Relative Population Density Research Articles

Growth and biomass of Wolffia arrhiza with different sources of organic fertilizer

Wolffia arrhiza has a growth rate and biomass as well as a good nutritional content for the growth of cultivated fish, especially herbivorous fish. Due to the high protein content (up to 45% of the dry weight), Wolffia is an excellent plant for the production of various biologically active substances, especially proteins. These plants can double every 1-6 days, similar to algae or mushrooms, and the number of leaves doubles every 2-3 days. This study aims to determine the effect of different fertilizer sources on doubling time, relative growth rate, population density and biomass of Wolffia arrhiza and water quality. The method used in this research is experimental. The research design used a completely randomized design (CRD) consisting of 4 treatments and 3 replications. The treatments were as follows: treatment A: chicken manure, B: cow manure, C: buffalo manure and D: goat manure with each dose of 200 grams. Parameters observed included doubling time, relative growth rate, population density, biomass and water quality parameters. The results showed that treatment B (cow manure) gave the highest value for doubling time, 1.59 days, relative growth rate 0.392 g/day, population density 209.75 ind/cm2, biomass 94.97. Keyword: Biomass; Fertilizer; Growth; Wolffia

Accumulation of Per- and Polyfluoroalkyl Substances (PFAS) in Coastal Sharks from Contrasting Marine Environments: The New York Bight and The Bahamas.

Per- and polyfluoroalkyl substances (PFAS) enter the marine food web, accumulate in organisms, and potentially have adverse effects on predators and consumers of seafood. However, evaluations of PFAS in meso-to-apex predators, like sharks, are scarce. This study investigated PFAS occurrence in five shark species from two marine ecosystems with contrasting relative human population densities, the New York Bight (NYB) and the coastal waters of The Bahamas archipelago. The total detected PFAS (∑PFAS) concentrations in muscle tissue ranged from 1.10 to 58.5 ng g-1 wet weight, and perfluorocarboxylic acids (PFCAs) were dominant. Fewer PFAS were detected in Caribbean reef sharks (Carcharhinus perezi) from The Bahamas, and concentrations of those detected were, on average, ∼79% lower than in the NYB sharks. In the NYB, ∑PFAS concentrations followed: common thresher (Alopias vulpinus) > shortfin mako (Isurus oxyrinchus) > sandbar (Carcharhinus plumbeus) > smooth dogfish (Mustelus canis). PFAS precursors/intermediates, such as 2H,2H,3H,3H-perfluorodecanoic acid and perfluorooctanesulfonamide, were only detected in the NYB sharks, suggesting higher ambient concentrations and diversity of PFAS sources in this region. Ultralong-chain PFAS (C ≥ 10) were positively correlated with nitrogen isotope values (δ15N) and total mercury in some species. Our results provide some of the first baseline information on PFAS concentrations in shark species from the northwest Atlantic Ocean, and correlations between PFAS, stable isotopes, and mercury further contextualize the drivers of PFAS occurrence.

Asociación entre el empleo informal y los casos positivos de COVID-19 en el Perú

Objectives: To identify the association between the number of informal employees and the number of positive COVID-19 cases in Peru. Methods: Data from the Peruvian National Institute of Statistics and Informatics and the National COVID-19 database were used. Bivariate linear regression and multivariate logistic regression were performed to evaluate the number of informal employees, population density, and altitude in relation to the number of COVID-19 positive cases. Results: Bivariate analysis showed that the number of informal employees was significantly associated with the number of COVID-19 positive cases in both high and low altitude regions (p<0.001). In the multivariate analysis, it was found that the number of informal employees (p<0.001), population density (p=0.02), and altitude (p<0.001) were associated with the number of COVID-19 positive cases. Conclusions: Informal employees are common in low- and middle-income countries where there is no social security and they are economically dependent on daily wages. Their situation worsened due to social mobility restrictions, forcing them to continue working and, consequently, becoming quickly infected, further contributing as a contagion focus.

Time-resolved measurement of optical emission line profiles from electron cyclotron resonance ion source plasma

Optical emission spectroscopy provides a non-invasive method to probe the properties of hot and highly charged magnetically confined plasmas. The optical emission line profiles enable, for example, to identify the different species and characterize the relative population densities and temperatures of the ions and neutrals forming the plasma. The feasibility of this approach has been demonstrated at the University of Jyväskylä accelerator laboratory by measuring the light emitted by Electron Cyclotron Resonance Ion Source (ECRIS) plasma with a high-resolution spectrometer setup POSSU (Plasma Optical SpectroScopy Unit). In these previous studies, the emission line profiles were measured by scanning the desired wavelength range by rotating the diffraction grating of the spectrometer. This process is slow compared to many interesting plasma phenomena, thus limiting the applicability of the setup. Recently, POSSU has been upgraded by changing the light sensor from a photomultiplier tube to a position-sensitive imaging sensor. As a result, it is possible to measure simultaneously a 1 - 2 nm wavelength range, with a spectral resolution in the order of picometers, without moving the grating. This enables a time-resolved study of the optical emission line profiles. By turning the grating, the measured wavelength region can be chosen between 370 nm and 870 nm, which covers the visible light spectrum. The time-evolution of optical emission line profiles emitted from the JYFL 14 GHz ECRIS plasma, during shifting plasma conditions induced by changing the gas balance, has been measured to demonstrate this new capability. The time-evolution of temperatures and emission intensities of selected ion species, correlated with extracted ion beam currents, are presented.

Hybrid instrument network optimization for air quality monitoring

Abstract. The significance of air quality monitoring for analyzing impact on public health is growing worldwide. A crucial part of smart city development includes deployment of suitable air pollution sensors at critical locations. Note that there are various air quality measurement instruments, ranging from expensive reference stations that provide accurate data to low-cost sensors that provide less accurate air quality measurements. In this research, we use a combination of sensors and monitors, which we call hybrid instruments, and focus on optimal placement of such instruments across a region. The objective of the problem is to maximize a satisfaction function that quantifies the weighted closeness of different regions to the places where such hybrid instruments are placed (here weights for different regions are quantified in terms of the relative population density and relative PM2.5 concentration). Note that there can be several constraints such as those on budget, the minimum number of reference stations to be placed, or the set of important regions where at least one sensor should be placed. We develop two algorithms to solve this problem. The first one is a genetic algorithm that is a metaheuristic and that works on the principles of evolution. The second one is a greedy algorithm that selects the locally best choice in each iteration. We test these algorithms on different regions from India with varying sizes and other characteristics such as population distribution, PM2.5 emissions, or available budget. The insights obtained from this paper can be used to quantitatively place reference stations and sensors in large cities rather than using ad hoc procedures or rules of thumb.

Breeding birds of high-elevation mixed-conifer forests have declined in national parks of the southwestern U.S. while lower-elevation species have increased, with responses to drought varying by habitat

Abstract Climate change is considered a major driver of recent avian population declines, particularly in the drought-stricken southwestern United States. Predicting how bird populations will respond requires understanding the climatic drivers influencing population density across the region’s diverse habitats. We modelled breeding-season densities of 50 bird species in relation to spring and summer drought and the timing of North American monsoon rainfall over a 12-year period (2007–2018) and across 4 habitats comprising an approximately 1,500 m elevational gradient. We estimated annual breeding-season population density in relation to climate in the previous year by fitting a Bayesian hierarchical N-mixture model to point-count data from each of 6 national parks on the Colorado Plateau. Specifically, we asked whether (1) population trends were stable, increasing, or decreasing in the focal parks; (2) breeding densities were affected by drought or the timing of monsoon rains; and (3) climatic effects differed across habitat types and among species that molt on the breeding grounds, the nonbreeding grounds, or stopover to molt in the monsoon region of northwestern Mexico (molt migrants). Population trends varied with habitat. Species of high-elevation mixed-conifer forest declined over the study period, matching regional Breeding Bird Survey trends, likely in response to climate-related habitat loss and disturbance. By contrast, lower-elevation pinyon-juniper and grassland-shrubland species density generally increased. Effects of drought varied by habitat with elevation: mixed-conifer species responded positively to drought in the previous year, likely due to earlier snowmelt and breeding phenology, whereas pinyon-juniper species were unaffected, and grassland-shrubland species responded negatively, perhaps due to reduced nest survival. Later arrival of monsoon rains, a common prediction of climate models, had a positive effect on grassland bird densities, but a negative effect on molt-migrant densities. Late monsoon rains may result in a phenological mismatch between migration timing and the pulse of resources required to molt.

Impact of forest fragmentation and associated edge effects on the population density of four nocturnal lemur species in North West Madagascar

AbstractThe clearing and fragmentation of tropical forests is the single biggest threat to primate populations who depend on this habitat for survival. In contrast to primates that live in continuous, undisturbed forests, primate communities of fragmented forests need to adapt to decreased food availability and increased inter‐ and intraspecific competition typical of these degraded and anthropogenically disturbed habitats. Some primate species are highly sensitive to habitat fragmentation, whilst other species can adapt and even thrive in fragmented and degraded forests. Here, we assessed how forest fragmentation and associated edge effects impact the population density of four species of nocturnal lemur in the Sahamalaza‐Iles Radama National Park, North West Madagascar. We conducted 118 transect walks over a 3‐year period covering a total distance of 107 km to collect encounter rate (N/km) and population density (N/Ha) data for each species, which we then compared between the edge and core areas of a continuous forest and a fragmented forest. Our results were highly species‐specific, with the population densities of two species (Lepilemur sahamalaza and Microcebus sambiranensis) increasing in edge and fragmented habitat, whilst we observed the opposite for Cheirogaleus medius. Mirza zaza density appeared consistent between the continuous and fragmented forest and in both edge and core areas. We also found evidence of species‐specific population density relationships with fragment size, core area and fragment shape; however, further work is needed to support these findings. This study demonstrates that some nocturnal lemurs can adapt to degraded habitats and thrive within fragmented forests, whilst other species are less capable of doing so.

The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study.

The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise). The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses. We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State. In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status. The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States.

Shifts in population density centers of a hibernating mammal driven by conflicting effects of climate change and disease.

Populations wax and wane over time in response to an organism's interactions with abiotic and biotic forces. Numerous studies demonstrate that fluctuations in local populations can lead to shifts in relative population densities across the geographic range of a species over time. Fewer studies attempt to disentangle the causes of such shifts. Over four decades (1983-2022), we monitored populations of hibernating Indiana bats (Myotis sodalis) in two areas separated by ~110 km. The number of bats hibernating in the northern area increased from 1983 to 2011, while populations in the southern area remained relatively constant. We used simulation models and long-term weather data to demonstrate the duration of time bats must rely on stored fat during hibernation has decreased in both areas over that period, but at a faster rate in the northern area. Likewise, increasing autumn and spring temperatures shortened the periods of sporadic prey (flying insect) availability at the beginning and end of hibernation. Climate change thus increased the viability of northern hibernacula for an increasing number of bats by decreasing energetic costs of hibernation. Then in 2011, white-nose syndrome (WNS), a disease of hibernating bats that increases energetic costs of hibernation, was detected in the area. From 2011 to 2022, the population rapidly decreased in the northern area and increased in the southern area, completely reversing the northerly shift in population densities associated with climate change. Energy balance during hibernation is the singular link explaining the northerly shift under a changing climate and the southerly shift in response to a novel disease. Continued population persistence suggests that bats may mitigate many impacts of WNS by hibernating farther south, where insects are available longer each year.

Bayesian areal disaggregation regression to predict wildlife distribution and relative density with low-resolution data.

For species of conservation concern and human-wildlife conflict, it is imperative that spatial population data be available to design adaptive-management strategies and be prepared to meet challenges such as land use and climate change, disease outbreaks, and invasive species spread. This can be difficult, perhaps impossible, if spatially explicit wildlife data are not available. Low-resolution areal counts, however, are common in wildlife monitoring, that is, the number of animals reported for a region, usually corresponding to administrative subdivisions, for example, region, province, county, departments, or cantons. Bayesian areal disaggregation regression is a solution to exploit areal counts and provide conservation biologists with high-resolution species distribution predictive models. This method originated in epidemiology but lacks experimentation in ecology. It provides a plethora of applications to change the way we collect and analyze data for wildlife populations. Based on high-resolution environmental rasters, the disaggregation method disaggregates the number of individuals observed in a region and distributes them at the pixel level (e.g., 5 × 5 km or finer resolution), thereby converting low-resolution data into a high-resolution distribution and indices of relative density. In our demonstrative study, we disaggregated areal count data from hunting bag returns to disentangle the changing distribution and population dynamics of three deer species (red, sika, and fallow) in Ireland from 2000 to 2018. We show an application of the Bayesian areal disaggregation regression method and document marked increases in relative population density and extensive range expansion for each of the three deer species across Ireland. We challenged our disaggregated model predictions by correlating them with independent deer surveys carried out in field sites and alternative deer distribution models built using presence-only and presence-absence data. Finding a high correlation with both independent data sets, we highlighted the ability of Bayesian areal disaggregation regression to accurately capture fine-scale spatial patterns of animal distribution. This study uncovers new scenarios for wildlife managers and conservation biologists to reliably use regional count data disregarded so far in species distribution modeling. Thus, it represents a step forward in our ability to monitor wildlife population and meet challenges in our changing world.

Modeling the effect of improved sewage disposal rates on ecological status for aquatic organisms in Japan

Improving sewage disposal rates is an important policy for maintaining the health of aquatic organisms in river environments. In Japan, the rate is not yet 100 %. Two measures are necessary to eliminate the discharge of untreated greywater: (1) increase the number of households connected to sewage lines in areas with sewage systems, and (2) replace single-type household onsite wastewater treatment systems (OWTSs) with combined-type systems. To estimate the effect of improving the disposal rate on river water quality, we developed a hydrology-based organic pollution assessment model with a gridded spatial resolution of 250 m to estimate the biochemical oxygen demand (BOD) in rivers in Gunma Prefecture, Japan. We considered three scenarios based on the sewage disposal rate of 70.5 % in 2015. In Scenario A, the disposal rate is increased to 75.2 % in 2030 by increasing the connection rate to sewage lines. In Scenario B, the rate is increased to 88.2 % in 2030 through additional progress in converting from single-to combined-type OWTSs. In Scenario C, the rate reaches 100 % by 2040. The ecological status of rivers was evaluated using taxon richness of Ephemeroptera, Plecoptera, and Trichoptera estimated from its reported relationship to BOD. The number of sites in Gunma Prefecture polluted by organic waste classified as III (poor) and IV (very poor) was estimated to be 1610 under the present state (2015) and decreased to 1212 (25 % reduction) in Scenario A, 619 (62 % reduction) in Scenario B, and 50 (97 % reduction) in Scenario C, with the improvements mainly in small branch rivers. The effects of improved disposal rates were mainly evident in areas with relative high population densities using single-type OWTSs outside of areas with a sewage system, and measures taken in these areas were shown to be effective.

Monitoring spatiotemporal changes of NO2 using TROPOMI and sentinel-5 images for Dhaka city and its surrounding areas of Bangladesh

Introduction: Discernable air pollution occurs in most developing countries due to rapid urbanization which can be parameterized by air, humidity, population density, temperature, contaminants, exorbitant fossil fuel consumption, and inadequate transportation. Nitrogen dioxide (NO2), one of the most widely recognized air pollutants, has a detrimental impact on human health explicitly or implicitly and considerably influences on atmospheric composition.
 Materials and methods: In this study, NO2 intensity was analyzed from 2018 with aiming to monitor spatiotemporal changes in Dhaka and its surrounding areas with the Tropospheric Monitoring Instrument (TROPOMI) sensor data. Copernicus Sentinel-5 Precursor satellite data was used in the Google Earth Engine platform to get the result.
 Results: The results revealed a strong relationship (R2 =0.9478) between the NO2 concentration and high population density and the temporal variation is higher during the pre-monsoon than throughout the post-monsoon. The reason behind is the lack of sunlight and the difficulty to break down the NO2, which causes the removal of NO2 from the atmosphere to proceed more slowly. In contrast, Land Use and Land Cover (LULC) are also impacted by the high concentration which is remains in the built-up area.
 Conclusion: This research mainly considered that how NO2 concentration measured from satellite images with temporal variation within a year and what factors strongly influence raising NO2 levels. This model can be used for policy-making to take proper initiatives to reduce NO2 concentrations. The result showed significant uses of TROPOMI with relating population density and LULC in Dhaka and its surrounding areas of Bangladesh.

Phenological mismatch affects individual fitness and population growth in the winter moth.

Climate change can severely impact species that depend on temporary resources by inducing phenological mismatches between consumer and resource seasonal timing. In the winter moth, warmer winters caused eggs to hatch before their food source, young oak leaves, became available. This phenological mismatch changed the selection on the temperature sensitivity of egg development rate. However, we know little about the fine-scale fitness consequences of phenological mismatch at the individual level and how this mismatch affects population dynamics in the winter moth. To determine the fitness consequences of mistimed egg hatching relative to timing of oak budburst, we quantified survival and pupation weight in a feeding experiment. We found that mismatch greatly increased mortality rates of freshly hatched caterpillars, as well as affecting caterpillar growth and development time. We then investigated whether these individual fitness consequences have population-level impacts by estimating the effect of phenological mismatch on population dynamics, using our long-term data (1994-2021) on relative winter moth population densities at four locations in The Netherlands. We found a significant effect of mismatch on population density with higher population growth rates in years with a smaller phenological mismatch. Our results indicate that climate change-induced phenological mismatch can incur severe individual fitness consequences that can impact population density in the wild.

Habitat quality affects the social organization in mouse lemurs (Microcebus griseorufus)

Species can either maintain a certain social organization in different habitats or show different social organizations in similar habitats. The reasons underlying this variability are not always clear but might have consequences for population dynamics, especially under changing environmental conditions. Among mammals, the primate genus Microcebus lives in small groups of closely related females, derived from female philopatry and dispersed males, as illustrated by the well-studied Microcebus murinus. Here, we studied the genetic structure of a population of the congeneric Microcebus griseorufus, inhabiting three adjacent habitats with different resource availabilities. In order to learn more about the plasticity of the species’ social organization under these different conditions, we analyzed the spatial arrangement of mitochondrial haplotypes of 122 individuals. The study revealed high haplotype diversity and a pronounced difference in spatial distribution between the sexes. Females exhibited spatial aggregation of haplotypes, suggesting a system of female philopatry and matrilines, similar to M. murinus. Male haplotypes were dispersed, and males were more likely to carry rare haplotypes, indicating higher dispersal activity. These findings hint towards the unity of the social organization across the genus Microcebus, suggesting a phylogenetic origin of the social organization. Yet, with decreasing resources, the clustering of female haplotypes declined and approached a random distribution in the marginal habitat, with cluster sizes correlating with resource availability as predicted by the socioecological model. Our study supports the notion that social organization is shaped by both phylogenetic origin and ecological conditions, at least in these small primates.Significance statementImpacts of habitat degradation are mostly described in terms of changes in population densities in relation to the reduction of resources. This neglects the possible effects of altered social organizations due to declining resources or population densities. Using a genetic sampling of three subpopulations of mouse lemurs in Madagascar along a gradient of food availability up to the limit of the species’ ecological tolerance, we show that their social organization consisting of spatial clusters of closely related females and overdispersed males converges towards random spatial distributions of both sexes with declining food availability.

Quantifying the human cost of global warming

AbstractThe costs of climate change are often estimated in monetary terms, but this raises ethical issues. Here we express them in terms of numbers of people left outside the ‘human climate niche’—defined as the historically highly conserved distribution of relative human population density with respect to mean annual temperature. We show that climate change has already put ~9% of people (>600 million) outside this niche. By end-of-century (2080–2100), current policies leading to around 2.7 °C global warming could leave one-third (22–39%) of people outside the niche. Reducing global warming from 2.7 to 1.5 °C results in a ~5-fold decrease in the population exposed to unprecedented heat (mean annual temperature ≥29 °C). The lifetime emissions of ~3.5 global average citizens today (or ~1.2 average US citizens) expose one future person to unprecedented heat by end-of-century. That person comes from a place where emissions today are around half of the global average. These results highlight the need for more decisive policy action to limit the human costs and inequities of climate change.

Upaya Meningkatkan Aktivitas dan Hasil Belajar Siswa pada Mata Pelajaran IPA dengan Materi Pokok Manusia dan Lingkungan Menggunakan Metode Berjubel (Belajar dengan Bermain Jual Beli) pada Siswa Kelas VII SMP Negeri 21 Mataram

The purpose of this study was to determine the increase in the activity and learning outcomes of science on the subject of Population Density in relation to the Environment and the material on Pollution and Environmental Damage in relation to human activity for class VII students of SMP Negeri 21 Mataram in the Academic Year 2022/2023 through the use of the Judgment method. This research was conducted at SMP Negeri 21 Mataram in the 2022/2023 academic year with research subjects being class VII students consisting of 14 male students and 14 female students. The method used is the Classroom Action Research method which consists of two cycles. In the first cycle, learning was carried out using the Jubel method in large groups, while in the second cycle, the Jubel method was used in small groups. In each cycle consists of four stages of research namely planning, implementation of action, observation, and reflection. The research data were analyzed using a comparative descriptive followed by reflection. Comparative descriptive is done by comparing the initial condition data, cycle 1 and cycle 2, both for learning activities and learning outcomes. The results of this study indicate that: First, the use of the Jubilee method can increase science learning activities on population density in relation to the environment and environmental pollution and damage in relation to human activity for class VII students of SMP Negeri 21 Mataram semester of the 2022/2023 academic year. It is proven that the percentage of students in the good learning activity category increased from the initial conditions of 29% to 64% in cycle I and to 82% in cycle II or in the final conditions there was an increase of 51% from the initial conditions. Second, the use of the Jubilee method can improve science learning outcomes on population density in relation to the environment and environmental pollution and damage in relation to human activity for class VII students at SMP Negeri 21 Mataram in the 2022/2023 academic year. It is proven that the percentage of student learning completeness increased from the initial conditions of 57% to 64% in cycle I and to 74% in cycle II or in the final conditions an increase of 17% from the initial conditions.

Динамика численности и демография красной (Clethrionomys rutilus) и красно-серой (Craseomys rufocanus) полевок в лиственничном редколесье Северного Приохотья

The article presents the results of 13-year (2010-2022) studies of the dynamics of the red-backed and grey red-backed vole number in the sparse larch forest of the Northern Priokhotye. The author describes сyclicism in population fluctuations and variability of demographic indicators of populations. The relationship of population density with external and intrapopulation factors is analyzed. The results of the study have been compared with similar data from other parts of the area.

Camera-trapping estimates of the relative population density of Sympetrum dragonflies: application to multihabitat users in agricultural landscapes.

Although camera trapping has been effectively used for wildlife monitoring, its application to multihabitat insects (i.e., insects requiring terrestrial and aquatic ecosystems) is limited. Among such insects, perching dragonflies of the genus Sympetrum (darter dragonflies) are agroenvironmental indicators that substantially contribute to agricultural biodiversity. To examine whether custom-developed camera traps for perching dragonflies can be used to assess the relative population density of darter dragonflies, camera trapping, a line-transect survey of mature adult dragonflies, and a line-transect survey of exuviae were conducted for three years in rice paddy fields in Japan. The detection frequency of camera traps in autumn was significantly correlated with the density index of mature adults recorded during the transect surveys in the same season for both Sympetrum infuscatum and other darter species. In analyses of camera-detection frequency in autumn and exuviae in early summer, a significant correlation was observed between the camera-detection frequency of mature adults and the exuviae-density index in the following year for S. infuscatum; however, a similar correlation was not observed for other darter species. These results suggest that terrestrial camera trapping has the potential to be effective for monitoring the relative density of multihabitat users such as S. infuscatum, which shows frequent perching behavior and relatively short-distance dispersal.

Investigation of the biological diversity of Trichoptera larvae in the streams of the Kastamonu (Cide)-Sinop (Ayancık) coastal region of Türkiye

This study was carried out to determine the biodiversity and densities of Trichoptera larvae at stations in the Kastamonu (Cide)-Sinop (Ayanc?k) coastal region. Benthic macroinvertebrate samples were collected from each of the 19 stations using the kick-net sampling method with a D-frame net (500-?m mesh). Using the data from collected Trichoptera larvae, the similarity, diversity, dominance and population density relationships among habitats were measured. According to the calculated Shannon-Wiener and Simpson diversity index results, the station with the highest Trichoptera diversity was determined at S2, and the station with the least diversity was S14. Similar results were obtained for the calculated population density values. Station S2 was the most balanced station in population density. Thus, biodiversity was directly related to habitat structure, anthropogenic impact and geographical conditions, and environmental factors suppress biological species diversity. It was concluded that species diversity is greater in undestroyed habitats and less in heavily destroyed habitats. In addition, the species that dominate in biodiversity similarity rates prefer their habitat.

Microplastics in surface water of Laguna de Bay: first documented evidence on the largest lake in the Philippines.

The pollution of aquatic systems by microplastics is a well-known environmental problem. However, limited studies have been conducted in freshwater systems, especially in the Philippines. Here, we determined for the first time the amount of microplastics in the Philippines' largest freshwater lake, the Laguna de Bay. Ten (10) sampling stations on the lake's surface water were sampled using a plankton net. Samples were extracted and analyzed using Fourier-transform infrared spectroscopy (FTIR). A total of 100 microplastics were identified from 10 sites with a mean density of 14.29items/m3. Most microplastics were fibers (57%), while blue-colored microplastics predominated in the sampling areas (53%). There were 11 microplastic polymers identified, predominantly polypropylene (PP), ethylene vinyl acetate copolymer (EVA), and polyethylene terephthalate (PET), which together account for 65% of the total microplastics in the areas. The results show that there is a higher microplastic density in areas with high relative population density, which necessitates implementing proper plastic waste management measures in the communities operating on the lake and in its vicinity to protect the lake's ecosystem services. Furthermore, future research should also focus on the environmental risks posed by these microplastics, especially on the fisheries and aquatic resources.