The Dimensions and Units of the Population Interaction Coefficients

We discuss the interpretation and dimensions of the population dynamic parameters that are commonly used to quantify the strength of intraspecific and interspecific interactions. The concept of “interaction strength” is not unequivocal. Its theoretical formalization relies on the generalized Lotka–Volterra model. However, four different ways of parameterizing the model have been proposed in the literature, leading to four different definitions of the term “interaction strength.” In particular, the dimensions of these four definitions are not identical, some of these incorporating explicitly the dimension used to measure the population size. Using an individual-based simulation model as an illustration, we show that, in the latter case, the interaction strength depends implicitly on the habitat size. As a consequence, it is of crucial importance to quantify the population as a density rather than an absolute population abundance. We insist that the dimension of the interaction strength coefficient should not be overlooked and any quantitative estimation must be given with explicit units.

How to Count Bugs: A Method to Estimate the Most Probable Absolute Population Density and Its Statistical Bounds from a Single Trap Catch

Knowledge of insect population density is crucial for establishing management and conservation tactics and evaluating treatment efficacies. Here, we propose a simple and universal method for estimating the most probable absolute population density and its statistical bounds. The method is based on a novel relationship between experimentally measurable characteristics of insect trap systems and the probability to catch an insect located a given distance away from the trap. The generality of the proposed relationship is tested using 10 distinct trapping datasets collected for insects from 5 different orders and using major trapping methods, i.e., chemical-baited traps and light. For all datasets, the relationship faithfully (R=0.91) describes the experiment. The proposed approach will take insect detection and monitoring to a new, rigorously quantitative level. It will improve conservation and management, while driving future basic and applied research in population and chemical ecology.

Global and country-level estimates of human population at high altitude

Estimates of the global population of humans living at high altitude vary widely, and such data at the country level are unavailable. Herein, we use a geographic information system (GIS)-based approach to quantify human population at 500-m elevation intervals for each country. Based on georeferenced data for population (LandScan Global 2019) and elevation (Global Multiresolution Terrain Elevation Data), 500.3 million humans live at ≥1,500 m, 81.6 million at ≥2,500 m, and 14.4 million at ≥3,500 m. Ethiopia has the largest absolute population at ≥1,500 m and ≥2,500 m, while China has the greatest at ≥3,500 m. Lesotho has the greatest percentage of its population above 1,500 m, while Bolivia has the greatest at ≥2,500 m and ≥3,500 m. High altitude presents a myriad of environmental stresses that provoke physiological responses and adaptation, and consequently impact disease prevalence and severity. While the majority of high-altitude physiology research is based upon lowlanders from western, educated, industrialized, rich, and democratic countries ascending to high altitude, the global population distribution of high-altitude residents encourages an increased emphasis on understanding high-altitude physiology, adaptation, epidemiology, and public health in the ∼500 million permanent high-altitude residents.

Absolute Population Estimates Using Capture–Recapture Experiments

The main methods used to estimate population size using capture–recapture for both closed and open populations are described, including the Peterson–Lincoln estimator, the Schabel census, Bailey’s triple catch, the Jolly–Seber stochastic method, and Cormack’s log-linear method. The robust design approach is described. R code listings for commonly used packages are presented. The assumptions common to capture–recapture methods are reviewed, and tests for assumptions such as equal catchability described. The use of programs to select model assumptions are described. The main methods for marking different animal groups are described, together with the use of natural marks and parasites and DNA. Marking methods include paint marks, dyes, tagging, protein marking, DNA, natural marks, tattooing, and mutilation. Methods for handling and release are described.

Absolute Population Estimates by Sampling a Unit of Habitat: Air, Plants, Plant Products, and Vertebrate Hosts

Suction and other samplers for aerial insects and other invertebrates, such as the exposed-cone Johnson–Taylor trap, are described, and their efficiencies under different meteorological conditions defined. Techniques for sampling small animals from plants are described, including the use of suction apparatus such as the D-Vac and Vectis for grassland sampling. Specialized methods for counting insects within plant tissues are described, and techniques for sampling parasites from their vertebrate hosts and homes are reviewed.

Absolute Population Estimates by Sampling a Unit of Aquatic Habitat

Methods for quantitative sampling of open marine and freshwaters are described, including fishing nets, plankton nets, pump samplers, the Patalas–Schindler volume sampler, and specialized methods for freshwater insects. Specialist methods for sampling freshwater floating, emergent, and submerged vegetation are described. Methods for quantitatively sampling the bottom fauna in the various substrates found in streams, rivers, lakes, and the sea bed are reviewed. The use of various poisons and anaesthetics for sampling fish are described.

Absolute Population Estimates by Sampling a Unit of Soil or Litter Habitat: Extraction Techniques

Quantitative methods for taking sediment, soil, and litter samples, together with the different approaches and apparatus to extract the animals, are described. Mechanical methods discussed include wet and dry sieving, flotation, and elutriation. Behavioural or dynamic methods such as Berlese and Baermann funnels are described. Chemical and electrical methods to drive animals from cover are described, and the efficiency of the different extraction techniques is reviewed.

Epidemiological overview of epilepsy by Brazilian macro-regions

Introdution: Studying the epidemiology of epilepsy is important for the knowledge of this disease in the national territory, and also to improve the Public System. Objectives: Describe the epidemiological profile of epilepsy in Brazilian regions between 2010 and 2019. Methods: Refers to an ecological study with secondary data from the Ministry of Health, through DATASUS. The period investigated was from January 2010 to December 2019, in Brazilian regions. The variables explored were region, sex, number of hospitalizations, average length of stay and mortality rate. Results: 507,443 hospitalizations were identified, with the highest numbers of cases being in the Southeast (44.34%) and the lowest in the North (5.43%). There was a predominance of hospitalizations in males (58%).The mortality rate varied between 2.97 (Northeast) and 1.44 (South). Southeast had the longest stay (6.8 days) and the shortest was in the South (4.4 days). Conclusions: After analyzing this study, males have the highest rate of hospitalization and the Southeast has the highest number of hospitalizations and average length of stay for epilepsy, which may be associated with the fact that this region has the largest absolute population. Although, the Northeast had the highest mortality rate, a situation possibly related to a lower integration of the health system compared to the other regions.

Population of the north Caucasus in the present stage: indicators of regional differentiation

Based on the collected statistical material, the analysis of population changes in the North Caucasus regions since the last allRussian population census until 2018 was conducted. The article considers the main factors of the current population reproduction, and trends in the dynamics of the population in the North Caucasus were set. Based on the obtained data, the subjects of the North Caucasus are divided into two categories. The first are Russian-speaking regions where the absolute population growth is observed due to a positive migration balance that covers the natural decline of the population. The other category includes mainly national republics with a high natural growth that covers a significant migration outflow of the population. Despite the favorable demographic situation in the region under study, there is a trend towards the end of the demographic boom that is typical of the entire North Caucasus region. In general, there is a stabilization of the birth rate and natural growth, and a decrease in the intensity of migration movements.

Clash of the pandemics – At least 150’000 adults in Switzerland suffer from obesity grades 2 or 3 and are thus at elevated risk for severe COVID-19

Background: Grade 2 and 3 obesity, alongside with other relevant risk factors, are substantially and independently associated with adverse outcomes of coronavirus disease 2019 (COVID-19). However, for Switzerland, due to the lack of synthesis studies, it is currently unknown how many people are affected by obesity at all. This knowledge may help to better estimate the relevance and size of this group at elevated risk, which could be incorporated into strategies to protect risk groups during the still unfolding COVID-19 pandemic. This study aimed to provide a first overall estimation of how many people in Switzerland are currently affected by grade 2 or 3 obesity. Methods: Five representative national population-based studies were accessed which were conducted between 2012 and 2017 and which include data on height and weight of adult men and women in Switzerland. Results: In Switzerland in 2012-2017, among the 11.20% adults who were obese (body mass index (BMI) ≥30.0kg/m2), 1.76% (95% CI 1.50-2.02) suffered from grade 2 obesity (BMI 35.0-39.9 kg/m2), and 0.58% (95% CI 0.50-0.66) from grade severe 3 obesity (BMI ≥40.0 kg/m2). Converted into estimated absolute population numbers, this corresponds to a total of approximately n=154,515 people who suffer from grade 2 or 3 obesity (n=116,216 and n=38,298, respectively). Conclusions: This risk group includes many younger people in Switzerland. The number of people with obesity-related risk becomes 3.8 to 13.6 times higher if grade 1 obesity and overweight people are also included in this risk group, for which there are arguments arising in the latest literature. In general, this large group at risk for severe COVID-19 should be given more attention and support. If it is confirmed that obesity plays a major role in severe COVID-19 courses, then every kilo of body weight that is not gained or that is lost in lockdown counts.