Competition For Resources Research Articles

Psychological effects of water scarcity on community members: a case study of Lephalale municipality, Limpopo province, South Africa

IntroductionWater is essential for human survival and serves various purposes, including domestic, socioeconomic, and agricultural activities. However, water scarcity has emerged as a significant threat to this vital resource, posing a global challenge. While discussions surrounding the consequences of water scarcity typically emphasizes its effects on physical health and socioeconomic impacts, the mental and psychological effects on communities are often overlooked. Thus, the study aimed to explore the psychological effects of water scarcity on community members in Lephalale municipality, Limpopo province, South Africa.MethodsA qualitative research approach was used in the study. Participants were selected using purposive sampling and twenty participants who relied mainly on communal taps to access water were included (10 males and 10 females). Semi-structured in-depth interviews were used to collect data and interviews were audio recorded and later transcribed and translated by a language expert. Data were analyzed using content thematic analysis.ResultsThree main themes emerged from the study results: (1) emotional distress; (2) interpersonal conflicts; (3) disruptions in the activities of daily living. Emotional distress included feelings of shame, embarrassment, anger, disappointment, hopelessness and helplessness. Additionally, interpersonal conflicts arose due to competition for water resources, and disruptions in daily activities were linked to water access challenges.ConclusionThe study findings demonstrated that water scarcity has a significant psychological impact on community members. The study concludes by recommending the integration of psychological principles and involvement of mental health care practitioners when developing water management programmes, strategies, interventions, and policy. The study can provide policy makers and mental health care practitioners valuable insights into the mental health challenges faced by communities affected by water scarcity. Moreover, these study findings can assist mental health care practitioners to tailor their interventions to address the specific needs of communities experiencing water scarcity, particularly community members presenting with mental health challenges associated with this issue.

The race for AI hegemony

The growing use of Artificial Intelligence (AI) raises technical, economic, social, legal, and ethical questions. AI can transform industries, automate tasks, and create jobs, but it also brings concerns about infrastructure, resource redistribution, inequality, regulation, and ethics. The race for AI Hegemony between the US and China intensifies economic and political polarization. Investments in research and development will be massive, with competition for talent and resources. Without international coordination, the uncontrolled advance of AI could threaten security and social justice. An inclusive debate is essential to ensure the responsible use of this technology. This text was motivated by recent geopolitical events (already in the first month of 2025), which directly affect people's daily lives worldwide, leaving possible reflections on the power of AI as an active agent in shaping the future of humanity.

Parental conflicts and resource sharing: Evolutionary trade-off

The genetic struggle between parents and their offspring is a fundamental aspect of kin selection theory and the gene-centered perspective of evolution. Parental resource conflict, or parent-offspring conflict, is an intriguing concept within evolutionary biology. It refers to the natural disagreement between parents and their young regarding how parental resources should be distributed. This disagreement emerges from the differing evolutionary goals of parents for their offspring. Conflict arises only if parental behavior is influenced by genetic trade-offs concerning offspring success and the parent’s capacity to nurture more offspring, and its manifestation is significantly influenced by the nature of these trade-offs. There is a hypothetical scenario in which parents can influence gene expression in embryos directly. Similar to genomic imprinting, this may happen as a result of sexual selection in males competing with other males to gain more resources for their offspring from their mothers. One significant evolutionary theory that sheds light on parent-offspring resource conflict is parental investment theory, introduced by Robert Trivers in 1972. This theory posits that to enhance the survival prospects of their young, parents need to dedicate resources (such as time, energy, food, and care) to their offspring. However, given that resources are finite, parents must determine the amount of their available resources to distribute among each child or prospective child as well as who will contribute what. Mothers and fathers possess distinct reproductive priorities. Females generally put more effort into raising their young due to biological reasons (such as gestation and breastfeeding). Conversely, males may encounter different advantages and disadvantages regarding their contribution to offspring, which could result in conflicts over how resources ought to be allocated between parents and their young. Males and females employ distinct strategies to enhance their reproductive success, leading to competition over how resources are distributed to offspring. These strategies are influenced by sexual selection. To sum up, the competition for resources between parents, viewed through the lens of evolution, arises from the differing reproductive goals of parents and their offspring, fuelled by the fight for scarce resources. This interaction has molded the strategies and behaviors that affect resource distribution within families, applicable to both humans and other species.

Impact of Management Practices on Coffee-Pine Agroforestry: Coffee Yield and Soil Respiration

The coffee-pine agroforestry system offers a promising solution to enhance coffee yields and maintain soil health on degraded lands. This study aims to evaluate the impact of various agroforestry management practices on coffee yield and soil respiration. The experiment was conducted using a complete randomized block design across five management treatments: without management, without fertilization, organic fertilization, mixed fertilization, and recommended management by Perhutani. The observed parameters included coffee yield, soil respiration, soil moisture, soil temperature, litter biomass, canopy cover, and soil organic carbon (SOC) content. Results indicated that the recommended management (RM) plot achieved the highest coffee yield (834 kg ha⁻¹), attributed to wider planting spacing, which reduced resource competition between coffee and pine trees. The RM plot also displayed stable soil moisture and temperature, supporting coffee growth. Meanwhile, soil respiration showed no significant differences across treatments, though the mixed fertilization (MF) plot exhibited the highest respiration rate, indicating higher microbial activity due to combined fertilizer use. In conclusion, optimal management in agroforestry systems can enhance coffee productivity while preserving soil health. Keywords: Agroforestry, Coffee Yield, Soil Management, Soil Moisture, Soil Respiration.

Heat and Hate: Climate Security and Farmer-Herder Conflicts in Africa

Abstract We investigate the impact of climate shocks on farmer-herder violence, using geolocalized data on conflict events for Africa, 1997-2014. We find that a one degree temperature increase yields a 54% increase in conflict probability in mixed areas populated by both farmers and herders (versus 17% in non-mixed areas). Quantifying the impact of projected climate change in 2040, we find that -when factoring in the magnifying effect of mixed settlements- annual conflicts are predicted to rise by a third. Drawing on a fine-grained analysis of groups' mobility patterns, we show that resource competition is a major driver of farmer-herder violence.

Date Palm and Water Management in Gulf Cooperation Council Countries: New Insights Using Bayesian Longitudinal Model

This study applies panel techniques with macro variables to analyze the connection between date palms production and water management in GCC countries using the Bayesian random and mixed effects models. Also, this study utilizes panel-corrected standard error (PCSE) and feasibly generalized least squares (FGLSs) methods to test the robustness and verify the Bayesian results. By utilizing a Bayesian longitudinal model, this study not only fills in a critical research gap but also provides a fresh perspective on the dynamics of water management practices and their impact on date palm cultivation over time. The results of this study confirm that the posterior means for coefficients of the water efficiencies for all purposes are positive with a magnitude of 11%, 28%, and 125%, respectively, for agriculture, services, and industrial purposes, determining that the Bayesian inference is efficient and reasonable. This result indicates the fit of the model, the validation of the results, and the knowledge that decision-making can suggest water management strategies for date palm cultivation. The findings from the PCSE and FGLSs models confirm that efficient water use in services (β = −0.329, significant at 1%) and agriculture (β = −2.834, significant at 1%) can lead to increased competition for limited water resources, reducing water availability for palm cultivation. Water use efficiency for industrial purposes (β = 0.503, significant at 1%) shows a positive relationship. Industrial water efficiency practices, such as water recycling, can help preserve water resources, managing more water available for agricultural activities. In addition, industrial water efficiency initiatives often involve technological innovations that can be applied to agriculture, improving water management practices in palm production. Developing and implementing comprehensive strategies, such as Integrated Water Resource Management (IWRM), that consider water needs for all purposes and establish coordinated water distribution plans to ensure sustainable water use practices across various sectors are highly recommended for policymakers and stakeholders. Also, further research must be performed to investigate the implications of climate change on water resources and date production to develop adaptation strategies that enhance the resilience of date palm cultivation. This will help the development of sustainable agricultural practices that balance water conservation with agrarian productivity.

Trade-off strategies between growth and defense of spring ephemeral plants in early spring

IntroductionSpring ephemeral plants represent a unique ecological category of herbaceous plants, characterized by early blooming and vivid flowers with significant ornamental value. Understanding the adaptive strategies of spring ephemerals is crucial for the introduction and cultivation of early spring plants, as well as for optimizing light energy utilization and nutrient cycling within ecosystems.MethodsWe evaluated 26 functional traits across four spring ephemerals and four spring non-ephemeral plants along an elevation gradient. By establishing a plant functional trait network, we examined the adaptation strategies of early spring plants at different elevations and compared the differences in adaptation strategies between two types of plants.ResultsSpring ephemerals exhibited higher concentrations of carbon and nitrogen, lower concentrations of carbohydrates, higher edge density and modularity in trait networks, and stronger linkages between defense traits. Plants at higher elevations demonstrated higher leaf dry matter content and leaf total flavonoid concentration, and lower nitrogen concentration, influenced by temperature, precipitation, and soil nutrients.DiscussionThese results demonstrated that spring ephemerals have a strong nutrient uptake capacity, and adopt resource competition strategies to rapidly accumulate nutrients and reproduce. The plants at higher elevations adopt more conservative strategies, with trait networks showing increased modularity, edge density, and closer correlations among traits to enhance resource utilization. This study provides new insights into the adaptive strategies of spring ephemerals by demonstrating how plants allocate resources for growth and defense through the regulation of trait variation and correlations among traits.

Contrasting habitat associations and ecophysiological adaptations drive interspecific growth differences among Himalayan high-mountain plants.

Understanding interspecific differences in plant growth rates and their internal and external drivers is key to predicting species responses to ongoing environmental changes. Annual growth rates vary among plants based on their ecological preferences, growth forms, ecophysiological adaptations, and evolutionary history. However, the relative importance of these factors remains unclear, particularly in high-mountain ecosystems experiencing rapid changes. We examined how habitat associations, elevational optima, growth forms, and ecophysiological and anatomical traits influence interspecific differences in radial growth rates among 324 vascular dicot species naturally occurring in the western Himalayas. Growth rates were determined from annual ring width measurements on the oldest plant sections of over 7,800 individuals from a range of habitats (desert, steppe, wetland, alpine, subnival), growth forms (perennial tap-rooted, rhizomatous, cushiony, woody), and climatic gradients (elevations of 2,650-6,150 m). Habitat associations accounted for 24% of the variability in interspecific growth rates. Adding growth form and height increased the explanation to 42%, and incorporating plant functional traits further improved predictions to 46%. Growth rates were higher in warmer, drier conditions and lower in cold, wet environments. Subnival cushion plants had the slowest growth, while ruderal plants grew the fastest. Desert plants showed higher growth rates, reflecting their drought adaptive strategies, while wetland forbs had lower growth rates due to increased resource competition. Growth was positively correlated with leaf nitrogen content and non-structural carbohydrates (mainly fructans), due to enhanced photosynthesis and stress tolerance, and negatively correlated with leaf carbon and root nitrogen content. Our study of 324 dicot species in the western Himalayas suggests that plant growth in high elevations is determined by a combination of habitat conditions, morphological traits, and ecophysiological adaptations. Growth variations among the highest-growing angiosperms reflect adaptive strategies along the global 'fast-slow' and 'acquisitive-conservative' spectrums. These results underscore the importance of habitat-specific studies for predicting plant growth responses to environmental changes, emphasizing a species-specific approach for effective conservation in fragile ecosystems.

Spatial, environmental and trophic niche partitioning by seabirds in a climate change hotspot.

For similar species to co-occur in places where resources are limited, they need to adopt strategies that partition resources to reduce competition. Our understanding of the mechanisms behind resource partitioning among sympatric marine predators is evolving, but we lack a clear understanding of how environmental change is impacting these dynamics. We investigated spatial and trophic resource partitioning among three sympatric seabirds with contrasting biological characteristics: greater crested terns Thalasseus bergii (efficient flyer, limited diver, and preference for high quality forage fish), little penguins Eudyptula minor (flightless, efficient diver, and preference for high quality forage fish) and silver gulls Chroicocephalus novaehollandiae (efficient flyer, limited diver and generalist diet). We investigated interannual variability in resource partitioning in relation to environmental variability in a climate change hotspot influenced by the warm and intensifying East Australian Current (EAC). Sampling was conducted from 2012 to 2014 during the austral summer breeding season of seabirds at Montague Island, Australia. Daily seabird movements were monitored using GPS trackers and feather tissues were collected and processed for stable isotope analysis (δ15N and δ13C). Generalised Linear Mixed Models were used to assess how changes in oceanographic conditions influenced space use for each species. Schoener's D and Bayesian mixing models were used to respectively investigate the levels of yearly inter-specific environmental and trophic niche overlaps. Crested terns and little penguins were less likely to be observed in warm, saline EAC waters and crested terns and silver gulls had smaller foraging areas on days when more than 30% of available habitat was classified as EAC origin. All species preferred areas with low variability in sea surface temperature (<0.5°C). Terns and penguins occupied similar marine trophic levels, with penguins having larger isotopic niche spaces in 2014 when the EAC was more dominant in the study area. Gulls occupied the lowest trophic level, with the widest niche and lowest interannual variability in niche area. As the EAC intensifies along the southeast coast of Australia under climate change, interspecific competition for resources may increase, with the greatest impacts on species like little penguins that have relatively restricted foraging ranges. This study suggests that species-specific biological traits and behavioural plasticity should be accounted for when predicting the effects of climate change on marine species.

Climate change and migration dynamics in Somalia: a time series analysis of environmental displacement

Climate change is a significant driver of human migration, especially in vulnerable regions like Somalia. This study investigates the relationship between climate variables—average annual precipitation, temperature, and CO₂ emissions—and net migration in Somalia, using time series data from 1990 to 2020. Additionally, it examines the role of population growth as a factor influencing migration. Applying the Autoregressive Distributed Lag (ARDL) model, this research captures both short- and long-term dynamics, providing insights into how environmental and demographic factors impact migration in this climate-sensitive region. The results indicate that favorable rainfall conditions positively influence net migration, as improved agricultural productivity stabilizes livelihoods, reducing pressures to migrate. In contrast, increased CO₂ emissions, associated with environmental degradation, negatively impact migration by limiting financial capacity, creating a “trapped population” effect. Population growth also intensifies migration pressures by increasing competition for limited resources. Interestingly, temperature variations do not significantly influence migration, possibly due to adaptive strategies or resilience to temperature fluctuations in the region. These findings underscore the need for policies focused on enhancing agricultural resilience, restoring degraded environments, and creating economic opportunities to reduce migration pressures in Somalia. Investments in sustainable land use, climate adaptation, and population management strategies are essential to address the complex challenges of climate-induced migration.

Assessing decarbonization strategies and industrial symbiosis in the chemical and waste‐to‐energy sector

AbstractSwiss waste‐to‐energy (WtE) plants are required to capture their CO2 emissions by 2050 to meet the net‐zero climate target, with options for underground storage (carbon capture and storage [CCS]) or utilization (carbon capture and utilization [CCU]). This opens up a synergistic opportunity for the petrochemical industry to utilize the captured CO2 as a feedstock, potentially helping both sectors reduce their carbon footprints. We conducted a prospective carbon footprint analysis on various net‐zero strategies within the Swiss WtE plants (CCU and CCS) and German ethylene production (CO2‐based ethylene, bio‐ethylene, and fossil ethylene with CCS), including scenarios of industrial symbiosis. While focusing on these two countries, the findings offer valuable insights applicable to similar sectors in other regions. All assessed pathways reduce the carbon footprint by at least 60% relative to the reference scenario (no carbon capture in WtE plants and fossil ethylene production). Bio‐ethylene and direct air capture–based ethylene combined with CCS in WtE exhibit the lowest climate change impacts, achieving net negative emissions when powered by renewable electricity. However, these pathways all come with trade‐offs: The availability of sustainable biomass and low‐carbon electricity is limited, and future resource competition may delimit the penetration of these technology combinations. CCS in ethylene production plants could reduce emissions while utilizing existing infrastructure but does not eliminate emissions from fossil fuel extraction. Ethylene produced with CO2 from WtE plants could be a viable interim solution until CCS barriers are overcome.

From fossil fuels to alternative fuels: strategy development for a sustainable transport sector in Germany

BackgroundMany countries agreed to reduce CO2 emissions to limit global warming under the terms of the Paris Agreement. In Europe, this agreement is supported by the climate targets introduced under the European Green Deal and the Fit for 55 package. Although Germany has made substantial progress in reducing emissions across various sectors, the transport sector remains a notable exception, showing little improvement. It is therefore essential to reevaluate the transport sector to strengthen its contribution to achieving the emission reduction targets. The aim of this study is to identify and propose strategies for shifting from fossil fuel-based transport to a more sustainable mode centred on alternative fuels. To investigate the potential pathways, an integrated approach is developed using a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis and multi-criteria decision analysis (MCDA).ResultsA two-step survey was used to collect data from different stakeholders in order to derive the key factors for the implementation of alternative fuels and devise transition strategies. The findings show that reducing GHG emissions, resource competition, and the impacts of environmental regulations are the most important factors for evaluating the transition strategies. On the other hand, reducing the competitiveness of fossil fuels through increased prices, as well as technical and infrastructural support, are the most promising strategies.ConclusionsThe sustainable transition in the transport sector is fundamentally driven by the use of renewable fuel alternatives as sustainable energy carriers to replace fossil fuels. The use and deployment of renewable fuel alternatives will play the most significant role in the defossilization of the transport sector, on course to achieve a 55% reduction by 2030 and reaching climate-neutrality by 2050. However, identification of the proper transition strategies in the phase-out of fossil fuels and their replacement with renewable fuel alternatives necessitates a comprehensive evaluation framework. This work contributes to this by developing a holistic evaluation framework, enabling the incorporation of multiple stakeholders within the identification and evaluation of the transition strategies. While several strategies are identified, stakeholders agree that reducing the competitiveness of fossil fuels through increased prices and lower subsidies would be the best strategy.

An Effective Approach for Kidney Diseases detection using Transfer Learning

An essential issue in public health, chronic kidney disease is characterized by a high prevalence, morbidity, and mortality rate. India is home to 17% of the world's population, but having less than 3% of the total land mass. Results have been less than ideal due to a combination of factors, including a low gross domestic product, a large percentage of patients living below the poverty line, and inadequate funding for health care. In addition, despite ongoing concerns about communicable diseases, high rates of child and maternal mortality, and a competition for resources, chronic kidney disease (CKD) and other non-communicable diseases have frequently been disregarded. High prevalence of chronic kidney disease in India is due to multiple factors. According to data from the United Nations Children's Emergency Fund, 28% of infants weigh less than 2.5 kg when they are born. Reduced estimated glomerular filtration rate and reduced kidney volume at delivery may result from nutrients deficiency during pregnancy, such as hypovitaminosis A.A GFR of 60 or above is considered normal. Consult your physician regarding the reevaluation of your GFR(Glomerular Filtration Rate).GFRs below 60 may signify kidney pathology. Inquire with your physician on the preservation of kidney health.A GFR of 15 or lower indicates renal failure. Dialysis or kidney transplants are necessary for the majority falling below this threshold. Consanguinity and genetic inbreeding enhance kidney and urinary tract congenital abnormalities and obstructive or reflux nephropathy risk. Poverty, poor sanitation, pollution, water contamination, overcrowding, and known and unknown nephrotoxins (including heavy metals and plant poisons in indigenous treatments) can cause glomerular and interstitial kidney disorders. The rising prevalence of hypertension and diabetes compounds these exposures. India is anticipated to have the most diabetics by 2030.

Optimizing Early Growth of Laminaria hyperborea in Controlled Settings: A Pathway to Improved Restoration Efforts

Laminaria hyperborea, a key species in marine forest ecosystems, is experiencing pressure at its southern distribution limit in northern Portugal due to climate change and human-induced stressors. The ongoing degradation of marine forests highlights the need for effective restoration strategies to protect biodiversity and maintain the essential services provided by these habitats. Cultivation of juvenile kelps in laboratory settings is a common approach shared across multiple strategies aimed at supporting reforestation efforts; however, the specific cultivation process for L. hyperborea remains largely underexplored. In this study, we tested two seeding densities to optimize the production of L. hyperborea recruits for reforestation initiatives. We assessed the effects of seeding density on juvenile development by measuring both area coverage and length. Our findings revealed that higher seeding density initially promoted greater area coverage (e.g., 8.69 ± 0.38 cm2 vs. 3.35 ± 0.27 cm2) but reduced the length of individual recruits over time (e.g., 0.26 ± 0.0026 cm vs. 0.39 ± 0.003 cm at T3). This suggests that increased competition for resources at high densities limits individual growth. In contrast, lower densities produced larger, more robust individuals (e.g., 0.50 ± 0.004 cm vs. 0.262 ± 0.003 cm at T4), which may enhance post-transplantation survival in challenging environmental conditions. This suggests that utilizing lower seeding densities may improve individual growth while decreasing overall resource use and maintenance needs, promoting a more sustainable cultivation process and minimizing impacts on donor populations. However, further research is essential to refine the cultivation protocols and fully understand the variables influencing juvenile kelp development. Improving all phases of the restoration process, from laboratory cultivation to field deployment, will be critical for reducing costs, streamlining logistics, and ensuring the scalability of future kelp restoration efforts.

Congestion Control Scheme for Link Quality Improvement Using Bio‐Inspired Fuzzy Inference System–Based CoAP in IoT

ABSTRACTThe Internet of Things (IoT) represents the Internet's future by including devices that can connect with one another. IoT devices in IoT networks collect data from their surroundings and send it in bursts to a server in a remote location. The quantity of applications using computer networks causes resource competition, which in turn causes congestion. The most difficult task in enhancing network quality of service (QoS) is IoT congestion control. For IoT items with modest resource requirements, various protocols have arisen. Different shortages and issues affect basic congestion control, which increases bandwidth use, data loss, and delay. Thus, to solve this issue, in this paper, we propose a bio‐inspired fuzzy inference system (FIS)–based constrained application protocol (BIFIS‐CoAP) for avoiding congestion over network. In order to determine the level of congestion, we use the bottleneck bandwidth gradient (BG‐gradient) and round‐trip time gradient (RT‐gradient) as inputs for BIFIS‐CoAP. By using this indication, BIFIS‐CoAP may anticipate impending congestion and alter the sending rate to prevent it. In order to achieve high performance for burst data transfer, BIFIS‐CoAP constantly checks for bandwidth that is available and uses the congestion degree for updating the variable retransmission time out (RTO) for retransmissions. Using the adaptive Tasmanian devil optimization method (ATDO), input parameters like the RT‐gradient and BG‐gradient are modified to enhance the performance of the FIS. Numerous simulation studies have shown that BIFIS‐CoAP is feasible, and the simulation results show that it performs better than basic CoAP and fuzzy CoAP in terms of delay, throughput, delivery ratio, and retransmissions.

Keeping up with the Joneses? Perceptions of mobility and opportunity within local knowledge economies across Germany

Abstract Recent work on the rise of the knowledge economy has identified the importance of economic context in shaping individual perceptions and preferences. Combining novel survey and locally fine-grained data for the case of Germany, we analyze the association between local knowledge economies and individual perceptions of social mobility and economic opportunity. We find that individual perceptions of mobility, access to affordable housing, and employment security are negatively associated with thriving local knowledge economies. This finding is partly at odds with accounts of ‘aspirational voters’ being the beneficiaries of local economic growth. Rather, we interpret our findings as supporting the ‘status anxiety’ hypothesis, which attributes negative mobility perceptions with competition for scarce economic and social resources. In time, these perceptions can become fertile ground for the development of populist attitudes and vote choices.

Impact of Urbanization on Water Resource Competition Between Energy and Food: A Case Study of Jing-Jin-Ji

Water resources, energy, and food are important resources in China, which play an important role in the process of urban development and are important basic resources for sustainable urban development. This study applied water footprint theory to water–energy–food relations. The regional integration of the Jing-Jin-Ji region faced new challenges during urbanization, and unified measures were applied to quantify the urban water demands and energy and food competition in the Jing-Jin-Ji region from 2003 to 2017. The index was used to evaluate the intensity of the competition for water for food and energy. The results indicated that from 2003 to 2017, the water footprint of grain production in the Jing-Jin-Ji region decreased from 30.984 billion m3 to 21.36 billion m3, of which the blue water footprint decreased from 13.032 billion m3 to 9.854 billion m3. The water footprint of energy production increased from 578 million m3 to 1.175 billion m3. The competition relation between cities in the Jing-Jin-Ji region was obtained according to the competition index, and corresponding measures were identified according to different competition levels. This study provides valuable insights for policymakers in designing sustainable urban development strategies for cities facing similar challenges of water resource, energy, and food competition during rapid urbanization.

The Wildcat That Lives in Me: A Review on Free-Roaming Cats (Felis catus) in Brazil, Focusing on Research Priorities, Management, and Their Impacts on Cat Welfare.

Domestic cats (Felis catus) currently occupy the 38th place in the Global Invasive Species Database. Free-roaming cats potentially have broad-ranging impacts on wildlife, occupying most terrestrial environments globally as house pets, strays, or feral animals. In Australia, for example, cats are responsible for the decline in many vertebrate populations and extinction of several native mammals. However, in Brazil, few studies have explored either direct impacts of predation on wildlife, or other indirect impacts, such as competition for resources, niche overlap, hybridization, and disease transmission. In this review, we summarize and discuss 34 original research reports, published between 2001 and 2020, on impacts of free-roaming cats in Brazil. We briefly contextualize the history of cat domestication and present that, in Brazil, more studies have focused on the potential of free-roaming cats to transmit disease than to exert impacts via predation or competition on wildlife. More studies were conducted in Brazilian mainland areas (n = 23)-notably in Atlantic Forest-than on islands (n = 11). The review highlights potential impacts of cats on wildlife. We also discuss how control management strategies can affect the welfare of domestic cats, identifying potential knowledge gaps as well as opportunities for future research. Finally, understanding risks of cat predation is necessary to inform future measures to mitigate impacts on wildlife, without neglecting cat welfare.

Inferring resource competition in microbial communities from time series.

The competition for resources is a defining feature of microbial communities. In many contexts, from soils to host-associated communities, highly diverse microbes are organized into metabolic groups or guilds with similar resource preferences. The resource preferences of individual taxa that give rise to these guilds are critical for understanding fluxes of resources through the community and the structure of diversity in the system. However, inferring the metabolic capabilities of individual taxa, and their competition with other taxa, within a community is challenging and unresolved. Here we address this gap in knowledge by leveraging dynamic measurements of abundances in communities. We show that simple correlations are often misleading in predicting resource competition. We show that spectral methods such as the cross-power spectral density (CPSD) and coherence that account for time-delayed effects are superior metrics for inferring the structure of resource competition in communities. We first demonstrate this fact on synthetic data generated from consumer-resource models with time-dependent resource availability, where taxa are organized into groups or guilds with similar resource preferences. By applying spectral methods to oceanic plankton time-series data, we demonstrate that these methods detect interaction structures among species with similar genomic sequences. Our results indicate that analyzing temporal data across multiple timescales can reveal the underlying structure of resource competition within communities.

Innovative Research on Physical Data Management of Football Players Under the Background of Smart Medical Treatment

With the intensification of the competition for public medical resources and the rapid development of smart medical technology, the demand for in-depth analysis of athletes’ basic information and decision support is growing day by day. However, the practice of applying smart medicine to athletes’ physical information management is still relatively limited. This paper aims to explore how to use smart medical decision technology to build an integrated athlete physical information management and decision support platform. Taking football players as the research object, this paper integrates data mining technology into a smart medical decision-making model, to achieve accurate analysis and effective management of athletes’ physical fitness information. The core of the research is to develop a smart healthcare decision model that can identify key information and patterns on the platform through data mining technology. In the selection of the decision algorithm, this paper adopts cluster analysis and association rule mining algorithms, which can deeply dig into the potential rules and correlations in the data. Through the application of an algorithm, we can accurately evaluate the physical condition of football players, and provide scientific guidance and suggestions for their subsequent physical training. The algorithm in this study is not only innovative in theory, but also shows good adaptability and effectiveness in practical application.