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A rapidly expanding range of Pectinatella magnifica has been reported globally. Although many studies have been conducted to manage this invasive species, surveying methods have mainly been limited to visual observation of bryozoan colonies. For efficient monitoring and early detection of bryozoan species, we compared three different monitoring methods: visually detecting bryozoan colonies (visual observation of colonies, VOC), floating statoblasts (statoblasts in filtered water, SFW), and attached statoblasts (statoblasts attached to artificial substrate, SAS). Using these sampling methods, we compared the occurrences of P. magnifica in the littoral zones of lotic ecosystems from 117 sites in South Korea from 2015 to 2019. Occurrence frequency of P. magnifica was higher using both SFW (37.3%) and SAS (72.5%) than the traditional VOC (28.0%) method. The agreement of occurrence detection of P. magnifica between VOC, SFW and SAS was more consistent in tributaries than in main channels. Density estimations using colony (VOC) and statoblast detection methods (SFW, SAS) also showed a higher positive correlation in tributaries. To identify early P. magnifica invasion in an unidentified area, collecting statoblasts is a more efficient alternative to determine the occurrence of bryozoan species in field conditions.

We look at the population dynamics of an ecological system considering the Allee effect across different levels of population growth rates. The model is described by the growth and degradation of population size by multiplying a threshold term by the Allee effect. When the population of a species is low, the population of the system is not maintained and collapses to extinction. A wide survival region is observed in the dynamics of the Allee effect, and we report a bifurcation diagram for selected control parameters. We identify the chaotic region based on Lyapunov exponents. We obtain a phase diagram distinguishing extinction, periodic oscillation, the chaotic region, and the unstable region in the control parameter space. We observe two sets of chaotic bands one for low and the other for high values of the Allee effect. The Allee effect diversifies the dynamic region in parameter space.

In order to evaluate the possibility of the circadian rhythm as an indicator, the effects of contaminants on the behavior responses of goldfish (Carassius auratus) in the characteristic of behavior strength in 6 days were investigated. Circadian rhythms were characteristically observed in the exposures of 0.002 mg/L Deltamethrin (DM), 0.003 mg/L Dibutyl phthalate (DBP), 0.003 mg/L Atrazine (ATZ), and 0.003 mg/L Cadmium chloride (CdCl2) according to the Environmental Quality Standard for Surface Water of China (GB3838-2002). Data variance in both tendency analysis and Self-Organizing Map was most closely associated with photoperiods. Behavior activity (BA) effectively differentiated behavior modes according to organic compounds comparing with CdCl2. Circadian rhythm most consistently appeared after in ATZ exposure, by showing clear peaks during the light periods, being followed by CdCl2 and DM. DBP, in contrast, had no clear biorhythm with minimum fluctuation in BS curves. Totally, circadian rhythms were overall affected greatly until the second day. Auto-correlation analyses demonstrated that the affectedness by toxins would be addressed in an extra dimension in circadian rhythm. The studies on BS along with periodicity analyses and BA fitting suggest that circadian rhythm is a good indicator in the environmental assessment and contribute to broaden the scope of integrated assessments of toxic effects.

In the 1970s, a theoretical ecologist deduced that a biological community tends to be unstable with increasing numbers of species and interactions. Because many species coexist and have complex interactions in natural communities, ecologists have investigated the characteristics and underlying mechanisms of species diversity. In this chapter, we review theoretical studies that investigate mechanisms of coexistence in complex biological networks. A variety of hypotheses have been proposed to explain the mechanism of species diversity, each of which is focused on specific processes of species interactions and/or community dynamics. We categorize these theoretical models, describing types of focal mechanisms as either “fitness dependence” or “fitness independence.” Despite the diverse hypotheses, no key factor of species diversity has been clarified, mainly due to difficulties in testing the hypotheses. We conclude that more interdisciplinary and integrative studies are needed to understand species diversity in depth.

Point detection (e.g., the centroid of the body) of species has been conducted in numerous studies. However, line detection (i.e., the line body shape) of elongated species has rarely been investigated under stressful conditions. We analyzed the line movements of an Oligochaeta Lumbriculus variegatus in response to treatments with a toxic chemical, copper sulfate, at low concentrations (0.01 mg/L and 0.1 mg/L). The automatic line-tracking system was devised to identify the movement of body segments (body length) and the movements of segments (i.e., the speed and angles between segments) were recorded before and after treatment. Total body length was shortened from 31.22 (±5.18) mm to 20.91 (±4.65) mm after the 0.1 mg/L treatment. The Shannon entropy index decreased from 0.44 (±0.1) to 0.28 (±0.08) after treatment. On the other hand, the body and movement segments did not significantly change after the 0.01 mg/L treatment. Sequential movements of test organisms were further analyzed with a recurrent self-organizing map (RSOM) to determine the pattern of time-series line movements. The RSOM made it feasible to classify sequential behaviors of indicator organisms and identify various continuous body movements under stressful conditions.

Secreted proteins (secretomes) play crucial roles during bacterial pathogenesis in both plant and human hosts. The identification and characterization of secretomes in the two plant pathogens Burkholderia glumae BGR1 and B. gladioli BSR3, which cause diseases in rice such as seedling blight, panicle blight, and grain rot, are important steps to not only understand the disease-causing mechanisms but also find remedies for the diseases. Here, we identified two datasets of secretomes in B. glumae BGR1 and B. gladioli BSR3, which consist of 118 and 111 proteins, respectively, using mass spectrometry approach and literature curation. Next, we characterized the functional properties, potential secretion pathways and sequence information properties of secretomes of two plant pathogens in a comparative analysis by various computational approaches. The ratio of potential non-classically secreted proteins (NCSPs) to classically secreted proteins (CSPs) in B. glumae BGR1 was greater than that in B. gladioli BSR3. For CSPs, the putative hydrophobic regions (PHRs) which are essential for secretion process of CSPs were screened in detail at their N-terminal sequences using hidden Markov model (HMM)-based method. Total 31 pairs of homologous proteins in two bacterial secretomes were indicated based on the global alignment (identity ≥ 70%). Our results may facilitate the understanding of the species-specific features of secretomes in two plant pathogenic Burkholderia species.

Pine wilt disease is a serious pest for pine trees in many countries, especially in Asia (e.g., South Korea, Japan, China and Taiwan). In this study, we characterised dispersal patterns (e.g., direction and area) of pine wilt disease in the southern part of Korea in four-year period based on the cross-correlation function. The most likely distance of the highest infestation probability after one year is around 1.2 km from the disease source according to the distribution of pairwise distance. Subsequently, a spatially explicit model was developed in two dimensions by incorporating biological and environmental events, including influence of infested neighbourhoods, short- and long-distance dispersal, asymptomatic carriers and typhoon. The model results were in good agreement with field data when evaluated using the receiver operating characteristics and pair-correlation functions. Asymptomatic carrier played an important role in the spread of PWD. The infestation probabilities based on the spatially explicit model provided the map of spatial conformations that would be effective in addressing disease occurrence in both local and global aspects.

A novel scheme for the behavioral monitoring of multiple fish is presented based on measurements of the fish posture. Image identification of the fish head and tail is proposed by examining the gray level appearance features. A simplified posture of fish was calculated from its head and centroid. Multiple individual tracking was developed by incorporating the fish posture and global nearest neighbor. The proposed tracking scheme was tested with 2-5 individual Zebra fish (Cyprinidae, Danio rerio) under laboratory conditions. The experimental results confirmed the stability of the identification of a fish head and tail and a robust tracking performance was achieved. The proposed method could accurately record the movement trajectories and posture information of each individual. The tracking errors were only 0.278%-1.572% for 2-5 individual fish while the posture measurement error rates were less than 0.16%. Furthermore, the movement patterns of the fish, e.g., angular variations and distribution of the movement angle, were investigated from the behavioral data, which revealed the advantages of the proposed posture measurement for behavioral studies. The aggregation behavior of multiple fish was also analyzed to reveal the interaction patterns of the individuals in response to the spatial formation of the neighbors. (C) 2016 Elsevier B.V. All rights reserved.

Management of water-quality in a river ecosystem needs to be focused on susceptible regions to eutrophication based on proper measurements. The stress–response relationships between nutrients and primary productivity of phytoplankton allow the derivation of ecologically acceptable thresholds of stressors under field conditions. However, spatio-temporal variations in heterogeneous environmental conditions have hindered the development of locally applicable criteria. To address these issues, we utilized a combination of a geographically specialized artificial neural network (Geo-SOM, geo-self-organizing map) and linear mixed-effect models (LMMs). The model was applied to a 24-month dataset of 54 stations that spanned a wide spatial gradient in the Nakdong River basin. The Geo-SOM classified 1286 observations in the basin into 13 clusters that were regionally and seasonally distinct. Inclusion of the random effects of Geo-SOM clustering improved the performance of each LMM, which suggests that there were significant spatio-temporal variations in the Chla–stressor relationships. These variations arise owing to differences in background seasonality and the effects of local pollutant variables and land-use patterns. Among the 16 environmental variables, the major stressors for Chla were total phosphate (TP) as a nutrient and biological oxygen demand (BOD) as a non-nutrient according to the results of both Geo-SOM and LMM analyses. Based on LMMs with the random effect of the Geo-SOM clusters on the intercept and the slope, we can propose recommended thresholds for TP (18.5 μg L−1) and BOD (1.6 mg L−1) in the Nakdong River. The combined method of LMM and Geo-SOM will be useful in guiding appropriate local water-quality-management strategies and in the global development of large-scale nutrient criteria.

Species abundance distributions (SADs) are an efficient means of assessing community structure to define macroecological states and ecological integrity in responding to environmental impacts. Rank abundance distributions of benthic macroinvertebrate communities collected from streams with different levels of pollution in Korea were obtained and used to confirm water quality classification based on empirical assessment. The pollution states were broadly divided into weak and strong pollution groups according to SAD models, log-normal distribution and geometric series, respectively. A lower γ value in the log-normal distribution also differentiated weak pollution from strong pollution. Lower coefficient variation in the SAD slopes was further suitable in dividing less and slightly polluted states within the weak pollution group. Within the strong pollution group, a mixture of log-normal distribution to geometric series separated, polluted and severely polluted states. Higher correlation coefficients were observed between γ and other water quality parameters, as well as community and biological water quality indices. Similar patterns in SADs were presented between spring and fall; however, γ values of the less polluted state differed between seasons. Overall, developing SADs of related parameters is an efficient method of addressing ecological integrity that could serve as a reference system describing anthropogenic impact in streams.

Response behaviors of animals to stressors are complicated. Especially, it is difficult to analyze temporal data in addressing the time course development of behavioral states to stressors. Not much study has been conducted in identifying the short-term behavior conditions of indicator organisms responding to stressors. Hence, in the present study, we selected three temporal networks, Temporal Kohonen Map (TKM), Recurrent Self-Organizing Map (RSOM), and Recursive Self-Organizing Map (RecSOM) to characterize the behavior strength of individual fish exposed to Atrazine (ATZ, 0.12 mg/L) for 15 days. The trained networks were able to detect the characteristic behavior strength segments presenting the Stepwise Behavior Response Model (SBRM). TKM was found suitable for detecting strong curves in a short training time, but clustering was limited in grouped segments. In contrast, RecSOM was found to be most suitable for detecting behavior segments with both high and low contrast response under toxic exposure. RecSOM was effective in clustering but could not detect segments with strong changes. Finally, our results presented that the temporal SOMs, especially RecSOMs, were feasible in identifying short-term time series data and could be utilized for on-line monitoring of test organisms under stressful conditions.

Point detection (e.g., the centroid of the body) of species has been conducted in numerous studies. However, line detection (i.e., the line body shape) of elongated species has rarely been investigated under stressful conditions. We analyzed the line movements of an Oligochaeta Lumbriculus variegatus in response to treatments with a toxic chemical, copper sulfate, at low concentrations (0.01 mg/L and 0.1 mg/L). The automatic line-tracking system was devised to identify the movement of body segments (body length) and the movements of segments (i.e., the speed and angles between segments) were recorded before and after treatment. Total body length was shortened from 31.22 (&plusmn, 5.18) mm to 20.91 (&plusmn, 4.65) mm after the 0.1 mg/L treatment. The Shannon entropy index decreased from 0.44 (&plusmn, 0.1) to 0.28 (&plusmn, 0.08) after treatment. On the other hand, the body and movement segments did not significantly change after the 0.01 mg/L treatment. Sequential movements of test organisms were further analyzed with a recurrent self-organizing map (RSOM) to determine the pattern of time-series line movements. The RSOM made it feasible to classify sequential behaviors of indicator organisms and identify various continuous body movements under stressful conditions.

We propose an automatic pest identification method suitable for large scale, long term monitoring for mobile or embedded devices in situ with less computational cost. A procedure of segmentation and image separation was devised to identify common greenhouse pests, whiteflies, aphid and thrips. Initially, the watershed algorithm was used to segment insects from the background (i.e., sticky trap) images. Color feature of the insects were subsequently extracted by Mahalanobis distance for identification of pest species. Accuracy and computational costs were evaluated across different image resolutions. The correlation of determination (R-2) between the proposed identification scheme and manual identification were high, showing 0.934 for whitefly, 0.925 for thrips, and 0.945 for aphids even with low resolution images. Comparing with the conventional methods, pests were efficiently identified with low computational cost. Optimal image resolution for species identification regarding long-term survey was discussed in practical aspect with less computational complexity. (C) 2014 Elsevier B.V. All rights reserved.

We observed zebrafish ( Danio rerio ) movement continuously in response to conflicting stimuli (food and predator). Linear parameters (i.e., speed, acceleration, locomotory rate) were lower when food was provided to the arena, whereas angular parameters (i.e., turning rate) decreased in response to predator. Self-organizing map (SOM) trained with parameters revealed that stop duration, stop number, and x - and y -coordinates played major roles in determining variations in movement. Behavior patterns (e.g., rightward movement to food) were identifiable in different clusters in association with parameters responding to sources and order of stimuli. Distribution shapes obtained from the SOM were suitable for identifying responses of test organisms. Acceleration intermittency in movement data in different distribution shapes addressed data structure variation caused by sources and order of stimuli. The order of stimuli was influential in determining the behavioral states in the following courses of stimulus provision (i.e., addition of secondary stimulus and removal of the initial stimulus). Predator-first stimuli caused stronger response behaviors than food-first stimuli. Computational analysis of response behavior to stimuli could be an additional indicator of stress in animals.

Water velocity is one of the most important abiotic factors influencing the survival of aquatic insects in rivers and streams. The unidirectional water flow shaping their habitat and characteristically dividing it into alternating zones of high and low water velocity (riffles and pools) also imposes on them the special necessity to adapt to continual downstream drift. Here, we analyze an individual-based eco-evolutionary model parameterized with field data, and show how species adapted to riffles and pools, respectively, emerge if three basic processes are considered: density-dependent local competition, drifting, and adult flight. We also find that evolutionary branching in velocity adaptation is accompanied by an differentiation of drifting behavior. Generally, individuals drift either frequently and for only a short duration, or infrequently and for a longer duration. While riffle and pool species each exhibit both drifting strategies, a third species that can stably establish at intermediate water velocities (runs) exhibits exclusively the former. As the run species is therefore particularly susceptible to drift loss, long-range adult flight turns out to be crucial for its persistence. These insights highlight the ability of process-based eco-evolutionary models to generate testable hypotheses and stimulate empirical research.

Variance and invariance residing in multi-individual movement of zebrafish under chemical stress were addressed concurrently before and after treatment with formaldehyde. Variance was observed in movement parameters. Without treatment, linear speed was highest in groups with two-individuals, followed by those with one- and four-individuals. Following treatment, linear speed decreased significantly in groups with one- and two-individuals, but not in those with four-individuals. Inter-distances between two-individuals in groups with two-individuals decreased markedly after treatment, whereas inter-distances between two randomly selected individuals in the groups with four-individuals were not affected. The zero- and peak-values in the time-lag of autocorrelation of inter-distances decreased further after treatment in groups of two individuals relative to those in groups of four individuals. However, the empirical transition probability matrix between predefined behavioral patterns remained invariant among groups with different numbers of individuals as well as before and after treatment. Variance and invariance in multi-individual behaviors are suitable in expressing complex behaviors under chemical stress and could be a reference for detecting contaminants in the environment using indicator species.

Zebrafish behavior was monitored based on continuous movement tracking of individuals in response to two conflicting stimuli, food and predators. The shape parameters describing positional distribution along the x -axis (mean, standard deviation (SD) and skewness) were differentiated according to source and time order (i.e., food first or predator first) of stimuli. Behavioral states were expressed by primary (mean and SD of x -coordinates) and secondary (skewness of x -coordinates) affectedness, and were addressed by specificity of individual response to stimuli. Even after adjusting spatial location and movement range in primary affectedness, secondary affectedness still occurred owing to a residual effect of the stimulus according to asymmetry of the positional distribution (e.g., away from the predator). Predator (as initial or secondary stimulus) produced stronger affectedness than food given as initial stimulus. Even after removal of initial stimulus, it still influenced affectedness of test organisms in the subsequent phases, implying memory effect of initial stimulus. Quantification of stress based on expression of behavioral state changes is feasible and could provide insight for monitoring based on indicator organism behavior under stressful conditions.

The golden apple snail (Pomacea canaliculata) is a detrimental invasive pest of rice in Asia. Temperature is a critical factor to determine their invasiveness including the behavior and distribution of snails. In this study, the behavioral responses of golden apple snails acclimated to different water temperatures (15 °C, 20 °C, 25 °C, and 30 °C) were examined based on Markov chain analysis, Shannon entropy, and Random forest modeling. Markov chains revealed that most snails maintained their previous behavior at low temperatures, while behavior transition tended to be higher at high temperature. Shannon entropy was also dependent on temperature (low at low temperature and high at high temperature), indicating that snails maintained their previous behavior for a long time at low temperature regardless having motion and motionless behavior, whereas they changed continuously their behavioral types at high temperature. The Random forest model showed that Shannon entropy at low temperature was influenced by crawling at the bottom or at side of the aquarium (motion behavior), while clinging to the side of the aquarium or clinging to the side of the aquarium with stretching out antennae were important behaviors determining Shannon entropy at high temperature. Our results showed that snails controlled their behavior to reduce their thermal stress and maintain a stable internal state in harsh environment. With this mechanism, they are able to overwinter in the open fields with low temperature in Korea, resulting in the increase of potential damage in agricultural ecosystems. Therefore, further study on the development of adequate management system is required to avoid their invasiveness to open water systems and ecological impacts. Finally, Shannon entropy, Markov chain, and Random forest model are useful computation methods to quantify the effects of temperature changes on the behavior of golden apple snails.

Online monitoring systems provided a significant evidence for feasibility of the stepwise behavioral response model in detecting the effects of organophosphorus pesticides on movements of medaka (Oryzias latipes), being able to determine the state of indicator organisms, "no effect," "stimulation," "acclimation," "adjustment (readjustment)," and "toxic effect." Though the stepwise behavioral response model postulated that an organism displays a time-dependent sequence of compensatory stepwise behavioral response during exposure to pollutants above their respective thresholds of resistance, it was still a conceptual model based on tendency only in analysis. In this study, the phenomenon of bacterial persistence was used to interpret the relationship between the stepwise behavioral response model and the environmental stress caused by both exposure time and different treatments. Quantitative measurements of the stepwise behavioral response model led to a simple mathematical description of the threshold switch, which evaluated the effects of environmental stress on behavioral responses to decide the tendency. The adjustment ability correlated to "persisters (p)" is very important for test individuals to overcome the "threshold" from the outside environmental stress. The computational modeling results suggested that "persister (p)," as described in the general equations of bacterial persistence model in changing environments, illustrated behavior acclimation and adjustment (or readjustment) clearly. Consequently, the persistence parameter, p, was critical in addressing for medaka to be adapted to fluctuating environments under different environmental stress.