Search

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. [ABSTRACT FROM AUTHOR]

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally. [ABSTRACT FROM AUTHOR]

This paper presents the results of a consensus-driven process identifying 50 priority research questions for historical ecology obtained through crowdsourcing, literature reviews, and in-person workshopping. A deliberative approach was designed to maximize discussion and debate with defined outcomes. Two in-person workshops (in Sweden and Canada) over the course of two years and online discussions were peer facilitated to define specific key questions for historical ecology from anthropological and archaeological perspectives. The aim of this research is to showcase the variety of questions that reflect the broad scope for historical-ecological research trajectories across scientific disciplines. Historical ecology encompasses research concerned with decadal, centennial, and millennial human-environmental interactions, and the consequences that those relationships have in the formation of contemporary landscapes. Six interrelated themes arose from our consensus-building workshop model: (1) climate and environmental change and variability; (2) multi-scalar, multi-disciplinary; (3) biodiversity and community ecology; (4) resource and environmental management and governance; (5) methods and applications; and (6) communication and policy. The 50 questions represented by these themes highlight meaningful trends in historical ecology that distill the field down to three explicit findings. First, historical ecology is fundamentally an applied research program. Second, this program seeks to understand long-term human-environment interactions with a focus on avoiding, mitigating, and reversing adverse ecological effects. Third, historical ecology is part of convergent trends toward transdisciplinary research science, which erodes scientific boundaries between the cultural and natural. [ABSTRACT FROM AUTHOR]

Understanding and managing dynamic coastal landscapes for beach-dependent species requires biological and geological data across the range of relevant environments and habitats. It is difficult to acquire such information; data often have limited focus due to resource constraints, are collected by non-specialists, or lack observational uniformity. We developed an open-source smartphone application called iPlover that addresses these difficulties in collecting biogeomorphic information at piping plover (Charadrius melodus) nest sites on coastal beaches. This paper describes iPlover development and evaluates data quality and utility following two years of collection (n = 1799 data points over 1500 km of coast between Maine and North Carolina, USA). We found strong agreement between field user and expert assessments and high model skill when data were used for habitat suitability prediction. Methods used here to develop and deploy a distributed data collection system have broad applicability to interdisciplinary environmental monitoring and modeling. [ABSTRACT FROM AUTHOR]

In previous work, the authors demonstrated how data from climate simulations can be utilized to estimate regional wind power densities. In particular, it was shown that the quality of wind power densities, estimated from the UPSCALE global dataset in offshore regions of Mexico, compared well with regional high resolution studies. Additionally, a link between surface temperature and moist air density in the estimates was presented. UPSCALE is an acronym for UK on PRACE (the Partnership for Advanced Computing in Europe)—weather-resolving Simulations of Climate for globAL Environmental risk. The UPSCALE experiment was performed in 2012 by NCAS (National Centre for Atmospheric Science)-Climate, at the University of Reading and the UK Met Office Hadley Centre. The study included a 25.6-year, five-member ensemble simulation of the HadGEM3 global atmosphere, at 25km resolution for present climate conditions. The initial conditions for the ensemble runs were taken from consecutive days of a test configuration. In the present paper, the emphasis is placed on the single climate run for a potential future climate scenario in the UPSCALE experiment dataset, using the Representation Concentrations Pathways (RCP) 8.5 climate change scenario. Firstly, some tests were performed to ensure that the results using only one instantiation of the current climate dataset are as robust as possible within the constraints of the available data. In order to achieve this, an artificial time series over a longer sampling period was created. Then, it was shown that these longer time series provided almost the same results than the short ones, thus leading to the argument that the short time series is sufficient to capture the climate. Finally, with the confidence that one instantiation is sufficient, the future climate dataset was analysed to provide, for the first time, a projection of future changes in wind power resources using the UPSCALE dataset. It is hoped that this, in turn, will provide some guidance for wind power developers and policy makers to prepare and adapt for climate change impacts on wind energy production. Although offshore locations around Mexico were used as a case study, the dataset is global and hence the methodology presented can be readily applied at any desired location. [ABSTRACT FROM AUTHOR]

Rapid reduction of anthropogenic greenhouse gas emissions is required to mitigate disastrous impacts of climate change. The Kyoto Protocol introduced international emissions trading (IET) to accelerate the reduction of carbon dioxide (CO2) emissions. The IET controls CO2 emissions through the allocation of marketable emission permits to sovereign countries. The costs for acquiring additional permits provide buyers with an incentive to reduce their CO2 emissions. However, permit price has declined to a low level during the first commitment period (CP1). The downward trend in permit price is attributed to deficiencies of the Kyoto Protocol: weak compliance enforcement, the generous allocation of permits to transition economies (hot air), and the withdrawal of the US. These deficiencies created a buyer's market dominated by price-making buyers. In this paper, I develop a coalitional game of the IET, and demonstrate that permit buyers have dominant bargaining power. In my model, called cooperative emissions trading (CET) game, a buyer purchases permits from sellers only if the buyer forms a coalition with the sellers. Permit price is determined by bargaining among the coalition members. I evaluated the demand-side and supply-side bargaining power (DBP and SBP) using Shapley value, and obtained the following results: (1) Permit price is given by the product of the buyer's willingness-to-pay and the SBP (= 1 - DBP). (2) The DBP is greater than or equal to the SBP. These results indicate that buyers can suppress permit price to low levels through bargaining. The deficiencies of the Kyoto Protocol enhance the DBP, and contribute to the demand-side dominance in the international permit market.

Human-caused climate change is happening; nearly all climate scientists are convinced of this basic fact according to surveys of experts and reviews of the peer-reviewed literature. Yet, among the American public, there is widespread misunderstanding of this scientific consensus. In this paper, we report results from two experiments, conducted with national samples of American adults, that tested messages designed to convey the high level of agreement in the climate science community about human-caused climate change. The first experiment tested hypotheses about providing numeric versus non-numeric assertions concerning the level of scientific agreement. We found that numeric statements resulted in higher estimates of the scientific agreement. The second experiment tested the effect of eliciting respondents' estimates of scientific agreement prior to presenting them with a statement about the level of scientific agreement. Participants who estimated the level of agreement prior to being shown the corrective statement gave higher estimates of the scientific consensus than respondents who were not asked to estimate in advance, indicating that incorporating an "estimation and reveal" technique into public communication about scientific consensus may be effective. The interaction of messages with political ideology was also tested, and demonstrated that messages were approximately equally effective among liberals and conservatives. Implications for theory and practice are discussed.

There is currently widespread public misunderstanding about the degree of scientific consensus on human-caused climate change, both in the US as well as internationally. Moreover, previous research has identified important associations between public perceptions of the scientific consensus, belief in climate change and support for climate policy. This paper extends this line of research by advancing and providing experimental evidence for a "gateway belief model" (GBM). Using national data (N = 1104) from a consensus-message experiment, we find that increasing public perceptions of the scientific consensus is significantly and causally associated with an increase in the belief that climate change is happening, human-caused and a worrisome threat. In turn, changes in these key beliefs are predictive of increased support for public action. In short, we find that perceived scientific agreement is an important gateway belief, ultimately influencing public responses to climate change.

Understanding the topographic basis for microclimatic variation remains fundamental to predicting the site level effects of warming air temperatures. Quantifying diurnal fluctuation and seasonal extremes in relation to topography offers insight into the potential relationship between site level conditions and changes in regional climate. The present study investigated an annual understory temperature regime for 50 sites distributed across a topographically diverse area (>12 km2) comprised of mixed evergreen-deciduous woodland vegetation typical of California coastal ranges. We investigated the effect of topography and tree cover on site-to-site variation in near-surface temperatures using a combination of multiple linear regression and multivariate techniques. Sites in topographically depressed areas (e.g., valley bottoms) exhibited larger seasonal and diurnal variation. Elevation (at 10 m resolution) was found to be the primary driver of daily and seasonal variations, in addition to hillslope position, canopy cover and northness. The elevation effect on seasonal mean temperatures was inverted, reflecting large-scale cold-air pooling in the study region, with elevated minimum and mean temperature at higher elevations. Additionally, several of our sites showed considerable buffering (dampened diurnal and seasonal temperature fluctuations) compared to average regional conditions measured at an on-site weather station. Results from this study help inform efforts to extrapolate temperature records across large landscapes and have the potential to improve our ecological understanding of fine-scale seasonal climate variation in coastal range environments. [ABSTRACT FROM AUTHOR]

Beliefs and attitudes form the core of public opinion about climate change. Network analysis can reveal the structural configuration of these beliefs and attitudes. In this research, we utilize a belief system framework to identify key psychological elements, track change in the density of these belief systems over time and across political groups, and analyze the structural heterogeneity of belief systems within and between political groups in the United States. Drawing on fifteen waves of nationally representative survey data from 2010 to 2021 (N = 16,742), our findings indicate that worry about climate change is the most central psychological element. Interestingly, we find that among politically unaffiliated individuals, the connections between psychological elements have strengthened over time, implying an increase in the consistency of belief systems within this group. Despite the political polarization in beliefs about climate change between Republicans and Democrats, our findings reveal that the ways these two groups organize and structure climate change beliefs systems are not markedly different compared to those of other groups. These findings provide theoretical and practical insights for climate change experts and communicators. [ABSTRACT FROM AUTHOR]

Climate change challenges countries around the world, and news media are key to the public's awareness and perception of it. But how are news media approaching climate change across countries? With the problem of climate change and its solution being global, it is key to determine whether differences in climate change news reports exist and what they are across countries. This study employs supervised machine learning to uncover topical and terminological differences between newspaper articles on climate change. An original dataset of climate change articles is presented, originating from 7 newspapers and 3 countries across the world, and published in English during 26 Conference of the Parties (COP) meetings from the United Nations Framework Convention on Climate Change (UNFCC). Three aspects are used to discriminate between articles, being (1) countries, (2) political orientations, and (3) COP meetings. Our results reveal differences with regard to how newspaper articles approach climate change globally. Specifically, climate change-related terminology of left-oriented newspapers is more prevalent compared to their right-oriented counterparts. Also, over the years, newspapers' climate change-related terminology has evolved to convey a greater sense of urgency. [ABSTRACT FROM AUTHOR]

Ongoing climate change substantially alters snowfall patterns with severe but diverging consequences for global ski areas. A global assessment as well as the investigation of potential implications for mountain ecosystems is currently lacking. We quantify future trends in natural snow cover days under different climate change scenarios until 2100 in seven major global skiing regions and discuss implications for mountainous biodiversity by analysing how natural snow cover days relate to regional human population density. Within all major skiing regions, snow cover days are projected to decrease substantially under every assessed climate change scenario. Thirteen percent of all current ski areas are projected to completely lose natural annual snow cover and one fifth will experience a reduction of more than 50% by 2071–2100 relative to historic baselines. Future skiable areas will concentrate in less populated areas, towards continental regions and inner parts of the mountain ranges. As skiable areas will be located at greater distances to highly populated areas in the future, we expect an expansion of infrastructure and increasing intervening actions (i.e., artificial snowmaking, slope grooming) to prolong snow duration. Our results are concerning for both the recreational and economic value of skiing as well as for mountain biodiversity since vulnerable high-altitude species might be threatened by space reductions with ski area expansion. [ABSTRACT FROM AUTHOR]

Climate change and non-communicable diseases (NCDs) are considered the 21st Century's major health and development challenges. Both pose a disproportionate burden on low- and middle-income countries that are unprepared to cope with their synergistic effects. These two challenges pose risks for achieving many of the sustainable development goals (SDGs) and are both impacted by globalization through different pathways. While there are important insights on how climate change and or globalization impact NCDs in the general literature, comprehensive research that explores the influence of climate change and or globalization on NCDs is limited, particularly in the context of Africa. This review documents the pathways through which climate change and or globalization influence NCDs in Africa. We conducted a comprehensive literature search in eight electronic databases—Web of Science, PubMed, Scopus, Global Health Library, Science Direct, Medline, ProQuest, and Google Scholar. A total of 13864 studies were identified. Studies that were identified from more than one of the databases were automatically removed as duplicates (n = 9649). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 27 studies were eventually included in the final review. We found that the impacts of climate change and or globalization on NCDs act through three potential pathways: reduction in food production and nutrition, urbanization and transformation of food systems. Our review contributes to the existing literature by providing insights into the impact of climate change and or globalization on human health. We believe that our findings will help enlighten policy makers working on these pathways to facilitate the development of effective policy and public health interventions to mitigate the effects of climate change and globalization on the rising burden of NCDs and goal 3 of the SDG, in particular. [ABSTRACT FROM AUTHOR]

Palynological analysis of surface soil and sub-surface sediments from the outwash plain of Hamtah Glacier, Lahaul-Spiti, India, has brought out the vegetation and climatic changes in the area during the last 1580 years. The arboreal and non-arboreal pollen ratio (AP/NAP) has been used to demarcate the different vegetation and climatic zones, complemented by the frequencies of the broad-leaved taxa. Lower values of thermophilous, broad-leaved arboreal taxa, indicate that the region experienced cold-arid conditions between 1580 and 1330 yr BP (AD 370–620); which can be related to the Dark Ages Cold Period (DACP). Thereafter, between 1330 and 950 yr BP (AD 620–1000), a rejuvenation of the broad-leaved elements reflects the initiation of a comparatively warm and moist phase, marking the Medieval Climatic Anomaly (MCA) in the region. The warm-moist phase was, however, short-lived, and from 950 yr BP to the Present (AD 1000 onwards), the region saw a return to cold-arid conditions, as evidenced by a sharp fall in the AP/NAP ratio. This cold-arid phase was, nevertheless, punctuated by a warm-moist period during 790 to 680 yr BP (AD 1160–1270), which marks the terminal phase of the MCA. After the termination of the MCA, the Little Ice Age (LIA) is well-marked in the area. The culmination of the long cold-arid regime is characterized by warmer conditions over the last 160 years, which is the manifestation of the Current Warm Period (CWP). Magnetic susceptibility (χlf) and sediment geochemistry (Weathering Index of Parker) were also attempted to have a multi-proxy approach, and show a general compatibility with the palynological data. The palaeoclimatic evidences suggest shorter warm periods and extended colder phases during the last 1580 years; in this high-altitude, cold-desert, Trans Himalayan region. [ABSTRACT FROM AUTHOR]

Plant and pollinator communities are vital for transnational food chains. Like many natural systems, they are affected by global change: rapidly deteriorating conditions threaten their numbers. Previous theoretical studies identified the potential for community-wide collapse above critical levels of environmental stressors—so-called bifurcation-induced tipping points. Fortunately, even as conditions deteriorate, individuals have some adaptive capacity, potentially increasing the boundary for a safe operating space where changes in ecological processes are reversible. Our study considers this adaptive capacity of pollinators to resource availability and identifies a new threat to disturbed pollinator communities. We model the adaptive foraging of pollinators in changing environments. Pollinator's adaptive foraging alters the dynamical responses of species, to the advantage of some—typically generalists—and the disadvantage of others, with systematic non-linear and non-monotonic effects on the abundance of particular species. We show that, in addition to the extent of environmental stress, the pace of change of environmental stress can also lead to the early collapse of both adaptive and nonadaptive pollinator communities. Specifically, perturbed communities exhibit rate-induced tipping points at stress levels within the safe boundary defined for constant stressors. With adaptive foraging, tipping is a more asynchronous collapse of species compared to nonadaptive pollinator communities, meaning that not all pollinator species reach a tipping event simultaneously. These results suggest that it is essential to consider the adaptive capacity of pollinator communities for monitoring and conservation. Both the extent and the rate of stress change relative to the ability of communities to recover are critical environmental boundaries. Author summary: Plant and pollinator communities, which support global food chains, are threatened. A significant problem is the reduction of pollination, where not enough plants are pollinated and are at risk of becoming extinct. Environmental change, such as climate change or increasing pesticide use, can cause this reduction. As long as these changes stay under certain boundaries, undesirable ecological processes like the reduction in pollination are reversible. Crossing these boundaries means tipping of pollinator communities might occur; the system might collapse. Pollinator communities can adapt, for instance, through adaptive foraging by changing which plants they prefer in response to environmental deterioration. We include adaptive foraging in a theoretical model of plant and pollinator communities. We show that plant and pollinator communities are vulnerable to the extent of stressors but also to how fast these stressors increase. Our model shows that, with adaptation, the extinction of species is more sequential and spreads out in time and may even temporarily favor especially generalist species. [ABSTRACT FROM AUTHOR]

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. [ABSTRACT FROM AUTHOR]

The analysis of the tree radial growth response to climate is crucial for dendroclimatological research. However, the response relationships between tree-ring indices and climatic factors at different timescales are not yet clear. In this study, the tree-ring width of Huashan pine (Pinus armandii) from Huashan in the Qinling Mountains, north-central China, was used to explore the response differences of tree growth to climatic factors at daily, pentad (5 days), dekad (10 days) and monthly timescales. Correlation function and linear regression analysis were applied in this paper. The tree-ring width showed a more sensitive response to daily and pentad climatic factors. With the timescale decreasing, the absolute value of the maximum correlation coefficient between the tree-ring data and precipitation increases as well as temperature (mean, minimum and maximum temperature). Compared to the other three timescales, pentad was more suitable for analysing the response of tree growth to climate. Relative to the monthly climate data, the association between the tree-ring data and the pentad climate data was more remarkable and accurate, and the reconstruction function based on the pentad climate was also more reliable and stable. We found that the major climatic factor limiting Huashan pine growth was the precipitation of pentads 20–35 (from April 6 to June 24) rather than the well-known April–June precipitation. The pentad was also proved to be a better timescale for analysing the climate and tree growth in the western and eastern Qinling Mountains. The formation of the earlywood density of Chinese pine (Pinus tabulaeformis) from Shimenshan in western Qinling was mainly affected by the maximum temperature of pentads 28–32 (from May 16 to June 9). The maximum temperature of pentads 28–33 (from May 16 to June 14) was the major factor affecting the ring width of Chinese pine from Shirenshan in eastern Qinling. [ABSTRACT FROM AUTHOR]

The scientific community has recognized the importance of integrating farmer’s perceptions and knowledge (FPK) for the development of sustainable pest and disease management strategies. However, the knowledge gap between indigenous and scientific knowledge still contributes to misidentification of plant health constraints and poor adoption of management solutions. This is particularly the case in the context of smallholder farming in developing countries. In this paper, we present a case study on coffee production in Uganda, a sector depending mostly on smallholder farming facing a simultaneous and increasing number of socio-ecological pressures. The objectives of this study were (i) to examine and relate FPK on Arabica Coffee Pests and Diseases (CPaD) to altitude and the vegetation structure of the production systems; (ii) to contrast results with perceptions from experts and (iii) to compare results with field observations, in order to identify constraints for improving the information flow between scientists and farmers. Data were acquired by means of interviews and workshops. One hundred and fifty farmer households managing coffee either at sun exposure, under shade trees or inter-cropped with bananas and spread across an altitudinal gradient were selected. Field sampling of the two most important CPaD was conducted on a subset of 34 plots. The study revealed the following findings: (i) Perceptions on CPaD with respect to their distribution across altitudes and perceived impact are partially concordant among farmers, experts and field observations (ii) There are discrepancies among farmers and experts regarding management practices and the development of CPaD issues of the previous years. (iii) Field observations comparing CPaD in different altitudes and production systems indicate ambiguity of the role of shade trees. According to the locality-specific variability in CPaD pressure as well as in FPK, the importance of developing spatially variable and relevant CPaD control practices is proposed. [ABSTRACT FROM AUTHOR]

Large-scale climate history of the past millennium reconstructed solely from tree-ring data is prone to underestimate the amplitude of low-frequency variability. In this paper, we aimed at solving this problem by utilizing a novel method termed “MDVM”, which was a combination of the ensemble empirical mode decomposition (EEMD) and variance matching techniques. We compiled a set of 211 tree-ring records from the extratropical Northern Hemisphere (30–90°N) in an effort to develop a new reconstruction of the annual mean temperature by the MDVM method. Among these dataset, a number of 126 records were screened out to reconstruct temperature variability longer than decadal scale for the period 850–2000 AD. The MDVM reconstruction depicted significant low-frequency variability in the past millennium with evident Medieval Warm Period (MWP) over the interval 950–1150 AD and pronounced Little Ice Age (LIA) cumulating in 1450–1850 AD. In the context of 1150-year reconstruction, the accelerating warming in 20th century was likely unprecedented, and the coldest decades appeared in the 1640s, 1600s and 1580s, whereas the warmest decades occurred in the 1990s, 1940s and 1930s. Additionally, the MDVM reconstruction covaried broadly with changes in natural radiative forcing, and especially showed distinct footprints of multiple volcanic eruptions in the last millennium. Comparisons of our results with previous reconstructions and model simulations showed the efficiency of the MDVM method on capturing low-frequency variability, particularly much colder signals of the LIA relative to the reference period. Our results demonstrated that the MDVM method has advantages in studying large-scale and low-frequency climate signals using pure tree-ring data. [ABSTRACT FROM AUTHOR]

The Giant African Snail (Achatina fulica) is considered to be one the world’s 100 worst invasive alien species. The snail has an impact on native biodiversity, and on agricultural and horticultural crops. In India, it is known to feed on more than fifty species of native plants and agricultural crops and also outcompetes the native snails. It was introduced into India in 1847 and since then it has spread all across the country. In this paper, we use ecological niche modeling (ENM) to assess the distribution pattern of Giant African Snail (GAS) under different climate change scenarios. The niche modeling results indicate that under the current climate scenario, Eastern India, peninsular India and the Andaman and Nicobar Islands are at high risk of invasion. The three different future climate scenarios show that there is no significant change in the geographical distribution of invasion prone areas. However, certain currently invaded areas will be more prone to invasion in the future. These regions include parts of Bihar, Southern Karnataka, parts of Gujarat and Assam. The Andaman and Nicobar and Lakshadweep Islands are highly vulnerable to invasion under changed climate. The Central Indian region is at low risk due to high temperature and low rainfall. An understanding of the invasion pattern can help in better management of this invasive species and also in formulating policies for its control. [ABSTRACT FROM AUTHOR]

The Central African Republic is one of the world’s most vulnerable countries, suffering from chronic poverty, violent conflicts and weak disaster resilience. In collaboration with Doctors without Borders/Médecins Sans Frontières (MSF), this study presents a novel approach to collect information about socio-economic vulnerabilities related to malnutrition, access to resources and coping capacities. The first technical test was carried out in the North of the country (sub-prefecture Kabo) in May 2015. All activities were aimed at the investigation of technical feasibility, not at operational data collection, which requires a random sampling strategy. At the core of the study is an open-source Android application named SATIDA COLLECT that facilitates rapid and simple data collection. All assessments were carried out by local MSF staff after they had been trained for one day. Once a mobile network is available, all assessments can easily be uploaded to a database for further processing and trend analysis via MSF in-house software. On one hand, regularly updated food security assessments can complement traditional large-scale surveys, whose completion can take up to eight months. Ideally, this leads to a gain in time for disaster logistics. On the other hand, recording the location of every assessment via the smart phones’ GPS receiver helps to analyze and display the coupling between drought risk and impacts over many years. Although the current situation in the Central African Republic is mostly related to violent conflict it is necessary to consider information about drought risk, because climatic shocks can further disrupt the already vulnerable system. SATIDA COLLECT can easily be adapted to local conditions or other applications, such as the evaluation of vaccination campaigns. Most importantly, it facilitates the standardized collection of information without pen and paper, as well as straightforward sharing of collected data with the MSF headquarters or other aid organizations. [ABSTRACT FROM AUTHOR]

This paper reports the first find of pika remains in the Iberian Peninsula, at a site in central Spain. A fragmented mandible of Ochotona cf. pusilla was unearthed from Layer 3 (deposited some 63.4±5.5 ka ago as determined by thermoluminescence) of the Buena Pinta Cave. This record establishes new limits for the genus geographic distribution during the Pleistocene, shifting the previous edge of its known range southwest by some 500 km. It also supports the idea that, even though Europe’s alpine mountain ranges represented a barrier that prevented the dispersal into the south to this and other taxa of small mammals from central and eastern Europe, they were crossed or circumvented at the coldest time intervals of the end of the Middle Pleistocene and of the Late Pleistocene. During those periods both the reduction of the forest cover and the emersion of large areas of the continental shelf due to the drop of the sea level probably provided these species a way to surpass this barrier. The pika mandible was found accompanying the remains of other small mammals adapted to cold climates, indicating the presence of steppe environments in central Iberia during the Late Pleistocene. [ABSTRACT FROM AUTHOR]

The urgency of climate change mitigation calls for a profound shift in personal behavior. This paper investigates psycho-social correlates of extra mitigation behavior in response to climate change, while also testing for potential (unobserved) heterogeneity in European citizens' decision-making. A person's extra mitigation behavior in response to climate change is conceptualized--and differentiated from common mitigation behavior--as some people's broader and greater levels of behavioral engagement (compared to others) across specific self-reported mitigation actions and behavioral domains. Regression analyses highlight the importance of environmental psychographics (i.e., attitudes, motivations, and knowledge about climate change) and socio-demographics (especially country-level variables) in understanding extra mitigation behavior. By looking at the data through the lens of segmentation, significant heterogeneity is uncovered in the associations of attitudes and knowledge about climate change--but not in motivational or socio-demographic links--with extra mitigation behavior in response to climate change, across two groups of environmentally active respondents. The study has implications for promoting more ambitious behavioral responses to climate change, both at the individual level and across countries.

We present an integrated hydrology/water operations simulation model of the Tuolumne and Merced River Basins, California, using the Water Evaluation and Planning (WEAP) platform. The model represents hydrology as well as water operations, which together influence water supplied for agricultural, urban, and environmental uses. The model is developed for impacts assessment using scenarios for climate change and other drivers of water system behavior. In this paper, we describe the model structure, its representation of historical streamflow, agricultural and urban water demands, and water operations. We describe projected impacts of climate change on hydrology and water supply to the major irrigation districts in the area, using uniform 2 °C, 4 °C, and 6 °C increases applied to climate inputs from the calibration period. Consistent with other studies, we find that the timing of hydrology shifts earlier in the water year in response to temperature warming (5-21 days). The integrated agricultural model responds with increased water demands 2 °C (1.4-2.0%), 4 °C (2.8-3.9%), and 6 °C (4.2-5.8%). In this sensitivity analysis, the combination of altered hydrology and increased demands results in decreased reliability of surface water supplied for agricultural purposes, with modeled quantity-based reliability metrics decreasing from a range of 0.84-0.90 under historical conditions to 0.75-0.79 under 6 °C warming scenario.

Saving energy is an important pillar for the mitigation of climate change. Electric devices (e.g., freezer and television) are an important player in the residential sector in the final demand for energy. Consumers’ purchase decisions are therefore crucial to successfully reach the energy-efficiency goals. Putting energy labels on products is often considered an adequate way of empowering consumers to make informed purchase decisions. Consequently, this approach should contribute to reducing overall energy consumption. The effectiveness of its measurement depends on consumers’ use and interpretation of the information provided. Despite advances in energy efficiency and a mandatory labeling policy, final energy consumption per capita is in many countries still increasing. This paper provides a systematic analysis of consumers’ reactions to one of the most widely used eco-labels, the European Union (EU) energy label, by using eye-tracking methodology as an objective measurement. The study’s results partially support the EU’s mandatory policy, showing that the energy label triggers attention toward energy information in general. However, the energy label’s effect on consumers’ actual product choices seems to be rather low. The study’s results show that the currently used presentation format on the label is insufficient. The findings suggest that it does not facilitate the integration of energy-related information. Furthermore, the current format can attract consumers to focus more on energy-efficiency information, leading them to disregard information about actual energy consumption. As a result, the final energy consumption may increase because excellent ratings on energy efficiency (e.g., A++) do not automatically imply little consumption. Finally, implications for policymakers and suggestions for further research are discussed. [ABSTRACT FROM AUTHOR]

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in . [ABSTRACT FROM AUTHOR]

The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012). I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult. [ABSTRACT FROM AUTHOR]

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition. [ABSTRACT FROM AUTHOR]

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind—the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns. [ABSTRACT FROM AUTHOR]

In this work, I evaluate the impact of species distribution models (SDMs) on the current status of environmental and ecological journals by asking the question to which degree development of SDMs in the literature is related to recent changes in the impact factors of ecological journals. The hypothesis evaluated states that research fronts are likely to attract research attention and potentially drive citation patterns, with journals concentrating papers related to the research front receiving more attention and benefiting from faster increases in their impact on the ecological literature. My results indicate a positive relationship between the number of SDM related articles published in a journal and its impact factor (IF) growth during the period 2000–09. However, the percentage of SDM related papers in a journal was strongly and positively associated with the percentage of papers on climate change and statistical issues. The results support the hypothesis that global change science has been critical in the development of SDMs and that interest in climate change research in particular, rather than the usage of SDM per se, appears as an important factor behind journal IF increases in ecology and environmental sciences. Finally, our results on SDM application in global change science support the view that scientific interest rather than methodological fashion appears to be the major driver of research attraction in the scientific literature. [ABSTRACT FROM AUTHOR]

Rice production in the Mekong River Delta of Vietnam (MRD) is endangered by sea-level rise and an associated increase in the incidence of salinity intrusion. This paper examines the diffusion of salt tolerant rice varieties in the MRD that were promoted through Consortium for Unfavorable Rice Environments (CURE) activities. Factors associated with adoption of CURE-related varieties are estimated using a random utilty model and a dataset of 800 farm households with rice fields in salinity prone areas of the MRD. Results suggest that there has been widespread adoption of CURE-related varieties in salinity-prone areas. Further, multivariate analysis reveals that environment and location characteristics, rather than household characteristics, are the most important determinants of adoption. In particular, CURE-related varieties are more likely to be adopted in high-salinity-risk areas that are not protected by salinity barrier gates. Neighbhors' adoption decisions also strongly influence household decisions to adopt CURE-related varieties. The contracting of mechanization, particularly for land preparation and harvest, requires the coordination of village households in timing of planting, harvest and varietal duration. This coordination appears to extend to choice of CURE-related varieties. Finally, CURE-related varieties and other varieties generate similar net revenues in a year with low salinity exposure, suggesting that CURE-related varieties are a low-cost insurance policy against salinity inundation in high risk areas. Combined, these results highlight the need to address complex factors beyond current economic profits, like environment, community choices, and risk mitigation, when designing technologies and policies that support farmer adaptation to climatic change. [ABSTRACT FROM AUTHOR]

Background: Dengue is a mosquito-borne viral disease and its transmission is closely linked to climate. We aimed to review available information on the projection of dengue in the future under climate change scenarios. Methods: Using five databases (PubMed, ProQuest, ScienceDirect, Scopus and Web of Science), a systematic review was conducted to retrieve all articles from database inception to 30th June 2019 which projected the future of dengue under climate change scenarios. In this review, "the future of dengue" refers to disease burden of dengue, epidemic potential of dengue cases, geographical distribution of dengue cases, and population exposed to climatically suitable areas of dengue. Results: Sixteen studies fulfilled the inclusion criteria, and five of them projected a global dengue future. Most studies reported an increase in disease burden, a wider spatial distribution of dengue cases or more people exposed to climatically suitable areas of dengue as climate change proceeds. The years 1961–1990 and 2050 were the most commonly used baseline and projection periods, respectively. Multiple climate change scenarios introduced by the Intergovernmental Panel on Climate Change (IPCC), including B1, A1B, and A2, as well as Representative Concentration Pathway 2.6 (RCP2.6), RCP4.5, RCP6.0 and RCP8.5, were most widely employed. Instead of projecting the future number of dengue cases, there is a growing consensus on using "population exposed to climatically suitable areas for dengue" or "epidemic potential of dengue cases" as the outcome variable. Future studies exploring non-climatic drivers which determine the presence/absence of dengue vectors, and identifying the pivotal factors triggering the transmission of dengue in those climatically suitable areas would help yield a more accurate projection for dengue in the future. Conclusions: Projecting the future of dengue requires a systematic consideration of assumptions and uncertainties, which will facilitate the development of tailored climate change adaptation strategies to manage dengue. Author summary: Dengue is the most important arboviral disease globally, and the transmission of dengue is closely linked to climate. This review assembled all existing studies which have quantified the impact of climate change on dengue under climate change scenarios. We observed that most studies reported an increase in disease burden, a wider spatial distribution of dengue cases or more people exposed to climatically suitable areas of dengue as climate change proceeds. The years 1961–1990 and 2050 were the most commonly used baseline and projection periods, respectively. Multiple climate change scenarios introduced by the Intergovernmental Panel on Climate Change (IPCC), including B1, A1B, and A2, as well as Representative Concentration Pathway 2.6 (RCP2.6), RCP4.5, RCP6.0 and RCP8.5, were most widely employed. Instead of projecting the future number of dengue cases, there is a growing consensus on using "population exposed to climatically suitable areas for dengue" or "epidemic potential of dengue cases" as the outcome variable. Future studies exploring non-climatic drivers which determine the presence/absence of dengue vectors, and identifying the pivotal factors triggering the transmission of dengue in those climatically suitable areas would help yield a more accurate projection for dengue in the future. [ABSTRACT FROM AUTHOR]

This paper investigates the correlation between climate, environment and human land use in the Westernmost Mediterranean on both sides of the Strait of Gibraltar during the Late Glacial. Using a multi-proxy approach on a sample of 300 sites from the Solutrean and Magdalenian of the Iberian Peninsula and from the Iberomaurusian in Morocco, we find evidence for significant changes in settlement patterns and site density after the Last Glacial Maximum. In Southern Iberia, during Heinrich Stadial 1, hyperarid zones expanded drastically from the south-eastern coast to the West through the Interior. This aridification process heavily affected Magdalenian settlement in the South and caused a strong decline of hunter-gatherer population. Southern Iberia during Heinrich Stadial 1 turned out to be a high-risk environment when compared to Northern Iberia. At the same time, the Late Iberomaurusian of Morocco, although considered to be situated in a high-risk environment as well, experiences an increase of sites and expansion of settlement area. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) are excellent tools for quantifying many aspects of future climate dynamics but are too computationally expensive to produce large collections of scenarios for downstream users of ESM data. In particular, many researchers focused on the impacts of climate change require large collections of ESM runs to rigorously study the impacts to both human and natural systems of low-frequency high-importance events, such as multi-year droughts. Climate model emulators provide an effective mechanism for filling this gap, reproducing many aspects of ESMs rapidly but with lower precision. The R package quickly generates thousands of realizations of gridded temperature fields by randomizing the residuals of pattern scaling temperature output from any single ESM, retaining the spatial and temporal variance and covariance structures of the input data at a low computational cost. The R package described here extends this capability to produce joint realizations of multiple variables, with a focus on temperature and precipitation in an open source software package available for community use (). This substantially improves the package by removing the requirement that the ESM variables be normally distributed, and will enable researchers to quickly generate covarying temperature and precipitation data that are synthetic but faithful to the characteristics of the original ESM. [ABSTRACT FROM AUTHOR]

When attempting to estimate the impacts of future climate change it is important to reflect on information gathered during the past. Understanding historical trends may also aid in the assessment of likely future agricultural and horticultural changes. The timing of agricultural activities, such as grape harvest dates, is known to be influenced by climate and weather. However, fewer studies have been carried out on grapevine yield and quality. In this paper an analysis is undertaken of long-term data from the period 1805-2010 on grapevine yield (hl/ha) and must sugar content (°Oe) and their relation to temperature. Monthly mean temperatures were obtained for the same time period. Multiple regression was used to relate the viticulture variables to temperature, and long-term trends were calculated. Overall, the observed trends over time are compatible with results from other long term studies. The findings confirm a relationship between yield, must sugar content and temperature data; increased temperatures were associated with higher yields and higher must sugar content. However, the potential increase in yield is currently limited by legislation, while must sugar content is likely to further increase with rising temperatures.

Agricultural irrigation practices will likely be affected by climate change. In this paper, we use a statistical model relating observed water use by U.S. producers to the moisture deficit, and then use this statistical model to project climate changes impact on both the fraction of agricultural land irrigated and the irrigation rate (m³ ha⁻¹). Data on water withdrawals for US states (1985-2005) show that both quantities are highly positively correlated with moisture deficit (precipitation--PET). If current trends hold, climate change would increase agricultural demand for irrigation in 2090 by 4.5-21.9 million ha (B1 scenario demand: 4.5-8.7 million ha, A2 scenario demand: 9.1-21.9 million ha). Much of this new irrigated area would occur in states that currently have a wet climate and a small fraction of their agricultural land currently irrigated, posing a challenge to policymakers in states with less experience with strict regulation of agriculture water use. Moreover, most of this expansion will occur in states where current agricultural production has relatively low market value per hectare, which may make installation of irrigation uneconomical without significant changes in crops or practices by producers. Without significant increases in irrigation efficiency, climate change would also increase the average irrigation rate from 7,963 to 8,400-10,415 m³ ha⁻¹ (B1 rate: 8,400-9,145 m³ ha⁻¹, A2 rate: 9,380-10,415 m³ ha⁻¹). The irrigation rate will increase the most in states that already have dry climates and large irrigation rates, posing a challenge for water supply systems in these states. Accounting for both the increase in irrigated area and irrigation rate, total withdrawals might increase by 47.7-283.4 billion m³ (B1 withdrawal: 47.7-106.0 billion m³, A2 withdrawal: 117.4-283.4 billion m³). Increases in irrigation water-use efficiency, particularly by reducing the prevalence of surface irrigation, could eliminate the increase in total irrigation withdrawals in many states.

Background: Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia., Methods/principal Findings: We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections., Conclusions/significance: We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

In this paper evidence of anthropogenic influence over the warming of the 20th century is presented and the debate regarding the time-series properties of global temperatures is addressed in depth. The 20th century global temperature simulations produced for the Intergovernmental Panel on Climate Change's Fourth Assessment Report and a set of the radiative forcing series used to drive them are analyzed using modern econometric techniques. Results show that both temperatures and radiative forcing series share similar time-series properties and a common nonlinear secular movement. This long-term co-movement is characterized by the existence of time-ordered breaks in the slope of their trend functions. The evidence presented in this paper suggests that while natural forcing factors may help explain the warming of the first part of the century, anthropogenic forcing has been its main driver since the 1970's. In terms of Article 2 of the United Nations Framework Convention on Climate Change, significant anthropogenic interference with the climate system has already occurred and the current climate models are capable of accurately simulating the response of the climate system, even if it consists in a rapid or abrupt change, to changes in external forcing factors. This paper presents a new methodological approach for conducting time-series based attribution studies.

Background: Monitoring vegetation dynamics and their responses to climate change has been the subject of considerable research. This paper aims to detect change trends in grassland activity on the Tibetan Plateau between 1982 and 2006 and relate these to changes in climate., Methodology/principal Findings: Grassland activity was analyzed by evaluating remotely sensed Normalized Difference Vegetation Index (NDVI) data collected at 15-day intervals between 1982 and 2006. The timings of vegetation stages (start of green-up, beginning of the growing season, plant maturity, start of senescence and end of the growing season) were assessed using the NDVI ratio method. Mean NDVI values were determined for major vegetation stages (green-up, fast growth, maturity and senescence). All vegetation variables were linked with datasets of monthly temperature and precipitation, and correlations between variables were established using Partial Least Squares regression. Most parts of the Tibetan Plateau showed significantly increasing temperatures, as well as clear advances in late season phenological stages by several weeks. Rainfall trends and significant long-term changes in early season phenology occurred on small parts of the plateau. Vegetation activity increased significantly for all vegetation stages. Most of these changes were related to increasing temperatures during the growing season and in some cases during the previous winter. Precipitation effects appeared less pronounced. Warming thus appears to have shortened the growing season, while increasing vegetation activity., Conclusions/significance: Shortening of the growing season despite a longer thermally favorable period implies that vegetation on the Tibetan Plateau is unable to exploit additional thermal resources availed by climate change. Ecosystem composition may no longer be well attuned to the local temperature regime, which has changed rapidly over the past three decades. This apparent lag of the vegetation assemblage behind changes in climate should be taken into account when projecting the impacts of climate change on ecosystem processes.

Heatwaves pose an important risk for population health and are associated with an increased demand for emergency care. To find factors causing such overload, an online Delphi study included 15 experts in emergency medicine, disaster medicine, or public health. One open-ended question was delivered in the first round. After content analysis, the obtained statements were sent to the experts in two rounds to be rated on a 7-point linear scale. Consensus was defined as a standard deviation ≤ 1.0. Thirty-one statements were obtained after content analysis. The experts agreed on 18 statements, mostly focusing on the input section of patient processing and identifying stakeholders, the population, and primary care as targets of potential interventions. Additional dedicated resources and bed capacity were deemed important as per throughput and output sections, respectively. These findings could be used in the future to implement and test solutions to increase emergency healthcare resilience during heatwaves and reduce disaster risk due to climatic change. [ABSTRACT FROM AUTHOR]

The multifaceted effects of climate change on physical and biogeochemical processes are rapidly altering marine ecosystems but often are considered in isolation, leaving our understanding of interactions between these drivers of ecosystem change relatively poor. This is particularly true for shallow coastal ecosystems, which are fuelled by a combination of distinct pelagic and benthic energy pathways that may respond to climate change in fundamentally distinct ways. The fish production supported by these systems is likely to be impacted by climate change differently to those of offshore and shelf ecosystems, which have relatively simpler food webs and mostly lack benthic primary production sources. We developed a novel, multispecies size spectrum model for shallow coastal reefs, specifically designed to simulate potential interactive outcomes of changing benthic and pelagic energy inputs and temperatures and calculate the relative importance of these variables for the fish community. Our model, calibrated using field data from an extensive temperate reef monitoring program, predicts that changes in resource levels will have much stronger impacts on fish biomass and yields than changes driven by physiological responses to temperature. Under increased plankton abundance, species in all fish trophic groups were predicted to increase in biomass, average size, and yields. By contrast, changes in benthic resources produced variable responses across fish trophic groups. Increased benthic resources led to increasing benthivorous and piscivorous fish biomasses, yields, and mean body sizes, but biomass decreases among herbivore and planktivore species. When resource changes were combined with warming seas, physiological responses generally decreased species' biomass and yields. Our results suggest that understanding changes in benthic production and its implications for coastal fisheries should be a priority research area. Our modified size spectrum model provides a framework for further study of benthic and pelagic energy pathways that can be easily adapted to other ecosystems. The multifaceted effects of climate change on physical and biogeochemical processes are rapidly altering marine ecosystems. This size-based modelling study shows that the source, size and abundance of primary and secondary producers are critical to understanding impacts of global heating on coastal fish communities. [ABSTRACT FROM AUTHOR]

Background: Despite the wealth of scientific information on the health effects of air pollution, the adult public's lifestyle continues to be largely detrimental towards the environment. Objective: The purpose of the study was to determine whether a short interactive teaching session on air pollution could shift reported behavioral choices of adolescents towards environmentally friendlier options. Methods: We performed a pilot randomized control trial in which eighth-grade students were randomized to receive a one-hour script-based teaching on either the effects of air pollution on lung health (intervention group) or the role of vaccination in public health (active control group). The enrolled students completed a survey (15 multiple-choice questions; five targeting understanding (score range 5 to 20); ten targeting behavioral choices (score range 10 to 38) newly designed for this study to evaluate their understanding and predict their future behavior towards air pollution immediately before, immediately after, and one month after the teaching sessions. Results: Seventy-seven students (age = 13.5±0.6 years; 50.4% female; median annual family income = $25K-$50K with 70.1% <$50K; 39 assigned to intervention group) were enrolled in the study. The teaching sessions did not result in any significant change in the participants' understanding domain scores in either the intervention or the control groups. However, the intervention (air pollution) teaching session resulted in a statistically significant increase in behavior domain score from baseline to immediately post-teaching, which continued to be present at one-month follow-up (mean ± standard deviation of score change immediately after = 1.7±3.3; score change 1-month after = 2.5±3.2; P<0.001; minimally important difference = 1.0). Discussion: This pilot study highlights the potential of a short one-time teaching session in promoting environmentally friendly behavior choices among adolescents. [ABSTRACT FROM AUTHOR]

Food insecurity in recent years has increased worldwide due to many planetary events such as the COVID-19 pandemic, geopolitical conflicts, the climate crisis, and globalization of markets. Adolescents are a particularly vulnerable group to food insecurity, as they enter adulthood with less parental supervision and greater personal autonomy, but less legislative or institutional protection. The experience of food insecurity in adolescents is influenced by several environmental factors at different levels (interpersonal, organizational, community, and societal), although they are not usually addressed in the design of interventions, prioritizing the individual behavioural factors. We present a scoping review protocol for assessing and identifying the environmental factors that could influence adolescents' food insecurity. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) and the PRISMA guidelines for Scoping Reviews (PRISMA-ScR) to prepare the protocol. The search strategy will be performed in the following databases: Pubmed/Medline, EMBASE, Biblioteca Virtual de Salud, EBSCOHost, Scopus, Web of Science, and Cochrane Library Plus. The reference list of the included studies will also be hand-searched. Grey literature will be search through the electronic database Grey Literature Report, and local, provincial, national, and international organisations' websites. Assessment of eligibility after screening of titles, abstract and full text, and the resolution of discrepancies will be performed by three independent reviewers. This scoping review will contribute to refine the "logic model of the problem" which constitutes the first step in the intervention mapping protocol. The "logic model of the problem" from the intervention mapping protocol will serve to classify and analyse the environmental factors. The findings from this review will be presented to relevant stakeholders that have a role in shaping the environmental factors. [ABSTRACT FROM AUTHOR]

Societies of the later Early to Middle Bronze Age (ca. 2200–1600 BC) in the Carpathian Basin exhibited complex, hierarchical and regionally influential socio-political organisation that came to an abrupt end in the 16th century BC. Considered a collapse by some, this change was characterised by abandonment of virtually all central places / nodes in settlement networks. Until recently, the complexity that characterised the period was believed to have substantially diminished alongside depopulation. This model was reinforced by a combination of the loss of established external networks and low-resolution knowledge of where and how people lived in the first stages of the Late Bronze Age (between 1600 and 1200 BC). We contest the idea of a diminished Late Bronze Age and argue that a fully opposite trajectory can be identified–increased scale, complexity and density in settlement systems and intensification of long-distance networks. We present results of a settlement survey in the southern Pannonian Plain using remote and pedestrian prospection, augmented by small-scale excavations. New absolute dates are used to define the occupational history of sites dating primarily between 1500–1200 BC. We argue that climate change played a substantial role in in the transformation of settlement networks, creating a particular ecological niche enabling societies to thrive. New and specific forms of landscape exploitation developed that were characterised by proximity to wetlands and minor watercourses. In this context, the largest monuments of Bronze Age Europe were created and inhabited. In considering the origins and demise of these megasites and related settlements, we provide a new model for Late Bronze Age societies in the Carpathian Basin and their regional relevance. [ABSTRACT FROM AUTHOR]

Extreme weather events are increasing in frequency and severity due to climate change, yet many of their impacts on human populations are not well understood. We examine the relationship between prior extreme weather events and food environment characteristics. To do so, we conduct a U.S. county-level analysis that assesses the association between extreme weather events and two common food retail environment dimensions. Overall, we find a relationship between higher levels of historic extreme weather exposure and lower food availability and accessibility. In addition, we find heterogeneity in association across the distribution of the number of extreme weather events and event type. Specifically, we find that more localized extreme weather events are more associated with a reduction of access and availability than broad geographic events. Our findings suggest that as extreme weather events amplify in intensity and increase in frequency, new approaches for mitigating less acute and longer-term impacts are needed to address how extreme weather may interact with and reinforce existing disparities in food environment factors. Furthermore, our research argues that integrated approaches to improving vulnerable food retail environments will become an important component of extreme weather planning and should be a consideration in both disaster- and food-related policy. [ABSTRACT FROM AUTHOR]

The Karner blue butterfly (Lycaeides melissa samuelis, or Kbb), a federally endangered species under the U.S. Endangered Species Act in decline due to habitat loss, can be further threatened by climate change. Evaluating how climate shapes the population trend of the Kbb can help in the development of adaptive management plans. Current demographic models for the Kbb incorporate in either a density-dependent or density-independent manner. We instead created mixed density-dependent and -independent (hereafter "endo-exogenous") models for Kbbs based on long-term count data of five isolated populations in the upper Midwest, United States during two flight periods (May to June and July to August) to understand how the growth rates were related to previous population densities and abiotic environmental conditions, including various macro- and micro-climatic variables. Our endo-exogenous extinction risk models showed that both density-dependent and -independent components were vital drivers of the historical population trends. However, climate change impacts were not always detrimental to Kbbs. Despite the decrease of population growth rate with higher overwinter temperatures and spring precipitations in the first generation, the growth rate increased with higher summer temperatures and precipitations in the second generation. We concluded that finer spatiotemporally scaled models could be more rewarding in guiding the decision-making process of Kbb restoration under climate change. [ABSTRACT FROM AUTHOR]

The increasing prevalence of antibiotic-resistant bacteria poses a significant threat to global human health. Countering this threat requires the public to understand the causes of, and risks posed by, antibiotic resistance (AR) to support changing healthcare and societal approaches to antibiotic use. To gauge public knowledge, we designed a questionnaire to assess awareness of causes of AR (both personal and societal) and knowledge of absolute and relative risks posed by antibiotic-resistant bacteria. Our findings reveal that while >90% respondents recognized personal behaviours as limiting AR, few individuals recognized the importance of societal factors e.g. the use of antibiotics in livestock. Furthermore, more respondents named viruses (either by name or as a group) than bacteria as reasons to take antibiotics, indicating lack of understanding. The absolute numbers of current and predicted future deaths attributed to antibiotic-resistant bacteria were under-estimated and respondents were more concerned about climate change and cancer than AR across all age groups and educational backgrounds. Our data reveal that despite heightened public awareness of infection-control measures following the COVID-19 pandemic, there remains a knowledge gap related to contributors and impacts of increasing numbers of antibiotic-resistant bacteria. [ABSTRACT FROM AUTHOR]

Settlement crises in ancient cultures of Western Asia are commonly thought to be caused by climatic events such as severe droughts. However, the insufficient climate proxy situation in this region challenges the inference of clear relationships between climate and settlement dynamics. We investigate the Holocene climatic changes on the Varamin Plain in the context of the climatic history of Western Central Asia by using a transient comprehensive Earth System Model simulation (8 ka BP to pre-industrial), a high-resolution regional snapshot simulation and a synthesis of pollen-based climate reconstructions. In line with the reconstructions, the models reveal only slightly varying mean climatic conditions on the Varamin Plain but indicate substantial changes in seasonality during the Holocene. Increased precipitation during spring, combined with lower temperature and potentially stronger snow accumulation on the upstream Alborz mountains may have led to an increased water supply on the alluvial fan during the vegetation period and thus to more favourable conditions for agricultural production during the Mid-Holocene compared to modern times. According to the model, dry periods on the Central Iranian Plateau are related to particularly weak Westerly winds, fostering the subsidence in the mid-troposphere and hampering precipitation over the region. The model reveals that dry periods have spatially heterogenous manifestations, thus explaining why they do not appear in all proxy records in the wider study region. In fact, the climatic signal may depend on local environmental conditions. The interaction of the topography with the atmospheric circulation leads to additional spatial heterogeneity. Although our results provide several indications for a connection between climate and settlement dynamics, the small overall changes in moisture call into question whether climate is the main driver for settlement discontinuities on the Central Iranian Plateau. To shed further light on this issue, more high-resolution long-term proxy records are needed. [ABSTRACT FROM AUTHOR]

Climatic changes, such as heatwaves, pose unprecedented challenges for insects, as escalated temperatures above the thermal optimum alter insect reproductive strategies and energy metabolism. While thermal stress responses have been reported in different insect species, thermo-induced developmental abnormalities in phloem-feeding pests are largely unknown. In this laboratory study, we raised two groups of first instar nymphs belonging to two clones of the pea aphid Acyrthosiphon pisum, on fava beans Vicia faba. The instars developed and then asexually reproduced under constant exposure to a sub-lethal heatwave (27°C) for 14 days. Most mothers survived but their progenies showed abnormalities, as stillbirths and appendageless or weak nymphs with folded appendages were delivered. Clone N116 produced more deceased and appendageless embryos, contrary to N127, which produced fewer dead and more malformed premature embryos. Interestingly, the expression of the HSP70 and HSP83 genes differed in mothers between the clones. Moreover, noticeable changes in metabolism, e.g., lipids, were also detected and that differed in response to stress. Deformed offspring production after heat exposure may be due to heat injury and differential HSP gene expression, but may also be indicative of a conflict between maternal and offspring fitness. Reproductive altruism might have occurred to ensure some of the genetically identical daughters survive. This is because maintaining homeostasis and complete embryogenesis could not be simultaneously fulfilled due to the high costs of stress. Our findings shine new light on pea aphid responses to heatwaves and merit further examination across different lineages and species. [ABSTRACT FROM AUTHOR]

As the current climate crisis intensifies, drought resistant crops are becoming more important due to their ability to withstand the increasingly hotter and drier summers. Such crops are valuable for pollinators as they provide food resources for wild and managed species. The carob tree (Ceratonia siliqua L.) represents an example of a heat- and drought- resistant crop, able to grow in dry areas with practically no inputs. The current study assessed over two growing seasons the diversity of wild bees and other pollinators relying on carob flowers, as well as the contribution of animal pollination to carob production. Carob flowers were subjected to two treatments: Open pollination, where inflorescences were left untreated, and wind pollination, where inflorescences were bagged in a mesh during blooming. Weekly observations during blooming showed that Apis mellifera was the most frequent floral visitor followed by wild bees and wasps. Carob flowers were visited by at least 10 different wild bee species. Open-pollinated flowers produced significantly more pods, with the benefit ranging from 4 to 16 times higher production, depending on the region. Open pollination led to pods with greater weight, length and number of seeds compared to pods derived from wind pollination. The results of the current study highlight the importance of animal pollination to carob production, as well as the significance of carob trees to wild bee conservation. [ABSTRACT FROM AUTHOR]