Accurately demarcating distributions of biological taxa has long been at the core of ecology. Yet our understanding of the factors defining species range limits is incomplete, especially for tropical species in the Global South. Human-driven threats to the survival of many taxa are increasing, particularly habitat loss and climate change. Identifying distributional range limits of at-risk and data-limited species using Species Distribution Models (SDMs) can thus inform spatial conservation planning to mitigate these threats. The Madagascar Peregrine Falcon Falco peregrinus radama is the resident sub-species of the Peregrine Falcon complex distributed across Madagascar, Mayotte, and the Comoros Islands. There are currently significant knowledge gaps regarding its distribution, habitat preferences, and population size. Here, we use penalized logistic regression and environmental ordination to identify Madagascar Peregrine Falcon habitat in both geographic and environmental space and propose a population size estimate based on inferred habitat. From the penalized logistic regression model, the core habitat area of the Madagascar Peregrine Falcon extends across the central and northern upland plateau of Madagascar with patchier habitat across coastal and low-elevation areas. Range-wide habitat use in both geographic and environmental space indicated positive associations with high elevation and aridity, coupled with high vegetation heterogeneity and >95% herbaceous landcover, but general avoidance of areas >30% cultivated land and >10% mosaic forest. Based on inferred high-class habitat from the penalized logistic regression model, we estimate this habitat area could potentially support a population size ranging between 150 and 300 pairs. Following IUCN Red List guidelines, this subspecies would be classed as ‘Vulnerable’ due to its small population size. Despite its potentially large range, the Madagascar Peregrine Falcon has specialised habitat requirements and would benefit from targeted conservation measures based on spatial models to maintain viable populations.

The Vulnerable marsh deer Blastocerus dichotomus, the largest native cervid in South America, is declining throughout its range as a result of the conversion of wetlands and overhunting. Estimated densities in open wetlands of several types are 0.1–6.8 individuals per km2. We undertook the first unmanned aerial vehicle (UAV) survey of the marsh deer to estimate the density of this species in a 113.6 km2 area under forestry management in the lower delta of the Paraná River, Argentina. During 6–8 August 2019, at a time of year when canopy cover is minimal, we surveyed marsh deer using Phantom 4 Pro UAVs along 94 transects totalling 127.8 km and 8.6 km2 (8.1% of the study area). The 5,506 photographs obtained were manually checked by us and by a group of 39 trained volunteers, following a standardized protocol. We detected a total of 58 marsh deer, giving an estimated density of 6.90 individuals per km2 (95% CI 5.26–8.54), which extrapolates to 559–908 individuals in our 113.6 km2 study area. As it has generally been assumed that marsh deer prefer open habitats, this relatively high estimate of density within a forestry plantation matrix is unexpected. We discuss the advantages of using UAVs to survey marsh deer and other related ungulates.

Habitat loss and fragmentation are major threats to primate populations globally. The Endangered golden monkey Cercopithecus mitis kandti is only found in two small forest fragments: the Virunga massif in Rwanda, Uganda and the Democratic Republic of the Congo, and the Gishwati Forest in Rwanda. Little is known about the abundance and distribution of this subspecies, or threats to its survival. During 2007–2018, we collected data along 893.7 km of line transects and 354.2 km of recce trails in Volcanoes National Park and in Gishwati–Mukura National Park to estimate golden monkey density and examine any threats. In Volcanoes National Park, golden monkeys were found almost exclusively in the bamboo zone, and in Gishwati–Mukura National Park they occurred only in the remnant tropical montane Gishwati Forest. In Volcanoes National Park, density was estimated to be 7.89 (95% CI: 3.85–16.19), 5.41 (2.64–11.08), and 5.47 (3.68–8.14) groups per km2 in 2007, 2011 and 2017–2018, respectively. This corresponds to a total of 4,331 individuals (95% CI: 2,723–5,938) in 2007, 4,487 (2,903–6,071) in 2011 and 4,626 (4,165–5,088) in 2017–2018. In Gishwati Forest, group density averaged 1.98 (95% CI: 1.27–3.16) per km2, corresponding to 172 (95% CI: 154–190) individuals in 2017–2018. Survey results from Volcanoes National Park suggest that the golden monkey population has been stable during 2007–2018. Limited habitat, illegal activities such as harvesting of bamboo and firewood, and the presence of feral dogs, threaten the golden monkey in Rwanda and require continued monitoring. The development of a conservation action plan is a priority to protect this species.

Most research on attitudes towards immigrants and immigration problematically conflates the documented and the undocumented. Previous studies also largely ignore the autonomous role of population density. Based on data drawn from two nationally representative surveys, this paper focuses on contemporary American attitudes towards undocumented immigration and immigrants. Contra the dominant view, we find that education and income have no effect. More important, population density, measured at the county level, significantly predicts favorable attitudes, controlling for factors often erroneously conflated with density: race, income, education, political affiliation, age, gender, and interaction with immigrants. In fact, interaction tends to decrease favorable attitudes. We explain these findings by proposing a novel account of cosmopolitanism, using favorable attitudes towards undocumented immigrants and immigration as an empirical indicator. Those who live in places with higher density are more used to see and be seen in everyday life by countless people with whom they share the same spaces without necessarily interacting with them. As a result, they are more likely to consider all them, including undocumented immigrants, in a superficial yet egalitarian way as generalized others to be ignored. It is this tolerance based on general indifference that is the basis of cosmopolitanism.

The leopard Panthera pardus is in range-wide decline, and many populations are highly threatened. Prey depletion is a major cause of global carnivore declines, but the response of leopard survival and density to this threat is unclear: by reducing the density of a dominant competitor (the lion Panthera leo) prey depletion could create both costs and benefits for subordinate competitors. We used capture–recapture models fitted to data from a 7-year camera-trap study in Kafue National Park, Zambia, to obtain baseline estimates of leopard population density and sex-specific apparent survival rates. Kafue is affected by prey depletion, and densities of large herbivores preferred by lions have declined more than the densities of smaller herbivores preferred by leopards. Lion density is consequently low. Estimates of leopard density were comparable to ecosystems with more intensive protection and favourable prey densities. However, our study site is located in an area with good ecological conditions and high levels of protection relative to other portions of the ecosystem, so extrapolating our estimates across the Park or into adjacent Game Management Areas would not be valid. Our results show that leopard density and survival within north-central Kafue remain good despite prey depletion, perhaps because (1) prey depletion has had weaker effects on preferred leopard prey compared to larger prey preferred by lions, and (2) the density of dominant competitors is consequently low. Our results show that the effects of prey depletion can be more complex than uniform decline of all large carnivore species, and warrant further investigation.

Although vaccines have become available, emergence and rapid transmission of new variants have added new paradigm in the coronavirus disease-2019 (COVID-19) pandemic. Weather, population and host immunity have been detected as the regulatory elements of COVID-19. This study aims to investigate the effects of weather, population and host factors on the outcome of COVID-19 and mutation frequency in Japan. Data were collected during January 2020 to February 2021. About 92% isolates were form GR clades. Variants 501Y.V1 (53%) and 452R.V1 (24%) were most prevalent in Japan. The strongest correlation was detected between fatalities and population density (rs = 0.81) followed by total population (rs = 0.72). Relative humidity had the highest correlation (rs = −0.71) with the case fatality rate. Cluster mutations namely N501Y (45%), E484K (30%), N439K (16%), K417N (6%) and T478I (3%) at spike protein have increased during January to February 2021. Above 90% fatality was detected in patients aged >60 years. The ratio of male to female patients of COVID-19 was 1.35:1. This study will help to understand the seasonality of COVID-19 and impact of weather on the outcome which will add knowledge to reduce the health burden of COVID-19 by the international organisations and policy makers.

Coronavirus disease-2019 (COVID-19) has caused the recent pandemic worldwide. Research studies are focused on various factors affecting the pandemic to find effective vaccine or therapeutics against COVID-19. Environmental factors are the important regulators of COVID-19 pandemic. This study aims to determine the impact of weather on the COVID-19 cases, fatalities and frequency of mutations in Bangladesh. The impacts were determined on 1, 7 and 14 days of the case. The study was conducted based on Spearman's correlation coefficients. The highest correlation was found between population density and cases (rs = 0.712). Among metrological parameters, average temperature had the strongest correlation (rs = −0.675) with the cases. About 82% of Bangladeshi isolates had D614G at spike protein. Both temperature and UV index had strong effects on the frequency of mutations. Among host factors, coinfection is highly associated with frequency of different mutations. This study will give a complete picture of the effects of metrological parameters on COVID-19 cases, fatalities and mutation frequency that will help the authorities to take proper decisions.

The peoples of southern Mesoamerica, including the Classic period Maya, are often claimed to exhibit a distinct type of spatial organization relative to contemporary urban systems. Here, we use the settlement scaling framework and properties of settlements recorded in systematic, full-coverage surveys to examine ways in which southern Mesoamerican settlement systems were both similar to and different from contemporary systems. We find that the population-area relationship in these settlements differs greatly from that reported for other agrarian settlement systems, but that more typical patterns emerge when one considers a site epicenter as the relevant social interaction area, and the population administered from a given center as the relevant interacting population. Our results imply that southern Mesoamerican populations mixed socially at a slower temporal rhythm than is typical of contemporary systems. Residential locations reflected the need to balance energetic and transport costs of farming with lower-frequency costs of commuting to central places. Nevertheless, increasing returns in activities such as civic construction were still realized through lower-frequency social mixing. These findings suggest that the primary difference between low-density urbanism and contemporary urban systems lies in the spatial and temporal rhythms of social mixing.