Mi-Jung Bae

Biological early warning system based on the responses of aquatic organisms to disturbances: a review.

Aquatic ecosystems are subject to a number of anthropogenic disturbances, including environmental toxicants. The efficient monitoring of water resources is fundamental for effective management of water quality and aquatic ecosystems. Spot sampling and continuous water quality monitoring based on physicochemical factors are conducted to assess water quality. However, not all contaminants or synergistic and antagonistic toxic effects can be determined by solely analyzing the physicochemical factors. Thus, various biotests have been developed using long-term and automatic observation studies based on the ability of the aquatic organisms to continuously sense a wide range of pollutants. In addition, a biological early warning system (BEWS) has been developed based on the response behaviors of organisms to continuously detect a wide range of pollutants for effective water quality monitoring and management. However, large amounts of data exhibiting non-linearity and individual behavioral variation are continuously accumulated over long-term and continuous behavioral monitoring studies. Thus, appropriate mathematical and computational data analyses are necessary to manage and interpret such large datasets. Here, we review the development and application of BEWS by using various groups of organisms and the computational methods used to process the behavioral monitoring data.

Potential Impacts of Global Warming on the Diversity and Distribution of Stream Insects in South Korea

Globally, the East Asian monsoon region is one of the richest environments in terms of biodiversity. The region is undergoing rapid human development, yet its river ecosystems have not been well studied. Global warming represents a major challenge to the survival of species in this region and makes it necessary to assess and reduce the potential consequences of warming on species of conservation concern. We projected the effects of global warming on stream insect (Ephemeroptera, Odonata, Plecoptera, and Trichoptera [EOPT]) diversity and predicted the changes of geographical ranges for 121 species throughout South Korea. Plecoptera was the most sensitive (decrease of 71.4% in number of species from the 2000s through the 2080s) order, whereas Odonata benefited (increase of 66.7% in number of species from the 2000s through the 2080s) from the effects of global warming. The impact of global warming on stream insects was predicted to be minimal prior to the 2060s; however, by the 2080s, species extirpation of up to 20% in the highland areas and 2% in the lowland areas were predicted. The projected responses of stream insects under global warming indicated that species occupying specific habitats could undergo major reductions in habitat. Nevertheless, habitat of 33% of EOPT (including two-thirds of Odonata and one-third of Ephemeroptera, Plecoptera, and Trichoptera) was predicted to increase due to global warming. The community compositions predicted by generalized additive models varied over this century, and a large difference in community structure in the highland areas was predicted between the 2000s and the 2080s. However, stream insect communities, especially Odonata, Plecoptera, and Trichoptera, were predicted to become more homogenous under global warming.

Response of Fish Communities to Various Environmental Variables across Multiple Spatial Scales

A better understanding of the relative importance of different spatial scale determinants on fish communities will eventually increase the accuracy and precision of their bioassessments. Many studies have described the influence of environmental variables on fish communities on multiple spatial scales. However, there is very limited information available on this topic for the East Asian monsoon region, including Korea. In this study, we evaluated the relationship between fish communities and environmental variables at multiple spatial scales using self-organizing map (SOM), random forest, and theoretical path models. The SOM explored differences among fish communities, reflecting environmental gradients, such as a longitudinal gradient from upstream to downstream, and differences in land cover types and water quality. The random forest model for predicting fish community patterns that used all 14 environmental variables was more powerful than a model using any single variable or other combination of environmental variables, and the random forest model was effective at predicting the occurrence of species and evaluating the contribution of environmental variables to that prediction. The theoretical path model described the responses of different species to their environment at multiple spatial scales, showing the importance of altitude, forest, and water quality factors to fish assemblages.

Predicting potential impacts of climate change on freshwater fish in Korea

Abstract Climate change is expected to have profound effects on the distribution and phenology of species and the productivity of aquatic ecosystem. In this study, we projected the impacts of climate change on the distributions of 22 endemic fish species in Korea with climatic and geographical variables by using species distribution models (SDMs). Six different SDMs – linear discriminant analysis, generalized linear model, classification and regression trees, random forest, support vector machine, and multivariate adaptive regression splines – were implemented for the prediction, and compared for their prediction capacity. The results showed that the random forest displayed the highest predictive power for the prediction of current species distributions. Therefore, the random forest was used to assess the potential impacts of climate change on the distributions of 22 endemic fish species. The results revealed that five species (Acheilognathus yamatsutae, Sarcocheilichthys variegatus wakiyae, Squalidus japonicus coreanus, Microphysogobio longidorsalis, and Liobagrus andersoni) have a high probability of becoming extinct in their respective habitable sub-watersheds by the 2080s due to climate change. The sensitivity analysis of the model showed that geo-hydrological variables such as stream order and altitude and temperature-related variables such as mean temperature in January and difference between the minimum and maximum temperatures exhibited relatively higher importance in their contributions for the prediction of species occurrence than that other variables. The decline of endemic fish species richness, and their occurrence probability due to climate change, would lead to poleward and upward shifts, as well as extinctions of species. Finally, we believe that our projections are useful for understanding how climate change affects the distribution range of endemic species in Korea, while also providing the necessary information to develop preservation and conservation strategies for maintaining endemic fish.

Evaluation of Changes in Effluent Quality from Industrial Complexes on the Korean Nationwide Scale Using a Self-Organizing Map

One of the major issues related to the environment in the 21st century is sustainable development. The innovative economic growth policy has supported relatively successful economic development, but poor environmental conservation efforts, have consequently resulted in serious water quality pollution issues. Hence, assessments of water quality and health are fundamental processes towards conserving and restoring aquatic ecosystems. In this study, we characterized spatial and temporal changes in water quality (specifically physico-chemical variables plus priority and non-priority pollutants) of discharges from industrial complexes on a national scale in Korea. The data were provided by the Water Quality Monitoring Program operated by the Ministry of Environment, Korea and were measured from 1989 to 2008 on a monthly basis at 61 effluent monitoring sites located at industrial complexes. Analysis of monthly and annual changes in water quality, using the seasonal Mann-Kendall test, indicated an improvement in water quality, which was inferred from a continuous increase in dissolved oxygen and decrease in other water quality factors. A Self-Organizing Map, which is an unsupervised artificial neural network, also indicated an improvement of effluent water quality, by showing spatial and temporal differences in the effluent water quality as well as in the occurrence of priority pollutants. Finally, our results suggested that continued long-term monitoring is necessary to establish plans and policies for wastewater management and health assessment.

ANALYSIS OF MOVEMENT BEHAVIOR OF ZEBRAFISH (DANIO RERIO) UNDER CHEMICAL STRESS USING HIDDEN MARKOV MODEL

Based on computer vision techniques, the movement tracks of an indicator species (zebrafish) were continuously observed in two dimensions before and after the treatments with a toxic chemical (formaldehyde, 2.5 ppm). Behavioral patterns based on the shape of movement segments were regarded as states, while linear and angular speeds measured from the movement segments were used as observed events for training with a hidden Markov model (HMM). The state sequences were estimated by HMM based on transition and emission probability matrices, and observed events. The movement tracks were further reconstructed based on behavior state sequences generated by HMM. Subsequently, permutation entropy and fractal dimension were calculated to monitor behavioral changes before and after the treatments. Both parameters based on the real and reconstructed data significantly decreased after the treatments, and individual variability was minimized with the parameters obtained from the reconstructed tracks. The parameter extraction based on optimal state sequence by HMM was suitable for resolving the problem of variability in behavioral data, and would be an effective means of monitoring chemical stress in the environment.

Characterization of Ecological Exergy Based on Benthic Macroinvertebrates in Lotic Ecosystems

The evaluation of ecosystem health is a fundamental process for conducting effective ecosystem management. Ecological exergy is used primarily to summarize the complex dynamics of lotic ecosystems. In this study, we characterized the functional aspects of lotic ecosystems based on the exergy and specific exergy from headwaters to downstream regions in the river’s dimensions (i.e., river width and depth) and in parallel with the nutrient gradient. Data were extracted from the Ecologische Karakterisering van Oppervlaktewateren in Overijssel (EKOO) database, consisting of 249 lotic study sites (including springs, upper, middle and lower courses) and 690 species. Exergy values were calculated based on trophic groups (carnivores, detritivores, detriti-herbivores, herbivores and omnivores) of benthic macroinvertebrate communities. A Self-Organizing Map (SOM) was applied to characterize the different benthic macroinvertebrate communities in the lotic ecosystem, and the Random Forest model was used to predict the exergy and specific exergy based on environmental variables. The SOM classified the sampling sites into four clusters representing differences in the longitudinal distribution along the river, as well as along nutrient gradients. Exergy tended to increase with stream size, and specific exergy was lowest at sites with a high nutrient load. The Random Forest model results indicated that river width was the most important predictor of exergy followed by dissolved oxygen, ammonium and river depth. Orthophosphate was the most significant predictor for estimating specific exergy followed by nitrate and total phosphate. Exergy and specific exergy exhibited different responses to various environmental conditions. This result suggests that the combination of exergy and specific exergy, as complementary indicators, can be used reliably to evaluate the health condition of a lotic ecosystem.

Evaluation of global warming effects on the geographical distribution of weeds in paddy fields by characterizing germination time and morphological factors

Abstract Global warming, a consequence of climate change, alters rice-paddy ecosystems, especially through the changes of both growth rate of plants and the occurrences of pests, and affects both rice crop production and biodiversity. In this study, factors related to the germination temperatures of 80 weed species in paddy fields were analyzed to elucidate the effect of warming on morphological (leaf size), phenological (germination time), and population (distribution) responses. A self-organizing map (SOM) was used to classify the weed species on the basis of 5 factors related to germination temperature: the minimum, maximum, and optimum temperatures and the minimum and maximum optimal range. Climate data for the Korean Peninsula during 4 different decades (1990s, 2020s, 2050s, and 2080s) were obtained from a regional climate change model following the A1B emission scenario of the Intergovernmental Panel on Climate Change. Changes in the germination time and range of potential habitable areas for the weed species were estimated on the basis of the patterns of the SOM. The species associated with relatively lower germination temperatures tended to have smaller leaves, shorter stems, and earlier flowering and germination times than the species associated with higher germination temperature. The potential germination area increased progressively with rising temperature. The degree of potential increase in germination area was the greatest in the 2080s when the weeds could germinate in most of the southern Korean Peninsula. These results suggest that studying the patterns of germination temperature through SOM could provide necessary information for characterizing the germination of weeds on the basis of various characteristics (e.g., morphology, phenology, and distribution) and would be useful for maintaining agricultural productivity and agroecosystem biodiversity under global warming.

Evaluation of subsampling efforts in estimating community indices and community structures

Abstract Even though subsampling can minimize the research efforts needed to deal with numerous specimens, the accuracy of bioassessment and community analysis can be affected according to subsampled individuals. In this study, the effects of subsampling on community indices, the parameters of the species abundance distributions (SADs) and ordination based on communities were evaluated using benthic macroinvertebrates from three different stream pollution levels: less, intermediately, and heavily polluted. The values of the community indices and the parameters of the SADs were clearly different according to the differences in the pollution levels, regardless of subsampling efforts. Detrended correspondence analysis was applied to characterize similarities between the subsamples with different individuals based on community indices and the parameters of the SADs. A self-organizing map was used to characterize the community similarities and properties of the subsamples, differentiating the subsamples from their original datasets. Finally, our results revealed that the effects of subsampling were reflected differently in different indices, parameters, and ordinations of communities at different pollution levels, suggesting that subsample size should be determined differently at different pollution levels depending on the objectives of the study. However, if only one subsample size is to be used for simplicity and to reduce the cost of aquatic ecosystem health monitoring and assessment, then we recommend at least 400 individuals as the subsample size. At least 800 individuals should be subsampled for biodiversity studies.

Responses of the functional diversity of benthic macroinvertebrates to floods and droughts in small streams with different flow permanence

Abstract Floods and droughts are 2 of the most influential factors affecting the structure and function of benthic macroinverte-brate assemblages in stream ecosystems. Even if these natural disturbances occur at the same magnitude at multiple research sites, the responses may differ according to stream type. In our study, we examined the various responses of functional feeding guilds (FFGs), related to the feeding methods and food types of macroinvertebrates, and habit trait guilds (HTGs), related to the mobility of macroinvertebrates and location of food obtained, to floods and droughts in different stream types (perennial, intermittent, or ephemeral). The stream types were categorised according to the stream flow conditions, flow permanence, and stream connectivity. Perennial streams were those maintaining continuous lotic habitats; intermittent streams were lotic habitats during periods of heavy rain but either connected or isolated pools during dry periods; and ephemeral streams existed only during the rainy season. Among the substrates, cobbles and boulders were highly dominant during heavy rain, especially in the first periods of heavy rain, whereas silt and sand were more often present in high proportions at intermittent stream sites. Across all stream types, highly intense and heavy rain led to a decrease in species richness and abundance, with changes in the composition of both FFGs and HTGs. Organisms characterised as scrapers and/or clingers (e.g., Ecdyonurus dracon, E. levis, and Simuliidae sp.), were highly resistant to high discharge compared to other FFGs or HTGs and were dominant during floods. In dry periods, the composition and richness of FFGs and HTGs were more affected at intermittent streams than at perennial streams. Long-lasting dry periods consistently reduced lotic habitat abundance and diversity and increased the amount of lentic habitats as well as zones with sedimentation, especially at intermittent stream sites, resulting in a decrease in collector-filterer organisms and an increase in burrowers (e.g., Ephemera strigata). Despite seasonal predictability, however, floods of relatively lower magnitude and intensity provided opportunities for some species, especially clingers (e.g., Epeorus pellucidus) and swimmers (e.g., Baetis fuscatus), to be introduced and/or become established in new habitats downstream in the ephemeral streams. Our research indicated that spatial (i.e., stream type) and temporal (i.e., floods and drying events) heterogeneities are the defining factors that influence functional diversity in benthic macroinvertebrate communities.