Ecological Dynamics Research Articles

Investigating the biological diversity and ecological dynamics of oceanic fishery resources in the Andaman Sea, Indian Ocean

This research paper investigates the oceanic fishery resources of the Andaman archipelago. The primary objective of this study is to gain a comprehensive understanding of the fishery and its dynamics including the environmental linkage surrounding these oceanic resources and to develop an effective strategy for sustainable exploration. Data were collected during an exploratory tuna long-line survey conducted between July 2022 and February 2023. The study documented a total of 13 species of fishes belonging to 11 genera, with tuna being the most abundant. Additionally, the study observed a significant increase in the population of pelagic stingrays, which nearly matched the number of hooked sharks (32). However, the hooking rates of sharks and bill fishes were observed to be gradually declining, resulting in a lower contribution to the overall species composition. One notable finding of the study was that site 11oN; 93oE (S4) exhibited the highest species diversity and potential. Furthermore, the aggregate hooking rates of fishes were particularly high between latitudes 11oN and 12oN. The study also analysed the seasonal distribution of each fish species and explored the correlation between environmental factors such as depth and temperature with species abundance and distribution. Statistical analysis indicates that there is no significant variation (p value = 0.20) between the environmental factors and the frequency of the species occurrence. Specifically, depth shows the highest correlation (r = 0.57) with the species distribution. In light of the diminishing hooking rate of oceanic fishery resources, the study puts forth several possible reasons and emphasizes the urgent need to implement conservation measures.

Eco-evolutionary dynamics of structured populations in periodically fluctuating environments: a G function approach.

Understanding the ecological and evolutionary dynamics of populations is critical for both basic and applied purposes in a variety of biological contexts. Although several modeling frameworks have been developed to simulate eco-evolutionary dynamics, many fewer address how to model structured populations. In a prior paper, we put forth the first modeling approach to simulate eco-evolutionary dynamics in structured populations under the G function modeling framework. However, this approach does not allow for accurate simulation under fluctuating environmental conditions. To address this limitation, we draw on the study of periodic differential equations to propose a modified approach that uses a different definition of fitness more suitable for fluctuating environments. We illustrate this method with a simple toy model of life history trade-offs. The generality of this approach allows it to be used in a variety of biological contexts.

Disentangling the complexity of plant-bird relationships: From monolayer to multilayer network perspectives

Most plant-bird interaction research employing complex ecological networks focuses on pollination and seed dispersal interactions. However, birds and plants are immersed in a great variety and complexity of direct and indirect relationships. Therefore, the use of multilayer networks (i.e., species interaction networks involving different types of interactions) could provide new insights into the ecological and coevolutionary dynamics of plant-bird relationships. Here, we used a multilayer network approach to determine how a bird-plant interaction network involving different types of interactions (i.e., foraging for invertebrates on plants, frugivory, nectarivory, and perching) is organized in a peri-urban Mexican cloud forest. Moreover, we added information about the interactive roles of the winter migratory and resident birds in the multilayer network. In general, we found that the bird-plant multilayer network exhibits modular but a non-nested structure. We also observed that interactions involving perching and foraging for invertebrates on plants are more frequent than frugivory and nectarivory. Moreover, just a small proportion of birds and plant species were important to the network organization and for connecting different interaction types. In this case, we observed that only two bird species, Cardellina pusilla (Parulidae) and Dumetella carolinesis (Mimidae), and the plant species Telanthophora grandifolia (Asteraceae) and Platanus mexicanus (Platanaceae) presented higher centrality values (i.e., an interactive role). Finally, we found that betweenness values (i.e., the number of times a species acts as a bridge along the shortest path between two species) and network structure's contributions are similar for both migratory and resident bird species. Our results highlight the importance of key interacting species that connect other interacting species for the preservation of community cohesion and to the persistence of species-rich assemblages.

Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods

Coastal marine areas are frequently affected by human activities and face ecological and environmental threats, such as algal blooms and climate change. The community structure of phytoplankton—primary producers in marine ecosystems—is highly sensitive to environmental factors, such as temperature, salinity, and nutrients. However, traditional methods for exploring the relationship between phytoplankton communities and environmental factors in eutrophic marine areas are limited by various factors. Therefore, this study employed interpretable machine learning models, integrating high-dimensional data analysis and complex system modeling, to quantitatively and thoroughly analyze the dynamic relationship between phytoplankton communities and environmental variables in high-frequency samples collected over 53 weeks from eutrophic marine areas. The cell abundance of phytoplankton exhibited a distinct “two-peak pattern” variation. Interpretable machine learning model analysis revealed the dynamic contributions of different environmental factors during changes in the phytoplankton community structure. The results showed that temperature was a key environmental factor that affected phytoplankton growth during peak periods. In addition, the contribution of salinity increased during the second peak in phytoplankton abundance, highlighting its central role in the ecological dynamics of this phase. During green tide outbreaks, particularly in Area 01, the contributions of factors such as temperature and salinity increased, whereas those of phosphates and silicates decreased, indicating that green tide outbreaks substantially altered the nutritional dynamics of the ecosystem. Furthermore, different phytoplankton species, such as Skeletonema costatum, Thalassiosira spp., and Nitzschia spp., exhibit varying responses to environmental factors. Hence, the predictions made using random forest and generalized additive models for phytoplankton cell abundance in two marine areas revealed complex nonlinear relationships between environmental factors, such as temperature, salinity, and phytoplankton abundance.

Phytoremediation of crude oil-contaminated soil using Vigna Unguiculata and associated rhizosphere bacteria

Persistent crude oil contamination poses a significant environmental challenge. In this study, the efficacy of Vigna unguiculata (L.) and associated rhizospheric microorganisms in remediating crude oil-contaminated soil within a microcosm setting was investigated. A randomized block design was employed, and soil samples were subjected to varying degrees of contamination: 0% (UR), 2.5% (CR2), 5.0% (CR5), 7.5% (CR7), and 10.0% (CR10) w/w crude oil. The investigation aimed to assess the potential of Vigna unguiculata (L.) in mitigating crude oil contamination across these defined contamination gradients. The plant growth and crude oil removal were monitored concurrently post-emergence. Plant emergence and growth were significantly affected due to contamination, especially among plants in CR5 and CR10. The bacterial population was higher in the rhizosphere, and the treatments with lower hydrocarbon contamination. It was shown that plant density encouraged the growth of bacterial communities. Significant reduction in soil TPH was observed in CR2 (76.61%) and CR7 (65.88%). There was a strong correlation between plant growth and oil-utilizing bacterial population (r2 = 0.966) and plant growth and hydrocarbon reduction (r2 = 0.956), signifying the role of plant-bacterial synergy. Saturate fractions (C30 – C32) were significantly degraded to lower molecular weight compounds (C11 – C14). Except in CR5 and CR10, the remediation within the cowpea rhizosphere was effective even at regulatory standards. Understanding the rhizosphere ecological dynamics would further highlight the role the bacteria played; hence, it is recommended.

Noisy Circumnutations Facilitate Self-Organized Shade Avoidance in Sunflowers

Circumnutations are widespread in plants and typically associated with exploratory movements; however, a quantitative understanding of their role remains elusive. In this study we report, for the first time, the role of noisy circumnutations in facilitating an optimal growth pattern within a crowded group of mutually shading plants. We revisit the problem of self-organization observed for sunflowers, mediated by shade response interactions. Our analysis reveals that circumnutation movements conform to a bounded random walk characterized by a remarkably broad distribution of velocities, covering 3 orders of magnitude. In motile animal systems such wide distributions of movement velocities are frequently identified with enhancement of behavioral processes, suggesting that circumnutations may serve as a source of functional noise. To test our hypothesis, we developed a Langevin-type parsimonious model of interacting growing disks, informed by experiments, successfully capturing the characteristic dynamics of individual and multiple interacting plants. Employing our simulation framework we examine the role of circumnutations in the system, and find that the observed breadth of the velocity distribution represents a sharp transition in the force-noise ratio, conferring advantageous effects by facilitating exploration of potential configurations, leading to an optimized arrangement with minimal shading. These findings represent the first report of functional noise in plant movements and establish a theoretical foundation for investigating how plants navigate their environment by employing computational processes such as task-oriented processes, optimization, and active sensing. Since plants move by growing, space and time are coupled, and dynamics of self-organization lead to emergent 3D patterns. As such, this system provides conceptual insight for other interacting growth-driven systems such as fungal hyphae, neurons and self-growing robots, as well as active matter systems where agents interact with past trajectories of their counterparts, such as stigmergy in social insects. This foundational insight has implications in statistical physics, ecological dynamics, agriculture, and even swarm robotics. Published by the American Physical Society 2024

Integrating source tracking tools for marine shellfish tracing: Metataxonomic and isotopic analyses

Shellfish farming is a significant activity in the Northern Adriatic Sea, particularly in Italy, where it plays a crucial role in the European industry of live bivalve mollusks. This study aimed to exploit different analyses, including metataxonomy and isotopic profiling, to address these issues. Isotopic analysis showed differences between habitats, with lower δ15N in sea samples, likely indicating lesser anthropogenic impact compared to lagoon environments. Additionally, seasonal variations in δ15N, δ13C and C/N highlighted differences in primary productivity and organic matter sources across seasons. Metataxonomic analysis revealed significant variability in microbial taxa across harvesting habitats and seasons. While no marked differences were observed in alpha and beta diversity based on habitat, distinct seasonal clustering indicated the influence of environmental factors on microbial community structure. Gammaproteobacteria were prevalent across habitats and seasons, with notable fluctuations in other taxa, such as Alphaproteobacteria, Epsilonproteobacteria, Flavobacteria, and Bacteroidia, particularly in lagoon habitats during winter. Overall, this study highlights the potential of microbial and isotopic characterization for tracing the origin of shellfish products. Metataxonomic analysis identified microbial signatures indicative of habitat and season, with implications for ecological dynamics and consumer safety. Isotopic analysis provided information on habitat characteristics and harvesting seasons, enhancing product traceability.

Effect of biochar amendment on bacterial community and their role in nutrient acquisition in spinach (Spinacia oleracea L.) grown under elevated CO2

Global climate change is anticipated to shift the soil bacterial community structure and plant nutrient utilization. The use of biochar amendment can positively influence soil bacterial community structure, soil properties, and nutrient use efficiency of crops. However, little is known about the underlying mechanism and response of bacterial community structure to biochar amendment, and its role in nutrient enhancement in soil and plants under elevated CO2. Herein, the effect of biochar amendment (0, 0.5, 1.5%) on soil bacterial community structure, spinach growth, physiology, and soil and plant nutrient status were investigated under two CO2 concentrations (400 and 600 μmol mol−1). Findings showed that biochar application 1.5% (B.2.E) significantly increased the abundance of the bacterial community responsible for growth and nutrient uptake i.e. Firmicutes (42.25%) Bacteroidetes (10.46%), and Gemmatimonadetes (125.75%) as compared to respective control (CK.E) but interestingly abundance of proteobacteria decreased (9.18%) under elevated CO2. Furthermore, the soil available N, P, and K showed a significant increase in higher biochar-amended treatments under elevated CO2. Spinach plants exhibited a notable enhancement in growth and photosynthetic pigments when exposed to elevated CO2 levels and biochar, as compared to ambient CO2 conditions. However, there was variability observed in the leaf gas exchange attributes. Elevated CO2 reduced spinach roots and leaves nutrient concentration. In contrast, the biochar amendment (B2.E) enhanced root and shoot Zinc (494.99%–155.33%), magnesium (261.15%–183.37%), manganese (80.04%–152.86%), potassium (576.24%–355.17%), calcium (261.88%–165.65%), copper (325.42%–282.53%) and iron (717.63%–177.90%) concentration by influencing plant physiology and bacterial community. These findings provide insights into the interaction between plant and bacterial community under future agroecosystems in response to the addition of biochar contributing to a deeper understanding of ecological dynamics.

Interconnectivity can be as important as habitat type in explaining carbon stocks in the coastal lagoons of arid regions

Coastal blue carbon ecosystems, typically comprising interconnected habitat mosaics, are globally important pathways of carbon sequestration and play a significant role in climate change regulation and mitigation. Current coastal management strategies often rely on simplified regional carbon stock estimates, that overlook the geographical variability and intricate ecological dynamics within these ecosystems. This study adopts a seascape ecology approach to evaluate the role of multiple seascape characteristics on carbon storage in two arid region coastal lagoons. We show that seascape location is the most influential driver of carbon stocks. Additionally, carbon isotopic variability, a proxy for connectivity, can be as influential as habitat type, particularly in the UAQ lagoon. This challenges the conventional reliance on data from individual habitat types (e.g., seagrass, mangrove, or tidal marsh) and highlights the context-dependency of carbon stocks. Moreover, the specific characteristics driving carbon stocks vary between seascapes: in Khor Faridah, connectivity to seagrass and mangrove habitats is crucial, while in the UAQ lagoon, sheltered and elevated areas are more influential. Our findings suggest that the interconnectivity between different habitat types, such as mangroves and saltmarshes, significantly enhances carbon storage. This is especially pronounced in large, sheltered mangrove habitat types within upper intertidal zones. Notably, small patches of mangroves, up to 10 ha, are associated with an approximate 10 % increase in carbon stocks. These results underscore the need for a more holistic, context-specific approach to designing nature-based solutions for coastal management and ecosystem restoration. By considering the specific characteristics and connectivity of seascape mosaics, we can more effectively enhance carbon stock potential in coastal ecosystems. This study contributes to a deeper spatially explicit understanding of the complex factors influencing carbon stocks in blue carbon ecosystems, highlighting the importance of tailored management strategies that reflect the unique ecological patterns of each seascape.

Predictive Functional Profiling Reveals Putative Metabolic Capacities of Bacterial Communities in Drinking Water Resources and Distribution Supply in Mega Manila, Philippines

Assessing bacterial communities across water resources is crucial for understanding ecological dynamics and improving water quality management. This study examines the functional profiles of bacterial communities in drinking water resources in Mega Manila, Philippines, including Laguna Lake tributaries, pre-treatment plant sites, groundwater sources, and post-treatment plant sites. Using eDNA sequencing, flux balance analysis, and taxonomy-to-phenotype mapping, we identified metabolic pathways involved in nutrient metabolism, pollutant degradation, antibio- tic synthesis, and nutrient cycling. Despite site variations, there are shared metabolic pathways, suggesting the influence of common ecological factors. Site-specific differences in pathways like ascorbate, aldarate, and phenylalanine metabolism indicate localized environmental adaptations. Antibiotic synthesis pathways, such as streptomycin and polyketide sugar unit biosynthesis, were detected across sites. Bacterial communities in raw and pre-treatment water showed potential for pollutant degradation such as for endocrine-disrupting chemicals. High levels of ammonia-oxidizing and sulfate-reducing bacteria in pre- and post-treatment water suggest active nitrogen removal and pH neutralization, indicating a need to reassess existing water treatment approaches. This study underscores the adaptability of bacterial communities to environmental factors, as well as the importance of considering their functional profiles in assessing drinking water quality resources in urban areas.

Synergistic approach for land use and land cover dynamics prediction in Uttarakhand using cellular automata and Artificial neural network

Alterations in Land use and Land cover (LULC) stand out as a key catalyst for shifts in global climate patterns, environmental conditions, and ecological dynamics. In order to further enhance our comprehension of the effects of variability and climate shifts on the environment, Remote sensing and GIS analytical approaches have been thoroughly explored and are reflected in an imperative vision. Thus, the objective of this study is to model Uttarakhand’s LULC pattern for 2032 and analyse changes in Uttarakhand's LULC trend between 1992 and 2022. LULC change mapping was conducted utilizing a semi-automated hybrid classification approach for high level of accuracy which integrates both Maximum likelihood and Object based image analysis classification techniques on Landsat datasets. The machine learning techniques of Cellular automata and Artificial neural networks (CA-ANN) within MOLUSCE plugin of QGIS have been applied to model future LULC patterns. The accuracy assessment results showed that the overall accuracy of LULC for the years 1992, 2002, 2012, and 2022 was 96.94 %, 97.77 %, 98.61 % and 98.87 % respectively, and the overall kappa statistics coefficient was 0.92, 0.95, 0.94 and 0.95 respectively. The simulated and projected LULC map for 2022 implies a substantially high level of accuracy, with an overall Kappa coefficient value of 0.77 % and 85.39 % of overall correctness. Then, LULC changes for the year 2032 are predicted using CA-ANN. The observed alterations between 1992 and 2032 are significant, characterized by an augmentation in built-up areas, open land, and water bodies, alongside a decline in snow-covered regions, vegetation cover. Whereas, a slight increase is seen in Forested areas. Planners and policy makers aiming to accomplish a more sustainable future and efficient management of the environment will find the changes in LULC over a prolonged period of time to be a useful asset for optimal land use planning.

Insights into the physiology, biochemistry and ecological significance of the red seaweed Tricleocarpa fragilis in the Andaman Sea

The present study focused on the physiological and biochemical aspects of Tricleocarpa fragilis, red seaweed belonging to the phylum Rhodophyta, along the South Andaman coast, with particular attention given to its symbiotic relationships with associated flora and fauna. The physicochemical parameters of the seawater at the sampling station, such as its temperature, pH, and salinity, were meticulously analyzed to determine the optimal harvesting period for T. fragilis. Seaweeds attach to rocks, dead corals, and shells in shallow areas exposed to moderate wave action because of its habitat preferences. Temporal variations in biomass production were estimated, revealing the highest peak in March, which was correlated with optimal seawater conditions, including a temperature of 34 ± 1.1 °C, a pH of 8 ± 0.1, and a salinity of 32 ± 0.8 psu. GC‒MS analysis revealed n-hexadecanoic acid as the dominant compound among the 36 peaks, with major bioactive compounds identified as fatty acids, diterpenes, phenolic compounds, and hydrocarbons. This research not only enhances our understanding of ecological dynamics but also provides valuable insights into the intricate biochemical processes of T. fragilis. The established antimicrobial potential and characterization of bioactive compounds from T. fragilis lay a foundation for possible applications in the pharmaceutical industry and other industries.

Stability of equilibrium states for a stochastic difference equation of exponential form

It is well know that many process and problems in different fields of sciences and engineering can be modelled by linear and nonlinear difference equations. Particularly, in case of systems biology, ecology, biochemistry, genetics and physiology dynamics, many population models are governed by exponential difference equations, and lot of papers were published in this matter. The goal of this work is to study a nonlinear second order difference equation of exponential form: Xn+1 = bXn + cXne−σXn−1, n ≥ 0 where the parameters b, c have arbitrary values, σ > 0 and the initial values, X0, X−1 are arbitrary positive numbers. Our equation has an equilibrium points and is exposed to additive stochastic perturbations that are assumed a sequence of independent random variables with zero mean, unit variance and these perturbations are proportional to the deviation of the system state Xn from equilibrium points, and the result is stochastic difference equation. We cannot find the solutions of nonlinear stochastic difference equations of exponential form in all cases. So, one can study the behavior of solutions by asymptotic stability of equilibrium points. Additionally, with the general method of Lyapunov functional constructions for stochastic difference equations with discrete time, we provide the necessary and sufficient conditions for the asymptotic mean square stability of the two equilibrium points (zero and positive) within the linear approximation of the stochastic difference equation. These conditions also serve as sufficient conditions for the stability in probability of the equilibrium points of the initial nonlinear equation. Finally, to demonstrate the validity of the obtained results, some numerical examples and simulations of equations solutions are made and numerous graphical illustrations of stability trajectories of solutions are plotted.

Landcover-categorized fires respond distinctly to precipitation anomalies in the South-Central United States

Satellite detection of active fires has contributed to advance our understanding of fire ecology, fire and climate dynamics, fire emissions, and how to better manage the use of fires as a tool. In this study, we use active fire data of 12 years (2012–2023) combined with landcover information in the South-Central United States to derive a monthly, open-access dataset of categorized fires. This is done by calculating a fire predominance index used to rank fire-prone landcovers, which are then grouped into four main landscapes: grassland, forest, wildland, and crop fires. County-level aggregated analyses reveal spatial distributions, climatologies, and peak fire months that are particular to each fire type. Using the Standardized Precipitation Index (SPI), it was found that during the climatological fire peak-month, the SPI and fires exhibit an inverse relationship in forests and crops, whereas grassland and wildland fires show less consistent inverse or even direct relationship with the SPI. This varied behavior is discussed in the context of landscapes’ responses to anomalies in precipitation and fire management practices, such as prescribed fires and crop residue burning. In a case study of Osage County (OK), we find that large wildfires, known to be closely related to climate anomalies, occur where forest fires are located in the county and absent in areas of grassland fires. Weaker grassland fire response to precipitation anomalies can be attributed to the use of prescribed burning, which is normally planned under environmental conditions that facilitate control and thus avoided during droughts. Crop fires, on the other hand, are set to efficiently burn residue and are practiced more intensely in drier years than in wetter years, explaining the consistently strong inverse correlation between fires and precipitation anomalies. In our increasingly volatile climate, understanding how fires, vegetation, and precipitation interact has become imperative to prevent hazardous fire conflagrations and to better manage ecosystems.

An ecological population study of lampreys in the Lotka-Volterra tertiary trophic level based on sex differences

This study examines the adaptive changes in sex ratio on animal populations and its effects on ecosystem stability and interactions. The effects of sex ratio dynamics on the ecosystem were analyzed through mathematical modeling using lampreys as the study population. In this study, a two-stage tertiary trophic Lotka-Volterra mathematical model of ecological dynamics was developed, taking into account food preferences, ecological roles, and sex interactions of lampreys. The simulation results showed that a rapid adjustment in sex ratio led to a reduction in environmental loads, which triggered an early rebound increase in lampreys and predator populations. To assess the ability of lampreys populations to adjust sex ratios, this study used a combination of fuzzy integrated evaluation and hierarchical analysis methods. The results of the study revealed the importance of sex-adaptive traits for population development, including increased resource utilization efficiency and population fitness, as well as decreased reproductive success and reduced genetic diversity. Based on the RRT (resistance, resilience and temporal stability) method, this study constructed an ecosystem stability assessment model and investigated the effects of changes in the sex ratio of lampreys on ecosystem stability. The experimental results showed that ecosystem stability was highest when the sex ratio was 0.6 and lowest when the sex ratio was 0.2. Variation in sex ratio may affect the behavior and abundance of lampreys, thereby directly influencing their interactions with other species. Variability in sex ratio provides more resources for predators and parasites of lampreys, promotes their growth, and positively affects ecosystem balance. Simulation results showed that the model was highly stable under different interactions. In summary, this study reveals the important effects of sex ratio on ecosystem stability and interactions, and provides important insights into the understanding of adaptive evolutionary traits of species, ecosystem stability and ecological interactions.

Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations.

Large stochastic population abundance fluctuations are ubiquitous across the tree of life1-7, impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution, as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate that they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.

Influence of climate and banana growth stages on spatio‐temporal variation of banana mealybug Pseudococcus elisaeBorchsenius (Hemiptera: Coccomorpha: Pseudococcidae) population ecology

Abstract The banana mealybug Pseudococcus elisae Borchsenius (Hemiptera: Coccomorpha: Pseudococcidae) is a pest of economic importance in Cameroon that requires effective control practices, especially after the routinely used chlorpyrifos insecticide was banned in 2019. For effective mealybug control, it is imperative to understand their ecology in relation to banana growth stages and climate‐induced seasonal variations. Therefore, the influence of climatic variables and banana growth stages on a spatio‐temporal distribution of mealybugs in Esuke and Benoe banana plantations of the Cameroon Development Corporation in Tiko was assessed. A 60‐ha area was mapped in each plantation and divided into 12 plots of 5 ha each, which were further sub‐divided into four quadrants of 1.25 ha. A total of 10 banana suckers, 10 pre‐flowering, 10 flowering and 10 bunchy plants were sampled per quadrant. Monthly mealybug population dynamics were assessed across 2 years in 2021 and 2022 on lower or upper pseudostem, leaves and banana bunches. Significant yearly and monthly mealybug population variation on banana plants were observed, with more mealybugs in 2022 than 2021, and two monthly mealybug peaks in February and November (p < 0.001). Mealybug population was higher on banana bunches and lower or upper pseudostem than on leaves (p < 0.001). Mealybugs preferred bunchy plants than suckers or pre‐flowering and flowering plants, and exhibited clumped distribution with Taylor aggregation index (b) greater than one (p < 0.001). A simple linear regression revealed strong positive effects of high temperature on mealybug population ecology, while relative humidity and rainfall had inverse effects on the population of mealybug. These highlight the dynamics of banana mealybug population ecology under variable climatic conditions and banana growth stages, which provides valuable baseline information to facilitate developing effective control strategies for mealybugs in banana plantations.

First record of Ozolaimus cirratus (Oxyuroidea: Pharyngodonidae) infecting the casque-headed tree frog Corythomantis greeningi (Anura: Hylidae) from Northeast Brazil

ABSTRACT The genus Ozolaimus is characterised by presenting a dorsoventrally elongated mouth with two lateral lips, a very long oesophagus consisting of anterior portion strong and short, with a fusiform fold, and a thin posterior portion ending in a distinct bulb, an anteriorly dilated intestine, and absent lateral wings. Between February 2014 and September 2016, 11 specimens of the anuran Corythomantis greeningi were collected manually at the Ecological Station of Aiuaba, Ceará State, Brazil. After analysis, nine specimens of Ozolaimus cirratus infecting the large intestine of the referred specimen were recorded. Knowledge is still scarce about the ecological dynamics of pharyngodonid parasites and their parasitehost relationships; thus, this work is the first to record members of the genus Ozolaimus infecting the casqueheaded tree frog Corythomantis greeningi from the Caatinga biome. Previously, the only registered hosts of Ozalaimus parasites were iguanid lizards.

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.

Microhabitat and seasonal influence on bess beetle (Coleoptera: Passalidae) assemblage in Altitudinal Atlantic Forest

AbstractUnderstanding the spatiotemporal distribution of diversity has been a significant challenge in the field of conservation biology. Presently, there exists a limited understanding of the spatial distribution of passalid beetles within decomposing logs, as well as their distribution in microhabitats such as the cortex, heartwood and trunk–soil interface. Moreover, there is a scarcity of studies that delve into the temporal distribution patterns of passalid beetles. We evaluate the effect of seasons of the year and microhabitats on the distribution of passalid in an Altitudinal Atlantic Forest. More specifically, the effects of the period of the year and microhabitats were analysed on an assemblage scale and population structure scale. Collections were actively conducted monthly, during dry and rainy seasons, and distinct microhabitats of logs (tree cortex, heartwood and trunk–soil interface) were sampled. We discovered passalid galleries within 235 logs, housing a total of 785 individuals representing nine species across six genera and two tribes. Within the three examined microhabitats, the heartwood and cortex harboured the majority of individuals. In contrast, the trunk–soil interface microhabitat displayed reduced diversity and abundance and the absence of indicator species, exhibiting a distinct community structure compared with the others. The dry season stood out with a greater number of individuals, underscoring the influence of precipitation on passalid activity in this study. Our study contributes to understanding the ecological dynamics of these insects and evaluating their resilience to current landscape transformations on the planet.