Health and equity implications of individual adaptation to air pollution in a changing climate.

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyone's need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.

Utilising anterolateral bladder flap to create a continent cutaneous diversion in a patient with pelvic fracture urethral injury.

A male child in the first decade of life presented to us with a history of a pelvic fracture and urethral injury resulting from a road traffic accident 4 months prior. He had previously undergone an exploratory laparotomy and suprapubic cystostomy at another medical centre. He was circumcised and exhibited a substantial urethral defect on the retrograde urethrogram, as well as on the micturating cystourethrogram. Following a careful assessment of the patient's and caregivers' expectations, a continent cutaneous catheterisable channel was planned. This procedure involved the use of an anterolateral bladder flap, and continence was achieved through the creation of a Nissen-type seromuscular invagination. Three months postoperatively, the child remains continent, can easily catheterise the stoma and has resumed his education.

Predicting discrete-time bifurcations with deep learning.

Many natural and man-made systems are prone to critical transitions-abrupt and potentially devastating changes in dynamics. Deep learning classifiers can provide an early warning signal for critical transitions by learning generic features of bifurcations from large simulated training data sets. So far, classifiers have only been trained to predict continuous-time bifurcations, ignoring rich dynamics unique to discrete-time bifurcations. Here, we train a deep learning classifier to provide an early warning signal for the five local discrete-time bifurcations of codimension-one. We test the classifier on simulation data from discrete-time models used in physiology, economics and ecology, as well as experimental data of spontaneously beating chick-heart aggregates that undergo a period-doubling bifurcation. The classifier shows higher sensitivity and specificity than commonly used early warning signals under a wide range of noise intensities and rates of approach to the bifurcation. It also predicts the correct bifurcation in most cases, with particularly high accuracy for the period-doubling, Neimark-Sacker and fold bifurcations. Deep learning as a tool for bifurcation prediction is still in its nascence and has the potential to transform the way we monitor systems for critical transitions.

Clinical and Urodynamic Predictors for Failure of Medical Management with Alpha Blockers in PBNO: A Retrospective Cohort Analysis.

OBJECTIVE: To evaluate the clinical and urodynamic variables that may predict the failure of alpha-blockers in primary bladder neck obstruction (PBNO) patients. Alpha-blockers are useful as a treatment option in patients with PBNO. Nonresponders need to undergo bladder neck incision (BNI). Little is known about the predictive factors determining the success of treatment. MATERIALS AND METHODS: This was a retrospective study, spanning over a period of 8 years. PBNO was diagnosed in the presence of a bladder outlet obstruction index (BOOI) >40 with video-urodynamic evidence of obstruction at the bladder neck. The patients were initially managed with alpha-blockers (alfuzosin and tamsulosin) for 3-6 months, and BNI contemplated when pharmacotherapy failed. The patients with upper tract changes managed with upfront BNI or clean intermittent catheterization were excluded. The data for the international prostate symptom score (IPSS), uroflowmetry, urodynamic studies, and ultrasonography of pre and post-treatment periods were reviewed. Treatment outcomes were defined as complete response (>50% improvement in Qmax and IPSS score) and partial response (30%-50% improvement in Qmax and IPSS score) at 3 or 6 months. RESULTS: Ninety-nine patients were analyzed. 21 patients underwent BNI for the failure of medical management and 31 for recurrence of symptoms at a mean follow-up of 18.8 ± 3.5 months (12-70 months). Independent predictors of failure of pharmacotherapy with alpha-blockers were age (P = .021), Pdet@Qmax (P = .015), and BOOI (P = .019). CONCLUSION: Alpha-blockers are more likely to fail in PBNO in younger patients generating higher voiding pressures and BOOI > 60.

Global beta-diversity of angiosperm trees is shaped by Quaternary climate change.

As Earth's climate has varied strongly through geological time, studying the impacts of past climate change on biodiversity helps to understand the risks from future climate change. However, it remains unclear how paleoclimate shapes spatial variation in biodiversity. Here, we assessed the influence of Quaternary climate change on spatial dissimilarity in taxonomic, phylogenetic, and functional composition among neighboring 200-kilometer cells (beta-diversity) for angiosperm trees worldwide. We found that larger glacial-interglacial temperature change was strongly associated with lower spatial turnover (species replacements) and higher nestedness (richness changes) components of beta-diversity across all three biodiversity facets. Moreover, phylogenetic and functional turnover was lower and nestedness higher than random expectations based on taxonomic beta-diversity in regions that experienced large temperature change, reflecting phylogenetically and functionally selective processes in species replacement, extinction, and colonization during glacial-interglacial oscillations. Our results suggest that future human-driven climate change could cause local homogenization and reduction in taxonomic, phylogenetic, and functional diversity of angiosperm trees worldwide.

Universal early warning signals of phase transitions in climate systems.

The potential for complex systems to exhibit tipping points in which an equilibrium state undergoes a sudden and often irreversible shift is well established, but prediction of these events using standard forecast modelling techniques is quite difficult. This has led to the development of an alternative suite of methods that seek to identify signatures of critical phenomena in data, which are expected to occur in advance of many classes of dynamical bifurcation. Crucially, the manifestations of these critical phenomena are generic across a variety of systems, meaning that data-intensive deep learning methods can be trained on (abundant) synthetic data and plausibly prove effective when transferred to (more limited) empirical datasets. This paper provides a proof of concept for this approach as applied to lattice phase transitions: a deep neural network trained exclusively on two-dimensional Ising model phase transitions is tested on a number of real and simulated climate systems with considerable success. Its accuracy frequently surpasses that of conventional statistical indicators, with performance shown to be consistently improved by the inclusion of spatial indicators. Tools such as this may offer valuable insight into climate tipping events, as remote sensing measurements provide increasingly abundant data on complex geospatially resolved Earth systems.

Modelling coupled human-environment complexity for the future of the biosphere: strengths, gaps and promising directions.

Humans and the environment form a single complex system where humans not only influence ecosystems but also react to them. Despite this, there are far fewer coupled human-environment system (CHES) mathematical models than models of uncoupled ecosystems. We argue that these coupled models are essential to understand the impacts of social interventions and their potential to avoid catastrophic environmental events and support sustainable trajectories on multi-decadal timescales. A brief history of CHES modelling is presented, followed by a review spanning recent CHES models of systems including forests and land use, coral reefs and fishing and climate change mitigation. The ability of CHES modelling to capture dynamic two-way feedback confers advantages, such as the ability to represent ecosystem dynamics more realistically at longer timescales, and allowing insights that cannot be generated using ecological models. We discuss examples of such key insights from recent research. However, this strength brings with it challenges of model complexity and tractability, and the need for appropriate data to parameterize and validate CHES models. Finally, we suggest opportunities for CHES models to improve human-environment sustainability in future research spanning topics such as natural disturbances, social structure, social media data, model discovery and early warning signals. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

High exposure of global tree diversity to human pressure.

Safeguarding Earth's tree diversity is a conservation priority due to the importance of trees for biodiversity and ecosystem functions and services such as carbon sequestration. Here, we improve the foundation for effective conservation of global tree diversity by analyzing a recently developed database of tree species covering 46,752 species. We quantify range protection and anthropogenic pressures for each species and develop conservation priorities across taxonomic, phylogenetic, and functional diversity dimensions. We also assess the effectiveness of several influential proposed conservation prioritization frameworks to protect the top 17% and top 50% of tree priority areas. We find that an average of 50.2% of a tree species' range occurs in 110-km grid cells without any protected areas (PAs), with 6,377 small-range tree species fully unprotected, and that 83% of tree species experience nonnegligible human pressure across their range on average. Protecting high-priority areas for the top 17% and 50% priority thresholds would increase the average protected proportion of each tree species' range to 65.5% and 82.6%, respectively, leaving many fewer species (2,151 and 2,010) completely unprotected. The priority areas identified for trees match well to the Global 200 Ecoregions framework, revealing that priority areas for trees would in large part also optimize protection for terrestrial biodiversity overall. Based on range estimates for >46,000 tree species, our findings show that a large proportion of tree species receive limited protection by current PAs and are under substantial human pressure. Improved protection of biodiversity overall would also strongly benefit global tree diversity.

Percutaneous nephrostomy in Ureteropelvic junction obstruction with poorly functioning kidney: Is it still pertinent in adults?

OBJECTIVE: To determine the pertinence of percutaneous nephrostomy drainage in adult patients of primary ureteropelvic junction obstruction with poorly functioning kidneys (<20% split renal function). MATERIAL AND METHODS: Clinical records of all patients with primary ureteropelvic junction obstruction with poorly functioning kidneys who underwent percutaneous nephrostomy drainage in our institute between February 2015 and January 2020 were retrospectively reviewed. The patients were divided into 4 groups according to their split renal function obtained from the Tc-99m ethylenedicysteine diuretic renogram. Group I consisted of all patients having split renal function ≤5%, group II with split renal function 6-10%, groupIII with split renal function 11-15%, and finally group IV with split renal function 16-20%. Those patients inwhom split renal function was improved by >10% and had daily percutaneous nephrostomy output >400 mL, underwent pyeloplasty and the rest underwent nephrectomy. RESULTS: Seventy-two patients were studied, out of which 5 were in group I, 20 in groups II and III each, and27 in group IV. The mean age of presentation was 34.4 ± 14 years. The split renal function improvement of>10% was seen in 55 patients (76.4%) after percutaneous nephrostomy drainage (P < .05). Pyeloplasty wasdone in 40 patients (55.6%) and nephrectomy was done in 32 patients (44.4%). CONCLUSION: In conclusion, we recommend the use of a Tc-99m ethylenedicysteine scan for estimation of split renal function during the initial presentation in every patient followed by reconstructive surgery if split renal function is above 15% and nephrectomy if it is below 5%. The trial of percutaneous nephrostomy is pertinent if split renal function is between 6% and 15%.

Estimating COVID-19 cases and deaths prevented by non-pharmaceutical interventions, and the impact of individual actions: A retrospective model-based analysis.

Simulation models from the early COVID-19 pandemic highlighted the urgency of applying non-pharmaceutical interventions (NPIs), but had limited empirical data. Here we use data from 2020-2021 to retrospectively model the impact of NPIs in Ontario, Canada. Our model represents age groups and census divisions in Ontario, and is parameterized with epidemiological, testing, demographic, travel, and mobility data. The model captures how individuals adopt NPIs in response to reported cases. We compare a scenario representing NPIs introduced within Ontario (closures of workplaces/schools, reopening of schools/workplaces with NPIs in place, individual-level NPI adherence) to counterfactual scenarios wherein alternative strategies (e.g. no closures, reliance on individual NPI adherence) are adopted to ascertain the extent to which NPIs reduced cases and deaths. Combined school/workplace closure and individual NPI adoption reduced the number of deaths in the best-case scenario for the case fatality rate (CFR) from 178548 [CI: 171845, 185298] to 3190 [CI: 3095, 3290] in the Spring 2020 wave. In the Fall 2020/Winter 2021 wave, the introduction of NPIs in workplaces/schools reduced the number of deaths from 20183 [CI: 19296, 21057] to 4102 [CI: 4075, 4131]. Deaths were several times higher in the worst-case CFR scenario. Each additional 9-16 (resp. 285-578) individuals who adopted NPIs in the first wave prevented one additional infection (resp., death). Our results show that the adoption of NPIs prevented a public health catastrophe. A less comprehensive approach, employing only closures or individual-level NPI adherence, would have resulted in a large number of cases and deaths.

Safety and efficacy of retrograde intrarenal surgery in primary and residual renal calculi in children.

BACKGROUND: Minimal invasive approach is the current standard of care in the management of pediatric renal calculi. Current guidelines are clear with extra corporal shock wave lithotripsy (ESWL) and percutaneous nephrolithotomy (PCNL) for stone size less than and greater than 20 mm respectively. Although retrograde intrarenal surgery (RIRS) is well established in adults but literature on its role, safety and efficacy in children is sparsely available. OBJECTIVE: To share our experience of RIRS and its outcome in a pediatric population in both primary and residual calculi of size less than 20 mm. MATERIALS AND METHODS: We retrospectively analysed data of children who underwent RIRS for either primary or residual renal calculi from January 2017 to January 2021. Children less than 5 years underwent passive ureteric dilatation with stenting preoperatively. A7.5 Fr flexible ureteroscope with an access sheath was used in all cases while performing RIRS. All the patients had a stent left in situ at the end of the procedure. Data including stone burden, number of sittings, operative time, stone-free rate (SFR) and grade of post procedural complications were analysed with appropriate statistical methods. RESULTS: A total of 20 patients were included in this study. The median age at presentation was 9 years ranging from 9 months to 18 years. Eight patients (40%) presented with primary renal calculi and underwent RIRS directly while the rest of the 12 (60%) had residual calculi following other procedures like SWL, PCNL before undergoing RIRS. Seven patients (35%) had congenital renal anomalies. The mean stone size and operating time (OR) was 12.6 ± 3.2 mm 84.5 ± 7.2 min respectively. The post-procedural complications were seen in 4 (20%) patients in the form of Grade-1 modified Clavein classification in 3 and Grade 2 in 1 patient. The 100% stone-free rate was achieved in 80% of the cases after first attempt. DISCUSSION: In the present series, RIRS was effective in both the types of stones (primary and residual) less than 20 mm in size, showing 100% stone free rate with maximum of two attempts. Choosing age based optimised passive ureteric dilation led to injury free access for RIRS. Overall complications remained with in low grades and are comparable to current literature. Limitations of the study include small cohort, retrospective study and the need of three anaesthesia procedures in children under 5 years of age. CONCLUSION: RIRS is safe and effective in children with a renal stone(s) less than 20 mm and it has a high success rate in term of achieving stone free status in both primary and residual calculi.

Stochasticity-induced persistence in coupled social-ecological systems.

Stochasticity is often associated with negative consequences for population dynamics since a population may die out due to random chance during periods when population size is very low (stochastic fade-out). Here we develop a coupled social-ecological model based on stochastic differential equations that includes natural expansion and harvesting of a forest ecosystem, and dynamics of conservation opinions, social norms and social learning in a human population. Our objective was to identify mechanisms that influence long-term persistence of the forest ecosystem in the presence of noise. We found that most of the model parameters had a significant influence on the time to extinction of the forest ecosystem. Increasing the social learning rate and the net benefits of conservation significantly increased the time to extinction, for instance. Most interestingly, we found a parameter regime where an increase in the amount of system stochasticity caused an increase in the mean time to extinction, instead of causing stochastic fade-out. This effect occurs for a subset of realizations, but the effect is large enough to increase the mean time to extinction across all realizations. Such "stochasticity-induced persistence" occurs when stochastic dynamics in the social system generates benefits in the forest system at crucial points in its temporal dynamics. We conclude that studying relatively simple social-ecological models has the benefit of facilitating characterization of dynamical states and thereby enabling us to formulate new hypothesis about mechanisms that could be operating in empirical social-ecological systems.

Local Overfishing Patterns Have Regional Effects on Health of Coral, and Economic Transitions Can Promote Its Recovery.

Overfishing has the potential to severely disrupt coral reef ecosystems worldwide, while harvesting at more sustainable levels instead can boost fish yield without damaging reefs. The dispersal abilities of reef species mean that coral reefs form highly connected environments, and the viability of reef fish populations depends on spatially explicit processes such as the spillover effect and unauthorized harvesting inside marine protected areas. However, much of the literature on coral conservation and management has only examined overfishing on a local scale, without considering how different spatial patterns of fishing levels can affect reef health both locally and regionally. Here, we simulate a coupled human-environment model to determine how coral and herbivorous reef fish respond to overfishing across multiple spatial scales. We find that coral and reef fish react in opposite ways to habitat fragmentation driven by overfishing, and that a potential spillover effect from marine protected areas into overfished patches helps coral populations far less than it does reef fish. We also show that ongoing economic transitions from fishing to tourism have the potential to revive fish and coral populations over a relatively short timescale, and that large-scale reef recovery is possible even if these transitions only occur locally. Our results show the importance of considering spatial dynamics in marine conservation efforts and demonstrate the ability of economic factors to cause regime shifts in human-environment systems.

Increasing cover of natural areas at smaller scales can improve the provision of biodiversity and ecosystem services in agroecological mosaic landscapes.

In agroecological mosaic landscapes, the potential of the landscape to provide a broad range of ecosystem services (ES) is vital to human well-being. Landscape structure and composition plays an important role in ecosystem functioning and the production of ES. In this study, we aim to evaluate the potential of natural land use types within an agroecological mosaic landscape to provide biodiversity and ES, and evaluate landscape scales more suitable to identify ES production. We conducted our study in the Credit River Watershed, in southern Ontario (Canada). We assessed the proportion of land use types in the surrounding land cover for each site and, using field-based measurements, analyzed its association with the following parameters: plant species richness (biodiversity), aboveground carbon stock (global climate regulation), atmospheric temperature (local climate regulation), and several parameters for water quality regulation. Our results show that a higher percentage of natural areas within an agroecological mosaic landscape was associated with increased provision of many of the studied parameters. For three of them, the smallest spatial scales of assessment (site and local) had the highest proportion of the variance explained. Atmospheric temperature was the variable that could be assessed in all spatial scales, indicating that natural habitats, especially forests, can regulate temperature in both site, local and regional scales. Our findings highlight the importance of conserving natural ecosystems within the landscape mosaic, enabling the provision of biodiversity and ES. These results have implications for landscape management, as actions conducted at specific landscape scales, such as conservation/restoration efforts or urban expansion, can potentially impact biodiversity and the provision of ES that benefit human well-being.

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.

Correction: Go big or go home: A model-based assessment of general strategies to slow the spread of forest pests via infested firewood.

[This corrects the article DOI: 10.1371/journal.pone.0238979.].