Model Ecosystem Research Articles

Altitude patterns of seed C, N, and P concentrations and their stoichiometry in an alpine meadow on the eastern Tibetan Plateau

Understanding the altitudinal patterns of plant stoichiometry in seeds is critical for characterizing important germination and dormancy strategies, soil seed bank composition, seed predation probability, efficiency of seed dispersal and seedling performance, and to predict how biodiversity might be influenced by climate change. However, our understanding of the altitudinal patterns of seed stoichiometry is extremely limited. In this study, we measured the concentrations of carbon (C), nitrogen (N) and phosphorus (P) in the seeds of 253 herbaceous species along an altitudinal transect (2,000–4,200 m) on the eastern Tibetan Plateau, China, and further to characterize seed C:N:P stoichiometry. The geometric means of C, N, and P concentrations were 569.75 mg/g, 34.76 mg/g, and 5.03 mg/g, respectively. The C:N, C:P, and N:P ratios were 16.39, 113.31, and 6.91, respectively. The seed C, N, and P concentrations and C:N:P ratios varied widely among major plant groups and showed significant altitudinal trends. In general, C, N, and P concentrations increased, whereas seed C:N:P ratios decreased with elevation. These results inform our understanding of the altitudinal patterns of seed stoichiometry and how to model ecosystem nutrient cycling.

Spatial Pattern and Ecological Process Difference Analyses of the Boundary Habitats of a Treeline Patch: A Case Study from the Li Mountain, North China

Treeline patches are among Earth’s most sensitive and are important model ecosystems for assessing climate change trends. To explore ecological factors that limit the species’ survival in treelines, the treeline patch of Li Mountain National Nature Reserve was selected as the research site. Pinus armandii (P. armandii), Betula albo-sinensis (B. albo-sinensis), and Betula utilis (B. utilis) were selected as research species based on their dominance. Two 50 m × 50 m plots were established separately from the upper and lower limits of the highest treeline patch for point pattern analysis. Five 10 m × 10 m quadrats per plot were sampled to investigate the flora and environmental factors. The results showed that: (1) Slope and community composition at tree layer in quadrates had significant differences between upper and lower limits. Pinus armandii had a greater population size at the upper limit. Seedling recruitment restricted population development for B. albo-sinensis at the lower limit and B. utilis at the upper limit and less regeneration of B. albo-sinensis at the upper limit. (2) More aggregation scales occurred at the upper limit, and P. armandii had more aggregation scales than the other two species at 0–25 m. The heterogeneity caused by density distribution affected P. armandii pattern at the upper limit, and heterogeneity of seed dispersal could explain species patterns in both limits. Distinctness of size difference may have an influence on inter-specific species correlations.

Spatially Continuous Mapping of Forest Canopy Height in Canada by Combining GEDI and ICESat-2 with PALSAR and Sentinel

Continuous large-scale mapping of forest canopy height is crucial for estimating and reporting forest carbon content, analyzing forest degradation and restoration, or to model ecosystem variables such as aboveground biomass. Over the last years, the spaceborne Light Detection and Ranging (LiDAR) sensor specifically designed to acquire forest structure information, Global Ecosystem Dynamics Investigation (GEDI), has been used to extract forest canopy height information over large areas. Yet, GEDI has no spatial coverage for most forested areas in Canada and other high latitude regions. On the other hand, the spaceborne LiDAR called Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides a global coverage but was not specially developed to study forested ecosystems. Nonetheless, both spaceborne LiDAR sensors obtain point-based information, making spatially continuous forest canopy height estimation very challenging. This study compared the performance of both spaceborne LiDAR, GEDI and ICESat-2, combined with ALOS-2/PALSAR-2 and Sentinel-1 and -2 data to produce continuous canopy height maps in Canada for the year 2020. A set-aside dataset and airborne LiDAR (ALS) from a national LiDAR campaign were used for accuracy assessment. Both maps overestimated canopy height in relation to ALS data, but GEDI had a better performance than ICESat-2 with a mean difference (MD) of 0.9 m and 2.9 m, and a root mean square error (RMSE) of 4.2 m and 5.2 m, respectively. However, as both GEDI and ALS have no coverage in most of the hemi-boreal forests, ICESat-2 captures the tall canopy heights expected for these forests better than GEDI. PALSAR-2 HV polarization was the most important covariate to predict canopy height, showing the great potential of L-band in comparison to C-band from Sentinel-1 or optical data from Sentinel-2. The approach proposed here can be used operationally to produce annual canopy height maps for areas that lack GEDI and ICESat-2 coverage.

Sympoietic growth: living and producing with fungi in times of ecological distress.

Drawing upon ethnographic research on human living and producing with fungi, and Haraway’s theorization of sympoiesis and the model ecosystems of mycorrhizae developed in current mycological research, we offer a concept of sympoietic growth. Sympoiesis is a concept that suggests a way of thinking about growth as a more-than-human process and provides an alternative political imaginary both to current forms of economic growth and to the idea of “degrowth.” We explore human-fungi co-operation in forests, an urban park, and a shopping mall, on a miso production farm, and in a Catholic parish to provide insights into the logic and relationships involved in sympoietic growth in the field of agriculture and food production. We argue that this form of food provision has a sustainable, (re)generative potential not only in ecological and social but also economic terms. In conclusion, we highlight three patterns of sympoietic growth: the absence of any urge to “take (back) control” over the multispecies dynamic on the part of the humans; a non-instrumental passion for more-than-human life; and a combination of intellectual and manual labor as a form of attachment to the more-than-human world.

Ternary network models for disturbed ecosystems.

The complex network of interactions between species makes understanding the response of ecosystems to disturbances an enduring challenge. One commonplace way to deal with this complexity is to reduce the description of a species to a binary presence–absence variable. Though convenient, this limits the patterns of behaviours representable within such models. We address these shortcomings by considering discrete population models that expand species descriptions beyond the binary setting. Specifically, we focus on ternary (three-state) models which, alongside presence and absence, additionally permit species to become overabundant. We apply this ternary framework to the robustness analysis of model ecosystems and show that this expanded description permits the modelling of top-down extinction cascades emerging from consumer pressure or mesopredator release. Results therefore differ significantly from those seen in binary models, where such effects are absent. We also illustrate how this method opens up the modelling of ecosystem disturbances outside the scope of binary models, namely those in which species are externally raised to overabundance. Our method therefore has the potential to provide a richer description of ecosystem dynamics and their disturbances, while at the same time preserving the conceptual simplicity of familiar binary approaches.

Soil-atmosphere fluxes of CO2, CH4, and N2O across an experimentally-grown, successional gradient of biocrust community types.

Biological soil crusts (biocrusts) are critical components of dryland and other ecosystems worldwide, and are increasingly recognized as novel model ecosystems from which more general principles of ecology can be elucidated. Biocrusts are often diverse communities, comprised of both eukaryotic and prokaryotic organisms with a range of metabolic lifestyles that enable the fixation of atmospheric carbon and nitrogen. However, how the function of these biocrust communities varies with succession is incompletely characterized, especially in comparison to more familiar terrestrial ecosystem types such as forests. We conducted a greenhouse experiment to investigate how community composition and soil-atmosphere trace gas fluxes of CO2, CH4, and N2O varied from early-successional light cyanobacterial biocrusts to mid-successional dark cyanobacteria biocrusts and late-successional moss-lichen biocrusts and as biocrusts of each successional stage matured. Cover type richness increased as biocrusts developed, and richness was generally highest in the late-successional moss-lichen biocrusts. Microbial community composition varied in relation to successional stage, but microbial diversity did not differ significantly among stages. Net photosynthetic uptake of CO2 by each biocrust type also increased as biocrusts developed but tended to be moderately greater (by up to ≈25%) for the mid-successional dark cyanobacteria biocrusts than the light cyanobacterial biocrusts or the moss-lichen biocrusts. Rates of soil C accumulation were highest for the dark cyanobacteria biocrusts and light cyanobacteria biocrusts, and lowest for the moss-lichen biocrusts and bare soil controls. Biocrust CH4 and N2O fluxes were not consistently distinguishable from the same fluxes measured from bare soil controls; the measured rates were also substantially lower than have been reported in previous biocrust studies. Our experiment, which uniquely used greenhouse-grown biocrusts to manipulate community composition and accelerate biocrust development, shows how biocrust function varies along a dynamic gradient of biocrust successional stages.

Introducing a New Model for the Analysis of Iot Business Model Ecosystem in the Field Of Rehabilitation in Iran Using the Sem Approach

Background and Aims The purpose of this article was to present a local model for ecosystem analysis of the IoT business model in the field of rehabilitation in Iran with an emphasis on improving the quality of life of the disabled community in the country. Methods The current article can be categorized as applied, combined (qualitative and quantitative), and survey-based descriptive. The society, i.e., the statistical sample, included eight experts in the qualitative part and consisted of 100 executives and experts in the quantitative part. A questionnaire was used to analyze the dimensions and indicators. The face validation of the questionnaire was performed by the Delphi technique. Content validity ratio and content validity ratio were used as two content-related validity indicators for qualitative validation. The reliability of all dimensions and indicators was confirmed through Cronbach’s test with a population consisting of 30 experts. To analyze the proposed model of the researcher, we used inferential tests, loading factor analysis, t, structure equation modeling, and fitting techniques on a 100-person sample. Results The fitness of the model was approved by experts with 99% confidence according to the philosophy, goals of the theoretical foundations of dimensions and components, feedback, and output of the model. Conclusion The findings of this paper led to a model with several dimensions: (1) environment, (2) actors, (3) ecosystem cycle, and (4) IoT architecture in business. The corresponding indicators for the identified dimensions were validated. Independence, interaction, and empowerment were considered three principle values for the target community.

Entrepreneurial ecosystems: Multiple domains, dimensions and relationships

In this paper we examine the operation of entrepreneurial ecosystems. We use the work of Isenberg (2010) to frame a study of an ecosystem in Ireland. Following a review of the literature and guided by an expert panel (n = 8) we conducted a survey of small business owners (n = 100). Statistical analysis of the survey data revealed sixteen dimensions with a complex system of interrelationships. In the discussion we explain how and importantly why the dimensions can and should be identified and analysed. We propose that although an entrepreneurial ecosystem will align with an extended version of the six domains proposed by Isenberg (2010) each individual ecosystem must be studied to identify its complex system of unique dimensions. Implications for theory and practice, as well as limitations and future research directions, are discussed. It is envisaged that our approach to modelling ecosystems will serve as the basis for further thought and empiricism.

Stressful, isolated, yet diverse: Green roofs have rich microbiomes that are not dominated by oligotrophic taxa.

Green roofs are unique ecosystems combining two major community assembly filters, namely stress and spatial isolation. As such, they represent an interesting model ecosystem in community ecology. In this study, we characterized the microbiome structure on 19 green roofs and 5 urban parks as a benchmark comparison (i.e. non-isolated, non-stressful habitats). Green roofs were not species depauperate, showing similar α-diversity compared to surrounding parks. We also did not find an overrepresentation of bacterial phyla typically recognized as oligotrophs, which calls into question the notion of green roofs as highly stressful habitats for bacteria, and/or the conservatism of nutritional ecophysiology at the phylum level. The geographical position of a roof, or its degree of spatial isolation (assessed through its height and area) were not important predictors of microbiome diversity and structure, suggesting that dispersal limitations impose little constraints on green roof microbiome assembly. Finally, key microbial groups (e.g. archaeal nitrifiers, Actinobacteria) were much less frequent and/or abundant on green roofs, which may have important implications for nutrient cycling and urban biogeochemistry. More work will be required to phenotype the microorganisms overrepresented on green roofs and specifically measure key soil processes in these unique urban ecosystems.

Building a healthy mouse model ecosystem to interrogate cancer biology.

ABSTRACTIn a recent study, Sargent et al. characterise several novel Rag1−/− mouse strains and demonstrate that genetic background strongly influences xenograft development and phenotype. Here, we discuss this work within the broader context of cancer mouse modelling. We argue that new technologies will enable insights into how specific models align with human disease states and that this knowledge can be used to develop a diverse ecosystem of complementary mouse models of cancer. By utilising these diverse, well-characterised models to provide multiple perspectives on specific cancers, it should be possible to reduce the inappropriate attrition of sound hypotheses while protecting against false positives. Furthermore, careful re-introduction of biological variation, be that through outbred populations, environmental diversity or including animals of both sexes, can ensure that results are more broadly applicable and are less impacted by particular traits of homogeneous experimental populations. Thus, careful characterisation and judicious use of an array of mouse models provides an opportunity to address some of the issues surrounding both the reproducibility and translatability crises often referenced in pre-clinical cancer research.

Recovery Ecosystems: A Whole Health Approach to Substance Use Prevention and Treatment.

A recovery ecosystem is an evidence-based approach that creates the environment that individuals and families need by providing all the necessary tools, services, and supports for recovery to occur. Several models have been proposed in the literature, including the recovery-oriented systems of care model and Recovery Ready Ecosystems Model. A major concern with previous models is lack of focus on how the individual with substance use disorder (SUD) is a partner in the recovery process and interacts with the recovery ecosystem to optimize recovery wrap-around services and supports. Therefore, we propose the SUD Holistic Recovery Ecosystem Model (HREM), which uses a whole health approach to substance use prevention and treatment and builds on prior work by other researchers. The HREM has four domains: health support, social welfare support, occupational support, and legal and legislative support. [Journal of Psychosocial Nursing and Mental Health Services, 60(9), 10-14.].

Using Explainable Artificial Intelligence to Discover Interactions in an Ecological Model for Obesity.

Ecological theories suggest that environmental, social, and individual factors interact to cause obesity. Yet, many analytic techniques, such as multilevel modeling, require manual specification of interacting factors, making them inept in their ability to search for interactions. This paper shows evidence that an explainable artificial intelligence approach, commonly employed in genomics research, can address this problem. The method entails using random intersection trees to decode interactions learned by random forest models. Here, this approach is used to extract interactions between features of a multi-level environment from random forest models of waist-to-height ratios using 11,112 participants from the Adolescent Brain Cognitive Development study. This study shows that methods used to discover interactions between genes can also discover interacting features of the environment that impact obesity. This new approach to modeling ecosystems may help shine a spotlight on combinations of environmental features that are important to obesity, as well as other health outcomes.

Close to reality? Micro-/mesocosm communities do not represent natural macroinvertebrate communities

BackgroundThe European environmental risk assessment of plant protection products considers aquatic model ecosystem studies (microcosms/mesocosms, M/M) as suitable higher tier approach to assess treatment-related effects and to derive regulatory acceptable concentrations (RAC). However, it is under debate to what extent these artificial test systems reflect the risks of pesticidal substances with potential harmful effects on natural macroinvertebrate communities, and whether the field communities are adequately protected by the results of the M/M studies. We therefore compared the composition, sensitivity and vulnerability of benthic macroinvertebrates established in control (untreated) groups of 47 selected M/M studies with natural stream communities at 26 reference field sites.ResultsSince 2013 the number of benthic macroinvertebrate taxa present in M/M studies has increased by 39% to a mean of 38 families per study. However, there is only an average of 4 families per study that comply with the recommendations provided by EFSA (EFSA J 11:3290, 2013), i.e.: (i) allowing statistical identification of treatment-related effects of at least 70% according to the minimum detectable difference (here criteria are slightly modified) and (ii) belonging to insects or crustaceans (potentially sensitive taxa for pesticidal substances). Applying the criterion of physiological sensitivity according to the SPEARpesticides concept, the number of families decreases from 4 to 2.3 per study.ConclusionsMost taxa established in recent M/M studies do not suitably represent natural freshwater communities. First, because their abundances are often not sufficient for statistical detection of treatment-related effects in order to determine an appropriate endpoint and subsequent RAC. Recommendations are given to improve the detectability of such effects and their reliability. Second, the taxa often do not represent especially sensitive or vulnerable taxa in natural communities in terms of their traits. The uncertainties linked to vulnerable taxa in M/M studies are especially high considering their representativity for field assemblages and the comparability of factors determining their recovery time. Thus considering recovery for deriving a RAC (i.e., ERO-RAC) is not recommended. In addition, this paper discusses further concerns regarding M/M studies in a broader regulatory context and recommends the development of alternative assessment tools and a shift towards a new paradigm.

Temporal-spatial change of China's coastal ecosystems health and driving factors analysis

Understanding the spatial distribution pattern change and driving factors behind ecosystem health is essential to ecosystem management and restoration. However, in the research of regional ecosystem health, there is little research on ecosystem health in coastal regions, and there is little exploration of its temporal and spatial pattern change and its driving factors. In this study, we use the Vigor-Organization-Resilience-Services (VORS) model and marine ecosystem health index to diagnose the ecosystem health of the whole coastal area of China over the last 20 years, and find the main contributing factors affecting ecosystem health with the help of geographic detectors and geographic weighted regression analysis. Our results show that: (1) the ecosystem health level in the south of the coastal region is higher than that in the north, mainly with 30° north latitude as the main dividing line. (2) The regions with high change rate are mainly concentrated in Bohai Bay, the Yangtze River Estuary, Hangzhou Bay and the Pearl River Estuary, and the change is mainly negative. (3) Both natural and human factors have an impact on ecosystem health, and the influencing factors are different on different scales. The interaction between different factors is greater than the impact of a single factor on ecosystem health. The study puts forward a new evaluation framework for the study of ecosystem health in coastal areas, which can be applied to other coastal areas with similar conditions, and can help the sustainable and healthy development of coastal areas.

Life on the edge: Hawaiian model for coral evolution

AbstractDegradation and loss of coral reefs due to climate change and other anthropogenic stressors has fueled genomics, proteomics, and genetics research to investigate coral stress response pathways and to identify resilient species, genotypes, and populations to restore these biodiverse ecosystems. Much of the research and conservation effort has understandably focused on the most taxonomically rich regions, such as the Great Barrier Reef in Australia and the Coral Triangle in the western Pacific. These ecosystems are analogous to tropical rainforests that also house enormous biodiversity and complex biotic interactions among different trophic levels. An alternative model ecosystem for studying coral reef biology is the relatively species poor but abundant coral reefs in the Hawaiian Archipelago that exist at the northern edge of the Indo‐Pacific coral distribution. The Hawaiian Islands are the world's most isolated archipelago, geographically isolated from other Pacific reef systems. This region houses about 80 species of scleractinian corals in three dominant genera (Porites, Montipora, and Pocillopora). Here we briefly review knowledge about the Hawaiian coral fauna with a focus on our model species, the rice coral Montipora capitata. We suggest that this simpler, relatively isolated reef system provides an ideal platform for advancing coral biology and conservation using multi‐omics and genetic tools.

Scaling inclusive business impacts at the Base of the Pyramid: A framework inspired by business model ecosystems research

Scaling the social impact of inclusive business models that provide solutions to basic needs of Bottom of the Pyramid (BoP) communities through firm-centric approaches has proven challenging. Researchers have proposed that scaling strategies at the BoP should go beyond firm-centric approaches by inclusive businesses and involve coordinated synergistic action of their entire ecosystem to overcome systemic challenges and create value for all ecosystem actors. However, current research on this topic remains abstract and difficult to implement. This paper presents an empirically validated scaling framework designed to overcome this weakness and documents its design process. The framework takes account of the fact that inclusive businesses must work out scaling strategies together with key ecosystem actors, and that implementing a scaling strategy will almost always require mutual adaptation of business models. The framework design process entailed an extensive literature review and practitioner interviews as a first step, followed by testing, evaluation and iterative improvement through a series of validation workshops with actors of four inclusive business initiatives in Africa and Asia. The results indicate that the framework helps workshop participants to expand their mental frame, encouraging them to adopt a broader ecosystems perspective on scaling. This leads to identification and exploration of valuable business model adaptations for scaling that can be achieved through collaboration and assessment of the practical feasibility of different scaling strategies.

Influence of temperature on the toxicity of the elutriate from a pesticide contaminated soil to two cladoceran species.

Brazil has become one of the largest consumers of pesticides in the world. However, there are still few studies evaluating pesticide toxicity integrating local aquatic and terrestrial environments. In addition, there is growing concern about the influence of temperature conditions related with climate change on contaminants toxicity. The aim of the present study was to evaluate the elutriate toxicity of the insecticide Kraft® 36 EC (a.i. abamectin), the fungicide Score® 250 EC (a.i. difenoconazole) and their mixture to the cladocerans Ceriodaphnia silvestrii and Daphnia similis, using model ecosystems (mesocosms). To this end, mesocosms were filled with natural soil and subjected to the following treatments: Control (Milli-Q water), Kraft (10.8 g abamectin ha-1), Score (20 g difenoconazole ha-1), and Kraft + Score (10.8 g abamectin ha-1 + 20 g difenoconazole ha-1). The experiment lasted 18 days, and the applications were made on days 1, 8, and 15; the occurrence of rainfall was simulated on days 1, 8, and 15 after applications and only rainfall simulation on days 4, 11, and 18. The experiment was conducted under two different temperatures: 23 °C and 33 °C. At 23 °C, single Kraft treatment and in combination with Score showed high toxicity to both cladocerans. At 33 °C, elutriate of the Kraft® and mixture treatments were highly toxic to D. similis but not to C. silvestrii. The results indicate that while Kraft had higher toxicity than Score to both cladocerans, this toxicity was counteracted at 33 °C only for the exotic species, D. similis. The results portray the complexity of pesticide toxicity when considering realistic experimental settings including different organisms and temperature treatments.

Mechanistic support for increased primary production around artificial reefs.

Understanding factors controlling primary production is fundamental for the protection, management, and restoration of ecosystems. Tropical seagrass ecosystems are among the most productive ecosystems worldwide, yielding tremendous services for society. Yet they are also among the most impaired from anthropogenic stressors, prompting calls for ecosystem-based restoration approaches. Artificial reefs (ARs) are commonly applied in coastal marine ecosystems to rebuild failing fisheries and have recently gained attention for their potential to promote carbon sequestration. Nutrient hotspots formed via excretion from aggregating fishes have been empirically shown to enhance local primary production around ARs in seagrass systems. Yet, if and how increased local production affects primary production at ecosystem scale remains unclear, and empirical tests are challenging. We used a spatially explicit individual-based simulation model that combined a data-rich single-nutrient primary production model for seagrass and bioenergetics models for fish to test how aggregating fish on ARs affect seagrass primary production at patch and ecosystem scales. Specifically, we tested how the aggregation of fish alters (i) ecosystem seagrass primary production at varying fish densities and levels of ambient nutrient availability and (ii) the spatial distribution of seagrass primary production. Comparing model ecosystems with equivalent nutrient levels, we found that when fish aggregate around ARs, ecosystem-scale primary production is enhanced synergistically. This synergistic increase in production was caused by nonlinear dynamics associated with nutrient uptake and biomass allocation that enhances aboveground primary production more than belowground production. Seagrass production increased near the AR and decreased in areas away from the AR, despite marginal reductions in seagrass biomass at the ecosystem level. Our simulation's findings that ARs can increase ecosystem production provide novel support for ARs in seagrass ecosystems as an effective means to promote (i) fishery restoration (increased primary production can increase energy input to the food web) and (ii) carbon sequestration, via higher rates of primary production. Although our model represents a simplified, closed seagrass system without complex trophic interactions, it nonetheless provides an important first step in quantifying ecosystem-level implications of ARs as a tool for ecological restoration.

Increased river flow enhances the resilience of spatially patterned mudflats to erosion

Estuarine mudflats are profoundly affected by increased coastal erosion and reduced sediment delivery from major rivers. Although managers are having difficulties to control the cause of increased coastal erosion, they can help to manage the resilience of mudflat ecosystems to erosion through river flow regulation. In this study, we associated the resilience of a mudflat ecosystem to erosion with various magnitudes of river flow using a mechanism-based eco-morphodynamic model. Ecosystem resilience was reported in terms of i) what range of erosion rate the system can withstand before function collapse (persistence), ii) at which point function can be recovered (recovery), and iii) the uncertainty of system response to disturbances (response uncertainty). Specifically, the function of intertidal mudflat was characterized by landscape heterogeneity, primary productivity, and sediment stabilization. In a case study of the Yellow River Estuary (YRE) of China, it is found that increased erosion induced a collapse of the functioning state. Once collapsed, the erosion rate at which mudflat could recovered was lower than the erosion rate at which mudflat collapsed. Increased river flow enhanced the resilience of the mudflat ecosystem to erosion by increasing sediment deposition rate, which was an important attribute in the interaction process driving ecosystem resilience. Furthermore, given the same river flow allocation, the system with dynamic grazer population was more resilient than the system with a constant grazer number, highlighting the importance of controlling mudflat aquaculture to optimize the performance of river flow regulation. Our modeling results are dependent on the environment with several assumptions, however, as a preliminary, we believe our work represents a fundamental shift to modeling ecosystem resilience based on the mechanism of bio-physical interactions rather than relying on just quantifying the vital rates of particular species to compare river flow scenarios.

Genotoxicity of Natural Water during the Mass Development of Cyanobacteria Evaluated by the Allium Test Method: A Model Experiment with Microcosms

Cyanobacteria, which develop abundantly in aquatic ecosystems, can be harmful to humans and animals not only by releasing toxins that cause poisoning but also by provoking cytogenetic effects. The influence of the mass development of cyanobacteria on the genotoxic properties of natural water has been studied in model ecosystems (microcosms) with different compositions of biotic components (zooplankton, amphipods and fish). The validated plant test system “Allium test” was used in this study. Genotoxic effects were detected at microcystin concentrations below those established by the World Health Organization (WHO) for drinking water. In all experimental treatments, cells with disorders such as polyploidy and mitotic abnormalities associated with damage to the mitotic spindle, including c-mitosis, as well as lagging chromosomes were found. Genotoxic effects were associated with the abundance of cyanobacteria, which, in turn, depended on the composition of aquatic organisms in the experimental ecosystem. Fish, to a greater extent than other aquatic animals, maintain an abundance of cyanobacteria. After one month, in microcosms with fish, mitotic abnormalities and polyploidy continued to be detected, whereas in other treatments, there were no statistically significant genotoxic effects. In microcosms with amphipods, the number and biomass of cyanobacteria decreased to the greatest extent, and only one parameter of genotoxic activity (frequency of polyploidy) significantly differed from the control.