Competition For Resources Research Articles

Shared use of a mass‐flowering crop drives dietary niche overlap between managed honeybees and bumblebees

Abstract Resource competition between wild pollinators and managed honeybees (Apis mellifera) has the potential to detrimentally impact insect biodiversity as well as wild plant and crop pollination. As honeybees are central place foragers, their competitive impact on wild bees is expected to be structured by hive proximity, in conjunction with foraging decisions related to landscape‐level resource availability. Yet, how these factors structure dietary niche overlap between wild bees and managed honeybees remains unclear. We conducted a field experiment in seminatural grasslands, where honeybee foraging densities and niche overlap with buff‐tailed bumblebees (Bombus terrestris) were measured at four distances (<100, 500, 1000 and 2000 m) from experimentally placed apiaries, during and after the blooming period of mass‐flowering oilseed rape (Brassica napus). We measured honeybee foraging densities using standardized transect surveys, and quantified species diet composition and dietary niche overlap from pollen samples collected from both bee species. Honeybee foraging densities were highest near apiaries and declined sharply beyond 500 m from the apiaries. However, niche overlap was unrelated to hive proximity but positively related to the availability of oilseed rape. Furthermore, there were significant inter‐ and intraspecific differences in pollen diet composition and breadth throughout the season. Synthesis and applications: Niche overlap between honeybees and bumblebees in agricultural environments was due to resource sharing of mass‐flowering oilseed rape. When both honeybees and bumblebees predominantly forage on wild plants, they maintain distinct pollen diets, suggesting there is a low risk of resource competition between these generalist taxa. Conservation actions that promote floral resource availability and diversity in agricultural landscapes are crucial to maintain niche differentiation between managed honeybees and wild bees.

Alpine grassland community productivity and diversity differences influence significantly plant sexual reproduction strategies.

Whether and how community structure variation affects plant sexual reproduction is crucial for understanding species' local adaptation and plant community assembly, but remains unrevealed. In Qinghai-Tibetan grassland communities that differed in aboveground biomass (AGB) and species diversity, we found significant influence of AGB on both species' reproductive biomass allocation (RBA) and flowering and fruiting time, but of species diversity only on species' reproductive time. In high-AGB or high-diversity communities, smaller and earlier flowering species generally advanced their reproductive phenology and increased their reproductive allocation for maximizing their reproductive success, whereas larger and later flowering species delayed their reproductive phenology and decreased their reproductive allocation for maximizing their vegetative growth and resource competition. This change in reproductive allocation with the variation in community structures was more pronounced in nonclonal as compared to clonal plant species. Thus, we evidence an important influence of community structure on plant sexual reproduction strategies, and the pattern of the influence depends largely on species biological attributes.

The evolutionary consequences of learning under competition.

Learning is a taxonomically widespread process by which animals change their behavioural responses to stimuli as a result of experience. In this way, it plays a crucial role in the development of individual behaviour and underpins substantial phenotypic variation within populations. Nevertheless, the impact of learning in social contexts on evolutionary change is not well understood. Here, we develop game theoretical models of competition for resources in small groups (e.g. producer-scrounger and hawk-dove games) in which actions are controlled by reinforcement learning and show that biases in the subjective valuation of different actions readily evolve. Moreover, in many cases, the convergence stable levels of bias exist at fitness minima and therefore lead to disruptive selection on learning rules and, potentially, to the evolution of genetic polymorphisms. Thus, we show how reinforcement learning in social contexts can be a driver of evolutionary diversification. In addition, we consider the evolution of ability in our games, showing that learning can also drive disruptive selection on the ability to perform a task.

A 'rich-get-richer' mechanism drives patchy dynamics and resistance evolution in antibiotic-treated bacteria.

Bacteria in nature often form surface-attached communities that initially comprise distinct subpopulations, or patches. For pathogens, these patches can form at infection sites, persist during antibiotic treatment, and develop into mature biofilms. Evidence suggests that patches can emerge due to heterogeneity in the growth environment and bacterial seeding, as well as cell-cell signaling. However, it is unclear how these factors contribute to patch formation and how patch formation might affect bacterial survival and evolution. Here, we demonstrate that a 'rich-get-richer' mechanism drives patch formation in bacteria exhibiting collective survival (CS) during antibiotic treatment. Modeling predicts that the seeding heterogeneity of these bacteria is amplified by local CS and global resource competition, leading to patch formation. Increasing the dose of a non-eradicating antibiotic treatment increases the degree of patchiness. Experimentally, we first demonstrated the mechanism using engineered Escherichia coli and then demonstrated its applicability to a pathogen, Pseudomonas aeruginosa. We further showed that the formation of P. aeruginosa patches promoted the evolution of antibiotic resistance. Our work provides new insights into population dynamics and resistance evolution during surface-attached bacterial growth.

Meta-analytical evidence for frequency-dependent selection across the tree of life.

Explaining the maintenance of genetic variation in fitness-related traits within populations is a fundamental challenge in ecology and evolutionary biology. Frequency-dependent selection (FDS) is one mechanism that can maintain such variation, especially when selection favours rare variants (negative FDS). However, our general knowledge about the occurrence of FDS, its strength and direction remain fragmented, limiting general inferences about this important evolutionary process. We systematically reviewed the published literature on FDS and assembled a database of 747 effect sizes from 101 studies to analyse the occurrence, strength, and direction of FDS, and the factors that could explain heterogeneity in FDS. Using a meta-analysis, we found that overall, FDS is more commonly negative, although not significantly when accounting for phylogeny. An analysis of absolute values of effect sizes, however, revealed the widespread occurrence of modest FDS. However, negative FDS was only significant in laboratory experiments and non-significant in mesocosms and field-based studies. Moreover, negative FDS was stronger in studies measuring fecundity and involving resource competition over studies using other fitness components or focused on other ecological interactions. Our study unveils key general patterns of FDS and points in future promising research directions that can help us understand a long-standing fundamental problem in evolutionary biology and its consequences for demography and ecological dynamics.

Interspecific competition models and resource inequality between individuals.

Most classical discrete-time population models of interspecific competition have emerged as population-level phenomenological models with no evident basis at the individual level. This study shows that the Hassell-Comins model, a widely used discrete-time model of interspecific competition, can be derived in a bottom-up manner from a simple model of random resource competition between individuals of two species as an expression of expected population sizes in the next generation. The random competition leads to inequalities in resource allocation between individuals, which are related to the key parameters of the Hassell-Comins model that determine the density dependence of each species. The relationship between population-level parameters, such as intra- and interspecific competition coefficients, and individual-level parameters is discussed in detail, as is how the derived competition equations depend on the degree of inequality within each species. By considering limits of maximum or minimum resource inequality within each species, the derived model can describe interspecific competition for various combinations of two species exhibiting ideal scramble or ideal contest intraspecific competition.

Biomass response of chickpea (Cicer arietinum L.) to different textured soils and irrigation levels

Irrigation is required to supplement rainfall to enhance the productivity of chickpea in South Africa (SA). However, the dependence on irrigation can be problematic for SA and other countries with limited natural water resources and variable rainfall. Even though access to irrigation water has been identified as one of the challenges faced when planting chickpea in the winter season in SA, irrigation management strategies for chickpea grown on soils differing in texture have not gained considerable research attention. Hence, this study aimed to assess the effects of irrigation levels on dry matter production of chickpea grown on two soils differing in soil texture under greenhouse conditions. The experiment was arranged as a 3 × 2 factorial in a completely randomized design, with 3 irrigation levels (25%, 50% and 75% of the water-holding capacity of soil (WHC)) and 2 soils differing in soil textural class (Loamy sand (LS) soil and sandy loam (SL) soil), replicated thrice. Irrigation level, soil texture and their interaction significantly affected shoot biomass (SBM) and total plant biomass (TBM). Generally, SBM, TBM and root biomass decreased correspondingly with the reduction in irrigation. The 25% WHC significantly reduced the SBM by up to 60% and TBM by up to 56% compared to the 50% and 75% WHC. The SBM and TBM were higher in SL soil than in LS soil. A significantly higher root/shoot ratio (0.45) in the LS soil than in the SL soil (0.16) indicated that the conditions of LS soil encouraged plants to allocate higher proportions of biomass into roots, possibly due to increased competition for soil resources. In conclusion, maintaining soil moisture at 50% WHC ensures better chickpea dry matter production in SL soil.

Nationwide cost and capacity estimates for sedimentary basin geothermal power and implications for geologic CO2 storage

Introduction: Sedimentary basins are naturally porous and permeable subsurface formations that underlie approximately half of the United States. In addition to being targets for geologic CO2 storage, these resources could supply geothermal power: sedimentary basin geothermal heat can be extracted with water or CO2 and used to generate electricity. The geothermal power potential of these basins and the accompanying implication for geologic CO2 storage are, however, understudied.Methods: Here, we use the Sequestration of CO2 Tool (SCO2TPRO) and the generalizable GEOthermal techno-economic simulator (genGEO) to address this gap by a) estimating the cost and capacity of sedimentary basin geothermal power plants across the United States and b) comparing those results to nationwide CO2 sequestration cost and storage potential estimates.Results and discussion: We find that across the United States, using CO2 as a geothermal heat extraction fluid reduces the cost of sedimentary basin power compared to using water, and some of the lowest cost capacity occurs in locations not typically considered for their geothermal resources (e.g., Louisiana, South Dakota). Additionally, using CO2 effectively doubles the sedimentary basin geothermal resource base, equating to hundreds of gigawatts of new capacity, by enabling electricity generation in geologies that are otherwise (with water) too impermeable, too thin, too cold, or not deep enough. We find there is competition for the best sedimentary basin resources between water- and CO2-based power, but no overlap between the lowest-cost resources for CO2 storage and CO2-based power. In this way, our results suggest that deploying CO2-based power may increase the cost of water based systems (by using the best resources) and the cost of CO2 storage (by storing CO2 in locations that otherwise may not be targeted). As such, our findings demonstrate that determining the best role for sedimentary basins within the energy transition may require balancing tradeoffs between competing priorities.

Trait-Fitness Associations via Fecundity and Competition in a Two-Million-Year-Long Fossil Record.

AbstractThe evolution of phenotypic traits is usually studied on generational timescales or across species on million-year timescales. We bridge this conceptual gap by using high-density sampling of a species lineage, Microporella agonistes (Bryozoa, Cheilostomatida), over 2 million years of its evolutionary history, to ask whether trait-fitness associations are consistent with evolutionary trait models often applied to phenotypic time series. We use average fecundity and competitive outcome as two different fitness components, where competitive outcome is a proxy for partial survival. Examining three quantitative traits in multivariate analyses, we present evidence that some traits experienced substantial selective pressures, in part controlled by past environments. A complex interplay of resource competition with an altering set of competitors and past temperatures has contributed to the changing patterns of phenotypes within the focal species. A comparison with congeneric species living in the same regional community suggests that size traits are more temporally variable and less constrained than shape traits. Our analyses also show that while controls on phenotypes are complex and varied in time, ecological and evolutionary processes that unfold on shorter timescales are not inconsistent with macroevolutionary patterns observed on longer timescales.

Bioregionalization of the subarctic Pacific based on phytoplankton phenology and composition

The subarctic Pacific is generally perceived as relatively homogeneous since the North Pacific Subpolar Gyre dominates the water circulation in the area. However, previous research showed significant spatial differences in phytoplankton abundance and community structure. This study aimed to identify regions associated with distinct phytoplankton phenology and composition to comprehensively describe the main phytoplankton variability patterns across the subarctic Pacific. To this end, satellite GlobColour time series observations and an extensive in situ phytoplankton pigment dataset were used in the analysis. Five bioregions were identified, based on the Self-Organized Mapping technique, using a greater than 20-year satellite data series. The bioregions in the open Pacific waters were dominated by green algae, haptophytes, and pelagophytes and were divided into the areas affected by the North Pacific Transition Zone and beyond. The other bioregions were defined around the Pacific basin margins where the diatom contribution was generally higher, with a particular distinction of waters surrounding the Kuril and the Aleutian Islands. Our bioregion designations allow for future evaluation of the processes controlling the physical and biological dynamics within each bioregion, which has direct implications for foraging conditions available to higher trophic levels, including potential food resource competition.

Involvement of the gut microbiota in the metabolic phenotypes of two sympatric gerbils

Temporal niche partitioning is a crucial strategy for sympatric species to avoid predation and competition for habitat space and food resources. This study investigated the effect of the gut microbiota on the metabolic rhythms of two sympatric gerbil species (Meriones unguiculatus and Meriones meridianus) to test the hypothesis that the oscillatory patterns of microbiota may not fully mirror those of the host's metabolism. Experiment 1 compared the circadian metabolic and gut microbiota rhythms of M. unguiculatus (n = 12) and M. meridianus (n = 12) and measured the subjects' body temperatures and environmental temperature preferences. In Experiment 2.1, six M. meridianus gerbils were treated with antibiotics, and in Experiment 2.2, 21 M. unguiculatus gerbils (seven per treatment) were randomly gavaged with saline or a gut microbiota suspension from either M. unguiculatus or M. meridianus; their metabolic rhythms were subsequently measured. The results showed that the two gerbils had different metabolic phenotypes that determined activity heterogeneity and contributed to their coexistence. The relative abundances of Bacteroidetes, Actinobacteria, and Cyanobacteria in M. meridianus varied rhythmically in parallel with the daily metabolic rate, which was significantly higher at night than during the day. The rhythm of the metabolic rate was not noticeable in M. unguiculatus. However, in M.unguiculatus, the relative abundances of Firmicutes, Bacteroidetes, Proteobacteria, and Verrucomicrobia were significantly higher during the day than at night, while Cyanobacteria exhibited the opposite pattern. Antibiotic treatment significantly weakened the metabolic rhythms of M. meridianus, and the circadian rhythms slowly recovered after stopping antibiotic gavage. However, after transplanting M. meridianus' gut microbiota into M. unguiculatus, the metabolic rate of M. unguiculatus was not significantly different from that of the control groups. Our hypothesis was partly supported: the microbiota was only partially involved in regulating the metabolic rhythms of gerbils, and other factors could compensate for the effect of the gut microbiota on host metabolic rhythms. This finding underscores the complexity of host–microbiota interactions and highlights the need for further exploration into the multifaceted mechanisms governing host metabolic regulation.

Bringing a Systems Approach to Living Donor Kidney Transplantation

BackgroundLiving donor kidney transplantation (LDKT) is the best treatment option for patients with kidney failure. Efforts to increase LDKT have focused on micro-level interventions and the need for systems thinking has been highlighted. We aimed to identify and compare health system-level attributes and processes that are facilitators and barriers to LDKT. MethodsWe conducted a qualitative comparative case study analysis of three Canadian provincial healthcare systems with variable LDKT performance (Quebec:low, Ontario:moderate-high, British Columbia:high). Data collection entailed semi-structured interviews (n=91), document review (n=97) and focus groups (n=5 with 40 participants), analyzed using inductive thematic analysis. ResultsOur findings showed a strong relationship between the degree of centralized coordination between governing organizations and the capacity to deliver LDKT: 1) Macro-level coordination between governing organizations in British Columbia and Ontario increased capacities, while Québec was seen as decentralized with little formal coordination; 2) A higher degree of centralized coordination facilitated more effective resource deployment in the form of human resources and initiatives in British Columbia and Ontario, whereas in Québec resource deployment relied on hospital budgets leading to competition for resources and reduced capacity of initiatives; 3) Informal resource sharing through strong communities of practice and local champions facilitated LDKT in Ontario and British Columbia and was limited in Québec. ConclusionOur findings suggest that interventions that account for full-system function, particularly macro-level coordination between governing organizations can improve LDKT delivery. Findings may be used to guide structured organizational change towards increasing LDKT and mitigating the global burden of kidney failure.

NxtSPR: A deadlock-free shortest path routing dedicated to relaying for Triplet-Based many-core Architecture

Deadlock-free routing is a significant challenge in Network-on-Chip (NoC) design as it affects the network’s latency, power consumption, and load balance, impacting the performance of multi-processor systems-on-chip. However, achieving deadlock-free routing will routinely result in expensive overhead as previous solutions either sacrifice performance or power efficiency to proactively avoid deadlocks or impose high hardware complexity to resolve deadlocks when they occur reactively. Utilizing the various characteristics of NoC to implement deadlock-free routing can be significantly more cost-effective with less impact on performance. This paper proposes a relay routing algorithm (NxtSPR) with a shortest path property and a deadlock prevention mechanism based on a synchronized Hamiltonian ring. The proposal is based on an in-depth study of the characteristics of a Triplet-Based many-core Architecture (TriBA) NoC. We establish various important topology-related theories and perform a formal verification (proof-based) for them. By utilizing the critical subgraph and apex of TriBA, NxtSPR can pre-calculate downstream nodes forwarding ports for packets by using a concise judgment strategy. This significantly reduces the computational overhead required for data transmission while optimizing the pipeline design of routers to decrease packet transmission latency and power consumption compared to other TriBA routing algorithms. We group the data transmissions according to the levels of maximum Hamiltonian edges a packet will traverse during its transmission life cycle. Independent data transmissions between groups can avoid mutual interference and resource competition, eliminating potential deadlocks. Gem5 simulation results show that, under the synthetic traffic patterns, compared to the representative (Table) and up-to-date (SPR4T) routing algorithms, NxtSPR achieves a 20.19%, 14.76%, and 5.54%, 4.66% reduction in average packet latency and per-packet power consumption, respectively. Moreover, it has an average of 18.50% and 4.34% improvement in throughput, as compared to them. PARSEC benchmark results show that NxtSPR reduces application runtime by up to a maximum of 22.30% and 12.82% compared to Table and SPR4T, and running the same applications with TriBA results in a maximum runtime reduction of 10.77% compared to 2D-Mesh.

Neighborhood Diversity Promotes Tree Growth in a Secondary Forest: The Interplay of Intraspecific Competition, Interspecific Competition, and Spatial Scale.

Understanding the biodiversity-productivity relationship (BPR) is crucial for biodiversity conservation and ecosystem management. While it is known that diversity enhances forest productivity, the underlying mechanisms at the local neighborhood level remain poorly understood. We established a 9.6 ha dynamic forest plot to study how neighborhood diversity, intraspecific competition, and interspecific competition influence tree growth across spatial scales using linear mixed-effects models. Our analysis reveals a significant positive correlation between neighborhood species richness (NSR) and relative growth rate (RGR). Notably, intraspecific competition, measured by conspecific neighborhood density and resource competition, negatively impacts RGR at finer scales, indicating intense competition among conspecifics for limited resources. In contrast, interspecific competition, measured by heterospecific density and resource competition, has a negligible impact on RGR. The relative importance of diversity and intra/interspecific competition in influencing tree growth varies with scale. At fine scales, intraspecific competition dominates negatively, while at larger scales, the positive effect of NSR on RGR increases, contributing to a positive BPR. These findings highlight the intricate interplay between local interactions and spatial scale in modulating tree growth, emphasizing the importance of considering biotic interactions and spatial variability in studying BPR.

The effect of academic outcomes, equity, and student demographics on parental preferences for schools: evidence from a survey experiment

Abstract How does competition for school resources, along with racial and socioeconomic biases, shape parental preferences for schools? In this article, I investigate how school attributes affect preferences and choice, which sheds light on the processes that maintain school segregation. To do so, I conduct a survey experiment that explores parental preferences and the tradeoffs inherent in the process of school selection using school profiles that resemble those available on widely used education data platforms. I find that parents hold the strongest positive preferences for learning opportunities and overall school achievement compared to other attributes, including school racial and socioeconomic composition. Additionally, though parents prefer schools that have higher equity rankings, highly equitable schools are less desirable to parents than schools with more status and learning opportunities. However, parents also hold independent racial and socioeconomic preferences and —on average—avoid schools with more students of color and low-income students. Furthermore, results suggest they are largely unwilling to make tradeoffs that would result in schools with higher fractions of students of color or low-income students. Taken together, this study links prior studies on the segregating effects of educational data with literatures on school segregation by illustrating the specific dimensions that drive school choice.

Research analytics capabilities (RAC) survey: development, validation and revision using the Rasch model

PurposeThe research enterprise within higher education is becoming more competitive as funding agencies require more collaborative research projects, higher-level of accountability and competition for limited resources. As a result, research analytics has emerged as a field, like many other areas within higher education to act as a data-informed unit to better understand how research institutions can effectively grow their research strategy. This is a new and emerging field within higher education.Design/methodology/approachAs businesses and other industries are embracing recent advances in data technologies such as cloud computing and big data analytic tools to inform decision making, research administration in higher education is seeing a potential in incorporating advanced data analytics to improve day-to-day operations and strategic advancement in institutional research. This paper documents the development of a survey measuring research administrators’ perspectives on how higher education and other research institutions perceive the use of data and analytics within the research administration functions. The survey development process started with composing a literature review on recent developments in data analytics within the research administration in the higher education domain, from which major components of data analytics in research administration were conceptualized and identified. This was followed by an item matrix mapping the evidence from literature with corresponding, newly drafted survey items. After revising the initial survey based on suggestions from a panel of subject matter experts to review, a pilot study was conducted using the revised survey instrument and validated by employing the Rasch measurement analysis.FindingsAfter revising the survey based on suggestions from the subject matter experts, a pilot study was conducted using the revised survey instrument. The resultant survey instrument consists of six dimensions and 36 survey items with an establishment of reasonable item fit, item separation and reliability. This survey protocol is useful for higher educational institutions to gauge research administrators’ perceptions of the culture of data analytics use in the workplace. Suggestions for future revisions and potential use of the survey were made.Originality/valueVery limited scholarly work has been published on this topic. The use of data-informed and data-driven approaches with in research strategy within higher education is an emerging field of study and practice.

Attributive analysis of the anthropophytes fraction as part of the urban flora of Kyiv urban area (the degree of naturalization, invasive status, threat assessment for local ecosystems and biotic diversity)

International ecological scientific community pays special attention to urbanized territories as separate locations of alien invasive species of biota. The results of the attributive analysis of the structure of the alien fraction of KUA flora according to three current European categories are presented. The basis of the analysis is the final list of alien vascular plants of KUA flora, which contains 718 species. 166 taxa of alien vascular plants that immigrated to KUA from 2003 to 2023 were added to the list. It was found that the degree of naturalization of immigrant species is dominated by casual alien species, which make up 59.0% of the taxonomic composition of the fraction. Species that are elements of man-make environments reach 35.5%. At the same time, alien species that grow and persist for a long time in natural habitats, including protected areas, do not exceed 5.0%. According to the categories of invasive activity, there are species that are naturalized and do not show a tendency to invasions — 32.0%. The most dangerous among invasive plants are transformer species, represented by 2.5%, actual invasive species — 4.0%, potentially invasive species — 2.0%. Based on the «Classification of alien species according to their impact on the environment», adapted by the IUCN: the massive impact is 1.5% of the total number and 4.0% of the number of naturalized ones; accordingly, the major impact — 2.2% (5.4%); the moderate impact — 5.2% (11.2%); the minor impact — 28.1% (68.6%); the minimal impact — 4.2% (10.8%). Based on the results of screening the negative effects of invasive species on the environment, examples of threats are given. This is competition for natural resources, displacement of native plant species; penetration into forests of plants whose climamorphotypes are absent in local forest ecosystems (tree vines), etc. Threatening cases of spontaneous hybridization of immigrant species with local species and with each other have been identified (repeated occurrences in the genera Bidens L., Populus L., Reynoutria Houtt., etc.). The need for an experimental study of the chemical and physical negative effects of invasive plants on local species of biota and human health is indicated. It is noted that the flora of KUA, on the background of the flora of Europe, is currently uniformly affected by phytoinvasions as an urbanized spatial unit of Ukraine.

Conflict Resolution through Indigenous Knowledge Systems

Abstract Indigenous knowledge is the local knowledge that is unique to a given culture or society. It is the basis for local decision-making in agriculture, medicine, food education, environmental management, craft skills, linguistics and conflict management. The study explored mengehacha, an indigenous system of conflict resolution among the Gumuz people in northwest Ethiopia, which aims to restore peace and harmony within the community when conflicts result from natural resource competition, exchange marriage, clan-based conflict and theft. Data was collected through semi-structured interviews, focus group discussions, non-participatory observation and document analysis, and analysed qualitatively. The indigenous mechanisms of conflict resolution were found to be relatively participatory and supplementary to the state justice system. It is recommended that indigenous systems of conflict management be supported and given equal treatment with the modern court system and that exchange marriage be curbed, since it is becoming a trigger for conflict eruption among the Gumuz.

Analisis Konflik Sosial Dalam Cerpen “Panggung Terakhir” Karya M Rosyid HW

Social conflict usually occurs because competition in the economic field, such as competition for resources or jobs, can cause conflict between competing groups. This research explains the forms, causes and impacts in the short story "Last Stage" by M Rasyid Hw. The objectives of this research are: (1) Describe the form of social conflict; (2) analyzing the causes of social conflict; and (3) explain the negative and positive impacts of social conflict. This research method uses qualitative descriptive methods and literature. The primary data source is the short story "Last Stage" and secondary data sources are articles and theoretical books. Data collection techniques use reading and note-taking techniques. Data analysis techniques include data reduction, data presentation, and drawing conclusions. The results of this research are (1) a picture of social conflict in the form of arrogance, arrogance and nepotism; (2) the causes of social conflict are differences in individual character and differences in interests; (3) the negative impact of social conflict can lead to being hated by someone, the division of society, and a struggle for power.

Trophic effects of jellyfish blooms on fish populations in ecosystems of the coastal waters of China

Jellyfish play an important role in the material cycling and energy flow of food webs, and massive aggregations may have deleterious consequences for local fisheries; yet a theoretical framework of the trophic effects of jellyfish blooms on coastal fisheries is unclear. To address this knowledge gap, we assessed the trophic interactions between cooccurring bloom jellyfish and dominant fish groups (omnivorous fish and piscivorous fish) in the coastal waters of China (CWC) via stable isotope analysis; we subsequently discussed how jellyfish blooms may affect energy flow through coastal ecosystems. Our results indicate a considerable degree of trophic overlap (mean ratio > 65 %) between jellyfish and small omnivorous fish (< 10 cm), highlighting a similarity in feeding habits, while the overlap ratio decreased to <55 % of the large omnivorous fish group (> 10 cm). Relatively higher trophic levels and smaller overlaps of large omnivorous fish were found in the ecosystem with high jellyfish biomass, which suggested that they may reinforce the ontogenetic trophic shift pattern to alleviate the potential for resource competition with jellyfish under conditions of jellyfish explosion. The smallest trophic overlap (< 20 %) highlighted the strong trophic differentiation between jellyfish and piscivorous fish. Additionally, our study suggested that a massive aggregation of jellyfish can negatively influence zooplankton but may not transfer energy further up efficiently, implying a weak trophic coupling between jellyfish and upper-trophic levels in CWC ecosystems. Thus, we speculate that jellyfish play an important role in shaping pathways involved in the energy transfer of food webs and that large blooms may negatively affect fisheries through bottom-up control affecting prey availability. In general, these results hold strong potential to further improve the understanding of the trophic interactions between jellyfish and fish populations. Furthermore, this study provides valuable data for predicting the consequences of jellyfish blooms on ecosystems, and is crucial for ecosystem-based management of coastal fisheries.