Mortality Hotspots Research Articles

Bird electrocution on power lines: Spatial gaps and identification of driving factors at global scales

Universal energy access is one of the targets of the Sustainable Development Goals (SDGs), and thus the deployment of electricity grids is expected to expand globally in the coming decades. However, the installation of power lines is not biodiversity-friendly. In particular, electrocution on power pylons is a major cause of bird mortality worldwide, including for some severely endangered species. Over the last decades, different studies have improved our understanding of the factors influencing the risk of electrocution in birds, but until now spatial gaps in our knowledge of these impacts and the factors driving global patterns of bird electrocution have not been assessed. In this study, we evaluated data from a total of 114 studies that provided information on bird mortality rates on power lines, and we analyzed the factors driving electrocution rates for all bird species, and then for all raptors and large eagles separately. Our results showed a high spatial distribution bias, as more than 80% of the studies were carried out in developed countries, mostly in Europe and North America. By contrast, no systematic studies have been found for Oceania and very few for South America and Africa. Europe showed the highest electrocution rates for birds, South America for raptor species and Africa for eagles. Socio-economic factors best-explained bird and raptor electrocution rates, while climate-related factors were the most influential for eagles. Contrary to our expectations, factors related to pylon design were the least influential on overall electrocution rates. Variables related to study design showed highly variable levels of influence. This could be due to the lack of standardized protocols. Although bird electrocution has been extensively studied, there are large areas where no studies have been carried out or for which data are inaccessible. This could be because in these areas the power distribution network is still sparse, or that most studies are not public or accessible to the international community. Researchers and managers should promote the publication of studies, as awareness is the first step to solving these problems. The factors identified could be applied globally to the design and planning of power grids and the identification of mortality hotspots. This would help mitigate the creation of new mortality hotspots, especially in developing countries where the installation of new power lines has been growing exponentially in recent years.

Human-caused mortality of large carnivores in Iran during 1980–2021

Human-caused mortality is the main cause of death for large carnivores worldwide and has had serious adverse effects on their populations. Detailed quantitative information on potential causes and patterns of mortalities are vital for development of effective conservation strategies. We investigated human-caused large carnivore mortalities across Iran using reports provided by Iran’s Department of the Environment (DOE) during January 1980–January 2021, which comprised 399 mortality instances involving 443 carnivore deaths. Brown bears (Ursus arctos) had the highest frequency of occurrence (30%), followed by striped hyenas (Hyaena hyaena; 24%), and Persian leopards (Panthera pardus saxicolor; 17%). Overall, mortalities related to agricultural (i.e. livestock, or crops including plants, fruits, beehives) loss occurred more frequently (31%) than mortality related to illegal trade (21%) and risk to humans (7%). Specifically, brown bears were killed more frequently due to potential threats to human life and crops, whereas leopards and wolves were killed more often because of livestock depredations. Additionally, leopards were killed more frequently for illegal trade of their skins. We recommend the DOE improve local communities’ attitudes toward large carnivores by promoting conservation education programs and incentive compensation schemes, as well as implement mitigation measures (e.g. wildlife crossing structures or fencing) at road mortality hotspots to prevent unnecessary deaths of large carnivores in Iran.

Spatial modeling of mortality from acute lower respiratory infections in children under 5 years of age in 2000-2017: a global study.

BackgroundOver the past few decades, various goals have been defined to reduce the mortality of children caused by acute lower respiratory infections (ALRIs) worldwide. However, few spatial studies to date have reported on ALRI deaths.PurposeWe aimed to assess the spatial modeling of mortality from ALRI in children under 5 years of age during 2000–2017 using a global data.MethodsThe data on the mortality of children under 5 years old caused by ALRI were initially obtained from the official website of the World Health Organization. The income status of their home countries was also gathered from the Country Income Groups (World Bank Classification) website and divided into 5 categories. After that, in the ArcGIS 10.6 environment, a database was created and the statistical tests and related maps were extracted. The Global Moran’s I statistic, Getis-Ord Gi statistic, and geographically weighted regression were used for the analyses. In this study, higher z scores indicated the hot spots, while lower z scores indicated the cold spots.ResultsIn 2000–2017, child mortality showed a downward trend from 17.6 per 100,000 children to 8.1 and had a clustered pattern. Hot spots were concentrated in Asia in 2000 but shifted toward African countries by 2017. A cold spot that formed in Europe in 2007 showed an ascending trend by 2017. Based on the results of geographically weighted regression test, the regions identified as the hot spots of mortality from ALRI in children under 5 years old were among the middle-income countries (R2=0.01, adjusted R2=8.77).ConclusionWhile the total number of child deaths in 2000–2017 has decreased, the number of hot spots has increased among countries. This study also concluded that, during the study period, Central and Western Africa countries became the main new hot spots of deaths from ALRI.

The impact of urban and transport planning on health: Assessment of the attributable mortality burden in Madrid and Barcelona and its distribution by socioeconomic status

BackgroundThe population living in urban areas is growing rapidly. The level of exposure to adverse environmental factors is detrimental to human health and is directly related to urban and transport planning practices. ObjectiveTo estimate the premature mortality burden of non-compliance with international exposure guidelines for air pollution, noise, access to green space and heat for Barcelona and Madrid (Spain), and its distribution among the population by the socioeconomic status (SES). MethodsThe Urban and TranspOrt planning Health Impact Assessment (UTOPHIA) tool was applied and the attributable premature mortality due to non-compliance with recommended exposure levels was estimated. The distribution of the attributable mortality burden among the population by SES was investigated through Generalized Additive Models (GAMs) adjusting for spatial autocorrelation and a cluster analysis was performed to identify attributable mortality hot spots. ResultsAnnually, 7.1% and 3.4% of premature mortality in Barcelona and Madrid, respectively, could be attributed to non-compliance with the international exposure recommendations for air pollution, noise, heat and access to green space. In addition, analysis by SES showed that in Barcelona lower SES areas had an overall greater attributable mortality rate, while in Madrid, the distribution of the attributable mortality burden by SES varied by exposure. ConclusionThis study shows the impact of environmental exposures on mortality and highlights the importance of taking integrated actions when designing cities considering the health impacts, but also the specificities of each city such as the socio-demographic context. Moreover, the high precision scale of the analysis enables the identification of environmental hazards and mortality hot spots providing a powerful tool to support priority-setting and guide policymakers towards a healthy, sustainable and just city for all of their residents.

The Association of Social Determinants of Health With COVID-19 Mortality in Rural and Urban Counties.

PurposeTo identify the county‐level effects of social determinants of health (SDoH) on COVID‐19 (corona virus disease 2019) mortality rates by rural–urban residence and estimate county‐level exceedance probabilities for detecting clusters.MethodsThe county‐level data on COVID‐19 death counts as of October 23, 2020, were obtained from the Johns Hopkins University. SDoH data were collected from the County Health Ranking and Roadmaps, the US Department of Agriculture, and the Bureau of Labor Statistics. Semiparametric negative binomial regressions with expected counts based on standardized mortality rates as offset variables were fitted using integrated Laplace approximation. Bayesian significance was assessed by 95% credible intervals (CrI) of risk ratios (RR). County‐level mortality hotspots were identified by exceedance probabilities.FindingsThe COVID‐19 mortality rates per 100,000 were 65.43 for the urban and 50.78 for the rural counties. Percent of Blacks, HIV, and diabetes rates were significantly associated with higher mortality in rural and urban counties, whereas the unemployment rate (adjusted RR = 1.479, CrI = 1.171, 1.867) and residential segregation (adjusted RR = 1.034, CrI = 1.019, 1.050) were associated with increased mortality in urban counties. Counties with a higher percentage of college or associate degrees had lower COVID‐19 mortality rates.ConclusionsSDoH plays an important role in explaining differential COVID‐19 mortality rates and should be considered for resource allocations and policy decisions on operational needs for businesses and schools at county levels.

Racial/ethnic minority and neighborhood disadvantage leads to disproportionate mortality burden and years of potential life lost due to COVID-19 in Chicago, Illinois.

Epidemiological studies have highlighted the disparate impact of coronavirus disease 2019 (COVID-19) on racial and ethnic minority and socioeconomically disadvantaged populations, but data at the neighborhood-level is sparse. The objective of this study was to investigate the disparate impact of COVID-19 on disadvantaged neighborhoods and racial/ethnic minorities in Chicago, Illinois. Using data from the Cook County Medical Examiner, we conducted a neighborhood-level analysis of COVID-19 decedents in Chicago and quantified age-standardized years of potential life lost (YPLL) due to COVID-19 among demographic subgroups and neighborhoods with geospatial clustering of high and low rates of COVID-19 mortality. We show that age-standardized YPLL was markedly higher among the non-Hispanic (NH) Black (559 years per 100,000 population) and the Hispanic (811) compared with NH white decedents (312). We demonstrate that geomapping using residential address data at the individual-level identifies hot-spots of COVID-19 mortality in neighborhoods on the Northeast, West, and South areas of Chicago that reflect a legacy of residential segregation and persistence of inequality in education, income, and access to healthcare. Our results may contribute to ongoing public health and community-engaged efforts to prevent the spread of infection and mitigate the disproportionate loss of life among these communities due to COVID-19 as well as highlight the urgent need to broadly target neighborhood disadvantage as a cause of pervasive racial inequalities in life and health.

Snakes on a lane: Road type and edge habitat predict hotspots of snake road mortality

Roads constitute just 1% of the total land in the US, but their impacts on wildlife are significant and far-reaching. Snakes are particularly susceptible to road mortality because many species do not avoid crossing roads, may use the road’s surface to thermoregulate, or freeze when approached by a vehicle. We conducted opportunistic surveys to collect road mortality points for snakes in southeastern Ohio over 15 years (2003–2018). We used logistic regression to predict roadkill hotspots and evaluate variables that influence road mortality. The species most frequently found dead on roads were Black Ratsnakes (Pantherophis spiloides), Northern Black Racers (Coluber constrictor), Eastern Gartersnakes (Thamnophis sirtalis), and Rough Greensnakes (Opheodrys aestivus). Across the 14 snake species we recorded dead on roads, percent pasture within a 100 m buffer of the roadkill point, township route, county route, and state route were all negative predictors of road mortality. All surveys started in Athens, Ohio, and distance to roadkill locations was a positive predictor for road mortality. These results indicate that high-traffic roads pose a risk to snake populations, but that mortality also occurs on low-traffic roads as well. Our top model showed that low levels of pasture embedded in other land cover types was an important predictor of roadkill, suggesting that edge habitat contributes to snake road mortality. Because road mortality does not seem to be localized, road mortality mitigation structures such as underpasses and fences may have limited benefits for snake populations in our study area. The creation of edge habitat away from roads could provide snakes with necessary habitat without increasing their risk of mortality.

Restructuring of emergency services to COVID-19 in Brazil: a space-time analysis from February to August 2020.

To explore the reorganization of the health system in response to the COVID-19 pandemic. We conducted an ecological, descriptive-exploratory study with analysis of spatio-temporal clusters by epidemiological week in Brazilian municipalities. Secondary data sources were used, from the National Health Establishment Registry (April 2020) and on COVID-19 cases, February to August 2020. Intensive Care Units (ICU) availability was overlaid on incidence and mortality hot spots in order to assess expanded access in critical regions. Of the 5,570 municipalities analyzed, 54% were identified as incidence hot spots and 31% as mortality hot spots. Of the municipalities in incidence hot spots and with scarce access, 28% were covered by ICU expansion, while with regard to mortality 14% were covered. The opening of new beds was not able to provide broad coverage for critical regions and could be optimized with the use of spatial analysis techniques.

Preventing wildlife roadkill can offset mitigation investments in short-medium term

Wildlife vehicle collisions (WVC) are a threat to wildlife and humans, killing millions of animals of numerous species, as well as causing significant damage to vehicles, drivers and passengers. Road fencing is a highly effective mitigation measure at reducing WVC, however its large-scale implementation requires a high investment. We questioned how long it would take for savings from avoided collisions to offset the investments in road fencing mitigation, focusing on vehicle damage costs. Using the information of a 3-year systematic roadkill monitoring of 1158 km in Mato Grosso do Sul, Brazil, we estimated the real number of casualties accounting for bias in roadkill counting. We obtained information on the material costs on cars and trucks due to WVC and, considering the road traffic volume characteristics, estimated the total material costs resulting from collisions with larger animals. Cost-benefit analyses allowed estimating the time required to amortize the investment in fencing, considering its application along the full surveyed roads or only in hotspots of mortality. We recorded over 10,000 WVC, 40% of which involved animals that can cause significant material damage to vehicles, namely the endangered lowland tapir (Tapirus terrestris, n = 267) and giant anteater (Myrmecophaga tridactyla, n = 608). The average material cost per accident was US$ 885 ± 1575 (mean ± SD). We show that investments are likely to pay off in 16–40 years for the mitigation of the full roads, and in 9–25 years for hotspots of mortality. Thus, road mitigation is a win-win solution for increasing traffic safety for humans and reduces road-related negative effects on biodiversity.

County Differences in Liver Mortality in the United States: Impact of Sociodemographics, Disease Risk Factors, and Access to Care

Data have demonstrated state-wide variability in mortality rates from liver disease (cirrhosis + hepatocellular carcinoma), but data are lacking at the local level (eg, county) to identify factors associated with variability in liver disease-related mortality and hotspots of liver disease mortality. We used Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research data from 2009 to 2018 to calculate county-level, age-adjusted liver disease-related death rates. We fit multivariable linear regression models to adjust for county-level covariates related to demographics (ie, race and ethnicity), medical comorbidities (eg, obesity), access to care (eg, uninsured rate), and geographic (eg, distance to closest liver transplant center) variables. We used optimized hotspot analysis to identify clusters of liver disease mortality hotspots based on the final multivariable models. In multivariable models, 61% of the variability in among-county mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the closest transplant center, and local rates of obesity, diabetes, and alcohol use. Despite adjustment, significant within-state variability in county-level mortality rates was found. Of counties in the top fifth percentile (ie, highest mortality) of fully adjusted mortality, 60% were located in 3 states: Oklahoma, Texas, and New Mexico. Adjusted mortality rates were highly spatially correlated, representing 5 clusters: South Florida; Appalachia and the eastern part of the Midwest; Texas and Oklahoma; New Mexico, Arizona, California, and southern Oregon; and parts of Washington and Montana. Our data demonstrate significant intrastate differences in liver disease-related mortality, with more than 60% of the variability explained by patient demographics, clinical risk factors for liver disease, and access to specialty liver care.

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns

Wildlife roadkill hotspots are frequently used to identify priority locations for implementing mitigation measures. However, understanding the landscape-context and the spatial and temporal dynamics of these hotspots is challenging. Here, we investigate the factors that drive the spatiotemporal variation of bat mortality hotspots on roads along three years. We hypothesize that hotspot locations occur where bat activity is higher and that this activity is related to vegetation density and productivity, probably because this is associated with food availability. Statistically significant clusters of bat-vehicle collisions for each year were identified using the Kernel Density Estimation (KDE) approach. Additionally, we used a spatiotemporal analysis and generalized linear mixed models to evaluate the effect of local spatiotemporal variation of environmental indices and bat activity to predict the variation on roadkill hotspot locations and to asses hotspot strength over time. Between 2009 and 2011 we conducted daily surveys of bat casualties along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 509 casualties and we identified 86 statistically significant roadkill hotspots, which comprised 12% of the road network length and contained 61% of the casualties. Hotspots tended to be located in areas with higher accumulation of vegetation productivity along the three-year period, high bat activity and low temperature. Furthermore, we found that only 17% of the road network length was consistently classified as hotspots across all years; while 43% of hotspots vanished in consecutive years and 40% of new road segments were classified as hotspots. Thus, non-persistent hotspots were the most frequent category. Spatiotemporal changes in hotspot location are associated with decreasing vegetation production and increasing water stress on road surroundings. This supports our hypothesis that a decline on overall vegetation productivity and increase of roadside water deficit, and the presumed lower abundance of prey, have a significant effect on the decrease of bat roadkills. To our knowledge, this is the first study demonstrating that freely available remote sensing data can be a powerful tool to quantify bat roadkill risk and assess its spatiotemporal dynamics.

Breast Cancer Mortality Hot Spots Among Black Women With de Novo Metastatic Breast Cancer.

BackgroundBlack women living in southern states have the highest breast cancer mortality rate in the United States. The prognosis of de novo metastatic breast cancer is poor. Given these mortality rates, we are the first to link nationally representative data on breast cancer mortality hot spots (counties with high breast cancer mortality rates) with cancer mortality data in the United States and investigate the association of geographic breast cancer mortality hot spots with de novo metastatic breast cancer mortality among Black women.MethodsWe identified 7292 Black women diagnosed with de novo metastatic breast cancer in Surveillance, Epidemiology, and End Results (SEER). The county-level characteristics were obtained from 2014 County Health Rankings and linked to SEER. We used Cox proportional hazards models to calculate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for mortality between hot spot and non–hot spot counties.ResultsAmong 7292 patients, 393 (5.4%) resided in breast cancer mortality hot spots. Women residing in hot spots had similar risks of breast cancer–specific mortality (aHR = 0.99, 95% CI = 0.85 to 1.15) and all-cause mortality (aHR = 0.97, 95% CI = 0.84 to 1.11) as women in non–hot spots after adjusting for individual and tumor-level factors and treatments. Additional adjustment for county-level characteristics did not impact mortality.ConclusionLiving in a breast cancer mortality hot spot was not associated with de novo metastatic breast cancer mortality among Black women. Future research should begin to examine variation in both individual and population-level determinants, as well as in molecular and genetic determinants that underlie the aggressive nature of de novo metastatic breast cancer.

Road mortality threatens endemic species in a national park in Sulawesi, Indonesia

The emerging economy of Indonesia has triggered rapid infrastructure development that threatens ecological communities, including within protected areas. The national parks of Indonesia are renowned for their high levels of biodiversity and endemism, yet the impacts of road development within these parks remains understudied. We conducted road mortality surveys along a 21.8-km section of paved highway that bisects Rawa Aopa Watumohai National Park in Sulawesi, Indonesia from January to April 2018. We documented wildlife carcasses during morning and afternoon surveys and identified hotspots of road mortality for amphibians, reptiles, birds, and mammals. A total of 790 carcasses were observed during 16 surveys, amounting to 2.3 carcasses km−1, one of the highest levels reported for Asia. Wildlife recorded during our surveys represented 40 taxa, of which 15% are endemic to the Wallacea region. We documented two hotspots of road mortality for each major taxonomic group. We propose that mitigation measures be implemented at the largest hotspot for amphibians, one overlapping hotspot for amphibians and reptiles, and one overlapping hotspot for birds and mammals, for a total of three areas targeted for mitigation along this 21.8-km section of highway. We recommend the implementation of mitigation measures including highway undercrossings with fencing, reduced speeds with associated signage, and highway lighting at these three hotspot locations to protect the diverse and unique fauna in this national park.

Identifying Potential Connectivity for an Urban Population of Rattlesnakes (Sistrurus catenatus) in a Canadian Park System

In the face of ongoing habitat loss and fragmentation, maintaining an adequate level of landscape connectivity is needed to both encourage dispersal between habitat patches and to reduce the extinction risk of fragmented wildlife populations. In a developing region of southwestern Ontario, Canada, a declining population of Eastern Massasauga rattlesnakes (Sistrurus catenatus) persists in fragmented remnants of tallgrass prairie in an urban park system. The goal of this study was to identify potential connectivity pathways between habitat patches for this species by using a GIS least-cost permeability swath model, and to evaluate the outputs with snake road mortality data. Results identified seven pathways between five core habitat blocks, a subset of which were validated with aerial imagery and mortality data. Four high-ranking pathways intersected roads through or near road mortality hotspots. This research will guide conservation interventions aimed at recovering endangered reptiles in a globally rare ecosystem, and will inform the use of permeability swaths for the identification of locations most suitable for connectivity interventions in dynamic, urbanizing landscapes.

A virtual community-of-practice approach by rural stakeholders in managing pneumoconiosis in the USA: a cross-sectional analysis.

The re-emergence of pneumoconiosis, particularly among coal miners (ie black lung), in the USA is a challenge for rural communities because more miners require specialized care while expertise is scarce. The Miners' Wellness TeleECHO (Extension for Community Health Outcomes) Clinic, jointly held by the University of New Mexico and a community hospital in New Mexico, provides structured telementoring to professionals caring for miners, including clinicians, respiratory therapists, home health professionals, benefits counselors, lawyers/attorneys and others, forming a virtual 'community of practice'. This approach has not been utilized and evaluated previously. The study's bimonthly program uses the ECHO telementoring model, which uses technology to leverage scarce mentoring resources; uses a disease-management model that is proven to improve outcomes in other disease states, by reducing variation in processes of care and sharing best practices; uses the principle of case-based learning with highly contextualized discussions, which fulfils key learning theory principles; creates a virtual community of practice; and uses an internet-based database to monitor outcomes. This 1-year cross-sectional study from September 2018 to September 2019 used geographical mapping of all attendee locations, web-based continuing medical education surveys completed by attendees using iECHO software, and a Research Electronic Data Capture-based survey of a convenience sample of participants, which obtained detailed information on demographics, knowledge, self-efficacy and collective efficacy. Knowledge sharing among participants was examined using insights and methods from social network analysis. Subgroup analysis involved comparisons between clinical and non-clinical professional groups, and between new and existing participants. Groups were compared using Fisher's exact test for categorical variables, and non-parametric Wilcoxon ranked sum test or student's t-test for continuous variables. Participants were largely located in pneumoconiosis mortality hotspots of the USA. In a convenience sample of 70 participants, clinical professional groups such as clinicians (29%), home health professionals (20%) and respiratory therapists (17%) constituted the majority of the stakeholders. Participants demonstrated the lowest knowledge score on 'legal pneumoconiosis' among the knowledge areas questioned; reported low self-efficacy with respect to managing miners' conditions and interpreting test results; and rated the learning community highly in terms of trust (86%), willingness to help each other (93%) and being closely knit (87%). Analysis of knowledge sources indicated that participants receive substantial proportions of knowledge from individuals outside of their stakeholder and professional groups, but proportions differ among clinical and non-clinical professional groups, as well as among 'fresh' and existing participants. The present study demonstrates the successful creation of a virtual multidisciplinary community of practice in pneumoconiosis mortality hotspot rural regions of the USA, with participants reporting multidisciplinary knowledge transfer. The community is regarded highly by participants in relation to trust, willingness to help and being closely knit. This innovative educational approach may help ensure the delivery of high-quality interdisciplinary care to rural miners in pneumoconiosis mortality hotspots in the USA.

Mortality by cause of death in Colombia: a local analysis using spatial econometrics

Colombia is undergoing major changes in mortality patterns. National- and department-level cause-specific analyses have previously been carried out, but very little is known about municipal-level trends, despite their epidemiological interest. We first analyze standardized mortality rates for seven cause-of-death groups to obtain high and low mortality clusters based on the spatial autocorrelation indicators Global Moran’s I and Local Moran’s I. The Mann–Whitney nonparametric test is then used to ascertain statistical associations between the high and low mortality clusters and known health determinants. We subsequently apply spatial lag and Durbin (when spatial autocorrelation was present) and OLS models (when not) to explain overall spatial patterns in cause-specific mortality. Age- and sex-specific cause-of-death mortality and population data were obtained from the National Administrative Department of Statistics (DANE). Deaths were corrected for each municipality due to under-registration. Results show that spatial autocorrelation declined over time for all cause-of-death categories, except male circulatory system diseases and perinatal mortality. It is highest in external causes, especially among men, with mortality hotspots moving from the central Andean area to Orinoquia and the Amazon rainforest. Male mortality is also more spatially clustered than female mortality and especially neoplasms, and external-cause mortality is also indirectly affected by the conditions of neighboring municipalities. Municipal surface area, ethnicity and public expenditure on health and education are the most frequent contextual variables explaining territorial differences in mortality. The identification of geographical mortality clusters in Colombia will allow decision makers to prioritize those regions with higher mortality.

On the identification of mortality hotspots in linear infrastructures

One of the main tasks when dealing with the impacts of infrastructures on wildlife is to identify hotspots of high mortality so one can devise and implement mitigation measures. A common strategy to identify hotspots is to divide an infrastructure into several segments and determine when the number of collisions in a segment is above a given threshold, reflecting a desired significance level that is obtained assuming a probability distribution for the number of collisions, which is often the Poisson distribution. The problem with this approach, when applied to each segment individually, is that the probability of identifying false hotspots (Type I error) is potentially high. The way to solve this problem is to recognize that it requires multiple testing corrections or a Bayesian approach. Here, we apply three different methods that implement the required corrections to the identification of hotspots: (i) the familywise error rate correction, (ii) the false discovery rate, and (iii) a Bayesian hierarchical procedure. We illustrate the application of these methods with data on two bird species collected on a road in Brazil. The proposed methods provide practitioners with procedures that are reliable and simple to use in real situations and, in addition, can reflect a practitioner’s concerns towards identifying false positive or missing true hotspots. Although one may argue that an overly cautionary approach (reducing the probability of type I error) may be beneficial from a biological conservation perspective, it may lead to a waste of resources and, probably worse, it may raise doubts about the methodology adopted and the credibility of those suggesting it.

Spatio-temporal distribution of under-five malaria morbidity and mortality hotspots in Ghana, 2012 � 2017: a case for evidence-based targeting of malaria interventions

Introduction: The spatiotemporal variation in malaria burden underpins the need for targeted malaria interventions. Despite the scale-up of malaria control interventions in Ghana, malaria remains the leading cause of hospital admissions and deaths among children below 5 years (U5). We described spatiotemporal distribution of U5 malaria morbidity and mortality from 2012 to 2017 to provide evidence for deployment of specific malaria interventions to regions of hotspots in Ghana.

Mortality hotspots: Nitrogen cycling in forest soils during vertebrate decomposition

Decomposing animals alter soil biogeochemical cycles, and these natural ephemeral nutrient patches (or ‘hotspots’) are important for maintaining landscape heterogeneity and enriching local biodiversity. Soil nitrogen (N) enrichment associated with decomposing animals has been documented, but to date an integrated systems-level understanding of the fate and rates of N compound transformations is lacking. The goal of this study was to develop a comprehensive view of temporal changes in N biogeochemical cycling during vertebrate decay. Vertebrate decomposition significantly altered soil N cycling, and was divided into three main biogeochemical phases based on soil chemistry. Phase one included initial and early decay, distinguished by oxic soils with low, background carbon and N cycling rates. Fluid release and insect colonization during active and advanced decay, defined as phase two, stimulated soil microbial communities, particularly those able to degrade phospholipids and nucleic acids. This resulted in anaerobic soils, 250 times greater ammonium and ten times greater carbon dioxide than background, and the highest 15N-enrichment rates. The final biogeochemical phase, encompassing the early and late skeletal stages, was characterized by enhanced nitrification and denitrification as evidenced by significantly elevated nitrate, dissolved organic nitrogen, and enhanced nitrous oxide release. As a result of decay and multiple synchronous processes, soil δ15N was enriched by 6–10‰ above background, demonstrating the influence of decay on soil isotopic signatures. This work provides a systems-level synthesis of N redistribution during animal decay and has significant implications for our understanding of nutrient turnover rates and dynamics in terrestrial ecosystems.

Consequences of drift and carcass decomposition for estimating sea turtle mortality hotspots

Sea turtle strandings provide important mortality information, yet knowledge of turtle carcass at-sea drift and decomposition characteristics are needed to better understand and manage where these mortalities occur. We used empirical sea turtle carcass decomposition and drift experiments in the Chesapeake Bay, Virginia, USA to estimate probable carcass oceanic drift times and quantify the impact of direct wind forcing on carcass drift. Based on the time period during which free-floating turtle carcasses tethered nearshore were buoyant, we determined that oceanic drift duration of turtle carcasses was highly dependent on water temperature and varied from 2 to 15days during typical late spring to early fall Bay water conditions. The importance of direct wind forcing for turtle carcass drift was assessed based on track divergence rates from multiple simultaneous deployments of three types of surface drifters: bucket drifters, artificial turtles and turtle carcass drifters. Turtle drift along-wind leeway was found to vary from 1 to 4% of wind speed, representing an added drift velocity of approximately 0.03–0.1m/s for typical Bay wind conditions. This is comparable to current speeds in the Bay (0.1–0.2m/s), suggesting wind is important for carcass drift. Estimated carcass drift parameters were integrated into a Chesapeake Bay oceanographic drift model to predict carcass drift to terrestrial stranding locations. Increased drift duration (e.g., due to low temperatures) increases mean distance between expected mortality events and stranding locations, as well as decreases overall likelihood of retention in the Bay. Probable mortality hotspots for the peak month of strandings (June) were identified off coastal southeastern Virginia and within the lower Bay, including the Bay mouth and lower James River. Overall, results support that sea turtle drift time is quite variable, and varies greatly depending on water and air temperature as well as oceanic conditions. Knowledge of these parameters will improve our ability to interpret stranding events around the globe.