Word Diffusion and Climate Science

As public and political debates often demonstrate, a substantial disjoint can exist between the findings of science and the impact it has on the public. Using climate-change science as a case example, we reconsider the role of scientists in the information-dissemination process, our hypothesis being that important keywords used in climate science follow “boom and bust” fashion cycles in public usage. Representing this public usage through extraordinary new data on word frequencies in books published up to the year 2008, we show that a classic two-parameter social-diffusion model closely fits the comings and goings of many keywords over generational or longer time scales. We suggest that the fashions of word usage contributes an empirical, possibly regular, correlate to the impact of climate science on society.     

Tracking Public Beliefs About Anthropogenic Climate Change

A simple question about climate change, with one choice designed to match consensus statements by scientists, was asked on 35 US nationwide, single-state or regional surveys from 2010 to 2015. Analysis of these data (over 28,000 interviews) yields robust and exceptionally well replicated findings on public beliefs about anthropogenic climate change, including regional variations, change over time, demographic bases, and the interacting effects of respondent education and political views. We find that more than half of the US public accepts the scientific consensus that climate change is happening now, caused mainly by human activities. A sizable, politically opposite minority (about 30 to 40%) concede the fact of climate change, but believe it has mainly natural causes. Few (about 10 to 15%) say they believe climate is not changing, or express no opinion. The overall proportions appear relatively stable nationwide, but exhibit place-to-place variations. Detailed analysis of 21 consecutive surveys within one fairly representative state (New Hampshire) finds a mild but statistically significant rise in agreement with the scientific consensus over 2010–2015. Effects from daily temperature are detectable but minor. Hurricane Sandy, which brushed New Hampshire but caused no disaster there, shows no lasting impact on that state’s time series—suggesting that non-immediate weather disasters have limited effects. In all datasets political orientation dominates among individual-level predictors of climate beliefs, moderating the otherwise positive effects from education. Acceptance of anthropogenic climate change rises with education among Democrats and Independents, but not so among Republicans. The continuing series of surveys provides a baseline for tracking how future scientific, political, socioeconomic or climate developments impact public acceptance of the scientific consensus.     

Dissociation of the Tubulin-sequestering and Microtubule Catastrophe-promoting Activities of Oncoprotein 18/Stathmin

Oncoprotein 18/stathmin (Op18) has been identified recently as a protein that destabilizes microtubules, but the mechanism of destabilization is currently controversial. Based on in vitro microtubule assembly assays, evidence has been presented supporting conflicting destabilization models of either tubulin sequestration or promotion of microtubule catastrophes. We found that Op18 can destabilize microtubules by both of these mechanisms and that these activities can be dissociated by changing pH. At pH 6.8, Op18 slowed microtubule elongation and increased catastrophes at both plus and minus ends, consistent with a tubulin-sequestering activity. In contrast, at pH 7.5, Op18 promoted microtubule catastrophes, particularly at plus ends, with little effect on elongation rates at either microtubule end. Dissociation of tubulin-sequestering and catastrophe-promoting activities of Op18 was further demonstrated by analysis of truncated Op18 derivatives. Lack of a C-terminal region of Op18 (aa 100–147) resulted in a truncated protein that lost sequestering activity at pH 6.8 but retained catastrophe-promoting activity. In contrast, lack of an N-terminal region of Op18 (aa 5–25) resulted in a truncated protein that still sequestered tubulin at pH 6.8 but was unable to promote catastrophes at pH 7.5. At pH 6.8, both the full length and the N-terminal–truncated Op18 bound tubulin, whereas truncation at the C-terminus resulted in a pronounced decrease in tubulin binding. Based on these results, and a previous study documenting a pH-dependent change in binding affinity between Op18 and tubulin, it is likely that tubulin sequestering observed at lower pH resulted from the relatively tight interaction between Op18 and tubulin and that this tight binding requires the C-terminus of Op18; however, under conditions in which Op18 binds weakly to tubulin (pH 7.5), Op18 stimulated catastrophes without altering tubulin subunit association or dissociation rates, and Op18 did not depolymerize microtubules capped with guanylyl (α, β)-methylene diphosphonate–tubulin subunits. We hypothesize that weak binding between Op18 and tubulin results in free Op18, which is available to interact with microtubule ends and thereby promote catastrophes by a mechanism that likely involves GTP hydrolysis.     

Mental Imagery,Impact, and Affect: A Mediation Model for Charitable Giving

One of the puzzling phenomena in philanthropy is that people can show strong compassion for identified individual victims but remain unmoved by catastrophes that affect large numbers of victims. Two prominent findings in research on charitable giving reflect this idiosyncrasy: The (1) identified victim and (2) victim number effects. The first of these suggests that identifying victims increases donations and the second refers to the finding that people’s willingness to donate often decreases as the number of victims increases. While these effects have been documented in the literature, their underlying psychological processes need further study. We propose a model in which identified victim and victim number effects operate through different cognitive and affective mechanisms. In two experiments we present empirical evidence for such a model and show that different affective motivations (donor-focused vs. victim-focused feelings) are related to the cognitive processes of impact judgments and mental imagery. Moreover, we argue that different mediation pathways exist for identifiability and victim number effects.     

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983–1999 and 2000–2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6–11.0% and 19.5–92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming.     

Future Bloom and Blossom Frost Risk for Malus domestica Considering Climate Model and Impact Model Uncertainties

The future bloom and risk of blossom frosts for Malus domestica were projected using regional climate realizations and phenological ( = impact) models. As climate impact projections are susceptible to uncertainties of climate and impact models and model concatenation, the significant horizon of the climate impact signal was analyzed by applying 7 impact models, including two new developments, on 13 climate realizations of the IPCC emission scenario A1B. Advancement of phenophases and a decrease in blossom frost risk for Lower Saxony (Germany) for early and late ripeners was determined by six out of seven phenological models. Single model/single grid point time series of bloom showed significant trends by 2021–2050 compared to 1971–2000, whereas the joint signal of all climate and impact models did not stabilize until 2043. Regarding blossom frost risk, joint projection variability exceeded the projected signal. Thus, blossom frost risk cannot be stated to be lower by the end of the 21st century despite a negative trend. As a consequence it is however unlikely to increase. Uncertainty of temperature, blooming date and blossom frost risk projection reached a minimum at 2078–2087. The projected phenophases advanced by 5.5 d K⁻¹, showing partial compensation of delayed fulfillment of the winter chill requirement and faster completion of the following forcing phase in spring. Finally, phenological model performance was improved by considering the length of day.     

Culture or climate? The relative influences of past processes on the composition of the lowland Congo rainforest

This paper presents the results from a palaeoecological study to establish the impact of prehistoric human activity and climate change on the vegetation and soils of the Goualougo area of the Nouabalé-Ndoki National Park, in the Republic of Congo (Congo-Brazzaville). This is a region that is known from previous work (through evidence of pottery, furnaces and charcoal layers beneath the present day rainforest vegetation) to have had prehistoric settlement dating back to at least 2000 calibrated years before present. In addition, there is climatic evidence to suggest that significant variations in precipitation have occurred in central Africa over the last few millennia. Presently, the region is covered in uninhabited moist semi-evergreen rainforest. Key research questions addressed in this paper include the extent to which the present-day composition of rainforest in this region is as a result of processes of the past (climate change and/or human activity), and the resilience of the rainforest to these perturbations.Statistical analyses of pollen, microscopic charcoal and geochemical data are used to determine the relationship over time between vegetation dynamics and climate change, anthropogenic burning and metal smelting. Significant changes in forest composition are linked to burning and climate change but not metallurgy. The strongest influence on the present day composition appears to be related to the increased anthropogenic burning that started approximately 1000 years ago. Results from this study are discussed in terms of their implications for the present and future management of this globally important forested region.     

A 250-year index of first flowering dates and its response to temperature changes

Widespread concerns about global biodiversity loss have led to a growing demand for indices of biodiversity status. Today, climate change is among the most serious threats to global biodiversity. Although many studies have revealed phenological responses to climate change, no long-term community-level indices have been developed. We derived a 250-year index of first flowering dates for 405 plant species in the UK for assessing the impact of climate change on plant communities. The estimated community-level index in the most recent 25 years was 2.2–12.7 days earlier than any other consecutive 25-year period since 1760. The index was closely correlated with February–April mean Central England Temperature, with flowering 5.0 days earlier for every 1°C increase in temperature. The index was relatively sensitive to the number of species, not records per species, included in the model. Our results demonstrate how multi-species, multiple-site phenological events can be integrated to obtain indices showing trends for each species and across species. This index should play an important role in monitoring the impact of climate change on biodiversity. Furthermore, this approach can be extended to incorporate data from other taxa and countries for evaluating cross-taxa and cross-country phenological responses to climate change.     

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.     

Effects of City Expansion on Heat Stress under Climate Change Conditions

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990–2009) and future (2040–2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort.     

The Scientific Consensus on Climate Change as a Gateway Belief: Experimental Evidence

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.     

农户对气候变化的感知与适应研究综述

气候变化是21世纪人类面临的最严峻挑战之一,加剧了许多国家和地区的脆弱性,人类如何适应气候变化已成为当前全社会普遍关注的话题.气候变化对以自然资源为生计基础的农业人口的影响尤为显著,更好地理解农户对气候变化的适应机制和适应过程对于制定有效的适应政策非常重要.公众感知作为理解人文响应行动的基础,已为探明农户对气候变化的适应机制和适应过程提供了一个新视角.本文基于国内外农户对气候变化的感知和适应的理论研究和实践进展,在分析气候变化对农户生计的影响、系统总结农户面临的主要适应障碍的基础上,梳理了农户的气候变化感知与适应的关系,阐释了农户适应气候变化过程中的关键认知要素,介绍了农户对气候变化的感知与适应关系分析框架,提出了农户对气候变化的感知与适应关系研究中应关注的关键问题.     

Mechanisms underpinning climatic impacts on natural populations: altered species interactions are more important than direct effects

Shifts in species' distribution and abundance in response to climate change have been well documented, but the underpinning processes are still poorly understood. We present the results of a systematic literature review and meta‐analysis investigating the frequency and importance of different mechanisms by which climate has impacted natural populations. Most studies were from temperate latitudes of North America and Europe; almost half investigated bird populations. We found significantly greater support for indirect, biotic mechanisms than direct, abiotic mechanisms as mediators of the impact of climate on populations. In addition, biotic effects tended to have greater support than abiotic factors in studies of species from higher trophic levels. For primary consumers, the impact of climate was equally mediated by biotic and abiotic mechanisms, whereas for higher level consumers the mechanisms were most frequently biotic, such as predation or food availability. Biotic mechanisms were more frequently supported in studies that reported a directional trend in climate than in studies with no such climatic change, although sample sizes for this comparison were small. We call for more mechanistic studies of climate change impacts on populations, particularly in tropical systems.     

Quantifying Trends in Disease Impact to Produce a Consistent and Reproducible Definition of an Emerging Infectious Disease

The proper allocation of public health resources for research and control requires quantification of both a disease''s current burden and the trend in its impact. Infectious diseases that have been labeled as “emerging infectious diseases” (EIDs) have received heightened scientific and public attention and resources. However, the label ‘emerging’ is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled “emerging,” and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health.     

The role of public policy in biological control: Some global trends

The past decade has been a rapid development in the view that contemporary agricultural practices should meet the needs of the present without compromising the ability of future generations. This philosophy has broadened the priorities for research and development in primary production systems. Now there is reduced emphasis on efficiency and productivity, and an increased concern for ecological sustainability. This has had an impact on policies relating to biological control technologies and associated policies have been developed to enhance the uptake of biopesticides. At the same time international agreements on climate change, biodiversity and global trading have potential influences on the use of biological control agents and biological technologies. In this review some of these trends in public policy are highlighted as well as the likely effect they may have in the adoption, implementation and ongoing development of biological control technologies.     

Voluntary Climate Change Mitigation Actions of Young Adults: A Classification of Mitigators through Latent Class Analysis

Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.     

Bumblebees moving up: shifts in elevation ranges in the Pyrenees over 115 years

In a warming climate, species are expected to shift their geographical ranges to higher elevations and latitudes, and if interacting species shift at different rates, networks may be disrupted. To quantify the effects of ongoing climate change, repeating historical biodiversity surveys is necessary. In this study, we compare the distribution of a plant–pollinator community between two surveys 115 years apart (1889 and 2005–06), reporting distribution patterns and changes observed for bumblebee species and bumblebee-visited plants in the Gavarnie-Gèdre commune in the Pyrenees, located in southwest Europe at the French–Spanish border. The region has warmed significantly over this period, alongside shifts in agricultural land use and forest. The composition of the bumblebee community shows relative stability, but we observed clear shifts to higher elevations for bumblebees (averaging 129 m) and plants (229 m) and provide preliminary evidence that some bumblebee species shift with the plants they visit. We also observe that some species have been able to occupy the same climate range in both periods by shifting elevation range. The results suggest the need for long-term monitoring to determine the role and impact of the different drivers of global change, especially in montane habitats where the impacts of climate changes are anticipated to be more extreme.     

Sheltered from the storm? Population viability analysis of a rare endemic under periodic catastrophe regimes

Rare species are important targets for biodiversity conservation efforts because rarity often equates to small populations and increased endangerment. Rare species are prone to stochastic extinction events and may be particularly susceptible to catastrophes. Therefore, understanding how rare species respond to disturbances is critical for evaluating extinction risk and guiding conservation managers. Population viability analyses (PVAs) are essential for assessing rare species' status yet they seldom consider catastrophic events. Accordingly, we present a PVA of a rare tropical epiphyte, Lepanthes caritensis (Orchidaceae), under simulated disturbance regimes to evaluate its demographics and extinction risk. We aimed to test how demographic models incorporating catastrophes affect population viability estimates. Our goal was to better guide management of these orchids and other rare plants. Results revealed L. caritensis numbers have declined recently, but projected growth rates indicated that most subpopulations should increase in size if undisturbed. Still, projection models show that moderate catastrophes reduce growth rates, increase stochasticity in subpopulation sizes, and elevate extinction risk. Severe catastrophes had a more pronounced effect in simulations; growth rates fell below replacement level, there was greater variation in projected population sizes, and extinction risk was significantly higher. PVAs incorporating periodic catastrophes indicate that rare species may have greater extinction probabilities than standard models suggest. Thus, precautionary conservation measures should be taken in disturbance prone settings and we encourage careful monitoring after environmental catastrophes. Future rare plant PVAs should incorporate catastrophes and aim to determine if rescue and reintroduction efforts are necessary after disturbances to insure long-term population viability.     

Downy mildew (Plasmopara viticola) epidemics on grapevine under climate change

As climate is a key agro‐ecosystem driving force, climate change could have a severe impact on agriculture. Many assessments have been carried out to date on the possible effects of climate change (temperature, precipitation and carbon dioxide concentration changes) on plant physiology. At present however, likely effects on plant pathogens have not been investigated deeply. The aim of this work was to simulate future scenarios of downy mildew (Plasmopara viticola) epidemics on grape under climate change, by combining a disease model to output from two general circulation models (GCMs). Model runs corresponding to the SRES‐A2 emissions scenario, characterized by high projections of both population and greenhouse gas emissions from present to 2100, were chosen in order to investigate impacts of worst‐case scenarios, among those currently available from IPCC. Three future decades were simulated (2030, 2050, 2080), using as baseline historical series of meteorological data collected from 1955 to 2001 in Acqui Terme, an important grape‐growing area in the north‐west of Italy. Both GCMs predicted increase of temperature and decrease of precipitation in this region. The simulations obtained by combining the disease model to the two GCM outputs predicted an increase of the disease pressure in each decade: more severe epidemics were a direct consequence of more favourable temperature conditions during the months of May and June. These negative effects of increasing temperatures more than counterbalanced the effects of precipitation reductions, which alone would have diminished disease pressure. Results suggested that, as adaptation response to future climate change, more attention would have to be paid in the management of early downy mildew infections; two more fungicide sprays were necessary under the most negative climate scenario, compared with present management regimes. At the same time, increased knowledge on the effects of climate change on host–pathogen interactions will be necessary to improve current predictions.     

Implications of climate change for agricultural productivity in the early twenty-first century

This paper reviews recent literature concerning a wide range of processes through which climate change could potentially impact global-scale agricultural productivity, and presents projections of changes in relevant meteorological, hydrological and plant physiological quantities from a climate model ensemble to illustrate key areas of uncertainty. Few global-scale assessments have been carried out, and these are limited in their ability to capture the uncertainty in climate projections, and omit potentially important aspects such as extreme events and changes in pests and diseases. There is a lack of clarity on how climate change impacts on drought are best quantified from an agricultural perspective, with different metrics giving very different impressions of future risk. The dependence of some regional agriculture on remote rainfall, snowmelt and glaciers adds to the complexity. Indirect impacts via sea-level rise, storms and diseases have not been quantified. Perhaps most seriously, there is high uncertainty in the extent to which the direct effects of CO₂ rise on plant physiology will interact with climate change in affecting productivity. At present, the aggregate impacts of climate change on global-scale agricultural productivity cannot be reliably quantified.