Ecology in the age of climate change: Challenges facing the effective implementation of nature-based solutions in terrestrial ecosystems

At this stage of the Great Acceleration of the Anthropocene, humanity is experiencing the global issues of worsening climate change impacts, devastating damage from more frequent and severe natural disasters and the COVID-19 pandemic, all of which are attributable to ecosystem degradation and biodiversity loss. The global community recognises that these issues pose severe societal and economic risks. “Nature-based solutions” have been posited as a means to address these threats. Nature-based solutions utilise natural terrestrial ecosystem functions to provide environmental, social and economic benefits at low cost. The growing social demand for nature-based solutions constitutes an opportunity for the field of ecology to expand beyond the conventional focus on biodiversity and conservation and shift to presenting biodiversity and ecosystem functions as the basis of human well-being and social sustainability. We sought to identify a trajectory for ecological research that is aimed at contributing to the effective implementation of nature-based solutions. First, we summarise current social needs related to terrestrial ecosystem utilisation. Next, we provide an overview of existing literature and knowledge regarding biodiversity and terrestrial ecosystem function, which are critical to nature-based solutions. Finally, we identify outstanding ecological hurdles to the implementation of these strategies and propose a way forward based on our findings. We explain that any basic presentation of ecological processes requires addressing the impacts of climate change and the interrelatedness of biodiversity, climate and social systems. Enhanced ecological process models are critical for linking biodiversity and ecosystems with climate and social systems. It is crucial to establish a framework that embeds monitoring systems, data infrastructure and delivery systems within society to mobilise terrestrial ecosystem and biodiversity data and results. Furthermore, the implementation of nature-based solutions must include acknowledging trade-offs in objectives and transdisciplinary research with other fields and stakeholders with the shared goal of transformative change. Ecological research must demonstrate more clearly how terrestrial biodiversity and ecosystems are linked to human health and well-being, as well as how they are affected by production and consumption systems. In the age of climate change, the knowledge and tools of the ecologist form the foundation of nature-based solutions and provide an indispensable theoretical basis for this approach.Alternate :æŠ„éŒ²äººæ–°ä¸–ã®å¤§åŠ é€Ÿã¨ã‚‚å‘¼ã°ã‚Œã‚‹æ°—å€™å¤‰å‹•ã®æ™‚ä»£ã«ãŠã„ã¦ã€æ°—å€™å¤‰å‹•å½±éŸ¿ã®é¡•åœ¨åŒ–ã€è‡ªç„¶ç½å®³ã®æ¿€ç”šåŒ–ãƒ»é »ç™ºåŒ–ã€COVID-19の世界的流行などの地球規模の問題が増大している。国際社会では、ã"ã‚Œã‚‰ã®å•é¡Œã¯ç”Ÿæ…‹ç³»ã®åŠ£åŒ–ã‚„ç”Ÿç‰©å¤šæ§˜æ€§ã®æå¤±ãŒè¦å› ã§ã‚ã‚‹ã"と、そして社会経済にも多大な損害ã‚'与える大きなリスクであるã"とが共通の認識となりつつある。そのような状況ã‚'åæ˜ ã—ã€é™¸åŸŸç”Ÿæ…‹ç³»ã®å¤šé¢çš„ãªæ©Ÿèƒ½ã‚'活用するã"とで、低いコストでç'°å¢ƒãƒ»ç¤¾ä¼šãƒ»çµŒæ¸ˆã«ä¾¿ç›Šã‚'もたらし、社会が抱える複数の課題の解決に貢献する「自然ã‚'基盤とした解決策」という新しい概念に大きな期待が寄せられている。ã"の解決策への社会的なニーズの高まりは、生態学が長年取り組ã‚"できた生物多様性や生態系の保全に関する課題ã‚'超えて、生態学が生物多様性や生態系が豊かな人é–"社会ã‚'継続し発展させる知的基盤となるã"とや、生態学の社会的有用性ã‚'示す機会である。そã"で本稿では、気候変動時代における「自然ã‚'åŸºç›¤ã¨ã—ãŸè§£æ±ºç­–ã€ã®å®Ÿè·µã«å‘ã‘ãŸç”Ÿæ…‹å­¦ç ”ç©¶ã®æ–¹å‘ã¥ã‘ã‚'目的とし、陸域生態系の活用に対する社会的なニーズの現状ã‚'概観する。その上で、「自然ã‚'åŸºç›¤ã¨ã—ãŸè§£æ±ºç­–ã€ã®éµã¨ãªã‚‹é™¸åŸŸç”Ÿæ ‹ç³»ã®ç”Ÿç‰©å¤šæ§˜æ€§ã‚„ç”Ÿæ…‹ç³»æ©Ÿèƒ½ã«é–¢ã™ã‚‹çŸ¥è¦‹ã‚'整理して課題ã‚'抽出し、ã"れらã‚'è¸ã¾ãˆã¦ä»Šå¾Œã®ç”Ÿæ…‹å­¦ç ”ç©¶ã®æ–¹å‘æ€§ã‚'å…·ä½"的に示す。まず、現象の基礎的な理解という観点からは、生物多様性ã‚'含む陸域生態系と気候システムや社会システムとの相äº'関係性ã‚'含めた包括的な気候変動影響のメカニズムの解明と、予測・評価のためのプロセスモデルの高度化ã‚'進めるã"と、そして同時に、陸域生態系と生物多様性の変化ã‚'ç¤ºã™ãŸã‚ã®åŠ¹æžœçš„ãªãƒ¢ãƒ‹ã‚¿ãƒªãƒ³ã‚°ã¨æƒ…å ±åŸºç›¤ã®å¼·åŒ–ã‚'行い、データや分析結果ã‚'社会に還元するフレームワークã‚'構築するã"ã¨ãŒå„ªå…ˆäº‹é …ã§ã‚ã‚‹ã€‚ã‚ˆã‚Šå®Ÿè·µçš„ãªè¦³ç‚¹ã‹ã‚‰ã¯ã€ã€Œè‡ªç„¶ã‚'基盤とした解決策」の実装や社会変革などにおいて共通の目標ã‚'ã‚‚ã¤ä»–åˆ†é‡Žã¨ã®å­¦éš›ç ”ç©¶ã‚'積極的に行うã"とにより、実装における目的é–"のトレードオフã‚'示すã"と、健康・福祉の課題や生産・消費システムの中での陸域生態系や生物多様性への影響や役割ã‚'示すã"ã¨ãªã©ãŒå„ªå…ˆäº‹é …ã¨ãªã‚‹ã€‚æ°—å€™å¤‰å‹•ã«ä»£è¡¨ã•ã‚Œã‚‹ä¸ç¢ºå®Ÿæ€§ã®é«˜ã„ç'°å¢ƒä¸‹ã§ã€åŠ¹æžœçš„な「自然ã‚'åŸºç›¤ã¨ã—ãŸè§£æ±ºç­–ã€ã®å®Ÿæ–½ãŸã‚ã«ã¯ã€ãã®ç§‘å­¦çš„åŸºç›¤ã¨ãªã‚‹ç”Ÿæ…‹å­¦ã®çŸ¥è¦‹ã¨ãƒ„ãƒ¼ãƒ«ã¯ä¸å¯æ¬ ã§ã‚ã‚Šã€ã¾ãŸãã®å®Ÿè£…ã‚'通じた社会変革へのé"筋においても生態学の貢献が期待されている。

Extraction of Respiratory Patterns Using Thoracic Bio-Impedance Channels

The world is witnessing a rapid increase in the need for new techniques and methods that allow monitoring of the respiratory system, especially after the emergence of the Covid-19 pandemic. To determine the respiratory rate, respiratory pattern, and inhaled and exhaled cycles, transthoracic bio-impedance signals were used. That showed great effectiveness in monitoring, but to obtain this signal in most cases method requires a large number of electrodes, which must be placed in uncomfortable places for the patient in the case of long-term monitoring. In this work, the possibility of monitoring the respiratory rate and pattern has been studied using signals recorded from different thoracic areas by four bio- impedance channels, which are placed in comfortable places for long-term monitoring. The right thoracic channel showed stability in signal and the best correlation with the respiratory pattern extracted from the transthoracic channel and the study results recommend using it for long-term monitoring. © 2022 IEEE.

Single-arm diagnostic electrocardiography with printed graphene on wearable textiles.

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types of graphene textile electrodes differentiated by the employed fabrication techniques (i.e., dip-coating and spray printing) and successful demonstration of ergonomic and truly wearable, single-arm diagnostic electrocardiography (SADE) using only 3 electrodes positioned on only 1 arm. The performance of the printed graphene e-textile wearable systems were benchmarked against the "gold standard" silver/silver chloride (Ag/AgCl) "wet" electrodes; achieving excellent correlation up to ∼ 96% and ∼ 98% in ECG recordings (15 s duration) acquired with graphene textiles fabricated by dip-coating and spray printing techniques, respectively. In addition, we successfully implemented automatic detection of heartrate of 8 volunteers (mean value: 74.4 bpm) during 5 min of static and dynamic daily activities and benchmarked their recordings with a standard fingertip photoplethysmography (PPG) device. Heart rate variability (HRV) was calculated, and the root means successive square difference (rMMSD) metric was 30 ms during 5 min of recording. Other cardiac parameters such as R-R interval, QRS complex duration, S-T segment duration, and T-wave duration were also detected and compared to typical chest ECG values.

High Incidence of SARS-CoV-2 Variant of Concern Breakthrough Infections Despite Residual Humoral and Cellular Immunity Induced by BNT162b2 Vaccination in Healthcare Workers: A Long-Term Follow-Up Study in Belgium.

To mitigate the massive COVID-19 burden caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), several vaccination campaigns were initiated. We performed a single-center observational trial to monitor the mid- (3 months) and long-term (10 months) adaptive immune response and to document breakthrough infections (BTI) in healthcare workers (n = 84) upon BNT162b2 vaccination in a real-world setting. Firstly, serology was determined through immunoassays. Secondly, antibody functionality was analyzed via in vitro binding inhibition and pseudovirus neutralization and circulating receptor-binding domain (RBD)-specific B cells were assessed. Moreover, the induction of SARS-CoV-2-specific T cells was investigated by an interferon-γ release assay combined with flowcytometric profiling of activated CD4+ and CD8+ T cells. Within individuals that did not experience BTI (n = 62), vaccine-induced humoral and cellular immune responses were not correlated. Interestingly, waning over time was more pronounced within humoral compared to cellular immunity. In particular, 45 of these 62 subjects no longer displayed functional neutralization against the delta variant of concern (VoC) at long-term follow-up. Noteworthily, we reported a high incidence of symptomatic BTI cases (17.11%) caused by alpha and delta VoCs, although vaccine-induced immunity was only slightly reduced compared to subjects without BTI at mid-term follow-up.

Long-term monitoring of drug consumption patterns during the COVID-19 pandemic in a small-sized community in Brazil through wastewater-based epidemiology.

The abuse of legal and illegal drugs is a global public health problem, also affecting the social and economic well-being of the population. Thus, there is a significant interest in monitoring drug consumption. Relevant epidemiological information on lifestyle habits can be obtained from the chemical analysis of urban wastewater. In this work, passive sampling using polar organic chemical integrative samplers (POCIS) was used to quantify licit and illicit drugs biomarkers in wastewater for the application of wastewater-based epidemiology (WBE). In this WBE study, a small urban community of approximately 1179 inhabitants was monitored from 18 March 2020 to 3 March 2021, covering the mobility restriction and flexibilization periods of the COVID-19 pandemic in Brazil. Consumption was estimated for amphetamine, caffeine, cocaine, MDMA, methamphetamine, nicotine, and THC. The highest estimated consumption among illicit drugs was for THC (2369 ± 1037 mg day-1 1000 inh-1) followed by cocaine (353 ± 192 mg day-1 1000 inh-1). There was a negative correlation between consumption of caffeine, cocaine, MDMA, nicotine, and THC with human mobility, expressed by cellular phone mobility reports (P-value = 0.0094, 0.0019, 0.0080, 0.0009, and 0.0133, respectively). Our study is the first long-term drug consumption evaluation during the COVID-19 pandemic, with continuous sampling for almost a whole year. The observed reduction in consumption of both licit and illicit drugs is probably associated with stay-at-home orders and reduced access, which can be due to the closure of commercial facilities during some time of the evaluated period, smaller drug supply, and reduced income of the population due to the shutdown of companies and unemployment. The assay described in this study can be used as a complementary and cost-effective tool to the long-term monitoring of drug use biomarkers in wastewater, a relevant epidemiological strategy currently limited to short collection times.

Assessment of Social Housing Energy and Thermal Performance in Relation to Occupants' Behaviour and COVID-19 Influence-A Case Study in the Basque Country, Spain

Evidence shows that people have a major impact on building performance. Occupants' impact is especially important in social housing, where their occupants may present greater vulnerabilities, and their needs are not always considered. This study aims to analyse the socio-demographic influence in social rental housing concerning hygrothermal comfort and energy consumption in a case study located in Vitoria, Spain during the first 4-month period of 2020 and 2021 (during and after COVID-19 lockdown). An innovative data management system is included, where the users and administration can see in real-time the temperature and consumption in the dwellings. A 2-phase method has been applied;phase 1 is associated with outdoor climate conditions, building properties and social profile. Phase 2 determined the results in energy consumption, indoor hygrothermal comfort and occupant energy-use pattern. The results show that the comfort levels and energy consumption vary according to the analysed social profiles, as well as the heating activation periods and domestic hot water system usage. In conclusion, socio-demographic characteristics of social housing households influence the hygrothermal comfort of their dwellings, occupants' behaviour and heating and domestic hot water energy consumption.

Assessment of Social Housing Energy and Thermal Performance in Relation to Occupants’ Behaviour and COVID-19 Influence—A Case Study in the Basque Country, Spain

Evidence shows that people have a major impact on building performance. Occupants’ impact is especially important in social housing, where their occupants may present greater vulnerabilities, and their needs are not always considered. This study aims to analyse the socio-demographic influence in social rental housing concerning hygrothermal comfort and energy consumption in a case study located in Vitoria, Spain during the first 4-month period of 2020 and 2021 (during and after COVID-19 lockdown). An innovative data management system is included, where the users and administration can see in real-time the temperature and consumption in the dwellings. A 2-phase method has been applied;phase 1 is associated with outdoor climate conditions, building properties and social profile. Phase 2 determined the results in energy consumption, indoor hygrothermal comfort and occupant energy-use pattern. The results show that the comfort levels and energy consumption vary according to the analysed social profiles, as well as the heating activation periods and domestic hot water system usage. In conclusion, socio-demographic characteristics of social housing households influence the hygrothermal comfort of their dwellings, occupants’ behaviour and heating and domestic hot water energy consumption.

Revealing Microclimate around Buildings with Long-Term Monitoring through the Neural Network Algorithms

The profile of urban microclimates is important in many engineering fields, such as occupant’s thermal comfort and health, and other building engineering. To predict the profile of urban microclimate, this study applies the artificial neural network and long short-term memory network predictive models, and an urban microclimate dataset was obtained with a long-term monitoring from year 2017 to 2019 with 5-min resolution including temperature, relative humidity, and solar radiation. Two predictive models were applied, and the first (Model 1) is to apply the predictive techniques to predict the urban microclimate in the real-time sequence, and then extract the characteristics of urban microclimate, while the second (Model 2) is to directly extract the characteristics of the microclimate, and then predict the characteristics of the microclimate. Backpropagation artificial neural network (BP-ANN) and long-short term memory (LSTM) techniques were applied in both models. The results show Model 1 with as the time-series prediction can reach the best (99.92%) of correlation coefficient and 98% of the mean average percentage error (MAPE), for temperature, while 99.66% and 98.18% for relative humidity, respectively, while accuracies in Model 2 decreased to 79% and 88.6% of MAPE for temperature and relative humidity, respectively. The prediction of solar radiation using ANN and LSTM are 51.1% and 57.8% of the correlation coefficient, respectively.

Longitudinal monitoring of SARS-CoV-2 in wastewater using viral genetic markers and the estimation of unconfirmed COVID-19 cases.

In this study, wastewater-based surveillance was carried out to establish the correlation between SARS-CoV-2 viral RNA concentrations in wastewater and the incidence of corona virus disease 2019 (COVID-19) from clinical testing. The influent wastewater of three major water reclamation facilities (WRFs) in Northern Nevada, serving a population of 390,750, was monitored for SARS-CoV-2 viral RNA gene markers, N1 and N2, from June 2020 through September 2021. A total of 614 samples were collected and analyzed. The SARS-CoV-2 concentrations in wastewater were observed to peak twice during the study period. A moderate correlation trend between coronavirus disease 2019 (COVID-19) incidence data from clinical testing and SARS-CoV-2 viral RNA concentrations in wastewater was observed (Spearman r = 0.533). This correlation improved when using weekly average SARS-CoV-2 marker concentrations of wastewater and clinical case data (Spearman r = 0.790), presumably by mitigating the inherent variability of the environmental dataset and the effects of clinical testing artifacts (e.g., reporting lags). The research also demonstrated the value of wastewater-based surveillance as an early warning signal for early detection of trends in COVID-19 incidence. This was accomplished by identifying that the reported clinical cases had a stronger correlation to SARS-CoV-2 wastewater monitoring data when they were estimated to lag 7-days behind the wastewater data. The results aided local decision makers in developing strategies to manage COVID-19 in the region and provide a framework for how wastewater-based surveillance can be applied across localities to enhance the public health monitoring of the ongoing pandemic.

Office buildings occupancy analysis and prediction associated with the impact of the COVID-19 pandemic.

Buildings' occupancy is one of the important factors causing the energy performance and sustainability gap in buildings. Better occupancy prediction decreases this gap both in the design stage and in the use phase of the building. Machine learning-based models proved to be very accurate and fast for occupancy prediction when buildings are exploited under normal conditions. Meanwhile, during the Covid-19 pandemic occupancy of the offices has dramatically changed. The study presents 2 office buildings' long-term monitoring results for different periods of the pandemic. It aims to analyse actual occupancies during the pandemic and its influence on the ELM (Extreme Learning Machine) based occupancy-forecasting models' reliability. The results show much lower actual occupancies in the offices than given in standards and methodologies; it is still low even when quarantines are cancelled. Average peak occupancy within the whole measured period is: for Building A - 12-20% and for Building B - 2-23%. The daily occupancy schedules differ for both offices as they belong to different industries. ELM-SA model has shown low accuracies during pandemic periods as a result of lower occupancies - R2 = 0.27-0.56.

Long-term monitoring of the development and extinction of IgA and IgG responses to SARS-CoV-2 infection.

Despite the great interest of the scientific community in the behavior of the human body after contact with the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), long-term (more than 6 months) monitoring of the immunological status of patients with coronavirus disease 2019 (COVID-19) having varying severity degrees and of the people with a low SARS-CoV-2 viral load is practically absent. The aim of this study is a 9-month monitoring of SARS-CoV-2 infection immune response development and extinction using quantitative assessment of IgA and IgG levels in the blood of healthy donors living in the context of the coronavirus pandemic and of the patients who have undergone COVID-19. The project involved 180 volunteers, of whom 51 persons (28.33%) fell ill with COVID-19 during the observation period. All people who underwent COVID-19 developed a stable humoral immune response but their individual immune status had a number of features. Approximately 39.22% (20 of 51 people) of project participants diagnosed with COVID-19 showed an unusual change in plasma anti-SARS-CoV-2 IgA levels. Relatively high levels of IgA (ratio ~ 3) after recovery persisted for a long time (more than 6 months). In one-third (17 of 51 people) of patients with COVID-19, the IgA level exceeded the IgG level. IgA antibodies appeared earlier and showed a stronger and more robust response to the SARS-CoV-2 virus than IgG. Increased levels of anti-SARS-CoV-2 IgA (ratio from 0.8 to 2.36) throughout the observation period were recorded in 28 of 180 project participants (15.56%) of whom only one person fell ill with COVID-19.