Secondary Extinction Research Articles

Extinction cascades, community collapse, and recovery across a Mesozoic hyperthermal event

Mass extinctions are considered to be quintessential examples of Court Jester drivers of macroevolution, whereby abiotic pressures drive a suite of extinctions leading to huge ecosystem changes across geological timescales. Most research on mass extinctions ignores species interactions and community structure, limiting inference about which and why species go extinct, and how Red Queen processes that link speciation to extinction rates affect the subsequent recovery of biodiversity, structure and function. Here, we apply network reconstruction, secondary extinction modelling and community structure analysis to the Early Toarcian (Lower Jurassic; 183 Ma) Extinction Event and recovery. We find that primary extinctions targeted towards infaunal guilds, which caused secondary extinction cascades to higher trophic levels, reproduce the empirical post-extinction community most accurately. We find that the extinction event caused a switch from a diverse community with high levels of functional redundancy to a less diverse, more densely connected community of generalists. Recovery was characterised by a return to pre-extinction levels of some elements of community structure and function prior to the recovery of biodiversity. Full ecosystem recovery took ~7 million years at which point we see evidence of dramatically increased vertical structure linked to the Mesozoic Marine Revolution and modern marine ecosystem structure.

Predicted community consequences of spatially explicit global change-induced processes on plant-insect networks.

Plant-insect trophic systems should be particularly sensitive to processes altering species spatial co-occurrences, as impacts on one level can cascade effectively through the strong trophic reliance to the other level. Here, we predicted the biogeography of Lepidoptera-plant communities under global-change scenarios, exploiting spatially resolved data on 423 Lepidoptera species and their 848 food plants across the German state of Baden-Württemberg (ca. 36,000 km2). We performed simulations of plant extinction and Lepidoptera expansion, and respectively assessed their cascading consequences-namely secondary extinction of Lepidoptera and change in functional distance of plants-on the interaction networks. Importantly, the simulations were spatially explicit, as we accounted for realistic landscape contexts of both processes: Plant extinctions were simulated as "regional" (a species goes extinct in the whole region at once) vs. "isolation-driven" (a species gradually goes extinct from the peripheral or isolated localities according to its real regional distribution); Lepidoptera expansions were simulated with random, northward, and upward directions according to real topography. The consequences were assessed based on empirical community composition and trophic relationships. When evaluated by regional richness, the robustness of Lepidoptera assemblages against secondary extinctions was higher under isolation-driven plant extinctions than regional plant extinction; however, this relationship was reversed when evaluated by averaged local richness. Also, with isolation-driven plant extinctions, Lepidoptera at the central sub-region of Baden-Württemberg appeared to be especially vulnerable. With Lepidoptera expansions, plants' functional distances in local communities dropped, indicating a possible increase of competition among plants, yet to a lesser extent particularly with upward movements. Together, our results suggested that the communities' composition context at the landscape scale (i.e., how communities, with respective species composition, are arranged within the landscape) matters when assessing global-change influences on interaction systems; spatially explicit consideration of such context can reveal localised consequences that are not necessarily captured via a spatially implicit, regional perspective.

Species motif participation provides unique information about species risk of extinction.

Loss of species in food webs can set in motion a cascade of additional (secondary) extinctions. A species' position in a food web (e.g. its trophic level or number of interactions) is known to affect its ability to persist following disturbance. These simple measures, however, offer only a coarse description of how species fit into their community. One would therefore expect that more detailed structural measures such as participation in three-species motifs (meso-scale structures which provide information on a species' direct and indirect interactions) will also be related to probability of persistence. Disturbances affecting the basal resources have particularly strong effects on the rest of the food web. However, how disturbances branch out and affect consumer persistence depends on the structural pattern of species interactions in several steps. The magnitude, for example, the proportion of basal resources lost, will likely also affect the outcome. Here, we analyse whether a consumer's risk of secondary extinction after the removal of basal resources depends on the consumer's motif participation and how this relationship varies with the severity of disturbance. We show that consumer species which participate more frequently in the direct competition motif and less frequently in the omnivory motif generally have higher probability of persistence following disturbance to basal resources. However, both the strength of the disturbance and the overall network structure (i.e. connectance) affect the strength and direction of relationships between motif participation and persistence. Motif participation therefore captures important trends in species persistence and provides a rich description of species' structural roles in their communities, but must be considered in the context of network structure as a whole and of the specific disturbance applied.

Novel analytic methods for predicting extinctions in ecological networks

AbstractEcological networks describe the interactions between different species, informing us how they rely on one another for food, pollination, and survival. If a species in an ecosystem is under threat of extinction, it can affect other species in the system and possibly result in their secondary extinction as well. Understanding how (primary) extinctions cause secondary extinctions on ecological networks has been considered previously using computational methods. However, these methods do not provide an explanation for the properties that make ecological networks robust, and they can be computationally expensive. We develop a new analytic model for predicting secondary extinctions that requires no stochastic simulation. Our model can predict secondary extinctions when primary extinctions occur at random or due to some targeting based on the number of links per species or risk of extinction, and can be applied to an ecological network of any number of layers. Using our model, we consider how false negatives and positives in network data affect predictions for network robustness. We have also extended the model to predict scenarios in which secondary extinctions occur once species lose a certain percentage of interaction strength, and to model the loss of interactions as opposed to just species extinction. From our model, it is possible to derive new analytic results such as how ecological networks are most robust when secondary species are of equal degree. Additionally, we show that both specialization and generalization in the distribution of interaction strength can be advantageous for network robustness, depending upon the extinction scenario being considered.

Prescribed fire increases plant-pollinator network robustness to losses of rare native forbs.

Restoration efforts often focus on changing the composition and structure of invaded plant communities, with two implicit assumptions: (1) functional interactions with species of other trophic levels, such as pollinators, will reassemble automatically when native plant diversity is restored and (2) restored communities will be more resilient to future stressors. However, the impact of restoration activities on pollinator richness, plant-pollinator interaction network structure, and network robustness is incompletely understood. Leveraging a restoration chronosequence in Pacific Northwest prairies, we examined the effects of restoration-focused prescribed fire and native forb replanting on floral resources, pollinator visitation, and plant-pollinator network structure. We then simulated the effects of plant species loss/removal scenarios on secondary extinction cascades in the networks. Specifically, we explored three management-relevant plant loss scenarios (removal of an abundant exotic forb, removal of an abundant forb designated a noxious weed, and loss of the rarest native forb) and compared them to control scenarios. Pyrodiversity and proportion of area recently burned increased the abundance and diversity of floral resources, with concomitant increases in pollinator visitation and diversity. Pyrodiversity also decreased network connectance and nestedness, increased modularity, and buffered networks against secondary extinction cascades. Rare forbs contributed disproportionately to network robustness in less restored prairies, while removal of typical "problem" plants like exotic and noxious species had relatively small impacts on network robustness, particularly in prairies with a long history of restoration activities. Restoration actions aimed mainly at improving the diversity and abundance of pollinator-provisioning plants may also produce plant-pollinator networks with increased resilience to plant species losses.

Detection of secondary arc extinction and auto-reclosing in compensated AC transmission lines based on machine learning

Detecting and recognizing the secondary arc extinction is considered as a backbone of the single pole auto reclosing schemes. This paper proposes a multi-channel convolutional network to detect the secondary arc extinction during a long AC power transmission line arc fault. In contrast to the conventional methods, the proposed Machin learning-based method can automatically learn the features from the raw data given as input. Multivariate time series data of phase voltage, current and neutral reactor signals were used as the input to the proposed model. The features are extracted in the convolution layer instead of using hand-crafted feature extraction like most of the existing research. The softmax classifier is used to detect fault and secondary arc extinction. Matlab Simulink is used to simulate the test system and collect the dataset to evaluate the proposed neural network model. To verify the generalizability of the proposed architecture datasets were collected at various locations and different phase lines. The proposed algorithm was able to detect the secondary arc extinction with 98.26% accuracy and able to give signal for auto-recloser logic with the maximum window length of three cycles. The result shows that the proposed neural network architecture is accurate and robust to detect the secondary arc extinction further can be used as a signal for a single pole adaptive auto recloser scheme.

Adaptive single-phase auto-reclosing scheme based on the moving average filter-quadrature signal generator for transmission lines with shunt reactors

An adaptive single-phase auto-reclosing method based on the moving average filter (MAF)-quadrature signal generator (QSG) is developed to determine secondary arc extinction time for high-voltage transmission lines with shunt reactors. Firstly, the difference between permanent and transient faults is derived and analyzed by the equivalent circuit model. Then, MAF-QSG is utilized to extract these features from the fault voltage. During the second arc period, for transient fault, the fundamental component and subharmonic component with around 50 Hz are reserved by MAF-QSG; however, in the case of permanent fault, only the fundamental component is retained. Finally, the identification index and its threshold are designed above the extraction fault features. The performance of the proposed method is evaluated by simulation and field data studies, accounting for different transmission line compensation levels, transition resistances, and fault location conditions.

NetworkExtinction: An R package to simulate extinction propagation and rewiring potential in ecological networks

Abstract Earth's biosphere is undergoing drastic reorganization due to the sixth mass extinction brought on by the Anthropocene. Impacts of local and regional extirpation of species have been demonstrated to propagate through the complex interaction networks they are part of, leading to secondary extinctions and exacerbating biodiversity loss. Contemporary ecological theory has developed several measures to analyse the structure and robustness of ecological networks under biodiversity loss. However, a toolbox for directly simulating and quantifying extinction cascades and creating novel interactions (i.e. rewiring) remains absent. Here, we present NetworkExtinction—a novel R package which we have developed to explore the propagation of species extinction sequences through ecological networks and quantify the effects of rewiring potential in response to primary species extinctions. With NetworkExtinction, we integrate ecological theory and computational simulations to develop functionality with which users may analyse and visualize the structure and robustness of ecological networks. The core functions introduced with NetworkExtinction focus on simulations of sequential primary extinctions and associated secondary extinctions, allowing user‐specified secondary extinction thresholds and realization of rewiring potential. With the package NetworkExtinction, users can estimate the robustness of ecological networks after performing species extinction routines based on several algorithms. Moreover, users can compare the number of simulated secondary extinctions against a null model of random extinctions. In‐built visualizations enable graphing topological indices calculated by the deletion sequence functions after each simulation step. Finally, the user can estimate the network's degree distribution by fitting different common distributions. Here, we illustrate the use of the package and its outputs by analysing a Chilean coastal marine food web. NetworkExtinction is a compact and easy‐to‐use R package with which users can quantify changes in ecological network structure in response to different patterns of species loss, thresholds and rewiring potential. Therefore, this package is particularly useful for evaluating ecosystem responses to anthropogenic and environmental perturbations that produce nonrandom and sometimes targeted, species extinctions.

Efficient keystone species identification strategy based on tabu search.

As species extinction accelerates globally and biodiversity declines dramatically, identifying keystone species becomes an effective way to conserve biodiversity. In traditional approaches, it is considered that the extinction of species with high centrality poses the greatest threat to secondary extinction. However, the indirect effect, which is equally important as the local and direct effects, is not included. Here, we propose an optimized disintegration strategy model for quantitative food webs and introduced tabu search, a metaheuristic optimization algorithm, to identify keystone species. Topological simulations are used to record secondary extinctions during species removal and secondary extinction areas, as well as to evaluate food web robustness. The effectiveness of the proposed strategy is also validated by comparing it with traditional methods. Results of our experiments demonstrate that our strategy can optimize the effect of food web disintegration and identify the species whose extinction is most destructive to the food web through global search. The algorithm provides an innovative and efficient way for further development of keystone species identification in the ecosystem.

Study on the secondary current characteristics of transmission lines coupling arc dynamics model with Mayr resistance model

In high-voltage transmission lines, secondary arcs severely affect the stability of power systems. However, there has been no research to combine transmission line model with time-varying resistance secondary arc. In this study, the improved arc dynamics model, the Mayr resistance model, and the transmission line system were combined in the simulation model to investigate the influence of the compensation reactor, line length, and short-circuit fault location on the characteristics of secondary arc current. The results revealed that the inhibitory effect of shunt reactors was the best at the midpoint between the fault point and the end of transmission line. When the series reactance satisfied a certain value, the short-circuit current was considerably suppressed with only a slight increase in the secondary current. The lower resistance along the line and longer transmission lines accelerated the secondary arc extinction rapidly. The location of the short-circuit fault had a limited effect on secondary arc extinction. The arc extinction time fluctuated within a small range with the changes in the location of the short-circuit fault. The results of the study can provide a reference for suppressing secondary arc currents.

Selectivity of mass extinctions: Patterns, processes, and future directions

AbstractA central question in the study of mass extinction is whether these events simply intensify background extinction processes and patterns versus change the driving mechanisms and associated patterns of selectivity. Over the past two decades, aided by the development of new fossil occurrence databases, selectivity patterns associated with mass extinction have become increasingly well quantified and their differences from background patterns established. In general, differences in geographic range matter less during mass extinction than during background intervals, while differences in respiratory and circulatory anatomy that may correlate with tolerance to rapid change in oxygen availability, temperature, and pH show greater evidence of selectivity during mass extinction. The recent expansion of physiological experiments on living representatives of diverse clades and the development of simple, quantitative theories linking temperature and oxygen availability to the extent of viable habitat in the oceans have enabled the use of Earth system models to link geochemical proxy constraints on environmental change with quantitative predictions of the amount and biogeography of habitat loss. Early indications are that the interaction between physiological traits and environmental change can explain substantial proportions of observed extinction selectivity for at least some mass extinction events. A remaining challenge is quantifying the effects of primary extinction resulting from the limits of physiological tolerance versus secondary extinction resulting from the loss of taxa on which a given species depended ecologically. The calibration of physiology-based models to past extinction events will enhance their value in prediction and mitigation efforts related to the current biodiversity crisis.

Single-Phase Auto-Reclosing Scheme Using Particle Filter and Convolutional Neural Network

Single-phaseauto-reclosing schemes depend on two main characteristics:(i) secondary arc extinction instant (ii) fault type (temporary or permanent). However, secondary arc quenching time greatly varies from no-arc to prolonged-arc generation depending on the secondary arc current and meteorological factors (wind, thermal buoyancy, etc.). Existing solutions face challenges in making reclosing decisions owing to variable secondary arc quenching instant, non-linear arc voltage characteristics, and varying recovery voltage waveform magnitude. To comprehensively address the discussed problems, an approach based on a particle filter algorithm along with a convolutional neural network is developed. Initially, harmonics of compromised phase are online estimated using a particle filter algorithm, and two indices are developed: (i) estimation of the precise moment of secondary arc extinction (ii) fault nature. Then, extensive simulations are carried out with variable arc resistance, line lengths, no-shunt, and shunt configurations to develop a database based on these two indices. Finally, support vector machine, fully connected deep neural network, and the convolutional neural network are applied to the dataset to predict the reclosing decisions. The comparative study of classifiers confirms the effectiveness of the proposed convolutional neural network in terms of overall model and inter-class accuracy under a noisy and noise-free environment.

Influence of the Secondary Arc on the Operation of Single Phase Autoreclosure of the 400 kV interconnection between Hungary and Croatia


 
 Sažetak: Faults on EHV lines are generally single-phase-to-ground ones and not permanent in the majority of cases. Thus single phase auto reclosure (SPAR), at which the faulty phases are tripped for a short time, eliminates the predominant part of the faults [1,2]. The secondary arc, which follows the high power arc after tripping the faulty phases at both side of the line may endanger the successfulness of reclosing if the duration of the switched off interval (dead time) is not long enough to ensure the extinction of the arc. The secondary arcing times recorded on different EHV lines or measured in laboratory tests show significant spread, consequently, to select a dead time according to the longest experimental secondary arc extinction time is not feasible. During commissioning of the double circuit 420 kV interconnection between Hungary and Croatia several staged faults were initiated to analyze the arc extinction performance. Initially the line was in operation by connecting the two circuits in parallel along the 1/3rd of the full length. In this configuration the longest secondary arc extinction time was 4 seconds and the secondary arc has not extinguished in 27s in one of the tests, so the line had to be tripped out to clear the staged fault. Later on, the length of the Croatian section of the line has been significantly shortened after putting a new substation into service. The increased performance of SPAR of the new arrangement has been proved with field tests. A realistic representation of the secondary arcs is essential in determining the auto-reclosure performance of EHV transmission lines. As shown in the paper, the random variation of the arc parameters influences significantly the arc extinction time. The results of the field tests confirmed the importance of the distributed nature of the transmission line and the nonlinear characteristic of the arc resistance in the intermittent region of arcing, where temporary extinctions and sudden re-ignitions in the arc channel produce transient wave processes along the line.

Extinction of biotic interactions due to habitat loss could accelerate the current biodiversity crisis.

Habitat loss disrupts species interactions through local extinctions, potentially orphaning species that depend on interacting partners, via mutualisms or commensalisms, and increasing secondary extinction risk. Orphaned species may become functionally or secondarily extinct, increasing the severity of the current biodiversity crisis. While habitat destruction is a major cause of biodiversity loss, the number of secondary extinctions is largely unknown. We investigate the relationship between habitat loss, orphaned species, and bipartite network properties. Using a real seed dispersal network, we simulate habitat loss to estimate the rate at which species are orphaned. To be able to draw general conclusions, we also simulate habitat loss in synthetic networks to quantify how changes in network properties affect orphan rates across broader parameter space. Both real and synthetic network simulations show that even small amounts of habitat loss can cause up to 10% of species to be orphaned. More area loss, less connected networks, and a greater disparity in the species richness of the network's trophic levels generally result in more orphaned species. As habitat is lost to land-use conversion and climate change, more orphaned species increase the loss of community-level and ecosystem functions. However, the potential severity of repercussions ranges from minimal (no species orphaned) to catastrophic (up to 60% of species within a network orphaned). Severity of repercussions also depends on how much the interaction richness and intactness of the community affects the degree of redundancy within networks. Orphaned species could add substantially to the loss of ecosystem function and secondary extinction worldwide.

Single-Pole Autoreclosure in uncompensated EHV AC mixed overhead-cable lines: A parametric time-domain analysis

The successful application of the Single-Pole Autoreclosure (SPAR) to Extra-High Voltage (EHV) overhead lines (OHLs), as well as to the overhead portion of EHV mixed cable-overhead lines (MLs), significantly improves system stability. SPAR success requires that the secondary arc self-extinguishes during the dead time: according to the literature, self-extinction times increase with the increase of both secondary arc current and recovery voltage. Steady-state analyses of EHV MLs not equipped with inductive shunt compensation showed larger secondary arc currents and smaller recovery voltages compared to OHLs. Since steady-state analyses cannot give indications on arc self-extinction times, transient studies are required to assess which of the above effects has a prevailing influence, i.e., whether SPAR in uncompensated MLs results hindered or facilitated. This paper presents a time-domain study of the SPAR cycle in an uncompensated 400 kV-50 Hz ML, making use of detailed ATP-EMTP line and fault arc models. A parametric study has been carried out, evaluating secondary arc current, extinction time and recovery voltage for different single-phase fault locations along the overhead section of the line. Transient simulation results point out to extinction times being shorter in MLs than in OHLs of the same total length.

Extinction Accelerating Device of Secondary Arc Design Based on Wind Load

The rapid extinction of secondary arc on the transmission line is essential to the stable operation of power system. Recently, there are a few specific designs of secondary arc prevention device applied into operation condition. In this article, a low-voltage secondary arc model was carried out and the wind load was found to have a significant influence on the extinction characteristics of secondary arc. For further analysis, a dynamic model was established and found that the wind load perpendicular to the electrode direction could significantly accelerate the arc extinction. Consequently, a device for accelerating secondary arc extinction close to the insulator was designed. Wind directions and velocities were chosen as variables in the measurement for verification. The device could ensure that the upper electrode on the insulator string is in the direction perpendicular to the wind direction at any time, and it could promote the extinction of secondary arc. The proposal of the device could provide some practical reference for the protection of secondary arc on the transmission lines.

A deep long Short-Term memory based scheme for Auto-Reclosing of power transmission lines

The operating speed of adaptive single-phase auto-reclosure (ASPAR) is of great importance to maintain power systems stability in high-voltage power transmission lines (PTLs). This paper proposes a two-step protection scheme using the long short-term memory (LSTM) network to enhance the ASPAR performance. The discrimination between transient and permanent faults is made by an LSTM with high accuracy in the first step. If transient faults are detected in the second step, another LSTM is applied to predict the secondary arc extinction time (SAET). To this end, the second LSTM accurately foresees the voltage waveform of the faulty phase a half-power cycle earlier, and predicts the SAET in order to get a successful reclosing. The results obtained from extensive simulations using EMTP-RV and MATLAB software environments indicate that the presented protection scheme outperforms other ones in terms of fault type classification, achieving an F-measure value of 98.90%. Moreover, the results verify that the LSTM can accurately estimate the voltage waveform and the SAET, that ensures a successful reclosing of the faulty phase.

Unscented-Kalman-filter-based single-phase adaptive reclosing of shunt-compensated extra-high-voltage transmission lines

This paper proposes a novel two-stage adaptive reclosing mechanism for shunt-compensated extra-high-voltage transmission lines. In the first stage, secondary arc extinction peak-based criterion (SAEPC) is established to monitor the precise instant of secondary arc extinction. The approach depends on the magnitude of the faulty phase voltage and the estimated weighted lower-order harmonics. The harmonics root mean square factor (HRF) is presented in the second stage for fault classification, i.e., temporary or permanent. The proposed scheme not only identifies the quenching instant regardless of fault location, compensation level, and arc extinction speed but also determines the nature of the fault. Simulation studies demonstrate the effectiveness and reliability of the proposed scheme and its ability to mitigate the limitations of existing single-criterion harmonics-based reclosing techniques.

Robustness of temperate versus tropical food webs: comparing species trait-based sequential deletions

Loss of species can unleash a cascade of secondary extinctions that cause dramatic changes in the structure and dynamics of food webs. The consequences for the food web depend on the traits of the species that are lost; thus, it is crucial to identify species’ traits associated with secondary extinction risk. Another important issue is to determine where the most vulnerable ecosystems are located. In this study, we aimed to compare the robustness of temperate versus tropical ecosystems to species loss. A total of 34 intertidal rock pools were analysed from a temperate and a tropical region (17 pools in each). Binary food web networks were assembled for each pool depicting who eats whom. Eighteen topological network properties were estimated to compare temperate and tropical webs. Robustness, a measure of network tolerance to species extinction, was assessed. Species loss was simulated in silico using sequential deletion protocols aimed at species that were (1) most connected, (2) least connected, (3) most abundant, and had the largest (4) body mass (mean weight) and (5) size (mean length). Tropical food webs exhibited higher robustness than temperate food webs. Both temperate and tropical food webs were less robust when the removal was directed at the most-connected species, confirming that highly connected species are particularly important in food webs. This study revealed, for the first time, that the positive relationship previously found between robustness and connectance is only confirmed for temperate webs, highlighting the need for more tropical case-studies in general data sets.

Study on the Influence of Injected Lightning Current on the Space-Time Evolution of Secondary Arc

The timely extinction of secondary arc is of great significance to the single-phase reclosing of transmission lines. However, very little research has been carried on the space-time evolution of secondary arc under lightning strikes. In this article, considering the electromagnetic force, thermal buoyant force, wind load and air resistance in the motion of secondary arc, a chain arc model was established, which was combined with the double exponential function injected lightning current model. The motion of secondary arc and the change of arc extinction time with or without injected lightning current were observed. The results show that lightning could accelerate the motion of secondary arc and shorten the extinction time of secondary arc. Then, by adjusting the different parameters of injected lightning current function, lightning start time, and lightning duration, the impact of various factors on the motion process of secondary arc and extinction time was obtained. Different wind loads and secondary currents were selected to observe the impact of the same injected lightning current with different secondary current and arc movement environment. The results show that a higher injected lightning current level and a lower secondary current could both make the impact of the injected lightning current more obvious. The lightning duration and lightning start time would not have a significant impact on the extinction of secondary arc. Lightning can reduce the difference between secondary arcs under different winds, and further promote the extinction of secondary arcs. The abovementioned research work can provide some reference for the protection of secondary arc in thunderstorm field.