Mapping global eco-environment vulnerability due to human and nature disturbances.
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ABSTRACT:
SUBMITTER: Nguyen KA
PROVIDER: S-EPMC6495093 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundSnakebite envenoming is a frequently overlooked cause of mortality and morbidity. Data for snake ecology and existing snakebite interventions are scarce, limiting accurate burden estimation initiatives. Low global awareness stunts new interventions, adequate health resources, and available health care. Therefore, we aimed to synthesise currently available data to identify the most vulnerable populations at risk of snakebite, and where additional data to manage this global problem are needed.MethodsWe assembled a list of snake species using WHO guidelines. Where relevant, we obtained expert opinion range (EOR) maps from WHO or the Clinical Toxinology Resources. We also obtained occurrence data for each snake species from a variety of websites, such as VertNet and iNaturalist, using the spocc R package (version 0.7.0). We removed duplicate occurrence data and categorised snakes into three groups: group A (no available EOR map or species occurrence records), group B (EOR map but <5 species occurrence records), and group C (EOR map and ≥5 species occurrence records). For group C species, we did a multivariate environmental similarity analysis using the 2008 WHO EOR maps and newly available evidence. Using these data and the EOR maps, we produced contemporary range maps for medically important venomous snake species at a 5 × 5 km resolution. We subsequently triangulated these data with three health system metrics (antivenom availability, accessibility to urban centres, and the Healthcare Access and Quality [HAQ] Index) to identify the populations most vulnerable to snakebite morbidity and mortality.FindingsWe provide a map showing the ranges of 278 snake species globally. Although about 6·85 billion people worldwide live within range of areas inhabited by snakes, about 146·70 million live within remote areas lacking quality health-care provisioning. Comparing opposite ends of the HAQ Index, 272·91 million individuals (65·25%) of the population within the lowest decile are at risk of exposure to any snake for which no effective therapy exists compared with 519·46 million individuals (27·79%) within the highest HAQ Index decile, showing a disproportionate coverage in reported antivenom availability. Antivenoms were available for 119 (43%) of 278 snake species evaluated by WHO, while globally 750·19 million (10·95%) of those living within snake ranges live more than 1 h from population centres. In total, we identify about 92·66 million people living within these vulnerable geographies, including many sub-Saharan countries, Indonesia, and other parts of southeast Asia.InterpretationIdentifying exact populations vulnerable to the most severe outcomes of snakebite envenoming at a subnational level is important for prioritising new data collection and collation, reinforcing envenoming treatment, existing health-care systems, and deploying currently available and future interventions. These maps can guide future research efforts on snakebite envenoming from both ecological and public health perspectives and better target future estimates of the burden of this neglected tropical disease.FundingBill & Melinda Gates Foundation.
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Project description:High-resolution global flood risk maps are increasingly used to inform disaster risk planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation in social vulnerability, which is a key determinant of variation in outcomes for exposed populations. Here we integrate annual average exceedance probability estimates from a high-resolution fluvial flood model with gridded population and poverty data to create a global vulnerability-adjusted risk index for flooding (VARI Flood) at 90-meter resolution. The index provides estimates of relative risk within or between countries and changes how we understand the geography of risk by identifying 'hotspots' characterised by high population density and high levels of social vulnerability. This approach, which emphasises risks to human well-being, could be used as a complement to traditional population or asset-centred approaches.
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Project description:The relationship between climate change and human migration is not homogenous and depends critically on the differential vulnerability of population and places. If places and populations are not vulnerable, or susceptible, to climate change, then the climate-migration relationship may not materialize. The key to understanding and, from a policy perspective, planning for whether and how climate change will impact future migration patterns is therefore knowledge of the link between climate vulnerability and migration. However, beyond specific case studies, little is known about this association in global perspective. We therefore provide a descriptive, country-level portrait of this relationship. We show that the negative association between climate vulnerability and international migration holds only for countries least vulnerable to climate change, which suggests the potential for trapped populations in more vulnerable countries. However, when analyzed separately by life supporting sector (food, water, health, ecosystem services, human habitat, and infrastructure) and vulnerability dimension (exposure, sensitivity, and adaptive capacity), we detect evidence of a relationship among more, but not the most, vulnerable countries. The bilateral (i.e., country-to-country) migration show that, on average, people move from countries of higher vulnerability to lower vulnerability, reducing global risk by 15%. This finding is consistent with the idea that migration is a climate adaptation strategy. Still, ~6% of bilateral migration is maladaptive with respect to climate change, with some movement toward countries with greater climate change vulnerability.
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Project description:Forest disturbance regimes are expected to intensify as Earth's climate changes. Quantifying forest vulnerability to disturbances and understanding the underlying mechanisms is crucial to develop mitigation and adaptation strategies. However, observational evidence is largely missing at regional to continental scales. Here, we quantify the vulnerability of European forests to fires, windthrows and insect outbreaks during the period 1979-2018 by integrating machine learning with disturbance data and satellite products. We show that about 33.4 billion tonnes of forest biomass could be seriously affected by these disturbances, with higher relative losses when exposed to windthrows (40%) and fires (34%) compared to insect outbreaks (26%). The spatial pattern in vulnerability is strongly controlled by the interplay between forest characteristics and background climate. Hotspot regions for vulnerability are located at the borders of the climate envelope, in both southern and northern Europe. There is a clear trend in overall forest vulnerability that is driven by a warming-induced reduction in plant defence mechanisms to insect outbreaks, especially at high latitudes.
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Project description:Indicators are increasingly used to measure environmental systems; however, they are often criticized for failing to measure and describe uncertainty. Uncertainty is particularly difficult to evaluate and communicate in the case of composite indicators which aggregate many indicators of ecosystem condition. One of the ongoing goals of the Ocean Health Index (OHI) has been to improve our approach to dealing with missing data, which is a major source of uncertainty. Here we: (1) quantify the potential influence of gapfilled data on index scores from the 2015 global OHI assessment; (2) develop effective methods of tracking, quantifying, and communicating this information; and (3) provide general guidance for implementing gapfilling procedures for existing and emerging indicators, including regional OHI assessments. For the overall OHI global index score, the percent contribution of gapfilled data was relatively small (18.5%); however, it varied substantially among regions and goals. In general, smaller territorial jurisdictions and the food provision and tourism and recreation goals required the most gapfilling. We found the best approach for managing gapfilled data was to mirror the general framework used to organize, calculate, and communicate the Index data and scores. Quantifying gapfilling provides a measure of the reliability of the scores for different regions and components of an indicator. Importantly, this information highlights the importance of the underlying datasets used to calculate composite indicators and can inform and incentivize future data collection.
| S-EPMC4970671 | biostudies-literature
Project description:Coronavirus Disease (COVID-19) has become the largest pandemic that has affected 210 countries. Rolling data indicate that 257,3605 people are infected by the disease, from which 701,838 have recovered and 178,562 have died. No specific medicine or vaccine is available yet to control the disease, hence, social distancing via lockdown is widely adopted as the only preventive measure. Social distancing is observed at different level of strictness in different counties but it almost made the world to stands still. Although scientific articles on this largest social move are scanty, it resulted in benefiting the deteriorated environment to revive back. Many environmental indices such as lowering NO2 and CO2 emissions and reduction in particulate matters in air as a result of less human activities have led to clean air and pollution free water in many countries. Undoubtedly, the world was experiencing pollution in several countries due to mainly human activities including urbanization, industrialization, fossil fuel exhaustion etc. Under such situation a special (natural) a protective measure was awaited to fix environmental issues. Probably, the lockdown is one of the natural effects expected by nature via introduction of COVID-19. It is because, introduction of COVID-19 to nature was an outcome of mutation from two of its pre-existing forms, although, debate on it is still continuing. Viability of CoV-19 virus found to have a lot of correlation with aquatic and terrestrial environmental parameters such as pH, surface type, temperature etc. Air pollution is found to increase the risk of COVID-19 infection, therefore, use of mask and alcohols based standard sterilisers is strongly recommended. However, the self-revival rate of nature shall continue during post-lockdown period and a master plan must be adapted by national and international (mostly political) bodies to revive the Mother Nature completely.
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Project description:Vulnerability, understood as the propensity to be adversely affected, has attained importance in the context of climate change by helping to understand what makes populations and territories predisposed to its impacts. Conditions of vulnerability may vary depending on the characteristics of each territory studied-social, environmental, infrastructural, public policies, among others. Thus, the present study aimed to evaluate what makes the municipalities of the state of Amazonas, Brazil, vulnerable to climate change in the context of the largest tropical forest in the world, and which regions of the State are the most susceptible. A Municipal Vulnerability Index was developed, which was used to associate current socio-environmental characteristics of municipalities with climate change scenarios in order to identify those that may be most affected by climate change. The results showed that poor adaptive capacity and poverty had the most influence on current vulnerability of the municipalities of Amazonas with the most vulnerable areas being the southern, northern, and eastern regions of the state. When current vulnerability was related to future climate change projections, the most vulnerable areas were the northern, northeastern, extreme southern, and southwestern regions. From a socio-environmental and climatic point of view, these regions should be a priority for public policy efforts to reduce their vulnerability and prepare them to cope with the adverse aspects of climate change.
| S-EPMC5812563 | biostudies-literature
Project description:The understanding of eco-evolutionary dynamics, and in particular the mechanism of coexistence of species, is still fragmentary and in need of test bench model systems. To this aim we developed a variant of SELEX in vitro selection to study the evolution of a population of ∼1015 single-strand DNA oligonucleotide 'individuals'. We begin with a seed of random sequences which we select via affinity capture from ∼1012 DNA oligomers of fixed sequence ('resources') over which they compete. At each cycle ('generation'), the ecosystem is replenished via PCR amplification of survivors. Massive parallel sequencing indicates that across generations the variety of sequences ('species') drastically decreases, while some of them become populous and dominate the ecosystem. The simplicity of our approach, in which survival is granted by hybridization, enables a quantitative investigation of fitness through a statistical analysis of binding energies. We find that the strength of individual resource binding dominates the selection in the first generations, while inter- and intra-individual interactions become important in later stages, in parallel with the emergence of prototypical forms of mutualism and parasitism.
| S-EPMC10965223 | biostudies-literature
Project description:BackgroundExtreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping.ObjectiveWe investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA.MethodsWe acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) "unsupervised"-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) "supervised"-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles).ResultsUnsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups.DiscussionHVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.
| S-EPMC7466325 | biostudies-literature
Project description:Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit-based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995-2000, 2000-2005, 2005-2009 and 2015-2020, and the improvement was most significant in 1995-2000, covering an area of 823.95 km2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.
| S-EPMC11018612 | biostudies-literature