High Human Population Density Research Articles

Ensembling machine learning models to identify forest fire-susceptible zones in Northeast India

Forest fires pose significant challenges by disrupting ecological balance, impacting socio-economic harmony, and raising global concerns. North-East India (NEI) experiences high incidences of forest fires, making it crucial to implement suitable management measures considering the driving forces influencing fire likelihood. This study aims to identify forest fire susceptibility zones in NEI by using five machine-learning modeling approaches, Boosted Regression Tree (BRT), Random Forest (RF), Support Vector Machine (SVM), Classification and Regression Tree (CART), and Multivariate Adaptive Regression Splines (MARS), and an ensemble method. Forest fire data from the SNPP – VIIRS sensor (2018–2019) were rectified for spatial autocorrelation. Thirty-two responsive predictor variables related to topographic, climatic, biophysical, and anthropogenic factors were used as model inputs and multicollinearity analysis was performed to eliminate highly correlated predictors. Results indicate that the southern and southeastern regions of NEI, characterized by ample solar radiation, enhanced vegetation index, high human population density, and jhum cultivation, contribute significantly to higher susceptibility to forest fires. The Random Forest model performs best among the models employed, achieving an AUC value of 0.87. The ensemble susceptibility map, binarized based on AUC weighting, covers 29.54% of the total geographic area and 44.42% of the forested area of NEI. The vulnerability levels vary among states, with Mizoram showing the highest susceptibility at 89.27% and Sikkim exhibiting the lowest vulnerability at only 0.49% of their respective geographic areas. This map provides valuable insights for implementing effective forest fire management plans in the region. Moreover, the methodology utilized in this study, which incorporates satellite imagery, GIS techniques, and improved modeling techniques, can be replicated in any geographical region worldwide to facilitate effective forest fire management at a regional to large scale.

Predicting severe wildlife vehicle crashes (WVCs) on New Hampshire roads using a hybrid generalized additive model

Across the United States, wildlife vehicle crashes (WVCs) are increasing and remain consistently deadly to drivers, despite a downward trend in fatal automobile accidents overall. That said, the factors related to severe WVCs are unclear. With this in mind, we pursued a statistical model to reveal factors associated with WVCs that result in severe injury or death to drivers. We hypothesize that there are statistically significant interactions and non-linear relationships between these factors and severity occurrence. We developed a generalized additive model (GAM) with linear terms, additive terms, and a binary response for severity. We surmise that our fitted model results will quantify the relationship between significant variables and severity occurrence, and ultimately help to develop countermeasures to mitigate serious injury. The model was fitted to WVC records occurring between 2002 and 2019 in the state of New Hampshire. Fitted linear terms revealed: 1) in inclement weather, there is about a 22% increase in the odds of severity for slick surface conditions compared to dry surface conditions; 2) for the warmer months (spring/summer), there is a 42% decrease in the odds of severity for straight roads compared to those with curvature/incline; 3) for highways, the odds of severity decreases by 48% for accidents occurring on NH’s two major intestates highways, and 4) for spring/summer (as compared to the fall/winter), there is more than a 3-fold increase in the odds of severity for two-way traffic. Fitted additive terms revealed: 1) the odds of severity increased in the early hours, between midnight and 6AM, and after 5PM; 2) speeds between 45 and 60 mph are associated with an increase in the odds of a severe accident, while both lower and higher speeds (those below 45 and above 60 mph) are associated with a decrease in the odds of a severe accident; and 3) low, mid-range, and high human population densities are associated with decreases, increases, and decreases in odds of severity, respectively. Cross validation and resulting ROC curves gave evidence that our model is well specified and an effective predictor. Results could be used to inform drivers of potentially dangerous roadways/conditions/times.

Environmental and sociodemographic factors associated with zoonotic pathogen occurrence in Norway rats (Rattus norvegicus) from Windsor, Ontario.

Rat-associated zoonotic pathogen transmission at the human-wildlife interface is a public health concern in urban environments where Norway rats (Rattus norvegicus) thrive on abundant anthropogenic resources and live in close contact with humans and other animal species. To identify potential factors influencing zoonotic pathogen occurrence in rats, we investigated associations between environmental and sociodemographic factors and Leptospira interrogans and Bartonella spp. infections in rats from Windsor, Ontario, Canada, while controlling for the potential confounding effects of animal characteristics (i.e., sexual maturity and body condition). Between November 2018 and June 2021, 252 rats were submitted by collaborating pest control professionals. Kidney and spleen samples were collected for L. interrogans and Bartonella spp. PCR and sequencing, respectively. Of the rats tested by PCR, 12.7% (32/252) were positive for L. interrogans and 16.3% (37/227) were positive for Bartonella species. Associations between infection status and environmental and sociodemographic variables of interest were assessed via mixed multivariable logistic regression models with a random intercept for social group and fixed effects to control for sexual maturity and body condition in each model. The odds of L. interrogans infection were significantly higher in rats from areas with high building density (odds ratio [OR]: 3.76; 95% CI: 1.31-10.79; p = 0.014), high human population density (OR: 3.31; 95% CI: 1.20-9.11; p = 0.021), high proportion of buildings built in 1960 or before (OR: 11.21; 95% CI: 2.06-60.89; p = 0.005), and a moderate number of reports of uncollected garbage compared to a low number of reports (OR: 4.88; 95% CI: 1.01-23.63; p = 0.049). A negative association was observed between median household income and Bartonella spp. infection in rats (OR: 0.26; 95% CI: 0.08-0.89; p = 0.031). Due to the complexity of the ecology of rat-associated zoonoses, consideration of environmental and sociodemographic factors is of critical importance to better understand the nuances of host-pathogen systems and inform how urban rat surveillance and intervention efforts should be distributed within cities.

Human population density and blue carbon stocks in mangroves soils

Mangrove soils provide many important ecosystem services such as carbon sequestration, yet they are vulnerable to the negative impacts brought on by anthropogenic activities. Research in recent decades has shown a progressive loss of blue carbon in mangrove forests as they are converted to aquaculture, agriculture, and urban development. We seek to study the relationship between human population density and soil carbon stocks in urban mangrove forests to quantify their role in the global carbon budget. To this end, we conducted a global analysis, collecting mangrove soil carbon data from previous studies and calculating population density for each study location utilizing a recent database from the European Commission. Results indicate population density has a negative association with mangrove soil carbon stocks. When human population density reaches 300 people km−2, which is defined as ‘urban domains’ in the European Commission database, mangrove soil carbon is estimated to be lower than isolated mangrove forests by 37%. Nonetheless, after accounting for climatic factors in the model, we see the negative relationship between population density and soil carbon is reduced and is even non-significant in mixed effects models. This suggests population density is not a good measure for the direct effects of humans on mangrove ecosystems and further implies mangrove ecosystems in close proximity to very high population density can still possess valuable carbon stocks. Our work provides a better understanding of how soil carbon stocks in existing mangrove forests correlate with different levels of population density, underscores the importance of protecting existing mangroves and especially those in areas with high human population density, and calls for further studies on the association between human activities and mangrove forest carbon stocks.

Mapping the potential distribution of Asian elephants: Implications for conservation and human–elephant conflict mitigation in South and Southeast Asia

Asian elephants play a pivotal role in their ecosystem. Understanding the potential distribution area of this species is vital for effective conservation efforts and mitigation of human-elephant conflicts. In this study, we used the maximum entropy to simulate the potential distribution area of Asian elephants across South and Southeast Asia, leveraging Maximum Entropy (MaxEnt) and presence data sourced from the Global Biodiversity Information Facility (GBIF). The analysis revealed that the potential distribution area of Asian elephants spans 530,418 km2 (10.59% of the study area), with significant potential distribution areas observed in Indonesia (136,890 km2) and Malaysia (119,497 km2). Vegetation type emerged as the dominant environmental factor influencing model outcomes, encompassing aspects such as broadleaved evergreen tree coverage, broadleaved deciduous closed tree coverage and EVI. The potential distribution area of Asian elephants overlaps with regions inhabited by 55.25 million people, with 6.07 million people residing in highly suitable habitats. India and Malaysia have high potential for human-elephant conflict (HEC) due to the high number of people living in potential and highly suitable habitats for elephants. Bangladesh and Nepal, on the other hand, have fewer people living in these habitats suitable for elephants, but they face relatively high human population density in these areas.

Underlying and proximate drivers of biodiversity changes in Mesoamerican biosphere reserves

Protected areas are of paramount relevance to conserving wildlife and ecosystem contributions to people. Yet, their conservation success is increasingly threatened by human activities including habitat loss, climate change, pollution, and species overexploitation. Thus, understanding the underlying and proximate drivers of anthropogenic threats is urgently needed to improve protected areas' effectiveness, especially in the biodiversity-rich tropics. We addressed this issue by analyzing expert-provided data on long-term biodiversity change (last three decades) over 14 biosphere reserves from the Mesoamerican Biodiversity Hotspot. Using multivariate analyses and structural equation modeling, we tested the influence of major socioeconomic drivers (demographic, economic, and political factors), spatial indicators of human activities (agriculture expansion and road extension), and forest landscape modifications (forest loss and isolation) as drivers of biodiversity change. We uncovered a significant proliferation of disturbance-tolerant guilds and the loss or decline of disturbance-sensitive guilds within reserves causing a "winner and loser" species replacement over time. Guild change was directly related to forest spatial changes promoted by the expansion of agriculture and roads within reserves. High human population density and low nonfarming occupation were identified as the main underlying drivers of biodiversity change. Our findings suggest that to mitigate anthropogenic threats to biodiversity within biosphere reserves, fostering human population well-being via sustainable, nonfarming livelihood opportunities around reserves is imperative.

The fear factor—Snakes in Africa might be at an alarming extinction risk

AbstractSnakes in Africa are responsible for over 20,000 deaths annually, their indiscriminate killing. As a result, snakes are vulnerable to human population increases even at low intensities. Thus, the predicted doubling of Africa's population by 2050 is likely to pose a disproportionate threat to snakes compared to other taxa. Here we quantify the current and future overlap of snake distributions and human population density under three scenarios of population growth. We find that by 2050, on average, 71% of snake ranges of conservation concern will overlap with areas occupied by ten or more people per km2, a 22% increase from 2020. In addition, the number of Least Concern species with most of their range within areas with high human population density will more than double, likely increasing the number of threatened species over the next decades. Our results call for immediate policy action targeting people's perceptions and fears of snakes, and incorporating snakes directly into development and conservation plans to reduce the impact of future urban expansions across Africa.

Environmental Health Assessment of the Northwest Portuguese Coast—Biochemical Biomarker Responses in the Marine Gastropod Phorcus lineatus

Coastal areas are frequently impacted by anthropogenic pollution, due to intense human activity in these zones. Our study aimed to monitor the impacts of anthropogenic pollution in four Portuguese locations on the northwest coast, and to identify the most affected areas and/or seasons by applying a multi-biomarker approach. Water and specimens of Phorcus lineatus were collected on the rocky shore during low tide in four sites along the northwest Portuguese coast (1. Amorosa; 2. Cabo do Mundo; 3. Homem do Leme; 4. S. Félix da Marinha) with different anthropogenic pressures, including an industrial maritime shipyard; an oil refinery; an international airport; and an area with high human population density. The collection took place over two seasons: the summer of 2021 and the winter of 2022. Several biochemical biomarkers, including reactive oxygen species; protein carbonyl content; lipid peroxidation (LPO); carboxylesterase (CE); and antioxidant (superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), and neurotoxicity—acetylcholinesterase (AChE)) enzymes were measured. The results showed seasonal variation, with the ROS, LPO, CE, and GST activities depending particularly on the season, but the SOD and CAT activities being similar between summer and winter. CAT showed lower activity in Site 1 than in the other sites during both seasons (p < 0.05). The Integrated Biomarker Response (IBR) index showed that biomarker responses were higher in winter. The multivariate analysis confirmed the higher contribution of the factor season to the P. lineatus’ response to pollutants, compared to the spatial variation in the northwest Portuguese coast. Overall, this study shows that P. lineatus can be a suitable bioindicator species for environmental biomonitoring, and that the IBR index allows the identification of temporal contamination patterns.

Integrating global microbiome data into antibiotic resistance assessment in large rivers

Rivers are important in spreading antimicrobial resistance (AMR). Assessing AMR risk in large rivers is challenged by large spatial scale and numerous contamination sources. Integrating river resistome data into a global framework may help addressing this difficulty. Here, we conducted an omics-based assessment of AMR in a large river (i.e. the Pearl River in China) with global microbiome data. Results showed that antibiotic resistome in river water and sediment was more diversified than that in other rivers, with contamination levels in some river reaches higher than global baselines. Discharge of WWTP effluent and landfill waste drove AMR prevalence in the river, and the resistome level was highly associated with human and animal sources. Detection of 54 risk rank I ARGs and emerging mobilizable mcr and tet(X) highlighted AMR risk in the river reaches with high human population density and livestock pollution. Florfenicol-resistant floR therein deserved priority concerns due to its high detection frequency, dissimilar phylogenetic distance, mobilizable potential, and presence in multiple pathogens. Co-sharing of ARGs across taxonomic ranks implied their transfer potentials in the community. By comparing with global genomic data, we found that Burkholderiaceae, Enterobacteriaceae, Moraxellaceae and Pseudomonadaceae were important potential ARG-carrying bacteria in the river, and WHO priority carbapenem-resistant Enterobacteriaceae, A. baumannii and P. aeruginosa should be included in future surveillance. Collectively, the findings from this study provide an omics-benchmarked assessment strategy for public risk associated with AMR in large rivers.

The fate of nitrogen in the Zarin-Gol River receiving trout farm effluent

This study investigated the Zarrin-Gol River ecosystem in Iran to trace organic matter in the food web and evaluate the impact of aquaculture farm effluent using stable isotopes of nitrogen (δ15N) and carbon (δ13C). Using a previously-developed model (Islam 2005), we estimated that a trout farm in the vicinity released 1.4 tons of nitrogen into the river. This was comparable to an estimated total nutrient load of 2.1 tons of nitrogen for the six-month fish-rearing period based on a web-based constituent load estimator (LOADEST). A model estimate of river nitrogen concentration at the time of minimum river discharge (100 L/s) was 2.74 mg/L. Despite relatively high nitrogen loading from the farm, isotope data showed typical food web structure. Several biological groups had elevated δ13C or δ15N values, but there was limited evidence for the entry of organic matter from the trout farm into the food web, with sites above and below trout farms having inconsistent patterns in 15N enrichment. By coupling nitrogen load modeling with stable isotope analysis we showed that stable isotopes might not be effective tracers of organic matter into food webs, depending on surrounding land use and other point sources of nutrients. The Zarrin-Gol River ecosystem, like other basins with high human population density, remains vulnerable to eutrophication in part due to trout farm effluent.

Threats to aquatic biodiversity and possible management strategies in Lake Victoria

AbstractLake Victoria is the second‐largest freshwater lake in the world, with a surface area of 68,800 km2. The lake is rich in natural resources that are essential to the local economy and livelihoods. However, International Union for Conservation of Nature (IUCN) ranks 76% of freshwater species endemic to the Lake Victoria Basin as threatened with extinction. The biodiversity richness of the lake is still diminishing, and the risk of species extinction is increasing. Many species are yet to be identified, and thus the number of species threatened with extinction exceeds what is currently known. Furthermore, the lake is home to species that are found nowhere else on the planet, but its protection is never given the attention it needs. Genetic diversity loss is harmful to future populations and influences sustainability of the ecosystem. The decline in Lake Victoria's biodiversity is primarily attributed to various pressing issues, including water pollution, invasive species, climate change, overexploitation and the challenges stemming from high human population density. These problems are exacerbated by inadequate regulatory enforcement and a lack of comprehensive data and information to inform and guide conservation efforts. If these factors are not addressed, they may have a detrimental impact on Lake Biodiversity. This article aims to document the main threats to aquatic biodiversity as well as potential management strategies for preventing further losses of the aquatic biodiversity in Lake Victoria. The study recommends reviewing, bolstering and reinforcing the rules and regulations governing the extraction, accessibility and discharge of nutrients into the lake. The national governments should work with local governments, non‐governmental organizations and local people to safeguard and conserve the lake's biodiversity. The national governments of the riparian nations should also reserve funds each fiscal year specifically for research that would inform effective management measures to prevent further losses of the lake's biodiversity.

Social development and biodiversity conservation synergies for the West African giraffe in a human–wildlife landscape

SummaryThe West African giraffe is restricted to Niger, but historically it inhabited much of the Sudano-Sahelian zone. The population is concentrated in the ‘Giraffe Zone’ (GZ), an unprotected area with a high human population density. Since the mid-1990s, the giraffe population has steadily increased mainly due to the collective social and conservation initiatives of the government, non-governmental organizations and the local community. In 2018, the first West African giraffe satellite population was established through the reintroduction of eight individuals into Gadabedji Biosphere Reserve (GBR). In this study, we aimed to describe the current state of human–giraffe coexistence, human attitudes towards giraffe and human habits of natural resources use through a questionnaire survey conducted in the GZ and GBR. Although most of the GZ respondents highlighted crop damage caused by giraffe, we also found overall positive attitudes towards the animals. Most respondents from both sites expressed positive attitudes towards giraffe, highlighting that they do not see poaching as a major current threat. However, the giraffe population continues to be directly threatened by habitat loss through firewood cutting, livestock overgrazing and agriculture expansion. Long-term conservation of the West African giraffe is dependent on better habitat protection and understanding of current human–giraffe coexistence through ensuring that giraffe presence will benefit local communities across their range.

Spatiotemporal organization of cryptic North American Culex species along an urbanization gradient

Abstract Landscape heterogeneity creates diverse habitat and resources for mosquito vectors of disease. A consequence may be varied distribution and abundance of vector species over space and time dependent on niche requirements. We tested the hypothesis that landscape heterogeneity driven by urbanization influences the distribution and relative abundance of Culex pipiens, Cx. restuans and Cx. quinquefasciatus, three vectors of West Nile virus (WNv) in the eastern North American landscape. We collected 9803 cryptic Culex from urban, suburban and rural sites in metropolitan Washington, District of Columbia, during the months of June–October, 2019–2021. In 2021, we also collected mosquitoes in April and May to measure early season abundance and distribution. Molecular techniques were used to identify a subset of collected Culex to species (n = 2461). Ecological correlates of the spatiotemporal distribution of these cryptic Culex were examined using constrained and unconstrained ordination. Seasonality was not associated with Culex community composition in June–October over 3 years, but introducing April and May data revealed seasonal shifts in community composition in the final year of our study. Culex pipiens were dominant across site types, while Cx. quinquefasciatus were associated with urban environments, and Cx. restuans were associated with rural and suburban sites. All three species rarely coexisted. Our work demonstrates that human‐mediated land‐use changes influence the distribution and relative abundance of Culex vectors of WNv, even on fine geospatial scales. Site classification, per cent impervious surface, distance to city centre and longitude predicted Culex community composition. We documented active Culex months before vector surveillance typically commences in this region, with Culex restuans being most abundant during April and May. Active suppression of Cx. restuans in April and May could reduce early enzootic transmission, delay the seasonal spread of WNv and thereby reduce overall WNv burden. By June, the highest risk of epizootic spillover of WNv to human hosts may be in suburban areas with high human population density and mixed Culex assemblages that can transmit WNv between birds and humans. Focusing management efforts there may further reduce human disease burden.

Landscape-level determinants of butterfly species richness in northern Europe: A country-wide survey reveals the paramount importance of forest land

Human-induced changes in habitat amount and quality constitute the key driver behind negative trends in global biodiversity. Conservation actions must be based on solid knowledge of the factors affecting species richness in the remaining habitat fragments. Besides local characteristics, it is critical to consider a broader spatial context when evaluating habitat quality. Here we present an analysis of landscape-level determinants of butterfly species richness based on a country-wide survey in Estonia, representing the northern European forest zone. This study compares favourably to previous research in its scope (over 1200 systematically selected sites), and provides a relatively ‘natural’ reference point for the analyses based on areas with higher human population density. The number of butterfly species locally recorded was sought to be explained by variables describing the surroundings of the study sites at four spatial scales. The proportion of forest land was by far the strongest factor (positively) affecting the number of butterfly species recorded, followed by soil alkalinity. Notably, the effects of forest land area at the smallest (in a radius of 250 m) and largest (2000 m) spatial scales were partly independent of each other. The former likely reflects immediate habitat quality while the latter should be related to the colonisation-extinction balance in the metapopulation context. The correlates of anthropogenic pressure (e.g., urbanization, roads, agriculture) had little effect. The results highlight the key role of designing responsible forestry practices in the regional context of nature conservation.

Exposure assessment to bisphenol A (BPA) and its analogues bisphenol S (BPS) and bisphenol F (BPF) in wild boars by hair analysis

Bisphenols are widely used in various branches of industry for the production of plastics. They penetrate to the natural environment and thus living organisms. As endocrine disruptors, bisphenols have adverse effects on various internal organs and systems. Contrary to humans, the knowledge of the exposure of wild terrestrial mammals to bisphenols is extremely limited.Therefore, this study for the first time assessed the exposure level of wild boars to three bisphenols commonly used in industry (i.e. bisphenol A - BPA, bisphenol S - BPS and bisphenol F - BPF) using hair sample analysis in liquid chromatography-mass spectrometry (LC-MS).The presence of BPA and/or BPS has been noted in the samples collected from >80 % of animals included in the study (n = 54), while the presence of BPF was not found in any sample. At least one of the bisphenols was present in every sample tested. Mean concentrations of BPA and BPS in the hair of wild boars were 151.40 ± 135.10 pg/mg dry weight (dw.) and 29.40 ± 36.97 pg./mg dw, respectively. Concentrations of BPA and BPS in females were statistically higher than in males (p < 0.05). Moreover, statistically significantly higher concentration levels of BPA (and not BPS) in the areas with higher degree of industrialization and higher human population density were also found.This is the first study concerning the use of hair samples to assess the exposure of wild terrestrial mammals to bisphenols. The obtained results show that an analysis of the hair may be a useful tool of biomonitoring bisphenols in wild animals. The presence of BPA and BPS in wild boar hair in relatively high concentration also suggests that these substances may have an influence on the health status not only in humans and aquatic animals, but also in wild terrestrial mammals. However, many aspects connected with this issue are not clear and require further study.

Shift in habitat selection during natal dispersal in a long‐lived raptor species

Animals select their habitat along environmental gradients, but the mechanisms that constrain the ecological requirements of an individual can differ between life stages. Dispersal is a key demographic process that determines gene flow and alters species distributions, yet few empirical studies have examined whether habitat selection in animals is changing during dispersal. In this study, we examined changes in habitat preferences during natal dispersal of red kites Milvus milvus, a European raptor species. By deploying solar‐powered GPS‐GSM transmitters on nestlings, we continuously tracked individuals up to six years (2015–2020), from fledging to settlement. We applied habitat selection functions (HSF) to the tracking data using hierarchical generalized additive models, a flexible method which combines individual‐ and population‐level inference, while allowing for the contrast of the prospecting and settlement phases. During the prospecting phase (n = 204 birds), individuals were less responsive to their environment than during the settlement phase, resulting in a predicted wide distribution in western Europe. During the settlement phase, individuals (n = 78 birds) selected a narrower range of environmental gradients, while avoiding areas of high elevation, steep topographic slopes, high human population density and highly heterogeneous landscapes. During this phase, individuals were also more philopatric, i.e. they were more inclined to choose an environment closer to their natal area, than during the prospecting phase. Suitable habitats predicted during settlement were much more spatially contrasted than during prospecting. Our study provides empirical evidence that habitat selection changes across natal dispersal phases in a long‐lived species, indicating that species conservation strategies should account for different environmental constraints before and after settlement. Furthermore, our findings underscore the importance of long‐term tracking data, with sufficient sample size, to study the link between habitat selection and natal dispersal.

Co-occurrence of climate-change induced and anthropogenic pressures in Central American key biodiversity areas

Central America hosts many key biodiversity areas (KBAs), areas which represent unique and irreplaceable ecosystems of global importance for species conservation. However, large extents of these areas are not under legal protection and could be threatened by pressures from land use change (e.g. deforestation and agricultural expansion), high human population density (e.g. population growth and urban sprawl) and climate-driven biome shifts. Here, we simulated future biome stability under the influence of climate change across KBAs in the Mesoamerican biodiversity hot spot and combined the results with projections of land use and population density up to the end of the 21st century. We applied four forcing scenarios based on two global climate models (GFDL-ESM4 and IPSL-CM6A-LR) and two shared socio-economic pathways (SSP1-2.6 and SSP3-7.0), which represent a range from low to high emission pathways. Our model projected decreased biome stability in 39%–46% of protected areas in KBAs, whereas this number even increased to 59%–60% for unprotected areas in KBAs (depending on the climate scenario). While human interferences in protected parts of KBAs are expected to be limited, large parts of unprotected areas in KBAs were projected to be pressured by multiple factors at once and are reason for concern. In particular, high human population pressures (>10 people km−2) emerged as a main threat over 30%–44% of the unprotected area in KBAs. These were largely accompanied by pressures from land use and sporadically reinforced by pressures from climate-driven biome shifts. Among the hot spots facing multiple high pressures are some of the last tropical dry and montane forest ecosystems in Central America, which stresses the need for urgent conservation action.

Human density impacts Nubian Flapshell turtle survival in Sub-Saharan Africa: Future conservation strategies

The Nubian Flapshell Turtle, Cyclanorbis elegans, is classified as one of the most threatened chelonian species globally (Critically Endangered according to the IUCN Red List). The species is presumed extinct in most of its historical distribution range, but still survives along the White Nile between South Sudan and northern Uganda. In this paper, we utilised the maximum entropy model (MaxEnt) to evaluate the habitat suitability of the species to explore its distribution decline by comparing historical and current presence data, as well as correlate the predicted past and present distribution with human population density. Our assumption is that overexploitation of the turtle occurs (and has occurred in the past) in sites with high human density. We show that: (1) a large number of historical sites where the turtle was present had high human population densities, whereas (2) the current distribution model showed low overlap between areas with high probability of turtle presence and high human population density. We suggest that Nubian flapshells are likely to have become extinct because of high human density (and therefore high overexploitation) and remnant populations have only survived along waterbodies with low numbers of people. However, the presence sites of this species in northern Uganda are under pressure by rapidly growing refugees'settlements. We also hypothesize that the range of the Nubian Flapshell may be shifting to the south (where the general environment is wetter and cooler) due to climate change affecting the distribution of this freshwater species. The conservation implications of these evidence are also presented.

Predicting dengue incidence using panel data analysis

Dengue is the most rapidly spreading infectious disease, especially in Indonesia. Dengue virus is transmitted by the bite of female Aedes mosquitoes. The high human population density and proximity to vector breeding places strengthen the interaction between the virus, vector, and humans as hosts. Using dengue incidence panel data during 2018-2019 in 34 provinces in Indonesia, this study examined the effect of human population density as a demographic variable and vector control on dengue incidence in Indonesia. The time series data were analyzed using EViews. The fixed effect model estimation showed that dengue incidence was significantly associated with demographic variables measured as human population density, with a P-value of 0.02. The vector control variable shows an insignificant association with dengue incidence. But simultaneous analysis between human population density and vector control on dengue incidence has a significant association with probability F (statistic) = 0.000. Our study demonstrated that densely populated provinces in Indonesia have a very high incidence of dengue. Improving sanitation in densely populated settlements can prevent and control dengue incidence.

Inferring microbial community assembly in an urban river basin through geo-multi-omics and phylogenetic bin-based null-model analysis of surface water

Understanding the community assembly process is a central issue in microbial ecology. In this study, we analyzed the community assembly of particle-associated (PA) and free-living (FL) surface water microbiomes in 54 sites from the headstream to the river mouth of an urban river in Japan, the river basin of which has the highest human population density in the country. Analyses were conducted from two perspectives: (1) analysis of deterministic processes considering only environmental factors using a geo-multi-omics dataset and (2) analysis of deterministic and stochastic processes to estimate the contributions of heterogeneous selection (HeS), homogeneous selection (HoS), dispersal limitation (DL), homogenizing dispersal (HD), and drift (DR) as community assembly processes using a phylogenetic bin-based null model. The variation in microbiomes was successfully explained from a deterministic perspective by environmental factors, such as organic matter–related, nitrogen metabolism, and salinity-related parameters, using multivariate statistical analysis, network analysis, and habitat prediction. In addition, we demonstrated the dominance of stochastic processes (DL, HD, and DR) over deterministic processes (HeS and HoS) in community assembly from both deterministic and stochastic perspectives. Our analysis revealed that as the distance between two sites increased, the effect of HoS sharply decreased while the effect of HeS increased, particularly between upstream and estuary sites, indicating that the salinity gradient could potentially enhance the contribution of HeS to community assembly. Our study highlights the importance of both stochastic and deterministic processes in community assembly of PA and FL surface water microbiomes in urban riverine ecosystems.