Variety Of Changes Research Articles

Leadership Strategies for Managing Human and Technological Diversity in the Industrial 5.0 Era: A Systematic Review

The problem formulation that arises from this research is how the efforts made by leaders in the industrial era 5.0 overcome problems related to the process of managing HR diversity and technological changes in increasing business innovation in order to increase business productivity and business sustainability, so that they can survive the changes that exist. This research focuses on discussing the efforts of leaders to overcome the problems of the process of managing HR diversity and technological changes in the 5.0 era in order to increase business innovation to increase business productivity and business sustainability. The results of the data analysis used used descriptive qualitative analysis using literature studies through systematic literature review. The research method uses a quantitative descriptive method of data analysis using the structural equation model (SEM) method, where the results of data processing with the SEM method are carried out with the PLS application. From the results of the study, it is concluded that the 5.0 leadership efforts in overcoming the management of HR diversity in increasing business innovation, namely building an inclusive culture, recognizing and appreciating diverse contributions, empowering employees, building intercultural skills, supporting inclusive research and development, using technology that supports engagement and collaboration and diversity-oriented monitoring and evaluation. The results concluded that the 5.0 leadership efforts in overcoming technology management in increasing business innovation, namely a deep understanding of technology, creating an environment that supports technological innovation, focusing on employee engagement and skills, partnering with technology experts, using technology for collaboration and communication, encouraging a culture of experimentation and learning, continuous review of processes and practices and recognition and reward for innovative contributions. Along with managing the diversity of human resources and technology in increasing business innovation, it can create more creativity and make leaders have to follow the direction and be able to adapt to changes so that the company can improve its performance and can continue to run its business optimally and be able to meet consumer needs properly.

Long-term nitrogen deposition reduces the diversity of nitrogen-fixing plants.

Biological nitrogen fixation is a fundamental part of ecosystem functioning. Anthropogenic nitrogen deposition and climate change may, however, limit the competitive advantage of nitrogen-fixing plants, leading to reduced relative diversity of nitrogen-fixing plants. Yet, assessments of changes of nitrogen-fixing plant long-term community diversity are rare. Here, we examine temporal trends in the diversity of nitrogen-fixing plants and their relationships with anthropogenic nitrogen deposition while accounting for changes in temperature and aridity. We used forest-floor vegetation resurveys of temperate forests in Europe and the United States spanning multiple decades. Nitrogen-fixer richness declined as nitrogen deposition increased over time but did not respond to changes in climate. Phylogenetic diversity also declined, as distinct lineages of N-fixers were lost between surveys, but the "winners" and "losers" among nitrogen-fixing lineages varied among study sites, suggesting that losses are context dependent. Anthropogenic nitrogen deposition reduces nitrogen-fixing plant diversity in ways that may strongly affect natural nitrogen fixation.

Aquaculture activities associated with the invasion of Oreochromis niloticus and changes in stream fish diversity

Aquaculture activities associated with the invasion of Oreochromis niloticus and changes in stream fish diversity

Faba bean-wheat intercropping controls the occurrence of faba bean Fusarium wilt by improving the microecological environment of rhizosphere soil

BackgroundFusarium wilt is a severe soil-borne disease that affects faba bean production. Faba bean-wheat intercropping is often used to control the occurrence of Fusarium wilt in faba bean. AimsTo evaluate the effects of faba bean-wheat intercropping on the occurrence of faba bean Fusarium wilt and soil microecology. MethodsWe established two planting patterns, faba bean monocropping (M) and faba bean-wheat intercropping (I), to investigate Fusarium wilt occurrence and plant dry weight and assess changes in soil enzyme activities, microbial diversity, and community composition during different stages of disease onset. ResultsIntercropping effectively controlled faba bean Fusarium wilt at the three disease stages and increased the dry weight of faba bean plants. Intercropping promoted the activities of catalase (CAT), urease, sucrase, and acid phosphatase in the rhizosphere soil of faba bean at three disease stages. Bacterial and fungal diversity decreased with disease progression, and intercropping mitigated this trend. Compared with monocropping, intercropping increased the abundance of beneficial bacteria such as Proteobacteria, Actinobacteriota, Gemmatimonadota, Gemmatimonas, Conexibacter, and Sphingomonas, while reducing the abundance of pathogenic fungi such as Alternaria, Cladosporium, and Fusarium. Intercropping also increased the abundance of arbuscular mycorrhiza, soil saprophytes, and undefined saprophytes while decreasing the abundance of plant pathogens. ConclusionFaba bean-wheat intercropping enhanced soil enzyme activities, effective nutrient content, and alpha diversity indices of bacteria and fungi in the rhizosphere soil of faba bean, while promoting the abundance of beneficial bacteria, arbuscular mycorrhizal fungi, as well as both soil and undefined humus. Simultaneously, intercropping reduced the abundance of plant pathogens, facilitated nutrient cycling in the soil, provided sufficient nutrients for crop uptake, and mitigated the toxic effects of hydrogen peroxide on cells. Ultimately, this resulted in a reduced occurrence of Fusarium wilt.

Ptačí diverzita v historickém zámeckém parku – implikace pro ochranu biodiverzity v hospodářských lesích

Long-term trends of abundance and diversity of forest birds have been very stable over past decades in European managed forests. It can be caused by high heterogeneity on habitat scale. In European cultural landscapes, there is another habitat very similar to managed forests, and that is a historic manor park. The parks can even show higher bird diversity than managed forests. However, there is an evident knowledge gap related to long-term changes of bird abundance and diversity in the habitats of manor parks. In this study we observed long-term changes of bird community in the historic manor park Čechy pod Kosířem (Czech Republic) using comparison of bird territory mapping in 2022–2023 with older bird studies in this locality. We gained an overview of bird community changes in the manor park for the period of 1997–2023. Results show that the bird community in historic manor park was remarkably unvarying in abundance and diversity. Historic manor parks can be considered as important refuges for forest bird diversity in cultural landscapes. We discuss the research implications for conserving bird diversity in managed forests especially in connection with large old trees preservation providing heterogeneity of nest habitats.

Historical knowledge transfer driven self-adaptive evolutionary multitasking algorithm with hybrid resource release for solving nonlinear equation systems

In reality, there are many extremely complex nonlinear optimization problems. How to locate the roots of nonlinear equation systems (NESs) more accurately and efficiently has always been a major numerical challenge. Although there are many excellent algorithms to solve NESs, which are all limited by the fact that the algorithm can solve at most one NES in a single run. Therefore, this paper proposes a historical knowledge transfer driven self-adaptive evolutionary multitasking algorithm framework (EMSaRNES) with hybrid resource release to solve NESs. Its core is that in one run, EMSaRNES can efficiently and accurately locate the roots of multiple NESs. In EMSaRNES, self-adaptive parameter method is proposed to dynamically adjust parameters of the algorithm. Secondly, adaptive selection mutation mechanism with historical knowledge transfer is designed, which dynamically adjusts the evolution of populations with or without knowledge sharing according to changes in the current population diversity, thereby balancing population diversity and convergence. Finally, hybrid resource release strategy is developed, which archives the roots that meet the accuracy requirements, and then three distributions are selected to generate new populations, thus ensuring that the population diversity is maintained at high level. After a variety of experiments, it has been proven that compared to comparative algorithms EMSaRNES has superior performance on 30 general NESs test sets. In addition, the results on 18 extremely complex NESs test sets and two real-life application problems further prove that EMSaRNES finds more roots in the face of complex problems and real-life problems.

Gut Microbiota Alterations in Alzheimer's Disease: Relation with Cognitive Impairment and Mediterranean Lifestyle.

Recently, an association between dysbiosis of the gut microbiota (GMB) and the development of several diseases, such as Alzheimer's disease (AD), has been proposed. Dysbiosis involves changes in microbial diversity influenced by environmental factors, like diet or lifestyle. In this study, we investigated the role of GMB parameters in Spanish AD patients, assessing the impact of adherence to the Mediterranean lifestyle (ML), as well as to characterize these parameters in relation to neuropsychological, neuropsychiatric, emotional, and functionality parameters. A case-control study was conducted to investigate the association between the composition of the GMB and cognitive, emotional, neuropsychiatric, and functionality status in Spanish AD patients, along with a shotgun metagenomics approach. Richness and alpha-diversity were significantly lower in the AD group compared to the controls. PERMANOVA and ANOSIM tests of Bray-Curtis dissimilarity, Aitchison distance, and Jaccard similarity did not showed significant differences in beta-diversity between the two groups. Moreover, associations between various phyla of the AD group and orientation performance, food consumption, and activities of daily living were identified. Dysbiosis observed in Spanish AD patients is characterized by reductions in richness and alpha-diversity, alongside alterations in GMB composition, which may be linked to adherence to the ML and cognitive and functionality symptoms.

Are Changes Occurring in Bacterial Taxa Community and Diversity with the Utilization of Different Substrates within SIR Measurements?

This research explores how the availability of substrates affects the regulation of soil microbial communities and the taxonomical composition of bacteria. The goal is to understand the impact of organic matter and substrate availability and quality on the diversity of soil bacteria. The study observed gradual changes in bacterial diversity in response to the addition of different substrate-induced respiration (SIR) substrates. Understanding the structure, dynamics, and functions of soil microbial communities is essential for assessing soil quality in sustainable agriculture. The preference for carbon sources among bacterial phyla is largely influenced by their life history and trophic strategies. Bacterial phyla like Proteobacteria, Bacteroidetes, and Actinobacteria, which thrive in nutrient-rich environments, preferentially utilize glucose. On the other hand, oligotrophic bacterial phyla such as Acidobacteria or Chloroflexi, which are found in lower numbers, have a lower ability to utilize labile C. The main difference between the two lies in their substrate utilization strategies. Understanding these distinct strategies is crucial for uncovering the bacterial functional traits involved in soil organic carbon turnover. Additionally, adding organic matter can promote the growth of copiotrophic bacteria, thus enhancing soil fertility.

Machine Learning Assessment of Gestational Age in Accelerated Maturation, Delayed Maturation, Villous Edema, Chorangiosis, and Intrauterine Fetal Demise.

Assessment of placental villous maturation is among the most common tasks in perinatal pathology. However, the significance of abnormalities in morphology is unclear and interobserver variability is significant. To develop a machine learning model of placental maturation across the second and third trimesters and quantify the impact of different pathologist-diagnosed abnormalities of villous morphology. Digitize placental villous slides from more than 2500 placentas at 12.0 to 42.6 weeks. Build whole slide learning models to estimate obstetrician-determined gestational age for cases with appropriate maturation and normal morphology. Define the model output as "placental age" and compare it to the chronologic gestational age. Our model showed an r2 of 0.864 and mean absolute error of 1.62 weeks for placentas with appropriate maturation in the test set. Pathologist diagnosis of accelerated maturation was associated with a 2.56-week increase in placental age (±2.91 weeks, P < .001), while delayed maturation was associated with a 0.92-week decrease in placental age (±1.82 weeks, P < .001). Intrauterine fetal demise causes diverse changes to placental age, driven by the nature of the demise. We tested the impact of training a model, using all live births. The resulting r2 was 0.874 and mean absolute error was 1.73 weeks. Furthermore, by including cases with abnormal maturation in the training data, the effect size of accelerated maturation was blunted to only 0.56 ± 2.35 weeks (P < .001). We show that various abnormalities of villous maturation and morphology correlate with abnormalities in placental age. This "no pathologist" model could be useful in situations where pathologists are unavailable or the need for consistency outweighs the utility of expertise.

New Extracted Features to Recognize Faces Effected by Occlusions and Common Variations

Face recognition from non-identical face photos is a prominent area of research in pattern recognition and computer vision. Existing face recognition systems struggle with diverse changes like lighting conditions, expressions, and facial occlusions. This paper proposes a new Face Recognition (FR) approach that combines the Elastic Bunch Graph Matching (EBGM) approach with the greedy algorithm to automatically identify face landmarks. The proposed approach independently selects each optimal landmark of face image from different corresponding face images where the corresponding landmark of corresponding face image which achieves the best similarity is used rather than using one or at most two corresponding face images and computing the average between both. The locations of corresponding landmarks can be displaced to achieve maximum similarity with optimal landmarks. This proposed approach demonstrates improved recognition performance compared to contemporary face recognition methods. It effectively handles changing ratios of face parts and can recognize faces even with increasing occlusion sizes.

Temporal dynamics of alpha and beta diversity of lake algae: Opposing patterns and influencing factors over the past 200 years

Abstract Better understanding of the responses of algal biodiversity to multiple pressures, such as climate warming and eutrophication, is a key issue in aquatic ecology. Alpha and beta diversity may have various patterns over temporal scales, especially in the Anthropocene, when external pressures became more multifaceted. However, the limited availability of historical data hampers the exploration of algal biodiversity through time. Recently, sediment DNA has emerged as a potential tool for elucidating temporal patterns in algal communities. Here, we used sediment DNA to reconstruct temporal turnover and diversity of algal communities in four remote lakes in northern China over the past 200 years. Furthermore, to distinguish the contributions of possible influencing environmental factors, we conducted structural equation modelling. Our results revealed that algal communities have experienced rapid shifts since the Anthropocene, characterized by increased alpha diversity and decreased temporal beta diversity. Warmer climate and eutrophication were associated with changes in alpha diversity, while temporal environmental variation was associated with temporal beta diversity. This study revealed opposing patterns in alpha and beta diversity for algal communities, possibly caused by warming, eutrophication and lower temporal environmental variation, respectively. While climatic factors played a major role in remote lakes with a natural environment, lakes that are more human impacted may be more structured by nutrient‐related factors. Under climate warming and intensified human activities, remote lakes may encounter complex pressures in the near future. Our findings offer valuable insights into patterns in aquatic biodiversity and possible factors underlying multiple pressures.

Physical Therapy for Knee Pain Relief Induces Changes in Gut Microbiome Composition: A Secondary Analysis of Data From a Randomized Controlled Trial.

Aerobic exercise alters gut microbiome composition, yet the impact of gentle physiotherapy on gut microbiome and its relation to muscle strengthening and physical function remains unexplored. Physiotherapy exercises modulate gut microbiome composition and changes in gut microbes are linked to improvements in muscle strength or function. Secondary data analysis of samples from a randomized controlled trial. Level 2b. Data from a 6-week randomized controlled trial of physiotherapy for knee pain were analyzed. Gut microbiota profiling utilized 16S sequencing. We compared intervention and control (usual care) groups using microbial diversity metrics. Amplicon sequence variants (ASVs) that changed after the program were identified with ALDEX2, and correlations between these ASVs and measures of physical function, muscle strength, and interleukin-6 (IL-6) were explored. No diversity changes were observed between standard care (n = 43) and physiotherapy (n = 34). Physiotherapy led to significant increases in Alistipes, Bacteroides, Clostridium sensu stricto 1, and Faecalibacterium ASVs. Of these, Clostridium sensu stricto 1 and Faecalibacterium were associated with postintervention muscle strength. Increase in Faecalibacterium was correlated with a decrease in IL-6 in the physiotherapy group. Physiotherapy had modest effects on gut microbiome composition affecting 4 taxa. Increases in muscle strength were correlated with increases in 2 taxa including Faecalibacterium. Faecalibacterium was also linked to reduced inflammation. Improved walking speed was linked to an increase in Alistipes with no differences found for strength or squatting ability. Improved gut microbiome composition is linked to better overall health outcomes, including enhanced immune function, reduced inflammation, and improved metabolic health. This is particularly relevant for patients with osteoarthritis, who are known to have a high prevalence of cardiometabolic comorbidities. Integrating physiotherapy protocols that positively influence the gut microbiome can thus enhance overall patient outcomes.

Unsupervised Change Detection Methods Applied to Landslide Mapping: Case Study in São Sebastião, Brazil

ABSTRACTLandslides represent a growing global geological hazard, further intensified by climate‐induced changes. Remote sensing data, through its capacity for repetitive collection and change detection techniques, that compare and quantify the spatio‐temporal alterations over time, plays a critical role in landslide detection. Considering the February 2023 São Sebastião event and Sentinel‐2 imagery, we assessed diverse unsupervised change detection techniques, encompassing both traditional and recent machine learning‐based approaches. Notably, the Floating References (FR) and Homogeneous Blocks Single‐class Classification (HBSC) methods outperform classic approaches and deliver the most accurate results with F1‐Score and kappa coefficient exceeding 0.96 and 0.92, respectively. These outcomes demonstrate the efficacy of machine learning in automating landslide delineation and underscore the necessity of meticulous data and parameter selection in achieving high‐accuracy automatic landslide mapping. Lastly, this study fills a significant gap in the existing literature by evaluating unsupervised change detection methods for landslide mapping within the Brazilian context.

12468 Loss Of Enterococcus And Faecalibacterium Associate With Polycystic Ovary Syndrome And Hirsutism In A Sample Of Hispanic Patients

Abstract Disclosure: L.A. Gonzalez-Rodriguez: Research Investigator; Self; Eli Lilly &amp; Company. C.M. Casas Loyola: None. C.I. Martinez-Hernandez: None. L. El Musa Penna: None. J. Romaguera: None. F. Godoy-Vitorino: None. Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age. It is characterized by symptoms such as irregular menstrual periods, excess androgen levels and polycystic ovaries. Women with PCOS often display insulin resistance independent of fat and have been associated with an increased risk of diabetes mellitus, cardiovascular disease, and mood disorders. The gut microbiota, the community of microbes living in the human gastrointestinal tract, plays a crucial role in human health and has been implicated in various diseases, including metabolic and inflammatory conditions. We aimed to characterize the gut microbiota in a sample of Hispanic women living in Puerto Rico (n=50). Of these 38 had confirmed PCOS as per Rotterdam criteria and 12 were controls. A stool sample was collected for genomic DNA extractions followed by amplification and sequencing of 16S rRNA genes (V4 region) with Illumina MiSEQ. Data analyses were performed with standard pipelines with variables sample group (PCOS vs Controls), insulin resistance assessed using HOMA-IR and hirsutism status according to modified-Ferriman Gallwey (mFG) score and controlled for age and other clinical variables. Despite there were no changes in alpha or beta diversity among the microbiota of these groups, composition was significantly different. Women with PCOS had significantly lower levels of Enterococcus species as well as Hungatella, taxa that are part of a physiologically normal gut flora. Enterococcus species contribute to the balance of the microbial community and play roles in the metabolism and immune function and are very resilient. Hungatella species are a known source of catabolic enzymes that degrade glycosaminoglycans which are important in tissue repair. These dominant taxa in controls was substituted by other taxa in PCOS. Women with prominent hirsutism had significantly lower levels of Faecalibacterium while those with insulin resistance had increased levels of Clostridium. We found that higher levels Clostridium, and lower levels of protective anti-inflammatory taxa such as Faecalibacterium or Enterococci, which are important for gut health and metabolic regulation, are linked to this metabolic disturbance. Even though this is a preliminary report, it opens potential therapeutic strategies, such as the use probiotics, and dietary modifications to modulate the gut microbiome and improve PCOS outcomes. Presentation: 6/1/2024

12468 Loss Of Enterococcus And Faecalibacterium Associate With Polycystic Ovary Syndrome And Hirsutism In A Sample Of Hispanic Patients

Abstract Disclosure: L.A. Gonzalez-Rodriguez: Research Investigator; Self; Eli Lilly &amp; Company. C.M. Casas Loyola: None. C.I. Martinez-Hernandez: None. L. El Musa Penna: None. J. Romaguera: None. F. Godoy-Vitorino: None. Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age. It is characterized by symptoms such as irregular menstrual periods, excess androgen levels and polycystic ovaries. Women with PCOS often display insulin resistance independent of fat and have been associated with an increased risk of diabetes mellitus, cardiovascular disease, and mood disorders. The gut microbiota, the community of microbes living in the human gastrointestinal tract, plays a crucial role in human health and has been implicated in various diseases, including metabolic and inflammatory conditions. We aimed to characterize the gut microbiota in a sample of Hispanic women living in Puerto Rico (n=50). Of these 38 had confirmed PCOS as per Rotterdam criteria and 12 were controls. A stool sample was collected for genomic DNA extractions followed by amplification and sequencing of 16S rRNA genes (V4 region) with Illumina MiSEQ. Data analyses were performed with standard pipelines with variables sample group (PCOS vs Controls), insulin resistance assessed using HOMA-IR and hirsutism status according to modified-Ferriman Gallwey (mFG) score and controlled for age and other clinical variables. Despite there were no changes in alpha or beta diversity among the microbiota of these groups, composition was significantly different. Women with PCOS had significantly lower levels of Enterococcus species as well as Hungatella, taxa that are part of a physiologically normal gut flora. Enterococcus species contribute to the balance of the microbial community and play roles in the metabolism and immune function and are very resilient. Hungatella species are a known source of catabolic enzymes that degrade glycosaminoglycans which are important in tissue repair. These dominant taxa in controls was substituted by other taxa in PCOS. Women with prominent hirsutism had significantly lower levels of Faecalibacterium while those with insulin resistance had increased levels of Clostridium. We found that higher levels Clostridium, and lower levels of protective anti-inflammatory taxa such as Faecalibacterium or Enterococci, which are important for gut health and metabolic regulation, are linked to this metabolic disturbance. Even though this is a preliminary report, it opens potential therapeutic strategies, such as the use probiotics, and dietary modifications to modulate the gut microbiome and improve PCOS outcomes. Presentation: 6/1/2024

Southern African precipitation changes in a warmer world: insights from the PlioMIP2 mid-Pliocene Warm Period (∼3.3–3.0 Ma) ensemble

Near-modern geography and atmospheric carbon dioxide concentrations (∼400 ppmv) coupled with temperatures ∼3°C warmer than the pre-Industrial era are suggested to make the mid-Pliocene warm period (mPWP; 3.264–3.025 Ma) an important near-future climate change analogue. To date, however, few studies explore mPWP hydroclimatic characteristics for the full southern Africa area using proxy records and/or Pliocene Model Intercomparison Project (PlioMIP) climate projections. Hence, we analyse precipitation outputs from 17 PlioMIP phase 2 models to explore southern African mPWP precipitation changes compared to pre-Industrial outputs. Despite diverse inter-model changes, robust signals exist. Most models project annual precipitation declines, up to 0.5 mm/day in the ensemble median. Drying of a similar magnitude for the summer (October-March) and winter (April-September) half-year periods contribute to this change, with models more consistently projecting winter drying. Consequently, the summer and winter precipitation zones (SRZ and WRZ) are projected to shift poleward by ∼1°. For WRZ regions, relatively stable summer precipitation and reduced winter precipitation is projected to result in reduced seasonality. Over SRZ regions, early (late) summer precipitation declines (increases) projected for October–December (January–March) re-organise the summer wet-season to be more concentrated in late summer. Qualitatively good consistency with future projections highlights the mPWPs relevance considering southern Africa’s future climate changes, however, limited model-proxy agreement suggests a need to further (re)assess Pliocene (mPWP) proxy records and/or the PlioMIP2 model boundary conditions towards better capturing mechanisms driving mPWP climatic changes.

Host diversity of Aedes albopictus in relation to invasion history: a meta-analysis of blood-feeding studies

BackgroundThe invasive mosquito Aedes albopictus is a major concern for human and animal health given its high potential to spread over large geographical distances, adapt to various habitats and food sources, and act as a vector for pathogens. It is crucial to understand how this species establishes ecological relationships at different locations, as it determines its role in transmission of diseases.MethodsBased on published blood meal surveys, a meta-analysis was performed to investigate how host diversity changes along the process of invasion at a large scale. For 48 independent localities, the Shannon diversity index was calculated and was then assessed against several moderator variables describing invasion status, habitat type, methodology, survey year and the year of introduction for invasive populations.ResultsDiet diversity was higher in the invasive than in the native populations when the strong habitat effects were held constant. Furthermore, the year of introduction also had a significant role, as invasive populations that had been established earlier had wider diet diversity than more recent populations.ConclusionsInvasive Ae. albopictus has considerable ecological flexibility. The species’ ability to adapt to various food sources goes hand in hand with its successful worldwide dispersion, which has strong implications for its role in pathogen transmission.Graphical

Seasonality Structures Avian Functional Diversity and Niche Packing Across North America.

Assemblages in seasonal ecosystems undergo striking changes in species composition and diversity across the annual cycle. Despite a long-standing recognition that seasonality structures biogeographic gradients in taxonomic diversity (e.g., species richness), our understanding of how seasonality structures other aspects of biodiversity (e.g., functional diversity) has lagged. Integrating seasonal species distributions with comprehensive data on key morphological traits for bird assemblages across North America, we find that seasonal turnover in functional diversity increases with the magnitude and predictability of seasonality. Furthermore, seasonal increases in bird species richness led to a denser packing of functional trait space, but functional expansion was important, especially in regions with higher seasonality. Our results suggest that the magnitude and predictability of seasonality and total productivity can explain the geography of changes in functional diversity with broader implications for understanding species redistribution, community assembly and ecosystem functioning.

Community Trait Variation Drives Selection on Species Diversity Through Feedback With Predator Density.

Identifying the processes underlying community assembly and dynamics remains a central goal in ecology. Although much research has been devoted to analyzing how environments affect species diversity, fewer studies have resolved the link between the fundamental process of ecological selection and species diversity. It has been suggested that identifying ecological selection by estimating changes in community-weighted variance (CWV) and mean (CWM) of functional traits may help to identify more general rules of community assembly. Here, we asked whether and how selection by predation and competition affect species diversity, and how this is determined by the initial CWV and CWM for traits governing species interactions, as in our case: Competitiveness and defense against a predator. We tracked experimental five-species phytoplankton communities in the presence and absence of a rotifer predator over time. We manipulated the initial community composition so that communities shared at least three of the five species but differed in CWV and CWM for defense against predation. We found that species diversity was highest with higher initial trait distributions and that temporal changes in diversity correlated with trait selection. The initial distributions determined the form of selection over time, with directional selection for defense and competitiveness, followed by reduced selection and an increase in niche availability when the initial trait distribution was low or high. For intermediate initial trait distributions, we observed directional selection in only one trait, followed by stabilizing selection. Differences and changes in selection for defense, competitiveness, and species diversity correlated with the changes in predator density over time. This suggests that the initial trait distribution determined species diversity through a feedback loop with changes in selection on traits and predator density. Overall, our study shows that identifying ecological selection on functional traits can provide a mechanistic understanding of community assembly.

Polyconnectomic scoring of functional connectivity patterns across eight neuropsychiatric and three neurodegenerative disorders

BackgroundNeuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches searching for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores. MethodsThe polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity (FC) mirrors the whole-brain circuitry characteristics of a trait. We computed PCS for eight neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and three neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson’s disease) across 22 datasets with resting-state functional MRI of 10,667 individuals (5,325 patients, 5,342 controls). We further examined PCS in 26,673 individuals from the population-based UK Biobank cohort. ResultsPCS was consistently higher in out-of-sample patients across six of the eight neuropsychiatric and across all three investigated neurodegenerative disorders ([min, max]: AUC = [0.55, 0.73], pFDR = [1.8 x 10-16, 4.5 x 10-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (pFDR < 9.7 x 10-5), lower cognitive performance (pFDR < 5.3 x 10-5), and lower general wellbeing (pFDR < 9.7 x 10-4). ConclusionsOur findings reveal generalizable whole-brain connectivity alterations in brain disorders. PCS effectively aggregates disorder-related signatures across the entire brain into an interpretable, subject-specific metric. A toolbox is provided for PCS computation.