Individual Species Research Articles

Three-dimensional conservation planning of fish biodiversity metrics to achieve the deep-sea 30×30 conservation target.

Accelerating rate of human impact and environmental change severely affects marine biodiversity and increases the urgency to implement the Convention on Biological Diversity (CBD) 30×30 plan for conserving 30% of sea areas by 2030. However, area-based conservation targets are complex to identify in a 3-dimensional (3D) ocean where deep-sea features such as seamounts have been seldom studied mostly due to challenging methodologies to implement at great depths. Yet, the use of emerging technologies, such as environmental DNA combined with modern modeling frameworks, could help address the problem. We collected environmental DNA, echosounder acoustic, and video data at 15 seamounts and deep island slopes across the Coral Sea. We modeled 7 fish community metrics and the abundances of 45 individual species and molecular operational taxonomic units (MOTUs) in benthic and pelagic waters (down to 600-m deep) with boosted regression trees and generalized joint attribute models to describe biodiversity on seamounts and deep slopes and identify 3D protection solutions for achieving the CBD area target in New Caledonia (1.4millionkm2). We prioritized the identified conservation units in a 3D space, based on various biodiversity targets, to meet the goal of protecting at least 30% of the spatial domain, with a focus on areas with high biodiversity. The relationship between biodiversity protection targets and the spatial area protected by the solution was linear. The scenario protecting 30% of each biodiversity metric preserved almost 30% of the considered spatial domain and accounted for the 3D distribution of biodiversity. Our study paves the way for the use of combined data collection methodologies to improve biodiversity estimates in 3D structured marine environments for the selection of conservation areas and for the use of biodiversity targets to achieve area-based international targets.

Investigation of Neighboring Group Participation in 3,4-Diacetylated Glycosyl Donors in the Gas Phase.

A key challenge in oligosaccharide synthesis is the stereoselective installation of glycosidic bonds. Each glycosidic linkage has one of two possible stereo-chemical geometries, α/β or 1,2-cis/trans. An established approach to install 1,2-trans glycosidic bonds is neighboring group participation (NGP), mediated by a 2-O-acyl group. Extension of this intramolecular stabilization to nucleophilic groups located at more remote positions has also been suggested, but remains poorly understood. Previously, we employed infrared ion spectroscopy to characterize the molecular ions of monoacetylated sugar donors and showed how the strength of the stabilizing effect depends on the position of the participating ester group on the glycosyl donor ring as well as on its relative stereochemistry. In this work, we investigated glycosyl donors carrying two acyl groups. Using isotope labelling and isomer population analysis we were able to resolving spectra of isomeric mixtures and establish the relative contribution of individual species. We conclude that 3,4-diacetyl mannosyl donors exclusively form a dioxanium ion as a result of C-3 acyl stabilization. In contrast, the glucosyl and galactosyl cations form mixtures of C-3 and C-4 acyl participation products. Hence, the combination of isotope labeling and population analysis allows for the study of increasingly complex glycosyl cations.

Nanorod inside hollow-nanosphere structured magnetoelectric nanocatalyst for remotely controlled electrocatalysis assisted environmental remediation

We introduce a highly efficient method for the catalytic breakdown of organic compounds using nanorods embedded within hollow nanospheres structured magnetoelectric nanocatalyst (MENC). MENCs were fabricated through a single-step process utilizing the ultrasonic spray pyrolysis technique. The dynamic electric dipole generation capability due to synergistic interaction between nanorods at the core and the hollow nanosphere shell creates a nanoscale magnetoelectric device capable of electrocatalysis-assisted water purification through advanced oxidation processes under remotely applied magnetic field excitation. Our study examines the electrocatalytic degradation of organic pollutants by MENCs under magnetic field excitation, achieving an unprecedented 90% removal efficiency for synthetic dyes. This remarkable efficiency is a result of surface redox reactions facilitated by electron and hole transfer, resulting in the production of Reactive oxygen species (ROS) such as O2•− and •OH. Additionally, antioxidant experiments were performed to confirm the ROS generation capability of MENCs under magnetic field excitation. Furthermore, trapping experiments performed employing specific scavengers for individual reactive species reveal the mechanism responsible for the magnetic field-driven catalytic breakdown of organic contaminants by MENCs. Interestingly, the MENCs exhibit >95% reduction in Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) bacteria, respectively, within 90 min of exposure to a (20 mT& 1.9 kHz) AC magnetic field.

Microbiological analysis of tunneled hemodialysis catheters isolated from patients receiving hemodialysis in Saskatchewan.

Aim: To compare the microbial communities inside hemodialysis catheters from symptomatic and asymptomatic patients to determine their differences.Materials & methods: Catheters (n=41) were removed from patients in the Saskatchewan Health Authority over an 18-month period. The catheter section inside the body was flushed and the contents were evaluated using culture-dependent and culture-independent analysis.Results: All catheters were colonized by bacteria, with considerable overlap between groups based on microbial communities and the individual species detected. More Gram-negative species were detected by sequencing, whereas predominantly Gram-positive strains were cultured. Antibiotic resistance and biofilm formation was widespread and not correlated with either catheter group.Conclusion: Common pathogens were detected in each set of catheters, therefore predicting infections based on the microbiology is difficult.

Leptospira infection of rodents captured at the slaughterhouses and their risk to public health in Unguja island, Tanzania

Background: Leptospira infection is an invasion of animal or human body with the pathogenic spirochete bacteria of the genus Leptospira resulting to a disease called leptospirosis. This study aimed to investigate Leptospira infection and the carrier status of rodents caught near slaughterhouses at Unguja Island, Tanzania. Methods: This cross-sectional study was conducted from January to April 2022 at Unguja Island to determine the seroprevalence of Leptospira infection in rodents captured in and around the slaughterhouse’s compounds. A total of 302 sera samples from four slaughterhouses were tested for anti-leptospiral antibodies using microscopic agglutination test (MAT) with a panel of 5 Leptospira serovars: Pomona, Lora, Hebdomadis, Grippotyphosa and Sokoine; and were considered positive at MAT titer ≥1:20. Chi-square test and the Fisher exact test were used to assess the statistical association between variables at a p value of < 0.05. Results: The overall seroprevalence of Leptospira infection in rodents was 10.6% (32/302). Individual rodent species had seroprevalence of 8.5% for Mus musculus, 0.0% for Mastomys natalensis, 20.8% for Rattus norvegicus, 9.3% for Rattus rattus and Cricetomys gambianus at 12.5%. However, the apparent seroprevalence in the individual slaughter facilities was 15.0% (15/100) Kinyasini, 10.4% (5/48) Mfenesini, 9.3% (5/54) Kisakasaka, and 7.0% (7/100) Muwanda. Conclusion: With over ten percent of rodents testing positive for Leptospira infection, it is crucial to implement rodent control measures to prevent the spread of the disease to those working in or around the slaughterhouses in Unguja Island.

High among‐species variability in the context dependence of herbivory across disturbance, weather and topoedaphic gradients

Abstract Species interaction effects on populations can vary in both magnitude (i.e. strong vs. weak) and sign (positive, negative, or no effect). Context‐dependent effects of species interactions occur when the sign or strength of the interaction's effect on population growth rate changes across abiotic gradients. We know that species can vary substantially in the degree of context dependence they exhibit, even across similar abiotic gradients. However, few studies have characterised context dependence of co‐occurring species, limiting our ability to understand the implications of context dependence for species interaction effects on community composition. Using over three decades of data collected for 13 tallgrass prairie forbs at the Konza Prairie Biological Station, we parameterise density structured population models that predict population dynamics as functions of abiotic conditions and bison herbivory. We use these models to estimate the degree of context dependence in responses to bison herbivory for 13 species across three abiotic gradients: weather, fire frequency and soil type. All species showed significant context dependence for fire frequency in the same direction, though with variable magnitude, such that herbivory increased cover with more frequent fires. Context dependence with weather and soil type varied dramatically across species in both direction and magnitude. For example, herbivory effects on 3/13 species were stronger in wet conditions, but herbivory effects on 5/13 species were stronger in dry conditions. Thus, context dependence exhibited by individual species, as opposed to effects of abiotic conditions on the relative abundances of species, could generate much of the weather‐dependent effects of herbivory on community composition. Synthesis: Our work suggests that species can vary dramatically in the presence, direction and magnitude of context dependence, even when occurring in the same community and when considering the same species interaction (i.e. response to a herbivore). In addition, we find that context dependence could drive substantial variation in the effect of species interactions on community characteristics (e.g. composition) across multiple abiotic gradients.

Maternal Exposure to Tap Water Disinfection By-Products and Risk of Selected Congenital Heart Defects.

The use of chlorine to treat drinking water produces disinfection by-products (DBPs), which have been associated with congenital heart defects (CHDs) in some studies. Using National Birth Defects Prevention Study data, we linked geocoded residential addresses to public water supply measurement data for DBPs. Self-reported water consumption and filtration methods were used to estimate maternal ingestion of DBPs. We estimated adjusted odds ratios and 95% confidence intervals using logistic regression controlling for maternal age, education, body mass index (BMI), race/ethnicity, and study site to examine associations between CHDs and both household DBP level and estimated ingestion of DBPs. Household DBP exposure was assessed for 2717 participants (1495 cases and 1222 controls). We observed a broad range of positive, null, and negative estimates across eight specific CHDs and two summary exposures (trihalomethanes and haloacetic acids) plus nine individual DBP species. Examining ingestion exposure among 2488 participants (1347 cases, 1141 controls) produced similarly inconsistent results. Assessing both household DBP level and estimated ingestion of DBPs, we did not find strong evidence of an association between CHDs and DBPs. Despite a large study population, DBP measurements were available for less than half of participant addresses, limiting study power.

Changing Nepali children's attitudes toward conservation through a participatory education program.

People's attitude toward wildlife is known to affect the success of conservation programs. Public education can increase support for conservation measures by providing the knowledge necessary to make informed decisions, improve pro-environmental behaviour and potentially enlist participation. To that end, we developed a participatory conservation education program in Nepal with a target audience of secondary school students. Our lessons emphasized ecological balance by highlighting the roles of individual species, including the rhesus macaque (Macaca mulatta). This species presents a challenge for educating the public about maintaining balance in nature, because although an important seed disperser and species of religious significance, macaques are frequently involved in human-wildlife conflict and considered a pest species. We evaluated the impact of our program by surveying students from six socioeconomically similar schools, four that participated in our program and two that had not. Our questionnaire was comprised of knowledge questions about local wildlife and conservation issues, an open-ended listing exercise to determine species preferences, and statements that elicited students' opinions regarding empathy toward animals. Knowledge about and attitude toward wildlife, including M. mulatta, were greater in students that participated in the program. More importantly, these students were more likely to understand the role individual species play in a balanced ecosystem, how human behaviour can negatively impact wildlife, and how they could participate in conservation efforts. Gender was not a factor in any response. We discuss the merits of using a participatory learning platform in a standalone education program that has long-term purpose, funding, and buy-in.

Lack of ceramide synthase 5 protects retinal ganglion cells from ocular hypertensive injury

Ceramides with varying acyl-chain lengths can have unique biological actions and hence, cellular responses to ceramides may depend not on their overall concentration but on that of individual ceramide species. The purpose of this study was to determine individual ceramide species impacting retinal ganglion cell (RGC) loss under the ocular hypertensive condition.Induced pluripotent stem cell (iPSC)-derived RGCs and primary cultures of human astrocytes were used to determine the effect of individual ceramide species on both RGC viability and astrocyte secretion of inflammatory cytokines in vitro. In in vivo experiments with wild-type (WT) and ceramide synthase 5 (CerS5) knockout mice, intraocular pressure was unilaterally elevated with microbead injection. Retinal function and morphology were evaluated using pattern electroretinography (pERG) and immunofluorescence, respectively. Ceramide levels were determined by LC-MS/MS analysis.Exposure to C16:0-, C18:0-, C18:1-, C20:0- and C24:0-ceramides significantly reduces RGC viability in vitro, with the very long chain C24:0-ceramide being the most neurotoxic; treatment with C18:0-, C18:1- and C24:0-ceramides stimulates an increase of TNF-α secretion by astrocytes. The retinas of CerS5 KO mice have significantly reduced levels of C16:0- and C18:1-ceramides compared to WT; ocular hypertensive eyes of these mice maintain higher pERG amplitudes and RGC numbers compared to WT.Individual ceramides with different chain lengths have different effects on RGCs and astrocytes. Our results demonstrate that suppressing C16:0- and C18:1-ceramide species effectively protects RGCs against ocular hypertensive injury. These results provide a basis for targeting specific ceramide species in the treatment of glaucoma.

Phenological Analysis of Grasses (Poaceae) in Comparison with Aerobiological Data in Moscow (Russia).

Grasses (Poaceae) produce large amounts of pollen and are among the main causes of pollinosis worldwide. Despite their morphological similarity, pollen grains of different grass species may have different allergenicities. Therefore, quantification of the roles of individual species in airborne pollen is an important task. There are very few studies on this topic, and none of them have been conducted in a temperate continental climate. Our study was carried out for three years (2020-2022) in the urban territory of Moscow (Russia) and aimed to understand what grass species contribute the most to the total pollen load of the atmosphere. The comparison of aerobiological and phenological data was based on calculating the phenological index, which is a combination of phenological parameters, pollen productivity of individual species, and their abundance. Our data showed that the decomposition of pollination curves based on the phenological index was sometimes very efficient but not always possible in temperate continental climates. The main reasons for disagreement between aerobiological and phenological data were weather conditions and lawn mowing. Not all grasses were equally important as sources of allergenic pollen. The greatest contribution to the pollen load at the beginning of the season in Moscow was made by Dactylis glomerata, and to a lesser extent by Phleum pratense and Festuca pratensis. These are the most common species, which are widespread throughout Europe. The contribution of minor components is insignificant.

The answer, my friend, is blowin' in the wind: Blow sampling provides a new dimension to whale population monitoring.

Marine mammals play a fundamental role in the functioning of healthy marine ecosystems and are important indicator species. Studying their biology, distributions, behaviour and health are still technically and logistically demanding for researchers. However, the efforts and commitment have not been in vain, since we are witnessing constant and exponential advancement in the study of these animals, thanks to technological progress in numerous fields. These include miniaturization and performance of biologger tags, which are equipped with sensors for measuring physiological parameters, hydrophones, accelerometers, time-depth records and spatial locations; the use of high throughput 'Next Generation' Sequencing to gain genetic information about communities and individual species from nucleic acids in environmental samples at miniscule concentrations; through, to the possibility of monitoring species with autonomous aerial and underwater vehicles. In parallel advances in computing and statistical modelling frameworks support the analysis of increasingly large and complex data sets. In this issue, O'Mahony etal.(2024) draw from at least two of these innovations: (a) the collection of biological material retrieved from large whales' blows using a modified drone and (b) the use of the samples to infer a wide spectrum of genetic information (both nuclear and mitochondrial) about the target animal/population. The methodology is not completely novel, but the study shows an impressive advancement in the amount of data obtained compared to preceding studies using the same approach. In the wake of these promising results, future perspectives are evaluated in relation to alternative sampling methodologies currently in use. It is possible to speculate that, in the next few years, the combination of non-invasive molecular profiling and enhanced drone technology (e.g. assembling increasingly smaller components, thus expanding capacity for autonomous operation) will open up perspectives that were unimaginable at the beginning of this millennium.

Beyond species richness: Forest structure and edaphic conditions have similar importance but different effects on multi-taxon biodiversity

Managed forests represent a major fraction of the global forest area and are known to host impoverished biodiversity compared to natural forests. The effect of forest management has focused mainly on aggregated community metrics such as species richness of single taxa and on simplistic managed vs. unmanaged comparisons. However, the effect of forest management is expected to vary among species and taxa and to be contingent on site-specific conditions. In this study, we focus on fine-scale multi-taxon biodiversity patterns to disentangle the impact of forest management on the forest structure and the abiotic soil conditions of the stands. We base our comparisons on carefully selected pairs of managed and unmanaged stands to minimize regional differences that could confound the effects of management. We found that the total effect of forest management on alpha diversity was positive on plants and rove beetles, neutral on ground beetles and mosses, and negative on crane flies, fungi, and lichens. However, using joint species distribution modeling we show that individual species’ responses to the local underlying soil conditions can be as important as the forest structural changes induced by management, but this varied among the different taxa. Based on these responses we disclose synergies and trade-offs among some of the taxa. Our results indicate that the balance between forest management and abiotic conditions can shape the patterns of forest multi-taxon biodiversity. Considering these conditions can be important in predicting the response of biodiversity to forest management and act as key criteria when prioritizing areas for the conservation of biodiversity.

LC-HRMS analysis of phospholipids bearing oxylipins

BackgroundSeveral oxylipins including hydroxy- and epoxy-polyunsaturated fatty acids act as lipid mediators. In biological samples they can be present as non-esterified form, but the major part occurs esterified in phospholipids (PL) or other lipids. Esterified oxylipins are quantified indirectly after alkaline hydrolysis as non-esterified oxylipins. However, in this indirect analysis the information in which lipid class oxylipins are bound is lost. In this work, an untargeted liquid chromatography high-resolution mass spectrometry (LC-HRMS) method for the direct analysis of PL bearing oxylipins was developed. ResultsOptimized reversed-phase LC separation achieved a sufficient separation of isobaric and isomeric PL from different lipid classes bearing oxylipin positional isomers. Individual PL species bearing oxylipins were identified based on retention time, precursor ion and characteristic product ions. The bound oxylipin could be characterized based on product ions resulting from the α-cleavage occurring at the hydroxy/epoxy group. PL sn-1/sn-2 isomers were identified based on the neutral loss of the fatty acyl in the sn-2 position. A total of 422 individual oxPL species from 7 different lipid classes i.e., PI, PS, PC, PE, PC-P, PC-O, and PE-P were detected in human serum and cells. This method enabled to determine in which PL class supplemented oxylipins are incorporated in HEK293 cells: 20:4;15OH, 20:4;14Ep, and 20:5;14Ep were mostly bound to PI. 20:4;8Ep and 20:5;8Ep were esterified to PC and PE while other oxylipins were mainly found in PC. SignificanceThe developed LC-HRMS method enables the comprehensive detection as well as the semi-quantification of isobaric and isomeric PL species bearing oxylipins. With this method, we show that the position of the oxidation has a great impact and directs the incorporation of oxylipins into the different PL classes in human cells.

Arsenic speciation analysis in human urine for long term epidemiological studies: The Multi-Ethnic Study of Atherosclerosis (MESA)

Arsenic is a ubiquitous toxic metalloid causing serious health problems. Speciation analysis of arsenic in human urine provides valuable insights for large-scale epidemiological studies and informs on sources of exposure as well as human metabolism. The Multi-Ethnic Study of Atherosclerosis (MESA) is a valuable cohort for assessing chronic low-moderate arsenic exposure and health effects in an ethnically diverse US population. We present a state-of-the-art arsenic speciation analysis methodology and its application to 7677 MESA spot urine samples based on high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. This method is fast, robust and detects a total of 11 individual As species at method detection limits of 0.02–0.03 μg arsenic/L urine for each individual species. Our analytical approach features excellent mean method accuracy (98%) and precision (5%) for the main arsenic species in urine (arsenobetaine, methylarsonic acid, dimethylarsinic acid, and total inorganic As); intra- (3–6%) and inter-day coefficients of variability (5–6%); column recovery (96 ± 7%); and spike recovery (97 ± 6%). The main arsenic species were detectable in ≥95% of urine samples due to the implementation of an oxidation step. Each individual minor arsenic species was detectable in ≤25% of all urines, although at least one of them was detected in almost half the participants. We identified two minor urinary arsenic species as dimethylarsinoylacetic acid and dimethylarsinoylpropionic acid, potential metabolites of seafood-related arsenicals. We observed differences in individual As species excretion by race/ethnicity, with Asian-American participants featuring 3–4 times higher concentrations compared to other participants. We also found differences by site, body mass index, smoking status, rice intake, and water arsenic levels, potentially indicating different exposures or related to individual bio-metabolism. The proposed approach is suitable for epidemiological studies and the collected data will constitute the base for future research on potential health effects of chronic low-level arsenic exposure.

Analysis of subcellular energy metabolism in five Lacertidae lizards across varied environmental conditions

Aerobic respiration is the main energy source for most eukaryotes, and efficient mitochondrial energy transfer greatly influences organismal fitness. To survive environmental changes, cells have evolved to adjust their biochemistry. Thus, measuring energy metabolism at the subcellular level can enhance our understanding of individual performance, population dynamics, and species distribution ranges. We investigated three important metabolic traits at the subcellular level in five lacertid lizard species sampled from different elevations, from sea level up to 2000 m. We examined hemoglobin concentration, two markers of oxidative stress (catalase activity and carbonyl concentration) and maximum rate of metabolic respiration at the subcellular level (potential metabolic activity at the electron transport system). The traits were analysed in laboratory acclimated adult male lizards to investigate the adaptive metabolic responses to the variable environmental conditions at the local sampling sites. Potential metabolic activity at the cellular level was measured at four temperatures – 28 °C, 30 °C, 32 °C and 34 °C – covering the range of preferred body temperatures of the species studied. Hemoglobin content, carbonyl concentration and potential metabolic activity did not differ significantly among species. Interspecific differences were found in the catalase activity, Potential metabolic activity increased with temperature in parallel in all five species. The highest response of the metabolic rate with temperature (Q10) and Arrhenius activation energy (Ea) was recorded in the high-mountain species Iberolacerta monticola.

Ca2+-dependent lipid preferences shape synaptotagmin-1 C2A and C2B dynamics: Insights from experiments and simulations

Signal transmission between neurons requires exocytosis of neurotransmitters from the lumen of synaptic vesicles into the synaptic cleft. Following an influx of Ca2+, this process is facilitated by the Ca2+ sensor synaptotagmin-1. The underlying mechanisms involve electrostatic and hydrophobic interactions tuning the lipid preferences of the two C2 domains of synaptotagmin-1; however, the details are still controversially discussed. We, therefore, follow a multidisciplinary approach and characterize lipid and membrane binding of the isolated C2A and C2B domains. We first target interactions with individual lipid species, and then study interactions with model membranes of liposomes. Finally, we perform molecular dynamics simulations to unravel differences in membrane binding. We found that both C2 domains, as a response to Ca2+, insert into the lipid membrane; however, C2A adopts a more perpendicular orientation while C2B remains parallel. These findings allow us to propose a mechanism for synaptotagmin-1 during membrane fusion.

A new perspective on tree growing season determination

AbstractDefining plant development timing through seasonal growth and dormancy phases is a valuable proxy for studying climate change and serves as an annual bioindicator. However, current methods for determining the growing season vary due to species‐specific interpretations and differing understandings of its main drivers. Körner et al. (2023) introduced four non‐interchangeable definitions of growing seasons to clarify this complex issue. While some studies have paired different methods, none have simultaneously applied a full set of methods at the individual tree or species level. Here, I aim to present a new perspective to understanding growing season timing by focusing on all facets of above‐ground tree growth and measurable biological and phenological markers. This approach calls for simultaneous, continuous monitoring during active and dormancy periods on the same trees and across different species at a large spatial scale. The goal is to comprehensively understand each method's errors, temporal lags, and the factors determining each growing season, as defined by Körner et al. (2023, Ecology Letters, 26, 1277). Accurate estimation of growing season timing can reshape our understanding of its environmental drivers, improve terrestrial ecosystem models, assess the impact of climate change on tree growth, determine the biological zero for various species, verify remote sensing indices and forecast species distribution.

Using joint species distribution modelling to identify climatic and non‐climatic drivers of Afrotropical ungulate distributions

The relative importance of the different processes that determine the distribution of species and the assembly of communities is a key question in ecology. The distribution of any individual species is affected by a wide range of environmental variables as well as through interactions with other species; the resulting distributions determine the pool of species available to form local communities at fine spatial scales. A challenge in community ecology is that these interactions (e.g. competition, facilitation, etc.) often are not directly measurable. Here, we used hierarchical modelling of species communities (HMSC), a recently developed framework for joint species distribution modelling, to estimate the role of biotic effects alongside environmental factors using latent variables. We investigate the role of these factors determining species distributions in communities of Artiodactyla, Perissodactyla and Proboscidea in the Afrotropics, an area of peak species richness for hoofed mammals. We also calculate pairwise trait dissimilarity between these species, from a mixture of morphological and behavioural traits, and investigate the relationship between dissimilarity and estimated residual co‐occurrence in the model. We find that while ungulate distributions appear to be predominantly determined (~ 70%) by climatic variables, such as precipitation, a substantial proportion of the variance in ungulate species distributions (~ 30%) can also be attributed to modelled latent variables that likely represent a combination of dispersal barriers and biotic factors. Although we find only a weak relationship between residual co‐occurrence and trait dissimilarity, we suggest that our results may show evidence that biotic factors, likely influenced by historical barriers to species dispersal, are important in determining species communities over a continental area. The HMSC framework can be used to provide insight into factors affecting community assembly at broad scales, and to make more powerful predictions about future species distributions as we enter an era of increasing impacts from anthropogenic change.

Understory Vegetation Influences Insect Diversity in Rubber Plantations of Kanyakumari, India

Insects play a crucial role in maintaining ecological balance, and their decline has detrimental effects on various organisms. Globally, rubber plantations have been associated with a reduction in insect diversity. However, the impact of monoculture rubber plantations on biodiversity in India, particularly in Kanyakumari, is not well understood and has received little research attention. This study aimed to assess the status of insect diversity in rubber plantations in this region. Kanyakumari, Tamil Nadu, with its extensive monoculture rubber plantations, provides an ideal setting for this investigation. Three adjacent rubber plantations with varying topography and understory vegetation were selected for the study. Data was collected between July 2021 to January 2022 and analysis was done using biodiversity indices - Simpson and Shannon-Weiner indices. Results indicated that insect diversity was significantly higher in one plantation when compared to the other two plantations. Canopy and understory vegetation were identified as key factors influencing insect diversity. Plantations with dense understory vegetation consisting of diverse native plant species exhibited greater insect richness. The predominant insect orders across all plantations were Hymenoptera (29.70%) and Diptera (29.40 %). However, the impact of rubber plantations on individual insect species varied based on their habitat preferences. Seasonal fluctuations in diversity were particularly noticeable during the monsoon season. Further comparative studies are needed to understand the broader implications of rubber plantations on insect diversity across the district.

Field-based multispecies weed and crop detection using ground robots and advanced YOLO models: A data and model-centric approach

The implementation of a machine-vision system for real-time precision weed management is a crucial step towards the development of smart spraying robotic vehicles. The intelligent machine-vision system, constructed using deep learning object detection models, has the potential to accurately detect weeds and crops from images. Both data-centric and model-centric approaches of deep learning model development offer advantages depending on environment and non-environment factors. To assess the performance of weed detection in real-field conditions for eight crop species, the Yolov8, Yolov9, and customized Yolov9 deep learning models were trained and evaluated using RGB images from four locations (Casselton, Fargo, and Carrington) over a two-year period in the Great Plains region of the U.S. The experiment encompassed eight crop species—dry bean, canola, corn, field pea, flax, lentil, soybean, and sugar beet—and five weed species—horseweed, kochia, redroot pigweed, common ragweed, and water hemp. Six Yolov8 and eight Yolov9 model variants were trained using annotated weed and crop images gathered from four different sites including combined dataset from four sites. The Yolov8 and Yolov9 models’ performance in weed detection were assessed based on mean average precision (mAP50) metrics for five datasets, eight crop species, and five weed species. The results of the weed and crop detection evaluation showed high mAP50 values of 86.2 %. The mAP50 values for individual weed and crop species detection ranged from 80.8 % to 98 %. The results demonstrated that the performance of the model varied by model type (model-centric), location due to environment (data-centric), data size (data-centric), data quality (data-centric), and object size in the image (data-centric). Nevertheless, the Yolov9 customized lightweight model has the potential to play a significant role in building a real time machine-vision-based precision weed management system.