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Introduction: In connection to food insecurity, adaptation of new techniques or alteration of regular behavior is executed that translates to coping strategies. This paper has used data from food security and nutrition surveillance project (FSNSP), which collects information from a nationally representative sample in Bangladesh on coping behaviors associated with household food insecurity. To complement the current understanding of different coping strategies implemented by the Bangladeshi households, the objective of this paper has been set to examine the demographic and socio-economic characteristics of the food insecure households which define their propensity towards adaptation of different types of coping strategies. Methodology: FSNSP follows a repeated cross-sectional survey design. Information of 23,374 food insecure households available from February 2011 to November 2013 was selected for the analyses. Coping strategies were categorized as financial, food compromised and both. Multinomial logistic regression was employed to draw inference. Results: Majority of the households were significantly more inclined to adopt both multiple financial and food compromisation coping strategies. Post-aman season, educational status of the household head and household women, occupation of the household’s main earner, household income, food insecurity status, asset, size and possession of agricultural land were found to be independently and significantly associated with adaptation of both financial and food compromisation coping strategies relative to only financial coping strategies. The relative risk ratio of adopting food compromisation coping relative to financial coping strategies when compared to mildly food insecure households, was 4.54 times higher for households with moderate food insecurity but 0.3 times lower when the households were severely food insecure. Whereas, households were 8.04 times and 4.98 times more likely to adopt both food compromisation and financial relative to only financial coping strategies if moderately and severely food insecure respectively when compared to being mildly food insecure. Conclusion: Households suffering from moderate and severe food insecurity, are more likely to adopt both financial and food compromisation coping strategies. [ABSTRACT FROM AUTHOR]

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa demonstrate the replicability of this approach in rural and peri-urban areas of other developing and least developed countries around the world. [ABSTRACT FROM AUTHOR]

Although substantial attention has focused on efforts by the new Administration to block environmental policies, climate politics have been contentious in the US since well before the election of Donald Trump. In this paper, we extend previous work on empirical examinations of echo chambers in US climate politics using new data collected on the federal climate policy network in summer 2016. We test for the similarity and differences at two points in time in homophily and echo chambers using Exponential Random Graph Models (ERGM) to compare new findings from 2016 to previous work on data from 2010. We show that echo chambers continue to play a significant role in the network of information exchange among policy elites working on the issue of climate change. In contrast to previous findings where echo chambers centered on a binding international commitment to emission reductions, we find that the pre-existing echo chambers have almost completely disappeared and new structures have formed around one of the main components of the Obama Administration’s national climate policy: the Clean Power Plan. These results provide empirical evidence that science communication and policymaking at the elite level shift in relation to the policy instruments under consideration. [ABSTRACT FROM AUTHOR]

Accurate reporting and forecasting of PM2.5 concentration are important for improving public health. In this paper, we propose a partial differential equation (PDE) model, specially, a linear diffusive equation, to describe the spatial-temporal characteristics of PM2.5 in order to make short-term prediction. We analyze the temporal and spatial patterns of a real dataset from China’s National Environmental Monitoring and validate the PDE-based model in terms of predicting the PM2.5 concentration of the next day by the former days’ history data. Our experiment results show that the PDE model is able to characterize and predict the process of PM2.5 transport. For example, for 300 continuous days of 2016, the average prediction accuracy of the PDE model over all city-regions is 93% or 83% based on different accuracy definitions. To our knowledge, this is the first attempt to use PDE-based model to study PM2.5 prediction in both temporal and spatial dimensions. [ABSTRACT FROM AUTHOR]

Background: There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species’ responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Objectives: Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. Data sources and study eligibility criteria: We systematically reviewed SDM studies published from 2003–2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. Synthesis methods and limitations: We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. Results: There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. Conclusions: We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis. [ABSTRACT FROM AUTHOR]

Many countries have some kind of energy-system transformation either planned or ongoing for various reasons, such as to curb carbon emissions or to compensate for the phasing out of nuclear energy. One important component of these transformations is the overall reduction in energy demand. It is generally acknowledged that the domestic sector represents a large share of total energy consumption in many countries. Increased energy efficiency is one factor that reduces energy demand, but behavioral approaches (known as “sufficiency”) and their respective interventions also play important roles. In this paper, we address citizens’ heterogeneity regarding both their current behaviors and their willingness to realize their sufficiency potentials—that is, to reduce their energy consumption through behavioral change. We collaborated with three Swiss cities for this study. A survey conducted in the three cities yielded thematic sets of energy-consumption behavior that various groups of participants rated differently. Using this data, we identified four groups of participants with different patterns of both current behaviors and sufficiency potentials. The paper discusses intervention types and addresses citizens’ heterogeneity and behaviors from a city-based perspective. [ABSTRACT FROM AUTHOR]

The paper explores the degree to which exposure to natural disasters and poor governance (quality of governance) is associated with absolute child poverty in sixty-seven middle- and low-income countries. The data is representative for about 2.8 billion of the world´s population. Institutionalist tend to argue that many of society’s ills, including poverty, derive from fragile or inefficient institutions. However, our findings show that although increasing quality of government tends to be associated with less poverty, the negative effects of natural disasters on child poverty are independent of a country´s institutional efficiency. Increasing disaster victims (killed and affected) is associated with higher rates of child poverty. A child´s estimated odds ratio to be in a state of absolute poverty increases by about a factor of 5.7 [95% CI: 1.7 to 18.7] when the average yearly toll of disasters in the child´s country increases by one on a log-10 scale. Better governance correlates with less child poverty, but it does not modify the correlation between child poverty and natural disasters. The results are based on hierarchical regression models that partition the variance into three parts: child, household, and country. The models were cross-sectional and based on observational data from the Demographic Health Survey and the Multiple Indicator Cluster Survey, which were collected at the beginning of the twenty-first millennium. The Sustainable Development Goals are a principle declaration to halt climate change, but they lack a clear plan on how the burden of this change should be shared by the global community. Based on our results, we suggest that the development agencies should take this into account and to articulate more equitable global policies to protect the most vulnerable, specifically children. [ABSTRACT FROM AUTHOR]

This paper brings advances in weather data collection and modeling, and developments in socioeconomic climate microsimulations to bear on the analysis of the implications of climate change (CC) in the design of public policies to combat food insecurity. It uses new downscaled predictions of future climate in 2050, derived from three Earth System Models calibrated with a new historical weather station dataset for Peru. This climate data is used in a three-stage socioeconomic microsimulation model that includes climate risk, and deals with the endogeneity of incomes and simultaneity of expected food consumption and its variability. We estimate the impact of CC on agricultural yields, and find results consistent and fully bounded within what the global simulations literature has found, with yields falling up to 13% in some regions. However, we show that these drops (and increases) in yields translate to much smaller changes in food consumption, and also surprisingly, to very minor impacts on vulnerability to food insecurity. The document explores what explains this surprising result, showing that in addition to characteristics that are specific to Peru, there are household and market mediating mechanisms that are available in all countries, which explain how changes in yields, and corresponding farm incomes have a reduced impact in vulnerability to food insecurity. Finally, in light of these findings, we explore which policies might have greater impact in reducing food insecurity in contexts of hunger prevalence. [ABSTRACT FROM AUTHOR]

This paper investigates how former hunter-gatherers living along the southern North Sea coast in NW Europe adapted to long-term and short-term climatic and environmental changes at the beginning of the Holocene. It is argued that contemporaneous hunter-gatherers repeatedly changed their hunting equipment in response to changing climate and environment, not just for functional reasons but mainly driven by socio-territorial considerations. Based on a Bayesian analysis of 122 critically selected radiocarbon dates a broad chronological correlation is demonstrated between rapid changes in the design and technology of stone projectiles and short but abrupt cooling events, occurring at 10.3, 9.3 and 8.2 ka cal BP. Combined with the rapid sea level rises and increased wildfires these climatic events probably impacted the lifeways of hunter-gatherers in such a way that they increasingly faced resource stress and competition, forcing them to invest in the symbolic defense of their social territories. [ABSTRACT FROM AUTHOR]

Cities are major drivers of environmental change at all scales and are especially at risk from the ensuing effects, which include poor air quality, flooding and heat waves. Typically, these issues are studied on a city-by-city basis owing to the spatial complexity of built landscapes, local topography and emission patterns. However, to ensure knowledge sharing and to integrate local-scale processes with regional and global scale modelling initiatives, there is a pressing need for a world-wide database on cities that is suited for environmental studies. In this paper we present a European database that has a particular focus on characterising urbanised landscapes. It has been derived using tools and techniques developed as part of the World Urban Database and Access Portal Tools (WUDAPT) project, which has the goal of acquiring and disseminating climate-relevant information on cities worldwide. The European map is the first major step toward creating a global database on cities that can be integrated with existing topographic and natural land-cover databases to support modelling initiatives. [ABSTRACT FROM AUTHOR]

This paper examines search and rescue and backcountry medical response constraints in the Canadian Arctic and potential for unmanned aerial vehicles (UAV) to aid in response and preparedness. Semi-structured interviews (n = 18) were conducted with search and rescue responders, Elders, and emergency management officials to collect data on current emergency response and potential for UAV use. UAV test flights (n = 17) were undertaken with community members. We analyzed five years of weather data to examine UAV flight suitability. Numerous challenges face Arctic search and rescue and backcountry emergency response. Changing social and environmental conditions were described as increasing vulnerability to backcountry emergencies. Responders desired additional first aid and emergency training. Legal and weather restrictions were found to limit where, when and who could fly UAVs. UAVs were demonstrated to have potential benefits for hazard monitoring but not for SAR or medical response due to legal restrictions, weather margins, and local capacity. We find that communities are ill-prepared for ongoing SAR demands, let alone a larger disaster. There are numerous limitations to the use of consumer UAVs by Arctic communities. Prevention of backcountry medical emergencies, building resilience to disasters, and first responder training should be prioritized over introducing UAVs to the response system. [ABSTRACT FROM AUTHOR]

While the 2016 Paris Agreement is in many ways an important attainment with the potential to represent a milestone in humanity’s path towards sustainable development, and avoid thus a potential calamitous and destructive future, the achievement of the goals set in the agreement is a long way off. This paper investigates one of the most important worldwide hurdles frustrating the implementation of the policies required to limit environmental degradation and limit pollution, namely the still insufficient public support for the necessary environmental policies and their associated cost. Using a comparative database generated through an experimental study on tax compliance and policy preferences run in five countries (USA, UK, Italy, Sweden and Romania), I will evaluate five explanatory models of the degree to which people support environmentally friendly policies by accepting higher tax burdens and increased collective solidarity. [ABSTRACT FROM AUTHOR]

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts. [ABSTRACT FROM AUTHOR]

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months. [ABSTRACT FROM AUTHOR]

Presently, climate change has increased the frequency of extreme meteorological events such as tropical cyclones. In the western Pacific basin, these cyclones are called typhoons, and in this area, around Taiwan Island, their frequency has almost doubled since 2000. When approaching landmasses, typhoons have devastating effects on coastal vegetation. The increased frequency of these events has challenged the survival of coastal plant species and their posttyphoon recovery. In this study, a population of coastal gynodioecious Ficus pedunculosa var. mearnsii (Mearns fig) was surveyed for two years to investigate its recovery after Typhoon Morakot, which occurred in August 2009. Similar to all the Ficus species, the Mearns fig has an obligate mutualistic association with pollinating fig wasp species, which requires syconia (the closed Ficus inflorescence) to complete its life cycle. Moreover, male gynodioecious fig species produces both pollen and pollen vectors, whereas the female counterpart produces only seeds. The recovery of the Mearns fig was observed to be rapid, with the production of both leaves and syconia. The syconium:leaf ratio was greater for male trees than for female trees, indicating the importance of syconium production for the wasp survival. Pollinating wasps live for approximately 1 day; therefore, receptive syconia are crucial. Every typhoon season, few typhoons pass by the coasts where the Mearns fig grows, destroying all the leaves and syconia. In this paper, we highlight the potential diminution of the fig population that can lead to the extinction of the mutualistic pair of species. The effects of climate change on coastal species warrant wider surveys. [ABSTRACT FROM AUTHOR]

The objective of this work is to develop a simple methodology for high resolution crop suitability analysis under current and future climate, easily applicable and useful in Least Developed Countries. The approach addresses both regional planning in the context of climate change projections and pre-emptive short-term rural extension interventions based on same-year agricultural season forecasts, while implemented with off-the-shelf resources. The developed tools are applied operationally in a case-study developed in three regions of Guinea-Bissau and the obtained results, as well as the advantages and limitations of methods applied, are discussed. In this paper we show how a simple approach can easily generate information on climate vulnerability and how it can be operationally used in rural extension services. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them. [ABSTRACT FROM AUTHOR]

The cotton mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae), is a serious invasive species that significantly damages plants of approximately 60 families around the world. It is originally from North America and has also been introduced to other continents. Our goals were to create a current and future potential global distribution map for this pest under climate change with MaxEnt software. We tested the hypothesis of niche conservatism for P. solenopsis by comparing its native niche in North America to its invasive niches on other continents using Principal components analyses (PCA) in R. The potentially suitable habitat for P. solenopsis in its native and non-native ranges is presented in the present paper. The results suggested that the mean temperature of the wettest quarter and the mean temperature of the driest quarter are the most important environmental variables determining the potential distribution of P. solenopsis. We found strong evidence for niche shifts in the realized climatic niche of this pest in South America and Australia due to niche unfilling; however, a niche shift in the realized climatic niche of this pest in Eurasian owing to niche expansion. [ABSTRACT FROM AUTHOR]

Up until now montane cloud forest (MCF) in Taiwan has only been mapped for selected areas of vegetation plots. This paper presents the first comprehensive map of MCF distribution for the entire island. For its creation, a Random Forest model was trained with vegetation plots from the National Vegetation Database of Taiwan that were classified as “MCF” or “non-MCF”. This model predicted the distribution of MCF from a raster data set of parameters derived from a digital elevation model (DEM), Landsat channels and texture measures derived from them as well as ground fog frequency data derived from the Moderate Resolution Imaging Spectroradiometer. While the DEM parameters and Landsat data predicted much of the cloud forest’s location, local deviations in the altitudinal distribution of MCF linked to the monsoonal influence as well as the Massenerhebung effect (causing MCF in atypically low altitudes) were only captured once fog frequency data was included. Therefore, our study suggests that ground fog data are most useful for accurately mapping MCF. [ABSTRACT FROM AUTHOR]

The dry subtropics are subject to a rapid expansion of crops and pastures over vast areas of natural woodlands and savannas. In this paper, we explored the effect of this transformation on vegetation productivity (magnitude, and seasonal and long-term variability) along aridity gradients which span from semiarid to subhumid conditions, considering exclusively those areas with summer rains (>66%). Vegetation productivity was characterized with the proxy metric “Enhanced Vegetation Index” (EVI) (2000 to 2012 period), on 6186 natural and cultivated sampling points on five continents, and combined with a global climatology database by means of additive models for quantile regressions. Globally and regionally, cultivation amplified the seasonal and inter-annual variability of EVI without affecting its magnitude. Natural and cultivated systems maintained a similar and continuous increase of EVI with increasing water availability, yet achieved through contrasting ways. In natural systems, the productivity peak and the growing season length displayed concurrent steady increases with water availability, while in cultivated systems the productivity peak increased from semiarid to dry-subhumid conditions, and stabilized thereafter giving place to an increase in the growing season length towards wetter conditions. Our results help to understand and predict the ecological impacts of deforestation on vegetation productivity, a key ecosystem process linked to a broad range of services. [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]

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change’s causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) are an effective way of predicting the potential distribution of species and their response to environmental change. Most SDMs apply presence data to a relatively generic set of predictive variables such as climate. However, this weakens the modelling process by overlooking the responses to more cryptic predictive variables. In this paper we demonstrate a means by which data gathered from an intensive animal trapping study can be used to enhance SDMs by combining field data with bioclimatic modelling techniques to determine the future potential distribution for the koomal (Trichosurus vulpecula hypoleucus). The koomal is a geographically isolated subspecies of the common brushtail possum, endemic to south-western Australia. Since European settlement this taxon has undergone a significant reduction in distribution due to its vulnerability to habitat fragmentation, introduced predators and tree/shrub dieback caused by a virulent group of plant pathogens of the genus Phytophthora. An intensive field study found: 1) the home range for the koomal rarely exceeded 1 km in in length at its widest point; 2) areas heavily infested with dieback were not occupied; 3) gap crossing between patches (>400 m) was common behaviour; 4) koomal presence was linked to the extent of suitable vegetation; and 5) where the needs of koomal were met, populations in fragments were demographically similar to those found in contiguous landscapes. We used this information to resolve a more accurate SDM for the koomal than that created from bioclimatic data alone. Specifically, we refined spatial coverages of remnant vegetation and dieback, to develop a set of variables that we combined with selected bioclimatic variables to construct models. We conclude that the utility value of an SDM can be enhanced and given greater resolution by identifying variables that reflect observed, species-specific responses to landscape parameters and incorporating these responses into the model. [ABSTRACT FROM AUTHOR]

The topics of climate change and renewable energy are often linked in policy discussions and scientific analysis, but public opinion on these topics exhibits both overlap and divergence. Although renewable energy has potentially broader acceptance than anthropogenic climate change, it can also face differently-based opposition. Analyses of US and regional surveys, including time series of repeated surveys in New Hampshire (2010–2018) and northeast Oregon (2011–2018), explore the social bases and trends of public views on both issues. Political divisions are prominent, although somewhat greater regarding climate change due to substantive differences and more partisan opposition. Regarding climate change and to a lesser extent renewable energy, political divisions tends to widen with education. There also are robust age and temporal effects: younger adults more often prioritize renewable energy development, and agree with scientists on the reality of anthropogenic climate change (ACC). Across all age groups and both regional series, support for renewable energy and recognition of ACC have been gradually rising. Contrary to widespread speculation, these trends have not visibly responded to events such as the US hurricanes of 2012, 2017 or 2018. Together with age-cohort replacement and the potential for changes in age-group voting participation, however, the gradual trends suggest that public pressure for action on these issues could grow. [ABSTRACT FROM AUTHOR]

Biodiversity loss and climate change are both globally significant issues that must be addressed through collaboration across countries and disciplines. With the December 2015 COP21 climate conference in Paris and the recent creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), it has become critical to evaluate the capacity for global research networks to develop at the interface between biodiversity and climate change. In the context of the European Union (EU) strategy to stand as a world leader in tackling global challenges, the European Commission has promoted ties between the EU and Latin America and the Caribbean (LAC) in science, technology and innovation. However, it is not clear how these significant interactions impact scientific cooperation at the interface of biodiversity and climate change. We looked at research collaborations between two major regions—the European Research Area (ERA) and LAC—that addressed both biodiversity and climate change. We analysed the temporal evolution of these collaborations, whether they were led by ERA or LAC teams, and which research domains they covered. We surveyed publications listed on the Web of Science that were authored by researchers from both the ERA and LAC and that were published between 2003 and 2013. We also run similar analyses on other topics and other continents to provide baseline comparisons. Our results revealed a steady increase in scientific co-authorships between ERA and LAC countries as a result of the increasingly complex web of relationships that has been weaved among scientists from the two regions. The ERA-LAC co-authorship increase for biodiversity and climate change was higher than those reported for other topics and for collaboration with other continents. We also found strong differences in international collaboration patterns within the LAC: co-publications were fewest from researchers in low- and lower-middle-income countries and most prevalent from researchers in emerging countries like Mexico and Brazil. Overall, interdisciplinary publications represented 25.8% of all publications at the interface of biodiversity and climate change in the ERA-LAC network. Further scientific collaborations should be promoted 1) to prevent less developed countries from being isolated from the global cooperation network, 2) to ensure that scientists from these countries are trained to lead visible and recognized biodiversity and climate change research, and 3) to develop common study models that better integrate multiple scientific disciplines and better support decision-making. [ABSTRACT FROM AUTHOR]

Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms—the on-average annual dates of the hottest and coldest days of the year. We analyse daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853–2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice. We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. Our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models. [ABSTRACT FROM AUTHOR]

We use agent-based computer simulation to test the effect of environmental conditions (available biomass/carrying capacity and environmental risk) on the development of wealth inequality and patron-client herding networks in nomadic pastoral economies. Our results show that 1) wealth inequality reaches very high levels when carrying capacity is high and risk is low, and 2) patron-client contract herding networks increase in size and duration when carrying capacity is high and risk is low. We compare empirical data from the Mongol (1206–1368 CE) and Xiongnu (209 BCE– 48 CE) empires with simulation results to develop an explanatory mechanism for the apparent correlation between nomadic empire creation and positive environmental conditions. We argue that the internal dynamics of nomadic pastoral societies are sufficient to produce high degrees of inequality and hierarchical herding networks. Nomadic empires are more likely to form during key periods of increased biomass and decreased environmental risk. [ABSTRACT FROM AUTHOR]

Australian fire weather shows spatiotemporal variability on interannual and multi-decadal time scales. We investigate the climate factors that drive this variability using 39 station-based historical time series of the seasonal 90th-percentile of the McArthur Forest Fire Danger Index (FFDI) extending from 1973 through 2017. Using correlation analyses, we examine the relationship of these time series to the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD), considering both concurrent and time-lagged relationships. Additionally, longer term behaviour of the time series using linear trend analysis is discussed in the context of the climate drivers, Interdecadal Pacific Oscillation (IPO) and anthropogenic climate change. The results show that ENSO is the main driver for interannual variability of fire weather, as defined by FFDI in this study, for most of Australia. In general, El Niño-like conditions lead to more extreme fire weather, with this effect stronger in eastern Australia. However, there are significant regional variations to this general rule. In NSW, particularly along the central coast, negative SAM is a primary influence for elevated fire weather in late-winter and spring. In the southeast (VIC and TAS), the El Niño-like impact is exacerbated when positive IOD conditions are simultaneously observed. The spring conditions are key, and strongly influence what is observed during the following summer. On longer time scales (45 years), linear trends are upward at most stations; this trend is strongest in the southeast and during the spring. The positive trends are not driven by the trends in the climate drivers and they are not consistent with hypothesized impacts of the IPO, either before or after its late-1990s shift to the cold phase. We propose that anthropogenic climate change is the primary driver of the trend, through both higher mean temperatures and potentially through associated shifts in large-scale rainfall patterns. Variations from interannual factors are generally larger in magnitude than the trend effects observed to date. [ABSTRACT FROM AUTHOR]

Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans. [ABSTRACT FROM AUTHOR]

Bemisia tabaci (the tobacco whitefly) is an important agricultural pest of global significance primarily because of its ability to transmit multiple damaging plant viruses. To date, UK outbreaks of the whitefly have been restricted to glasshouses and there are no records of the whitefly establishing outdoors during the summer. This is despite the fact that annual degree-day models (that estimate accumulated warmth over the year above the development threshold), indicate that B. tabaci has the thermal potential for multiple summer generations in the UK. A set of 49 climate indices calculated using the present day climate (1986–2015) were therefore compared between the UK and the south of France, where B. tabaci is able to establish outdoors, to identify the factors limiting its establishment. The number of cold days and nights in summer, as well as the time spent within the whitefly’s optimum temperature range, were most significantly different between the two areas. These indices may impact the development of B. tabaci and offer an explanation for the absence of the whitefly outdoors in the UK during the summer. Further analyses undertaken with climate projections suggest that in a 2–4°C warmer world this pest could pose a risk to outdoor UK crops in July and August. A clear south-north gradient can be demonstrated for these indices. Linking any possible northwards spread of B. tabaci populations outdoors in France with changes in these indices could therefore provide an important indicator of any change in the risks of outdoor populations of this species developing in the UK. The effectiveness of climate indices in pest risk analysis is compellingly demonstrated, and it is recommended that in-depth comparisons of climatic indices between areas of pest presence and absence are conducted in other situations where forecasting the risks of pest establishment are complex and challenging. [ABSTRACT FROM AUTHOR]

Black leaf streak disease, or black Sigatoka, is caused by the fungus Pseudocercospora fijiensis, and has been identified as a major constraint to global production of banana and plantain. We fitted a climatic niche model (CLIMEX) for P. fijiensis to gain an understanding of the patterns of climate suitability, and hence hazard from this disease. We then calibrated the climate suitability patterns against the results of an expert elicitation of disease pressure patterns. We found a moderately strong non-linear relationship between modelled climate suitability for P.°fijiensis and the expert ratings for disease pressure. The strength of the relationship provides a cross-validation between the CLIMEX model and the expert elicitation process. The bulk of global banana production experiences high potential threat from P. fijiensis, and the higher yielding areas for banana and plantain production are at greatest threat. By explicitly considering the role of irrigation we have been able to identify how strategic irrigation could be used to support banana production in areas that are at low risk from P. fijiensis. [ABSTRACT FROM AUTHOR]

Prior to the introduction of wheat and barley from Central Asia during the Neolithic period, northern Chinese agricultural groups subsisted heavily on millet. Despite being the focus of many decades of intensive interest and research, the exact route(s), date(s), and mechanisms of the spread and adoption of wheat and barley into the existing well-established millet-based diet in northern China are still debated. As the majority of the important introduced crops are C3 plants, while the indigenous millet is C4, archaeologists can effectively identify the consumption of any introduced crops using stable carbon isotope analysis. Here we examine published stable isotope and dental caries data of human skeletal remains from 77 archaeological sites across northern and northwestern China. These sites date between 9000 to 1750 BP, encompassing the period from the beginning of agriculture to wheat’s emergence as a staple crop in northern China. The aim of this study is to evaluate the implications of the spread and adoption of these crops in ancient China. Detailed analysis of human bone collagen δ13C values reveals an almost concurrent shift from a C4-based to a mixed C3/ C4– based subsistence economy across all regions at around 4500–4000 BP. This coincided with a global climatic event, Holocene Event 3 at 4200 BP, suggesting that the sudden change in subsistence economy across northern and northwestern China was likely related to climate change. Moreover, the substantially increased prevalence of dental caries from pre–to post–4000 BP indicates an increase in the consumption of cariogenic cereals during the later period. The results from this study have significant implications for understanding how the adoption of a staple crop can be indicative of large-scale environmental and socio-political changes in a region. [ABSTRACT FROM AUTHOR]

Despite an overwhelming scientific consensus that climate change poses severe risks to human and natural systems, many young Canadian adults do not view it as a major issue. We analyzed secondary science curricula in each province for their coverage of climate change according to six core topics: physical climate mechanisms (“It’s climate”), observed increase in temperature (“It’s warming”), anthropogenic causes of warming (“It’s us”), scientific consensus (“Experts agree”), negative consequences associated with warming (“It’s bad”), and the possibility for avoiding the worst effects (“We can fix it”). We found that learning objectives tend to focus on knowledge of the first three elements, with little or no emphasis on scientific consensus, climate change impacts, or ways to address the issue. The provinces of Saskatchewan and Ontario provide the most comprehensive standards for climate change education, while Nova Scotia and New Brunswick provide the least. We conducted interviews with individuals responsible for curriculum design in six different provinces to understand how curriculum documents are developed and whether political controversies influence the writing process. Interviewees described a process relying on input from professionals, institutions, and members of the public where curriculum developers made decisions independent of political concerns. In some cases, efforts to provide balance may have led to a focus on social controversy, contrary to overwhelming scientific consensus. Curriculum documents are the basis for teacher instruction and textbook content; aligning these documents with the best possible evidence can improve student learning and engage the next generation of Canadians on the critical issue of climate change. [ABSTRACT FROM AUTHOR]

Climate-related studies have generally focussed upon physiologically well-defined ‘mechanistic’ traits rather than ‘functional’ ones relating indirectly to resource capture. Nevertheless, field responses to climate are likely to typically include both ‘mechanistic’ specialization to climatic extremes and ‘functional’ strategies that optimize resource acquisition during less climatically-severe periods. Here, this hypothesis was tested. Seventeen traits (six ‘functional’, six ‘mechanistic’ and five ‘intermediate’) were measured from 19 populations of oleaster (wild olive) along a climatic gradient in Morocco. Principal components analysis of the trait dataset identified size and the ‘worldwide leaf economics spectrum’ as PCA axes 1 and 2. However, contrary to our prediction, these axes, and commonly-measured ‘functional’ traits, were little correlated with climate. Instead, PCA 3, perhaps relating to water-use and succulence, together stomatal density, specific leaf water content and leaf shape, patterned with altitude, aridity, rainfall and temperature. We concluded that, at least for slow-growing species, such as oleaster, ‘mechanistic’ traits are key to identifying mechanisms of climatic restriction. Meaningful collaboration between ‘mechanistic’ and ‘functional’ disciplines provides the best way of improving our understanding of the global impacts of climate change on species distribution and performance. [ABSTRACT FROM AUTHOR]

In this work we analyze potential environmental drivers of malaria cases in Northwestern Argentina. We inspect causal links between malaria and climatic variables by means of the convergent cross mapping technique, which provides a causality criterion from the theory of dynamic systems. Analysis is based on 12 years of weekly malaria P. vivax cases in Tartagal, Salta, Argentina—at the southern fringe of malaria incidence in the Americas—together with humidity and temperature time-series spanning the same period. Our results show that there are causal links between malaria cases and both maximum temperature, with a delay of five weeks, and minimum temperature, with delays of zero and twenty two weeks. Humidity is also a driver of malaria cases, with thirteen weeks delay between cause and effect. Furthermore we also determined the sign and strength of the effects. Temperature has always a positive non-linear effect on cases, with maximum temperature effects more pronounced above 25°C and minimum above 17°C, while effects of humidity are more intricate: maximum humidity above 85% has a negative effect, whereas minimum humidity has a positive effect on cases. These results might be signaling processes operating at short (below 5 weeks) and long (over 12 weeks) time delays, corresponding to effects related to parasite cycle and mosquito population dynamics respectively. The non-linearities found for the strength of the effect of temperature on malaria cases make warmer areas more prone to higher increases in the disease incidence. Moreover, our results indicate that an increase of extreme weather events could enhance the risks of malaria spreading and re-emergence beyond the current distribution. Both situations, warmer climate and increase of extreme events, will be remarkably increased by the end of the century in this hot spot of climate change. [ABSTRACT FROM AUTHOR]

Combating climate change requires unified action across all sectors of society. However, this collective action is precluded by the ‘consensus gap’ between scientific knowledge and public opinion. Here, we test the extent to which the iconic cities around the world are likely to shift in response to climate change. By analyzing city pairs for 520 major cities of the world, we test if their climate in 2050 will resemble more closely to their own current climate conditions or to the current conditions of other cities in different bioclimatic regions. Even under an optimistic climate scenario (RCP 4.5), we found that 77% of future cities are very likely to experience a climate that is closer to that of another existing city than to its own current climate. In addition, 22% of cities will experience climate conditions that are not currently experienced by any existing major cities. As a general trend, we found that all the cities tend to shift towards the sub-tropics, with cities from the Northern hemisphere shifting to warmer conditions, on average ~1000 km south (velocity ~20 km.year-1), and cities from the tropics shifting to drier conditions. We notably predict that Madrid’s climate in 2050 will resemble Marrakech’s climate today, Stockholm will resemble Budapest, London to Barcelona, Moscow to Sofia, Seattle to San Francisco, Tokyo to Changsha. Our approach illustrates how complex climate data can be packaged to provide tangible information. The global assessment of city analogues can facilitate the understanding of climate change at a global level but also help land managers and city planners to visualize the climate futures of their respective cities, which can facilitate effective decision-making in response to on-going climate change. [ABSTRACT FROM AUTHOR]

The study examines the potential influence of sub-regional variations in climate, and specifically heavy rain events, in determining relative vulnerabilities of locations in twelve Caribbean countries. An aggregate vulnerability index, referred to as the Caribbean Vulnerability Score (CVS), is created using historical demographic and socioeconomic data and climate data representing extreme rain events. Four scenarios are explored. Firstly, comparative vulnerabilities are determined when heavy rainfall is incorporated in CVS versus when it is excluded. The impact of climate change is also investigated using future climate data derived from statistical downscaling but holding demographic and socioeconomic sub-indices constant. The analysis is repeated with projections of future demographic structure from the Shared Socioeconomic Pathway data (SSP3), future climate projections and constant socioeconomic. Finally, the sensitivity of the results is examined with respect to applying different weights i.e. versus using equal weights for the climate and non-climatic components of CVS as is done for the first three scenarios. Results suggest that the inclusion of historical susceptibility to rainfall extremes influences relative vulnerabilities within the Caribbean when compared to the rankings of vulnerability derived using only socioeconomic and demographic inputs. In some cases significant increases in relative rankings are noted. Projected changes in the intensity of rain events across the Caribbean region in the 2030s and 2050s, do not significantly alter the top and lowest ranked vulnerable locations when demographic and socioeconomic indices are held constant. Changes may however occur in the order of the top ranked locations dependent on scenario and time slice. In general, future shifts in relative vulnerabilities were found to be dependent on (i) changes in both future climate and demographic scenarios, (ii) the time horizons being considered, and (iii) the weighting assigned to climate in the future. [ABSTRACT FROM AUTHOR]

This study assessed households’ resilience to climate change-induced shocks in Dinki watershed, northcentral highlands of Ethiopia. The data were collected through a cross-sectional survey conducted on 288 households, three focus group discussions, and 15 key informant interviews. The Climate Resilience Index (CRI) based on the three resilience capacities (absorptive, adaptive and transformative) frame was used to measure households’ resilience to climate change-induced shocks on an agro-ecological unit of analysis. A principal component analysis (PCA) and multiple regression analysis were used to identify determinant factors and indicators to households’ resilience, respectively. Findings indicate that the indexed scores of major components clearly differentiated the study communities in terms of their agro-ecological zones. Specifically, the absorptive capacity (0.495) was the leading contributing factor to resilience followed by adaptive (0.449) and transformative (0.387) capacities. Likewise, the Midland was relatively more resilient with a mean index value of 0.461. Both the PCA and multiple regression analysis indicated that access to and use of livelihood resources, such as farmlands and livestock holdings, diversity of income sources, infrastructure and social capital were determinants of households’ resilience. In general, it might be due to their exposure to recurrent shocks coupled with limited adaptive capacities including underdeveloped public services, poor livelihood diversification practices, among others, the study communities showed minimal resilience capacity with a mean score of 0.44. Thus, in addition to short-term buffering strategies, intervention priority focusing on both adaptive and transformative capacities, particularly focusing on most vulnerable localities and constrained livelihood strategies, would contribute to ensuring long-term resilience in the study communities. [ABSTRACT FROM AUTHOR]

Various models and datasets related to aflatoxins in the maize and dairy production chain have been developed and used but they have not yet been linked with each other. This study aimed to investigate the impacts of climate change on aflatoxin B1 production in maize and its consequences on aflatoxin M1 contamination in dairy cow’s milk, using a full chain modelling approach. To this end, available models and input data were chained together in a modelling framework. As a case study, we focused on maize grown in Eastern Europe and imported to the Netherlands to be fed–as part of dairy cows’ compound feed–to dairy cows in the Netherlands. Three different climate models, one aflatoxin B1 prediction model and five different carryover models were used. For this particular case study of East European maize, most of the calculations suggest an increase (up to 50%) of maximum mean aflatoxin M1 in milk by 2030, except for one climate (DMI) model suggesting a decrease. Results from all combinations of carryover and climate models suggest a similar or slight increase (up to 0.6%) of the chance of finding aflatoxin M1 in milk above the EC limit of 0.05 μg/kg by 2030. Results varied mainly with the climate model data and carryover model considered. The model framework infrastructure is flexible so that forecasting models for other mycotoxins or other food safety hazards as well as other production chains, together with necessary input databases, can easily be included as well. This modelling framework for the first time links datasets and models related to aflatoxin B1 in maize and related aflatoxin M1 the dairy production chain to obtain a unique predictive methodology based on Monte Carlo simulation. Such an integrated approach with scenario analysis provides possibilities for policy makers and risk managers to study the effects of changes in the beginning of the chain on the end product. [ABSTRACT FROM AUTHOR]

Risk assessment regarding the distribution of malaria vectors and environmental variables underpinning their distribution under changing climates is crucial towards malaria control and eradication. On this basis, we used Maximum Entropy (MaxEnt) Model to estimate the potential future distribution of major transmitters of malaria in Nigeria—Anopheles gambiae sensu lato and its siblings: Anopheles gambiae sensu stricto, and Anopheles arabiensis under low and high emissions scenarios. In the model, we used mosquito occurrence data sampled from 1900 to 2010 alongside land use and terrain variables, and bioclimatic variables for baseline climate 1960–1990 and future climates of 2050s (2041–2060) and 2070s (2061–2080) that follow RCP2.6 and RCP8.5 scenarios. The Anopheles gambiae species are projected to experience large shift in potential range and population with increased distribution density, higher under high emissions scenario (RCP8.5) and 2070s than low emission scenario (RCP2.6) and 2050s. Anopheles gambiae sensu stricto and Anopheles arabiensis are projected to have highest invasion with 47–70% and 10–14% percentage increase, respectively in Sahel and Sudan savannas within northern states in 2041–2080 under RCP8.5. Highest prevalence is predicted for Humid forest and Derived savanna in southern and North Central states in 2041–2080; 91–96% and 97–99% for Anopheles gambiae sensu stricto, and 67–71% and 72–75% for Anopheles arabiensis under RCP2.6 and RCP8.5, respectively. The higher magnitude of change in species prevalence predicted for the later part of the 21st century under high emission scenario, driven mainly by increasing and fluctuating temperature, alongside longer seasonal tropical rainfall accompanied by drier phases and inherent influence of rapid land use change, may lead to more significant increase in malaria burden when compared with other periods and scenarios during the century; especially in Humid forest, Derived savanna, Sahel and Sudan savannas. [ABSTRACT FROM AUTHOR]

Human populations in Western Europe during the Last Glacial Maximum were geographically constrained to glacial refugia by the severity of the climate and ecological risk factors. In this research we use an agent-based model of human mobility and interaction, based on ethnographic and archaeological data, to explore the impact of ecological risk on human population structure via a reconstructed landscape of habitat suitability. The agent-based model allows us to evaluate the size and location of glacial refugia, the size of the populations occupying them and the degree of genetic relatedness between people occupying these areas. To do this, we model the probability of an agent foraging groups’ survival as a function of habitat suitability. The model’s simulated “genomes” (composed of regionally specific genetic markers) allow us to track long-term trends of inter-regional interaction and mobility. The results agree with previous archaeological studies situating a large glacial refugium spanning southern France and northeastern Spain, but we expand on those studies by demonstrating that higher rates of population growth in this central refugium led to continuous out-migration and therefore genetic homogeneity across Western Europe, with the possible exception of the Italian peninsula. These results concur with material culture data from known archaeological sites dating to the Last Glacial Maximum and make predictions for future ancient DNA studies. [ABSTRACT FROM AUTHOR]

Background: The increase in the frequency of extreme events due to climate change poses a serious challenge to achieving the Sustainable Development Goal 2 of ending hunger by 2030. While evidence exists on the impact of drought on under-five children, its effect during late childhood and early adolescence remains less investigated. Objective: This study estimates the impact of concurrent and long-term exposure to drought on linear growth during late childhood and early adolescence. Methods: Four rounds (2002–2013) of data from the young lives Cohort Study dataset (n = 2000) was used. The associations of concurrent and long-term exposure to drought and Height-for-age z-score was analysed using structural equation modelling techniques. The study also explored the mediating role of interim period growth in the association of early exposure to drought and undernutrition at later age and the role of the Productive Safety Net Program in buffering the impact of drought on child nutrition. Results: Results show that both concurrent and long-term exposure to drought was negatively associated with Height-for-age z-score (p < 0.001). Exposure to drought at age 5, 8, and 12 years is associated with lower Height-for-age z- score at age 5, 8, and 12 years respectively. Exposure to drought at age 5 years was also negatively associated with Height-for-age z-score at age 12 years (p < 0.001). This association was mainly indirect (89%) and mediated through reduced child growth in subsequent years. Participation in productive safety net program by drought-affected children reduces but does not completely offset the negative effects of drought on Height-for-age z-score (p < 0.1). Moreover, girls were more likely to suffer poor growth than boys. Conclusion: Drought exposure after the 1,000 days window could have a lasting impact on child growth. Given the importance of this period for child physical and mental development, children beyond the 1,000 days window should also be a focus of disaster relief programs. [ABSTRACT FROM AUTHOR]

There is growing interest to restore oyster populations and develop oyster reefs for their role in ecosystem health and delivery of ecosystem services. Successful and sustainable oyster restoration efforts largely depend on the availability and selection of suitable sites that can support long-term growth and survival of oysters. Hence, in the present study a habitat suitability index (HSI) model was developed for the intertidal rock oyster (Saccostrea cucullata), with special attention: (1) to the role of the monsoon in the suitability of oyster habitats, and (2) to identify potential suitable sites along the south-eastern Bangladesh coast. Seven habitat factors were used as input variables for the HSI model: (1) water temperature; (2) salinity; (3) dissolved oxygen; (4) particulate inorganic matter (PIM); (5) pH; (6) Chlorophyll-a; and (7) water flow velocity. Seven field surveys were conducted at 80 locations to collect geo-spatial environmental data, which were then used to determine HSI scores using habitat suitability functions. The model results showed that the areas suitable (HSI >0.50) for oyster settlement and growth were characterized by relatively high salinities, Chlorophyll-a, dissolved oxygen and pH values. In contrast, freshwater dominated estuaries and nearby coastal areas with high suspended sediment were found less suitable (HSI <0.50) for oysters. HSI model results were validated with observed oyster distribution data. There was strong correlation between the HSI calculated by the model and observed oyster densities (r = 0.87; n = 53), shell height (r = 0.95; n = 53) and their condition index (r = 0.98; n = 53). The good correspondence with field data enhances the applicability of the HSI model as a quantitative tool for evaluating the quality of a site for oyster restoration and culture. [ABSTRACT FROM AUTHOR]

The adaptability of our species, as revealed by the geographic routes and palaeoenvironmental contexts of human dispersal beyond Africa, is a prominent topic in archaeology and palaeoanthropology. Northern and Central Asia have largely been neglected as it has been assumed that the deserts and mountain ranges of these regions acted as ‘barriers’, forcing human populations to arc north into temperate and arctic Siberia. Here, we test this proposition by constructing Least Cost Path models of human dispersal under glacial and interstadial conditions between prominent archaeological sites in Central and East Asia. Incorporating information from palaeoclimatic, palaeolake, and archaeological data, we demonstrate that regions such as the Gobi Desert and the Altai Mountain chains could have periodically acted as corridors and routes for human dispersals and framing biological interactions between hominin populations. Review of the archaeological datasets in these regions indicates the necessity of wide-scale archaeological survey and excavations in many poorly documented parts of Eurasia. We argue that such work is likely to highlight the ‘northern routes’ of human dispersal as variable, yet crucial, foci for understanding the extreme adaptive plasticity characteristic of the emergence of Homo sapiens as a global species, as well as the cultural and biological hybridization of the diverse hominin species present in Asia during the Late Pleistocene. [ABSTRACT FROM AUTHOR]

Global climate change alters the dynamic of natural ecosystems and directly affects species distributions, persistence and diversity. The impacts of climate change may lead to dramatic changes in biotic interactions, such as pollination and seed dispersal. Life history traits are extremely important to consider the vulnerability of a species to climate change, producing more robust models than those based primarily on species distributions. Here, we hypothesized that rising temperatures and aridity will reduce suitable habitats for the endemic flora of the Caatinga, the most diverse dry tropical forest on Earth. Specifically, species with specialized reproductive traits (e.g. vertebrate pollination, biotic dispersal, obligatory cross-pollination) should be more affected by climate change than those with generalist traits. We performed two ecological niche models (current and future) to simulate the effects of climate change on the distribution area of endemic species in relation to life-history traits. We used the MIROC-ESM and CCSM4 models for both intermediate (RCP4.5) and highest predicted (RCP8.5) GHG emission scenarios, with a resolution of 30' (~1 km2). Habitat with high occurrence probability (>80%) of endemic species will be reduced (up to ~10% for trees, ~13% for non-arboreous, 10–28% for species with any pollination/reproductive system), with the greatest reductions for species with specialized reproductive traits. In addition, the likely concentration of endemic plants in the extreme northeastern portion of the Caatinga, in more mesic areas, coincides with the currently most human-modified areas of the ecosystem, which combined with climate change will further contract suitable habitats of endemic species. In conclusion, plant species endemic to the Caatinga are highly vulnerable to even conservative scenarios of future climate change and may lose much of their climatic envelopes. New protected areas should be located in the northeastern portion of the Caatinga, which hosts a more favorable climate, but is currently exposed to escalating agricultural intensification. [ABSTRACT FROM AUTHOR]

The causes of disappearance of the Neanderthals, the only human population living in Europe before the arrival of Homo sapiens, have been debated for decades by the scientific community. Different hypotheses have been advanced to explain this demise, such as cognitive, adaptive and cultural inferiority of Neanderthals. Here, we investigate the disappearance of Neanderthals by examining the extent of demographic changes needed over a period of 10,000 years (yrs) to lead to their extinction. In regard to such fossil populations, we inferred demographic parameters from present day and past hunter-gatherer populations, and from bio-anthropological rules. We used demographic modeling and simulations to identify the set of plausible demographic parameters of the Neanderthal population compatible with the observed dynamics, and to explore the circumstances under which they might have led to the disappearance of Neanderthals. A slight (<4%) but continuous decrease in the fertility rate of younger Neanderthal women could have had a significant impact on these dynamics, and could have precipitated their demise. Our results open the way to non-catastrophic events as plausible explanations for Neanderthal extinction. [ABSTRACT FROM AUTHOR]

Acute gastrointestinal illness (AGI) is a global public health priority that often disproportionately effects Indigenous populations. While previous research examines the association between meteorological conditions and AGI, little is known about how socio-cultural factors may modify this relationship. This present study seeks to address this research gap by comparing AGI prevalence and determinants between an Indigenous and non-Indigenous population in Uganda. We estimate the 14-day self-reported prevalence of AGI among adults in an Indigenous Batwa population and their non-Indigenous neighbours using cross-sectional panel data collected over four periods spanning typically rainy and dry seasons (January 2013 to April 2014). The independent associations between Indigenous status, precipitation, and AGI are examined with multivariable multi-level logistic regression models, controlling for relative wealth status and clustering at the community level. Estimated prevalence of AGI among the Indigenous Batwa was greater than among the non-Indigenous Bakiga. Our models indicate that both Indigenous identity and decreased levels of precipitation in the weeks preceding the survey period were significantly associated with increased AGI, after adjusting for confounders. Multivariable models stratified by Indigenous identity suggest that Indigenous identity may not modify the association between precipitation and AGI in this context. Our results suggest that short-term changes in precipitation affect both Indigenous and non-Indigenous populations similarly, though from different baseline AGI prevalences, maintaining rather than exacerbating this socially patterned health disparity. In the context of climate change, these results may challenge the assumption that changing weather patterns will necessarily exacerbate existing socially patterned health disparities. [ABSTRACT FROM AUTHOR]

Introduction: Measuring staff perceptions with safety climate surveys is a promising approach to addressing patient safety. Variation in safety climate scores between work sites may predict variability in risk related to tasks, work environment, staff behavior, and patient outcomes. Safety climate measurements may identify considerable variation in staff perceptions across work sites. Objective: To explore variation in staff perceptions of patient safety climate across work sites in Norwegian General Practitioner (GP) practices and Out-of-hours clinics. Methods: The Norwegian Safety Attitudes QuestionnaireAmbulatory Version (SAQ A) was used to survey staff perceptions of patient safety climate across a sample of GP practices and Out-of-hours clinics in Norway. We invited 510 primary health care providers to fill out the questionnaire anonymously online in October and November 2012. Work sites were 17 regular GP practices in Sogn & Fjordane County, and seven Out-of-hours clinics, of which six were designated as “Watchtower Clinics”. Intra–class correlation coefficients were calculated to identify what proportion of the variation in the five factor scores (Teamwork climate, Safety climate, Job satisfaction, Perceptions of management, and Working conditions) were at work site-level. Results: Of the 510 invited health care providers, 266 (52%) answered the questionnaire. Staff perceptions varied considerably at the work site level: intra–class correlation coefficients (ICCs) were 12.3% or higher for all factors except for Job satisfaction–the highest ICC value was for Perceptions of management: 15.5%. Conclusion: Although most of the score variation was at the individual level, there was considerable response clustering within the GP practices and OOH clinics. This implies that the Norwegian SAQ A is able to identify GP practices and OOH clinics with high and low patient safety climate scores. Patient safety climate scores produced by the Norwegian version of the SAQ A may, thus, guide improvement and learning efforts to work sites according to the level of their scores. [ABSTRACT FROM AUTHOR]