than C. torulosa, providing an efficient restoration strategy for early revegetation. The mixed plantation of C. torulosa and A. nepalensis showed the higher moisture and soil organic carbon than did the monocultures, especially after 20 years of revegetation. Hence, our findings address a helpful guideline for selection of tree species and plantation practices, thereby aiding in long-term success of restoration.

Using Transfer Function Analysis to develop biologically and economically efficient restoration strategies

Rare species across taxonomic groups and biomes commonly suffer from multiple threats and require intensive restoration, including population reintroduction and threat control. Following reintroduction, it is necessary to identify what level of threat control is needed for species to persist over time. Population reintroduction and threat control are time intensive and costly. Thus, it is pragmatic to develop economically efficient restoration strategies. We combined transfer function analysis and economic cost analysis to evaluate the effects of biologically meaningful increases in demographic processes on the persistence of a reintroduced population of a Hawaii endemic long-lived shrub, Delissea waianaeensis. We show that an increase in fertility by 0.419 following the suppression of non-native rodents or an increase by 0.098 in seedling growth following the suppression of invasive molluscs would stabilize the population (i.e., λ = 1). Though a greater increase in fertility than seedling growth was needed for the reintroduced population to persist over time, increasing fertility by suppressing rodents was the most cost effective restoration strategy. Our study emphasizes the importance of considering the effects of large increases in plant vital rates in population projections and incorporating the economic cost of management actions in demographic models when developing restoration plans for endangered species.

Exploiting of honey-associated Bacillus strains as plant-growth promoting bacteria for enhancing barley growth in rare earth tailings

In the coming decades, exploitation of plant growth promoting bacteria (PGPB) will be a major trend in sustainable agriculture. Except for rhizobacteria, the bacteria inhabiting the non-rhizosphere could be considered the supplementary microbial source to exploit PGPB. Rare earth tailings soil (RETS) has caused a serious threat to sustainable agriculture due to excessive aluminum (Al) toxicity under acidic condition (pH < 5.5). The efficient restoration strategy is to combine phytoremediation and PGPB. The aim of this work was to screen honey-associated Bacillus strains as PGPB to improve barley (Hordeum vulgare L.) growth in RETS. Nine Bacillus strains from honey were initially selected with higher tolerance to acid (pH 4.0) and Al stress (1.5 mM). Only six strains among these nine strains could produce ACC deaminase. The nine strains were all efficient in dissolving phosphate, producing organic acid, siderophore, and IAA. The nine strains could promote barley seedlings growth mainly via production of organic acid, ACC deaminase. However, this growth promotion was weakened slightly by siderophore and phosphate solubilization under acidic condition. On the whole, inoculation with the nine strains obviously enhanced barley seedlings growth in RETS. Thus, the nine honey-associated Bacillus strains could be exploited as PGPB to enhance barley growth in RETS.

A novel adaptive tolerance filter for random valued impulse noise suppression in digital grey and color images

During acquisition, transmission, storage and retrieval, quite often digital images become noised and mask the important details of an image and also present themselves with an ugly look. Such images if not processed properly, become useless for subsequent image processing operations like segmentation, classification etc. Hence the quality improvement (through denoising) of such noisy images becomes an important operation in the field of image processing. This paper proposes a two stage detection-estimation based filtering system to suppress random valued impulse noise from digital grey and color images based on neighborhood statistics of pixels of the working window under consideration. An adaptive working window and the adaptive tolerance computed from the pixels belonging to the current filtering window facilitates an appropriate detection of noisy pixels in the first phase, followed by the simple and computationally efficient restoration strategy in the second stage. The Simulation results prove that the proposed scheme exhibits much superior performance in comparison with other state of art image filtering methods in suppressing the random valued impulse noise from the digital grey and color images.

An interdependent layered network model for a resilient supply chain

This paper addresses the problem of designing supply chains that are resilient to natural or human-induced extreme events. It focuses on the development of efficient restoration strategies that aid the supply chain in recovering from a disruption, thereby limiting the impact on its customers. The proposed restoration model takes into account possible disruptions to infrastructures, e.g., transportation and communications, by explicitly formulating their logical relationships with supply chains. A problem solving process is proposed that provides for cooperation between the managers of the infrastructures and the managers of the supply chains disrupted by an extreme event. Both the model and the problem solving process are exercised with a realistic industry problem.

Active restoration of woody canopy dominants in degraded South African semi‐arid thicket is neither ecologically nor economically feasible

AbstractQuestionWill the planting of nursery‐propagated woody canopy species within severely degraded Arid Subtropical Thicket once dominated by the succulent shrub Portulacaria afra (Spekboom) be an efficient restoration strategy to employ in addition to the current restoration protocol of planting a monoculture of P. afra truncheons?LocationKrompoort, a farm located on the northern footslopes of the Groot Winterhoek mountains, near Kirkwood, Eastern Cape, South Africa.MethodsWe planted, in degraded, intact and three differently aged post‐restoration (P. afra truncheons) sites, nursery‐propagated individuals of two woody canopy dominants (Pappea capensis and Searsia longispina), and two inter‐canopy shrubs (Lycium ferocissimum and Rhigozum obovatum) in Sep 2008 (spring). The experiment was repeated again in May 2009 (autumn) and a succulent canopy species (P. afra) was added. We assessed restoration success in terms of the survival of planted individuals after 24 mo (spring planting) and 12 mo (autumn planting). The estimated cost of a restoration effort to establish two woody canopy dominant species with the large‐scale planting of P. afra was calculated and compared with that of the already established protocol of planting only P. afra truncheons.ResultsSurvival after spring (24 mo) and autumn (12 mo) plantings of the two woody canopy species was less than 5%, whereas survival of L. ferocissimum was low (19%), R. obovatum good (70%) and P. afra excellent (100%). Contrary to expectations, survival was not related to a gradient of intactness encompassing degraded, restoration and intact treatments that are associated with increasing biomass and soil carbon. The costs of incorporating the four woody canopy species into the restoration programme's protocol were 2.4 times the costs of restoring with P. afra alone.ConclusionsPlanting propagules of canopy species other than P. afra is likely to render the programme economically unfeasible, depending on the price of carbon. We conclude that biodiversity goals for the restoration programme are better achieved via spontaneous recruitment of woody canopy and other species, even though this may take more than 40 yr post restoration.

Construction of System Restoration Strategy with PMU Measurements

Power system restoration is well-recognized as one of the major technologies to improve system reliability. A high efficient restoration strategy is established and implemented with accurate information acquisition. Phasor measurement unit (PMU) provides a state-of-the-art information monitoring technology. In this paper, with PMU measurements, several algorithms are proposed to ensure complete observability of systems under regular operating conditions and during system restoration process. Case studies on IEEE 14, 30, 57, 118 and 300 – bus systems validate efficiency of the proposed algorithms.

Comparative assessment of large-scale marine eutrophication: North Sea area and Adriatic Sea as case studies

In the last 50 yr, marginal seas under freshwater influence have become affected by eutrophication. The large areas involved render its assessment difficult. In this paper, a spatial and comparative approach is presented assuming that hydromorphology together with organic matter production control the various consequences of nutrient overenrichment. We have developed 2 eutrophication indices of shallow marine ecosystems using hydrodynamic modelling and optical satellite remote-sensing. The indices are tested in systems characterised by contrasting physical regimes, i.e. the Adriatic and North Sea. The physically sensitive area index (PSA) integrates the sup- porting factors of eutrophication, i.e. the physical conditions driving primary production in the upper layer and oxygen availability near the bottom. The eutrophication risk index (EUTRISK) characterises the spatial distribution of potential hypoxia at a monthly timescale. It is based on an oxygen budget between the physical capacity to store and renew the oxygen near the seabed and the flux of organic matter reaching the sediment, estimated primarily from satellite-derived chlorophyll a data. The indices identify 3 main types of eutrophicated waters: (1) eutrophic and sensitive, (2) mesotrophic and sensitive and (3) eutrophic and resistant. In Category 1 oxygen depletion occurs recurrently because both the main pressure and supporting factors are unfavourable (e.g. coastal waters south of the Po river mouth). In Category 2, severe hypoxia or anoxia occur due to particularly adverse physical con- ditions, even when primary production is relatively low (e.g. the Kattegat and NE part of the north- ern Adriatic Sea). Category 3 comprises areas where severe hypoxia near the seabed is prevented by permanent tidally induced vertical mixing; however nutrient overenrichment is recognised as lead- ing to alterations in the food-web structure and functioning (e.g. Bay of Seine). The EUTRISK index forms the basis of a comparative tool for the assessment and monitoring of marine eutrophication risk. The PSA index, which provides an understanding of physical vulnerability on a large scale, indicates the relative threshold of nutrient discharge, i.e. the assimilative capacity of marine ecosystems. This first assessment of the underlying processes controlling marine eutrophication is a prerequisite for efficient restoration strategies on a large scale.